Simonin-Wilmer Irving, Orozco-Del-Pino Pedro, Bishop D Timothy, Iles Mark M, Robles-Espinoza Carla Daniela
Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Campus Juriquilla, Queretaro, Mexico.
Biostatistics Department, University of Michigan, Ann Arbor, MI, United States.
Front Genet. 2021 Nov 5;12:703901. doi: 10.3389/fgene.2021.703901. eCollection 2021.
Genome-wide association studies (GWAS) have been very successful at identifying genetic variants influencing a large number of traits. Although the great majority of these studies have been performed in European-descent individuals, it has been recognised that including populations with differing ancestries enhances the potential for identifying causal SNPs due to their differing patterns of linkage disequilibrium. However, when individuals from distinct ethnicities are included in a GWAS, it is necessary to implement a number of control steps to ensure that the identified associations are real genotype-phenotype relationships. In this Review, we discuss the analyses that are required when performing multi-ethnic studies, including methods for determining ancestry at the global and local level for sample exclusion, controlling for ancestry in association testing, and post-GWAS interrogation methods such as genomic control and meta-analysis. We hope that this overview provides a primer for those researchers interested in including distinct populations in their studies.
全基因组关联研究（GWAS）在识别影响大量性状的基因变异方面非常成功。尽管这些研究绝大多数是在欧洲血统个体中进行的，但人们已经认识到，纳入不同血统的人群会因连锁不平衡模式不同而增加识别因果单核苷酸多态性（SNP）的潜力。然而，当来自不同种族的个体被纳入GWAS时，有必要实施一些控制步骤，以确保所识别的关联是真实的基因型-表型关系。在本综述中，我们讨论了进行多民族研究时所需的分析，包括在全球和局部层面确定血统以进行样本排除的方法、在关联测试中控制血统的方法，以及GWAS后 interrogation 方法，如基因组控制和荟萃分析。我们希望这一概述能为那些有兴趣在研究中纳入不同人群的研究人员提供一个入门指南。
