University of Dundee

A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease Nikpay, Majid; Goel, Anuj; Won, Hong-Hee; Hall, Leanne M.; Willenborg, Christina; Kanoni, Stavroula Published in: Nature Genetics

DOI: 10.1038/ng.3396

Publication date: 2015

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Citation for published version (APA): Nikpay, M., Goel, A., Won, H-H., Hall, L. M., Willenborg, C., Kanoni, S., Saleheen, D., Kyriakou, T., Nelson, C. P., Hopewell, J. C., Webb, T. R., Zeng, L., Dehghan, A., Elver, M., Armasu, S. M., Auro, K., Bjonnes, A., Chasman, D. I., Chen, S., ... Farrall, M. (2015). A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nature Genetics, 47(10), 1121-1130. https://doi.org/10.1038/ng.3396

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0 0 ABHD2

Recombination rate (cM/Mb) rate Recombination ) (cM/Mb rate Recombination ) REST-NOA1 (cM/Mb rate Recombination i ) locus ( ) locus ) and the 19q13.11 ( 19q13.11 the ) and h ABHD2 b e –log (P value) –log (P value) –log (P value) ) locus ( ) locus 10 10 10 10 10 10 0 2 4 6 8 0 2 4 6 8 0 2 4 6 8 ) locus, the lead lead the locus, ) MFGE8 LOC728743 LINC00996 SMARCB C22orf15 MMP11 ZNF77

f GIMAP8 VPREB3 ), the 18q21.32 ( 18q21.32 the ), CHCHD10 SLC2A1 ACAN 24.2 DERL r r 89.4 5 150. 2 2 GIMAP7 0. 0. 0. 0. 0. 0. 0. 0. (abhydrolase LOC284889 1 MIF SMAD3 3 8 2 4 6 8 2 4 6 ) locus ( ) locus 1 h HAPLN3 GIMAP4 DDTL LOC391322 ). ( ). 3 GSTT2B MFGE 1 2 GSTT DD GSTTP1 3 89.5 24.4 T (milk fat(milk . GSTT 2 GSTTP2 GIMAP1–GIMAP 8 GIMAP6 i rs8042271 ABHD2 GIMAP2 , Position onchr.22(Mb Position onchr.15(Mb CABIN1 1 Position onchr.7(Mb j GIMAP1 50.4 ) Two recessive CAD loci. loci. CAD ) Two recessive ) locus ( ) locus GIMAP5 a 89.6 SUSD2 TMEM176 rs180803 24.6 ), the 7q36.1 ( 7q36.1 the ), POM121L9 TMEM176 ZNF507-LOC400684 5 SPECC1L–ADORA2 GGT5 AOC1 ABHD2 A SPECC1 150. 89.7 P

B rs3918226 d ADORA2A PMAIP1-MC4R 24.8 U L ), the 15q26.1 15q26.1 the ), 1 6 KCNH ADORA2A–AS introns and showed strong association with CAD. CAD. with association strong showed and introns ( in lies rs7212798 features in this locus to guide the nomination of a putative causal gene. ENCODEor eQTL (QTL),quantitativefactor locuslapping trait risk with higher levels in patients with unstable angina. There were no over NOS3 RLBP ABCB S A Fig. 4 Fig. 89.8 ASIC3 ATG9 SLC4A2 2 PB1 FANCI 1 At the chromosome 17q23.2 ( At 17q23.2 chromosome the NRPD3 CDK 8 GUCD1 AGAP FAST B TMUB1 25.0 50.8 LRRC75B CGT1 1 BCRP3 a 5 MIR6766 POM121L10 POLG K ) 3 – 89.9 MIR9–3 LINC00925 ) ) GBX1 h NOS3 ASB1 f MIR671 CHPF2 TOP1P2 ) Eight ) Eight ). Multiple variants in LD with rs7212798 map to to map rs7212798 with LD in variants Multiple ). ABCF PIWIL3 SMARCD3 0 25.2 P 151. 90.0 2 SGSM r LINC00928 2 0. 0. 0. 0. TMEM211 NUB1 ) RHCG ) WDR86 1 0 2 4 6 8 )

0 20 40 60 80 10 0 20 40 60 80 10 0 20 40 60 80 10

0 0 0

BCAS3

) (cM/Mb rate Recombination ) (cM/Mb rate Recombination ) (cM/Mb rate Recombination f c j i –log10 (P value) –log10 (P value) –log10 (P value) –log10 (P value) 10 10 10 15 10 (breast carcinoma amplified sequence 3) 3) sequence amplified carcinoma (breast 0 2 4 6 8 0 2 4 6 8 0 5 0 2 4 6 8 118. 32.0 RP11–112H10. BZRAP1–AS1 THEG 56.5 MP MIR142 RNF4 BZRAP1 MIR4736 SUPT4H 8 1 0 r r HSF5 MTMR O STK3 5 .5 2 2 0. 0. 0. 0. 0. 0. 0. 0. 3 RAD51C SNORA4 SNORA3 RPL27A 2 4 6 8 2 4 6 8 3 1 TRIM66 4 4 BCAS3 PPM1E KSR2 57.0 5 rs11830157 TMEM9B–AS 18.2 ST AKIP CTC–360P9. 5 TRIM37 C11orf1 TMEM9B 9. ASCL PRR1 32.5 P Position onchr.11(Mb Position onchr.12(Mb Position onchr.19(Mb MIR301A 1 MIR454 SMG8 SKA2 GDPD KRT8P4 NRIP osition onchr.17(Mb 9 0 SCUBE MIR4729 3 MIR569 1 6 YPEL AC011518. 1 3 57.5 1 DENND5 RP11–567L7. 1 3 ) locus, the lead intronic SNP intronic lead the ) locus, 2 C 2 1 DHX4 TMEM41B 118. SNORA2 rs12976411 A LT IPO7 1 0 Z PTRH2 VMP1 LOC64465 ZNF143 C NF507 MIR2 rs10840293 RP11–178C3. 6 RPS6KB RFC5 TBC1D3P1–DHX40P1 DPY19L .5 AC007773.2 58.0 3 1 4 WEE1 TUBD1 1 RNFT SWAP70 WSB2 33.0 6 MIR4737 LOC645638 RP11–540A21. 1 HEATR6 SBF2-AS1 3 VSIG10 PDCD CA U 1 2 PEBP1 SCARNA2 4 RGS9BP ANKRD2 NUDT19 C17orf6 5 SP32 58.5 18.6 10.0 TDRD1 s e l c i t r A APPBP2 2 0 PPM1D 4 SBF2 C 7 2 rs7212798 BCAS3 ) ) ) ) SLC7A9 TAOK3 C19orf4 AD CAND1.1 59.0 M EP89 33.5 BCAS 118. AMPD 10.5 GPATCH RHPN 0 MRVI1–AS SUDS3 MTRNR2L8 1 MIR448 3 WDR8 C17orf8 r r RNF141 3 2 2 LYVE 2 0. 0. 0. 0. 0. 0. 0. 0. LRP3 TBX2 SLC7A1 8 1 MRVI encodes encodes 2 4 6 8 2 4 6 8 8 5 1 2 1 1 BCAS3 0 0 20 40 60 80 10 0 20 40 60 80 10 0 20 40 60 80 10 0 20 40 60 80 10

