韩国人肥胖的遗传决定因素:探索全基因组关联和多基因风险评分。

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Jinyeon Jo, Nayoung Ha, Yunmi Ji, Ahra Do, Je Hyun Seo, Bumjo Oh, Sungkyoung Choi, Eun Kyung Choe, Woojoo Lee, Jang Won Son, Sungho Won
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引用次数: 0

摘要

东亚人有肥胖的遗传倾向,但对这些特征的全面研究却很有限。我们对 93,673 名韩国受试者进行了全基因组关联研究(GWAS),以发现与肥胖相关的新基因位点,研究指标包括体重指数、腰围、体脂比和腹脂比。参与者被分为非肥胖组、代谢健康肥胖组(MHO)和代谢不健康肥胖组(MUO)。利用先进的计算方法,我们建立了一个多方面的多基因风险评分(PRS)模型来预测肥胖。与非肥胖组相比,我们的 GWAS 在 MHO 组和 MUO 组中发现了大小和方向不同的显著遗传效应。基于基因和基因组的分析以及聚类分析揭示了 3 号染色体(MUO 组)和 11 号染色体(MHO 组)上重要基因的异质性模式。在以代谢健康为基础的遗传易感性差异分析中,高 PRS 与中等 PRS 的几率比在非肥胖与 MUO 之间以及非肥胖与 MHO 之间存在显著差异。低 PRS 与中等 PRS 相比也有类似的模式。这些发现得到了估计遗传相关性(双变量 GREML 为 0.89)的支持。区域分析强调了 11 号染色体上显著的局部遗传相关性,而单一变异方法则表明存在广泛的多向效应,尤其是在 11 号染色体上。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 的异质性遗传因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic determinants of obesity in Korean populations: exploring genome-wide associations and polygenic risk scores.

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.

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来源期刊
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
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