Characterization of Extracellular Vesicle Cargo in Sjögren's Syndrome through a SWATH-MS Proteomics Approach.
Francesco FinamoreAntonella CecchettiniElisa CeccheriniGiovanni SignoreFrancesco FerroSilvia RocchiccioliChiara BaldiniPublished in: International journal of molecular sciences (2021)
Primary Sjögren's syndrome (pSS) is a complex heterogeneous disease characterized by a wide spectrum of glandular and extra-glandular manifestations. In this pilot study, a SWATH-MS approach was used to monitor extracellular vesicles-enriched saliva (EVs) sub-proteome in pSS patients, to compare it with whole saliva (WS) proteome, and assess differential expressed proteins between pSS and healthy control EVs samples. Comparison between EVs and WS led to the characterization of compartment-specific proteins with a moderate degree of overlap. A total of 290 proteins were identified and quantified in EVs from healthy and pSS patients. Among those, 121 proteins were found to be differentially expressed in pSS, 82% were found to be upregulated, and 18% downregulated in pSS samples. The most representative functional pathways associated to the protein networks were related to immune-innate response, including several members of S100 protein family, annexin A2, resistin, serpin peptidase inhibitors, azurocidin, and CD14 monocyte differentiation antigen. Our results highlight the usefulness of EVs for the discovery of novel salivary-omic biomarkers and open novel perspectives in pSS for the identification of proteins of clinical relevance that could be used not only for the disease diagnosis but also to improve patients' stratification and treatment-monitoring. Data are available via ProteomeXchange with identifier PXD025649.
Keyphrases
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- mass spectrometry
- immune response
- prognostic factors
- machine learning
- patient reported outcomes
- dendritic cells
- replacement therapy
- minimally invasive
- cross sectional
- deep learning
- big data
- amino acid
- data analysis
- bioinformatics analysis
- combination therapy