0 0 0 0

) (cM/Mb rate Recombination ) (cM/Mb rate Recombination ) (cM/Mb rate Recombination ) (cM/Mb rate Recombination  -

© 2015 Nature America, Inc. All rights reserved. mon, small-effect susceptibility variants for complex diseases has has diseases complex for variants susceptibility small-effect mon, a as wall pathogenesis. CAD of vessel component critical arterial the of biology the explore that suggest hypotheses approach unbiased this by implicated genes Finally, tions. annota functional with regions in enriched are and genes to close or within clustered are significantly alleles Moreover, risk-associated >1.5. OR having <0.05 MAF with variants detect to powered was it hypothesis variant disease–common common the ports sup strongly analysis comprehensive this Thus, of >5%. a frequency with alleles risk by represented are loci, identified previously the of but as one as all well analysis, present in the found associations CAD identified newly ten all Rather, CAD. for heritability missing the of associations and indel are polymorphisms unlikely to synthetic explain a portion significant effect, larger of variants low-frequency that conclude to us Genomes allowed has set 1000 reference this the with by Analysis Project. enhanced is traits complex of architecture genetic the investigate GWAS to of ability the that Wedemonstrate DISCUSSION ZNF507 ( LD strong in are which and rs71351160, rs12981453 including SNPs, several that suggests locus this of CAD (genotypic OR = 0.69) in the recessive model. ENCODE analysis of unchar an for ( RNA gene a noncoding in acterized lies 0.09) = (MAF rs12976411 SNP lead in recapitulated phenotype a are associated with severe obesity, hyperphagia and insulin resistance, in variants coding loss-of-function rare and (AMPK), kinase protein AMP-activated including proteins, multiple with interacts ras 2) ( recessive a in model (genotypic OR risk = 1.12) is CAD intronic to with associated 0.36) = (MAF rs11830157 the of regions ( LD in are which of most significance, genome-wide at CAD with associated were that region centered on this variant spans 1.2 Mb and 21 includes variants 2-cM A pseudogene). 9, nucleoporin–like transmembrane POM121 lead SNP rs180803 lies in susceptibility. CAD underlying gene implicate further to SNPs proxy or lead the for diabetes triglyceride higher and 2 type concentrations (HDL) including lipoprotein and lower high-density factors, risk obesity-associated and ( (BMI) index mass body with associated also are risk CAD proxy with higher that variants) were corresponding associated species oxygen MC4R reactive of generation the by death cell hypoxic (HIF)-1 factor inducible of 1) protein and 200 kb downstream 12-myristate-13-acetate–induced intergenic SNP rs663129 lies 266 kb downstream of angiogenesis to contributing thus cells, actin organization and control cell polarity and motility in endothelial the Rudhira protein, which has been shown to activate Cdc42 to affect s e l c i t r A  available publically with imputation genotype on heavily leaned The success of the GWAS meta-analysis strategy in mapping com of GWASthe strategy The success meta-analysis ( 19q13.11 chromosome the At ( 12q24.23 chromosome the At At the chromosome 22q11.23 ( ( 18q21.32 chromosome the At MC4R ZNF507 is a well-studied obesity-related locus, and the variant (and (and variant the and locus, obesity-related well-studied a is Fig. 4 37– , overlap with ENCODE functional elements. functional ENCODE with overlap , (melanocortin 4 receptor) ( receptor) 4 (melanocortin ( 4 1 i Fig. 4 Fig. . . However, we found no eQTL data or ENCODE features ) ) and overlaps with ENCODE functional elements. KSR2 SPECC1L j ). The minor allele showed a protective effect in in effect protective a showed allele minor The ). r 2 > 0.6) with the lead SNP and map to intronic intronic to map and SNP lead the with 0.6) > and and α POM121L9P –induced proapoptotic gene that mediates mediates that gene proapoptotic –induced LOC400684 ADORA2A Ksr2 POM121L9P -null mice -null PMAIP1 ZNF507 Fig. 4 Fig. (encoding the noncoding RNA KSR2 r 3 2 5 genes ( genes ) and is 3.4 kb downstream downstream kb 3.4 is and ) > 0.8) and are intronic to to intronic are and 0.8) > . KSR2 g - ) locus, the lead SNP SNP lead the locus, ) - 4 ). ). LOC400684 MC4R 2 - . PMAIP1 ADORA2A (kinase suppressor of Fig. 4 Fig. MC4R PMAIP1 ) locus, the lead lead the locus, ) h P as the causal causal the as is a hypoxia- a is ). 4 = 6 × 10 × 6 = 3 ) locus, the the locus, ) , given , that given ) ) locus, the (phorbol- KSR2 −42 3 6 - - - - ) .

