REVIEW URRENT C OPINION
New pathogenic insights into rheumatoid arthritis Gurpreet Jutley, Karim Raza, and Christopher D. Buckley
Purpose of review Rheumatoid arthritis (RA) is a heterogeneous chronic immune-mediated inflammatory disease, associated with significant morbidity and reduced life expectancy. Here, we review recent discoveries; particularly those which have attempted to integrate genome-wide association studies (GWAS) with biological pathways and cell types known to play a role in disease pathology in order to expand our current understanding of the pathogenesis of RA. As the role of stromal cells in the pathogenesis of RA has been reviewed in detail in Current Opinions in Rheumatology, this area will not be covered in this review. Recent findings Although our understandings of the pathogenic processes that drive disease in RA remain incomplete, remarkable advances over the past year can be highlighted. GWAS have raised awareness of important new risk loci with genes that either are the targets of approved therapies for RA, or involve pathways for drugs that could be repurposed from other disease indications such as cancer. Furthermore, promising strides have been made in predicting the likelihood of developing RA in those at risk using human leukocyte antigen (HLA), smoking, and autoantibody status prediction models. These findings give a fresh insight into RA pathogenesis and help identify new, or repurpose known therapeutic targets from other disease areas. Summary The findings discussed in this review underscore the progress made to date and the need for future studies, investigating disease mechanisms in RA, with particular interest in at-risk RA gene loci, their function in immune and stromal cells within the synovium, and how they interact with environmental factors to initiate and perpetuate disease. Keywords genetics, inflammation, rheumatoid arthritis, synovium
INTRODUCTION Work over the past 20 years, to define the phases and processes in the transition from health to established disease, places rheumatoid arthritis (RA) in a unique position amongst all immune-mediated inflammatory diseases (IMIDs). Very well validated genetic, epigenetic, and environmental factors have now been identified that interact with immunological and biochemical processes to drive disease pathology. However, it has only been in the past few years, using new bioinformatics methods that integrate genetic and epigenetic data with biochemical pathways and cell types involved in the disease, that real progress has been made in our understanding of how RA starts, where and when immune tolerance is broken, and why the synovial inflammation and bone destruction, so characteristic of the disease, persists. Recent European League of Associations for Rheumatology (EULAR) initiatives have laid down important consensus foundations that attempt to
‘map’ the ‘pathogenic journey’ from heath to disease in those who develop RA (Fig. 1). In some cases, individuals will move through phases sequentially from preclinical phases through clinical phases, and finally a disease classified as RA [1]. Although it is often assumed that all individuals move sequentially through these phases, the evidence for this is scant. Importantly, it is known that in some cases, individuals may also move ‘backwards’, for example, with an individual with unclassified clinical arthritis getting better with no further systemic features of the disease (Fig. 1). Furthermore, it is possible that individuals Rheumatology Research Group, Centre for Translational Inflammation Research, University of Birmingham, Edgbaston, Birmingham, UK Correspondence to Christopher D. Buckley, Centre for Translational Inflammation Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK. Tel: +44 121 371 3240; e-mail: c.d.buckley@bham. ac.uk Curr Opin Rheumatol 2015, 27:249–255 DOI:10.1097/BOR.0000000000000174
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KEY POINTS GWAS is an effective method for identifying at-risk gene loci; however, the exact mechanism of how they convey risk remains to be unidentified in the majority of cases. RA prediction models based on genetic variants and smoking status exist and have a potentially exciting and new role to play in screening the general population with a family history of RA. The synovium in phase C and D (i.e. the presence of musculoskeletal symptoms without joint swelling and evidence of RA-related systemic autoimmunity) is normal, suggesting RA tolerance is broken in extraarticular sites such as the lungs, lymphoid, or periodontal tissue. Treg cells – integral in regulating inflammation – malfunction in RA patients and this represents a promising therapeutic potential.
will skip particular phases, or that the phases will not develop in the order represented, for example, with evidence of systemic autoimmunity developing after the onset of the symptoms. Dissecting these relationships is central to the issue of prognostication in RA.
Despite compelling genetic and therapeutic evidence for a deregulated immune system in the pathogenesis of RA [2], predicting the development of RA, its severity, and collateral tissue damage based on immunogenic and serological markers alone remains unrewarding [3]. This may be due to the fact that other cellular (e.g. stromal [4,5]), molecular (e.g. epigenetic [6]), and environmental (e.g. periodontal disease [7]) mechanisms have not yet been fully taken into account. The introduction of biologic treatments that deplete leukocytes and their secreted products has led to dramatic improvements in the management of IMIDs [8,9]. However, these therapies do not reverse tissue damage and do not result in a cure. Many patients, in whom clinical remission has been achieved, subsequently relapse once treatment is withdrawn, suggesting that additional therapeutic targets, responsible for complete resolution of inflammation, still remain to be discovered. In this review, we will not cover these areas, but rather focus on new and exciting developments over the past year that have shown how a new interpretation of genetic studies that combine traditional genetic approaches with epigenetic and serological findings can contribute to understanding disease pathology and facilitate drug discovery.
Challenging linearity
Phase A&B
Phase C
Phase D
Phase E
Phase F
Challenging directionality
FIGURE 1. Variations of the traditional view of linear unidirectional progression from health to rheumatoid arthritis (RA). Transition between phases leading to the development of RA may not always be linear or unidirectional. ‘Challenging linearity’ illustrates that patients may skip phase C, and progress from phases A and B directly to phase D, E, or even F. Multiple potential routes to RA are possible; thus a patient could move from phases A and B to phase C, skip phase D, and develop, as their first clinical feature, a clinically apparent arthritis with synovitis (phase E). ’Challenging directionality’ illustrates that patients may have resolution of symptoms and move from phase D, E or even F back to phases A and B. 250
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New pathogenic insights into rheumatoid arthritis Jutley et al.
