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Characterizing the genetic architecture of drug response using gene-context interaction methods.
Cell Genom. 4:100722 (2024)
Identifying factors that affect treatment response is a central objective of clinical research, yet the role of common genetic variation remains largely unknown. Here, we develop a framework to study the genetic architecture of response to commonly prescribed drugs in large biobanks. We quantify treatment response heritability for statins, metformin, warfarin, and methotrexate in the UK Biobank. We find that genetic variation modifies the primary effect of statins on LDL cholesterol (9% heritable) as well as their side effects on hemoglobin A1c and blood glucose (10% and 11% heritable, respectively). We identify dozens of genes that modify drug response, which we replicate in a retrospective pharmacogenomic study. Finally, we find that polygenic score (PGS) accuracy varies up to 2-fold depending on treatment status, showing that standard PGSs are likely to underperform in clinical contexts.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Gene-environment Interactions ; Genetic Heterogeneity ; Genetic Testing ; Heritability ; Heteroskedasticity ; Personalized Medicine ; Pharmacogenomics
ISSN (print) / ISBN
2666-979X
e-ISSN
2666-979X
Journal
Cell Genomics
Quellenangaben
Volume: 4,
Issue: 12,
Article Number: 100722
Publisher
Elsevier
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Helmholtz Pioneer Campus (HPC)