Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA 02114, USA.
Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
Hum Mol Genet. 2021 Aug 28;30(18):1773-1783. doi: 10.1093/hmg/ddab109.
Diet is a significant modifiable risk factor for type 2 diabetes (T2D), and its effect on disease risk is under partial genetic control. Identification of specific gene-diet interactions (GDIs) influencing risk biomarkers such as glycated hemoglobin (HbA1c) is a critical step towards precision nutrition for T2D prevention, but progress has been slow due to limitations in sample size and accuracy of dietary exposure measurement. We leveraged the large UK Biobank (UKB) cohort and a diverse group of dietary exposures, including 30 individual dietary traits and 8 empirical dietary patterns, to conduct genome-wide interaction studies in ~340 000 European-ancestry participants to identify novel GDIs influencing HbA1c. We identified five variant-dietary trait pairs reaching genome-wide significance (P < 5 × 10-8): two involved dietary patterns (meat pattern with rs147678157 and a fruit & vegetable-based pattern with rs3010439) and three involved individual dietary traits (bread consumption with rs62218803, dried fruit consumption with rs140270534 and milk type [dairy vs. other] with 4:131148078_TAGAA_T). These were affected minimally by adjustment for geographical and lifestyle-related confounders, and four of the five variants lacked genetic main effects that would have allowed their detection in a traditional genome-wide association study for HbA1c. Notably, multiple loci near transient receptor potential subfamily M genes (TRPM2 and TRPM3) interacted with carbohydrate-containing food groups. These interactions were further characterized using non-European UKB subsets and alternative measures of glycaemia (fasting glucose and follow-up HbA1c measurements). Our results highlight GDIs influencing HbA1c for future investigation, while reinforcing known challenges in detecting and replicating GDIs.
饮食是 2 型糖尿病（T2D）的一个重要可改变风险因素，其对疾病风险的影响受部分遗传控制。鉴定影响糖化血红蛋白（HbA1c）等风险生物标志物的特定基因-饮食相互作用（GDIs）是迈向 T2D 预防精准营养的关键步骤，但由于样本量和饮食暴露测量准确性的限制，进展缓慢。我们利用大型英国生物库（UKB）队列和多种饮食暴露，包括 30 种个体饮食特征和 8 种经验性饮食模式，在约 340000 名欧洲血统参与者中进行全基因组相互作用研究，以鉴定影响 HbA1c 的新 GDIs。我们确定了五个达到全基因组显著水平的变异-饮食特征对（P < 5×10-8）：两个涉及饮食模式（与 rs147678157 相关的肉类模式和与 rs3010439 相关的以水果和蔬菜为基础的模式）和三个涉及个体饮食特征（与 rs62218803 相关的面包消费、与 rs140270534 相关的干果消费以及与 4:131148078_TAGAA_T 相关的牛奶类型[乳制品与其他]）。这些特征受地理位置和生活方式相关混杂因素的调整影响很小，五个变异中有四个缺乏会在传统的 HbA1c 全基因组关联研究中检测到的遗传主效应。值得注意的是，瞬时受体电位亚家族 M 基因（TRPM2 和 TRPM3）附近的多个基因座与含碳水化合物的食物组相互作用。使用非欧洲 UKB 子集和替代的血糖测量（空腹血糖和随访 HbA1c 测量）进一步对这些相互作用进行了特征描述。我们的结果突出了未来需要进一步研究影响 HbA1c 的 GDIs，同时也强调了检测和复制 GDIs 所面临的已知挑战。