GENETIC, IMMUNOLOGICAL, AND ENVIRONMENTAL RISK FACTORS FOR RHEUMATOID ARTHRITIS A number of common genetic risk variants associate with susceptibility to the two important subtypes of RA, defined according to the presence of a range of RA-specific autoantibodies – the anticitrullinated protein/peptide antibodies (ACPAs) [10,11]. Importantly, whilst the heritability of these two subtypes of RA is similar [12], the genetic variants which underlie these subtypes differ. These common risk variants, identified largely through whole genome association studies [13,14], are estimated to account for 20–60% of the genetic component of susceptibility. There is thus a significant ‘missing heritability’. Furthermore, the functional consequence of these genetic risk variants and the mechanisms whereby they interact with environmental risk factors is unclear. Genome-wide association studies have proven fruitful for gaining a better understanding of the genetic associations of RA. These studies can yield information that can prove to be difficult to interpret. Due to the haploid structure, GWAS tend to identify large groups of single-nucleotide polymorphisms (SNPs). Furthermore, if causal variants are identified, the significance of the non-coding elements is unknown, thereby rendering analysis difficult by existing gene regulatory models. For example, one recent study used a fine mapping algorithm to identify casual variants for 21 autoimmune diseases from pooled genotyping data. The study revealed 90% of causal nucleotide changes are non-coding, with 60% mapping to immune cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune activation. Causal variants frequently appeared at binding sites for master regulators of immune differentiation and gene activation, but only 10–20% altered known transcription factorbinding motifs [15 ]. Another exciting new GWAS meta-analysis revealed a total of 101 SNPs associated with RA. Many of these SNPs are associated with immune dysregulation and inflammation [16 ]. However, SNPs in CDK4-CDK6 were found to be associated with RA, providing new biological targets for drug discovery. Non-major histocompatibility complex (MHC) RA risk loci are associated with ‘permissive’ histone marks, particularly in regulatory T cells (T-reg cells), suggesting regulatory T cells play an important part in the initial phase of the disease [16 ]. This suggestion is underpinned further by studies evaluating T-reg cells as potential therapeutic targets, one animal study suggesting polyclonal T-reg cells’ effectiveness if given prior to onset of &&
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the symptoms [17]. T-reg cells appear to be defective in RA patients and there may be multiple explanations for this. Inflammatory cytokines may hinder T-reg cells’ ability to inhibit cytokine production of effector T cell or making effector T cells resistant to T-reg cells, and this function appears to be restored after treatment with anti-tumour necrosis factor (TNF) [18]. Cytotoxic T lymphocyte-associated antigen 4 – a protein receptor responsible for reducing CD80 and CD86 from antigen-presenting cell surfaces – may not be expressed on T-reg cells in RA [19]. Understanding of the T cells mediating RA and the self-antigens they recognize has been difficult primarily as they are negatively selected out of the circulation by the thymus. One of the self-antigens (RPL23A) identified as a result of generating T cells capable of mediating arthritis in mice was able to stimulate CD4þ T cells in R7–39 mice via RPL23Adervived peptide–MHC class II complexes, driving them to differentiate into T-helper effector cells capable of inducing autoimmune arthritis. RPL23A stimulated CD4þ T cells to secrete interferon (IFN)gamma in a subset of RA patients’ synovial fluid [20 ]. These findings in humans and mice suggest that abnormalities of T-cell selection in the thymus may play a pathogenic role at least in a subset of patients with RA. Interestingly, the effect of ethnicity on the subtypes of RA has been highlighted in recent GWAS studies. One study showed PAD14 – a specific nonMHC at-risk loci for RA – was significantly related only to ACPA-positive RA in the Asian population. However, it was related to both ACPA-positive and negative RA in the European population [21,22]. Genome-wide association studies have successfully identified potential therapeutic targets. One study showed RA risk loci in the nuclear factorkappaB signalling pathway (NF-kB); this pathway is involved in regulating genes involved in immunity. Engagement of CD40 is one of the ways this pathway can be triggered and therefore can be targeted for treatment [23]. Similarly, another new treatment strategy targets the Janus kinase (JAK) pathway [24 ]. Eleven genes from RA risk loci linked to the JAK STAT pathway [25]. This pathway is the principle signalling mechanism in response to many cytokines involved in RA, including interleukin (IL)-6 [26]. Studies to date have mainly assessed the contribution of genetic risk factors to the development of RA (phase F). Recent evidence suggests that the human leukocyte antigen (HLA) class II locus is associated less with the risk of developing ACPA and more with the risk of progression from a state of ACPA-positivity (phase C) to having RA [27]; by &&
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contrast, environmental factors including smoking [27,28] and pulmonary inflammation [29] may be more important in transition to phase C. Smoking is the major environmental risk identified to date and has specifically been associated with the development of ACPA-positive RA [30–32], but its mechanism of action and the potential for smoking cessation to influence transition between the different stages of the disease have not been fully investigated.
SYSTEMIC AUTOIMMUNITY ASSOCIATED WITH THE DEVELOPMENT OF RHEUMATOID ARTHRITIS An important goal in the study of early autoimmune disease is to identify the first signs of immunological dysregulation which constitute the starting point of the established immune response against self-antigens leading to tissue damage. Such identification would allow early and effective treatment to prevent precipitation of full-blown disease, which can rarely be cured once fully established. One study attempted to identify such patients by creating a RA prediction model. It combined the odds ratio (OR) of 15 HLA-DRB1 alleles, 31 SNPs, and ever-smoking status in men to determine the risk using computer simulation confidence interval (CI)based risk categorization [33 ]. The model was used to assess its ability to predict ACPA-positive RA in two large cohorts (Welcome Trust Case Control Consortium and UK RA Genetics Group Consortium). The study results suggested high-risk individuals from the HLA model were associated with young-onset RA, whereas smoking was associated with older-onset RA. The results also suggested that the model could be used as a screening tool for cohorts with a strong family history of RA in order to allow preventive methods to be evaluated [33 ]. Some biomarkers such as autoantibodies are indeed present several years before symptom onset. Importantly, rheumatoid factor and ACPA can be detected in serum of patients with RA up to 14 years before the first clinical signs and symptoms of arthritis become manifested [34]. Of these individuals at risk, 30% of the autoantibody-positive patients who experienced arthralgia developed clinical signs of arthritis after approximately 1 year of follow-up [35,36]. A common feature of these autoantibodies is their cross-reactivity with post-translationally modified (PTM) proteins. Disruption of PTMs by environmental factors and lifestyle has been linked to the multistep progression of other diseases such as cancer, as well as autoimmune diseases. In the healthy population, autoantibodies against PTM proteins are very rare, thereby providing proof of &&
