Original Research ARTICLE
A New Panel-Based Next-Generation Sequencing Method for ADME Genes Reveals Novel Associations of Common and Rare Variants with Expression in a Human Liver Cohort
- 1Pharmacogenetics, Dr. Margarete Fischer-Bosch Institut für Klinische Pharmakologie (IKP), Germany
- 2University of Tubingen, Germany
- 3CeGaT GmbH, Germany
- 4Abteilung für Klinische Pharmakologie, Universitätsklinikum Tübingen, Germany
- 5Institut für Pharmazie und Biochemie, Universität Tübingen, Germany
We developed a panel-based NGS pipeline for comprehensive analysis of 340 genes involved in absorption, distribution, metabolism and excretion (ADME) of drugs, other xenobiotics, and endogenous substances. The 340 genes comprised phase I and II enzymes, drug transporters and regulator/modifier genes within their entire coding regions, adjacent intron regions and 5’ and 3'UTR regions, resulting in a total panel size of 1,382 kbp. We applied the ADME NGS panel to sequence genomic DNA from 150 Caucasian liver donors with comprehensive phenotype data. This revealed an average read-depth of 343 (range 27 - 811), while 99% of the 340 genes were covered on average at least 100–fold. Direct comparison of variant calling with 363 available genotypes determined independently by other methods revealed an overall accuracy of > 99%. Of 15,727 SNV and small INDEL variants, 12,022 had a MAF below 2%, including 8,921 singletons. In total we found 7,167 novel variants. Functional predictions were computed for coding variants (n=4,017) by three algorithms (Polyphen 2, Provean, and SIFT), resulting in 1,466 variants (36.5%) concordantly predicted to be damaging, while 1,019 variants (25.4%) were predicted to be tolerable. In agreement with other studies we found that less common variants were enriched for deleterious variants. Cis-eQTL analysis of common variants (MAF ≥ 2%) revealed significant associations for 90 variants in 31 genes after Bonferroni correction, most of which were located in non-coding regions. For less common variants (MAF < 2%), we applied the SKAT-O test and identified significant associations to gene expression for ADH1C and GSTO1. Moreover, our data allow comparison of functional predictions with actual phenotypic data to prioritize variants for further analysis.
Keywords: ADME, next generation sequencing, pharmacogenomics, eQTL analysis, rare variants
Received: 26 Oct 2018;
Accepted: 09 Jan 2019.
Edited by:Rick Kittles, Irell & Manella Graduate School of Biological Sciences, City of Hope, United States
Reviewed by:Jeannine S. McCune, Beckman Research Institute, City of Hope, United States
Wenndy Hernandez, University of Chicago, United States
Jason H. Karnes, University of Arizona, United States
Copyright: © 2019 Klein, Tremmel, Winter, Fehr, Battke, Scheurenbrand, SchaEffeler, Biskup, Schwab and Zanger. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Ulrich M. Zanger, Dr. Margarete Fischer-Bosch Institut für Klinische Pharmakologie (IKP), Pharmacogenetics, Stuttgart, 70376, Germany, Uli.email@example.com