Combining pharmacogenetics and patient characteristic polygenic scores to improve outcome prediction for Calcium Channel Blocker treatment
Deniz TürkmeniD, Jack BowdeniD, Jane A. H. MasoliiD, João DelgadoiD, Chia‐Ling KuoiD, Luke C. PillingiD, David R. MelzeriD
Abstract
BackgroundCalcium channel blockers (CCBs) are common antihypertensive medications. Pharmacogenetic variants affect CCB clinical outcomes, although effect sizes are modest in community samples. Variation in patient characteristics may also predict CCB outcomes, and variation attributable to relevant polygenic scores is less prone to confounding. We aimed to test associations between genetically predicted patient characteristics plus pharmacogenetic variants with CCB outcomes in a large community cohort. MethodsWe extended our analysis of 32,000 UK Biobank dihydropiridine CCBs treated participants (mean duration 5.9 years) testing 23 variants, where NUMA1 rs10898815 and RYR3 rs877087 showed the most robust associations (for discontinuation and heart failure, respectively). We calculated polygenic scores for systolic and diastolic blood pressures (SBP and DBP), body fat mass, waist hip ratio, lean mass, serum calcium, eGFR, lipoprotein A, urinary sodium, and liver fibrosis. Outcomes were CCB discontinuation, heart failure, coronary heart disease and chronic kidney disease. ResultsFor heart failure, the highest risk 20% of polygenic scores for fat mass, lean mass and lipoprotein A were associated with increased risks (Hazard-Ratio (HR)Fat-mass 1.46, 95% CI 1.25-1.70, p=1*10-6; HRLean-mass 1.20, 95%CI 1.04-1.38, p=0.01; HRLipoproteinA 1.29, 95% CI 1.12 to 1.48, p= 4*10-4), versus the lowest risk 20% of each score respectively. Across the cohort, RYR3 T-allele modestly increased heart failure risks (HR 1.13: 1.02-1.25) versus non-carriers, but in subsets with high fat mass, lean mass, and lipoprotein A scores, estimates were substantially larger, e.g., in females aged 65-70 the heart failure Relative Risk was 4.4 (95% CI 1.54-12.4) versus no T-alleles and low scores. For CCB discontinuation, high polygenic scores for fat mass and lean mass increased risks versus the lowest 20%, whereas high SBP and DBP scores decreased discontinuation risks. Hazard ratios for discontinuation with the pharmacogenetic NUMA1 rs10898815 A-allele (overall HR 1.07: 1.02-1.12) were higher (HR 1.17: 1.05-1.29) in those with high polygenic scores for fat mass and lean mass. ConclusionPolygenic scores affecting adiposity and lipoprotein A levels add to known pharmacogenetic variants in predicting key clinical outcomes in CCB treatment. Combining pharmacogenetic variants and relevant individual characteristic polygenic scores may help for personalizing prescribing. What is needed, what do we add?We previously showed that pharmacogenetic variants in RYR3 and NUMA1 were associated with key clinical outcomes in community CCB patients, although effect sizes were modest. Various patient characteristics reportedly affect CCB outcomes. We therefore tested effects of relevant patient characteristics using polygenic scores. They minimize the effect of unmeasured confounders as genotypes are invariant since conception and reflect lifetime exposure to the risk factor. We showed that combining associated scores with the pharmacogenetic variants improved outcome prediction.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 0
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Genetic variants related to antihypertensive targets inform drug efficacy and side effects
Dipender Gill, Marios K. Georgakis, … Ioanna Tzoulaki·CirculationPeer-reviewed·Jun 25, 2019
- Genetic support for an adverse effect of calcium channel blockers on the human thoracic aorta
Julia Horjus, Sean Joseph Jurgens, … Nimrat Grewal·medRxiv·Oct 5, 2026
- Educational attainment as a modifier of the effect of polygenic scores for cardiovascular risk factors: cross-sectional and prospective analysis of UK Biobank
Alice R Carter, Sean Harrison, … Neil M Davies·International Journal of EpidemiologyPeer-reviewed·Jan 6, 2022
- Leveraging large-scale biobank EHRs to enhance pharmacogenetics of cardiometabolic disease medications
Marie C. Sadler, Alexander M Apostolov, … Zoltán Kutalik·Nature CommunicationsPeer-reviewed·Mar 25, 2025
- A polygenic risk score to predict sudden cardiac arrest in patients with coronary artery disease
Eleonora Porcu, Christian Thorball, … Jacques Fellay·medRxiv·Jul 26, 2022
- Use of polygenic risk scores and other molecular markers to enhance cardiovascular risk prediction: Prospective cohort study and modelling analysis
Luanluan Sun, Lisa A M Pennells, … Emanuele Di Angelantonio·bioRxiv·Aug 22, 2019