Background and Purpose
Ischemic stroke (IS) and coronary artery disease (CAD) share several risk factors and each have a substantial heritability. We conducted a genome-wide analysis to evaluate the extent of shared genetic determination of the two diseases.
Genome-wide association data were obtained from the METASTROKE, CARDIoGRAM, and C4D consortia. We first analyzed common variants reaching a nominal threshold of significance (p<0.01) for CAD for their association with IS and vice versa. We then examined specific overlap across phenotypes for variants that reached a high threshold of significance. Finally, we conducted a joint meta-analysis on the combined phenotype of IS or CAD. Corresponding analyses were performed restricted to the 2,167 individuals with the ischemic large artery stroke (LAS) subtype.
Common variants associated with CAD at p<0.01 were associated with a significant excess risk for IS and for LAS and vice versa. Among the 42 known genome-wide significant loci for CAD, three and five loci were significantly associated with IS and LAS, respectively. In the joint meta-analyses, 15 loci passed genome-wide significance (p<5×10-8) for the combined phenotype of IS or CAD and 17 loci passed genome-wide significance for LAS or CAD. Since these loci had prior evidence for genome-wide significance for CAD we specifically analyzed the respective signals for IS and LAS and found evidence for association at chr12q24/SH2B3 (pIS=1.62×10-07) and ABO (pIS =2.6×10-4) as well as at HDAC9 (pLAS=2.32×10-12), 9p21 (pLAS =3.70×10-6), RAI1-PEMT-RASD1 (pLAS =2.69×10-5), EDNRA (pLAS =7.29×10-4), and CYP17A1-CNNM2-NT5C2 (pLAS =4.9×10-4).
Our results demonstrate substantial overlap in the genetic risk of ischemic stroke and particularly the large artery stroke subtype with coronary artery disease.
Based on evidence that FHL2 (four and a half LIM domains protein 2) negatively regulates cardiac hypertrophy we tested whether FHL2 altered expression or variants could be associated with hypertrophic cardiomyopathy (HCM). HCM is a myocardial disease characterized by left ventricular hypertrophy, diastolic dysfunction and increased interstitial fibrosis and is mainly caused by mutations in genes coding for sarcomeric proteins. FHL2 mRNA level, FHL2 protein level and I-band-binding density were lower in HCM patients than control individuals. Screening of 121 HCM patients without mutations in established disease genes identified 2 novel (T171M, V187L) and 4 known (R177Q, N226N, D268D, P273P) FHL2 variants in unrelated HCM families. We assessed the structural and functional consequences of the nonsynonymous substitutions after adeno-associated viral-mediated gene transfer in cardiac myocytes and in 3D-engineered heart tissue (EHT). Overexpression of FHL2 wild type or nonsynonymous substitutions in cardiac myocytes markedly down-regulated α-skeletal actin and partially blunted hypertrophy induced by phenylephrine or endothelin-1. After gene transfer in EHTs, force and velocity of both contraction and relaxation were higher with T171M and V187L FHL2 variants than wild type under basal conditions. Finally, chronic phenylephrine stimulation depressed EHT function in all groups, but to a lower extent in T171M-transduced EHTs. These data suggest that (1) FHL2 is down-regulated in HCM, (2) both FHL2 wild type and variants partially protected phenylephrine- or endothelin-1-induced hypertrophy in cardiac myocytes, and (3) FHL2 T171M and V187L nonsynonymous variants induced altered EHT contractility. These findings provide evidence that the 2 novel FHL2 variants could increase cardiac function in HCM.
Electronic supplementary material
The online version of this article (doi:10.1007/s00395-014-0451-8) contains supplementary material, which is available to authorized users.
Hypertrophic cardiomyopathy; Hypertrophy; FHL2; Engineered heart tissue; Hypercontractility
The objective of the Aliskiren Trial on Acute Heart Failure Outcomes (ASTRONAUT) was to determine whether aliskiren, a direct renin inhibitor, would improve post-discharge outcomes in patients with hospitalization for heart failure (HHF) with reduced ejection fraction. Pre-specified subgroup analyses suggested potential heterogeneity in post-discharge outcomes with aliskiren in patients with and without baseline diabetes mellitus (DM).
