Abstract 14629: Rare Variants for Electrocardiographic Traits Identify Arrhythmia Susceptibility Genes

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Sean J Jurgens ◽  
Seung Hoan Choi ◽  
Christopher M Haggerty ◽  
Amelia W Hall ◽  
Jennifer Halford ◽  
...  
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Low Frequency ◽  
Population Based ◽  
P Wave ◽  
Cardiac Conduction ◽  
Incomplete Penetrance ◽  
Loss Of Function ◽  
Discovery Sample ◽  
Pathogenic Variants

Introduction: Electrocardiogram (ECG) intervals are quantitative and heritable endophenotypes for arrhythmias and sudden cardiac death (SCD). Studying rare sequence variation related to ECG intervals may help identify the genetic underpinnings of cardiac conduction and SCD. Methods: Using a discovery sample of 29,000 individuals with whole-genome sequences from TOPMed and a replication sample of about 100,000 individuals with whole-exome sequence data from the UK Biobank and MyCode, we examined associations between low-frequency (MAF<1%) and rare (MAF<0.1%) coding variants with 5 routinely ascertained ECG intervals (RR, P-wave, PR, QRS, and QTc intervals). We further assessed pathogenic variants in identified genes using ClinVar. Results: In low-frequency single variant analysis, we observed associations for PR interval in PAM ( P =2x10 -7 ) and MFGE8 ( P =5x10 -8 ). In gene-based tests, we identified rare coding variation associated with marked effects in established SCD genes KCNQ1, KCNH2, SCN5A and KCNE1 . For example, loss-of-function or pathogenic variants in KCNQ1 and KCNH2 were carried in 0.2% of individuals, were associated with 29 ms longer QTc intervals ( P =2x10 -82 ) and conferred up to 23-fold increased odds of marked QTc prolongation ( P =4x10 -25 ). Nevertheless, over 75% of carriers had normal QTc intervals. Similarly, loss-of-function or pathogenic variants in SCN5A , carried by 0.1% of individuals, conferred marked PR prolongation (31 ms), yet less than 30% of carriers had first-degree atrioventricular block. Discussion: This study demonstrates the value of studying ECGs in large sequenced biobanks for identifying rare variants predisposing to cardiac arrhythmias. Results define the frequency of pathogenic variation in SCD genes in the population and document incomplete penetrance of such variation. Our findings may serve as a benchmark for future population-based analyses aimed at discovering clinically actionable variants and genes.

scholarly journals Rare Coding Variants Associated with Electrocardiographic Intervals Identify Monogenic Arrhythmia Susceptibility Genes: A Multi-ancestry Analysis

2021 ◽  
Author(s):  
Seung Hoan Choi ◽  
Sean J. Jurgens ◽  
Christopher M. Haggerty ◽  
Amelia W. Hall ◽  
Jennifer L. Halford ◽  
...  
Keyword(s):  
Large Scale ◽  
Rare Variants ◽  
Sequence Data ◽  
Susceptibility Genes ◽  
P Wave ◽  
Cardiac Conduction ◽  
Incomplete Penetrance ◽  
Loss Of Function ◽  
Electrocardiographic Intervals ◽  
Coding Variants

