Dataset Information

Systems pharmacogenomics - gene, disease, drug and placebo interactions: a case study in COMT.

ABSTRACT: Disease, drugs and the placebos used as comparators are inextricably linked in the methodology of the double-blind, randomized controlled trial. Nonetheless, pharmacogenomics, the study of how individuals respond to drugs based on genetic substrate, focuses primarily on the link between genes and drugs, while the link between genes and disease is often overlooked and the link between genes and placebos is largely ignored. Herein, we use the example of the enzyme catechol-O-methyltransferase to examine the hypothesis that genes can function as pharmacogenomic hubs across system-wide regulatory processes that, if perturbed in andomized controlled trials, can have primary and combinatorial effects on drug and placebo responses.

SUBMITTER: Hall KT

PROVIDER: S-EPMC6563236 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Systems pharmacogenomics - gene, disease, drug and placebo interactions: a case study in COMT.

Hall Kathryn T KT Loscalzo Joseph J Kaptchuk Ted J TJ

Pharmacogenomics 20190501 7

Disease, drugs and the placebos used as comparators are inextricably linked in the methodology of the double-blind, randomized controlled trial. Nonetheless, pharmacogenomics, the study of how individuals respond to drugs based on genetic substrate, focuses primarily on the link between genes and drugs, while the link between genes and disease is often overlooked and the link between genes and placebos is largely ignored. Herein, we use the example of the enzyme catechol-O-methyltransferase to e ...[more]

PMID: 31124409

Similar Datasets

Project description: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.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).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.

Dataset Information

Systems pharmacogenomics - gene, disease, drug and placebo interactions: a case study in COMT.

Publications

Systems pharmacogenomics - gene, disease, drug and placebo interactions: a case study in COMT.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets