© 2014 Nature America, Inc. All rights reserved. A A full list of authors and affiliations appears at the end further of the paper. and phenotypes, human other on or eQTLs) as tissues (acting various in expression gene on effects interval– have QT SNPs associated whether determined LQTS, elusive genetically 33,316 with to probands in up analysis in mutational completed genotyping individuals, additional targeted with ancestry European of performed an expanded meta challenging. more QT been has population general the in underlying variation genes causal the of Identification elusive. genetically remaining ~20% and LQT4–LQT13 to due cases of <5% in mutations from stemming cases LQTS of 75% with reported, been have genes susceptibility LQTS 13 in mutations rare of far, hundreds Thus loci. value of both approaches and the overlap of common and rare variant boring QT GWASand LQTS of mendelian with of families studies linkage wide QTGEN QTSCD the including sizes sample large in (GWAS) studies and gene genome candidate through detected been QT in ms/allele) (~1–4 increments modest (ref. 30–40% of estimates heritability with ms), 460 to 380 from (ranging distributed normally is interval QT continuous in variation viduals, or channels channel ion encoding genes in ms) >~20–100 of mutation per tions of strong effect (increase or decrease, respectively, in QT interval LQTS and Mendelian short therapy. medication of effect side a as arrhythmia fatal and risk SCD of increased of and respectively, repolarization, myocardial ated electro­ the on interval QT are non (ECG) cardiogram the of shortening and Prolongation new proteins. requiring loci highlight we mendelian risk The calcium signaling pathways in myocardial repolarization Genetic association study of QT interval highlights role for Nature Ge Nature Received 10 June 2013; accepted 29 May 2014; published online 22 June 2014; Here GWASthe QT Interval–International (QT Consortium genome both in independently discovered been have loci Several

- identified

interval duration in unselected populations, including those har those including populations, duration in unselected interval factor

QT 2 in insights ). Common genetic variants that are associated individually with

KCNQ1 298

- 4 interval, interacting proteins. In unselected community unselected In proteins. interacting consortia, as well as others as well as consortia,

Our the validation.

n

for long-QT unrelated etics

KCNQ1

into

importance

35 , integration ventricular KCNH2

common an

cardiac ADVANCE ONLINE PUBLICATION ONLINE ADVANCE

electrocardiographic (LQT1), (LQT1), syndrome

Several probands , SCN5A

- of - electrophysiology of

arrhythmias invasive markers of delayed and acceler and of delayed markers invasive variant QT syndrome QT (SQTS) syndrome -

analysis analysis of GWAS in 76,061 individuals calcium

common newly KCNH2 ,

(LQTS). KCNE1

with

loci 5–

identified 9

(LQT2) and and (LQT2) LQTS regulation .

and variant

associated

and Using

measure - KCNJ2

interval duration have have duration interval identified sudden

and

a association, loci

1 genome-wide in -

stem from muta identifies , highlighting the wide association association wide

SCN5A

with

encode

myocardial

reflecting cardiac

- coding based indi based

QT (LQT3), (LQT3), - interval interval

expression proteins new

interval - death 3 IGC) IGC)

and and

variants

myocardial

association repolarization.

candidate ­ ­ ­ ­ -

(SCD) doi:10.1038/ng.301

that that typing in as many as 31,962 individuals of European ancestry ancestry European of individuals 31,962 as ( many as geno in replication typing targeted for independ 35 selected was top locus) the per of (1 set SNPs ent a First, replication. of forms two for Tables 1 Tables ( individuals 1,354 in genotyped and (Metabochip) ( interval QT ( SNPs pruned 2 Table interval QT in variation low of excess the ate of incorporation replication genotyping) did attenu not significantly SNP at tinel genome Fig. 1a Supplementary modest overdispersion only of the test statistics given the sample size observed ( and individuals 76,061 meta from results GWAS variance–weighted inverse performed We ( SNPs model imputed genetic or additive an under genotyped directly million 2.5 for with tested was association ancestry genetic of components principal and rate) QT QT or use pacemaker electronic delay,available, when and, conduction or intraventricular in shown block branch are bundle ms, 120 than greater duration QRS GWAS fibrillation, 1 stage the Table 1 to Supplementary contributed who ancestry of characteristics Clinical 31 study cohorts of individuals of European GWAS RESULTS protein using genes analyses. interaction interval–associated QT annotated Supplementary Table 1 Supplementary

not and In an interim meta interim an In -

interval duration adjusted for age, sex, RR interval (inverse heart heart (inverse for adjusted duration age, RR sex, interval interval collectively physically and

repolarization, found

and genes orthogonal

identifies . eod a e o ~,0 lnae ieulbim (LD) disequilibrium linkage ~5,000 of set a Second, ). ,

4 4 could

Rare replication and

in P for

r

5 ≤

controls interact

2 4 indicate

variant

0.015) was included in a custom genotyping array array genotyping custom a in included was 0.015) > 0.2) with nominal evidence of association with with association of evidence nominal with 0.2) > explain , and and , ventricular

22 protein-protein - wide significant loci (some identified only after identified (some loci significant wide P

-

new is analysis of GWAS results, SNPs were selected selected were SNPs GWAS of results, analysis values, consistent with a polygenic model of of model polygenic a with consistent values,

Supplementary Note Supplementary ). ). Exclusion of SNPs 500 within kb of the sen study - 1

. All studies excluded individuals with atrial atrial with individuals excluded studies All .

altering medication use. In each cohort, cohort, each In use. medication altering analysis a with

) on a variety of platforms ( of platforms ) on a variety 0

but the ~8– (

heritable

λ loci GC

of presence

arrhythmias, in 1 other 0% = 1.069; 1.069; =

uncertain for up

of Supplementary Tables 2 2 Tables Supplementary

of

to

QT

interaction 6 recognized trait.

1 QT-interval new

of 00,000 interval Supplementary Fig. 1b Fig. Supplementary

the QT

causality

QT LQTS ) 1

1 potentially prolongation

. Meta .

interval–associated

individuals,

screens repolarization s e l c i t r A

and

- variation analysis on the the on analysis Supplementary Supplementary Supplementary Supplementary

and -

analysis of all all of analysis SCD. λ

provides GC therefore

lethal - = 1.076;

protein protein and

is and

a ).

3

). ).  ­ ­ ­ ­ -

© 2014 Nature America, Inc. All rights reserved. rate and QT interval. QT and rate heart on SNPs the of effects pleiotropic independent favor findings with additional adjustment for RR between we found no evidence that QT associations interval–SNP were altered established well been (binomial rate heart and has interval QT that relationship inverse the SNPs interval–associated ( QT for effects rate heart and rate) heart QT of association of source QT of the as rate heart for adjustment inadequate ( including loci, 4 at SNPs 5 for rate heart with association significant found we ined, Indian or European of loci in a GWASinterval–associated of heart rate in 92,355 individuals ( QT interval of unadjusted rate is a determinant heart strong Because Variants populations. ancestral both in interval QT with associated are variants common of majority a that hypothesis ( 9 correlated Table Supplementary highly were effects and and African QT in The as direction of effect for the SNP direction was concordant between European same the in ( QT with interval associated were significantly loci nine at SNPs ten size, sample smaller to due power limited the Despite MAF). frequency, allele minor low to owing imputed poorly of African ancestry in the CARe We examined the association of 67 of these SNPs in 13,105 individuals Association 2 Fig. the SNPs, with a total of 68 SNPs independent on at 35 loci ( signals independent multiple basis of having low LD of ( evidence had loci Many SNP at mately ( a the most significant locus for were Some genotyping SNPsreplication selected not initially ulti reported previously ( nificant ( als individu up in to 103,331 results GWAS genotyping replication and dependent on direct replication genotyping. was poorly imputed in GWAS results and largely locus is not labeled, as the low-frequency variant wide significance ( dashed line represents the threshold for genome- causal gene at any given locus is unknown. The Nearest genes are used for annotation, but the previously reported (small font, blue peaks) loci. annotated for new (large font, red peaks) and upon meta-analysis with replication data are purposes). Loci meeting association (results are truncated at European ancestry across 22 autosomes of QT-interval GWAS in 76,198 individuals of meta-analysis from results are association Shown GWAS meta-analysis, annotated with gene names. 1 Figure s e l c i t r A  r r P 2 2 < 0.0007 = 0.05/68; 0.05/68; = 0.0007 < = 0.16). The effects on = rate The heart effects 0.16). of only 38 of the 68 SNPs showed ~0.5–0.8), we examined the 68 independent SNPs at the 35 QT QT 35 the at SNPs independent 68 the examined we ~0.5–0.8), Supplementary Note Supplementary , , - - interval effects (in models adjusting for RR interval, inverse inverse interval, RR for adjusting models (in effects interval Supplementary Table 8a Supplementary interval variants with heart rate was the modest correlation correlation modest the was rate heart with variants interval

Genome-wide association results for for results association Genome-wide

P with < 5 × 10 × 5 < -

ancestry samples for 51 of 67 SNPs (binomial of

additional QT-interval P PLN < 5 × 10 3– −8 5 , , ) loci, of which 22 were new and 13 have been been have 13 and new were 22 which of loci, ) P , 9 FEN1-FADS2 - = 1 × 10 ( r Supplementary Table 10 Table Supplementary Asian ancestry Asian 2 Fig. Fig. ). These findings are consistent with the the with consistent are findings These ). < 0.05) with other genome ) identified a total of 35 genome 35 of total a identified )

−8 non-QT

SNPs ). The 1 , , Table - −25 COGENT Consortium COGENT and and P

2 in < 5 × 10 - , RR KCNE1 for display G ( IGC

effects individuals

, , Supplementary Note Supplementary P 1 ATP2A2 3 and = 0.20). In ARIC ( In ARIC 0.20). = 1 , RR 3 r

. Among the 35 loci exam loci 35 the Among . = 0.60, 0.60, = upeetr Tbe 9 Table Supplementary

−8 Supplementary Table 7 Supplementary 1/2 Supplementary Supplementary Table 6

or RR and and P

of < 0.0007 = 0.05/67) = < 0.05/67) 0.0007 ). Arguing against against Arguing ).

African –log10 P value SCN5A P 10 15 20 1/3 - Supplementary Supplementary 1 5 wide wide significant 9 10 × 9 = . In total, these RNF207 TCEA3 1 P 2 (1 SNP was = 5 × 10 n -

- = 8,524), 8,524), = ). ancestry wide sig wide 1 SCN10A NOS1AP ATP1B1 SLC8A1 TT CCDC141 SPATS2L −10 −5

2 N SP3 ). ). ). ). ). ). ), ­ ­ ­ ­ - ;

- QT interval–associated SNPs, 15 at 8 loci were significantly associ significantly were loci 8 at 15 SNPs, interval–associated QT ventricles cardiac the in propagation impulse electrical ( duration QRS GWAS of published a in ( block branch bundle or duration QRS prolonged with individuals of myocardial repolarization and QT prolongation, hence, our exclusion at those loci. at those are SNP top the high with correlated highly SNPs missense significant ( vals Table 8b ( nonsynonymous. was SNP correlated SNP index highly the a or which in loci 5 were there loci, 35 at SNPs nificant genome total 68 the Among ancestry). WesternEuropean and Northern of residents Utah using (CEU, data loci Project Genomes 1000 interval–associated QT among variants coding pres of the ence investigated we causal, be to potential increased an have structure protein in for changes code that variants common Because Functional tissues. different in variation genetic same of the effects (pleiotropic) point to new repolarization mechanisms or simply reflect independent phosphatase alkaline and of assessment model homeostasis and lesterol, triglycerides of menarche with QT our of associations tional ( database GWAS (NHGRI) hold. not does duration QRS and interval QT on effects SNP type–specific effects and that a consistent general relationshipcell involve between many shared, be may SNPs some for relationships QRS SNP the underlying mechanisms electrophysiological fundamental the although that, suggest findings these Collectively, ( sizes of relation effect discordant (37 effects versus 31; binomial of versus excess concordant Across SNPs, all was no there significant showed effects concordant ( with positively associated QRS duration. However, genetic significant it is perhaps not surprising that some QT QRS Because duration is a of subinterval the QT on interval the ECG, ( duration QRS with ated C3orf75 SCN5A-SCN10A Supplementary Note Supplementary 3 SLC4A4 QRS QRS prolongation due to bundle branch block can result in delayed Examination of the National Human Genome Research Institute Institute Research Genome Human National the of Examination - r Supplementary Fig. 2 Fig. Supplementary roiy addts o nele h QT the underlie to candidates priority 2

> 0.8) at 4 SMARCAD1 ). Whereas most loci had multiple genes in associated inter in associated genes multiple had loci most ). Whereas SLC35F1-PL GFRA3

1

annotation 5 6 GMPR and at SCN5A a

DVANCE ONLINE PUBLICATION ONLINE DVANCE 6 N CAV Chromosom 1 FEN1 7 NCOA2

7 KCNH2 1 , , n ). We examined QT interval–associated SNPs interval–associated QT We ). examined - r SCN10A 2

= 0.03, - of P 2 3 3 fatty acids

- 8 0 LAPTM4B < 0.0007) ( 0.0007) <

FADS2 ( n associated AZIN1 ), the genes that harbored genome harbored that genes the ), Supplementary Note Supplementary = 6) as well as discordant ( Supplementary Table 11 Table Supplementary e - 9 interval SNPs (or their close proxies proxies close their (or SNPs interval GBF with PR interval P

= 0.18; 10 with high KCNQ1 1 FEN1-FADS2

1 11 Supplementary Table 10 Supplementary 8 β , , fasting plasma levels glucose

variants - cell function (HOMA function cell APT2A2 prolonging variants are also n P

Supplementary Table 10 Supplementary 12 = 40,407), which reflects reflects which 40,407), = = 0.27) or cor significant KLF12 ANKRD9 -

density lipoprotein cho 13 CREBBP USP50- TRPM7 -

interval association association interval

1 14 MKL2 5 Nature Ge Nature LITAF , , at ) identified addi identified )

15 CNOT1 Supplementary Supplementary MKL2

- 16 QT and SNP and QT LIG3 ), which may may which ), n

1 17 = 9) effects. 4

. Of the 68 68 the Of . 18 - PRKCA KCNJ2 wide sig wide

with age 19

n 20 etics - - wide wide B) 21 ) 7

, 22 1 1 4 9 ). ). ­ ­ ­ ­ ­ ­ ­ - , .

© 2014 Nature America, Inc. All rights reserved. of association( different fromthenearestgenelisted.Lociatwhich aSNP(indexorsecondary)closeproxy( Interactors fromimmunoprecipitation(IP)experiments areshownfrommousecardiactissueusingfivebaits(K1, KCNQ1;K2,KCNH2;CV, CAV3; CA,CACNA1C;S1,SNTA1) withproteinidentifiedinparentheses if in leftventricleforthesentinelSNP).Protein-protein interactor(PPI)relationshipsfornearbygenestoinlocipreviously establishedtoinfluencemyocardialrepolarizationareprovided ( proxy with1.0> For agivenSNP, theeffectivesamplesizeissumofproduct ofthecohort-specificsamplesizeandimputation quality(rangingfrom0to1).Functionshownforcodingvariantswith Common geneticvariantsatlociassociatedwithQT interval( PRKCA MKL2 CREBBP USP50-TRPM7 ANKRD9 KLF12 ATP2A2 FEN1-FADS2 GBF1 AZIN1 LAPTM4B NCOA2 CAV1 GMPR GFRA3 SMARCAD1 SLC4A4 C3ORF75 SPATS2L TTN-CCDC141 SP3 TCEA3 New loci KCNE1 KCNJ2 LIG3 CNOT1 LITAF KCNQ1 KCNH2 SLC35F1-PLN SCN5A-SCN10A SLC8A1 ATP1B1 NOS1AP RNF207 Previously discoveredloci Nearest gene T Nature Ge Nature able able 1 c S ommon ommon genetic variants at loci associated with Q upplementary r n 2 >0.8(-p)tothesentinelSNP. eQTLtranscriptsareshownifassociated at etics rs11153730 rs6793245 rs12997023 rs10919070 rs12143842 rs846111 rs9892651 rs246185 rs1296720 rs3105593 rs2273905 rs728926 rs3026445 rs174583 rs2485376 rs1961102 rs11779860 rs16936870 rs9920 rs7765828 rs10040989 rs3857067 rs2363719 rs17784882 rs295140 rs7561149 rs938291 rs2298632 rs1805128 rs1396515 rs1052536 rs246196 rs735951 rs7122937 rs2072413 SNP

T able 8a ADVANCE ONLINE PUBLICATION ONLINE ADVANCE 17q24 16p13.12 16p13.3 15q21 14q32 13q22 12q24 11q12 10q24 8q22.3 8q22.1 8q13 7q31 6p22 5q31 4q22 4q13 3p21 2q33 2q31.2 2q31.1 1p36 21q22 17q24 17q12 16q21 16p13 11p15 7q36 6q22 3p22 2p22 1q24 1q23 1p36 ). SE,standarderror. Chr. 61,366,326 104,039,996 104,002,021 98,919,506 71,351,896 115,987,328 16,402,701 137,601,624 95,245,457 72,357,080 47,519,007 200,868,944 179,398,101 174,450,854 23,583,062 34,743,550 65,942,588 30,355,688 57,131,754 11,601,037 2,443,126 150,278,902 118,774,215 38,574,041 40,606,486 167,365,661 160,300,514 6,201,957 61,734,255 14,302,933 3,813,643 48,632,310 102,044,752 73,411,123 109,207,586 Position (hg18) P <5×10

noncoded Coded/ allele A/G G/C A/G A/G G/C C/G A/G A/G C/G C/A A/C C/A C/T C/T T/C T/C T/C C/T T/C T/C C/T A/T C/T A/T T/C C/T T/C T/C C/T C/T T/C T/C T/C C/T T/C −8 ) onmeta-analysisofGWAS andreplicationresults(

frequency

Coded allele 0.43 0.34 0.20 0.45 0.35 0.36 0.36 0.34 0.39 0.33 0.47 0.10 0.09 0.40 0.13 0.46 0.11 0.40 0.42 0.42 0.39 0.50 0.01 0.52 0.53 0.26 0.46 0.19 0.27 0.50 0.32 0.05 0.13 0.24 0.28

100,900 102,060 101,382 103,331 101,902 20,061 77,058 75,961 76,513 62,994 72,978 65,331 74,932 73,697 70,311 75,707 75,053 47,041 74,683 77,411 59,812 77,240 83,532 69,219 95,768 70,552 82,677 73,404 74,196 93,262 87,942 70,821 76,184 85,299 83,031 T P <5×10 interval n r 2 >0.8)fallsinaleftventricularenhanceraremarked withIorS.Parenthesesindicateannotationsforsecondary signals –0.98 (0.09) –1.73 (0.11) –1.15 (0.10) –1.68 (0.11) –1.65 (0.10) –1.12 (0.10) –1.69 (0.22) –1.68 (0.14) –0.74 (0.10) –0.57 (0.09) –0.56 (0.10) –0.61 (0.10) –0.85 (0.13) –0.51 (0.08) –0.54 (0.10) –0.52 (0.09) −8 7.42 (0.85) 0.98 (0.10) 1.93 (0.12) 3.50 (0.11) 1.73 (0.13) 0.72 (0.10) 0.83 (0.13) 0.66 (0.10) 0.61 (0.09) 0.57 (0.10) 0.62 (0.09) 0.57 (0.10) 0.99 (0.16) 0.79 (0.14) 0.55 (0.09) 0.97 (0.16) 0.57 (0.09) 0.53 (0.09) 0.70 (0.09) withsentinelSNPsortheircloseproxies( Effect in ms (SE)

2 ×10 2 ×10 6 ×10 2 ×10 2 ×10 1 ×10 1 ×10 2 ×10 4 ×10 5 ×10 1 ×10 1 ×10 7 ×10 3 ×10 3 ×10 4 ×10 3 ×10 4 ×10 2 ×10 3 ×10 8 ×10 3 ×10 3 ×10 2 ×10 1 ×10 3 ×10 3 ×10 5 ×10 1 ×10 8 ×10 3 ×10 2 ×10 7 ×10 6 ×10 1 ×10 S upplementary P −18 −25 −25 −57 −28 −54 −49 −67 −27 −14 −31 –213 –40 −14 −13 −10 −12 −11 −8 −12 −11 −8 −9 −10 −9 −8 −10 −11 −9 −10 −8 −11 −9 −10 −14 LQT7, LQT1, LQT2, SQT3 SQT2 SQT1 LQT5 LQT3 LQTS locus gene T able 7

Function ). Intron 3 D85N 3 Intron Intron Intron Intron Intron G603A Intron Intron 5 Intron Intron Intron Intron Intron (F256I-p) Intron Intron Intron Intron r 2 ′ ′ ′ n UTR UTR UTR >0.8; istheeffectivenumberofsamplescontributingto thesignal. S FADS3 FADS2 FADS1 SPATS2L CCT6B LIG3 CNOT1 NDRG4 LITAF TSPAN32 PHEMX C11ORF21 NME7 ATP1B1 PRKCA ANKRD9 KLF12 C12ORF24 ARPC3 GPN3 VPS29 ATXN1 FAM13B SETD2 SCAP PTPN23 KLHL18 TCEA3 upplementary transcript eQTL , , , ,

, ,

, , , , , ,

, CAV2-ATP1B1 CAV-ATP1B1, SGOL2-SCN5A KCNQ1, KCNH2 KCNE1, KCNE1 SCN5A-SNTA1 ANK2, CAV3 KCNE1 CACNA1C, PLN ATXN1-KCNAB2 ATXN1-ACOT7, ETF1-RPL22 KCNH2 T PPI interactor able 12 QT loci known ; inboldiftheeQTLwasfound

r 2 s e l c i t r A =1tosentinelSNPor S upplementary

UNC45B-CV UNC45B-K1, GOT2-K1 GOT2-CV, PLN-CA PLN-CV, ATP1B1-CV ATP1B1-CA, ATP1B1-K2, ATP1B1-K1, CV-TRAP1 ATP2A2-CA ATP2A2-CV, ACTR1A-CV CAV2-CV CAV1-CV, CAV1-S1, CAV1-CA, MYL3-CA TTN-CV CV, TTN-K2, CCDC141- interactor IP

T able 17 enhancer I,S I,S I,S LV S S S S S S I I I I I I I I I I I I I I ).

 © 2014 Nature America, Inc. All rights reserved. enhancer elements enhancer marked by combinations of histone modifications Program Epigenomics Roadmap (NIH) Health of Institutes National US the from available data examined we enhancers, of modulation through act may sion high thus QT the by modulated plausibly is which of expression the genes several highlight findings In these not sum, shown). (data results the not did status alter failure heart for terms interaction of Inclusion eQTLs. eight these for effect nine SNP SNP associations became non adjustment for the best eQTL SNP for a given associations; transcript, ­transcript the QT ( testing multiple for ­correction after transcripts), two with associated SNP was (one transcripts nine of one with associated significantly were loci eight at SNPs nine ure, SNP. each of Mb 1 within genes all of genome from imputed well were that SNPs interval–associated QT 68 the of 63 examined ( ( failure heart for transplanted of individuals hearts the from samples included col lection This Consortium. MAGNet the in samples biopsy ventricular of association the QT examined we manner, type–specific cell a in so ( expression mouse and human of atlas an in type cell or tissue specific a implicated that loci interval–associated QT the among eQTLs of signature significant a We genes. of multiple expression not the did observe with associated were loci signal, some However, variation. association regulatory through repolarization presumably the of source potential a as loci LIG3 including loci at gene nearest the of expression with associated were SNPs interval–associated QT ( SNP correlation high with tissues, ( more or one in gene one least at of expression variable the with associated were loci interval–associated Twelve QT tissues. diverse from sets data eQTL available publicly in examined the index SNPs or proxies ( QT-interval SNP T s e l c i t r A  4 lysine at H3 histone of monomethylation of presence (specifically, rs246196 rs735951 rs728926 rs17457880 rs17457880 rs9892651 rs3026445 rs174583 rs295140 show attenuationofassociationinconditionalmodelsandcomparablestrengthwithQTinterval forboththeQTSNPandbesteQTLwhenavailable. association withtranscriptisshownandwithoutadjustmentforthebesteQTLSNPthattranscript.QT SNPs andtranscriptsareshowninboldiftheQTSNPbesteQTLhighlycorrelated( Shown areQT-interval SNPsassociatedwithexpressionofatranscriptwithin1Mbatexperiment-widesignificance ( r n able able 2

2 = 136) that were ultimately not used ( used not ultimately were that 136) = aty bcue eei vrain ht nlecs ee expres gene influences that variation genetic because Lastly, fail heart of presence and site study sex, age, for adjusting After do may expression gene influence that variants genetic Because we expression, gene influence may variants noncoding Because > 0.8) between the top QT interval–associated SNP and the top eQTL - interval SNPs with gene expression in a collection of 313 left left 313 of collection a in expression gene with SNPs interval and Table

Association Association of Q - - TCEA3 transcript associations, consistent with a potentially causal causal with consistent a potentially associations, transcript priority targets for further experimental work. experimental further for targets priority 1 , , Chr. 16 16 13 17 12 11

Supplementary Table 12 Supplementary 1 1 2 . . The eQTL data help point genes at to specific these n = 177) or healthy hearts from potential donors donors potential from hearts healthy or 177) = 160,434,778 160,434,778 109,207,586 200,868,944 - 57,131,754 11,601,037 73,411,123 61,734,255 61,366,326 interval SNP (or a correlated variant) and are are and variant) correlated a (or SNP interval 2 - Position 2 wide genotyping in relation to to relation in genotyping wide P . We specifically focused on transcriptional transcriptional on focused We . specifically Table T > 0.01; 0.01; > -interval -interval - significant significant (all ANKRD9 2 and and Supplementary Note Supplementary P < 4.4 × 10 × 4.4 < S Transcript LITAF SETD6 KLF12 SPATS2L FCGR3A FCGR2B PRKCA VPS29 FADS2 r NPs NPs with gene expression in human left ventricle 2 upeetr Note Supplementary > 0.8) at the 68 SNPs in 35 loci and and , , Supplementary Note Supplementary ATP1B1 P Supplementary Note Supplementary rs7187498 rs42945 rs1886512 rs6606686 rs295113 rs9727076 rs17457880 rs11658550 rs174548

−5 ≥ transcript SNP for 0.01) for eight of the = 0.05/1,146 SNP 0.05/1,146 = eQTL Best , , CNOT1

cis ) 2 1 and eQTL SNP expression expression . r

2 QT SNP , , between - Same 0.30 0.93 0.93 0.53 0.97 0.86 0.80 ). After After ). FADS1 interval 0 ). We ).

). ). ­ ­ ­ - ,

QT-increasing of eQTLSNP effect for Direction Increase Increase Increase Increase Increase Increase Increase Decrease Decrease lead QT interval–associated SNPs or highly correlated variants variants 68 lead (or correlated) SNPs, 34 correlated overlapped a left ventricular enhancer, highly or ( SNPs interval–associated expression QT gene lead affect can and regions with complex traits preferentially reside in these noncoding regulatory that indicates variants associated as evidence emerging (H3K4me3)), 4 lysine at H3 histone of trimethylation of absence and (H3K4me1) 5 10 × (5 ( contraction’ heart of force the of ‘regulation including processes, calcium in involved specifically are ( annotations set gene Ingenuity and Panther (KEGG), Genomes and of Genes Kyoto the Encyclopedia (GO), Ontology Gene using whole pathways in QT of specific follow experimental for prioritized be can that loci interval–associated QT at SNPs noncoding specific 3 Fig. ( SNPs matched of sets sampled randomly with than proportion greater substantially a ent signals of association at the 35 loci described here. described loci 35 at the association of signals ent to identify additional QT continue to likely are studies Larger SNPs. individual identifying for we a set variance, stringent overall than explaining rather loci specific of associations fide bona identifying on focused genome contemporary on was captured SNPs autosomal interval common QT by in explained variation) heritable of (>50% ( variance overall variance of 7.6–9.9% 15 Tables explained loci 35 SNPs the independent at 68 all whereas 5.5–7.0%, to explained variance rate heart and of sex age, of 3–6% effects for accounting after explained interval, QT in consortia variation QTSCD and QTGEN the from loci The common variants at the 12 previously published common variant Population ( mice knockout Note in Supplementary phenotype cardiac a having on for QT enriched Three GO were terms involving ‘ion transport’ significantly wide SNPs to calculate ( statistical significance genome selected randomly to SNPs interval–associated QT 68 the matched we which in analysis secondary a by confirmed were nals 14 Table Supplementary allele Supplementary Note Supplementary r 2 We also examined the association results for over for results association the examined Wealso S > 0.8) overlapped enhancers in adult left ventricular tissue. Of Of tissue. ventricular left adult in enhancers overlapped 0.8) > upplementary Note

- and and interval associations ( associations interval - −4 wide genotyping arrays genotyping wide 3

association 4×10 and Transcript

, ad clua clim o hmotss ( × 10 × (1 homeostasis’ ion calcium ‘cellular and ) 2 ×10 4 ×10 4 ×10 1 ×10 8 ×10 1 ×10 1 ×10 6 ×10 SNP ( 4

. The top SNPs at the additional new loci increased the the increased loci new additional the at SNPs top The . of QT variation upeetr Note Supplementary 16 P ). Foreachtranscript,thebesteQTLSNPforthattranscriptisshown.TheQT −13 a −41 −7 −5 −6 −7 −7 −5 −8

) DVANCE ONLINE PUBLICATION ONLINE DVANCE ). A recent heritability analysis found that 21% of of 21% that found analysis heritability recent A ).

z SNP withadjust score = 9.45, 9.45, = score sociation ofQT eQTL SNP( Transcript as ment forbest ). ). ). Three of the top ten pathways in this analysis

9 ×10 in 0.20 0.62 0.25 0.99 0.22 0.84 0.94 0.74 -

interval interval loci, as well as additional independ QT and and - interval loci compared to compared loci the genome as a interval −9

P P interval -

) < 0.00044) as well as a gene set based based set a as gene well as < 0.00044) Supplementary Note Supplementary - 1 0 significance P Attenuated - . Because the current study was was study current the Because . P < < 1 × 10 × 1 < < up ( up = 1 × 10 × 1 = Yes Yes Yes Yes Yes Yes Yes Yes No ). These findings highlight highlight findings These ).

explained Supplementary Table 13 Supplementary 23 , 2 4 Supplementary NoteSupplementary . We tested whether whether tested We . −4

association −200

2 ×10 2 ×10 4 ×10 3 ×10 3 ×10 3 ×10 1 ×10

2 ×10 1 ×10 SNP ( ), ‘cation transport’ transport’ ‘cation ), of QT Nature Ge Nature QT P ; ; Supplementary Supplementary - Supplementary Supplementary P

−28 −57 −13 −10 −10 −14 −10 −8 −8 - value threshold threshold value

) ) representation representation 2 P 5

< 0.00025; 0.00025; < . These sig These . eQTL SNP( association 9 ×10 4 ×10 2 ×10 8 ×10 of best r Same n 0.76 2 NA NA NA QT >0.8), etics −22

−8 −7 −8 ). −3

P ). ).

) ­ ­ - ;

© 2014 Nature America, Inc. All rights reserved. variant variant loci interact physically with known myocardial repolarization at common by genes encoded proteins that We evidence sought next Protein-protein alone. observations these from determined be cannot individuals these in pathogenesis LQTS to contribute alleles loss two these not or QTc.Whether normal a had who proband’s father, the in absent QTc,was and normal a had whom of both brother, and proband’s mother the in found was mutation The of a QTc symptoms. basis on the without ms of 500 diagnosed LQTS The QTc. normal a had and mutation the lacked proband’s the father malities; mutant allele and had borderline QTc prolongation and T wave abnor (QTc) of 492 ms without symptoms. The proband’s QT mother rate–corrected carried the heart a of basis the on diagnosed LQTS with girl The product. protein resulted in and frameshifts and premature truncation of the corresponding p.Ile276fs*281) (encoding ( to function protein to disruptive be are predicted several array; Chip Exome the on included or (ESP) Project Sequencing Exome the by whole whom on individuals ( ancestry acids present in cases but not in Note Supplementary ( genes six these in variants sequence splice or exonic rare for genes, LQTS1–LQTS3 the in mutations cally diagnosed LQTS on the basis of the Schwartz score, but free from We with clini mutation screening. individuals 298 unrelated studied ( CAV1 genes six flux, ion in involvement or expression cardiac absence of multiple nearby genes in the associated interval and known of to proximity association, the signal significance, of basis statistical LQTS mendelian unrecognized the new QT interval–associated loci might likewise contain previously of some that hypothesized we LQTS, to relevant genes in mutations QT common of ( studies LQTS previous monogenic cause to and established previously current genes five include the in found loci variant Common LQTS Predicted functionbyPolyphen2(benign,possiblydamagingorprobablydamaging)SIFT(tolerated isalsoindicated.See chip arraydesignedfromexomesequencingof>12,000multi-ancestrysamples(numberalternateallelesshown) andintheExomeSequencingProject(alternateallelecountspertotalnumberofindividualsshown). Six genes( TRPM7 TRPM7 TRPM7 TRPM7 TRPM7 SRL SRL SRL SLC8A1 SLC8A1 SLC8A1 ATP2A2 ATP2A2 Gene T Nature Ge Nature Weproteins. a protein have constructed KCNQ1 Table able able 3 Of Of the 13 variants that altered amino acids, 2 mutations in , ,

proband CAV2 ATP2A2 3 c and and , KCNH2 Table andidate andidate gene mutational screening TRPM7 n Chr. 15:50,884,280 Chr. 15:50,884,406 Chr. 15:50,884,537 Chr. 15:50,935,731 C Chr. 16:4,256,384 Chr. 16:4,256,754 Chr. 16:4,256,990 Chr. 2:40,342,664 Chr. 2:40,397,450 Chr. 2:40,656,318 110,765,554 C Chr. 12:110,734,419 Position (hg19) , hr. 15:50,955,189 hr. 12:110,765,553– , , etics CAV1 Supplementary Note Supplementary SLC8A1 -

3 interval variants at loci with established rare coding coding rare established with at loci variants interval , mutation

CAV2 ). Of these variants, 11 were not observed in ~6,800 in ~6,800 11 were not variants, observed ). Of these , interaction mutation was detected in a 14 a in detected was mutation SCN5A

ADVANCE ONLINE PUBLICATION ONLINE ADVANCE , ATP2A2 SLC8A1 , , ). We identified 13 variants that altered amino amino altered that variants 13 We ). identified SRL , and

KCNE1 , screening SRL

mutation was detected in a in 6 detected was mutation networks and - TRPM7 - ≥ exome sequencing was performed performed was sequencing exome associated genes. Weassociated on selected, the Exon 300 300 controls of the same continental 26 26 26 10

TRPM7 and TRPM7 5 2 7 2 2 6 1 8 5 ). Supplementary Table 17 Table Supplementary ) at5lociwerescreenedforaminoacid–alteringvariantsin298LQTScasesandcomparedto>300controlsof thesameancestry, presenceonanexome KCNJ2 ) ) from five new loci for coding - protein interaction network network interaction protein c.4152A>T c.4026A>T c.3895A>C c.341A>T c.58_59insA c.2566C>T c.1409G>A c.1177G>T c.2651T>G c.2009C>T c.1104C>T c.826_827insA c.340A>G (encoding p.Ile19fs*59) p.Ile19fs*59) (encoding Nucleotide change ). Given the coexistence - year

- old girl with with girl old - p.Leu1384Phe p.Glu1342Asp p.Ser1299Arg p.Asp114Val p. p.Arg856Cys p.Arg470Lys p.Gly393Cys p.Val884Gly p.Pro670Leu p.Ala368Val p. p.Asn114Asp of Amino acid I I le19fs*59 le276fs*281 change - - ATP2A2 function function ATP2A2 year and and - - site site old old

­ ­ ,

of cases Number causal genes underlying the QT the underlying genes causal the as intervals associated relevant the in others not and genes these implicates strongly repolarization myocardial underlying currents of the mediators known with loci by at genes QT interval–associated and 1), (caveolin Consistent with the known relationships among several of the mende QT common lian LQTS algorithm from the InWeb database ( ei) wih euae SRAa n cardiomyocytes in SERCA2a regulates which menin), including permutation), using significant enrichment compared to random expectation ( a LQTS, with associated genes mendelian 5 with the by encoded proteins interact physically that GWAS our by identified loci 10 from genes 12 by Weencoded proteins found spectrometry. mass tandem high by with interact they proteins identified KCNH2 LQTS mendelian by the encoded proteins Lundby by paper accompanying an QT in involved functionally are LQTS with associated genes mendelian of interactors that gests and yet to ( be associations discovered true include associated than more expected by chance (rank were proteins interacting that found We regions. in those genes compared to all genes in the genome from the non 35 loci already identified) and tested for enrichment of association scores to association proteins assigned all interacting (except in those be nonetheless might network for even if enriched association, not at genome seed the with directly interacting and (hypergeometric expectation null to compared the enrichment significant representing loci, new seven CAV1 study. ( current We the in interactors eight found identified tions could help identify candidate genes within any of the 22 new loci proteins seed and protein these investigated whether Note direct connections, ( was observed interconnectivity significant lian genes, 1 2 1 1 1 1 1 1 1 1 1 1 1 This conclusion is further supported by by supported further is conclusion This Supplementary Note Supplementary Supplementary Note Supplementary ATP1B1

). We thus identified 606 proteins interacting directly with the the with directly interacting proteins 606 identified We thus ). , , CAV2 In controls , , (yes/ no) CACNA1C 2 - No No No No No No No No No No No No No 7 associated associated genes and 7 loci harboring previously identified , we seeded the network with the first 12 known mende known 12 first the with network the seeded we , ( PLN - , , interval variants (but not known mendelian genes) mendelian known not (but variants interval Table PRKCA

S (phospholamban), which also regulates SERCA2a, SERCA2a, regulates also which (phospholamban), upplementary Note Alt allelesinExome P , , = 0.008 for indirect connections; Chip (yes/no) CAV3 1 ). Molecular interactions of proteins encoded encoded proteins of interactions Molecular ). , , SLC8A1 No No No No No No No No No No No No No Supplementary Note ). ). Protein network interaction analysis sug ). We hypothesized that the other proteins proteins other the that We ). hypothesized and - interval duration. interval fordetails. - sum sum SNTA1 - ATP2A2 , , interval association. interval ATXN1 P = 0.03; = 0.03; P et al. et No No No No No 1/4,915 No No No No 24/5,379 No No In ESP = 0.00012), suggesting that they from mouse cardiac tissue and (SERCA2a), (SERCA2a), 2 , , 8 - . We immunoprecipitated We . immunoprecipitated associated genes genes associated ETF1 Supplementary Table 18 Supplementary in vivo in Possibly damaging,tolerated Benign, tolerated Benign, tolerated Probably damaging,damaging S Probably damaging,tolerated Benign, tolerated Probably damaging,damaging Probably damaging,damaging Benign, damaging Probably damaging,tolerated S Benign, tolerated - - top top Supplementary Fig. 4 Supplementary ) performance orbitrap orbitrap performance wide significance. We wide significance. 2 6 and and . Using the DAPPLE PolyPhen, SIFT s e l c i t r A data presented in in presented data - Supplementary protein protein interac SGOL2 P SRL = 0.0006 for = 0.0006 29– P - = 1 × 10 associated (sarcalu 3 ATP2A2 KCNQ1 1 , , ) from from ) CAV1 3 −6 , 4  ­ ­ ­ ­ ­ , , .

© 2014 Nature America, Inc. All rights reserved. permeable and has protein kinase function astatin 7 protein, a six arrhythmias in reduction substantial a strated demon failure heart of model rat a in SERCA2a of overexpression channel (TRPC1) 1 canonical potential receptor sient by haploinsufficiency transient with third a about by in deficits myocardial relaxation and and contractility a protein reduced Ca Serca2 in reduction a showed mice in changes humans, affected cardiac but investigation detailed of heterozygous other or electrocardiographic described has of follicularis keratosis Darier of cause a are mutations SERCA2 Dominant to the centrality of calcium cycling to excitation owing failure heart in implicated is dysregulation its and reticulum, Ca for responsible is a gene in a newly discovered QT interval–associated locus locus ­associated ( phospholamban by regulated negatively ( pump calcium SERCA2b expressed ubiquitously a splicing, alternative by and, pump calcium arrhythmias ventricular to and leads repolarization myocardial delays and its overexpression shortened and arrhythmia action reduced with associated is exchanger Na the of inhibitor an of administration fact, In fibrillation. de torsade pointes and including ventricular arrhythmias lethal tially activity, and (EADs) to triggered leading poten after depolarizations action Ca on impact profound particular, in and, balance effect cation depolarizing delicate this of net Disruption a of repolarization). prolonging expense (potentially the at balance, cation even Na a Ca The locus). by encoded is which of by is myocyte an counterbalanced Naactive Na The contraction. myocardial halt to reticulum Ca so, less and, intervals QT prolonged mogenic Timothy syndrome (LQT8) that is associated with extremely L the in gain mutations fact, In substrate. lethal potentially and mogenic arrhyth highly a and electrocardiogram on interval QT prolonged potential subsequent a action repolarization, myocyte cardiac ventricular in the delays to of leads phase plateau the during current ( contraction myocardial to leading reticulum, sarcoplasmic the from Ca by sustained Na is and with influx begins depolarization Cellular fluxes. channel ion nated coordi multiple of interplay the requires second per once average the in loci several at Note genes Supplementary of description detailed (see mogenic an process having cellular is arrhyth as of which derangement the the QT interval, the underlies that repolarization, signaling myocardial calcium in role highlight important transcriptomic data genomic, of proteomic analysis and integrated our Altogether, DISCUSSION s e l c i t r A  upeetr Fg 5 Fig. Supplementary TRPM7 ATP2A2 potassium of efflux from results repolarization myocyte Normal on myocyte ventricular the of relaxation and activation Electrical + /Ca - - potential duration in models of LQTS of models in duration potential White disease (MIM (MIM disease White 2+ encodes the widely expressed transient receptor channel mel encodes the SERCA2a cardiac sarcoplasmic reticulum reticulum sarcoplasmic cardiac SERCA2a the encodes exchanger (NCX1, encoded by by encoded (NCX1, exchanger 2+ 3 2+ , 4 that enters the myocyte is counterbalanced by by counterbalanced is myocyte the enters that , Ca ; 6 - . In turn, . In turn, type Ca type - ). 2+ transmembrane molecule that is Mg 2+ 3 sequestration by the cardiac sarcoplasmic sarcoplasmic cardiac the by sequestration 3 ATP1B1 2 . rlne iwr (eoaiig Ca (depolarizing) inward Prolonged ). is actively taken up by the sarcoplasmic sarcoplasmic the by up taken actively is 5 . . Supplementary Fig. 5 Fig. Supplementary - 2+ potential duration, formation of early early of formation duration, potential PLN 12420 2+ channel lead to the highly arrhyth highly the to lead channel 3 8 influx, which triggers Ca triggers which influx, , at a common variant QT variant common a at , as well as upregulation of the tran the of upregulation as well as is negatively regulated by regulated negatively is 0 ) 3 7 . No study that we are aware aware are we that study No . 2+ 41 oesai cn ae a have can homeostasis PLN , + 4 /K 2 SLC8A1 . The 4 - 3 ), also a QT interval– QT a also ), + 0 contraction coupling. 3 . ATPase (a and heart failure heart and touchtone ). The protein is is protein The ). + that enters the the enters that ) to ensure net net ensure to ) 3 - 9 3 of . Moreover, . 6 2+ . SERCA2a - 2+ β and Ca Serca2 - function function PRKCA ( subunit interval interval release release nutria + /Ca +/− 3 2+ 2+ 2+ 2+ 4 + ­ ­ ­ ­ ­ ­ ­ ­ ) , ,

nelig QS s ciia efco o moada repolariza myocardial of effector Ca tion. critical a as LQTS underlying signaling. calcium involving ences or potentially in through ongoing effects adulthood, functional differ developmental through leads repolarization humans myocardial in altered to TRPM7 that possibility the raises work previous in late phenotype aberrant cardiogenesis recognizably no and midcardiogenesis; in block heart and cardiomyopathy, repolarization delayed cardiogenesis; early in cardiomyopathy lethal in targeted recently, TRPM7 TRPM7 increased with associated is in steering cell involved migration microdomains), calcium intracellular high (focally ers flick calcium underlying influx calcium into stretch mechanical of transduction mediates TRPM7 fibroblasts, lung embryonic human including cycling, calcium in involved genes several of downregulation to leads myocytes ventricular onic thymogenesis mal nor disrupts deletion targeted lethal; embryonic is mice in deletion skeletogenesis, defective stones kidney demonstrates mutant TRPM7 zebrafish online ver Note: Any Supplementary Information and Source Data files are available in the the of in version available are references associated any and Methods M population. general the in arrhythmias ventricular lethal from death prevent and to predict approaches new expose to promises arrhythmogenesis of of mechanisms elucidation fundamental The process. electrophysiological critical this of ing plementary experiments represent a quantum leap in our understand QT the gene underlies which certainty with say cannot we medi Although to effects. repolarization likely ate the loci these at genes specific highlight to approaches to of 35. loci Wenumber variant common total the diverse have used arrhythmogenesis. to contribute fact in could teins pro some of target discovered the newly that inadvertently therapies existing Conversely, arrhythmia. causing without arrhythmias some treat potentially could repolarization myocardial to contribute that sity to cause other arrhythmias, targeting the newly identified proteins to managementclinical of some arrhythmias because of their propen responding to anti ment. Although derange their from arising consequences pathophysiological the as contribution to repolarization of these Ca on Ca ers contribute to repolarization is unclear, but its involvement in Ca PRKCA loci: atgenes common variant QT interval–associated syndrome tion given the role of the proteins by encoded the mendelian Timothy rare and common genetic variation now of place Ca studies our However, coupling. ­contraction et Potassium flux has long been recognized through rare mutations rare through recognized been long has flux Potassium We have identified 22 new QT interval–associated loci, bringing bringing loci, interval–associated QT new 22 identified We have Much work to the be physiological normal will needed understand 4 6 suggests a potential role in localized Ca h 2+ ods , knockdown results in loss of spontaneous Ca - sion of the pape 2+ SRL sensitive potassium sensitive channels potassium or the Na – has been recognized as a central mediator in excitation in mediator central a as recognized been has the pape the associated gene (LQT8) and 4 KCNH2 3 and abnormal melanophores and abnormal a SLC8A1 DVANCE ONLINE PUBLICATION ONLINE DVANCE Trpm7 4 r 1 . - r . Targeted cardiac deletion in cultured embry cultured in deletion cardiac Targeted . . arrhythmic agents targeting the I agents targeting arrhythmic 4 ) ) channel have a relatively limited contribution 6 . . In human atrial fibroblasts, atrial fibrillation deletion in mice has been shown to result result to shown been has mice in deletion . How the Mg - interval trait at every locus, these com these locus, at trait every interval 2+ as a central modulator of repolariza CACNA1C - mediated Ca mediated 2+ 2+ /Ca SERCA2a - regulating proteins, as well 2+ 2+ fluxes or indirect effects 4 , as well as the following channel TRPM7 might 4 . Homozygous . Homozygous +

/Ca Nature Ge Nature 2+ 4 2+ 2+ influx, whereas whereas influx, 5 . In migrating migrating In . 4 exchanger. ATP2A2 influx Kr 8 . . In total, this (LQT2, cor (LQT2, 4 2+ n 7 Trpm7 online online . . More , , etics flick PLN - ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ­ ,

© 2014 Nature America, Inc. All rights reserved. preparation: O.T.R., M. Kähönen, J.S.V. Analysis: T.J.L., O.T.R., M. Kähönen, J.S.V., M. Kähönen, J.S.V. Genotyping: T.J.L., N.M. Genotyping: T.J.L. Phenotype Obtained funding: Y.J., T.D.S. Data acquisition: T.D.S. Statistical analysis and interpretation: I.M.N., H.S., Y.J. Obtained funding: S.B.F., U.V. S.B.F. Statistical analysis: U.V., M.D., M.R.P.M. Interpretation: U.V., M.D., S.B.F. principal investigators: D.S., M.U. E.G.L., A. Mulas, M.O., S.S., D.S., K.V.T., M.U. study Overall and supervision B.H.S. M.E., B.H.S. Obtained funding: A.H., J.C.M.W., A.G.U., B.H.S. Study supervision: J.A.K., A.H., J.C.M.W., B.H.S., A.G.U. Statistical analysis: M.E. Interpretation: Study concept and design: M.E., B.H.S. Data acquisition: M.E., O.H.F., B.P.K., Obtained funding: G.N., D.J.v.V., F.W.A., P.v.d.H. M.P.v.d.B., D.J.v.V., G.N. Genotyping and data analysis: F.W.A., I.M.L., P.v.d.H. preparation: A.F. Data preparation and analysis: D.E. J.F.W. H.C., J.F.W. GWAS analysis: P.N. funding: J.F.W.Raised study Overall supervision: F.D.G.M., C.F. P.P.P. Study genotypingsupervision, and data coordination: A.A.H. Data analysis: L. Franke. Phenotyping: R.A.d.B., P.A.v.d.V. Genotyping: L. Franke. Analyses: I.M.N. and S. Kääb, T.M., M.W. study Overall principal investigator: A. Peters. genetic analysis: C.G., M.M. measurementcollection, and interpretation: M.F.S., S. Perz, B.M.B., E.M. Primary QT Overall project A. supervision: Pfeufer. Genotyping oversight: T.M. ECG study Overall design and principal investigators: K. R.E., generation: M.M.N., P.H., T.W.M. Data analysis: L.E., P.H., T.W.M., M.M.N. M.A.N. HealthABC: data andcollection analysis: K.K.K. Principal investigator and V.S.supervision: genotyping: M.P. ofDesign ECG study, analysis and interpretation: L.O. Genetic ECGs: A.J. Electrocardiographic measurements: K.P. GWAS and replication control: dataA.M.L. Primary analysis: A. Marjamaa. Phenotyping, including G.S. supervision: M. Bobbo. analysis: Primary A. Iorio. Statistical analysis: A.P.D.A. studyOverall analysis: X.Y., funding: M.G.L. C.N. Secured B.A.O. A. Isaacs, B.A.O., J.A.K., A.G.U. study Overall principal investigators: C.M.v.D., case ascertainment: J.C.D. set: M.D.R. Study conception and analysis framework: D.M.R. Algorithm for GWAS analysis: Y.B.R.L.Z., ofSupervision quality control and analysis of data K. Stefansson, U.T., H. Hólm, D.F.G., D.O.A. statistical analysis: D.F.G. Additional analysis and interpretation of results: K. Stefansson, U.T., H. Hólm, D.F.G., D.O.A. Data alignment, imputation and of analyses: A.D.P. design and funding: A.F.W.I.R., phenotype measurement, data andentry field work I.K., O.P.supervision: Study B.M.P. interpretation: J.C.B., N.S. ofSupervision analyses: B.M.P. Funding for GWAS: B.M.P., N.S. Data B.M.P.,S.R.H., collection: D.S.S. Genotyping: J.I.R. Analysis, and/orcollection statistical analysis: S.U. Sample and/or data M.C., collection: studyL.Z. Overall P.G.supervision: Data S.J.N. study Overall M. supervision: Brown, M.J.C., P.B.M., N.J.S. M. Brown, M.J.C., P.W.M., P.B.M., N.J.S. Genotyping: P.B.M., S.J.N. Analysis: J.B.S.collection: project L. Overall supervision: Ferrucci. A. Chakravarti. Writing: D.E.A., A. Chakravarti. Analyses: D.E.A., J.S.B., A. Chakravarti, G.E., H. Huang. Steering: D.E.A., A. Parsa, W.S.P. EKGA.R.S. data W.S.P.collection: Analysis: A. Parsa, J.R.O. Interpretation: L.J.L., V.G. GWAS cohorts. AGES: to all coauthors. was in revised critically detail by members of the writing team before circulation respective study groups. The manuscript was written by C.N. T.T.K., P.B.M., C.N. The study design was developed by M.J.A., D.E.A., A. Chakravarti, L.C., P.I.W.d.B., Writing group. approved the manuscript. Author contributions are indicated by cohort and group. All coauthors andrevised A listing full of acknowledgments is provided in the Nature Ge Nature L. AU Acknowledgments - P.L. Obtained funding: T.J.L., O.T.R., M. Kähönen, J.S.V. T H PopGen: SardiNIA: Croatia-Korcula Croatia-Korcula and Croatia-Split: O FHS: HNR: R R MICROS: Amish studies CONT Analysis plan development: C.N. Data andY.L.collection S.R.C., supervision: Data analysis: D.S.E., n Data H.K. collection: Data generation: H.K., T.W.M. data Genetic ORCADES: Recruitment and phenotyping: N.E.E.M., N.F. Genotyping and data C.N. etics ARIC: Health2000: Phenotyping: M.O. Genotyping and data analysis: G.R.A., RIBU deCODE: - C., C., A. Pfeufer, S.L.P., P.J.S. and N.S. in consultation with the - Sample recruitment and overall study principal investigator: C. C. takes overall responsibility for the QT

Study design: A.A., D.E.A., A. Chakravarti, W.H.L.K. Phenotyping: V.G. Data analysis: A.V.S. Oversight: T.B.H., T ADVANCE ONLINE PUBLICATION ONLINE ADVANCE I : Clinical : data Clinical genotypingcollection, and oversight: ERF: ONS Phenotype S.H.W.collection: generation:Genotype - Data D.O.A.,collection: H. Hólm. Study design: N. N. Interpretation of results: C.G., A. Pfeufer, H.P., Young Finns Study: Data analysis, replication genotyping and quality TwinsUK: Analysis: A. Isaacs. Data acquisition: C.M.v.D., DCCT/EDIC: SHIP: Data acquisition: M.D., M.R.P.M., U.V., Study concept and design: H.S., Y.J. CHS: GWAS analysis: C.H. Data collection, - eMERGE: C., C., C.J.O. - C., C., C.J.O., P.A.N., M.G.L. GWAS Study design: J.C.B., S.R.H., Analyses: D.W. Supervision BLSA: Rotterdam Study I and II: Data T.J.L.,collection: O.T.R., Supplementary Supplementary Note PREVEND: FVG: Data curation and Analysis: T.T. Phenotype - BRIGHT: H.J. Data collection: - KORA-F3/S4: C. C. The manuscript - IGC study.

Carlantino: Phenotyping: LifeLines: Phenotyping:

.

characteristic characteristic organization: D.J.T. LQT2 and LQT3 and sample management: C.D. Recruitment, phenotyping E.R.B. and Screening for strategy: mutations in LQT1, and submission: M. Kumari. M. supervision: Kivimaki. Funding:Overall A.D.H. and supervision Overall principal investigator: E.I. B.P. L.K., F. Kronenberg, C.L., B.P., B.S. Study design and principal investigator: preparation: F. Kronenberg, C.L. Data L.K., collection: B.P., B.S. Data analysis: analysis: and supervision S.G. Overall principal investigator: E.I. A.F.D., G.C.M.W. Genotyping: W.K.L. study Overall data supervision, andcollection funding: Study: Study design, data andcollection area disease knowledge: D.S.T. analysis F.N. and expertise: epidemiology Genotyping and Å.T.N. genetic expertise: A. Carracedo. Financial support: A. Carracedo. A. Carracedo. Genotyping: M.T. Analysis: M.T. Interpretation: M. Brion, M. collection: Brion. Study design: M. Brion. Genotyping platform management: Post-MONICA: M.G. biochemical data Genetic, acquisition and statistical analysis: A.G.P. and supervision analysis: A.N.N. Data acquisition, analysis and interpretation: and supervision principal investigator: J.H. K.W.H.M.z.S. Supervision: Study design and analysis: A.K. Study concept, investigator: J.W. and database: M. Knoflach. funding, Supervision, administration and principal and writing: S. Kiechl. DNA preparation: F. Kronenberg, C.L. ECG measurement P.H.W., R.W.M. ECG analyses: P.W.M. genetic resource: A.D.H. study Overall and supervision principal investigators: R.W.M., P.H.W. Data forcollection genetic resource: P.H.W. Development of GWAS above.)entry that contributed to both GWAS and replication genotyping are shown under the SNP genotyped Directly replication cohorts reprint at online available is information permissions and Reprints version of The authors declare competing interests:financial details are available in the studyA.L. Overall J.V.O.supervision: Immunoprecipitation experiments. DAPPLE analysis. free of LQT1, LQT2 and LQT3 mutations: ProgramR.M.H. codevelopment: S.W.S. SRL patientcollection, and selection L.C., molecular screening P.J.S.supervision: gene diagnosis management: F. Kyndt. Patient enrollment: V.P. mutations in LQT1, LQT2 and LQT3 and clinical data J.collection: Barc. LQTS genetic information S.C. collection: B.M.B., E.M. Genotyping: H.P. M.J.A.supervision: D.J.T., A.M. A.B.,collection: N.H., A.A.M.W. Study C.R.B., A.A.M.W.supervision: LQTS mutation Amsterdam:screening. P.v.d.H. Mouse knockout. M. Kellis. ventricle enhancer Left analyses. J. Brandimarto. Statistical analysis: M.M. sample K.M., collection: C.E.M. Sample processing and expression analysis: ventricle eQTLLeft analyses. interpretation: A.D.J. enrichment tests: K. type–specific S.R., Cell Slowikowski. Non-cardiac eQTL analyses. lookup: S.L.P. QRS GWAS: HRGEN: Non-QT trait lookups. CARe-COGENT: the analyses. results. Polygenic analysis: R.D.K. P.I.W.d.B., A. Pfeufer. and C.N. performed quality control and meta Meta-analysis of GWAS and replication. COM mutation screening: A.G., R.I. ULSAM: P s/index.htm Data acquisition, statistical analysis and interpretation: S. Padmanabhan. ET Meta the pape I NG - D., J.R.G. Patient studycollection, design, data review and overall Study N.S. Metasupervision: Genotyping: A. - FI analysis and lookup: studyM.d.H. Overall R.J.F.L.supervision: Data andcollection submission: J.A.H., V.A. Carla: N PIVUS: Enrichment tests: K. S.R., Slowikowski. Candidate gene list: l . Concept, design and analysis: E.J.R. K.L., Supervision: M.J.D. r . A Munich: BRHS: NC Study concept and design: K.H.G., K.W. Genotyping: IA Genotyping: A. L Analysis: R.W.M. Custodian of genetic resource: Study oversight: S. Kääb, A. Pfeufer. Patient collection: I - Data set acquisition: A.S.P., V.E. Analysis and C.S. C.S. Phenotyping: L.L., J.Ä., J.S. Data analysis: S.G. Overall supervision: T.P.C. supervision: Overall Recruitment, NTE Nantes: TRPM7 Analysis: X.W. L.A.B., supervision: Overall Toronto: R - ATP2A2 analysis of GWAS and replication association Proteomic experiments and analysis: ESTS Bruneck: Scientific management:Scientific J.

mutation analysis and interpretation: D.E.A. and S.L.P. independently SLC8A1 - Meta - C.S. C.S. Phenotyping: L.L., J.Ä., J.S. Data analysis: analysis: D.E.A., P.I.W.d.B. Results Cyprus: Identification of patients with LQTS sequencing: S.C. Screening for . . (Author contributions for cohorts Intergene: - Data analysis, interpretation Mayo Clinic: analysis and lookup: J.G.S. sequencing: T.T.K. data Clinical Whitehall Whitehall II: Study concept, funding, Genotyping, data http://ww s e l c i t r A Galicia: LQTS cohort Pavia: MIDSPAN Family Data collection SAPHIR: - - J.S. Clinical, C. supervised C. supervised Patient w.nature.com/ Cohort London:

Czech Czech DNA

online



© 2014 Nature America, Inc. All rights reserved. M Joel Runjun M S S D W Ilja 26. Yuki Bradford Andrew T D 25. 24. 23. 22. 21. 20. 19. 18. 17. 16. 15. 14. 13. 12. 11. 10. 9. 8. 7. 6. 5. 4. 3. 2. 1. s e l c i t r A  téphanie andosh andosh Padmanabhan

amara amara avid avid an orris Brown

endy endy ichael ichael

ae K. Lage, Segrè, A.V. O. Corradin, J. Ernst, B.E. Bernstein, X. Hu, J.C. Chambers, J. Dupuis, R.N. Lemaitre, metabolic the of study association genome-wide A D.J. Balding, & D. Zabaneh, C.E. Elks, A. Pfeufer, Sotoodehnia, N. M. Hoed, den J.G. Smith, B.F.Voight, J. Yang, J.W. Kim, P.A.Noseworthy, H. Holm, I.M. Nolte, D.E. Arking, Pfeufer,A. C. Newton-Cheh, to genetics from syndrome: C. Long-QT Newton-Cheh, R. Insolia, & L. Crotti, P.J., Schwartz, implicated in genetic disorders. genetic in implicated traits. glycemic (2010). related e1001058 or diabetes 2 type with associations for traits. common to susceptibility confer to expression gene of levels dictate disequilibrium types. cell Nat. specific pathogenic immune cell subsets. plasma. in enzymes liver of concentrations risk. diabetes 2 type on impact their CHARGE the from studies association genome-wide Consortium. of meta-analysis a acids: men. Asian Indian in syndrome studies. association genome-wide of (2010). 153–159 conduction. ventricular cardiac and disorders. rhythm and conduction cardiac on Americans. African in (2012). traits. anthropometric cardiovascular,and metabolic, of SNPs. common interval. QT electrocardiographic the (2011). et i a ins pplto-ae study. population-based Finnish a in death genome-wide duration. three of meta-analysis repolarisation: studies. association cardiac with associated repolarization. cardiac modulates Study. QTSCD the Study. QTGEN the in Study. linkage to chromosome 3 in a genome-wide linkage analysis: The Framingham Heart management. M S E

Bader Biotechnol.

Arking N E Genome Heart et S D llinghaus T olte et D et

K Nat. Post et et al. et et

Nature

et et et

et K noflach al. Johnson al. et

K C al.

et

et PLoS nertn atimn rs lc wt gn-xrsin aa identifies gene-expression data with loci Integrating risk autoimmune

et

Rhythm al. al.

al. et al.

al.

al. Circ.

oopmann Mapping and analysis of chromatin state dynamics in nine human nine in dynamics state chromatin of analysis and Mapping

al. eoe attoig f eei vrain o cmlx ris using traits complex for variation genetic of partitioning Genome umar Genet. 38 83 Several common variants modulate heart rate, PR interval and QRS and interval PR rate, heart modulate variants common Several hatel al.

et al. Res.

al. et Thirty new loci for age at menarche identified by a meta-analysis a by identified menarche at age for loci new Thirty A common variant in variant common A al. hmn hnm-neatm ntok f rti complexes protein of network phenome-interactome human A Nat. Common inherited variation in mitochondrial genes is not enriched

et Common variants at ten loci modulate the QT interval duration in duration interval QT the modulate loci ten at variants Common e gntc oi mlctd n atn guoe oesai and homeostasis glucose fasting in implicated loci genetic New et al.

eoewd ascain td o P interval. PR of study association Genome-wide 28 43 et Impact of ancestry and common genetic variants on QT interval QT on variants genetic common and ancestry of Impact et 85 et et , Albert , VernonAlbert , , The metabochip, a custom genotyping array for genetic studies genetic for array genotyping custom a metabochip, The

1

al. omn eei vrain er h popoabn ee is gene phospholamban the near variation genetic Common

27 obntra efcs f utpe nacr ains n linkage in variants enhancer multiple of effects Combinatorial

473 Genet.

al. Nat. al. ,

cmo gntc ain i the in variant genetic common A

G

Arrhythm. al.

186 , 1045–1048 (2010). 1045–1048 , , al. al. , al. PLoS

dniiain f er rt–soitd oi n theireffects and loci rate–associated heart of Identification 24 44 al.

eei lc ascae wt pam popoii n3 fatty n-3 phospholipid plasma with associated loci Genetic

, , Genet. Common variants in 22 loci are associated with QRS duration M 2 Nat. 42 Genome-wide association study identifies loci influencing loci identifies study association Genome-wide eorg eorg Circ. 55 Common genetic variants, QT interval, and sudden cardiac sudden and interval, QT variants, genetic Common QT interval is a heritable quantitative trait with evidence of evidence with trait quantitative heritable a is interval QT Common variants at ten loci influence QT interval duration interval QT influence loci ten at variants Common , 43–49 (2011). 43–49 , K 49

, 277–284 (2005). 277–284 , 76 h NH oda Eieois apn Consortium. Mapping Epigenomics Roadmap NIH The , 1–13 (2014). 1–13 , , , 69 Genet. , , , 117–122 (2010). 117–122 , ark J

D ,

irill V irill 21 S , , 7 56 ,

ONE , , Jaroslav A Hubacek 77 Genet.

, e1002193 (2011). e1002193 , C ara ara

Cardiovasc. aryl aryl , Alicia 43 , ,

, , 12 E Electrophysiol. aroline Hayward

S

T 41 , 519–525 (2011). 519–525 , 4 hret PLoS tefan Nat. , , C 63 , e6138 (2009). e6138 , amara amara B Harris L

Nat. , 407–414 (2009). 407–414 , N 41 W aulfield Pulit T , , Alexander Nat.

Nat. ona , 399–406 (2009). 399–406 , Am.

Biotechnol. arasov Nat.

ONE aggott 1 Genet. SLC8A1

, , Hailiang Huang Genet. L

Am.

G

Genet. Genet.

undby J. S

Genet. S Nat. 5

ustafsson 2

Circ. mith Hum.

, e11961 (2010). e11961 , J.

– otoodehnia 5 Nat. 38

10

4 , 868–877 (2012). 868–877 , is associated with the duration of duration the with associated is 5 Hum.

28 , 45

42 , 647–655 (2012). 647–655 , Genet.

186 , 644–651 (2006). 644–651 ,

42

, 25

Cardiovasc.

42 , , Genet. Genet. N , , , 1068–1076 (2010). 1068–1076 , 3 , 1077–1085 (2010). 1077–1085 , 39 M , 309–316 (2007). 309–316 ,

L , 105–116 (2010). 105–116 , , , , Genet. ilesh J 22 K L , eo-Pekka eo-Pekka

PLoS 40 arcus arcus 43 50 NOS1 , luttig ia ia 78

23 45 91 , , Joshua 57 , 1131–1138 (2011). 1131–1138 , 70 , , Pau

, , ,

89 C , 621–631 (2013). 621–631 , , 180–184 (2012). 180–184 ,

, Genet. , , L D 58 Genet. regulator rotti , 496–506,(2011). K S 13 enore J aníel F D , , amani 64 amil amil Nat. , PLoS 3 M 14 N örr

, , , Bernhard 8 15

4 , , eena eena , e1002793 , L 5 avarro

305–311 , Genet.

