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John S, Klumsathian S, Own‐eium P, Eu‐ahsunthornwattana J, Sura T, Dejsuphong D, Sritara P, Vathesatogkit P, Thongchompoo N, Thabthimthong W, Teerakulkittipong N, Chantratita W, Sukasem C. A comprehensive Thai pharmacogenomics database (TPGxD-1): Phenotype prediction and variants identification in 942 whole-genome sequencing data. Clin Transl Sci 2024; 17:e13830. [PMID: 38853370 PMCID: PMC11163017 DOI: 10.1111/cts.13830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 04/21/2024] [Accepted: 04/27/2024] [Indexed: 06/11/2024] Open
Abstract
Computational methods analyze genomic data to identify genetic variants linked to drug responses, thereby guiding personalized medicine. This study analyzed 942 whole-genome sequences from the Electricity Generating Authority of Thailand (EGAT) cohort to establish a population-specific pharmacogenomic database (TPGxD-1) in the Thai population. Sentieon (version 201808.08) implemented the GATK best workflow practice for variant calling. We then annotated variant call format (VCF) files using Golden Helix VarSeq 2.5.0 and employed Stargazer v2.0.2 for star allele analysis. The analysis of 63 very important pharmacogenes (VIPGx) reveals 85,566 variants, including 13,532 novel discoveries. Notably, we identified 464 known PGx variants and 275 clinically relevant novel variants. The phenotypic prediction of 15 VIPGx demonstrated a varied metabolic profile for the Thai population. Genes like CYP2C9 (9%), CYP3A5 (45.2%), CYP2B6 (9.4%), NUDT15 (15%), CYP2D6 (47%) and CYP2C19 (43%) showed a high number of intermediate metabolizers; CYP3A5 (41%), and CYP2C19 (9.9%) showed more poor metabolizers. CYP1A2 (52.7%) and CYP2B6 (7.6%) were found to have a higher number of ultra-metabolizers. The functional prediction of the remaining 10 VIPGx genes reveals a high frequency of decreased functional alleles in SULT1A1 (12%), NAT2 (84%), and G6PD (12%). SLCO1B1 reports 20% poor functional alleles, while PTGIS (42%), SLCO1B1 (4%), and TPMT (5.96%) showed increased functional alleles. This study discovered new variants and alleles in the 63 VIPGx genes among the Thai population, offering insights into advancing clinical pharmacogenomics (PGx). However, further validation is needed using other computational and genotyping methods.
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Affiliation(s)
- Shobana John
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
- Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center (SDMC)Ramathibodi HospitalBangkokThailand
| | - Sommon Klumsathian
- Center for Medical Genomics, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Paravee Own‐eium
- Center for Medical Genomics, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | | | - Thanyachai Sura
- Division of Medical Genetics and Molecular Medicine, Department of Internal Medicine, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Donniphat Dejsuphong
- Program in Translational Medicine, Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathobodi HospitalMahidol UniversityBang PhliSamutprakarnThailand
| | - Piyamitr Sritara
- Department of Medicine, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Prin Vathesatogkit
- Department of Medicine, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Nartthawee Thongchompoo
- Center for Medical Genomics, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Wiphaporn Thabthimthong
- Center for Medical Genomics, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Nuttinee Teerakulkittipong
- Department of Pharmacology and Biopharmaceutical Sciences, Faculty of Pharmaceutical SciencesBurapha UniversityChonburiThailand
| | - Wasun Chantratita
- Center for Medical Genomics, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
| | - Chonlaphat Sukasem
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi HospitalMahidol UniversityBangkokThailand
- Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center (SDMC)Ramathibodi HospitalBangkokThailand
- Department of Pharmacology and Biopharmaceutical Sciences, Faculty of Pharmaceutical SciencesBurapha UniversityChonburiThailand
- Department of Pharmacology and Therapeutics, MRC Centre for Drug Safety Science, Institute of Systems, Molecular and Integrative BiologyUniversity of LiverpoolLiverpoolUK
- Pharmacogenomics and Precision MedicineThe Preventive Genomics & Family Check‐up Services Center, Bumrungrad International HospitalBangkokThailand
