Early and long-standing rheumatoid arthritis: distinct molecular signatures identified by gene-expression profiling in synovia

RNA Editing-Associated Post-Transcriptional Gene Regulation in Rheumatoid Arthritis

Background:

Rheumatoid arthritis (RA) is an autoimmune disease characterised by systemic inflammation of joints. The observed complexity of RA pathogenesis and studies that have been carried out so far indicate that RA pathogenesis is regulated at multiple levels. Given the role of RNA editing in autoimmune disease, we hypothesised that RNA editing could contribute to RA pathogenesis by regulating gene expression through post-transcriptional mechanisms.

Methods:

We identified RNA editing events in synovial tissues from early and established RA compared with normal subjects from an available transcriptome data set using REDItools. To investigate the potential effect of these RNA editing events on gene expression, we carried out an analysis of differential exon usage in the vicinity of the differentially edited sites using DEXSeq. We then used STRING to identify putative interactions between differentially edited genes identified from REDItools analysis. We also investigated the possible effects of these RNA editing events on miRNA-target mRNA interactions as predicted by miRanda.

Results:

Our analysis revealed that there is extensive RNA editing in RA, with 304 and 273 differentially edited events in early RA and established RA, respectively. Of these, 25 sites were within 11 genes in early RA, and 34 sites were within 7 genes in established RA. DEXSeq analysis revealed that RNA editing correlated with differential exon usage in 4 differentially edited genes that have previously also been associated with RA in some measure: ATM, ZEB1, ANXA4, and TIMP3. DEXSeq analysis also revealed enrichment of some non-functional isoforms of these genes, perhaps at the expense of their full-length counterparts. Network analysis using STRING showed that several edited genes were part of the p53 protein-protein interaction network. We also identified several putative miRNA binding sites in the differentially edited genes that were lost upon editing.

Conclusions:

Our results suggested that the expression of genes involved in DNA repair and cell cycle, including ATM and ZEB1 which are well-known functional regulators of the DNA damage response pathway, could be regulated by RNA editing in RA synovia. This may contribute to an impaired DNA damage response in synovial tissues.

Associations between inflammation-related LL-37 with subgingival microbial dysbiosis in rheumatoid arthritis patients

OBJECTIVE

This study investigated the subgingival microbial profile of rheumatoid arthritis (RA) patients and its associations with disease parameters and the inflammation-related antimicrobial peptide, LL-37.

METHODS

RA and non-RA (NRA) patients were assessed for periodontal status and divided into periodontitis (CP), gingivitis (G), and healthy (H) groups. Subgingival plaque 16s rRNA gene sequencing data was processed and analyzed using the CLC Genomic Workbench (Qiagen). Bacterial diversity and co-occurrence patterns were examined. Differential abundance between groups was also investigated. Associations between bacterial genera with disease parameters and LL-37 levels were explored qualitatively using canonical correlation analysis.

RESULTS

Subgingival microbial community clustered in CP status. Co-occurrence network in NRA-H was dominated by health-associated genera, while the rest of the networks' key genera were both health- and disease-associated. RA-CP displayed highly inter-generic networks with a statistically significant increase in periodontal disease-associated genera (p<0.05). In NRA-H, disease parameters and LL-37 were correlated positively with disease-associated genera while negatively with health-associated genera. However, in the remaining groups, mixed positive and negative correlations were noted with genera.

CONCLUSION

RA patients demonstrated subgingival microbial dysbiosis where the bacteria networks were dominated by health- and disease-associated genera. Mixed correlations with disease parameters and LL-37 levels were noted.

CLINICAL RELEVANCE

The subgingival microbial dysbiosis in RA may predispose these patients to developing periodontal inflammation with an associated detrimental effect on host immune responses. Routine periodontal assessment may allow initiation of treatment strategies to minimize the effects of gingival inflammation on the existing heightened immune response present in RA patients.

Impact of synovial biopsy procedures and disease-specific aspects on synovial tissue outcome: a systematic literature review informing the EULAR points to consider for the minimal reporting requirements in synovial tissue research in rheumatology

BACKGROUND

The aim of this work was to summarise the literature evaluating the impact of biopsy procedures, tissue handling, tissue quality and disease-specific aspects including joint biopsied and disease stage, on synovial tissue outcome.

METHODS

Two reviewers independently identified eligible studies according to the Patients, Intervention, Comparator and Outcome framework obtained for five research questions formulated during the first EULAR task force meeting to produce points to consider (PtC) for minimal reporting requirements in synovial tissue studies. The databases explored were Medline, Embase, CENTRAL and Cinhal. The risk of bias of each study was evaluated using an adapted version of the Joanna Briggs Institute checklist for analytical cross-sectional studies.

