{"title":"泰国药物基因组学数据库-2（TPGxD-2）是 TPGxD-1 的续集，分析泰国人口中 26 个非 VIPGx 基因的遗传变异。","authors":"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","doi":"10.1111/cts.70019","DOIUrl":null,"url":null,"abstract":"<p>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 <i>TBXAS1</i> 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 (<i>n</i> = 12,201), with <i>UGT2B7</i> (19.64%), <i>CYP1B1</i> (8.9%), <i>SLCO2B1</i> (8.9%), and <i>POR</i> (8.9%) being the most common. We reported a high frequency of intermediate metabolizers (IMs) in <i>CYP2F1</i> (34.6%) and <i>CYP4A11</i> (8.6%), and a high frequency of decreased functional alleles in <i>POR</i> (53.9%) and <i>SLCO1B3</i> (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.</p>","PeriodicalId":50610,"journal":{"name":"Cts-Clinical and Translational Science","volume":"17 10","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11502937/pdf/","citationCount":"0","resultStr":"{\"title\":\"Thai pharmacogenomics database −2 (TPGxD-2) sequel to TPGxD-1, analyzing genetic variants in 26 non-VIPGx genes within the Thai population\",\"authors\":\"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\",\"doi\":\"10.1111/cts.70019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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 <i>TBXAS1</i> 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 (<i>n</i> = 12,201), with <i>UGT2B7</i> (19.64%), <i>CYP1B1</i> (8.9%), <i>SLCO2B1</i> (8.9%), and <i>POR</i> (8.9%) being the most common. We reported a high frequency of intermediate metabolizers (IMs) in <i>CYP2F1</i> (34.6%) and <i>CYP4A11</i> (8.6%), and a high frequency of decreased functional alleles in <i>POR</i> (53.9%) and <i>SLCO1B3</i> (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.</p>\",\"PeriodicalId\":50610,\"journal\":{\"name\":\"Cts-Clinical and Translational Science\",\"volume\":\"17 10\",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11502937/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cts-Clinical and Translational Science\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/cts.70019\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICINE, RESEARCH & EXPERIMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cts-Clinical and Translational Science","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/cts.70019","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
Thai pharmacogenomics database −2 (TPGxD-2) sequel to TPGxD-1, analyzing genetic variants in 26 non-VIPGx genes within the Thai population
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.
期刊介绍：
Clinical and Translational Science (CTS), an official journal of the American Society for Clinical Pharmacology and Therapeutics, highlights original translational medicine research that helps bridge laboratory discoveries with the diagnosis and treatment of human disease. Translational medicine is a multi-faceted discipline with a focus on translational therapeutics. In a broad sense, translational medicine bridges across the discovery, development, regulation, and utilization spectrum. Research may appear as Full Articles, Brief Reports, Commentaries, Phase Forwards (clinical trials), Reviews, or Tutorials. CTS also includes invited didactic content that covers the connections between clinical pharmacology and translational medicine. Best-in-class methodologies and best practices are also welcomed as Tutorials. These additional features provide context for research articles and facilitate understanding for a wide array of individuals interested in clinical and translational science. CTS welcomes high quality, scientifically sound, original manuscripts focused on clinical pharmacology and translational science, including animal, in vitro, in silico, and clinical studies supporting the breadth of drug discovery, development, regulation and clinical use of both traditional drugs and innovative modalities.
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