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Heterogeneity of Synovial Molecular Patterns in Patients with Arthritis
Abstract and Figures
Objectives:
Early diagnosis of rheumatoid arthritis (RA) is an unmet medical need in the field of rheumatology. Previously, we performed high-density transcriptomic studies on synovial biopsies from patients with arthritis, and found that synovial gene expression profiles were significantly different according to the underlying disorder. Here, we wanted to further explore the consistency of the gene expression signals in synovial biopsies of patients with arthritis, using low-density platforms.
Methods:
Low-density assays (cDNA microarray and microfluidics qPCR) were designed, based on the results of the high-density microarray data. Knee synovial biopsies were obtained from patients with RA, spondyloarthropathies (SA) or osteoarthritis (OA) (n = 39), and also from patients with initial undifferentiated arthritis (UA) (n = 49).
Results:
According to high-density microarray data, several molecular pathways are differentially expressed in patients with RA, SA and OA: T and B cell activation, chromatin remodelling, RAS GTPase activation and extracellular matrix regulation. Strikingly, disease activity (DAS28-CRP) has a significant influence on gene expression patterns in RA samples. Using the low-density assays, samples from patients with OA are easily discriminated from RA and SA samples. However, overlapping molecular patterns are found, in particular between RA and SA biopsies. Therefore, prediction of the clinical diagnosis based on gene expression data results in a diagnostic accuracy of 56.8%, which is increased up to 98.6% by the addition of specific clinical symptoms in the prediction algorithm. Similar observations are made in initial UA samples, in which overlapping molecular patterns also impact the accuracy of the diagnostic algorithm. When clinical symptoms are added, the diagnostic accuracy is strongly improved.
Conclusions:
Gene expression signatures are overall different in patients with OA, RA and SA, but overlapping molecular signatures are found in patients with these conditions. Therefore, an accurate diagnosis in patients with UA requires a combination of gene expression and clinical data.
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... However, very few datasets contained COP expression except for a microarray dataset (GEO: GSE36700) of synovial biopsies from patients with rheumatologic diseases (rheumatoid arthritis, systemic lupus erythematosus, osteoarthritis, and psoriatic arthritis) and crystal-induced arthritis (CIA). 43,44 Interestingly, CARD16 expression was lower in CIA than in other forms of arthritis and only narrowly missed significance (p = 0.0506), while CARD18 expression trended higher but was not significant ( Figure 1A). A CARD17 probe was not present in this dataset. ...
... Since COPs are thought to block inflammasome activation by binding to and inhibiting caspase-1, COPs consequently should affect other inflammasomes besides the NLRP3 inflammasome. Indeed, IL-1b and IL-18 release was also reduced by COPs and in Casp1 À/À BMDM in response to AIM2 inflammasome activation by poly(dA:dT) transfection, NLRP1b inflammasome activation by Bacillus anthracis lethal toxin, and NLRC4 inflammasome activation by transfection 43,44 (B) THP-1 cells were left untreated or were treated with MSU crystals (90 mg mL À1 ) for 5 h, and mRNA expression of CARD16, CARD17, and CARD18 was determined by qPCR and presented as fold expression compared with untreated cells (n = 6, mean ± SD). *p < 0.05. (C) In vivo imaging of MPO activity correlating with MSU-induced neutrophil infiltration into air pouches 7 h after MSU crystal injection (3 mg per air pouch) in wildtype (WT), CARD16 TG , CARD17 TG , CARD18 TG , and Casp1 À/À mice (left) and average radiance (right) presented as photons/s/cm 2 /sr (n = 4-5, mean ± SD). *p < 0.05. ...
Inflammatory responses are crucial for controlling infections and initiating tissue repair. However, excessive and uncontrolled inflammation causes inflammatory disease. Processing and release of the pro-inflammatory cytokines interleukin-1β (IL-1β) and IL-18 depend on caspase-1 activation within inflammasomes. Assembly of inflammasomes is initiated upon activation of cytosolic pattern recognition receptors (PRRs), followed by sequential polymerization of pyrin domain (PYD)-containing and caspase recruitment domain (CARD)-containing proteins mediated by homotypic PYD and CARD interactions. Small PYD- or CARD-only proteins (POPs and COPs, respectively) evolved in higher primates to target these crucial interactions to limit inflammation. Here, we show the ability of COPs to regulate inflammasome activation by modulating homotypic CARD-CARD interactions in vitro and in vivo. CARD16, CARD17, and CARD18 displace crucial CARD interactions between caspase-1 proteins through competitive binding and ameliorate uric acid crystal-mediated NLRP3 inflammasome activation and inflammatory disease. COPs therefore represent an important family of inflammasome regulators and ameliorate inflammatory disease.