RESULTS

Of the 7654 records yielded, 75 full texts were assessed, leading to the inclusion of 26 manuscripts in the systematic literature review (SLR). Two papers assessed the impact of biopsy procedures on the quality and quantity of tissue retrieved alongside patient tolerability; six papers focused on synovial tissue variability. Four papers studied the impact of sample handling or randomisation and 14 assessed the impact of disease stage and state, namely early or established active rheumatoid arthritis and remission on histopathological and transcriptomic results.

CONCLUSIONS

This SLR informs the EULAR PtC for minimal reporting requirements in synovial tissue research in rheumatology. Characteristics related to the study design, population, sample handling, randomisation and analysis can affect the final synovial tissue outcome in the studies reviewed. Thus, accurate reporting of these factors is required in order to ensure the scientific validity of manuscripts describing synovial tissue outcomes.

Methotrexate in early rheumatoid arthritis: Is the anchor drug still holding?

Treat-to-target (T2T) is currently the most fashionable strategy for treatment-naïve, early rheumatoid arthritis (RA) patients. A T2T approach can lead to a complete and drug-free disease remission, whereas failure to obtain remission leads to damage early in the disease course. Hence, one should try to achieve high remission rates as early as possible, implementing the best therapeutic strategies available. Methotrexate (MTX) combined with glucocorticoid bridging is the mainstay of T2T. However, MTX is often used suboptimally in RA patients for many reasons, including poor tolerability, low compliance, and safety issues. Recent evidence has suggested that novel targeted synthetic DMARDs (tsDMARDs) such as the Janus-kinase (JAK) inhibitors in combination with glucocorticoids yielded better outcomes in early RA than conventional treatment. Such an approach may have advantages in terms of patients' outcomes, though some concerns about serious adverse events need to be addressed.

Novel Insights Into Rheumatoid Arthritis Through Characterization of Concordant Changes in DNA Methylation and Gene Expression in Synovial Biopsies of Patients With Differing Numbers of Swollen Joints

In this study, we sought to characterize synovial tissue obtained from individuals with arthralgia and disease-specific auto-antibodies and patients with established rheumatoid arthritis (RA), by applying an integrative multi-omics approach where we investigated differences at the level of DNA methylation and gene expression in relation to disease pathogenesis. We performed concurrent whole-genome bisulphite sequencing and RNA-Sequencing on synovial tissue obtained from the knee and ankle from 4 auto-antibody positive arthralgia patients and thirteen RA patients. Through multi-omics factor analysis we observed that the latent factor explaining the variance in gene expression and DNA methylation was associated with Swollen Joint Count 66 (SJC66), with patients with SJC66 of 9 or more displaying separation from the rest. Interrogating these observed differences revealed activation of the immune response as well as dysregulation of cell adhesion pathways at the level of both DNA methylation and gene expression. We observed differences for 59 genes in particular at the level of both transcript expression and DNA methylation. Our results highlight the utility of genome-wide multi-omics profiling of synovial samples for improved understanding of changes associated with disease spread in arthralgia and RA patients, and point to novel candidate targets for the treatment of the disease.

Metabolomic and transcriptomic analyses of the anti-rheumatoid arthritis potential of xylopic acid in a bioinspired lipoprotein nanoformulation

Xylopic acid (XA), a diterpene kaurene and the major active ingredient of the African spice Xylopia aethiopica (Annonaceae), is reported to possess anti-inflammatory and analgesic properties. Here, we investigated the therapeutic potential of XA for rheumatoid arthritis (RA), a debilitating autoimmune inflammatory disease characterized by joint damage, in the complete Freund's adjuvant (CFA)-induced arthritis model in rats. We synthesized bioinspired reconstituted high-density lipoprotein (rHDL) nanoparticles loaded with purified XA crystals (rHDL/XA) that passively accumulate in inflamed joints of CFA-induced arthritic rats. Treatment with rHDL/XA minimized mononuclear cell infiltration of CFA-induced arthritic sites and ameliorated disease burden. Metabolomic and transcriptomic analyses revealed that the major molecular pathways perturbed following CFA-induced arthritis correlated with amino acid and lipid metabolism, which were restored to normal states by rHDL/XA treatment. This work demonstrates the anti-RA potential of XA in a nanoformulation and uncovers its underlying therapeutic mechanisms at the transcript and metabolite levels.

Treatment patterns and achievement of the treat-to-target goals in a real-life rheumatoid arthritis patient cohort: data from 1317 patients

Background

Data regarding the real-life predictors of low disease activity (LDA) in rheumatoid arthritis (RA) patients are limited. Our aim was to evaluate the rate and predictors of LDA and treatment patterns in RA.

Methods

This was a multicenter, prospective, RA cohort study where patients were evaluated in two different time points approximately 12 months apart. Statistical analysis was performed in order to identify predictors of LDA while patterns of disease-modifying anti-rheumatic drug [DMARDs; conventional synthetic (csDMARD) or biologic (bDMARD)] and glucocorticoid (GC) use were also recorded.

