UKBB self-reported medications

UKBB self-reported medications (UKBB-SRMed) maps UK Biobank self-reported medication descriptions to standardized drug classification systems to structure medication data for clinical phenotyping and genetic association studies.

Key Features:

• Automated classification: Maps UK Biobank medication descriptions to the World Health Organization Anatomical Therapeutic Chemical (ATC) Classification System and the British National Formulary (BNF) using automated text-matching.
• High matching efficiency: Matches 80.5% of 3,646 self-reported medication descriptions to ATC codes and 91.6% to BNF codes.
• Manual intervention capability: Permits manual addition of matches and clinician curation to resolve failed or ambiguous automated mappings.
• Application in phenotyping: Groups medications into broader, structured categories to create medication-based phenotype proxies for clinical phenotyping.
• Increased research utility: Demonstrated that grouping medications increases genetic association significance compared with using individual medications as phenotypes in a case study.
• General applicability: Applicable to other descriptive text–to–classification matching problems beyond UK Biobank medication data.

Scientific Applications:

• Genetic epidemiology: Enables creation of medication-based phenotypes for genetic association studies.
• Pharmacogenomics: Facilitates investigation of genetic determinants of drug response and adverse effects.
• Clinical phenotyping and association studies: Produces structured phenotype proxies that can improve association signal and analytical robustness in studies using medication data.

Methodology:

Matches UKBB medication descriptions to terms from the ATC and BNF classification systems using automated text-matching algorithms, supplemented by manual curation.