First-trimester metabolomic prediction of stillbirth. (18th October 2019)

• Record Type: Journal Article
• Authors: Bahado-Singh, Ray O.; Syngelaki, Argyro; Mandal, Rupsari; Han, BeomSoo; Li, Liang; Bjorndahl, Trent C.; Wang, Nan; Maulik, Dev; Dong, Edison; Turkoglu, Onur; Tseng, Chiao-Li; Zeb, Amna; Redman, Mark; Wishart, David S.; Nicolaides, Kypros H.
• Is Part Of: Journal of maternal-fetal & neonatal medicine. Volume 32:Number 20(2019)
• Page Start: 3435
• Page End: 3441
• Publication Date: 2019-10-18
• Subjects: Stillbirth prediction -- metabolomics -- nuclear magnetic resonance -- mass spectrometry -- metabolites; Obstetrics -- Periodicals; Perinatology -- Periodicals; Infants (Newborn) -- Diseases -- Periodicals; Neonatology -- Periodicals; 618.2
• DOI: 10.1080/14767058.2018.1465552
• Languages: English
• ISSNs: 1476-7058

Abstract

Abstract: Background: Stillbirth remains a major problem in both developing and developed countries. Omics evaluation of stillbirth has been highlighted as a top research priority. Objective: To identify new putative first-trimester biomarkers in maternal serum for stillbirth prediction using metabolomics-based approach. Methods: Targeted, nuclear magnetic resonance (NMR) and mass spectrometry (MS), and untargeted liquid chromatography-MS (LC-MS) metabolomic analyses were performed on first-trimester maternal serum obtained from 60 cases that subsequently had a stillbirth and 120 matched controls. Metabolites by themselves or in combination with clinical factors were used to develop logistic regression models for stillbirth prediction. Prediction of stillbirths overall, early (<28 weeks and <32 weeks), those related to growth restriction/placental disorder, and unexplained stillbirths were evaluated. Results: Targeted metabolites including glycine, acetic acid, L -carnitine, creatine, lysoPCaC18:1, PCaeC34:3, and PCaeC44:4 predicted stillbirth overall with an area under the curve [AUC, 95% confidence interval (CI)] = 0.707 (0.628–0.785). When combined with clinical predictors the AUC value increased to 0.740 (0.667–0.812). First-trimester targeted metabolites also significantly predicted early, unexplained, and placental-related stillbirths. Untargeted LC-MS features combined with other clinical predictors achieved an AUC (95%CI) = 0.860 (0.793–0.927) for the prediction of stillbirths overall. We found novel preliminary evidence that, verruculotoxin, a toxin produced by common household molds, might be linked to stillbirth. Conclusions: We have identified novel biomarkers for stillbirth using metabolomics and demonstrated the feasibility of first-trimester prediction.