The horizontal dotted line represents genome-wide significance (5 × 10−8). The red dots are the most associated single-nucleotide polymorphism at each of the LEPR, IL6R, CRP, and HNF1A loci and the APOE-CI-CII cluster.
Numbers totaled 28 112 cases with coronary heart disease and 100 823 controls. Effects are given as odds ratios (ORs) and 95% confidence intervals (CIs) per 20% lower C-reactive protein (CRP) level. E indicates European; IA, Indian Asian; SNP, single-nucleotide polymorphism.
Prospective studies were included that reported all 3 analyses. CHD indicates coronary heart disease; CI, confidence interval; CRP, C-reactive protein; OR, odds ratio; SNPs, single-nucleotide polymorphisms.
A random-effects estimate is presented; the fixed-effects estimate has an odds ratio (OR) of 0.95 (95% confidence interval [CI], 0.94-0.96). Effects are given as ORs and 95% CIs per 20% lower C-reactive protein (CRP) level. For cohort studies, number of “controls” represents the number of event-free individuals. Number of controls was not available for ARIC.54 CHD indicates coronary heart disease; C, cohort; CC, case-cohort; NCC, nested case-control.
Effects are given as odds ratios (ORs) and 95% confidence intervals (CIs) per copy of minor allele. CHD indicates coronary heart disease; E, European; IA, Indian Asian; SNPs, single-nucleotide polymorphisms.
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Elliott P, Chambers JC, Zhang W, et al. Genetic Loci Associated With C-Reactive Protein Levels and Risk of Coronary Heart Disease. JAMA. 2009;302(1):37–48. doi:10.1001/jama.2009.954
Author Affiliations: Faculty of Medicine, Imperial College London, London, United Kingdom (Drs Elliott, Chambers, Zhang, Coin, Ashby, Tzoulaki, Brown, Mt-Isa, Ashby, Froguel, Jarvelin, Scott, and Kooner); Institute of Health Science (Dr Jarvelin), Institute of Diagnostics (Dr Ruokonen), and Biocenter Oulu (Dr Jarvelin), University of Oulu, Oulu, Finland; National Institute for Health and Welfare, Oulu (Dr Jarvelin); Clinical Trial Service Unit and Epidemiological Studies Unit (Drs Clarke, Hopewell, Bennett, and Collins), and Department of Cardiovascular Medicine and Wellcome Trust Centre for Human Genetics (Drs Peden, Farrall, and Watkins), University of Oxford, Oxford, United Kingdom; Oxford Centre for Diabetes, Endocrinology and Metabolism and Oxford National Institute for Health Research Biomedical Research Centre, Oxford (Dr McCarthy); Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom (Dr Peltonen); Department of Cardiovascular Sciences, University of Leicester, Leicester, United Kingdom (Drs Braund and Samani); Departments of Medicine and Human Genetics, McGill University, Montreal, Quebec, Canada (Dr Engert); Leeds Institute for Genetics and Therapeutics, University of Leeds, Leeds, United Kingdom (Dr Hall); Universität zu Lübeck, Lübeck, Germany (Drs Erdmann and Schunkert); Population Health Research Institute, Hamilton Health Sciences, Hamilton, Ontario, Canada (Dr Anand); Departments of Medicine and Clinical Epidemiology and Biostatistics, McMaster University, Hamilton (Dr Anand); Department of Medicine, CHUV University Hospital, Lausanne, Switzerland (Drs Vollenweider and Waeber); Center for Neurobehavioral Genetics, University of California at Los Angeles (Dr Freimer); Department of Medicine, Karolinska Institutet, Stockholm, Sweden (Dr Hamsten); and Genetics Division, GlaxoSmithKline, King of Prussia, Pennsylvania (Drs Lim, Waterworth, and Mooser).
Context Plasma levels of C-reactive protein (CRP) are independently associated with risk of coronary heart disease, but whether CRP is causally associated with coronary heart disease or merely a marker of underlying atherosclerosis is uncertain.
Objective To investigate association of genetic loci with CRP levels and risk of coronary heart disease.
Design, Setting, and Participants We first carried out a genome-wide association (n = 17 967) and replication study (n = 13 615) to identify genetic loci associated with plasma CRP concentrations. Data collection took place between 1989 and 2008 and genotyping between 2003 and 2008. We carried out a mendelian randomization study of the most closely associated single-nucleotide polymorphism (SNP) in the CRP locus and published data on other CRP variants involving a total of 28 112 cases and 100 823 controls, to investigate the association of CRP variants with coronary heart disease. We compared our finding with that predicted from meta-analysis of observational studies of CRP levels and risk of coronary heart disease. For the other loci associated with CRP levels, we selected the most closely associated SNP for testing against coronary heart disease among 14 365 cases and 32 069 controls.
Main Outcome Measure Risk of coronary heart disease.