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Soko ND, Muyambo S, Dandara MTL, Kampira E, Blom D, Jones ESW, Rayner B, Shamley D, Sinxadi P, Dandara C. Towards Evidence-Based Implementation of Pharmacogenomics in Southern Africa: Comorbidities and Polypharmacy Profiles across Diseases. J Pers Med 2023; 13:1185. [PMID: 37623436 PMCID: PMC10455498 DOI: 10.3390/jpm13081185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/21/2023] [Accepted: 07/23/2023] [Indexed: 08/26/2023] Open
Abstract
Pharmacogenomics may improve patient care by guiding drug selection and dosing; however, this requires prior knowledge of the pharmacogenomics of drugs commonly used in a specific setting. The aim of this study was to identify a preliminary set of pharmacogenetic variants important in Southern Africa. We describe comorbidities in 3997 patients from Malawi, South Africa, and Zimbabwe. These patient cohorts were included in pharmacogenomic studies of anticoagulation, dyslipidemia, hypertension, HIV and breast cancer. The 20 topmost prescribed drugs in this population were identified. Using the literature, a list of pharmacogenes vital in the response to the top 20 drugs was constructed leading to drug-gene pairs potentially informative in translation of pharmacogenomics. The most reported morbidity was hypertension (58.4%), making antihypertensives the most prescribed drugs, particularly amlodipine. Dyslipidemia occurred in 31.5% of the participants, and statins were the most frequently prescribed as cholesterol-lowering drugs. HIV was reported in 20.3% of the study participants, with lamivudine/stavudine/efavirenz being the most prescribed antiretroviral combination. Based on these data, pharmacogenes of immediate interest in Southern African populations include ABCB1, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, SLC22A1, SLCO1B1 and UGT1A1. Variants in these genes are a good starting point for pharmacogenomic translation programs in Southern Africa.
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Affiliation(s)
- Nyarai Desiree Soko
- Platform for Pharmacogenomics Research and Translation (PREMED), University of Cape Town, South African Medical Research Council, Cape Town 7935, South Africa
- Department of Pharmaceutical Technology, School of Allied Health Sciences, Harare Institute of Technology, Harare, Zimbabwe
- Pharmacogenomics and Drug Metabolism Research Group, Division of Human Genetics, Department of Pathology and Institute of Infectious Diseases and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town 7935, South Africa
| | - Sarudzai Muyambo
- Department of Biological Sciences and Ecology, Faculty of Science, University of Zimbabwe, Harare, Zimbabwe
| | - Michelle T. L. Dandara
- Platform for Pharmacogenomics Research and Translation (PREMED), University of Cape Town, South African Medical Research Council, Cape Town 7935, South Africa
| | - Elizabeth Kampira
- Medical Laboratory Sciences, School of Life Sciences and Health Professionals, Kamuzu University of Health Sciences (KUHES), Blantyre, Malawi
| | - Dirk Blom
- Platform for Pharmacogenomics Research and Translation (PREMED), University of Cape Town, South African Medical Research Council, Cape Town 7935, South Africa
- Division of Lipidology and Cape Heart Institute, Department of Medicine, Groote Schuur Hospital and Faculty of Health Sciences, University of Cape Town, Cape Town 7935, South Africa
| | - Erika S. W. Jones
- Platform for Pharmacogenomics Research and Translation (PREMED), University of Cape Town, South African Medical Research Council, Cape Town 7935, South Africa
- Division of Nephrology and Hypertension, Department of Medicine, Groote Schuur Hospital and Faculty of Health Sciences, University of Cape Town, Cape Town 7935, South Africa
| | - Brian Rayner
- Platform for Pharmacogenomics Research and Translation (PREMED), University of Cape Town, South African Medical Research Council, Cape Town 7935, South Africa
| | - Delva Shamley
- Division of Clinical Anatomy and Biological Anthropology, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town 7935, South Africa
| | - Phumla Sinxadi
- Platform for Pharmacogenomics Research and Translation (PREMED), University of Cape Town, South African Medical Research Council, Cape Town 7935, South Africa
- Division of Clinical Pharmacology, Department of Medicine, Groote Schuur Hospital and Faculty of Health Sciences, University of Cape Town, Cape Town 7935, South Africa
| | - Collet Dandara
- Department of Pharmaceutical Technology, School of Allied Health Sciences, Harare Institute of Technology, Harare, Zimbabwe
- Pharmacogenomics and Drug Metabolism Research Group, Division of Human Genetics, Department of Pathology and Institute of Infectious Diseases and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town 7935, South Africa
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