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利用肥胖遗传风险评分预测巴基斯坦人群的人体测量和代谢特征。

Predicting anthropometric and metabolic traits with a genetic risk score for obesity in a sample of Pakistanis.

机构信息

Molecular Biology and Human Genetics Laboratory, Dr. Panjwani Center for Molecular Medicine and Drug Research (PCMD), International Center for Chemical and Biological Sciences (ICCBS), University of Karachi, Karachi, 75270, Pakistan.

出版信息

Sci Rep. 2021 Apr 15;11(1):8320. doi: 10.1038/s41598-021-87702-0.

Abstract

Obesity is an outcome of multiple factors including environmental and genetic influences. Common obesity is a polygenic trait indicating that multiple genetic variants act synergistically to influence its expression. We constructed a genetic risk score (GRS) based on five genetic variants (MC4R rs17782313, BDNF rs6265, FTO rs1421085, TMEM18 rs7561317, and NEGR1 rs2815752) and examined its association with obesity-related traits in a sample of Pakistanis. The study involved 306 overweight/obese (OW/OB) and 300 normal-weight (NW) individuals. The age range of the study participants was 12-63 years. All anthropometric and metabolic parameters were measured for each participant via standard procedures and biochemical assays, respectively. The genetic variants were genotyped by allelic discrimination assays. The age- and gender-adjusted associations between the GRS and obesity-related anthropometric and metabolic measures were determined using linear regression analyses. The results showed that OW/OB individuals had significantly higher mean ranks of GRS than NW individuals. Moreover, a significant association of the GRS with obesity-related anthropometric traits was seen. However, the GRS did not appear to affect any obesity-related metabolic parameter. In conclusion, our findings indicate the combined effect of multiple genetic variants on the obesity-related anthropometric phenotypes in Pakistanis.

摘要

肥胖是多种因素的结果,包括环境和遗传影响。常见的肥胖是一种多基因特征,表明多种遗传变异协同作用影响其表达。我们构建了一个基于五个遗传变异(MC4R rs17782313、BDNF rs6265、FTO rs1421085、TMEM18 rs7561317 和 NEGR1 rs2815752)的遗传风险评分(GRS),并在巴基斯坦人的样本中检查了它与肥胖相关特征的关联。该研究涉及 306 名超重/肥胖(OW/OB)和 300 名正常体重(NW)个体。研究参与者的年龄范围为 12-63 岁。通过标准程序和生化分析分别测量了每位参与者的所有人体测量和代谢参数。通过等位基因区分测定法对遗传变异进行基因分型。使用线性回归分析确定了 GRS 与肥胖相关的人体测量和代谢测量之间的年龄和性别调整关联。结果表明,OW/OB 个体的 GRS 平均等级明显高于 NW 个体。此外,还发现 GRS 与肥胖相关的人体测量特征存在显著关联。然而,GRS 似乎并不影响任何肥胖相关的代谢参数。总之,我们的研究结果表明,多个遗传变异在巴基斯坦人肥胖相关的人体测量表型中具有综合作用。

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