Published at www.nejm.org July 18, 2007 (10.1056/NEJMoa072366)
Genomewide Association Analysis of Coronary Artery Disease
Nilesh J. Samani, F.Med.Sci., Jeanette Erdmann, Ph.D., Alistair S. Hall, F.R.C.P., Christian Hengstenberg, M.D., Massimo Mangino, Ph.D., Bjoern Mayer, M.D., Richard J. Dixon, Ph.D., Thomas Meitinger, M.D., Peter Braund, M.Sc., H.-Erich Wichmann, M.D., Jennifer H. Barrett, Ph.D., Inke R. König, Ph.D., Suzanne E. Stevens, M.Sc., Silke Szymczak, M.Sc., David-Alexandre Tregouet, Ph.D., Mark M. Iles, Ph.D., Friedrich Pahlke, M.Sc., Helen Pollard, M.Sc., Wolfgang Lieb, M.D., Francois Cambien, M.D., Marcus Fischer, M.D., Willem Ouwehand, F.R.C.Path., Stefan Blankenberg, M.D., Anthony J. Balmforth, Ph.D., Andrea Baessler, M.D., Stephen G. Ball, F.R.C.P., Tim M. Strom, M.D., Ingrid Brænne, M.Sc., Christian Gieger, Ph.D., Panos Deloukas, Ph.D., Martin D. Tobin, M.F.P.H.M., Andreas Ziegler, Ph.D., John R. Thompson, Ph.D., Heribert Schunkert, M.D., for the WTCCC and the Cardiogenics Consortium
Background Modern genotyping platforms permit a systematic searchfor inherited components of complex diseases. We performed ajoint analysis of two genomewide association studies of coronaryartery disease.
Methods We first identified chromosomal loci that were stronglyassociated with coronary artery disease in the Wellcome TrustCase Control Consortium (WTCCC) study (which involved 1926 casesubjects with coronary artery disease and 2938 controls) andlooked for replication in the German MI [Myocardial Infarction]Family Study (which involved 875 case subjects with myocardialinfarction and 1644 controls). Data on other single-nucleotidepolymorphisms (SNPs) that were significantly associated withcoronary artery disease in either study (P<0.001) were thencombined to identify additional loci with a high probabilityof true association. Genotyping in both studies was performedwith the use of the GeneChip Human Mapping 500K Array Set (Affymetrix).
Results Of thousands of chromosomal loci studied, the same locushad the strongest association with coronary artery disease inboth the WTCCC and the German studies: chromosome 9p21.3 (SNP,rs1333049) (P=1.80x10–14 and P=3.40x10–6, respectively).Overall, the WTCCC study revealed nine loci that were stronglyassociated with coronary artery disease (P<1.2x10–5and less than a 50% chance of being falsely positive). In additionto chromosome 9p21.3, two of these loci were successfully replicated(adjusted P<0.05) in the German study: chromosome 6q25.1(rs6922269) and chromosome 2q36.3 (rs2943634). The combinedanalysis of the two studies identified four additional locisignificantly associated with coronary artery disease (P<1.3x10–6)and a high probability (>80%) of a true association: chromosomes1p13.3 (rs599839), 1q41 (rs17465637), 10q11.21 (rs501120), and15q22.33 (rs17228212).
Conclusions We identified several genetic loci that, individuallyand in aggregate, substantially affect the risk of developmentof coronary artery disease.
Coronary artery disease and its main complication, myocardialinfarction, are leading causes of death and disability worldwide.1Lifestyle and environmental factors play an important role intheir development.2 In addition, these complex diseases clusterin families, suggesting a substantial genetic cause.3 Despiteextensive exploration of many genes, strong evidence of a moleculargenetic association with coronary artery disease or myocardialinfarction remains to be obtained.
The recent development of high-density genotyping arrays providesunprecedented resolution for whole-genome assessment of variantsassociated with common diseases.4 Using the GeneChip Human Mapping500K Array Set (Affymetrix), which simultaneously types approximately500,000 genetic variants, the Wellcome Trust Case Control Consortium(WTCCC) recently reported on an analysis of data from approximately2000 people (and a shared set of 3000 controls) for each ofseven complex diseases, including coronary artery disease.5Several loci showed strong associations with coronary arterydisease, but the large number of statistical tests poses thechallenge of discriminating between true and false associations.By providing a detailed analysis of the WTCCC data in conjunctionwith data from another large genomewide association study, theGerman MI [Myocardial Infarction] Family Study, we sought robustevidence for associations of genetic loci with the risk of coronaryartery disease and myocardial infarction.
Methods
Subjects
All participants in both studies were of white European origin.Detailed descriptions of recruitment and ascertainment in bothstudies are given in the Supplementary Appendix, available withthe full text of this article at www.nejm.org. Local ethicscommittees approved the study protocols, and all participantsgave written informed consent.
WTCCC Study
The 1988 case subjects in the WTCCC study had a history of eithermyocardial infarction or coronary revascularization before theage of 66 years, as well as a strong family history of coronaryartery disease.6,7 Two independent control groups were studied:1504 controls from the British 1958 Birth Cohort and 1500 controlsselected from a sample of blood donors recruited as part ofthe WTCCC project.5
German MI Family Study
The 875 case subjects in the German MI Family Study were personswho had myocardial infarction before the age of 60 years andat least one first-degree relative with premature coronary arterydisease.8,9 The 1644 controls were selected from a well-characterizedrandom sample of German residents, stratified according to sexand age.10
Genotyping
All analyses were performed with the use of the GeneChip HumanMapping 500K Array Set, including a StyI and a NspI chip. Detailson genotype-calling algorithms, quality criteria (at the levelof both the individual and the SNP), and validation steps aredescribed in the Supplementary Appendix. This left 377,857 SNPsin 1926 case subjects and 2938 controls in the WTCCC study and272,602 SNPs in 870 and 772 case subjects for the StyI chipand the NspI chips, respectively, and from 1644 controls forboth chips in the German study.
Statistical Analysis
Before performing the genetic analyses, we examined the datafrom each cohort individually for population substructure andascertained that such variation was negligible in both studies(see the Supplementary Appendix). We then undertook three typesof genetic analysis. First, after identifying the SNPs withthe strongest associations with coronary artery disease in theWTCCC sample, we sought to replicate these loci in the Germanstudy (primary analysis). Second, we combined data on otherSNPs for which there was evidence of an association in eitherstudy, to identify additional loci with a low probability ofbeing falsely positive (combined analysis). Third, we examinedthe data from both studies for associations with coronary arterydisease among SNPs in genes reported to be associated with thisdisease (candidate-gene analysis).
Primary Analysis
All autosomal SNPs that showed evidence of a significant associationwith coronary artery disease in the WTCCC study (P<0.001with use of the two-sided Cochran–Armitage trend test)were assessed for the false-positive-report probability (FPRP).11(The rationale for the FPRP calculations and the assumptionsunderlying them are given in the Supplementary Appendix.) Asmall FPRP suggests that the association of a SNP is unlikelyto be a false positive result. A SNP with an FPRP of less than0.5 (i.e., one for which the chance of a truly positive associationwas greater than 50%), as well as SNPs within 100 kb in eitherdirection of this SNP, also with P values of less than 0.001,were considered to represent a single locus. Formal replicationtesting of such loci was then performed in the German studywith the use of the lead SNP (defined as the SNP with the lowestFPRP) for each locus and adjustment for multiple testing. AP value of less than 0.05 with use of the two-sided Cochran–Armitagetrend test was considered to indicate statistical significance.Haplotype analysis was carried out on replicated loci, as describedin the Supplementary Appendix. The power for replication inthe German study was estimated for each locus for an odds ratiofor myocardial infarction of 1.25 per allele and an adjustedsignificance level of 0.05.
Combined Analysis
All SNPs that showed evidence of a significant association (P<0.001)with coronary artery disease in the WTCCC study or with myocardialinfarction in the German study were combined to assess theircombined FPRP. Pooled odds ratios for the risk allele and 95%confidence intervals were calculated within each stratum, accordingto the study.
Candidate-Gene Analysis
Candidate genes were identified as described in the Supplementary Appendix.On the GeneChip array, we distinguished between SNPs that wereidentical to those identified in previous studies as showingan association with coronary artery disease and SNPs that werein complete or near-complete linkage disequilibrium with thoseidentified in previous studies as showing an association withcoronary artery disease. We used either of two measures of linkagedisequilibrium — an r2 value of 0.8 or more or a disequilibriumcoefficient (D') of 0.9 or more — on the basis of datafrom the International HapMap Project.12
Population Attributable Fractions
Population attributable fractions were estimated in the Germanstudy with the use of the lead SNP from each of the three replicatedloci. Adjustments were made for age, sex, the interaction betweenage and sex, the Prospective Cardiovascular Munster (PROCAM)study score, and the Framingham risk score. Further detailsare given in the Supplementary Appendix.
In both the WTCCC and the German studies, the case subjectswere young (mean age at first event, approximately 50 years)and had a strong familial basis for their disease (Table 1).
Table 1. Baseline Characteristics of Case Subjects in the WTCCC Study and the German MI Family Study.
Primary Analysis
The distribution of P values for the association of SNPs withcoronary artery disease in the WTCCC study and with MI in theGerman Study, according to chromosome, is shown in Figure 1.In the WTCCC study, 396 SNPs were significantly associated withcoronary artery disease (P<0.001). Thirty of these SNPs clusteringin nine chromosomal regions met the predefined criterion ofan FPRP of less than 0.5 (Table 1 in the Supplementary Appendix).We tested these nine loci for a significant association withmyocardial infarction in the German study. Three of the loci— chromosomes 9p21.3, 6q25.1, and 2q36.3 — had suchan association, even after adjustment for multiple testing fornine loci (Table 2).
Figure 1. Signal-Intensity Plots Showing the Association of Single-Nucleotide Polymorphisms (SNPs) with Coronary Artery Disease or Myocardial Infarction in the Genomewide Association Analysis.
The –log P values are for the association of each SNP with coronary artery disease or myocardial infarction, from two-sided Cochran–Armitage tests for trend. Only SNPs of sufficient quality (see the Supplementary Appendix) are shown. The signal-intensity plots of all SNPs with significant associations (P<0.001) were visually inspected by two independent reviewers in each study to rule out possible artifactual results due to miscalling of genotypes (see Supplementary Appendix). Within each chromosome shown on the x axis, the data are plotted from the p-ter end. The y-axis scale for associations in the WTCCC study (Panel A) differs from the scale for the German MI Family Study (Panel B).
Table 2. Loci from the WTCCC Study with Significant Associations with Coronary Artery Disease That Were Replicated in the German MI Family Study.
The locus on chromosome 9p21.3 showed the strongest signal inboth the WTCCC and the German studies (P=1.80x10–14 andP=3.40x10–6, respectively) (Figure 1 and Table 2). Thecombined P value for the association with coronary artery diseaseof the lead SNP in that locus, rs1333049, was 2.9x10–19,with the risk increased by 36% per copy of the C allele (95%confidence interval [CI], 27 to 46). Approximately 22% of thestudy participants were homozygous for this allele, with anadditional 50% carrying a single copy. In the WTCCC and Germanstudies, a similar pattern of association with respect to directionand magnitude of effect was found across a region of approximately100 kb on 9p21.3 (Figure 2). The 19 SNPs showing an associationwithin this region were in strong linkage disequilibrium. However,two blocks could be distinguished, with strong linkage disequilibriumwithin each block (average D'>0.90) and moderate linkagedisequilibrium between blocks (average D', approximately 0.60)(Figure 2). Three SNPs in block 1 (rs7044859, rs1292136, andrs7865618) and one SNP in block 2 (rs1333049) were sufficientto tag the region. Haplotype analysis showed that the associationwas mainly due to two mutually exclusive haplotypes for thefour SNPs (TTGG and ACAC) (Supplementary Appendix). In the WTCCCstudy, the odds ratio for coronary artery disease with the ACAChaplotype (frequency, 0.324 among controls and 0.386 among casesubjects), as compared with the TTGG haplotype (frequency, 0.333among controls and 0.271 among case subjects), was 1.48 (95%CI, 1.34 to 1.64) per copy of the haplotype (P=2.1x10–14).The results of haplotype analysis in the German study were similar(Supplementary Appendix).
