Decoding Preterm Birth: Non-Invasive Biomarkers and Personalized Multi-Omics Strategies

Abstract

A birth that occurs prior to 37 weeks of gestation is referred to as preterm birth (PTB). PTB is a health concern globally with significant outcomes including neonatal morbidity and mortality. Advancements in multi-omics have revolutionized the understanding of PTB pathogenesis, offering new opportunities for early prediction and risk categorization. This review highlights emerging liquid biomarkers derived from proteomic, metabolomic, genomic, transcriptomic, and epigenomic studies, emphasizing the integrative power of multi-omics approaches. Proteomic analyses have revealed key proteins in maternal and fetal compartments associated with inflammatory and extracellular matrix pathways, while metabolomics have identified lipid and metabolite profiles linked to energy metabolism and fetal development. Genomic and epigenomic studies have uncovered genetic variations and microRNAs involved in uterine contractility and immune modulation, providing novel insights into PTB's molecular underpinnings. Transcriptomic research further underscores the act of long noncoding RNAs (ncRNAs) in regulating gene expression and inflammatory responses. Multi-omics integration, coupled with machine learning models, has demonstrated superior predictive accuracy by synthesizing data across these domains, revealing intricate molecular interactions underlying PTB. Future research should prioritize longitudinal multi-omics studies to capture dynamic biological changes during pregnancy, expanding diverse population cohorts to enhance generalizability. Translating multi-omics insights into clinical practice necessitates collaborative efforts to develop cost-effective, accessible biomarker panels and establish standardized guidelines for implementation. These advancements hold the potential to transform prenatal care through personalized risk assessment and targeted preventive strategies, reducing the global burden of PTB.