Medina-Gomez Carolina, Felix Janine Frédérique, Estrada Karol, Peters Marjoline Josephine, Herrera Lizbeth, Kruithof Claudia Jeanette, Duijts Liesbeth, Hofman Albert, van Duijn Cornelia Marja, Uitterlinden Andreas Gerardus, Jaddoe Vincent Wilfred Vishal, Rivadeneira Fernando
The Generation R Study Group, Erasmus University Medical Center, Rotterdam, The Netherlands.
Eur J Epidemiol. 2015 Apr;30(4):317-30. doi: 10.1007/s10654-015-9998-4. Epub 2015 Mar 12.
Genome-wide association studies (GWAS) have been successful in identifying loci associated with a wide range of complex human traits and diseases. Up to now, the majority of GWAS have focused on European populations. However, the inclusion of other ethnic groups as well as admixed populations in GWAS studies is rapidly rising following the pressing need to extrapolate findings to non-European populations and to increase statistical power. In this paper, we describe the methodological steps surrounding genetic data generation, quality control, study design and analytical procedures needed to run GWAS in the multiethnic and highly admixed Generation R Study, a large prospective birth cohort in Rotterdam, the Netherlands. Furthermore, we highlight a number of practical considerations and alternatives pertinent to the quality control and analysis of admixed GWAS data.
全基因组关联研究（GWAS）已成功识别出与多种复杂人类性状和疾病相关的基因座。到目前为止，大多数GWAS都集中在欧洲人群上。然而，鉴于迫切需要将研究结果外推至非欧洲人群并提高统计效力，GWAS研究中纳入其他种族群体以及混合人群的情况正在迅速增加。在本文中，我们描述了在荷兰鹿特丹一项大型前瞻性出生队列——Generation R研究中进行多民族和高度混合GWAS所需的围绕遗传数据生成、质量控制、研究设计和分析程序的方法步骤。此外，我们强调了一些与混合GWAS数据的质量控制和分析相关的实际考虑因素和替代方案。