risk loci, loci, risk meta-analysis using a recessive model, which identified two new CAD alleles with lower-frequency particularly traits, inherited recessively to detect underpowered is model systematically traits inherited dominantly detect also to power adequate has conveniently but variance dominance traits no detect with to powered optimally is GWAS in used widely model GWAS. HapMap-based in missed were that detecting lower-frequency, imperfectly imputed susceptibility variants in analysis Project of our Genomes 1000 sensitivity the and reinforce showed strong associations mechanisms, LDL via cholesterol–linked SNPs in Key meta-analysis that includes ancestry groups from multipleglobal continents. a to tractable are that variants low-MAF numerous includes differentiation analyses. Although lower-frequency variants often show geographical in loci GWASprevious the these power reduced of discovering meta- ( tagged imperfectly or SNPs for four CAD were loci absent of either the ten identified newly lower-frequency variants and the of integration ( of indel polymorphism coverage of terms in era HapMap the from up step- a substantial provides Project Genomes 1000 The sets. training genes with rare mutation burdens. For example, example, For burdens. mutation rare with genes that GWAS acknowledge on SNP based array power to data has analysis resolve limited to important is It setting. population-based a in to ants with respect risk prediction in CAD susceptibility, specifically vari low-frequency of role the for expectations temper will ciations asso synthetic of evidence no provided and heritability CAD of 2% explained <0.05 MAF with variants 15 that finding the and variants these for associations significant of paucity relative Yet the modest. power to detect alleles of moderate penetrance (OR > 1.3) might seem the of million 1.5 the 2.7 million lower-frequencyvariation, variantsgenetic included human in theof meta-analysis withtotality the ing FDR an with variants 202 the of 10% represented they association, CAD for enriched systematically were indels that lower- no evidence was there of Although variants. panel frequency extended an and indels includes it as CAD, for ity scan. association additive conventional vulnerability and the extent of the thrombotic reaction to plaque plaque presence to the in infarction myocardial to reaction predispose may disruption, thrombotic the of extent the and two plaque vulnerability as the such factors, therefore, additional However, cases; related. intimately infarction are myocardial of majority vast databases. association in limiting the 1000 cross-referencing Genomes Project and HapMap that of use the can proxy be may variants this reflect in part data sets; available in eQTLs or QTLs factor risk with overlap of suggestions nomination and the design of future studies. functional We found few and traits for diseases other reported relevant to CAD pathogenesis. This phenomenon has previously been types the cell in of particularly features, overlap ENCODE with for associations CAD enrichment independent and strong was there Furthermore, genes. to close or within clustered significantly were CAD for heritability missing the of 1% than less explain and controls and cases large of in series studies sequencing whole-exome by discovered only were mutations These CAD. for mutations protective or risk-conferring (ref. Association analysis under the customary additive inheritance inheritance additive customary the under analysis Association Our GWAS explores two potential sources of missing heritabil missing of sources potential two explores GWAS Our Coronary atherosclerosis underlies the development of the the of development the underlies atherosclerosis Coronary variants CAD-associated the that showed analysis Annotation 4 5 ), ), KSR2 APOC3 APOE and and 5 , the 1000 Genomes Project phase 1 v3 training set set training v3 1 phase Project Genomes 1000 the , a DVANCE ONLINE PUBLICATION ONLINE DVANCE (ref. (ref. and and ZNF507 4 5 . r 4 PCSK9 2 < 0.8) in the HapMap 2 training set, which which set, training HapMap 2 the in 0.8) < 6 ) and and ) - LOC400684 , which mediate their effects on CAD CAD on effects their mediate which , NPC1L1 q value <5%. In terms of survey of terms In <5%. value 4 8 and can guide candidate gene candidate and can guide , that escaped detection in a in detection escaped , that (ref. (ref. 4 4 . However, the additive additive the However, . 4 4 4

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© 2015 Nature America, Inc. All rights reserved. onlin Note: Any Supplementary Information and Source Data files are available in the the in versio available are references associated any and Methods M www.cardiogramplusc4 Tools/g porta eqtl browser, eQTL Chicago URLs. targets. new identify hence, and, disease of etiology complex the into insights new provide may atherosclerosis in explored been previously not have but association tion of new aspects of vessel wall biology that are implicated by genetic levels and few target directly investiga vessel Detailed wall processes. lipid of manipulation CAD circulating risk lowering operate through for treatments drug existing of majority large the but cessation), ing and smok pressure of blood (control wall vessel the target strategies links to biology vascular can be established. A number of preventative firm before validation and investigation further substantial require ( ( effects sparing ( signaling ABHD2 and VSMC ( and migration leukocyte adhesion cell including processes, diverse in involved are products gene Their genes so implicated have the well-documented roles CAD, in for vessel wall biology.gene candidate plausible a suggest associations eQTL and precedent biological data, genomic where loci identified newly it for is that, In notable some of respect, so this at the large scale. very completely unbiased approach and, to our knowledge, is the first to do CAD GWASbased meta-analysis data association with risk factor traits as well as an earlier HapMap 2– studies Metabochip the and genes, candidate on for traits; HumanCVD example, BeadChip factor risk in involved genes some targeted because particularly analyses also previous but the of CAD of etiology the in factors risk known these of importance undoubted the of because partly unsurprising, are findings Such hypertension. and inflammation systemic in cated impli genes including factors, risk atherosclerosis known other to are related genes susceptibility other of lipoproteins; metabolism the the and in levels lipid role circulating notably CAD, known for factors a risk of with biology proteins encode susceptibility CAD of CAD.of progression and development suggest that loci may certain mechanisms related distinct affect to the they findings, these to data are substantiate required as experimental of a sclerosis large artery athero to due embolism or thrombosis involving strokes ischemic However, infarction. to but to not a the leading precipitant events myocardial atherosclerosis predispose might it that suggesting infarction, myocardial with In thrombosis. contrast, and/or rupture plaque of risk the increase cifically infarction myocardial of risk CAD of Nature Ge Nature BCAS3 et It is important to note that these putative new susceptibility genes genes susceptibility new putative these that note to It important is analyses large-scale in far thus implicated genes the of Several / e e version of the pape ; Genotype-Tissue Expression (GTEx) Portal, Portal, (GTEx) Expression Genotype-Tissue ; h l.org/home n of the pape the of n Ensembl database, database, Ensembl ods euvadis-das (ref. (ref. (ref. (ref. 4 9 HDAC9 . We confirmed that that confirmed We . n SMAD3 etics 3 5 5 5 )) and NO signaling ( signaling NO and )) ) VM peoyi sicig ( switching phenotypic VSMC )), ADORA2A / ; Geuvadis Data Browser, Browser, Data Geuvadis ; showed a stronger association with CAD than than CAD with association stronger a showed

r (refs. (refs. / . r ; CARDIoGRAMplusC4D Consortium, Consortium, CARDIoGRAMplusC4D ; ADVANCE ONLINE PUBLICATION ONLINE ADVANCE . HDAC9 d.org 5 1 http:// . Although further epidemiological as well epidemiological further . Although 56 http://www. 5 / , 8 5 shows even stronger association with with association stronger even shows 5 . and and 0 7 , suggesting that this locus may spe may locus this that suggesting , ABO eqtl.uchicago.edu/cg ) at-nlmaoy n infarct- and anti-inflammatory )), 5 4 . The current experiment . adopts a The current experiment MFGE8 is particularly associated with with associated particularly is NOS3 ensembl.org (ref. (ref. (ref. (ref. http://w SWAP70 2 3 5 5 4 , 2 5 design was based was based design 9 )). http://www.gtex 3 REST )), angiogenesis angiogenesis )), drew on earlier earlier on drew