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concept that it is possible to identify disease-specific biomarkers before the disease onset. These autoantibodies and other blood-based biomarkers are thus suitable and readily available identifiers of the atrisk population. Very excitingly, new studies have recently been performed to evaluate the presence of these or other biomarkers to predict further disease development in healthy individuals who may be at risk of RA [37 ]. &
WHERE IS TOLERANCE BROKEN AND WHERE DOES RHEUMATOID ARTHRITIS ‘BEGIN’? Although the principal site of pathology in established RA is the synovial tissue, there has been considerable controversy as to when, in the natural history of RA, synovial inflammation first develops, and in particular how its onset relates to the development of systemic autoimmunity. Although autoantibodies precede the development of clinical symptoms and signs of arthritis, there have been suggestions that a phase of asymptomatic synovitis precedes clinically manifested arthritis [38]. This concept has recently been challenged in a prospective study [39] of patients who are positive for the presence of RA-specific autoantibodies (ACPA) and have joint pain, but without clinically apparent arthritis. In these patients, no evidence of infiltrating inflammatory cells normally characterizing early and established RA could be demonstrated [39]. However, histological studies in early RA patients have not shown features of synovial inflammation. Rather, the data suggest that synovial inflammation develops very near the time when the joint first swells clinically [40]. Does this mean that the synovium in patients in phases C and D is ‘normal’? This remains unclear as PET imaging and MRI in patients in this phase have revealed abnormalities [41,42], and other non-haemopoietic cells such as fibroblasts that play a role in inflammation have not been systematically assessed. If the synovium is ‘normal’, in which compartment of the body does the disease originate, and where do genetic and environmental risk factors interact in the breaking of immunological tolerance? Extra-articular sites proposed for the breakdown of tolerance include the gums of patients with periodontitis and the lungs of smokers, both of which are chronically inflamed [43,44]. Addressing these will be crucial to understanding which sites to study (e.g. by imaging and histology) in the prediction of outcome and which biomarkers to investigate. The immune responses occurring in lymphoid periodontal and lung tissue may play a pivotal role in the earliest phases of the disease. In the lymph Volume 27 Number 3 May 2015
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nodes, cells of both the innate and the adaptive immune response reside in close contact, reacting to specific antigens leading to the production of antibodies. In animal models, changes in the lymph nodes are observed in the latency phase of arthritis, before any sign of synovitis develops [45,46]. Similar studies have now been confirmed in humans in phases C and D [47]. The lung is the site where environmental triggers are in direct contact with cells of the immune system, such as macrophages and dendritic cells, possibly leading to activation of the immune response. Epidemiological studies have proposed smoking as one of the main environmental factors associated with RA [48], and there is the suggestion that citrullination induced by smoking might be the first step in the pathogenic chain of RA [49]. Genomic analysis of tissue from the lung from smokers and non-smokers provides an opportunity for increased understanding of how genes, environment, and immunity interact. A number of clinical studies point toward an association between periodontal disease and RA [7]. There are remarkable similarities between RA and chronic and/or aggressive periodontitis. Both diseases are chronic destructive inflammatory disorders characterized by dysregulation of the host inflammatory response. Since periodontal disease is associated with the occurrence of RA and shows many of the inflammatory features also found in the inflamed synovium, this site is of importance to study in the pre-arthritic phase [50 ]. &
SEROLOGICAL BIOMARKERS Considerable evidence suggests that rheumatoid factor and ACPA are useful in the prediction of the development of RA when measured at phases C, D, and E [35,51]. Furthermore, the predictive utility of these antibodies in addition to clinical and genetic markers has been assessed [52,53]. Low-molecular-weight metabolites have been assessed in a range of chronic inflammatory and malignant diseases, in which case identification has not only provided prognostically useful information [54] but has also shed light on disease pathways which conventional approaches failed to identify [55]. Most work on soluble molecules in the field of chronic inflammatory disease has focussed on proteins, in particular, pro-inflammatory cytokines and chemokines. Recent work in the patients with RA has shown that low-molecularweight metabolite signatures can be used to predict treatment response [56 ] and associate with the extent of inflammation [57 ]. Therefore, characterization of predictive metabolites may shed light on &
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the pathogenic processes. There is also increasing evidence that lipid mediators [58–61] are key orchestrators of the inflammatory process and that many of these play an important role in the resolution of inflammation. Finally, a direct pathogenic role for ACPA antibodies has been shown in work which highlights how ACPA can drive osteoclastogenesis [62] and how patients in phases C and D of disease have evidence of bone destruction well before the onset of synovitis [63 ]. &
CONCLUSION Discoveries regarding the mechanisms that drive pathogenesis have important implications for the development of new treatments for RA. There have been significant breakthroughs in our understanding of disease pathology in the past year, but large gaps in knowledge remain which are reflected in practice with a significant proportion of patients refractive to current treatment. An area of interest lies in identifying further genetic risk and investigating the implication of the genetic variants and the effect on disease biology. In addition to this, environmental factors need to be recognized and their role in breaking RA tolerance explored further. These areas could potentially hold the key for preventing RA from developing. Acknowledgements We would like to thank members of the Euro-TEAM consortium for discussions www.team-arthritis.eu Financial support and sponsorship The study was supported by Arthritis Research UK. Conflicts of interest C.B. and K.R. have received honoraria from Pfizer, UCB, Novartis, Roche, and BMS. The remaining author has no conflicts of interest.
REFERENCES AND RECOMMENDED READING Papers of particular interest, published within the annual period of review, have been highlighted as: & of special interest && of outstanding interest 1. Gerlag DM, Raza K, van Baarsen LG, et al. EULAR recommendations for terminology and research in individuals at risk of rheumatoid arthritis (RA): report from the Study Group for Risk Factors for RA. Ann Rheum Dis 2012; 71:638–641. 2. McInnes IB, Schett G. The pathogenesis of rheumatoid arthritis. N Engl J Med 2011; 365:2205–2219. 3. Raza K, Filer A. Predicting the development of RA in patients with early undifferentiated arthritis. Best Pract Res Clin Rheumatol 2009; 23:25–36. 4. Buckley CD, Pilling D, Lord JM, et al. Fibroblasts regulate the switch from acute resolving to chronic persistent inflammation. Trends Immunol 2001; 22:199–204. 5. Buckley CD, Filer A, Haworth O, et al. Defining a role for fibroblasts in the persistence of chronic inflammatory joint disease. Ann Rheum Dis 2004; 63 (Suppl 2):ii92–ii95.
