Abstract Extracellular vesicles (EVs) play important roles in cell-to-cell communication and are potential biomarkers as they carry markers of their derived tissues and disease signatures. However, obtaining pure EV preparations from biofluids is challenging due to contaminants with similar physicochemical properties. Here, we performed a meta-analysis of plasma EV proteomics data deposited in public repositories to refine the protein composition of EVs and investigate potential roles in type 1 diabetes development. With the concept that each purification method yields different proportions of distinct contaminants, we grouped proteins into clusters based on their abundance profiles. This allowed us to separate clusters with classical EV markers, such as CD9, CD40, C63 and CD81, from clusters of well-known contaminants, such as serum albumin, apolipoproteins and components of the complement and coagulation pathways. Two clusters containing a total of 1720 proteins combined were enriched with EV markers and depleted in common contaminants; therefore, they were considered to contain bona fide EV components. As possible origins of plasma EVs, these clusters had markers of tissues such as spleen, liver, brain, lungs, pancreas, and blood/immune cells. These clusters were also enriched in cell surface markers CD antigens, and proteins from cell-to-cell communication and signaling pathways, such as chemokine signaling and antigen presentation. We also show that the EV component and type 1 diabetes biomarker, platelet basic protein (PPBP/CXCL7) regulates apoptosis in both beta and macrophage cell lines. Overall, our meta-analysis refined the composition of plasma EVs, reinforcing a primary function as messengers for cell-to-cell communication and signaling. Furthermore, this analysis identifies optimal avenues to target EVs for development of disease biomarkers.

Meta-analysis refinement of plasma extracellular vesicle composition identifies proplatelet basic protein as a signaling messenger in type 1 diabetes