@article{TEXTUAL,
      recid = {10033},
      author = {Vallejo, Milene C. and Sarkar, Soumyadeep and Elliott,  Emily C. and Henry, Hayden R. and Powell, Samantha M. and  Ludovico, Ivo Diaz and You, Youngki and Huang, Fei and  Payne, Samuel H. and Ramanadham, Sasanka and Sims, Emily K.  and Metz, Thomas O. and Mirmira, Raghavendra G. and  Nakayasu, Ernesto S.},
      title = {A proteomic meta-analysis refinement of plasma  extracellular vesicles},
      journal = {Scientific Data },
      address = {2023-11-28},
      number = {TEXTUAL},
      abstract = {Extracellular vesicles play major roles in cell-to-cell  communication and are excellent biomarker candidates.  However, studying plasma extracellular vesicles is  challenging due to contaminants. Here, we performed a  proteomics meta-analysis of public data to refine the  plasma EV composition by separating EV proteins and  contaminants into different clusters. We obtained two  clusters with a total of 1717 proteins that were depleted  of known contaminants and enriched in EV markers with  independently validated 71% true-positive. These clusters  had 133 clusters of differentiation (CD) antigens and were  enriched with proteins from cell-to-cell communication and  signaling. We compared our data with the proteins deposited  in PeptideAtlas, making our refined EV protein list a  resource for mechanistic and biomarker studies. As a use  case example for this resource, we validated the type 1  diabetes biomarker proplatelet basic protein in EVs and  showed that it regulates apoptosis of β cells and  macrophages, two key players in the disease development.  Our approach provides a refinement of the EV composition  and a resource for the scientific community.},
      url = {http://knowledge.uchicago.edu/record/10033},
}