OBJECTIVE: The aim of this study was to characterize and compare the proteome in whole saliva, plasma, and salivary gland tissue in patients with primary Sjögren's syndrome (pSS) and patients having symptoms of pSS, but not fulfilling the classification criteria, and to search for diagnostic biomarker candidates for pSS.

METHODS: Liquid chromatography tandem mass spectrometry was conducted on whole saliva, plasma, and labial salivary gland tissue samples from 24 patients with pSS and 16 non-Sjögren control subjects (non-pSS). Gene Ontology (GO)-terms and Kyoto Encyclopedia of Genes and Genomes (KEGG)-pathways were applied for functional annotation.

RESULTS: 1013 proteins were identified in whole saliva, 219 in plasma, and 3166 in salivary gland tissue. In saliva, 40 proteins differed significantly between the two groups. In pSS, proteins involved in immunoinflammatory processes were upregulated, whereas proteins related to salivary secretion were downregulated. The combination of neutrophil elastase, calreticulin, and tripartite motif-containing protein 29 yielded a receiver-operating characteristic (ROC) value of 0.97 (CI 0.93-1.00). Protein expression in plasma and salivary gland tissue did not differ between the patient groups.

CONCLUSION: The salivary proteome of patients with pSS differed from that of non-pSS patients, indicating that saliva proteomics represents a promising non-invasive diagnostic tool for pSS.

SIGNIFICANCE: Primary Sjögren's syndrome (pSS) is a chronic systemic autoimmune disease, which clinically may present with a wide variety of symptoms and signs. Symptoms of dry eyes and dry mouth due to lacrimal and salivary gland dysfunction are prominent, but not pathognomonic, and an extensive diagnostic work-up including blood tests and labial salivary gland biopsy is often required to distinguish pSS from non-pSS. In this study, we used high throughput proteomics and identified a non-invasive biomarker candidate comprising a combination of three different upregulated salivary proteins, which enables differentiation between patients with pSS and non-pSS patients with an accuracy of 97%. In the future, this could contribute to earlier, more accurate and less costly diagnosis of pSS.