Getting Personal: Omics of the Heart
Each monthly episode will discuss recent publications in the fields of genomics and precision medicine of cardiovascular disease.
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February 2020
04/08/2020
February 2020
Jane Ferguson: Hi there. Welcome to Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson, and this is Episode 36 from February 2020. First up, we have “Identification of Circulating Proteins Associated with Blood Pressure Using Mendelian Randomization” from Sébastien Thériault, Guillaume Paré, and colleagues from McMaster University in Ontario. They set out to assess whether they could identify protein biomarkers of hypertension using a Mendelian randomization approach. They analyzed data from a genome-wide association study of 227 biomarkers which were profiled on a custom Luminex-based platform in over 4,000 diabetic or prediabetic participants of the origin trial. They constructed genetic predictors of each protein and then used these as instruments for Mendelian randomization. They obtained systolic and diastolic blood pressure measurements in almost 70,000 individuals, in addition to mean arterial pressure and pulse pressure in over 74,000 individuals, all European ancestry with GWAS data, as part of the International Consortium for Blood Pressure. Out of the 227 biomarkers tested, six of them were significantly associated with blood pressure traits by Mendelian randomization after correction for multiple testing. These included known biomarkers such as NT-proBNP, but also novel associations including urokinase-type plasminogen activator, adrenomedullin, interleukin-16, cellular fibronectin and insulin-like growth factor binding protein-3. They validated all of the associations apart from IL-16 in over 300,000 participants in UK Biobank. They probed associations with other cardiovascular risk markers and found that NT-proBNP associated with large artery atherosclerotic stroke, IGFBP3 associated with diabetes, and CFN associated with body mass index. This study identified novel biomarkers of blood pressure, which may be causal in hypertension. Further study of the underlying mechanisms is required to understand whether these could be useful therapeutic targets in hypertensive disease. The next paper comes from Sony Tuteja, Dan Rader, Jay Giri and colleagues from the University of Pennsylvania and it's entitled, “Prospective CYP2C19 Genotyping to Guide Antiplatelet Therapy Following Percutaneous Coronary Intervention: A Pragmatic Randomized Clinical Trial”. They designed a pharmacode genomic trial to assess effects of CYP2C19 genotyping on antiplatelet therapy following PCI. Because loss of function alleles in CYP2C19 impair the effectiveness of clopidogrel, the team were interested in understanding whether knowledge of genotype status would affect prescribing in a clinical setting. They randomized 504 participants to genotype guided or usual care groups and assessed the rate of prasugrel or ticagrelor prescribing in place of clopidogrel within each arm. As a secondary outcome, they assessed whether prescribers adhere to genotype guided recommendations. Of genotyped individuals, 28% carried loss of function alleles. Within the genotype guided group overall, there was higher use of prasugrel or ticagrelor with these being prescribed to 30% of patients compared with only 21% in the usual care group. Within genotype individuals carrying loss of function alleles, 53% were started on prasugrel or ticagrelor, demonstrating some adherence to genotype guided recommendations. However, this also meant that 47% of people whose genotype suggested reduced effectiveness were nevertheless prescribed clopidogrel. This study highlights that even when genotype information is available, interventional cardiologists consider clinical factors such as disease presentation and may weight these more highly than genotype information when selecting antiplatelet therapy following PCI. The next paper is about “Deep Mutational Scan of an SCN5A Voltage Sensor and comes to us from Andrew Glazer, Dan Roden and colleagues from Vanderbilt University Medical Center. In this paper, the team aim to characterize the functional consequences of variants and the S4 voltage sensor of domain IV and the SCN5A gene using a high throughput method that they developed. SCN5A encodes the major voltage gated sodium channel in the heart and variants in SCN5A can cause multiple distinct genetic arrhythmia syndromes, including Brugada syndrome, long QT syndrome, atrial fibrillation, and dilated cardiomyopathy, and have been linked to sudden cardiac death. Because of this, there's considerable interest in understanding the functional and clinical consequences of different variants, but previous approaches were time consuming and results were often inconclusive with many variants being classified as uncertain significance. This newly developed deep mutational scanning approach allows for simultaneous assessment of the function of thousands of variants, making it much more efficient than low throughput patch clamping. The team assessed the function of 248 variants using a triple drug assay in HEK293T cells expressing each variant and they identified 40 putative gain of function and 33 putative loss of function variants. They successfully validated eight of nine of these by patch clamping data. Their study highlights the effectiveness of this deep mutational scanning approach for investigating variants in the cardiac sodium channel SCN5A gene and suggests that this may also be an effective approach for investigating putative disease variants and other ion channels. The next article is a research letter from Connor Emdin, Amit Khera, and colleagues from Mass General Hospital in the Broad Institute entitled, “Genome-Wide Polygenic Score and Cardiovascular Outcomes with Evacetrapib in Patients with High-Risk Vascular Disease: A Nested Case-Control Study”. In this study, the team set out to probe the utility of using polygenic risk scores to predict the risk of major adverse cardiovascular events within individuals already known to be at high cardiovascular risk and to assess whether genetic scores can identify individuals who would benefit from the use of a CETP inhibitor such as Evacetrapib. They analyze data from the ACCELERATE trial which had tested Evacetrapib in a high risk population, and they found no effect on the incidents of major adverse cardiovascular events overall. Within a nested case-control sample of individuals experiencing major CVD events versus no events, they applied a polygenic risk score and found that the score predicted major cardiovascular events. Patients in the highest quintile of the risk score were at 60% higher risk of a major cardiovascular event than patients in the lowest quintile. There was no evidence of any interaction between the genetic risk score and Evacetrapib. These data suggest that genetic risk scores may have utility in identifying individuals at high risk events but may not have utility in identifying individuals who may derive more benefit from CETP inhibition. The next letter concerns “Epigenome-Wide Association Study Identifies a Novel DNA Methylation in Patients with Severe Aortic Valve Stenosis” and comes from Takahito Nasu, Mamoru Satoh, Makoto Sasaki and colleagues from Iwate Medical University in Japan. They were interested in understanding whether differences in DNA methylation could underlie the risk of aortic valve stenosis. They conducted an EWAS or epigenome-wide association study of peripheral blood mononuclear cells or PBMCs from 44 individuals with aortic stenosis and 44 disease free controls. They collected samples at baseline before a surgical intervention in the individuals with aortic stenosis and collected a follow-up sample one year later. They found that DNA methylation at a site on chromosome eight mapping to the TRIB1, or tribbles homolog one gene, was lower in the aortic stenosis group than in the controls at baseline. They replicated the association in an independent sample of 50 cases and 50 controls. TRIB1 MRNA levels were higher in the aortic stenosis group than the controls. When they looked at methylation status one year after aortic valve replacement or a transcatheter aortic valve implantation in patients with stenosis, they found that DNA methylation had increased in the cases while TRIB1 MRNA decreased. These data suggests that methylation status of TRIB1 and expression of TRIB1 may relate to the disease processes in aortic stenosis such as hemodynamic dysregulation and they can be reversed through surgical intervention. Changes in the methylation status of TRIB1 could be a novel biomarker of response to aortic valve replacement. The next letter comes from Niels Grote Beverborg, Pim van der Harst, and colleagues from University Medical Center Groningen and is entitled, “Genetically Determined High Levels of Iron Parameters Are Protective for Coronary Artery Disease”. Their study addresses the conflicting hypotheses that high iron status is either deleterious or protective against cardiovascular disease. The team constructed genetic predictors of serum iron status using 11 previously identified snips and tested the genetic association with CAD in UK Biobank data from over 408,000 white participants. Overall, the genetic score for higher iron status was associated with protection against CAD. Ten of the snips suggested individual neutral or protective effects of higher iron status on CAD, while one iron increasing snip was associated with increased risk of disease but this was thought to be likely through an iron independent mechanism. Overall, these data suggest that a genetic predisposition to higher iron status does not increase risk of CAD and is actually protective against disease. The final letter is entitled, “Confidence Weighting for Robust Automated Measurements of Popliteal Vessel Wall MRI” and comes from Daniel Hippe, Jenq-Neng Hwang, and colleagues from the University of Washington. They were interested in assessing whether images of popliteal artery wall incidentally obtained during knee MRI as part of an osteoarthritis study could be used to study the development and progression of atherosclerosis. They developed an automated deep learning based algorithm to segment and quantify the popliteal artery wall in images obtained over 10 years in over 4,700 individuals. Their approach, which they named FRAPPE, or fully automated and robust analysis technique for popliteal artery evaluation, was able to reduce the average time required for segmentation analysis from four hours to eight minutes per image. They applied weights based on confidence for each segment to automatically improve the accuracy of aggregate measurements such as mean wall thickness or mean lumen area. Their data suggest that this automated method can rapidly generate useful information on atherosclerosis from MRI images obtained as part of other studies. When combined with other data. This approach may facilitate novel discovery in secondary analyses of existing studies in an efficient and cost effective way. And that's all for issue one of 2020. Come back next time for more of the latest papers from Circulation: Genomic and Precision Medicine. Speaker 2: This podcast is copyright American Heart Association 2020.
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December 2019
04/08/2020
December 2019
Jane Ferguson: Hi, everyone. Welcome to episode 35 of Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson, an assistant professor of medicine at Vanderbilt University Medical Center, and an associate editor at Circulation: Genomic and Precision Medicine. This episode is first airing in December 2019. Let's see what we published this month. Our first paper is an “Integrated Multiomics Approach to Identify Genetic Underpinnings of Heart Failure and Its Echocardiographic Precursors: The Framingham Heart Study” from Charlotte Anderson, Ramachandran Vasan and colleagues from Herlev and Gentofte Hospital, Denmark and Boston University. In this paper, the team investigated the genomics of heart failure, combining GWAS with methylation and gene expression data, to prioritize candidate genes. They analyzed four heart failure related and eight echocardiography related phenotypes in several thousand individuals, and then identified SNPs, methylation markers, and differential gene expression associated with those phenotypes. They then created scores for each gene, based on the rank of statistical significance, aggregated across the different omics analysis. They examined the top ranked genes for evidence of pathway enrichment, and also looked up top SNPs for PheWAS associations in UK Biobank, and examined tissue specific expression in public data. While their data cannot definitively identify causal genes, they highlight several genes of potential relevance to heart failure pathogenesis, which may be promising candidates for future mechanistic studies. The next paper is “Genetic Determinants of Lipids and Cardiovascular Disease Outcomes: A Wide-Angled Mendelian Randomization Investigation” and comes from Elias Allara, Stephen Burgess and colleagues, from the University of Cambridge and the INVENT consortium. While it has been established, therapies to lower LDL cholesterol and triglycerides lead to lower risk of coronary artery disease, it remains less clear whether these lipid lowering efforts can also reduce risk for other cardiovascular outcomes. The team set out to address this question using Mendelian randomization. They generated genetic predictors of LDL cholesterol and triglycerides using data from the Global Lipids Genetics Consortium, and then assessed whether genetically predicted increased LDL and triglycerides associated with risk of cardiovascular phenotypes using UK Biobank data. Beyond CAD, they found that higher LDL was associated with abdominal aortic aneurysm and aortic valve stenosis. High triglyceride levels were positively associated with aortic valve stenosis and hypertension, but inversely associated with venous thromboembolism and hemorrhagic stroke. High LDL cholesterol and triglycerides were also associated with heart failure, which appeared to be mediated by CAD. Their data suggests that LDL lowering may have additional cardiovascular benefits in reducing aortic aneurism and aortic stenosis, while efforts to lower triglycerides may reduce the risk of aortic valve stenosis, but could result in increased thromboembolic risk. Next up is a paper from Steven Joffe, G.L. Splansky and colleagues, from the University of Pennsylvania and Boston University, on “Preferences for Return of Genetic Results Among Participants in the Jackson Heart Study and Framingham Heart Study”. There has been increasing discussion and concern about how to handle genetic data, and whether genetic results should be returned to participants, and under which circumstances. In this study, the teams that had to assess what participants themselves think. They query participants in the Jackson Heart Study, the Framingham Heart Study and the FHS Omni cohort, presenting them with potential scenarios that varied by five factors including phenotype severity, actionability, reproductive significance and relative of the absolute risk of the phenotype. Across all scenarios, 88 to 92% of respondents said that they would definitely or probably want to learn their result. In Jackson Heart Study respondents, factors increasing the desire for results included a positive attitude towards genetic testing, lower education, higher subjective numeracy, and younger age. The five pre-identified factors did not affect desire to receive results in Jackson Heart Study. Among Framingham Heart Study respondents, desire for results was associated with higher absolute risk, presentability, reproductive risk and positive attitudes towards genetic testing. Among FHS Omni respondents, desire for results was associated with positive attitudes towards genetic testing and younger age. Overall, these data show that across a variety of studies, there a high level of interest in receiving genetic results and that these are not necessarily linked to the phenotype or clinical significance of the results themselves. The next paper concerns “Peripheral Blood RNA Levels of QSOX1 and PLBD1 Are New Independent Predictors of Left Ventricular Dysfunction after Acute Myocardial Infarction” and this comes from Martin Vanhaverbeke, Peter Sinnaeve and colleagues, from University Hospital Leuven. They were interested in understanding whether they could identify subsequent left ventricular dysfunction in patients who suffered an acute myocardial infarction. They obtained blood and performed RNA-Seq at multiple time points in 143 individuals, following acute MI, to identify transcripts that were associated with subsequent LV dysfunction. They validated candidate gene transcripts in a validation sample of 449 individuals, confirming that expression of QSOX1 and PLBD1 at admission, were associated with LV dysfunction at follow-up. Adding QSOX1 to a model, consisting of clinical variables and cardiac biomarkers, including NT proBNP, had an incremental predictive value. They took their findings to a pig model and found that whole blood expression of both genes was associated with neutrophil infiltration in these ischemic myocardium. This study suggests that expression of QSOX1 and PLBD1 following MI, may have utility in predicting development of LV dysfunction and may be markers of cardiac inflammation. The next paper is a research letter from Hanna Hanania, Denver Sallee and Dianna Milewicz, from the University of Texas Health Science Center, and Emory University School of Medicine. Who set out to answer the question, “Do HCN4 Variants Predisposed to Thoracic Aortic Aneurysms and Dissections?” Previous work has suggested that rare variants in HCN4 associated with thoracic aortic disease, including ascending aortic dilation, left ventricular noncompaction cardiomyopathy, and sinus bradycardia. However, the evidence for disease segregation was relatively weak. The team set out to explore these potential associations using exome sequencing data from 521 individuals, from 347 unrelated families with heritable thoracic aortic disease, as well as 355 individuals with early onset sporadic aortic dissections, but no family history of disease. They identified a missense variant G482R, which segregated with disease in four unrelated families, was absent from the nomad database and was predicted to disrupt protein function and have deleterious effects. Their data support the evidence that HCN4 rare variants can cause heritable thoracic aortic disease with left ventricular noncompaction cardiomyopathy and bradycardia. Our final paper is a white paper from H. Li, X. J. Luo and colleagues, from the National Heart, Lung and Blood Institute at the NIH, and will likely interest anybody who applies for NIH grants, which I'm assuming is most of you listening to this podcast. Their paper on, “Portfolio Analysis of Research Grants in Data Science Funded by the National Heart, Lung, and Blood Institute”, delves into the type of data science research funded by NHLBI between fiscal year 2008 and fiscal year 2017. They identified 630 data science focused grants, funded by NHLBI, using keywords for bioinformatics and computational biology. They then analyzed the distribution of these grants across different disease areas and compared the results to data science grants funded by other NIH institutes or centers. Around 64% of funded grants were for cardiovascular disease with 22% in lung and airway disease, 12% in blood disease and 2% in sleep. NHLBI's investment in data science research grants averaged about 1% of its overall research grant investment, and this remained constant over the 10-year period. However, this proportion does not include other large scale investment by NHLBI in building data science platforms through other mechanisms. Of relevance to our listeners across all institutes, most funded data science research grants were related to genomics and other omics data. In this paper they include lots of graphs breaking down grant distributions across different categories, so it's worth a look as you plan your next grant application. That's all for December and the final episode of 2019. Thanks for listening and happy holidays to all who celebrate. I'm excited to be back in 2020, to kick off the next decade of exciting advances in genomic and precision cardiovascular medicine. This podcast was brought to you by Circulation: Genomic and Precision Medicine, and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.
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34 November 2019
12/04/2019
34 November 2019
Jane Ferguson: Hi there. Welcome to the November 2019 issue of Getting Personal: Omics of the Heart. I'm Jane Ferguson. This is your podcast from Circulation: Genomic and Precision Medicine. Let's get started. First up from Eric Curruth, Christopher Haggerty and colleagues from Geisinger, we have a paper entitled, “Prevalence and Electronic Health Record-based Phenotype of Loss-of-function Genetic Variance in Arrhythmogenic Right Ventricular Cardiomyopathy-associated Genes”. In this study, the team set out to understand the phenotypic consequences of variants and desmosome genes which has been associated with a arrhythmogenic right ventricular cardiomyopathy or ARVC. In clinical genetic testing, secondary findings of pathogenic or likely pathogenic variants in desmosome genes are recommended for clinical reporting. However, relatively little is known about the phenotypic consequences of these variants in a general clinical population. The team obtained whole exome sequencing data for over 61,000 individuals from the DiscovEHR cohort, part of the Geisinger MyCode Community Health Initiative. They then screened individuals for a putative loss of function variants in PKP2, DSC2, DSG2, and DSP. They evaluated ARVC diagnostic criteria using previously conducted ECG and echocardiograms and performed a phenom-wide association study or PHeWAS using EHR derived phenotypes. They found 140 people with an ARVC variant in one of the four genes, none of whom had an existing diagnosis of ARVC in the EHR. Further, there were no measurable differences in their ECG or echocardiogram findings compared with matched controls. There were also no associations with any heart disease phenotypes as assessed by PHeWAS. Overall, they report a prevalence of ARVC loss of function variants of around one in 435 in a general clinical population of predominantly European descent, but they did not find evidence that these variants associated with specific phenotypes. Thus, the clinical relevance of putative loss of function variants in desmosome genes still remains to be determined. The next paper is titled, “MRAS Variants Cause Cardiomyocyte Hypertrophy in Patients-specific iPSC-derived Cardiomyocytes”. Additional evidence for MRS as a definitive Noonan syndrome susceptibility gene. This comes from Erin Higgins, Michael Ackerman, and colleagues from the Mayo Clinic. They were interested in understanding whether a recently identified Noonan syndrome variant in the MRS gene was necessary and sufficient to cause Noonan syndrome with cardiac hypertrophy. They generated induced pluripotent STEM cell or IPS C lines from patient derived cells carrying the glycine 23 veiling variant and MRS. In addition to isogenic control cells where the pathogenic variant was corrected back to wild-type using CRISPR CAS nine gene editing, they also created a disease model cell line by introducing the MRS variant into unrelated control cells. They then comprehensively characterized the phenotypes of the three cell lines using a variety of approaches including microscopy, immunofluorescence, single cell RNA seek, Western blot, qPCR, and live cell calcium imaging. Both the patient derived and the disease model IPS cardiomyocytes were larger than control cells and demonstrated changes in gene expression and intracellular pathway signaling characteristic of cardiac hypertrophy. The patient and disease model cells also displayed impaired calcium handling. Through in-vitro phenotyping, the team was able to demonstrate that the glycine 23 veiling MRS variant elicits a cardiac hypertrophy phenotype and IPSC cardiomyocytes, that strongly suggests that this variant is responsible for the observed Noonan syndrome associated cardiac hypertrophy in the effected patients. Next up is a review from Christopher Lee, Iftikhar Kullo, and colleagues also from the Mayo Clinic on “New Case Detection by Cascade Testing in Familial Hypercholesterolemia: A Systematic Review of the Literature”. In this review they set out to systematically assess cascade testing programs for familial hypercholesterolemia, a disease which has a prevalence of about one and 250 but is estimated to be diagnosed in under 10% of patients. They identified published studies across the world which had conducted cascade testing and had reported the number of index cases and number of relatives tested and had also specified their methods of contacting relatives and testing. Using these criteria, they identified 10 studies for inclusion spanning several European countries, South Africa, New Zealand, Australia, and Brazil. The team calculated the proportion of relatives testing positive and the number of new cases per index case to facilitate comparison between studies. The mean number of programs was 242 with an average of 826 relatives per study. The average yield was 45%, ranging from 30 to 60%. the mean new cases per index case was 1.65 with a range of 0.22 to 8.0. Studies that use direct contact versus indirect contact for relatives and those that tested beyond first degree relatives had a greater yield. Further, active sample collection versus collection at clinic and using genetic testing versus biochemical testing was similarly associated with a higher yield. Despite differences between the United States and other countries, applying these strategies when establishing new cascade testing programs in the US may help promote success of these programs. Our next paper concerns “Randomization of Left-right Asymmetry and Congenital Heart Defects: The Role of DNAH5 in Humans and Mice”. And this was conducted by Tabea Nöthe-Menchen, Heymut Omran, and colleagues from University Children's Hospital Muenster and the PCD study group. They were interested in understanding the relationship between congenital heart defects and laterality defects where internal organs are atypically positioned, such as in a mirror image as occurs in situs inversus. Ciliary dyskinesia is thought to play a role in situs inversus and the most frequently mutated gene in primary ciliary dyskinesia is DNAH5. The team does hypothesize that DNAH5 mutations may play a role in congenital heart disease. They characterized phenotypes in 132 patients with primary ciliary dyskinesia carrying disease causing DNAH5 mutations and also studied left right access establishment using a DNAH5 mutant mouse model. 66% of patients in their study had laterality defects, 88% of whom presented with situs inversus totalis and 6% presented with congenital heart disease. In the mass model, they observed immotile cilia, impaired flow with the left right organizer and randomization of nodal signaling with normal reversed or bilateral expression of key molecules. Their study thus demonstrates that mutation of DNAH5 is associated with congenital heart defects and they further highlight the ciliary mechanisms underlying defects and development of left right positioning during embryogenesis. Consideration of celiopathy related symptoms may be warranted when examining patients with congenital heart defects. Next up, we have a research letter from William Goodyear, Marco Perez and colleagues from Stanford University on “Broad Genetic Testing in a Clinical Setting Uncovers a High Prevalence of Titan Loss-of-Function Variants in Very Early-Onset Atrial Fibrillation”. They were interested in understanding genetic determinants of atrial fibrillation and hypothesized that causal genetic variants would be enriched in individuals with very early onset AF, who are diagnosed with AF under the age of 45 with no other significant comorbidities. They identified 25 families comprising 23 unrelated patients with very early onset AF who had been evaluated and received genetic counseling at Stanford between 2014 and 2018. The mean age of AF diagnosis was 27.2 years and 76% of patients were male. 40% of patients had a first or second degree relative with very early onset AF, while 36% at first or second degree relatives with either early onset idiopathic cardiomyopathy, unexplained sudden death or strokes. 85% of patients were identified as having at least one rare variant in a cardiomyopathy associated gene. Six patients carried actionable pathogenic or likely pathogenic variants, four of which were in the titan gene. A subset of individuals were further evaluated by MRI or computed tomography on average 817 days after their first presentation and this revealed high rates of cardiac abnormalities including reduced ventricular function, chamber enlargement, borderline LV non compaction, or late gadolinium enhancement. These were not noted on echocardiogram at presentation, suggesting there may have been subsequent disease development or progression. Overall, this study highlights a high rate of familial disease and implicates an association between very early onset AF and rare variants in titan before the clinical onset of cardiomyopathy. The final letter this month comes from Yu Xia, Shaoxian Chen, Ping Li, Jian Zhuang and colleagues from Guangdong Academy of Medical Sciences and is entitled, “A Novel Mutation in MYH6 in Two Unrelated Chinese Han Families with Familial Atrial Septal Defect”. They report on two unrelated families who presented with secundum atrial septal defect or ASD2. Whole exome sequencing revealed a novel variant and the MYH6 gene in both families, with the same variant present in all effected individuals but not in unaffected family members or unrelated controls. Because other variants in MYH6 have been reported to effect myofibril formation. The team studied the effect of the novel variant on the myofibrillar organization through transient transfection of CTC 12 cells. The MYH6 E526K variant was associated with a reduced striated I pattern and increased non-striated patterning. There was no effect on ATPase activity. Protein modeling suggested a variant of the effective position would reduce hydrogen bonding between alpha helices in the actin interface two region, increasing the volume of the cavity between the alpha helices and promoting the exposure of the alkaline side chain in the actin binding region. This could impair the interaction between the myosin motor head and actin. What these data suggests are that this novel MYH6 heterozygous variant may underlie ASD2 in two unrelated Chinese Han families by impairing myofibrillar organization. That's all for November 2019. Thank you for listening and I look forward to being back in December for the final episode of 2019. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association council on genomic and precision medicine. This program is copyright American Heart Association 2019.
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33 October 2019
10/21/2019
33 October 2019
Jane Ferguson: Hello. Welcome to episode 33 of Getting Personal: Omics Of The Heart, your podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson. This episode is from October 2019. Let's get started. First up is a paper from Sébastien Thériault, Yohan Bossé, Jean-Jacques Schott and colleagues from Laval University, Quebec and INSERM in Mont. They published on genetic association analyses, highlight IL6, ALPL and NAV1 as three new susceptibility genes underlying Calcific Aortic Valve Stenosis. In this paper, they were interested in finding out whether they could identify novel susceptibility genes for Calcific Aortic Valve Stenosis, or CAVS, which is a severe and often fatal condition with limited treatment options other than surgical aortic valve replacement. They conducted a GWAS meta-analysis across four European ancestry cohorts comprising over 5,000 cases and over 354,000 controls. They identified four loci at genome-wide significance, including two known loci in LPA and PALMD as well as two novel loci, IL6 which encodes the interleukin six cytokine, and ALPL, which encodes an alkaline phosphatase. They then integrated transcriptomic data from 233 human aortic valves to conduct the transcriptome wide association study and find an additional risk locus associated with higher expression of NAV1 encoding neuron navigator one. Through fine mapping, integrating conservation scores, and methylation peaks, they narrowed down the putative causal variants at each locus identifying one snip in each of PALMD and IL6 as likely causal in addition to two candidates snips at ALPL and three plausible candidate snips in NAV1. Phenome-Wide Association Analysis, or PheWAS of the top candidate functional snips found that the IL6 risk variant associated with higher eosinophil count, pulse pressure and systolic blood pressure. Overall, this study was able to identify novel loci associated with CAVS potentially implicating inflammation and hypertension in CAVS etiology. Additional functional studies are required to further explore these potential mechanisms. Next up is a paper from Elisavet Fotiou, Bernard Keavney and colleagues from the University of Manchester. Their paper entitled Integration of Large-Scale Genomic Data Sources With Evolutionary History Reveals Novel Genetic Loci for Congenital Heart Disease explored the genetic etiology of sporadic non syndromic congenital heart disease using an evolution informed approach. Ohnologs are related genes that have been retained following ancestral whole genome duplication events which occurred around 500 million years ago. The authors hypothesized that ohnologs which were retained versus duplicated genes that were lost were likely to have been under greater evolutionary pressure due to the need to maintain consistent gene dosage. For example, as could occur when the resulting proteins form complexes that require stochiometric balance. Thus, ohnologs may be enriched for genes that are sensitive to dosage. The group analyzed copy number variant data from over 4,600 non syndromic coronary heart disease patients as well as whole exome sequence data from 829 cases of Tetralogy of Fallot. Compared to control data obtained from public databases, there was evidence for significant enrichment in CHD associated variants in ohnologs but not in other duplicated genes arising from small scale duplications. Through this and various other filtering steps to prioritize likely variants, the group was able to identify 54 novel candidate genes for congenital CHD highlighting the utility of considering the evolutionary origin of genes in the search for disease relevant biology. Next, we have a clinical letter entitled Pathological Overlap of Arrhythmogenic Right Ventricular Cardiomyopathy and Cardiac Sarcoidosis from Ashwini Kerkar, Victoria Parikh and colleagues at Stanford University. They describe a case of a 50 year old woman previously healthy and a long distance runner who presented with tachycardia. She was found to have normal left ventricular size but severe right ventricular enlargement and systolic dysfunction. Genetic testing using an Arrhythmogenic Right Ventricular Cardiomyopathy or ARVC panel identified a variant in DSG2. through cascade testing it was found that two of the patient's three children also carried this variant. The patient experienced worsening RV failure and subsequently underwent heart transplantation at age 55. Pathology of the heart showed evidence of cardiac sarcoidosis. There have been some previous reports of overlap in ARVC and cardiac sarcoid pathology but not in cases with a high confidence genetic diagnosis such as this one. This case raises the possibility of shared disease mechanisms underlying ARVC and cardiac sarcoidosis and suggests that therapies aimed at immune modulation may also have utility in ARVC. However, further work is required to test this hypothesis. Our next paper is a perspective piece from Babken Asatryan and Helga Servatius from Bern University Hospital. In Revisiting the Approach to Diagnosis of Arrhythmogenic Cardiomyopathy: Stick to the Arrhythmia Criterion!, they outline the challenges in defining diagnostic criteria for a Arrhythmogenic Right Ventricular Cardiomyopathy or ARVC, given the variable presentation of the disease. Given recent advances in knowledge, particularly in recognizing disease overlap with Arrhythmogenic Left Ventricular Cardiomyopathy or ALVC and Biventricular Arrhythmogenic Cardiomyopathy, a new clinical perspective was warranted. The Heart Rhythm Society updated their recommendations this year to introduce a new umbrella term that better encompasses the spectrum of disease, Arrhythmogenic Cardiomyopathy or ACM. This recommends the arrhythmia criterion Should be used as a first line screening criteria for ACM. This is a broad criteria and a definitive diagnosis of ACM requires exclusion of systemic disorders such as sarcoidosis, amyloidosis, mild carditis, Chagas disease, and other cardiomyopathies. Implementation of this new approach to diagnosis may require more extensive investigation of arrhythmias including the use of ambulatory ECG monitors or cardiac loop recorders. These changes may also affect who's referred for genetic testing, potentially shifting diagnoses towards genotype rather than phenotype based disease classifications. Despite challenges and adopting new approaches, it is hoped that these changes will ultimately serve to improve risk stratification and allow for improved disease management and intervention to prevent sudden cardiac death. We end with a scientific statement chaired by Sharon Cresci and co-chaired by Naveen Pereira with a writing group representing the AHA Councils on Genomic and Precision Medicine, Cardiovascular and Stroke Nursing and Quality of Care and Outcomes Research entitled Heart Failure in the Era of Precision Medicine: A Scientific Statement From the American Heart Association. This paper provides a comprehensive overview of the current state of omics technologies as they relate to the development and progression of heart failure and considers the current and potential future applications of these high throughput data for precision medicine with respect to prevention, diagnosis and therapy of heart failure. They discuss advances in genomics, pharmacogenomics, epigenomics, proteomics, metabolomics, and the microbiome, and integrate the findings from this rapidly developing field as they pertain to new methods to diagnose, treat, and prevent heart failure. And that's it for October. I hope to see many of you at AHA Scientific Sessions in Philadelphia in November and look forward to bringing you more of the best new science next month. Thanks for listening. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.
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32 September 2019
09/24/2019
32 September 2019
Jane Ferguson: Hi, everyone. Welcome to Getting Personal: Omics of the Heart, the monthly podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson, an assistant professor of medicine at Vanderbilt University Medical Center and an associate editor at CircGen. This is episode 32 from September 2019. Starting off this month, we have a paper on Genetic Mosaicism in Calmodulinopathy brought to us by Lisa Wren, Alfred George and colleagues from Northwestern University. They were interested in exploring the disease phenotypes that result from variation in the calmodulin genes, CALM1, 2 and 3. Mutations in calmodulin are known to associate with congenital arrhythmia, but the group hypothesized that there may be a broader range of phenotypes associated with calmodulin mutations. They report on four unrelated families all with pro bands exhibiting symptoms of prolonged QTC interval and documented ventricular arrhythmia. They conducted targeted exome sequencing in these individuals and in their families and identified mutations in calmodulin genes, including two novel mutations. In one family with multiple occurrences of intrauterine fetal demise, there was evidence for sematic mosaicism in both parents. The team studied the two novel mutations and found that the variants led to alterations in a calcium binding site resulting in impaired calcium binding. In human induced pluripotent stem cell derived cardiomyocytes, the team showed that the mutations impaired calcium dependent inactivation of L-type calcium channels and prolonged action potential duration. Their study not only demonstrates that mutations in calmodulins can cause dysregulation of L-type calcium channels, but that parental mosaicism maybe a factor in families with unexplained fetal arrhythmia or fetal demise. Our next paper come from Wan G Pang, Christiana Kartsonaki, Michael Holmes and Zing Min Chen from the University of Oxford and Peking University Health Science Center and is entitled Physical Activity, Sedentary Leisure Time, Circulating Metabolic Markers, and Risk of Major Vascular Diseases. In this study, the authors were interested in finding out whether circulating metabolites are associated with the relationship between physical inactivity or sedentary behavior and increased risk of cardiovascular disease. They identified over 3000 cases of incident CVD from the China Kadoorie Biobank and included over 1400 controls without CVD. They measured 225 different metabolites and baseline plasma samples using NMR. They used measures of self-reported physical activity and sedentary leisure time to associate physical activity with circulating metabolites, and then they ran analysis to relate the metabolites to CVD. Physical activity and sedentary leisure time were associated with over 100 metabolic markers. In general, the patterns of associations were similar using either activity measure. Physical activity was inversely related to very low and low density HDL particles, but positively related to large and very large HDL particle concentrations. Physical activity was also inversely associated with alanine, glucose, lactate, acetoacetate, and glycoprotein acetyls. When they examined the associations of these same metabolites with CVD, the directions were generally consistent with expectation, going on the premise that physical activity is protective, and that sedentary behavior is a risk factor for CVD. Their analyses suggests that metabolite markers could explain about 70% of the protective associations of physical activity and around 50% of the risk associations of sedentary leisure time with cardiovascular disease. Next up, we have a paper on Biallelic Variants in ASNA1, Encoding a Cytosolic Targeting Factor of Tail-Anchored Proteins, Cause Rapidly Progressive Pediatric Cardiomyopathy, coming from Judith Verhagen, Ingrid van de Laar and colleagues from University Medical Center Rotterdam. Their focus was on pediatric cardiomyopathies, which are both clinically and genetically heterogeneous. They had identified a family where two siblings had died during early infancy of rapidly progressive dilated cardiomyopathy. Through exome sequencing, they identified variants in the ASNA-1 gene and established that the children were compound heterozygotes for the variants. This highly conserved gene encodes an ATPase, which is required for post-translational membrane insertion of tail-anchored proteins. The team looked at expression of this protein in patient samples and then followed this up with functional analyses using cells and zebrafish. They found that one of the variants was predicted to result in a premature stop codon. In support of this, they observed decreased protein expression in myocardial tissue and skin fibroblasts. The other variant caused a missense mutation, and the team found that this resulted in protein misfolding, as well as less effective tail-anchored protein insertion. In zebrafish, knock out of the ASNA1 gene resulted in reduced cardiac contractility and early lethality, which could not be rescued by either version of the variant mRNA. This translational study highlights the importance of the ASNA1 gene as a cardiomyopathy susceptibility gene and further reveals the importance of tail-anchored membrane protein insertion pathways in cardiac function. The next paper from Karni Moshal, Gideon Koren and colleagues from Brown University is entitled LITAF Regulates Cardiac L-Type Calcium Channels by Modulating NEDD 4-1 Ubiquitin Ligase. In this paper, the authors report on the role of ubiquitination as a crucial component in cardiac ion channel turnover and action potential duration. Previous genome wide association studies of QT interval had identified snips in or near genes regulating protein ubiquitination, particularly the LITAF or lipopolysaccharide-induced tumor necrosis factor gene. Using zebrafish, the team performed optical mapping in hearts to identify calcium and found that knocked down of LITAF resulted in an increase in calcium transients. They studied intracellular calcium handling and rapid derived cardiomyocytes and found that over expression of LITAF caused a decrease in L-type calcium channel current and abundance of the L-type calcium channel alpha1c sub unit or Cava1c, whereas LITAF knocked down increased calcium channel current and Cava1c protein. LITAF downregulated total and surface pools of Cava1c via increased Cava1c ubiquitination and lysosomal degradation in tsA201 kidney cells. There was evidence of colocalization between LITAF and L-type calcium channel, or LTCC, in the tsA201 kidney cells and in cardiomyocytes. In the tsA201 cells, NEDD4-1 protein increased Cava1c ubiquitination, but a catalytically inactive form of NEDD4-1 had no effect. Cava1c ubiquitination was further increased by co-expressed LITAF NEDD4-1, but not the inactive version of NeNEDD4-1. NEDD4-1 knockdown abolished the negative effect of LITAF on L-type calcium channel current and Cava1c levels in three week old rapid cardiomyocytes. Taken together, these data show that LITAF acts as an adapter protein promoting NEDD4-1 mediated ubiquitination and subsequent degradation of LTCC, highlighting LITAF as a novel regulator of cardiac excitation. Rounding out this issue is a review on the Gut Microbiome and Response to Cardiovascular Drugs from Sony Tuteja and Jane Ferguson from the University of Pennsylvania and Vanderbilt University Medical Center. Since that last author is me, I'm sure I have a biased view of the importance of the topic, but the increasing awareness of the microbiome in every aspect of health has also led to increased awareness of the role of commensal microbiota in drug metabolism, including in the metabolism of drugs used to treat cardiovascular diseases. In this article, we aim to review what is currently known about how the gut microbiome interacts with cardiovascular drugs and to summarize some of the mechanisms whereby gut microbiota might affect drug metabolism. Early evidence suggests that the gut microbiome modulates response to statins and antihypertensive medications, but there may be many other drugs that are susceptible to interaction with microbiota. Drug metabolism by the gut microbiome can result in altered drug pharmacokinetics and pharmacodynamics or in the formation of toxic metabolites which can interfere with drug response. While we are still in a relatively early stage in this field, we suggest that a better understanding of the complex interactions of the gut microbiome, host factors and response to medications will be important for the development of novel precision therapeutics in cardiovascular disease prevention and treatment. That's all for the September issue of Circulation: Genomic and Precision Medicine. Come back next month for the next installment. Thanks for listening. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.
