A maternal serum metabolite ratio predicts fetal growth restriction at term

Ulla Sovio*, Neil Goulding, Nancy McBride, Emma Cook, Francesca Gaccioli, D Stephen Charnock-Jones, Debbie A Lawlor, Gordon C S Smith

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

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Abstract

Fetal growth restriction (FGR) is the major single cause of stillbirth1 and is also associated with neonatal morbidity and mortality2,3, impaired health and educational achievement in childhood4,5 and with a range of diseases in later life6. Effective screening and intervention for FGR is an unmet clinical need. Here, we performed ultrahigh performance liquid chromatography–tandem mass spectroscopy (UPLC–MS/MS) metabolomics on maternal serum at 12, 20 and 28 weeks of gestational age (wkGA) using 175 cases of term FGR and 299 controls from the Pregnancy Outcome Prediction (POP) study, conducted in Cambridge, UK, to identify predictive metabolites. Internal validation using 36 wkGA samples demonstrated that a ratio of the products of the relative concentrations of two positively associated metabolites (1-(1-enyl-stearoyl)-2-oleoyl-GPC (P-18:0/18:1) and 1,5-anhydroglucitol) to the product of the relative concentrations of two negatively associated metabolites (5α-androstan-3α,17α-diol disulfate and N1,N12-diacetylspermine) predicted FGR at term. The ratio had approximately double the discrimination as compared to a previously developed angiogenic biomarker7, the soluble fms-like tyrosine kinase 1:placental growth factor (sFLT1:PlGF) ratio (AUC 0.78 versus 0.64, P = 0.0001). We validated the predictive performance of the metabolite ratio in two sub-samples of a demographically dissimilar cohort, Born in Bradford (BiB), conducted in Bradford, UK (P = 0.0002). Screening and intervention using this metabolite ratio in conjunction with ultrasonic imaging at around 36 wkGA could plausibly prevent adverse events through enhanced fetal monitoring and targeted induction of labor.
Original languageEnglish
Pages (from-to)348-353
Number of pages6
JournalNature Medicine
Volume26
DOIs
Publication statusPublished - 11 Mar 2020

Keywords

  • predictive markers
  • risk factors

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