Current and Future Therapy Strategies in Rheumatoid Arthritis: Where Are We Going?

Abstract
Rheumatoid arthritis is autoimmune disease in which bones and cartilage erosion lead to joint destruction. The subsequent interaction of activated synovial fibroblasts and immune cells through the release proinflammatory mediators and matrix degrading enzymes creates a loop that makes inflammation chronic. Although current treatment strategies advance our understanding about arthritis, they have involved serious side effects as they targeted immune system. Therefore, novel drugs and research are required to understand nature of disease and apply appropriate treatments with less or no side effects. This review described the pathogenesis of rheumatoid arthritis and therapeutic strategies for its treatment based on previous studies and focused on some gaps potentially arisen in current literature.

Introduction

The human immune system has consisted of different types of cells that function differently to create an activated immune response [1]. Dysregulated inflammation in response to activated immune response results in an autoimmune disease that affects 3.2 – 9.4% of the general population [2]. More than 80 different autoimmune diseases have been studied and have been shown to affect more women than men [3], rheumatoid arthritis (RA) is one of the autoimmune conditions of joints characterised by synovial inflammation, autoantibody formation, and finally destruction of bone and cartilage [4]. The prevalence of RA in the UK is 0.44% and 1.16% in men and women, respectively. Although there is no cure for RA, the emergence of gold standard regimens such as biologics targeting important cytokines involved in the pathogenesis of RA has advanced our knowledge and treatment efficiency. However, there are still treatment-resistant patients who do not respond to any of the biologic therapies [5]. This indicates that we are still in need of finding alternative treatment strategies for the treatment of RA. In the current review, using RA as a primary example of an autoimmune disease based on previous research, I will describe (i) molecular mechanisms involved in the pathogenesis of RA, (ii) current therapy strategies for the treatment of RA, (iii) recent advances in RA research for the prediction of clinical outcomes of treatment, and finally (iv) I will discuss and provide some examples for future therapy strategies.

Molecular Mechanisms in the Pathogenesis of RA

Genetics, environmental factors, and epigenetics have been shown to influence the development of RA. The presence of the HLA-DRB1 positive and PTPN22 variant is associated with the production of rheumatoid factor and autoantibodies, suggesting that the genetic background is important for the development of RA [6]. Environmental factors such as smoking elevated the expression of peptidylarginine deiminase in the lungs that is involved in the production of citrullinated antibody formation, as observed in RA, indicating that smoking may lead to citrulline autoimmunity [7]. Epigenetic studies in early arthritis patients have also identified differential methylation characteristics in naive CD4+ T cells [8]. Although the mentioned factors have contributed to the development of RA, changes in cellular behavior within the surrounding synovial microenvironment have also been involved in the pathology of the disease.

In healthy joints, synovial fibroblasts (SF) are stromal non-immune cells that are involved in maintaining correct matrix remodelling and wound repair. Activation of SFs has been observed in RA, as they acquired a destructive phenotype through increased release of pro-inflammatory mediators and matrix-degrading enzymes [9]. These alterations have been initiated in SFs, where they further interact with immune cells. In fact, tumor necrosis factor-α (TNF-α), interleukins such as IL-6 and IL-1β can increase the destructive characteristics of SF, in turn increasing the release of inflammatory mediators by immune cells as well. This situation further creates an autoimmune loop where inflammatory stimuli have become consistent [9]. Therefore, inflammation in RA cannot resolve itself and result in chronic autoimmune disease (see Fig. 1). As a result, although fibroblasts are nonimmune cells, their activation covers important characteristics in the pathogenesis of inflammatory RA. Surprisingly, current treatment strategies only target immune cells for RA treatment, but not stromal SFs.

Figure 1: Illustration of the development of rheumatoid arthritis (RA) (self-drawing). Genetic, environmental, and epigenetic factors trigger the initiation and expansion of RA autoimmunity (left). Synovial alteration is initiated in nonimmune stromal synovial fibroblasts (SFs) by releasing pro-inflammatory cytokines (IL-6) and matrix degrading enzymes (MMPs) that interact with immune cells (i.e. macrophages, T cells and B cells) that further release pro-inflammatory mediators (i.e, TNF-α, IL-17) into the synovial microenvironment. Subsequent release of the mediators involved in the creation of an autoimmune loop where inflammation becomes chronic and cannot be resolved (right).

Recent advances in single cell transcriptomics have identified important human cell subpopulations that regulate inflammation or remission in the RA synovium. Mizoguchi et al. [10] described three SF subtypes based on the location and markers they expressed that were involved in the progression of RA through the release of inflammatory cytokines or matrix-degrading enzymes. Furthermore, Alivernini et al. [11] identified markers in resident synovial tissue that are negative regulators of inflammation. Different human cells that regulate inflammation or remission in the RA synovium are summarized in Table 1.

Table 1: Different human cells regulate inflammation or remission in the synovium of the RA.

Current treatment strategies in RA

Conventional treatments such as a combination of non-steroid anti-inflammatory drugs (NSAIDs) and disease-modifying antirheumatic drugs (DMARD) have been initially used to reduce inflammation in newly diagnosed RA patients [16]. However, most patients did not respond because DMARD and NSAIDs have been reduced to lack of efficacy [17]. Thus, biologic therapy has been substantially preferred over conventional treatments, as it targets immune cells and inhibit aberrant cytokine production observed in the synovial microenvironment. Synovial macrophages,  B cells, and T cells produce TNF-α cytokine that is important for the pathogenesis of RA [18]. IL-6, on the other hand, is mainly produced by B-cell differentiation and is involved in autoantibody production [19].

TNF-α inhibitors have been commercialized as neutralizing antibodies (Infiximab, Adalimumab), pegylated antibody fragment (Certolizumab pegol), or soluble TNF-α receptor (Etanercept) [20]. These medications mainly inhibit the binding of TNF-α to its receptor. Therefore, the mode of action of drugs aims to reduce inflammation. Although the reasons remain unclear, some patients did not respond to anti-TNF-a therapies. A recent study compared two sets of gene expression data for the identification of Infliximab response in RA. The DERL-1 gene has been found to be significantly differentially expressed in non-responders where it is involved in autophagy [21]. Golimumab, on the other hand, is a human IgG1κ monoclonal antibody that functions as neutralising TNF-α, and prevents bone erosion and cartilage degradation by reducing TNFR-II and MMP in human serum [22].

IL-6 inhibitor biologics have also been used for RA treatment. Although the mechanisms of action in Siltuximab and Sirukimab directly neutralize antibodies, Tociluzimab binds to the IL-6 receptor and then inhibits IL-6-mediated cell signalling [23]. A recent study evaluated the efficacy of tociluzumab in patients with RA and successful low disease activity has emerged after its use. However, reducing its dose after treatment increased the risk of low disease activity [24].

Rituximab has offered RA patients if they do not respond to at least one anti-TNF-α therapy regimen. It targets the CD20 molecule on B cells and therefore mature B cells depleted by this compound [25]. Patients who took Rituxumab and previously discontinued to anti-TNF-α therapy have higher failure rates than others [26], although some patients have benefited from Rituxumab treatment [25].

Abatacept is a co-stimulation blocker biologic where it neutralizes CTLA-4 binding to CD80 / CD86 on antigen presenting cells (APC). Therefore, it targets T-cell-mediated inflammatory pathways [27]. The efficacy of Abatacept has shown significant disease reductions in clinical trials [27]. The biologics mentioned in this essay are summarized in Figure 2.

