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Nat Genet. Author manuscript; available in PMC 2009 September 1.
Published in final edited form as:
Published online 2009 February 8. doi:  10.1038/ng.307
PMCID: PMC2695543

New susceptibility locus for coronary artery disease on chromosome 3q22.3


We present a three-stage analysis of genome-wide SNP data in 1,222 German individuals with myocardial infarction and 1,298 controls, in silico replication in three additional genome-wide datasets of coronary artery disease (CAD) and subsequent replication in ~25,000 subjects. We identified one new CAD risk locus on 3q22.3 in MRAS (P = 7.44 × 10−13; OR = 1.15, 95% CI = 1.11–1.19), and suggestive association with a locus on 12q24.31 near HNF1A-C12orf43 (P = 4.81 × 10−7; OR = 1.08, 95% CI = 1.05–1.11).

Recent genome-wide association studies (GWAS) of coronary artery disease (CAD) have focused on a few chromosomal regions with strong signals1-4. We hypothesized that the application of stringent statistical thresholds may have dismissed SNPs with modest effects or low allele frequencies (Supplementary Fig. 1 and Supplementary Table 1 online). For this study, we started r by identifying SNPs meeting a less-stringent cutoff for association (P ≤ 1 × 10−3) in a new GWAS for myocardial infarction.

In stage 1, we genotyped 869,224 autosomal SNPs from the Affymetrix Genome-Wide Human SNP Array 6.0 in 1,222 myocardial infarction cases (German MI Family Study II (GerMIFS II); Supplementary Methods online) with premature disease onset and positive family history and 1,298 population-based Germans of European descent. After quality control (Supplementary Fig. 2 online), 567,119 SNPs remained. The inflation factor estimated for all SNPs that passed quality control is 1.04 (s.e.m. = 9.2 × 10−5). Of these, 694 SNPs showed association with myocardial infarction at P ≤ 1 × 10−3 in a two-sided trend test. These SNPs were evaluated by in silico analysis in three additional GWAS datasets (stage 2), comprising a total of 5,768 cases and 7,657 controls (WTCCC CAD study4, GerMIFS I1 and Myocardial Infarction Genetics Consortium5 together with the Italian Atherosclerosis, Thrombosis, and Vascular Biology Working Group6; the latter two form a single data source and are grouped together (MIGen/IATVB); Supplementary Methods). SNPs that were selected for large-scale replication all met the following two criteria: (i) the same allele was associated in the same direction as in the exploratory GWAS in at least two of the three in silico GWAS datasets using a one-sided trend test (P ≤ 0.05, Table 1), and (ii) the SNP had nearby correlated SNPs (within 25 kb) that also showed a signal (one-sided trend test P ≤ 0.05). A total of 21 SNPs met these criteria. They clustered into five chromosomal regions: two regions known to be associated with CAD (9p21.3 and 1q41)1-4,7 and three previously unreported regions (3q22.3, 9p24.2 and 12q24.31; Supplementary Table 2 online).

Table 1
Association results for the three new candidate CAD risk loci identified in stage 1, represented by the corresponding lead SNPs

In stage 3, we evaluated the lead SNPs of the three previously unreported loci in 12,417 cases and 12,411 controls. Two loci, represented by rs9818870 in the MRAS gene and rs2259816 in the HNF1A-C12orf43 region, showed replication in this stage at P = 2.69 × 10−7 and P = 0.0277, respectively, when adjusted for study and multiple testing. Results from stages 1–3 are displayed in Table 1 and Supplementary Figure 3 online.

Our rationale for these three stages was to be liberal in terms of a broad inclusion of SNPs at stage I and conservative with respect to a stringent replication strategy in stages 2 and 3. To determine the genuineness of effects in an efficient manner and to eliminate inconsistent findings, we carried out the second stage using in silico replication. The final stage served as a test for significance while adjusting for multiple testing. Power analyses showed that this three-staged strategy detects relevant effects with high probability (Supplementary Methods).

SNP rs9818870 in MRAS on 3q22.3 showed an aggregate P = 7.44 × 10−13 (OR = 1.15; 95% CI = 1.11–1.19), whereas SNP rs2259816 located in the HNF1A-C12orf43 region on 12q24.31 showed an aggregate P = 4.81 × 10−7 (OR = 1.08; 95% CI = 1.05–1.11) in 19,407 cases and 21,366 controls, respectively. Both SNPs met the formal criterion for genome-wide significance of 5 × 10−7 suggested by the WTCCC4 that has been applied to several GWAS. However, SNP rs2259816 in HNF1A-C12orf43 failed to reach the more stringent threshold of 7.2 × 10−8 suggested for an infinitely dense SNP map8.

To further explore the association between SNPs in MRAS and HNF1A-C12orf43, we tested whether the lead SNPs were associated with traditional risk factors for CAD in 3,276 controls from MONICA/KORA Augsburg survey S4; however, no significant association was found (Supplementary Table 3 online). In addition, we carried out exploratory subgroup analyses to test for interaction (Supplementary Fig. 4 online).

SNP rs9818870 is located in the 3′ UTR of MRAS in close proximity to a cluster of miRNA binding sites. This SNP is among a cluster of four associated SNPs (rs1199338, rs2347252, rs3732837, rs9818870) that are in a block of strong LD covering the whole gene (Fig. 1a), which consists of five exons and is ~33 kb in size (MIM608435). The M-ras protein belongs to the ras superfamily of GTP-binding proteins and is widely expressed in all tissues, with a very high expression in the cardiovascular system, especially in the heart (SymAtlas). Previous work has shown that M-ras is involved in TNF-α-stimulated LFA-1 activation in splenocytes by using mice deficient in this process9. These findings suggest a role for M-ras in adhesion signaling, which is important in the atherosclerotic process10.

