Cytokine and autoantibody clusters interaction in systemic lupus erythematosus

Abstract

BackgroundEvidence supports the existence of different subphenotypes in systemic lupus erythematosus (SLE) and the pivotal role of cytokines and autoantibodies, which interact in a highly complex network. Thus, understanding how these complex nonlinear processes are connected and observed in real-life settings is a major challenge. Cluster approaches may assist in the identification of these subphenotypes, which represent such a phenomenon, and may contribute to the development of personalized medicine. Therefore, the relationship between autoantibody and cytokine clusters in SLE was analyzed.MethodsThis was an exploratory study in which 67 consecutive women with established SLE were assessed. Clinical characteristics including disease activity, a 14-autoantibody profile, and a panel of 15 serum cytokines were measured simultaneously. Mixed-cluster methodology and bivariate analyses were used to define autoantibody and cytokine clusters and to identify associations between them and related variables.ResultsFirst, three clusters of autoantibodies were defined: (1) neutral, (2) antiphospholipid antibodies (APLA)-dominant, and (3) anti-dsDNA/ENA-dominant. Second, eight cytokines showed levels above the threshold thus making possible to find 4 clusters: (1) neutral, (2) chemotactic, (3) G-CSF dominant, and (4) IFNα/Pro-inflammatory. Furthermore, the disease activity was associated with cytokine clusters, which, in turn, were associated with autoantibody clusters. Finally, when all biomarkers were included, three clusters were found: (1) neutral, (2) chemotactic/APLA, and (3) IFN/dsDNA, which were also associated with disease activity.ConclusionThese results support the existence of three SLE cytokine-autoantibody driven subphenotypes. They encourage the practice of personalized medicine, and support proof-of-concept studies.Electronic supplementary materialThe online version of this article (10.1186/s12967-017-1345-y) contains supplementary material, which is available to authorized users.

Lack of standardisation of ANA and implications for drug development and precision medicine

“…It is widely appreciated that SLE can manifest in various forms and that autoantibody profiles can subdivide patients into more homogeneous groups 13–15. Also, it is possible that stratification of patients powered by machine learning techniques will lead to a novel, molecular-based nomenclature of disease that will likely improve patient outcome 16.…”

“…For clinical trials in patients with AARD, ANA, even if clearly defined, is unlikely to provide the full insight into meaningful disease subsets of patients who respond to a particular treatment. Along those lines, autoantibodies might not provide a robust reflection of pathogenic pathways where other biomarkers such as cytokines, inflammatory proteins or complement components can provide further insights into potential treatment strategies 15…”

Serum interleukin-6 level is correlated with the disease activity of systemic lupus erythematosus: a meta-analysis

“…Additionally, excessive pro-inflammatory cytokine release may also promote SLE development (3)(4)(5)(6).…”

Cytokine profiling in active and quiescent SLE reveals distinct patient subpopulations

“…In contrast, group 2 contained increased levels of CXCL10 and CXCL13. In a study of 67 patients by Pacheco et al (2017), using cytokine levels alone four groups were identified: neutral, chemokine, G-colony stimulating factor (G-CSF)-dominant and IFNα/pro-inflammatory [ 21 ]. Despite marked differences in the cytokines measures, our larger study also demonstrates “chemokine” and “cytokine” clusters of patients.…”