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

ABSTRACT: 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 proteomic, 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 = 0.8

SUBMITTER: Espinosa CA 

PROVIDER: S-EPMC10208584 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature