Extracellular vesicle RNAs reflect placenta dysfunction and are a biomarker source for preterm labour

Abstract

Preterm birth (PTB) can lead to lifelong complications and challenges. Identifying and monitoring molecular signals in easily accessible biological samples that can diagnose or predict the risk of preterm labour (PTL) in pregnant women will reduce or prevent PTBs. A number of studies identified putative biomarkers for PTL including protein, miRNA and hormones from various body fluids. However, biomarkers identified from these studies usually lack consistency and reproducibility. Extracellular vesicles (EVs) in circulation have gained significant interest in recent years as these vesicles may be involved in cell‐cell communication. We have used an improved small RNA library construction protocol and a newly developed size exclusion chromatography (SEC)‐based EV purification method to gain a comprehensive view of circulating RNA in plasma and its distribution by analysing RNAs in whole plasma and EV‐associated and EV‐depleted plasma. We identified a number of miRNAs in EVs that can be used as biomarkers for PTL, and these miRNAs may reflect the pathological changes of the placenta during the development of PTL. To our knowledge, this is the first study to report a comprehensive picture of circulating RNA, including RNA in whole plasma, EV and EV‐depleted plasma, in PTL and reveal the usefulness of EV‐associated RNAs in disease diagnosis.

Document Details

Document Type
Pub Defense Publication
Publication Date
Mar 08, 2018
Source ID
10.1111/jcmm.13570

Entities

People

  • David Baxter
  • Kai Wang
  • Kelsey Scherler
  • Leroy Hood
  • Min Young Lee
  • Oksana Shynlova
  • Shannon Fallen
  • Stephen Lye
  • Taek‐kyun Kim
  • Xiaogang Wu

Organizations

  • Institute for Systems Biology
  • Mount Sinai Hospital, Toronto
  • National Institutes of Health
  • United States Department of Defense
  • University of Toronto

Tags

Fields of Study

  • Biology

Readers

  • Molecular and genetic basis of cancer.
  • Systems Analysis and Design
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.