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 > 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

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 ofmajor 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 regressionmodels 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 > 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 genom

Nociceptive Afferent Activity Alters the SI RA Neuron Response to Mechanical Skin Stimulation

Procedures that reliably evoke cutaneous pain in humans (i.e., 5–7 s skin contact with a 47–51 °C probe, intradermal algogen injection) are shown to decrease the mean spike firing rate (MFR) and degree to which the rapidly adapting (RA) neurons in areas 3b/1 of squirrel monkey primary somatosensory cortex (SI) entrain to a 25-Hz stimulus to the receptive field center (RFcenter) when stimulus amplitude is “near-threshold” (i.e., 10–50 μm). In contrast, RA neuron MFR and entrainment are either unaffected or enhanced by 47–51 °C contact or intradermal algogen injection when the amplitude of 25-Hz stimulation is 100–200 μm (suprathreshold). The results are attributed to an “activity dependence” of γ-aminobutyric acid (GABA) action on the GABAA receptors of RA neurons. The nociceptive afferent drive triggered by skin contact with a 47–51 °C probe or intradermal algogen is proposed to activate nociresponsive neurons in area 3a which, via corticocortical connections, leads to the release of GABA in areas 3b/1. It is hypothesized that GABA is hyperpolarizing/inhibitory and suppresses stimulus-evoked RA neuron MFR and entrainment whenever RA neuron activity is low (as when the RFcenter stimulus is weak/near-threshold) but is depolarizing/excitatory and augments MFR and entrainment when RA neuron activity is high (when the stimulus is strong/suprathreshold)

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Prediction of Incident Heart Failure in General Practice: The Atherosclerosis Risk in Communities (ARIC) Study

A simple and effective heart failure (HF) risk score would facilitate the primary prevention and early diagnosis of HF in general practice. We examined the external validity of existing HF risk scores, optimized a 10-year HF risk function, and examined the incremental value of several biomarkers, including N-terminal pro-brain natriuretic peptide

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10^−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group

Bronchodilator Responsiveness in Tobacco-Exposed People With or Without COPD

Background: Bronchodilator responsiveness (BDR) in obstructive lung disease varies over time and may be associated with distinct clinical features. Research Question: Is consistent BDR over time (always present) differentially associated with obstructive lung disease features relative to inconsistent (sometimes present) or never (never present) BDR in tobacco-exposed people with or without COPD? Study Design and Methods: We retrospectively analyzed data from 2,269 tobacco-exposed participants in the Subpopulations and Intermediate Outcome Measures in COPD Study with or without COPD. We used various BDR definitions: change of ≥ 200 mL and ≥ 12% in FEV1 (FEV1-BDR), change in FVC (FVC-BDR), and change in in FEV1, FVC or both (ATS-BDR). Using generalized linear models adjusted for demographics, smoking history, FEV1 % predicted after bronchodilator administration, and number of visits that the participant completed, we assessed the association of BDR group: (1) consistent BDR, (2) inconsistent BDR, and (3) never BDR with asthma, CT scan features, blood eosinophil levels, and FEV1 decline in participants without COPD (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stage 0) and the entire cohort (participants with or without COPD). Results: Both consistent and inconsistent ATS-BDR were associated with asthma history and greater small airways disease (%parametric response mapping functional small airways disease) relative to never ATS-BDR in participants with GOLD stage 0 disease and the entire cohort. We observed similar findings using FEV1-BDR and FVC-BDR definitions. Eosinophils did not vary consistently among BDR groups. Consistent BDR was associated with FEV1 decline over time relative to never BDR in the entire cohort. In participants with GOLD stage 0 disease, both the inconsistent ATS-BDR group (OR, 3.20; 95% CI, 2.21-4.66; P &lt; .001) and consistent ATS-BDR group (OR, 9.48; 95% CI, 3.77-29.12; P &lt; .001) were associated with progression to COPD relative to the never ATS-BDR group. Interpretation: Demonstration of BDR, even once, describes an obstructive lung disease phenotype with a history of asthma and greater small airways disease. Consistent demonstration of BDR indicated a high risk of lung function decline over time in the entire cohort and was associated with higher risk of progression to COPD in patients with GOLD stage 0 disease

Post-genome-wide association study challenges for lipid traits: Describing age as a modifier of gene-lipid associations in the population architecture using genomics and epidemiology (PAGE) study

Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age-dependent has largely been overlooked.We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: &lt;50 or ≥50 years of age; females: pre-or postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet &lt; 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 1.74E-03, I2 = 89.8), with a significant association in older males (P = 1.39E-06) but not younger males (P = 0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes

Genetic Determinants of Lipid Traits in Diverse Populations from the Population Architecture using Genomics and Epidemiology (PAGE) Study

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits