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

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

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

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

Common and Rare Coding Genetic Variation Underlying the Electrocardiographic PR Interval

Background: Electrical conduction from the cardiac sinoatrial node to the ventricles is critical for normal heart function. Genome-wide association studies have identified more than a dozen common genetic loci that are associated with PR interval. However, it is unclear whether rare and low-frequency variants also contribute to PR interval heritability. Methods: We performed large-scale meta-analyses of the PR interval that included 83 367 participants of European ancestry and 9436 of African ancestry. We examined both common and rare variants associated with the PR interval. Results: We identified 31 genetic loci that were significantly associated with PR interval after Bonferroni correction (P<1.2×10−6), including 11 novel loci that have not been reported previously. Many of these loci are involved in heart morphogenesis. In gene-based analysis, we found that multiple rare variants at MYH6 (P=5.9×10−11) and SCN5A (P=1.1×10−7) were associated with PR interval. SCN5A locus also was implicated in the common variant analysis, whereas MYH6 was a novel locus. Conclusions: We identified common variants at 11 novel loci and rare variants within 2 gene regions that were significantly associated with PR interval. Our findings provide novel insights to the current understanding of atrioventricular conduction, which is critical for cardiac activity and an important determinant of health

Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6.

BACKGROUND: Genome-wide association studies conducted on QRS duration, an electrocardiographic measurement associated with heart failure and sudden cardiac death, have led to novel biological insights into cardiac function. However, the variants identified fall predominantly in non-coding regions and their underlying mechanisms remain unclear. RESULTS: Here, we identify putative functional coding variation associated with changes in the QRS interval duration by combining Illumina HumanExome BeadChip genotype data from 77,898 participants of European ancestry and 7695 of African descent in our discovery cohort, followed by replication in 111,874 individuals of European ancestry from the UK Biobank and deCODE cohorts. We identify ten novel loci, seven within coding regions, including ADAMTS6, significantly associated with QRS duration in gene-based analyses. ADAMTS6 encodes a secreted metalloprotease of currently unknown function. In vitro validation analysis shows that the QRS-associated variants lead to impaired ADAMTS6 secretion and loss-of function analysis in mice demonstrates a previously unappreciated role for ADAMTS6 in connexin 43 gap junction expression, which is essential for myocardial conduction. CONCLUSIONS: Our approach identifies novel coding and non-coding variants underlying ventricular depolarization and provides a possible mechanism for the ADAMTS6-associated conduction changes.BH

Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery

Discovery of novel heart rate-associated loci using the Exome Chip

Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. Genome-wide association study analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation. This study aims to discover new genetic loci associated with heart rate from Exome Chip meta-analyses. Heart rate was measured from either elecrtrocardiograms or pulse recordings. We meta-analysed heart rate association results from 104 452 European-ancestry individuals from 30 cohorts, genotyped using the Exome Chip. Twenty-four variants were selected for follow-up in an independent dataset (UK Biobank, N = 134 251). Conditional and gene-based testing was undertaken, and variants were investigated with bioinformatics methods. We discovered five novel heart rate loci, and one new independent low-frequency non-synonymous variant in an established heart rate locus (KIAA1755). Lead variants in four of the novel loci are non-synonymous variants in the genes C10orf71, DALDR3, TESK2 and SEC31B. The variant at SEC31B is significantly associated with SEC31B expression in heart and tibial nerve tissue. Further candidate genes were detected from long-range regulatory chromatin interactions in heart tissue (SCD, SLF2 and MAPK8). We observed significant enrichment in DNase I hypersensitive sites in fetal heart and lung. Moreover, enrichment was seen for the first time in human neuronal progenitor cells (derived from embryonic stem cells) and fetal muscle samples by including our novel variants. Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies

Multi-ethnic genome-wide association study for atrial fibrillation

Atrial fibrillation (AF) affects more than 33 million individuals worldwide and has a complex heritability. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF

Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6

Background: Genome-wide association studies conducted on QRS duration, an electrocardiographic measurement associated with heart failure and sudden cardiac death, have led to novel biological insights into cardiac function. However, the variants identified fall predominantly in non-coding regions and their underlying mechanisms remain unclear.Results: Here, we identify putative functional coding variation associated with changes in the QRS interval duration by combining Illumina HumanExome BeadChip genotype data from 77,898 participants of European ancestry and 7695 of African descent in our discovery cohort, followed by replication in 111,874 individuals of European ancestry from the UK Biobank and deCODE cohorts. We identify ten novel loci, seven within coding regions, including ADAMTS6, significantly associated with QRS duration in gene-based analyses. ADAMTS6 encodes a secreted metalloprotease of currently unknown function. In vitro validation analysis shows that the QRS-associated variants lead to impaired ADAMTS6 secretion and loss-of function analysis in mice demonstrates a previously unappreciated role for ADAMTS6 in connexin 43 gap junction expression, which is essential for myocardial conduction.Conclusions: Our approach identifies novel coding and non-coding variants underlying ventricular depolarization and provides a possible mechanism for the ADAMTS6-associated conduction changes

Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility.

Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.CHARGE: Funding support for ‘Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium’ was provided by the NIH through the American Recovery and Reinvestment Act of 2009 (ARRA) (5RC2HL102419). Sequence data for ‘Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium’ was provided by Eric Boerwinkle on behalf of the Atherosclerosis Risk in Communities (ARIC) Study, L. Adrienne Cupples, principal investigator for the Framingham Heart Study, and Bruce Psaty, principal investigator for the Cardiovascular Health Study. Sequencing was carried out at the Baylor Genome Center (U54 HG003273). Further support came from HL120393, ‘Rare variants and NHLBI traits in deeply phenotyped cohorts’ (Bruce Psaty, principal investigator). Supporting funding was also provided by NHLBI with the CHARGE infrastructure grant HL105756. In addition, M.J.P. was supported through the 2014 CHARGE Visiting Fellow grant—HL105756, Dr Bruce Psaty, PI. ENCODE: ENCODE collaborators Ben Brown and Marcus Stoiber were supported by the LDRD# 14-200 (B.B. and M.S.) and 4R00HG006698-03 (B.B.) grants. AGES: This study has been funded by NIA contract N01-AG-12100 with contributions from NEI, NIDCD and NHLBI, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association) and the Althingi (the Icelandic Parliament). ARIC: The Atherosclerosis Risk in Communities (ARIC) Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute (NHLBI) contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C and HHSN268201100012C), R01HL087641, R01HL59367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. We thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. CARDIA: The CARDIA Study is conducted and supported by the National Heart, Lung, and Blood Institute in collaboration with the University of Alabama at Birmingham (HHSN268201300025C & HHSN268201300026C), Northwestern University (HHSN268201300027C), University of Minnesota (HHSN268201300028C), Kaiser Foundation Research Institute (HHSN268201300029C), and Johns Hopkins University School of Medicine (HHSN268200900041C). CARDIA is also partially supported by the Intramural Research Program of the National Institute on Aging. Exome chip genotyping and data analyses were funded in part by grants U01-HG004729, R01-HL093029 and R01-HL084099 from the National Institutes of Health to Dr Myriam Fornage. This manuscript has been reviewed by CARDIA for scientific content. CHES: This work was supported in part by The Chinese-American Eye Study (CHES) grant EY017337, an unrestricted departmental grant from Research to Prevent Blindness, and the Genetics of Latinos Diabetic Retinopathy (GOLDR) Study grant EY14684. CHS: This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants HL080295, HL087652, HL103612, HL068986 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG023629 from the National Institute on Aging (NIA). A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The CoLaus Study: We thank the co-primary investigators of the CoLaus study, Gerard Waeber and Peter Vollenweider, and the PI of the PsyColaus Study Martin Preisig. We gratefully acknowledge Yolande Barreau, Anne-Lise Bastian, Binasa Ramic, Martine Moranville, Martine Baumer, Marcy Sagette, Jeanne Ecoffey and Sylvie Mermoud for their role in the CoLaus data collection. The CoLaus study was supported by research grants from GlaxoSmithKline and from the Faculty of Biology and Medicine of Lausanne, Switzerland. The PsyCoLaus study was supported by grants from the Swiss National Science Foundation (#3200B0–105993) and from GlaxoSmithKline (Drug Discovery—Verona, R&D). CROATIA-Korcula: The CROATIA-Korcula study would like to acknowledge the invaluable contributions of the recruitment team in Korcula, the administrative teams in Croatia and Edinburgh and the people of Korcula. Exome array genotyping was performed at the Wellcome Trust Clinical Research Facility Genetics Core at Western General Hospital, Edinburgh, UK. The CROATIA-Korcula study on the Croatian island of Korucla was supported through grants from the Medical Research Council UK and the Ministry of Science, Education and Sport in the Republic of Croatia (number 108-1080315-0302). EFSOCH: We are extremely grateful to the EFSOCH study participants and the EFSOCH study team. The opinions given in this paper do not necessarily represent those of NIHR, the NHS or the Department of Health. The EFSOCH study was supported by South West NHS Research and Development, Exeter NHS Research and Development, the Darlington Trust, and the Peninsula NIHR Clinical Research Facility at the University of Exeter. Timothy Frayling, PI, is supported by the European Research Council grant: SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC. EPIC-Potsdam: We thank all EPIC-Potsdam participants for their invaluable contribution to the study. The study was supported in part by a grant from the German Federal Ministry of Education and Research (BMBF) to the German Center for Diabetes Research (DZD e.V.). The recruitment phase of the EPIC-Potsdam study was supported by the Federal Ministry of Science, Germany (01 EA 9401) and the European Union (SOC 95201408 05 F02). The follow-up of the EPIC-Potsdam study was supported by German Cancer Aid (70-2488-Ha I) and the European Community (SOC 98200769 05 F02). Furthermore, we thank Ellen Kohlsdorf for data management as well as the follow-up team headed by Dr Manuala Bergmann for case ascertainment. ERF: The ERF study was supported by grants from the Netherlands Organization for Scientific Research (NWO) and a joint grant from NWO and the Russian Foundation for Basic research (Pionier, 047.016.009, 047.017.043), Erasmus MC, and the Centre for Medical Systems Biology (CMSB; National Genomics Initiative). Exome sequencing analysis in ERF was supported by the ZonMw grant (91111025). For the ERF Study, we are grateful to all participants and their relatives, to general practitioners and neurologists for their contributions, to P. Veraart for her help in genealogy and to P. Snijders for his help in data collection. FamHS: The Family Heart Study (FamHS) was supported by NIH grants R01-HL-087700 and R01-HL-088215 (Michael A. Province, PI) from NHLBI; and R01-DK-8925601 and R01-DK-075681 (Ingrid B. Borecki, PI) from NIDDK. FENLAND: The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust. We are grateful to all the volunteers for their time and help, and to the General Practitioners and practice staff for assistance with recruitment. We thank the Fenland Study Investigators, Fenland Study Co-ordination team and the Epidemiology Field, Data and Laboratory teams. The Fenland Study is funded by the Medical Research Council (MC_U106179471) and Wellcome Trust. FHS: Genotyping, quality control and calling of the Illumina HumanExome BeadChip in the Framingham Heart Study was supported by funding from the National Heart, Lung and Blood Institute Division of Intramural Research (Daniel Levy and Christopher J. O’Donnell, Principle Investigators). A portion of this research was conducted using the Linux Clusters for Genetic Analysis (LinGA) computing resources at Boston University Medical Campus. Also supported by National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK078616, NIDDK K24 DK080140 and American Diabetes Association Mentor-Based Postdoctoral Fellowship Award #7-09-MN-32, all to Dr Meigs, a Canadian Diabetes Association Research Fellowship Award to Dr Leong, a research grant from the University of Verona, Italy to Dr Dauriz, and NIDDK Research Career Award K23 DK65978, a Massachusetts General Hospital Physician Scientist Development Award and a Doris Duke Charitable Foundation Clinical Scientist Development Award to Dr Florez. FIA3: We are indebted to the study participants who dedicated their time and samples to these studies. We thank Åsa Ågren (Umeå Medical Biobank) for data organization and Kerstin Enquist and Thore Johansson (Västerbottens County Council) for technical assistance with DNA extraction. This particular project was supported by project grants from the Swedish Heart-Lung Foundation, Umeå Medical Research Foundation and Västerbotten County Council. The Genetics Epidemiology of Metabolic Syndrome (GEMS) Study: We thank Metabolic Syndrome GEMs investigators: Scott Grundy, Jonathan Cohen, Ruth McPherson, Antero Kesaniemi, Robert Mahley, Tom Bersot, Philip Barter and Gerard Waeber. We gratefully acknowledge the contributions of the study personnel at each of the collaborating sites: John Farrell, Nicholas Nikolopoulos and Maureen Sutton (Boston); Judy Walshe, Monica Prentice, Anne Whitehouse, Julie Butters and Tori Nicholls (Australia); Heather Doelle, Lynn Lewis and Anna Toma (Canada); Kari Kervinen, Seppo Poykko, Liisa