Background - Alterations in electrocardiographic (ECG) intervals are well-known markers for arrhythmia and sudden cardiac death (SCD) risk. While the genetics of arrhythmia syndromes have been studied, relations between ECG intervals and rare genetic variation at a population level are poorly understood. Methods - Using a discovery sample of 29,000 individuals with whole-genome sequencing from TOPMed and replication in nearly 100,000 with whole-exome sequencing from the UK Biobank and MyCode, we examined associations between low-frequency and rare coding variants with 5 routinely measured ECG traits (RR, P-wave, PR, and QRS intervals and corrected QT interval [QTc]). Results - We found that rare variants associated with population-based ECG intervals identify established monogenic SCD genes ( KCNQ1 , KCNH2 , SCN5A ), a controversial monogenic SCD gene ( KCNE1 ), and novel genes ( PAM , MFGE8 ) involved in cardiac conduction. Loss-of-function and pathogenic SCN5A variants, carried by 0.1% of individuals, were associated with a nearly 6-fold increased odds of first-degree atrioventricular block ( P =8.4x10 -5 ). Similar variants in KCNQ1 and KCNH2 (0.2% of individuals) were associated with a 23-fold increased odds of marked QTc prolongation ( P =4x10 -25 ), a marker of SCD risk. Incomplete penetrance of such deleterious variation was common as over 70% of carriers had normal ECG intervals. Conclusions - Our findings indicate that large-scale high-depth sequence data and ECG analysis identifies monogenic arrhythmia susceptibility genes and rare variants with large effects. Known pathogenic variation in conventional arrhythmia and SCD genes exhibited incomplete penetrance and accounted for only a small fraction of marked ECG interval prolongation.

scholarly journals Predicting RNA splicing from DNA sequence using Pangolin

2021 ◽  
Author(s):  
Tony Zeng ◽  
Yang I Li
Keyword(s):  
Deep Learning ◽  
Dna Sequence ◽  
Rna Splicing ◽  
Rare Variants ◽  
Sequence Data ◽  
Learning Approaches ◽  
Loss Of Function ◽  
Pathogenic Variants ◽  
Uncertain Significance ◽  
The Impact

Recent progress in deep learning approaches have greatly improved the prediction of RNA splicing from DNA sequence. Here, we present Pangolin, a deep learning model to predict splice site strength in multiple tissues that has been trained on RNA splicing and sequence data from four species. Pangolin outperforms state of the art methods for predicting RNA splicing on a variety of prediction tasks. We use Pangolin to study the impact of genetic variants on RNA splicing, including lineage-specific variants and rare variants of uncertain significance. Pangolin predicts loss-of-function mutations with high accuracy and recall, particularly for mutations that are not missense or nonsense (AUPRC = 0.93), demonstrating remarkable potential for identifying pathogenic variants.

scholarly journals Genetic Determinants of Electrocardiographic P-Wave Duration and Relation to Atrial Fibrillation

2020 ◽  
Vol 13 (5) ◽  
pp. 387-395
Author(s):  
Lu-Chen Weng ◽  
Amelia Weber Hall ◽  
Seung Hoan Choi ◽  
Sean J. Jurgens ◽  
Jeffrey Haessler ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Rare Variants ◽  
Association Studies ◽  
Low Frequency ◽  
P Wave ◽  
Cardiac Conduction ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Wave Duration ◽  
P Wave Duration

Background: The P-wave duration (PWD) is an electrocardiographic measurement that represents cardiac conduction in the atria. Shortened or prolonged PWD is associated with atrial fibrillation (AF). We used exome-chip data to examine the associations between common and rare variants with PWD. Methods: Fifteen studies comprising 64 440 individuals (56 943 European, 5681 African, 1186 Hispanic, 630 Asian) and ≈230 000 variants were used to examine associations with maximum PWD across the 12-lead ECG. Meta-analyses summarized association results for common variants; gene-based burden and sequence kernel association tests examined low-frequency variant-PWD associations. Additionally, we examined the associations between PWD loci and AF using previous AF genome-wide association studies. Results: We identified 21 common and low-frequency genetic loci (14 novel) associated with maximum PWD, including several AF loci ( TTN , CAND2 , SCN10A , PITX2 , CAV1 , SYNPO2L , SOX5 , TBX5, MYH6, RPL3L ). The top variants at known sarcomere genes ( TTN, MYH6 ) were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, PITX2 and SCN10A ) were associated with longer PWD but lower AF risk. Conclusions: Our results highlight multiple novel genetic loci associated with PWD, and underscore the shared mechanisms of atrial conduction and AF. Prolonged PWD may be an endophenotype for several different genetic mechanisms of AF.

scholarly journals Ancestrally and Temporally Diverse Analysis of Penetrance of Clinical Variants in 72,434 Individuals

2021 ◽  
Author(s):  
Iain S. Forrest ◽  
Kumardeep Chaudhary ◽  
Ha My T. Vy ◽  
Shantanu Bafna ◽  
Daniel M. Jordan ◽  
...  
Keyword(s):  
Large Scale ◽  
Disease Risk ◽  
Sequence Data ◽  
Genomic Medicine ◽  
Population Based ◽  
Loss Of Function ◽  
Pathogenic Variants ◽  
Scale Population ◽  
Predisposition Genes ◽  
Disease Predisposition

ABSTRACTA major goal of genomic medicine is to quantify the disease risk of genetic variants. Here, we report the penetrance of 37,772 clinically relevant variants (including those reported in ClinVar1 and of loss-of-function consequence) for 197 diseases in an analysis of exome sequence data for 72,434 individuals over five ancestries and six decades of ages from two large-scale population-based biobanks (BioMe Biobank and UK Biobank). With a high-quality set of 5,359 clinically impactful variants, we evaluate disease prevalence in carriers and non-carriers to interrogate major determinants and implications of penetrance. First, we associate biomarker levels with penetrance of variants in known disease-predisposition genes and illustrate their clear biological link to disease. We then systematically uncover large numbers of ClinVar pathogenic variants that confer low risk of disease, even among those reviewed by experts, while delineating stark differences in variant penetrance by molecular consequence. Furthermore, we ascertain numerous variants present in non-European ancestries and reveal how increasing carrier age modifies penetrance estimates. Lastly, we examine substantial heterogeneity of penetrance among variants in known disease-predisposition genes for conditions such as familial hypercholesterolemia and breast cancer. These data indicate that existing categorical systems for variant classification do not adequately capture disease risk and warrant consideration of a more quantitative system based on population-based penetrance to evaluate clinical impact.

scholarly journals Exome sequencing identifies novel AD-associated genes.

2020 ◽  
Author(s):  
Henne Holstege ◽  
Marc Hulsman ◽  
Camille Charbonnier ◽  
Benjamin Grenier-Boley ◽  
Olivier Quenez ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Genetic Variants ◽  
Rare Variants ◽  
Mendelian Inheritance ◽  
Loss Of Function ◽  
App Processing ◽  
Complex Disorders ◽  
Pathogenic Variants ◽  
Increased Risk ◽  
The Impact

Background: With the development of next-generation sequencing technologies, it is possible to identify rare genetic variants that influence the risk of complex disorders. To date, whole exome sequencing (WES) strategies have shown that specific clusters of damaging rare variants in the TREM2, SORL1 and ABCA7 genes are associated with an increased risk of developing Alzheimers Disease (AD), reaching odds ratios comparable with the APOE-ε4 allele, the main common AD genetic risk factor. Here, we set out to identify additional AD-associated genes by an exome-wide investigation of the burden of rare damaging variants in the genomes of AD cases and cognitively healthy controls. Method: We integrated the data from 25,982 samples from the European ADES consortium and the American ADSP consortium. We developed new techniques to homogenise and analyse these data. Carriers of pathogenic variants in genes associated with Mendelian inheritance of dementia were excluded. After quality control, we used 12,652 AD cases and 8,693 controls for analysis. Genes were analysed using a burden analysis, including both non-synonymous and loss-of-function rare variants, the impact of which was prioritised using REVEL. Result: We confirmed that carrying rare protein-damaging genetic variants in TREM2, SORL1 or ABCA7 is associated with increased AD-risk. Moreover, we found that carrying rare damaging variants in the microglial ATP8B4 gene was significantly associated with AD, and we found suggestive evidence that rare variants in ADAM10, ABCA1, ORC6, B3GNT4 and SRC genes associated with increased AD risk. High-impact variants in these genes were mostly extremely rare and enriched in AD patients with earlier ages at onset. Additionally, we identified two suggestive protective associations in CBX3 and PRSS3. We are currently replicating these associations in independent datasets. Conclusion: With our newly developed homogenisation methods, we identified novel genetic determinants of AD which provide further evidence for a pivotal role of APP processing, lipid metabolism, and microglia and neuro-inflammatory processes in AD pathophysiology.

