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Original Articles

Metabolomic identification of placental alterations in fetal growth restriction

, ORCID Icon, , , , , , , , , & ORCID Icon show all
Pages 447-456 | Received 01 May 2019, Accepted 24 Jan 2020, Published online: 10 Feb 2020
 

Abstract

Introduction

Fetal growth restriction (FGR), viz., birth weight <10th percentile is a common pregnancy complication which increases the risk of adverse fetal and newborn outcomes. The placenta is the key organ for fetal growth as it controls oxygen and nutrient availability. This study aims to elucidate the mechanisms of and identify putative placental biomarkers for FGR using high-resolution metabolomics.

Methods

Placenta samples from 19 FGR cases and 30 controls were analyzed using proton magnetic resonance (1H NMR) spectroscopy and direct flow injection mass spectrometry with reverse-phase liquid-chromatography mass spectrometry (DI-LC-MS/MS). Significant concentration differences (p-value <.05) in 179 of the 220 metabolites were measured.

Results

Of the 179 metabolites, 176 (98.3%) had reduced placental levels in FGR cases. The best performing metabolite model: 3-hydroxybutyrate, glycine and PCaaC42:0 achieved an AUC (95% CI) = 0.912 (0.814–1.000) with a sensitivity of 86.7% and specificity of 84.2% for FGR detection. Metabolite set enrichment analysis (MSEA) revealed significant (p < .05) perturbation of multiple placental metabolite pathways including urea metabolism, ammonia recycling, porphyrin metabolism, bile acid biosynthesis, galactose metabolism and perturbed protein biosynthesis.

Conclusion

The placental metabolic pathway analysis revealed abnormalities that are consistent with fetal hepatic dysfunction in FGR. Near global reduction of metabolite concentrations was found in the placenta from FGR cases and metabolites demonstrated excellent diagnostic accuracy for FGR detection.

Author contributions

RBS supervised and designed the experiment, SFG supervised all experimental procedures, PK, OT, AY, RBS, DM, AO wrote the manuscript, OT performed statistical data analysis and bioinformatics, OT, AZ performed specimen collection; PK, AY, ES, SK, JK, MA performed the experiments and analyzed the raw data, and all authors reviewed the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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