First-trimester metabolomic prediction of stillbirth

<b>Background:</b> Stillbirth remains a major problem in both developing and developed countries. Omics evaluation of stillbirth has been highlighted as a top research priority. <b>Objective:</b> To identify new putative first-trimester biomarkers in maternal serum for stillbirth prediction using metabolomics-based approach. <b>Methods:</b> 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 (&lt;28 weeks and &lt;32 weeks), those related to growth restriction/placental disorder, and unexplained stillbirths were evaluated. <b>Results:</b> 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. <b>Conclusions:</b> We have identified novel biomarkers for stillbirth using metabolomics and demonstrated the feasibility of first-trimester prediction.