Results Polymorphisms in 5 genetic loci were strongly associated with CRP levels (% difference per minor allele): SNP rs6700896 in LEPR (−14.8%; 95% confidence interval [CI], −17.6% to −12.0%; P = 6.2 × 10−22), rs4537545 in IL6R (−11.5%; 95% CI, −14.4% to −8.5%; P = 1.3 × 10−12), rs7553007 in the CRP locus (−20.7%; 95% CI, −23.4% to −17.9%; P = 1.3 × 10−38), rs1183910 in HNF1A (−13.8%; 95% CI, −16.6% to −10.9%; P = 1.9 × 10−18), and rs4420638 in APOE-CI-CII (−21.8%; 95% CI, −25.3% to −18.1%; P = 8.1 × 10−26). Association of SNP rs7553007 in the CRP locus with coronary heart disease gave an odds ratio (OR) of 0.98 (95% CI, 0.94 to 1.01) per 20% lower CRP level. Our mendelian randomization study of variants in the CRP locus showed no association with coronary heart disease: OR, 1.00; 95% CI, 0.97 to 1.02; per 20% lower CRP level, compared with OR, 0.94; 95% CI, 0.94 to 0.95; predicted from meta-analysis of the observational studies of CRP levels and coronary heart disease (z score, −3.45; P < .001). SNPs rs6700896 in LEPR (OR, 1.06; 95% CI, 1.02 to 1.09; per minor allele), rs4537545 in IL6R (OR, 0.94; 95% CI, 0.91 to 0.97), and rs4420638 in the APOE-CI-CII cluster (OR, 1.16; 95% CI, 1.12 to 1.21) were all associated with risk of coronary heart disease.
Conclusion The lack of concordance between the effect on coronary heart disease risk of CRP genotypes and CRP levels argues against a causal association of CRP with coronary heart disease.
Coronary heart disease (CHD) is the leading cause of death worldwide.1 Inflammation plays a key role in the pathogenesis of CHD at every stage from initiation to progression and rupture of the atherosclerotic plaque.2 C-reactive protein (CRP), an acute-phase protein synthesized primarily by the liver, is currently the most widely used biomarker of inflammation.3 Observational studies have consistently demonstrated that higher plasma levels of CRP are associated with higher risk of CHD,4,5 and measurement of CRP has been advocated as a means of improving risk prediction.6 There is considerable interest in whether CRP has a causal role in CHD7,8 or whether CRP is merely a marker of underlying atherosclerosis. Although previous studies have addressed this question, it is unclear whether they included a sufficient number of cases to have adequate statistical power to confirm or refute associations of CHD with genetically determined differences in CRP levels.8 Resolution of this question will improve understanding of inflammatory mechanisms in atherosclerosis.
The mendelian randomization concept has been used to investigate possible causal relationships of an intermediate trait (such as CRP levels) with disease, taking advantage of the random allocation of alleles at conception.9 If the intermediate trait is causally linked to disease, then genetic variants influencing the trait should also influence disease risk.10 Mendelian randomization studies should be unaffected by confounding from environmental factors, eg, smoking, and reverse causation bias, ie, where the disease itself (atherosclerosis) influences the trait (CRP levels).9
The aims of the present study were to conduct a genome-wide association study to identify common genetic variants associated with CRP levels and use mendelian randomization to improve understanding of the possible causal relationship of CRP levels with CHD.
The study involved 4 interrelated components. First, a genome-wide association and replication study was performed to identify genetic loci associated with CRP levels, and at each locus, the most closely associated single-nucleotide polymorphism (SNP) was selected. Second, a mendelian randomization study for the most associated SNP in the CRP locus in our data together with published data on CRP variants with CHD let us assess the potential causal association of CRP with CHD. Third, we compared the finding from the mendelian randomization study with that predicted from meta-analysis of the relationship of CRP levels with CHD from observational studies. Fourth, we carried out genetic association between CHD and the most associated SNPs in genetic loci outside the CRP locus using the concept of CRP as an intermediate phenotype,10 to identify putative pathways linking inflammation with CHD.
Genome-wide and Replication Study for CRP. Genome-wide association to identify variants related to CRP levels, measured using high-sensitivity assays, was carried out in 17 967 participants from 5 studies: the London Life Sciences Population (LOLIPOP) study (n = 5502), a population-based cohort of European and Indian Asian men and women aged 35 to 75 years and living in West London, United Kingdom11 (data collection, 2001-2007; genotyping, 2003-2008); the 1966 Northern Finnish Birth Cohort (NFBC) (n = 4761), a prospective birth cohort of persons born in 1966 in the 2 northernmost provinces of Finland12,13 (data collection, 1997-1998; genotyping, 2007-2008); the Lausanne Cohort (CoLaus) (n = 5226), a cross-sectional study of a random sample of European men and women aged 35 to 75 years and living in Lausanne, Switzerland14 (data collection, 2003-2006; genotyping, 2006-2007); the Genetic Epidemiology of Metabolic Syndrome (GEMS) study (n = 1781), a case-control study of dyslipidemic cases (age, 20-65 years) matched with normolipidemic controls by sex and recruitment site15 (data collection, 2003-2006; genotyping, 2006-2007); and the Data from an Epidemiological Study on the Insulin Resistance syndrome (DESIR) study (n = 697), a longitudinal French general population cohort of persons aged 30 to 64 years recruited through the French social security system16 (data collection, 1994-2004; genotyping, 2006-2007). Replication of SNPs associated with CRP levels, identified in the genome-wide association study, was performed in a further 13 615 LOLIPOP participants who were not included in the genome-wide association study and were free of known CHD.
Mendelian Randomization and Genetic Association Studies With CHD. Variants related to CRP levels were tested for association with CHD among 14 365 CHD cases and 32 069 controls. The participating studies comprised the Precocious Coronary Artery Disease study (PROCARDIS) (n = 8328), a case-control study of premature CHD before age 66 years17 (data collection, 1999-2006; genotyping, 2008); the International Studies of Infarct Survival (ISIS) (n = 3624), comprising men aged 30 to 54 years and women aged 30 to 64 years with nonfatal myocardial infarction (MI) and their spouse controls18,19 (data collection, 1989-1992; genotyping, 2008); the British Heart Foundation Family Heart Study, comprising individuals with MI or coronary revascularization before the age of 66 years and at least 1 first-degree relative with premature CHD, who were also studied as part of the Wellcome Trust Case Control Consortium (WTCCC) (n = 3249-4863)20 (data collection, 1998-2006; genotyping, 2006-2008); the German MI Family Studies (GerMIFS I: n = 2519; GerMIFS II: n = 2520), comprising persons with MI before the age of 60 years and at least 1 first-degree relative with premature CHD and matched controls20,21 (data collection, 1996-2008; genotyping, 2006-2008); the INTERHEART study, a multinational case-control study of persons presenting with first MI (n = 4043),22 (data collection, 1999-2003; genotyping, 2008); and the LOLIPOP study (n = 20 475) (data collection, 2001-2007; genotyping, 2008).
Genome-wide association scans were performed using the Affymetrix 500K mapping array (Affymetrix Inc, Santa Clara, California), the Illumina 317K array (Illumina Inc, San Diego, California), and Perlegen Sciences customized arrays (Perlegen Sciences Inc, Mountain View, California). To combine data across genotyping platforms, imputation was done using a hidden Markov model algorithm implemented in MACH version 1.0 (Center for Statistical Genetics, University of Michigan, Ann Arbor) (in LOLIPOP) or IMPUTE version 0.5.0 (Genetics Software Suite, University of Oxford, Oxford, United Kingdom) (in other studies) and phased haplotypes from National Center for Biotechnology Information (NCBI) build 35, dbSNP build 125. For the European data sets, the HapMap CEU sample was used for reference haplotypes; Indian Asian data sets were imputed based on a combination (mixed) of HapMap populations. Imputed SNPs with minor allele frequency (MAF) less than 0.01 or a low-quality score (r2 < 0.30 in MACH or information score <0.50 in IMPUTE) were removed. This left approximately 1.4 million directly genotyped or imputed autosomal SNPs per participant with data available in all samples. Genotyping for replication testing and for evaluation against CHD was performed using KASPar (KBiosciences Ltd, Hoddesdon, Hertfordshire, United Kingdom) (in LOLIPOP), Sequenom (Sequenom Inc, San Diego) (in INTERHEART and PROCARDIS), TaqMan (Applied Biosystems, Foster City, California) (in ISIS and WTCCC), or Affymetrix mapping arrays (in GerMIFS I and II and WTCCC).
Genome-wide Association and Replication Study for CRP. Genome-wide SNP associations for CRP were tested in multiple linear regression analyses using an additive genetic model. CRP levels were log-transformed to achieve approximate normal distribution and analyzed as a quantitative trait with adjustment for age and sex (analysis of residuals showed good adherence to normality assumptions). To account for heterogeneity in population structure, principal components derived from EIGENSTRAT version 2.0 (Reich Laboratory, Harvard University, Cambridge, Massachusetts) were included as covariates in age- and age-sex–adjusted analyses for CoLaus, GEMS, NFBC, and LOLIPOP Indian Asian Illumina analyses (the number of principal components included varied from 4 to 10, depending on the population structure of the specific cohort). For other LOLIPOP data sets, genomic control factors were used to correct for any inflation. No principal components were included for DESIR because the population was recruited from a geographically restricted area.
Statistical software used for genome-wide associations comprised SNPTEST (Genetics Software Suite) version 1.1.3 (in DESIR), and version 1.1.4 (in CoLaus, GEMS, and NFBC); and MACH2QTL version 1.0 (Center for Statistical Genetics) (in LOLIPOP). Results of the separate genome-wide association studies were combined using weighted z scores, and a fixed- rather than random-effects model to maximize discovery, since random-effects estimates are associated with larger variance. Quantile-quantile plots showed good adherence to null expectations (λ for combined data = 1.0625). We used P < 5 × 10−8 to designate genome-wide significance, taking account of the approximately 1 million independent tests for common variants across the genome.23 For 5 genetic loci associated with CRP levels at genome-wide significance, we selected the single most closely associated SNP (ie, smallest P value) for replication against CRP.
Using Quanto24 version 1.2 for quantitative traits, we estimated that the genome-wide association study had 80% power to detect SNPs associated with 0.2% of population variation in CRP levels, or an 11% difference in CRP level per allele copy, at MAF 0.3 and genome-wide level of significance (P < 5 × 10−8).
Mendelian Randomization Study of Genetic Variants in theCRPLocus and CHD. We analyzed the relationship of SNP rs7553007 in the CRP locus, the SNP most strongly associated with CRP levels in our data, for association with CHD risk using logistic regression under an additive genetic model as part of a mendelian randomization study. To identify published data on the relationship of CRP variants with CHD, 2 electronic databases (Medline and EMBASE) were searched up to and including November 2008 for all prospective studies (including cohort, nested case-control, and case-cohort studies) and case-control studies, with no threshold sample size. For the search, the MeSH terms C-reactive protein and polymorphism, single nucleotide or polymorphism, genetic or haplotype in combination with coronary disease or heart disease were used, and the search was limited by the terms human and English language. We also scanned reference lists of previous reports.
Eight studies of 18 cohorts were identified. Two studies25,26 examining 9 cohorts reported results for a single SNP (SNP rs1130864); for these studies, odds ratios (ORs) were reported under a recessive model comparing homozygotes (TT) for the minor allele with CT/CC genotype, and mean effect on CRP levels was obtained from published ratio of geometric means (1.21).25,26 For the remaining studies,8,27-31 we selected SNP rs1205 on the basis of MAF greater than 0.1 and largest per-allele effect size on CRP levels (−0.35 mg/L) reported in the study of CRP variants and CRP levels by Verzilli et al.32 (To convert CRP to nmol/L, multiply by 9.524.) We used a per-allele OR of rs1205 with CHD where available27,29 or where this could be estimated directly from the data8,31; otherwise, ORs were estimated from averaging published effect sizes for minor allele homozygotes (TT) and heterozygotes (CT) compared with wild type (CC).28,30 We estimated standard errors of the effect sizes of CRP variants on CHD from the reported 95% confidence intervals (CIs), assuming normality.
Estimated ORs for CRP variants on CHD were converted to a common scale by standardizing to 20% lower CRP, ie, the approximate effect per minor allele of rs7553007 on CRP levels. Results were combined across studies by SNP and across the 3 SNPs weighted by the inverse of variance. We used 95% CIs and assessed heterogeneity with standard χ2 statistics, expressed as I2, the proportion of variability between studies due to heterogeneity.33 In the absence of heterogeneity, we used a fixed-effects model.
We also investigated the 3-way associations between CRP genetic variants, CRP levels, and CHD in prospective studies that reported all 3 sets of data in the same cohorts.25-27,30 We did not include retrospective (case-control) studies since these could be biased by treatment effects.34
Comparison of the Result of the Mendelian Randomization Study With Meta-analysis of the CRP-CHD Relationship. We compared the result from our mendelian randomization study with that predicted from a meta-analysis of the observational studies of CRP levels and CHD.4,5,8,26,35-61 This was obtained from a systematic review of the CRP-CHD relationship published by Shah et al,5 updated with all studies published from August 2007 until November 2008. For the search, the MeSH terms C-reactive protein and CRP in combination with coronary, coronary heart disease, CHD, and CVD were used, and the search was limited by the terms human and English language. Studies in which total mortality was the only outcome reported were excluded; if more than 1 article was published on the same cohort or population, the most recent one was used in the meta-analysis.
Five new population studies were identified from 4 reports.8,26,35,36 Risk ratios for CHD associated with CRP levels (logarithmically transformed) were extracted from each study. Two studies were excluded: one62 that cited risk ratios per unit increase in CRP (ie, not logarithmically transformed) and one63 that did not provide CIs for the association of CRP with CHD. The studies reported risk ratios based on different comparisons of CRP (tertiles, quintiles, or quartiles) or as differences in risk for a given increase in CRP level; these were converted to a common unit of 1 SD change. The risk ratio per standard deviation change was converted to per 20% lower CRP by multiplying coefficients (and 95% CIs) on the logarithmic scale by −0.223, assuming that a 20% reduction in CRP is equivalent to a 0.223 SD reduction in log CRP.
Multivariate-adjusted risk ratios, controlled for conventional cardiovascular risk factors, were used when available; 2 studies reported risk ratios adjusted for age only and age and smoking only.37,38 Because of significant heterogeneity, random-effects meta-analysis was used to combine the risk ratios from the individual studies. The overall OR for CHD was used to test the observed vs predicted association of CRP variants with CHD, standardized to 20% lower CRP level.
Genetic Association of Variants Outside theCRPLocus and CHD. The relationships with risk of CHD of the most associated SNP in the 4 genetic loci other than the CRP locus in our data were analyzed by logistic regression under an additive genetic model. Results were combined across studies by SNP using a fixed-effects model weighted by the inverse of variance because there was no significant heterogeneity. By use of the Genetic Power Calculator,64 we estimated that the genetic association study with CHD had 80% power to detect an OR of 1.04 per allele copy at P < .05 and MAF 0.3.
With the exception of the genome-wide association analyses described here, statistical analyses were done with Stata version 10 (StataCorp, College Station, Texas) or SAS version 9.1 (SAS Institute Inc, Cary, North Carolina). A significance level of P < .05 was used; all tests were 2-sided.
Ethics approval was obtained locally for each of the participating cohorts for analyses of genetic markers of cardiovascular disease risk. No additional ethics approvals were required for this study.
