The Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, The School of Public Health, Guilin Medical University, Guilin, 541000, China.
Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Guilin Medical University, Guilin, 541000, China.
Sci Rep. 2024 Aug 5;14(1):18123. doi: 10.1038/s41598-024-69079-y.
The aetiological mechanism of gestational diabetes mellitus (GDM) has still not been fully understood. The aim of this study was to explore the associations between functional genetic variants screened from a genome-wide association study (GWAS) and GDM risk among 554 GDM patients and 641 healthy controls in China. Functional analysis of single nucleotide polymorphisms (SNPs) positively associated with GDM was further performed. Univariate regression and multivariate logistic regression analyses were used to screen clinical risk factors, and a predictive nomogram model was established. After adjusting for age and prepregnancy BMI, rs9283638 was significantly associated with GDM susceptibility (P < 0.05). Moreover, an obvious interaction between rs9283638 and clinical variables was detected (P < 0.05). Functional analysis confirmed that rs9283638 can regulate not only target gene transcription factor binding, but it also regulates the mRNA levels of SAMD7 (P < 0.05). The nomogram model constructed with the factors of age, FPG, 1hPG, 2hPG, HbA1c, TG and rs9283638 revealed an area under the ROC curve of 0.920 (95% CI 0.902-0.939). Decision curve analysis (DCA) suggested that the model had greater net clinical benefit. Conclusively, genetic variants can alter women's susceptibility to GDM by affecting the transcription of target genes. The predictive nomogram model constructed based on genetic and clinical variables can effectively distinguish individuals with different GDM risk factors.
妊娠糖尿病（GDM）的病因机制尚未完全阐明。本研究旨在探讨在中国 554 例 GDM 患者和 641 例健康对照中，从全基因组关联研究（GWAS）筛选出的功能遗传变异与 GDM 风险之间的关联。对与 GDM 呈正相关的单核苷酸多态性（SNP）进行了功能分析。采用单变量回归和多变量逻辑回归分析筛选临床危险因素，并建立预测列线图模型。在调整年龄和孕前 BMI 后，rs9283638 与 GDM 易感性显著相关（P<0.05）。此外，还检测到 rs9283638 与临床变量之间存在明显的交互作用（P<0.05）。功能分析证实，rs9283638 不仅可以调节靶基因转录因子的结合，还可以调节 SAMD7 的 mRNA 水平（P<0.05）。用年龄、FPG、1hPG、2hPG、HbA1c、TG 和 rs9283638 等因素构建的列线图模型显示 ROC 曲线下面积为 0.920（95%CI 0.902-0.939）。决策曲线分析（DCA）表明该模型具有更大的净临床获益。总之，遗传变异可通过影响靶基因的转录改变女性对 GDM 的易感性。基于遗传和临床变量构建的预测列线图模型可有效区分具有不同 GDM 危险因素的个体。
