Rheumatoid arthritis (RA) is a chronic inflammatory joint disease affecting synovial tissue in multiple joints in which immune and nonimmune cellular systems mediate pathology. Despite uncertainty about its etiology, RA is thought to be an immune-mediated disease that promotes inflammation and tissue destruction. Rheumatoid synovial tissue is characterized by intimal lining layer hyperplasia and infiltration of the sublining by macrophages, plasma cells, T and B cells, and other inflammatory cells that promote inflammation and tissue destruction (1–3). However, the pathogenesis of RA is still poorly understood, and fundamental questions remain to be answered regarding the precise molecular nature and biologic significance of the inflammatory changes.
Owing to the lack of knowledge of the etiology and pathogenesis of RA, there is an awareness that current methods for classifying this disease, based as they are on a set of clinical variables supplemented with minimal laboratory evidence in the form of molecular markers, are not optimal. For RA, the classifying diagnosis is based on the presence of 4 of 7 criteria, which include 5 clinical variables supplemented with radiographic evidence for erosions and the presence of rheumatoid factor as laboratory evidence (4, 5). Moreover, the current modes of classification fall short with regard to the challenge posed by the fact that diagnosed RA is a heterogeneous disease in itself. The clinical presentation of RA may reveal striking heterogeneity, with a spectrum ranging from mild to severe disease. In addition, marked variability in the features of synovial inflammation among RA patients has been described (6–8). The wide variation in responsiveness to different modes of antirheumatic treatment is consistent with this notion (9, 10). Hence, the data suggest that distinct pathogenetic mechanisms contribute to disease in RA.
A powerful way to gain insight into the molecular complexity and pathogenesis of arthritides has arisen from complementary DNA (cDNA) microarray technology (11–17), which provides the opportunity to determine differences in gene expression of a large portion of the genome in search of genes that are differently expressed between clinically diagnosed arthritides (18). Therefore, we used microarrays containing ∼18,000 cDNA representing predominantly genes thought to be of relevance in immunology.
In the present study, we have conducted a systematic characterization of gene expression in synovial tissues from affected joints of patients with RA and compared this expression with that in tissues from patients with osteoarthritis (OA), a degenerative joint disease characterized by progressive loss of cartilage, as a control (19–22). Both diseases are complex clinical entities that share clinical and demographic characteristics, but they also harbor key differences in tissue destruction and prognosis. Although the etiology of OA is also unknown, it is believed that, in contrast to RA, biomechanical insults and cartilage abnormalities are primary events in the development of OA, with minor subsequent activation of the immune response (23). In our interpretation, we focused particularly on RA to determine whether gene expression profiling could subdivide clinically diagnosed RA on the basis of molecular criteria. In addition, by this approach novel insights into the biologic dysregulation underlying RA might be found.
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- PATIENTS AND METHODS
OA and RA are related complex clinical entities resulting from the interaction of multiple gene products. The objective of this study was to generate a molecular description of these diseases focused on immune-related genes that would allow us to differentiate these arthritides, subclassify RA as a heterogeneous disease, unravel novel aspects of RA pathogenesis, and identify genes and biologic processes not hitherto associated with this disease. We identified molecularly distinct forms of RA synovium, which had expression patterns that suggested the occurrence of different pathologic mechanisms. One RA type expressed genes characteristic of ongoing inflammation, while another type expressed genes indicative of an increased tissue remodeling activity reminiscent of the profile seen in OA tissues.
Previously, Zanders et al (17) applied high-density cDNA arrays printed on nylon membranes. Their analysis revealed an overall increased expression of inflammation-related genes in rheumatoid tissue compared with normal synovium. Since those investigators performed an analysis on pooled RA synovial tissue compared with pooled tissue from healthy controls, their strategy excluded an evaluation of disease heterogeneity and might therefore have diluted differences that existed between tissues. We chose to profile gene expression in whole synovial tissue, which comprises heterogeneous cell types, with the specific purpose of gaining a global representative insight into the molecular changes associated with OA and RA (19, 33, 34).
Gene expression profiling of synovial membranes of RA and OA patients revealed a spectrum of expression that ranged from an extensive inflammatory expression signature, indicative of massive infiltration of mononuclear cells, to an ECM remodeling activity, indicative of fibrosis that is accompanied by a scarce cellular infiltrate. What is also clear from the cluster analysis is that all but one of the OA tissues formed a homogeneous group with a gene expression profile that reflected the fibrosis arm of the spectrum. These data are in accordance with data from histologic studies that suggested that the amount of fibrosis was inversely proportional to the extent of the cellular infiltrate, and that fibrosis was mainly encountered in OA tissue (22). In the present study, we have identified a class of genes grouped in the stromal cell gene clusters that are likely to be implicated in tissue fibrosis in OA.
The RA synovia showed considerable heterogeneity in gene expression, indicating the existence of molecularly distinct classes of rheumatoid synovium. The T/B cell and APC signatures were prominent features in the RAhigh tissues. These features correlate with increased expression of T and B cell genes, genes involved in inflammation, and high expression of major histocompatibility complex (MHC) class I and class II genes as hallmarks of the activation of the immune system (33, 35–37).
Although it is not a priori evident whether measurements of gene expression levels either reflect genuine gene activity or are representative of the cellular composition, it is most likely that these discrete, cell-specific gene expression patterns at least indicated the abundant presence of immune cells such as T and B cells in the RAhigh tissues. The presence of such characteristic cell-specific gene clusters correlates with reported data on infiltration of mononuclear cells into the rheumatoid synovium (6, 19, 33, 34). Overexpression of these gene clusters is consistent with increased ESRs. Another class (RAlow) showed high expression of stromal cell genes that is accompanied by a profile of a scarce cellular infiltrate. An intermediate class (RAinterm) displayed a gene expression profile that included both genetic profiles. These results indicate the existence of extreme differences in cellular infiltration between RA synovial tissues. The combined analysis of cellular complexity, together with a comprehensive overview of the concomitant gene expression profile, provides opportunities for further research.
The expression data suggest involvement of two distinct disease processes in rheumatoid pathogenesis, which is in accordance with data from several studies that indicated biologic heterogeneity in RA (6, 19, 33, 34). The existence of a spectrum of molecular variation that may be translated into distinct pathophysiologic mechanisms at the site of the lesion would fit a model proposed by Firestein and Zvaifler (3), who suggested two processes in the destruction stage of RA. One is a T cell–mediated process that might progress to a T cell–independent process that is centered on autonomous fibroblast-like synoviocyte (FLS) aggression. This model is further supported by data from several animal models in which FLS acquire a degree of independence from T cell control in late destructive disease, implying that an autonomous role of stromal cell elements is responsible for tissue destruction. Hence, both the T cell–involved and the autonomous stromal cell form of disease might drive destruction of bone and cartilage.
Clearly, the molecular dissection of the rheumatoid synovium allows for a biologic interpretation of processes that take place in the tissues. Among the genes that were significantly increased in the RAhigh tissue group were genes indicative of an activated STAT-1 pathway (i.e., STAT-1 itself and a number of genes that are dependent on STAT-1 for their transcription). The induction of these genes is known to occur via the activation of janus-activated kinases, resulting in the phosphorylation and subsequent translocation of specific STAT proteins to the nucleus (38), where it directly activates transcription of target genes including STAT-1 itself (38, 39). We confirmed the differential STAT-1 expression by real-time PCR. Moreover, heterogeneity in STAT-1 protein expression was also found upon immunohistologic analysis of specimens from RA patients with active disease. These findings are in accordance with recently reported data on increased STAT-1 protein expression in RA synovial tissues obtained during joint replacement surgery, compared with normal tissues (40).
Gene expression studies on macrophages and fibroblasts from wild-type and STAT-1–deficient mice revealed ∼66 genes that were part of the interferon-γ (IFNγ)–induced STAT-1–dependent genetic profile (41, 42). A number of the genes from our analysis that met our filtering criteria corresponded to the STAT-1–dependent genes mentioned in those reports. This number will probably increase when purified cells are used as the source for gene expression profiling.
Activation of STAT-1 is involved in MHC class I–restricted antigen presentation through up-regulation of TAP-1, and it indirectly up-regulates MHC class II genes (Table 2). Other genes induced by STAT-1, such as MMPs, caspase-1, IP-10, IRF-1, GBP1, and ICSBP, are also selectively up-regulated in RAhigh tissue (Table 2). Although not definitely proven, this suggests that STAT-1 may be responsible for the activation of these genes.
The STAT-1–dependent chemokine IP-10 attracts T cells and monocytes, which suggests that STAT-1 activation may also be partly responsible for the inflammatory cell influx. The expression of STAT-1 coincided with increased expression of genes encoding receptors activating STAT pathways (e.g., IL-6Rβ, IL-2Rγ, CCR5, and BCR). The data indicated that in addition to the increase in the number of STAT-1–positive cells, the intensity per cell was increased. Hence, conditions in the inflamed joint contribute to an increase per cell. A likely explanation would be that increased STAT-1 expression is a consequence of increased cytokine activity in the synovium. STAT-1 can be activated by a number of cytokines, including the type I and type II IFNs, interleukin-6 (IL-6), IL-9, IL-11, oncostatin M, and leukemia inhibitory factor, and by the chemokines RANTES and macrophage inflammatory protein 1α (43, 44). Although the prototype STAT-1–inducing cytokine IFNγ is barely detectable in the rheumatoid synovium, low doses of IFNγ are able to sensitize the STAT-1 activation pathway, which has been shown to yield increased STAT-1 activity upon subsequent activation (40).
Obviously, the various cytokines present in the RA synovium create a complex situation with simultaneous activation of multiple signaling pathways that may influence STAT-1 signaling (e.g., STAT-1 activation may negatively influence the tumor necrosis factor α and IFNα/β signaling pathways [for review, see ref. 45]). The importance of STAT activation in arthritis has been demonstrated in an animal model; periarticular administration of adenoviral suppressor of cytokine signaling 3 dramatically reduced the severity of collagen-induced arthritis and synovial IgG production (46). These findings justify further research on the cell-specific expression of STAT signaling components, including the activating receptors and their ligands, which is crucial for our understanding of the molecular and cellular events that take place in the effector phase.
The abundant expression of specific chemokines and their receptors revives data from studies proposing that cell-specific expression of selective chemokines and their cognate receptors is involved in the accumulation of mononuclear cells in the inflamed synovium (47). In the RAhigh tissues, we found significantly higher expression levels of the chemokine RANTES (and its receptors CCR1 and CCR5), which activates STAT-1. The higher expression of stromal cell–derived factor 1 plus its ligand CXC receptor 4 may account for the attraction and retention of T cells, B cells, and monocyte/macrophages, while the expression of B lymphocyte chemoattractant explains the increased B cell activity in the RAhigh synovial tissue with greatly enhanced production of immunoglobulins.
What does the molecular classification of RA patients into the subgroups RAhigh and RAlow mean in clinical terms? Based on the expression profiles, it suggests that different pathologic mechanisms may contribute to disease. However, we realize that the design of this study does not allow any firm conclusions to be drawn concerning the clinical parameters associated with the molecular phenotype. Further studies, which are necessary to address this issue, may provide a means to dissect and analyze the rheumatoid synovium of these patients and perform a thorough clinical association study based on molecular variation among patients. Moreover, since the molecular differences most likely reflect distinct pathophysiologic processes underlying disease, it is tempting to speculate that these differences predict individual responsiveness to treatment. Hence, the molecular stratification of patients may be helpful in assembling homogeneous populations of patients, which will improve the likelihood of observing efficacy in clinical trials.