, C E – yytikäinen 16 Genet. 29 7 NOS1AP S lizabeth J lizabeth Rossin Bis , , Pim van der Harst 86 , , , lowikowski L G 30 W , Florian

auner K udbjartsson 42

, , 13 6 umari 50 H M , ,

, , Aaron Isaacs , , artina artina S L S 36. 38. 37. 35. 34. 33. 32. 31. 30. 29. 28. 27. 48. 47. 46. 45. 44. 43. 42. 41. 40. 39. heila Ulivi heila 78 inda inda trohmer 46

, , Alan R 59 Braz, J.C. Braz, Ji, Y.Ji, A. Sakuntabhai, C. Pott, P.Milberg, P. Milberg, I. Splawski, Q. Jiao, M. Shimura, M. Yoshida, A. Lundby, E.J. Rossin, a, R. Sah, J. Du, C. Wei, R. Sah, for requirement sublineage-specific Melanophore P.D. Henion, & B.L. Arduini, M.R. Elizondo, with protein bifunctional a TRP-PLIK, D.E. Clapham, & L. Yue, L.W., Runnels, J. Jin, Lyon,A.R. B. Pani, disease. failure. Res. Na failure. heart chronic (2012). of model experimental an in Heart syndrome-3. QT long and syndrome-2 QT long of model heart intact an in pointes (2005). 8086–8088 mutations. channel (2009). training. exercise endurance (2008). 362–370 Ca improving by mice. (2005). sarcalumenin-deficient from cells nmeth.299 proteomics. interaction quantitative tissue-specific 7 biology. underlying suggest and interact physically disease mediated 101–114 (2013). 101–114 repolarization. and conduction, function, ventricular adult disrupts fibrillation. (2009). automaticity. (2004). development. crest neural during touchtone zebrafish for mutant zebrafish activities. channel ion and kinase Mg altering without failure. heart chronic of model a in Circ. arrhythmias ventricular reduces and leak disease. Darier’s in TRPC1 for (2006). 4446–4458 role potential a survival: Ca reticulum sarco(endo)plasmic following (2000). function. cardiomyocyte and homeostasis K , e1001273 (2011). e1001273 , , , Andrew A Hicks , , Richard + 71 ronenberg /Ca

M

K Cardiol.

Arrhythm. et , Rhythm 72 et 24 et

ao üller- Nat. 2+ al. et Nat.

et et et et

et al. , , 3 , Peter A exchanger overexpression: whole heart and cellular mechanisms. cellular and heart whole overexpression: exchanger al.

et Disruption of a single copy of the of copy single a of Disruption

65 et 7

, 44 et

S Circ. al. al. 15 et

al. Deletion of Deletion et al. (22 June 2014). June (22 al.

et et Med. RM-eitd Ca TRPM7-mediated et al. 51

S

al. oumya Raychaudhuri al. Proc. , , Andrie 107

al.

Genet. iig f myocardial of Timing , , James B

41 aclmnn s seta fr anann cric ucin during function cardiac maintaining for essential is Sarcalumenin et prglto o taset eetr oeta cnncl (TRPC1) 1 canonical potential receptor transient of Up-regulation 8 ,

5 raryhi i a o-aln mrn mdl f cardiac-specific of model murine non-failing a in Proarrhythmia

al. huldiner o canlkns TP7 s eurd o mitiig cardiac maintaining for required is TRPM7 channel–kinase Ion

et 16 al. Calcium flickers steer cell migration. cell steer flickers Calcium al. PKC- al. , , al. SERCA2a gene transfer decreases sarcoplasmic reticulum calcium reticulum sarcoplasmic decreases transfer gene SERCA2a Electrophysiol. , a

, 1444–1452 (2008). 1444–1452 , N Acute inhibition of the Na the of inhibition Acute 2+ et 9 Res. , ,

noain f oi rm eoewd ascain tde using studies association genome-wide from loci of Annotation al. T W , 247 (2012). 247 , niiin f h Na the of Inhibition

DVANCE ONLINE PUBLICATION ONLINE DVANCE al. Proteins encoded in genomic regions associated with immune- with associated regions genomic in encoded Proteins , , Patricia B , , mard Ca Impaired eee rhtma iodr asd y ada Ltp calcium L-type cardiac by caused disorder arrhythmia Severe adig f h srolsi reticulum. sarcoplasmic the of handling

10 S urasyid 87 2+ al. Natl. oshiko oshiko M aclmnn leits tesidcd ada dysfunction cardiac stress-induced alleviates Sarcalumenin

Defective skeletogenesis with kidney stone formation in dwarf in formation stone kidney with skeletogenesis Defective tephen J Proc. trpm7 21

homeostasis.

, 248–254 (2004). 248–254 , α Mutations in Mutations , Johann 106 M regulates cardiac contractility and propensity toward heart toward propensity and contractility cardiac regulates ichael ichael N , 271–277 (1999). 271–277 ,

Trpm7 Acad. orris

oseworthy , 992–1003 (2010). 992–1003 , . G Natl. 79– Am. Curr. S 47 Panayiotou

31

trait T disrupts embryonic development and thymopoiesis and development embryonic disrupts 4 Sci. 2+ , ,

, 362–372 (2011). 362–372 , 81 anaka 60 M J.

– Acad. L store functions in skeletal and cardiac muscle muscle cardiac and skeletal in functions store Biol. N Science

35 2+ W

, , Alvaro Alonso Physiol. ewin ewin , , Åsa Science M ATP2A2 USA orley ewhouse signals confer fibrogenesis in human atrial human in fibrogenesis confer signals trpm7 28 , Annukka , Annukka

illeit

unroe 15 + , Sci.

/Ca 52 110 2+ 52

, 667–671 (2005). 667–671 , 2 + 291 eein uig adoeei variably cardiogenesis during deletion

/Ca ATPase cell promotes silencing gene 2 , , , Peter , encoding a Ca a encoding , 2+ Heart T E J.

3 17 322 J. , , SERCA2 69 , E3037–E3046 (2013). E3037–E3046 , USA

, xhne sprse trae de torsades suppresses exchanger isele

25 D 2+ 3 , 1043–1047 (2001). 1043–1047 , Biol. N , Xinchen , Xinchen , Biol. , 66 10 , 756–760 (2008). 756–760 , exchanger reduces proarrhythmia reduces exchanger 71 ,

avid avid J C aluai

Circ. 10 M , , 102

, 67 11 ARe 73 Mech.

48 Chem. , , Nat. gene results in altered Ca altered in results gene Heart ark W

, , , Chem. M D – Physiol. 88–06 discussion 8089–8096, , ,

M

75

61

aniel aniel Nature

Nature Ge Nature

M Methods L T

Dev. C 2+ , aria aria 82 E , Rhythm 275 Cardiovasc. ester 62 ahtinen

Mol. pump, cause Darier cause pump, onsortium acfarlane ijgelsheim , W 280

297 ,

121

38073–38080 ,

Circulation S 457 ang T , 3500–3506 3500–3506 , Biol.

, H576–H582 ,

53 , 1353–1364 , orres doi:10.1038/ E 9 PLoS 901–905 , 570–578 , vans ,

54 18 n 36 Res. Cell etics , – Genet. , 20

84 68 Basic 37

128

26 42 88 17 77 , , , , 2+

,

, ,

, , ,

© 2014 Nature America, Inc. All rights reserved. C M Jesper V M Vilmundur T D Ben A André M Maximilians Maximilians Universität, Munich, Germany. 30 on Aging, US National Institutes of Health, Baltimore, Maryland, USA. Vanderbilt University School of Medicine, Nashville, Tennessee, USA. Boston, USA. Massachusetts, University of Copenhagen, Copenhagen, Denmark. Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark. 21 Institute of Technology, Cambridge, USA. Massachusetts, USA. Pennsylvania, USA. Massachusetts, 14 Medical Center, Amsterdam, The Netherlands. School of Medicine, Queen Mary University of London, London, UK. School of Medicine, Queen Mary University of London, London, UK. of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Germany. Istituto di Ricerca e Cura a Carattere Scientifico Istituto Auxologico Italiano, Milan, Italy. The Netherlands. of Harvard and MIT, Cambridge, USA. Massachusetts, 2 1 Andrew Andre Franke C Anna F S M Folkert W C Roberto Insolia Argelia N L Annette Peters Ruth J F K L S Adamo P M Joshua DCCT Jerome I Rotter K COGENT Nature Ge Nature Munich, Germany. Center Center for Human Genetic Research, General Massachusetts Hospital, Boston, USA. Massachusetts, Center for Complex Disease Genomics, Institute McKusick-Nathans of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. tefan teven R ude ude Franke asse asse DZHK DZHK (German Center for Research), Cardiovascular partner site Greifswald, Greifswald, Germany. National Heart, Lung, and Blood Institute (NHLBI) Framingham Heart Study, Framingham, USA. Massachusetts, Cardiology Division, University of Washington, Seattle, Washington, USA. imothy arl-Heinz Jöckel arl hristopher onnie R Bezzina hristine ynke ynke Hofman avid avid arylyn ika anolis anolis artin artin att ichael ichael J Ackerman 146 W K O S O / / K 8 G erdan C ivimaki Department Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. , , Harry W G ikarinen D chlessinger M ED iechl ostra D Uitterlinden L K O

D n C D

D ominiczak D L Asselbergs edeiros- E oos

ellis etics Paterson C lsen Ritchie ummings

enny arson I

S ’Adamo G M 5 C onsortium 9 pector N 33 Department Department of Molecular Medicine, Section of Cardiology, University of Pavia, Pavia, Italy. 92 69 , , Pieter A van der Vleuten 126– udnason 26 18 88 49 oravec Institute Institute of Genetic Epidemiology, Helmholtz Zentrum Research Munich–German Center for Health, Environmental Neuherberg, Germany. 18 ewton- , , 22 59 16

, , Broad Broad Institute of MIT and Harvard, Cambridge, USA. Massachusetts, C 35 98 , , 138 5 , , , , M 102 , M Harvard Harvard Medical School, Boston, USA. Massachusetts, 117 , G ADVANCE ONLINE PUBLICATION ONLINE ADVANCE , , , 19 D T ampbell 21 6 , 128 , , Ivana 134 M K 12 , Robert 48 assimo assimo D , , Arthur A 179 aria aria Brion onçalo R onçalo Abecasis homas , , Bouwe P avid avid , , , , 159 107 162 51 103 asper asper , , , Hagen 176 ika , , omingo 63 M , , Hanna Prucha 53 42 26 E 17 150 , Bruno H , D 111 C 26 , , Department Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands. , , Fredrik rik Ingelsson , , Johan Ärnlöv , , , , , arkus Perola 39 108 , , Fabiola , , Afshin Parsa 54 M ag ag 88 D heh K M O , – 154 , , , Annamaria Iorio 152 K , 40 , , J 183 ähönen an 147 anuela Uda , , Arnar L C ichael ichael A W S olcic C M , , Yalda Jamshidi , age

2 , Irene 156 arella G T , , , 54 hristopher J K ,

M 186 3 M 68 Hamilton K S helle ustav M , älsch , , Julien Barc 16 32 , , Jacqueline 3 arah arah H Roden , rijthe ühleisen 99 169 , , Arne Pfeufer , N S Institute Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig Maximilians Universität,

15 47 , 101 W 13 25 tricker 165 , , 93 yberg , , , Cardiovascular Health Cardiovascular Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA. , , Andrew 22 O M 129 , N ilde 186 C 24 , , , , Hilma Hólm 121 58 118 S , , zren Polašek L ateo alls 181 135 deCODE deCODE genetics, Reykjavik, Iceland. mith 26 N hristian hristian Fuchsberger 158 79 , 145 , 58 172 130 eopoldo Zelante eopoldo 4 103– , , – W Department Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, ina , 12 , 154 130 , 120 M , , 80 142 163 26 182 136 , , 122 , , 8 114 20 , , , , ild , 139 M E O L , , Yongmei 9 arkus L , Department Department of Biology, Institute Massachusetts of Technology, Cambridge, USA. Massachusetts, C 2 105 , , , 154 , , M , 170 , , Britt , , , each dward , , Peter J , , 56 C , 143 uigi Ferrucci , , Antti Jula ’ O 3 K 123

arcello arcello R P 110 hristian hristian 178 147 L D M , , , N

ononen 25 , , Florence , Rebecca , Rebecca – M immo immo Porthan scar H scar Franco E ars , Peter H onnell , 156 47 , oritz F

, , , , Veikko , , , lijah lijah R Behr 173 N S 89

G 8 N 12 11 W M , tephen , 131 icolaides , L 28 , , 180 M Heart Heart Failure Research Center, Department of Clinical and Experimental Cardiology, Academic Barts and the London Genome Centre, William Harvey Research Institute, Barts and the London ianfranco ianfranco G 99 our , , Peter P Pramstaller 29 24 G K

ind itteman Laboratory Laboratory of Sciences, Cardiovascular Human Studies Cardiovascular Unit, National Institute N Department Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany. , erjan , , Alan F aria aria Beckmann S , , Unnur 184

arin arin H , G L 21 L 46 öthen chwartz 15 K S E akatta 164 iu ieger Analytic Analytic and Translational Genetics Unit, General Massachusetts Hospital, Boston, , , 115 , ari 93 109 W inner 186 L

M 17 O S K E W 177 52 Zuvich , , Johan , , alomaa Perelman Perelman School of Medicine, University of Philadelphia, Pennsylvania, 10 N yndt l l , , hincup lli arkus , , Xiaoyan Yin S 67 , , Paul I S , Paolo K

