韩国人口体重指数和体脂率的直接面向消费者基因测试和生活方式问卷分析

Hyo-Eun Kim, K. Park, Dasom Lee, Soram Lee, Sang-Woon Kim, Tae Soon Hwang, Kyung-Won Hong
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引用次数: 0

摘要

背景:直接面向消费者(DTC)基因检测为消费者提供了遗传风险,并激励消费者照顾自己的定制医疗保健。2018年,我们与康宝莱韩国有限公司合作开发并提供DTC基因检测服务(GENESTART™)。方法:分析24447人的体脂率(BFP)、体重指数(BMI)、31种遗传多态性基因型和19项问卷调查结果。采用线性回归分析检验BFP和BMI的遗传主效应,采用控制年龄和性别为协变量的广义线性模型检验交互效应。结果:在BFP的情况下,样本平均值为31.47%,男性为24.76%,女性为32.79%,表明男性的平均BFP比女性低8个百分点。总体平均BMI为25.38,男性为26.45,女性为25.17,表明男性的平均BMI比女性高1.2 kg/m2。众所周知的肥胖标志物FTO和MC4R基因与两种表型均有显著相关性,与应激性肥胖相关的BDNF基因与BMI呈极显著相关性,与BFP相关性较弱。其余基因中,TRIB1、ABCA1、MYL2、G6PC、GCKR、GLIS3、CYP17A1、hector 4和NT5C2基因与肥胖相关表型显著相关。在这项研究中,我们发现了BFP的四种相互作用结果(ABO和水果、CYP1A2和含糖食物、FTO和肌肉锻炼、MC4R和维生素)和BMI的五种相互作用结果(MC4R和蛋白质、CSK和水果、MC4R和钙、DGKB和钙、CSK和水)。结论:本研究有望为接受基因检测的客户提供个性化和准确的BFP和BMI管理解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Direct-to-Consumer Genetic Test and Lifestyle Questionnaire Analysis of Body Mass Index and Body Fat Percentage in a Large Korean Population
Background: Direct-to-Consumer (DTC) genetic testing provides genetic risk to consumers and motivates consumers to take care of their own customized health care. In 2018, we developed and provided a DTC genetic testing service (GENESTART™) in collaboration with Herbalife Korea Co. Ltd. Methods: The analyzed dataset consisted of the body fat percentage (BFP), body mass index (BMI), 31 genetic polymorphism genotypes, and responses to 19 questionnaire items of 24,447 individuals. The genetic main effects for BFP and BMI were examined by linear regression analysis, and the interaction effects were examined using a generalized linear model that controlled age and sex as covariates. Results: In the case of BFP, the sample average was 31.47% overall, 24.76% for men, and 32.79% for women, showing that men had an average BFP that was 8 percentage points lower than that of women. The average BMI was 25.38 overall, 26.45 for men, and 25.17 for women, showing that men had an average BMI of 1.2 kg/m2 higher than that of women. The FTO and MC4R genes, well-known obesity markers, showed a significant correlation with both phenotypes, and the BDNF gene, which is related to stress obesity, showed a highly significant association with BMI but only a weak association with BFP. Among the remaining genes, TRIB1, ABCA1, MYL2, G6PC, GCKR, GLIS3, CYP17A1, HECTD4, and NT5C2 genes showed significant associations with the obesity-related phenotypes. In this study, we found four interaction results for BFP (ABO and fruits, CYP1A2 and sugary foods, FTO and muscle exercise, MC4R and vitamins) and five interactions for BMI (MC4R and proteins, CSK and fruits, MC4R and calcium, DGKB and calcium, CSK and water). Conclusions: This study is expected to enable the provision of personalized and accurate solutions for BFP and BMI management to customers who have undergone genetic testing.
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