Results

The total number of patients included was 1317 (79% females, mean age: 62.9 years, mean disease duration: 10.3 years). After 1 year, 57% had achieved LDA (DAS28ESR<3.2) while 43% did not (34%: moderate disease activity: DAS28ESR ⩾3.2 to <5.1, 9%: high disease activity, DAS28ESR ⩾5.1). By multivariate analysis, male sex was positively associated with LDA [odds ratio (OR) = 2.29 p < 0.001] whereas advanced age (OR = 0.98, p = 0.005), high Health Assessment Questionnaire (HAQ) score (OR = 0.57, p < 0.001), use of GCs (OR = 0.75, p = 0.037) or ⩾2 bDMARDs (OR = 0.61, p = 0.002), high co-morbidity index (OR = 0.86, p = 0.011) and obesity (OR = 0.62, p = 0.002) were negative predictors of LDA. During follow-up, among active patients (DAS28ESR >3.2), 21% initiated (among csDMARDs users) and 22% switched (among bDMARDs users) their bDMARDs.

Conclusion

In a real-life RA cohort, during 1 year of follow-up, 43% of patients do not reach treatment targets while only ~20% of those with active RA started or switched their bDMARDs. Male sex, younger age, lower HAQ, body mass index and co-morbidity index were independent factors associated with LDA while use of GCs or ⩾2 bDMARDs were negative predictors.

Established rheumatoid arthritis. The pathogenic aspects

The development of rheumatoid arthritis (RA), at least in its autoantibody-positive subset, evolves through a series of events starting well before the appearance of synovitis. The distinction between 'early' and 'established' RA is, therefore, an evolving concept. In routine practice, however, the management of RA still starts with the occurrence of clinically detectable synovitis. As such, the synovial membrane remains a major target for the exploitation of possible stage-specific drivers of the disease. The recognition of a 'window of opportunity', in which treatment is more likely to succeed, raises the hypothesis that there might be a period in which the biological processes of RA are less mature and potentially reversible. The present review aims to provide a general picture of the modifications occurring in RA synovium, analysing the contribution of both infiltrating immune cells and stromal cells. When available, differences between early and established RA will be discussed.

Synovial Tissue: Turning the Page to Precision Medicine in Arthritis

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease targeting the joints. Current treatment strategies are based on clinical, biological and radiological features, yet still fail to reach the goal of early low disease activity in a significant number of cases. Hence, there is a need for refining current treatment algorithms, using accurate markers of response to therapy. Because RA induces histological and molecular alterations in the synovium even before apparition of clinical symptoms, synovial biopsies are a promising tool in the search of such new biomarkers. Histological and molecular characteristics of RA synovitis are heterogeneous. Variations in synovial lining layer hyperplasia, in cellular infiltration of the sublining by immune cells of myeloid and lymphoid lineages, and in molecular triggers of these features are currently categorized using well-defined pathotypes: myeloid, lymphoid, fibroid and pauci-immune. Here, we first bring the plasticity of RA synovitis under scrutiny, i.e., how variations in synovial characteristics are associated with relevant clinical features (disease duration, disease activity, effects of therapies, disease severity). Primary response to a specific drug could be, at least theoretically, related to the representation of the molecular pathway targeted by the drug in the synovium. Alternatively, absence of primary response to a specific agent could be due to disease severity, i.e., overrepresentation of all synovial molecular pathways driving disease activity overwhelming the capacity of any drug to block them. Using this theoretical frame, we will highlight how the findings of previous studies trying to link response to therapy with synovial changes provide promising perspectives on bridging the gap to personalized medicine in RA.

Synovial Tissue Heterogeneity in Rheumatoid Arthritis and Changes With Biologic and Targeted Synthetic Therapies to Inform Stratified Therapy

The treatment of rheumatoid arthritis (RA) has been transformed with the introduction of biologic disease modifying anti-rheumatic drugs (bDMARD) and more recently, targeted synthetic DMARD (tsDMARD) therapies in the form of janus-kinase inhibitors. Nevertheless, response to these agents varies such that a trial and error approach is adopted; leading to poor patient quality of life, and long-term outcomes. There is thus an urgent need to identify effective biomarkers to guide treatment selection. A wealth of research has been invested in this field but with minimal progress. Increasingly recognized is the importance of evaluating synovial tissue, the primary site of RA, as opposed to peripheral blood-based investigation. In this mini-review, we summarize the literature supporting synovial tissue heterogeneity, the conceptual basis for stratified therapy. This includes recognition of distinct synovial pathobiological subtypes and associated molecular pathways. We also review synovial tissue studies that have been conducted to evaluate the effect of individual bDMARD and tsDMARD on the cellular and molecular characteristics, with a view to identifying tissue predictors of response. Initial observations are being brought into the clinical trial landscape with stratified biopsy trials to validate toward implementation. Furthermore, development of tissue based omics technology holds still more promise in advancing our understanding of disease processes and guiding future drug selection.