We found 160 SNPs to be associated with CRP levels at P < 5 × 10−8, distributed in the following 5 loci: LEPR (GeneID 3953, GenBank NC_000001.9, region 65658906 to 65875410), IL6R (GeneID 3570, GenBank NC_000001.9, region 152644293 to 152706812), CRP (GeneID 1401, GenBank NC_000001.9, region 157951003 to 157948703), HNF1A (GeneID 6927, GenBank NC_000012.10, region 119900932 to 119924698) and APOE-CI-CII (GeneID 348, 341, 344, GenBank NC_000019.8, region 50100879 to 50104490). A Manhattan plot of results from the combined analysis of genome-wide association data is shown in Figure 1. Genomic context and P values for the most associated SNP at each of the 5 loci are shown in Table 1. The association of these SNPs with CRP levels was confirmed in replication testing (all P ≤ 10−10); for all 5 SNPs, the minor allele was associated with reduced levels of CRP (Table 1). For the most associated SNP in the CRP locus (rs7553007), CRP levels were lower by 21% (95% CI, −23.4% to −17.9%) per minor allele. For the other 4 SNPs, per-minor-allele differences in CRP levels ranged from −11.5% (95% CI, −14.4% to −8.5%) for SNP rs4537545 in IL6R to −21.8% (95% CI, −25.3% to −18.1%) for SNP rs4420638 in the APOE-CI-CII cluster (Table 1).
In the replication study (LOLIPOP), the percent variance of CRP explained ranged from 0.2% (SNP rs1183910 in HNF1A) to 1.3% (rs7553007 in the CRP locus). SNP rs4420638 in the APOE-CI-CII cluster was strongly associated with total cholesterol (6.27 mg/dL; 95% CI, 4.88 to 7.66 mg/dL; per minor allele), low-density lipoprotein (LDL) cholesterol (5.77 mg/dL; 95% CI, 4.60 to 6.93 mg/dL; per minor allele), triglycerides (11.05 mg/dL; 95% CI, 7.54 to 14.56 mg/dL; per minor allele) and high-density lipoprotein (HDL) cholesterol (−1.17 mg/dL; 95% CI, −1.57 to −0.76 mg/dL; per minor allele) (Table 2). SNP rs1183910 in HNF1A was associated with total cholesterol (1.24 mg/dL; 95% CI, 0.23 to 2.25 mg/dL; per minor allele), LDL cholesterol (1.22 mg/dL; 95% CI, 0.38 to 2.07 mg/dL; per minor allele), and HDL cholesterol (0.30 mg/dL; 95% CI, 0.01 to 0.59 mg/dL; per minor allele). (To convert total, LDL, and HDL cholesterol to mmol/L, multiply by 0.0259; to convert triglycerides to mmol/L, multiply by 0.0113.) SNP rs6700896 in LEPR was associated with weight (−0.44 kg; 95% CI, −0.78 to −0.10 kg; per minor allele) and body mass index (−0.12; 95% CI, −0.23 to −0.00; per minor allele; body mass index is calculated as weight in kilograms divided by height in meters squared). The remaining 2 SNPs were not significantly related to any of the phenotypes tested (Table 2).
Figure 2 shows the results of the mendelian randomization experiment of CHD with variants in the CRP locus: SNP rs7553007 (our data) and published data for SNPs rs1130864 and rs1205 for 18 cohorts. SNP rs7553007 was not significantly associated with CHD; the estimated OR was 0.98 (95% CI, 0.94 to 1.01) per 20% lower CRP level. For rs1130864, the OR was 1.00 (95% CI, 0.86 to 1.15), and for rs1205, the OR was 1.03 (95% CI, 0.99 to 1.07). There was no association of CHD with CRP variants (per 20% lower CRP level) when results for all 3 SNPs were combined (OR, 1.00; 95% CI, 0.97 to 1.02) (Figure 2).
In the 3-way comparison of CRP genetic variants, CRP levels, and CHD risk reported in prospective studies, there was significant association of CRP variants with CRP levels, and CRP levels with CHD, but not CRP variants with CHD (Figure 3).
The meta-analysis of observational studies of CRP levels and CHD gave a predicted OR of 0.94 (95% CI, 0.94 to 0.95) per 20% lower CRP level (Figure 4). This is significantly different from the estimated effect on CHD (OR, 1.00) of genetically determined differences in CRP levels obtained from our mendelian randomization study (z = −3.45, P < .001).
Minor alleles of SNP rs6700896 in LEPR and rs4420638 in APOE-CI-CII cluster were associated with significantly increased risk of CHD (OR, 1.06; 95% CI, 1.02 to 1.09; and OR, 1.16; 95% CI, 1.12 to 1.21; respectively), and SNP rs4537545 in IL6R with a decreased risk of CHD (OR, 0.94; 95% CI, 0.91 to 0.97), while SNP rs1183910 in HNF1A was not significantly associated with CHD (Figure 5). The effects of SNPs rs6700896 in LEPR and rs4420638 in the APOE-CI-CII cluster on CHD were in the opposite direction to that predicted from the relationship of CRP levels with CHD (Figure 4); for rs4420638 the finding was consistent with the effects on blood lipid concentrations (Table 2).
The present genome-wide association study confirms the associations of common genetic variants in the LEPR, IL6R, CRP, and HNF1A loci and APOE-CI-CII cluster with CRP levels.65,66 However, the minor allele of SNP rs7553007 and other variants in the CRP locus included in our mendelian randomization study were not associated with CHD risk.