Recent Advances in RA Research

Machine learning has been utilized to predict clinical outcomes of treatment. Koo et al. [28] in their paper used artificial intelligence tools to identify remission in RA patients who treated with biologics. Authors obtained important clinical parameters such as disease duration, C-reactive protein, rheumatoid factor, erythrocyte sedimentation and age from the follow-up data of 1204 patients registered to Korean College of Rheumatology Biologics and Targeted Therapy Registry. Using a different types of machine learning algorithms, findings demonstrated that remission in use of adalimumab, infliximab, etanercept, abatacept, golimumab and tocilizumab were predicted by age, erythrocyte sedimentation rates, rheumatoid factor, disease duration, erythrocyte sedimentation rates and C-reactive protein levels, respectively. Although presence of some limitations such as no dosage requirement has considered and authors did not separate primary and secondary responder failures, this paper provided important concept for how we can utilize artificial intelligence in terms of developing personalized medicine tools.

Figure 2: Illustration of the mechanism of action in biologics for rheumatoid arthritis (RA) (self-drawing). Biologics involved in the treatment of RA have been summarized. (A) Infliximab, certolizumab pegol, adalimumab, golimumab and etanercept neutralize TNF-α, (B) Tocilizumab binds to IL-6R and thus inhibits IL-6-mediated cell signalling, (C) Abatacept inhibits CTLA4 binding to CD80 / 86 in APC and thus T-cell co-stimulation was prevented since CD80 / 86 cannot be bound to CD28. (D) Rituximab binds to CD20 on B cells, and thus mature B cells are depleted.

Tao et al. [29], in their paper, investigated RA patients’ transcription signatures to predict response to anti-TNF therapy prior to start biologics and compared this data after patients have used adalimumab or etanercept. Etanercept but not adalimumab responders have shown differentially hypermethylated gene signatures in their peripheral blood mononuclear cells, indicating the importance of epigenetics in defining response to anti-TNF therapy. Furthermore, using transcriptomics data they have built machine learning models and data obtained from machine learning has confirmed all responders and non-responders correctly.

Apart from those research, recently Wang et al. [30] have shown that reduced α2-6 sialylation turns SFs into more inflammatory phenotype in arthritic mouse model and different sialylation levels correlated with disease stages in human RA. If sialic acid could be identified a novel marker for RA SFs, we should also be able to develop novel drugs to target SFs, rather than targeting immune cells.

Discussion and Future Perspectives

In the current essay, I have described RA pathogenesis and treatment strategies which shaped RA research. Current RA treatments are not perfect, RA patients first treated with conventional NSAIDs and DMARDs, and if they did not respond to first line medications, biologics will be prescribed. Both conventional drugs and biologics are impersonalized, In addition, biologics have serious side effects as they supressed immune system, anti-TNFs for instance increase risk of skin cancers and tuberculosis infections [31]. Thus, this leads us to find alternative treatment strategies and a more detailed understanding about RA pathogenesis. Achieving a successful understanding of disease pathology will open up novel opportunities for personalized medicine, we should also need more understanding about individual differences that are leading to the failure or respond after biologics therapies. This either should be done to create biobanking and profiling RA samples, or application of multi-omics approaches will provide us picture about what is going on in the RA and provide important information about novel biomarkers as well. Also, if composition of cells can predict the outcome of RA treatment through machine learning approaches mentioned here, it should be applied patient biopsies prior to treatment starts and the correct biologics can be chosen for treatment that will result in desired outcomes for the right person in the right time.

As already discussed, RA SFs are the stromal cells where their activation leads to interact with immune cells and triggers autoimmune loop formation involved in chronic inflammation [9]. None of the biologics target SFs alone and finding some markers in RA SFs will help to develop drugs targeting stromal cells. As a result, immune system related consequences may be prevented. It is also important to identify early-stage markers for RA, as we may be able to control disease pathogenesis easier in earlier stages than the advanced stage.

Although it is challenging, if more specific autoantigen can be identified for RA, tolerogenic vaccines can be developed to prevent disease development. We also require identifying more different cell subsets controlling remission and resistance in order to identify disease outcomes.

In conclusion, I have presented some information about RA pathogenesis, and identified some gaps in current literature. Focusing on those gaps will make us move forward in RA research, as we still in need of understanding nature of disease.

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