M 26 Clinical Clinical Pharmacology, William Harvey Research Institute, Barts and the London 145 122 , , S avis usan usan R Heckbert 140 G tefansson 33 , 26 T S C W immo immo cherer 100 28 T , 117 31 okhtari 154 6 reiser , , inagra , , Jeffrey R , Raitakari , ornelia ornelia horsteinsdottir , , 123 55 , , 154 , , Antonella right T 7 , , 23 153 , , Bernhard Paulweber S C Institute Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, 160 , , Raimund M , , 25 , homas The The Danish National Research Foundation Centre for Cardiac Arrhythmia, tefan 56 27 115 S 171 , , HR L 19 hrysoula hrysoula , Albert , HofmanAlbert Cardiovascular Research Cardiovascular Center, General Massachusetts Hospital, G , undström W elanie elanie , , Uwe Völker yudmyla yudmyla , , Vincent Probst , , Valur Computer Computer Science and Artificial Intelligence Laboratory, Massachusetts M 144 64 K 31 , , asparini , Aroon 50 110 de Bakker 148 S

, aarten P van den Berg 24 , , K 90 , , GEN , Jeffrey Brandimarto tephan B Felix M K E M 31 , , Angel , 47 ontula , , Henriette , , 40 3 M 166 imo imo 21 ääb van Department Department of Medicine I, University Hospital Munich, Ludwig Program Program in Medical and Population Genetics, Broad Institute O N W aura , , 174 eitinger , E ’ 107 M orbert Freyorbert L , C D 167

aldenberger E milsson C 31 aurie A Boyer 51 K D , 164 onnell ulas rbel 13 M 175 alageorgou 6 D , , onsortium , edenko Center Center for Cardiac Arrhythmias of Genetic Origin, , Jorma , 24 116 Hingorani 35 G 111 M , C artens uijn 94 , , Ann- 4 30 , , , , e , , Aravinda riffin , arco Bobbo arracedo T 121 , Annukka , Annukka 158 185 , , Bruce , James F 22 , 161 35 ME erho erho J 27 26 Novo Novo Nordisk Foundation Center for Protein M 26 79 55 , , Per Hoffmann , , , 39 Center Center for Human Genetics Research, , 186 , 131 , , Harold 154 M 29 , , , , eyer eyer zu 157 31 100 80 , , Andrew 56 S R C 157 149 D , Viikari & arco 30 , , GE , , , , Alice hristine hristine 132 , , Jan A 132 137 avid avid , , 88 141 , , W M , , Johannes Haerting L , , , 59 C M

68 20

S , , ehtimäki , , Rudolf A de Boer , , , , Abdennasser Bardai W

ai Psaty laudia laudia , Jean-Jacques , , John R C 8 9 M C erena S , , ark J 17 Department Department of Genetics, University O , 112 M 110 T iegfried Perziegfried ilson onsortium S K hakravarti S D arcel den Hoed , S rrú

homas P arjamaa 168 chwabedissen G S K K

, nieder irk J van Veldhuisen , L 113 S iscovick S hidoni

enneth ors Plump ee 13 D , Vera Adamkova yvänen 158 S 147 L , , anna aly 63 94

amina 46 122 155 G , , Igor Rudan , , –

, s e l c i t r A iudicessi 38 3 G 97 –

, 36 , 5 15 125 C ,

raham raham 88 1 , 158 , M 106 13 6 ,

58 ,

37 , appola , S , 87 133

, ,

argulies , 94

,

chott , ,

,

, 91 ,

97 58 64

8 , , 54 , , , C 126

17 55 , 12

147 M , , , , 70 17 56

8

 , , , , ,

© 2014 Nature America, Inc. All rights reserved. Germany. Cardiology, University Hospital of Essen, University Essen, Duisburg-Essen, Germany. Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. Helsinki University Central Hospital, Helsinki, Finland. Health and Welfare, Helsinki, Finland. National Institute on Aging, US National Institutes of Health, Bethesda, Maryland, USA. Compostela, Spain. Surgical and Health Sciences, University of Trieste, Trieste, Italy. Hospital, Boston, USA. Massachusetts, USA. Massachusetts, Nashville, Tennessee, USA. Tennessee, USA. Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA. Diagnostic Centre, London, UK. Medical Center, Torrance, California, USA. 98 Health Research Institute, Group Health Cooperative, Seattle, Washington, USA. Epidemiology, University of Washington, Seattle, Washington, USA. Luther University Halle-Wittenberg, Halle, Germany. Germany. S Leicester, UK. Pharmacology, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK. Baltimore, Maryland, USA. Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA. 81 of Maryland School of Medicine, Baltimore, Maryland, USA. Missouri, USA. Washington University in St. Louis, St. Louis, Missouri, USA. Human Sciences, University of Manchester, Manchester, UK. USA. Massachusetts, 72 Prague, Czech Republic. 69 Genotipado, Centro de Biomédica Investigación en Red de Enfermedades Raras, Universidade de Santiago de Compostela, Santiago de Compostela, Spain. Technology, Limassol, Cyprus. Salzburg, Austria. Martin Luther University Halle-Wittenberg, Halle, Germany. Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK. Molecular Resource of Infrastructure Sweden (BBMRI), Gothenburg, Sweden. London, UK. Science, Cardiovascular University College London, London, UK. Stockholm, Sweden. INSERM UMR1087, CNRS UMR 6291, Université de Nantes, Nantes, France. Mayo Clinic, Rochester, Minnesota, USA. Rochester, Minnesota, USA. 52 Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK. 49 Lübeck, Germany). Medicine, Tampere, Finland. Ontario Institute for Cancer Research, Toronto, Ontario, Canada. 44 Medical Center Research Institute, San Francisco, California, USA. Reykjavik, Iceland. University Medical Center Groningen, Groningen, The Netherlands. Helsinki, Finland. Centre for Research), Cardiovascular partner site Munich Heart Alliance, Munich, Germany. 34 s e l c i t r A 1 Cardiovascular Science, Cardiovascular Faculty of Population Health Sciences, University College London, London, UK. Utrecht, The Netherlands. Campus Kiel, Kiel, Germany. Experimental Medicine, Christian Albrechts University of Kiel, Kiel, Germany. Care, University of Glasgow, Glasgow, UK. Ontario, Canada. 143 141 Excellence in Research of Hereditary Disorders, Jeddah, Saudi Arabia. Friedberg, Germany. Munich, Germany. Helmholtz Zentrum Research München–German Center for Health, Environmental Neuherberg, Germany. Medical Imaging, Helmholtz Zentrum Research München–German Center for Health, Environmental Neuherberg, Germany. Molecular Epidemiology, Helmholtz Zentrum Research München–German Center for Health, Environmental Neuherberg, Germany. Academy, University of Gothenburg, Gothenburg, Sweden. Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway. 128 Addenbrooke’s Hospital, Cambridge, UK. 125 upplementary upplementary Note 0 Institute Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at of Harbor–University California, Los Angeles (UCLA) Geriatric Research and Education Clinical Center, Veterans Medical Administration Center, Baltimore, Maryland, USA. Harvard and Bioinformatics Integrative Genomics, Boston, USA. Massachusetts, Department of Neurology, Innsbruck Medical University, Innsbruck, Austria. Translational Gerontology Branch, National Institute on Aging, Baltimore, Maryland, USA. Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany. Department of Epidemiology, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, USA. Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig Maximilians Universität, Munich, Germany.

Department Department of Pediatrics, The Hospital for Sick Children, Toronto, Ontario, Canada. Biomedical Sciences, St George’s University of London, London, UK. Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Department of Biomedicine, University of Basel, Basel, Switzerland. 123 91 Department Department of Pharmacology, Ernst Moritz Arndt University of Greifswald, Greifswald, Germany. Institute Institute of Human Genetics, University of Bonn, Bonn, Germany. 61 87 Department Department of Medical and Clinical Genetics, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden. 78 Division Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria. 145 104 Laboratory Laboratory of Epidemiology, Demography and Biometry, National Institute on Aging, Bethesda, Maryland, USA. 66 37 136 48 41 113 . . Cyprus International Cyprus Institute International for and Environmental Public Health in association with the Harvard School of Public Health, Cyprus University of Department Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland. Center Center for Statistical Genetics, Department of University Biostatistics, of Michigan, Ann Arbor, Michigan, USA. Department Department of Pharmacology, Vanderbilt University, Nashville, Tennessee, USA. 138 58 Institute Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University Essen, Duisburg-Essen, Germany. Genetic Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands. 89 108 74 Department Department of Dermatology and Allergy, Technische Universität München, Munich, Germany. Department Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden. Center Center of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia. Department Department of Cardiology, Lund University, Lund, Sweden. Division Division of Rheumatology, Immunology and Allergy, Brigham and Women’s Hospital, Boston, USA. Massachusetts, Department Department of Clinical Genetics, Academic Medical Center, Amsterdam, The Netherlands. Department Department of Mathematics and Statistics, Boston University, Boston, USA. Massachusetts, 71 151 Department Department of Medicine, Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA. Massachusetts, 84 106 54 47 150 Electrocardiology, University of Glasgow Institute of and Cardiovascular Medical Sciences, Royal Infirmary, Glasgow, UK. Department Department of Cardiology, Division of Heart and Lungs, University Medical Centre Utrecht, Utrecht, The Netherlands. 67 Windland Smith Rice Sudden Death Genomics Laboratory, Department of Molecular Pharmacology and Experimental Therapeutics, Sanofi Sanofi Research and Development, Paris, France. Center Center for Biomedicine, European Academy (EURAC), Bozen/Bolzano Bolzano, Italy (affiliated institute of the University of Lübeck, 101 Durrer Durrer Center for Research, Cardiogenetic Cardiology Interuniversity Institute of Heart The Institute, Netherlands–Netherlands Cyprus Cardiovascular Cyprus and Cardiovascular Educational Research Trust, Nicosia, Cyprus. Department Department of Medicine, Division of Cardiology, Landspitali University Hospital, Reykjavik, Iceland. 116 110 127 55 Department Department of Medicine, University of Helsinki, Helsinki, Finland. 147 99 Cardiovascular Department, Cardiovascular Ospedali Riuniti and University of Trieste, Trieste, Italy. Institut Institut du Thorax, Centre Hospitalier de Universitaire Nantes, Université de Nantes, Nantes, France. Mindich Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Department Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia. Centre Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK. 93 Medical Medical Genetics Unit, Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy. 118 Public Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland. 131 65 80 77 76 Institute Institute of Human Genetics, Technische Universität München, Munich, Germany. Second Second Department of Internal Medicine, Landeskliniken, Paracelsus Medical University/Salzburger Program Program for Personalized and Genomic Medicine, University of Maryland, Baltimore, Maryland, USA. Department Department of Medicine, Division of Oncology, Washington University School of Medicine, St. Louis, Computational and Computational Systems Biology Program, Division of Biology and Biomedical Sciences, 46 60 112 Department Department of Clinical Chemistry, Fimlab Laboratories and University of Tampere School of Department Department of Primary Care and Population Health, University College London, Royal Free Campus, 39 43 95 Fundación Fundación Publica Galega de Medicina Xenómica, Servicio Galego de Saude, Santiago de Icelandic Icelandic Heart Association, Kopavogur, Iceland. Division Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 130 Department Department of Health Services, University of Washington, Seattle, Washington, USA. 140 126 142 Department Department of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Cardiovascular and Cardiovascular Cell Sciences Institute, St George’s University of London, London, UK. MRC MRC Epidemiology Unit, University of Cambridge, Institute of Metabolic Science, The The Labatt Family Heart Centre, The Hospital for Sick Children, Toronto, Ontario, Canada. 51 149 63 70 120 124 57 Institute Institute for Maternal and Child Health, “Burlo Garofolo” Trieste, Trieste, Italy. BHF BHF Glasgow Research Cardiovascular Centre, Institute of and Cardiovascular Medical Centre Centre for Experimental Medicine, Institute for Clinical and Experimental Medicine, 97 Department Department of Internal Medicine III, University Medical Center Schleswig-Holstein, 107 Department Department of Medical Epidemiology and Karolinska Biostatistics, Institutet, Estonian Estonian Genome Center, University of Tartu, Tartu, Estonia. 86 Division Division of Medical Genetics, University Hospital Basel, Basel, Switzerland. 103 73 90 Department Department of Medicine, University of Washington, Seattle, Washington, USA. Department Department of Science, Cardiovascular University of Leicester, Glenfield Hospital, Department Department of Boston Biostatistics, University School of Public Health, Boston, Partners Partners HealthCare Center for Personalized Genetic Medicine, Boston, Division Division of Cancer Epidemiology, German Cancer Research Centre, Heidelberg, 122 Department Department of Medicine, Vanderbilt University School of Medicine, Nashville, 144 115 Department Department of Genomics, Life and Brain Center, University of Bonn, Bonn, 83 The The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Department Department of Biomedical Engineering, Johns Hopkins University, 36 Chronic Chronic Disease Epidemiology and Prevention Unit, National Institute for 53 Research Research Programs Unit, Molecular Medicine, University of Helsinki, Department Department of Pediatrics, Division of Pediatric Cardiology, Mayo Clinic, 50 64 Medical Medical Research Council (MRC) Human Genetics Unit, Institute of Institute Institute of Medical Epidemiology, and Biostatistics Informatics, 105 88 38 Full Full list of members and affiliations appear in the Department Department of Epidemiology, University of Groningen, Office Office of Personalized Medicine, Vanderbilt University, a 153 68 135 DVANCE ONLINE PUBLICATION ONLINE DVANCE Grupo Grupo de Medicina Xenómica, Centro Nacional de Department Department of Internal Medicine, University of Groningen, 92 Christine Christine Kühne–Center for Allergy and Education, 117 Department Department of Medicine III, Medical Faculty, Martin Department Department of Medicine, Division of Cardiology, 139 137 109 Princess Princess Al-Jawhara Al-Brahim Centre of Department Department of Medicine, Hospital of Friedberg, 40 82 Cardiology Cardiology Division, General Massachusetts Faculty Faculty of Medicine, University of Iceland, 45 Division Division of Epidemiology and Community 134 Informatics Informatics and Biocomputing Platform, 148 114 Institute Institute of Epidemiology II, 111 129 79 Biobank Biobank PopGen, Institute of Laboratory Laboratory of Neurogenetics, 100 Clinical Clinical Department of Medical, Department Department of Biostatistics, 133 Department Department of Medicine, University 146 Vascular Screening and Institute Institute for Biological and General General Practice and Primary 102 75 Department Department of Biomedical 94 62 Faculty Faculty of Medical and Department Department of Biobanking Biobanking and

