Genetic variation in human drug-related genes.

Publisher: BioMed Central Country of Publication: England NLM ID: 101475844 Publication Model: Electronic Cited Medium: Internet ISSN: 1756-994X (Electronic) Linking ISSN: 1756994X NLM ISO Abbreviation: Genome Med Subsets: MEDLINE

Original Publication: [London] : BioMed Central

Mutation Rate* ; Pharmacogenomic Variants*; Drug-Related Side Effects and Adverse Reactions/*genetics; Drug-Related Side Effects and Adverse Reactions/epidemiology ; Genome, Human ; Humans

Background: Variability in drug efficacy and adverse effects are observed in clinical practice. While the extent of genetic variability in classic pharmacokinetic genes is rather well understood, the role of genetic variation in drug targets is typically less studied.
Methods: Based on 60,706 human exomes from the ExAC dataset, we performed an in-depth computational analysis of the prevalence of functional variants in 806 drug-related genes, including 628 known drug targets. We further computed the likelihood of 1236 FDA-approved drugs to be affected by functional variants in their targets in the whole ExAC population as well as different geographic sub-populations.
Results: We find that most genetic variants in drug-related genes are very rare (f < 0.1%) and thus will likely not be observed in clinical trials. Furthermore, we show that patient risk varies for many drugs and with respect to geographic ancestry. A focused analysis of oncological drug targets indicates that the probability of a patient carrying germline variants in oncological drug targets is, at 44%, high enough to suggest that not only somatic alterations but also germline variants carried over into the tumor genome could affect the response to antineoplastic agents.
Conclusions: This study indicates that even though many variants are very rare and thus likely not observed in clinical trials, four in five patients are likely to carry a variant with possibly functional effects in a target for commonly prescribed drugs. Such variants could potentially alter drug efficacy.

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668353 International Horizon 2020

Keywords: Bioinformatics analysis; Exome sequence analysis; Pharmacogenomics

figshare 10.6084/m9.figshare.5631751

Date Created: 20171224 Date Completed: 20181108 Latest Revision: 20181113

20250114

PMC5740940

10.1186/s13073-017-0502-5

29273096