Mannermaa and Sari Paavola (Finland); Claire Hurrel, Diane Morin, Alice Mermod, Myriam Genoud and Roger Darioli (Switzerland); Guy Pepin, Sibel Tanir, Erhan Palaoglu, Kerem Ozer, Linda Mahley and Aysen Agacdiken (Turkey); and Deborah A. Widmer, Rhonda Harris and Selena Dixon (United States). Funding for the GEMS study was provided by GlaxoSmithKline. GeneSTAR: The Johns Hopkins Genetic Study of Atherosclerosis Risk (GeneSTAR) Study was supported by NIH grants through the National Heart, Lung, and Blood Institute (HL58625-01A1, HL59684, HL071025-01A1, U01HL72518, HL112064, and HL087698) and the National Institute of Nursing Research (NR0224103) and by M01-RR000052 to the Johns Hopkins General Clinical Research Center. Genotyping services were provided through the RS&G Service by the Northwest Genomics Center at the University of Washington, Department of Genome Sciences, under U.S. Federal Government contract number HHSN268201100037C from the National Heart, Lung, and Blood Institute. GLACIER: We are indebted to the study participants who dedicated their time, data and samples to the GLACIER Study as part of the Västerbottens hälsoundersökningar (Västerbottens Health Survey). We thank John Hutiainen and Åsa Ågren (Northern Sweden Biobank) for data organization and Kerstin Enquist and Thore Johansson (Västerbottens County Council) for extracting DNA. We also thank M. Sterner, M. Juhas and P. Storm (Lund University Diabetes Center) for their expert technical assistance with genotyping and genotype data preparation. The GLACIER Study was supported by grants from Novo Nordisk, the Swedish Research Council, Påhlssons Foundation, The Heart Foundation of Northern Sweden, the Swedish Heart Lung Foundation, the Skåne Regional Health Authority, Umeå Medical Research Foundation and the Wellcome Trust. This particular project was supported by project grants from the Swedish Heart-Lung Foundation, the Swedish Research Council, the Swedish Diabetes Association, Påhlssons Foundation and Novo nordisk (all grants to P. W. Franks). GOMAP (Genetic Overlap between Metabolic and Psychiatric Disease): This work was funded by the Wellcome Trust (098051). We thank all participants for their important contribution. We are grateful to Georgia Markou, Laiko General Hospital Diabetes Centre, Maria Emetsidou and Panagiota Fotinopoulou, Hippokratio General Hospital Diabetes Centre, Athina Karabela, Dafni Psychiatric Hospital, Eirini Glezou and Marios Matzioros, Dromokaiteio Psychiatric Hospital, Angela Rentari, Harokopio University of Athens, and Danielle Walker, Wellcome Trust Sanger Institute. Generation Scotland: Scottish Family Health Study (GS:SFHS): GS:SFHS is funded by the Chief Scientist Office of the Scottish Government Health Directorates, grant number CZD/16/6 and the Scottish Funding Council. Exome array genotyping for GS:SFHS was funded by the Medical Research Council UK and performed at the Wellcome Trust Clinical Research Facility Genetics Core at Western General Hospital, Edinburgh, UK. We also acknowledge the invaluable contributions of the families who took part in the Generation Scotland: Scottish Family Health Study, the general practitioners and Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes academic researchers, IT staff, laboratory technicians, statisticians and research managers. The chief investigators of Generation Scotland are David J. Porteous (University of Edinburgh), Lynne Hocking (University of Aberdeen), Blair Smith (University of Dundee), and Sandosh Padmanabhan (University of Glasgow). GSK (CoLaus, GEMS, Lolipop): We thank the GEMS Study Investigators: Philip Barter, PhD; Y. Antero Kesäniemi, PhD; Robert W. Mahley, PhD; Ruth McPherson, FRCP; and Scott M. Grundy, PhD. Dr Waeber MD, the CoLaus PI’s Peter Vollenweider MD and Gerard Waeber MD, the LOLIPOP PI’s, Jaspal Kooner MD and John Chambers MD, as well as the participants in all the studies. The GEMS study was sponsored in part by GlaxoSmithKline. The CoLaus study was supported by grants from GlaxoSmithKline, the Swiss National Science Foundation (Grant 33CSCO-122661) and the Faculty of Biology and Medicine of Lausanne. Health ABC: The Health, Aging and Body Composition (HABC) Study is supported by NIA contracts N01AG62101, N01AG62103 and N01AG62106. The exome-wide association study was funded by NIA grant 1R01AG032098-01A1 to Wake Forest University Health Sciences and was supported in part by the Intramural Research Program of the NIH, National Institute on Aging (Z01 AG000949-02 and Z01 AG007390-07, Human subjects protocol UCSF IRB is H5254-12688-11). Portions of this study utilized the high-performance computational capabilities of the Biowulf Linux cluster at the National Institutes of Health, Bethesda, MD. (http:/biowulf.nih.gov). Health2008: The Health2008 cohort was supported by the Timber Merchant Vilhelm Bang’s Foundation, the Danish Heart Foundation (Grant number 07-10-R61-A1754-B838-22392F), and the Health Insurance Foundation (Helsefonden) (Grant number 2012B233). HELIC: This work was funded by the Wellcome Trust (098051) and the European Research Council (ERC-2011-StG 280559-SEPI). The