Figure 2. Association Signal for Coronary Artery Disease on Chromosome 9.
The –log P values, calculated with the use of the two-sided Cochran–Armitage test for trend, according to the location on chromosome 9 are shown (I). Arrows indicate the lead SNP. The inset graph shows the correlation between the odds ratios for coronary artery disease associated with the minor allele of SNPs from the WTCCC and German studies on chromosome 9. The genomic locations of genes or expressed-sequence tags (ESTs) (according to the Reference Sequence collection of the National Center for Biotechnology Information [NCBI]) are also shown (II). All data are from the Genome Browser of the University of California, Santa Cruz (NCBI build 35). Red boxes represent recombination hot spots, as estimated from HapMap data (Phase II, release 21) (III). Disequilibrium coefficient values for SNPs genotyped in case subjects with coronary artery disease in the WTCCC study, generated with the use of Haploview software, are shown (IV). There were two distinct blocks (1 and 2) of SNPs with significant associations. Disequilibrium coefficients for all SNPs from HapMap CEU data (from persons of Northern and Western European ancestry) across chromosome 9, generated with the use of Haploview software, are shown (V). In IV and V, the strength of the linkage disequilibrium between SNPs increases from white to blue to red (white: disequilibrium coefficient <1 and LOD score <2; blue: disequilibrium coefficient=1 and LOD score <2; pink or light red: disequilibrium coefficient <1 and LOD score 2; and bright red: disequilibrium coefficient=1 and LOD score 2). References relevant to II, III, and IV are given in the Supplementary Appendix.
The lead SNP on chromosome 6q25.1 (rs6922269, with a combinedP value of 2.90x10–8 for the association with coronaryartery disease) is in the gene for methylenetetrahydrofolatedehydrogenase (NADP±dependent) 1–like protein (MTHFD1L).All positive SNPs in the region are located in introns in themiddle portion of the gene (Fig. 1A in the Supplementary Appendix).The risk allele (A) for rs6922269 has a prevalence of approximately25%, with the risk increased by 23% per copy (95% CI, 15 to33). Haplotype analysis showed that only the two haplotypescarrying the A allele were more frequent in case subjects thanin controls, confirming the increased odds ratio for coronaryartery disease with the A allele in the single-locus analysis(Supplementary Appendix).
The third replicated locus, on chromosome 2q36.3 (rs2943634,with a combined P value of 1.61x10–7 for the associationwith coronary artery disease) encompasses a region of 233 kb(Fig. 1B in the Supplementary Appendix). There is only one pseudogene(ENSG00000197218) located within this region. The risk allele(C) for rs2943634 has a prevalence of approximately 65%, withthe risk increased by 21% per copy (95% CI, 13 to 30). Haplotypeanalysis showed that the other associations observed in thelinkage-disequilibrium block around rs2943634 are due to linkagedisequilibrium with it (Supplementary Appendix).
The association of the loci on chromosomes 9p21.3 and 6q25.1with myocardial infarction in the German study was not affectedby adjustment for cardiovascular risk factors and scores. Incontrast, the odds ratio for myocardial infarction at the locuson chromosome 2q36.3 was reduced after such adjustment (Table 2).Further analysis showed that this locus was also significantlyrelated to the body-mass index (P=0.004 in an additive model),the presence or absence of hypertension (P=0.04), and the levelof low-density lipoprotein cholesterol (P=0.03). The fully adjustedpopulation attributable fractions for the three loci in theGerman study are shown in Table 2. The combined fraction forthe three loci was 0.38 (95% CI, 0.13 to 0.55). The predictionof myocardial infarction on the basis of the Framingham riskscore and the PROCAM study score was substantially improvedby adding the predictive information of these three loci tothe model (deviance, 191.48; P<1x10–10).
For the six loci with an FPRP of less than 0.5 in the WTCCCstudy for which the associations were not replicated in theGerman study, the results of each of the two studies are shownin Table 2 of the Supplementary Appendix. The power to replicatethese loci ranged from 43 to 80%.