Genetic identification and characterization of Lynch syndrome in a multi-ethnic biobank.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 1520-1520
Author(s):  
Rachel Rosenblum ◽  
Sabrina A. Suckiel ◽  
Gillian M. Belbin ◽  
Sinead Cullina ◽  
Judy H. Cho ◽  
...  
Keyword(s):  
Lynch Syndrome ◽  
Diagnostic Criteria ◽  
Sequence Data ◽  
Genetic Identification ◽  
European Ancestry ◽  
Gene Variants ◽  
Loss Of Function ◽  
Mmr Genes ◽  
Pathogenic Variants ◽  
Increased Risk

1520 Background: Lynch syndrome (LS), caused by germline pathogenic variants in mismatch repair (MMR) genes, results in increased risk of colorectal, endometrial, and other cancers. LS has a prevalence of ~1 in 440 in European ancestry populations; prevalence data in other populations are limited. We identified and characterized carriers of pathogenic MMR gene variants in the multi-ethnic Bio Me Biobank in New York City. Methods: Exome sequence data from ~31,000 Bio Me participants were evaluated for known (per ClinVar) and predicted (loss-of-function) pathogenic variants in MMR genes. Population groups were defined by genetic ancestry. Participant questionnaires and electronic health records (EHRs) of carriers were reviewed for personal or family history of malignancy. Results: We identified 48 carriers of 33 distinct pathogenic variants in PMS2 (48%), MLH1 (27%), MSH6 (15%), and MSH2 (10%), for an estimated prevalence of ~1/640 in the Bio Me Biobank. Prevalence was higher among individuals of Non-Jewish European (N = 14; 1/400) and African (N = 14; 1/490) ancestries, compared to Puerto Rican (N = 8; 1/640), Ashkenazi Jewish (N = 6; 1/690), and other/mixed (N = 6) ancestries. Carriers had a median age of 56 (range 27 to 77) years and were 50% female. Overall rate of malignancy among carriers was 38%, with the lowest rate in PMS2 (26%) and the highest rate in MSH6 (57%) variant carriers. We found a high prevalence of endometrial cancer (21% of female carriers) and a lower prevalence of colorectal cancer (4% of all carriers). Only 2 carriers (4%) had a diagnosis of LS in their EHRs, and only 1 carrier met Amsterdam diagnostic criteria for LS. Conclusions: These data show that ~0.15% of participants in a multi-ethnic biobank are carriers of pathogenic MMR gene variants and suggest that the prevalence is higher in European and lower in non-European ancestry populations. Notably, most carriers do not have a clinical diagnosis of LS and do not meet diagnostic criteria for LS. Carriers demonstrate variable rates of cancer, which may contribute to under-diagnosis of LS. Genomic screening for pathogenic MMR variants may lead to earlier diagnosis of LS and improved outcomes.

scholarly journals Surveying the contribution of rare variants to the genetic architecture of human disease through exome sequencing of 177,882 UK Biobank participants

2020 ◽  
Author(s):  
Quanli Wang ◽  
Ryan S. Dhindsa ◽  
Keren Carss ◽  
Andrew R Harper ◽  
Abhishek Nag ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Drug Targets ◽  
Rare Variants ◽  
Population Based ◽  
Uk Biobank ◽  
Loss Of Function ◽  
Sequencing Data ◽  
Phenotypic Data ◽  
Protein Coding ◽  
The Uk

