Objective: 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.
Methods: 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.
Results: 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%.
Conclusions: 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.
Keywords: Cytokines; Inflammation; Preeclampsia; Pregnancy.
© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.