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Tissue-specific genetic features inform prediction of drug side effects in clinical trials.
Duffy, Áine; Verbanck, Marie; Dobbyn, Amanda; Won, Hong-Hee; Rein, Joshua L; Forrest, Iain S; Nadkarni, Girish; Rocheleau, Ghislain; Do, Ron.
Affiliation
  • Duffy Á; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Verbanck M; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Dobbyn A; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Won HH; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Rein JL; Université de Paris, UR 7537 BioSTM, Paris, France.
  • Forrest IS; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Nadkarni G; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Rocheleau G; Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Do R; Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, South Korea.
Sci Adv ; 6(37)2020 09.
Article in En | MEDLINE | ID: mdl-32917698
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Drug-Related Side Effects and Adverse Reactions / Genome-Wide Association Study Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Sci Adv Year: 2020 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Drug-Related Side Effects and Adverse Reactions / Genome-Wide Association Study Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Sci Adv Year: 2020 Document type: Article Affiliation country: Estados Unidos