Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis
Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis
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DOI：
10.1038/s41467-018-08219-1
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发表时间：
2019-01-18
影响因子：
16.6
通讯作者：
Timpson, Nicholas J.
中科院分区：
文献类型：
--
作者：
Haworth, Simon;Mitchell, Ruth;Timpson, Nicholas J.
大型研究使用基因型数据来发现复杂性状的遗传贡献，并推断这些性状之间的关系。同时发生的基因类型和健康特征的地理差异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量和由多个变量组成的遗传分数与英国生物库中的出生地点相关，并且不能使用对来自基因数据的研究中心和主成分的常规调整来解释基因数据中的地理结构。我们发现，主要的健康结果似乎具有地域结构，健康结果和基因数据中的一致结构可能会产生有偏见的关联。当在大型研究中从基因数据中做出推断时，理解和解释这一现象将是重要的。
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.