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The extent of the anticitrullinated protein antibody repertoire is associated with arthritis development in patients with seropositive arthralgia. Ann Rheum Dis 2011; 70:128–133. 36. Bos WH, Wolbink GJ, Boers M, et al. Arthritis development in patients with arthralgia is strongly associated with anticitrullinated protein antibody status: a prospective cohort study. Ann Rheum Dis 2010; 69:490–494. 37. Young KA, Deane KD, Derber LA, et al. Relatives without rheumatoid arthritis & show reactivity to anticitrullinated protein/peptide antibodies that are associated with arthritis-related traits: studies of the etiology of rheumatoid arthritis. Arthritis Rheum 2013; 65:1995–2004. This study demonstrated that free first degree relatives of patients with RA who were seronegative for ACPA demonstrated reactivity in their sera to multiple ACPAs. 38. Kraan MC, Versendaal H, Jonker M, et al. Asymptomatic synovitis precedes clinically manifest arthritis. Arthritis Rheum 1998; 41:1481–1488. 39. van de Sande MG, de Hair MJ, van der Leij C, et al. Different stages of rheumatoid arthritis: features of the synovium in the preclinical phase. Ann Rheum Dis 2011; 70:772–777. 40. de Hair MJ, van de Sande MG, Ramwadhdoebe TH, et al. Features of the synovium of individuals at risk of developing rheumatoid arthritis: implications for understanding preclinical rheumatoid arthritis. Arthritis Rheumatol 2014; 66:513–522. 41. Gent YY, Voskuyl AE, Kloet RW, et al. Macrophage PET imaging as biomarker for preclinical rheumatoid arthritis. Arthritis Rheum 2012; 64:62–66. 42. van Steenbergen HW, van Nies JA, Huizinga TW, et al. Characterising arthralgia in the preclinical phase of rheumatoid arthritis using MRI. Ann Rheum Dis 2014; doi: 10.1136/annrheumdis-2014-205522. [Epub ahead of print] 43. Ytterberg AJ, Joshua V, Reynisdottir G, et al. Shared immunological targets in the lungs and joints of patients with rheumatoid arthritis: identification and validation. Ann Rheum Dis 2014; doi: 10.1136/annrheumdis-2013-204912. [Epub ahead of print] 44. Catrina AI, Deane KD, Scher JU. Gene, environment, microbiome and mucosal immune tolerance in rheumatoid arthritis. Rheumatology 2014. [Epub ahead of print] 45. Li J, Kuzin I, Moshkani S, et al. Expanded CD23(þ)/CD21(hi) B cells in inflamed lymph nodes are associated with the onset of inflammatory-erosive arthritis in TNF-transgenic mice and are targets of anti-CD20 therapy. J Immunol 2010; 184:6142–6150. 46. Rodriguez-Palmero M, Pelegri C, Ferri MJ, et al. Alterations of lymphocyte populations in lymph nodes but not in spleen during the latency period of adjuvant arthritis. Inflammation 1999; 23:153–165. 47. van Baarsen LG, de Hair MJ, Ramwadhdoebe TH, et al. The cellular composition of lymph nodes in the earliest phase of inflammatory arthritis. Ann Rheum Dis 2013; 72:1420–1424. 48. Stolt P, Bengtsson C, Nordmark B, et al. Quantification of the influence of cigarette smoking on rheumatoid arthritis: results from a population based case-control study, using incident cases. Ann Rheum Dis 2003; 62:835– 841. 49. Reynisdottir G, Karimi R, Joshua V, et al. Structural changes and antibody enrichment in the lungs are early features of anticitrullinated protein antibodypositive rheumatoid arthritis. Arthritis Rheumatol 2014; 66:31–39. 50. de Pablo P, Dietrich T, Chapple IL, et al. The autoantibody repertoire in & periodontitis: a role in the induction of autoimmunity to citrullinated proteins in rheumatoid arthritis? Ann Rheum Dis 2014; 73:580–586. This study showed an autoantibody response, predominately uncitrullinated, with periodontitis, after taking into account confounders such as smoking. The data suggest that loss of tolerance could lead to citrullinated epitopes emerging. 51. Raza K, Breese M, Nightingale P, et al. Predictive value of antibodies to cyclic citrullinated peptide in patients with very early inflammatory arthritis. J Rheumatol 2005; 32:231–238. 52. van der Helm-van Mil AH, le Cessie S, van Dongen H, et al. A prediction rule for disease outcome in patients with recent-onset undifferentiated arthritis: how to guide individual treatment decisions. Arthritis Rheum 2007; 56:433– 440. 53. van der Helm-van Mil AH, Detert J, le Cessie S, et al. Validation of a prediction rule for disease outcome in patients with recent-onset undifferentiated arthritis: moving toward individualized treatment decision-making. Arthritis Rheum 2008; 58:2241–2247. 54. Brindle JT, Antti H, Holmes E, et al. Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics. Nat Med 2002; 8:1439–1444.
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New pathogenic insights into rheumatoid arthritis Jutley et al. 55. Sreekumar A, Poisson LM, Rajendiran TM, et al. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature 2009; 457:910–914. 56. Kapoor SR, Filer A, Fitzpatrick MA, et al. Metabolic profiling predicts response & to antitumor necrosis factor a therapy in patients with rheumatoid arthritis. Arthritis Rheum 2013; 65:1448–1456. The urine of RA patients before and after treatment shows changes in metabolic fingerprint. Differences in metabolic profile also seen when treating with infliximab and etanercept, suggesting a difference in mode of action of there two biologic agents. 57. Young SP, Kapoor SR, Viant MR, et al. The impact of inflammation on metabo& lomic profiles in patients with arthritis. Arthritis Rheum 2013; 65:2015–2023. Lactate and lipids are important discriminators of inflammatory burden in early arthritis patient groups. 58. Haworth O, Cernadas M, Yang R, et al. Resolving E1 regulates interleukin 23, interferon-gamma and lipoxin A4 to promote the resolution of allergic airway inflammation. Nat Immunol 2008; 9:873–879.
59. Lawrence T, Willoughby DA, Gilroy DW. Anti-inflammatory lipid mediators and insights into the resolution of inflammation. Nat Rev Immunol 2002; 2:787– 795. 60. Serhan CN, Brain SD, Buckley CD, et al. Resolution of inflammation: state of the art, definitions and terms. FASEB J 2007; 21:325–332. 61. Serhan CN, Krishnamoorthy S, Recchiuti A, et al. Novel anti-inflammatory proresolving mediators and their receptors. Curr Top Med Chem 2011; 11:629– 647. 62. Harre U, Georgess D, Bang H, et al. Induction of osteoclastogenesis and bone loss by human autoantibodies against citrullinated vimentin. J Clin Invest 2012; 122:1791–1802. 63. Kleyer A, Finzel S, Rech J, et al. Bone loss before the clinical onset of & rheumatoid arthritis in subjects with anticitrullinated protein antibodies. Ann Rheum Dis 2014; 73:854–860. This study shows that structural bone damage occurs before the onset of clinical synovitis in people who carry anti-CCP antibodies.
