Genotype-predicted drug response phenotypes and their co-occurrence with dispensed medicines among 738,531 participants in the UK Our Future Health study
Rentsch, C. T.; Bhaskaran, K.; Pavicic, M.; Warren, H. R.; Matthewman, J.; Barry, E.; Rafi, I.; Hayward, J.; Gerada, C.; Shah, A.; Munroe, P. B.; Silver, M. J.; Pirmohamed, M.
Show abstract
Pharmacogenomics (PGx) can improve safety and effectiveness of commonly dispensed medicines, but its value at the population level depends on how often clinically actionable PGx phenotypes co-occur with the medicines they affect. We assessed this co-occurrence in a cross-sectional analysis of Our Future Health (OFH), a new UK national biobank, by applying Pharmacogenomics Clinical Annotation Tool (PharmCAT v3.1.1) to imputed genotypes from 738,531 participants across 17 pharmacogenes with established PGx prescribing guidelines. Every participant had at least one actionable PGx phenotype, with a mean of 6.1 (SD 1.3). The number of actionable PGx phenotypes was similar across genetically inferred ancestry groups, although the pharmacogenes contributing to that count differed between groups. Using linked primary care dispensing records, 36.8% (95% CI 36.7-36.9) had been dispensed at least one medicine between April 2018 and June 2025 matched to a gene for which they carried an actionable PGx phenotype. Co-occurrence rose with age, ranging from 43.7% to 58.9% across ancestry groups among those aged [≥]70 years. Participants carried an actionable PGx phenotype for a mean of 13.8 (SD 6.5) of the 33 medicines dispensed in English primary care with PGx prescribing guidance, of which a mean of 0.6 (SD 1.0) had been dispensed. Co-occurrence was concentrated in a few widely dispensed classes, principally proton-pump inhibitors and antidepressants acting through CYP2C19 and statins through SLCO1B1. These findings highlight opportunities to optimise treatment for a large proportion of patients receiving routine medications and identify where pre-emptive PGx testing could have the greatest clinical benefit.
Matching journals
The top 13 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Understanding genetic risk factors for common side effects of antidepressant medications 89%
- Clinical trial emulation can identify new opportunities to enhance the regulation of drug safety in pregnancy 89%
- Estimating Heritability of Glycaemic Response to Metformin using Nationwide Electronic Health Records and Population-Sized Pedigree 88%
Similar papers in this journal
Similar papers in this journal
- Cohort Profile: Investigating Antidepressant Response within Generation Scotland 91%
- What’s UPDOG? A novel tool for trans-ancestral polygenic score prediction 88%
- The consequences of adjustment, correction and selection in genome-wide association studies used for two-sample Mendelian randomization 88%
Similar papers in this journal
- Changes in dispensing of medicines proposed for re-purposing in the first year of the COVID-19 pandemic in Australia 93%
- Effect of common maintenance drugs on the risk and severity of COVID-19 in elderly patients 90%
- Multimorbidity, Polypharmacy, and COVID-19 infection within the UK Biobank cohort. 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.