Methods and results
ASTRONAUT included 953 patients without DM (aliskiren 489; placebo 464) and 662 patients with DM (aliskiren 319; placebo 343) (as reported by study investigators). Study endpoints included the first occurrence of cardiovascular death or HHF within 6 and 12 months, all-cause death within 6 and 12 months, and change from baseline in N-terminal pro-B-type natriuretic peptide (NT-proBNP) at 1, 6, and 12 months. Data regarding risk of hyperkalaemia, renal impairment, and hypotension, and changes in additional serum biomarkers were collected. The effect of aliskiren on cardiovascular death or HHF within 6 months (primary endpoint) did not significantly differ by baseline DM status (P = 0.08 for interaction), but reached statistical significance at 12 months (non-DM: HR: 0.80, 95% CI: 0.64–0.99; DM: HR: 1.16, 95% CI: 0.91–1.47; P = 0.03 for interaction). Risk of 12-month all-cause death with aliskiren significantly differed by the presence of baseline DM (non-DM: HR: 0.69, 95% CI: 0.50–0.94; DM: HR: 1.64, 95% CI: 1.15–2.33; P < 0.01 for interaction). Among non-diabetics, aliskiren significantly reduced NT-proBNP through 6 months and plasma troponin I and aldosterone through 12 months, as compared to placebo. Among diabetic patients, aliskiren reduced plasma troponin I and aldosterone relative to placebo through 1 month only. There was a trend towards differing risk of post-baseline potassium ≥6 mmol/L with aliskiren by underlying DM status (non-DM: HR: 1.17, 95% CI: 0.71–1.93; DM: HR: 2.39, 95% CI: 1.30–4.42; P = 0.07 for interaction).
This pre-specified subgroup analysis from the ASTRONAUT trial generates the hypothesis that the addition of aliskiren to standard HHF therapy in non-diabetic patients is generally well-tolerated and improves post-discharge outcomes and biomarker profiles. In contrast, diabetic patients receiving aliskiren appear to have worse post-discharge outcomes. Future prospective investigations are needed to confirm potential benefits of renin inhibition in a large cohort of HHF patients without DM.
Aliskiren; Diabetes; Outcomes; Post-discharge
Familial hypercholesterolemia (FH) is an autosomal-dominant disease leading to markedly elevated low-density lipoprotein (LDL) cholesterol levels and increased risk for premature myocardial infarction (MI). Mutation carriers display variable LDL cholesterol levels, which may obscure the diagnosis. We examined by whole-exome sequencing a family in which multiple myocardial infarctions occurred at a young age with unclear etiology.
Whole-exome sequencing of three affected family members, validation of the identified variant with Sanger-sequencing, and subsequent co-segregation analysis in the family.
The index patient (LDL cholesterol 188 mg/dL) was referred for molecular-genetic investigations. He had coronary artery bypass graft (CABG) at the age of 59 years; 12 out of 15 1st, 2nd and 3rd degree relatives were affected with coronary artery disease (CAD) and/or premature myocardial infarction (MI). We sequenced the whole-exome of the patient and two cousins with premature MI. After filtering, we were left with a potentially disease causing variant in the LDL receptor (LDLR) gene, which we validated by Sanger-sequencing (nucleotide substitution in the acceptor splice-site of exon 10, c.1359-1G > A). Sequencing of all family members available for genetic analysis revealed co-segregation of the variant with CAD (LOD 3.0) and increased LDLC (>190 mg/dL), following correction for statin treatment (LOD 4.3). Interestingly, mutation carriers presented with highly variable corrected (183–354 mg/dL) and on-treatment LDL levels (116–274 mg/dL) such that the diagnosis of FH in this family was made only after the molecular-genetic analysis.
Even in families with unusual clustering of CAD FH remains to be underdiagnosed, which underscores the need for implementation of systematic screening programs. Whole-exome sequencing may facilitate identification of disease-causing variants in families with unclear etiology of MI and enable preventive treatment of mutation carriers in a more timely fashion.
Familial hypercholesterolemia; Myocardial infarction; Whole-exome sequencing
Hypertension is a risk factor for coronary artery disease. Recent genome-wide association studies have identified 30 genetic variants associated with higher blood pressure at genome-wide significance (p<5×10−8). If elevated blood pressure is a causative factor for coronary artery disease, these variants should also increase coronary artery disease risk. Analyzing genome-wide association data from 22,233 coronary artery disease cases and 64,762 controls, we observed in the Coronary artery disease Genome-Wide Replication And Meta-Analysis (CARDIoGRAM) consortium that 88% of these blood pressure-associated polymorphisms were likewise positively associated with coronary artery disease, i.e. they had an odds ratio >1 for coronary artery disease, a proportion much higher than expected by chance (p=4.10−5). The average relative coronary artery disease risk increase per each of the multiple blood pressure-raising alleles observed in the consortium was 3.0% for systolic blood pressure-associated polymorphisms (95% confidence interval, 1.8 to 4.3%) and 2.9% for diastolic blood pressure-associated polymorphisms (95% confidence interval, 1.7 to 4.1%). In sub-studies, individuals carrying most systolic blood pressure- and diastolic blood pressure-related risk alleles (top quintile of a genetic risk score distribution) had 70% (95% confidence interval, 50-94%) and 59% (95% confidence interval, 40-81%) higher odds of having coronary artery disease, respectively, as compared to individuals in the bottom quintile. In conclusion, most blood pressure-associated polymorphisms also confer an increased risk for coronary artery disease. These findings are consistent with a causal relationship of increasing blood pressure to coronary artery disease. Genetic variants primarily affecting blood pressure contribute to the genetic basis of coronary artery disease.
Blood pressure; polymorphism; genetics; coronary artery disease
Approaches exploiting extremes of the trait distribution may reveal novel loci for common traits, but it is unknown whether such loci are generalizable to the general population. In a genome-wide search for loci associated with upper vs. lower 5th percentiles of body mass index, height and waist-hip ratio, as well as clinical classes of obesity including up to 263,407 European individuals, we identified four new loci (IGFBP4, H6PD, RSRC1, PPP2R2A) influencing height detected in the tails and seven new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3, ZZZ3) for clinical classes of obesity. Further, we show that there is large overlap in terms of genetic structure and distribution of variants between traits based on extremes and the general population and little etiologic heterogeneity between obesity subgroups.
Several studies have investigated associations between the -174G>C polymorphism (rs1800795) of the IL6-gene, but presented inconsistent results.
This joint analysis aimed to clarify whether IL6 -174G>C was associated with type 2 diabetes mellitus (T2DM) related quantitative phenotypes.
Individual-level data from all studies of the IL6-T2DM consortium on Caucasian subjects with available BMI were collected. As study-specific estimates did not show heterogeneity (P>0.1), they were combined by using the inverse-variance fixed-effect model.
The main analysis included 9440, 7398, 24,117, or 5659 nondiabetic and manifest T2DM subjects for fasting glucose, 2-hour glucose, BMI or circulating interleukin-6 levels, respectively. IL6 -174 C-allele carriers had significantly lower fasting glucose (−0.091mmol/L, P=0.014). There was no evidence for association between IL6 -174G>C and BMI or interleukin-6. In an additional analysis of 641 subjects known to develop T2DM later on, the IL6 -174 CC-genotype was associated with higher baseline interleukin-6 (+0.75pg/mL, P=0.004), which was consistent with higher interleukin-6 in the 966 manifest T2DM subjects (+0.50pg/mL, P=0.044).
Our data suggest association between IL6 -174G>C and quantitative glucose, and exploratory analysis indicated modulated interleukin-6 levels in pre-diabetic subjects, being in-line with this SNP’s previously reported T2DM association and a role of circulating interleukin-6 as intermediate phenotype.
blood glucose; body mass index; diabetes mellitus; type 2; epidemiology; molecular; genes; inflammation mediators; interleukin-6; intermediate phenotype; meta-analysis; polymorphism; single nucleotide
The early repolarization pattern (ERP) is common and associated with risk of sudden cardiac death. ERP is heritable and mutations have been described in syndromatic cases.