... Frontiers in Genetics frontiersin.org 10 previous studies on synovial inflammation, but the overall design of these studies involved RNA-seq for synovial tissues from inflammatory/degenerative joint diseases compared with healthy individuals/trauma patients (Woetzel et al., 2014;Lauwerys et al., 2015). To our knowledge, high-throughput RNA sequencing of inflamed and normal synovial tissues following ACL/meniscus injury have not been performed. ...
Background: Despite ample evidence demonstrating that anterior cruciate ligament (ACL) and meniscus tears are associated with posttraumatic osteoarthritis (PTOA) development, the contributing factors remain unknown. Synovial inflammation has recently been recognized as a pivotal factor in the pathogenesis of OA. However, there is a lack of data on synovial profiles after ACL or meniscus injuries, which may contribute to PTOA.
Methods: Twelve patients with ACL tears and/or meniscus injuries were recruited. During surgery, synovial tissues were obtained from the injured knees. The inflammation status of the synovium was characterized according to macroscopic criteria and histological synovitis grades. Then the synovial tissues were classified as control group or inflamed group. High-throughput RNA sequencing of the synovial samples (3 vs. 3) was conducted to identify differentially expressed (DE) RNAs. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein–protein interaction (PPI) analyses were performed to investigate DE mRNAs. Next, competing endogenous RNA (ceRNA) networks were constructed based on bioinformatics analyses. Associations of the identified DE genes (DEGs) with infiltrating immune cells were explored using Pearson correlation analysis.
Results: The results showed that 2793 mRNAs, 3392 lncRNAs and 211 miRNAs were significantly DE between two groups. The top 3 significantly upregulated GO terms and KEGG pathways were immune response, adaptive immune response and immune system process, systemic lupus erythematosus, haematopoietic cell lineage and cytokine–cytokine receptor interaction, respectively. In PPI networks, the top 10 hub genes were IL6, CCR7, C3, CCR5, CXCR3, CXCL8, IL2, CCR3, CCR2 and CXCL1. Seven mRNAs (EPHA5, GSN, ORC1, TLN2, SOX6, NKD2 and ADAMTS19), 4 lncRNAs (MIR4435-2HG, TNXA, CEROX1 and TMEM92-AS1) and 3 miRNAs (miR-486-5p, miR-199a-3p and miR-21-3p) were validated by quantitative real-time polymerase chain reaction and sub-networks were constructed. In correlation analysis, MMP9 correlated positively with M0 macrophages and plasma cells, NKD2 positively with CD8 T cells, and CCR7 and IL2RB positively with naive B cells.
Conclusion: Our study provides foundational synovial inflammation profiles following knee trauma. The ceRNA and PPI networks provide new insight into the biological processes and underlying mechanisms of PTOA. The differential infiltration profiles of immune cells in synovium may contribute to PTOA development. This study also highlights immune-related DEGs as potential PTOA treatment biomarkers.
... There have been many different attempts to delve into the etiology and mechanisms of different joint diseases in order to differentiate one joint disease from another and to improve the diagnosis and treatment, with synovial fluid (SF) as the main sample source [5]. Actually, SF is also commonly used in evaluation of efficacy or prognosis of various treatments or manage-ment of joint diseases [6]. For example, genetic influences in various types of arthritis have been explored, and some genetic backgrounds have been found to predispose certain individuals to OA or rheumatoid arthritis [7]. ...
Objective:
To investigate the RNA profile of synovial fluid (SF) from osteoarthritis (OA) patients and carry out cluster analysis of OA-related genes.
Methods:
RNA of SF from OA patients was isolated using RNA-specific Trizol. A cDNA library was built and subjected to the second-generation sequencing using HisSeq4000 with a data size of 8G. The sequencing reads were aligned to the UCSC human reference genome (hg38) using Tophat with default parameters. Gene function enrichment was generated using DAVID.
