Warren David Raymond1, Gro Østli Eilertsen2, Johannes Nossent3. 1. Rheumatology Group, School of Medicine & Pharmacology, The University of Western Australia, Australia. 2. Molecular Inflammation Research Group, Department of Clinical Medicine, Artic University, Tromso, Norway. 3. Rheumatology Group, School of Medicine & Pharmacology, The University of Western Australia, Australia; Department of Rheumatology, Sir Charles Gairdner Hospital, Perth Western, Australia. Electronic address: johannes.nossent@uwa.edu.au.
Abstract
OBJECTIVE: Cytokine dysregulation contributes to inflammation and organ damage in Systemic Lupus Erythematosus (SLE). Principle Component Analysis (PCA) can determine which groups of cytokines have the most influence across disease activity states. MATERIAL AND METHOD: A cross-sectional study of age- and gender-matched SLE patients (n = 100) and controls (n = 31). SLE patients had a median Systemic Lupus Erythematosus Disease Activity Index - 2000 (SLEDAI-2K) score of 6 (IQR 2, 11). IFN-γ, interleukin (IL)-1β, IL-4, IL-6, IL-10, IL-12, IL-17, BAFF, TNF-α, TGF-β1, MIP-1α, MIP-1β and MCP-1 levels were quantified by sandwich ELISA, and compared non-parametrically between groups. PCA was used to determine the principal components across controls, SLE patients in states of remission (SLEDAI-2K = 0), low disease activity (LDA = SLEDAI-2K from 1 ≤ x ≤ 4) or high disease activity (HDA = SLEDAI-2K > 4). RESULTS: TGF-β1 (Rs -0.266, p = 0.005) and IL-1β (Rs -0.199, p = 0.004) inversely correlated, whereas BAFF correlated with increasing disease activity (Rs 0.465, p < 0.001). IL-1β, IL-4, IL-10, IL-12, IL-17, IFN-γ, MCP-1, and TNF-α were featured consistently in the PC1 of all study groups. PC1 changes from controls to SLE-HDA patients, included: the increased impact of IL-1β (from 0.58 to >0.95); increased impact of IL-6 in HDA (0.76); increased influence of MIP-1α (0.60) and MIP-1β (0.85); and the uncoupling of TGF-β1 (0.14). PC2 changes from healthy controls to the HDA state, included: the increased influence of BAFF (from -0.18 to 0.88); the oppositional effect of TGF-β1 (-0.36); and, the inclusion of MCP-1 (0.65). Levels of cytokine profiles were equivalent between controls and SLE patients (p > 0.18). BAFF was not associated with the cytokine profiles. TGF-β1 associated with Th1 (Rs 0.36), Th1 + Th17 (Rs 0.22), and inversely with Th17/Th2 (Rs -0.23) profiles. IL-1β associated with the proinflammatory (Rs 0.47), Th1 (Rs 0.55), Th2 (Rs 0.55), Th17 (Rs 0.51), Th1 + Th17 (Rs 0.56), Th2 + Treg (Rs 0.45), and inversely with the (Th1 + Th17 / Th2 + Treg) (Rs -0.22) and Th17/Th2 (Rs -0.27) profiles (all, p < 0.05). CONCLUSION: Principal component analysis helped to describe the influence of complex cytokine interactions in SLE in a manner congruent with the wider literature. The typical univariate changes in BAFF and TGF-β1 levels with increasing levels of disease activity, were not the dominant factors (in PC1) in the PCA. The PCA demonstrated that IL-1β did not seem to change its regulatory function in SLE.
OBJECTIVE: Cytokine dysregulation contributes to inflammation and organ damage in Systemic Lupus Erythematosus (SLE). Principle Component Analysis (PCA) can determine which groups of cytokines have the most influence across disease activity states. MATERIAL AND METHOD: A cross-sectional study of age- and gender-matched SLEpatients (n = 100) and controls (n = 31). SLEpatients had a median Systemic Lupus Erythematosus Disease Activity Index - 2000 (SLEDAI-2K) score of 6 (IQR 2, 11). IFN-γ, interleukin (IL)-1β, IL-4, IL-6, IL-10, IL-12, IL-17, BAFF, TNF-α, TGF-β1, MIP-1α, MIP-1β and MCP-1 levels were quantified by sandwich ELISA, and compared non-parametrically between groups. PCA was used to determine the principal components across controls, SLEpatients in states of remission (SLEDAI-2K = 0), low disease activity (LDA = SLEDAI-2K from 1 ≤ x ≤ 4) or high disease activity (HDA = SLEDAI-2K > 4). RESULTS: TGF-β1 (Rs -0.266, p = 0.005) and IL-1β (Rs -0.199, p = 0.004) inversely correlated, whereas BAFF correlated with increasing disease activity (Rs 0.465, p < 0.001). IL-1β, IL-4, IL-10, IL-12, IL-17, IFN-γ, MCP-1, and TNF-α were featured consistently in the PC1 of all study groups. PC1 changes from controls to SLE-HDApatients, included: the increased impact of IL-1β (from 0.58 to >0.95); increased impact of IL-6 in HDA (0.76); increased influence of MIP-1α (0.60) and MIP-1β (0.85); and the uncoupling of TGF-β1 (0.14). PC2 changes from healthy controls to the HDA state, included: the increased influence of BAFF (from -0.18 to 0.88); the oppositional effect of TGF-β1 (-0.36); and, the inclusion of MCP-1 (0.65). Levels of cytokine profiles were equivalent between controls and SLEpatients (p > 0.18). BAFF was not associated with the cytokine profiles. TGF-β1 associated with Th1 (Rs 0.36), Th1 + Th17 (Rs 0.22), and inversely with Th17/Th2 (Rs -0.23) profiles. IL-1β associated with the proinflammatory (Rs 0.47), Th1 (Rs 0.55), Th2 (Rs 0.55), Th17 (Rs 0.51), Th1 + Th17 (Rs 0.56), Th2 + Treg (Rs 0.45), and inversely with the (Th1 + Th17 / Th2 + Treg) (Rs -0.22) and Th17/Th2 (Rs -0.27) profiles (all, p < 0.05). CONCLUSION: Principal component analysis helped to describe the influence of complex cytokine interactions in SLE in a manner congruent with the wider literature. The typical univariate changes in BAFF and TGF-β1 levels with increasing levels of disease activity, were not the dominant factors (in PC1) in the PCA. The PCA demonstrated that IL-1β did not seem to change its regulatory function in SLE.