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New pathogenic insights into rheumatoid arthritis Gurpreet Jutley, Karim Raza, and Christopher D. Buckley
Purpose of review Rheumatoid arthritis (RA) is a heterogeneous chronic immune-mediated inflammatory disease, associated with significant morbidity and reduced life expectancy. Here, we review recent discoveries; particularly those which have attempted to integrate genome-wide association studies (GWAS) with biological pathways and cell types known to play a role in disease pathology in order to expand our current understanding of the pathogenesis of RA. As the role of stromal cells in the pathogenesis of RA has been reviewed in detail in Current Opinions in Rheumatology, this area will not be covered in this review. Recent findings Although our understandings of the pathogenic processes that drive disease in RA remain incomplete, remarkable advances over the past year can be highlighted. GWAS have raised awareness of important new risk loci with genes that either are the targets of approved therapies for RA, or involve pathways for drugs that could be repurposed from other disease indications such as cancer. Furthermore, promising strides have been made in predicting the likelihood of developing RA in those at risk using human leukocyte antigen (HLA), smoking, and autoantibody status prediction models. These findings give a fresh insight into RA pathogenesis and help identify new, or repurpose known therapeutic targets from other disease areas. Summary The findings discussed in this review underscore the progress made to date and the need for future studies, investigating disease mechanisms in RA, with particular interest in at-risk RA gene loci, their function in immune and stromal cells within the synovium, and how they interact with environmental factors to initiate and perpetuate disease. Keywords genetics, inflammation, rheumatoid arthritis, synovium
INTRODUCTION Work over the past 20 years, to define the phases and processes in the transition from health to established disease, places rheumatoid arthritis (RA) in a unique position amongst all immune-mediated inflammatory diseases (IMIDs). Very well validated genetic, epigenetic, and environmental factors have now been identified that interact with immunological and biochemical processes to drive disease pathology. However, it has only been in the past few years, using new bioinformatics methods that integrate genetic and epigenetic data with biochemical pathways and cell types involved in the disease, that real progress has been made in our understanding of how RA starts, where and when immune tolerance is broken, and why the synovial inflammation and bone destruction, so characteristic of the disease, persists. Recent European League of Associations for Rheumatology (EULAR) initiatives have laid down important consensus foundations that attempt to
‘map’ the ‘pathogenic journey’ from heath to disease in those who develop RA (Fig. 1). In some cases, individuals will move through phases sequentially from preclinical phases through clinical phases, and finally a disease classified as RA [1]. Although it is often assumed that all individuals move sequentially through these phases, the evidence for this is scant. Importantly, it is known that in some cases, individuals may also move ‘backwards’, for example, with an individual with unclassified clinical arthritis getting better with no further systemic features of the disease (Fig. 1). Furthermore, it is possible that individuals Rheumatology Research Group, Centre for Translational Inflammation Research, University of Birmingham, Edgbaston, Birmingham, UK Correspondence to Christopher D. Buckley, Centre for Translational Inflammation Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK. Tel: +44 121 371 3240; e-mail: c.d.buckley@bham. ac.uk Curr Opin Rheumatol 2015, 27:249–255 DOI:10.1097/BOR.0000000000000174
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Rheumatoid arthritis
KEY POINTS GWAS is an effective method for identifying at-risk gene loci; however, the exact mechanism of how they convey risk remains to be unidentified in the majority of cases. RA prediction models based on genetic variants and smoking status exist and have a potentially exciting and new role to play in screening the general population with a family history of RA. The synovium in phase C and D (i.e. the presence of musculoskeletal symptoms without joint swelling and evidence of RA-related systemic autoimmunity) is normal, suggesting RA tolerance is broken in extraarticular sites such as the lungs, lymphoid, or periodontal tissue. Treg cells – integral in regulating inflammation – malfunction in RA patients and this represents a promising therapeutic potential.
will skip particular phases, or that the phases will not develop in the order represented, for example, with evidence of systemic autoimmunity developing after the onset of the symptoms. Dissecting these relationships is central to the issue of prognostication in RA.
Despite compelling genetic and therapeutic evidence for a deregulated immune system in the pathogenesis of RA [2], predicting the development of RA, its severity, and collateral tissue damage based on immunogenic and serological markers alone remains unrewarding [3]. This may be due to the fact that other cellular (e.g. stromal [4,5]), molecular (e.g. epigenetic [6]), and environmental (e.g. periodontal disease [7]) mechanisms have not yet been fully taken into account. The introduction of biologic treatments that deplete leukocytes and their secreted products has led to dramatic improvements in the management of IMIDs [8,9]. However, these therapies do not reverse tissue damage and do not result in a cure. Many patients, in whom clinical remission has been achieved, subsequently relapse once treatment is withdrawn, suggesting that additional therapeutic targets, responsible for complete resolution of inflammation, still remain to be discovered. In this review, we will not cover these areas, but rather focus on new and exciting developments over the past year that have shown how a new interpretation of genetic studies that combine traditional genetic approaches with epigenetic and serological findings can contribute to understanding disease pathology and facilitate drug discovery.
Challenging linearity
Phase A&B
Phase C
Phase D
Phase E
Phase F
Challenging directionality
FIGURE 1. Variations of the traditional view of linear unidirectional progression from health to rheumatoid arthritis (RA). Transition between phases leading to the development of RA may not always be linear or unidirectional. ‘Challenging linearity’ illustrates that patients may skip phase C, and progress from phases A and B directly to phase D, E, or even F. Multiple potential routes to RA are possible; thus a patient could move from phases A and B to phase C, skip phase D, and develop, as their first clinical feature, a clinically apparent arthritis with synovitis (phase E). ’Challenging directionality’ illustrates that patients may have resolution of symptoms and move from phase D, E or even F back to phases A and B. 250