/ i-bin/gbrowse/ ; University of of University ; ww.ebi.ac.uk/ (ref. 2 0 , TGF- ), 2 online online http:// 6 ) ) and β ------

A.G., A.G., H.-H.W., L.M.H., C.P.N., J.R.T. and M.F. Variant annotation: M.N., A.G., W. Zhao, M.d.A., P.S.d.V., N.R.v.Z., M.F.F., J.R.T. and M.F. Meta-analysis: M.N., A.C.M., N.P., L.Q., E.S., M. L.M.R., R.S., Scholz, A.V.S., E.T., A.U., X.Y., W. Zhang, C. Grace, S.G., Jie Huang, S.-J.H., Y.K.K., M.E.K., K.W.L., X.L., Y.L., L.-P.L., E.M., J.C.H., T.R.W., L.Z., A.D., M.A., S.M.A., K.A., A.B., D.I.C., S.C., I.F., N.F., C. Gieger, analyst: M.N., A.G., H.-H.W., L.M.H., C.W., S. Kanoni, D.S., T. Kyriakou, C.P.N., A.F.S., D.J.S., P.A.Z., M.P.R., R. Clarke, S. Kathiresan, H.S. and N.J.S. Cohort data A. Hamsten, S.L.H., E.I., J.W.J., P.J.K., J.S.K., I.J.K., O.M., A.M., M.P., D.K.S.,R.R., M. Samuel, S.H.S., K.S.Z., D.A., J.E.B., J.C.C., C.B.G., R.E., R. Collins, V.G., A.S.H., C.M.L., P.K.M., N.H.M., N.M., T.M., F.-ur-R.M., A.P.M., N.L.P., A.P., A.R., L.S.R., P.F., A.H.G., O.G., Jianfeng Huang, T. Kessler, L. I.R.K., Lannfelt, W.L., L. Lind, phenotyping: D.S., J.C.H., A.D., M.A., K.A., Y.K.K., E.M., S.S.A., F.B.,L.M.R., G.D., A. Hofman, E.I., J.S.K., T.L., D.K.S.,R.R., A.F.S., R. Clarke, P.D. and N.J.S. Cohort A.P.M., M.S.N., N.L.P., J.S., K.E.S., S.T., L.W., I.B.B., J.C.C., M.F.F.,R. Collins, G.D., D. Gauguier, A.H.G., M.H., B.-G.H., S.J., L. Lind, C.M.L., M.-L.L., P.K.M., H.-H.W., S. Kanoni, D.S., J.C.H., Jie Huang, M.E.K., Y.L., L.-P.L., A.U., S.S.A., L.B., J.E., H.W., S. Kathiresan, P.D.,R.M., H.S., N.J.S. and M.F. Cohort genotyping: V.S., D.K.S., S.M.S., U.S., A.F.S., D.J.S., J.T., P.A.Z., C.J.O’D., M.P.R., T.L.A., J.R.T.,I.J.K., T.L., R.J.F.L., O.M., A.M., W.M., C.N.P., M.P., T.Q., D.J.R., P.M.R., R.R., S.R., A. Hamsten, T.B.H., S.L.H., C.H., A. Hofman, E.I., C.I., J.W.J., P.J.K., B.-J.K., J.S.K., I.D., S.E.E., R.E., T.E., M.F.F., O.H.F., M.G.F., C.B.G., D. Gu, V.G., A.S.H., Cohort oversight: D.A., E.B., I.B.B., E.P.B., J.E.B., J.C.C., L.A.C., R. Collins, J.D., are included in the We are grateful for support from our funders; more acknowledgments detailed administrative staff in each of the studies who have contributed to this project. We sincerely thank the participants and the medical, nursing, technical and 14. 13. 12. 11. 10. 9. 8. 7. 6. 5. 4. 3. 2. 1. reprints/index.htm at online available is information permissions and Reprints The authors declare no competing interests.financial H.W.,R.R., S. Kathiresan, P.D., H.S. and N.J.S. CARDIoGRAMplusC4D executive committee: J.D., D. Gu, A. Hamsten, J.S.K., S. Kathiresan, P.D.,R.M., H.S., N.J.S. and M.F. (secretariat: J.C.H. and R. Clarke). M.E.K., N.R.v.Z., C.N.P., C.J.O’D.,R.R., M.P.R., T.L.A., J.R.T., J.E., R. Clarke, H.W., steering committee: M.N., A.G., H.-H.W., L.M.H., S. Kanoni., J.C.H., D.I.C., L.M.H., T. Kyriakou, J.C.H., H.W., S. Kathiresan, H.S., R.M., N.J.S. and M.F. Project H.-H.W., T. Kyriakou, J.C.H. and T.R.W. Manuscript drafting: M.N., A.G., H.-H.W., AU Acknowledgments COM

