Gene-centric meta-analysis in 87,736 individuals of European ancestry identifies multiple blood-pressure-related loci.

Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ~50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10(-7)) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification.

Mendelian randomization of blood lipids for coronary heart disease.

AIMS: To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. METHODS AND RESULTS: We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). CONCLUSION: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.

Loci influencing blood pressure identified using a cardiovascular gene-centric array.

Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ∼50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ∼2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10(-6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.

Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.

HBsAg loss in patients treated with peginterferon alfa-2a and adefovir is associated with SLC16A9 gene variation and lower plasma carnitine levels.

BACKGROUND & AIMS: Achievement of HBsAg loss remains the hallmark of chronic hepatitis B treatment. In order to identify host factors contributing to treatment-induced HBsAg loss, we performed a genome-wide screen of single nucleotide polymorphisms (SNPs) and studied its immunological consequence. METHODS: Chronic hepatitis B patients (40 HBeAg-positive and 44 HBeAg-negative) treated with peginterferon alfa-2a and adefovir were genotyped for 999,091 SNPs, which were associated with HBsAg loss at week 96 (n = 9). Plasma carnitine levels were measured by tandem-mass spectrometry, and the effect of carnitine on the proliferative capacity of hepatitis B virus (HBV)-specific and non-specific CD8 T cells was studied in vitro. RESULTS: One polymorphism, rs12356193 located in the SLC16A9 gene, was genome-wide significantly associated with HBsAg loss at week 96 (p = 1.84 × 10(-8)). The previously reported association of rs12356193 with lower carnitine levels was confirmed in our cohort, and baseline carnitine levels were lower in patients with HBsAg loss compared to patients with HBsAg persistence (p = 0.02). Furthermore, we demonstrated that carnitine suppressed HBV-specific CD8 T cell proliferation. CONCLUSIONS: In chronic hepatitis B patients treated with peginterferon and adefovir, we identified strong associations of SLC16A9 gene variation and carnitine levels with HBsAg loss. Our results further suggest that a lower baseline plasma carnitine level increases the proliferative capacity of CD8 T cells, making patients more susceptible to the immunological effect of this treatment. These novel findings may provide new insight into factors involved in treatment-induced HBsAg loss, and play a role in the prediction of treatment outcome.

Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height.

Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.

Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals.

BACKGROUND: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG). RESULTS: Our analysis consisted of a discovery phase using a merged dataset of five different cohorts (n = 12,853 to n = 16,849 depending on lipid phenotype) and a replication phase with ten independent cohorts totaling up to 36,938 additional samples. Filters are often applied before interaction testing to correct for the burden of testing all pairwise interactions. We used two different filters: 1. A filter that tested only single nucleotide polymorphisms (SNPs) with a main effect of p < 0.001 in a previous association study. 2. A filter that only tested interactions identified by Biofilter 2.0. Pairwise models that reached an interaction significance level of p < 0.001 in the discovery dataset were tested for replication. We identified thirteen SNP-SNP models that were significant in more than one replication cohort after accounting for multiple testing. CONCLUSIONS: These results may reveal novel insights into the genetic etiology of lipid levels. Furthermore, we developed a pipeline to perform a computationally efficient interaction analysis with multi-cohort replication.

Genetic analysis of emerging risk factors in coronary artery disease.

BACKGROUND AND AIMS: Type 2 diabetes (T2D), low-density lipoprotein-cholesterol (LDL-c), body mass index (BMI), blood pressure and smoking are established risk factors that play a causal role in coronary artery disease (CAD). Numerous common genetic variants associating with these and other risk factors have been identified, but their association with CAD has not been comprehensively examined in a single study. Our goal was to comprehensively evaluate the associations of established and emerging risk factors with CAD using genetic variants identified from Genome-wide Association Studies (GWAS). METHODS: We tested the effect of 60 traditional and putative risk factors with CAD, using summary statistics obtained in GWAS. We approximated the regression of a response variable onto an additive multi-SNP genetic risk score in the Coronary Artery DIsease Genomewide Replication And Meta-analysis (CARDIoGRAM) consortium dataset weighted by the effect of the SNP on the risk factors. RESULTS: The strongest association with risk of CAD was for LDL-c SNPs (p = 3.96E-34). For non-established CAD risk factors, we found significant CAD associations for coronary artery calcification (CAC), Lp(a), LP-PLA2 activity, plaque, vWF and FVIII. In an attempt to identify independent associations between risk factors and CAD, only SNPs with an effect on the target trait were included. This identified CAD associations for Lp(a)(p = 1.77E-21), LDL-c (p = 4.16E-06), triglycerides (TG) (p = 1.94E-05), height (p = 2.06E-05), CAC (p = 3.13E-23) and carotid plaque (p = 2.08E-05). CONCLUSIONS: We identified SNPs associated with the emerging risk factors Lp(a), TG, plaque, height and CAC to be independently associated with risk of CAD. This provides further support for-ongoing clinical trials of Lp(a) and TG, and suggests that CAC and plaque could be used as surrogate markers for CAD in clinical trials.

Common genetic variants do not associate with CAD in familial hypercholesterolemia.

In recent years, multiple loci dispersed on the genome have been shown to be associated with coronary artery disease (CAD). We investigated whether these common genetic variants also hold value for CAD prediction in a large cohort of patients with familial hypercholesterolemia (FH). We genotyped a total of 41 single-nucleotide polymorphisms (SNPs) in 1701 FH patients, of whom 482 patients (28.3%) had at least one coronary event during an average follow up of 66 years. The association of each SNP with event-free survival time was calculated with a Cox proportional hazard model. In the cardiovascular disease risk factor adjusted analysis, the most significant SNP was rs1122608:G>T in the SMARCA4 gene near the LDL-receptor (LDLR) gene, with a hazard ratio for CAD risk of 0.74 (95% CI 0.49-0.99; P-value 0.021). However, none of the SNPs reached the Bonferroni threshold. Of all the known CAD loci analyzed, the SMARCA4 locus near the LDLR had the strongest negative association with CAD in this high-risk FH cohort. The effect is contrary to what was expected. None of the other loci showed association with CAD.

Secretory phospholipase A(2)-IIA and cardiovascular disease: a mendelian randomization study.

OBJECTIVES: This study sought to investigate the role of secretory phospholipase A2 (sPLA2)-IIA in cardiovascular disease. BACKGROUND: Higher circulating levels of sPLA2-IIA mass or sPLA2 enzyme activity have been associated with increased risk of cardiovascular events. However, it is not clear if this association is causal. A recent phase III clinical trial of an sPLA2 inhibitor (varespladib) was stopped prematurely for lack of efficacy. METHODS: We conducted a Mendelian randomization meta-analysis of 19 general population studies (8,021 incident, 7,513 prevalent major vascular events [MVE] in 74,683 individuals) and 10 acute coronary syndrome (ACS) cohorts (2,520 recurrent MVE in 18,355 individuals) using rs11573156, a variant in PLA2G2A encoding the sPLA2-IIA isoenzyme, as an instrumental variable. RESULTS: PLA2G2A rs11573156 C allele associated with lower circulating sPLA2-IIA mass (38% to 44%) and sPLA2 enzyme activity (3% to 23%) per C allele. The odds ratio (OR) for MVE per rs11573156 C allele was 1.02 (95% confidence interval [CI]: 0.98 to 1.06) in general populations and 0.96 (95% CI: 0.90 to 1.03) in ACS cohorts. In the general population studies, the OR derived from the genetic instrumental variable analysis for MVE for a 1-log unit lower sPLA2-IIA mass was 1.04 (95% CI: 0.96 to 1.13), and differed from the non-genetic observational estimate (OR: 0.69; 95% CI: 0.61 to 0.79). In the ACS cohorts, both the genetic instrumental variable and observational ORs showed a null association with MVE. Instrumental variable analysis failed to show associations between sPLA2 enzyme activity and MVE. CONCLUSIONS: Reducing sPLA2-IIA mass is unlikely to be a useful therapeutic goal for preventing cardiovascular events.

Gene-centric meta-analysis of lipid traits in African, East Asian and Hispanic populations.

Meta-analyses of European populations has successfully identified genetic variants in over 100 loci associated with lipid levels, but our knowledge in other ethnicities remains limited. To address this, we performed dense genotyping of ∼2,000 candidate genes in 7,657 African Americans, 1,315 Hispanics and 841 East Asians, using the IBC array, a custom ∼50,000 SNP genotyping array. Meta-analyses confirmed 16 lipid loci previously established in European populations at genome-wide significance level, and found multiple independent association signals within these lipid loci. Initial discovery and in silico follow-up in 7,000 additional African American samples, confirmed two novel loci: rs5030359 within ICAM1 is associated with total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) (p = 8.8×10(-7) and p = 1.5×10(-6) respectively) and a nonsense mutation rs3211938 within CD36 is associated with high-density lipoprotein cholesterol (HDL-C) levels (p = 13.5×10(-12)). The rs3211938-G allele, which is nearly absent in European and Asian populations, has been previously found to be associated with CD36 deficiency and shows a signature of selection in Africans and African Americans. Finally, we have evaluated the effect of SNPs established in European populations on lipid levels in multi-ethnic populations and show that most known lipid association signals span across ethnicities. However, differences between populations, especially differences in allele frequency, can be leveraged to identify novel signals, as shown by the discovery of ICAM1 and CD36 in the current report.