Development of a Preterm Birth Risk Prediction Model Based on CCL28 Biomarker Selection and Multidimensional Data...

Area of Science:

• Reproductive biology
• Biomarker discovery
• Clinical proteomics

Background:

• Preterm birth (PTB) remains a leading cause of neonatal morbidity and mortality.
• Accurate prediction of PTB is crucial for timely clinical intervention.
• Identifying novel biomarkers and integrating them into predictive models is essential.

Purpose of the Study:

• To identify novel biomarkers for preterm birth (PTB).
• To develop a multidimensional risk prediction model for PTB.
• To investigate the role of CCL28 as a potential PTB biomarker.

Main Methods:

• Plasma and placental samples from pregnant women were analyzed using OLINK proteomics and ELISA.
• Immunohistochemistry was used to assess CCL28 expression in placental tissue.
• Logistic regression and nomogram modeling were employed for risk prediction, with ROC analysis for performance evaluation.

Main Results:

• Significantly lower plasma CCL28 levels were observed in the PTB group compared to the term birth (TB) group (p < 0.01).
• Reduced CCL28 expression was confirmed in placental tissues of PTB cases.
• CCL28 was identified as an independent predictor of PTB (OR = 0.150, p = 0.01).
• The integrated nomogram model, including CCL28, showed strong predictive performance (AUC = 0.841).

Conclusions:

• CCL28 is a significant biomarker for predicting preterm birth.
• An integrated prediction model incorporating CCL28 enhances early risk assessment for PTB.
• This model offers a valuable tool for targeted clinical interventions in high-risk pregnancies.