英国生物银行饮食习惯的综合基因组分析确定了数百种遗传关联。
Comprehensive genomic analysis of dietary habits in UK Biobank identifies hundreds of genetic associations.
机构信息
Programs in Metabolism and Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
出版信息
Nat Commun. 2020 Mar 19;11(1):1467. doi: 10.1038/s41467-020-15193-0.
Unhealthful dietary habits are leading risk factors for life-altering diseases and mortality. Large-scale biobanks now enable genetic analysis of traits with modest heritability, such as diet. We perform a genomewide association on 85 single food intake and 85 principal component-derived dietary patterns from food frequency questionnaires in UK Biobank. We identify 814 associated loci, including olfactory receptor associations with fruit and tea intake; 136 associations are only identified using dietary patterns. Mendelian randomization suggests our top healthful dietary pattern driven by wholemeal vs. white bread consumption is causally influenced by factors correlated with education but is not strongly causal for coronary artery disease or type 2 diabetes. Overall, we demonstrate the value in complementary phenotyping approaches to complex dietary datasets, and the utility of genomic analysis to understand the relationships between diet and human health.
不健康的饮食习惯是导致改变生活的疾病和死亡的主要危险因素。大规模的生物银行现在使具有适度遗传性的特征（如饮食）的基因分析成为可能。我们对 UK Biobank 中的 85 种单一食物摄入和 85 种主要成分衍生的饮食模式进行了全基因组关联分析。我们确定了 814 个相关基因座，包括嗅觉受体与水果和茶摄入的关联；仅使用饮食模式可识别 136 个关联。孟德尔随机化表明，我们由全麦与白面包消费驱动的最佳健康饮食模式是由与教育相关的因素引起的，但对冠状动脉疾病或 2 型糖尿病的影响不是很强。总的来说，我们证明了互补表型方法在复杂饮食数据集中的价值，以及基因组分析在理解饮食与人类健康之间关系方面的效用。
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