Related Experiment Video
Updated: Aug 7, 2025
Author Spotlight: Modeling an Aspect of Preeclampsia in Female Mice Using Hypoxic Human Placenta-Derived Small Extracellular Vesicles
Published on: January 26, 2024
Distinct cytokine profiles in patients with preeclampsia
Ling Guo1,2,3, Xiangxin Lan1,2,3, Shanshan Liu4
1Center for Reproductive Medicine, Shandong University, Jinan, 250012, Shandong, China.
Insights
A new diagnostic model using nine serum cytokines shows high accuracy in identifying preeclampsia (PE), a serious pregnancy complication. This offers potential for earlier diagnosis and treatment strategies for PE.
Area of Science:
- Obstetrics and Gynecology
- Immunology
- Biomarker Discovery
Background:
- Preeclampsia (PE) is a significant pregnancy complication impacting maternal and fetal health.
- Current understanding of PE pathogenesis is incomplete, and early diagnostic biomarkers are lacking.
Purpose of the Study:
- To identify serum cytokine profiles associated with preeclampsia.
- To develop a predictive diagnostic model for early preeclampsia detection.
Main Methods:
- Retrospective analysis of serum cytokine profiles in preeclampsia patients and normotensive controls.
- Utilized comprehensive bioinformatic and logistic regression analyses.
- Selected nine cytokines with high discriminatory capacity (AUC ≥ 0.7) for model development.
Main Results:
- Serum cytokine profiles differed significantly between preeclampsia and control groups.
- A multivariate logistic regression model incorporating nine cytokines demonstrated high diagnostic performance (AUC = 0.97).
- The model achieved 96.30% sensitivity and 90.24% specificity for preeclampsia diagnosis.
Conclusions:
- A panel of nine serum cytokines and a derived risk assessment model show promise for preeclampsia diagnosis.
- This approach can form the foundation for developing early clinical diagnostic and therapeutic strategies for preeclampsia.
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.