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27 August 2019
08/27/2019
27 August 2019
Jane Ferguson: Hello, and welcome to Getting Personal, Omics of the Heart, your monthly podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson. It is August, 2019, and this is episode 31. Let's get started. Our first paper comes from Freyja van Lint and Cynthia James, from University Medical Center Utrecht, and is entitled Arrhythmogenic Right Ventricular Cardiomyopathy-Associated Desmosomal Variants Are Rarely De Novo, Segregation and Haplotype Analysis of a Multinational Cohort. In this study, the team was interested in exploring variants that are associated with arrhythmogenic right ventricular cardiomyopathy or ARVC. ARVC is often attributable to pathogenic variants in genes encoding cardiac desmosomal proteins, but the origin of these variants had not been comprehensively studied. The investigators identified ARVC probands meeting 2010 task force criteria from three ARVC registries in the United States and Europe and who had undergone sequencing of desmosomal genes. All 501 probands, 322 of them, or over 64%, carried a pathogenic or likely pathogenic variant in the desmosomal genes PKP2, DSP DSG2, DSC2, and JUP. The majority of these, over 75%, we're not unique with these variants occurring in more than one proband. The team performed cascade screening and were able to identify the parental origin of almost all of the variants. However, they identified three de novo variants, including two whole gene deletions. They conducted haplotype analysis for 24 PKP2 variants across 183 seemingly unrelated families and concluded that all of these variants originated from common founders. This analysis sheds light on the origin of variants in desmosomal genes and suggests that the vast majority of these ARVC variants originate from ancient founders with only a very small proportion of de novo variants. These data can inform clinical care particularly concerning genetic counseling and cascade screening of relatives. The next paper continues a theme of cardiomyopathy and comes from Derk Frank, Ashraf Yusuf Rangrez, Corinna Friedrich, Sven Dittmann, Norbert Frey, Eric Schulze-Bahr and colleagues from University Medical Center Schleswig-Holstein. In this paper, Cardiac α-Actin Gene Mutation Causes Atrial-Septal Defects Associated with Late-Onset Dilated Cardiomyopathy, the team was interested in understanding the genetics of familial atrial-septal defect. They studied large multi-generational family with 78 family members and mapped a causal variant on chromosome 15q14, which caused nonsynonymous change in exon 5 of the ACTC1 gene. In silico tools predicted this variant to be deleterious. Analysis of myocardial tissue from an affected individual revealed sarcomeric disarray, myofibrillar degeneration, and increased apoptosis. Proteomic analysis highlighted extracellular matrix proteins as being affected. The team over-expressed the mutation in rats and found structural defects and increased apoptosis in neonatal rat ventricular cardiomyocytes and confirmed defects in actin polymerization and turnover which affected contractility. These data implicate the variant in ACTC1 as causing atrial-septal defects and late-onset cardiomyopathy in this family and revealed the underlying molecular mechanisms affecting development and contractility. The next paper is entitled Characterization of the CACNA1C-R518C Missense Mutation in the Pathobiology of Long-QT Syndrome Using Human Induced Pluripotent Stem Cell Cardiomyocytes Shows Action Potential Prolongation and L-Type Calcium Channel Perturbation, and it comes from Steven Estes, Michael Ackerman and colleagues at the Mayo Clinic. They set out to use patient-derived human induced pluripotent stem cells to understand the pathogenicity of a variant in the CACNA1C gene in Long-QT Syndrome. They obtained cells from dermal punch biopsy from an individual with long-QT and a family history of sudden cardiac death who carried an R518C missense mutation in CACNA1C. Starting with fibroblasts, they reprogrammed the cells into iPSCs and then differentiated these into cardiomyocytes. They corrected the mutation back to wild type using CRISPR/Cas9 and then compared the cardiomyocytes carrying the original patient mutation with isogenic corrected cardiomyocyte controls. They found significant differences in action, potential duration, and in calcium handling. Patch clamp analysis revealed increased L-type calcium channel window current in the original mutation-carrying cells in addition to slow decay time and increased late calcium current compared with the isogenic corrected control human iPSC cardiomyocytes. These data strongly suggest that CACNA1C is a long-QT susceptibility gene and demonstrate the potential in using patient-derived iPSCs and CRISPR/Cas9 to understand underlying mechanisms linking variants to disease. The final paper this month is Blood Pressure-Associated Genetic Variants in the Natriuretic Peptide Receptor-1 Gene Modulate Guanylate Cyclase Activity and comes from Sara Vandenwijngaert, Chris Newton-Cheh and colleagues on behalf of the CHARGE+ Exome Chip Blood Pressure Consortium, the CHD Exome+ Consortium, the Exome BP Consortium, the GoT2D Consortium, the T2D-GENES Consortium, and the UK Biobank CardioMetabolic Consortium Blood Pressure Working Group. This team wanted to understand how variants in the NPR-1 gene affect the function of the atrial natriuretic peptide receptor-1. They performed a meta-analysis across over 491,000 unrelated individuals, including both low frequency and rare variants in NPR-1 to identify their association with blood pressure. They identified three nonsynonymous variants associated with altered blood pressure at genome-wide significance and examined the function of these variants in vitro. Using cells expressing either wild type NPR-1 or one of the three identified variants, they explored the impact of the variants on the ability of cells to catalyzes the conversion of guanosine triphosphate to cyclic 3′,5′-guanosine monophosphate in response to binding of atrial or brain natriuretic peptide. Increased levels of cyclic GMP are known to decrease blood pressure by inducing by natriuresis, diuresis, and vasodilation. Two variants which associated with high blood pressure in the population meta-analysis were associated with decreased cyclic GMP in response to ANP or BNP in vitro, while one variant which associated with lower blood pressure in humans was associated with higher cyclic GMP production in vitro. These data show that variants affecting loss or gain of function in guanylate cyclase activity could have downstream effects on blood pressure at the population level. That's it for this month. Thank you for listening. We will be back with more next month. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.
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30 July 2019
07/17/2019
30 July 2019
Jane Ferguson: Hi everyone. Welcome to Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson and this is episode 30 from July 2019. First up we have a paper, the Subtype Specificity of Genetic Loci Associated With Stroke in 16664 cases and 32792 Controls, from Matthew Trailer and colleagues on behalf of the NINDS Stroke Genetics Network and the International Stroke Genetics Consortium. They were interested in understanding whether genetic loci previously found to be associated with stroke have distinct associations with stroke subtypes, specifically ischemic and hemorrhagic stroke. They compiled data sets through an international consortium to analyze 16664 stroke cases and 32792 controls, all of European ancestry. The cases were subtyped using two different stroke classification systems: the Trial of ORG 10172 in Acute Stroke Treatment, or TOAST system, and the Causative Classification of Stroke, or CCS system. They selected genetic loci for consideration based on previous association with stroke in general or stroke subtypes in the MEGASTROKE consortium, which had included a large number of the subjects included in the present study. They used a Bayesian multinomial logistic regression approach to evaluate the association of snips at each locus with stroke subtypes identified under the TOAST and CCS classifications, giving five different case groups compared with a set of controls. 16 loci were taken forward for further analysis. There were seven loci which associated with both ischemic and hemorrhagic strokes subtypes, four which clearly associated with either ischemic or hemorrhagic stroke, with the rest showing less consistent effects. One locus, EDNRA, showed opposite affects for ischemic and hemorrhagic stroke. Overall, the findings indicate a large degree of genetic heterogeneity, but some overlap, suggesting common underlying pathophysiological pathways in different stroke subtypes, potentially related to small vessel disease. More detailed phenotyping and further analysis in large samples is required to fully understand genetic mechanisms underlying the risk of different stroke subtypes. And, just to add, this paper was previously submitted to the pre-print server Bio Archive. We support open science and are always happy to consider papers that have been submitted to pre-print servers. So, if you have a particularly cool paper on Bio Archive that fits our scope, do feel free to send it our way. Next up, we have a paper from Fabiola del Greco, Cristian Pattaro, Peter Pramstaller, Alessandera Rossini, and colleagues, from Eurac Research Institute for Biomedicine. This paper, entitled Lipidomics, Atrial Conduction, and Body Mass Index, Evidence from Association, Mediation, and Mendelian Randomization Models, aims to investigate the mechanisms underlying associations between circulating lipids and atrial conduction. They used mass spectrometry measurement of 151 sphingo- and phospholipids in plasma or serum from individuals who had undergone electrocardiogram measurements to ascertain P-wave duration. They first looked for associations in 839 individuals from the micro islets in South Tyrol, or MICROS study, based in Italy, and replicated in 951 participants of the Orkney Complex Disease Study, ORCADES, based in Scotland. They identified and replicated an association between levels of phosphatidylcholine 38-3 and P-wave duration, which was independent of cholesterol, triglycerides, and glucose levels. However, the association was mediated by BMI, and suggested that increased BMI may cause both increased levels of PC38-3 and longer P-wave duration, suggesting a role for body mass in altered lipids in atrial electrical activity. The next paper is a research letter from Hana Bangash, Iftikhar Kullo, and colleagues from the Mayo Clinic on Use of Twitter to Promote Awareness of Familial Hypercholesterolemia. Scientists and health professionals are increasingly using Twitter to communicate. This team wondered whether organized awareness campaigns, including Twitter events like Tweetathons, really make a different. They analyzed Twitter activity related to familial hypercholesterolemia in September 2018, during national cholesterol education month, which included an international familial hypercholesterolemia awareness day and Tweetathon. They also analyzed tweets from August and October 2018, where there was no formal awareness campaign and compared the FH Twitter activity with that of colorectal cancer, which did not have any formal awareness campaigns at that time. In September, FH-related tweets increased by 152.9% compared to August, and then declined by over 58% in October. The topic reach for familial hypercholesterolemia was 11.1 million in August, and increased over 250% in September to 37.7 million. The reach declined by over 71% in October to just over 10 million. In comparison, the reach for colorectal cancer declined from 453 million in August to 300 million in September and then increased to 677 million in October, which happened to be breast cancer awareness month. These data suggest that awareness campaigns like national cholesterol education month do lead to an increase in Twitter activity. However, this increase isn't necessarily sustained during the following month, and it remains unclear whether Twitter activity actually translates into a wider awareness amongst providers or patients, which could translate into clinical benefits. Nonetheless, as the use of Twitter increases, this may be a promising avenue to promote awareness and to disseminate knowledge. And, of course, I have to take this opportunity to mention that Circulation: Genomic and Precision Medicine is on Twitter and you can follow us @Circ_Gen to keep up with what's going on at the journal. Next up, we have a letter entitled B-iallelic Mutations in NUP205 and NUP210 Are Associated with Abnormal Cardiac Left-Right Patterning from WeiCheng Chen, Yuan Zhang, Sunhu Yang, Xiangyu Zhou, and colleagues from Tongji University. They set out to understand the genetic underpinnings of cardiac left-right patterning and to probe why individuals with situs inversus totalis, or SIT, where the chest organs are in a complete mirror image to typical, have almost no symptoms or complications, while individuals with heterotaxy, who have abnormal organ arrangement that is not a mirror image, typically have severe phenotypes including congenital heart disease. They performed whole exome and whole genome sequencing in 61 family trios with SIT or heterotaxy and identified ballielic missense mutations in nucleoporins NUP205 and NUP210. Nucleoporins comprise the main components of the nuclear pore complex in eukaryotic cells. The team generated induced pluripotent sense cells from peripheral blood cells of an affected patient and a healthy control, and found that there were impairments in protein interactions in the variant cells, particularly interactions with another crucial nucleoporin, NUP93. In zebra fish, NUP205 knockdown resulted in left-right assymetry and defects in heart looping formation in a subset of fish embryos. Knockdown of both NUP205 and NUP93 resulted in impairments in cilia and human retinal pigment epithelial cells. Gene expression analysis revealed affects in known cilia genes NEC2 and NEC3. Overall, this study provides evidence that mutations in nucleoporins NUP205 and NUP210 may cause defects in cardiac left/right patterning, potentially through effects on ciliary function. This issue closes with a letter and response conversation around a recent article on missense mutations in the FLNC gene, causing familial restrictive cardiomyopathy. Hisham Ahamed and Muthiah Subramanian from Amrita Institute of Medical Scientists write to share a case of a woman presenting with features of heart failure and muscular weakness consistent with distal myopathy who was found to carry a deletion in exome 37 of the FLNC gene. This case adds to the previous evidence published by Alvaro Roldan Sofia and Julian Palomino-Doza in March 2019 in our journal, Highlighting Mutations in the FLNC Gene in Cardiomyopathy. That's all for this month. Come back in August for your roundup of the next issue. Thanks for listening! This podcast was brought to you by Circulation: Genomic and Precision Medicine, and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association, 2019.
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29 June 2019
07/02/2019
29 June 2019
Jane Ferguson: Hi, everyone. Welcome to episode 29 of Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson from Vanderbilt University Medical Center and an associate editor at Circ: Genomic and Precision Medicine. Let's dive in and see what's new in the June issue. First up, Validation of Genome-Wide Polygenic Risk Scores for Coronary Artery Disease in French Canadians from Florian Wünnemann, Guillaume Lettre and colleagues from the University of Montreal. Polygenic scores have the potential to be used to predict disease risk, but have not been broadly validated in different populations. This team was interested in whether polygenic risk scores that have been found to predict coronary artery disease in European ancestry subjects in the UK Biobank would also predict disease in French Canadians. They calculated two different polygenic risk scores in over 3600 cases and over 7000 controls and tested their ability to predict prevalent, incident and recurrent CAD. Both scores predicted prevalent CAD, but did not perform as well in predicting incident or recurrent disease. This maybe because the majority of subjects were on statant treatment. Overall, the study confirms that polygenic risk scores for CAD developed in European ancestry can be used in other populations of European ancestry. However, further work is needed to develop and validate polygenic risk scores in other ancestries and to explore whether well performing risk scores can be developed to predict incident or recurrent disease. Our next paper comes from Farnaz Shoja-Taheri, Michael Davis and colleagues from Emory University and is entitled Using Statistical Modeling to Understand and Predict Pediatric Stem Cell Function. Stem cell therapy is emerging as a potential therapeutic option for treating pediatric heart failure, which otherwise can only be cured through heart transplantation. The success of stem cell therapy depends on many variables, including the reparative ability of the infused cells. In this paper, the author set out to test whether they could predict the behavior of c-kit+ progenitor cells or human CPCs using RNA seq and computational modeling. They obtained CPCs from 32 patients, including eight neonates whose cells are thought to have the highest reparative capacity, and they performed RNA sequencing. The team had previously developed regression models that could link gene expression data from sequencing to phenotypes in the cells, and they tested these models in the CPC cell lines. They tested seven neonate cell lines in vitro and found that cellular proliferation and the chemotactic potential of condition media matched what was predicted by the RNA seq-based model. They used pathway analysis to identify potential mechanisms regulating CPC performance and identified several genes related to immune response, including interleukins and chemokines. They further confirmed the presence of cytokines at the protein level that were associated with well performing cells showing that at least one of the outcomes could be functionally predicted using an ELISA ASA. This type of approach may prove useful to inform ongoing clinical trials to stem cell therapy in congenital heart disease. The next paper, Systems Pharmacology Identifies an Arterial Wall Regulatory Gene Network Mediating Coronary Artery Disease Side Effects of Antiretroviral Therapy comes to us from Itziar Frades, Johan Björkegren, Inga Peter and colleagues from the Icahn School of Medicine at Mount Sinai. They were interested in understanding mechanisms whereby antiretroviral therapy for HIV leads to increased risk for coronary artery disease. They analyzed the transcriptional responses to 15 different antiretroviral therapy or ART drugs in human cell lines and cataloged the common transcriptional signatures. They then cross-referenced these against gene networks associated with CAD and CAD related phenotypes. They found that 10 of 15 ART response networks were enriched for differential expression and connectivity in an atherosclerotic arterial wall of regulatory gene network identified as causal for CAD. They used cholesteryl ester loaded foam cells in an in vitro model to validate their findings and found that ART treatment increased cholesteryl ester accumulation in foam cells which was prevented when the key network regulator gene, PQBP1, was silenced. Their study highlights a gene network which is altered in response to ART and which promotes foam cells formation, highlighting a mechanistic link between HIV treatment and CAD. Targeting this network potentially through PQBP1 maybe a way to reduce the risk of CAD in individuals treated with antiretroviral drugs. The next paper comes from Brooke Wolford, Whitney Hornsby, Cristen Willer, Bo Yang and colleagues from the University of Michigan and is entitled Clinical Implications of Identifying Pathogenic Variants in Individuals With Thoracic Aortic Dissection. They were interested in whether exome sequencing in individuals with thoracic aortic dissection could identify disease associated variance. They conducted exome sequencing in 240 patients and 258 controls and screened 11 genes for potentially pathogenic variance. They identified 24 variance in six genes across 26 cases with no potentially pathogenic variance identified in the controls. They found that carriers of pathogenic variance had significantly earlier age of onset of dissection, higher rates of root aneurysm and greater incidents of aortic disease in family members, while patients without identified variance had more hypertension and a higher rate of smoking. Their study suggests that genetic testing should be considered in patients with thoracic artery dissection particularly in individuals with early age of onset before age 50 and no hypertension with the possibility of cascade screening to follow to identify at risk family members before onset of dissection and possible death. Our next paper is a research letter from Seyedeh Zekavat, Pradeep Natarajan and colleagues from Harvard Medical School, Investigating the Genetic Link Between Arterial Stiffness and Atrial Fibrillation. They aimed to investigate whether arterial stiffness is causal for atrial fibrillation using Mendelian randomization to probe genetic causality. They calculated the genetic component of the arterial stiffness index or ASI, a noninvasive measure of arterial stiffness, in over 131,000 individuals in the UK Biobank. They then assessed whether the genetic predictors of ASI defined as the top six independent variance were also associated with atrial fibrillation in over 225,000 participants in the UK Biobank and in over 588,000 individuals from a multi-ethnic GWAS. They found that the ASI genetic risk score was significantly associated with incident atrial fibrillation in both the UK Biobank and the multi-ethnic AF GWAS. The association held true even after adjustment for age, sex, smoking status, prevalent heart failure, prevalent hypertension, prevalent CAD, prevalent hypercholesterolemia, prevalent diabetes, heart rate, alcohol intake and exercise frequency in the UK Biobank participants. Because some people have hypothesized that atrial fibrillation may actually precede and cause arterial stiffness, the team did the reverse Mendelian randomization experiment and tested whether genetic predictors of AF were associated with the arterial stiffness index. They found no association suggesting that AF does not cause arterial stiffness. In summary, this paper provides genetic evidence supporting arterial stiffness as a causal contributor to atrial fibrillation and suggests that future randomized controlled studies would be warrantied to assess whether methods to reduce arterial stiffness could be protective against atrial fibrillation. The next research letter comes from Scott Damrauer, Kara Hardie, Reed Pyeritz and colleagues from the University of Pennsylvania and is entitled FBN1 Coding Variants and Nonsyndromic Aortic Disease. In this study, the authors were interested in characterizing the frequency of variance associated with Marfan syndrome in the general population. They analyzed data from the Penn Medicine BioBank looking at 12 variance in the FBN1 gene all of which have been reported to associate with Marfan syndrome. Of almost 11,000 individuals who underwent exome sequencing, they identified 70 individuals who were carriers of one of the 12 preselected FBN1 variance. These individuals ranged in age from age 28 to 87 years and 56% of them were male. They combed through clinical data from the participant's electronic health records, including office notes, diagnostic tests and imaging studies. Two individuals had a clinical diagnosis of Marfan syndrome while 21 individuals had evidence of cardiovascular phenotypes related to Marfan syndrome including mitral valve disease, dilated sinus of valsalva, dilated ascending aorta, descending thoracic or abdominal aneurysms or dissections or had undergone surgical procedures involving the mitral valve or thoracic aorta. Compared to age and sex matched controls without known or suspected pathogenic FBN1 variance, the FBN1 variant carriers were significantly more likely to have Marfan syndrome related cardiovascular disease. Although the majority of individuals carrying FBN1 variance did not have documented cardiovascular disease in this study, the data were somewhat limited, meaning that some affected individuals could have been missed. Thus, while the penetrance of these variance appears to be variable, the severe consequences of these FBN1 variance observed in some individuals suggests that clinical screening for carries of these variance is important. To round up this month's issue, we have a scientific statement led by Ferhaan Ahmad and Elizabeth McNally on Establishment of Specialized Clinical Cardiovascular Genetics Programs: Recognizing the Need and Meeting Standards. This statement comes from the American Heart Association Council on Genomic and Precision Medicine, the Council on Arteriosclerosis, Thrombosis and Vascular Biology, the Council on Basic Cardiovascular Sciences, the Council on Cardiovascular and Stroke Nursing, the Council on Clinical Cardiology and the Stroke Council. In this statement, the writing group lays out the importance of establishing specialized centers of care for individuals affected by inherited cardiovascular diseases. As cardiovascular genetics as a field continues to grow and as genomic medicine becomes part of practice, it is essential for programs to evolve to include this new knowledge and specialization. There are significant challenges in interpreting genetic test results and in evaluating counseling and managing the care of genetically at risk family members who have inherited pathogenic variance, but not yet shown signs of disease. Establishing specialized programs to combine cardiovascular medicine and genetics expertise is an effective way to allow for the integration of multiple types of clinical and genetic data and to improve diagnosis, prognostication and cascade family testing in affected individuals and their families. Training individuals in genetic cardiology will allow for improved care and management of risk in affected or at risk individuals and potentially pave the way for genotype specific therapy. This important and timely scientific statement outlines current best practices for delivering cardiovascular genetic evaluation and care in both the pediatric and the adult settings with a focus on team member expertise and conditions that most benefit from genetic evaluation. That's all for this month. Thank you as always for listening and come back next month for the next installment of papers in Genomic and Precision Medicine. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.
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28 May 2019
06/06/2019
28 May 2019
Jane Ferguson: Hi, everyone. Welcome to Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. It's May 2019, and this is episode 28. So let's see what papers we have in the journal this month. First up, a paper from Mengyao Yu, Nabila Bouatia-Naji and colleagues from the Inserm Cardiovascular Research Center in Paris, entitled GWAS-Driven Gene-set Analyses, Genetic and Functional Follow-Up Suggest Glis1 as a Susceptibility Gene for Mitral Valve Prolapse. In this paper, they set out to characterize the genetic contributions to mitral valve prolapse, or MVP, to better understand the biological mechanisms underlying disease. They applied the gene-set enrichment analysis for QWAS tool and the pathway enrichment tool DEPICT to existing GWAS for MVP in a French sample to identify gene sets associated with MVP. They find significant enrichment of genes involved in pathways of relevance to valve biology and enrichment for gene expression in tissues of relevance to cardiovascular disease. They zeroed in a Glis family zinc finger gene Glis1 with consistently strong pattern of evidence across the GWAS enrichment and transcription analyses. They replicated the association between Glis1 and MVP in a UK biobank sample. They found that Glis1 is expressed in valvular cells during embryonic development in mice, but is mostly absent at later times. They targeted two Glis1 orthologs in zebrafish and found that knockdown of Glis1 B was associated with a significant increase in the incidence of severe atrioventricular regurgitation. These data highlight Glis1 as a potential regulator of cardiac valve development with relevance for risk of mitral valve prolapse. Next up is a paper from Gina Peloso, Akihiro Namuro, Sek Kathiresan and colleagues from Boston University, Kanazawa University, and Mass General Hospital. In their paper, Rare Protein Truncating Variance in APOB, Lower LDL-C, and Protection Against Coronary Heart Disease, the team was interested in understanding whether protein truncating variance in APOB underlying familial hypobetalipoproteinemia confer any protection against coronary heart disease. They sequenced the APOB gene in 29 Japanese families with hypobetalipoproteinemia as well as in over 57,000 individuals, some with early onset CHD and some without CHD. They found that presence of an APOB truncating variant was associated with lower LDL cholesterol and lower triglycerides, and also with significantly lower risk for coronary heart disease. This study confirms that variance in APOB, leading to reduced LDL and triglycerides are also protective against coronary heart disease. : The next paper entitled Mortality Risk Associated with Truncating Founder Mutations in Titin comes to us from Mark Jansen, Dennis Dooijes, and colleagues from University Medical Center Utrecht. They analyzed the effect of titin truncating variance on mortality in Dutch families. Titin truncating variants are associated with dilated cardiomyopathy, but have a very variable penetrance. In this study, the authors looked at three titin truncating variants, established to be founder mutations, and traced the pedigrees back to 18th century ancestors. They looked at 61 individuals on the transmission line and 360 of their first-degree relatives. They find no evidence for excess mortality in variant carriers overall. However, when they restrict it to individuals over 60 years of age, they did find a significant difference in mortality, which was also observed in individuals born after 1965. What these data tell us is that these titin truncating variants have a relatively mild phenotype with effects on mortality only manifesting later in life in many carriers. Given increases in life expectancy over the past several decades, the prevalence of morbidity and mortality attributable to titin truncating variants may increase. Genetic screening may identify genotype-positive, phenotype-negative individuals who would benefit from preventative interventions. Continuing on the theme of genetic variance, we have a paper from John Giudicessi, Michael Ackerman, and colleagues from the Mayo Clinic, Assessment and Validation of a Phenotype-Enhanced Variant Classification Framework to Promote or Demote RYR2 Missense Variants of Uncertain Significance. In this paper, they aim to find a better way to classify variants of unknown significance, of VUS, in the RYR2 gene. Variants in this gene are commonly associated with catecholaminergic polymorphic ventricular tachycardia, or CPVT. They examined 72 distinct variants in 84 Mayo Clinic cases and find that 48% were classified as VUS under ACMG guidelines. The rate was similar in a second sample from the Netherlands, with 42% of variants originally classified as VUS. They developed a diagnostic scorecard to incorporate a pretest clinical probability of CPVT, which included various clinical criteria, including symptoms and stress test results. Application of the phenotype enhanced ACMG criteria brought the VUS rate down to 7% in Mayo Clinic and 9% in the Dutch samples. The majority of VUS were reclassified as likely pathogenic. This study highlights how incorporation of disease-specific phenotype information can help to improve variant classification and reduce the ambiguity of reporting variants of unknown significance. We also have a number of research letters in the journal this month. From Karine Ngoyen, Gilbert Habib, and coauthors from Marseilles, we have a paper entitled Whole Exome Sequencing Reveals a Large Genetic Heterogeneity and Revisits the Causes of Hypertrophic Cardiomyopathy, Experience of a Multicentric study of 200 French Patients. In this study, they examined the genetic contributions to hypertrophic cardiomyopathy, or HCM, in 200 individuals as part of the HYPERGEN study and compared the benefits of whole exome sequencing compared with targeted sequencing of candidates' sarcomeric genes. All subjects had HCM documented by echocardiography. In the whole exome sequencing data, they first looked for mutations within 167 genes known to be involved in cardiomyopathies or other hereditary diseases. Of these 167 virtual panel genes, they find variants in 101 genes. Following whole exome sequencing, over 87% of the patients had an identified pathogenic, or likely pathogenic, mutation compared with only 35% of patients who only had targeted sequencing of sarcomeric genes. This highlights the generic heterogeneity of HCM and suggests that whole exome sequencing has utility in identifying variants not covered by sarcomeric gene panels. The next letter is from Wouter Te Rijdt, Martin [Vandenberg] and colleagues from University Medical Center Groningen and states that [dissynchronopathy] can be a manifestation of heritable cardiomyopathy. They hypothesized that left bundle branch block, also designated as dissynchronopathy, may be a manifestation of familial cardiomyopathy. They analyzed patients from a database of cardiac resynchronization therapy and identified super-responders whose left ventricular dysfunction was normalized by therapy. They carried out targeted sequencing in 60 known cardiomyopathy genes in 16 of these super-responder individuals and identified several variants, including a pathogenic variant in troponin T in one individual and variants of unknown significance in nine individuals. Pedigree analysis identified multiple family members with dilated cardiomyopathy. This study highlights that dissynchronopathy can be a manifestation of DCM, but that affected individuals may still benefit from cardiac resynchronization therapy. The next letter entitled Targeted Long-Read RNA Sequencing Demonstrates Transcriptional Diversity Driven by Splice-Site Variation in MYBPC3 comes from Alexandra Dainis, Euan Ashley, and colleagues from Stanford University. They set out to understand whether transcriptome sequencing could improve the diagnostic yield over genome sequencing in patients with hypertrophic cardiomyopathy. In particular, they hypothesized that long-read sequencing would allow for identification of alternative splicing linked to disease variance. They used long-read RNA and DNA sequencing to target the MYBPC3 gene in an individual with severe HCM who carried a putative splice-site altering variant in the gene. They were able to obtain heart tissue for sequencing and included several HCM and control subjects in addition to the patient with the MYBPC3 variant. They identified several novel isoforms that were only present in the patient sample, as well as some additional isoforms, including retained introns, extended exons, and an additional cryptic exon, which would not have been predicted based on the DNA variant. While the effects on protein function is not known, the transcripts are predicted to be translated. This analysis highlights the effect of a rare variant on transcription of MYBPC3 and provides additional evidence to link the variant to disease. This is a really nice approach, which could be used to probe causality and mechanisms, not only for cardiovascular disease, but for other rare variants in many disease settings. We finish with a perspective piece from Nosheen Reza, Anjali Owens, and coauthors from the University of Pennsylvania entitled Good Intentions Gone Bad, The Dangers of Sponsored Personalized Genomics. They present a case of a 23-year-old woman who presented for genetic counseling and evaluation after discovering she carried a likely pathogenic MYH7 variant associated with cardiomyopathy. She had no significant medical history, but had participated in employer-sponsored genetic testing motivated to identify potential variants related to cancer given a family history of cancer. After receiving her results, she experienced considerable anxiety and stopped exercising out of fear of cardiac complications. She visited an ER after experiencing chest pain, something she had not experienced previously. There was no appropriate counseling available at her institution for her genetic test results, leading her to seek out the additional counseling. Thus, while she was initially motivated to complete genetic testing because her employer offered it free of change, she ended up incurring costs related to the followup evaluation and counseling. Ultimately, she had no significant clinical findings. Although the variant had been listed as likely pathogenic, other sources consider it to be of unknown significance. This story highlights the psychological and financial impact that genetic testing can have on individuals, particularly when carried out without any pretest counseling or accessible post-test support when variants are identified. Despite the considerable promise of personalized medicine, there are many complexities to be considered, particularly with direct-to-consumer testing and employer-sponsored testing. This perspective highlights the ethical considerations and urges caution to maintain the best interests of patients. That's all for this month. Thanks for listening. I look forward to bringing you more next month. This podcast was brought to you by Circulation Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.
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27 April 2019
04/23/2019
27 April 2019
Jane Ferguson: Hello and welcome to Getting Personal: Omics of the Heart, your podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson from Vanderbilt University Medical Center, and this is episode 27 from April 2019. This month, I talk to Riyaz Patel, the first author on not one, but two articles published this issue, presenting analyses from the GENIUS-CHD consortium. But before we get to the interview, let's review what else was published this month. First up, we have a paper from Tamiel Turley, Timothy Olson and colleagues from the Mayo Clinic, entitled Rare Missense Variants in TLN1 Are Associated With Familial and Sporadic Spontaneous Coronary Artery Dissection. In this study, the authors were interested in identifying novel susceptibility genes for spontaneous coronary artery dissection or SCAD, which predominantly affects young women who appeared otherwise healthy. They conducted whole exome sequencing in a family with three affected family members and found a rare missense variant in the TLN1, or talin 1, gene. This gene encodes the talin protein which is part of the integrin adhesion complex linking the actin cytoskeleton to the extracellular matrix. This gene and protein is highly expressed in coronary arteries. They went on to sequence additional sporadic cases of SCAD, and they found additional talin 1 variants in these individuals. While there was evidence for incomplete penetrance, these data implicate TLN1 as a disease-associated gene in both familial and sporadic SCAD. The next paper comes from Miroslaw Lech, Jane Burns, and colleagues from UCSD School of Medicine and Momenta Pharmaceuticals and is entitled Circulating Markers of Inflammation Persist In Children And Adults With Giant Aneurysms After Kawasaki Disease. Kawasaki disease is the most common cause of acquired pediatric heart disease, but disease progression can vary a lot, and it's likely modulated by complex gene-environment interactions. Coronary artery aneurysms occur in about 25% of untreated patients, but early treatment with intravenous immunoglobulin or aspirin reduces the risk for these aneurysms to 5%, suggesting an important role for inflammation. In this study, the authors applied shotgun proteomics, transcriptomics, and glycomics on eight pediatric Kawasaki disease patients at the acute, subacute, and convalescent time points. They identified inflammatory profiles characterizing acute disease which resolved during the subacute and convalescent time points, except for in the patients who went on to develop giant coronary artery aneurysms. They went on to carry out proteomics on nine Kawasaki disease adults with giant coronary artery aneurysms and matched healthy controls, and they confirmed the inflammatory profiles in the adult samples. In particular, calprotectin, which is composed of S100A8 and S100A9, was elevated in the plasma of patients with CAA, an association they confirmed in additional samples of pediatric and adult Kawasaki disease patients and healthy controls. These data suggest that calprotectin may serve as a biomarker of ongoing inflammation in Kawasaki disease patients following acute illness, and may be able to identify individuals at increased risk of aneurysms. Next up, we have a research letter, Heart BioPortal: An Internet-of-Omics for Human Cardiovascular Disease Data, from Bohdan Khomtchouk, Tim Assimes, and colleagues from Stanford University. They had noticed that, in contrast to the field of cancer research, there were no open access platforms for cardiovascular disease data that offered users the ability to visualize and explore high quality data. They set out to fix this and developed the Heart BioPortal, which is accessible at www.heartbioportal.com. This portal allows the user to integrate existing CDD related omics data sets in real time and provides intuitive visualization and analyses in addition to data downloads. The primary goals are to support gene, disease, or variant-specific request, and to visualize the search results in a multi-omics context. They currently collate gene expression, genetic association, and ancestry allele frequency information for over 23,000 human genes and almost 6,000 variants across 12 broadly defined cardiovascular diseases spanning 199 different research studies. And this is just the start, they're hoping to add more studies, more data, and functionality for querying CDD drug targets, along with lots more. This is a really great resource which will no doubt be of real value to the community. I urge you to go online, check it out, put in your favorite gene, and see what you find. Riyaz Patel, Folkert Asselbergs, and many, many collaborators published Subsequent Event Risk in Individuals With Established Coronary Heart Disease: Design and Rationale of the GENIUS-CHD Consortium and Association of Chromosome 9p21 with Subsequent Coronary Heart Disease Events: A GENIUS-CHD Study Of Individual Participant Data. These papers present the design of the genetics of subsequent coronary heart disease, or GENIUS-CHD consortium, which was established to facilitate discovery and validation of genetic variants and biomarkers for risk of subsequent CHD events in individuals with established CHD. The consortium currently includes 57 studies from 18 countries, recruiting over 185,000 participants with either acute coronary syndrome, stable CHD, or a mixture of both at baseline. All studies collected biological samples and followed up study participants prospectively for subsequent events. Enrollment into the individual studies took place between 1985 to the present day, and the duration of follow-up ranges from nine months to 15 years. Participants have mostly European ancestry, are more likely to be male, and were recruited between 40 to 75 years of age. In their first analysis using these data, they investigated whether the established 9p21 locus associated with subsequent events in individuals with established coronary heart disease. Confirming previous smaller studies, they showed that while genotype at 9p21 is associated with coronary disease when compared to healthy controls, 9p21 genotype is not associated with a risk of future events in people who already have coronary disease. Dr. Patel joins me to tell me more about the GENIUS-CHD consortium and the analyses described in these papers. Today, I'm joined by Dr. Riyaz Patel, who's an associate professor at University College London and a cardiologist at the Barts Heart Centre in London. Dr. Patel, thank you so much for joining me. Dr. Riyaz Patel: Pleasure to be on, thanks. Jane Ferguson: So, as we're going to discuss, you are the lead author on two back-to-back publications that were published in Circ Gen this month exploring genetic predictors of coronary heart disease as part of the GENIUS-CHD consortium. Before we delve fully into them, could you tell us a little bit about your background and how you got into this research field? Dr. Riyaz Patel: Yes. I'm an academic cardiologist, as you know, and I first got into genetics of coronary disease about 12-13 years ago, now, around the time that genome wide association studies were about to take off, or were taking off. I studied, I worked at Emory University, in fact, in Atlanta, in the US. We had a very big cohort of patients who had coronary disease, who were undergoing coronary angiography. At that time, we were doing quite a lot of genetic association studies and biomarker work in patients with heart disease. One of the key problems we often encountered was sort of looking for replication cohorts and trying to do things at a bigger scale than what we had available. So that kind of really was the initial driver for trying to bring together a bigger collaboration to take that sort of work to the next level. Jane Ferguson: It sounds like you've got valuable expertise, because looking at the author list for these papers, I think it's one of the longest author lists I've ever seen. It's a huge endeavor. I'd love to hear more about how that got started and how you managed to build this consortium, and you know, and tell us what the consortium actually is. Dr. Riyaz Patel: Yeah, it's been a labor of love. And essentially, I started when I returned back to the UK and we were looking to develop this further. We had already collaborated with several colleagues in the US and abroad from my time at Emory. So, we pulled together a small group of people who we were already working together with and then we did predicts of systematic searches of literature to identify cohorts who were also doing similar things. Again, investigating people with heart disease and looking at subsequent event risk. So, we did that and then we systematically approached, very much, as many people as we could find and over the course of the last, maybe 3 or 4 years, we've brought together a small community of collaborators around the world, and as you rightly said, it's a very long list. In total, we're counting around 180 or so investigators. But, in a way, that also speaks to how this consortium is not just a collection of studies. It is a collection of people and a lot of expertise was brought to the table because of that. People have been thinking about these questions for many, many years and this platform essentially is an opportunity for everyone to share that knowledge. Dr. Riyaz Patel: So that's kind of how the consortium started and is being pulled together. We operate on a sort of loose memorandum of understanding where every member of the consortium is free to participate in studies as they wish. We run analysis in a federated way which means that [inaudible 00:10:50] scripts are shared and people standardize their data and then they run analyses locally and they only share summary level data so that obviously overcomes the big governance hurdle. So, that's pretty much how the consortium works at moment. Jane Ferguson: Yeah. I'm sure there was probably a lot of challenges along the way in figuring this out and getting scripts that work for everybody, dealing with all the people, so how do you do this? Do you have regular phone calls with 180 people on it? Do you have lots and lots of emails? Dr. Riyaz Patel: (laughs) Jane Ferguson: How's it actually working? Dr. Riyaz Patel: So, we have a steering committee which is represented by at least one person from each study. So, that limits the number of people down to about, a more manageable number, about 50 or 60. And we do have regular teleconferences, particularly in the early days when we were still pulling everything together. Now, we try and meet at least once a year, if not twice at year at the major conferences, at the European Site of Cardiology and one of the big American meetings, ACC or AHA, so that's usually a good face to face meeting that we have with everyone and then as with all consortia, we have regular email lists and contact through that means. Jane Ferguson: So, now that you've got everybody together, you have over 185,000 participants as part of this from 18 different countries. So, how have you been able to use all of these different data and harmonize the different phenotypes and sort of put everything together to actually run the analyses. Dr. Riyaz Patel: The way we started off is by asking everyone to share almost an inventory of what they have collected. We then sought to try and standardize all of the core variables: age, sex, smoking and so forth. Once we were happy about the key variables had been standardized, units were the same and so forth, we then created, effectively a GENIUS-CHD data set that each cohort had curated. So, this was the main way of harmonizing the data set. Now, obviously, there are a lot of other differences between each of these studies. So, we have within the consortium a combination of different studies. We have randomized clinical trials, we have cohort studies, we have nested cohorts from larger population studies and we try and, in all of the analyses, we have pre specified subgroup analyses to try and look out and check for any heterogeneity that is introduced because of all of this. But the biggest, sort of, difference that we have factored in is that each of these studies collects patients with different types of coronary heart disease. Dr. Riyaz Patel: So, there are about ... 40% or so are acute coronary syndrome recruited patients, where these people are recruited at the time or after their acute event. And a similar proportion are recruited when they're much more stable. So, in all of our analyses we do try and factor in the differences in terms of the type of CHD patients are enrolled with but everything else, as best as we can, we have tried to standardize including all of the outcomes. So, for example, we share the ICD codes that would define a particular type of outcome across all the different cohorts, so even if you're in a different country, they will generally be reasonably well standardized. Jane Ferguson: Mm-hmm (affirmative), yeah, yeah. I think it's important and I can see the pros and the cons, you know, you have more diversity and you're representing a broader spectrum of disease by including everybody but then, of course, it's hard to figure it out, but I'd say it gives you a lot of versatility with the types of analyses you can do. Jane Ferguson: As we mentioned, there's two papers so people can go online and read those two papers. And the first one, is sort of the design and goes really into detail of how you guys set this up and I think is a really nice, sort of, example of, if anybody else was trying to (laughs) do something like this, of how to follow it. But then you also did, sort of, an initial analysis, right, to show what this consortium can actually do. I looked at 9p21, so I'd love to hear more about those analyses. Dr. Riyaz Patel: Yeah, so 9p21 is one of the most reproduced variants with coronary disease across the world. And it's remarkable how well replicated it's been in all sorts of settings in different countries. But the key thing is that it's been associated mostly in case controlled studies or in first event type of studies. And when we looked at this question some years ago now, at whether a variation of chromosome 9p21 is also associated with subsequent events, IE., we could test in people who've already had a heart attack or coronary disease, does it predict a worse outcome for them. We found that it hadn't. Dr. Riyaz Patel: [inaudible 00:16:06] was in the literature metro analyses and, sort of, all the caveats that come with that. So, we thought that as a feasibility analysis within the consortium, "why don't we also look at 9p21," which we did and this time around, we were able to identify that 93,000 people with coronary heart disease who had our primary endpoint of coronary heart disease death or MI subsequent to other index events. Again, we confirmed our previously met analyses findings that in this particular setting, 9p21 doesn't seem to associate with risk of subsequent events. And that sort of fits with our understanding of 9p21 so far. And interestingly, in one of our analyses, we identified that it does associate with risk of repeat revascularization. And from what we know about 9p21 so far, it seems to associate with risk of atheroma development or progression as opposed to perhaps plaque vulnerability or rupture which might give you an acute coronary event. Dr. Riyaz Patel: So, it's been a good example, I think, and really an illustration of how this consortium can work at scale. We have a lot of flexibility in terms of different subgroups that we can look at. And we really drilled down in this paper at all the possible reasons why a neutral finding may have occurred. We've looked at selection bias, we've looked at all the different subgroups which was can do because of the scale of the analysis. So, yeah, so that's kind ... it's really, the findings are not particularly novel in their own...
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26 March 2019
03/22/2019
26 March 2019
Jane Ferguson: Hello, and welcome to episode 26 of Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. I'm Jane Ferguson. It's March 2019, and I'm ready to spring into this month's papers, and apparently make really bad seasonal related jokes. Sorry all. Okay, let's get started. First up, is a paper from Oren Akerborg, Rapolas Spalinskas, Sailendra Pradhananga, Pelin Sahlén and colleagues from the Royal Institute of Technology in Solna, Sweden entitled "High Resolution Regulatory Maps Connect Vascular Risk Variants to Disease Related Pathways." Their goal was to identify non-coding variants associated with coronary artery disease, particularly those with putative enhancers and to map these to changes in gene function. They generated genomic interaction maps using Hi-C chromosome confirmation capture, coupled with sequence capture in several cell types, including aortic and ethelial cells, smooth muscle cells and LPS stimulated THP-1 macrophages. They captured over 25,000 features and they additionally sequenced the cellular transcriptomes and looked at epigenetic signatures using chromatin immunoprecipitation. They looked at regions interacting with gene promoters and found significant enrichment for enhancer elements. Looking at variants previously implicated in genome-wide associated studies, they identified 727 variants with promoter interactions and they were able to assign potential target genes for 398 GWAS variants. In many cases, the gene associated with a particular variant was not the closest neighbor, highlighting the importance of considering chromatin lupane when assigning intergenic variants to a gene. They identified several variants that interacted with multiple promoters, influencing expression of several genes simultaneously. Overall, this paper is a great resource for the community and takes many of these GWAS hits to the next level in starting to understand their biological relevance. They have a lot of supplemental material available online so it's definitely worth checking that out and taking a look for your favorite non-coding variant or chromosomal region to see if you can get some more information on it. Next up, Pierrick Henneton, Michael Frank and colleagues from the Hopital Europeen Georges-Pompidou in Paris bring us "Accuracy of Clinical Diagnostic Criteria For Patients with Vascular Ehlers-Danlos Syndrome in a Tertiary Referral Center." The authors were interested in determining the accuracy of the diagnostic criteria used to select patients for genetic testing for suspected vascular Ehlers-Danlos syndrome. This is because, despite the Villefrench criteria being recommended for diagnosis, the accuracy of the diagnostic criteria was never formally tested. They selected 519 subjects, including 384 probands and 135 relatives who had been seen between 2001 and 2016. They assessed the sensitivity and specificity of the Villefrench classification. Almost 32% of tested individuals carried a pathogenic COL3A1 variant. The sensitivity of the Villefrench criteria was 79% with a negative predictor value of 87%. Symptomatic probands had the highest accuracy at 92% sensitivity and 95% negative predictive value. However, the specificity was just 60%. Applying revised diagnostic criteria from 2017, it was actually less accurate because even though there was an increase in specificity, the sensitivity was reduced. Overall diagnostic performance was worst in individuals under 25 and neither set of diagnostic classifications allowed for early clinical diagnosis in individuals without a family history. Our next paper is a Mendelian randomization analysis from Susanna Larsson, Stephen Burgess and colleagues from Uppsala University and the University of Cambridge. This paper entitled "Thyroid Function And Dysfunction In Relation to Sixteen Cardiovascular Diseases: A Mendelian Randomization Study" aims to understand how subclinical thyroid dysfunction relates to risk of cardiovascular diseases. They generated genetic predictors for thyroid stimulating hormone, or TSH, through a GWAS meta-analysis in over 72,000 individuals. They then analyzed the association of genetically predicted TSH with cardiovascular outcomes in large GWAS studies of atrial fibrillation, coronary artery disease, and ischemic stroke, and further assessed associations with phenotypes in the UK Biobank. They found genetically decreased TSH levels and hyperthyroidism were associated with increased risk of atrial fibrillation but not other tested phenotypes. Overall, these data support a causal role for TSH and thyroid dysfunction in atrial fibrillation but not in other cardiovascular diseases. The next paper is also a Mendelian randomization analysis from members of the same group, Susanna Larsson, Stephen Burgess and colleagues published "Resting Heart Rate and Cardiovascular Diseases: A Mendelian Randomization Analysis." In this letter, they describe a study of the relationship between genetically increased resting heart rate and cardiovascular diseases. They constructed genetic predictors of resting heart rate and similarly to the previous study, used that as an instrument to test for associations with coronary artery disease, atrial fibrillation, and ischemic stroke in the cardiogram, atrial fibrillation, and mega stroke consortia respectively. They also looked at 13 CVD outcomes in the UK Biobank. They found that genetically predicted heart rate was inversely associated with atrial fibrillation with suggestive evidence for an inverse association with ischemic, cardioembolic, and large artery stroke. The inverse association with AF was replicated in the UK Biobank, supporting previous reports linking resting heart rate to atrial fibrillation. Next up, we have a letter from Robyn Hylind, Dominic Abrams, and colleagues from Boston Children's Hospital. This study entitled "Phenotypic Characterization of Individuals with Variants in Cardiovascular Genes in the Absence of a Primary Cardiovascular Indication For Testing" describes their work to probe incidental findings for potential cardiovascular disease variants in individuals undergoing clinical genomic sequencing for non-cardiac indications. They included 33 individuals who had been referred as carrying variants that were indicated as being associated with cardiovascular disease in primary or secondary findings. The variants were reclassified using the 2015 ACMG guidelines, and then were compared to the original classification report obtained at the time of sequencing. Of 10 pathogenic or likely pathogenic variants, only four of these were actually considered pathogenic or likely pathogenic after reclassification under the 2015 ACMG criteria, and none of these were associated with a cardiac phenotype. None of the variants could be definitively linked to any cardiac phenotype. The costs ranged from $75 to over $3700 per subject with a cost per clinical cardiac finding estimated at almost $14,000. This study highlights the relatively high cost and low yield of investigating potential cardiovascular variants and prompts consideration of how to implement strategies to ensure that variant reporting maximizes clinical return but minimizes the financial, time, and psychological burdens inherent in lengthy follow-ups. The next paper is a clinical letter from Serwet Demirdas, Gerben Schaaf and colleagues from Erasmus University Rotterdam entitled "Delayed Diagnosis of Danon Disease in Patients Presenting with Isolated Cardiomyopathy." They report on a clinical case of a 14-year-old boy presenting with cardiac arrest due to ventricular fibrillation during exercise. Echocardiography and MRI showed cardiac concentric hypertrophy, particularly in the left ventricle. The boy's mother had died at age 31 after being diagnosed with peripartum dilated cardiomyopathy. Sequencing in the boy revealed a variant in the LAMP2 gene, known to be responsible for Danon disease, which typically presents as cardiomyopathy, skeletal myopathy, and intellectual disability. This same LAMP2 variant was found in preserved maternal tissue, but not in other family members. In this case, there was no evidence of muscle or intellectual abnormalities. However, sequencing had allowed for this diagnosis of Danon disease in the child and posthumously in his mother. This study demonstrates a utility of using extended gene panels in clinical sequencing to aid in diagnosis and to inform management of patients. The next letter is from Alvaro Roldan, Julian Palomino-Doza, Fernando Arribas and colleagues from University Hospital of the 12th of October in Madrid and is entitled "Missense Mutations in the FLNC Causing Familial Restrictive Cardiomyopathy: Growing Evidence." This report also highlights clinical cases. In this case, two individuals with variants in the filamin C, or FLNC gene. Two unrelated individuals presenting with restricting cardiomyopathy were sequenced and found to carry two different variants in the FLNC gene, one of which had not been previously reported. This expands the number of reported cases of filamin C mutations in restrictive cardiomyopathy and highlights the need for further study of the pathophysiology linking filamin C to cardiac function. Finally, we have some correspondence related to a previously published article. In the letter, Christopher Chung, Briana Davies, and Andrew Krahn comment on the recently published article from Jody Ingles on concealed arrhythmogenic right ventricular cardiomyopathy in sudden unexplained cardiac death events. In that paper earlier this year, they had reported on four cases of individuals presenting with cardiac arrest or sudden cardiac death, attributable to concealed arrhythmogenic right ventricular cardiomyopathy with underlying mutations in the plakophilin-2 gene. In the letter from Chung et al, they report similar findings where individuals may first experience electrical phenotypes before manifesting structurally detectable disease. Indeed, in their response to this letter, Ingles et al report identification of an additional case since publication of their original article. Taken together, this further strengthens the case for development of additional strategies to identify at risk individuals and predict and prevent disease events. That's all for the papers for March 2019. Go online to check them out and follow us on Twitter @Circ_Gen to see new papers as they are published online. Thanks for listening. Until next month everyone. This podcast was brought to you by Circulation Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.
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25 February 2019
02/21/2019
25 February 2019
Jane Ferguson: Hi everybody. Welcome to Episode 25. I'm Jane Ferguson. This is Getting Personal: Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine, and it is February 2019. Let's get started. The first paper this issue is a concurrent publication and comes to us from 29 different editors-in-chief of 27 major cardiovascular journals, led by Joseph Hill, editor-in-chief of Circulation. This editorial, entitled Medical Misinformation: Vet the Message! gives a pointed reminder of the real life risks of misinformation that spreads rapidly through social media and influences people who are making crucial decisions about healthcare for themselves and their families. Quoting directly from the paper they say, "We, the editors-in-chief of the major cardiovascular scientific journals around the globe, sound the alarm that human lives are at stake. People who decline to use a statin when recommended by their doctor, or parents who withhold vaccines from their children, put lives in harm’s way." In this editorial they call on those in the media to do a better job of taking responsibility for the information they disseminate. In particular, in evaluating content before disseminating it, and avoiding false equivalencies where overwhelming scientific evidence favors one side of the so called "debate." I'll add to that that those of us who are medical or scientific professionals need to do our best to take the time to explain our science to those around us. The science underlying most of medicine is complex and hard to explain and sometimes incomplete, but we do a disservice to people if we don't at least try. Let's all join the editors in calling everyone to vet information and hold those with power in the media accountable for the spread of misinformation they enable. Next up this issue, a paper from Jody Ingles, Birgit Funke, and co-authors from the University of Sydney, Harvard Medical School and others, entitled Evaluating the Clinical Validity of Hypertrophic Cardiomyopathy Genes. As panels for clinical genetic testing expands to include more genes, there are more and more variants that are detected and reported to patients, but do not necessarily have underlying evidence to support or disprove pathogenicity. This group aimed to systematically assess the validity of potential gene disease associations with hypertrophic cardiomyopathy and left ventricular hypertrophy by curating variants based on multiple lines of genetic and experimental evidence. They categorized genes based on the strength of evidence of disease causation and reviewed HCM variant classification in the ClinVar variant and phenotype repository. They selected 57 genes to study based on those which were frequently included on test panels or had previous reports of association with HCM. Of HCM genes, only 24% were characterized as having definitive evidence for disease causation, 10% of the genes had moderate evidence, while 66% had limited or no evidence for disease causation. Of syndromic genes, 50% were definitively associated with left ventricular hypertrophy. Of over 4,000 HCM variants in ClinVar, 31% were in genes that, on review, had limited or no evidence for association with disease. What this study shows is that many genes that are included on panels for diagnostic testing for HCM actually have little evidence for any relationship to disease. Systematic curation is required to improve the accuracy of information being acquired and reported to patients and families with HCM. Moving on to the next paper. This manuscript describes the international Triadin Knockout Syndrome Registry: The Clinical Phenotype and Treatment Outcomes of Patients with Triadin Knockout Syndrome. It comes from Daniel Clemens, Michael Ackerman and colleagues from the Mayo Clinic. So, Triadin Knockout Syndrome is a rare inherited arrhythmia syndrome and it is caused by recessive null mutations in the cardiac triadin gene. To improve the ability to study this rare syndrome, this group established the International Triadin Knockout Syndrome Registry, with the goal of including patients across the world with homozygous or compound heterozygous triadin null mutations. The registry currently includes 21 patients from 16 families who have been carefully phenotyped and many of whom exhibit T wave inversions and have transient QTC prolongation. The average age for first presentation with cardiac arrest or syncope was three years of age. Despite a variety of treatments, the majority still have recurrent breakthrough cardiac events. These data highlight the importance of conducting testing for triadin mutations in patients, particularly young children presenting with cardiac arrest, and as this registry grows it will enable a better understanding of the disease and hopefully pave the way for future triadin gene therapy trials. The next paper comes from Daiane Hemerich, Folkert Asselbergs and colleagues from Utrecht University, and is entitled Integrative Functional Annotation of 52 Genetic Loci Influencing Myocardial Mass Identifies Candidate Regulatory Variants and Target Genes. They were interested in whether variants that have been associated with myocardial mass may exert their influence through regulatory elements. They analyze the hearts of hypertrophic cardiomyopathy patients and non-disease controls and ran ChIP-seq in 14 patients and 4 controls and RNA-seq in 11 patients and 11 controls. They selected 52 loci that have been associated with electric cardiogram defined abnormalities in amplitude and duration of the QRS complex and looked specifically at these gene regions. They found differential expression of over 2,700 different genes between HCM and control. They further found differential acetylation over 7,000 regions. They identified over 1000 super enhancers that were unique to the HCM samples. They found significant enrichment for differential regulation between disease and control hearts within the loci previously associated with HCM, compared with loci not associated with HCM. They analyzed regions where putative causal SNPs overlapped regulatory regions, and identified 74 co-localized variants within 20 loci, with particular enrichment for SNPs in differentially expressed promoters. They confirmed associations with 18 previously implicated genes, as well as identifying 14 new genes. Overall, what this study demonstrates is that by looking at regulatory features that differ in affected tissues between disease and healthy individuals, we can learn more about the underlying mechanisms of disease. Moving on, we have a paper entitled Interleukin-6 Receptor Signalling and Abdominal Aortic Aneurysm Growth Rates from Ellie Paige, Marc Clément, Daniel Freitag, Dirk Paul, Ziad Mallatt and colleagues from the University of Cambridge. They aimed to investigate a specific SNP in the Interleukin-6 receptor rs2228145, which has been associated with abdominal aortic aneurysms. Inflammation is thought to be a contributor to aneurism progression. The authors hypothesized that the IL-6 receptor's SNP may affect aneurysm growth. They use data from over 2,800 subjects from nine different prospective cohorts and examine the effect of genotype on annual change in aneurysm diameter. Although there was a significant association between genotype and baseline aneurysm size, there was no statistically significant association with growth over time. It appeared that growth was less in minor allele carriers, but the effect if true, was small and the analyses were not powered for small effect sizes. Sample sizes are limited for cohorts with abdominal aortic aneurysms and the authors already used all available worldwide data. In complimentary experiments in mice, they examined the effect of blocking the IL-6 receptor pathway. They found that selective blockage of the IL-6 trans-signaling pathway mediated by soluble IL-6 receptor was associated with improved survival in two different mouse models. However, blocking the classical membrane-bound IL-6 signaling pathway in addition to the trans-signaling pathway did not lead to improved survival. Although the severe lack of enough subjects for well powered genetic analyses is a major limitation for the study of abdominal aortic aneurism and humans, this paper demonstrates the potential relevance of the IL-6 trans-signaling pathway and aneurysm growth, and suggests that further interrogation of this pathway may be informative in figuring out new ways to prevent aneurysm progression and rupture. Next, we have the first of two research letters this issue. The letter on Common Genetic Variation in Relation to Brachial Vascular Dimensions and Flow-Mediated Vasodilation comes to us from Marcus Dorr, Renate Schnabel and co-authors from several institutions including University Heart Center in Hamburg. They were interested in gaining a better understanding of the genetics underlying vascular function. They ran a meta-analysis of brachial artery diameter, maximum brachial artery diameter adjusted for baseline diameter, and flow-mediated dilation in over 17,000 individuals of European ancestry from six different GWA studies. They sought to replicate findings in over 9,500 newly genotyped individuals. They identified two novel SNPs for baseline brachial artery diameter, but no SNPs reached significance or replication from maximum brachial artery diameter or flow-mediated dilation. One of the significant SNPs was located in the insulin-like growth factor binding protein 3, or IGFBP-3 gene. They analyzed plasma IGFBP-3 protein levels in 1,400 individuals and found a significant association with brachial artery diameter. The second SNP they identified is located within the AS3MT gene for arsenite methyltransferase, and this SNP appears to be an eQTL for AS3MT expression in monocytes and arterial tissue. Along with identifying these two genes with potential involvement in baseline brachial artery diameter, this study also supports a low genetic component to flow-mediated dilation, indicating that environmental factors may be or more influential in FMD. The final research letter comes from Alexis Williams, Craig Lee and colleagues from the University of North Carolina and is entitled CYP2C19 Genotype-Guided Antiplatelet Therapy and 30-Day Outcomes After Percutaneous Coronary Intervention. It is known that loss of function variants in CYP2C19 effect bioactivation of clopidogrel, and CYP2C19 genotyping is increasingly used to guide antiplatelet therapies. The authors were interested in whether genotype-guided therapy is effective in reducing major adverse cardiovascular events in the short term, specifically in the 30 days following percutaneous coronary intervention, when most MACE occurs. They followed over a thousand individuals undergoing PCI and CYP2C19 testing and looked at atherothrombotic and bleeding outcomes. Consistent with implementation of genotype-guided therapy, individuals carrying loss of function alleles were less likely to be prescribed clopidogrel. However, out of loss of function carriers, those who did take clopidogrel had significantly higher risk of MACE with no difference in bleeding risk. There was no difference by therapy in individuals without a loss of function allele. What this study shows us is that even in the 30 days following PCI, genotype-guided therapy can be effective in protecting individuals carrying loss of function CYP2C19 variants. And that's it from us for February. Go online to ahajournals.org/journal/circgen to read the full papers, access videos and more, and of course to delve into the podcast archives. Thank you for listening and I look forward to bringing you more next month. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2019.
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23 December 2018 5
01/29/2019
23 December 2018 5
Jane Ferguson: Hello, everyone. Welcome to Episode 23 of Getting Personal, Omics of the Heart, the podcast from Circulation: Genomic and Precision Medicine. It's December 2018. I'm Jane Ferguson. So let's get started. This month I talked to Dr. Merlin Butler from Kansas University Medical Center about an interesting clinical case he described recently in the Journal of Pediatric Genetics, concerning cardiac presentations in a case of classic Ehlers-Danlos syndrome with COL5A1 mutations. Keep listening for that interview, but first, let's talk about the papers in this month's issue of the Journal. Our first paper, entitled "Effects of Genetic Variance Associated With Familial Hypercholesterolemia on LDL Cholesterol Levels and Cardiovascular Outcomes in the Million Veteran Program." Comes from Yan Sun, Peter Wilson and co-authors on behalf of the V.A. Million Veterans Program. They were interested in the relatively between variants in LDLR, APOB and PCSK9, and LDL cholesterol in the general population. Low-frequency variants in these genes have been identified to underlie the greatly elevated LDL cholesterol seen in cases of familial hypercholesterolemia, but the effects of the population level are unknown. Using data from the Million Veterans Program, the team analyzed the associations between putatively pathogenic variants and the maximum recorded LDL cholesterol level, as measured repeatedly over a 15-year period, in over 330,000 participants. They restricted analysis to variants that were present in at least 30 people and found that eight of the 16 variants tested were associated with significantly higher LDL cholesterol. Through phenome-wide association analysis, they found that carriers had a higher likelihood of a diagnosis of hypercholesterolemia or coronary heart disease, but not of other diagnoses. Even though individuals carrying risk variants generally reduce their LDL cholesterol through statin treatment, they still had residual risk, suggesting that even earlier initiation of treatment may be required in individuals with genetic risk of high HDL. Continuing the theme, the next paper comes from Laurens Reeskamp, Merel Hartgers, Kees Hovingh and colleagues from the University of Amsterdam, and is entitled, "A Deep Intronic Variant in LDLR in Familial Hypercholesterolemia: Time to Widen the Scope?" This team had encountered a family with familial hypercholesterolemia, who did not carry a coding mutation in LDLR, APOB or PCSK9, and they wanted to figure out what was causing the elevated LDL cholesterol in this family. They conducted whole-genome sequencing in nine family members, five affected and four unaffected. They found a variant in an intron in LDLR, which resulted in an insertion of 97 nucleotides, leading to a frame shift in premature stop codon in exon 15 of LDLR. They confirmed the disease segregation in a second family, and found a frequency of over 0.2% in additional FH cases without a confirmed mutation. This study highlights the need to consider more than just exons when looking for causal variants, particularly in families where no coding mutations are identified. Next up, from Kathryn Siewert and Ben Voight from University of Pennsylvania, a paper reporting that "Bivariate Genome-Wide Association Scan Identified 6 Novel Loci Associated With Lipid Levels and Coronary Artery Disease." This paper started with a premise that, because heritable plasma lipids are genetically linked to coronary artery disease, we would have greater power to detect variants contributing to both traits by conducting joint GWAS analysis, rather than independent analyses for lipids or coronary disease, as has been done traditionally. Using data from over 500,000 individuals for CAD and over 180,000 individuals from the Global Lipid Genetics Consortium, they conducted a bivariate GWAS and identified six previously unreported loci that associated with CAD and either triglycerides, LDL cholesterol or total cholesterol. Many of these loci also had signals for effects on gene expression of genes in the region, suggesting that these novel loci may affect lipid levels and CAD risk through modulation of gene expression. Interestingly, for some of the newly-identified loci, there were multiple potential regulatory targets, suggesting that these loci may affect lipids and CAD through separate mechanisms. Overall, for closely-linked traits such as lipids and CAD, this joint GWAS approach gives additional power to detect novel variants. The next article comes from Terry Solomon, John-Bjarne Hansen and colleagues from University of California-San Diego and the Arctic University of Norway. Their paper concerns the "Identification of Common and Rare Genetic Variation Associated With Plasma Protein Levels Using Whole-Exome Sequencing and Mass Spectrometry." They were interested in identifying genetic variants that associate with plasma protein levels, both to understand genetic regulation and to identify potential sources of bias, where a genetic variant affects the assay used to quantify the protein, without necessarily altering biological components of the protein. Using data from 165 participants of the Tromsø Study, they quantified 664 proteins in plasma by tandem mass tag mass spectrometry and genotypes by whole-exome sequencing. They identified 109 proteins or peptides associated with genotype, and of these identified 49 that appeared to be technical artifacts based on genotype data. Of the rest, many of the genetic variants affected protein level by modulation of RNA, but some appeared to directly affect protein metabolism. Their method of quantifying multiple peptides from each protein and sequencing exons allowed them to identify spurious associations that would often be missed, and highlights the large number of artifacts that could be present in protein quantitative trait locus studies. At the same time, they show that over half of the pQTLs are real, with genetic variants affecting circulating proteins through diverse mechanisms. Our last of the full-length original research articles also applied proteomics. "Proteomic Analysis of the Myocardium in Hypertrophic Obstructive Cardiomyopathy" comes from Caroline Coats, Perry Elliott and coauthors from University College, London. They obtained myocardial samples from 11 patients with hypertrophic cardiomyopathy and measured over 1500 proteins using label-free proteomic analysis. They compared protein expression to six control samples from healthy hearts. They identified 151 proteins that were differentially expressed in HCM hearts, compared with control, and they validated a subset of these using an additional 65 myocardial samples from healthy and diseased subjects. Of eight validated differentially expressed proteins, they represented pathways in metabolism, muscle contraction, calcium regulation and oxidative stress. Of particular interest, they highlighted lumican as a novel disease protein, and showed the potential of proteomics to identify mechanisms underlying HCM. We have two research letters this month, the first from Hisato Suzuki, Kenjiro Kosaki and coauthors from Keio University School of Medicine at Tokyo. It's titled, "Genomic Comparison With Supercentenarians Identifies RNF213 as a Risk Gene for Pulmonary Arterial Hypertension." In this letter, they were interested in identifying genetic variants underlying pulmonary arterial hypertension. They hypothesized that individuals with extremely long lifespan would be less likely to carry potentially pathogenic variants. They performed whole-exome sequencing in 76 individuals with PAH and compared them to 79 supercentenarians who had lived for over 110 years. They report variants in RNF213 and TMEM8A that were present in PAH but not in the controls, suggesting these genes may be important in the pathophysiology of PAH. The second research letter comes from Tessa Barrett, Jeffrey Berger and colleagues from New York University School of Medicine, and is entitled, "Whole-Blood Transcriptome Profiling Identifies Women With Myocardial Infarction With Nonobstructive Coronary Artery Disease: Findings From the American Heart Association Go Red for Women Strategically Focused Research Network." Most of the 750,000 acute MIs occurring in the U.S. each year are caused by obstructive coronary artery disease, but around 15% of the acute MIs occur in individuals whose arteries have less than 50% stenosis and are defined as unobstructed. These individuals are more likely to be female and of higher morbidity and mortality. In this AHSAFRM-funded project, the team sequenced whole-blood RNA from 32 women who presented with an MI with or without CAD, or controls. They report several thousand transcripts differing between groups on conducted pathway analysis, which highlighted several pathways, most notably estrogen signaling. This suggests that estrogen may be a novel component in MIs occurring in the absence of obstructive disease. We also have two clinical letters this month. The first, "Desmoplakin Variant-Associated Arrhythmogenic Cardiomyopathy Presenting as Acute Myocarditis," is brought to us by Kaitlyn Reichl, Chetan Shenoy and colleagues from University of Minnesota Medical School. They report a case of a 24-year-old man presenting with acute myocarditis, who was found to have a pathogenic variant in desmoplakin underlying arrhythmogenic cardiomyopathy, also present in his father and one brother. This case highlights myocarditis as a possible initial presentation of arrhythmogenic cardiomyopathy, which requires cardiac MRI and genetic testing for full evaluation. The second clinical letter comes from Judith Verhagen, Marja Wessels and co-authors from University Medical Center, Rotterdam, and is entitled, "Homozygous Truncating Variant in PKP2 Causes Hypoplastic Left Heart Syndrome." They report on a family with consanguineous parents, where two children were affected with left ventricular hypoplasia, leading to intrauterine death in one child and death at day 19 of life in a second child. Sequencing identified a variant in PKP2, which encodes plakophilin 2. Both parents were heterozygous for the mutation, and their affected children were homozygous for the mutation. This mutation resulted in disorganization of the sarcomere and affected localization of other proteins affecting gap junctions. The case highlights PKP2 variants as causal in hypoplastic left heart syndrome. Dr. Merlin Butler is a professor at Kansas University Medical Center and Director of their Division of Research and Genetics. Dr. Butler joined me to discuss an interesting case of Ehlers-Danlos Syndrome in a father and son, with heart failure in the father. This case is in press in the Journal of Pediatric Genetics, and the prepublication version is available online, published on the 13th of October 2018. We'll tweet out a link to that paper, if you're interested in viewing the full case, but here's Dr. Butler, who joined me to discuss it now. Dr. Butler: ... I'm a clinical geneticist here at University of Kansas Medical Center, and I see both adult and pediatric patients, but one of the more common reasons for referral to my adult side clinical genetic services is connective tissue disorders. And that's how we were involved with this particular family, a son and father, that led to my interest in looking at the question about genetics of cardiac transplantation of those patients that present for cardiology services because of heart failure and worked up and ultimately end up as a candidate for transplantation. And that transpired in this particular family, which the patient was a 13-year-old boy who was referred into the clinic because of connective tissue disorder. Actually the primary care wanted to rule out Ehlers-Danlos Syndrome. And so we evaluated the 13-year-old boy in the clinic setting, and then we ordered comprehensive connective tissue and next-generation DNA sequencing panel, and lo and behold, he had a mutation of the classical gene that causes classic Ehlers-Danlos, the collagen 5A1 gene. The gene variant was classified as unknown clinical significance, which is often the case as we know with this technology, next-generation sequencing. Regardless of the condition we're looking at, we find about 10% of time, the panel of tests, the panel of genes that come back that are tested. 10% of the time we find no variants, no spelling errors, no mutations. 10% of the time the results come back from the commercial laboratory ... these are clinic patients, so it's done in commercially-approved laboratories, clinically-approved laboratories ... and we find that about 10% is pathogenic, which means it's disease-causing. The gene variant or mutation has been reported before. There is information in the literature that we know that it causes disease, Ehlers-Danlos, whatever type. About 80% of the time, the results come back as unknown clinical significance, and this is related to connective tissue. You probably order a test in cardiology or any other service and you'll find the same area. Most of the variants come back as unknown. What is meant by that is they haven't been reported previously in the literature, and therefore we don't know ... They may be disease-causing, that particular change, but we don't know that. We as geneticists, we have to then figure out whether that gene variant is a mutation or background noise. So we go through a process by where we try to characterize that particular gene finding to see whether it could be causative in that particular patient we see, or if it looks like it's probably tolerated and is just background noise, and it has really probably no apparent phenotypic change resulting from that particular gene variant. So this particular gene variant that we found, the collagen 5A1, did meet the criteria. We looked for computer programs and silica prediction to see if it was tolerated or damaging. We looked at how common that gene variant is seen in the general population, looking at exact various types of genome databases at the laboratories used to search for that variant in the population that's been serviced by genetic services, to see how rare it is or how common it is. We also check to see if it's a missense change, missense variant that is, one amino acid got switched for a different amino acid. There are five classes of amino acids, so if they stay within the same class, that change one amino acid to the next probably doesn't have much meaning, but if it changes to an entirely different class, like positive to negative, hydrophilic to hydrophobic, that could make a big change at the protein translation level, and therefore impact on protein development and function. And then we looked to see if it's conserved in evolution. The laboratories that we use, they look at approximately 80 different animals, mammals, vertebrates, primates, non-mammal vertebrates, to see if that particular spelling change is conserved throughout evolution. If it is, if C is always that position 205 in the coding sequence of that gene throughout evolution, that means you need to have C at that position, not A, G or T, because that would be conserved and impact that we don't want to change that, because it's conserved through evolution. So those kind of criteria, how common it is in the population, how conserved it is, what the amino acid change might be and what the computer programs predict that change might relate to the function of the protein. So we used those criteria, found this gene variant, although it hadn't been reported before ... well, it hasn't been characterized as pathogenic. In this particular family, 13-year-old son and 55-year-old father, they both had the classical features of classic Ehlers-Danlos, so that gene variant, we know at this point is informative. Dr. Ferguson: That's a really helpful introduction to how you go about looking at variants and screening them and picking the ones of most importance. So you had this 13-year-old patient who came in and then you tested the patient, and then did you also test both parents? Other family members? Dr. Butler: Well, the mother was no longer in the loop, so the primary care, the pediatrician, referred this 13-year-old boy because of joint laxity. He had experienced multiple spontaneous knee dislocations, beginning around nine years of age. He was 13 when I saw him in clinic. He had a history of knee pain, generalized joint hypermobility, loose skin, excessive bruising and poor scarring. And he had that history coming in, and we certainly could identify those findings on this patient. In fact, we reported this patient in the literature. The title of the paper is "Classic Ehlers-Danlos Syndrome in a Son and Father with a Heart Transplant...
