Fine-scale population structure in the UK Biobank: implications for genome-wide association studies
Fine-scale population structure in the UK Biobank: implications for genome-wide association studies
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DOI：
10.1093/hmg/ddaa157
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发表时间：
2020-08-15
影响因子：
3.5
通讯作者：
Morris, Andrew P.
中科院分区：
文献类型：
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作者：
Cook, James P.;Mahajan, Anubha;Morris, Andrew P.
英国生物银行是一项超过 500,000 名参与者的前瞻性研究，它汇总了来自问卷调查、身体测量、生物标志物、成像和随访的数据，以了解广泛的健康相关结果，以及辅以高密度插补的全基因组基因分型。先前的研究强调了英国从西北到东南的小规模人口结构，但未测量的地理混杂对英国生物库中复杂人类特征的全基因组关联研究（GWAS）的影响尚未得到调查。我们考虑了英国生物库中的 368,325 名英国白人，并对他们的出生地进行了 GWAS。我们证明，广泛使用的调整种群结构的方法，包括主成分分析和对遗传关系矩阵具有随机效应的混合建模，不能完全解释英国生物库中的精细地理混杂因素。我们观察到出生地点与一系列生活方式相关特征（包括体重指数和脂肪量、高血压和肺功能）之间存在显着的遗传相关性，即使在对人口结构进行调整后也是如此。在对人口结构进行校正后，与出生地点相关的变异也与许多与生活方式相关的特征密切相关，这表明可能存在与地理混淆的环境因素，但尚未得到充分考虑。我们的研究结果强调，在解释英国生物银行中与生活方式相关的性状 GWAS 时需要谨慎，特别是在显示与出生地点强烈残留关联的基因座中。
The UK Biobank is a prospective study of more than 500 000 participants, which has aggregated data from questionnaires, physical measures, biomarkers, imaging and follow-up for a wide range of health-related outcomes, together with genome-wide genotyping supplemented with high-density imputation. Previous studies have highlighted fine-scale population structure in the UK on a North-West to South-East cline, but the impact of unmeasured geographical confounding on genome-wide association studies (GWAS) of complex human traits in the UK Biobank has not been investigated. We considered 368 325 white British individuals from the UK Biobank and performed GWAS of their birth location. We demonstrate that widely used approaches to adjust for population structure, including principal component analysis and mixed modelling with a random effect for a genetic relationship matrix, cannot fully account for the fine-scale geographical confounding in the UK Biobank. We observe significant genetic correlation of birth location with a range of lifestyle-related traits, including body-mass index and fat mass, hypertension and lung function, even after adjustment for population structure. Variants driving associations with birth location are also strongly associated with many of these lifestyle-related traits after correction for population structure, indicating that there could be environmental factors that are confounded with geography that have not been adequately accounted for. Our findings highlight the need for caution in the interpretation of lifestyle-related trait GWAS in UK Biobank, particularly in loci demonstrating strong residual association with birth location.