Department of Public Health Sciences, Graduate school of Public Health, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea.
Interdisciplinary Program in Bioinformatics, College of Natural Sciences, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea.
Brief Bioinform. 2024 Jul 25;25(5). doi: 10.1093/bib/bbae389.
East Asian populations exhibit a genetic predisposition to obesity, yet comprehensive research on these traits is limited. We conducted a genome-wide association study (GWAS) with 93,673 Korean subjects to uncover novel genetic loci linked to obesity, examining metrics such as body mass index, waist circumference, body fat ratio, and abdominal fat ratio. Participants were categorized into non-obese, metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO) groups. Using advanced computational methods, we developed a multifaceted polygenic risk scores (PRS) model to predict obesity. Our GWAS identified significant genetic effects with distinct sizes and directions within the MHO and MUO groups compared with the non-obese group. Gene-based and gene-set analyses, along with cluster analysis, revealed heterogeneous patterns of significant genes on chromosomes 3 (MUO group) and 11 (MHO group). In analyses targeting genetic predisposition differences based on metabolic health, odds ratios of high PRS compared with medium PRS showed significant differences between non-obese and MUO, and non-obese and MHO. Similar patterns were seen for low PRS compared with medium PRS. These findings were supported by the estimated genetic correlation (0.89 from bivariate GREML). Regional analyses highlighted significant local genetic correlations on chromosome 11, while single variant approaches suggested widespread pleiotropic effects, especially on chromosome 11. In conclusion, our study identifies specific genetic loci and risks associated with obesity in the Korean population, emphasizing the heterogeneous genetic factors contributing to MHO and MUO.
东亚人群表现出肥胖的遗传易感性,但对这些特征的综合研究有限。我们对 93673 名韩国人进行了全基因组关联研究(GWAS),以揭示与肥胖相关的新遗传位点,研究指标包括体重指数、腰围、体脂比和腹脂比。参与者分为非肥胖、代谢健康肥胖(MHO)和代谢不健康肥胖(MUO)组。我们使用先进的计算方法,开发了一个多方面的多基因风险评分(PRS)模型来预测肥胖。我们的 GWAS 在 MHO 和 MUO 组与非肥胖组相比,发现了具有不同大小和方向的显著遗传效应。基于基因和基因集的分析,以及聚类分析,揭示了染色体 3(MUO 组)和 11(MHO 组)上显著基因的异质模式。在针对基于代谢健康的遗传易感性差异的分析中,与中 PRS 相比,高 PRS 的优势比在非肥胖和 MUO 以及非肥胖和 MHO 之间显示出显著差异。与中 PRS 相比,低 PRS 也出现了类似的模式。这些发现得到了双变量 GREML 估计遗传相关性(0.89)的支持。区域分析强调了染色体 11 上显著的局部遗传相关性,而单变异方法表明存在广泛的多效性效应,特别是在染色体 11 上。总之,我们的研究确定了韩国人群中与肥胖相关的特定遗传位点和风险,强调了导致 MHO 和 MUO 的异质遗传因素。