Hellbach Fabian, Baumeister Sebastian-Edgar, Wilson Rory, Wawro Nina, Dahal Chetana, Freuer Dennis, Hauner Hans, Peters Annette, Winkelmann Juliane, Schwettmann Lars, Rathmann Wolfgang, Kronenberg Florian, Koenig Wolfgang, Meisinger Christa, Waldenberger Melanie, Linseisen Jakob
Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilian University of Munich, Marchioninistr. 15, 81377 Munich, Germany.
Epidemiology, Faculty of Medicine, University Hospital Augsburg, University of Augsburg, Stenglinstraße 2, 86156 Augsburg, Germany.
Life (Basel). 2022 Jul 15;12(7):1064. doi: 10.3390/life12071064.
Associations between diet and DNA methylation may vary among subjects with different metabolic states, which can be captured by clustering populations in metabolically homogenous subgroups, called metabotypes. Our aim was to examine the relationship between habitual consumption of various food groups and DNA methylation as well as to test for effect modification by metabotype. A cross-sectional analysis of participants (median age 58 years) of the population-based prospective KORA FF4 study, habitual dietary intake was modeled based on repeated 24-h diet recalls and a food frequency questionnaire. DNA methylation was measured using the Infinium MethylationEPIC BeadChip providing data on >850,000 sites in this epigenome-wide association study (EWAS). Three metabotype clusters were identified using four standard clinical parameters and BMI. Regression models were used to associate diet and DNA methylation, and to test for effect modification. Few significant signals were identified in the basic analysis while many significant signals were observed in models including food group-metabotype interaction terms. Most findings refer to interactions of food intake with metabotype 3, which is the metabotype with the most unfavorable metabolic profile. This research highlights the importance of the metabolic characteristics of subjects when identifying associations between diet and white blood cell DNA methylation in EWAS.
饮食与DNA甲基化之间的关联在具有不同代谢状态的个体中可能存在差异,这种差异可以通过将人群聚类到代谢同质的亚组(即代谢型)中来体现。我们的目的是研究各类食物的习惯性摄入量与DNA甲基化之间的关系,并检验代谢型对这种关系的影响修正作用。在基于人群的前瞻性KORA FF4研究中,对参与者(中位年龄58岁)进行横断面分析,基于重复的24小时饮食回忆和食物频率问卷对习惯性饮食摄入量进行建模。在这项全基因组关联研究(EWAS)中,使用Infinium MethylationEPIC BeadChip测量DNA甲基化,该芯片可提供超过85万个位点的数据。使用四个标准临床参数和BMI确定了三个代谢型聚类。回归模型用于关联饮食与DNA甲基化,并检验影响修正作用。在基础分析中发现的显著信号较少,而在包含食物组 - 代谢型交互项的模型中观察到许多显著信号。大多数研究结果涉及食物摄入量与代谢型3的相互作用,代谢型3是代谢特征最不利的代谢型。这项研究强调了在EWAS中识别饮食与白细胞DNA甲基化之间的关联时,受试者代谢特征的重要性。