Brief Report: Circulating Cytokine Profiles and Antineutrophil Cytoplasmic Antibody Specificity in Patients With Antineutrophil Cytoplasmic Antibody-Associated Vasculitis

Abstract

Objective: To evaluate circulating cytokine profiles in patients with antineutrophil cytoplasmic antibody-associated vasculitis (AAV), classified by antineutrophil cytoplasmic antibody (ANCA) specificity (proteinase 3 ANCA [PR3-ANCA] versus myeloperoxidase ANCA [MPO-ANCA]) or by clinical diagnosis (granulomatosis with polyangiitis [GPA] versus microscopic polyangiitis [MPA]).

Methods: A panel of 29 cytokines was tested in 186 patients with active AAV at inclusion into the Rituximab in AAV trial. Cytokine concentrations were compared between groups within each classification system. Multivariable analyses adjusted for age, sex, and renal insufficiency were performed, with each biomarker as a dependent variable and ANCA specificity and clinical diagnosis as explanatory variables of interest.

Results: Levels of 9 circulating cytokines (interleukin-6 [IL-6], granulocyte-macrophage colony-stimulating factor [GM-CSF], IL-15, IL-18, CXCL8/IL-8, CCL-17/thymus and activation-regulated chemokine [TARC], IL-18 binding protein [IL-18 BP], soluble IL-2 receptor α [sIL-2Rα], and nerve growth factor β [NGFβ]) were significantly higher in PR3-AAV than MPO-AAV, 4 cytokines (sIL6R, soluble tumor necrosis factor receptor type II [sTNFRII], neutrophil gelatinase-associated lipocalin [NGAL], and soluble intercellular adhesion molecule 1 [sICAM-1]) were higher in MPO-AAV than in PR3-AAV, 6 cytokines (IL-6, GM-CSF, IL-15, IL-18, sIL-2Rα, and NGFβ) were higher in GPA than in MPA, and 3 cytokines (osteopontin, sTNFRII, and NGAL) were higher in MPA than in GPA (all P < 0.05). For nearly all cytokines, the difference between PR3-AAV and MPO-AAV was larger than that between GPA and MPA. The multivariate analysis showed that 8 cytokines (IL-15, IL-8, IL-18 BP, NGF-β, sICAM-1, TARC, osteopontin, and kidney injury molecule 1 (P < 0.05) distinguished patients with AAV better (lower P values and larger effect sizes) when grouped by ANCA specificity than by clinical diagnosis.

Conclusion: Distinct cytokine profiles were identified for PR3-AAV versus MPO-AAV and for GPA versus MPA. Differences in these circulating immune mediators are more strongly associated with ANCA specificity than with clinical diagnosis, suggesting that heterogeneity in the AAV subtypes extends beyond clinical phenotypes.

Figure 1. Association of circulating cytokines with ANCA type and AAV clinical diagnosis subgroups (PR3-AAV versus MPO-AAV and GPA versus MPA

A Graphical representation of circulating cytokine profiles. The strengths of associations are represented by colors (yellow, 0.01<p ≤0.05; orange, 0.001<p≤0.01; red, p≤0.001) in each classification system. B Parametric analyses of the biomarkers (effect size) (see Methods for further information). Footnotes: AAV, anti-neutrophil cytoplasmic antibody-associated vasculitis; GPA, granulomatous polyangiitis; MPA, microscopic polyangiitis; MPO, myeloperoxidase; PR3, proteinase 3; IL, interleukin; BAFF, B-Cell Activating Factor; GM-CSF, granulocyte–monocyte colony-stimulating factor; G-CSF, granulocyte colony-stimulating factor; IFNγ, interferon gamma; BCA-1, CXCL13; IL-8, CXCL8; IP-10, CXCL10; RANTES, CCL5 (also known as Regulated on Activation, Normal T Cell Expressed and Secreted); TARC, CCL17 (also known as thymus and activation regulated chemokine); sIL-6R, soluble IL 6 receptor; IL-18Bp, interleukin 18 binding protein; sIL-2R, soluble IL 2 receptor; sTNF-RII, soluble TNF receptor II; ACE, Angiotensin-converting enzyme; NGFβ, nerve growth factor β; bFGF, basic fibroblast growth factor; KIM-1, kidney injury molecule-1; MMP-3, matrix metalloproteinase-3; PDGF-AB, platelet-derived growth factor, A and B subunits; TIMP-1, tissue inhibitor of metalloproteinases-1; NGAL, neutrophil gelatinase-associated lipocalin; PAI-1, plasminogen activator inhibitor-1; ICAM1, intercellular adhesion molecule-1; VCAM-1, vascular cell adhesion molecule-1.

Figure 2. Multivariate analysis comparing the two classification systems (PR3-AAV versus MPO-AAV and GPA versus MPA) for each cytokine

A The panel displays the 8 soluble mediators with a significant association with ANCA type and/or clinical diagnosis classifications and an explanatory figure of a molecule not associated with either ANCA specificity or clinical diagnosis is shown (sTNFR II; upper left). For each biomarker, the association with both ANCA specificity and clinical diagnosis is represented. The magnitude of the difference between GPA and MPA is visually depicted by the distance between 2 lines, each one representing a clinical diagnosis (dotted line for GPA and the solid line for MPA), whereas the difference between PR3-AAV versus MPO-AAV is visually represented by the slope of the lines. The statistical model forces them to be parallel. The direction and the grade of inclination represent the type and the strength of the association with ANCA-type classification, respectively. B Scatter plot representing all the serum cytokines studied, comparing the effect of ANCA type (x-axis) and of clinical diagnosis (y-axis). The more a biomarker is skewed to the left or to the right, the stronger it discriminates patients by ANCA type classification, the more a biomarker is skewed to the bottom or to the top, the stronger it discriminates patients by clinical diagnosis classification.