Lipidomic Biomarkers of Extracellular Vesicles for the Prediction of Preterm Birth in the Early Second Trimester

J Proteome Res. 2020 Oct 2;19(10):4104-4113. doi: 10.1021/acs.jproteome.0c00525. Epub 2020 Sep 22.

Abstract

Preterm birth is the leading cause of infant death worldwide and results in a high societal economic burden associated with newborn care. Recent studies have shown that extracellular vesicles (EVs) play an important role in fetal development during pregnancy. Lipids in EVs related to preterm birth remain undefined. Here, we fully investigated differences in lipids in plasma, microvesicles (MVs), and exosomes (Exos) between 27 preterm and 66 full-term pregnant women in the early second trimester (12-24 weeks) using an untargeted lipidomics approach. Independent of other characteristics of samples, we detected 97, 58, and 10 differential features (retention time (RT) and m/z) with identification in plasma, MVs, and Exos, respectively. A panel of five lipids from MVs has an area under the receiver operating characteristic curve (AUC) of 0.87 for the prediction of preterm birth. One lipid of the panel (PS (34:0)) was validated in an additional 83 plasma samples (41 preterm and 42 full-term deliveries) by the pseudotargeted lipidomics method (AUC = 0.71). Our results provide useful information about the early prediction of preterm birth, as well as a better understanding of the underlying mechanisms and intervention of preterm birth. The MS data have been deposited in the CNSA (https://db.cngb.org/cnsa/) of CNGBdb with accession code CNP0001076.

Keywords: extracellular vesicles; lipidomics; preterm birth.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers
  • Extracellular Vesicles*
  • Female
  • Humans
  • Infant, Newborn
  • Lipidomics
  • Pregnancy
  • Pregnancy Trimester, Second
  • Premature Birth* / diagnosis

Substances

  • Biomarkers