[Upcoming value of gene expression analysis in rheumatology]

Rheumatoid arthritis (RA) is a chronic inflammatory disease of unknown etiology, which involves disturbance in immune system signaling pathway functions, damage of other tissues, pain and joint destruction. Modern treatment attempts to improve pathophysiological and biochemical mechanisms damaged by the disease. However, due to the RA patient heterogeneity personalized approach to treatment is required; the choice of personalized treatment is complicated by the variability of patient's response to treatment. Gene expression analysis might serve a tool for the disease control and therapy personification for inhibition of inflammation and pain as well as for prevention of joint destruction.

Phenotypic and Transcriptomic Analysis of Peripheral Blood Plasmacytoid and Conventional Dendritic Cells in Early Drug Naïve Rheumatoid Arthritis

Objective

Dendritic cells (DCs) are key orchestrators of immune function. To date, rheumatoid arthritis (RA) researchers have predominantly focused on a potential pathogenic role for CD1c+ DCs. In contrast, CD141+ DCs and plasmacytoid DCs (pDCs) have not been systematically examined, at least in early RA. In established RA, the role of pDCs is ambiguous and, since disease duration and treatment both impact RA pathophysiology, we examined pDCs, and CD1c+ and CD141+ conventional DCs (cDCs), in early, drug-naïve RA (eRA) patients.

Methods

We analyzed the frequency and phenotype of pDCs, CD1c+, and CD141+ DCs from eRA patients and compared findings with healthy controls. In parallel, we performed transcriptional analysis of >600 immunology-related genes (Nanostring) from peripheral blood pDCs, CD1c+ DCs, B cells, T cells, and monocytes.

Results

All DC subsets were reduced in eRA (n = 44) compared with healthy controls (n = 30) and, for pDCs, this was most marked in seropositive patients. CD141+ and CD1c+ DCs, but not pDCs, had a comparatively activated phenotype at baseline (increased CD86) and CD1c+ DC frequency inversely associated with disease activity. All DC frequencies remained static 12 months after initiation of immunomodulatory therapy despite a fall in activation markers (e.g., HLA-DR, CD40). There was no association between the whole blood interferon gene signature (IGS) and pDC or CD1c+ DC parameters but an inverse association between CD141+ DC frequency and IGS was noted. Furthermore, IFN-I and IFN-III mRNA transcripts were comparable between eRA pDC and other leukocyte subsets (B cells, CD4+, and CD8+ T cells and monocytes) with no obvious circulating cellular source of IFN-I or IFN-III. Transcriptomic analysis suggested increased pDC and CD1c+ DC proliferation in eRA; pDC differentially expressed genes also suggested enhanced tolerogenic function, whereas for CD1c+ DCs, pro-inflammatory transcripts were upregulated.

Discussion

This is the first detailed examination of DC subsets in eRA peripheral blood. Compared with CD1c+ DCs, pDCs are less activated and may be skewed toward tolerogenic functions. CD141+ DCs may be implicated in RA pathophysiology. Our findings justify further investigation of early RA DC biology.

The clinical utility of gene expression examination in rheumatology

Rheumatoid arthritis (RA) is a chronic inflammatory disease with unknown etiology that affects various pathways within the immune system, involves many other tissues and is associated with pain and joint destruction. Current treatments fail to address pathophysiological and biochemical mechanisms involved in joint degeneration and the induction of pain. Moreover, RA patients are extremely heterogeneous and require specific treatments, the choice of which is complicated by the fact that not all patients equally respond to therapy. Gene expression analysis offer tools for patient management and personalization of patient’s care to meet individual needs in controlling inflammation and pain and delaying joint destruction.

TcoF-DB v2: update of the database of human and mouse transcription co-factors and transcription factor interactions

Transcription factors (TFs) play a pivotal role in transcriptional regulation, making them crucial for cell survival and important biological functions. For the regulation of transcription, interactions of different regulatory proteins known as transcription co-factors (TcoFs) and TFs are essential in forming necessary protein complexes. Although TcoFs themselves do not bind DNA directly, their influence on transcriptional regulation and initiation, although indirect, has been shown to be significant, with the functionality of TFs strongly influenced by the presence of TcoFs. In the TcoF-DB v2 database, we collect information on TcoFs. In this article, we describe updates and improvements implemented in TcoF-DB v2. TcoF-DB v2 provides several new features that enables exploration of the roles of TcoFs. The content of the database has significantly expanded, and is enriched with information from Gene Ontology, biological pathways, diseases and molecular signatures. TcoF-DB v2 now includes many more TFs; has substantially increased the number of human TcoFs to 958, and now includes information on mouse (418 new TcoFs). TcoF-DB v2 enables the exploration of information on TcoFs and allows investigations into their influence on transcriptional regulation in humans and mice. TcoF-DB v2 can be accessed at http://tcofdb.org/.

Dysregulation of RasGRP1 in rheumatoid arthritis and modulation of RasGRP3 as a biomarker of TNFα inhibitors

Background

B and T cells play a key role in rheumatoid arthritis (RA) pathophysiology. RasGRP1 and RasGRP3 are involved in T and B cell receptors signaling, and belong to gene combination able to predict infliximab responsiveness, leading to the question of RasGRP1 and RasGRP3 involvement in RA.

Methods

RasGRP1 and RasGRP3 expression levels were measured by qRT-PCR and/or western-blot in peripheral blood mononuclear cells (PBMCs), in T and B cells from untreated RA patients and in RA patients treated by TNFα inhibitors. T and B cells from healthy controls (HC) were cultured with TNFα, and TNFα receptors neutralizing antibodies to highlight the TNFα effects on RasGRP1 and RasGRP3 pathways. MAPK pathways and apoptosis were respectively analyzed using the Proteome Profiler arrays and flow cytometry.

Results

In PBMCs from RA patients, gene expression levels of RasGRP1 were invariant while RasGRP3 was downregulated under TNFα inhibitors and upregulated under TNFα. In T cells from RA patients, RasGRP1 was decreased and its gene expression level was correlated with disease activity. In T cells from HC, TNFα stimulation increased RasGRP1 gene expression level while it reduced RasGRP1 protein expression level. Bryostatin-1 experiments have confirmed that the TNFα effect observed on T cells proliferation was due to the decrease of RasGRP1 expression. Besides, RasGRP3 expression level increased in PBMCs from RA patients under TNFα and in B cells from HC leading us to conclude that RasGRP3 in B cells was modulated by TNFα.

Conclusion

This study demonstrates RasGRP1 dysregulation in RA patients while RasGRP3 is characterized as a biomarker linked to TNFα inhibitors. After binding to TNFR1, TNFα reduced RasGRP1 protein expression resulting in inhibition of T cell activation.

Trial registration

Clinicaltrials.gov NCT00234234, registered 04 November 2008; NCT00767325, registered 05 October 2005.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-015-0894-9) contains supplementary material, which is available to authorized users.

CD4 T-cell transcriptome analysis reveals aberrant regulation of STAT3 and Wnt signaling pathways in rheumatoid arthritis: evidence from a case-control study

INTRODUCTION

Rheumatoid arthritis (RA) is a systemic autoimmune disease in which T cells play a pivotal role in the pathogenesis. Knowledge in terms of the CD4 T-cell transcriptome in RA is limited. The aim of this study was to examine the whole-genome transcription profile of CD4 T cells in RA by comparing patients with RA to healthy controls.

METHODS

Peripheral blood CD4 T cells were isolated from 53 RA patients with active disease and 45 healthy individuals; 13 cases and 10 controls were enrolled in microarray analysis. The remaining 40 cases and 35 controls were recruited as an independent cohort for the validation study. Bioinformatics was performed on Gene Ontology (GO), gene-gene interaction networks, and pathway analysis. The gene modules, by combining the results from GO, gene networks, and pathway analysis, were selected for further validation.

RESULTS

The CD4 T cells showed 1,496 differentially expressed (DE) genes in RA patients relative to healthy individuals. GO analysis revealed that the DE genes were enriched in immune response, T-cell response, apoptosis process, and Wnt receptor signaling. Pathway analysis also identified that 'Wnt signaling pathway' was differentially regulated between two groups (P=2.78×10(-10)). By gene-gene network analysis, we found that the DE genes were enriched in T-cell receptor (TCR), JAK-STAT signaling, and Wnt signaling pathway. By gene module analysis, we found that a number of DE genes overlapped in the three different analyses. In total, 23 genes were selected for further validation, and nine genes were confirmed. Of these, four genes (SOCS3, CBL, IFNAR1, and PIK3CA) were involved in STAT3 (signal transducer and activator of transcription 3) signaling, and three genes (CBL, KLF9, and CSNK2A1) were involved in the Wnt signaling pathway. Additionally, several zinc finger transcription factors (ZEB1, ZNF292, and ZNF644) were confirmed.

CONCLUSIONS

We report here the first case-control study of the CD4 T-cell transcriptome profile in RA. Our data provide evidence that CD4 T cells from patients with RA have abnormal functional networks in STAT3 signaling and Wnt signaling. Our results also suggest that the aberrant expression of several zinc finger transcription factors (ZEB1, ZNF292, and ZNF644) may be potential pathogenic factors for RA.

Current and future trends in biomarker discovery and development of companion diagnostics for arthritis

Musculoskeletal diseases such as rheumatoid arthritis are complex multifactorial disorders that are chronic in nature and debilitating for patients. A number of drug families are available to clinicians to manage these disorders but few tests exist to target these to the most responsive patients. As a consequence, drug failure and switching to drugs with alternate modes of action is common. In parallel, a limited number of laboratory tests are available which measure biological indicators or 'biomarkers' of disease activity, autoimmune status, or joint damage. There is a growing awareness that assimilating the fields of drug selection and diagnostic tests into 'companion diagnostics' could greatly advance disease management and improve outcomes for patients. This review aims to highlight: the current applications of biomarkers in rheumatology with particular focus on companion diagnostics; developments in the fields of proteomics, genomics, microbiomics, imaging and bioinformatics and how integration of these technologies into clinical practice could support therapeutic decisions.

