Genetic loci on chromosome 5 are associated with circulating levels of interleukin-5 and eosinophil count in a European population with high risk for cardiovascular disease

IL-5 is a Th2 cytokine which activates eosinophils and is suggested to have an atheroprotective role. Genetic variants in the IL5 locus have been associated with increased risk of CAD and ischemic stroke. In this study we aimed to identify genetic variants associated with IL-5 concentrations and apply a Mendelian randomisation approach to assess IL-5 levels for causal effect on intima-media thickness in a European population at high risk of coronary artery disease. We analysed SNPs within robustly associated candidate loci for immune, inflammatory, metabolic and cardiovascular traits. We identified 2 genetic loci for IL-5 levels (chromosome 5, rs56183820, BETA = 0.11, P = 6.73E−5 and chromosome 14, rs4902762, BETA = 0.12, P = 5.76E−6) and one for eosinophil count (rs72797327, BETA = −0.10, P = 1.41E−6). Both chromosome 5 loci were in the vicinity of the IL5 gene, however the association with IL-5 levels failed to replicate in a meta-analysis of 2 independent cohorts (rs56183820, BETA = 0.04, P = 0.2763, I2 = 24, I2 − P = 0.2516). No significant associations were observed between SNPs associated with IL-5 levels or eosinophil count and IMT measures. Expression quantitative trait analyses indicate effects of the IL-5 and eosinophil-associated SNPs on RAD50 mRNA expression levels (rs12652920 (r2 = 0.93 with rs56183820) BETA = −0.10, P = 8.64E−6 and rs11739623 (r2 = 0.96 with rs72797327) BETA = −0.23, P = 1.74E−29, respectively). Our data do not support a role for IL-5 levels and eosinophil count in intima-media thickness, however SNPs associated with IL-5 and eosinophils might influence stability of the atherosclerotic plaque via modulation of RAD50 levels

Apolipoprotein Proteomics for Residual Lipid-Related Risk in Coronary Heart Disease

BACKGROUND: Recognition of the importance of conventional lipid measures and the advent of novel lipid-lowering medications have prompted the need for more comprehensive lipid panels to guide use of emerging treatments for the prevention of coronary heart disease (CHD). This report assessed the relevance of 13 apolipoproteins measured using a single mass-spectrometry assay for risk of CHD in the PROCARDIS case-control study of CHD (941 cases/975 controls). METHODS: The associations of apolipoproteins with CHD were assessed after adjustment for established risk factors and correction for statin use. Apolipoproteins were grouped into 4 lipid-related classes [lipoprotein(a), low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and triglycerides] and their associations with CHD were adjusted for established CHD risk factors and conventional lipids. Analyses of these apolipoproteins in a subset of the ASCOT trial (Anglo-Scandinavian Cardiac Outcomes Trial) were used to assess their within-person variability and to estimate a correction for statin use. The findings in the PROCARDIS study were compared with those for incident cardiovascular disease in the Bruneck prospective study (n=688), including new measurements of Apo(a). RESULTS: Triglyceride-carrying ApoC1, ApoC3, and ApoE (apolipoproteins) were most strongly associated with the risk of CHD (2- to 3-fold higher odds ratios for top versus bottom quintile) independent of conventional lipid measures. Likewise, ApoB was independently associated with a 2-fold higher odds ratios of CHD. Lipoprotein(a) was measured using peptides from the Apo(a)-kringle repeat and Apo(a)-constant regions, but neither of these associations differed from the association with conventionally measured lipoprotein(a). Among HDL-related apolipoproteins, ApoA4 and ApoM were inversely related to CHD, independent of conventional lipid measures. The disease associations with all apolipoproteins were directionally consistent in the PROCARDIS and Bruneck studies, with the exception of ApoM. CONCLUSIONS: Apolipoproteins were associated with CHD independent of conventional risk factors and lipids, suggesting apolipoproteins could help to identify patients with residual lipid-related risk and guide personalized approaches to CHD risk reduction