To conduct a meta-analysis of genome-wide association studies (GWAS) to identify common genetic variants influencing ERP.
We ascertained ERP based on electrocardiograms in three large community-based cohorts from Europe and the US: the Framingham Heart Study, the Health 2000 Study, and the KORA F4 Study. We analyzed GWAS in participants with and without ERP by logistic regression assuming an additive genetic model and meta-analyzed individual cohort results. We then sought to strengthen support for findings that reached p≤1×10−5 in independent individuals by direct genotyping or in-silico analysis of genome-wide data. We meta-analyzed the results from both stages.
Of 7482 individuals in the discovery stage, 452 showed ERP (ERP positive: mean age 46.9±8.9 years, 30.3% women; ERP negative: 47.5±9.4 years, 54.2% women). After meta-analysis, eight single nucleotide polymorphisms reached p≤1×10−5: The most significant finding was intergenic rs11653989 (odds ratio 0.47; 95% confidence interval 0.36–0.61; p=6.9×10−9). The most biologically relevant finding was intronic to KCND3: rs17029069 (odds ratio 1.46; 95% confidence interval 1.25–1.69; p=8.5×10−7). In the replication step (7151 individuals), none of the eight variants replicated, and combined meta-analysis results failed to reach genome-wide significance.
In a GWAS, we were not able to reliably identify genetic variants predisposing to ERP, presumably due to insufficient statistical power and phenotype heterogeneity. The reported heritability of ERP warrants continued investigation in larger well-phenotyped populations.
Early repolarization; Sudden cardiac death; Arrhythmia; GWAS; Meta-analysis; Electrocardiogram
Previously, we reported strong influences of genetic variants on metabolic phenotypes, some of them with clinical relevance. Here, we hypothesize that DNA methylation may have an important and potentially independent effect on human metabolism. To test this hypothesis, we conducted what is to the best of our knowledge the first epigenome-wide association study (EWAS) between DNA methylation and metabolic traits (metabotypes) in human blood. We assess 649 blood metabolic traits from 1814 participants of the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) population study for association with methylation of 457 004 CpG sites, determined on the Infinium HumanMethylation450 BeadChip platform. Using the EWAS approach, we identified two types of methylome–metabotype associations. One type is driven by an underlying genetic effect; the other type is independent of genetic variation and potentially driven by common environmental and life-style-dependent factors. We report eight CpG loci at genome-wide significance that have a genetic variant as confounder (P = 3.9 × 10−20 to 2.0 × 10−108, r2 = 0.036 to 0.221). Seven loci display CpG site-specific associations to metabotypes, but do not exhibit any underlying genetic signals (P = 9.2 × 10−14 to 2.7 × 10−27, r2 = 0.008 to 0.107). We further identify several groups of CpG loci that associate with a same metabotype, such as 4-vinylphenol sulfate and 4-androsten-3-beta,17-beta-diol disulfate. In these cases, the association between CpG-methylation and metabotype is likely the result of a common external environmental factor, including smoking. Our study shows that analysis of EWAS with large numbers of metabolic traits in large population cohorts are, in principle, feasible. Taken together, our data suggest that DNA methylation plays an important role in regulating human metabolism.
Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.
Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
Men and women differ substantially regarding height, weight, and body fat. Interestingly, previous work detecting genetic effects for waist-to-hip ratio, to assess body fat distribution, has found that many of these showed sex-differences. However, systematic searches for sex-differences in genetic effects have not yet been conducted. Therefore, we undertook a genome-wide search for sexually dimorphic genetic effects for anthropometric traits including 133,723 individuals in a large meta-analysis and followed promising variants in further 137,052 individuals, including a total of 94 studies. We identified seven loci with significant sex-difference including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were significant in women, but not in men. Of interest is that sex-difference was only observed for waist phenotypes, but not for height or body-mass-index. We found no evidence for sex-differences with opposite effect direction for men and women. The PPARG locus is of specific interest due to its link to diabetes genetics and therapy. Our findings demonstrate the importance of investigating sex differences, which may lead to a better understanding of disease mechanisms with a potential relevance to treatment options.