CD38 and E2F transcription factor 2 have uniquely increased expression in rheumatoid arthritis synovial tissues

The purpose of the current study was to find novel rheumatoid arthritis (RA)-specific gene expression by simultaneously comparing the expression profiles of the synovial tissues from patients with RA, osteoarthritis (OA) and ankylosing spondylitis (AS). The Illumina Human HT-12 v4 Expression BeadChip was used to investigate the global gene expression profiles in synovial tissues from RA (n = 12), OA (n = 14) and AS (n = 7) patients. By comparing the profiles in synovial tissues from RA, OA and AS, we identified the CD38, ankyrin repeat domain 38 (ANKRD38), E2F transcription factor 2 (E2F2), craniofacial development protein 1 (CFDP1), cluster of differentiation (CD)7, interferon-stimulated exonuclease gene 20 kDa (ISG20) and interleukin-2 receptor gamma (IL)-2RG genes as differentially expressed gene expression in RA synovial tissues. The increased expression of CD38, E2F2 and IL-2RG, as revealed using real-time polymerase chain reaction (PCR) with synovial tissues from RA (n = 30), OA (n = 26) and AS patients (n = 20), was in agreement with the microarray data. Immunohistochemistry revealed significant CD38 expression and E2F2 in synovial membranes from RA patients (n = 5). The CD38(+) cells had high a percentage in the RA patients' blood (n = 103) and in the CD3(+) and CD56(+) subsets. The CD38(+) cell percentage was correlated significantly with RF level (P = 0·026) in RA patients. The IL-1α and IL-β levels were depressed significantly in the culture medium of RA synovial fibroblast cells (n = 5) following treatment with siRNAs targeting the E2F2 or CD38 genes. This study suggests that the uniquely increased expression of CD38 and E2F2 in RA synovial tissues contribute to the immunoactivation of the disease.

Gene expression analysis in RA: towards personalized medicine

Gene expression has recently been at the forefront of advance in personalized medicine, notably in the field of cancer and transplantation, providing a rational for a similar approach in rheumatoid arthritis (RA). RA is a prototypic inflammatory autoimmune disease with a poorly understood etiopathogenesis. Inflammation is the main feature of RA; however, many biological processes are involved at different stages of the disease. Gene expression signatures offer management tools to meet the current needs for personalization of RA patients' care. This review analyses currently available information with respect to RA diagnostic, prognostic and prediction of response to therapy with a view to highlight the abundance of data, whose comparison is often inconclusive due to the mixed use of material source, experimental methodologies and analysis tools, reinforcing the need for harmonization if gene expression signatures are to become a useful clinical tool in personalized medicine for RA patients.

Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation

INTRODUCTION

Discrimination of rheumatoid arthritis (RA) patients from patients with other inflammatory or degenerative joint diseases or healthy individuals purely on the basis of genes differentially expressed in high-throughput data has proven very difficult. Thus, the present study sought to achieve such discrimination by employing a novel unbiased approach using rule-based classifiers.

METHODS

Three multi-center genome-wide transcriptomic data sets (Affymetrix HG-U133 A/B) from a total of 79 individuals, including 20 healthy controls (control group - CG), as well as 26 osteoarthritis (OA) and 33 RA patients, were used to infer rule-based classifiers to discriminate the disease groups. The rules were ranked with respect to Kiendl's statistical relevance index, and the resulting rule set was optimized by pruning. The rule sets were inferred separately from data of one of three centers and applied to the two remaining centers for validation. All rules from the optimized rule sets of all centers were used to analyze their biological relevance applying the software Pathway Studio.

RESULTS

The optimized rule sets for the three centers contained a total of 29, 20, and 8 rules (including 10, 8, and 4 rules for 'RA'), respectively. The mean sensitivity for the prediction of RA based on six center-to-center tests was 96% (range 90% to 100%), that for OA 86% (range 40% to 100%). The mean specificity for RA prediction was 94% (range 80% to 100%), that for OA 96% (range 83.3% to 100%). The average overall accuracy of the three different rule-based classifiers was 91% (range 80% to 100%). Unbiased analyses by Pathway Studio of the gene sets obtained by discrimination of RA from OA and CG with rule-based classifiers resulted in the identification of the pathogenetically and/or therapeutically relevant interferon-gamma and GM-CSF pathways.

CONCLUSION

First-time application of rule-based classifiers for the discrimination of RA resulted in high performance, with means for all assessment parameters close to or higher than 90%. In addition, this unbiased, new approach resulted in the identification not only of pathways known to be critical to RA, but also of novel molecules such as serine/threonine kinase 10.