The variants included in our mendelian randomization study are associated with approximately 20% lower CRP levels,32 corresponding to a 6% reduction in CHD risk predicted by the meta-analysis of observational studies of CHD risk. The lack of association with CHD of genetic variants in the CRP locus suggests that the observational data linking CRP levels and CHD may be confounded by association with other CHD risk factors, or reflect a secondary inflammatory response associated with atherosclerosis (reverse causation), rather than indicate a causal relationship.
Our analysis of SNP rs7553007 with CHD risk includes more cases than all previously published studies of CRP variants and CHD combined,8,25-31 yielding with the 2 published SNPs a total of more than 28 000 cases and 100 000 controls for the mendelian randomization study. The largest previous study, of 3 cohorts in Copenhagen, included 6545 cases.8 In addition to rs1205 included in our mendelian randomization study, it provided data on the triallelic SNP rs3091244 and SNP rs3093077, both having variants with larger effects on CRP levels (20%-30%) than rs1205; however, both variants are rare, and neither was associated with CHD in the Copenhagen study.8
The JUPITER trial recently reported a benefit of treatment with rosuvastatin on CHD risk among men and women with elevated CRP levels (2.0 mg/L or higher) and with LDL cholesterol levels below 130 mg/dL.34 In the treatment group, there was 54% reduction in rates of MI compared with placebo; LDL levels were reduced by 50% and CRP levels by 37%. Although the JUPITER trial demonstrated the benefits of statin therapy in people with LDL levels below current treatment threshold, the results may simply reflect the benefits of lipid-lowering therapy in people who would not currently be considered for pharmacotherapy, rather than the benefits of CRP lowering per se.67
Investigation of genetic variants underlying an intermediate phenotype (such as CRP) has been advocated as a means of discovering new disease susceptibility loci.10 In our study, minor alleles of SNPs rs6700896 in LEPR and rs4420638 in the APOE-CI-CII cluster showed significantly increased risk of CHD. However, both variants were associated with reduced levels of CRP (and for SNP rs6700896 in LEPR, lower body weight and body mass index), suggesting that the links with CHD are not mediated by CRP. LEPR has not previously been reported to increase risk of CHD, although associations of variants in the APOE-CI-CII cluster with CHD have been observed.68,69 While the association of genetic variation in APOE-CI-CII with CHD can be explained in large part by its effects on blood lipids, this is not the case for SNP rs6700896 in LEPR. SNP rs6700896 is located in intron 19 of LEPR, the gene encoding the leptin receptor, a member of the class I cytokine receptor family.70LEPR is expressed in the hypothalamus and vascular endothelial cells,71 and LEPR signaling has a role in appetite control, weight regulation, glucose homeostasis, blood pressure regulation, and angiogenesis.70-72 The minor allele of SNP rs4537545 in IL6R was also associated with reduced CRP levels and reduced risk of CHD. SNP rs4537545 in IL6R is in high linkage disequilibrium (r2 = 0.96 in the HapMap CEU reference population) with a nonsynonymous SNP (rs8192284, Asp358Ala) associated with increased IL6R expression and alterations of IL6R membrane binding,39 providing a potential mechanism linking rs4537545 to biological function. Further studies will be needed to confirm LEPR and IL6R as new susceptibility loci for CHD.
Our study has limitations. Because of the relatively small effect of common genetic variants in CRP locus on CRP levels, a large sample size is needed to detect associations with CHD. To combine data across studies in our mendelian randomization study, we assumed a common effect on risk of CHD from different variants in the CRP locus by standardizing to a common difference on the log CRP scale. This approach is valid to the extent that the hypothesized effect of CRP variants on CHD risk reflects circulating levels of CRP. Although we found no association of CRP variants with CHD risk, it is not possible to exclude a small effect, despite the large sample size. However, we can effectively exclude the size of association predicted from observational data on the relationship of CRP levels to CHD. The mendelian randomization approach makes a number of assumptions concerning possible causality. These include the potential for pleiotropic effects of the genetic variants under study (or variants in high linkage disequilibrium with them) giving an alternative pathway to CHD or confounding through associations with disease risk factors.9 Neither rs7553007 or the other 2 variants included from the CRP locus correlate with CHD risk factors,8,26 satisfying an important condition for a valid mendelian randomization experiment.9
In summary, our mendelian randomization study of more than 28 000 cases and 100 000 controls found no association of variants in the CRP locus and CHD, arguing against a causal role for CRP in atherosclerosis. Moreover, this study suggests that development of therapeutic strategies targeting specific reductions in plasma levels of CRP are unlikely to be fruitful.
Corresponding Author: Paul Elliott, FRCP, MRC-HPA Centre for Environment and Health, Department of Epidemiology and Public Health, Imperial College London, St Mary's Campus, Norfolk Place, London W2 1PG, United Kingdom (email@example.com).
Author Contributions: Dr Elliott had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Elliott and Chambers contributed equally to this work.
Study concept and design: Elliott, Chambers, Scott, Kooner.
Acquisition of data: Elliott, Chambers, Clarke, Peden, Erdmann, Braund, Engert, Peltonen, Freimer, Ruokonen, Hamsten, Froguel, Waterworth, Vollenweider, Waeber, Jarvelin, Mooser, Hall, Schunkert, Anand, Collins, Samani, Watkins, Kooner.
