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英国生物库样本中明显的潜在结构对流行病学分析有影响。

Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis.

机构信息

Medical Research Council Integrative Epidemiology Unit, Department of Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.

Avon Longitudinal Study of Parents and Children, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.

出版信息

Nat Commun. 2019 Jan 18;10(1):333. doi: 10.1038/s41467-018-08219-1.

Abstract

Large studies use genotype data to discover genetic contributions to complex traits and infer relationships between those traits. Co-incident geographical variation in genotypes and health traits can bias these analyses. Here we show that single genetic variants and genetic scores composed of multiple variants are associated with birth location within UK Biobank and that geographic structure in genotype data cannot be accounted for using routine adjustment for study centre and principal components derived from genotype data. We find that major health outcomes appear geographically structured and that coincident structure in health outcomes and genotype data can yield biased associations. Understanding and accounting for this phenomenon will be important when making inference from genotype data in large studies.

摘要

大型研究利用基因型数据来发现复杂特征的遗传贡献,并推断这些特征之间的关系。基因型和健康特征在地理位置上的巧合变化可能会使这些分析产生偏差。在这里,我们表明,单一的遗传变异和由多个变异组成的遗传评分与英国生物银行内的出生地点有关,而且基因型数据中的地理结构不能通过常规的研究中心调整和从基因型数据中得出的主要成分来解释。我们发现主要的健康结果在地理上呈现出结构性,而健康结果和基因型数据中的巧合结构可能会产生有偏差的关联。在大型研究中从基因型数据进行推断时,了解和解释这种现象非常重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65e7/6338768/96d0a4031436/41467_2018_8219_Fig1_HTML.jpg

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