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. 2024 May 18;20(3):56.
doi: 10.1007/s11306-024-02123-0.

Metabolomic prediction of severe maternal and newborn complications in preeclampsia

Jay Idler  1   2 , Onur Turkoglu  3 , Ali Yilmaz  4 , Nadia Ashrafi  4 , Marta Szymanska  5 , Ilyas Ustun  6 , Kara Patek  5 , Amy Whitten  3   4 , Stewart F Graham  4 , Ray O Bahado-Singh  3   4
Affiliations

Metabolomic prediction of severe maternal and newborn complications in preeclampsia

Jay Idler et al. Metabolomics. .

Abstract

Introduction: Preeclampsia (PreE) remains a major source of maternal and newborn complications. Prenatal prediction of these complications could significantly improve pregnancy management.

Objectives: Using metabolomic analysis we investigated the prenatal prediction of maternal and newborn complications in early and late PreE and investigated the pathogenesis of such complications.

Methods: Serum samples from 76 cases of PreE (36 early-onset and 40 late-onset), and 40 unaffected controls were collected. Direct Injection Liquid Chromatography-Mass Spectrometry combined with Nuclear Magnetic Resonance (NMR) spectroscopy was performed. Logistic regression analysis was used to generate models for prediction of adverse maternal and neonatal outcomes in patients with PreE. Metabolite set enrichment analysis (MSEA) was used to identify the most dysregulated metabolites and pathways in PreE.

Results: Forty-three metabolites were significantly altered (p < 0.05) in PreE cases with maternal complications and 162 metabolites were altered in PreE cases with newborn adverse outcomes. The top metabolite prediction model achieved an area under the receiver operating characteristic curve (AUC) = 0.806 (0.660-0.952) for predicting adverse maternal outcomes in early-onset PreE, while the AUC for late-onset PreE was 0.843 (0.712-0.974). For the prediction of adverse newborn outcomes, regression models achieved an AUC = 0.828 (0.674-0.982) in early-onset PreE and 0.911 (0.828-0.994) in late-onset PreE. Profound alterations of lipid metabolism were associated with adverse outcomes.

Conclusion: Prenatal metabolomic markers achieved robust prediction, superior to conventional markers for the prediction of adverse maternal and newborn outcomes in patients with PreE. We report for the first-time the prediction and metabolomic basis of adverse maternal and newborn outcomes in patients with PreE.

Keywords: Adverse outcomes; Mass spectrometry; Metabolomics; Nuclear magnetic resonance; Preeclampsia.

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Conflict of interest statement

SFG has received commercial support as a consultant from Biogen, Roche, Iollo and Coleman Research. The remaining authors report no conflicts of interest.

Figures

Fig. 1
Fig. 1
Volcano plots in distinguishing PreE cases with maternal and neonatal adverse outcome
Fig. 2
Fig. 2
Metabolite set enrichment analysis for the altered pathways in PreE cases with maternal and neonatal adverse outcome
See this image and copyright information in PMC

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