Liang Qiulian, Sun Yan, Li Ming, Li Ruiqi, Nie Lijie, Lin Lin, Yu Xiangyuan
School of Public Health and Guangxi Key Laboratory of Diabetic Systems Medicine, Guilin Medical University, Guilin, China.
Department of Histology and Embryology, School of Basic Medicine, Hunan University of Medicine, Huaihua, China.
Front Endocrinol (Lausanne). 2024 Dec 24;15:1476222. doi: 10.3389/fendo.2024.1476222. eCollection 2024.
Gestational diabetes mellitus (GDM) is a complex metabolic disease that has short-term and long-term adverse effects on mothers and infants. However, the specific pathogenic mechanism has not been elucidated.
The aim of this study was to confirm the associations between candidate genetic variants (rs4134819, rs720918, rs2034410, rs11109509, and rs12524768) and GDM risk and prediction in a southern Chinese population.
Candidate variants were genotyped in 538 GDM cases and 626 healthy controls. The odds ratio (OR) and its corresponding 95% confidence interval (CI) were calculated to assess the associations between genotypes and GDM risk. Then, the false-positive report probability (FPRP) analysis was adopted to confirm the significant associations, and bioinformatics tools were used to explore the potential biological function of studied variants. Finally, risk factors of genetic variants and clinical indicators identified by logistics regression were used to construct a nomogram model for GDM prediction.
It was shown that the gene rs4134819 was significantly associated with GDM susceptibility (CT vs. CC: adjusted OR = 1.38, 95% CI: 1.01-1.87, = 0.044; CT/TT vs. CC: crude OR = 1.42, 95% CI: 1.08-1.86, = 0.013). Functional analysis suggested that rs4134819 can alter the specific transcription factors (CPE bind and GATE-1) binding to the promoter of the gene, regulating the transcription of . The nomogram established with factors such as age, FPG, HbA1c, 1hPG, 2hPG, TG, and rs4134819 showed a good discriminated and calibrated ability with an area under the curve (AUC) = 0.931 and a Hosmer-Lemeshow test -value > 0.05.
The variant rs4134819 can significantly alter the susceptibility of the Chinese population to GDM possibly by regulating the transcription of functional genes. The nomogram prediction model constructed with genetic variants and clinical factors can help distinguish high-risk GDM individuals.
妊娠期糖尿病（GDM）是一种复杂的代谢性疾病，对母婴有短期和长期的不良影响。然而，其具体致病机制尚未阐明。
本研究旨在证实候选基因变异（rs4134819、rs720918、rs2034410、rs11109509和rs12524768）与中国南方人群GDM风险及预测之间的关联。
对538例GDM患者和626例健康对照进行候选变异基因分型。计算比值比（OR）及其相应的95%置信区间（CI），以评估基因型与GDM风险之间的关联。然后，采用假阳性报告概率（FPRP）分析来确认显著关联，并使用生物信息学工具探索所研究变异的潜在生物学功能。最后，将通过逻辑回归确定的基因变异风险因素和临床指标用于构建GDM预测的列线图模型。
结果显示，基因rs4134819与GDM易感性显著相关（CT与CC：调整后的OR = 1.38，95% CI：1.01 - 1.87，P = 0.044；CT/TT与CC：粗OR = 1.42，95% CI：1.08 - 1.86，P = 0.013）。功能分析表明，rs4134819可改变与该基因启动子结合的特定转录因子（CPE结合和GATE - 1），从而调节该基因的转录。由年龄、空腹血糖（FPG）、糖化血红蛋白（HbA1c）、1小时血糖（1hPG）、2小时血糖（2hPG）、甘油三酯（TG）和rs4134819等因素建立的列线图显示出良好的区分和校准能力，曲线下面积（AUC） = 0.931，Hosmer - Lemeshow检验P值> 0.05。
变异rs4134819可能通过调节功能基因的转录显著改变中国人群对GDM的易感性。由基因变异和临床因素构建的列线图预测模型有助于区分GDM高危个体。
