Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
Department of Statistics and Actuarial Science, Soongsil University, Seoul, Republic of Korea.
Front Endocrinol (Lausanne). 2023 Aug 23;14:1165744. doi: 10.3389/fendo.2023.1165744. eCollection 2023.
The influence of dietary patterns measured using Recommended Food Score (RFS) with foods with high amounts of antioxidant nutrients for Type 2 diabetes (T2D) was analyzed. Our analysis aims to find associations between dietary patterns and T2D and conduct a gene-diet interaction analysis related to T2D.
Data analyzed in the current study were obtained from the Korean Genome and Epidemiology Study Cohort. The dietary patterns of 46 food items were assessed using a validated food frequency questionnaire. To maximize the predictive power of the RFS, we propose two weighted food scores, namely HisCoM-RFS calculated using the novel Hierarchical Structural Component model (HisCoM) and PLSDA-RFS calculated using Partial Least Squares-Discriminant Analysis (PLS-DA) method.
Both RFS (OR: 1.11; 95% CI: 1.03- 1.20; P = 0.009) and PLSDA-RFS (OR: 1.10; 95% CI: 1.02-1.19, P = 0.011) were positively associated with T2D. Mapping of SNPs (P < 0.05) from the interaction analysis between SNPs and the food scores to genes and pathways yielded some 12 genes (CACNA2D3, RELN, DOCK2, SLIT3, CTNNA2, etc.) and pathways associated with T2D. The strongest association was observed with the adipocytokine signalling pathway, highlighting 32 genes (STAT3, MAPK10, MAPK8, IRS1, AKT1-3, ADIPOR2, etc.) most likely associated with T2D. Finally, the group of the subjects in low, intermediate and high using both the food scores and a polygenic risk score found an association between diet quality groups with issues at high genetic risk of T2D.
A dietary pattern of poor amounts of antioxidant nutrients is associated with the risk of T2D, and diet affects pathway mechanisms involved in developing T2D.
本研究分析了使用推荐食物评分（RFS）衡量的饮食模式与富含抗氧化营养素的食物对 2 型糖尿病（T2D）的影响。我们的分析旨在寻找饮食模式与 T2D 之间的关联，并进行与 T2D 相关的基因-饮食相互作用分析。
本研究分析的数据来自韩国基因组与流行病学研究队列。使用经过验证的食物频率问卷评估 46 种食物的饮食模式。为了最大限度地提高 RFS 的预测能力，我们提出了两种加权食物评分，即使用新的层次结构成分模型（HisCoM）计算的 HisCoM-RFS 和使用偏最小二乘判别分析（PLS-DA）方法计算的 PLSDA-RFS。
RFS（OR：1.11；95%CI：1.03-1.20；P=0.009）和 PLSDA-RFS（OR：1.10；95%CI：1.02-1.19，P=0.011）均与 T2D 呈正相关。基因与通路分析中 SNP 与食物评分之间的交互作用分析（P<0.05）映射到基因和通路，得到了一些与 T2D 相关的 12 个基因（CACNA2D3、RELN、DOCK2、SLIT3、CTNNA2 等）和通路。与脂肪细胞因子信号通路的关联最强，突出了 32 个最有可能与 T2D 相关的基因（STAT3、MAPK10、MAPK8、IRS1、AKT1-3、ADIPOR2 等）。最后，在使用食物评分和多基因风险评分的低、中、高三组受试者中，发现饮食质量组与 T2D 高遗传风险之间存在关联。
富含抗氧化营养素的饮食模式与 T2D 风险相关，饮食会影响与 T2D 发生相关的通路机制。