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© 2015 Nature America, Inc. All rights reserved. Biostatistics, Karolinska Biostatistics, Institutet, Stockholm, Sweden. University, Uppsala, Sweden. 67 und Statistik, Universität zu Lübeck, Lübeck, Germany. Academy of Medical Sciences and Peking Union Medical College, Beijing, China. 62 UMRS 1138, Centre de Recherche des Cordeliers, Paris, France. 58 57 Canada. of Dundee, Dundee, UK. London, London, UK. Reykjavik, Iceland. 48 School, Boston, USA. Massachusetts, Stanford University, Stanford, California, USA. and Biostatistics Epidemiology, University of USA. Pennsylvania, Philadelphia, Pennsylvania, Tampere, Finland. 41 New York, New York, USA. Mannheim, University of Heidelberg, Mannheim, Germany. Health, Korea. Chungcheongbuk-do, 36 Sweden. 32 31 North Carolina, USA. University Biostatistics, of Glasgow, Glasgow, UK. National Center of Diseases, Cardiovascular Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Hospital, Boston, USA. Massachusetts, Helsinki, Finland. 22 Tartu, Tartu, Estonia. Medical Center, Rotterdam, the Netherlands. 17 Department of Population Health, University of Oxford, Oxford, UK. Leicester Biomedical Cardiovascular Research Unit, Glenfield Hospital, Leicester, UK. USA. Pennsylvania, Philadelphia, Pennsylvania, Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK. Lübeck, Germany. USA. Human Genetic Research, General Massachusetts Hospital, Boston, USA. Massachusetts, Harvard University, Cambridge, USA. Massachusetts, Department of Medicine, University of Oxford, Oxford, UK. 1 T J C Vilmundur M John E L Asif Rasheed Andrew P N Nature Ge Nature M Ruth John R Pierre A Zalloua S Paul C Ruddy Ruddy Canadian Genetics Cardiovascular Centre, University of Ottawa Heart Institute, Ottawa, Ontario, Canada. tephen erho erho W aiyuan aiyuan rwin P Bottinger rwin Institut Institut für Christian Epidemiologie, Albrechts Universität zu Kiel, Kiel, Germany. School of Medicine, Lebanese American University, Beirut, Lebanon. Heart Center Leipzig, Cardiology, University of Leipzig, Leipzig, Germany. and Neuroepidemiology Ageing Research Unit, School of Public Health, Faculty of Medicine, Imperial College of Science, Technology and Medicine, London, UK. LIFE Research Center of Civilization Diseases, Leipzig, Germany. Department of Clinical Chemistry, Fimlab Tampere,Laboratories, Finland. Department of Boston Biostatistics, University School of Public Health, Boston, USA. Massachusetts, Molecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden. Research Unit of Molecular Epidemiology, Helmholtz Zentrum Research München–German Center for Health, Environmental Neuherberg, Germany. Department of Health, National Institute for Health and Welfare, Helsinki, Finland. DZHK (German Centre for Research), Cardiovascular partner site Munich Heart Alliance, Munich, Germany. hristian hristian Hengstenberg olin olin adeem H adeem ary F ary Feitosa artin artin Farrall outer Jukema 8 Department Department of Sciences, Cardiovascular University of Leicester, Leicester, UK. M D M 56 N 34 L anesh Ridker T Platform Platform for Genome Analytics, Institutes of and Neurogenetics Integrative and Experimental Genomics, University of Lübeck, Lübeck, Germany. cPherson Wellcome Trust Sanger Institute, Hinxton, UK. ehtimäki Palmer M W hompson n etics M

ang S M G chwartz 24 10 orris 43 34 13 51 allick udnason Diabetes Diabetes and Obesity Research Program, University of Helsinki, Helsinki, Finland. DZHK DZHK (German Research Center for Research), Cardiovascular partner site Lübeck, Germany.Hamburg-Lübeck-Kiel, Human Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA. 2 27 25 21 30 , Department Department of Public Health, University of Helsinki, Helsinki, Finland. , 88

53 90 75 , 54 3 Division Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA. Institute Institute of Epidemiology II, Helmholtz Zentrum Research München–German Center for Health, Environmental Neuherberg, Germany. , , Department Department of Cardiology, Ealing Hospital National Health Service (NHS) Trust, Middlesex, UK. ADVANCE ONLINE PUBLICATION ONLINE ADVANCE 62 , , , 83 41 26 81 1 , , Ilja 55 131 , , 3 , , O , M 39 40 131 , 128 , Population Population Health Research Institute, Hamilton Health Sciences, Department of Medicine, McMaster University, Hamilton, Ontario, , , , , , M , 76 125 71 42 103 K scar H scar Franco Genetics Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, New York, USA. S for the , , Julie 69 aria aria 120 , , , , arkus Perola , , Ruth J F amuli Ripatti , , Panos , , Jeanette han , , Transplantation Laboratory, Haartman Institute, University of Helsinki, Helsinki, Finland. M N D , 49 104 C , arinder arinder 121 emuth arkku arkku 16 , hristopher J 50 S 38 , , Pekka J S , 47 amuel E , , Udo 17 , , Alistair Vth Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Medical Rheumatology), Faculty of Zaman 26 Institute Institute for Medical Informatics, Statistics and Epidemiology, Medical Faculty, University of Leipzig, Leipzig, Germany. C Buring , Albert , HofmanAlbert Harvard Harvard Medical School, Boston, USA. Massachusetts, D AR S 91 eloukas L E 19

M 46 N oos , rdmann 13 S Estonian Estonian Genome Center, University of Tartu, Tartu, Estonia. D 92 13 19 Department Department of Anesthesia, Critical Care and Pain Medicine, General Massachusetts Hospital, Harvard Medical eedorf 18 ehra ieminen , , 29 K 23 Io Center Center for Diseases, Non-Communicable Karachi, Pakistan. , , Roberto 84 , S 25 , , Department Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, 22 39 S arhunen , vati H , , 5 G 34 M Hall O , , John Cardiovascular Research Cardiovascular Center, General Massachusetts Hospital, Boston, USA. Massachusetts, – , D 40 66 72 RA 11 24 71 , ’ aria aria 51 D iego iego Ardissino Department Department of Public Health and Caring Sciences, Geriatrics, Uppsala University, Uppsala, Sweden. 35 , Punjab Punjab Institute of Cardiology, Lahore, Pakistan. , , , 122 3 , , 108 39 9 129 , Robert , Roberts Robert Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. National National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, USA. Massachusetts, T onnell T , M 98 10 Charles Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, 77

homas homas Quertermous , , Alexandre F , , S G , C , , Anders Hamsten , Robert , Robert plus 131 , , O hah E 41 61 18 razia Franzosirazia N

C losua 49 lle lle Department Department of Sciences, Cardiovascular University of Leicester, Glenfield Hospital, Leicester, UK. 16 , , , Heribert , , 105 ancy ancy Icelandic Icelandic Heart Association, Kopavogur, Iceland. hambers 35 Deutsches Deutsches Herzzentrum München, Technische Universität München, Munich, Germany. E C 79 63 M rik rik Ingelsson , , , Bong-Jo 4 , , Juha 126 M Hypertension Hypertension Division, Fuwai Hospital, National Center for Diseases, Cardiovascular Chinese D elander 93 59 42 eitinger L C ,

Department Department of Harokopio University,Dietetics-Nutrition, Athens, Greece. , , 127 C Department Department of Clinical Chemistry, University of Tampere School of Medicine, Pedersen larke 85 S onsortium tephen 64 , , , S 52 86 S S M Klinikum Klinikum Rechts der Isar, Munich, Germany. 68 inisalo 115 , tewart chunkert , , 23 53 9 109 Department Department of Medical Sciences, Epidemiology,Cardiovascular Uppsala 15 15 uredach uredach P Reilly Institut Institut für Integrative und Genomik, Experimentelle Universität zu Lübeck, E 97 K Institute Institute for Molecular Medicine Finland (FIMM), University of Helsinki, 17 , , Veikko , Clinical Clinical Trial Service Unit and Studies Epidemiological Unit (CTSU), Nuffield 89 ric ric Boerwinkle , , Hugh im , , , , Andres 7 99 , 73 Department Department of Medicine, Harvard Medical School, Boston, Massachusetts, C 3 , Rory , Rory E 70 , 52 , , 32 45 45 37 hristopher B , 77

74 1 T E Department Department of Epidemiology and Imperial Biostatistics, College , , Annette Peters Division Division of Medicine, Cardiovascular Department of Medicine, , , , , , , Jaspal , , 33 amara amara B Harris 112 pstein 27 , , Fazal-ur-Rehman D K 16 State State Key Laboratory of Disease, Cardiovascular Fuwai Hospital, , 33 W 45 avid avid J athleen athleen , , S C , Science Science for Life Laboratory, Uppsala University, Uppsala, 17 D alomaa , , 25 M atkins ollins 37 C , Division Division of Preventive Medicine, Brigham and Women’s aniel aniel J Rader 131 94 Center Center for Genome Science, Korea National Institute of etspalu arlos arlos Iribarren 72 S 20 , ,

S , , All All India Institute of Medical Sciences, New Delhi, India. 18 K T Institute Institute of Molecular and Cell Biology, University of 14 114 43 N tott Department Department of Epidemiology, Erasmus University 15 2 õnu ooner E National National Institute for Health Research (NIHR) 2 G 116 , ilesh ilesh J , Division Division of Medicine, Cardiovascular Radcliffe 12 3 87

, , , , S , ranger Perelman Perelman School of Medicine, University of 131 123 L T 19 tirrups , , Ingrid B Borecki , , Adrienne 50 E 17 hemistocles hemistocles D 100 , 54 , , 20 , , Joachim Faculty Faculty of Medicine, University of Iceland, sko 70 53 , S harambir 30 Medical Medical Research Institute, University , , Department Department of Medical Epidemiology and S , , ekar ekar , 113 89 W , , S amani 79 M 4 L tanley tanley , , 11 106 19 infried infried , , , oukianos oukianos 102 65 114 emon D , , 80 Institut Institut für Medizinische Biometrie K 95 , , Iftikhar J ongfeng , , athiresan , , , C

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, ,  © 2015 Nature America, Inc. All rights reserved. or or M.F. ( work. should Correspondence be addressed to H.W. ( Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia. USA. Lung, and Blood Institute Division of Intramural Research, Bethesda, Maryland, USA. Diagnostics, University Hospital Leipzig, Medical Faculty, Leipzig, Germany. and Cardiovascular Medical Sciences, Faculty of Medicine, University of Glasgow, Glasgow, UK. 122 Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA. University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA. Canada. Institute, Perelman School of Medicine at the University of USA. Pennsylvania, Philadelphia, Pennsylvania, California, USA. of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria. Disease, Cardiovascular Lund University, University Hospital Malmö, Malmö, Sweden. Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Imperial College London, London, UK. 105 103 101 Sweden. Leeds, UK. Scientifico (IRCCS) Istituto di Ricerche Mario Farmacologiche Negri, Milan, Italy. 96 Center, Washington, DC, USA. Cardiovascular, Institut Hospital del Mar Mèdiques d’Investigacions (IMIM), Barcelona, Spain. Berlin, Berlin, Germany. of Public Health and Primary Care, University of Cambridge, Cambridge, UK. 88 86 Beijing, China. Netherlands. Carolina, USA. Cardiology, Attikon Hospital, School of Medicine, University of Athens, Athens, Greece. Liverpool, Liverpool, UK. Technische Universität München, Munich, Germany. 73 s e l c i t r A 1 0 Department Department of Genetics, Harvard Medical School, Boston, USA. Massachusetts, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, USA. Associazione per lo Studio della Trombosi in Cardiologia, Pavia, Italy. Institut für Helmholtz Humangenetik, Zentrum Research München–German Center for Health, Environmental Neuherberg, Germany.

