Frontiers in Pharmacology (Apr 2020)

The Identification of Admixture Patterns Could Refine Pharmacogenetic Counseling: Analysis of a Population-Based Sample in Mexico

  • José Jaime Martínez-Magaña,
  • Alma Delia Genis-Mendoza,
  • Alma Delia Genis-Mendoza,
  • Jorge Ameth Villatoro Velázquez,
  • Jorge Ameth Villatoro Velázquez,
  • Beatriz Camarena,
  • Raul Martín del Campo Sanchez,
  • Raul Martín del Campo Sanchez,
  • Clara Fleiz Bautista,
  • Clara Fleiz Bautista,
  • Marycarmen Bustos Gamiño,
  • Esbehidy Reséndiz,
  • Alejandro Aguilar,
  • María Elena Medina-Mora,
  • María Elena Medina-Mora,
  • Humberto Nicolini

DOI
https://doi.org/10.3389/fphar.2020.00324
Journal volume & issue
Vol. 11

Abstract

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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 FST. 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.

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