Thai pharmacogenomics database −2 (TPGxD‐2) sequel to TPGxD‐1, analyzing genetic variants in 26 non‐VIPGx genes within the Thai population | doi.page

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Thai pharmacogenomics database −2 (TPGxD‐2) sequel to TPGxD‐1, analyzing genetic variants in 26 non‐VIPGx genes within the Thai population

Clinical and Translational Science2024Vol. 17(10), pp. e70019–e70019

Shobana John, Sommon Klumsathian, Paravee Own‐eium, Angkana Charoenyingwattana, Jakris Eu‐ahsunthornwattana, Thanyachai Sura, Donniphat Dejsuphong, Piyamitr Sritara, Prin Vathesatogkit, Nartthawee Thongchompoo, Wiphaporn Thabthimthong, Nuttinee Teerakulkittipong, Wasun Chantratita, Chonlaphat Sukasem

Abstract

Next-generation sequencing (NGS) has transformed pharmacogenomics (PGx), enabling thorough profiling of pharmacogenes using computational methods and advancing personalized medicine. The Thai Pharmacogenomic Database-2 (TPGxD-2) analyzed 948 whole genome sequences, primarily from the Electricity Generating Authority of Thailand (EGAT) cohort. This study is an extension of the previous Thai Pharmacogenomic Database (TPGxD-1) and specifically focused on 26 non-very important pharmacogenes (VIPGx) genes. Variant calling was conducted using Sentieon (version 201808.08) following GATK's best workflow practices. We then annotated variant call format (VCF) files using Golden Helix VarSeq 2.5.0. Star allele analysis was performed with Stargazer v2.0.2, which called star alleles for 22 of 26 non-VIPGx genes. The variant analysis revealed a total of 14,529 variants in 26 non-VIPGx genes, with TBXAS1 had the highest number of variants (27%). Among the 14,529 variants, 2328 were novel (without rsID), with 87 identified as clinically relevant. We also found 56 known PGx variants among the known variants (n = 12,201), with UGT2B7 (19.64%), CYP1B1 (8.9%), SLCO2B1 (8.9%), and POR (8.9%) being the most common. We reported a high frequency of intermediate metabolizers (IMs) in CYP2F1 (34.6%) and CYP4A11 (8.6%), and a high frequency of decreased functional alleles in POR (53.9%) and SLCO1B3 (34.9%) genes. This study enhances our understanding of pharmacogenomic profiling of 26 non-VIPGx genes of notable clinical importance in the Thai population. However, further validation with additional computational and reference genotyping methods is necessary, and novel alleles identified in this study should undergo further orthogonal validation.

Abstract

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