Department Department of Prosthetic Dentistry, Center for Dental and Oral Medicine, University Medical Center Hamburg, Germany.Hamburg-Eppendorf, Department of Forensic Medicine, University of Tampere School of Medicine, Tampere, Finland. Durrer Center for Research, Cardiogenetic Amsterdam, the Netherlands. Department of Cellular and Molecular Medicine, Cleveland Clinic, Cleveland, Ohio, USA. 128 [email protected] 116 Department Department of Health Sciences, University of Leicester, Leicester, UK. 100 99 Department Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland. Laboratory Laboratory of Epidemiology, Demography and Biometry, National Institute on Aging, US National Institutes of Health, Bethesda, Maryland, USA. 82 Cardiovascular Genetics Cardiovascular and Genomics Group, Research Atherosclerosis Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, 80 84 Department Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands. 113 Department Department of Haematology, University of Cambridge, Cambridge, UK. National National Institute of Diseases, Cardiovascular Karachi, Pakistan. Department Department of Genetics, Perelman School of Medicine at the University of USA. Pennsylvania, Philadelphia, Pennsylvania, 92 77 Institute Institute of Medical and Human Genetics, Berlin, Charité Berlin, Universitätsmedizin Germany. Department Department of Cardiology, Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland. 95 Division Division of and Endocrinology Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, USA. Massachusetts, ). 107 Division Division of Diseases, Cardiovascular Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA. [email protected] 75 Red Red Crescent Institute of Cardiology, Hyderabad, Pakistan. 119 Oklahoma Oklahoma Center for Oklahoma Neuroscience, City, Oklahoma, USA. 87 130 Human Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA. 104 These These authors contributed equally to this work. 125 91 Interuniversity Cardiology Interuniversity Institute of the Netherlands, Utrecht, the Netherlands. 121 Berlin Berlin Aging Study II; Research Group on Geriatrics, Charité Universitätsmedizin Harvard Harvard School of Public Health, Boston, USA. Massachusetts, 129 ), ), S. Kathiresan ( 118 98 Department Department of Epidemiology, University of Washington, Seattle, Washington, USA. 97 85 Princess Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Leeds Leeds Institute of Genetics, Health and University Therapeutics, of Leeds, Department Department of Sciences, Pharmaceutical College of Pharmacy, University of Department Department of Research, Cardiovascular Istituto di Ricerca e Cura a Carattere Division Division of Cardiology, Azienda Ospedaliero di Universitaria Parma, Parma, Italy. 127 110 79 81 Cardiology Cardiology Division, General Massachusetts Hospital, Boston, Massachusetts, Synlab Synlab Academy, Synlab Services, Mannheim, Germany. Department Department of Medicine, Duke University Medical Center, Durham, North Department Department of Cardiology, Leiden University Medical Center, Leiden, the 112 102 Stanford Cardiovascular Stanford Institute, Cardiovascular Stanford University, Stanford, 94 Kaiser Kaiser Permanente Division of Research, Oakland, California, USA. 124 89 MedStar MedStar Heart and Vascular Institute, MedStar Washington Hospital [email protected] Imperial Imperial College Healthcare NHS Trust, London, UK. Institute Institute for Laboratory Medicine, Clinical Chemistry and Molecular 106 Cardiovascular Science, Cardiovascular National Heart and Lung Institute, a 109 DVANCE ONLINE PUBLICATION ONLINE DVANCE Department Department of Clinical Sciences, Hypertension and 115 University University of Ottawa Heart Institute, Ottawa, Ontario, 76 117 Department Department of University Biostatistics, of 83 Department Department of Pediatrics, College of Medicine, National National Human Genome Center at Beijing, ), ), R.M. ( 93 131 Grupo Grupo de y Epidemiología Genética These These authors jointly supervised this [email protected] 74 78 Institute Institute of Human Genetics, Second Second Department of 120

114 Public Public Health Sciences 126 Nature Ge Nature 123 108 111 Cardiovascular Cardiovascular National National Heart, Institute Institute of Mindich Mindich Child Clinical Clinical Institute 90 Department Department n

) etics

© 2015 Nature America, Inc. All rights reserved. sizes were used following the GCTA joint association analysis. The standard standard The analysis. association GCTA joint the following used were sizes (ref. 40% was CAD of ability model ( < (0.86 The –log mated. β contributing four in analysis ( studies regression multiple–logistic standard a for those with results association GCTA joint comparing by analysis association 0.90 between (ref. 0.95 and be will genotypes experimental on based regression multiple and samples genotyped 1,000 of panel reference a using between correlation expected the that precise acceptably and unbiased are correlations LD as well as the samplematching size of the reference genotype ancestry panel to ensure appropriate that estimated on depends analysis this of accuracy The LD. strong in variants associated multiple be might there where situations in model joint association in the final retained is variant not the lead necessarily analysis, this In individuals). 1,092 for genotypes includes that populations database and continents for all set 1 v3 training phase genotype Project Genomes 1000 the (here reference a from derived information LD and statistics association summary of basis the on model regression multiple approximate software GCTA using performed was results meta-analysis GCTA and heritability analysis. set. training v3 1 phase Project Genomes 1000 the in prevalent cal that the FDR was controlled (theoretical conservatively demonstrated data imputed PROCARDIS the of replicates permuted 1,000 conditions dependency regression positive under led Stata qqvalue program estimation. FDR ( tics was adjusted for by a second application of the genomic control procedure model random-effects index by Cochran’swas assessed heterogeneity gram GWAMA the using pro for meta-analysis submitted were studies of the 60% values were submitted for Variantsmeta-analysis. that were retained in at least method control genomic the by ( compared with from those other studies to flipping systematic of detect alleles (ref. IMPUTE2 for >0.4 info_proper or Minimac for >0.3 rsq metric, quality imputation an and combined) controls and cases in (estimated >0.005 MAF for filtered vidually control. Data quality ( used were dosages allelic or probabilities genotype analysis, additive the for quality; imputation variable for allow to studies contributing all by were analyzed probabilities genotype analyses, dominant and recessive the For data. v3 1 phase Project Genomes 1000 of continents) (all populations pooled the allele. in major frequencies allele to the reference by for identified were alleles homozygotes major and Minor in risk reference a with compared heterozygotes with was pooled allele minor the for homozygotes for log(GRR) heterozygotes the where model pooled dominant a (iii) and in allele; major risk the for homozygotes and reference a with compared was the for allele homozygotes for minor log(GRR) the where model recessive a (ii) alleles; of risk number the to proportional was a for genotype (log(GRR)) ratio) risk log(genotype the where model an (i) additive regression: by logistic analyzed analysis. Association ONLINE doi: Supplementary Fig. 5 Supplementary Supplementary Fig. 6 Fig. Supplementary P Supplementary Table 1 Supplementary values and (regression coefficients) standard errors were accurately approxi > 0.20) toward yielding slightly inflated values. inflated slightly yielding toward 0.20) > Heritability calculations were based on a multifactorial liability-threshold liability-threshold multifactorial a on based were calculations Heritability q 10.1038/ng.3396 value = 0.026, 95% CI = 0.017–0.038) in the context of the LD patterns patterns LD the of context the in 0.017–0.038) = CI 95% 0.026, = value 6 6 3 7 5 . Following an inverse variance–weighted fixed-effects meta-analysis, meta-analysis, fixed-effects variance–weighted inverse an Following . 0 , and variants showing marked heterogeneity were reanalyzed using a using reanalyzed were heterogeneity marked showing , variants and assuming that the disease prevalence was 5% and herit that the total prevalence that the disease assuming ρ Supplementary Fig. 7 Fig. Supplementary < 0.93), with the GCTA method showing an insignificant trend trend insignificant an showing method GCTA the with 0.93), <

