Clinical expression of SS shows considerable interpatient heterogeneity. Thus, the aim of this study was to assess whether individual salivary proteomic profiles provide a framework for identification of disease-phenotype-driven biomarker signatures.
Using a 187-plex capture antibody-based assay, proteomic biomarker profiles from unstimulated whole saliva were generated from a SS-cohort representing six clinically distinct disease phenotypes. Discriminant function analyses identified the most powerful biomarker signatures for correct recapitulation of each patient's status with respect to hyposalivation and histopathological features of salivary gland inflammation. In addition, gene ontology-based network analyses allowed systematic interpretation of the molecular patterns underlying these specific disease features.
Presentation of hyposalivation was associated with significant alteration in 22 out of 119 reliably detectable biomarkers. Thereof, a 4-plex signature allowed accurate prediction of salivary gland function for >80% of the cases. With respect to histopathological features, the most distinct profiles were identified in conjunction with ectopic germinal centres. Selected from the 13 analytes relevant here, pregnancy-associated plasma protein A, thrombospondin 1 and peptide YY would recapitulate the presence or absence of tertiary lymphoid organization for 93.8% of the patients. Whereas functional annotation of alterations associated with hyposalivation identified the IL1 system as a dominant pro-inflammatory component, changes observed in context with ectopic lymphoid organization revealed specific shifts in chemotactic profiles and altered regulation of apoptotic processes.
Multivariate analyses of a patient's salivary proteome could reliably recapitulate specific aspects of SS disease. Accessible and repetitively collectable, such biomarker signatures harbour great potential for patient subclassification and subsequent follow-up.