Gestational diabetes & diabetes in pregnancy
Integrative Proteomics–Metabolomics Profiling of Umbilical Cord Plasma With Machine Learning Reveals Candidate Biomarkers for Gestational Diabetes Mellitus
Authors' conclusion
Integrative proteomic-metabolomic profiling of umbilical cord plasma revealed coordinated immune, barrier and metabolic dysregulation in GDM, supporting exploratory multi-omics biomarker development and future mechanistic studies.
Study context
- Population
- Pregnant women; umbilical cord plasma
- Participants
- 61 women
- Comparison
- Gestational diabetes mellitus (GDM) vs normoglycemic controls
- GDMn = 34
- Normoglycemic controlsn = 27reference
- Outcome
- Discrimination of GDM by composite scores
Methodological detailshigh-resolution proteomics, untargeted metabolomics, machine learning (LASSO, random forest, XGBoost), internal validation by bootstrap resampling and repeated cross-validation, immunohistochemistry (IHC) and RT-qPCR validation
- High-resolution proteomics
- Untargeted metabolomics
- Machine learning (LASSO, random forest, XGBoost)
- Internal validation by bootstrap resampling and repeated cross-validation
- IHC and RT-qPCR validation
Main finding
As reported in the abstract
- Differentially expressed proteins
- 37
- Hub proteins: AFP, ORM1, PRSS2, LACRT, LCN1
- 5
- Composite protein score AUC
- 0.984 (95% CI 0.958-1.000)
- Differential metabolites
- 185
- Hub metabolites: C30H38O7, nicotine N-oxide, 7(1)-hydroxychlorophyll
- 3
- Composite metabolite score AUC
- 0.991 (95% CI 0.977-1.000)
Observational data: associations, not effects.
Further findings
Tissue and transcriptional validation
- IHC confirmed dysregulation of hub proteins in GDM placentas
- AFP, ORM1 and PRSS2 mRNA consistently upregulated under high glucose (RT-qPCR, HTR8/SVneo cells)
Cross-omics integration
- Exploratory proteome-metabolome network associated with cornified envelope formation, keratinisation, humoral immunity and vitamin/nucleoside transport
Original publication
Integrative Proteomics–Metabolomics Profiling of Umbilical Cord Plasma With Machine Learning Reveals Candidate Biomarkers for Gestational Diabetes Mellitus. Diabetes Obes Metab. Published 17 August 2026. doi:10.
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