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The identification of admixture patterns could refine pharmacogenetic counseling: analysis of a population-based sample in Mexico

dc.creatorMartínez-Magaña, José Jaimees_ES
dc.creatorGenis-Mendoza, Alma Deliaes_ES
dc.creatorVillatoro Velázquez, Jorge Amethes_ES
dc.creatorCamarena, Beatrizes_ES
dc.creatorCampo Sanchez, Raul Martín deles_ES
dc.creatorFleiz Bautista, Claraes_ES
dc.creatorBustos Gamiño, Marycarmenes_ES
dc.creatorReséndiz, Esbehidyes_ES
dc.creatorAguilar, Alejandroes_ES
dc.creatorMedina-Mora, María Elenaes_ES
dc.creatorNicolini, Humbertoes_ES
dc.date2020
dc.date.accessioned2023-09-05T20:19:39Z
dc.date.available2023-09-05T20:19:39Z
dc.date.issued2020
dc.identifierJC28DIEP20es_ES
dc.identifier.urihttp://repositorio.inprf.gob.mx/handle/123456789/7753
dc.identifier.urihttps://doi.org/10.3389/fphar.2020.00324
dc.identifier.urihttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188951/
dc.descriptionPharmacogenetic 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.es_ES
dc.formatPDFes_ES
dc.language.isoenges_ES
dc.publisherFrontiers Mediaes_ES
dc.relation11:324
dc.rightsAcceso Cerradoes_ES
dc.titleThe identification of admixture patterns could refine pharmacogenetic counseling: analysis of a population-based sample in Mexicoes_ES
dc.typeArtículoes_ES
dc.contributor.affiliationLaboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City, Mexico
dc.contributor.emailmetmmora@gmail.com (María Elena Medina-Mora) hnicolini@inmegen.gob.mx (Humberto Nicolini)
dc.relation.jnabreviadoFRONT PHARMACOL
dc.relation.journalFrontiers in Pharmacology
dc.identifier.placeSuiza
dc.date.published2020
dc.identifier.eissn1663-9812
dc.identifier.doi10.3389/fphar.2020.00324
dc.subject.kwMexican population-based sample
dc.subject.kwMxGDAR/Encodat
dc.subject.kwPharmacogenetics
dc.subject.kwGenomics
dc.subject.kwAdmixture


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