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混合模式的识别可优化药物遗传学咨询:对墨西哥一个基于人群的样本的分析。

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

作者信息

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

机构信息

Laboratorio de Genómica de Enfermedades Psiquiátricas y Neurodegenerativas, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico City, Mexico.

Hospital Psiquiátrico Infantil "Juan N. Navarro," Servicios de Atención Psiquiátrica, Mexico City, Mexico.

出版信息

Front Pharmacol. 2020 Apr 22;11:324. doi: 10.3389/fphar.2020.00324. eCollection 2020.

Abstract

Pharmacogenetic analysis has generated translational data that could be applied to guide treatments according to individual genetic variations. However, pharmacogenetic counseling in some (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. 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. p.I49M, p.Q141K p.D398N, rs2851069 show a low degree of differentiation between admixture groups. 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.

摘要

药物遗传学分析已产生了可用于根据个体基因变异指导治疗的转化数据。然而,在一些(混合)人群中进行药物遗传学咨询可能需要根据不同的混合模式进行调整。识别此类人群中具有相关混合模式的个体并进行聚类,有助于完善药物遗传学咨询的实践。本研究在来自墨西哥的高度混合的基于人群的样本中识别相关群体,并分析可操作的药物遗传学变异的差异分布。对来自墨西哥成瘾研究基因组数据库(MxGDAR/Encodat)的1728名个体的子样本进行了分析。使用商业PsychArray BeadChip进行基因分型,使用EIGENSOFT估计全基因组祖先,并将基于模型的聚类应用于定义的混合群体。通过查询药物基因组学知识库(PharmGKB)数据库并使用变异效应预测器(VEP)进行功能预测,识别可操作的药物遗传学变异。通过卡方检验比较等位基因频率,并通过F估计分化程度。在墨西哥识别出七个混合群体。其中一些群体,如第1组、第4组和第5组,仅在某些地理区域发现。在某些群体(第1组、第4组和第5组)中,超过90%的个体位于该国的中东部和东南部地区。p.I49M、p.Q141K、p.D398N、rs2851069在混合群体之间显示出较低的分化程度。p.G318R和p.H90R在第1组中的等位基因频率最低。这些等位基因的减少降低了抗癌和抗高胆固醇药物毒性的风险。我们的分析确定了不同的混合模式,并描述了如何利用它们来完善针对该混合人群的药物遗传学咨询实践。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7132/7188951/850c55258234/fphar-11-00324-g001.jpg

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