Combined Analysis
The combined analysis of all SNPs identified four additionalloci with a high likelihood of association with coronary arterydisease (FPRP<0.2) (Table 3, and Table 3 in the Supplementary Appendix).The locus on chromosome 1p13.3 involves the PSRC1 gene, whichencodes a proline-rich protein (Fig. 1C in the Supplementary Appendix).The other region of chromosome 1 (1q41) maps to the melanomainhibitory activity 3 (MIA3) gene (also known as ARNT or TANGO)(Fig. 1D in the Supplementary Appendix). The SNPs associatedwith chromosome 10q11.21 cluster in a region 100 kb downstreamof the CXCL12 gene (also known as the gene for stromal-cell–derivedfactor 1 precursor) (Fig. 1E in the Supplementary Appendix).Finally, the SNP on chromosome 15q22.33 is an intronic SNP inthe SMAD3 gene (Fig. 1F in the Supplementary Appendix). SMAD3is a transcriptional modulator activated by transforming growthfactor (TGF-) and activin type 1 receptor kinase.
Table 3. Additional Loci Associated with Coronary Artery Disease from Combined Analysis of Data from the WTCCC and German MI Family Studies.
Subphenotype and Subgroup Analysis
In the WTCCC study, approximately 30% of subjects had confirmedevidence of coronary artery disease but had not had a myocardialinfarction at the time of recruitment (Table 1). When subjectswith coronary artery disease only and those with coronary arterydisease and myocardial infarction were analyzed individually,the odds ratios for both phenotypes across all seven chromosomalregions remained significant (Table 4 in the Supplementary Appendix).For the chromosome 15 locus, the effect size was significantlygreater (P=0.004) in the subgroup of patients with coronaryartery disease only than in the subgroup with coronary arterydisease and myocardial infarction. Analysis according to sexin the two studies combined showed that all seven loci affectedthe risk of coronary artery disease to a similar extent in womenand in men (Table 5 in the Supplementary Appendix).
Candidate-Gene Analysis
From a literature search, we identified 142 SNPs, in 91 candidategenes, that had been reported to be associated with coronaryartery disease or myocardial infarction. Only 13 of these SNPsare represented on the GeneChip array. For 36 genes, there wereno primary or tagging SNPs. For the other genes, we identified270 SNPs in complete or near-complete linkage disequilibriumwith the SNPs that were previously found to be associated withcoronary artery disease or myocardial infarction. Although anumber of SNPs had a promising association with coronary arterydisease in the WTCCC study or with myocardial infarction inthe German study, only two linked SNPs (rs17489268 and rs17411031)tagging the Ser447Ter variant in the lipoprotein lipase genehad a significant association in both studies (Table 6 in theSupplementary Appendix).
Discussion
We jointly analyzed data from two distinct but complementarygenomewide association studies of coronary artery disease andmyocardial infarction that performed ascertainment in similarways and that involved the same genotyping platform. Sequentialand combined analyses of the two data sets allowed us to identifyseveral new genetic loci, which individually and in aggregateconsiderably affect the risk of CAD.
The association of chromosome 9p21.3 with coronary artery diseasewas the strongest found in the WTCCC study.5 The finding thatthis locus was also most strongly associated with myocardialinfarction in the German study provides compelling proof ofits involvement in coronary artery disease. The evidence ofassociation is strong, the risk variant is common, and eachcopy of the allele substantially increases the probability ofthe disease. These findings unequivocally demonstrate a majorgenetic risk variant at this locus.
Indeed, during revision of this manuscript, two other genomewidestudies reported a strong association of the same 9p21.3 locuswith coronary artery disease and myocardial infarction,13,14making this the most highly replicated locus for coronary arterydisease identified to date. The region contains the coding sequencesof genes for two cyclin-dependent kinase inhibitors, CDKN2A(encoding the prototypic INK4 protein p16INK4a) and CDKN2B (encodingp15INK4b), which play an important role in the regulation ofthe cell cycle and may be implicated, through their role inTGF-–induced growth inhibition, in the pathogenesis ofatherosclerosis.15,16,17 Although regulation of one or bothof the CDKN2 genes may explain the association with coronaryartery disease, other explanations also need to be considered,including involvement of the methylthioadenosine phosphorylase(MTAP) gene or of other expressed sequences located in the region.The same region has also recently been associated with increasedsusceptibility to type 2 diabetes,18,19,20 raising the possibilityof a shared, rather than a single, mechanism causing both coronaryartery disease and diabetes.
