ArticleBMC pregnancy and childbirth2026
Quantitative proteomic profiling of placental extracellular vesicles in recurrent pregnancy loss reveals their role in feto-maternal crosstalk.
Article in BMC pregnancy and childbirth, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Recurrent pregnancy loss (RPL) remains a devastating outcome for many women, with up to 40–60% of cases classified as unexplained despite extensive clinical workup. During pregnancy, extracellular vesicles (EVs) from the placenta enters into maternal circulation and plays a vital role in completion of a successful pregnancy. Profiling of EVs cargo proteins offers a promising avenue for the pathophysiology of RPL, with the potential to revolutionize diagnosis, prognosis, and treatment strategies. Blood samples were collected from 5 pregnant women with history of RPL and 5 gestational aged-matched healthy pregnant controls. EVs were extracted from plasma and characterized for their size, morphology, number and presence of surface markers. Further, liquid chromatography-tandem mass spectrometry (LC–MS/MS) analysis of EV protein was performed to identify differentially expressed proteins (DEPs). In total 508 proteins with unique peptides were identified. Among these 330 proteins were differentially expressed between patients and controls, out of which 94 were significantly expressed (p < 0.05). Based on the expression pattern, 25 proteins were upregulated (log2FC > 1, P < 0.05) and 69 were downregulated. GO enrichment and KEGG pathway enrichment indicated involvement of pathways such as innate immune response, neutrophil degranulation, complement cascade regulation and intrinsic pathway of fibrin clot formation. Protein-protein interaction analysis identified 10 hub proteins (APOH, APOB, APOA1, APOA2, AHSG, TTR, A2M, SERPINC1, ALB, FGB) potentially implicated in RPL pathophysiology. While preliminary, this study provides molecular insights into EV-associated proteins in RPL and highlights potential biomarkers for future validation.
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