Objectives: Stratification approaches are vital to address clinical heterogeneity in Sjogren's syndrome (SS). We previously described that the Newcastle Sjogren's Stratification Tool (NSST) identified four distinct clinical subtypes of SS. We performed proteomic and network analysis to analyse the underlying pathobiology and highlight potential therapeutic targets for different SS subtypes.
Method: We profiled serum proteins using O-link technology of 180 SS subjects. We used 5 O-link proteomics panels which included a total of 454 unique proteins. Network reconstruction was performed using the ARACNE algorithm, with differential expression estimates overlaid on these networks to reveal the key subnetworks of differential expression. Furthermore, data from a phase III trial of tocilizumab in SS were reanalysed by stratifying patients at baseline using NSST.
Results: Our analysis highlights differential expression of chemokines, cytokines and the major autoantigen TRIM21 between the SS subtypes. Furthermore, we observe differential expression of several transcription factors associated with energy metabolism and redox balance namely APE1/Ref-1, FOXO1, TIGAR and BACH1. The differentially expressed proteins were inter-related in our network analysis, supporting the concept that distinct molecular networks underlie the clinical subtypes of SS. Stratification of patients at baseline using NSST revealed improvement of fatigue score only in the subtype expressing the highest levels of serum IL-6.
Conclusions: Our data provide clues to the pathways contributing to the glandular and non-glandular manifestations of SS and to potential therapeutic targets for different SS subtypes. In addition, our analysis highlights the need for further exploration of altered metabolism and mitochondrial dysfunction in the context of SS subtypes.
Keywords: Autoantibodies; Autoimmune Diseases; Inflammation; Patient Reported Outcome Measures; Sjogren's Syndrome.
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