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GENETIC, IMMUNOLOGICAL, AND ENVIRONMENTAL RISK FACTORS FOR RHEUMATOID ARTHRITIS A number of common genetic risk variants associate with susceptibility to the two important subtypes of RA, defined according to the presence of a range of RA-specific autoantibodies – the anticitrullinated protein/peptide antibodies (ACPAs) [10,11]. Importantly, whilst the heritability of these two subtypes of RA is similar [12], the genetic variants which underlie these subtypes differ. These common risk variants, identified largely through whole genome association studies [13,14], are estimated to account for 20–60% of the genetic component of susceptibility. There is thus a significant ‘missing heritability’. Furthermore, the functional consequence of these genetic risk variants and the mechanisms whereby they interact with environmental risk factors is unclear. Genome-wide association studies have proven fruitful for gaining a better understanding of the genetic associations of RA. These studies can yield information that can prove to be difficult to interpret. Due to the haploid structure, GWAS tend to identify large groups of single-nucleotide polymorphisms (SNPs). Furthermore, if causal variants are identified, the significance of the non-coding elements is unknown, thereby rendering analysis difficult by existing gene regulatory models. For example, one recent study used a fine mapping algorithm to identify casual variants for 21 autoimmune diseases from pooled genotyping data. The study revealed 90% of causal nucleotide changes are non-coding, with 60% mapping to immune cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune activation. Causal variants frequently appeared at binding sites for master regulators of immune differentiation and gene activation, but only 10–20% altered known transcription factorbinding motifs [15 ]. Another exciting new GWAS meta-analysis revealed a total of 101 SNPs associated with RA. Many of these SNPs are associated with immune dysregulation and inflammation [16 ]. However, SNPs in CDK4-CDK6 were found to be associated with RA, providing new biological targets for drug discovery. Non-major histocompatibility complex (MHC) RA risk loci are associated with ‘permissive’ histone marks, particularly in regulatory T cells (T-reg cells), suggesting regulatory T cells play an important part in the initial phase of the disease [16 ]. This suggestion is underpinned further by studies evaluating T-reg cells as potential therapeutic targets, one animal study suggesting polyclonal T-reg cells’ effectiveness if given prior to onset of &&
&&
&&
the symptoms [17]. T-reg cells appear to be defective in RA patients and there may be multiple explanations for this. Inflammatory cytokines may hinder T-reg cells’ ability to inhibit cytokine production of effector T cell or making effector T cells resistant to T-reg cells, and this function appears to be restored after treatment with anti-tumour necrosis factor (TNF) [18]. Cytotoxic T lymphocyte-associated antigen 4 – a protein receptor responsible for reducing CD80 and CD86 from antigen-presenting cell surfaces – may not be expressed on T-reg cells in RA [19]. Understanding of the T cells mediating RA and the self-antigens they recognize has been difficult primarily as they are negatively selected out of the circulation by the thymus. One of the self-antigens (RPL23A) identified as a result of generating T cells capable of mediating arthritis in mice was able to stimulate CD4þ T cells in R7–39 mice via RPL23Adervived peptide–MHC class II complexes, driving them to differentiate into T-helper effector cells capable of inducing autoimmune arthritis. RPL23A stimulated CD4þ T cells to secrete interferon (IFN)gamma in a subset of RA patients’ synovial fluid [20 ]. These findings in humans and mice suggest that abnormalities of T-cell selection in the thymus may play a pathogenic role at least in a subset of patients with RA. Interestingly, the effect of ethnicity on the subtypes of RA has been highlighted in recent GWAS studies. One study showed PAD14 – a specific nonMHC at-risk loci for RA – was significantly related only to ACPA-positive RA in the Asian population. However, it was related to both ACPA-positive and negative RA in the European population [21,22]. Genome-wide association studies have successfully identified potential therapeutic targets. One study showed RA risk loci in the nuclear factorkappaB signalling pathway (NF-kB); this pathway is involved in regulating genes involved in immunity. Engagement of CD40 is one of the ways this pathway can be triggered and therefore can be targeted for treatment [23]. Similarly, another new treatment strategy targets the Janus kinase (JAK) pathway [24 ]. Eleven genes from RA risk loci linked to the JAK STAT pathway [25]. This pathway is the principle signalling mechanism in response to many cytokines involved in RA, including interleukin (IL)-6 [26]. Studies to date have mainly assessed the contribution of genetic risk factors to the development of RA (phase F). Recent evidence suggests that the human leukocyte antigen (HLA) class II locus is associated less with the risk of developing ACPA and more with the risk of progression from a state of ACPA-positivity (phase C) to having RA [27]; by &&
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contrast, environmental factors including smoking [27,28] and pulmonary inflammation [29] may be more important in transition to phase C. Smoking is the major environmental risk identified to date and has specifically been associated with the development of ACPA-positive RA [30–32], but its mechanism of action and the potential for smoking cessation to influence transition between the different stages of the disease have not been fully investigated.
SYSTEMIC AUTOIMMUNITY ASSOCIATED WITH THE DEVELOPMENT OF RHEUMATOID ARTHRITIS An important goal in the study of early autoimmune disease is to identify the first signs of immunological dysregulation which constitute the starting point of the established immune response against self-antigens leading to tissue damage. Such identification would allow early and effective treatment to prevent precipitation of full-blown disease, which can rarely be cured once fully established. One study attempted to identify such patients by creating a RA prediction model. It combined the odds ratio (OR) of 15 HLA-DRB1 alleles, 31 SNPs, and ever-smoking status in men to determine the risk using computer simulation confidence interval (CI)based risk categorization [33 ]. The model was used to assess its ability to predict ACPA-positive RA in two large cohorts (Welcome Trust Case Control Consortium and UK RA Genetics Group Consortium). The study results suggested high-risk individuals from the HLA model were associated with young-onset RA, whereas smoking was associated with older-onset RA. The results also suggested that the model could be used as a screening tool for cohorts with a strong family history of RA in order to allow preventive methods to be evaluated [33 ]. Some biomarkers such as autoantibodies are indeed present several years before symptom onset. Importantly, rheumatoid factor and ACPA can be detected in serum of patients with RA up to 14 years before the first clinical signs and symptoms of arthritis become manifested [34]. Of these individuals at risk, 30% of the autoantibody-positive patients who experienced arthralgia developed clinical signs of arthritis after approximately 1 year of follow-up [35,36]. A common feature of these autoantibodies is their cross-reactivity with post-translationally modified (PTM) proteins. Disruption of PTMs by environmental factors and lifestyle has been linked to the multistep progression of other diseases such as cancer, as well as autoimmune diseases. In the healthy population, autoantibodies against PTM proteins are very rare, thereby providing proof of &&
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concept that it is possible to identify disease-specific biomarkers before the disease onset. These autoantibodies and other blood-based biomarkers are thus suitable and readily available identifiers of the atrisk population. Very excitingly, new studies have recently been performed to evaluate the presence of these or other biomarkers to predict further disease development in healthy individuals who may be at risk of RA [37 ]. &
