Tissue-specific genetic features inform prediction of drug side effects in clinical trials

Áine Duffy, Marie Verbanck, Amanda Dobbyn, Hong Hee Won, Joshua L. Rein, Iain S. Forrest, Girish Nadkarni, Ghislain Rocheleau, Ron Do

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Adverse side effects often account for the failure of drug clinical trials. We evaluated whether a phenome-wide association study (PheWAS) of 1167 phenotypes in >360,000 U.K. Biobank individuals, in combination with gene expression and expression quantitative trait loci (eQTL) in 48 tissues, can inform prediction of drug side effects in clinical trials. We determined that drug target genes with five genetic features—tissue specificity of gene expression, Mendelian associations, phenotype- and tissue-level effects of genome-wide association (GWA) loci driven by eQTL, and genetic constraint—confer a 2.6-fold greater risk of side effects, compared to genes without such features. The presence of eQTL in multiple tissues resulted in more unique phenotypes driven by GWA loci, suggesting that drugs delivered to multiple tissues can induce several side effects. We demonstrate the utility of PheWAS and eQTL data from multiple tissues for informing drug side effect prediction and highlight the need for tissue-specific drug delivery.

Original languageEnglish
Article numbereabb6242
JournalScience advances
Volume6
Issue number37
DOIs
StatePublished - Sep 2020

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