id_1041. A NOVEL CONTINUOUS SCORING APPROACH FOR LARGE-SCALE PHARMACOGENOMIC PROFILING IN THE UK BIOBANK
Jacek Hajto, Małgorzata Borczyk, Marcin Piechota, Sylwia Grubarek, Paula Konowalska, Dżesika Hoinkis, Michał Korostyński
Maj Institute of Pharmacology, Polish Academy of Sciences, Kraków, Poland
INTRODUCTION: Pharmacogenomics (PGx) is moving toward a personalized approach, emphasizing the role of genetic individuality in optimizing pharmacotherapy. Biomedical datasets, such as the UK Biobank, provide opportunities to perform comprehensive genomic analyses and overcome the limitations of traditional pharmacogenetic classifications.
AIM(S): The study aims to conduct a comprehensive, large-scale pharmacogenomic investigation using data from 140,000 UK Biobank participants to explore the genetic determinants of drug response and find novel variants associated with clinical outcomes.
METHOD(S): We extracted clinical phenotypes from approximately 28 million primary care prescriptions and hospital admission records. We also integrated diverse genetic data types: ~1,5 million single-nucleotide polymorphisms, copy number variation, loss-of-function, and missense variants. For key pharmacogenes, we compared standard star-allele nomenclature against our custom tool, PharmGScore, which provides continuous functional scoring. Association analyses were conducted utilizing four statistical tools: PLINK2, LDAK, REGENIE, and CI-GWAS.
RESULTS: Our first results for warfarin dosing replicated established pharmacogenes (CYP2C9, VKORC1, CYP4F2), showing consistency with known determinants. Notably, continuous PharmGScore profiling of the CYP2C9 gene was highly significant (p < 1e-43). Furthermore, utilizing PharmGScore to capture functional variations, we identified a significant association between CYP2C19 genetic burden and fluoxetine prescription (p = 8.13e-5).
CONCLUSIONS: The UK Biobank is an exceptional database for large-scale medical data research and pharmacogenetic studies. Integrating deep longitudinal records with functional scoring allows for the discovery of novel variants and genes potentially linked to adverse drug reactions or specific drug treatments, paving the way for improved personalized therapy in somatic and psychiatric diseases.
FINANCIAL SUPPORT: Funding for this study was provided by National Science Centre, Poland PRELUDIUM BIS-3 nr 2021/43/O/NZ7/01187 and the Medical Research Agency with funds from the National Recovery and Resilience Plan (KPO) from the Recovery and Resilience Facility (RRF) KPOD.07.07-IW.07-0099/24.