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24 January 2019
01/29/2019
24 January 2019
Jane Ferguson: Hello everyone, and happy new year. Welcome to episode 24 of Getting Personal: Omics of the Heart. It's January 2019, I am Jane Ferguson, an assistant professor at Vanderbilt University Medical Center and an associate editor at Circulation Genomic and Precision Medicine. We have a great line-up of papers this month in the journal, so let's jump right into the articles. First up, a paper from Christopher Nelson, Nilesh Samani, and colleagues from the University of Lester entitled, "Genetic Assessment of Potential Long-Term On-Target Side Effects of PCSK9 Inhibitors." I think most listeners are well aware of the efficacy of PCSK9 inhibition in reducing cardiovascular risk. However, as a relatively new treatment option, we do not yet have data on potential long-term side effects of PCSK9 inhibition. In this study, they utilized genetics as a proxy to understand potential long-term consequences of lower PCSK9 activity. They examined a PCSK9 variant that associates with lower LDL, as well as examining two LDL-lowering variants in HMGCR, the target of statins, which served as a positive control of sorts. They used data from over 479,000 individuals in the UK Biobank and looked for associations between the three LDL-lowering variants and 80 different phenotypes. For the PCSK9 variant, the allele which is associated with lower LDL was significantly associated with the higher risk of type 2 diabetes, higher BMI, higher waist circumference, higher waist-hip ratio, higher diastolic blood pressure, as well as increased risk of type 2 diabetes and insulin use. The HMGCR variants were similarly associated with type 2 diabetes as expected. Mediation analysis suggested that the effect of the PCSK9 variant on type 2 diabetes is independent of its effect on obesity. There were nominal associations between the PCSK9 variant and other diseases, including depression, asthma, chronic kidney disease, venous thromboembolism, and peptic ulcer. While genetics cannot fully recapitulate the information that would be gained from long-term clinical follow up, these data suggest that like statins, PCSK9 inhibition may increase the risk of diabetes and potentially other disease. Overall, the cardiovascular efficacy of PCSK9 inhibition may outweigh these other risks, however, future studies should carefully examine these potential side effects. Next up, we have a paper from Xiao Cui, Fang Qin, Xinping Tian, Jun Cai, and colleagues from Peking Uni and Medical College, on "Novel Biomarkers for the Precise Diagnoses and Activity Classification of Takayasu's Arteritis." They were interested in identifying protein biomarkers of Takayasu arteritis, to improve diagnosis and understanding of disease activity in this chronic vascular disease. They ran a proteomic panel including 440 cytokines on 90 individuals, including individuals with active disease, inactive disease, and healthy controls. They found a number of candidates and validated one protein, TIMP-1, as a specific diagnostic biomarker for Takayasu arteritis. For assessing disease activity, there was no single biomarker that could be used for classification, however, the combination of eight different cytokines identified through random forest-based recursive feature elimination and [inaudible] regression, including CA 125, FLRG, IGFBP-2, CA15-3, GROa, LYVE-1, ULBP-2, and CD 99, were able to accurately discriminate disease activity versus inactivity. Overall, this study was able to identify novel biomarkers that could be used for improved diagnosis and assessment of Takayasu arteritis, and may give some clues as to the mechanisms of pathogenesis. Our next paper is entitled, "Familial Sinus Node Disease Caused By Gain of GIRK Channel Function," and comes from Johanna Kuß, Birgit Stallmeyer, Marie-Cécile Kienitz, and Eric Schulze-Bahr, from University Hospital Münster. They were interested in understanding novel genetic underpinnings of inherited sinus node dysfunction. A recent study identified a gain of function mutation in GNB2 associated with sinus node disease. This mutation led to enhanced activation of the G-protein activated inwardly rectifying potassium channel, or GIRK, prompting the researchers to focus their interest on the genes encoding the GIRK subunits, KCNJ3 and KCNJ5. They sequenced both genes in 52 patients with idiopathic sinus node disease, and then carried out whole exome sequencing in family members of patients with potential disease variants in either gene. They identified a non-synonymous variant in KCNJ5, which was not present in the EVS or ExAC databases, and which segregated with disease in the affected family. This variant was associated with increased GIRK currents in a cell system, and in silico models, predicted the variant altered or spermine binding site within the GIRK channel. Thus, this study demonstrated that a gain of function mutation in a GIRK channel subunit associates with sinus node disease, and suggests that modulation of GIRK channels may be a viable therapeutic target for cardiac pacemaking. Our next paper, "Key Value of RNA Analysis of MYBPC3 Splice-Site Variants in Hypertrophic Cardiomyopathy," comes from Emma Singer, Richard Bagnall, and colleagues from the Centenary Institute and the University of Sydney. They wanted to understand the impact of variants in MYBCP3, a known hypertrophic cardiomyopathy gene, on splicing. They recruited individuals with a clinical diagnosis of hypertrophic cardiomyopathy and genetic testing of cardiomyopathy-related genes. They further examined individuals with a variant in MYBCP3 which had an in silico prediction to affect splicing. They sequenced RNA from blood or from fixed myocardial tissue and assessed the relationship between each DNA variant and gene splicing variation. Of 557 subjects, 10% carried rare splice site variants. Of 29 potential variants identified, they examined 9 which were predicted to affect splicing, and found that 7 of these were indeed associated with splicing errors. Going back to the families, they were able to reclassify four variants in four families from uncertain clinical significance to likely pathogenic, demonstrating the utility of using RNA analysis to understand pathogenicity in genetic testing. The next paper this issue comes from Catriona Syme, Jean Shin, Zdenka Pausova, and colleagues from the University of Toronto, and is entitled, "Epigenetic Loci of Blood Pressure: Underlying Hemodynamics in Adolescents and Adults." A recent large meta epigenome-wide association study identified methylation loci that associate with blood pressure. In this study, they wanted to understand more about how these loci related to blood pressure and hemodynamics. They recruited adolescents and middle-aged adults and assessed 13 CPG loci for associations with hemodynamic markers, including systolic and diastolic blood pressure, heart rate, stroke volume, and total peripheral resistance, measured over almost an hour during normal activities. Several of the loci replicated associations with blood pressure, and two of these also showed age-specific associations with hemodynamic variables. One site in PHGDH was particularly associated with blood pressure and stroke volume in adolescents, as well as with body weight and BMI, where lower methylation resulting in higher gene expression associated with higher blood pressure. A second site in SLC7A11 associated with blood pressure in adults but not adolescents, with lower methylation and consequent higher gene expression associated with increased blood pressure. Overall, this study indicates that methylation mediated changes in gene expression may modulate blood pressure and hemodynamic responses in an age-dependent manner. Next up is a research letter from Ben Brumpton, Cristen Willer, George Davey Smith, Bjørn Olav Åsvold, and colleagues from the Norwegian University of Science and Technology, entitled, "Variation in Serum PCSK9, Cardiovascular Disease Risk, and an Investigation of Potential Unanticipated Effects of PCSK9 Inhibition: A GWAS and Mendelian Randomization Study in the Nord-Trøndelag Health Study, Norway." As we heard about from the first study this issue, the long-term side effects of PCSK9 inhibition remain unknown. In this study, they also applied a genetic approach to understand potential unanticipated consequences of PCSK9 inhibition. They analyzed phenotypes from over 69,000 participants in the Nord-Trøndelag Health Study and measured serum PCSK9 in a subset. In PCSK9 GWAS of over 3,600 people, with replication in over 5,000 individuals from the twin gene study. They defined a genetic risk score for serum PCSK9 and assessed the relationship between genetically predicted PCSK9 and outcomes. They saw the expected associations between lower PCSK9 and lower LDL and coronary heart disease risk. However, there was minimal evidence for associations with other outcomes. While our first study in this issue, from Nelson, et al, found that lower PCSK9 from a single genetic variant was associated with higher diabetes risk, this risk was not found here using the genetic risk score. Differences in the genetic definitions and in the populations used can perhaps explain these differences between the two studies, but overall, the studies are consistent in suggesting that long-term PCSK9 inhibition is unlikely to be associated with major adverse outcomes. Our second research letter comes from Young-Chang Kwon, Bo Kyung Sim, Jong-Keuk Lee, and colleagues from Asan Medical Center in Seoul, on behalf of the Korean Kawasaki Disease Genetics Consortium. The title is, "HLA-B54:01 is Associated with Susceptibility to Kawasaki Disease," and reports on novel Kawasaki disease variants. HLA genes have been previously associated with disease, and in this report, the authors sequenced selected axons in HLA-DRB1, HLA-DQB1, HLA-A, HLA-B, HLA-C, and HLA-DBP1 in 160 Kawasaki disease patients and 278 controls. They find a significant association with HLA-B, and replicated this in a sample of 618 Kawasaki disease patients, compared with over 14,000 in-house controls. They identified specific amino acid residues conferring disease susceptibility, highlighting HLA-B as a potential modulator of Kawasaki disease. Our third and final research letter concerns "Serum Magnesium and Calcium Levels and Risk of Atrial Fibrillation: a Mendelian Randomization Study," and comes to us from Susanna Larsson, Nikola Drca, and Karl Michaëlsson, from the Karolinska Institute. Because magnesium and calcium are known to influence atrial fibrillation, this group was interested in whether genetic predictors of serum methyls associated with disease. They constructed genetic predictors from GWAS of calcium in over 61,000 individuals, and GWAS of magnesium in over 23,000 individuals. They applied these predictors to an AF GWAS including over 65,000 cases and over 522,000 controls. Genetically predicted magnesium was inversely associated with atrial fibrillation, while there was no association with genetically predicted calcium. While this study does not definitively prove causality, future studies aimed at assessing whether dietary or other strategies to raise serum magnesium are protective against AF may yield novel strategies for disease prevention. And that's it from us for this month. Thank you for listening, and come back next month for more from Circulation Genomic and Precision Medicine. This podcast was brought to you by Circulation Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association, 2019.
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Episode 22 Nov 2018
01/28/2019
Episode 22 Nov 2018
Jane Ferguson: Hello, welcome to Getting Personal: Omics of the Heart, Episode 22. This is a podcast from Circulation: Genomic and Precision Medicine, and the AHA Council on Genomic and Precision Medicine. I am Jane Ferguson and it's November 2018. Our first article comes from Carlos Vanoye, Alfred George and colleagues from Northwestern University Feinberg School of Medicine and is entitled, High Throughput Functional Evaluation of KCNQ1 Decrypts Variance of Unknown Significance. So a major growing problem in clinical genomics is that following the identification of a variant that is potentially linked to a disease phenotype, without further interrogation, it's really hard to make sense of the functional significance of that variant. Right now, the large number of variants of unknown significance lead to confusion for patients and clinicians alike. To allow for accurate diagnoses and the best treatment plans, we need a way to be able to screen variants to assess their function in a fast and cost-effective manner. In this paper, the authors decided to focus in the KCNQ1 gene, a cardiac ion channel, which can affect arrhythmias. They aim to assess whether a novel high-throughput functional evaluation strategy could identify functional mutations, as well as an in vitro electrophysiological approach. Which is effective, but expensive and time-consuming. Their approach capitalized on an existing automated electrophysiological recording platform that had originally had been developed for drug discovery essays. They selected 78 variants in KCNQ1 and assessed their function using the High-Throughput platform, which coupled high efficiency, cell electroporation with automated plain or patch clamp recording. They compared the results to traditional electrophysiological essays and find a high rate of concordance between the two methods. Overall, they were able to reclassify over 65% of the variants tested, with far greater efficiency than traditional methods. While this method will not work for all genes and phenotypes, the authors have demonstrated an efficient method for functional interrogation of variants. Which may greatly accelerate discovery and conditions such as Long QT or other congenital arrhythmias. The next paper, Nocturnal Atrial Fibrillation Caused by Mutations in KCND2 Encoding Poor Forming Alpha Subunit of the Cardiac KV 4.2 Potassium Channel, comes from Max Drabkin, Ohad Birk, and colleagues at Soroka University Medical Center in Israel. This paper also focuses on cardiac ion channels and the role of mutations in atrial fibrillation. In a family with early-onset peroxisomal AF across three generations, whole XM sequencing revealed a variant in KCND2 encoding the KV 4.2 Potassium Channel, which segregated consistent with autosomal dominant heredity. This variant resulted in a replacement of a conserved [inaudible] residue with an arginine. To investigate functional consequences of this novel variant, they conducted experiments in xenopos laevis oocytes and found that there is decreased voltage depended channel and activation and impaired formation of the KV 4.2 Homotetramer and the KV 4.2, KV 4.3 Heterotetramer. Overall, this study shows that a novel mutation in a conserved Protein kinase C Phosphorylation site within the KV 4.2 Potassium Channel underlies the phenotypes observed in a family of peroxisomal atrial fibrillation. The targeting Atrial KV 4.2 might be an effective therapeutic avenue. Next up, Michael Levin and Scott Damrauer and colleagues from the University of Pennsylvania published an article entitled, Genomic Risks Stratification Predicts All-Cause Mortality After Cardiac Catheterization. They were interested in understanding the utility of polygenic risk scores for disease prediction. They constructed a genome Y genetic risk score for CAD and applied it to individuals from the Penn Medicine Bio-bank who had undergone Coronary angiography and genotyping. They included over 139,000 variants for the 1,500 ancestry subjects who were included and classified them as high or low polygenic risk. Individuals who were classified as high polygenic risk were shown to have higher risk of All-Cause mortality than low polygenic risk individuals despite no differences in traditional risk factor profiles. This was particularly evident in individuals with high genetic risk but no evidence of angiographic CAD. Adding the polygenic risk score to a traditional risk assessment model was able to improve prediction of five year All-Cause mortality. Highlighting the utility of a polygenic score and underscoring traditional risk factors do not yet fully capture mortality risk. The next article entitled, "Bio-marker Glycoprotein Acetyls is Associated with the Risk of A Wide Spectrum of Incident Diseases and Stratifies Mortality Risk in Angiography Patients" comes from Johannes Kettunen, Scott Ritchie, Peter Würtz and colleagues from the University of Oulu Finland. GlycA is a circulating biomarker that reflects the amount of Glycated proteins in the circulation. It has been associated with cardiovascular disease, Type 2 Diabetes, and all-cause mortality. In this paper, the authors used electronic health record data from over 11,000 adults from the finish general population previously included in the "FINRISK" and "Dilgom" studies and they tested for a associations between GlycA and 468 different health outcomes over an 8-12 year follow up. They report new associations between GlycA and multiple conditions including incident alcoholic liver disease, chronic renal failure, glomerular diseases, chronic obstructive pulmonary disease, inflammatory polyarthric disease and hypertension. These associations held true even after adjusting for CRP suggesting that GlycA represents an independent biological contributor to inflammation and disease. Their findings highlight potential utility for GlycA as a biomarker of many diseases and underscore the importance future functional and mechanistic studies to understand how GlycA is linked to disease risk. Our last original research article entitled, "Tissue Specific Differential Expression of Novel Jeans and Long Intergenic Non-coding RNAs in Humans with Extreme Response to Endotoxic glycemia comes from Jane Ferguson, Murdock Riley, and colleagues from Vanderbilt University, Columbia University, and the University of Pennsylvania. That first author is none other than me, so I'm not unbiased reader of this particular manuscript, but I'd like to tell you a little bit about it anyway. We were interested in understanding the transcriptional changes that occur in tissues during acute inflammation. As part of the genetics of evoked responses to Niacin and Endotoxemia, or gene study, we recruited healthy individuals and performed an inpatient endotoxin challenge where we administered a low dose of LPS and looked at the systemic inflammatory response. Individuals vary greatly in the degree of their inflammatory response to LPS and we identified high and low responders, men and women, of African and European ancestry, who had responses in the top or bottom 10% for cytokines and fever. We conducted RNA seek and adipose tissue in 25 individuals and CD-14 positive monosites for 15 individuals in pre and two or four hours post LPS samples. We found that the differences in transcriptional response between high or low responders are mostly explained by magnitude rather than discrete sets of genes. So some core genes were altered similarly, in both groups, but overall the high responders mounted a large transcription of response to LPS or low responders rather than mounting an anti-inflammatory response actually just barely responded on the transcription level. We saw clear tissue specificity between manosites and adipose tissue we identified several long non-coding RNAs that were up or down regulated in response to LPS and validated these independent samples one of these link RNAs which we have now named Monosite LPs induced link RNA regulator vile six or Mahler Isle six, with highly regulated by LPs and monosites but not in adipose tissue. We [inaudible] THP-1 monosites and find a significant effect on iOS six expression suggesting that this is a novel link RNA that regulates Isle six expression in manosites potentially through a cd-86 dependent pathway. Overall our data revealed tissue specific transcriptional of changes that correlate with clinical inflammatory responses and highlight the role of specifically incarnate and inflammatory response. Next up is a research letter entitled "Reduced Sodium Current in Native Cardiomyocytes of a Regatta Syndrome Patient Associated with Beta Two Central Mutation" published by Constance Schmidt, Felix Wiedmann, Ibrahim El-Battrawy, Dierk Thomas, and co-authors from University Hospital Heidelberg. They obtained cardiomyocytes from a patient with Regatta Syndrome previous whole XM sequencing had implicated a variant in the Beta Two Syntrophin or "SNTB2" gene as potentially causal in this individual. Expression analysis showed lower SNTB2 expression and atrial tissue of the affected individual compared with controls. They performed electrophysiology on the Microcytes and found reduced peak sodium density and reduced late sodium current. They co-express wild type or mutant SNTB2 in heck 293 T cells and [inaudible] with the cardiac sodium channel NAV-1.5 and found a significant effect on binding which adversely affected sodium currents. This study nicely demonstrates the functional effect of this SNTB2 mutation underlying Regatta Syndrome in this patient. A second research letter comes from A.T. van den Hoven and Jolien Roos- Hesselink and colleagues from Erasmus University Medical Center in the Netherlands and is entitled "Aortic Dimensions and Clinical Outcome in Patients with SMAD three mutations, they were interested in understanding how the Aortic dilation comment individuals with SMAD three mutations compared to individuals with other syndrome and causes of Aortic dilation. In 28 patients with SMAD three mutations, there were significant growth in the Sinotubular Junction the ascending Aorta on the diaphragm over an average of 10 years of follow up at reads far higher population averages but lower than might be seen in other syndromes, such as [inaudible]. Intensive management and preventive surgery and many of the patients prevented any mortality in this group. Rounding out this issue is a clinical letter entitled "Concealed Arrhythmogenic Right Ventricular Cardiomyopathy in Sudden unexplained Cardiac Death events from Jodie Ingles, Chris Semsarian, and colleagues from the University of Sydney, Australia. They report on for clinical cases where individuals presented in early adulthood with unexplained cardiac arrest, which was later found to be attributable to mutations in the PKP2 gene. PKP2 or, Plakophilin 2, encodes an integral component of the Desmosome, which is important and Cell-Cell adhesion. Further PKP2 is involved in transcriptional activation of genes controlling intracellular calcium cycling. This gene has been implicated arrhythmogenic right ventricular cardiomyopathy in individuals with cardiac structural abnormalities. These four cases where unrelated individuals were all fans to have loss of function variants and PKP2 underlying sudden cardiac death or events, despite structurally normal hearts. This prompts questions on the clinical management of such cases of concealed ARVC. That's all from us for November, thanks to all of you out there listening. We'll be back in December for the final episode of 2018. This podcast was brought to you by Circulation Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is copyright American Heart Association 2018.
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Episode 21 October 2018
11/30/2018
Episode 21 October 2018
Speaker 1: Hi, everyone. Welcome to episode 21 of Getting Personal, Omics of the Heart from October 2018. I'm Jane Ferguson, an Assistant Professor at Vanderbilt University Medical Center and an Associate Editor at Circulation: Genomic and Precision Medicine. We have a great issue this month. So, let's dive straight in. First up, an article on "Loss-of-Function ABCC8 Mutations in Pulmonary Arterial Hypertension" from Michael Bohnen, Wendy Chung and colleagues from Columbia University. In pulmonary arterial hypertension, or PAH, compromised pulmonary arterial function can raise pressure in the pulmonary artery which leads to increased pulmonary vascular resistance. This ultimately results in right heart failure. While PAH is relatively rare, it has a high rate of mortality. Some genetic underpinnings have been identified, notably the KCNK3 gene identified by the same research group where they find that mutations result in potassium channelopathy. However, here the authors hypothesized that other genetic contributors also exist and that identification of these could highlight new therapeutic targets to improve treatment and outcomes in PAH. In their study, the authors performed exome sequencing for discovery of novel disease variants in 233 PAH patients, 99 of whom had pediatric-onset and 134 with adult-onset. They sequenced a replication sample of 680 individuals with adult-onset PAH. They found a de novo missense variant in the ABCC8 gene in one patient and then found 10 more ABCC8 variants in other unrelated patients in the discovery and replication samples. Half of these were novel mutations and all were located in conserved regions and predicted to be deleterious. They screened over 33,000 subjects from the Exome Aggregation Consortium and over 49,000 from the Regeneron-Geisinger DiscovEHR study and found significant overrepresentation on rare ABCC8 variants in the PAH cases compared with population controls. ABCC8 encodes sulfonylurea receptor ... part of the potassium ATP channel. The authors determined that it is expressed in lungs in both PAH and healthy individuals and is particularly localized to alveolar macrophages and proximal pulmonary arteries. They expressed eight of the newly discovered ABCC8 mutations in COS cells, which are a monkey-derived, fiberglass-like cell line and they assessed the effects on function. They used patch-clamp experiments to assess potassium ATP channel activity and recorded efflux rates of Rubidium-86. Every mutation was associated with impairments in one or both functional assays, suggesting that mutations in ABCC8 are responsible for PAH by a modulating potassium channel function and flux. An existing drug, Diazoxide, targets ABCC8 and has anti-hypertensive and insulin-lowering effects. The authors find that all mutants were pharmacologically activated by Diazoxide in the functional assays. Now, whether this drug would be safe or effective in PAH remains unknown, but these findings open up targeting of ABCC8 as a possible treatment in PaH and highlight the importance of potassium channels in PAH. Our next paper also used whole-exome sequencing for novel discovery. Marzia de Bortoli, Alessandra Rampazza and colleagues from the University of Padua in Italy published "Whole-Exome Sequencing Identifies Pathogenic Variants in TJP1 Gene Associated With Arrhythmogenic Cardiomyopathy". Arrhythmogenic Cardiomyopathy, or ACM, is one of the most common causes of sudden unexpected death in athletes and young people. It is known to be frequently caused by mutations in genes encoding mechanical junction proteins of the intercalated disks within the cardiac muscle. However, some individuals with ACM do not have any mutations in known genes. This research group was interested in finding novel causal gene mutation and they use whole-exome sequencing to identify mutations from a single patient in Italy. They used InSilica tools to screen for potentially damaging mutations which brought their list of candidate mutations down to 52 and this was topped by a novel mutation in the TJP1 gene which was predicted to be highly deleterious using various algorithms. Using Sanger sequencing, they found that this mutation was also present in several family members. A second mutation in TJP1, also predicted to be damaging, was identified in a second Italian family. They then screened a sample of 43 Dutch and German subjects diagnosed with ACM and found that, once again, mutations in TJP1 topped the list as predicted to be damaging. The TJP1, or tight junction protein 1, encodes the intercalated disk proteins ZO1. The identified mutations may affect folding and local interactions within the protein, affecting protein-protein interactions and gap junction organization. Well, within this paper, they were not able to fully disentangle the mechanisms linking these mutations to disease, given that the prevalence of TJP1 mutations in their ACM samples was almost 5%. Screening for TJP1 mutations in ACM cohorts may identify many additional affected subjects. Further research into TJP1 is needed to identify how these variants may cause ACM. If you want to read more about this paper, you can check out the accompanying editorial from Jason Roberts ... Western University, Ontario ... in this same issue. Next up is a paper from Natsuko Tamura, Yasuhiro Maejima, Mitsuaki Isobe and colleagues from Tokyo Medical and Dental University entitled "Single-nucleotide Polymorphism of the MLX Gene Is Associated With Takayasu Arteritis". Takayasu Arteritis, or TAK, is an autoimmune disease causing aortic vasculitis that is poorly understood and disproportionately affects young Asian women. In previous genome-wide associations, study of TAK in Japanese individuals conducted by this group, indicated SNPs in the MLX gene. In this paper, the authors aim to identify mechanisms linking MLX mutations with TAK. The top GWAS SNP rs665268 is a missense mutation causing L-Glutamine Arginine substitution in the DNA binding site of MLX. They found that this SNP was associated with severity in disease in TAK. With additional copies of the risk alleles associated with more severe aortic regurgitation and greater number arterial lesions. In mice, the highest expression of MLX was found in the aortic valves. Using crystallography, they found that the missense mutation likely stabilizes a complex formed between MLX and MondoA. Immunoprecipitation experiments confirmed that the missense mutation was associated with enhanced MLX MondoA heterodimer formation and MLX transcriptional activity. This resulted in upregulation of TXNIP and higher TXNIP expression is associated with increased intracellular oxidative stress and the authors found for increased oxidative stress in cells carrying the MLX mutation. Further, additional cell experiments showed evidence of this MLX mutation reduces autophagy and stimulates inflammasome activation. Overall, through a series of really elegant experiments, the authors demonstrate that a missense mutation in MLX leads to inflammasome activation and accumulation of cells within the aorta, potentially underlying the pathophysiology seen in TAK patients and highlighting novel causal pathways that may be probed therapeutically.regular Our next paper from Danxin Wang, Wolfgang Sadee and colleagues from the University of Florida and The Ohio State University, also delves into the functional impact of disease-associated SNPs. In their paper, "Interactions Between Regulatory Variants in CYP7A1 Promoter and Enhancer Regions Regulate CYP7A1 Expression", they used a series of experiments to demonstrate how SNPs in CYP7A1 ... which have been associated with cholesterol and cardiovascular disease ... are related to gene function. CYP7A1 is a gene which coordinates a key pathway for cholesterol removal from the body because it encodes an enzyme which is rate-limiting for bioassay synthesis from cholesterol. Although several SNPs in the gene have been associated with cardiovascular phenotypes, the reported effects on gene function have been inconsistent and/or unclear. Because of the linkage disequilibrium between SNPs, it has been hard to understand which SNP or SNPs are actually functional. What this team set out to do was to systematically screen functionality of individual CYP7A1 SNPs to understand the independent effects of each functional variant. First, they used chromatin conformation capture, or 4C assay, to identify regions that associated with a CYP7A1 promoter. They found three distinct regions with evidence of enhancer function and [phonetic 00:09:05] active A>G regulation. They, next, used CRISPR Cas9 to delete each of the three regions in HepG2 cells and assess effects on CYP7A1 expression. One region had no effect, while one led to increased expression and one led to decreased expression ... thus, identifying the presence of both enhancer and repressor regions. Using reporter gene assays, they confirmed the effects seen in CRISPR experiments. Based on reported SNP associations, they narrowed down candidate functional SNPs within the regions and constructed reporter assays containing haplotypes of potential functional SNPs. They were able to identify two SNPs acting together to determine differences in CYP7A1 gene expression. Because these SNPs are in LD, but the minor alleles have effects in opposite directions, considering genotype at both SNPs is required to understand the effects on gene expression. This explains why previous studies found inconsistent results. Both during the functional experiments, they went to human samples and they assessed the combined effect of the two SNPs on clinical phenotypes. Designating people as high or low activity based on the two SNPs, they found significant differences in cholesterol and in the likelihood to reach cholesterol targets on statin, as well as in the risk of MI. This paper is a lovely example of how careful functional interrogation can tease out a complex problem and I think it highlights how much more of this type of work needs to be done for the many other genomic regions with confusing or discord in associations. The last full-length article concerns the "Effect of Ascertainment Bias on Estimates of Patient Mortality in Inherited Cardiac Diseases" and comes from Eline Nannenberg, Imke Christiaans and colleagues at the Academic Medical Center, Amsterdam. They were interested in how much ascertainment bias and the tendency to publish findings from more severe disease cases affects the mortality estimates that are used to guide clinicians and genetic counselors when helping patients understand their disease prognosis. They revisited three inherited cardiac diseases including idiopathic ventricular fibrillation associated with a mutation in DPP6, SCN5A overlap syndrome associated with SCN5A mutations, and Arrhythmogenic Cardiomyopathy caused by a founder PLN mutation. They analyzed mortality over 2-10 years of clinical screening and cascade screening and found that the median age of survival quickly increased in all three conditions. In many cases, the reason that a mutation was identified was because of severe disease in that patient or family, but as the authors highlight here, this can bias publications towards associating the variant with more severe phenotypes and higher mortality. Following up the initial findings with additional screening and tracking of affected individuals is important to subsequently give a more accurate estimation of the effect of the mutation which can be used to inform treatment plans. Moving on to this month's research letters, Catherine Hajek, Jerome Rotter and colleagues from LA BioMed and the University of South Dakota, published the results of their study, "A Coronary Heart Disease Genetic Risk Score Predicts Cardiovascular Disease Risk in Men, Not Women: The Multi-Ethnic Study of Atherosclerosis". The genetic risk scores are being increasingly applied to estimate disease risk in individuals. However, these scores are based on the GWAS discovery from specific populations which have often been disproportionately male and with individuals of European ancestry. In this letter, the authors wanted to understand whether coronary heart disease genetic risk scores performed the same in men and women of European ancestry. Using data from the MESA Study, they applied a 46 locus genetic risk score to over 2500 individuals. In men, this risk score was strongly associated with event rates. However, in women, there was no association. Given the known differences in disease pathophysiology and manifestation between men and women, this finding additionally highlights the need to conduct genetic studies in underrepresented groups so that we can design scores that accurately predict risk within specific groups. Our next letter comes from Xiao Wang and Kiran Musunru at the University of Pennsylvania ... "Confirmation of Causal rs9349379- PHACTR1 Expression Quantitative Trait Locus in iPSC Endothelial Cells". They were interested in understanding the affect of a coronary disease SNP in the PHACTR1 gene on gene expression. Previous efforts to investigate this had yielded conflicting results showing either a significant eQTL effect for PHACTR1 and vascular tissue or no effect on PHACTR1, but an effect on a distal gene EDN1 in endothelial cells. For this study, the authors used CRISPR Cas9 to introduce the SNP to iPS cells and then expanded isogenic lines at the major and minor allele homozygous and differentiated these into endothelial cells. They find that the major allele was associated with significantly higher factorial expression, but no difference in EDN1 expression. Thus, based on these experiments, it appears that PHACTR1 may indeed be the causal gene in that region underlying the GWAS signal and whether or not EDN1 is involved remains unclear. Our next letter is a clinical letter from Nosheen Raza, Anjali Owens and co-authors at the University of Pennsylvania. They report on "ACTA1 Novel Likely Pathogenic Variant in a Family With Dilated Cardiomyopathy". In this case report, they describe that the discovery of a mutation in ACTA1 in a family with dilated cardiomyopathy, but no skeletal muscle symptoms. As a gene that is predominantly expressed in skeletal muscle, ACTA1 mutations have previously been associated with skeletal muscle myopathies and would not have been expected to cause cardiac symptoms in the absence of skeletal muscle dysfunction. However, sequencing suggests that this variant is a causal mutation in this family, highlighting the need to consider potential mechanisms for cardiac muscle specifics of highly expressed skeletal muscle genes. Our second clinical letter comes from Laura Zahavich, Seema Mital and co-authors from the Hospital for Sick Children in Ontario. They report a "Novel Association of a De Novo CALM2 Mutation With Long QT Syndrome and Hypertrophic Cardiomyopathy". They report finding mutation in the calcium transporter CALM2 gene in the child who presented with hypertrophic cardiomyopathy and ultimately died from sudden cardiac death. While this patient also had some variants of un-insignificance, the CALM2 gene is highly conserved and mutations are likely to be pathogenic. The CALM2 is not on all of the clinical genetic testing panels and in this case, whole-exome sequencing was required to identify a mutation. CALM2 have been described in other individuals and together with the findings reported here, there's compelling evidence for inclusion of CALM2 on cardiomyopathy in clinical testing panels. This issue also contains a perspective article from Michael Mackley, Elizabeth Ormondroyd and colleagues from the University of Oxford entitled "From Genotype to Phenotype: Clinical Assessment and Participant Perspective of a Secondary Genomic Finding Associated with Long QT Syndrome". They describe some of the challenges arising from more widespread genetic testing including how to deal with incidental findings. A larger number of people including apparently healthy individuals are receiving sequencing results that highlight potential disease-related mutations, but with varying penetrance and uncertain effects. This perspective paper highlights the issues through case study and discusses future directions and challenges in this rapidly growing area. Finally, we ride out this issue with an AHA scientific statement on "Cardiovascular Health in Turner Syndrome: A Scientific Statement From the American Heart Association" led by Michael Silberbach and Jolien Roos-Hesselink and a group of co-authors representing the American Heart Association Council on Cardiovascular Disease in the Young; Council on Genomic and Precision Medicine; and Council on Peripheral Vascular Disease. In this statement, they discuss the cardiovascular complications that commonly occur in girls and women Turner syndrome. Cardiovascular disease contributes significantly to premature death in individuals with Turner syndrome. Because of the unique nature of the cardiac presentations in Turner syndrome, better clinical guidelines are needed to improve diagnosis and treatment of [phonetic 00:17:26] ischemia in these individuals. This statement takes a first step to outline suggestions to improve clinical practice and highlights the work that still remains to be done to inform disease management. That rounds out the October issue of Circulation: Genomic and Precision Medicine. Thanks for listening! You can go online to ahajournals.org/journal/circgen to access the latest issue and browse previous issues. As a last reminder, AHA Sessions is approaching fast and I hope to see many of you in Chicago, November 10-12. This podcast was brought to you by Circulation: Genomic and Precision Medicine and the American Heart Association Council on Genomic and Precision Medicine. This program is Copyright American Heart Association, 2018.
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Ep 20 Brian ByrdSeptember 2018
09/20/2018
Ep 20 Brian ByrdSeptember 2018
Jane Ferguson: Hi everyone. Welcome to episode 20 of Getting Personal Omics of the Heart, the podcast brought to you by the Circulation: Genomic and Precision Medicine Journal and the American Heart Association Council on Genomic and Precision Medicine. I'm Jane Ferguson from Vanderbilt University. It's September 2018 and let's dive straight into the papers from this month's issue of Circulation: Genomic and Precision Medicine. We're starting off with some pharmacogenomics. Bruce Peyser, Deepak Voora and colleagues from Duke University published an article entitled, "Effects of Delivering SLCO1B1 Pharmacogenetic Information in Randomized Trial and Observational Settings." Although statins are generally well tolerated, 5-15% of patients taking statins for LDL lowering and cardiovascular protection end up developing statin associated muscular symptoms. Because onset of muscular symptoms associated with discontinuing statin use, as well as increased cardiovascular morbidity, there is a clear need to identify ways to prevent or reduce symptoms in these people. Variants affecting statin related myopathy have previously been discovered through GWAS, including a variant in the SLCO1B1 gene, which also has been shown to relate to statin myalgia and discontinuation of statin use. The risks appear to be greatest with simvastatin, indicating the people at risk of muscle complications may do better on either low-dose Simvastatin or another statin. However, there's still some uncertainty surrounding the risks and benefits of various statins as they pertain to risk of muscular symptoms. The authors have previously shown that pharmacogenetics testing led to increased number of people reporting statin use, but effects of pharmacogenetic testing on adherence, prescribing, and LDL cholesterol had never been tested in a randomized control trial. In this study, they randomized 159 participants to either genotype informed statin therapy or usual care, and then followed them for months to eight months. 25% of participants were carriers of the SLCO1B1 star five genotype. The authors found that statin adherence was similar in both groups, but gene type guided therapy resulted in more new statin prescriptions and significantly lower LDL cholesterol at three months, and levels that were lower but no longer significantly different at eight months. In individual's randomized to usual care who then crossed over to genotype informed therapy after the trial period ended, there was an additional decrease in LDL cholesterol. Overall, genotype informed statin therapy led to an increase in re-initiation of statins and decreases in LDL cholesterol, but did not appear to affect adherence. The authors also examined the effects of commercial genetic testing for SLCO1B1 variants in an observational setting by looking at over 92000 individuals with data available in the EHR. They found the people who receive genetic testing results had a larger drop in LDL cholesterol compared to untested controls. Overall, the study indicates that carriers of the SLCO1B1 risk variant may benefit from genotype informed statin therapy, while for non-carriers receiving their results may has limited effects. If you want to read more on this, Sony Tuteja and Dan Rader from UPenn wrote an editorial to accompany this article, which was published in the same issue. We're staying on the topic of statins and LDL for our next paper. This article comes from Akinyemi Oni-Orisan, and Neil Risch and colleagues from the University of California and is entitled, "Characterization of Statin Low-Density Lipoprotein Cholesterol Dose-Response Utilizing Electronic Health Records in a Large Population-Based Cohort." They were interested in understanding what determines variation in statin induced LDL reduction, particularly the genetic component, and they used a large EHR derived data set, the Kaiser Permanente Genetic Epidemiology research on adult health and aging cohort to address this important question. An EHR dataset does have intrinsic limitations, but also has some clear strengths, not only as a readily available and cost-effective data source for large sample sizes, but also because it reflects real world clinical care in diverse individuals, which is not always well represented within the selective constraints of a randomized trial. There were over 33000 individuals who met their inclusion criteria. To account for differences in potency between different statins and doses, the authors generated a defined daily dose value, with one defined daily dose equal to 40 milligrams per day of Lovastatin. The slope of the dose response was similar across statin types and across different sex and race or ethnicity groups. But there were differences by statin type in the response independent of dose, as well as differences in absolute responses by sex, age, race, smoking, and diabetes. Based on these differences, the authors revised the defined daily doses and they highlight how previously defined equivalencies between different statins may not be accurate. They found that individuals with East Asian ancestry had an enhanced response to therapy compared with individuals of European ancestry. The authors identified related individuals within the data set and the estimated heritability of statin response using parent-offspring and sibling pairs. They found only modest heritability, indicating that non-genetic factors may be more important in determining variability in statin response. Overall, this large single cohort study adds to our knowledge on determinants of statin response and raises further questions on the relative effects of different statins and doses within patient subgroups. Okay, so now let's talk about GWAS and Athero. Sander van der Lann, Paul de Bakker, Gerard Pasterkamp and coauthors from University Medical Center Utrecht published a paper entitled, "Genetic Susceptibility Loci for Cardiovascular Disease and Their Impact on Atherosclerotic Plaques." Over the past decade, genome-wide association studies in large cohorts have been very successful in identifying cardiovascular risk loci. However, relating these to subclinical disease or two mechanisms has been more challenging. The authors were interested in understanding whether established GWAS loci for stroke and coronary disease are associated with characteristics of atherosclerotic plaque, the idea being that some of the risk loci may alter disease risk by determining the development and stability of plaque. They identified seven plaque characteristics to study and histological samples, including intraplaque fat, collagen content, smooth muscle cell percentage, macrophage percentage, calcification, intraplaque hemorrhage, and intraplaque vessel density. They selected 61 known loci and examined association of those SNiPA with black phenotypes in over 1400 specimens from the athero express biobank study. Out of the 61 loci, 21 were associated with some black phenotype compared with zero of five negative control loci, which were chosen as established GWAS loci for bipolar disorder, which, presumably, should share limited mechanistic etiology with plaque. They used the software package VEGAS to run gene-based analyses. They also assessed SNiPA relationships with gene expression and methylation in multiple tissues derived from two independence Swedish biobanks, which included atherosclerotic arterial wall, internal mammary artery, liver, subcutaneous fat, skeletal muscle, visceral fat, and fasting whole blood. One CAD locus on chromosome 7q22 that survived correction for multiple testing was associated with intraplaque fat, and was also an EQTL for expression of several genes across multiple tissues. In addition, it was also a methylation QTL. The authors focused on this locus and looked at correlation of expression within the LDL receptor and noted associations with HDL and LDL cholesterol in the global lipids genetics contortion data, which suggests that this locus may have a role in the metabolism. At this locus, the HBP1 gene expressed foam cells may be an interesting candidate as a causal gene in determining plaque-lipid accumulation and cardiovascular risk. So next up, we have a paper that is also about athero and is coauthored by many of the same group as did that previous study. So yeah, this group's productivity is kind of making the rest of us look bad this month. So Martin Siemelink, Sander van de Lann, and Gerard Pasterkamp and their colleagues published, "Smoking is Associated to DNA Methylation in Atherosclerotic Carotid Lesions." Okay. So I think one of the few things we can all definitely agree on is that smoking is bad. But, does smoking exert any of its cardiovascular damage by altering within atherosclerotic plaques? That's the question this group set out to answer. They carried out a two-stage epigenome-wide association study, or EWAS, with discovery and replication of differentially methylated loci with tobacco smoking within carotid arteriosclerotic plaques of a total of 664 patients undergoing carotid endarterectomy and enrolled in the arthero-expressed biobanks study. In discovery, they found 10 CpG loci within six genes that associated with smoking. Four of the CpG loci replicated. These four loci mapping within six genes showed reduced methylation in current smokers compared with former or never smokers. However, there was no difference in specific plaque characteristics based on methylation at any of the four loci. There was also no significant difference in plaque gene expression at these loci based on smoking status. However, a SNiPA at a nearby locus located in the 3' UTR of the PLEKHGB4 Gene was associated with methylation at AHRR, and was a [inaudible 00:09:58] QTL for PLEKHGB4 of expression but not a AHRR expression. The authors speculate that PLEKHGB4 may co-regulate AHRR expression. The authors also examined blood methylation in a subset of the same subjects, and they were able to replicate previously identified CPG sites associated with smoking. This is a really complex area, and it's hard to identify mechanisms and causality from these multiple layers of data, but the authors demonstrate the importance of using disease relevant tissues to start to understand how environmental factors interact with genetics and other underlying physiology to modify methylation and function within the vasculature. Our final full-length research paper this issue from Brian Byrd and colleagues Michigan, is actually the subject of our interview today. So I won't go into too much detail on it right now, but keep listening for an interview with Brian about their paper, "Human Urinary mRNA as a Biomarker of Cardiovascular Disease: A Proof-of-Principle Study of Sodium-Loading in Prehypertension." Our review article this month is about the "Dawn of Epitranscriptomic Medicine" from Konstantinos Stellos from Newcastle University and Aikaterini Gatsiou from Goethe-Universität Frankfurt. In this paper, they're taking us to the next level beyond just RNA, but towards RNA epigenetics. Given the large number of possible modifications that can and are made to RNA during RNA name metabolism, there's huge potential to gain a new biological and mechanistic understanding by studying the RNA epitranscriptome. I think we'll ignore this at our peril. So if you need to catch up on this new field, this comprehensive review will get you right up to speed. Moving on, our research letters are short format papers that allow authors to present focused results. These are also a great avenue to submit findings from replication studies that might not necessitate a full-length paper. So if you have some data from a replication study that you've been procrastinating writing up, a short research letter is a great format to consider. This month, Bertrand Favre, Luca Borradori and coauthors from Bern University Hospital published a letter entitled, "Desmoplakin Gene Variants and Risk for Arrhythmogenic Cardiomyopathy: Usefulness of a Functional Biochemical Assay." The desmoplakin is essential for the cell-cell adhesion complex's desmosomes. Mutations in this gene have been associated with a wide range of phenotypes, including some in skin and hair, but also in heart, which can manifest arrhythmogenic or dilated cardiomyopathy. This protein anchors intermediate filaments, so mutations that alter binding to intermediate filaments may pathogenicity. The author selected seven reported amino acid altering mutations in desmoplakin, and they screened for effects on binding using a novel fluorescence binding assay. They found that three of the seven mutations had a clear impact on binding. This assay is a novel way to assess functional impact of desmoplakin variants, and may be useful to inform the severity of future phenotypes in individuals carrying a desmoplakin mutation. Finally, if you want to stay up-to-date on the genetics of aortic disease and Marfan syndrome, you can find a letter from Christian Groth and colleagues and an author response from Norifumi Takeda and colleagues regarding their previously published paper on impact of pathogenic FBN1 variant types on the progression of aortic disease in patients with Marfan syndrome. I am joined today by Dr. Brian Byrd from the University of Michigan, who is the senior author on a Manuscript published in this month's issue, entitled, "Human Urinary mRNA as a Biomarker of Cardiovascular Disease: A Proof-of-Principle Study of Sodium-Loading in Prehypertension." So welcome Brian. Thanks so much for coming on the podcast. Brian Byrd: Thank you for having me. Jane Ferguson: So before we get started, could you give a brief introduction of yourself to the listeners and maybe tell us a little bit about how you got into the field? Brian Byrd: Absolutely. So I am a cardiologist and a physician scientist. I'm an assistant professor at the University of Michigan, where I have a laboratory engaged in clinical investigation. My background is that I did my Internal Medicine Residency at Vanderbilt University. And after I finished residency, I entered Nancy Brown's lab. She's the Chair of Medicine at Vanderbilt, as I know you're aware. And she had a laboratory focused, and still does...
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Ep19 August 2018
08/21/2018
Ep19 August 2018
Jane Ferguson: Hello. Welcome to episode 19 of Getting Personal: Omics of the Heart, the issue from August 2018. I am Jane Ferguson, and this podcast is brought to you by the Circulation: Genomic and Precision Medicine Journal and the American Heart Association Council on Genomic and Precision Medicine. Before I dive into the papers from this month, a reminder that early bird registration for AHA Scientific Sessions runs until September 4th, so go register now if you haven't already to take advantage of reduced rates. The meeting will be held in Chicago from November 10th through 12th, and it's the first year of the new three-day meeting format. It's already promising to be a really great meeting, and I'm hoping to see a lot of you there. The August issue has a number of really interesting papers. First up, Gardar Sveinbjornsson, Eva Olafsdottir, Kari Stefansson, and colleagues from deCODE genetics-Amgen report that variants in NKX2-5 and FLNC cause dilated cardiomyopathy and sudden cardiac death. This team leveraged available DNA samples from the Icelandic population to carry out a genome-wide association study in 424 cases of dilated cardiomyopathy and over 337,000 controls. They applied whole genome sequencing to all of these samples, allowing them to identify common and rare variants. In total, they tested over 32 million variants. They found two variants that were significantly associated with DCM at genome-wide significance, a missense variant in NKX2-5 and a frameshift in FLNC, both associated with heart failure and sudden cardiac death. Further, the NKX2-5 variant was associated with atrioventricular block and atrial septal defect. Although these variants are rare and not documented in other populations, they are significant contributors to familial DCM in Iceland. Because of the unique population structure of Iceland and known genealogy, the researchers were able to trace the NKX2-5 variant back to a common ancestor born in 1865. They traced the FLNC variants to a common ancestor born in 1595. While the specific variants identified in this study may not be present in other populations, they are located in genes with known relevance for cardiac function. NKX2-5 encodes a cardiac transcription factor, which is required for embryonic cardiac development, and other variants in this gene have been associated with cardiac dysfunction in other populations. FLNC encodes filamin-C, a muscle cross-linking protein. Variants in FLNC have previously been ascribed to associate with myofibrillar myopathy, muscular dystrophy, and cardiomyopathy. This study adds to our knowledge of the genetics of dilated cardiomyopathy and supports screening for NKX2-5 and FLNC variants, particularly in the Icelandic population, which would allow for early intervention and monitoring in carriers. Staying with the topic of dilated cardiomyopathy, Inken Huttner, Louis Wang, Diane Fatkin, and colleagues from the Victor Chang Cardiac Research Institute in Australia report that an A-band titin truncation in zebrafish causes dilated cardiomyopathy and hemodynamic stress intolerance. We actually talked to Dr. Wang about this research last year when he was presenting this as a finalist for the FGTB Young Investigator Award. You can go back in the archives to episode 10 from November 2017 if you'd like to hear more. Titin mutations are responsible for a large number of cases of dilated cardiomyopathy, but there are also individuals with titin mutations that remain asymptomatic. This group used zebrafish as a model of human titin mutations and generated fish with a truncating variant in the A-band of titin, as has been identified in families with DCM. They found that homozygous mutants had a severe cardiac phenotype with premature death, but that heterozygous carriers survived into adulthood and developed spontaneous DCM. Prior to onset of DCM, the heterozygous fish had reduced baseline ventricular systolic function and reduced contractile response to hemodynamic stress, as well as ventricular diastolic dysfunction. Overall, the mutant fish displayed impaired ability to mount stress responses, which may have contributed to development of disease. Extrapolating this to humans, this could suggest that hemodynamic stress may be a factor that contributes to timing and severity of disease in individuals with titin variants. Hemodynamic stress can be exerted by exercise, pregnancy, and other diseases contributing to ventricular volume overload. Modifying these hemodynamic stressors in at-risk subjects could potentially help to modulate the severity of DCM phenotypes. Moving on to the topic of coronary artery disease, Vinicius Tragante, Daiane Hemerich, Folkert Asselbergs, and colleagues from University Medical Center Utrecht in the Netherlands report on druggability of coronary artery disease risk loci. This group was interested in using results from genome-wide association studies for CAD to identify new targets that may be amenable for drug repurposing. They used results from published GWAS for CAD and created a pipeline to integrate these loci with data on drug-gene interactions, chemical interactions, and potential side effects. They also calculated a druggability score based on the gene products to prioritize targets that are accessible and localized to increase the chance of a drug being able to find the target without affecting core systemic processes or housekeeping genes. Their pipelines allowed them to identify three possible drug-gene pairs, including pentolinium to target CHRNB4, adenosine triphosphate to target ACSS2, and riociguat to target GUCY1A3. They also identified three proteins to be prioritized for drug development, including leiomodin 1, huntingtin-interacting protein 1, and protein phosphatase 2, regulatory subunit b-double prime, alpha). While these predictions were all made in silico and need to be extensively tested in clinical trials, the pipeline did identify many current therapies for CAD and myocardial infarction, including statins, PCSK9 inhibitors, and angiotensin II receptor blockers. These positive controls support that this method can successfully discover effective CAD therapies. Staying on the topic of drugs, Kishan Parikh, Michael Bristow, and colleagues from Duke University report on dose response of beta-blockers in adrenergic receptor polymorphism genotypes. Two clinical trials have reported pharmacogenomic interactions between beta-blockers and beta-1 adrenergic receptor genotype in the setting of heart failure with reduced ejection fraction. In a retrospective analysis in almost 2,000 subjects from the BEST and HF-ACTION studies, the authors analyzed whether genotype at the Arg389Gly polymorphism in beta-1 adrenergic receptor, or an indel in the alpha-2C adrenergic receptor interacted with drug dose to affect mortality and hospitalization. They found that ADRB1 genotype affected mortality in response to drug dose with less all-cause mortality in high versus no or low-dose beta-blockers in individuals homozygous for arginine at position 389, but not in individuals carrying a glycine at that position. In individuals on high-dose beta-blockers, genotype did not affect outcomes, but there was a significant difference by genotype in all-cause mortality in individuals on no or low-dose beta-blockers. These data support the guideline recommendations to use high-target doses of beta-blockers in HFrEF. Switching gears towards precision medicine and genotype-guided approaches, Laney Jones, Michael Murray, and colleagues from Geisinger were interested in the patient's perspective. In their paper, Healthcare Utilization and Patients’ Perspectives After Receiving a Positive Genetic Test for Familial Hypercholesterolemia, they explored the impact of providing genotype test results for familial hypercholesterolemia to subjects participating in the MyCode Community Health Initiative. In MyCode, exome sequencing is conducted in participants, and results are returned for pathogenic and likely pathogenic variants in genes representing actionable conditions based on American College of Medical Genetics secondary findings and recommendations. It is estimated that 3.5% of MyCode participants will be carriers of such variants, and this number may increase as more variants are discovered. In this pilot study, the authors screened for individuals with mutations in LDLR, APOB, or PCSK9, consistent with FH. They identified 28 individuals, of which 23 were eligible for inclusion in the study. Only five of the 23 subjects had previously been diagnosed with FH. Receipt of genetic test results led to change in medications in 39% of individuals. 96% of the subjects had previous LDL measurements, but only four subjects had ever met LDL goals. After genetic test results, three individuals met their LDL goals. Seven individuals consented to participate in interviews about their experience. Almost all of these subjects already had a personal or family history of high cholesterol or heart disease, and all subjects felt that they were being adequately treated. Only three of the seven subjects mentioned using diet and exercise to control their high cholesterol, with most individuals being relatively unconcerned because they felt their medication was effective in controlling disease risk. While the numbers studied here are too small for any statistical testing or inference, the paper describes the results from the interviews, including some excerpts from patients, which really highlight the complexities of returning results and of helping patients understand what their results mean. Given increasing genetic testing and returning of results, studies like this are really important to help us figure out the most effective ways to communicate results and support patients and their care providers. Also from a patient-centric perspective, we have an article from Susan Christian, Joseph Atallah, and colleagues from the University of Alberta in Canada on when to offer predictive genetic testing to children at risk of an inherited arrhythmia or cardiomyopathy, the family perspective. This article considers the timing of cascade testing to predict inherited arrhythmias and cardiomyopathy in children of affected individuals. European and North American guidelines differ on when or if they recommend genetic testing in children. In this study, surveys were circulated to foundations and patient groups to solicit familial perspectives on when genetic testing should be offered to children. In total, 213 individuals responded. In the case of long QT syndrome, 92% of respondents thought testing should be offered before the age of five, while 77% of respondents thought genetic testing should be offered before the age of 10 for hypertrophic cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy. Overall, the potential benefits of genetic testing, including guiding therapies, sport participation, and decreasing worry were ranked more highly than potential risks of discrimination or increasing worry that could occur from genetic testing. Overall, the responses indicated that families would welcome the option of genetic testing for at-risk children from a young age and support initiating early discussions with families to explore costs and benefits of early genetic testing. Finally in this issue, we have a review from Paul Franks and Nicholas Timpson from Lund University and the University of Bristol entitled Genotype-Based Recall in Complex Cardiometabolic Traits. This review looks at the increasing practice of selecting samples or individuals from larger cohorts or biobanks based on their genotype to carry out additional studies. The article focuses on examples of such genotype-based recall studies in cardiometabolic disease, highlights approaches and new methods, and discusses the ways these types of studies can be used to extend and supplement randomized trials and large population-based studies. As always, you can find all the articles, accompanying editorials, and video summaries online. Our website recently underwent some redesigns and has moved. You should be redirected if you have the older site bookmarked, but you can also find us directly at ahajournals.org/journal/circgen. Also, thanks to everyone who participated in the Twitter poll last month. You were pretty evenly split on what you want to hear in the podcast, but please continue to leave suggestions and feedback on what we're doing and where we can improve things. That's it for the August issue of Circulation: Genomic and Precision Medicine. Thanks for listening, and tune in next month for more.
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Ep 18 Khetarpal
07/23/2018
Ep 18 Khetarpal
Jane: Hi, everyone. Welcome to Episode 18 of Getting Personal: Omics of the Heart. I'm Jane Ferguson, and this podcast is brought to you by the Circulation: Genomic and Precision Medicine Journal and the American Heart Association Counsel on Genomic and Precision Medicine. It is July 2018, which means that the best possible place to be listening to this episode is at the beach, but failing that I can also recommend listening on planes, during your commute, while exercising or while drinking a nice cup of tea. So before I get into the papers we published this month, I want to ask for your help. If you're listening to this right now, hi, that means you, we're a year and a half into podcasting and I would love to know what content you like and where we could improve things. We have a poll up on Twitter this week, and I would really appreciate your input. If you're listening to this a little bit later and miss the active voting part of the poll, you can still leave suggestions. Okay, so what I would like you to do right now is to go to Twitter. You can find us as Circ_Gen and locate the poll. If you don't already follow us on Twitter, go do that now too. We want you to let us know what content we should focus on and what is most useful to you, so go ahead and pick your favorites from the options and also please reply or tweet at us with other thoughts and suggestions. Options include giving summaries of the recent articles like I'm about to do later this episode, conducting interviews with authors of recently published papers, interviews with people working in cardiovascular genomics, broader topics. For example, to get their insight on career paths and lessons learned along the way. And something we have not done yet on the podcast but are considering, would be to record podcasts that focus on particular topics in genomics and precision medicine. These could give some background on an emerging field or technology and we could talk to experts who are leading particular innovations in the field. So, if that sounds good to you, let me know! If you're not on Twitter, I don't want to exclude you, so you can email me at [email protected] and give me your thoughts that way. I'm looking forward to hearing from you. Okay, so on to the July 2018 issue of Circ.: Genomic and Precision Medicine. First up is a PhWAS from Abrahim Rao, Eric Ingelsson, and colleagues from Stanford. The discovery of the PCSK9 gene as a regulator of cholesterol levels has led to a new avenue of LDL lowering therapies through PCSK9 inhibition. However, some studies suggest that long term use of PCSK9 inhibitors could have adverse consequences. Because of the long follow-up time required, it will take many more years to address this question through clinical studies. However, genetic approaches offer a fast and convenient alternative to address the issue. In this paper, entitled: "Large Scale Phenome-Wide Association Study of PCSK9 Variants Demonstrates Protection Against Ischemic Stroke," the authors use genetic and phenotype data from over 300,000 individuals in the UK BioBank to address whether genetic loss of function variants in PCSK9 are associated with phenotypes including coronary heart disease, stroke, type II diabetes, cataracts, heart failure, atrial fibrillation, epilepsy, and cognitive function. The missense variant RS11591147 was associated with protection against coronary heart disease and ischemic stroke. This SNP also associated with type II diabetes after adjustment for lipid medication status. Overall, this study recapitulated the associations between PCSK9 and coronary disease, and revealed an association with stroke. Previous studies suggested use of LDL lowering therapies may increase risk of cataracts, epilepsy, and cognitive dysfunction, but there was no evidence of association in this study. Overall, this study provides some reassurance that the primary effect of PCSK9 is on lipids and lipid related diseases, and that any effects on other phenotypes appear to be modest at best. While a PhWAS can't recapitulate a clinical trial, what this study indicates is that PCSK9 inhibition is an effective strategy for CVD prevention, which may confer protection against ischemic stroke and does not appear to convey increased risk for cognitive side effects. Next up we have a manuscript form Jason Cowan, Ray Hershberger, and colleagues from Ohio State University College of Medicine. Their paper, "Multigenic Disease and Bilineal Inheritance in Dilated Cardiomyopathy Is Illustrated in Non-segregating LMNA Pedigrees," explored pedigrees of apparent LMNA related cardiomyopathy identifying family members who manifested disease, despite not carrying the purported causal LMNA variant. Of 19 pedigrees studies, six of them had family members with dilated cardiomyopathy who did not carry the family's LMNA mutation. In five of those six pedigrees, the authors identified at least one additional rare variant in a known DCM gene that was a plausible candidate for disease causation. Presence of additional variants was associated with more severe disease phenotype in those individuals. Overall, what this study tells us is that in DCM, there is evidence for multi-gene causality and bilineal inheritance may be more common than previously suspected. Future larger studies should consider multi-genic causes and will be required to fully understand the genetic architecture of DCM. Yukiko Nakano, Yasuki Kihara, and colleagues from Hiroshima University published a manuscript detailing how HCN4 gene polymorphisms are associated with tachycardia inducted cardiomyopathy in patients with atrial fibrillation. Tachycardia induced cardiomyopathy is common in subjects with atrial fibrillation, but the pathophysiology is poorly understood. Recent studies have implicated the cardiac hyperpolarization activated cyclic nucleotide gated channel gene, or HCN4, in atrial fibrillation and ventricular function. In this paper, the authors enrolled almost 3,000 Japanese subjects with atrial fibrillation, both with and without tachycardia-induced cardiomyopathy, as well as non-AF controls. They compared frequency of variants in HCN4 in AF subjects with or without tachycardia-induced cardiomyopathy, and found a SNP, RS7164883, that may be a novel marker of tachycardia-induced cardiomyopathy in atrial fibrillation. Xinyu Yang, Fuli Yu, and coauthors from Tianjin University were interested in finding causal genes for intracranial aneurysms, and report their results in a manuscript entitled, "Rho Guanine Nucleotide Exchange Factor ARHGEF17 Is a Risk Gene for Intracranial Aneurysms." They sequenced the genomes of 20 Chinese intracranial aneurysm patients to search for potentially deleterious, rare, and low frequency variants. They found a coding variant in the ARHGEF17 gene which was associated with associated with increased risk in the discovery sample, and which they replicated in a sample of Japanese IA and in a larger Chinese sample. They expanded this to other published studies, including individuals of European-American and French-Canadian origin and found a significantly increased mutation burden in ARHGEF17 in IA patients across all samples. They were interested in further functional characterization of this gene and found that Zebra fish ARHGEF17 was highly expressed in blood vessels in the brain. They used morpholinos to knock down ARHGEF17 in Zebra fish, and found that ARHGEF17 deficient Zebra fish developed endothelial lesions on cerebral blood vessels, and showed evidence of bleeding consistent with defects in the vessel. This study implicates ARHGEF17 as a cerebro-vascular disease gene which may impact disease risk through effects on endothelial function and blood vessel stability. Sumeet Khetarpal, Paul Babb, Dan Rader, Ben Voight, and colleagues from the University of Pennsylvania used targeted resequencing to look at determinants of extreme HDL cholesterol in their aptly titled manuscript, "Multiplexed Targeted Resequencing Identifies Coding and Regulatory Variation Underlying Phenotypic Extremes of HDL Cholesterol in Humans." Stay tuned because we're gonna hear more about this paper from the first author Dr. Sumeet Khetarpal later this episode. Rounding out this issue we have a Perspective article from Chris Haggerty, Cynthia James, and coauthors from Geisinger and Johns Hopkins Medical Center entitled, "Managing Secondary Genomic Findings Associated With Arrhythmogenic Right Ventricular Cardiomyopathy: Case Studies and Proposal for Clinical Surveillance." In this paper the authors discuss the challenges for returning findings from clinical sequencing for arrhythmogenic right ventricular cardiomyopathy, presenting case studies exemplifying these challenges. They also propose a management approach for returning clinical genomic findings, and discuss new innovations in the light of precision medicine. We also published a review article by Pradeep Natarajan, Siddhartha Jaiswal, and Sekar Kathiresan from MGH on "Clonal Hematopoiesis Somatic Mutations in Blood Cells and Atherosclerosis", which discusses recent advances in our knowledge on the role of somatic mutations in cardiovascular disease risk. Finally, we have an update on some pharmacogenomics research into CYP2C19 Genotype-Guided Antiplatelet Therapy by Craig Lee and colleagues which we published a few months ago. Dr. Lee was also featured on Podcast episode 15 in April of this year. Jernice Aw and colleagues from Khoo Teck Puat Hospital, Singapore shared from complimentary data from their sample of 247 Asian subjects which found the risk for major adverse cardiovascular events was over 30-fold greater for poor metabolizers, as defined by CYP2C19 genotype on clopidogrel, as compared to those with no loss of function allele. You can read that letter and the response from Dr. Lee and colleagues online now. And, as usual, all of the original research articles come with an editorial to help give some more background and perspective to each paper. Go to circgenetics.ahajournals.org to find all the papers and to access video summaries and more. Our interview is with Dr. Sumeet Khetarpal who recently completed his MD-PhD training at the University of Pennsylvania, and is currently a resident in Internal Medicine at Massachusets General Hospital. Sumeet kindly took some time out from his busy residency schedule to talk to me about his recently published paper, and to explain how molecular inversion probe target capture actually works. So I am here with Dr. Sumeet Khetarpal who is co-first author on a manuscript entitled, "Multiplexed Targeted Resequencing Identifies Coding and Regulatory Variation Underlying Phenotypic Extremes of High-Density Lipoprotein Cholesterol in Humans." Welcome Sumeet, thanks for taking the time to talk to me. Dr. Khetarpal: Thank you so much Dr. Ferguson, it's really a pleasure to talk to you today. Jane: Before we get started, maybe you could give a brief introduction on yourself and then how you started working on this paper. Dr. Khetarpal: Sure, so this work actually was a collaboration that came out at the University of Pennsylvania that I was involved with through my PhD thesis lab, my mentor was Dan Rader, and also a lab that is a somewhat newer lab at Penn, Benjamin Voight's lab which is a strong sort of computational genomic lab. This work actually highlights the fun of collaborating within your institution. We had, for some time, been interested in developing a way to sequence candidate genes. Both known genes and also new genes that have come out of genome-wide association studies that underlie the extremes of HDL cholesterol, namely very high cholesterol versus low HDL cholesterol. We've been looking for a cost-effective and scalable way to do this. Independently, Ben, who is very interested in capturing the non-coding genome, was interested in developing a method to better understand the non-coding variation, both common and rare variation that may be present at all of these new loci that have come out for complex traits such as HDL. ...
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Ep 17 Jennie Lin Beth McNally
06/19/2018
Ep 17 Jennie Lin Beth McNally
Jane Ferguson: Hello, welcome to Getting Personal: Omics of the Heart. It is June 2018, and this is podcast episode 17. I'm Jane Ferguson, an assistant professor of medicine at Vanderbilt University Medical Center, and a proponent of precision medicine, genomics, and finding ways to prevent and treat heart disease. Jane Ferguson: This podcast is brought to you by Circulation: Genomic and Precision Medicine, and the AHA Council on Genomic and Precision Medicine. Jane Ferguson: For our interview this month, early career member, Jennie Lin talked to Beth McNally about science and careers in genomic medicine. We'll have more on that later but first I want to tell you about the cool papers we published in the journal this month. Jane Ferguson: First up, Orlando Gutierrez, Marguerite Irvin, Jeffrey Kopp, Cheryl Winkler, and colleagues from the University of Alabama at Birmingham, and the NIH, published an article entitled APOL1 Nephropathy Risk Variants and Incident Cardiovascular Disease Events in Community-Dwelling Black Adults. This study was conducted in over 10 thousand participants of the Reasons for Geographic and Racial Differences in Stroke, or, REGARDS Study. They examined associations between APOL1 variants and incident coronary heart disease, ischemic stroke, or composite CVD outcome. Because there are coding variants in the APOL1 Gene that are only found in individuals of African ancestry, these are hypothesized to contribute to the disparities in cardiovascular and renal disease in African Americans. Jane Ferguson: The authors found that carrying the risk variants was associated with increased risk of ischemic stroke, but only in individuals who did not have diabetes, or chronic kidney disease. They hypothesize that because diabetes and kidney disease already increase CVD risk, the variant does not have an additional effect on risk in individuals with existing comorbidities. But, it contributes to small vessel occlusion and stroke in individuals without diabetes. Jane Ferguson: They also found that the magnitude and strength of the association became stronger in a model adjusted for African ancestry, suggesting an independent effect of the APOL1 risk variants. Jane Ferguson: While future work is needed to study this more, this is an important step in understanding the complex relationship between APOL1 and disease. Jane Ferguson: Next up, Daniela Zanetti, Erik Ingelsson, and colleagues from Stanford, published a paper on Birthweight, Type 2 Diabetes, and Cardiovascular Disease: Addressing the Barker Hypothesis with Mendelian Randomization. The Barker Hypothesis considers that low birthweight as a result of intrauterine growth restriction, causes a higher future risk of hypertension, type 2 diabetes, and cardiovascular disease. However, observational studies have been unable to establish causality or mechanisms. Jane Ferguson: In this paper, the authors used Mendelian Randomization as a tool to address causality. They used data from the UK Biobank, and included over 237,000 participants who knew their weight at birth. They constructed genetic predictors of birthweight from published genome wide association studies, and then looked for genetic associations with multiple outcomes, including CAD, stroke, hypertension, obesity, dyslipidemia, dysregulated glucose and insulin metabolism, and diabetes. Jane Ferguson: The Mendelian randomization analysis indicated that higher birthweight is protective against CAD type 2 diabetes, LDL cholesterol, and high 2 hour glucose from oral tolerance test. But, higher birthweight was associated with higher adult BMI. This suggests that the association between low birthweight and higher disease risk is independent of effects on BMI later in life. While the study was limited to a well nourished population of European ancestry, and would need to be confirmed in other samples, and through non-genetic studies, it suggests that improving prenatal nutrition may be protective against future cardiometabolic disease risk. Jane Ferguson: Laura Muino-Mosquera, Julie De Backer, and co-authors from Ghent University Hospital, delved into the complexities of interpreting genetic variants, as published in their manuscript, Tailoring the ACMG and AMP Guidelines for the Interpretation of Sequenced Variants in the FBN1 Gene for Marfan Syndrome: Proposal for a Disease- and Gene-Specific Guideline. Jane Ferguson: With a large number of variants being uncovered through widespread sequencing efforts, a crucial challenge arises in their interpretation. The American College of Medical Genetics and Genomics, and the Association for Molecular Pathology put forward variant interpretation guidelines in 2015, but these were not tailored to individual genes. Because some genes have unique characteristics, the guidelines may not always allow for uniform interpretation. Jane Ferguson: In their manuscript, the authors focused on variants in fibrillin-1 that cause Marfan Syndrome, and reclassified 713 variants using the guidelines, comparing those classifications to previous in-depth methods which had indicated these variants' causal or uncertain significance. They find 86.4% agreement between the two methods. Jane Ferguson: Applying the ACMG, AMP guidelines without considering additional evidence may thus miss causal mutations. And it suggests that adopting gene specific guidelines may be helpful to improve clinical decision making and accurate variant interpretation. Jane Ferguson: Delving deeper into FBN1 and Marfan Syndrome, Norifumi Takeda, Ryo Inuzuka, Sonoko Maemura, Issei Komuro, and colleagues from the University of Tokyo examined the Impact of Pathogenic FBN1 Variant Types on the Progression of Aortic Disease in Patients With Marfan Syndrome. They evaluated 248 patients with pathogenic, or likely pathogenic, FBN1 variants, and examined the effect of variant subtype on severe aortopathy, including aortic root replacement, type A dissections, and related death. They found that the cumulative aortic event risk was higher in individuals with haploinsufficient type variants, compared with dominant negative variants. Jane Ferguson: Within individuals with dominant negative variants, those that affected Cysteine residues, or caused in-frame deletions, were associated with higher risk compared with other dominant negative mutations, and were comparable to the risk of the haploinsufficient variants. These results highlight the heterogeneity and risk of the FBN1 variants, and suggest that individuals with haploinsufficient variants, and those carrying dominant negative variants affecting Cysteine residues or in-frame Deletions, may need more careful monitoring for development of aortic root aneurysms. Jane Ferguson: Lydia Hellwig, William Klein, and colleagues from the NIH, investigated the Ability of Patients to Distinguish Among Cardiac Genomic Variant Subclassifications. In this study, they analyzed whether different subclassifications of variants of uncertain significance were associated with different degrees of concern amongst recipients of genetic test results. 289 subjects were recruited from the NIH ClinSeq Study, and were presented with three categories of variants, including variants of uncertain significance, possibly pathogenic, and likely pathogenic variants. Participants were better able to distinguish between the categories when presented with all three. Whereas, a result of possibly pathogenic given on its own, produced as much worry as a result of likely pathogenic. The authors conclude that multiple categories are helpful for subjects to distinguish pathogenicity subclassification, and that subjects receiving only a single uncertain result, may benefit from interventions to address their worry and to calibrate their risk perceptions. Jane Ferguson: Erik Ingelsson and Mark McCarthy from Stanford, published a really nice review article entitled Human Genetics of Obesity and Type 2 Diabetes: Past, Present, and Future. Over the past decade, we've had a lot of excitement, optimism, and also disappointment in what genome-wide association studies can deliver. Doctors Ingelsson and McCarthy do a great job laying out the history and the successes in the field of genetic interrogation of obesity and diabetes, as well as acknowledging where reality may not live up to the hype, what challenges remain, and what the future may hold. They also have a figure that uses an analogy of a ski resort to emphasize the importance of taking a longitudinal perspective. And I would argue that any paper that manages to connect apres-ski with genomics is worth reading, for that alone. Jane Ferguson: Robert Roberts wrote a perspective on the 1986 A.J. Buer program, pivotal to current management and research of heart disease. Highlighting how the decision by the AHA in 1986 to establish centers to train cardiologists and scientists in molecular biology, has led to huge advances in knowledge and treatment of heart disease. Jane Ferguson: Finally, rounding out this issue, Kiran Musunuru and colleagues, representing the AHA Council on Genomic and Precision Medicine, Council on Cardiovascular Disease in the Young, Council on Cardiovascular and Stroke Nursing, Council on Cardiovascular Radiology and Intervention, Council on Peripheral Vascular Disease, Council on Quality of Care and Outcomes Research, and the Stroke Council, published a scientific statement on Interdisciplinary Models for Research and Clinical Endeavors in Genomic Medicine. Jane Ferguson: This paper lays out the field of cardiovascular research in the post genomic era, highlights current practices in research and treatment, and outlines vision for interdisciplinary, translational research and clinical practice, that could improve how we understand disease, and how we use those understandings to help patients. Jane Ferguson: Our guest interviewer today is Dr. Jennie Lin, an Assistant Professor at Northwestern Universities Feinberg School of Medicine, and the incoming Vice Chair of the Early Career Committee of the AHA Council on Genomic and Precision Medicine. As an aside, Jennie is a great person to follow on Twitter for insights into genomics and kidney disease, and as a bonus, she also posts the occasional dog photo. So she's well worth following just for that. You can find her on Twitter @jenniejlin. As you'll hear, Jennie talked to Dr. Beth McNally about her view on genomic medicine, and Beth also shared some really great practical tips for early career investigators building their independent labs. So make sure you listen all the way to the end. Take it away Jennie. Dr. Lin: Thank you for tuning in to this edition of Getting Personal: Omics of the Heart, a podcast by the Genomic and Precision Medicine Council of the American Heart Association, and by Circulation: Genomic and Precision Medicine. Today I am joined by Dr. Elizabeth McNally, the Elizabeth J Ward Professor of Genetic Medicine, and director of the Center for Genetic Medicine at Northwestern University. Beth, thank you for taking time to chat with all of us. Dr. McNally: Happy to be here. Dr. Lin: As a successful physician scientist, you have been interviewed in the past about your life, your scientific interests, and advice for budding investigators. I don't want to rehash everything you have already stated beautifully in an interview with Circ Res, for example. But instead wanted to focus more on your views of genetic medicine and genome science today. Dr. Lin: So you mentioned in that prior Circ Res interview that you started your laboratory science training and career during college, when you participated in a project focused on genetic variation among children with muscular diseases. What have you found to be most interesting about the process of identifying functional genetic variants back then, and also that on-going work now. Dr. McNally: Well, I think over the years I've been doing this is the tools have gotten so much better, to be able to actually define the variants much more comprehensibly than we ever could in the past. And then also to be able to study them, and very much to be able to study them in context. And so I look at the revolutions in science that will cause people to look back on this era as the era of genetics. It began obviously with PCR, we couldn't have gotten anywhere without that. Dr. Lin: Right. Dr. McNally: And then you leap forward to things like next generation sequencing, and IPS cells, and now CRISPR/Cas gene editing. And to realize that the last three happened within a decade of each other, is going to be so meaningful when you think about the next few decades, and what will happen. So being able to take an IPS cell and actually study a mutation or a variant in context of that patient, the rest of their genome, is really important to be able to do. Dr. Lin: Okay, Great. And so, where do you envision ... with taking say for example, this next gen. technology, CRISPR/Cas9, studying variants in an IPS cell, for example. How do you envision this really revolutionizing the study of human genetics for patients? And how far do you think we've come in fulfilling that vision, and what do you think should be our focus going forward? Dr. McNally: I think broadly thinking about human genetics we're really very much still at the beginning, which I know is hard to say and hard to hear. But, we've spent a lot of the last 15 years very focused on that fraction of the genome that has high frequency, or common variation, through a lot of the GWA studies. With those common variants, we had a lot of associations, but relatively small effects of a lot of those, causing a lot of people to focus on the missing heritability and where we might find that hiding. And of course, now that we have deep sequencing, and we have deep sequencing where we've really sampled so much more of the genome, and from so many more people, I think we're just at the beginning of really appreciating that rare variation. And beginning again to really appreciate that 80-85% of the variation that's in each of our genomes is really characterized as rare. Dr. McNally: And so we really each are quite unique, and that when we understand a variant we do have to understand it in the context of all that other variation. So computationally that's very challenging to do. Obviously requires larger and larger data sets. But even in doing that, you are not going to find exact replicates of the combinations that you see in any one individual. While I know everybody would love that we're going to have the computational answer to all of this, it's still going to come down to a physician and a patient and making what you think is that best decision for the patient, based hopefully on some genetic data that helps inform those decisions. Dr. Lin: Right, right. So it kind of gets into this whole concept of precision medicine, which has gained a lot of popularity and buzz in recent years, and Obama has really brought it to the forefront in the public arena. You mention rare variants in ... finding rare variants in each patient, for example. And moving a little bit away from some of the common variants that we find in GWAs. What does it mean for a patient to have a rare variant and come see you in your cardiomyopathy clinic, is it going to be precision for that patient, or suing rare variants among many different individual patients to try to find function for a gene? Dr. McNally: It's a great question. So I think the first way we approach it is, it depends who's asking the question. So if it's somebody who comes to me who has cardiomyopathy, or has a family history of cardiomyopathy and sudden death, that's a very different question to ask what's going on with their rare variants, for example in cardiomyopathy genes. Now if you translate that over to, I have a big population of people, I don't particularly...
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Ep16 Caitrin McDonagh
05/23/2018
Ep16 Caitrin McDonagh
Jane Ferguson: Hi, everyone. Welcome to Getting Personal: Omics of the Heart. This is podcast episode 16 from May 2018. I'm Jane Ferguson from Vanderbilt University Medical Center and this podcast is brought to you by Circulation Genomic and Precision Medicine and the AHA Council on Genomic and Precision Medicine. Jane Ferguson: This month we talked to Dr. Caitrin McDonough from the University of Florida. We briefly mentioned her paper in last month's episode Genetic Variants Influencing Plasma Renin Activity in Hypertensive Patients From the PEAR Study, but we wanted to go into it in more depth this month. Caitrin shared with us that this manuscript actually resulted from student course work and was a collaborative effort between students and instructors. The manuscript highlights has successful as approach can be both in increasing student engagement and as an effective way to do high quality research. You can hear her talk more about her innovative approach to student learning and the study findings later in this episode. Jane Ferguson: Of course, we have a great lineup of papers in Circulation Genomic and Precision Medicine this month. First up, a paper entitled, "SCN5A Variant Functional Perturbation and Clinical Presentation Variants of a Certain Significance" by Brett Kroncke, Andrew Glazer, and Dan M. Roden and colleagues from Vanderbilt University Medical Center. They were interested in investigating the functional significance of variants in the cardiac sodium channel in particular to see if they could explain why some variant carriers present with cardiac arrhythmias while others remain asymptomatic. Through a comprehensive literature search, they identified 1712 SCN5A variants and characterized the carriers by disease presentation. Variants associated with disease were more likely to fall in transmembrane domains consistent with the importance of these domains for channel function. Jane Ferguson: Using American College of Medical Genetics Criteria for variant classification, they found that variants classified as more pathogenic were also more penetrant. Penetrance was also associated with electrophysiological parameters. This approach highlights how modeling the penetrance of different variants can help define disease risk for individuals who carry potentially pathogenic variants. Jane Ferguson: Next we have a paper from Vincenzo Macri, Jennifer Brody, Patrick Ellinor, Nona Sotoodehnia and colleagues from the University of Washington and Massachusets General Hospital. This is also related to sodium channels and the paper is entitled, "Common Coding Variants in SCN10A Are Associated With the Nav1.8 Late Current and Cardiac Conduction". They were interested in SCN10A and sequenced this gene in over 3600 individuals from the CHARGE consortium to identify variants associated with cardiac conduction. They were able to replicate associations between variants and PR and the QRS intervals in a sample of almost 21,000 individuals from the CHARGE Exome sample. They identified several missense variants have clustered into distinct haplotypes and they showed that these haplotypes were associated with late sodium current. Jane Ferguson: Continuing the cardiac conduction theme, Honghuang Lin, Aaron Isaacs and colleagues published a manuscript entitled, "Common and Rare Coding Genetic Variation Underlying the Electrocardiographic PR Interval". They conducted a meta-analyses of PR interval in over 93000 individuals which included over 9000 individuals of African ancestry. They identified 31 loci, 11 of which have not been reported before. We see SCN5A come up again as a gene of interest in this study but their analyses also implicated a novel locus, MYH6. Jane Ferguson: Next up moving from the heart to the vasculature, Janne Pott, Markus Scholz and colleagues from the University of Leipzig published a manuscript entitled, "Genetic Regulation of PCSK9 Plasma Levels and Its Impact on Atherosclerotic Vascular Disease Phenotypes". They were interested in whether circulating PCSK9 can be used as a diagnostic or predictive biomarker. To address this, they conducted a GWAS of plasma PCSK9 in over 3000 individuals from the LIFE-Heart study. They found that several independent variants within the PCSK9 gene were associated with plasma PCSK9 as well as some suggestive variants in another gene locus FBXL18. They used Mendelian randomization to probe causality and the data suggest that PCSK9 variants have a causal role in the presence and severity of atherosclerosis. Jane Ferguson: Moving on to another biomarker, Lisanne Blauw, Ko Willems van Dijk and colleagues from the Einthoven Laboratory for Experimental Vascular Medicine report on CETP in their manuscript Cholesteryl Ester Transfer Protein Concentration A Genome-Wide Association Study Followed by Mendelian Randomization on Coronary Artery Disease. They aimed to assess potential causal effects of circulating CDP on cardiovascular disease through GWAS and Mendelian randomization. Jane Ferguson: In a study of over 4000 individuals from the Netherlands Epidemiology of Obesity Study, they identified three variants in CTP that associated with plasma levels of CETP and explained over 16% in the total variation in CDP levels. Genetically predicted in CETP was associated with reduced HDL and LDL cholesterol suggesting that CETP may be causally associated with coronary disease. Jane Ferguson: Rounding out the table of contents we also have a clinical case perspective from Nosheen Reza, Anjali The Importance of Timely Genetic Evaluation in family members in cases of cardiac disfunction and cardiomyopathy. We have a report from Adrianna Vlachos, Jeffrey Lipton and colleagues on the Diamond Blackfan Anemia Registry and we have a clinical case from Yukihiro Saito, Hiroshi Ito and colleagues on TRP and poor mutations in patients with ventricular non-compaction and cardiac conduction disease. Jane Ferguson: To read all of these papers and the accompanying commentaries, log on to circgenetics.aha.journals.org and if you're a visual learner or you need a work related excuse to spend time on YouTube, you can also access video summaries of all our articles from the CircGen website or directly from our YouTube channel Circulation Journal. Lastly, follow us on Twitter at circ_gen or on Facebook to get new content directly in your feed. Jane Ferguson: I'm joined today by Caitrin McDonough from the University of Florida and Caitrin is an Assistant Professor in the Department of Pharmacotherapy and Translational research in the College of Pharmacy and she's the first author on a recently published manuscript entitled, "Genetic Variants Influencing Plasma Renin Activity in Hypertensive Patients From the PEAR Study". This was published in the April 2018 issue of Circulation Genomic and Precision Medicine. Welcome, Caitrin. Caitrin M.: Thank you. Jane Ferguson: For listeners who haven't had a chance to read the paper yet, I wonder could you give us a brief overview of what prompted you to do this study? Caitrin M.: Sure so this looks at plasma renin activity and just initially a GWAS but it was done in a hypertensive population from the pharmogenomic evaluation of antihypertensive responses study. Particularly, since our group here at the University of Florida is more interested in pharmacogenomics we wanted to address plasma renin since it can influence blood pressure response to antihypertensive medication particularly if you use it as something to predict but also to correlate it with that as there have been also prior data from our group that shows if you have different levels of plasma renin that would predict if you would respond better to certain types of antihypertensive medications such as a beta-blocker or a diuretic. Caitrin M.: We used both a GWAS approach as well as a prioritization through blood pressure response to focus in on signals and then furthered by using prioritization using data from RNA seq and looking at eQTLs and then finally looking at more of just a traditional net replication of the original plasma renin activity signal. Caitrin M.: Overall, one of the interesting things and why we were initially doing this study was really in connection with a graduate course that myself and another faculty member here who's also an author on the paper, Yan Gong [inaudible 00:09:12]. We often have the students analyze data from the PEAR study as we have a lot of data from that study and it helped us analyze additional papers but we didn't necessarily know if this was going to be an interesting phenotype but through that course work which turned out that it really did have some interesting signals so we wanted to follow up more on. Jane Ferguson: Yeah, I love that approach so I think that's a really smart way to do it. To actually get your students to analyze your data and get them really involved in the process. How much then did the students ... how much were then they able to get involved when it started transpiring that their results would actually be something that could be put together for a manuscript? Caitrin M.: Overall, they are fairly involved. During the course work, what we usually do is give them just directly types data since a lot of them have not done this type of genetic analysis before and we split it up where each student gets about four to five chromosomes of data and then different phenotypes in the different race groups as we have both whites and African Americans. They get a certain race group, certain number of chromosomes and so they're able to conduct the analysis just using the Uplink software which is fairly user-friendly and straightforward. Then they get experience making Manhattan plots and using LocusZoom. Caitrin M.: After they have the basic techniques, then we teach them how to start following up top signals and determine what is a good signal. They're looking at the LD or SNP function or possibly gene function or looking at their genotype, phenotype relationships and making sure that it's not just one person who's driving the whole signal. Then selecting what top reasons and top SNPs may need a follow up. That part they all do there in the class and learn more of the basics. Caitrin M.: After the class, the students who want to continue to participate we get together and redistribute data where they would then move on to working on the imputed data sets and we teach them how to do that. Then we give them ... operate it somewhat similar to a consortia level meta-analysis type thing. I write up an analysis plan, each student does some part of the analysis. They have to bring it all back to me. I sort through it. We meet and go through it. Then we set our next steps to follow up. Then different students get different SNPs to investigate the function of or different subanalyses to do. Caitrin M.: One of our graduate students who is on this particular project, her dissertation project was very focused on our RNA seq data so that was how we were able to bring in the eQTL analysis using the RNA seq data as she had done a lot of the groundwork with that already. In one of our discussions that was one of the ways that we were able to incorporate the prioritization since she was intimately familiar with that data set. Jane Ferguson: Yeah and I think that's great. I can imagine that, that's a much more compelling way for students to learn about how to analyze data when they see the natural follow through. Do you find that some of the students maybe get more excited about research or are more likely to pursue future research opportunities by having had this hands on experience with the publication process and completing a project really did to this very end? Caitrin M.: They do, yeah. I see some of the students that end up sticking with it more are the students who I work more closely with and see more closely some of the students who are from other departments still stay involved but sometimes don't stay quite as involved. But, all of them really do continue to follow up and ask if they can still help or if there's anything they need to do until we get it to publication which is really nice. Jane Ferguson: Yeah, right. I think that's fantastic and I'm sure every study has its challenges. I'm interested what were the challenges you encountered in doing this study and which one of them may be unique to the way you have a lot of different people analyzing different aspects of the data versus the regular challenges that would come up in a study like this. Caitrin M.: Yeah so some of it I think is just keeping everyone on track and keeping it organized, making sure I think some of our challenges with this study was just me making I think on a lot of other studies, while I had certainly hands on the data it was more of an oversight rule for some pieces of it and just making sure everything looked the way that I thought it did, double checking. Some of it I think the teaching aspect of it just making sure everything was also done correctly and then keeping everything organized made the study a little bit more challenging. Caitrin M.: I think part of it too was with the PEAR study, it is a very rich data set. Determining what we wanted for our prioritization scheme and how to work through the different types of data sets that we had and put it all together as initially we just assign each student a different piece and we had a vague plan but it was a little bit more tricky as to work through how it was all coming together then when everyone came back together since a lot of people were doing as opposed to just one person doing it. Jane Ferguson: Right, so yeah and I think you're touching on the part that all of us have when we're writing papers that you sometimes end up with a lot of data at the beginning, you're trying to sift through it and then sometimes at a certain point you see something and you're like, "Okay, yes. This is interesting." Then you start following it up. Jane Ferguson: I wonder at what point did that happen? I suppose you probably ... You ran the GWAS for plasma renin activity and then find a number of suggested SNPs that were significant you associated but then ... Describe your strategy and you did so the second screening stuff to look at the pharmacological aspect defining [crosstalk 00:15:12]? Caitrin M.: Yeah, our initial plan going in was the first two steps, to do the GWAS for plasma renin activity and then to do the prioritization through blood pressure responses. I was very familiar with what our lab was familiar with but then after we got there, I think we were then troubled with what we did next and where to go. When we decided to bring in the RNA seq data, I think that was when it really started coming together as our top signal, the SNN-TXNDC11 gene region really stuck out then and it showed up. That seemed like a much stronger signal and it gave us a little bit more focus and also brought it much more of a functional aspect where we would maybe start to believe that signal more. That I think was really when we did that more of a turning point for the study and helped us focus more on where then to go with the results. Jane Ferguson: As far as the data you had I think over 700 people for your GWAS. Then you had a pretty large number of ... Was it the same subjects or different subjects where you also had the RNA seq data to do the QTL analysis? Caitrin M.: The same subject so not everyone has RNA seq. We have RNA seq data on 50 individuals and they were selected from whites and at the extremes of the blood pressure response so that it has a slightly interesting selection process. It's the main data analysis there was a best responder, worse responder to thiazide diuretics. Caitrin M.: When we do the eQTL analysis, we aren't always sure what we're going to get since we're missing the middle of blood pressure response. But, when we're just looking strictly at eQTL analysis sometimes we get lucky...
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15 April 2018 Sony Tuteja Craig Lee
04/20/2018
15 April 2018 Sony Tuteja Craig Lee
Jane Ferguson: Hello, welcome to Getting Personal: Omics of the Heart. This is podcast Episode 15 from April 2018. I'm Jane Ferguson, an Assistant Professor of Medicine at Vanderbilt University Medical Center, and this podcast is brought to you by Circulation Genomic and Precision Medicine and the AHA Council on Genomic and Precision Medicine. As usual, we have a great lineup of papers in Circ Genomic and Precision Medicine this month. The first is actually the subject of our interview this month. Sony Tuteja talked to Craig Lee from the University of North Carolina about his manuscript entitled, "Clinical Outcomes and Sustainability of Using CYP2C19 Genotype Guided Antiplatelet Therapy After Percutaneous Coronary Intervention." This manuscript investigated the use of pharmacogenomics to improve treatment after PCI, and you can hear a lot more about it directly from the first author later in the podcast. Our next manuscript also used pharmacogenomics approaches to look for snips associated with plasma renin activity and to assess the effect of top snips with blood pressure response to atenolol and hydrochlorothiazide. The first and last authors are Caitrin McDonough and Julie Johnson from the University of Florida. And their manuscript is entitled, "Genetic Variants Influencing Plasma Renin Activity in Hypertensive Patients from the Pharmacogenomic Evaluation of Antihypertensive Response," or PEAR study. They find that snips in the SNNTXNDC11 gene region associate with higher baseline plasma renin activity in their sample of over 700 subjects and with a smaller systolic blood pressure reduction to hydrochlorothiazide. Variation in the region may act through modulation of TXNDC11 gene expression. They also identified several other candidate genes of interest. These new candidates may allow for precision medicine approach to selection of hypertensive treatment and further study the mechanisms may reveal novel biology on blood pressure response to pharmacological treatment. Next up is a manuscript by Deirdre Tobias and colleagues entitled, "Circulating Branch Chain Amino Acids and Incident Cardiovascular Disease in a Prospective Cohort of U.S. Women." I actually had the chance to talk to Deirdre about her research last month. So check out the March podcast, Episode 14, to hear more from Dr. Tobias about this study. A study of hypertrophic cardiomyopathy from Hannah [inaudible 00:02:36] and Michelle Michels and colleagues from the Erasmus Medical Center in the Netherlands assessed the effects of genetic screening in family members of patients with a known hypertrophic cardiomyopathy mutation. In their manuscript entitled, "Outcomes of Contemporary Family Screening and Hypertrophic Cardiomyopathy," they described their study which assessed cascade screening in 777 relatives of 209 probans between 1985 and 2016. Genetic and clinical screening resulted in a diagnosis of HCM in 30% of family members at the time of testing. An additional 16% of family members developed HCM over seven years of follow up. Of the 43% of family members who were genotype positive, 37% were ultimately diagnosed with HCM. There was no difference in survival between genotype positive and genotype negative family members or with relatives who did not undergo genetic testing. There are genetic considerations that are unique to the ancestral composition of the Netherlands with a high proportion of individuals with a founder mutation, so the proportion of probans with identified mutations is higher than in other reported studies. This paper demonstrates the potential benefit of genetic screening in family members, which can identify individuals who should undergo intensive screening, and at the same time reduce concerns for family members who are genotype negative. However, the classification of the pathogenicity of variants and understanding variable penetrance remains a challenge. A manuscript entitled, "Exome Sequencing in Children with Pulmonary Arterial Hypertension Demonstrates Differences Compared to Adults." From Na Zhu, Claudia Gonzaga-Jauregui, Carrie Welch, Wendy Chung, and colleagues from Columbia University, ask the question whether there were differences in the genetic mutations responsible for early onset pulmonary arterial hypertension, or PAH, in a pediatric sample compared with adult onset disease. While some mutations, particularly in BMPR2 appear to be similar in the pediatric and adult samples there were significantly more mutations in TBX4 in the children compared with adults. Further, children were more likely to have de novo mutations identified through exam sequencing that were predicted missense variants. Given the additional complications associated with pediatric onset of PAH, understanding the genetic differences in this population is an important step towards identifying novel genes and mechanisms which could guide future therapeutic development. Our next manuscript authored by Iisan Kadhen, Carolyn Macdonald, Mark Lindsay, and colleagues from Harvard Medical School is entitled, "Prospective Cardiovascular Genetics Evaluation in Spontaneous Coronary Artery Dissection," or SCAD. They genotyped individuals with SCAD to find out the genetic contribution to the disease. Of the patients for whom genetic testing was performed, six of them were 8.2%. Identifiable mutations in genes known to be involved in vascular disease, including COL3A1, LMX1B, PKD1, and SMAD3. These individuals were significantly younger at the time of their first SCAD event compared to patients with no identifiable mutation. Given the relatively higher rate of mutations identified in this sample, there may be a rationale to conduct genetic testing in all individuals presenting with SCAD, particularly in younger individuals. Shiu Lun Au Yeung, Maria-Carolina Borges, and Debbie Lawlor, from the University of Hong Kong and the University of Bristol, set out to find out if reduced lung function is causal in coronary artery disease. As reported in their manuscript, entitled "The Association of Genetic Instrumental Variables for Lung Function on Coronary Artery Disease Risk, A 2-Sample Mendelian Randomization Study," they used a Mendelian Randomization approach to assess causal relationships between two measures of lung function. Forced expiratory volume in one second, and forced vital capacity on CAD. Genetic predictors of increased forced expiratory volume were associated with lower risk of CAD. While there was a similar association with forced vital capacity, this was attenuated in sensitivity analyses. Overall, the data suggests that higher forced expiratory volume may independently protect against CAD. However, the mechanisms remain unclear. Finally, the April issue also contains a white paper from Kiran Musunuru, Xiao-zhong Luo, and colleagues entitled, "Functional Assays to Screen and Dissect Genomic Hits, Doubling Down on the National Investment in Genomic Research." This paper lays out strategies to followup on findings from high-throughput genomic analyses, including the use of novel technologies, assays, and model systems that can help to effectively translate big data findings and capitalize on previous investment in genomic discovery. To see the latest issue of Circulation Genomic and Precision Medicine, and to access all the papers we talked about and to browse previous issues, go to "circgenetics.ahajournals.org." Sony Tuteja: Hello, my name is Sony Tuteja, I'm an assistant Professor of Medicine at the University of Pennsylvania in Philadelphia, I'm also an early career member of the American Heart Association Council on Genomic and Precision Medicine. Today I'm joined by Dr. Craig Lee, an associate Professor of Pharmacy at the University of North Carolina School of Pharmacy. Dr. Lee is a first author of an article published in April 2018 issue of Circulation Genomic and Precision Medicine entitled, "Clinical Outcomes and Sustainability of Using CYP2C19 Genotype Guided Anti-Platelet Therapy After Percutaneous Coronary Intervention." Welcome Dr. Lee, and thank you for joining me today. Craig Lee: Thanks for having me. Sony Tuteja: First let me just say congratulations on spearheading such impactful work on the implementation of CYP2C19 pharmacogenetic testing. Craig Lee: Thanks, this has been a very complicated project, but a lot of fun. Sony Tuteja: Great. So I think some of our listeners may have not had time to read your paper yet so I was wondering if you could provide a brief overview of the paper and what the study was about. Craig Lee: Sure. Although it's been widely described that loss of function polymorphisms in the drug metabolizing enzyme, CYP2C19, which is responsible for the bio-activation of the antiplatelet drug clopidogrel, impairs its effectiveness, there remains considerable debate and uncertainties surrounding whether CYP2C19 genetic testing should be used clinically for guiding antiplatelet therapy in percutaneous coronary intervention, or PCI patients. As the evidence base is expanded, an increasing number of institutions are seeking to implement CYP2C19 genetic testing despite limited data on the use and impact of using this genetic testing to guide antiplatelet therapy selection following PCI in real world clinical settings. UNC was an early adopter for CYP2C19 genotype-guided antiplatelet therapy in high-risk PCI patients. Our algorithm recommends that patients carrying one or two loss of function alleles in CYP2C19 be prescribed an alternative antiplatelet therapy such as prasugrel or ticagrelor. Our algorithm was implemented back in the summer of 2012, under our then-director of the Catheterization Laboratory, and now Chief of Cardiology, Dr. Rick Stouffer. We conducted the study to better understand the feasibility, sustainability, and clinical impact of using CYP2C19 genetic testing to optimize antiplatelet therapy selection in PCI patients in real-world clinical practice. Basically what we did was following the implementation of our algorithm in the summer of 2012, we've been retrospectively collecting data from all patients that come through our Cath lab that undergo a PCI. We collect information on their clinical characteristics, whether or not they underwent CYP2C19 genetic testing, what antiplatelet therapy they were prescribed when they were in the hospital at discharge and over the course of followup, and more recently we've been assessing clinical outcomes, both ischemic outcomes and bleeding outcomes. The data presented in our paper described the algorithm's use at our institution over the first two years following its implementation from 2012 to 2014 with one year of followup data. Since we do about 600 PCI procedures per year on our Cath lab, the study population is just under 1200 patients. Our main findings were that CYP2C19 genotypes were frequently ordered, efficiently returned, and routinely used to guide antiplatelet therapy selection after PCI over this two year period. However, we also observed that the frequency of genotype testing and frequency of using alternative therapy such as prasugrel or ticagrelor in the patients that carried CYP2C19 loss of function alleles fluctuated over time. We also observed that use of clopidogrel in patients that were tested, but carried either one or two copies of a CYP2C19 loss of function allele was associated with a significantly higher risk of experiencing a major ischemic cardiovascular event compared to use of alternative therapy. These risks were particularly evident in the highest risk patients, and largely driven by patients who carry only one copy of the loss of function allele, the so-called intermediate metabolizers. Our primary takeaway from this analysis is that implementing a genotype-guided antiplatelet therapy algorithm is feasible, sustainable, and associated with better clinical outcomes in a real-world clinical settling, but challenging to maintain at a consistently high level over time. Sony Tuteja: Great. I know it's always challenging to implement new work flow and new testing into the clinical setting. Can you describe how the algorithm was incorporated in the cardiologist workflow to minimize disruption? Craig Lee: Absolutely. This algorithm was spearheaded by our interventional cardiologists with the support of our clinical pharmacy specialists and pathology laboratory. They key element to our success is that we have the capacity to do the genotype testing in our molecular pathology lab on site. Dr. Karen Weck is the director of that laboratory and is a coauthor on our paper. Since the prescribing decision for antiplatelet occurs in a highly specialized clinical setting, we have all the pieces in place to do this in-house at UNC, which seems to make things very efficient. There really wasn't very much disruption in the workflow given that the testing is done on-site and the test seems to be treated like another laboratory test that's done, which is really the ultimate goal of pharmacogenomics. We don't currently actually have clinical decision support built into our electronic health record, so the reason we could actually get this off the ground was because of the substantial collaboration between our physicians, pharmacists, and pathology lab. But one of the things we learned through this experience, which is described in the paper, is that there are fluctuations in the use of the genetic testing to guide prescribing over time that we believe could be remedied by developing more automated clinical decision support, to help make things a little bit more efficient for the clinicians. But at the start of it, it was really just a will to do it, which was really exciting to observe. Sony Tuteja: Absolutely. That's exciting that...
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Ep14 0318 Deirdre Tobias Kiran Musunuru
03/21/2018
Ep14 0318 Deirdre Tobias Kiran Musunuru
Jane Ferguson: Hello, welcome to Getting Personal: Omics of the Heart, episode 14 from March, 2018. I'm Jane Ferguson, and this podcast is brought to you by Circulation Genomic and Precision Medicine, and the AHA Council on Genomic and Precision Medicine. This month I talk to Deirdre Tobias about her research on branch gene amino acids and incident cardiovascular disease in women, and I got the chance to talk to Kiran Musunuru, the new editor in chief of Circulation Genomic and Precision Medicine, about his take of the publishing process and new directions the journal has been taking. I'm joined today by Dr. Deirdre Tobias who is an instructor in medicine at the Brigham and Women's Hospital in Boston. Dr. Tobias is the first author of a paper entitled Circulating Branch Chain Amino Acids and CBD Risk in Women that is published this month in Circulation Genomic and Precision Medicine. Deirdre is also presenting this work at the lifestyle sessions in New Orleans this month, where she is receiving the Scott Grundy fellowship award for excellence in metabolism research. Deirdre, thank you so much for joining us, and congratulations on your manuscript and your upcoming award. Deirdre Tobias: You're very welcome, and thank you. Jane Ferguson: Could you tell us a little bit more about your background, and what led you to this specific research focus? Deirdre Tobias: Sure. I am an epidemiologist, and I investigate risk factors for type two diabetes and other obesity related chronic diseases. Most recently I've been interested in looking at the mechanisms linking obesity with many of it's associated risk factors through metabolomics. Metabolomics is a field that's relatively new, and it identifies, or seeks to identify small circulating molecules throughout the blood, or urine, or other specimen samples, and then relate those levels to risk of disease. Type two diabetes has had large successes with finding markers that are novel, and these are often consistently identified across studies, which is very reassuring, and not always the case for many risk factors of chronic diseases. Branch chain amino acids in particular have been consistently associated with diabetes risk across study populations, and tissue type samples, and methodologies for measuring metabolites. This is reassuring that these metabolite markers might really be picking up on an important signal in diabetes risk. Jane Ferguson: For any of our listeners who haven't had a chance to read your paper yet, I wondered. Can you give us sort of a brief overview of what you did, and a summary of your findings? Deirdre Tobias: Sure. Metabolomic studies, as I mentioned, have been successful in the field of type two diabetes, but less so for cardiovascular disease endpoints. With branch chain amino acids being a risk factor for type two diabetes we then thought to establish, or to examine whether they were also associated with incidents of cardiovascular disease risk. In our study we had branch chain amino acids measured on over 27,000 women from their baseline blood samples, and these women were participants in the women's health study in the US. This cohort already has over 18 years of mean follow up with a number of CBD and diabetes cases already accrued, so we used these baseline measures of branch chain amino acids measured from plasma samples to then relate these to incident CBD risk. We had over 22,000 MI, stroke, and revascularization events in these women. What we then did was analyze the relationship between branch chain amino acids levels with incident in CBD. Jane Ferguson: That's a really amazing data set. I mean, that's a huge number of subject, so that's really, really powerful. Deirdre Tobias: Yeah. For metabolomics most of the prior evidence has come from smaller case control studies, so this is really an unprecedented number of women participants in general that have had metabolomics with this much follow up. It was definitely a rich resource to be able to address this question and with a substantial amount of statistical power. Jane Ferguson: Right. I know you ran a large number of different models, and you looked at a lot of different covariances, so what were the primary findings? Deirdre Tobias: The main results indicated that even adjusting for the traditional CBD risk factors, including behavioral, and lifestyle, smoking status, family history, race and ethnicity, even body mass index which is a strong predictor of branch chain amino acids levels, we observed a striking association indicating that higher levels of branch chain amino acids were associated with a greater risk of MI stroke or revascularization during follow up. Jane Ferguson: Yeah, and I thought it was really interesting that you saw this in the whole sample, and then you also saw this sort of same association, in sort of like attenuated strengths in individuals without type two diabetes. Then, when I was looking I suppose you had adjusted for a number of different biomarkers, and then when you adjusted for the biomarkers as pre diabetic risks, so hemoglobin A1C or insulin resistance, the association went away. I wonder, even in your subjects who didn't have diabetes yet, were the association between the branch chain amino acids and CBD events was significant, but do you think that this was primarily driven by the pre-diabetes level, where these women are probably on track to developing diabetes, and just haven't hit that threshold for diagnosis yet? Deirdre Tobias: I suspect that could be the case. We do know that diabetes is a risk factor for CBD, and as I mentioned with the strong, consistent evidence indicating branch chain amino acids as a risk factor for type two diabetes we wanted to disentangle any association that we would see with branch chain and CBD to be able to show if that was independent of intermediate type two diabetes or not. When we did stratify by diabetes, clearly the majority of that risk seemed to be driven through type two diabetes. The women who had diabetes prior to their CBD event, clearly we saw the relationship much stronger for them. The residual is still there among those without type two diabetes, could be some clinical diabetes or pre-diabetes. It's hard to really say for sure, but we do have additional models where we adjusted for biomarkers that were measured in the same baseline blood samples as the branch chain amino acids. When we adjust for these markers that are more related to insulin resistance and glycemic control we see that the relationship between branch chain amino acids and CBD becomes attenuated. We can interpret this as being that the branch chain amino acids may be mediating the relationship with CBD through these markers of insulin resistance and glucose metabolism. If we similarly adjust for cholesterol, LDL or HDL, the relationship between branch chain amino acids and CBD didn't budge. That would indicate that perhaps branch chain amino acids and CBD risk is being mediated largely through this diabetic pathway rather than other more traditional CB pathways such dyslipidemia or inflammation. Jane Ferguson: Right, so it's an entirely independent pathway, I guess, that probably adds to the risk rather than being complimentary with traditional risk factors like LDL cholesterol. Deirdre Tobias: Yeah. The common soil hypothesis which has been around for many years suggests that there's a common set of risk factors, or cardio metabolic dysfunction, that leads to both diabetes and CBD. This suggests that branch chain amino acids and impaired branch chain amino acid metabolism could be one pattern or marker of this common predisposition to both type two diabetes and CBD. Jane Ferguson: Right. It's really interesting stuff, and I think this field, it's so challenging following up these markers when you're trying to find out, is a biomarker, when it's associated with a disease is it actually causal, is it a bystander? Are branch chain amino acids increased by insulin resistance, but don't actually themselves contribute to disease, or are they also individually contributing to disease. I know there's been some papers trying to address this through Mandelian randomization approach. It's indicated that the genetic predictors of branch chain amino acids aren't necessarily causal for diabetes, but that's sort of a consequence for insulin resistance. I wonder how that fits into your findings with, then, the additional associations with cardiovascular disease where we think of this pathway where we get this increased diabetic risk, and then perhaps as a consequence of the increased diabetic risk you have increased branch chain amino acids. Are these, then, themselves increasing oxidative stress or some other mechanism that's then leading to pro-atherogenic, pro-cardiovascular risk, or is it still just, well, it's a bystander, and they're there? They're a biomarker, but they're maybe not great targets for therapeutic interventions. I don't know what you think of this. Deirdre Tobias: Yeah. No, that's a completely fair interpretation of the data, and the literature overall. I think with observational epi, disentangling not only the causality but the temporality, so which biomarker is really, if it is causal, occurring first on this pathophysiology from say obesity or lifestyle to ultimately CBD? I think that it's difficult to really determine from one single study what that directionality is. Looking to the other literature we do see that there is the Mandelian Randomization. I think there have been more than one now, but one did indicate that genetic predictors of circulating branch chain amino acid levels were associated with type two diabetes risk, which supports there being a causal relationship between branch chain and diabetes. I haven't seen that also done for CBD, but that could be a next step. I think another next step for branch chain amino acids and metabolomics in general is to establish whether or not these are modifiable. If they're just along for the ride, or they're even just a strong biomarker, what does that mean clinically? I think it's still a very open question for many of these metabolomic studies, and even when we have these metabolites that really rise to the top as strong biomarkers, what do they mean? It could even be that we know they're causal, but that they're not entirely modifiable. Maybe they are just very strongly genetically determined. I think the next step might be to then identify what modifies levels of branch chain amino acids, whether it's lifestyle, or pharmacologic therapies, I think is still unknown, but if we can identify what can modify branch chain amino acids and then answer that next step of, "Well, does the modifying branch chain amino acids then confer a lower risk in disease," that would be an ultimate question to answer. I think these large scale epidemiological studies are very important as that first step in telling us whether we're even going in the right direction, and then subsequent studies will only strengthen these results, especially when it comes to the causality point. Jane Ferguson: Right. Right. I know in your current study, you're limited somewhat by the data, but I wonder. Were you able to look at whether dietary factors, or physical activity and exercise levels were even associated with branch chain amino acids. Obviously protein intake, or carbohydrate, sort of a prudent versus a western diet, were you able to look at that, or is that something that you may be able to look at in the future? Deirdre Tobias: Right. In the future we are hoping to disentangle what the determinants are for branch chain amino acids in this cohort, so looking at the role of physical activity, or dietary patterns, or specific foods and nutrients might play. But for this analysis here, we adjusted for all of those factors, and when we do compare, the first model where we only adjust for age, with the second model where we include adjusting for all the more traditional CBD factors as well as the behavioral, lifestyle, dietary patterns or et cetera, we see that there is quite an attenuation. This does suggest that there is some room for modifiability, because these other potential confounders are impacting the association that we see. If there was no effect in our results when we adjusted for all of these behavioral factors then they might not be that strong determinant of branch chain amino acids, but we do see some attenuation. It is possible that many of these factors, or maybe collectively they impact branch chain amino acid levels. But that's another next step, and I think that's something that we can address very well with the data that we have in our current data set, the women's health study. Jane Ferguson: Right. I mean, given the large number of subjects, even with messy dietary or exercise data, I think you'll have a lot of power to at least get you in the right direction to then define interventional trials that could specifically address that issue. Deirdre Tobias: Right. Another thing to keep in mind about branch chain amino acids is that they're essential amino acids, meaning that they're derived from diet and not synthesized within our bodies, but surprisingly the correlation between dietary intake and circulating levels is quite low. This, to me, tells the message that metabolism of branch chain amino acids, more so than their dietary intake, is what's driving these elevated levels, and what leads to this impaired ability to break down branch chain amino acids leaving these higher circulating levels, I think that's the risk factor that might predispose to these other cardio metabolic conditions down the road. Really I think the next steps would be to determine why certain people have more impaired metabolism of branch chain than others. Body mass index is highly correlated with branch chain amino acid levels, that's, you know, an obvious next direction would then be to look at lifestyle factors and anthropometrics to see where those lead us. Jane Ferguson: Right. Right, and I wonder, is there some genetic [inaudible 00:16:05] where you could maybe find the people who don't fit the profile, like say somebody who has really dysregulated glucose and insulin homeostasis but actually has very low...
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Ep 13 Svati Shah Kiran Musunuru Andrew Landstrom Katelyn Gerbin Brock Roberts
02/21/2018
Ep 13 Svati Shah Kiran Musunuru Andrew Landstrom Katelyn Gerbin Brock Roberts
Transcript of the February Podcast, “Getting Personal: Omics of the Heart”, Episode 13 Hosted by Jane Ferguson Assistant Professor at Vanderbilt University Medical Center & Associate Editor of the Circulation: Precision and Genomic Medicine journal of the American Heart Association Jane Ferguson: Hello. This is episode 13 of Getting Personal: Omics of the Heart. It's February 2018. I'm Jane Ferguson, an assistant professor at Vanderbilt University Medical Center, an associate editor at Circulation: Precision and Genomic Medicine, and an occasional podcast host. This month, I talked to Kiran Musunuru and Svati Shah about how they spearheaded name changes for Circulation Cardiovascular Genetics and for the AHA Council on Functional Genomics and Translational Biology, and Andrew Landstrom talked to Kaytlyn Gerbin and Brock Roberts from the Allen Institute about some extremely cool work they are doing with CRISPR and IPS cells to create fluorescently tagged maps of live cells, which allowed them to image and better understand the structure and function of individual cells. I'm delighted to have two guests on the podcast today, Dr. Svati Shah is the current chair of the AHA Council on Genomic and Precision Medicine formerly called the Council on Functional Genomics and Translational Biology. She is an associate professor of medicine at Duke University Medical Center. Dr. Kiran Musunuru is editor in chief of Circulation Genomic and Precision Medicine formerly named Circulation Cardiovascular Genetics, and he's an associate professor of medicine at the University of Pennsylvania Perleman School of Medicine. Dr. Shah and Dr. Musunuru were kind enough to take time out of their busy schedules to join me for a joint discussion on the recent enhancement of name changes for our council and our journal. With tight schedules and last-minute flight cancellations we didn't have ideal settings for recording, so apologies in advance for a little more background than usual. My instruction highlighted a number of name changes and astute listeners will have noticed that the new names for both the journal and the council are very nicely aligned, so I know this was not a coincidence, and I'd love to hear from both of you, what prompted the decision to change the respective names of the council and the journal, and how did you come together to streamline these name changes? Svati Shah: Well, maybe I'll take a first start, you know, we, we're really lucky in our council, we have a very, you know, certainly one of the smaller councils [inaudible 00:02:26] we have a very collegial spirit that wants to get things done. So, these conversations actually started probably three years ago, umm, when Jen Howell was chair of the FGTB council. And we realized that not only was our constituency broadening in expertise and breadth and depth, but also, umm, the desire to kind of move beyond the really wonderful work the council is doing around technology platform, genomics, genetics and you know important advances in many of our council members have made in the translational biology field and really thinking about the fact that we have this amazing expertise that can come together across a wealth of disciplines to really translate what's being done in the omic space, and apply it in this new world of precision medicine. And so, umm, that is what stirred really thinking about a name change so that not only would it reflect this expanding constituency in expertise and hopefully draw even more people, across the, you know, wide expertise. But also to harmonize more with people who are in other councils, including clinical cardiology, and people that, really, in the end we are actually quite allied with scientifically, but perhaps those councils didn't recognize really what our council was about because of our previous name. So in that context, you know, it's been wonderful. Kiran has been a wonderful partner in all of this, he's been a real leader in the council and over the past two years we have had many conversations across council leadership and the entire council, and thinking about what this name change would be. And actually, it was almost a consensus amongst council leadership to choose Genomic and Precision Medicine as the name, really to reflect our core beliefs and our core science in genetics and genomics, but also to reflect the expanding expertise of all the different omics platforms, our expertise in clinical genetics with more genetic counselors joining our council, and our expanding expertise in computational biology. And this really allied nicely also with the American Heart Association building a very important institute, the Precision Medicine Cardiovascular Institute. So, I'll let Kiran go from here but again, Kiran has really been a great partner in this and he can kind of expand on that story and how that led to the journal name change. Kiran Musunuru: Sure, so, with respect to the journal, I think these changes have been growing for a while. I think a lot of the same considerations came into play, the feeling that the journal with the name Circulation Cardiovascular Genetics was perhaps too narrowly defined given how the field, how the science was evolving. And the other consideration is that the Functional Genomics and Translational Biology Council has had a journal, a companion journal if you will, all of this time with a fairly distinct name, Circulation Cardiovascular Genetics, and so it wasn't necessarily obvious to those who are not on the inside so to speak that there was supposed to be a very tight connection between council and journal, that the journal really was the journal of the council and so in the process about deliberating about a council name change, it became natural to think that, "Wow, wouldn't it be nice if the journal could execute a similar name change", and separately, even though this predates my tenure as editor of the journal there had been conversations going on separately or independently that perhaps the journal would benefit from signaling that it was not just about cardiovascular genetics in the very narrow sense, but was really about a much larger area of science. And so there had already been contemplation for quite a while about a name change and so when I assumed the editorship I didn't really have to do much to convince anyone that this would be a useful thing. The scientific publishing committee of the American Heart Association and all the various people involved publishing the journal were already sort of primed for a name change and then it just ended up being a nice convergence of opportunities, Svati with her work in the council and really showing the leadership to lead the transition from Functional Genomics and Transitional Biology to Genomic and Precision Medicine. That really laid the groundwork, and because it was such a deliberative process, such an inclusive process, involving dozens of people on the leadership committee of the council as well as general membership of the council, it was really a no-brainer. The hard part had already been done, the thinking had already been done and I was straightforward to say that we should change the name of the journal to match, Circulation Genomic and Precision Medicine. Jane Ferguson: Have there been any logistical difficulties in getting this name change through, or has it all happened very organically? Svati Shah: The American Heart Association has been a real partner in the name change, sometimes things require many layers of approval and in fact, it has been a relatively seamless process. We came up with a consensus around the name change and later applied formally for that change in the council name, and that was pretty quickly approved by the Scientific Advisory Committee, within a few months really. Our name change became official and we are in the exciting time now of advertising and kind of marketing the name change and appeal to a broader constituency and really reach out to group that perhaps wouldn't have realized that this council is a great home for them again thinking of genetic counselors and computational biologists. So, it really, you know, has been a surprisingly seamless and fun process. Kiran Musunuru: As I mentioned before it was already kind of in the air that a change was imminent and so when I posed the name change to the Circulation Genomic and Precision Medicine it ended up being a very smooth transition. It was timed so that the volume change, that is changing from the volume associated with the calendar year 2017 to the volume associated with the calendar year 2018, January first ended up being a very logical transition time and so that's when the change occurred. And happily, the council name change ended up occurring almost in lockstep; whereas, you know within a few weeks of the journal announcing its name change the council was able to announce its name change as well. I think that has had a reinforcing effect across the American Heart Association and its membership. It really signals that the council and the journal are tightly tied together, are partners in moving in lockstep. Jane Ferguson: Svati, this question's probably more for you, so what does the name change mean specifically for existing FGTB council members, and what if anything will change, and then what might it mean for potential new members who are trying to decide what council to join? Svati Shah: That's a great question, Jane, you know I am a pragmatic person and I think our council also reflects that pragmatism. We get a lot of things done and we, I think, spiritually all agree that we shouldn't just change the name just for the sake of changing the name. And so we really, actually the name change followed [inaudible 00:10:18] were involved in, these discussions are a year and a half of really thinking about what direction we wanted the council to go and then what the sort of short and long term goals of our council are and then how does the name change effect the long term goals. So, we have a lot of great initiatives in the short and long term, which again will capitalize on our broadening expertise in these different clinical genetics and precision medicine and really, translating genomic and omic findings into, into important patient care. And so, we have several things coming down the pipe that are sort of proof of principle examples of what the name change reflects. So, one example is that we are now working on developing a certificate in medical genomics with the idea that we really need more genetics education. Our council has been very much embedded in genetics and genomics education, Kiran being a key example of that. And now we are expanding that into thinking about how genomics is applied to clinical medicine but making it at the level that is digestible and understandable and is easily applied by a general cardiologist and even primary care doctors will be able to use that resource. And the idea is this will be your self-sustaining certificate that's given through the American Heart Association, so we have a group that's been working on that certificate and hopefully that will be coming out soon. Another key component of what we're doing is trying to reach out more and partnering with other associations including the American College of Medical Genetics and the National Society of Genetic Counselors, again really thinking about how we transition our important scientific discovery work into translation implementation science around patient care. To give you some examples of what that means in terms of what the name change is reflecting, I think with the right use, for the second part of your question, which I think is a really important part of your question is, we want to attract more people in the computational biology field, in the precision medicine space, in the clinical genetic space and again reaching out to genetic counselors through some of these societies, because we, just the wave of precision medicine is here, is going to expand even more and the expertise within our council that was already there but that now we can expand. I think it will be leveraged to really make important contributions to making sure that those efforts in precision medicine are done well, or done responsibly and are done with the patient in mind because in the end the American Heart Association is at the forefront of patient advocacy group. This is a really exciting time, I think that, you know, however you want to define precision medicine the bottom line is precision medicine is here and we can't have, it's not going to be a single faction of individuals or a single expertise that is really, is going to be able to leverage fundamental scientific discoveries whether its genetics, genomics, metabolomics, proteomics, and really translate them responsibly into patient care, so it's going to involve an interdisciplinary and multi-disciplinary effort. I feel really proud that I'm part of the AHA and that we sort of have this perfect storm between Kiran's leadership in the journal, our council changing, you know, its goals and its name aligning with the Institute for Precision Cardiovascular Medicine within the AHA. And I think that, you know, it's not all rainbows and sunshine. We have a lot of work that is cut out for us in the next few years to figure out ways that we can tangibly and concretely, and again responsibly, work together across each of these three components of this perfect storm to make sure that it’s not just a glitzy name change and that there is actually substance and behind all of it, so, you know, it will be, there will be challenges, there will be obstacles, but I think that the amazing people within each of those three components, I feel very confident that we are going to be able to do it well. Jane Ferguson: Yeah, I agree, as a member of the council, if anybody can do it I think this group of people can do it, so it's very exciting to see, so thank you both for joining, and congratulations again on the new names. It's really exciting to see these, you know, new directions for the council and the journal working together. And I really look forward to seeing all the great initiative that will be coming out in the next few years. Svati Shah: Thank you, Jane. Kiran Musunuru: Thank you, Jane. Andrew Landstrom: My name is Andrew Landstrom, and I'm an assistant professor in the department of pediatrics section of cardiology at Baylor College of Medicine. I'm a member of the early career committee of the American Heart Association Council on Genomic and Precision Medicine, previously the Council on Functional Genomics and Translational Biology, and I'm joined today by Brock Roberts and Kaytlyn Gerbin, who are scientists on the stem cell and gene editing team at the Allen Institute. Here to discuss a little bit more about CRISPR editing and what they have done for live cell imaging using fluorescent proteins. So, Brock and Kaytlyn, I'm hoping you can discuss a little bit about what the Allen Institute is and your overall research mission and goals. Kaytlyn Gerbin: Yeah, great, so this is Kaytlyn and thanks Andrew for having us on, and we're really excited to share a little bit of the information about what the institute is doing, because we're building a bunch of tools that we think would be really useful for the research community. So, we're excited to get the word out there. And so, the Allen Institute is a non-profit research institute, and we're based in Seattle, Washington, and, essentially what we're trying to do is better understand the cell. We want to understand the various states the cell can take based on structural organization of how different organelles work together. And so, we're doing this, essentially by live cell imaging and...
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12 Journal Name Change Theriault Pare GRS
01/24/2018
12 Journal Name Change Theriault Pare GRS
Transcript for January 2018 Podcast Circulation: Genomic and Precision Medicine Jane Ferguson: Hi, everyone. Happy New Year. You are listening to "Getting Personable: Omics of the Heart". I'm Jane Ferguson and this is episode twelve from January 2018. This month I have some exciting announcements to make. The journal formerly known as "Circulation: Cardiovascular Genetics" has a new name. As of this month, the podcast is brought to you by "Circulation: Genomic and Precision Medicine". We're still publishing papers focused on cardiovascular genetics but as genomics and other omics have expanded our scope has grown to so much more than just genetics. The new name, "Genomic and Precision Medicine" signifies the journals focus not only on genetics, but also genomics and all the other omic technologies and the feel of precision medicine. Along with the new name we have a new editing team. Dr. Kiran Musunuru, an associate professor of cardiovascular medicine and genetics at the Perelman School of Medicine at the University of Pennsylvania has officially taken over as editor-in-chief. He has already been implementing new initiatives to allow the journal to serve authors and readers even better. Along with create original research articles you can find accompanying editorials, videos and interviews with authors, including the interview we're featuring in this month's podcast. Finally, while "Circulation: Cardiovascular Genetics" was published every two months, "Circulation: Genomic and Precision Medicine" will now be published monthly. So, you can look forward to a new issue every month and even less time waiting for the newest research to be published. Check out the latest issue and all of the new material at circgenetics.ahajournals.org and follow us on Twitter at Circ_Gen. Now, along with the name change for the journal, we have another name change in the pipeline. Our AHA Council, Functional Genomics and Translational Biology, is also being renamed to "The Council on Genomic and Precision Medicine". As with the journal name change this better reflects the evolution in our scope and focus. This name change will be formalized in the coming months. So, if you are one of the many people who could never remember what the acronym FGTB stood for or what order all those letters came in, your struggles will soon be over. We have a number of interesting papers published this month, including an article by George Hindy and colleagues on how smoking modifies the relationship between a genetic risk score and coronary heart disease; a mendelian randomization study from Jie Zhao and Mary Schooling on coagulation factors and ischemic heart disease; an exome wide association study of QT interfolds from Nathan Bihlmeyer and colleagues; a study on genetic testing of cardiac ion-channelopathies and still births from Patricia Munroe and colleagues; and a genetic study of cardiac disfunction in Duchenne Muscular Dystrophy from Tetsushi Yamamoto and colleagues. You can also catch up on the genetic cardi-oncology literature with a review by Marijke Linschoten and colleagues on chemotherapy related cardiac disfunction. And read a clinical case on left-ventricular non-compaction by Vi Tang and colleagues. Finally, we also have a scientific statement on the use of induced pluripotent stem cells for cardiovascular disease modeling in precision medicine by Kiran Musunuru and colleagues. Moving on to our feature article, Andrew Landstrom, an early career member of the Genomic and Precision Medicine Council, formerly FGTB, talk to Guillaume Paré and Sébastien Thériault about their article published this month entitled, "Polygenic Contribution in Individuals with Early Onset Coronary Artery Disease". In this paper, Dr. Thériault and colleagues report the use of the genetic risk score which improves on our ability to predict very early onset CAD. Listen on to the authors talk more about the background to this study and what they learned along the way. Andrew: Welcome. My name is Andrew Landstrom, an assistant professor in the Department of Pediatrics, Section of Cardiology at Baylor College of Medicine. I am a member of the early career committee of the American Heart Association Council on Genomic and Precision Medicine, previously the Council Functional Genomics and Translational Biology. I'm joined today by Sebastien Theriault, assistant professor in the Department of Molecular Biology Medical Biochemistry and Pathology at Laval University, and Guillaume Pare, the Canada Research Chair in genetic and molecular epidemiology, assistant professor in integrative health bio-systems and associate professor of medicine at McMaster University. Guillaume: Hi. Good morning. Andrew: Well, I'm wondering if we could just start by introducing ourselves maybe a little bit more thoroughly than I just did and talking a bit about your research paper and what brought you to this as a research question. Guillaume: Absolutely. So, this … [inaudible] and thank you for having us. My name is Guillaume Pare, and as stated, I'm an associate professor at McMaster University, and I would say like my longstanding clinical interest is about individuals and families with very early coronary artery disease and heart disease. And this really was the basis for this project and to try to understand why do some people in family are afflicted by this disease when we cannot find any of the conventional risk factors. And as Sebastien came to join me and this endeavor, and spent two years with us here at McMaster and was instrumental in getting this project off the ground. Sebastien: Yes, exactly. So, I was a physician trained in Quebec City and I went to McMaster University as a research and clinical fellowship. And that's where I did some cardiovascular clinics with Dr. Pare and that's when we noted that some patients with early coronary artery disease didn't have much explanation for their disease. So, that's how this project stem, that we wanted to understand what was going on and we thought that really genetic factors could be involved. Andrew: And speaking of these genetic factors, in fact, you established a genetic risk score as sort of a way of aggregating a large number of genetic variants into a single prognostic risk indicator. How did you come up with the score, and where did these genetic variants that you aggregated come from? Sebastien: So, the results of many of our studies looking at the association between common genetic variants and coronary artery disease have recently been released. For this study, we use the variants identified in the latest CARDIoGRAM for C4D consortium meter analysis, which includes more than 60000 individuals with coronary artery disease and 120000 individuals without coronary artery disease from a total of 48 studies. Most of the participants in these studies were European. And so we decided to use the independent variants that were associated with the disease in that very study and look if we could predict early coronary artery disease in some patients. Guillaume: Andrew, maybe I'll backtrack a little bit. The initial idea about the gene score, first of all came from the observation that a lot of the patients who we're seeing do not have any traditional risk factor. The second observation is that we already knew that genetic risk scores are predictive of coronary artery disease. But the key question is, is it possible that there are people at the extreme of severity of a cardiovascular or genetic risk score that could be at much, much higher risk of having the disease. And this is what the hypotheses really that we wanted to test is whether these genes scores they could identify people that clearly have outlying risk, outlying genetic risk of having the disease. And to explain, the patients that we were seeing a deflation in the clinic will clearly have an outlying risk of disease because they have a First Earth attack or multi vessel disease in their 30s or 40s, and we thought that this cannot be just like bad luck, there had to be some ... and this something is really most likely genetics. We cannot put a finger on it because all the known mutations that we know could cause this, well, we're just not finding them. Andrew: Sure, sure. And there's certainly having a large number of genome association studies, which have implicated a number of common variants and not so common variants in coronary artery disease. So, is this where some of this idea behind the genetic risk or was initially thought of? Guillaume: Absolutely. And I think you know ... and this is where Sebastian really came in and to really like look at this literature, to feel like the variants that went in into the score. Andrew: And certainly to go to your earlier point, it seemed like you were saying early on that coronary artery disease would be a great phenotypic model to explore this question in, mainly because it would seem that at that age, with that severe disease, that it must be something innate to that person, and genetics would certainly play a role. Guillaume: Absolutely. And to me, it's more than simply scientific because we see these patients at our clinic and we've got a lot of ref roles for these patients, and we really feel for them because they're really young people, and I think like when we think about genomic and like preventative medicine having an impact, I cannot see a greater impact than preventing a first heart attack in the 30s or early 40s. So, this is a ... it's a very vulnerable patient population. It's also a patient population that has a lot of questions about why this might be happening to them, and often what we see is that, I think everyone feels that clearly there's a genetic component, and one, a loved one has first attack in his or her 30s, this raises questions for the whole family really, and it clearly sends a shock wave in the family, and everyone, I think rightfully, is quite scared of having the disease and the fact that there is no answer for these people, to me is a huge unmet clinical need. And it's just for the sake of providing people with answers. Andrew: Yeah. Absolutely, I think it's certainly a clinically relevant question that you attempted to answer. And to try to get to this a little bit, and you utilized a large UK-based biobank as your primary study population to establish this risk score. Can you tell me more about this biobank and what sort of data you were able to obtain from it? Sebastien: Sure, I can speak a bit about it. So, the UK biobank is a large prospective cohort of about 500000 individuals between the age of 40 and 69, with an average of 58 years, and they were recruited from 2006 to 2010 in several centers in the United Kingdom, and the general objective is to study the effect on the environment and genetics on health. And what's interesting is that the data is made available to the research community worldwide following registration process. And the data in that includes a very vast amount of information, from questionnaires, specific evaluations, such as height, and weight, and aging data, and the diagnosis from the participants, medical charts, in addition to the genetic data of course. And for this study we used the first release of the genetic data, which included information on about 40 million variants in about 150000 individuals, and selected the individuals who had a diagnosis of early coronary artery disease, so aged 40 or less for men, 45 or less for women, and then it underwent a reversed relation procedure in order to identify patients with obstruction in coronary artery disease, and we used all the other participants as controls. And that's basically leveraging this huge amount of data that we were able to confirm the fact that patients with early coronary artery disease, some of them very high and pathogenic components of their disease. Andrew: That certainly sounds like a really amazing, both biobank and cohort of information that could be utilized. Such a huge sample population with so many clinical variables as well as genetic variables and collected prospectively. What a great resource. Sebastien: Yes indeed. Guillaume: It's a fantastic resource and to me, this type of initiative it's a game changer to accelerate research, because with these data being made available, then it's really up to testing new bold ideas to try to improve our understanding of this disease. So, I think you know we have to say kudos to United Kingdom for financing this this great cohort and making it available to researcher worldwide. Andrew: And you didn't just stop there. You also utilized a local cohort as a foundation cohort for your study. Could you speak a little more about that? Guillaume: So, that's interesting because this cohort really stems from the patients that we've seen at the clinic. And essentially, we felt this was this huge unmet clinical need. To better address causes of disease, and these roles that's barely a disease. And then we said, well, if we were to do this, let's do this formal, and let's do this properly and collect the information and samples and everything, and we had a very enthusiastic response from our cardiologist, and international cardiologist colleagues that really helped us identify these early cases and send them to us and in our study. And so these are local patients. These are people that we care deeply about, and that's really want to make a difference. And again, you know, when Sebastian was with us at McMaster, we were seeing these patients together, and maybe he can add some of the details there if you want. Sebastien: Yeah. Just to specify again, these were patients at the very early coronary artery disease, for age 40 or less for men, and age 45 or less for women. And these were patients without the clear secondary cause of their disease. Most of them were clueless about what were the factors that caused the disease outside a few risk factors such as smoking or hypertension, there wasn't clear explanation as to why they had such early disease, and we could see that it was a struggle to try to understand and then see if there is a risk for their family also. So yeah, it was really interesting to find an explanation for some of them, and we did report the findings to a few of them who seemed to have polygenic contribution to their disease, and it did make a difference. They were quite happy to at least have some kind of an explanation to what was happening to them. Guillaume: And I think that one thing that I think was striking to me when doing this is that when we started to formally collect family history in these individuals, we just realized that and in many, if not most of them, the family history is really striking. And these are folks that clearly has a very severe individual disease, but when we start asking about their brothers, and sisters, and parents, and uncles, you just realized that coronary artery disease was just all over the place and was very aggressive and early. And I think to us, this gave us purpose in this project to say that, 'Yes, we have to do something about this,' but also, I think it also reassures us that our primary hypothesis was right in thinking that there has to be a genetic component that goes beyond just having bad luck, and this genetic component was expressing itself by the family history that we saw. ...
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Dr. Hall Precision Cardiovascular Medicine
12/20/2017
Dr. Hall Precision Cardiovascular Medicine
Jane Ferguson: Hi everyone. Welcome to Getting Personal: Omics of the Heart. This is episode 11 from December 2017. I'm Jane Ferguson, and this podcast comes to you courtesy of Circulation: Cardiovascular Genetics and the AHA Functional Genomics and Translational Biology Council. I'm particularity excited about our interview this month. Doctor Kent Arell from the Mayo Clinic talked to Doctor Jennifer Hall from the University of Minnesota about her role as Chief of the AHA institute for Precision Cardiovascular Medicine. This is a really exciting initiative, which is bringing together researchers, patients and stakeholder to foster the growth and development of cardiovascular genomic and precision medicine. Through their Precision Medicine Platform you can access a virtual big data research hub and find data, tools, and collaborations. The institute also provides funding for projects related to precision cardiovascular medicine. You can find out more and register to access the platform at precision.heart.org. And listen on to hear Jen describe the platform and how this initiative first came about. Dr. Kent A.: Hello. My name is Doctor Kent Arell. I'm the Chair of the American Heart Association's FGTB Council early Career Committee, and a proteomic and network systems biologist in the Department of Cardiovascular Medicine and the Center for Regenerative Medicine at Mayo Clinic in Rochester, Minnesota. As part of a highly collaborative team, my research efforts focus on omic space systems approaches for heart failure prediction, diagnosis and therapy. Specifically regenerative approaches to cardiac repair. This November during American Heart Association Scientific Sessions 2017, FGTB Early Career Committee programming complimented the FGTB Council Precision Medicine Summit with a hands-on bootcamp on network systems biology, followed by a session introducing online computational portals and tools designed to enhance and facilitate basic and clinical cardiovascular research. A highlight of the second Early Career session was an introduction on the use of the Precision Medicine Platform of the American Heart Association's Institute for Precision Cardiovascular Medicine presented by the Institute's lead bioinformaticist, Laura Stevens. With these recent presentations in the many ongoing developments in precision molecular medicine combined with my own research approach and interests, I'm especially delighted today to be speaking with Doctor Jennifer Hall, Chief of the American Heart Association's Institute for Precision cardiovascular Medicine. Doctor Hall received her PhD from U.C. Berkeley and completed post-docs at Stanford and Harvard prior to taking up her first faculty position. Welcome, Doctor Hall. Is there anything I've missed that you would like to add? Dr. Jennifer H.: No, you're doing a great job, Kent. Dr. Kent A.: All right. Doctor Hall, the Institute for Precision Cardiovascular Medicine is one of the newest additions to the American Heart Association. And as far as I'm aware, you've been involved with the Institute since the beginning. Could you first tell us a little bit about the history of how the Institute came to be, and perhaps how you first became involved? Dr. Jennifer H.: I would be very happy to do that. So the Institute actually started in 2013 in the Fall, when the American Heart Association Board of Directors made an initial investment. And the vision for the Institute for Precision Cardiovascular Medicine was Nancy Brown’s, our CEO. And in the early years it was really led by the Chief of Staff, Laura Sol. And our lead strategist, Prad Presoon. And the original grants came out from the institute but was then called the Cardiovascular Genome-Phenome Center, or Study. Dr. Kent A.: Right. I'm familiar with that. Okay. Dr. Jennifer H.: Yes. That was the very early history. And it was rebranded in 2015. So that's the history. I joined about a year and a half ago now. And I'm just thrilled to be part of the team. Dr. Kent A.: Well, there's exciting things on the horizon, definitely. So what is the mandate of the institute? And what are its principal or primary objectives then? Dr. Jennifer H.: So the mandate is to really provide a better understanding in the area of precision cardiovascular medicine to all individuals. And that means participants across the United States and across the globe, patients and those that are healthy individuals as well. And finally to scientists, researchers and clinicians. Dr. Kent A.: Okay. Dr. Jennifer H.: And the five things that we are really focused on in terms of, I would say our principal objectives are really to convene people all over the world, experts, students, trainees. Provide transformative grants and this is at least half of our budget every year, if not up to 80% of our budget. Enable data discoverability and access. And that's through some of the new tools that we are creating. Act as a translation agent. And we can talk more about that if you'd wish. And finally to offer research enabling services or tools to our young trainees as well as our established investigators. Dr. Kent A.: Okay. Perfect. Well, I think I had some questions to cover most of those topics. But the translation agent would be interesting, if you wouldn't mind sort of expanding on that a little bit right now maybe, perhaps before I get to the other questions I had. Dr. Jennifer H.: Yes, absolutely. I think this means a lot of things to a lot of different people. Like one of the ways it can help people are, scientist that have been very focused in academics for a long time has not thought about intellectual property, or ways to really begin to commercialize their ideas and take them forward. So we used to think about bench to bedside. And the institute is focusing on helping these individuals. Helping these grantees really begin to think through how to talk about their ideas and to take them to market. So I'd say that is one way of thinking of the translation agent. The other is to really begin to take participant data and to bring new people into the field. So not only will we think about volunteers as being Heart Walkers anymore or being Go Red for Women volunteers, or one of the many 30 million volunteers we have throughout the United States within the American Heart Association and around the globe. But we want to ask them to contribute to precision medicine, and ask them to be a part of this new exciting movement as well and contribute data, interact, provide answers to surveys, and be educated a little bit more in the area of precision medicine. So those are the two big ways that we think about acting as a translation agent. Dr. Kent A.: Okay. Excellent. With respect to intellectual property, is there an intermediary that you connect researchers to, to facilitate that? Or is it more of an awareness of how to approach your own institutional technology transfer offices, or what have you? Dr. Jennifer H.: Well, you're going right where I would've led the conversation. So we're trying to do both I should say. Dr. Kent A.: Okay. Dr. Jennifer H.: It's just originally getting off the ground and talking to our volunteers at those academic institutions and figuring out the best way to do that. And then talking to some people in the industry as well to figure out how does it work best coming from that side. Dr. Kent A.: Okay. Excellent. Well, I think the next thing that I might transition to is the grants, because points one, three and five that you made about convening people, enabling data access and enabling services and platforms may all sort of relate to the Precision Medicine Platform. And we'll definitely be speaking about that quite a bit. But one thing I wanted to mention is the variety and the number of grants that have been awarded by the institute since it inaugurated grants I believe in 2015, is that correct? Dr. Jennifer H.: Yes. That's exactly right. And- Dr. Kent A.: Yeah. Dr. Jennifer H.: ... I think- Dr. Kent A.: Go ahead. Dr. Jennifer H.: ... we're quite happy. We've given over 72 grants and that totals, I think, just over 15 million. But more importantly the grantees have just done a remarkable job I think. The running total I have, which I know is a little bit out of date is 98 publications, and many of those in high impact journals. And certainly in new areas that AHA has not been in the past, which is artificial intelligence, machine learning, and creating new tools. Dr. Kent A.: So you're also trying to bridge multiple disciplines then I guess as well with some of these grants, correct? Dr. Jennifer H.: Yes. And many of the fields like you're working in as well, thinking about systems biology and proteomics, and bringing the field to beta science along with that as well. So exactly. And in many cases we have private partnerships or strategic partnerships with others like Amazon Web Services. So many of the grants at least, one of the portfolios we have has many grants in it in which the tech credits, or the cloud computing credits if you will, are given to us by our strategic partner Amazon Web Services. So AHA provides the salary support for the PI and others on the grant, as well as any supplies that are needed. And then those tech credits for cloud compute and storage come from Amazon. Dr. Kent A.: Excellent. Okay. And then there are other collaborative efforts with other institutions as well, is that correct? Like the Broad Institute? Dr. Jennifer H.: Yes, exactly. We have a great relationship with the Broad Institute as well. They've been extremely helpful in helping us get our direct to participant recruitment program off the ground. And we are co-investigators with them on an upcoming NIH data platform grant. So we're extremely excited to be working with them and their team. We've worked with several people, and Doctor Anthony Philippakis' team, and with Noel Burtt and David [inaudible 00:11:24] and others there. So we just couldn't be happier with that relationship. Dr. Kent A.: Perfect. Perfect. I know the current round of funding is defined as Uncovering New Patterns, and there are fellowships in grants available for that round of funding. What is the scope of the Uncovering New Patterns effort here? Dr. Jennifer H.: There's a lot of both science and tech built into that. And so, one of the ideas from the institute executive committee ... So one question people might ask is, "How do these ... How do you come up with these grants?" And it's really talking people, finding a need, listening to a lot of people no matter where we're traveling. And then bringing that up to our Institute Executive Committee who makes the final call on these grants. In this case, we were looking for a way to bring science and technology together. So if there was a way to combine datasets that hadn't been combined in the past, which creates some new data harmonization standards, perhaps there's some new methodologies around that. And that's one way to uncover new patterns that we were thinking about. That was the- Dr. Kent A.: Right. Dr. Jennifer H.: ... original example that came to mind. Dr. Kent A.: Okay. Or some new algorithms for- Dr. Jennifer H.: Yeah. Dr. Kent A.: ... interpreting data or what have you. And it sounds like there's goo dialogue back and forth and between the institute, and those who are sort of interested in the topic as well from the researchers' standpoint both clinically and for basic researchers. Dr. Jennifer H.: Yeah. We try. Dr. Kent A.: Yeah. Yep. Oh, I think you do more than try. I think it's a wonderful operation. So I see on the website that there's a new round of funding opportunities are soon to be announced. Can you give us any hint as to what the focus will be for the upcoming round or other things that may be in the pipeline in that regard for the upcoming months? Or do you want to keep it a secret? Dr. Jennifer H.: I can't disclose that. But there will be some things that are a little bit similar to what we've done in the past. Our focus is to really be on the cutting edge, and we are democratizing data on this Precision Medicine Platform making it open in a controlled access way. So you have to fill out a form. But we're really trying to get to those forms and turn over access to people, qualified researchers and scientists as quickly as possible in a very responsible way. And so we're piloting some new objectives around that. We'd love to bring all cardiovascular and brain health data together. And so people can identify and find new discoveries in this area. Dr. Kent A.: Right. Dr. Jennifer H.: And use new technique to do it. So the grants will be focused in that particular area. Dr. Kent A.: Okay. Well that give me an easy segue then into my next question, which is focusing on some of the resources that are currently available to basic and clinical investigators. And after maybe perhaps describing those, where or how can individuals access these particular resources? So I know definitely the Precision Medicine Platform is one that we'll hopefully hear quite a bit about. Dr. Jennifer H.: Yes. That's something that's been underway for about a year now. And we started with two beta testers that you can find the site at precision.heart.org. And we had two beta testers who Gabe [Lucenero 00:15:07] and Laura Stevens, and they were absolutely fantastic and gave us a lot of feedback. We've since hired Laura. Gabe runs his own company up in Canada in the area of bioinformatics. And they've just been fantastic. And since those two, in the last year we've grown to over a 1000 registered users. And once you register on the platform, you can register with your Google account, or however you ... It's a very simple process. ...
