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Lipidomic profiling of amniotic fluid and its application in fetal lung maturity prediction

Authors :
Zheng Cao
Xin Xie
Min Shen
Guodong Tang
Yanhong Zhai
Xiaowei Liu
Shao-Wen Wu
Ying Dong
Lin Li
Zheng Sun
Wei Song
Jingrui Liu
Jihua Zou
Yilin Liu
Sien Zhan
Source :
Journal of Clinical Laboratory Analysis
Publication Year :
2019
Publisher :
John Wiley and Sons Inc., 2019.

Abstract

Background The pulmonary surfactant especially lipids in amniotic fluid can reflect the development stage of fetal lung maturity (FLM). However, the conventional lecithin/sphingomyelin (L/S) ratio method by thin layer chromatography (TLC) is insufficient and inconvenient for FLM prediction in clinical practice. Methods The amniotic fluid samples were collected from the pregnant women in labor or undergoing amniocentesis and analyzed for its lipid contents with the liquid chromatography coupled with high‐resolution mass spectrometry (LC‐HRMS) method and the lamellar body count (LBC) method. To reveal the lipidomic profiling of different FLM stages, three groups of amniotic fluid samples including 8 from premature group (gestational week (GW) 38) were compared with the control group (n = 6) of 18 GWs separately. Results In the FLM prediction study, the sensitivity of the LC‐HRMS method and LBC method was 91% and 73%, respectively; the specificity was 100% and 95%, respectively. The most significant metabolic pathway was linoleic acid metabolism between the premature group and the control group. Both glycerophospholipid metabolism and glycosylphosphatidylinositol‐anchor biosynthesis were enriched in the mature groups. In search of potential FLM prediction markers in amniotic fluid, 8 phosphatidylcholines, 1 sphingomyelin, and 1 phosphatidylethanolamine were significantly increased in the mature groups compared with the premature group. Conclusion An efficient LC‐HRMS method for L/S ratio in predicting FLM was established. The linoleic acid metabolism may play an important role in the fetal lung development.

Details

Language :
English
ISSN :
10982825 and 08878013
Volume :
34
Issue :
4
Database :
OpenAIRE
Journal :
Journal of Clinical Laboratory Analysis
Accession number :
edsair.doi.dedup.....fb5bc9a21ea802d28ae06293ff41b1fe