121 132 Nature Ge Nature 56 42 Department Department of 35 Institut Institut du Thorax, California California Pacific 152 Research Research Unit of DZHK DZHK (German 119 85 Institute Institute of Clinical Clinical Institute Institute for 59 Institute Institute of 96

Group Group n etics © 2014 Nature America, Inc. All rights reserved. Pennsylvania Pennsylvania State University, University Park, USA. Pennsylvania, Winston-Salem, North Carolina, USA. Children Research Institute, Toronto, Ontario, Canada. of Lübeck, Lübeck, Germany. (INM-1), Structural and Functional Organization of the Brain, Genomic Imaging, Research Centre Juelich, Juelich, Germany. University of London, London, UK. Spain. e Enfermidades Cardiovasculares Complexo Oftalmolóxicas, Hospitalario de Universitario Santiago de Compostela, Servicio Galego de Saude, Santiago de Compostela, Medicine, University of Turku, Turku, Finland. 166 University, Uppsala, Sweden. King’s College London, London, UK. for Genetics and Functional Genomics, Ernst Moritz Arndt University Greifswald, Greifswald, Germany. Institutes of Health, Baltimore, Maryland, USA. Consiglio Nazionale delle Ricerche, Monserrato, Cagliari, Italy. 157 Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands. University Medical Center Groningen, Groningen, The Netherlands. Nature Ge Nature addressed addressed to C.N.-C. ( Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. Minnesota, USA. Children, General Massachusetts Hospital, Boston, USA. Massachusetts, Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. Department Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland. First Department of Internal Medicine, Salzburg, Landeskliniken, Paracelsus Austria. Medical University/Salzburger 170 Global Global Epidemiology, AstraZeneca Research and Development, Mölndal, Sweden. n etics 184 Institute Institute for and Bioinformatics Systems Biology, Helmholtz Zentrum, Munich, Germany.

[email protected] ADVANCE ONLINE PUBLICATION ONLINE ADVANCE 175 165 Department Department of Neurology, General Central Hospital, Bolzano, Italy. Department Department of Clinical Physiology, Tampere University Hospital and University of Tampere School of Medicine, Tampere, Finland. 172 163 178 Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. School School of Health and Social Sciences, Dalarna University, Falun, Sweden. Human Human Genetics Research Centre, St George’s University of London, London, UK. 168 160 Department Department of Medicine, Turku University Hospital and University of Turku, Turku, Finland. Institute Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. ). 177 Department Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University,

159 Laboratory Laboratory of Genetics, Intramural Research Program, National Institute on Aging, US National 154 180 Netherlands Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands. Inspectorate Inspectorate of Health Care, The Hague, The Netherlands. 183 156 Department Department of Medicine, Division of Diseases, Cardiovascular Mayo Clinic, Rochester, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands. 186 171 These authors contributed equally to this work. Correspondence should be 182 Division Division of Population Health Sciences and Education, St George’s Pediatric Pediatric Surgical Research MassGeneral Laboratories, Hospital for 176 162 Genetics Genetics and Genome Biology Program, The Hospital for Sick 167 Department Department of Twin Research and Genetic Epidemiology, Research Research Centre of Applied and Preventive Cardiovascular 185 Department Department of Epidemiology, Julius Center for Health 164 173 Department Department of Medical Sciences, Uppsala 158 Institute Institute of Neuroscience and Medicine Istituto Istituto di Ricerca Genetica e Biomedica, 179 174 Center Center for Systems Genomics, Department Department of Neurology, University 181 Center Center for Biological Sequence 161 169 Interfaculty Interfaculty Institute Xenética Xenética de s e l c i t r A 155 Department Department of

11

© 2014 Nature America, Inc. All rights reserved. loci against 100,000 sets of randomly sampled control SNPs. Control SNPs SNPs Control SNPs. control sampled randomly of sets 100,000 against loci cance of the overlap, we compared the set of SNPs at 68 QT interval–associated Program using the command intersectBED Epigenomics in BEDTools To(v2.12.0). Roadmap assess the NIH signifi US the in N41) Ventricle Left (BC ChromHMM from the 1000 Genomes Project (CEU population) and computed overlap with ( ChromHMM using project Epigenomics Roadmap the from obtained modifications histone of combinations grating analyses. enhancer Cardiac adjustment for attenuated best the additional after substantially was association interval SNP–QT the when association interval tion. We inferred that the SNP after additional adjustment for the best experiment not owing available imputation). to SNP poor 1 within Mb of transcripts the SNPall waswith examinedSNP for 63 QT interval–associated interval–associated QT each SNPs of (5 SNPsAssociation were batch. and status disease site, study sex, age, for adjustment after levels, sion log with association for tested was genotype SNP try. European ances inferred to were samples with Analyses restricted genetically performed. was Project Genomes 1000 the in genotypes SNP to Imputation array. ST1.2 Genechip Affymetrix the using measured was expression RNA genome 6.0 Affymetrix the using genotyped were samples DNA hearts. donor unused from or transplantation undergoing failure heart free ventricular Left Network. Genomics Applied Myocardial the in individuals samples. in cardiac Expression populations ancestry European of genome the in tests variant common independent of number at set was significance fixed variance–weighted, inverse with at MANTEL sites using in two analytic parallel were performed genome meta-analysis. and analyses Association arrays. of ( factor inflation of quantile the distortion any test statistic minimize Hardy and rate call metric, Cohort results. with SNPs and SNPs Monomorphic samples. discovery all across available was SNPs million 2.5 of set common a that so SNPs HapMap unmeasured at genotypes impute to approaches model Markov hidden used studies All arrays. genotyping wide Genotyping, imputation and quality control. consent. informed provided all participants and committees, ethics local by reviewed were studies All pregnancy. or medications, presence of a pacemaker or implantable cardioverter defibrillator bundle branch block. Optional exclusions included use left of or QT interval–altering right of presence or ms >120 of duration QRS of presence and flutter Mandatory exclusions interval. included presence of or fibrillation atrial atrial case with few a population with largely individuals cohorts. Study ONLINE Nature Ge Nature r 2 > 0.8) with each of the 68 QT interval–associated loci using genotype data genotype using loci of 68 QT each the interval–associated > with 0.8) - wall tissue was collected at with from the was time of tissue subjects collected wall surgery cardiac - wide results from each cohort before meta before cohort each from results wide

- MET wide significance ( n - etics annotated enhancer elements in the left ventricle tissue sample tissue in ventricle the elements left enhancer annotated - - oot fr QT for Cohorts specific SNP filters on minimum MAF, imputation quality quality imputation MAF, minimum on filters SNP specific control sampling for traits not strongly associated with QT QT with associated strongly not traits for sampling control H λ ). Replication genotyping was performed using a variety variety a using performed was genotyping Replication ). ODS 5 β 0 . estimates larger than 100,000 were removed from all all from removed were 100,000 than larger estimates P < 5 × 10 × 5 < - Weinberg equilibrium equilibrium Weinberg Enhancer annotations were generated by inte by generated were annotations Enhancer - transcript association could explain the SNP–QT P < 4.4 × 10 Samples of cardiac tissue were acquired from were Samples of tissue acquired cardiac −8 - - , a threshold accounting for the effective effective the for accounting threshold a , interval association analyses included included analyses association interval or community cis - effects meta effects - eQTL SNP for the transcript in ques −5 Genomic control was applied to to applied was control Genomic 23 = 0.05/1,146 tests) were examined , GWAS used a variety of genome - 5 transcript associations meeting meeting associations transcript 1 . We identified SNPs in LD LD in SNPs identified We . cis - - based ascertainment and ascertainment based - P - quantile plot or quantile genomic - analysis. Genome analysis. analysis. Meta analysis. value were selected to to selected were value eQTL SNP.eQTL 2 - transformed expres transformed - wide array, and and array, wide 3 or METAL - analyses analyses - wide wide 2 4 2 9 - ­ ­ ­ ­ ­ -

related cardiac event (syncope or cardiac arrest). Six genes ( genes Six arrest). cardiac or (syncope event cardiac related sequencing of only samples showing an aberrant DHPLC elution profile. elution DHPLC aberrant an showing samples only of sequencing high of all case samples or an intermediate mutation detection platform (denaturing was using DNAperformed either direct Sanger sequencing–based sequencing in ion channel complexes. macromolecular For each gene, mutational analysis and or known expression cardiac interval genes in involvement the associated proximity to significance, the of signal absence of association, multiple nearby statistical nominal of basis the on chosen were genes candidate six These sis. cant loci, were selected for comprehensive ORF and splice CAV2 with symptomatic were (66%) 175 history, clinical documented a ( ( Canada Ontario, Amsterdam, The Netherlands ( ( du Nantes, Thorax, France ( (Institut centers recruitment LQTS congenital international 7 from derived of QTc QTcaverage 20 years; = 529 negative for mutations in LQT1–LQT3 (191 average (64%); females age = 27 analysis. mutation LQTS ( gene nearest the to ( block LD the of size for matched were and array genotyping 660W Affymetrix the from chosen were 52. 51. 50. 49. InWeb the in were database. which of 85 total, in genes 124 QT protein generated are that networks a using within matched random, 10,000 to it it within comparing proteins by individual and network the of significance the evaluates DAPPLE loci. different from proteins between on connections filtering teins, pro other through connections indirect as well as proteins seed the among QT variant common ated associ previously 7 from genes by encoded proteins as well as SCN4B) and SCN5A, KCNE1, KCNE2, CAV3, SNTA1, KCNJ2, CACNA1C, ANK2, AKAP9 network with 12 LQTS known mendelian Evaluator) Link to build and a analyze network of genes seed Protein Association (Disease DAPPLE used Wecalled cited. algorithm published been a had interaction the which in publications different of the of in scale and was the which interaction, reported experiment interaction the number the of neighborhood the of basis the on score a assigned probabilistic was interaction Each included. also were transfer, orthology for thresholds stringent using organisms, in genes other by orthologous encoded proteins between interactions reported pooled; were interactions human All high are which of 169,810 protein interaction Protein-protein n n = 23); and St George’s Hospital, London, UK ( = 72); University of Pavia, Pavia, Italy ( Italy Pavia, of Pavia, University = 72);

- Schwartz, P.J., Moss, A.J., Vincent, G.M. & Crampton, R.S. Diagnostic criteria for criteria Diagnostic R.S. Crampton, & G.M. Vincent, A.J., P.J.,Moss, Schwartz, for states chromatin of characterization and Discovery M. Kellis, & J. Ernst, testing multiple the of Estimation Daly,M.J. & Yelensky,Altshuler,D. Pe’er,I., R., of meta-analysis efficient and fast METAL: G.R. Abecasis, & Y. Li, C.J., Willer, the long QT syndrome. An update. An syndrome. QT long the genome. human (2010). the of annotation systematic Epidemiol. variants. common all nearly of studies association genomewide for burden scans. association genomewide IGC meta IGC - performance liquid chromatography, DHPLC) followed by direct DNA direct by followed chromatography, DHPLC) liquid performance , , SLC8A1 ≥ - - protein interactions protein protein interactions to identify proteins newly associated in the the in associated newly proteins identify to interactions protein 480 ms (

32 - - , , degree node degree analysis. We translated the new loci into genes, identifying identifying genes, into loci new the translated We analysis. SRL , 381–385 (2008). 381–385 , n n = 261; 86%) or score Schwartz = 24); Munich Medical International, Munich, Germany Germany Munich, International, Medical Munich 24); = and ± 25 kb if outside of a gene). a of outside if kb 25 TRPM7 ± - A cohort of 298 unrelated individuals with LQTS LQTS with individuals unrelated 298 of cohort A 5 SNPs), MAF of the lead SNP ( SNP lead the of MAF SNPs), 5 interval loci interval - - n ± confidence interactions across 12,793 proteins. proteins. 12,793 across interactions confidence label permutation label 2 = 91); Mayo Clinic, Rochester, Minnesota, USA = Rochester, Mayo 91); Minnesota, Clinic, 58 ms), who satisfied the case inclusion criteria criteria inclusion case the 58 satisfied who ms), in silico in 6 n . This database contains 428,430 interactions, interactions, 428,430 contains database This . = 30); The Hospital for Sick Children, Toronto, Bioinformatics ), ), derived from five new genome Circulation analyses. 3 , 4 - . We considered direct connections connections direct We . considered n related related proteins (KCNQ1, KCNH2, = 38); Academic Medical Centre, Centre, Medical Academic = 38);

88 26 2 7 n We used a public database of database We public a used Nat. , 782–784 (1993). 782–784 , , 2190–2191 (2010). 2190–2191 , . . We of ability the considered = 20)). Of the 265 cases with 5 2

≥

3.0 ( Biotechnol. - doi: site mutation analy n ± = was 298; 100%), 0.1) and distance distance and 0.1) 2 7 10.1038/ng.3014 ATP2A2 . . We the seeded

- 28 wide wide signifi 817–825 , ≥ 1 LQTS 1 - , , Protein Protein CAV1 Genet. ± ­ ­ ­ ­ - ,