| Title: | Biobank Scale Pharmacogenomics Informs the Genetic Underpinnings of Simvastatin Use |
| Journal: | Clinical Pharmacology & Therapeutics |
| Published: | 30 Apr 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/33837531/ |
| DOI: | https://doi.org/10.1002/cpt.2260 |
| URL: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8376807 |
| Citations: | 5 (1 in last 2 years) as of 8 Aug 2024 |
Publication 4350
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Abstract
Studying drug-metabolizing enzymes, encoded by pharmacogenes, may inform biological mechanisms underlying the diseases for which a medication is prescribed. Until recently, pharmacogenes could not be studied at biobank scale. In 7,649 unrelated African-ancestry (AFR) and 326,214 unrelated European-ancestry (EUR) participants from the UK Biobank, we associated pharmacogene haplotypes from 50 genes with 265 (EUR) and 17 (AFR) medication use phenotypes using generalized linear models. In EUR, N-acetyltransferase 2 (NAT2) metabolizer phenotype and activity score were associated with simvastatin use. The dose of NAT2*1 was associated with simvastatin use when compared with NAT2*5 (the most common haplotype). This association was robust to effects of low-density lipoprotein cholesterol (LDL-C) concentration (NAT2*1 odds ratio (OR) = 1.07, 95% CI: 1.05-1.09, P = 1.14 × 10-8 ) and polygenic risk for LDL-C concentration (NAT2*1 OR = 1.09, 95% CI: 1.04-1.14, P = 2.26 × 10-4 ). Interactive effects between NAT2*1 and simvastatin use on LDL-C concentration (OR = 0.957, 95% CI: 0.916-0.998, P = 0.045) were replicated in the electronic Medical Records and Genomics Pharmacogenetic Sequencing Pilot (eMERGE-PGx) cohort (OR = 0.987, 95% CI: 0.976-0.998, P = 0.029). We used biobank-scale data to uncover and replicate an association between NAT2 locus variation and better response to statin therapy. Testing NAT2 alleles may be useful for making clinical decisions regarding the potential benefit (e.g., absolute risk reduction) in LDL-C concentration prior to statin treatment.</p>
6 Authors
- Frank R. Wendt
- Dora Koller
- Gita A. Pathak
- Daniel Jacoby
- Edward J. Miller
- Renato Polimanti
Enabling scientific discoveries that improve human health