Coagulation factor VIII, white matter hyperintensities and cognitive function: Results from the Cardiovascular Health Study

Objective: To investigate the relationship between high FVIII clotting activity (FVIII:C), MRI-defined white matter hyperintensities (WMH) and cognitive function over time. Methods: Data from the population-based Cardiovascular Health Study (n = 5,888, aged ≥ 65) were used. FVIII:C was measured in blood samples taken at baseline. WMH burden was assessed on two cranial MRI scans taken roughly 5 years apart. Cognitive function was assessed annually using the Modified Mini-Mental State Examination (3MSE) and Digit Symbol Substitution Test (DSST). We used ordinal logistic regression models adjusted for demographic and cardiovascular factors in cross-sectional and longitudinal WMH analyses, and adjusted linear regression and linear mixed models in the analyses of cognitive function. Results: After adjustment for confounding, higher levels of FVIII:C were not strongly associated with the burden of WMH on the initial MRI scan (OR>p75 = 1.20, 95% CI 0.99-1.45; N = 2,735) nor with WMH burden worsening over time (OR>p75 = 1.18, 95% CI 0.87-1.59; N = 1,527). High FVIII:C showed no strong association with cognitive scores cross-sectionally (3MSE>p75 β = -0.06, 95%CI -0.45 to 0.32, N = 4,005; DSST>p75 β = -0.69, 95%CI -1.52 to 0.13, N = 3,954) or over time (3MSE>p75 β = -0.07,95% CI -0.58 to 0.44, N = 2,764; DSST>p75 β = -0.22, 95% CI -0.97 to 0.53, N = 2,306) after confounding adjustment. Interpretation: The results from this cohort study of older adult participants indicate no strong relationships between higher FVIII:C levels and WMH burden or cognitive function in cross-sectional and longitudinal analyses

Plasma Phospholipid Saturated Fatty Acids and Incident Atrial Fibrillation: The Cardiovascular Health Study

Background: Prior studies suggest that circulating fatty acids may influence the risk of atrial fibrillation (AF), but little is known about the associations of circulating saturated fatty acids with risk of AF. Methods and Results: The study population included 2899 participants from the Cardiovascular Health Study, a community‐based longitudinal cohort of adults aged 65 years or older in the United States who were free of prevalent coronary heart disease and AF in 1992. Cox regression was used to assess the association of all the long‐chain saturated fatty acids—palmitic acid (16:0), stearic acid (18:0), arachidic acid (20:0), behenic acid (22:0), and lignoceric acid (24:0)—with incident AF. During a median of 11.2 years of follow‐up, 707 cases of incident AF occurred. After adjustment for other AF risk factors, higher levels of circulating 16:0 were associated with a higher risk of AF (hazard ratio comparing highest and lowest quartiles: 1.48; 95% CI: 1.18, 1.86). In contrast, higher levels of circulating 18:0, 20:0, 22:0, and 24:0 were each associated with a lower risk of AF. The hazard ratios (95% CI) for AF in the top and bottom quartiles were 0.76 (95% CI: 0.61, 0.95) for 18:0; 0.78 (95% CI: 0.63, 0.97) for 20:0; 0.62 (95% CI: 0.50, 0.78) for 22:0; and 0.68 (95% CI: 0.55, 0.85) for 24:0. Conclusions: Results from this prospective cohort study of older adults demonstrate divergent associations of circulating 16:0 versus longer‐chain saturated fatty acids with incident AF, highlighting the need to investigate both determinants of these levels and potential pathways of the observed differential risk

Generalized estimating equations for genome-wide association studies using longitudinal phenotype data

Many longitudinal cohort studies have both genome-wide measures of genetic variation and repeated measures of phenotypes and environmental exposures. Genome-wide association study analyses have typically used only cross-sectional data to evaluate quantitative phenotypes and binary traits. Incorporation of repeated measures may increase power to detect associations, but also requires specialized analysis methods. Here we discuss one such method – generalized estimating equations (GEE) – in the contexts of analysis of main effects of rare genetic variants and analysis of gene-environment interactions. We illustrate the potential for increased power using GEE analyses instead of cross-sectional analyses. We also address challenges that arise, such as the need for small-sample corrections when the minor allele frequency of a genetic variant and/or the prevalence of an environmental exposure is low. To illustrate methods for detection of gene-drug interactions on a genome-wide scale, using repeated measures data, we conduct single-study analyses and meta-analyses across studies in three large cohort studies participating in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium – the Atherosclerosis Risk in Communities (ARIC) study, the Cardiovascular Health Study (CHS), and the Rotterdam Study (RS)

Genome-wide Association Study of Susceptibility to Particulate Matter–Associated QT Prolongation

BACKGROUND: Ambient particulate matter (PM) air pollution exposure has been associated with increases in QT interval duration (QT). However, innate susceptibility to PM-associated QT prolongation has not been characterized. OBJECTIVE: To characterize genetic susceptibility to PM-associated QT prolongation in a multi-racial/ethnic, genome-wide association study (GWAS). METHODS: Using repeated electrocardiograms (1986–2004), longitudinal data on PM<10 μm in diameter (PM10), and generalized estimating equations methods adapted for low-prevalence exposure, we estimated approximately 2.5×106 SNP×PM10 interactions among nine Women’s Health Initiative clinical trials and Atherosclerosis Risk in Communities Study subpopulations (n=22,158), then combined subpopulation-specific results in a fixed-effects, inverse variance-weighted meta-analysis. RESULTS: A common variant (rs1619661; coded allele: T) significantly modified the QT-PM10 association (p=2.11×10−8). At PM10 concentrations >90th percentile, QT increased 7 ms across the CC and TT genotypes: 397 (95% confidence interval: 396, 399) to 404 (403, 404) ms. However, QT changed minimally across rs1619661 genotypes at lower PM10 concentrations. The rs1619661 variant is on chromosome 10, 132 kilobase (kb) downstream from CXCL12, which encodes a chemokine, stromal cell-derived factor 1, that is expressed in cardiomyocytes and decreases calcium influx across the L-type Ca2+ channel. CONCLUSIONS: The findings suggest that biologically plausible genetic factors may alter susceptibility to PM10-associated QT prolongation in populations protected by the U.S. Environmental Protection Agency’s National Ambient Air Quality Standards. Independent replication and functional characterization are necessary to validate our findings. https://doi.org/10.1289/EHP34

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction &gt; 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD

Pharmacogenomics of statin-related myopathy:Meta-analysis of rare variants from whole-exome sequencing

AIMS:Statin-related myopathy (SRM), which includes rhabdomyolysis, is an uncommon but important adverse drug reaction because the number of people prescribed statins world-wide is large. Previous association studies of common genetic variants have had limited success in identifying a genetic basis for this adverse drug reaction. We conducted a multi-site whole-exome sequencing study to investigate whether rare coding variants confer an increased risk of SRM. METHODS AND RESULTS:SRM 3-5 cases (N = 505) and statin treatment-tolerant controls (N = 2047) were recruited from multiple sites in North America and Europe. SRM 3-5 was defined as symptoms consistent with muscle injury and an elevated creatine phosphokinase level >4 times upper limit of normal without another likely cause of muscle injury. Whole-exome sequencing and variant calling was coordinated from two analysis centres, and results of single-variant and gene-based burden tests were meta-analysed. No genome-wide significant associations were identified. Given the large number of cases, we had 80% power to identify a variant with minor allele frequency of 0.01 that increases the risk of SRM 6-fold at genome-wide significance. CONCLUSIONS:In this large whole-exome sequencing study of severe statin-related muscle injury conducted to date, we did not find evidence that rare coding variants are responsible for this adverse drug reaction. Larger sample sizes would be required to identify rare variants with small effects, but it is unclear whether such findings would be clinically actionable

The challenges of genome-wide interaction studies: Lessons to learn from the analysis of HDL blood levels

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP6SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value, 1 · 1028 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30, 011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP6SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS

Rare and low-frequency exonic variants and gene-by-smoking interactions in pulmonary function

Genome-wide association studies have identified numerous common genetic variants associated with spirometric measures of pulmonary function, including forced expiratory volume in one second (FEV1), forced vital capacity, and their ratio. However, variants with lower minor allele frequencies are less explored. We conducted a large-scale gene-smoking interaction meta-analysis on exonic rare and low-frequency variants involving 44,429 individuals of European ancestry in the discovery stage and sought replication in the UK BiLEVE study with 45,133 European ancestry samples and UK Biobank study with 59,478 samples. We leveraged data on cigarette smoking, the major environmental risk factor for reduced lung function, by testing gene-by-smoking interaction effects only and simultaneously testing the genetic main effects and interaction effects. The most statistically significant signal that replicated was a previously reported low-frequency signal in GPR126, distinct from common variant associations in this gene. Although only nominal replication was obtained for a top rare variant signal rs142935352 in one of the two studies, interaction and joint tests for current smoking and PDE3B were s

Meta-analysis of exome array data identifies six novel genetic loci for lung function [version 1; peer review:1 approved, 1 approved with reservations]

Background: Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. Methods: We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and the ratio of FEV1 to FVC (FEV1/FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. Results: We identified significant (P&lt;2•8x10 -7 ) associations with six SNPs: a nonsynonymous variant in RPAP1, which is predicted to be damaging, three intronic SNPs (SEC24C, CASC17 and UQCC1) and two intergenic SNPs near to LY86 and FGF10. Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including TYRO3 and PLAU. Conclusions: Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease.</p