Gene expression patterns in peripheral blood cells associated with radiographic severity in African Americans with early rheumatoid arthritis

Gene expression profiling may be used to stratify patients by disease severity to test the hypothesis that variable disease outcome has a genetic component. In order to define unique expression signatures in African American rheumatoid arthritis (RA) patients with severe erosive disease, we undertook a gene expression study using samples of RNA from peripheral blood mononuclear cells (PBMCs). RNA from baseline PBMC samples of 96 African American RA patients with early RA (<2 years disease duration) was hybridized to cDNA probes of the Illumina Human HT-V3 expression array. Expression analyses were performed using the ca. 25,000 cDNA probes, and then expression levels were compared to the total number of erosions in radiographs of the hands and feet at baseline and 36 months. Using a false discovery rate cutoff of Q = 0.30, 1,138 genes at baseline and 680 genes at 36 months significantly correlated with total erosions. No evidence of a signal differentiating disease progression, or change in erosion scores between baseline and 36 months, was found. Further analyses demonstrated that the differential gene expression signature was localized to the patients with the most erosive disease (>10 erosions). Ingenuity Pathway Analysis demonstrated that genes with fold change greater than 1.5 implicated immune pathways such as CTLA signaling in cytotoxic T lymphocytes. These results demonstrate that CLEAR patients with early RA having the most severe erosive disease, as compared to more mild cases (<10 erosions), may be characterized by a set of differentially expressed genes that represent biological pathways with relevance to autoimmune disease.

Detection of gene expression signatures related to underlying disease and treatment in rheumatoid arthritis patients

OBJECTIVES

Gene expression signatures can provide an unbiased view into the molecular changes underlying biologically and medically interesting phenotypes. We therefore initiated this study to identify signatures that would be of utility in studying rheumatoid arthritis (RA).

METHODS

We used microarray profiling of peripheral blood mononuclear cells (PBMCs) in 30 RA patients to assess the effect of different biologic agent (biologics) treatments and to quantify the degree of a type-I interferon (IFN) signature in these patients. A numeric score was derived for the quantification step and applied to patients with RA. To further characterize the IFN response in our cohort, we employed type-I IFN treatment of PBMCs in vitro and in reporter assays.

RESULTS

Profiling identified a subset of RA patients with upregulation of type-I IFN-regulated transcripts, thereby corroborating previous reports showing RA to be heterogeneous for an IFN component. A comparison of individuals currently untreated with a biologic with those treated with infliximab, tocilizumab, or abatacept suggested that each biologic induces a specific gene signature in PBMCs.

CONCLUSIONS

It is possible to observe signs of type-I IFN pathway activation in a subset of clinically active RA patients without C-reactive protein elevation. Furthermore, biologics-specific gene signatures in patients with RA indicate that looking for a biologic-specific response pattern may be a potential future tool for predicting individual patient response.

A systems biology approach to synovial joint lubrication in health, injury, and disease

The synovial joint contains synovial fluid (SF) within a cavity bounded by articular cartilage and synovium. SF is a viscous fluid that has lubrication, metabolic, and regulatory functions within synovial joints. SF contains lubricant molecules, including proteoglycan-4 and hyaluronan. SF is an ultrafiltrate of plasma with secreted contributions from cell populations lining and within the synovial joint space, including chondrocytes and synoviocytes. Maintenance of normal SF lubricant composition and function are important for joint homeostasis. In osteoarthritis, rheumatoid arthritis, and joint injury, changes in lubricant composition and function accompany alterations in the cytokine and growth factor environment and increased fluid and molecular transport through joint tissues. Thus, understanding the synovial joint lubrication system requires a multifaceted study of the various parts of the synovial joint and their interactions. Systems biology approaches at multiple scales are being used to describe the molecular, cellular, and tissue components and their interactions that comprise the functioning synovial joint. Analyses of the transcriptome and proteome of SF, cartilage, and synovium suggest that particular molecules and pathways play important roles in joint homeostasis and disease. Such information may be integrated with physicochemical tissue descriptions to construct integrative models of the synovial joint that ultimately may explain maintenance of health, recovery from injury, or development and progression of arthritis.