Combined analyses of gene networks and DNA sequence variation can provide new insights into the aetiology of common diseases. Here, we used integrated genome-wide approaches across seven rat tissues to identify gene networks and the loci underlying their regulation. We defined an interferon regulatory factor 7 (IRF7)1-driven inflammatory network (iDIN) enriched for viral response genes, which represents a molecular biomarker for macrophages and was regulated in multiple tissues by a locus on rat chromosome 15q25. At this locus, Epstein-Barr virus induced gene 2 (Ebi2 or Gpr183), which we localised to macrophages and is known to control B lymphocyte migration2,3, regulated the iDIN. The human chromosome 13q32 locus, orthologous to rat 15q25, controlled the human equivalent of iDIN, which was conserved in monocytes. For the macrophage-associated autoimmune disease type 1 diabetes (T1D) iDIN genes were more likely to associate with T1D susceptibility than randomly selected immune response genes (P = 8.85 × 10−6). The human locus controlling the iDIN, was associated with the risk of T1D at SNP rs9585056 (P = 7.0 × 10−10, odds ratio = 1.15), which was one of five SNPs in this region associated with EBI2 expression. These data implicate IRF7 network genes and their regulatory locus in the pathogenesis of T1D.
There is evidence across several species for genetic control of phenotypic variation of complex traits1–4, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using 170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)5–7, is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of 0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation9,10. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
Nuclear magnetic resonance spectroscopy (NMR) provides robust readouts of many metabolic parameters in one experiment. However, identification of clinically relevant markers in 1H NMR spectra is a major challenge. Association of NMR-derived quantities with genetic variants can uncover biologically relevant metabolic traits. Using NMR data of plasma samples from 1,757 individuals from the KORA study together with 655,658 genetic variants, we show that ratios between NMR intensities at two chemical shift positions can provide informative and robust biomarkers. We report seven loci of genetic association with NMR-derived traits (APOA1, CETP, CPS1, GCKR, FADS1, LIPC, PYROXD2) and characterize these traits biochemically using mass spectrometry. These ratios may now be used in clinical studies.
In order to assess whether gene expression variability could be influenced by several SNPs acting in cis, either through additive or more complex haplotype effects, a systematic genome-wide search for cis haplotype expression quantitative trait loci (eQTL) was conducted in a sample of 758 individuals, part of the Cardiogenics Transcriptomic Study, for which genome-wide monocyte expression and GWAS data were available. 19,805 RNA probes were assessed for cis haplotypic regulation through investigation of ∼2,1×109 haplotypic combinations. 2,650 probes demonstrated haplotypic p-values >104-fold smaller than the best single SNP p-value. Replication of significant haplotype effects were tested for 412 probes for which SNPs (or proxies) that defined the detected haplotypes were available in the Gutenberg Health Study composed of 1,374 individuals. At the Bonferroni correction level of 1.2×10−4 (∼0.05/412), 193 haplotypic signals replicated. 1000G imputation was then conducted, and 105 haplotypic signals still remained more informative than imputed SNPs. In-depth analysis of these 105 cis eQTL revealed that at 76 loci genetic associations were compatible with additive effects of several SNPs, while for the 29 remaining regions data could be compatible with a more complex haplotypic pattern. As 24 of the 105 cis eQTL have previously been reported to be disease-associated loci, this work highlights the need for conducting haplotype-based and 1000G imputed cis eQTL analysis before commencing functional studies at disease-associated loci.
In order to assess whether gene expression variability could be influenced by the presence of more than one cis-acting SNP, we have conducted a systematic genome-wide search for haplotypic cis eQTL effects in a sample of 758 individuals and replicated the findings in an independent sample of 1,374 subjects. In both studies, genome-wide monocytes expression and genotype data were available. We identified 105 genes whose monocyte expression was under the influence of multiple cis-acting SNPs. About 75% of the detected genetic effects were related to independent additive SNP effects and the last quarter due to more complex haplotype effects. Of note, 24 of the genes identified to be affected by multiple cis eSNPs have been previously reported to reside at disease-associated loci. This could suggest that such multiple locus-specific genetic effects could contribute to the susceptibility to human diseases.
