4.8 Article

Multiomic signals associated with maternal epidemiological factors contributing to preterm birth in low- and middle-income countries

Journal

SCIENCE ADVANCES
Volume 9, Issue 21, Pages -

Publisher

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/sciadv.ade7692

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Preterm birth is the leading cause of death in children under five, and its complex etiologies have hindered comprehensive studies. This study used multiomic profiling and multivariate modeling to investigate the biological signatures of maternal characteristics associated with preterm birth. Machine learning models showed reliable predictive performance for preterm birth, time-to-delivery, maternal age, gravidity, and BMI. Biological correlates of time-to-delivery included fetal-associated proteins and immune proteins, while maternal age, gravidity, and BMI were correlated with specific proteins and molecules related to collagen, endothelial function, inflammation, and metabolic regulation.
Preterm birth (PTB) is the leading cause of death in children under five, yet comprehensive studies are hindered by its multiple complex etiologies. Epidemiological associations between PTB and maternal characteristics have been previously described. This work used multiomic profiling and multivariate modeling to investigate the biological signatures of these characteristics. Maternal covariates were collected during pregnancy from 13,841 pregnant women across five sites. Plasma samples from 231 participants were analyzed to generate pro-teomic, metabolomic, and lipidomic datasets. Machine learning models showed robust performance for the prediction of PTB (AUROC = 0.70), time-to-delivery (r = 0.65), maternal age (r = 0.59), gravidity (r = 0.56), and BMI (r = 0.81). Time-to-delivery biological correlates included fetal-associated proteins (e.g., ALPP, AFP, and PGF) and immune proteins (e.g., PD-L1, CCL28, and LIFR). Maternal age negatively correlated with collagen COL9A1, gravidity with endothelial NOS and inflammatory chemokine CXCL13, and BMI with leptin and structural protein FABP4. These results provide an integrated view of epidemiological factors associated with PTB and identify biological signatures of clinical covariates affecting this disease.

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