The UK Biobank (UKB) represents an unprecedented population-based study of 502,543 participants with detailed phenotypic data and linkage to medical records. While the release of genotyping array data for this cohort has bolstered genomic discovery for common variants, the contribution of rare variants to this broad phenotype collection remains relatively unknown. Here, we use exome sequencing data from 177,882 UKB participants to evaluate the association between rare protein-coding variants with 10,533 binary and 1,419 quantitative phenotypes. We performed both a variant-level phenome-wide association study (PheWAS) and a gene-level collapsing analysis-based PheWAS tailored to detecting the aggregate contribution of rare variants. The latter revealed 911 statistically significant gene-phenotype relationships, with a median odds ratio of 15.7 for binary traits. Among the binary trait associations identified using collapsing analysis, 83% were undetectable using single variant association tests, emphasizing the power of collapsing analysis to detect signal in the setting of high allelic heterogeneity. As a whole, these genotype-phenotype associations were significantly enriched for loss-of-function mediated traits and currently approved drug targets. Using these results, we summarise the contribution of rare variants to common diseases in the context of the UKB phenome and provide an example of how novel gene-phenotype associations can aid in therapeutic target prioritisation.

scholarly journals Genome-wide rare variant analysis for thousands of phenotypes in 54,000 exomes

2019 ◽  
Author(s):  
Elizabeth T. Cirulli ◽  
Simon White ◽  
Robert W. Read ◽  
Gai Elhanan ◽  
William J Metcalf ◽  
...  
Keyword(s):  
Rare Variant ◽  
Large Scale ◽  
Rare Variants ◽  
Sequence Data ◽  
Statistical Significance ◽  
European Ancestry ◽  
Hair Color ◽  
Common Variants ◽  
Loss Of Function ◽  
Test Statistic

Defining the effects that rare variants can have on human phenotypes is essential to advancing our understanding of human health and disease. Large-scale human genetic analyses have thus far focused on common variants, but the development of large cohorts of deeply phenotyped individuals with exome sequence data has now made comprehensive analyses of rare variants possible. We analyzed the effects of rare (MAF<0.1%) variants on 3,166 phenotypes in 40,468 exome-sequenced individuals from the UK Biobank and performed replication as well as meta-analyses with 1,067 phenotypes in 13,470 members of the Healthy Nevada Project (HNP) cohort who underwent Exome+ sequencing at Helix. Our analyses of non-benign coding and loss of function (LoF) variants identified 78 gene-based associations that passed our statistical significance threshold (p<5×10-9). These are associations in which carrying any rare coding or LoF variant in the gene is associated with an enrichment for a specific phenotype, as opposed to GWAS-based associations of strictly single variants. Importantly, our results do not suffer from the test statistic inflation that is often seen with rare variant analyses of biobank-scale data because of our rare variant-tailored methodology, which includes a step that optimizes the carrier frequency threshold for each phenotype based on prevalence. Of the 47 discovery associations whose phenotypes were represented in the replication cohort, 98% showed effects in the expected direction, and 45% attained formal replication significance (p<0.001). Six additional significant associations were identified in our meta-analysis of both cohorts. Among the results, we confirm known associations of PCSK9 and APOB variation with LDL levels; we extend knowledge of variation in the TYRP1 gene, previously associated with blonde hair color only in Solomon Islanders to blonde hair color in individuals of European ancestry; we show that PAPPA, a gene in which common variants had previously associated with height via GWAS, contains rare variants that decrease height; and we make the novel discovery that STAB1 variation is associated with blood flow in the brain. Our results are available for download and interactive browsing in an app (https://ukb.research.helix.com). This comprehensive analysis of the effects of rare variants on human phenotypes marks one of the first steps in the next big phase of human genetics, where large, deeply phenotyped cohorts with next generation sequence data will elucidate the effects of rare variants.

scholarly journals The impact of Mendelian sleep and circadian genetic variants in a population setting