A large number of genome-wide association studies have been performed during the past five years to identify associations between SNPs and human complex diseases and traits. The assignment of a functional role for the identified disease-associated SNP is not straight-forward. Genome-wide expression quantitative trait locus (eQTL) analysis is frequently used as the initial step to define a function while allele-specific gene expression (ASE) analysis has not yet gained a wide-spread use in disease mapping studies. We compared the power to identify cis-acting regulatory SNPs (cis-rSNPs) by genome-wide allele-specific gene expression (ASE) analysis with that of traditional expression quantitative trait locus (eQTL) mapping. Our study included 395 healthy blood donors for whom global gene expression profiles in circulating monocytes were determined by Illumina BeadArrays. ASE was assessed in a subset of these monocytes from 188 donors by quantitative genotyping of mRNA using a genome-wide panel of SNP markers. The performance of the two methods for detecting cis-rSNPs was evaluated by comparing associations between SNP genotypes and gene expression levels in sample sets of varying size. We found that up to 8-fold more samples are required for eQTL mapping to reach the same statistical power as that obtained by ASE analysis for the same rSNPs. The performance of ASE is insensitive to SNPs with low minor allele frequencies and detects a larger number of significantly associated rSNPs using the same sample size as eQTL mapping. An unequivocal conclusion from our comparison is that ASE analysis is more sensitive for detecting cis-rSNPs than standard eQTL mapping. Our study shows the potential of ASE mapping in tissue samples and primary cells which are difficult to obtain in large numbers.
We aimed to assess whether pri-miRNA SNPs (miSNPs) could influence monocyte gene expression, either through marginal association or by interacting with polymorphisms located in 3'UTR regions (3utrSNPs). We then conducted a genome-wide search for marginal miSNPs effects and pairwise miSNPs × 3utrSNPs interactions in a sample of 1,467 individuals for which genome-wide monocyte expression and genotype data were available. Statistical associations that survived multiple testing correction were tested for replication in an independent sample of 758 individuals with both monocyte gene expression and genotype data. In both studies, the hsa-mir-1279 rs1463335 was found to modulate in cis the expression of LYZ and in trans the expression of CNTN6, CTRC, COPZ2, KRT9, LRRFIP1, NOD1, PCDHA6, ST5 and TRAF3IP2 genes, supporting the role of hsa-mir-1279 as a regulator of several genes in monocytes. In addition, we identified two robust miSNPs × 3utrSNPs interactions, one involving HLA-DPB1 rs1042448 and hsa-mir-219-1 rs107822, the second the H1F0 rs1894644 and hsa-mir-659 rs5750504, modulating the expression of the associated genes.
As some of the aforementioned genes have previously been reported to reside at disease-associated loci, our findings provide novel arguments supporting the hypothesis that the genetic variability of miRNAs could also contribute to the susceptibility to human diseases.
High plasma HDL cholesterol is associated with reduced risk of myocardial infarction, but whether this association is causal is unclear. Exploiting the fact that genotypes are randomly assigned at meiosis, are independent of non-genetic confounding, and are unmodified by disease processes, mendelian randomisation can be used to test the hypothesis that the association of a plasma biomarker with disease is causal.
We performed two mendelian randomisation analyses. First, we used as an instrument a single nucleotide polymorphism (SNP) in the endothelial lipase gene (LIPG Asn396Ser) and tested this SNP in 20 studies (20 913 myocardial infarction cases, 95 407 controls). Second, we used as an instrument a genetic score consisting of 14 common SNPs that exclusively associate with HDL cholesterol and tested this score in up to 12 482 cases of myocardial infarction and 41 331 controls. As a positive control, we also tested a genetic score of 13 common SNPs exclusively associated with LDL cholesterol.