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10 AHA Sessions Recap and FGTB YIA
12/19/2017
10 AHA Sessions Recap and FGTB YIA
Jane Ferguson: Hello, I'm Jane Ferguson and you are listening to Getting Personal: Omics of the Heart, the podcast from Circulation: Cardiovascular genetics, and the functional genomics and translational biology council of the AHA. This is episode ten, from November 2017. November is always a big month for AHA and the annual Scientific Sessions were held in Anaheim, California, November 11th through 15th. For those of you who were able to attend, hopefully you came away feeling refreshed and invigorated and with your desired level of Disney merchandise. For those of you who could not attend, or who didn't make it to all of the genomic sessions, this month's episode should catch you up. For the past several years, the FGTB Council has been organizing boot camps at AHA sessions to give people a chance for hands on learning in a flipped classroom model. This year was no exception and in addition to a clinical genomics boot camp focused on patient centric genomics including single gene testing, whole genome sequencing and pharmacogenomics there was also a new boot camp focused on tackling big data network systems analysis for high input data interpretation. These boot camps are always very well attended and popular, so if you're interested in attending one next year, make sure to get in early and sign up during registration. There was also a hands on session in collaboration with the AHA's Precision Medicine Institute to teach people how to use the precision medicine platform to further their research. In addition to this, there was a full day of programming related to precision medicine in the precision medicine summit, which is held on the Tuesday of Sessions. That covered topics ranging from big data, electronic health records, collaborations and the All of Us initiative to rapid fire reports from ongoing consortium, large scale analysis to disease specific approaches in cardiomyopathy. We were planning to have an in depth focus on the Institute for Precision Cardiovascular Medicine in a future podcast episode, so stay tuned for more on that coming soon. There were a number of individuals who were recognized for their contributions to science and we would like to congratulate all of these outstanding individuals. The FGTB medal of honor was awarded to Stuart Cook from the Duke National University of Singapore. The FGTB mentoring award was awarded to Robert Gerszten from Beth Israel Deaconess Medical Center. The FGTB distinguished achievement award went to Sekar Kathiresan from the Broad Institute. And the functional genomics and epidemiology mid-career research award went to Kiran Musunuru from the University of Pennsylvania. Congratulations to all of these. One of the highlights for the FGTB council at sessions is the FGTB young investigator award. This award celebrates early career investigators and recognizes outstanding research in basic science, populations science, genetic epidemiology, clinical genetics and translational biology. Four finalists presented their research on the Sunday afternoon sessions and I had the chance to chat with all four of them before and after their presentations. So listen on for a behind the scenes over view of the finalists research and the announcement of the winner. Mark Benson is a cardiology fellow at Brigham and Women's Hospital and is working on post-doctoral research at the Beth Israel Deaconess Medical Center in Boston with Dr. Robert Gerszten. His talk was entitled "The Genetic Architecture of the Cardiovascular Risk Proteum." Mark Benson: My name's Mark Benson. I'm just finishing up a cardiology fellowship at Brigham and Women's Hospital and am in the middle of post doc in Robert Gerszten’s lab at Beth Israel. Jane Ferguson: Great, and congratulations on being chosen as a finalist for the FGTB Young Investigator Award. We would love to hear a little bit more about what you’re working on and what you're gonna be telling us. Mark Benson: Yeah, absolutely. So the goal of the project was really to integrate proteomic data with genomic data, with the idea that we may be able to use the overlap between those data sets to identify potentially novel biological pathways that underlie very early cardiovascular disease risk. And the thinking behind that was that the lab had just finished up applying DNA-aptamer-based proteomic platform to profile over 110 proteins and the Framingham-Offspring Cohort and from that work, we had identified a very specific signature of 156 proteins in plasma that were each very strongly associated with cardio-metabolic risk. The idea was while those associations were very strong, it was unclear if we were capturing cart or horse or how these associations were fitting together. We wanted to incorporate the genomic data to try to get a better handle on that, to try to connect those pathways to see how these proteins might actually associate with the end phenotype of risk. Jane Ferguson: It's a sort of Mendelian randomization-esque. Mark Benson: Exactly, yeah. So what we were able to find in doing this, we were able to use peripheral blood samples from participants at the Framingham-Offspring study. With a validation in participants of the Swedish Malmo Cancer and Diet Study. Then we did protein profiling using commercial DNA aptamer platform, soma scan. What we were able to find is we were able to detect very strong associations between these circulating cardio metabolic risk-proteins and genetic variance. What was fascinating was we were able to see many things. We were able to start mapping where are these associations, where are these genetic variance in relation to, for example, the gene that's coding the protein that we're measuring. That had some interesting implications because for about half of the protein that had significant associations, we could track those genetic variance back to the gene. It was coding the protein that we were measuring, which was interesting because it's validating the specificity of the proteomic platform that we're using. Jane Ferguson: Right that's nice, because so often you found a gene that's nothing related to what you think it's going to be so it's nice actually the gene you expect. Mark Benson: Yeah, it's very reassuring too when you're looking at rows and rows and rows of data. When the top association of the p value of 10 in the minus 300 is the actual gene you thought would be coding the protein that you're measuring. So that was very reassuring, but we also found dozens and dozens and dozens of associations that were totally unexpected and that may point to completely unexplored biological pathways in cardiovascular disease. So that was obviously very exciting. That actually led us to do two things. One was to make all these data available publicly on dbGaP because as a resource for cardiovascular research there is just way too much data for one group or a handful of groups to digest. The other thing that was fun about the project, is we were able to take one association that was particularly interesting for a number of reasons and experimentally validate it in a tissue-culture model. Jane Ferguson: So how did that work? Mark Benson: So this was an interesting challenge where we all of a sudden got all of these hits back, which was probably to be expected, but to try to figure out which of these dozens and dozens and dozens of new, unexpected hits, what do you do? There was one hit, one association, that was particularly strong and it was between several variance around this gene. That's a phosphatase called PPM1G. It's a transcription factor. These variants, which was interesting, were associated with several different circulating cardio metabolic risk proteins. So our idea was, isn't that interesting? Is it possible that this is mapping to some central regulator? And so it fit that that would be ... that the nearest gene to these variants was a transcription factor and could be a central regulator. What made it more interesting to us was that several variants in the GLGC had recently been described that were highly associated with circulating levels of total cholesterol and triglycerides and they were located around this PPM1G locus as well. The association between those variants and circulating cholesterol didn't have a clear biological connection. So what our work had shown is that those same variants were associated with circulating levels of apolipoprotein E. So wouldn't that be interesting if these variants mapped to PPM1G, the transcription factor, this PBM1G in turn regulated circulating apolipoprotein E and that would provide some insight into the biology behind the GLGC findings. So sure enough we were able to knock down PPM1G using SRNA and hepatocytes and then see that that led to a significant down regulation of the transcription of Apo-B and extra-cellular presumably secreted Apo-B in this model, which is kind of a nice proof of principal that this idea of integrating proteomics and genomics may lead to some novel biological pathways. Jane Ferguson: Yeah, it's really interesting. So what's next. There are probably a lot more associations that you're going to have to go after? Mark Benson: Yeah, I think that what this showed us is that this seems like a powerful tool. Joining these orthogonal data sets to find new pathways and so we're continuing to pursue that with an increasing number of proteins for example, so we're doing genome-wide association studies and x-gamma rays. We've gone from 156 to 1100 to 1300 and are now going beyond that and so as those numbers get higher, you start to see these central nodes come together and more interesting targets and potential pathways. It's also interesting to use these data to find new associations or new tools that you would never think to look for as ways to modulate protein levels. So you can imagine, for example, one thing that we've been exploring for the last few months is can we identify, for example, SNP associated with an interesting circulating protein. That SNP maps to an enzyme or some other druggable mechanism and very preliminary studies, it seems like the answer is probably yes, but there is still a lot of work to be done. Jane Ferguson: Well that's cool. That sounds really interesting. Mark Benson: Yeah, I think the key thing is that all these data will soon be out there and so it's a very rich data set and I think there are many ways that we could use the data. Jane Ferguson: So is that the genomic data and all the proteomic data or it's the summary of the those associations? Mark Benson: All the genomic data, all the proteomic data and the associations as well. You can do the associations yourself if you'd like to. Jane Ferguson: We can find that dbGaP. Awesome, well thank you for talking to us. Mark Benson: Thank you. It's been fantastic. Jane Ferguson: Congratulations again. Mark Benson: Thanks so much. ... Jane Ferguson: Jenny Lin is an instructor at the University of Pennsylvania, working with Dr. Kiran Musunuru. Her presentation was entitled, "RNA binding protein A1CF Modulates Plasma Triglyceride Levels through Transcriptomic Regulation of Stress-Induced BLDL Secretion". Jenny, can you take a moment to introduce yourself? Jenny Lin: Yes, hi. Thank you for this opportunity to participate. I'm Jenny Lin. I'm an instructor of medicine at the University of Pennsylvania, a nephrologist by clinical training, but training in cardiovascular research in Kiran Musunuru's lab. Jane Ferguson: So congratulations for getting selected as a finalist for the Young Investigator Award. We'd love to hear a little bit more about what you've been presenting and what you've been working on. Jenny Lin: Thank you. So basically, what I've been working on over the past year is functional follow-up of this A1CF locus, which is a novel locus for triglycerides. So say Sek Kathiresan's group recently published in Nature Genetics and x and y association study on plasma lipids involving more than 300,000 individuals. One of the key findings from that study is this strong association between a lo-frequency coding variant and elevated plasma triglycerides. So we wanted to delve more deeply into the biology for why we have that genotype/phenotype connection. One of the key things that we wanted to do was ... A1CF is not a stranger to lipo-protein metabolism, but we wanted to see what else it may be doing outside of its canonical role of facilitating the editing of Apo-B messenger RNA. It really took us on a little...
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ASHG Virtual Poster Session
10/30/2017
ASHG Virtual Poster Session
We traveled to the American Society of Human Genetics (ASHG) Scientific Sessions in Orlando Florida. You can hear about the research of four presenters in our Virtual Poster Session: Dr. Gemma Cadby from the University of Western Australia, Dr. Sylwia Figarska from Stanford University, Dr. Marketa Sjogren from Lund University, and Dr. Jessica van Setten from University Medical Center Utrecht.
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Dolmatova Tucker PRRX1 in AFib
09/29/2017
Dolmatova Tucker PRRX1 in AFib
Jane Ferguson: Hi, everyone. Welcome to Episode 08 of Getting Personal: -Omics of the Heart. I'm Jane Ferguson, and this podcast is brought Circulation Cardiovascular Genetics and the AJ Functional Genomics and Translational Biology Council. This is the September 2017 episode, and this month we delve into some of the newest research coming out in the October 2017 issue of CircGenetics. If you go on to the CircGenetics website at circgenetics.ahajournals.org, you can see the table of contents for the latest issue, and see sneak previews of upcoming papers that are published online in advance of the next issue. You can also more in-depth materials for each paper, like editorials and other resources, so it's a really nice way to keep up with the newest cardiovascular genomics research. One particularly interesting paper included in the October 2017 issue is entitled "Diminished PRRX1 Expression Is Associated With Increased Risk of Atrial Fibrillation and Shortening of the Cardiac Action Potential," from Elena Dolmatova, Nathan Tucker, Patrick Ellinor, and colleagues. This is a really nice paper which highlights some beautiful approaches used to go from a GWAS hit to functional understanding. This type of research is challenging but really crucial as we move on from the GWAS discovery era, and I recommend you go online to read the whole paper. I talked to the first authors, Elena and Nathan, to find out more about their work. So I'm here with Doctor Nathan Tucker and Doctor Elena Dolmatova, they're the first authors on a recently published paper. So, welcome and thank you for joining us. Nathan Tucker: Thank you. Jane Ferguson: So, for the benefit of our listeners, could you tell us a little bit about yourselves? Nathan Tucker: Sure, so my name is Nathan Tucker, PhD, researcher, instructor of medicine at Mass General Hospital and the Broad Institute in Boston. Elena Dolmatova: And my name is Elena Dolmatova, if you could probably tell, I'm Russian by origin, currently I'm a internal medicine resident at Rutgers University and I'm in process of applying for a cardio research fellowship. Jane Ferguson: And so the two of you co-led a really interesting publication that came out this month, so congratulations on that. Nathan Tucker: Thank you. Jane Ferguson: So, some of our listeners may not have had the time yet to read your paper, so I was hoping you could give us just a brief summary of what this publication was about. Nathan Tucker: Sure, I'd be happy to start. So the focus of this paper, and a lot of the other work that goes on in our group, is genetics of what's the most common cardiac arrhythmia, which, atrial fibrillation. So, really over the past decade or so, once these large Genome-Wide Association Studies have been performed, in order to identify regions that are associated with disease, and then we followed up on that, to try to determine some of the mechanism that underlies those loci. So this is an example of that type of study. So, I think for the vast majority of these regions, and this is not exclusive to our disease at all, but the loci that are associated reside in what we used to refer to as "junk DNA" or intergenic DNA, that we now know is regulatory DNA. But the important point is, we have no ... for the majority of these loci, we have no idea of the mechanism through which they confer risk. So the point of this study was to examine a single locus for atrial fibrillation, which we'll call AF for the rest of this, and try to determine the mechanisms through which is might confer that risk. So, kind of the start, the study started back in an era where we were using, you know, genotyping chips, and large cohorts of cases and controls to identify variation then impute variants to see what's associated. But we wanted to go into this study with a comprehensive understanding of what's at that locus. So to do that, we performed sequencing and a pretty modest cohort of 500 cases and 500 reference from Framingham Heart Study. And although it didn't really change what we knew about the landscape of that region, we were able to go in with a confident understand of what variants might be associated with disease risk at that locus. So then Elena really spearheaded a lot of the work to identify which of those variants might be important at the locus, so I'll let her take over from here. Elena Dolmatova: So, as Nathan mentioned earlier, many of those intergenic regions contained enhancers of regulatory elements and a lot of data was coming up about the genetic loci in the genome. And we wanted maybe to narrow down that region, down to some of the pieces that could be active, or could be functional. So we used the activity markers that [inaudible 00:05:20] modifications and DNA hypersensitivity, to identify those potentially active elements. And then we tested them on zebra fish [inaudible 00:05:31] to see if they're actually active in the heart. When we realized that they are active in the heart, we were able to then do a little bit more targeted [inaudible 00:05:42] after that, identify the ones that are actually differential between the risk and non-risk allele. So in that some of the SNPs can be actually changing the enhancer function. So this is how we actually identified the SNP that was actually functional. Then next what we wanted to do is to link this enhancer to the gene. And initially we performed a Hi-C analysis, which is a chromatin conformation capture. Which is actually captures a 3D structure of the DNA and shows what regions are interacting with what regions. And we were able to see that this SNP was within the same block as the PRRX promoter. To maybe narrow down and to identify the interaction a little bit better, we performed 3C analysis. That allowed us actually to link the enhancer directly to to PRRX promoter. So, we have the SNP that would change the activity of the enhancer, we have the enhancer linked to the promoter, we wanted to see if the change in the SNP would have any functional consequences on gene expression. And we performed a QTL study. So what it was, is we looked at the genotype of the SNP and related it to the expression of the genes within that region. And among all the genes that we actually tested, only PRRX1 expression was affected, with the risk allele conferring decreased expression of the gene. However, the consequences of gene decreased PRRX expression were yet to be revealed, and that was part of the critical experiment that Nate focused a lot of his efforts on. Nathan Tucker: So, we found the gene that was important, we knew the directionality, but a lot of times, with these type of functional genomics where you, which I hope we can elaborate a little bit more later, is that the results given, like, what gene you identify and the direction, aren't as clear as you would sometimes think for a given disease or trait. So, for example, a lot of the coding variation for AF is identified in ion channel genes. It's thought to be an electrophysiological disease. But here we identified a transcription factor, which is what we actually thought to be a developmental transcription factor. So, you kind of went in from a functional angle and say, "Alright, what are the consequences of this alteration?" So we used two different models, the first was zebra fish, which I had reasonably strong background in. And we knocked the gene down, examined the development of the heart, everything seemed reasonably normal, and then we actually examined the electrophysiology of that heart by optical mapping, and we looked at the action potential duration. Which is basically the cellular phenotype for ... that governs depolarization, re-polarization and thus contraction of any given myosin. And found that that action potential duration in the zebra fish was shorter. We wanted to follow that up and confirm it in a different model, we actually created a CRISPR/Cas9 media knockout of the gene, and embryonic stem cells, and differentiated those into cardiomyocytes, and then saw that similar decrease in action potential duration. So, kind of altogether, I mean, a paper that spans a lot of different techniques, but what we did, we took associates in locus for a human disease, we found a variant at that locus that seems to drive differential expression of a nearby gene, and then modeled that gene effect in order to give a physiological phenotype that matches with the disease of interest. Jane Ferguson: Something that struck me, I think you sort of touched on this a little bit earlier, is, you know, the SNP that you end up showing to be causal, are S577676. It's not necessarily the one that you would have picked sort of a priori, by going through the GWAS strength of association, and you know, I know we sort of all know that we shouldn't place too much weight on the specific P value of an association when we're doing GWAS, but I think a lot of the time, that sort of ends up being a screening mechanism, and people look at sort of the strongest SNP and think that's probably going to be the most biologically relevant. But do you think that we're sort of, you know, by relying on this relative strength association the GWAS to pick targets, we're really missing a lot of the potential biology that's underlying these diseases? Nathan Tucker: The way you look at a normal GWAS locus is, we've always traditionally marked them with what we call a sentinel SNP which is a SNP that's most associated, and then other times, act as though that one might be mediating the function? Whereas in reality, you'll see a block of roughly equivalently associated SNPS that rely or lie within the same linkage to [inaudible 00:10:42] block. And, at least for our cases, when we move forward we really wanted to treat all of those SNPS to be equivalent. And in this one, the SNP that turned out to be functionally active was actually below, a little below that, what we would call that sentinel SNP. So I think there are a couple different explanations for that. One is, there could be more than one functional variant at a locus, and the LD structure kind of heightens that. The other could be that the sample you're using in order to identify the SNPs of interest or the SNPs that are functionally associated may be biasing you a little bit, particularly with a smaller cohort like this. But I will say, for our SNP, when you look at it in the larger GWAS studies, it's again roughly equivalently associated, is what we'd call a top SNP. So, to answer your question briefly, we always look at all of them. We have to be inclusive when we're trying to find functional variants. Jane Ferguson: Yeah, no, absolutely agree. And that's one thing I absolutely loved about your paper, was how you, you know, pulled together all these different data types and used as many different resources as you had access to to really tackle this question. So I wonder, out of all of the different things you did, what was the most challenging aspect of this study? Elena Dolmatova: Well, that was something that nobody's really done before. It was something that there were few studies out by when, the time we started, that would tie some of the GWAS hits with the mechanism of the disease development in [inaudible 00:12:16] in other conditions, but there was really no paved road to take to get an answer to our question. Nathan Tucker: For me, personally, I mean, I really started this project, which, you know, this project took a considerable amount of time, and I started as a cell biologist, and modeling gene function in zebra fish, and by the end, we ended up using so many different techniques, and integrating so many new types of data into this study, that I don't even know what I would define myself as anymore. So I think it's a, it's challenging to learn how to use all of these new data, and to generate these new data both. That's the kind of, I don't know, that's why we got into this business. That's why people want to do research. So that's, it's challenging, but it's rewarding too. Jane Ferguson: Absolutely. And so, to look at the converse aspect, then, was there anything that was easier than you expected? You know, did you have a eureka moment where you sort of said, "Yes, now everything is falling into place."? Nathan Tucker: So, I think, yeah. I've been part of studies where I've really felt that that's happened. And given all of the kind of independent moving parts that were in this study, it was, it's really hard to think of one thing that clicked. You know, every sub-component had its own individual moment where it may have clicked, but really, until they all started, all the pieces of data started to come together, you never really felt that eureka moment. And, you know, I think that's part of what science is in normal ... I mean, this paper was a lot of sweat. And not only mine and Elena's, you have all of our collaborators as well. But I will say, you know, at least using the genetics as a basis, and the GWAS data as a basis, we knew that something was there, going in. We knew that we weren't on some wild goose chase, but really we're filling in a gap knowing that we have a strong basis to build on. Jane Ferguson: Yeah. It's good to hear from you, sort of that, you know, you had to do all of those experiments, they were all necessary, because I think, a lot of the time, when people are trying to follow up GWAS findings, they're really, I don't know, they sort of have a preconceived idea maybe of what path they want to go down, and I think that's not the answer. I think we have a lot of GWAS hits now, and I think the sort of approach that you did to do all of these different experiments and to just do the hard work that's required to figure this out, I think is really necessary and very laudable. Nathan Tucker: Thank you. Jane Ferguson: So, was there anything that surprised you along the way? Elena Dolmatova: Well, Nathan touched a little bit on that. It was nice to see all the electrophysiological phenotype, that was quite amazing. And the fact that the directionality of the effect was ... fit with what we expected to be, with the risk allele, and how we were able to demonstrate it both in zebra fish and human cells, and they were, again, matching. Seeing how those results could tie to the genetic data and what we know about atrial fibrillation susceptibility, was great and rewarding. I wouldn't call it surprising. More like rewarding. Honestly, we were concerned that we wouldn't be able to observe any physiological phenotype. Because, I mean, we didn't even have a good reason why PRRX would be involved in atrial fibrillation, that was a transcription factor, not an ion channel, like everybody thinks about, everything is an ion channel, by the way, not the same. So it was great that we were actually tie the transcription factor to the disease when we not even quite sure that it would happen. Jane Ferguson: Yeah. Yeah, and I suppose, you mention the ion channels, and of course there has been several other loci that have been identified for AF, and from your work, how important do you think PRRX1 is, compared to these other loci, and, you know, do you think that this sort of study has to be done for every single one of these loci to really understand what's causing the disease in different people? Nathan Tucker: First of all, I think the answer to that question depends a little bit on what the person asking it would deem to be important. So, if we're looking at GWAS signals for effect size, generally the effects of each given locus are pretty modest, and PRRX1 locus isn't even at the top for AF. So if you were looking for,...
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Extra Feature: Calum MacRae Full Interview
09/27/2017
Extra Feature: Calum MacRae Full Interview
Speaker 1: Hi everyone. As a quick introduction, this is the full length recording of Anwar Chahal's interview with Calum MacRae from August 2017. A portion of this interview was included in episode seven of the Circulation Cardiovascular Genetics podcast "Getting Personal: Omics of the Heart". As we couldn't fit everything into that regular podcast episode, we've released the unedited version as a special, feature-length podcast. Enjoy. Dr Anwar Chahal: My name is Dr. Anwar Chahal. I'm a Cardiology Fellow in Training from London, U.K., and I'm doing my research fellowship here at the Mayo Clinic, and I'm very honored and delighted to have our guest, Dr. Calum MacRae. I searched for Dr. Calum MacRae's biography online and it came up with a Wikipedia page talking about somebody who's a rugby coach. So, Dr. MacRae, I hope that's not another one of strings to your bow, that's something else that you manage to squeeze in amongst everything else that you do in your busy and punishing schedule. Dr Calum MacRae: I did play a little rugby in my day, but I haven't coached any, I can assure you. Dr Anwar Chahal: So, you are the Chief of Cardiovascular Medicine, you are an MD, PhD by training, and you are Associate Professor at Harvard Medical School, and your expertise, amongst many other things, internal medicine, cardiovascular diseases, but in particular, inherited cardiovascular conditions. Is there anything else that you would add to that? Dr Calum MacRae: No, I'm a big fan of generalism, and I am quite interested in cardiovascular involvement in systemic disease as well, but largely as a means of keeping myself abreast with the biological mechanisms in every system that seems to be relevant to cardiovascular disease. Dr Anwar Chahal: So, that reminds me. Once I heard you talk, and you mentioned to all those people that were considering cardiovascular genetics the importance of phenotype and actually how people have become increasingly super-super-specialized, becoming the bundle branch block experts or the world's authority on the right coronary cusp of the aortic valve, and how things were now going full-circle as people actually need better and better, more general understanding so that we can accurately phenotype. And you once joked that you'd actually done residency three times, so you know the importance of having a good generalist base, so could you expand a little bit on that? Dr Calum MacRae: Well, I have to tell you, it wasn't a joke. I did actually do residency three times. But, I think the most important element of that theme is that biological processes do not, unfortunately, obey the silos in which medical subspecialists operate. So it is increasingly important to have a broad-based vision of how phenotypes might actually impact the whole organism. That's particularly true because it helps us ratify disease, so that there are mechanistic insights that come from the different cell types and tissues and biological processes that are affected. I think, in general, that is something that we've all appreciated, but as time goes by and people become more and more specialized, it's less regularly implemented in day to day clinical practice. And so, particularly as molecular medicine becomes more and more penetrant in clinical disease management, I think you're going to see a return toward some generalism. Obviously, procedural specialties are the exception in many ways in this setting, because you need concentrated procedural skill. But in general, particularly for translational scientists or scientists who are interested in the underlying mechanisms of disease I think, I see a general movement towards a degree of generalism. Dr Anwar Chahal: Indeed, and in terms of, as you say, trying to understand those disease processes and trying to, let's say for example, make sense of the incredible amounts of information that can now be gathered with genomics and high throughput omics, you believe that it is actually more of a requirement to be able to understand that now that we can gather this high resolution and broad depth of data? Dr Calum MacRae: Yes, I agree. I think one of the core elements of modern clinical medicine is that the phenotypes have, in the last 50 to 100 years, we've really focused more on improving the resolution of existing phenotypes than expanding the phenotypic space. To be completely frank, I think we've extracted a lot of the information content that we can from the phenotypic space that we've explored, and what we need to begin to do is to find ways to systematically expand that phenotypic space. I think there are a lot of reasonable ways of doing it just by thinking about other subspecialties. So, for example, in cardiovascular disease, we've focused very heavily on anatomy and physiology, but we haven't really done much in the way of cell biology. Whereas, in immunology, partly because there's access to those cell types, it's possible to do much more detailed cellular phenotyping. In neuroscience, we're now doing functional MRI, and looking at individual subsets of cells in the brain, and their function in the context of particular challenges. My general thesis would be that the type of strategy would serve us well and that there's also, I think, an important mismatch between the dimensionality of phenotyping that we currently undertake and the scale of the genome and epigenome, transcriptome, et cetera. So, it's not surprising that we can't be convoluted genome of 10 to the nine variants with a phenome that are present only really has about a 10 to the four phenotypes. And so, I think some systematic right-sizing of that balance will be necessary. There are lots of things that we record that we don't even think of as phenotypes, and there are phenotypes that we record that we don't really think about how to optimize the information of content. And so that's one of the things that we have begun to invest time and energy in. And thanks to the support of the American Heart Association, Verily, and AstraZeneca, as part of the One Brave Idea, we have elected to fully focus on that area in particular in coronary disease. But I think it's a generalizable problem with much of modern medicine that we tend to have focus on phenotypes that, in many instances, date back to the turn of the last century rather than to modern molecular and cellular biology. Dr Anwar Chahal: So, you beautifully brought us to the first question, which was to ask you about One Brave Idea. Could you just, for our listeners who aren't familiar with that, just give a little bit of a background on One Brave Idea, and you've already thanked the people who have funded that, but how did you actually reach the point where you thought that this is something that really, really needs to be done? What's the process of reaching that point of bringing this idea to fruition? Dr Calum MacRae: I think we had recognized in many instances that the families that we were seeing in cardiovascular genetics clinics were much smaller, the diseases appeared to be less penetrant than the original families that we studied when we cloned many of the disease genes. This was work that I did as a post-doctoral fellow in John and Christine Simons lab many years ago. One of the things that was pretty obvious was that there were subtle pre-clinically or sub-clinically affected individuals in almost every family. And that made me ... That implies that the average family is so different from the extreme family. Is it something to do with either the resolution with which we were assessing disease or are we actually just measuring the wrong elements of the underlying genetic trait? So that, for example, is a dilated cardiomyopathy family actually a family that is susceptible to dilated cardiomyopathy in the context of some unmeasured conditioning variable, maybe a viral infection or an exposure. And because we're not measuring the exposure, or we're not measuring the underlying diaphysis, we're only measuring the final state, so we only classify people as being affected if they actually have an extreme phenotype. Are we, therefore, missing the core elements of the biology? As part of doing that, we began to look outside the heart for other phenotypes, and one of the things we recognized ... This was in cardiomyopathy ... Was that different cardiac phenotypes were really aggregates of much more granular, multi-system phenotypes. So there would be families who would have dilated cardiomyopathy, but they would also actually have abnormalities, for example, of the distal interruptus muscles, and no other muscle group in their entire body. And in fact, the distal interruptus muscle phenotype was much more obvious than any cardiomyopathic phenotype. So you start to understand that either other extra cardiac or electrical phenotypes, or maybe even sometimes neurofunction phenotypes are more penitent features of some of these disorders, albeit rare disorders. And so that immediately leads you to think are most of the common traits that we look after really aggregates of things that really only share the relative frequency of the core phenotype, which often dates back to decades earlier when phenotyping was at a much more superficial level. So that vicious cycle perpetuates itself if we never look more deeply or look outside the constraints of a particular subspecialty. And so we have begun many, probably almost four years ago, to build a sort of next generation phenotyping clinic where we tried to bring either cell biology or molecular biology from outside the heart into phenotyping patients in a cardiovascular clinic. That idea was in our DNA, that's probably not the right way to say it, but it's something that we had worked on in a cardiomyopathy setting. Dr Anwar Chahal: Right. Dr Calum MacRae: And so then when the RFP for One Brave Idea came out, it seemed like a natural expansion of that to try and think about how you could apply new phenotyping in current disease. One of the inferences from that line of thought is to move, essentially, beyond ideally much upstream of the shared final common pathway so that you can begin to identify discreet underlying mechanisms. And then, given the success of cardiologists, and cardiology in general, in prevention, it became obvious that really what we wanted to do was to try and understand not just disease, but also wellness. And to do that in a way where we could potentially detect the transition from wellness to the very first stages of the disease or the diseases that we have labeled as atherosclerosis or coronary artery disease. That was the genesis of the central idea of the application and something that, obviously, we were excited to get the chance to pursue as a result of the generosity of the funders, and the vision of Nancy Brown at AHA and Andy Conrad at Verily, to not only award funding in a different way, but to also really try and drive us to think differently about how we executed on a research product. How we move forward, not with a five-year plan, but with a rapid cycle early hypothesis testing, fail fast and fail early, if you are going to fail, strategy. Rethink not just the focus of the research project, but the mechanisms by which you execute on it. I think one of the core elements of this is, obviously, we want to make sure in doing this that we build on all of the incredible work that's been done in the last 25 or 30 years in coronary disease, whether it's the pharmacologic work, or the genetics work that has emerged in the last few years. Those are all important building blocks, and what can you do that leverages all of that existing data and adds to it? Phenotype is obviously one of the most important areas where you can bring something to the table that add to existing genotypes and also layers in on top of existing pathophysiologic models. From my standpoint, it was an efficient strategy, and one that we hoped would also help us engage the people throughout the community in different ways of using data that might already have been collected or we were going to be able to collect for the first time. Dr Anwar Chahal: In terms of One Brave Idea, where is that right now in terms of execution, as you mentioned? What's the progress so far, and is anything that's come out already that you can share with us? Dr Calum MacRae: Yeah, of course. So we have begun a variety of different approaches to thinking through the best way of exploring this phenotypic space. One of the obvious things is you can take a couple of strategies to move into this unknown unknown. One of them is to take an incremental approach to move slowly from the areas where we have already established knowledge, and to move into new areas from that home base. And the other is to take a more agnostic strategy, which is to say are there orthogonal ways of thinking where you could look at a particular type of biology in a very focused way in coronary disease. You can define that in lots of different ways. You can say maybe we do it at an organelle level, or maybe we do it at some orthogonal component. The microbiome might be an obvious one. Another one that has been considered would be nutritional or other common environmental exposures. The nice thing about the flexibility of the funding is that we can afford to test multiple different hypotheses early on, see which of them has the best signal, and then invest more deeply in those that have shown early signal. At the moment, we have multiple active projects that are really testing those initial hypotheses. Is there a way of moving from the known genes that cause coronary artery disease and trying to understand are there novel phenotypes that are associated with those. And then another approach would be to take people with very early or pre-clinical disease and test areas of biology that have never been tested in atherosclerosis or in coronary disease in a systematic way. We could imagine lots of ways of doing it, but you might think about, lets say, looking at endocytosis, a process that we know already is affected by the core genes in familial hypoglycemia, but we've never really found ways to measure that in a rigorous fashion. In large populations of individuals, are there different ... Well, we know already there are different forms endocytosis, but are there discreet port ablations that might affect those. Another way of looking this might be to pick an organelle. Pick the peroxisome, or pick the nucleolus, pick some other element and ask how does the function of this organelle change in individuals who have early coronary disease. Where its boring each of these types of things systematically, and trying to learn not just which are the most important areas to focus on, but also trying to learn are there strategies that are useful that you could use in another disease. In other words, are there generalizable approaches to expanding phenotypic space that makes sense. ...
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