Departamento de Farmacología, Facultad de Medicina, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Nutrition and Clinical Trials Unit, GENYAL Platform IMDEA-Food Institute, CEI UAM + CSIC, 28049 Madrid, Spain.
Nutrients. 2020 Apr 19;12(4):1142. doi: 10.3390/nu12041142.
The aim of this study was to evaluate the distribution of energy intake and macronutrients consumption throughout the day, and how its effect on nutritional status can be modulated by the presence of the rs3749474 polymorphism of the CLOCK gene in the Cantoblanco Platform for Nutritional Genomics ("GENYAL Platform"). This cross-sectional study was carried out on 898 volunteers between 18 and 69 years old (65.5% women). Anthropometric measurements, social issues and health, dietary, biochemical, genetic, and physical activity data were collected. Subsequently, 21 statistical interaction models were designed to predict the body mass index (BMI) considering seven dietary variables analyzed by three genetic models (adjusted by age, sex, and physical activity). The average BMI was 26.9 ± 4.65 kg/m, 62.14% presented an excess weight (BMI > 25 kg/m). A significant interaction was observed between the presence of the rs3749474 polymorphism and the evening carbohydrate intake (% of the total daily energy intake [%TEI]) (adjusted = 0.046), when predicting the BMI. Participants carrying TT/CT genotype showed a positive association between the evening carbohydrate intake (%TEI) and BMI (β = 0.3379, 95% CI = (0.1689,0.5080)) and (β = 0.1529, 95% CI = (-0.0164,0.3227)), respectively, whereas the wild type allele (CC) showed a negative association (β = -0.0321, 95% CI = (-0.1505,0.0862)). No significant interaction with the remaining model variables was identified. New dietary strategies may be implemented to schedule the circadian distribution of macronutrients according to the genotype. Clinical Trial number: NCT04067921.
本研究旨在评估一天中能量摄入和宏量营养素消耗的分布情况,以及 CLOCK 基因 rs3749474 多态性的存在如何调节其对营养状况的影响。该横断面研究共纳入 898 名 18 至 69 岁志愿者(65.5%为女性)。收集了人体测量学指标、社会问题和健康状况、饮食、生化、遗传和身体活动数据。随后,设计了 21 个统计交互模型,以考虑通过三种遗传模型(按年龄、性别和身体活动调整)分析的 7 种饮食变量来预测体重指数(BMI)。平均 BMI 为 26.9 ± 4.65kg/m,62.14%的人体重超标(BMI>25kg/m)。在预测 BMI 时,观察到 rs3749474 多态性的存在与晚餐碳水化合物摄入(占总日能量摄入的百分比 [%TEI])之间存在显著的交互作用(调整后的 = 0.046)。携带 TT/CT 基因型的参与者显示,晚餐碳水化合物摄入(%TEI)与 BMI 之间存在正相关(β=0.3379,95%CI=(0.1689,0.5080))和(β=0.1529,95%CI=(-0.0164,0.3227)),而野生型等位基因(CC)则呈负相关(β=-0.0321,95%CI=(-0.1505,0.0862))。没有发现与其他模型变量有显著的交互作用。可能需要实施新的饮食策略,根据基因型安排宏量营养素的昼夜分布。临床试验注册号:NCT04067921。