MicroRNAs isolated from peripheral blood in the first trimester predict spontaneous preterm birth

Area of Science:

• Reproductive Medicine
• Genomics
• Maternal-Fetal Medicine

Background:

• Spontaneous preterm birth (sPTB) is a leading cause of neonatal morbidity and mortality.
• Predictive biomarkers for sPTB are crucial, especially in high-risk populations like African Americans.
• Current prediction methods often lack accuracy or are applied too late in pregnancy.

Purpose of the Study:

• To determine if first-trimester maternal peripheral blood microRNA profiles can predict spontaneous preterm birth in an African American population.
• To assess the efficacy of microRNA quantification for early risk stratification of sPTB.

Main Methods:

• Retrospective nested case-control study involving 486 pregnant patients meeting specific criteria.
• Analysis of 45 microRNAs using real-time reverse transcription quantitative polymerase chain reaction (rt-qPCR) on first-trimester blood samples.
• Calculation of MicroRNA Risk Scores and derivation of area-under-the-curve receiver-operating-characteristic (AUC-ROC) curves for validation.

Main Results:

• The validation set demonstrated a significant AUC-ROC of 0.80 (p=0.0001) for predicting preterm birth, with 89% sensitivity and 71% specificity.
• The predictive performance remained robust across early (AUC-ROC 0.79) and late (AUC-ROC 0.81) first-trimester samples.
• Mean gestational age at blood draw was 10.0 ±1.8 weeks, highlighting early detection potential.

Conclusions:

• First-trimester peripheral blood microRNA quantification is a viable method for predicting spontaneous preterm birth risk in African American women.
• This approach allows for risk identification early in pregnancy, enabling timely interventions.
• MicroRNA profiling offers a promising non-invasive biomarker for sPTB prediction.