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      Rheumatoid arthritis

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          Abstract

          Rheumatoid arthritis (RA) is a chronic, inflammatory, autoimmune disease that primarily affects the joints and is associated with autoantibodies that target various molecules including modified self-epitopes. The identification of novel autoantibodies has improved diagnostic accuracy, and newly developed classification criteria facilitate the recognition and study of the disease early in its course. New clinical assessment tools are able to better characterize disease activity states, which are correlated with progression of damage and disability, and permit improved follow-up. In addition, better understanding of the pathogenesis of RA through recognition of key cells and cytokines has led to the development of targeted disease-modifying antirheumatic drugs. Altogether, the improved understanding of the pathogenetic processes involved, rational use of established drugs and development of new drugs and reliable assessment tools have drastically altered the lives of individuals with RA over the past 2 decades. Current strategies strive for early referral, early diagnosis and early start of effective therapy aimed at remission or, at the least, low disease activity, with rapid adaptation of treatment if this target is not reached. This treat-to-target approach prevents progression of joint damage and optimizes physical functioning, work and social participation. In this Primer, we discuss the epidemiology, pathophysiology, diagnosis and management of RA.

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          Most cited references169

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          Fibroblast-like synoviocytes: key effector cells in rheumatoid arthritis.

          Rheumatoid arthritis (RA) remains a significant unmet medical need despite significant therapeutic advances. The pathogenesis of RA is complex and includes many cell types, including T cells, B cells, and macrophages. Fibroblast-like synoviocytes (FLS) in the synovial intimal lining also play a key role by producing cytokines that perpetuate inflammation and proteases that contribute to cartilage destruction. Rheumatoid FLS develop a unique aggressive phenotype that increases invasiveness into the extracellular matrix and further exacerbates joint damage. Recent advances in understanding the biology of FLS, including their regulation regulate innate immune responses and activation of intracellular signaling mechanisms that control their behavior, provide novel insights into disease mechanisms. New agents that target FLS could potentially complement the current therapies without major deleterious effect on adaptive immune responses.
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            Is Open Access

            An expansion of rare lineage intestinal microbes characterizes rheumatoid arthritis

            Background The adaptive immune response in rheumatoid arthritis (RA) is influenced by an interaction between host genetics and environment, particularly the host microbiome. Association of the gut microbiota with various diseases has been reported, though the specific components of the microbiota that affect the host response leading to disease remain unknown. However, there is limited information on the role of gut microbiota in RA. In this study we aimed to define a microbial and metabolite profile that could predict disease status. In addition, we aimed to generate a humanized model of arthritis to confirm the RA-associated microbe. Methods To identify an RA biomarker profile, the 16S ribosomal DNA of fecal samples from RA patients, first-degree relatives (to rule out environment/background as confounding factors), and random healthy non-RA controls were sequenced. Analysis of metabolites and their association with specific taxa was performed to investigate a potential mechanistic link. The role of an RA-associated microbe was confirmed using a human epithelial cell line and a humanized mouse model of arthritis. Results Patients with RA exhibited decreased gut microbial diversity compared with controls, which correlated with disease duration and autoantibody levels. A taxon-level analysis suggested an expansion of rare taxa, Actinobacteria, with a decrease in abundant taxa in patients with RA compared with controls. Prediction models based on the random forests algorithm suggested that three genera, Collinsella, Eggerthella, and Faecalibacterium, segregated with RA. The abundance of Collinsella correlated strongly with high levels of alpha-aminoadipic acid and asparagine as well as production of the proinflammatory cytokine IL-17A. A role for Collinsella in altering gut permeability and disease severity was confirmed in experimental arthritis. Conclusions These observations suggest dysbiosis in RA patients resulting from the abundance of certain rare bacterial lineages. A correlation between the intestinal microbiota and metabolic signatures could determine a predictive profile for disease causation and progression. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0299-7) contains supplementary material, which is available to authorized users.
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              Characterizing the quantitative genetic contribution to rheumatoid arthritis using data from twins.

              Twin concordance data for rheumatoid arthritis (RA) on their own provide only limited insight into the relative genetic and environmental contribution to the disease. We applied quantitative genetic methods to assess the heritability of RA and to examine for evidence of differences in the genetic contribution according to sex, age, and clinical disease characteristics. Data were analyzed from 2 previously published nationwide studies of twins with RA conducted in Finland and the United Kingdom. Heritability was assessed by variance components analysis. Differences in the genetic contribution by sex, age, age at disease onset, and clinical characteristics were examined by stratification. The power of the twin study design to detect these differences was examined through simulation. The heritability of RA was 65% (95% confidence interval [95% CI] 50-77) in the Finnish data and 53% (95% CI 40-65) in the UK data. There was no significant difference in the strength of the genetic contribution according to sex, age, age at onset, or disease severity subgroup. Both study designs had power to detect a contribution of at least 40% from the common family environment, and a difference in the genetic contribution of at least 50% between subgroups. Genetic factors have a substantial contribution to RA in the population, accounting for approximately 60% of the variation in liability to disease. Although tempered by power considerations, there is no evidence in these twin data that the overall genetic contribution to RA differs by sex, age, age at disease onset, and disease severity.
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                Author and article information

                Journal
                Nature Reviews Disease Primers
                Nat. Rev. Dis. Primers
                Springer Nature
                2056-676X
                February 8 2018
                February 8 2018
                : 4
                :
                : 18001
                Article
                10.1038/nrdp.2018.1
                29417936
                069010d0-8664-4ad2-8968-144ef5c016a0
                © 2018
                History

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