2022 ◽  
Author(s):  
Michael N Weedon ◽  
Samuel E Jones ◽  
Jacqueline Lane ◽  
Jiwon Lee ◽  
Hanna M Ollila ◽  
...  
Keyword(s):  
Sleep Duration ◽  
Rare Variants ◽  
Sequence Data ◽  
Large Population ◽  
Population Based ◽  
Self Report ◽  
Uk Biobank ◽  
Sleep Phase ◽  
Sleep Timing ◽  
The Impact

Rare variants in ten genes have been reported to cause Mendelian sleep conditions characterised by extreme sleep duration or timing. These include familial natural short sleep (ADRB1, DEC2/BHLHE41, GRM1 and NPSR1), advanced sleep phase (PER2, PER3, CRY2, CSNK1D and TIMELESS) and delayed sleep phase (CRY1). The association of variants of these genes with extreme sleep conditions were usually based on clinically ascertained families, and their effects when identified in the population are unknown. We aimed to determine the effects of these variants on sleep traits in large population-based cohorts. We performed genetic association analysis of variants previously reported to be causal for Mendelian sleep and circadian conditions. Analyses were performed using 191,929 individuals with data on sleep and whole-exome or genome-sequence data from 4 population-based studies: UK Biobank, FINRISK, Health-2000-2001, and the Multi-Ethnic Study of Atherosclerosis (MESA). We identified sleep disorders from self-report, hospital and primary care data. We estimated sleep duration and timing measures from self-report and accelerometery data. We identified carriers for 10 out of 12 previously reported pathogenic variants for 8 of the 10 genes. They ranged in frequency from 1 individual with the variant in CSNK1D to 1,574 individuals with a reported variant in the PER3 gene in the UK Biobank. We found no association of any of these variants with extreme sleep or circadian phenotypes. Using sleep timing as a proxy measure for sleep phase, only PER3 and CRY1 variants demonstrated association with earlier and later sleep timing, respectively; however, the magnitude of effect was smaller than previously reported (sleep midpoint ~7 mins earlier and ~5 mins later, respectively). We also performed burden tests of protein truncating (PTVs) or rare missense variants for the 10 genes. Only PTVs in PER2 and PER3 were associated with a relevant trait (for example, 64 individuals with a PTV in PER2 had an odds ratio of 4.4 for being "definitely a morning person", P=4x10-8; and had a 57-minute earlier midpoint sleep, P=5x10-7). Our results indicate that previously reported variants for Mendelian sleep and circadian conditions are often not highly penetrant when ascertained incidentally from the general population.

scholarly journals Characterizing rare and low-frequency height-associated variants in the Japanese population

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Masato Akiyama ◽  
Kazuyoshi Ishigaki ◽  
Saori Sakaue ◽  
Yukihide Momozawa ◽  
Momoko Horikoshi ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Rare Variants ◽  
Sequence Data ◽  
Low Frequency ◽  
European Population ◽  
Genotype Imputation ◽  
Whole Genome Sequence ◽  
General Tendency ◽  
Phenotypic Variance ◽  
A Genome

Abstract Human height is a representative phenotype to elucidate genetic architecture. However, the majority of large studies have been performed in European population. To investigate the rare and low-frequency variants associated with height, we construct a reference panel (N = 3,541) for genotype imputation by integrating the whole-genome sequence data from 1,037 Japanese with that of the 1000 Genomes Project, and perform a genome-wide association study in 191,787 Japanese. We report 573 height-associated variants, including 22 rare and 42 low-frequency variants. These 64 variants explain 1.7% of the phenotypic variance. Furthermore, a gene-based analysis identifies two genes with multiple height-increasing rare and low-frequency nonsynonymous variants (SLC27A3 and CYP26B1; PSKAT-O < 2.5 × 10−6). Our analysis shows a general tendency of the effect sizes of rare variants towards increasing height, which is contrary to findings among Europeans, suggesting that height-associated rare variants are under different selection pressure in Japanese and European populations.

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