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The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico
Pharmacogenetic analysis has generated translational data that could be applied to guide treatments according to individual genetic variations. However, pharmacogenetic counseling in some mestizo (admixed) populations may require tailoring to different patterns of admixture. The identification and c...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188951/ https://www.ncbi.nlm.nih.gov/pubmed/32390825 http://dx.doi.org/10.3389/fphar.2020.00324 |
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author | Martínez-Magaña, José Jaime Genis-Mendoza, Alma Delia Villatoro Velázquez, Jorge Ameth Camarena, Beatriz Martín del Campo Sanchez, Raul Fleiz Bautista, Clara Bustos Gamiño, Marycarmen Reséndiz, Esbehidy Aguilar, Alejandro Medina-Mora, María Elena Nicolini, Humberto |
author_facet | Martínez-Magaña, José Jaime Genis-Mendoza, Alma Delia Villatoro Velázquez, Jorge Ameth Camarena, Beatriz Martín del Campo Sanchez, Raul Fleiz Bautista, Clara Bustos Gamiño, Marycarmen Reséndiz, Esbehidy Aguilar, Alejandro Medina-Mora, María Elena Nicolini, Humberto |
author_sort | Martínez-Magaña, José Jaime |
collection | PubMed |
description | Pharmacogenetic analysis has generated translational data that could be applied to guide treatments according to individual genetic variations. However, pharmacogenetic counseling in some mestizo (admixed) populations may require tailoring to different patterns of admixture. The identification and clustering of individuals with related admixture patterns in such populations could help to refine the practice of pharmacogenetic counseling. This study identifies related groups in a highly admixed population-based sample from Mexico, and analyzes the differential distribution of actionable pharmacogenetic variants. A subsample of 1728 individuals from the Mexican Genomic Database for Addiction Research (MxGDAR/Encodat) was analyzed. Genotyping was performed with the commercial PsychArray BeadChip, genome-wide ancestry was estimated using EIGENSOFT, and model-based clustering was applied to defined admixture groups. Actionable pharmacogenetic variants were identified with a query to the Pharmacogenomics Knowledge Base (PharmGKB) database, and functional prediction using the Variant Effect Predictor (VEP). Allele frequencies were compared with chi-square tests and differentiation was estimated by F(ST). Seven admixture groups were identified in Mexico. Some, like Group 1, Group 4, and Group 5, were found exclusively in certain geographic areas. More than 90% of the individuals, in some groups (Group 1, Group 4 and Group 5) were found in the Central-East and Southeast region of the country. MTRR p.I49M, ABCG2 p.Q141K, CHRNA5 p.D398N, SLCO2B1 rs2851069 show a low degree of differentiation between admixture groups. ANKK1 p.G318R and p.H90R, had the lowest allele frequency of Group 1. The reduction in these alleles reduces the risk of toxicity from anticancer and antihypercholesterolemic drugs. Our analysis identified different admixture patterns and described how they could be used to refine the practice of pharmacogenetic counseling for this admixed population. |
format | Online Article Text |
id | pubmed-7188951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71889512020-05-08 The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico Martínez-Magaña, José Jaime Genis-Mendoza, Alma Delia Villatoro Velázquez, Jorge Ameth Camarena, Beatriz Martín del Campo Sanchez, Raul Fleiz Bautista, Clara Bustos Gamiño, Marycarmen Reséndiz, Esbehidy Aguilar, Alejandro Medina-Mora, María Elena Nicolini, Humberto Front Pharmacol Pharmacology Pharmacogenetic analysis has generated translational data that could be applied to guide treatments according to individual genetic variations. However, pharmacogenetic counseling in some mestizo (admixed) populations may require tailoring to different patterns of admixture. The identification and clustering of individuals with related admixture patterns in such populations could help to refine the practice of pharmacogenetic counseling. This study identifies related groups in a highly admixed population-based sample from Mexico, and analyzes the differential distribution of actionable pharmacogenetic variants. A subsample of 1728 individuals from the Mexican Genomic Database for Addiction Research (MxGDAR/Encodat) was analyzed. Genotyping was performed with the commercial PsychArray BeadChip, genome-wide ancestry was estimated using EIGENSOFT, and model-based clustering was applied to defined admixture groups. Actionable pharmacogenetic variants were identified with a query to the Pharmacogenomics Knowledge Base (PharmGKB) database, and functional prediction using the Variant Effect Predictor (VEP). Allele frequencies were compared with chi-square tests and differentiation was estimated by F(ST). Seven admixture groups were identified in Mexico. Some, like Group 1, Group 4, and Group 5, were found exclusively in certain geographic areas. More than 90% of the individuals, in some groups (Group 1, Group 4 and Group 5) were found in the Central-East and Southeast region of the country. MTRR p.I49M, ABCG2 p.Q141K, CHRNA5 p.D398N, SLCO2B1 rs2851069 show a low degree of differentiation between admixture groups. ANKK1 p.G318R and p.H90R, had the lowest allele frequency of Group 1. The reduction in these alleles reduces the risk of toxicity from anticancer and antihypercholesterolemic drugs. Our analysis identified different admixture patterns and described how they could be used to refine the practice of pharmacogenetic counseling for this admixed population. Frontiers Media S.A. 2020-04-22 /pmc/articles/PMC7188951/ /pubmed/32390825 http://dx.doi.org/10.3389/fphar.2020.00324 Text en Copyright © 2020 Martínez-Magaña, Genis-Mendoza, Villatoro Velázquez, Camarena, Martín del Campo Sanchez, Fleiz Bautista, Bustos Gamiño, Reséndiz, Aguilar, Medina-Mora and Nicolini http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Martínez-Magaña, José Jaime Genis-Mendoza, Alma Delia Villatoro Velázquez, Jorge Ameth Camarena, Beatriz Martín del Campo Sanchez, Raul Fleiz Bautista, Clara Bustos Gamiño, Marycarmen Reséndiz, Esbehidy Aguilar, Alejandro Medina-Mora, María Elena Nicolini, Humberto The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico |
title | The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico |
title_full | The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico |
title_fullStr | The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico |
title_full_unstemmed | The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico |
title_short | The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico |
title_sort | identification of admixture patterns could refine pharmacogenetic counseling: analysis of a population-based sample in mexico |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188951/ https://www.ncbi.nlm.nih.gov/pubmed/32390825 http://dx.doi.org/10.3389/fphar.2020.00324 |
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