Publication:

Genetic variation in human drug-related genes

Loading...
Thumbnail Image

Open/View Files

Date

2017

Journal Title

Journal ISSN

Volume Title

Publisher

BioMed Central
The Harvard community has made this article openly available. Please share how this access benefits you.

Research Projects

Organizational Units

Journal Issue

Citation

Schärfe, Charlotta Pauline Irmgard, Roman Tremmel, Matthias Schwab, Oliver Kohlbacher, and Debora Susan Marks. 2017. “Genetic variation in human drug-related genes.” Genome Medicine 9 (1): 117. doi:10.1186/s13073-017-0502-5. http://dx.doi.org/10.1186/s13073-017-0502-5.

Abstract

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. Electronic supplementary material The online version of this article (doi:10.1186/s13073-017-0502-5) contains supplementary material, which is available to authorized users.

Description

Research Data

Keywords

Bioinformatics analysis, Exome sequence analysis, Pharmacogenomics

Terms of Use

This article is made available under the terms and conditions applicable to Other Posted Material (LAA), as set forth at Terms of Service

Endorsement

Review

Supplemented By

Related Stories