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Meta-Analysis
. 2020 May 21;11(1):2542.
doi: 10.1038/s41467-020-15706-x.

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction

Ioanna Ntalla #  1 Lu-Chen Weng #  2   3 James H Cartwright  1 Amelia Weber Hall  2   3 Gardar Sveinbjornsson  4 Nathan R Tucker  2   3 Seung Hoan Choi  3 Mark D Chaffin  3 Carolina Roselli  3   5 Michael R Barnes  1   6 Borbala Mifsud  1   7 Helen R Warren  1   6 Caroline Hayward  8 Jonathan Marten  8 James J Cranley  1 Maria Pina Concas  9 Paolo Gasparini  9   10 Thibaud Boutin  8 Ivana Kolcic  11 Ozren Polasek  11   12   13 Igor Rudan  14 Nathalia M Araujo  15 Maria Fernanda Lima-Costa  16 Antonio Luiz P Ribeiro  17 Renan P Souza  15 Eduardo Tarazona-Santos  15 Vilmantas Giedraitis  18 Erik Ingelsson  19   20   21   22 Anubha Mahajan  23 Andrew P Morris  23   24   25 Fabiola Del Greco M  26 Luisa Foco  26 Martin Gögele  26 Andrew A Hicks  26 James P Cook  24 Lars Lind  27 Cecilia M Lindgren  28   29   30 Johan Sundström  31 Christopher P Nelson  32   33 Muhammad B Riaz  32   33 Nilesh J Samani  32   33 Gianfranco Sinagra  34 Sheila Ulivi  9 Mika Kähönen  35   36 Pashupati P Mishra  37   38 Nina Mononen  37   38 Kjell Nikus  39   40 Mark J Caulfield  1   6 Anna Dominiczak  41 Sandosh Padmanabhan  41   42 May E Montasser  43   44 Jeff R O'Connell  43   44 Kathleen Ryan  43   44 Alan R Shuldiner  43   44 Stefanie Aeschbacher  45 David Conen  45   46 Lorenz Risch  47   48   49 Sébastien Thériault  46   50 Nina Hutri-Kähönen  51   52 Terho Lehtimäki  37   38 Leo-Pekka Lyytikäinen  37   38   39 Olli T Raitakari  53   54   55 Catriona L K Barnes  14 Harry Campbell  14 Peter K Joshi  14 James F Wilson  8   14 Aaron Isaacs  56 Jan A Kors  57 Cornelia M van Duijn  58 Paul L Huang  2 Vilmundur Gudnason  59   60 Tamara B Harris  61 Lenore J Launer  61 Albert V Smith  59   62 Erwin P Bottinger  63 Ruth J F Loos  63   64 Girish N Nadkarni  63 Michael H Preuss  63 Adolfo Correa  65 Hao Mei  66 James Wilson  67 Thomas Meitinger  68   69   70 Martina Müller-Nurasyid  68   71   72   73 Annette Peters  68   74   75 Melanie Waldenberger  68   75   76 Massimo Mangino  77   78 Timothy D Spector  77 Michiel Rienstra  5 Yordi J van de Vegte  5 Pim van der Harst  5 Niek Verweij  5   79 Stefan Kääb  68   73 Katharina Schramm  68   71   73 Moritz F Sinner  68   73 Konstantin Strauch  71   72 Michael J Cutler  80 Diane Fatkin  81   82   83 Barry London  84 Morten Olesen  85   86 Dan M Roden  87 M Benjamin Shoemaker  88 J Gustav Smith  89 Mary L Biggs  90   91 Joshua C Bis  90 Jennifer A Brody  90 Bruce M Psaty  90   92   93 Kenneth Rice  91 Nona Sotoodehnia  90   92   94 Alessandro De Grandi  26 Christian Fuchsberger  26 Cristian Pattaro  26 Peter P Pramstaller  26 Ian Ford  95 J Wouter Jukema  96   97 Peter W Macfarlane  98 Stella Trompet  99 Marcus Dörr  100   101 Stephan B Felix  100   101 Uwe Völker  100   102 Stefan Weiss  100   102 Aki S Havulinna  103   104 Antti Jula  103 Katri Sääksjärvi  103 Veikko Salomaa  103 Xiuqing Guo  105 Susan R Heckbert  106 Henry J Lin  105 Jerome I Rotter  105 Kent D Taylor  105 Jie Yao  107 Renée de Mutsert  108 Arie C Maan  96 Dennis O Mook-Kanamori  108   109 Raymond Noordam  99 Francesco Cucca  110 Jun Ding  111 Edward G Lakatta  112 Yong Qian  111 Kirill V Tarasov  112 Daniel Levy  113   114 Honghuang Lin  114   115 Christopher H Newton-Cheh  3   116 Kathryn L Lunetta  114   117 Alison D Murray  118 David J Porteous  119   120 Blair H Smith  121 Bruno H Stricker  122 André Uitterlinden  123 Marten E van den Berg  122 Jeffrey Haessler  124 Rebecca D Jackson  125 Charles Kooperberg  124 Ulrike Peters  124 Alexander P Reiner  124   92 Eric A Whitsel  126 Alvaro Alonso  127 Dan E Arking  128 Eric Boerwinkle  129 Georg B Ehret  130 Elsayed Z Soliman  131 Christy L Avery  132   133 Stephanie M Gogarten  91 Kathleen F Kerr  91 Cathy C Laurie  91 Amanda A Seyerle  134 Adrienne Stilp  91 Solmaz Assa  5 M Abdullah Said  5 M Yldau van der Ende  5 Pier D Lambiase  135   136 Michele Orini  135   137 Julia Ramirez  1   136 Stefan Van Duijvenboden  1   136 David O Arnar  4   60   138 Daniel F Gudbjartsson  4   139 Hilma Holm  4 Patrick Sulem  4 Gudmar Thorleifsson  4 Rosa B Thorolfsdottir  4   60 Unnur Thorsteinsdottir  4   60 Emelia J Benjamin  114   140   141 Andrew Tinker  1   6 Kari Stefansson  4   60 Patrick T Ellinor  2   3   142 Yalda Jamshidi  143 Steven A Lubitz  144   145   146 Patricia B Munroe  147   148
Affiliations
Meta-Analysis

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction

Ioanna Ntalla et al. Nat Commun. .

Abstract

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

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Conflict of interest statement

I.N. became a full-time employee of Gilead Sciences Ltd following submission of the manuscript. S.A.L. receives sponsored research support from Bristol Myers Squibb/Pfizer, Bayer AG, and Boehringer Ingelheim, and has consulted for Bristol Myers Squibb/Pfizer and Bayer AG. P.T.E. is supported by a grant from Bayer AG to the Broad Institute focused on the genetics and therapeutics of cardiovascular diseases. P.T.E. has also served on advisory boards or consulted for Bayer AG, Quest Diagnostics, and Novartis. M.J.C. is Chief Scientist for Genomics England, a UK Government company. B.M.P. serves on the DSMB of a clinical trial funded by Zoll LifeCor and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. V.S. has participated in a conference trip sponsored by Novo Nordisk and received a modest honorarium for participating in an advisory board meeting. K.S., H.H., P.S., G.S., G.T., R.B.T., U.T., D.O.A., D.F.G. are employed by deCODE genetics/Amgen Inc. E.I. is employed by GlaxoSmithKline. A.M. is employed by Genentech Inc.

Figures

Fig. 1
Fig. 1. Overview of the study design.
An overview of contributing studies, single-stage discovery approach, and downstream bioinformatics and in silico annotations performed to link variants to genes, and polygenic risk score analysis to link variants to cardiovascular disease risk is illustrated. Asterisk (*) The multi-ancestry meta-analysis is our primary analysis. Previously not reported loci were identified from the multi-ancestry meta-analysis. Ancestry specific and chromosome X meta-analysis are secondary. Hash (#) For bioinformatics and in silico annotations we also included loci that reached genome-wide significance in European only meta-analysis (N = 8) and were borderline genome-wide significant in the multi-ancestry meta-analysis.
Fig. 2
Fig. 2. Manhattan plot of the multi-ancestry meta-analysis for PR interval.
P values are plotted on the -log10 scale for all variants present in at least 60% of the maximum sample size from the fixed-effects meta-analysis of 293,051 individuals from multiple ancestries (multi-ancestry meta-analysis). Associations of genome-wide significant (P < 5 × 10−8) variants at previously not reported (N = 141) and previously reported loci (N = 61) are plotted in dark and light blue colors respectively.
Fig. 3
Fig. 3. Plausible candidate genes of PR interval from S-PrediXcan.
Diagram of standard electrocardiographic intervals and the heart. The electrocardiographic features are illustratively aligned with the corresponding cardiac conduction system structures (orange) reflected on the tracing. The PR interval (labeled) indicates conduction through the atria, atrioventricular node, His bundle, and Purkinje fibers. Right: Supplementary Data 14 shows 113 genes whose expression in the left ventricle (N = 233) or right atrial appendage (N = 231) was associated with PR interval duration in a transcriptome-wide analysis using S-PrediXcan and GTEx v7. Displayed genes include those with significant associations after Bonferroni correction for all tested genes (P < 3.1 × 10−6). Longer PR intervals were associated with increased predicted expression of 56 genes (blue) and reduced expression of 57 genes (orange).
Fig. 4
Fig. 4. Bubble plot of phenome-wide association analysis of European ancestry PR interval polygenic risk score.
The polygenic risk score was derived from the European ancestry meta-analysis. Orange circles indicate that polygenic predisposition to longer PR interval is associated with an increased risk of the condition, whereas blue circles indicate that polygenic predisposition to longer PR interval is associated with lower risk of the condition. The darkness of the color reflects the effect size (odds ratio, OR) per 1 standard deviation (s.d.) increment of the polygenic risk score from logistic regression. Sample size (N) in each regression model is provided under X-axis. Given correlation between traits, we set significance threshold at P < 3.13 × 10−3 after Bonferroni correction (P < 0.05/16; dotted line) for the analysis and also report nominal associations (P < 0.05; dashed line).
Fig. 5
Fig. 5. Candidate genes in PR interval loci encoding proteins involved in cardiac muscle cytoskeleton.
Candidate genes or encoded proteins are indicated by a star symbol in the figure and are listed in Supplementary Data 3. More information about the genes is provided in Supplementary Data 18 and 19. This figure was created with BioRender. *Previously not reported locus, # genome-wide significant locus in transformed trait meta-analysis. 1Missense variant; 2Nearest gene to the lead variant; 3Gene within the region (r2 > 0.5); 4Variant(s) in the locus are associated with gene expression in left ventricle and/or right atrial appendage; 5Left ventricle best HiC locus interactor (RegulomeDB score ≤ 2); 6Animal model; 7Monogenic disease with a cardiovascular phenotype.

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