Department of Analysis and Bioanalysis of Medicines, Faculty of Pharmacy with the Division of Laboratory Medicine, Medical University of Bialystok, 15-089, Bialystok, Poland.
Clinical Research Centre, University Hospital of Bialystok, 15-276, Bialystok, Poland.
Pharmacogenomics J. 2022 Dec;22(5-6):276-283. doi: 10.1038/s41397-022-00286-4. Epub 2022 Aug 13.
This pilot study is aimed at implementing an approach for comprehensive clinical pharmacogenomics (PGx) profiling. Fifty patients with cardiovascular diseases and 50 healthy individuals underwent whole-exome sequencing. Data on 1800 PGx genes were extracted and analyzed through deep filtration separately. Theoretical drug induced phenoconversion was assessed for the patients, using sequence2script. In total, 4539 rare variants (including 115 damaging non-synonymous) were identified. Four publicly available PGx bioinformatics algorithms to assign PGx haplotypes were applied to nine selected very important pharmacogenes (VIP) and revealed a 45-70% concordance rate. To ensure availability of the results at point-of-care, actionable variants were stored in a web-hosted database and PGx-cards were developed for quick access and handed to the study subjects. While a comprehensive clinical PGx profile could be successfully extracted from WES data, available tools to interpret these data demonstrated inconsistencies that complicate clinical application.
本研究旨在探索一种全面的临床药物基因组学(PGx)分析方法。50 名心血管疾病患者和 50 名健康个体接受了全外显子组测序。通过深度过滤分别提取并分析了 1800 个 PGx 基因的数据。使用 sequence2script 评估了患者的潜在药物诱导表型转化。共鉴定出 4539 个罕见变异(包括 115 个有害错义变异)。应用了四种公开的 PGx 生物信息学算法对九个重要的药物基因(VIP)进行了 PGx 单倍型赋值,显示出 45-70%的一致性率。为了确保在床边获得结果,可操作的变异被存储在一个基于网络的数据库中,并为快速访问开发了 PGx 卡,分发给研究对象。虽然可以成功地从 WES 数据中提取全面的临床 PGx 图谱,但可用的数据分析工具显示出不一致性,这使得临床应用变得复杂。