Genome-Wide Approach to Measure Variant-Based Heritability of Drug Outcome Phenotypes.

Autor:	Muhammad A; Vanderbilt University School of Medicine, Nashville, Tennessee, USA., Aka IT; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Birdwell KA; Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Gordon AS; Department of Pharmacology, Northwestern University, Chicago, Illinois, USA.; Center for Genetic Medicine, Northwestern University, Chicago, Illinois, USA., Roden DM; Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Wei WQ; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Mosley JD; Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA., Van Driest SL; Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.; Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Jazyk:	angličtina
Zdroj:	Clinical pharmacology and therapeutics [Clin Pharmacol Ther] 2021 Sep; Vol. 110 (3), pp. 714-722. Date of Electronic Publication: 2021 Jul 12.
DOI:	10.1002/cpt.2323
Abstrakt:	Pharmacogenomic studies have successfully identified variants-typically with large effect sizes in drug target and metabolism enzymes-that predict drug outcome phenotypes. However, these variants may account for a limited proportion of phenotype variability attributable to the genome. Using genome-wide common variation, we measured the narrow-sense heritability ( h SNP 2 ) of seven pharmacodynamic and five pharmacokinetic phenotypes across three cardiovascular drugs, two antibiotics, and three immunosuppressants. We used a Bayesian hierarchical mixed model, BayesR, to model the distribution of genome-wide variant effect sizes for each drug phenotype as a mixture of four normal distributions of fixed variance (0, 0.01%, 0.1%, and 1% of the total additive genetic variance). This model allowed us to parse h SNP 2 into bins representing contributions of no-effect, small-effect, moderate-effect, and large-effect variants, respectively. For the 12 phenotypes, a median of 969 (range 235-6,304) unique individuals of European ancestry and a median of 1,201,626 (range 777,427-1,514,275) variants were included in our analyses. The number of variants contributing to h SNP 2 ranged from 2,791 to 5,356 (median 3,347). Estimates for h SNP 2 ranged from 0.05 (angiotensin-converting enzyme inhibitor-induced cough) to 0.59 (gentamicin concentration). Small-effect and moderate-effect variants contributed a majority to h SNP 2 for every phenotype (range 61-95%). We conclude that drug outcome phenotypes are highly polygenic. Thus, larger genome-wide association studies of drug phenotypes are needed both to discover novel variants and to determine how genome-wide approaches may improve clinical prediction of drug outcomes. (© 2021 The Authors. Clinical Pharmacology & Therapeutics © 2021 American Society for Clinical Pharmacology and Therapeutics.)
Databáze:	MEDLINE
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