Samsung Genome Institute, Samsung Medical Center, Gangnam-gu, Seoul 06351, Korea.
Department of Molecular Cell Biology, Sungkyunkwan University School of Medicine, Suwon 16419, Gyeonggi-do, Korea.
Nutrients. 2018 Feb 26;10(3):266. doi: 10.3390/nu10030266.
The past decade has witnessed the discovery of obesity-related genetic variants and their functions through genome-wide association studies. Combinations of risk alleles can influence obesity phenotypes with different degrees of effectiveness across various individuals by interacting with environmental factors. We examined the interaction between genetic variation and changes in dietary habits or exercise that influences body fat loss from a large Korean cohort ( = 8840). Out of 673 obesity-related SNPs, a total of 100 SNPs (37 for carbohydrate intake; 19 for fat intake; 44 for total calories intake; 25 for exercise onset) identified to have gene-environment interaction effect in generalized linear model were used to calculate genetic risk scores (GRS). Based on the GRS distribution, we divided the population into four levels, namely, "very insensitive", "insensitive", "sensitive", and "very sensitive" for each of the four categories, "carbohydrate intake", "fat intake", "total calories intake", and "exercise". Overall, the mean body fat loss became larger when the sensitivity level was increased. In conclusion, genetic variants influence the effectiveness of dietary regimes for body fat loss. Based on our findings, we suggest a platform for personalized body fat management by providing the most suitable and effective nutrition or activity plan specific to an individual.
在过去的十年中，通过全基因组关联研究发现了与肥胖相关的遗传变异及其功能。风险等位基因的组合可以通过与环境因素相互作用，对不同个体的肥胖表型产生不同程度的影响。我们从一个大型韩国队列（n=8840）中研究了遗传变异与饮食习惯或运动变化之间的相互作用，这些变化影响体脂的减少。在 673 个与肥胖相关的 SNP 中，共有 100 个 SNP（37 个与碳水化合物摄入有关；19 个与脂肪摄入有关；44 个与总热量摄入有关；25 个与运动开始有关）在广义线性模型中被确定具有基因-环境相互作用效应，用于计算遗传风险评分（GRS）。根据 GRS 的分布，我们将人群分为四个水平，即“非常不敏感”、“不敏感”、“敏感”和“非常敏感”，分别对应于四个类别，即“碳水化合物摄入”、“脂肪摄入”、“总热量摄入”和“运动”。总的来说，当敏感性水平增加时，体脂减少的平均值变得更大。总之，遗传变异影响饮食方案对体脂减少的效果。基于我们的发现，我们建议通过提供针对个体的最适合和有效的营养或活动计划，为个性化的体脂管理提供一个平台。
