Alicia Rodriguez-Pla1,2, Roscoe L Warner1,2, David Cuthbertson1,2, Simon Carette1,2, Nader A Khalidi1,2, Curry L Koening1,2, Carol A Langford1,2, Carol A McAlear1,2, Larry W Moreland1,2, Christian Pagnoux1,2, Philip Seo1,2, Ulrich Specks1,2, Antoine G Sreih1,2, Steven R Ytterberg1,2, Kent J Johnson1,2, Peter A Merkel1,2, Paul A Monach. 1. From Boston University, Boston, Massachusetts; University of Arizona, Tucson, Arizona; University of Michigan, Ann Arbor, Michigan; University of South Florida, Tampa, Florida, USA; Mount Sinai Hospital, Toronto; McMaster University, Hamilton, Ontario, Canada; University of Utah, Salt Lake City, Utah; Cleveland Clinic, Cleveland, Ohio; University of Pennsylvania, Philadelphia; University of Pittsburgh, Pittsburgh, Pennsylvania; Johns Hopkins University, Baltimore, Maryland; Mayo Clinic, Rochester, Minnesota; VA Boston Healthcare System, Boston, Massachusetts, USA. 2. A. Rodriguez-Pla, MD, PhD, MPH, Boston University, and the University of Arizona; R.L. Warner, PhD, University of Michigan; D. Cuthbertson, MS, University of South Florida; S. Carette, MD, Mount Sinai Hospital; N.A. Khalidi, MD, McMaster University; C.L. Koening, MD, MS, University of Utah; C.A. Langford, MD, MHS, Cleveland Clinic; C.A. McAlear, MD, University of Pennsylvania; L.W. Moreland, MD, University of Pittsburgh; C. Pagnoux, MD, MPH, Mount Sinai Hospital; P. Seo, MD, MHS, Johns Hopkins University; U. Specks, MD, Mayo Clinic; A.G. Sreih, MD, University of Pennsylvania; S.R. Ytterberg, MD, Mayo Clinic; K.J. Johnson, MD, University of Arizona; P.A. Merkel, MD, MPH, University of Pennsylvania; P.A. Monach, MD, PhD, Boston University, and the VA Boston Healthcare System.
Abstract
OBJECTIVE: 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. CONCLUSION: We identified novel biomarkers of disease activity in GCA and EGPA. Differences of biomarker levels between diseases, independent of disease activity, were more apparent than differences related to disease activity. Further studies are needed to determine whether these serum proteins have potential for clinical use in distinguishing active disease from remission or in predicting longer-term outcomes.
OBJECTIVE: 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. CONCLUSION: We identified novel biomarkers of disease activity in GCA and EGPA. Differences of biomarker levels between diseases, independent of disease activity, were more apparent than differences related to disease activity. Further studies are needed to determine whether these serum proteins have potential for clinical use in distinguishing active disease from remission or in predicting longer-term outcomes.
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