Results:
The minimum weight 0.096 µg RNA of SF sample was used for sequencing analysis, which produced 66,154,562 clean reads, 91.28% of which were matched to the reference with 2,682 genes identified. Some of the unmatchable reads matched RNAs of bacteria, mainly Pseudomonas. The detected human RNAs in samples fell into different categories of genes, including protein-coding ones, processed and unprocessed pseudogenes, and long noncoding, antisense and miscellaneous RNAs that mediate various biological functions. Interestingly, 80% of the expressed genes belonged to the mitochondrial genome.
Conclusion:
These results suggest that less than 0.1 µg RNA is sufficient for establishing a cDNA library and deep sequencing, and that the liquid fraction of SF contains a whole RNA repertoire that may reflect a history of previous microorganism infections.
... Because of this, there has been a longstanding interest in identifying predictive synovial biomarkers early in the disease process that could help classify the inflammatory lesions based on pathotypes which could, in turn, potentially inform difficult clinical decisions (7,20). Much progress has been made in this area, particularly recently, where large international consortia have provided intriguing new data based on state-of-the-art analyses of the synovial biopsies (3,7,21). Yet, despite the availability of sizable cohorts of RA patients who have undergone synovial biopsy in research settings, a key gap is the lack of data regarding the long-term outcomes of these biopsied RA patients in routine clinical settings where individuals typically cycle through several agents, alone or in combination. ...
Objective
Rheumatoid arthritis is a chronic inflammatory autoimmune disease that can lead to synovial damage, persistent joint pain, and functional disability. Our objective was to evaluate baseline synovial transcriptome from early inflammatory arthritis patients (EIA) and identify pretreatment biomarkers that could potentially provide insights into long-term functional outcomes of rheumatoid arthritis (RA).
Methods
Synovial biopsies from clinically inflamed knee joints were procured from either 17 EIA patients before initiation of disease modifying anti-rheumatic drug (DMARD) therapy (DMARD-naïve EIA) using the minimally invasive closed needle biopsy technique or advanced RA patients undergoing arthroplasty. Affymetrix Human Genome U133 Plus 2 microarray platform was used to profile the synovial transcriptome. The cohort was followed clinically for a median of 12.3 years, and patient data was collected at each visit. Short-term and long-term clinical outcomes were determined by assessing RA-associated clinical parameters Statistical adjustments were made to account for asynchronous clinical visits and duration of follow up.
Results
Based on the transcriptomic analysis, we identified 5 differentially expressed genes (DEGs), including matrix metalloproteinase (MMP)-1 (fibroblast collagenase) and MMP-3 (stromelysin-1) in DMARD-naïve EIA patients, relative to advanced RA patients ( q < 0.05). Dichotomous expression of MMP-1 and MMP-3 mRNA and protein was confirmed by qPCR and immunohistochemistry respectively, based on which DMARD-naïve EIA subjects were classified as MMP-high or MMP-low. Hierarchical clustering of transcriptomic data identified 947 DEGs between MMP-high and MMP-low cohorts. Co-expression and IPA analysis of DEGs in the MMP-high cohort showed an enrichment of genes that participated in metabolic or biochemical functions and intracellular immune signaling were regulated through NF-κB and β-catenin complexes and correlated with markers of systemic inflammation. Analysis of short-term clinical outcomes in MMP-high cohort showed a significant reduction in the DAS-CRP scores relative to baseline (P <0.001), whereas area under the curve analyses of modified HAQ (mHAQ) scores correlated negatively with baseline MMP-1 ( R = −0.59, P = 0.03). Further, longitudinal mHAQ scores, number of swollen joints, number of DMARDs and median follow-up duration appeared to be higher in MMP-low cohort.
Conclusion
Overall, our results indicate that the gene expression profiling of synovial biopsies obtained at the DMARD-naive stage in patients with EIA categorizes them into subsets with varying degrees of inflammation and can predict the future of long-term clinical outcome.
... nih. gov/ geo/ [8][9][10][11][12]. ...
Background
Rheumatoid arthritis (RA) and osteoarthritis (OA) share some similar arthritic symptoms, but different mechanisms underlie the pathogenesis of these two diseases. Analysis of differentially expressed molecules in rheumatoid arthritis and osteoarthritis may assist in improving diagnosis and treatment strategies in clinical practice.
Methods
Microarray and RNA-seq data were acquired from the gene expression omnibus database. Differentially expressed genes (DEGs) were identified using Bioconductor packages. Receiver operating characteristic curves were plotted to assess performance. Gene ontology enrichment analysis was conducted using the clusterProfiler application. During validation, synovial fluid was harvested from patients who had undergone in-hospital joint replacement, in which the expression of proteins was measured using enzyme-linked immunosorbent assays.