WHERE IS TOLERANCE BROKEN AND WHERE DOES RHEUMATOID ARTHRITIS ‘BEGIN’? Although the principal site of pathology in established RA is the synovial tissue, there has been considerable controversy as to when, in the natural history of RA, synovial inflammation first develops, and in particular how its onset relates to the development of systemic autoimmunity. Although autoantibodies precede the development of clinical symptoms and signs of arthritis, there have been suggestions that a phase of asymptomatic synovitis precedes clinically manifested arthritis [38]. This concept has recently been challenged in a prospective study [39] of patients who are positive for the presence of RA-specific autoantibodies (ACPA) and have joint pain, but without clinically apparent arthritis. In these patients, no evidence of infiltrating inflammatory cells normally characterizing early and established RA could be demonstrated [39]. However, histological studies in early RA patients have not shown features of synovial inflammation. Rather, the data suggest that synovial inflammation develops very near the time when the joint first swells clinically [40]. Does this mean that the synovium in patients in phases C and D is ‘normal’? This remains unclear as PET imaging and MRI in patients in this phase have revealed abnormalities [41,42], and other non-haemopoietic cells such as fibroblasts that play a role in inflammation have not been systematically assessed. If the synovium is ‘normal’, in which compartment of the body does the disease originate, and where do genetic and environmental risk factors interact in the breaking of immunological tolerance? Extra-articular sites proposed for the breakdown of tolerance include the gums of patients with periodontitis and the lungs of smokers, both of which are chronically inflamed [43,44]. Addressing these will be crucial to understanding which sites to study (e.g. by imaging and histology) in the prediction of outcome and which biomarkers to investigate. The immune responses occurring in lymphoid periodontal and lung tissue may play a pivotal role in the earliest phases of the disease. In the lymph Volume 27 Number 3 May 2015
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nodes, cells of both the innate and the adaptive immune response reside in close contact, reacting to specific antigens leading to the production of antibodies. In animal models, changes in the lymph nodes are observed in the latency phase of arthritis, before any sign of synovitis develops [45,46]. Similar studies have now been confirmed in humans in phases C and D [47]. The lung is the site where environmental triggers are in direct contact with cells of the immune system, such as macrophages and dendritic cells, possibly leading to activation of the immune response. Epidemiological studies have proposed smoking as one of the main environmental factors associated with RA [48], and there is the suggestion that citrullination induced by smoking might be the first step in the pathogenic chain of RA [49]. Genomic analysis of tissue from the lung from smokers and non-smokers provides an opportunity for increased understanding of how genes, environment, and immunity interact. A number of clinical studies point toward an association between periodontal disease and RA [7]. There are remarkable similarities between RA and chronic and/or aggressive periodontitis. Both diseases are chronic destructive inflammatory disorders characterized by dysregulation of the host inflammatory response. Since periodontal disease is associated with the occurrence of RA and shows many of the inflammatory features also found in the inflamed synovium, this site is of importance to study in the pre-arthritic phase [50 ]. &
SEROLOGICAL BIOMARKERS Considerable evidence suggests that rheumatoid factor and ACPA are useful in the prediction of the development of RA when measured at phases C, D, and E [35,51]. Furthermore, the predictive utility of these antibodies in addition to clinical and genetic markers has been assessed [52,53]. Low-molecular-weight metabolites have been assessed in a range of chronic inflammatory and malignant diseases, in which case identification has not only provided prognostically useful information [54] but has also shed light on disease pathways which conventional approaches failed to identify [55]. Most work on soluble molecules in the field of chronic inflammatory disease has focussed on proteins, in particular, pro-inflammatory cytokines and chemokines. Recent work in the patients with RA has shown that low-molecularweight metabolite signatures can be used to predict treatment response [56 ] and associate with the extent of inflammation [57 ]. Therefore, characterization of predictive metabolites may shed light on &
&
the pathogenic processes. There is also increasing evidence that lipid mediators [58–61] are key orchestrators of the inflammatory process and that many of these play an important role in the resolution of inflammation. Finally, a direct pathogenic role for ACPA antibodies has been shown in work which highlights how ACPA can drive osteoclastogenesis [62] and how patients in phases C and D of disease have evidence of bone destruction well before the onset of synovitis [63 ]. &
CONCLUSION Discoveries regarding the mechanisms that drive pathogenesis have important implications for the development of new treatments for RA. There have been significant breakthroughs in our understanding of disease pathology in the past year, but large gaps in knowledge remain which are reflected in practice with a significant proportion of patients refractive to current treatment. An area of interest lies in identifying further genetic risk and investigating the implication of the genetic variants and the effect on disease biology. In addition to this, environmental factors need to be recognized and their role in breaking RA tolerance explored further. These areas could potentially hold the key for preventing RA from developing. Acknowledgements We would like to thank members of the Euro-TEAM consortium for discussions www.team-arthritis.eu Financial support and sponsorship The study was supported by Arthritis Research UK. Conflicts of interest C.B. and K.R. have received honoraria from Pfizer, UCB, Novartis, Roche, and BMS. The remaining author has no conflicts of interest.
REFERENCES AND RECOMMENDED READING Papers of particular interest, published within the annual period of review, have been highlighted as: & of special interest && of outstanding interest 1. Gerlag DM, Raza K, van Baarsen LG, et al. EULAR recommendations for terminology and research in individuals at risk of rheumatoid arthritis (RA): report from the Study Group for Risk Factors for RA. Ann Rheum Dis 2012; 71:638–641. 2. McInnes IB, Schett G. The pathogenesis of rheumatoid arthritis. N Engl J Med 2011; 365:2205–2219. 3. Raza K, Filer A. Predicting the development of RA in patients with early undifferentiated arthritis. Best Pract Res Clin Rheumatol 2009; 23:25–36. 4. Buckley CD, Pilling D, Lord JM, et al. Fibroblasts regulate the switch from acute resolving to chronic persistent inflammation. Trends Immunol 2001; 22:199–204. 5. Buckley CD, Filer A, Haworth O, et al. Defining a role for fibroblasts in the persistence of chronic inflammatory joint disease. Ann Rheum Dis 2004; 63 (Suppl 2):ii92–ii95.
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Quantitative heritability of anticitrullinated protein antibody-positive and anticitrullinated protein antibody-negative rheumatoid arthritis. Arthritis Rheum 2009; 60:916–923. 13. Raychaudhuri S. Recent advances in the genetics of rheumatoid arthritis. Curr Opin Rheumatol 2010; 22:109–118. 14. Barton A, Worthington J. Genetic susceptibility to rheumatoid arthritis: an emerging picture. Arthritis Rheum 2009; 61:1441–1446. 15. Farh KKH, Marson A, Zhu J, et al. Genetic and epigenetic fine mapping of && causal autoimmune disease variants. Nature 2014; 0:1–7. The study uses a fine mapping algorithm combined with transcription and cisregulatory element annotations to identify causal genetic variants and attempts to identify their function. Interestingly, the study showed 90% of causal variants are non-coding. 16. Okada Y, Wu D, Trynka G, et al. Genetics of rheumatoid arthritis contributes && to biology and drug discovery. Nature 2014; 506:376–381. This study uses GWAS pooled from Asian and European patients discovered in 42 novel RA risk loci. It also suggests potential therapeutic targets such as CDK4-CDK6 coded proteins. 17. Wright GP, Notely CA, Bendle GM, et al. Adoptive therapy with redirected primary regulatory T cells results in antigen-specific suppression of arthritis. Proc Natl Acad Sci USA 2009; 106:19078–19083. 18. Ehrenstein MR, Evans JG, Singh A, et al. Compromised function of regulatory T cells in rheumatoid arthritis and reversal by anti-TNF alpha therapy. J Exp Med 2004; 200:277–285. 