ANALYSIS OF THE PLASMA PROTEOME PROVIDES MECHANISTIC INSIGHTS INTO THE PATHOPHYSIOLOGY OF ANCA-ASSOCIATED VASCULITIS

E. Hellbacher, V. Van Hoef, A. Johansson, A. Knight, I. Gunnarsson, A. Bruchfeld, P. Eriksson, S. Olsson, A. J. Mohammad, A. Soderbergh, E. Berglin, S. Rantapää Dahlqvist, J. DahlqvistUppsala University, Department of Medical Sciences, Uppsala, Sweden Uppsala University, NBIS Science for Life Laboratory, Uppsala, Sweden Karolinska Institutet, Department of Medicine, Stockholm, Sweden Linköping University, Department of Medical and Health Sciences, Linköping, Sweden Linköping University, Department of Biomedical and Clinical Sciences, Linköping, Sweden Lund University and Skåne University Hospital, Department of Clinical Sciences, Lund, Sweden Örebro University Hospital, Department of Rheumatology, Örebro, Sweden Umeå University, Department of Public Health and Clinical Medicine, Umeå, Sweden  Background The pathogenesis of ANCA-associated vasculitis (AAV) remains largely unknown. Proteinase 3 (PR3)- and myeloperoxidase (MPO)-AAV are two cateogories of AAV with distinct genetic background, but mechanistic differences between the two are poorly characterized. We hypothesized that in-depth studies of the plasma proteome in patients with active AAV would provide clues to the molecular and cellular mechanisms behind these disorders. Objectives To improve our understanding of the disease mechanisms behind AAV and pathophysiological differences between PR3- and MPO-AAV. Methods Plasma samples were collected at six Swedish rheumatological and/or nephrological centers from 42 PR3-AAV- and 25 MPO-AAV patients with active disease prior to commencement of therapy and from 138 healthy matched controls. All patients were classified into granulomatosis with polyangiitis or microscopic polyangiitis according to the European Medicines Agency algorithm. Samples were analysed for the relative levels of 181 proteins associated with inflammation or cardiovascular disease, using proximity extension assay (OLINK Proteomics). Differentially expressed proteins (DEPs) between groups were analyzed using ANOVA, where proteins with a fold change ≥ 1.5 and adjusted P value < 0.05 were considered as significant DEPs. Partial least square discriminant analysis (PLS-DA) was used to identify proteins contributing most to PR3-AAV/MPO-AAV separation from healthy controls. The STRING database was used to analyse protein–protein interaction networks. Gene ontology, KEGG and Reactome databases were used for pathway enrichment analyses using ClueGO. Results In comparison with healthy controls, 63 DEPs were identified for PR3-AAV and 62 for MPO-AAV; of these, 49 DEPs were common to both AAV groups. Pathway enrichment analysis of the 49 common DEPs identified IL-17-, IL-10-, TNF-α- and NF-kappa B signaling and neutrophil chemotaxis among the significantly enriched processes. The 14 DEPs unique for PR3-AAV formed a functional and physical protein-protein interaction network in STRING analysis, with significant enrichment for regulation of B cell proliferation, activation of matrix metalloproteinases, collagen degradation and IL-17- and TNF-α signaling pathways. The 13 DEPs unique for MPO-AAV did not show any significant functional enrichment. Of the top 15 proteins contributing most to group separation in the PLS-DA analysis, 11 proteins where common to both PR3- and MPO-AAV and 4 proteins were unique for PR3-AAV and MPO-AAV, respectively (Table 1). Conclusion Combining quantitative proteomics and bioinformatics analyses, we have identified a large group of DEPs characterizing both active PR3- and MPO-AAV and have determined their associated biological mechanisms. DEPs unique for PR3-AAV formed an interconnected protein network associated with biological processes of high relevance for AAV-pathogenesis. In conclusion, these findings may provide new insights into similarities and differences in the pathogenesis of MPO- and PR3-AAV. Table 1. PLS-DA results showing the top 15 proteins contributing most to separation of PR3-AAV and MPO-AAV patients, respectively, from healthy controls. Common for MPO-AAV and PR3-AAV vs healthy controls Unique for MPO-AAV vs healthy controls Unique for PR3-AAV vs healthy controls CCL23 EPHB4 EN-RAGE CD40 LTBR MCP-3 IL2-RA PLC PRTN3 OPN RETN ST2 TGF-alpha TIMP-1 TNF-R1 TNF-R2 TNFRSF14 U-PAR VEGFA REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests None Declared. Keywords: -Omics, Vasculitis DOI: 10.1136/annrheumdis-2023-eular.5500Citation: , volume 82, supplement 1, year 2023, page 1073Session: Vasculitis - aetiology, pathogenesis and animal models (Poster View)