Predictive Value of Maternal Blood Protein Signatures in Preterm Birth

Accurate prediction of preterm birth is critical for clinical management to improve the neonatal and maternal outcomes. A clinical challenge remains for current predicting biomarkers due to the complexity and multifactorial nature of underlying causes of preterm birth.

This study aims to evaluate the prediction performance of new maternal blood biomarkers (proteomic markers) on the occurrence of preterm birth.

Preterm birth (PTB), defined by delivery before 37 weeks of gestational age, represents a substantial public health challenge due to its elevated rates of neonatal morbidity and mortality worldwide. The prevalence of PTB exhibits variation, ranging from approximately 12-13% in the USA to 5-9% in other developed nations, underscoring a complex issue marked by regional disparities.

Emphasizing its significant public health ramifications, PTB is recognized as a primary contributor to mortality among children under five, particularly with 40% of deaths occurring within the first month of life in this demographic. Following PTB, infants face an increased vulnerability to severe complications like respiratory distress syndrome, intraventricular hemorrhage, and necrotizing enterocolitis, accentuating the acute threats to infant well-being and longevity. Addressing these early-life hurdles requires the formulation of robust strategies for prediction and prevention to alleviate the immediate hazards linked with premature birth.

Preventing PTB crucially depends on accurately identifying women at high risk. Interventions like vaginal progesterone and cervical cerclage are recommended for those with a short cervical length. However, the effectiveness of these strategies is frequently compromised by limitations in current screening methods, which struggle to accurately predict PTB. This underscores a significant gap in effectively identifying all at-risk women, underscoring the necessity for enhanced screening techniques to more precisely pinpoint women who would benefit from preventive interventions.

Current screening methods, primarily based on measuring cervical length and assessing historical risk factors, are inadequate in capturing the multifaceted nature of PTB risk, leading to missed opportunities for intervention and prevention. This inadequacy underscores the importance of developing methods that can more accurately identify women at high risk. Research efforts aimed at addressing these challenges suggest the potential of integrating new biomarkers and maternal characteristics into screening protocols to improve the predictive accuracy of PTB screenings.

Building upon the premise that the placenta plays a pivotal role in fetal health regulation, and that insights into the pathologic mechanisms leading to spontaneous preterm birth can be gleaned from the placental transcriptome, the investigators utilized existing transcriptomic data from the public domain, employing bioinformatics methodologies. This data was further complemented by quantitative proteomics analysis techniques using mass spectrometry. Through this integrated approach, the investigators have developed a novel PTB screening panel comprising three protein biomarkers. The efficacy and prediction performance of this three-protein predictor will be evaluated in this study with independent cohorts.

Eligibility Criteria:
Inclusion Criteria:

* Pregnant women between18 and 45 years of age
* Single pregnancy
* Consent to participate in the study

Exclusion Criteria:

* Premature rupture of membranes
* Uterine malformation
* Fetal malformation
* Pregestational Diabetes
* Systemic diseases (chronic kidney disease, autoimmune disease, etc.)
* Serious medical illness (renal insufficiency, congestive heart disease, chronic respiratory insufficiency, etc.).
* Suffering from other disease unfavorable to the trial such as metal illness
* Any maternal or fetal condition that requires termination of pregnancy.
* Active vaginal bleeding.
* Multifetal pregnancy with greater than or equal to 2 fetuses.
* Lack of clinical outcome or incomplete basic information
* Iatrogenic premature delivery or induced labor
* Lack of consent.