19. Flores-Borja F, Jury EC, Mauri C, Ehrenstein MR. Defects in CTLA-4 are associated with abnormal regulatory T cell function in rheumatoid arthritis. Proc Natl Acad Sci USA 2008; 105:19396–19401. 20. Ito Y, Hashimoto M, Hirota K, et al. Detection of T cell responses to a && ubiquitous cellular protein in autoimmune disease. Science 2014; 346:363–368. 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33. Scott IC, Seegobin SD, Steer S, et al. Predicting the risk of rheumatoid arthritis and its age of onset through modelling genetic risk variants with smoking. PloS Genet 2013; 9:1–13. This study uses a prediction model using HLA, SNP, and smoking status to predict risk of developing RA and the age of onset. Young-onset RA appeared to be linked with risk conferred from HLA status, whereas smoking associated with developing RA later in life. The model shows promise in identifying patients before the disease process begins, which could allow better insight into how the disease develops. 34. Rantapaa-Dahlqvist S, de Jong BA, Berglin E, et al. Antibodies against cyclic citrullinated peptide and IgA rheumatoid factor predict the development of rheumatoid arthritis. Arthritis Rheum 2003; 48:2741–2749. 35. van de Stadt LA, van der Horst AR, de Koning MH, et al. The extent of the anticitrullinated protein antibody repertoire is associated with arthritis development in patients with seropositive arthralgia. Ann Rheum Dis 2011; 70:128–133. 36. Bos WH, Wolbink GJ, Boers M, et al. Arthritis development in patients with arthralgia is strongly associated with anticitrullinated protein antibody status: a prospective cohort study. Ann Rheum Dis 2010; 69:490–494. 37. Young KA, Deane KD, Derber LA, et al. Relatives without rheumatoid arthritis & show reactivity to anticitrullinated protein/peptide antibodies that are associated with arthritis-related traits: studies of the etiology of rheumatoid arthritis. Arthritis Rheum 2013; 65:1995–2004. This study demonstrated that free first degree relatives of patients with RA who were seronegative for ACPA demonstrated reactivity in their sera to multiple ACPAs. 38. Kraan MC, Versendaal H, Jonker M, et al. Asymptomatic synovitis precedes clinically manifest arthritis. Arthritis Rheum 1998; 41:1481–1488. 39. van de Sande MG, de Hair MJ, van der Leij C, et al. Different stages of rheumatoid arthritis: features of the synovium in the preclinical phase. Ann Rheum Dis 2011; 70:772–777. 40. de Hair MJ, van de Sande MG, Ramwadhdoebe TH, et al. Features of the synovium of individuals at risk of developing rheumatoid arthritis: implications for understanding preclinical rheumatoid arthritis. Arthritis Rheumatol 2014; 66:513–522. 41. Gent YY, Voskuyl AE, Kloet RW, et al. Macrophage PET imaging as biomarker for preclinical rheumatoid arthritis. Arthritis Rheum 2012; 64:62–66. 42. van Steenbergen HW, van Nies JA, Huizinga TW, et al. Characterising arthralgia in the preclinical phase of rheumatoid arthritis using MRI. Ann Rheum Dis 2014; doi: 10.1136/annrheumdis-2014-205522. [Epub ahead of print] 43. Ytterberg AJ, Joshua V, Reynisdottir G, et al. Shared immunological targets in the lungs and joints of patients with rheumatoid arthritis: identification and validation. Ann Rheum Dis 2014; doi: 10.1136/annrheumdis-2013-204912. [Epub ahead of print] 44. Catrina AI, Deane KD, Scher JU. Gene, environment, microbiome and mucosal immune tolerance in rheumatoid arthritis. Rheumatology 2014. [Epub ahead of print] 45. Li J, Kuzin I, Moshkani S, et al. Expanded CD23(þ)/CD21(hi) B cells in inflamed lymph nodes are associated with the onset of inflammatory-erosive arthritis in TNF-transgenic mice and are targets of anti-CD20 therapy. J Immunol 2010; 184:6142–6150. 46. Rodriguez-Palmero M, Pelegri C, Ferri MJ, et al. Alterations of lymphocyte populations in lymph nodes but not in spleen during the latency period of adjuvant arthritis. Inflammation 1999; 23:153–165. 47. van Baarsen LG, de Hair MJ, Ramwadhdoebe TH, et al. The cellular composition of lymph nodes in the earliest phase of inflammatory arthritis. Ann Rheum Dis 2013; 72:1420–1424. 48. Stolt P, Bengtsson C, Nordmark B, et al. Quantification of the influence of cigarette smoking on rheumatoid arthritis: results from a population based case-control study, using incident cases. Ann Rheum Dis 2003; 62:835– 841. 49. Reynisdottir G, Karimi R, Joshua V, et al. Structural changes and antibody enrichment in the lungs are early features of anticitrullinated protein antibodypositive rheumatoid arthritis. Arthritis Rheumatol 2014; 66:31–39. 50. de Pablo P, Dietrich T, Chapple IL, et al. The autoantibody repertoire in & periodontitis: a role in the induction of autoimmunity to citrullinated proteins in rheumatoid arthritis? Ann Rheum Dis 2014; 73:580–586. This study showed an autoantibody response, predominately uncitrullinated, with periodontitis, after taking into account confounders such as smoking. The data suggest that loss of tolerance could lead to citrullinated epitopes emerging. 51. Raza K, Breese M, Nightingale P, et al. Predictive value of antibodies to cyclic citrullinated peptide in patients with very early inflammatory arthritis. J Rheumatol 2005; 32:231–238. 52. van der Helm-van Mil AH, le Cessie S, van Dongen H, et al. A prediction rule for disease outcome in patients with recent-onset undifferentiated arthritis: how to guide individual treatment decisions. Arthritis Rheum 2007; 56:433– 440. 53. van der Helm-van Mil AH, Detert J, le Cessie S, et al. Validation of a prediction rule for disease outcome in patients with recent-onset undifferentiated arthritis: moving toward individualized treatment decision-making. Arthritis Rheum 2008; 58:2241–2247. 54. Brindle JT, Antti H, Holmes E, et al. Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics. Nat Med 2002; 8:1439–1444.
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Volume 27 Number 3 May 2015
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New pathogenic insights into rheumatoid arthritis Jutley et al. 55. Sreekumar A, Poisson LM, Rajendiran TM, et al. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature 2009; 457:910–914. 56. Kapoor SR, Filer A, Fitzpatrick MA, et al. Metabolic profiling predicts response & to antitumor necrosis factor a therapy in patients with rheumatoid arthritis. Arthritis Rheum 2013; 65:1448–1456. The urine of RA patients before and after treatment shows changes in metabolic fingerprint. Differences in metabolic profile also seen when treating with infliximab and etanercept, suggesting a difference in mode of action of there two biologic agents. 57. Young SP, Kapoor SR, Viant MR, et al. The impact of inflammation on metabo& lomic profiles in patients with arthritis. Arthritis Rheum 2013; 65:2015–2023. Lactate and lipids are important discriminators of inflammatory burden in early arthritis patient groups. 58. Haworth O, Cernadas M, Yang R, et al. Resolving E1 regulates interleukin 23, interferon-gamma and lipoxin A4 to promote the resolution of allergic airway inflammation. Nat Immunol 2008; 9:873–879.
59. Lawrence T, Willoughby DA, Gilroy DW. Anti-inflammatory lipid mediators and insights into the resolution of inflammation. Nat Rev Immunol 2002; 2:787– 795. 60. Serhan CN, Brain SD, Buckley CD, et al. Resolution of inflammation: state of the art, definitions and terms. FASEB J 2007; 21:325–332. 61. Serhan CN, Krishnamoorthy S, Recchiuti A, et al. Novel anti-inflammatory proresolving mediators and their receptors. Curr Top Med Chem 2011; 11:629– 647. 62. Harre U, Georgess D, Bang H, et al. Induction of osteoclastogenesis and bone loss by human autoantibodies against citrullinated vimentin. J Clin Invest 2012; 122:1791–1802. 63. Kleyer A, Finzel S, Rech J, et al. Bone loss before the clinical onset of & rheumatoid arthritis in subjects with anticitrullinated protein antibodies. Ann Rheum Dis 2014; 73:854–860. This study shows that structural bone damage occurs before the onset of clinical synovitis in people who carry anti-CCP antibodies.
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