Figure 1
Association results from Stage 1

SNP rs2259816 (representing the locus on 12q24.31) is located in intron 7 of HNF1A. This and two further associated SNPs cluster (rs1169313 and rs2258287) are in a LD block that covers the coding region of HNF1A and C12orf43 (Fig. 1b). HNF1A (also known as TCF1; MIM142410) encodes a transcription factor that binds to promoters of a variety of genes that are expressed exclusively in the liver11. Variants in HNF1A may cause maturity-onset diabetes of the young (MODY) (MIM600496) and affect plasma concentrations of C-reactive protein (CRP), a powerful risk marker for cardiovascular disease12. Moreover, and in parallel to the present work, a risk allele at the HNF1A locus (rs2258287) has been mapped to higher plasma levels of low-density lipoprotein cholesterol13. SNPs rs1169313 and rs2258287 are located within the C12orf43 gene (alias FLJ12448, hypothetical protein LOC64897), which is located downstream of HNF1A in a tail-to-tail manner, with only 500 bp in between (Fig. 1b). RT-PCR studies showed that MRAS and C12orf43 are ubiquitously expressed, including in mouse and human aorta and heart, tissues that are potentially involved in atherosclerosis (Supplementary Table 4 and Supplementary Fig. 5 online).

In conclusion, analysis of a new GWAS followed by in silico replication in three GWAS datasets and a large-scale replication study identified one new susceptibility locus for CAD on 3q22.3 with compelling statistical evidence and a second locus on 12q24.31 with suggestive evidence. Further functional work is needed to define the mechanisms by which these loci translate into a higher risk of CAD, and whether this information can be used to improve prevention, prediction or treatment of this common condition.

Supplementary Material

Supplementary Information


We thank J. Stegmann, A. Medack, S. Wrobel and A. Thiemig for assistance. We thank M. Scholz and J. Neudert (Trium Analysis Online GmbH, Munich, Germany) for database management. The German Study was supported by the Deutsche Forschungsgemeinschaft and the German Federal Ministry of Education and Research (BMBF) in the context of the German National Genome Research Network (NGFN-2 and NGFN-plus). The WTCCC Study was funded by the Wellcome Trust. Recruitment of cases for the WTCCC Study was carried out by the British Heart Foundation (BHF) Family Heart Study Research Group and supported by the BHF and the UK Medical Research Council. We also acknowledge support of the Wellcome Trust Functional Genomics Initiative in Cardiovascular Genetics. The KORA research platform (KORA, Cooperative Research in the Region of Augsburg) was initiated and financed by the GSF-National Research Centre for Environment and Health, which is funded by the German Federal Ministry of Education and Research and of the State of Bavaria. N.J.S. and S.G.B. are supported by Chairs funded by the BHF. Recruitment for the Italian Atherosclerosis, Thrombosis and Vascular Biology Working Group was supported by the “Associazione per lo Studio della Trombosi in Cardiologia.” The MIGen/IATVB genotyping was supported by a grant to D. Altshuler (R01HL087676) from the STAMPEED program of the National Heart, Lung, and Blood Institute, US National Institutes of Health. In addition, the MIGen study was supported by grants from the Fannie Rippel Foundation (to S.K.) and the Doris Duke Charitable Foundation (to S.K.). The Broad Institute Center for Genotyping and Analysis subsidized genotyping in the MIGen study with support from the National Center for Research Resources (U54RR020278). The main sponsor of the current analysis is the EU-funded integrated project Cardiogenics (LSHM-CT-2006-037593).


Note: Supplementary information is available on the Nature Genetics website.

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1. Samani NJ, et al. N. Engl J. Med. 2007;357:443–453. [PMC free article] [PubMed]
2. McPherson R, et al. Science. 2007;316:1488–1491. [PMC free article] [PubMed]
3. Helgadottir A, et al. Science. 2007;316:1491–1493. [PubMed]
4. Wellcome Trust Case Control Consortium Nature. 2007;447:661–678. [PMC free article] [PubMed]
5. Kathiresan S, Myocardial Infarction Genetics Consortium N. Engl. J. Med. 2008;358:2299–2300. [PubMed]
6. Atherosclerosis, Thrombosis, and Vascular Biology Italian Study Group Circulation. 2003;107:111–1122. [PubMed]
7. Schunkert H, et al. Circulation. 2008;117:1675–1684. [PMC free article] [PubMed]
8. Dudbridge F, Gusnanto A. Genet. Epidemiol. 2008;32:227–234. [PMC free article] [PubMed]
9. Yoshikawa Y, et al. Mol. Biol. Cell. 2007;18:2949–2959. [PMC free article] [PubMed]
10. Galkina E, Ley K. Arterioscler. ThrombVasc. Biol. 2007;27:2292–2301. [PubMed]
11. Courtois G, Morgan JG, Campbell LA, Fourel G, Crabtree GR. Science. 1987;238:688–692. [PubMed]
12. Reiner AP, et al. Am. J. Hum. Genet. 2008;82:1193–1201. [PubMed]
13. Kathiresan S, et al. Nat. Genet. 2009;41:56–65. [PMC free article] [PubMed]
14. McVean GA, et al. Science. 2004;304:581–584. [PubMed]