ArticleBioengineering & translational medicine2024
Predicting the onset of preeclampsia by longitudinal monitoring of metabolic changes throughout pregnancy with Raman spectroscopy.
Article in Bioengineering & translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 12 citations in OpenAlex.
- A targeted metabolic intervention via exercise applied after vaccination shapes kinetics and durability of serum antibody accompanied by a distinct immunometabolic signature: pilot study.Brain, behavior, & immunity - health · 2026Article
- Metabolic and proteomic signatures differentiate inflammatory phenotypes from cancer and predict treatment response in patient sera.Bioengineering & translational medicine · 2025Article
- Diagnosis of pregnancy disorder in the first-trimester patient plasma with Raman spectroscopy and protein analysis.Bioengineering & translational medicine · 2024Article
- Metabolic Response to Small Molecule Therapy in Colorectal Cancer Tracked with Raman Spectroscopy and Metabolomics.Angewandte Chemie (International ed. in English) · 2024Article
- Predicting the onset of preeclampsia by longitudinal monitoring of metabolic changes throughout pregnancy with Raman spectroscopy.Bioengineering & translational medicine · 2024Article
- First Trimester Prediction of Preterm Birth in Patient Plasma with Machine-Learning-Guided Raman Spectroscopy and Metabolomics.ACS applied materials & interfaces · 2023Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
Preeclampsia is a life-threatening pregnancy disorder. Current clinical assays cannot predict the onset of preeclampsia until the late 2nd trimester, which often leads to poor maternal and neonatal outcomes. Here we show that Raman spectroscopy combined with machine learning in pregnant patient plasma enables rapid, highly sensitive maternal metabolome screening that predicts preeclampsia as early as the 1st trimester with >82% accuracy. We identified 12, 15 and 17 statistically significant metabolites in the 1st, 2nd and 3rd trimesters, respectively. Metabolic pathway analysis shows multiple pathways corresponding to amino acids, fatty acids, retinol, and sugars are enriched in the preeclamptic cohort relative to a healthy pregnancy. Leveraging Pearson's correlation analysis, we show
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Registered trials
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