Results
Compared with OA samples, RA samples showed 14 genes to be upregulated and 3 to be downregulated. Gene ontology analysis indicated that DEGs principally included molecules responsible for the regulation of a synovial tissue inflammatory response. Seven genes displayed a good discriminatory power with an AUC higher than 0.90. ADAMDEC1 was the biomarker that most clearly discriminated RA from OA in the database, exhibiting an AUC of 0.999, a sensitivity of 100%, and a specificity of 97.8%. Following validation, the expression levels of ADAMDEC1 in the synovial fluid from RA patients were significantly higher than those in the synovial fluid from OA patients ( P < 0.05). At the cut-off value of 1957 pg/mL, ADAMDEC1 expression in the synovial fluid discriminated RA from OA with an AUC of 0.951, a specificity of 88.6%, and a sensitivity of 92.9%.
Conclusion
The differential expression of genes in RA compared with OA indicates potential targets for molecular diagnosis and treatment. The presence of ADAMDEC1 in synovial fluid is a good biomarker of RA.
... In the 80s, it has been shown that synovial biopsy of the affected knee in RA patients changes in terms of T and B cells infiltrates according to disease activity when pre-and posttreatment were assessed (39,51). For this reason, synovial biopsy has also been proposed as a biomarker to evaluate drug response (19,21,52). ...
In the majority of joint diseases, changes in the organization of the synovial architecture appear early. Synovial tissue analysis might provide useful information for the diagnosis, especially in atypical and rare joint disorders, and might have a value in case of undifferentiated inflammatory arthritis, by improving disease classification. After patient selection, it is crucial to address the dialogue between the clinician and the pathologist for adequately handling the sample, allowing identifying histological patterns depending on the clinical suspicion. Moreover, synovial tissue analysis gives insight into disease progression helping patient stratification, by working as an actionable and mechanistic biomarker. Finally, it contributes to an understanding of joint disease pathogenesis holding promise for identifying new synovial biomarkers and developing new therapeutic strategies. All of the indications mentioned above are not so far from being investigated in everyday clinical practice in tertiary referral hospitals, thanks to the great feasibility and safety of old and more recent techniques such as ultrasound-guided needle biopsy and needle arthroscopy. Thus, even in rheumatology clinical practice, pathobiology might be a key component in the management and treatment decision-making process. This review aims to examine some essential and crucial points regarding why, when, where, and how to perform a synovial biopsy in clinical practice and research settings and what information you might expect after a proper patient selection.
Biological and targeted synthetic disease-modifying anti-rheumatic drugs (b/tsDMARDs) have revolutionized the management of multiple rheumatic inflammatory conditions. Amongst these, polyarticular juvenile idiopathic arthritis (pJIA) and rheumatoid arthritis (RA) display similarities in terms of disease pathophysiology and response pattern to b/tsDMARDs. Indeed, therapeutic efficacy of novel targeted drugs is variable among individual patients, in both RA and pJIA. Mechanisms and determinants of this heterogeneous response are diverse and complex, such that development of true “precision”-medicine strategies has proven highly challenging. In this review, we will discuss pathophysiological, patient-specific, drug-specific and environmental factors contributing to individual therapeutic response in polyarticular JIA in comparison to what is known in RA. Although some biomarkers have been identified that stratify for the likelihood of either therapeutic response or non-response, few have proved useful in clinical practice so far, likely due to the complexity of treatment-response mechanisms. Consequently, we propose a pragmatic, patient-centered and clinically-based approach, i.e. personalized instead of biomarker-based precision medicine in JIA.
Objectives
Transcriptomic profiling of synovial tissue from patients with early, untreated rheumatoid arthritis (RA) was used to explore the ability of unbiased, data-driven approaches to define clinically relevant subgroups.
Methods
RNASeq was performed on 74 samples, with disease activity data collected at inclusion. Principal components analysis (PCA) and unsupervised clustering were used to define patient clusters based on expression of the most variable genes, followed by pathway analysis and inference of relative abundance of immune cell subsets. Histological assessment and multiplex immunofluorescence (for CD45, CD68, CD206) were performed on paraffin sections.
Results
PCA on expression of the (n=894) most variable genes across this series did not divide samples into distinct groups, instead yielding a continuum correlated with baseline disease activity. Two patient clusters (PtC1, n=52; PtC2, n=22) were defined based on expression of these genes. PtC1, with significantly higher disease activity and probability of response to methotrexate therapy, showed upregulation of immune system genes; PtC2 showed upregulation of lipid metabolism genes, described to characterise tissue resident or M2-like macrophages. In keeping with these data, M2-like:M1-like macrophage ratios were inversely correlated with disease activity scores and were associated with lower synovial immune infiltration and the presence of thinner, M2-like macrophage-rich synovial lining layers.
Conclusion
In this large series of early, untreated RA, we show that the synovial transcriptome closely mirrors clinical disease activity and correlates with synovial inflammation. Intriguingly, lower inflammation and disease activity are associated with higher ratios of M2:M1 macrophages, particularly striking in the synovial lining layer. This may point to a protective role for tissue resident macrophages in RA.
Purpose of review:
To summarize recent studies stratifying SLE patients into subgroups based on gene expression profiling and suggest future improvements for employing transcriptomic data to foster precision medicine.
Recent findings:
Bioinformatic & machine learning pipelines have been employed to dissect the transcriptomic heterogeneity of lupus patients and identify more homogenous subgroups. Some examples include the use of unsupervised random forest and k-means clustering to separate adult SLE patients into seven clusters and hierarchical clustering of single-cell RNA-sequencing (scRNA-seq) of immune cells yielding four clusters in a cohort of adult SLE and pediatric SLE participants. Random forest classification of bulk RNA-seq data from sorted blood cells enabled prediction of high or low disease activity in European and Asian SLE patients. Inferred transcription factor activity stratified adult and pediatric SLE into two subgroups.
Summary:
Several different endotypes of SLE patients with differing molecular profiles have been reported but a global consensus of clinically actionable groups has not been reached. Moreover, heterogeneity between datasets, reproducibility of predictions as well as the most effective classification approach have not been resolved. Nevertheless, gene expression-based precision medicine remains an attractive option to subset lupus patients.
Introduction/objectivesRheumatoid arthritis (RA) and osteoarthritis (OA) are two common joint diseases with similar clinical manifestations. Our study aimed to identify differential gene biomarkers in the synovial tissue between RA and OA using bioinformatics analysis and validation.MethodGSE36700, GSE1919, GSE12021, GSE55235, GSE55584, and GSE55457 datasets were downloaded from the Gene Expression Omnibus database. A total of 57 RA samples and 46 OA samples were included. The differentially expressed genes (DEGs) were identified. The Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were also performed. Protein–protein interaction (PPI) network of DEGs and the hub genes were constructed and visualized via Search Tool for the Retrieval of Interacting Genes/Proteins, Cytoscape, and R. Selected hub genes were validated via reverse transcription-polymerase chain reaction.ResultsA total of 41 DEGs were identified. GO functional enrichment analysis showed that DEGs were enriched in immune response, signal transduction, regulation of immune response for biological process, in plasma membrane and extracellular region for cell component, and antigen binding and serine-type endopeptidase activity for molecular function. KEGG pathway analysis showed that DEGs were enriched in cytokine-cytokine receptor interaction and chemokine signaling pathway. PPI network analysis established 70 nodes and 120 edges and 15 hub genes were identified. The expression of CXCL13, CXCL10, and ADIPOQ was statistically different between RA and OA synovial tissue.Conclusion
Differential expression of CXCL13, CXCL10, and ADIPOQ between RA and OA synovial tissue may provide new insights for understanding the RA development and difference between RA and OA.
Key Points
• Bioinformatics analysis was used to identify the differentially expressed genes in the synovial tissue between rheumatoid arthritis and osteoarthritis.
• CXCL13, CXCL10, and ADIPOQ might provide new insight for understanding the differences between RA and OA.
The 1987 American College of Rheumatology (ACR; formerly the American Rheumatism Association) classification criteria for rheumatoid arthritis (RA) have been criticised for their lack of sensitivity in early disease. This work was undertaken to develop new classification criteria for RA.
A joint working group from the ACR and the European League Against Rheumatism developed, in three phases, a new approach to classifying RA. The work focused on identifying, among patients newly presenting with undifferentiated inflammatory synovitis, factors that best discriminated between those who were and those who were not at high risk for persistent and/or erosive disease--this being the appropriate current paradigm underlying the disease construct 'RA'.
