Center for Reproductive Medicine, Shandong University, Jinan, 250012, Shandong, China.
Key Laboratory of Reproductive Endocrinology of Ministry of Education, Shandong University, Jinan, 250012, Shandong, China.
Inflamm Res. 2023 Apr;72(4):847-858. doi: 10.1007/s00011-023-01709-z. Epub 2023 Mar 12.
Preeclampsia (PE) is a common but serious pregnancy complication that adversely affects both maternal and fetal health. However, the mechanisms of its pathogenesis remain unclear, and effective biomarkers for early diagnosis are still lacking.
In this retrospective study, comprehensive bioinformatic analysis and logistic regression analysis were used to compare profiles of 48 serum cytokines in 27 PE patients with those in 41 normotensive pregnant subjects.
The results revealed that serum cytokine profiles accumulated to different levels between the two groups, which had significant correlations with the clinical features of PE. Nine cytokines with high discriminatory capacity for diagnosising PE (AUC ≥ 0.7) were selected for inclusion in a multivariate logistic regression model for PE and calculated as a probability diagnostic formula. This model constructed from the panel of nine cytokines had better diagnostic performance than any individual cytokine (AUC = 0.97, 95% CI 0.94-1.00, P < 0.0001), with a sensitivity of 96.30% and a specificity of 90.24%.
The set of cytokine profiles and risk assessment model described here can serve as a basis for developing early clinical diagnostic and therapeutic strategies for PE.
子痫前期(PE)是一种常见但严重的妊娠并发症,对母婴健康均有不良影响。然而,其发病机制尚不清楚,且缺乏有效的早期诊断生物标志物。
本回顾性研究采用综合生物信息学分析和逻辑回归分析,比较了 27 例 PE 患者和 41 例正常妊娠孕妇的 48 种血清细胞因子谱。
结果显示,两组血清细胞因子谱积累到不同水平,与 PE 的临床特征有显著相关性。选择 9 种具有较高诊断 PE 能力的细胞因子(AUC≥0.7)纳入多变量逻辑回归模型,计算出 PE 的概率诊断公式。该模型由 9 种细胞因子组成,其诊断性能优于任何单个细胞因子(AUC=0.97,95%CI 0.94-1.00,P<0.0001),其灵敏度为 96.30%,特异性为 90.24%。
本研究中描述的细胞因子谱集和风险评估模型可作为开发 PE 早期临床诊断和治疗策略的基础。