A Hierarchical Cytokines Framework Defining Groups of Chronic Inflammatory Diseases: Learning From Cytokine-Targeted Therapies

A Hierarchical Cytokines Framework Defining Groups of Chronic Inflammatory Diseases: Learning From Cytokine-Targeted Therapies
on the study by George Schett et al, Nat Med, 2013 Jul;19(7):822-4
How cytokine networks fuel inflammation: Toward a cytokine-based disease taxonomy

Extensive genome-wide association and epidemiological studies have shed light on the causes of chronic inflammatory diseases and have confirmed a central role of the immune system and particularly of cytokines [1]. Secreted cytokines provide signals between immune cells that coordinate the inflammatory response and among these tumor necrosis factor (TNF)-α, interleukin (IL)-1 and IL-6 represent the dominant proinflammatory cytokines able to sustain and amplify an inflammatory process in the majority of chronic inflammatory diseases [3].

In the early 1990s, the remarkable therapeutic success of targeted inhibition of TNF-α in patients with rheumatoid arthritis, and the most recent preclinical studies, have indicated that a selective targeting of cytokines may suppress inflammation and tissue destruction [3], revising the concept that effective treatment requires broad immune pathway suppression [4].

Last year in Nature Medicine (‘Bedside to Bench’ section, volume 19), George Schett and colleagues from the University of Erlangen-Nuremberg, Erlangen, Germany, propose a new paradigm to define groups of chronic inflammatory diseases. Most of the chronic inflammatory diseases share clinical responsiveness to TNF-α inhibition, but substantially differ in their responsiveness to inhibition of other inflammatory cytokines, such as IL-1, IL-6, IL-17 and IL-23.

Taking into account the clinical efficacy of the inhibition of each cytokine, the authors were able to draw a molecular taxonomy tree of inflammatory cytokines for diseases such as rheumatoid arthritis, Crohn’s disease, psoriasis, juvenile idiopathic arthritis and gout. The taxonomy tree indicates clearly a hierarchical structure of cytokine effects in these diseases. For example, rheumatoid arthritis is classified as an IL-6R/TNF-α cluster disease because of the strong clinical efficacy of IL-6 and TNF-α inhibition. Rheumatoid arthritis is excluded from the IL-1 and IL-17/IL-23 clusters, due to the poor benefit seen in patients when these cytokines are inhibited, despite their involvement in the pathogenesis of inflammation. Furthermore, Schett et al. highlight the central role of IL-23→IL-17A axis in the pathogenesis of psoriasis.

The authors sustain that the discovery of new effective cytokine targets will help to fine-tune this classification, allowing future treatment strategies for chronic inflammatory diseases. They also argue that this new paradigm may replace the traditional classification of chronic inflammatory diseases, fundamentally based on the organ involved and on the clinical phenomenology. The authors conclude that these clinical findings have both basic and clinical relevance, and that the unanticipated clinical outcomes can shed more light on the homeostatic function of certain cytokines in our body.

The new paradigm proposed by the authors presents fundamental challenges that current medicine is suited to address. The approach to integrate hierarchical data in computational frameworks, in order to render biological functions understandable, in terms of molecular players, may finally address diseases in terms of molecules engaged in networking. Clinical studies have clearly demonstrated the existence of numerous pitfalls when translating preclinical data into the clinic.

The most critical issue is that several cytokine-targeted therapies are efficacious only in certain subgroups of patients, thus indicating that cytokine networks are regulated by genetic and immunological factors that differ among patients [5,6]. The revolutionary challenge to elucidate the mechanistic underpinnings of inflammatory immune-mediated disease will be the systems biology approach application. Integrating data from large scale measurements (e.g. transcriptomics, proteomics and genomics), using pathway information from multiple measurement platforms, tissues and species will improve disease prediction and prevention, and will lead to more personalized medicine. Although the application of systems biology to the study of chronic inflammatory diseases is in its early stage, we believe that this holistic approach is promising to address the multiple factors implicated in complex diseases such atherosclerosis, as discussed by Ramsey et al. [7].

In fact, the cardiovascular system is a network of organs and cell types each with specialized, but highly coordinated functions, often showing nonlinear interactions [8]. Numerous proinflammatory molecular and cellular mediators have been demonstrated contributing to or regulating inflammation in atherosclerosis [9-11]. Since they include both circulating and tissue-level inflammatory mediators, the networks transcend typical cytokine networks by associating inflammatory mechanisms with tissue/organ microenvironment via tissue damage/dysfunction. The precise behaviors and functions of these mediators are still active areas of investigation that continue to yield exciting new data.

Author(s) Affiliation

Brigitta Buttari, BSc, PhD, Elisabetta Profumo, BSc , Rachele Riganò, BSc – Department of Infectious, Parasitic and Immune-Mediated Diseases, Istituto Superiore di Sanità, Rome; Italy.
Corresponding author: Brigitta Buttari, email: brigitta.buttari@iss.it


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Source: Cover Image: Structure of protein IL15. Based on PyMOL rendering of PDB 2Z3Q. Author: Pleiotrope. Credit: Wikimedia Commons.

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