Carriers of the LIPG 396Ser allele (2·6% frequency) had higher HDL cholesterol (0·14 mmol/L higher, p=8×10−13) but similar levels of other lipid and non-lipid risk factors for myocardial infarction compared with non-carriers. This difference in HDL cholesterol is expected to decrease risk of myocardial infarction by 13% (odds ratio [OR] 0·87, 95% CI 0·84–0·91). However, we noted that the 396Ser allele was not associated with risk of myocardial infarction (OR 0·99, 95% CI 0·88–1·11, p=0·85). From observational epidemiology, an increase of 1 SD in HDL cholesterol was associated with reduced risk of myocardial infarction (OR 0·62, 95% CI 0·58–0·66). However, a 1 SD increase in HDL cholesterol due to genetic score was not associated with risk of myocardial infarction (OR 0·93, 95% CI 0·68–1·26, p=0·63). For LDL cholesterol, the estimate from observational epidemiology (a 1 SD increase in LDL cholesterol associated with OR 1·54, 95% CI 1·45–1·63) was concordant with that from genetic score (OR 2·13, 95% CI 1·69–2·69, p=2×10−10).
Some genetic mechanisms that raise plasma HDL cholesterol do not seem to lower risk of myocardial infarction. These data challenge the concept that raising of plasma HDL cholesterol will uniformly translate into reductions in risk of myocardial infarction.
US National Institutes of Health, The Wellcome Trust, European Union, British Heart Foundation, and the German Federal Ministry of Education and Research.
eQTL analyses are important to improve the understanding of genetic association results. Here, we performed a genome-wide association and global gene expression study to identify functionally relevant variants affecting the risk of coronary artery disease (CAD).
Methods and Results
In a genome-wide association analysis of 2,078 CAD cases and 2,953 controls, we identified 950 single nucleotide polymorphisms (SNPs) that were associated with CAD at P<10-3. Subsequent in silico and wet-lab replication stages and a final meta-analysis of 21,428 CAD cases and 38,361 controls revealed a novel association signal at chromosome 10q23.31 within the LIPA (Lysosomal Acid Lipase A) gene (P=3.7×10-8; OR 1.1; 95% CI: 1.07-1.14). The association of this locus with global gene expression was assessed by genome-wide expression analyses in the monocyte transcriptome of 1,494 individuals. The results showed a strong association of this locus with expression of the LIPA transcript (P=1.3×10-96). An assessment of LIPA SNPs and transcript with cardiovascular phenotypes revealed an association of LIPA transcript levels with impaired endothelial function (P=4.4×10-3).
The use of data on genetic variants and the addition of data on global monocytic gene expression led to the identification of the novel functional CAD susceptibility locus LIPA, located on chromosome 10q23.31. The respective eSNPs associated with CAD strongly affect LIPA gene expression level, which itself was related to endothelial dysfunction, a precursor of CAD.
coronary artery disease; genome-wide association studies; gene expression; genetic variation; genomics; eQTL; eSNP; LIPA
The male-to-female sex ratio at birth is constant across world populations with an average of 1.06 (106 male to 100 female live births) for populations of European descent. The sex ratio is considered to be affected by numerous biological and environmental factors and to have a heritable component. The aim of this study was to investigate the presence of common allele modest effects at autosomal and chromosome X variants that could explain the observed sex ratio at birth. We conducted a large-scale genome-wide association scan (GWAS) meta-analysis across 51 studies, comprising overall 114 863 individuals (61 094 women and 53 769 men) of European ancestry and 2 623 828 common (minor allele frequency >0.05) single-nucleotide polymorphisms (SNPs). Allele frequencies were compared between men and women for directly-typed and imputed variants within each study. Forward-time simulations for unlinked, neutral, autosomal, common loci were performed under the demographic model for European populations with a fixed sex ratio and a random mating scheme to assess the probability of detecting significant allele frequency differences. We do not detect any genome-wide significant (P < 5 × 10−8) common SNP differences between men and women in this well-powered meta-analysis. The simulated data provided results entirely consistent with these findings. This large-scale investigation across ∼115 000 individuals shows no detectable contribution from common genetic variants to the observed skew in the sex ratio. The absence of sex-specific differences is useful in guiding genetic association study design, for example when using mixed controls for sex-biased traits.
More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.
Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5–18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.
Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50–59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.
Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.
Dilated cardiomyopathy (DCM) is a major cause of heart failure with a high familial recurrence risk. So far, the genetics of DCM remains largely unresolved. We conducted the first genome-wide association study (GWAS) to identify loci contributing to sporadic DCM.
