Updated project metadata. Extracellular vesicles (EVs) are present in all body fluids. Shed by cells, their molecular make-up reflects that of their cell of origin and/or tissue pathological situation. Our working hypothesis was that analyzing the protein composition, protein abundance, and functional clustering of EVs released by peritoneal exudate cells (PECs) in the pristane experimental lupus model would allow us to identify predictive or diagnostic biomarkers that might discriminate the autoimmunity process in lupus from inflammatory reactions and/or normal physiological processes. Three pools of PE-EVs were isolated from pristane-treated mice (WT versus Cd38-/- mice) by qEV size exclusion column methodology (F5-12, F5-10 and F11-12). Protein extracts were analyzed by LC-MS/MS. Protein identification was performed with ProteinScape, and MASCOT data searching using Swiss-Prot database. For relative quantification the emPAI-based method was used. The functional enrichment analysis was based on the latest publicly available data from multiple annotation and ontology resources that can be automatically accessed through ClueGO + CluePedia apps within Cytoscape environment. STRING app and EnrichR tools were also used. Gene Ontology (GO) and signaling pathways enrichment analyses of F5-10 and F11-12 PE-EVs via ClueGO analyses showed that the proteins clustered in functionally distinct GO terms and signaling pathways. Moreover, the predominance of given GO terms in PE-EVs seemed to vary with the extent of the inflammatory/autoimmune reaction to pristane. Compared with the protein content and protein abundance in PECs (mainly Ly6Chi inflammatory monocytes and neutrophils), PE-EVs showed an enrichment in neutrophil-associated functions, in particular in PE-EVs from Cd38-/- mice.