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Predictive Metabolomic Markers in Early to Mid-Pregnancy for Gestational Diabetes: A Prospective Test and Validation Study

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posted on 10.05.2022, 19:47 by Yeyi Zhu, Dinesh K Barupal, Amanda L Ngo, Charles P Quesenberry, Juanran Feng, Oliver Fiehn, Assiamira Ferrara

 Gestational diabetes (GDM) predisposes pregnant individuals to perinatal complications and long-term diabetes and cardiovascular diseases. We developed and validated metabolomic markers for GDM in a prospective test-validation study. In a case-control sample within the PETALS cohort (91 GDM, 180 non-GDM; discovery set), a random PETALS subsample (42 GDM, 372 non-GDM; validation set 1), and a case-control sample within the GLOW trial (35 GDM, 70 non-GDM; validation set 2), fasting serum untargeted metabolomics were measured by gas chromatography/time-of-flight mass spectrometry. Multivariate enrichment analysis examined metabolites-GDM associations. Ten-fold cross-validated LASSO regression identified predictive metabolomic markers at gestational weeks (GW) 10-13 and 16-19 for GDM. The purinone metabolites at GW 10-13 and 16-19, and the amino acids, amino alcohols, hexoses, indoles, and pyrimidines metabolites at GW 16-19 were positively associated with GDM risk (FDR <0.05). A 17-metabolite panel at GW 10-13 outperformed the model using conventional risk factors including fasting glycemia (discovery AUC: 0.871 vs. 0.742; validation 1: 0.869 vs. 0.731; validation 2: 0.972 vs. 0.742; P <0.01). Similar results were observed for a 13-metabolite panel at GW 17-19. Dysmetabolism is present early in pregnancy among individuals progressing to GDM. Multi-metabolite panels in early pregnancy can predict GDM risk beyond conventional risk factors.  

Funding

The research was supported by the US National Institutes of Health Building Interdisciplinary Research Careers in Women's Health (BIRCWH) Program (grant K12HD052163) to YZ, National Institute of Diabetes and Digestive and Kidney Diseases (grant K01DK120807) to YZ, National Institute of Environmental Health Sciences (grant R01ES019196) to AF, National Institute of Child Health and Human Development (grant R01HD073572) to AF, and National Institutes of Health Office of Directors (grants UG3OD023289 and UH3OD023289) to AF. DKB was supported by National Institute of Environmental Health Sciences (grants U2CES026561, U2CES026555, P30ES023515, and U2CES030859) and National Center for Advancing Translational Sciences (grant UL1TR001433). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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