Cargando…

Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population

Differences in drug responses in individuals are partly due to genetic variations in pharmacogenes, which differ among populations. Here, genome sequencing of 171 unrelated Thai individuals from all regions of Thailand was used to call star alleles of 51 pharmacogenes by Stargazer, determine allele...

Descripción completa

Detalles Bibliográficos
Autores principales: Wankaew, Natnicha, Chariyavilaskul, Pajaree, Chamnanphon, Monpat, Assawapitaksakul, Adjima, Chetruengchai, Wanna, Pongpanich, Monnat, Shotelersuk, Vorasuk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853512/
https://www.ncbi.nlm.nih.gov/pubmed/35176049
http://dx.doi.org/10.1371/journal.pone.0263621
_version_ 1784653245576118272
author Wankaew, Natnicha
Chariyavilaskul, Pajaree
Chamnanphon, Monpat
Assawapitaksakul, Adjima
Chetruengchai, Wanna
Pongpanich, Monnat
Shotelersuk, Vorasuk
author_facet Wankaew, Natnicha
Chariyavilaskul, Pajaree
Chamnanphon, Monpat
Assawapitaksakul, Adjima
Chetruengchai, Wanna
Pongpanich, Monnat
Shotelersuk, Vorasuk
author_sort Wankaew, Natnicha
collection PubMed
description Differences in drug responses in individuals are partly due to genetic variations in pharmacogenes, which differ among populations. Here, genome sequencing of 171 unrelated Thai individuals from all regions of Thailand was used to call star alleles of 51 pharmacogenes by Stargazer, determine allele and genotype frequencies, predict phenotype and compare high-impact variant frequencies between Thai and other populations. Three control genes, EGFR, VDR, and RYR1, were used, giving consistent results. Every individual had at least three genes with variant or altered phenotype. Forty of the 51 pharmacogenes had at least one individual with variant or altered phenotype. Moreover, thirteen genes had at least 25% of individuals with variant or altered phenotype including SLCO1B3 (97.08%), CYP3A5 (88.3%), CYP2C19 (60.82%), CYP2A6 (60.2%), SULT1A1 (56.14%), G6PD (54.39%), CYP4B1 (50.00%), CYP2D6 (48.65%), CYP2F1 (46.41%), NAT2 (40.35%), SLCO2B1 (28.95%), UGT1A1 (28.07%), and SLCO1B1 (26.79%). Allele frequencies of high impact variants from our samples were most similar to East Asian. Remarkably, we identified twenty predicted high impact variants which have not previously been reported. Our results provide information that contributes to the implementation of pharmacogenetic testing in Thailand and other Southeast Asian countries, bringing a step closer to personalized medicine.
format Online
Article
Text
id pubmed-8853512
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-88535122022-02-18 Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population Wankaew, Natnicha Chariyavilaskul, Pajaree Chamnanphon, Monpat Assawapitaksakul, Adjima Chetruengchai, Wanna Pongpanich, Monnat Shotelersuk, Vorasuk PLoS One Research Article Differences in drug responses in individuals are partly due to genetic variations in pharmacogenes, which differ among populations. Here, genome sequencing of 171 unrelated Thai individuals from all regions of Thailand was used to call star alleles of 51 pharmacogenes by Stargazer, determine allele and genotype frequencies, predict phenotype and compare high-impact variant frequencies between Thai and other populations. Three control genes, EGFR, VDR, and RYR1, were used, giving consistent results. Every individual had at least three genes with variant or altered phenotype. Forty of the 51 pharmacogenes had at least one individual with variant or altered phenotype. Moreover, thirteen genes had at least 25% of individuals with variant or altered phenotype including SLCO1B3 (97.08%), CYP3A5 (88.3%), CYP2C19 (60.82%), CYP2A6 (60.2%), SULT1A1 (56.14%), G6PD (54.39%), CYP4B1 (50.00%), CYP2D6 (48.65%), CYP2F1 (46.41%), NAT2 (40.35%), SLCO2B1 (28.95%), UGT1A1 (28.07%), and SLCO1B1 (26.79%). Allele frequencies of high impact variants from our samples were most similar to East Asian. Remarkably, we identified twenty predicted high impact variants which have not previously been reported. Our results provide information that contributes to the implementation of pharmacogenetic testing in Thailand and other Southeast Asian countries, bringing a step closer to personalized medicine. Public Library of Science 2022-02-17 /pmc/articles/PMC8853512/ /pubmed/35176049 http://dx.doi.org/10.1371/journal.pone.0263621 Text en © 2022 Wankaew et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wankaew, Natnicha
Chariyavilaskul, Pajaree
Chamnanphon, Monpat
Assawapitaksakul, Adjima
Chetruengchai, Wanna
Pongpanich, Monnat
Shotelersuk, Vorasuk
Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population
title Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population
title_full Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population
title_fullStr Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population
title_full_unstemmed Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population
title_short Genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a Thai population
title_sort genotypic and phenotypic landscapes of 51 pharmacogenes derived from whole-genome sequencing in a thai population
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853512/
https://www.ncbi.nlm.nih.gov/pubmed/35176049
http://dx.doi.org/10.1371/journal.pone.0263621
work_keys_str_mv AT wankaewnatnicha genotypicandphenotypiclandscapesof51pharmacogenesderivedfromwholegenomesequencinginathaipopulation
AT chariyavilaskulpajaree genotypicandphenotypiclandscapesof51pharmacogenesderivedfromwholegenomesequencinginathaipopulation
AT chamnanphonmonpat genotypicandphenotypiclandscapesof51pharmacogenesderivedfromwholegenomesequencinginathaipopulation
AT assawapitaksakuladjima genotypicandphenotypiclandscapesof51pharmacogenesderivedfromwholegenomesequencinginathaipopulation
AT chetruengchaiwanna genotypicandphenotypiclandscapesof51pharmacogenesderivedfromwholegenomesequencinginathaipopulation
AT pongpanichmonnat genotypicandphenotypiclandscapesof51pharmacogenesderivedfromwholegenomesequencinginathaipopulation
AT shotelersukvorasuk genotypicandphenotypiclandscapesof51pharmacogenesderivedfromwholegenomesequencinginathaipopulation