Genetic and clinical markers for predicting treatment responsiveness in rheumatoid arthritis

The added value of predictive biomarkers in treat-to-target strategies for rheumatoid arthritis patients: a conceptual modelling study

OBJECTIVES

To quantify the additional value of a hypothetical biomarker predicting response to treatment for RA regarding efficacy and costs by using a modelling design.

METHODS

A Markov model was built comparing a usual care T2T strategy with a biomarker-steered strategy for RA patients starting biologic therapy. Outcome measures include time spent in remission or low disease activity (LDA) and costs. Four additional scenario analyses were performed by varying biomarker or clinical care characteristics: (i) costs of the biomarker; (ii) sensitivity and specificity of the biomarker; (iii) proportion of eligible patients tapering; and (iv) medication costs.

RESULTS

In the base model, patients spent 2.9 months extra in LDA or remission in the biomarker strategy compared with usual care T2T over 48 months. Total costs were €43 301 and €42 568 for, respectively, the usual care and biomarker strategy, and treatment costs accounted for 91% of total costs in both scenarios. Cost savings were driven due to patients in the biomarker strategy experiencing remission or LDA earlier, and starting tapering sooner. Cost-effectiveness was not so much driven by costs or test characteristics of the biomarker (scenario 1/2), but rather by the level of early and proactive tapering and drug costs (scenarios 3/4).

CONCLUSIONS

The use of a biomarker for prediction of response to b/tsDMARD treatment in RA can be of added value to current treat-to-target clinical care. However, gains in efficacy are modest and cost gains are depending on a combination of early proactive tapering and high medication costs.

Title Current Status of the Search for Biomarkers for Optimal Therapeutic Drug Selection for Patients with Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an autoimmune disease characterized by destructive synovitis. It is significantly associated with disability, impaired quality of life, and premature mortality. Recently, the development of biological agents (including tumor necrosis factor-α and interleukin-6 receptor inhibitors) and Janus kinase inhibitors have advanced the treatment of RA; however, it is still difficult to predict which drug will be effective for each patient. To break away from the current therapeutic approaches that could be described as a “lottery,” there is an urgent need to establish biomarkers that stratify patients in terms of expected therapeutic responsiveness. This review deals with recent progress from multi-faceted analyses of the synovial tissue in RA, which is now bringing new insights into diverse features at both the cellular and molecular levels and their potential links with particular clinical phenotypes.

Rheumatology in the era of precision medicine: synovial tissue molecular patterns and treatment response in rheumatoid arthritis

PURPOSE OF REVIEW

A critical unmet need in rheumatoid arthritis (RA) is the identification of biomarkers that predict which of the available medications will be most effective for an individual in order to lower disease activity sooner than is afforded by the current treat-to-target approach. Here we will discuss recent reports examining the potential for synovial tissue molecular, cellular, and spatial profiling in defining objective measures of treatment response and therein developing personalized medicine for RA.

RECENT FINDINGS

Recent high-dimensional molecular profiling of RA synovium has provided unprecedented resolution of the cell types and pathways in tissues affected by rheumatic diseases. Heightened attention to tissue architecture is also emerging as a means to classify individual disease variation that may allow patients to be further stratified by therapeutic response. Although this wealth of data may have already pinpointed promising biomarkers, additional studies, likely including tissue-based functional drug response assays, will be required to demonstrate how the complex tissue environment responds.

SUMMARY

Molecular, cellular, and more recently spatial profiling of the RA synovium are uncovering fundamental features of the disease. Current investigations are examining whether this information will provide meaningful biomarkers for individualized medicine in RA.

Potential mechanisms of action of celastrol against rheumatoid arthritis: Transcriptomic and proteomic analysis

The clinical efficacy for treating of celastrol rheumatoid arthritis (RA) has been well-documented, but its mechanism of action remains unclear. Here we explored through what proteins and processes celastrol may act in activated fibroblast-like synoviocytes (FLS) from RA patients. Differential expression of genes and proteins after celastrol treatment of FLS was examined using RNA sequencing, label-free relatively quantitative proteomics and molecular docking. In this paper, expression of 26,565 genes and 3,372 proteins was analyzed. Celastrol was associated with significant changes in genes that respond to oxidative stress and oxygen levels, as well as genes that stabilize or synthesize components of the extracellular matrix. These results identify several potential mechanisms through which celastrol may inhibit inflammation in RA.

Genetic Polymorphisms Associated with Rheumatoid Arthritis Development and Antirheumatic Therapy Response

Rheumatoid arthritis (RA) is the most common inflammatory arthropathy worldwide. Possible manifestations of RA can be represented by a wide variability of symptoms, clinical forms, and course options. This multifactorial disease is triggered by a genetic predisposition and environmental factors. Both clinical and genealogical studies have demonstrated disease case accumulation in families. Revealing the impact of candidate gene missense variants on the disease course elucidates understanding of RA molecular pathogenesis. A multivariate genomewide association study (GWAS) based analysis identified the genes and signalling pathways involved in the pathogenesis of the disease. However, these identified RA candidate gene variants only explain 30% of familial disease cases. The genetic causes for a significant proportion of familial RA have not been determined until now. Therefore, it is important to identify RA risk groups in different populations, as well as the possible prognostic value of some genetic variants for disease development, progression, and treatment. Our review has two purposes. First, to summarise the data on RA candidate genes and the increased disease risk associated with these alleles in various populations. Second, to describe how the genetic variants can be used in the selection of drugs for the treatment of RA.

Disease modifying drugs for rheumatological diseases: a brief history of everything

The rheumatological diseases are a group of chronic, painful, degenerative and debilitating conditions with an increasing prevalence across the globe. The pathogenesis of these disorders is complex, overlapping and not fully understood. As such, it is difficult and time consuming to achieve correct diagnosis and complete remission for an individual patient. In this review we describe the most common forms of inflammatory arthritis and discuss how the management and treatment options for these rheumatic diseases have developed over time. We outline the successes and the limitations of current treatment regimens and discuss the economic burden of the current options. With advancements in understanding of disease mechanisms, we discuss the importance of the biologics revolution in the context of rheumatological disease and how the development of biosimilars and small molecule inhibitors will impact current treatment options in order to alleviate some of the cost burden of biological therapies. The ideal treatment strategy for the future would involve personalized and predictive medicine where by treatments can be tailored to an individual patient's needs in order to achieve fast and successful remission with no adverse events.