Analysis and interpretation of data: Elliott, Chambers, Zhang, Clarke, Peden, Bennett, Engert, Hopewell, Coin, Ashby, Tzoulaki, Brown, Mt-Isa, McCarthy, Peltonen, Farrall, Ruokonen, Lim, Jarvelin, Scott, Anand, Samani, Kooner.
Drafting of the manuscript: Elliott, Chambers, Scott, Kooner.
Critical revision of the manuscript for important intellectual content: Elliott, Chambers, Zhang, Clarke, Hopewell, Peden, Erdmann, Braund, Engert, Bennett, Coin, Ashby, Tzoulaki, Brown, Mt-Isa, McCarthy, Peltonen, Freimer, Farrall, Ruokonen, Hamsten, Lim, Froguel, Waterworth, Vollenweider, Waeber, Jarvelin, Mooser, Hall, Schunkert, Anand, Collins, Samani, Watkins, Kooner.
Statistical analysis: Elliott, Chambers, Zhang, Peden, Bennett, Engert, Hopewell, Coin, Ashby, Tzoulaki, Brown, Mt-Isa, Farrall, Lim, Froguel, Schunkert, Kooner.
Obtained funding: Chambers, McCarthy, Freimer, Farrall, Hamsten, Froguel, Waterworth, Vollenweider, Waeber, Jarvelin, Mooser, Scott, Hall, Anand, Collins, Watkins, Kooner.
Administrative, technical, or material support: Elliott, Chambers, Clarke, Peden, Erdmann, Braund, Brown, Mt-Isa, Freimer, Ruokonen, Hamsten, Lim, Waterworth, Vollenweider, Jarvelin, Mooser.
Study supervision: Elliott, Chambers, Clarke, Coin, Farrall, Waterworth, Vollenweider, Waeber, Mooser, Samani, Watkins, Kooner.
Financial Disclosures: None reported.
Funding/Support: The Data from an Epidemiological Study on the Insulin Resistance syndrome (DESIR) received support from INSERM, CNAMTS, Lilly, Novartis Pharma, Sanofi-Aventis, the Association Diabète Risque Vasculaire, the Fédération Française de Cardiologie, La Fondation de France, ALFEDIAM, ONIVINS, Ardix Medical, Bayer Diagnostics, Becton Dickinson, Cardionics, Merck Santé, Novo Nordisk, Pierre Fabre, Roche, Topcon, and the European Union (P.F.) (Integrated Project EURODIA LSHM-CT-2006-518153 in the Framework Programme 6 [FP06] of the European Community). The Genetic Epidemiology of Metabolic Syndrome (GEMS) study was sponsored in part by GlaxoSmithKline. The German MI Family Study was supported by grants from the Deutsche Forschungsgemeinschaft and the Deutsche Herzstiftung, the National Genome Research Network 2 of the German Federal Ministry of Education and Research, and the Cardiogenics project of the European Union. From the INTERHEART study, Dr Anand holds the Michael G. DeGroot and Heart and Stroke Foundation of Ontario Chair in Population Health and the May Cohen Eli Lilly Endowed Chair in Women's Health Research, McMaster University. The INTERHEART study was funded by the Canadian Institutes of Health Research, the Heart and Stroke Foundation of Ontario, and the International Clinical Epidemiology Network (INCLEN); through unrestricted grants from several pharmaceutical companies (with major contributions from AstraZeneca, Novartis, Sanofi-Aventis, Knoll Pharmaceuticals [now Abbott], Bristol Myers Squibb, and King Pharma); and by various national bodies in different countries as follows: Chile, Universidad de la Frontera, Sociedad Chilena de Cardiologia Filial Sur; Colombia, Colciencias, Ministerio de Salud; Croatia, Croatian Ministry of Science and Technology; Guatemala, Liga Guatemalteca del Corazon; Hungary, Astra Hassle, National Health Science Council, George Gabor Foundation; Iran, Iran Ministry of Health; Italy, Boehringer-Ingelheim; Japan, Sankyo Pharmaceutical Co, Banyu Pharmaceutical Co, Astra Japan; Kuwait, Endowment Fund for Health Development in Kuwait; Pakistan, ATCO Laboratories; Philippines, Philippine Council for Health Research and Development, Pfizer Philippines Foundation, Inc, Astra Pharmaceuticals Inc and the Astra Fund for Clinical Research and Continuing Medical Education, Pharmacia and Upjohn Inc; Poland, Foundation PROCLINICA; Singapore, Singapore National Heart Association; South Africa, Medical Research Council of South Africa, Warner-Parke-Davis Pharmaceuticals, Aventis; Sweden, grant from the Swedish State under the LUA agreement, Swedish Heart and Lung Foundation; Thailand, Heart Association of Thailand, Thailand Research Fund. The International Studies of Infarct Survival (ISIS) trials and epidemiological studies were supported by the manufacturers of the study drugs and by the British Heart Foundation, Medical Research Council, Cancer Research UK, Tobacco Products Research Trust of the UK Department of Health Independent Scientific Committee on Smoking and Health, and Oxford NHS Genetic Knowledge Park. The Lausanne Cohort (CoLaus) study received support from the Giorgi-Cavaglieri Foundation (Toby Johnson, Sven Bergmann), the Université de Lausanne (Jacques S. Beckmann), and grant 3100AO-116323/1 (Sven Bergmann) from the Swiss National Science Foundation (Murielle Bochud). GlaxoSmithKline provided support to build the CoLaus study (Drs Vollenweider and Waeber). This work was supported by GlaxoSmithKline and the Faculty of Biology and Medicine, Université de Lausanne, Lausanne, Switzerland. The London Life Sciences Population (LOLIPOP) received support from grant SP/04/002 from the British Heart Foundation. The 1966 North Finland Birth Cohort received support from grant 5R01HL087679-02 from the National Heart, Lung, and Blood Institute through the STAMPEED program; the Medical Research Council of the United Kingdom; the European Birth Life-Course Study; contract QLG1-CT-2000-01643 from the European Commission “Quality of Life and Management of Living Resources”; the Biocenter Oulu of University of Oulu; the Academy of Finland; and grant 1RL1MH083268-01 from the National Institute of Mental Health. The Precocious Coronary Artery Disease study (PROCARDIS) was funded by the British Heart Foundation, EC Sixth Framework Programme (LSHM33 CT-2007-037273), AstraZeneca AB, and the Knut and Alice Wallenberg Foundation. The Wellcome Trust Case Control Consortium (WTCCC) study received support for recruitment from grants from the British Heart Foundation and the UK Medical Research Council. It also received support from the Wellcome Trust Functional Genomics Initiative in Cardiovascular Genetics. Dr Samani holds a chair funded by the British Heart Foundation.
Role of the Sponsor: With the exception of GlaxoSmith Kline, whose scientists were involved in the planning, data collection, and analysis for the GEMS and CoLaus studies, funders had no role in the design and conduct of the study; in the collection, management, analysis, or interpretation of the data; or in the preparation, review, or approval of the manuscript.
GEMS Study Investigators: Philip Barter, PhD; Y. Antero Kesäniemi, PhD; Robert W. Mahley, PhD; Ruth McPherson, FRCP; and Scott M. Grundy, PhD. Dr Waeber was also a GEMS investigator. Detailed information on the GEMS study design, sampling frame, and recruitment procedures has been published previously.15
INTERHEART Study. The clinical centers are named in the 2004 INTERHEART report (http://www.thelancet.com/journals/lancet/article/PIIS0140673604170189/abstract).
ISIS Study. A full list of the participating centers and collaborators is given in the ISIS-3 report.19
CoLaus Study Investigators: Jacques S. Beckmann, Sven Bergmann, Murielle Bochud, Toby Johnson, Kijoung Song, Xin Yuan, and Drs Lim, Mooser, Vollenweider, Waeber, and Waterworth. Principal investigators: Drs Mooser and Vollenweider. Study design: Jacques S. Beckmann and Drs Mooser, Vollenweider, Waeber, and Waterworth. Assembly of the cohort: Dr Waeber. Data analysis: Dr Lim. Project management: Jacques S. Beckmann, Sven Bergmann, Murielle Bochud, and Drs Mooser, Vollenweider, and Waterworth.
LOLIPOP Study Investigators: Drs Chambers, Elliott, Scott, and Kooner. Principal investigator: Dr Kooner. Data analysis: Drs Chambers and Zhang and Delilah Zabeneh, Robin Walters, Maria de Iorio, and David Balding.
1966 North Finland Birth Cohort Investigators: Drs Elliott, Freimer, Jarvelin, McCarthy, and Peltonen and Anna-Liisa Hartikainen and Anneli Pouta. Data analysis: Dr Coin and Pimphen Charoen. Biochemical analysis: Dr Ruokonen.
PROCARDIS Investigators: Drs Clarke, Farrall, Hamsten, Peden, and Watkins and Anuj Goel, Simon C. Heath, G. Mark Lathrop, Udo Seedorf, Ann-Christine Syvänen, and Giovanni Tognoni. Principal investigator for project: Dr Watkins. Principal investigators for collection center: Drs Clarke and Hamsten and Udo Seedorf and Giovanni Tognoni. Genotyping: Simon C. Heath, G. Mark Lathrop, and Ann-Christine Syvänen. Quality control: Simon C. Heath. Data analysis: Drs Farrall and Peden and Anuj Goel. Project management: Drs Peden and Watkins. A full membership list of the PROCARDIS consortium appears online at http://www.procardis.org.
Additional Contributions: Maria de Iorio, PhD, and Pimphen Charoen, MPhil, Imperial College, London helped with the statistical analyses for this article. They were not compensated for their contributions. In the INTERHEART study, Ron Do, MSc, helped with statistical analyses. Salim Yusuf initiated and, together with the steering committee members, supervised the conduct of the study. Members of the project office of the Population Health Research Institute, Sumathy Rangarajan and Laura Joldersma helped with study coordination, and Changchun Xie, PhD, provided statistical support. ISIS study investigators gratefully acknowledge the patients and their relatives who collaborated, their general practitioners, and the medical and nursing staff from more than 100 hospitals in the United Kingdom. PROCARDIS investigators are grateful to the participants and to the medical and nursing staff who assisted in the project. None of the INTERHEART contributors nor ISIS/PROCARDIS collaborators listed here were compensated for their contributions.