We evaluated potential circulating biomarkers of disease activity in giant cell arteritis (GCA), Takayasu arteritis (TA), polyarteritis nodosa (PAN), and eosinophilic granulomatosis with polyangiitis (EGPA).

Methods. A panel of 22 serum proteins was tested in patients enrolled in the Vasculitis Clinical Research Consortium Longitudinal Studies of GCA, TA, PAN, or EGPA. Mixed models were used for most analyses. A J48 classification tree method was used to find the most relevant markers to differentiate between active and inactive GCA.

Results. Tests were done on 418 samples from 152 patients (60 GCA, 29 TA, 26 PAN, 37 EGPA), during both active vasculitis and remission. In GCA, these showed significant (p < 0.05) differences between disease states: B cell–attracting chemokine 1 (BCA)-1/CXC motif ligand 13 (CXCL13), erythrocyte sedimentation rate (ESR), interferon-γ—induced protein 10/CXC motif chemokine 10, soluble interleukin 2 receptor α (sIL-2Rα), and tissue inhibitor of metalloproteinase-1 (TIMP-1). In EGPA, these showed significant increases during active disease: granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage—CSF, interleukin (IL)-6, IL-15, and sIL-2Rα. BCA-1/CXCL13 also showed such increases, but only after adjustment for treatment. In PAN, ESR and matrix metalloprotease (MMP)-3 showed significant differences between disease states. Differences in biomarker levels between diseases were significant for 11 markers and were more striking (all p < 0.01) than differences related to disease activity. A combination of lower values of TIMP-1, IL-6, interferon-γ, and MMP-3 correctly classified 87% of samples with inactive GCA.

Reference link- https://www.jrheum.org/content/47/7/1001