Gene expression profiling in peripheral blood cells of patients with rheumatoid arthritis in response to anti-TNF-alpha treatments

The efficacy of anti-TNF-α therapies highlights the role of TNF-α in the pathogenesis of rheumatoid arthritis (RA). However, the mechanism of action of these agents is poorly understood at the molecular level. The aim of this study was to characterize the effects of anti-TNF-α treatment on the global gene expression profile in peripheral blood mononuclear cells (PBMCs) of responder RA patients. Changes in gene expression were determined using oligonucleotide microarrays (25,341 genes) in PBMCs obtained before and after 12 wk of treatment with either etanercept or adalimumab from responder RA patients. Two hundred fifty-one genes displayed significant changes (false discovery rate < 0.1%) in expression level (178 upregulations with mean fold change = 1.5 and 73 downregulations with mean fold change = -1.50) after 12 wk of treatment. Importantly, the expression of several genes, including those coding for the calcium binding proteins S100A12 and A8, CD14 antigen, Selectin P, or ribosomal protein L39, reported to be upregulated in RA patients, were found to be decreased after anti-TNF-α treatment. Globally, inflammation, immune response, apoptosis, protein synthesis, and mitochondrial oxido-reduction were the most affected pathways in response to anti-TNF-α treatment. The obtained gene expression signature in PBMCs provides new information to better understand the mechanisms of action of anti-TNF-α treatment in RA patients.

Molecular signatures and new candidates to target the pathogenesis of rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic, inflammatory joint disease of unknown etiology and pronounced interpatient heterogeneity. To characterize RA at the molecular level and to uncover pathomechanisms, we performed genome-wide gene expression analysis. We identified a set of 1,054 genes significantly deregulated in pair-wise comparisons between RA and osteoarthritis (OA) patients, RA and normal donors (ND), or OA and ND. Correlation analysis revealed gene sets regulated identically in all three groups. As a prominent example secreted phosphoprotein 1 (SPP1) was identified to be significantly upregulated in RA compared with both OA and ND. SPP1 expression was found to correlate with genes expressed during an inflammatory response, T-cell activation and apoptosis, suggesting common underlying regulatory networks. A subclassification of RA patients was achieved on the basis of proteoglycan 4 (PRG4) expression, distinguishing PRG4 high and low expressors and reflecting the heterogeneity of the disease. In addition, we found that low PRG4 expression was associated with a more aggressive disease stage, which is in accordance with PRG4 loss-of-function mutations causing camptodactyly-arthropathy-coxa vara-pericarditis syndrome. Altogether we provide evidence for molecular signatures of RA and RA subclasses, sets of new candidate genes as well as for candidate gene networks, which extend our understanding of disease mechanisms and may lead to an improved diagnosis.

A comprehensive molecular interaction map for rheumatoid arthritis

Background

Computational biology contributes to a variety of areas related to life sciences and, due to the growing impact of translational medicine - the scientific approach to medicine in tight relation with basic science -, it is becoming an important player in clinical-related areas. In this study, we use computation methods in order to improve our understanding of the complex interactions that occur between molecules related to Rheumatoid Arthritis (RA).

Methodology

Due to the complexity of the disease and the numerous molecular players involved, we devised a method to construct a systemic network of interactions of the processes ongoing in patients affected by RA. The network is based on high-throughput data, refined semi-automatically with carefully curated literature-based information. This global network has then been topologically analysed, as a whole and tissue-specifically, in order to translate the experimental molecular connections into topological motifs meaningful in the identification of tissue-specific markers and targets in the diagnosis, and possibly in the therapy, of RA.

Significance

We find that some nodes in the network that prove to be topologically important, in particular AKT2, IL6, MAPK1 and TP53, are also known to be associated with drugs used for the treatment of RA. Importantly, based on topological consideration, we are also able to suggest CRKL as a novel potentially relevant molecule for the diagnosis or treatment of RA. This type of finding proves the potential of in silico analyses able to produce highly refined hypotheses, based on vast experimental data, to be tested further and more efficiently. As research on RA is ongoing, the present map is in fieri, despite being -at the moment- a reflection of the state of the art. For this reason we make the network freely available in the standardised and easily exportable .xml CellDesigner format at ‘www.picb.ac.cn/ClinicalGenomicNTW/temp.html’ and ‘www.celldesigner.org’.

Pharmacogenetics of rheumatoid arthritis: Potential targets from susceptibility genes and present therapies

Rheumatoid arthritis (RA) is a chronic heterogeneous autoimmune disorder of unknown etiology resulting in inflammation in the synovium, cartilage, and bone. Genetic factors play an important role in susceptibility to RA as the heritability of RA is between 50% and 60%, with the human leukocyte antigen (HLA) locus accounting for at least 30% of overall genetic risk. Outside the major histocompatibility complex (MHC) region, six additional risk loci have been identified and validated including PTPN22, STAT4, PADI4, CTLA4, TNFAIP3-OLIG3, and TRAF1/C5. Genetic factors are also important in RA pharmacotherapy due to the gene-dependent activity of enzymes involved in the pharmacokinetics and/or pharmacodynamics of RA medications. Indeed, there is great variability in drug efficacy as well as adverse events associated with any anti-rheumatic therapy and genetics is thought to contribute significantly to this inter-individual variability in response. This review will summarize the genetic factors that have been implicated in the pathogenesis of RA, and how these determinants may factor into the potential pharmacogenetics of this disease. We will also review the therapeutic agents that are currently being utilized or presently being evaluated in the treatment of RA, along with potential pharmacogenetic markers that have been proposed for such medications.