Center for Nutrition Research, Department of Nutrition, Food Science and Physiology, Faculty of Pharmacy and Nutrition, University of Navarra, 31008 Pamplona, Spain.
Navarra Institute for Health Research (IdiSNA), 31008 Pamplona, Spain.
Nutrients. 2023 Dec 6;15(24):5023. doi: 10.3390/nu15245023.
Obesity is a public health problem. The usual treatment is a reduction in calorie intake and an increase in energy expenditure, but not all individuals respond equally to these treatments. Epigenetics could be a factor that contributes to this heterogeneity. The aim of this research was to determine the association between DNA methylation at baseline and the percentage of BMI loss (%BMIL) after two dietary interventions, in order to design a prediction model to evaluate %BMIL based on methylation data.
Spanish participants with overweight or obesity ( = 306) were randomly assigned to two lifestyle interventions with hypocaloric diets: one moderately high in protein (MHP) and the other low in fat (LF) for 4 months (Obekit study; ClinicalTrials.gov ID: NCT02737267). Basal DNA methylation was analyzed in white blood cells using the Infinium MethylationEPIC array. After identifying those methylation sites associated with %BMIL ( < 0.05 and SD > 0.1), two weighted methylation sub-scores were constructed for each diet: 15 CpGs were used for the MHP diet and 11 CpGs for the LF diet. Afterwards, a total methylation score was made by subtracting the previous sub-scores. These data were used to design a prediction model for %BMIL through a linear mixed effect model with the interaction between diet and total score.
Overall, DNA methylation predicts the %BMIL of two 4-month hypocaloric diets and was able to determine which type of diet is the most appropriate for each individual. The results of this pioneer study confirm that epigenetic biomarkers may be further used for precision nutrition and the design of personalized dietary strategies against obesity.
肥胖是一个公共卫生问题。通常的治疗方法是减少热量摄入和增加能量消耗，但并非所有个体对这些治疗的反应都相同。表观遗传学可能是导致这种异质性的一个因素。本研究的目的是确定基线时 DNA 甲基化与两种饮食干预后 BMI 减轻百分比（%BMIL）之间的相关性，以便设计一个基于甲基化数据评估%BMIL 的预测模型。
西班牙超重或肥胖参与者（n=306）被随机分配到两种低热量饮食的生活方式干预中：一种蛋白质含量适中（MHP），另一种脂肪含量低（LF），持续 4 个月（Obekit 研究；ClinicalTrials.gov 标识符：NCT02737267）。使用 Infinium MethylationEPIC 阵列分析白细胞中的基础 DNA 甲基化。在确定与%BMIL 相关的甲基化位点（<0.05 和 SD > 0.1）后，为每种饮食构建了两个加权甲基化子评分：MHP 饮食使用 15 个 CpG，LF 饮食使用 11 个 CpG。之后，通过具有饮食和总评分之间相互作用的线性混合效应模型，构建总甲基化评分。
总的来说，DNA 甲基化预测了两种为期 4 个月的低热量饮食的%BMIL，并能够确定哪种饮食最适合每个个体。这项先驱性研究的结果证实，表观遗传学生物标志物可能进一步用于精准营养和设计针对肥胖的个性化饮食策略。
