Clin Lab. 2020 Dec 1;66(12). doi: 10.7754/Clin.Lab.2020.200434.
The current study aims to explore the relationship between gestational diabetes mellitus (GDM) and C1q/TNF-related protein 9 (CTRP9) level in early pregnancy.
Clinical data of 63 GDM patients and 70 normal pregnant women were included in the present study. Binary logistic regression analysis was used to explore the risk factors for GDM. To determine the value of CTPR9 for predicting GDM, the area under the receiver operating characteristic curve (AUC-ROC) was analyzed. Pearson's correlation assay was performed to explore the relationship between serum CTRP9 and body mass index (BMI) or oral glucose tolerance test (OGTT).
Our data showed that the age, median maternal prepregnancy BMI, and fasting blood glucose during pregnancy of GDM group were significantly higher than those of the control group. ELISA showed the level of first-trimester serum CTRP9 was significantly decreased in GDM patients compared with that of healthy controls. Multiple logistic regression analysis showed that first-trimester serum CTRP9 and BMI were risk factors of GDM. The AUC-ROC showed that the diagnostic efficiency of CTRP9 + BMI was much higher than that of BMI alone. Moreover, first-trimester serum CTRP9 was found to be negatively correlated with BMI or OGTT in GDM patients.
Serum CTRP9 was an independent risk factor for the progression of GDM in pregnant women. Combined use of first-trimester serum CTRP9 and maternal pre-pregnancy BMI may be able to more accurately predict the occurrence of GDM.
本研究旨在探讨早孕期妊娠糖尿病(GDM)与 C1q/肿瘤坏死因子相关蛋白 9(CTRP9)水平的关系。
本研究纳入了 63 例 GDM 患者和 70 例正常孕妇的临床资料。采用二项逻辑回归分析探讨 GDM 的危险因素。为了确定 CTRP9 预测 GDM 的价值,分析了受试者工作特征曲线(ROC)下面积(AUC-ROC)。采用 Pearson 相关分析探讨血清 CTRP9 与体重指数(BMI)或口服葡萄糖耐量试验(OGTT)之间的关系。
我们的数据显示,GDM 组的年龄、中位数孕妇孕前 BMI 和孕期空腹血糖明显高于对照组。ELISA 显示,与健康对照组相比,GDM 患者的早孕期血清 CTRP9 水平明显降低。多因素逻辑回归分析显示,早孕期血清 CTRP9 和 BMI 是 GDM 的危险因素。ROC 分析显示,CTRP9+BMI 的诊断效率明显高于 BMI 单独诊断。此外,在 GDM 患者中,早孕期血清 CTRP9 与 BMI 或 OGTT 呈负相关。
血清 CTRP9 是孕妇 GDM 进展的独立危险因素。早孕期血清 CTRP9 与孕妇孕前 BMI 联合使用可能能够更准确地预测 GDM 的发生。