MANOLIS cohort is named in honour of Manolis Giannakakis, 1978–2010. We thank the residents of Anogia and surrounding Mylopotamos villages, and of the Pomak villages, for taking part. The HELIC study has been supported by many individuals who have contributed to sample collection (including Antonis Athanasiadis, Olina Balafouti, Christina Batzaki, Georgios Daskalakis, Eleni Emmanouil, Chrisoula Giannakaki, Margarita Giannakopoulou, Anastasia Kaparou, Vasiliki Kariakli, Stella Koinaki, Dimitra Kokori, Maria Konidari, Hara Koundouraki, Dimitris Koutoukidis, Vasiliki Mamakou, Eirini Mamalaki, Eirini Mpamiaki, Maria Tsoukana, Dimitra Tzakou, Katerina Vosdogianni, Niovi Xenaki, Eleni Zengini), data entry (Thanos Antonos, Dimitra Papagrigoriou, Betty Spiliopoulou), sample logistics (Sarah Edkins, Emma Gray), genotyping (Robert Andrews, Hannah Blackburn, Doug Simpkin, Siobhan Whitehead), research administration (Anja Kolb-Kokocinski, Carol Smee, Danielle Walker) and informatics (Martin Pollard, Josh Randall). INCIPE: NIcole Soranzo’s research is supported by the Wellcome Trust (Grant Codes WT098051 and WT091310), the EU FP7 (EPIGENESYS Grant Code 257082 and BLUEPRINT Grant Code HEALTH-F5-2011-282510). Inter99: The Inter99 was initiated by Torben Jørgensen (PI), Knut Borch-Johnsen (co-PI), Hans Ibsen and Troels F. Thomsen. The steering committee comprises the former two and Charlotta Pisinger. The study was financially supported by research grants from the Danish Research Council, the Danish Centre for Health Technology Assessment, Novo Nordisk Inc., Research Foundation of Copenhagen County, Ministry of Internal Affairs and Health, the Danish Heart Foundation, the Danish Pharmaceutical Association, the Augustinus Foundation, the Ib Henriksen Foundation, the Becket Foundation and the Danish Diabetes Association. Genetic studies of both Inter99 and Health 2008 cohorts were funded by the Lundbeck Foundation and produced by The Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention and Care (LuCamp, www.lucamp.org ). The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk). InterAct Consortium: Funding for the InterAct project was provided by the EU FP6 programme (grant number LSHM_CT_2006_037197). We thank all EPIC participants and staff for their contribution to the study. We thank the lab team at the MRC Epidemiology Unit for sample management and Nicola Kerrison for data management. IPM BioMe Biobank: The Mount Sinai IPM BioMe Program is supported by The Andrea and Charles Bronfman Philanthropies. Analyses of BioMe data was supported in part through the computational resources and staff expertise provided by the Department of Scientific Computing at the Icahn School of Medicine at Mount Sinai. The Insulin Resistance Atherosclerosis Family Study (IRASFS): The IRASFS was conducted and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (HL060944, HL061019, and HL060919). Exome chip genotyping and data analyses were funded in part by grants DK081350 and HG007112. A subset of the IRASFS exome chips were contributed with funds from the Department of Internal Medicine at the University of Michigan. Computing resources were provided, in part, by the Wake Forest School of Medicine Center for Public Health Genomics. The Insulin Resistance Atherosclerosis Study (IRAS): The IRAS was conducted and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (HL047887, HL047889, HL047890 and HL47902). Exome chip genotyping and data analyses were funded in part by grants DK081350 and HG007112). Computing resources were provided, in part, by the Wake Forest School of Medicine Center for Public Health Genomics. JHS: The JHS is supported by contracts HHSN268201300046C, HHSN268201300047C, HHSN268201300048C, HHSN268201300049C, HHSN268201300050C from the National Heart, Lung and Blood Institute and the National Institute on Minority Health and Health Disparities. ExomeChip genotyping was supported by the NHLBI of the National Institutes of Health under award number R01HL107816 to S. Kathiresan. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The London Life Sciences Prospective Population (LOLIPOP) Study: We thank the co-primary investigators of the LOLIPOP study: Jaspal Kooner, John Chambers and Paul Elliott. The LOLIPOP study is supported by the National Institute for Health Research Comprehensive Biomedical Research Centre Imperial College Healthcare NHS Trust, the British Heart Foundation (SP/04/002), the Medical Research Council (G0700931), the Wellcome Trust (084723/Z/08/Z) and the National Institute for Health Research (RP-PG-0407-10371). MAGIC: Data on glycaemic traits were contributed by MAGIC investigators and were downloaded from www.magicinvestigators.org. MESA: The Multi-Ethnic Study of Atherosclerosis (MESA) and MESA SHARe project are conducted and supported by contracts N01-HC-95159 through N01-HC-95169 and RR-024156 from the National Heart, Lung, and Blood Institute (NHLBI). Funding for MESA SHARe genotyping was provided by NHLBI Contract N02-HL-6-4278. MESA Family is conducted and supported in collaboration with MESA investigators; support is provided by grants and co