The association of chromosome 6q25.1 with coronary artery diseasemaps to the MTHFD1L gene, which encodes the mitochondrial isozymeof C1-tetrahydrofolate (THF) synthase.21,22 The family of C1-THFsynthases is used in a variety of cellular processes, particularlythe synthesis of purine and methionine.21 Therefore, MTHFD1Lactivity may also contribute to plasma homocysteine levels,21,23raising the possibility of a link between MTHFD1L variants andthis risk factor for coronary artery disease.24 A preliminaryanalysis of data from 1070 persons in the AtheroGene study25has not revealed an association between rs6922269 genotypesand plasma homocysteine levels (Tiret L, Blankenberg S: personalcommunication). Nevertheless, further studies in a wider rangeof subjects are needed to investigate this possibility.
Our findings demonstrate the main strength of a genomewide approach— namely, the possibility of identifying hitherto unsuspectedloci that increase susceptibility to complex diseases. However,the mechanisms underlying the newly identified associationsare often not immediately obvious. Indeed, the mechanisms forthe association of signals on chromosomes 9p21.3, 6q25.1, and2q36.3 with coronary artery disease all require elucidation.Similarly, none of the chromosomal loci identified in the combinedanalysis have previously been strongly linked to coronary arterydisease. However, genes in several of the loci (PSRC1 at 1p13.3,MIA3 at 1q41, and SMAD3 at 15q22.33) play a role in cell growthor inhibition.26,27,28,29 These processes are fundamental forthe formation and progression of atherosclerotic plaque andalso for plaque instability.30 Our results suggest that geneticregulation of these processes plays an important role in thedevelopment of coronary artery disease and myocardial infarction.
Some loci from the WTCCC study that we attempted to replicatedid not show association in the German study. These negativedata underscore the need to view genomewide associations withcaution, despite their statistical strength, until they havebeen replicated in appropriate validation samples. In this context,caution should also be exercised with regard to the four lociidentified in our combined analysis.31
Our primary objective was to identify loci with significantassociations with coronary artery disease independently of anybiologic assumptions. Nonetheless, the genotyping platform alsooffered an opportunity to examine genetic variants in geneswith previously reported associations. Indeed, several showedevidence of an association in one of our studies. However, onlySNPs in the lipoprotein lipase gene had evidence of an associationin both studies. This finding is in agreement with those inmost recent systematic studies that were largely unsuccessfulin replicating initial findings in candidate genes.32 However,many of the previously studied gene variants are poorly taggedon the GeneChip array, which clearly fails to cover the fullextent of even common variation in these genes.
Whether our findings can be translated into better preventionor treatment for coronary artery disease will become clear onlyover time and with further research. Although the odds ratiosfor each locus are modest, as anticipated for a polygenic disorder,the estimates of population attributable fractions for the threevalidated loci are substantial, both individually and in aggregate.This observation offers the potential for improved overall coronaryrisk prediction. However, the case subjects in both studieshad a strong family history of premature coronary artery disease,which might have enhanced the power to detect an associationwith coronary artery disease but also might have increased theestimated population attributable risks beyond that of sporadiccases, and further analysis of the loci in a wider range ofsubjects is necessary. Further studies are also needed to investigatethe associations of the loci with other types of atheroscleroticdisease, as well as with cardiovascular risk factors and markers.At a genetic level, studies should focus on fine mapping ofthe associated regions and thorough investigation of candidategenes. Our results provide a framework for all these additionalstudies.
Our analysis has several important limitations. Although theGeneChip array typed over 500,000 variants, a substantial percentagecould not be evaluated, for reasons given in the Supplementary Appendix.Furthermore, to reduce the effect of multiple testing, we usedonly the rather conservative Cochran–Armitage test fortrend (an additive model) to screen the WTCCC data for significantassociations. These limitations make it likely that some lociwere missed and that further analysis of the data and subsequentvalidation will reveal other loci.
