Journal Article Ahead of print 2 citations
PubMed: 42545033 DOI: 10.1093/eurheartj/ehag575
Side effects in hypertension treatment: a pharmacogenomic analysis.
Eur Heart J
Authors: Felix Vaura, Kristi Krebs, Tuomo Kiiskinen, Joel Rämö, Max Tamlander, Simone Rubinacci, Lili Milani, Samuli Ripatti
Affiliations
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, P.O. Box 20, Helsinki FI-00014, Finland.
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
- Cardiovascular Disease Initiative, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Division of Cardiology, Heart and Vascular Institute, Mass General Brigham, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Public Health, University of Helsinki, Helsinki, Finland.
- ATGU, Department of Medicine, Mass General Brigham, Boston, MA, USA.
Abstract
BACKGROUND AND AIMS
Up to half of patients switch or discontinue antihypertensive medications within the first year, but underlying mechanisms remain elusive. This study aimed to identify genetic predictors of antihypertensive medication use trajectories within the first year.
METHODS
Using longitudinal medication data from >400 000 genotyped antihypertensive medication users across three cohorts (FinnGen, the UK Biobank, and the Estonian Biobank), short-term antihypertensive medication use trajectories were classified as Continue, Switch, or Discontinue. Genome-wide association studies were performed across five medication classes.
RESULTS
In total, 14 genome-wide significant loci were identified for switching from angiotensin-converting enzyme inhibitors (ACEI) and dihydropyridine calcium channel blockers (dCCB) to other antihypertensive medications. For ACEI switching, evidence converged on the neurotensin-NTSR1 pathway, including a 320-fold Finnish-enriched protective missense variant in the neurotensin receptor gene NTSR1 (rs148569146 [G301R], odds ratio [OR] 0.49, P = 3.3 × 10-43) and a variant near RASSF9 (rs181941187, OR = 0.74, P = 1.2 × 10-49) tagging the neurotensin gene NTS. In drug-gene interaction analyses, NTSR1 G301R was associated with reduced ACEI-induced cough risk (OR 0.39, P = 8.1 × 10-4). The dCCB switching locus at CYP3A43 was in near-complete linkage (r2 = 0.99) with the functional CYP3A4*22 allele (rs35599367, OR 1.23, P = 6.1 × 10-10). A polygenic risk score (PRS) for ACEI switching predicted two-fold ACEI cough risk in the top 10% PRS compared with the middle 20% in an independent sample of the Estonian Biobank.
CONCLUSIONS
These findings extend the bradykinin hypothesis of ACEI-induced cough by implicating neurotensin-NTSR1 signalling, pinpoint CYP3A4*22 as a novel functional predictor of dCCB switching with potential for genotype-guided prescribing, and validate medication use trajectories as a framework for pharmacogenetic discovery.
MeSH
Genes, Hypertension, Cardiology, Antihypertensive Agents, Genotype, Therapeutics, Cough, Pharmacogenomic Testing, Neurotensin