Plasma proteome differences between giant cell arteritis and polymyalgia rheumatica: a pilot study

BACKGROUND: Giant cell arteritis (GCA) is the most prevalent vasculitis in the elderly of Caucasian ancestry, with the risk of visual loss as the most serious complication if the glucocorticoid therapy does not succeed. While imaging and temporal artery biopsy (TAB) remain diagnostic gold standards, new laboratory tests are needed to assess disease activity and follow-up monitoring. OBJECTIVE: We aimed to characterize distinct proteomic signatures for the classification of polymyalgia rheumatica (PMR) and GCA (independent of concurrent therapy) and to identify specific markers of disease activity and markers that differentiate the two diseases. METHODS: The plasma of 15 PMR and 13 GCA patients was analysed via mass spectrometry with the UltiMate 3000 nano-HPLC system coupled to an Orbitrap Eclipse mass spectrometer. Immunofluorescence analyses in TABs were performed to confirm the elevated plasma expression of S100A12. RESULTS: We identified 50 protein signatures characteristic of active GCA patients, and 83 signatures altered only in active PMR samples. Strikingly, both groups shared only 13 proteins with altered protein expression levels. The newly identified proteins point to activation of biological pathways not yet linked to the diseases: mitochondrial membrane activity (ACACA, SLC25A31) and clotting cascade (VWF, TUBB) in active GCA; erythrocyte integrity (SLC4A1, SPTA1), muscle contraction (MYLK, MYL6B/12B), and glucocorticoid resistance (PTGES3) in active PMR. Importantly, S100A12 was increased not only in plasma (~ 1.6-fold), but also in PMR and GCA TABs. CONCLUSION: Active PMR and active GCA patients share an unexpectedly small plasma proteome signature related to immune activation (8.9%: 13 proteins). Instead, active PMR is characterized by distinct erythrocyte and muscle contraction proteome changes, whereas active GCA appears driven by mitochondrial and clotting cascade alterations. Prospective, longitudinal validation studies of the described proteomic signatures might support the clinical classification of both diseases.