In the new criteria set, classification as 'definite RA' is based on the confirmed presence of synovitis in at least one joint, absence of an alternative diagnosis better explaining the synovitis, and achievement of a total score of 6 or greater (of a possible 10) from the individual scores in four domains: number and site of involved joints (range 0-5), serological abnormality (range 0-3), elevated acute-phase response (range 0-1) and symptom duration (two levels; range 0-1).
This new classification system redefines the current paradigm of RA by focusing on features at earlier stages of disease that are associated with persistent and/or erosive disease, rather than defining the disease by its late-stage features. This will refocus attention on the important need for earlier diagnosis and institution of effective disease-suppressing therapy to prevent or minimise the occurrence of the undesirable sequelae that currently comprise the paradigm underlying the disease construct 'RA'.
Objective
The 1987 American College of Rheumatology (ACR; formerly, the American Rheumatism Association) classification criteria for rheumatoid arthritis (RA) have been criticized for their lack of sensitivity in early disease. This work was undertaken to develop new classification criteria for RA.
Methods
A joint working group from the ACR and the European League Against Rheumatism developed, in 3 phases, a new approach to classifying RA. The work focused on identifying, among patients newly presenting with undifferentiated inflammatory synovitis, factors that best discriminated between those who were and those who were not at high risk for persistent and/or erosive disease—this being the appropriate current paradigm underlying the disease construct “rheumatoid arthritis.”
Results
In the new criteria set, classification as “definite RA” is based on the confirmed presence of synovitis in at least 1 joint, absence of an alternative diagnosis that better explains the synovitis, and achievement of a total score of 6 or greater (of a possible 10) from the individual scores in 4 domains: number and site of involved joints (score range 0–5), serologic abnormality (score range 0–3), elevated acute-phase response (score range 0–1), and symptom duration (2 levels; range 0–1).
Conclusion
This new classification system redefines the current paradigm of RA by focusing on features at earlier stages of disease that are associated with persistent and/or erosive disease, rather than defining the disease by its late-stage features. This will refocus attention on the important need for earlier diagnosis and institution of effective disease-suppressing therapy to prevent or minimize the occurrence of the undesirable sequelae that currently comprise the paradigm underlying the disease construct “rheumatoid arthritis.”
We randomly assigned a total of 508 patients to receive sequential monotherapy (group 1, n = 126), step-up combination therapy (group 2, n = 121), initial combination therapy with prednisone (group 3, n = 133), or initial combination therapy with infliximab (group 4, n = 128) (Figure 1). At baseline, the groups were balanced with respect to demographic and disease characteristics (Table 1). Enrolled patients had a median disease duration of 23 weeks (interquartile range, 14 to 53 weeks) and had active disease with mean disease activity and HAQ scores of 4.4 (SD, 0.9) and 1.4 (SD, 0.7), respectively. Seventy-two percent of patients had joint erosions at baseline. Over time, 27 patients who were equally distributed across the treatment groups (P = 0.474) were lost to follow-up: 12 withdrew consent (7 declined follow-up, 4 discontinued all medications despite having no adverse events, and 1 moved from the area), 7 had a revised diagnosis, 1 discontinued treatment because of an adverse event, 4 died, and 3 were lost to follow-up for other reasons (2 were admitted to a nursing home and 1 wanted to become pregnant) (Figure 1). Furthermore, 12 (10%), 11 (9%), 14 (11%), and 6 (5%) patients in groups 1, 2, 3, and 4, respectively (P = 0.343), did not adhere to the treatment protocol but were included in the intention-to-treat analysis.
The revised criteria for the classification of rheumatoid arthritis (RA) were formulated from a computerized analysis of 262 contemporary, consecutively studied patients with RA and 262 control subjects with rheumatic diseases other than RA (non-RA). The new criteria are as follows: 1) morning stiffness in and around joints lasting at least 1 hour before maximal improvement; 2) soft tissue swelling (arthritis) of 3 or more joint areas observed by a physician; 3) swelling (arthritis) of the proximal interphalangeal, metacarpophalangeal, or wrist joints; 4) symmetric swelling (arthritis); 5) rheumatoid nodules; 6) the presence of rheumatoid factor; and 7) radiographic erosions and/or periarticular osteopenia in hand and/or wrist joints. Criteria 1 through 4 must have been present for at least 6 weeks. Rheumatoid arthritis is defined by the presence of 4 or more criteria, and no further qualifications (classic, definite, or probable) or list of exclusions are required. In addition, a “classification tree” schema is presented which performs equally as well as the traditional (4 of 7) format. The new criteria demonstrated 91–94% sensitivity and 89% specificity for RA when compared with non-RA rheumatic disease control subjects.
