First Trimester Prediction of Preterm Birth in Patient Plasma with Machine-Learning-Guided Raman Spectroscopy and Metabolomics.

ABSTRACT: Preterm birth (PTB) is the leading cause of infant deaths globally. Current clinical measures often fail to identify women who may deliver preterm. Therefore, accurate screening tools are imperative for early prediction of PTB. Here, we show that Raman spectroscopy is a promising tool for studying biological interfaces, and we examine differences in the maternal metabolome of the first trimester plasma of PTB patients and those that delivered at term (healthy). We identified fifteen statistically significant metabolites that are predictive of the onset of PTB. Mass spectrometry metabolomics validates the Raman findings identifying key metabolic pathways that are enriched in PTB. We also show that patient clinical information alone and protein quantification of standard inflammatory cytokin

SUBMITTER: Synan L 

PROVIDER: S-EPMC10625673 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature