Untargeted metabolomics for the early detection of preeclampsia: A systematic review of human studies - Celia García-Mañas; María Dolores Jara Montes; Ana Cristina Abreu; Manuel A. Rodríguez Maresca; Ignacio Fernández; Ana Maria Fernandez Alonso (PLoS ONE, 2026)
This systematic review synthesizes current evidence on metabolomics-based biomarkers for the early prediction or diagnosis of preeclampsia and highlights promising candidates with potential clinical application. Following PRISMA guidelines, a comprehensive search was performed in PubMed, Cochrane Library, Web of Science, and ClinicalTrials.gov up to September 2024, using predefined terms related to preeclampsia, metabolomics, and pregnancy. Study selection and risk of bias assessment were conducted with CADIMA, applying PICO-based inclusion criteria and predefined quality appraisal standards. Of 112 records identified, 16 were duplicates, 57 were excluded after title and abstract screening, and 31 after full-text review, leaving 12 studies for inclusion. These comprised cohort, case–cohort, case–control, validation, prospective control, and translational designs. Data extraction captured study characteristics, populations, methodologies, biological matrices, and main findings. Considerable heterogeneity was observed across studies, with limited overlap in identified metabolites. Nonetheless, alanine was reported in serum, lactate was observed in both serum and urine, and glutamate and glutamine were detected across serum, plasma, and placental tissue. These metabolites, interconnected through the Cori and glucose–alanine cycles, have been linked to hepatic dysfunction, immune regulation, and excitotoxicity. Overall, metabolomics shows strong potential as a sensitive tool for biomarker discovery in preeclampsia, though further research is required to confirm findings, improve reproducibility, and integrate metabolomic data with clinical parameters to support personalized medicine approaches. Systematic review registration PROSPERO, CRD42024540619.