Department of Biomedical Science, Hallym University, Chuncheon 24252, Republic of Korea.
Int J Mol Sci. 2023 Jul 17;24(14):11560. doi: 10.3390/ijms241411560.
Hundreds of genetic variants for body mass index (BMI) have been identified from numerous genome-wide association studies (GWAS) in different ethnicities. In this study, we aimed to develop a polygenic risk score (PRS) for BMI for predicting susceptibility to obesity and related traits in the Korean population. For this purpose, we obtained base data resulting from a GWAS on BMI using 57,110 HEXA study subjects from the Korean Genome and Epidemiology Study (KoGES). Subsequently, we calculated PRSs in 13,504 target subjects from the KARE and CAVAS studies of KoGES using the PRSice-2 software. The best-fit PRS for BMI (PRS) comprising 53,341 SNPs was selected at a -value threshold of 0.064, at which the model fit had the greatest score. The PRS was tested for its association with obesity-related quantitative traits and diseases in the target dataset. Linear regression analyses demonstrated significant associations of PRS with BMI, blood pressure, and lipid traits. Logistic regression analyses revealed significant associations of PRS with obesity, hypertension, and hypo-HDL cholesterolemia. We observed about 2-fold, 1.1-fold, and 1.2-fold risk for obesity, hypertension, and hypo-HDL cholesterolemia, respectively, in the highest-risk group in comparison to the lowest-risk group of PRS in the test population. We further detected approximately 26.0%, 2.8%, and 3.9% differences in prevalence between the highest and lowest risk groups for obesity, hypertension, and hypo-HDL cholesterolemia, respectively. To predict the incidence of obesity and related diseases, we applied PRS to the 16-year follow-up data of the KARE study. Kaplan-Meier survival analysis showed that the higher the PRS, the higher the incidence of dyslipidemia and hypo-HDL cholesterolemia. Taken together, this study demonstrated that a PRS developed for BMI may be a valuable indicator to assess the risk of obesity and related diseases in the Korean population.
数百个与体重指数（BMI）相关的遗传变异已从不同种族的全基因组关联研究（GWAS）中得到鉴定。在这项研究中，我们旨在为韩国人群开发一种用于预测肥胖易感性和相关特征的 BMI 多基因风险评分（PRS）。为此，我们从韩国基因组与流行病学研究（KoGES）的 HEXA 研究中获得了基于 57110 个个体的 BMI GWAS 的基础数据。随后，我们使用 PRSice-2 软件在 KoGES 的 KARE 和 CAVAS 研究中的 13504 个目标个体中计算了 PRS。选择最佳拟合 BMI（PRS）的 PRS 由 53341 个 SNP 组成，其 P 值阈值为 0.064，在此模型拟合度的得分最高。在目标数据集中，对 PRS 与肥胖相关的定量特征和疾病的相关性进行了测试。线性回归分析表明，PRS 与 BMI、血压和血脂特征显著相关。逻辑回归分析表明，PRS 与肥胖、高血压和低 HDL 血症显著相关。在测试人群中，与 PRS 最低风险组相比，PRS 最高风险组的肥胖、高血压和低 HDL 血症的风险分别增加了约 2 倍、1.1 倍和 1.2 倍。我们还检测到肥胖、高血压和低 HDL 血症的最高风险组和最低风险组之间的患病率差异分别约为 26.0%、2.8%和 3.9%。为了预测肥胖和相关疾病的发生率，我们将 PRS 应用于 KARE 研究的 16 年随访数据。Kaplan-Meier 生存分析表明，PRS 越高，血脂异常和低 HDL 血症的发生率越高。综上所述，这项研究表明，为 BMI 开发的 PRS 可能是评估韩国人群肥胖和相关疾病风险的一个有价值的指标。