Methods and results
One thousand one hundred and seventy-nine DCM patients and 1108 controls contributed to the discovery phase. Pools of DNA stratified on disease status, population, age, and gender were constituted and used for testing association of DCM with 517 382 single nucleotide polymorphisms (SNPs). Three DCM-associated SNPs were confirmed by individual genotyping (P < 5.0 10−7), and two of them, rs10927875 and rs2234962, were replicated in independent samples (1165 DCM patients and 1302 controls), with P-values of 0.002 and 0.009, respectively. rs10927875 maps to a region on chromosome 1p36.13 which encompasses several genes among which HSPB7 has been formerly suggested to be implicated in DCM. The second identified locus involves rs2234962, a non-synonymous SNP (c.T757C, p. C151R) located within the sequence of BAG3 on chromosome 10q26. To assess whether coding mutations of BAG3 might cause monogenic forms of the disease, we sequenced BAG3 exons in 168 independent index cases diagnosed with familial DCM and identified four truncating and two missense mutations. Each mutation was heterozygous, present in all genotyped relatives affected by the disease and absent in a control group of 347 healthy individuals, strongly suggesting that these mutations are causing the disease.
This GWAS identified two loci involved in sporadic DCM, one of them probably implicates BAG3. Our results show that rare mutations in BAG3 contribute to monogenic forms of the disease, while common variant(s) in the same gene are implicated in sporadic DCM.
Dilated cardiomyopathy; Heart failure; Genome wide association study; CLCNKA; HSPB7; BAG3
Platelets are the second most abundant cell type in blood and are essential for maintaining haemostasis. Their count and volume are tightly controlled within narrow physiological ranges, but there is only limited understanding of the molecular processes controlling both traits. Here we carried out a high-powered meta-analysis of genome-wide association studies (GWAS) in up to 66,867 individuals of European ancestry, followed by extensive biological and functional assessment. We identified 68 genomic loci reliably associated with platelet count and volume mapping to established and putative novel regulators of megakaryopoiesis and platelet formation. These genes show megakaryocyte-specific gene expression patterns and extensive network connectivity. Using gene silencing in Danio rerio and Drosophila melanogaster, we identified 11 of the genes as novel regulators of blood cell formation. Taken together, our findings advance understanding of novel gene functions controlling fate-determining events during megakaryopoiesis and platelet formation, providing a new example of successful translation of GWAS to function.
Recent genome-wide association studies (GWAS) have identified several novel loci that reproducibly associate with CAD and/or MI risk. However, known common CAD risk variants explain only 10% of the predicted genetic heritability of the disease, suggesting that important genetic signals remain to be discovered.
Methods and Results
We performed a discovery meta-analysis of 5 GWASs involving 13,949 subjects (7123 cases, 6826 controls) imputed at approximately 5 million SNPs using pilot 1000 Genomes based haplotypes. Promising loci were followed up in an additional 5 studies with 11,032 subjects (5211 cases, 5821 controls). A novel CAD locus on chromosome 6p21.3 in the major histocompatibility complex (MHC) between HCG27 and HLA-C was identified and achieved genome wide significance in the combined analysis (rs3869109; pdiscovery=3.3×10−7, preplication=5.3×10−4 pcombined=1.12×10−9). A sub-analysis combining discovery GWASs showed an attenuation of significance when stringent corrections for European population structure were employed (p=4.1×10-10 versus 3.2×10-7) suggesting the observed signal is partly confounded due to population stratification. This gene dense region plays an important role in inflammation, immunity and self cell recognition. To determine whether the underlying association was driven by MHC class I alleles, we statistically imputed common HLA alleles into the discovery subjects; however, no single common HLA type contributed significantly or fully explained the observed association.
We have identified a novel locus in the MHC associated with CAD. MHC genes regulate inflammation and T cell responses that contribute importantly to the initiation and propagation of atherosclerosis. Further laboratory studies will be required to understand the biological basis of this association and identify the causative allele(s).
coronary artery disease; myocardial infarction; meta-analysis; genetics