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Litong Zhu

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Open access Jul 2026

Integrative serum proteomic and metabolomic profiling in ovarian endometrioma: an exploratory multi-omics study

Background Ovarian endometrioma (OEM) is a common manifestation of endometriosis and is associated with both local lesions and systemic alterations. While immune dysregulation and metabolic disturbances have been individually reported in endometriosis, whether these changes are coordinated at the circulating molecular level in OEM remains unclear. Methods We performed an exploratory integrative analysis of serum proteomic and untargeted metabolomic profiles in women with OEM and healthy controls. Differential analyses were conducted for each omics layer, followed by cross-omics integration to assess pathway-level relationships between molecular alterations. Selected platelet-associated proteins were further evaluated by enzyme-linked immunosorbent assay (ELISA) in a small independent cohort. Results Serum proteomics profiling showed predominant alterations in immune-related and extracellular processes, whereas metabolomic analysis revealed changes mainly involving lipid metabolism, amino acid metabolism, and redox-related pathways. Cross-omics integration suggested pathway-level correspondence between the two omics layers, particularly in carbohydrate metabolism, nucleotide metabolism, lipid remodeling, and antioxidant defense. Among platelet-associated proteins, pro-platelet basic protein (PPBP/CXCL7) showed higher levels in OEM in both proteomic profiling and ELISA validation, while MMRN1 and PDGFA showed concordant but non-significant increases in the ELISA cohort. Conclusion These findings suggest that OEM is associated with concurrent immune-related and metabolic alterations detectable in the circulation. Integrative multi-omics analysis provides exploratory evidence for pathway-level correspondence between proteomic and metabolomic alterations in OEM and provides limited independent support for a platelet-associated circulating signal, with PPBP showing the most consistent validation.

Na Chen, Yubing Hu, Tianxia Xiao et al. · 0 citations