Genome-Wide Meta-analysis identifies three novel loci associated with stroke

We conducted a European‐only and transancestral genome‐wide association meta‐analysis in 72,147 stroke patients and 823,869 controls using data from UK Biobank (UKB) and the MEGASTROKE consortium. We identified an exonic polymorphism in NOS3 (rs1799983, p.Glu298Asp; p = 2.2E‐8, odds ratio [OR] = 1.05, 95% confidence interval [CI] = 1.04–1.07) and variants in an intron of COL4A1 (rs9521634; p = 3.8E‐8, OR = 1.04, 95% CI = 1.03–1.06) and near DYRK1A (rs720470; p = 6.1E‐9, OR = 1.05, 95% CI = 1.03–1.07) at genome‐wide significance for stroke. Effect sizes of known stroke loci were highly correlated between UKB and MEGASTROKE. Using Mendelian randomization, we further show that genetic variation in the nitric oxide synthase–nitric oxide pathway in part affects stroke risk via variation in blood pressure

The use of primary care big data for COVID-19 research: A consensus statement from the COVID-19 Primary Care Database Consortium

The use of big data containing millions of primary care medical records provides an opportunity for rapid research to help inform patient care and policy decisions during the first and subsequent waves of the COVID-19 pandemic. Routinely collected UK primary care data have previously been used for national pandemic surveillance, quantifying associations between exposures and outcomes, identifying high-risk populations and examining the effects of interventions at scale. However, there is no consensus on how to effectively conduct or report these data for COVID-19 research. A COVID-19 primary care database consortium was established in April 2020. Collectively, its researchers have ongoing COVID-19 projects in overlapping datasets with millions of primary care records representing 30% of the UK population, that are variously linked to public health, secondary care and vital status records. This consensus agreement is aimed at facilitating transparency and rigour in methodological approaches, as well as consistency in defining and reporting cases, exposures, confounders, stratification variables and outcomes in relation to the pharmacoepidemiology of COVID-19. This will facilitate comparison, validation and pooling of research during and after the pandemic.https://deepblue.lib.umich.edu/bitstream/2027.42/154864/1/Consensus statement.pdfDescription of Consensus statement.pdf : Main Articl

Genome-Wide Association Study of Peripheral Artery Disease

Background: Peripheral artery disease (PAD) affects >200 million people worldwide and is associated with high mortality and morbidity. We sought to identify genomic variants associated with PAD overall and in the contexts of diabetes and smoking status. Methods: We identified genetic variants associated with PAD and then meta-analyzed with published summary statistics from the Million Veterans Program and UK Biobank to replicate their findings. Next, we ran stratified genome-wide association analysis in ever smokers, never smokers, individuals with diabetes, and individuals with no history of diabetes and corresponding interaction analyses, to identify variants that modify the risk of PAD by diabetic or smoking status. Results: We identified 5 genome-wide significant (P-associationPeer reviewe

Large-Scale Candidate Gene Analysis of HDL Particle Features

Background: HDL cholesterol (HDL-C) is an established marker of cardiovascular risk with significant genetic determination. However, HDL particles are not homogenous, and refined HDL phenotyping may improve insight into regulation of HDL metabolism. We therefore assessed HDL particles by NMR spectroscopy and conducted a large-scale candidate gene association analysis. Methodology/Principal Findings: We measured plasma HDL-C and determined mean HDL particle size and particle number by NMR spectroscopy in 2024 individuals from 512 British Caucasian families. Genotypes were 49,094 SNPs in >2,100 cardiometabolic candidate genes/loci as represented on the HumanCVD BeadChip version 2. False discovery rates (FDR) were calculated to account for multiple testing. Analyses on classical HDL-C revealed significant associations (FDR<0.05) only for CETP (cholesteryl ester transfer protein; lead SNP rs3764261: p = 5.6*10(-15)) and SGCD (sarcoglycan delta; rs6877118: p = 8.6*10(-6)). In contrast, analysis with HDL mean particle size yielded additional associations in LIPC (hepatic lipase; rs261332: p = 6.1*10(-9)), PLTP (phospholipid transfer protein, rs4810479: p = 1.7*10(-8)) and FBLN5 (fibulin-5; rs2246416: p = 6.2*10(-6)). The associations of SGCD and Fibulin-5 with HDL particle size could not be replicated in PROCARDIS (n = 3,078) and/or the Women's Genome Health Study (n = 23,170). Conclusions: We show that refined HDL phenotyping by NMR spectroscopy can detect known genes of HDL metabolism better than analyses on HDL-C