ExomeChip-Wide Analysis of 95 626 Individuals Identifies 10 Novel Loci Associated With QT and JT Intervals

BACKGROUND: QT interval, measured through a standard ECG, captures the time it takes for the cardiac ventricles to depolarize and repolarize. JT interval is the component of the QT interval that reflects ventricular repolarization alone. Prolonged QT interval has been linked to higher risk of sudden cardiac arrest.METHODS AND RESULTS: We performed an ExomeChip-wide analysis for both QT and JT intervals, including 209 449 variants, both common and rare, in 17 341 genes from the Illumina Infinium HumanExome BeadChip. We identified 10 loci that modulate QT and JT interval duration that have not been previously reported in the literature using single-variant statistical models in a meta-analysis of 95 626 individuals from 23 cohorts (comprised 83 884 European ancestry individuals, 9610 blacks, 1382 Hispanics, and 750 Asians). This brings the total number of ventricular repolarization associated loci to 45. In addition, our approach of using coding variants has highlighted the role of 17 specific genes for involvement in ventricular repolarization, 7 of which are in novel loci.CONCLUSIONS: Our analyses show a role for myocyte internal structure and interconnections in modulating QT interval duration, adding to previous known roles of potassium, sodium, and calcium ion regulation, as well as autonomic control. We anticipate that these discoveries will open new paths to the goal of making novel remedies for the prevention of lethal ventricular arrhythmias and sudden cardiac arrest