Nonetheless, by using a sequential strategy of initial replicationand subsequent combination of information from the two genomewideassociation studies, we were able to describe several new geneticloci for coronary artery disease and myocardial infarction thathave a considerable effect on the risk of these diseases andthat merit in-depth follow-up studies. Most important, the findingthat a single locus was the strongest signal in two separatestudies carries promise for clinically relevant progress inour understanding of the genetics of coronary artery disease.As the current activity in genomewide association studies ofcomplex traits accelerates, our approach may also provide aparadigm for combining the results of such studies to maximizethe amount of valuable information that can be extracted fromthese expensive and laborious experiments.
Supported by grants from the Wellcome Trust, the National GenomeResearch Network 2 of the German Federal Ministry of Educationand Research, and the Cardiogenics project of the European Union.Recruitment for the WTCCC study was supported by grants fromthe British Heart Foundation and the U.K. Medical Research Council,and recruitment for the German MI Family Study was supportedby grants from the Deutsche Forschungsgemeinschaft and the DeutscheHerzstiftung. We also acknowledge support from the WellcomeTrust Functional Genomics Initiative in Cardiovascular Geneticsand the KORA (Cooperative Research in the Region of Augsburg)research platform of the GSF–National Research Centre.Drs. Samani and Ball hold chairs funded by the British HeartFoundation, and Dr. Tobin holds a U.K. Medical Research CouncilClinical Scientist Fellowship.
No potential conflict of interest relevant to this article wasreported.
We thank Peter Tooze, Andrew Kenniry, Simon Potter, Petra Bruse,Janine Stegmann, Anika Götz, Michaela Vöstner, KlausStark, and Viviane Nicaud for assistance.
* Members of the Wellcome Trust Case Control Consortium (WTCCC)and the Cardiogenics Consortium are listed in the Supplementary Appendix,available with the full text of this article at www.nejm.org.
Source Information
From the University of Leicester, Leicester (N.J.S., M.M., R.J.D., P.B., S.E.S., H.P., M.D.T., J.R.T.); University of Leeds, Leeds (A.S.H., J.H.B., M.M.I., A.J.B., S.G.B.); University of Cambridge and National Health Service Blood and Transplant, Cambridge (W.O.); and the Wellcome Trust Sanger Institute, Hinxton (P.D.) — all in the United Kingdom; Universität zu Lübeck, Lübeck (J.E., B.M., I.R.K., S.S., F.P., W.L., I.B., A.Z., H.S.); Universität Regensburg, Regensburg (C.H., M.F., A.B.); GSF–Nationales Forschungszentrum für Umwelt und Gesundheit, Neuherberg (T.M., H.-E.W., T.M.S., C.G.); Technische Universität München, Munich (T.M.); Ludwig Maximilians University, Munich (H.-E.W., C.G.); and Johannes Gutenberg University Mainz, Mainz (S.B.) — all in Germany; and INSERM, UMR S525, Université Pierre et Marie Curie, Paris (D.-A.T., F.C.). This article (10.1056/NEJMoa072366) was published at www.nejm.org on July 18, 2007. It will appear in the August 2 issue of the Journal.
Address reprint requests to Dr. Samani at the Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester LE3 9QP, United Kingdom, or at njs{at}le.ac.uk or to Dr. Schunkert at Medizinische Klinik II, Universität zu Lübeck, 23538 Lübeck, Germany, or at heribert.schunkert{at}innere2.uni-luebeck.de.
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Kathiresan, S., Melander, O., Anevski, D., Guiducci, C., Burtt, N. P., Roos, C., Hirschhorn, J. N., Berglund, G., Hedblad, B., Groop, L., Altshuler, D. M., Newton-Cheh, C., Orho-Melander, M.
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(TGF-
Ter variant in the lipoprotein lipase gene had a significant association in both studies (Table 6 in the Supplementary Appendix). 
2; and bright red: disequilibrium coefficient=1 and LOD score