MET 6 9 10 ). We investigated the empirical accuracy of the GCTA joint GCTA joint the of accuracy empirical the We ). investigated H FDR was assessed using a step-up procedure coded in the the in coded procedure step-up a using assessed was FDR ( ODS P 6 values) from the two analyses were positively correlated correlated were positively two from analyses the values) 1 Association data for study were Association each contributing indi 6 Three models of heritable disease susceptibility were were susceptibility disease heritable of models Three 6 ). Allele frequencies for each study were binned and and binned were study each for frequencies Allele ). 6 ). Overdispersion of association statistics was assessed was assessed statistics of association ). Overdispersion 7 ). . Overdispersion in the resulting meta-analysis statis in the meta-analysis . resulting Overdispersion . . This procedure has to been reported be well control ). 3 ); multiple regression estimates of allelic effect effect allelic of estimates regression multiple ); ). This comparison showed that 95% of the the of 95% that showed comparison This ). Joint association analysis of the CAD additive 6 2 ( Supplementary Table 15 Table Supplementary P values based on the GCTA method method GCTA the on based values Q statistic 6 4 and the 6 6 8 9 ; simulations based on based ; simulations q . Simulations suggest suggest Simulations . value = 0.05, empiri P values from ‘exact’ from values 1 I 7 ), and adjusted adjusted and ), 2 , which fits an an fits which , inconsistency inconsistency ------

variant’s variant, (for each replicates 1,000 with sampling Monteby Carlo generated were estimates heritability the for errors were grouped into CAD-relevant types and were into types others ( grouped CAD-relevant ciations from the University of Chicago eQTL browser (accessed July 2014), 2014), July (accessed browser eQTL Chicago of University the from ciations known with cross-referenced were loci associated newly The associations. factor risk for examined were variants new the with ( LD in SNPs all sets, data 2–imputed HapMap on based mainly were factors GWAS catalog (NHGRI) using downloads CAD for data GWAS factors consortium large-scale risk including resources, available heritable publically with associations for scanned were survey. QTL factor Risk assumed. was model risk additive estimates The across I studies. these type vary error typically was which set at 5 × 10 meta-analysis; model additive on frequency, integrate information and imputation allele quality sample size, the from estimates error standard controlled double–genomic on based risk were the calculations parameter rate, error I Non-centrality type size. sample the the and quality, imputation and size), frequency allele (effect risk genetic the of magnitude calculations. Power replicates). 1,000 the and, finally, the standard error across of is estimates calculated the heritability across summed is draw, heritability replicate the ENCODE data retrieved from the Ensembl database. Ensembl the from retrieved data ENCODE the issue or a more of consequence general our on being based analysis a of subset CAD-specific a reflect could which features), DHS 19.8% and factor cription 202 The FDR were variants less in feature prevalent slightly these groups trans (10.4% experiments. 1,640 of set data extended an in features (34%) DHS catalog NHGRI The the status. genic/intergenic and TFBS ENCODE DHS, HM, variables explanatory status independent the with FDR202 predicting model multiple regression tic Table Supplementary 13 in cell types ENCODE 11 for summarized are status) (FDR202 <5% FDR with ants vari of list the in inclusion ENCODE with status reporting annotation ANNOVAR and feature tables contingency Multiway phenotype. CAD the to repair and (injury myoblasts and metabolism lipid example, (for hepatocytes on roles of in the basis CAD potential pathophysiology; their DHSs and ( sets—HMs, TFBSs functional strongly enriched for genic annotation status. Variants were grouped into three mapped to one or more ENCODE features, andtheir ANNOVARvariants annotation instatus ( ENCODE features were Variants that overlapped one or more of these features were cross-tabulated with types for a total of 379 ENCODE experiments that identified 6,099,034 features.cell different 11 in evidence functional of types different 100 summarizes list org/Hom at browsed be can database Ensembl the in Funcgen Perl API module (release 75). The list of ENCODE experiments stored introns. to map variants genic in shown is meta-analysis additive CAD annotation genic a in the included variants of status 9.4 the million The annotation (42%). status assigned were annotation intergenic without Variants mapped that variants to assigned was status downstream or Upstream database. annotation gene analysis. software ANNOVAR ENCODE and Annotation data published other and 2014) June (accessed Browser Data Geuvadis the 2014), June (accessed Portal GTEx the r 2 > 0.8 based on the 1000 Genomes Project phase 1 v3 ALL reference panel) panel) 1 reference v3 ALL phase Project Genomes on 1000 the > based 0.8 ENCODE features were downloaded from the Ensembl database using the the using database Ensembl the from downloaded were features ENCODE β Supplementary Table 11 Table Supplementary o_sapiens/Experiment 8 value value 3 37– project has previously mapped 4,492 significant GWAS SNPs from 41 , 71– ± s.e.m. estimate, heritability is calculated for each is calculated heritability estimate, s.e.m. 7 7 3 4 and the National Human Genome Research Institute Institute Research Genome Human National the and Power to detect genetic associations depends on the the on depends associations genetic detect to Power (accessed June 2011) to transcription factor (12%) and and (12%) factor transcription to 2011) June (accessed 1 8 ≤ (version August 2013) based on a GRCh37/hg19 GRCh37/hg19 a on based 2013) August (version 1 kb from the transcript start or end, respectively. respectively. end, or start transcript the from kb 1 7 . Contingency table counts were modeled by a counts were table logis modeled . Contingency 4 The ten newly identified CAD-associated loci loci CAD-associated identified newly ten The (accessed May 2014). As previous GWAS risk for previous As 2014). May (accessed 8 0 ), vascular endothelial cells (atherosclerosis cells endothelial vascular ), /Sources?db=core;ex= 8 2 and for the 3 CAD-relevant cell types in in types cell CAD-relevant 3 the for and ) were selected as being the most relevant relevant most the being as selected were ) Supplementary Table 10 22 , β 28 values are drawn randomly from the from are randomly drawn values , Supplementary Table 8 Supplementary Variants were annotated using using annotated were Variants 29 Supplementary Table Supplementary 9 , 75– http://Feb2014.arc n 7 variants within each replicate replicate each within variants 9 . cis Supplementary Table Supplementary 12 project-ENCODE - and and - Nature Ge Nature trans ); 50% of variants hive.ensembl. -eQTL asso -eQTL ; 86% of the the of 86% ; ). Cell types ). types Cell β −8 value by value n , , and an - etics . This 8 1 ­ - - - ) )

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