Objective:
To investigate the global molecular effects of tocilizumab (TCZ) in comparison with methotrexate (MTX) treatment in synovial biopsy tissue obtained from patients with previously untreated rheumatoid arthritis (RA) before therapy (T0) and 12 weeks after the initiation of therapy (T12), and to compare the results with previous gene expression data obtained in synovial biopsy tissue from adalimumab (ADA)- and rituximab (RTX)-treated patients with RA.
Methods:
Paired synovial biopsy samples were obtained at T0 and T12 from the affected knee of TCZ-treated RA patients and MTX-treated RA patients. Gene expression studies were performed using GeneChip Human Genome U133 Plus 2.0 microarrays, and confirmatory quantitative real-time reverse transcription-polymerase chain reaction experiments were performed on selected transcripts. The effects of TCZ and MTX on synovial cell populations and histologic characteristics were assessed by immunohistochemistry.
Results:
Gene expression studies showed that blockade of the interleukin-6 receptor (IL-6R) gene (IL6R) using TCZ induced a significant decrease in the expression of numerous chemokine and T cell activation genes in the RA synovium. These effects strongly correlated with the molecular effects of MTX and RTX therapy on RA synovial tissue, but differed from the molecular changes induced by ADA (decreased expression of genes involved in cell proliferation).
Conclusion:
The molecular similarities between the effects of TCZ, RTX, and MTX therapies in the RA synovium indicate that B cell- and IL-6-dependent pathways play synergistic roles in the pathogenesis of the disease, in particular through activation of T cell responses. Moreover, these results open perspectives for the individualization of therapeutic decisions, based on a better knowledge of the synovial molecular effects of each type of RA therapy.
To examine the implications of using the new classification criteria for rheumatoid arthritis (RA) in clinical practice in a cohort of patients with very early arthritis.
The study group comprised 301 disease-modifying antirheumatic drug-naive patients with early arthritis. The baseline diagnosis was assessed by applying the 1987 American College of Rheumatology (ACR) and 2010 ACR/European League Against Rheumatism (EULAR) criteria for RA as well as established diagnostic criteria for other rheumatic diseases. Diagnostic and prognostic data were collected after 2 years of followup. Fulfillment of the 2010 ACR/EULAR criteria was evaluated in the subset of patients in whom undifferentiated arthritis (UA) was diagnosed when the 1987 ACR criteria were applied, and fulfillment of RA criteria over time was tested by applying the 2 different criteria sets.
The median arthritis duration at baseline was 4 months (range 0-12 months). At baseline, 28% of the patients fulfilled the 1987 ACR criteria, and 45% fulfilled the 2010 ACR/EULAR criteria for RA. Among the patients classified as having UA at baseline according to the 1987 ACR criteria, 36% had fulfilled the 2010 ACR/EULAR criteria already at baseline. Among the patients classified as having UA at baseline but who fulfilled the 1987 ACR criteria after 2 years of followup, 85% had fulfilled the 2010 ACR/EULAR criteria at baseline. Patients with early disease who fulfilled the 2010 ACR/EULAR criteria were less likely to be autoantibody positive and more likely to have monarthritis at presentation than those fulfilling the 1987 ACR criteria.
Use of the 2010 ACR/EULAR criteria clearly allows earlier diagnosis of RA, although the clinical picture is slightly different on the group level, and RA may be falsely diagnosed in some patients with self-limiting disease.
Recently, an American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) collaboration developed new classification criteria for rheumatoid arthritis (RA).
To evaluate the diagnostic and discriminative ability of these new criteria compared with the 1987 ACR criteria and the Visser decision rule.
455 patients with early arthritis were studied. The diagnostic performance of the criteria was evaluated using methotrexate treatment within 1 year, expert opinion RA and erosive disease as 'gold standards'. Erosive disease was defined as a 0-3 year change in radiographic score of ≥5.
The discriminative ability of the three criteria sets (2010 ACR/EULAR, 1987 ACR criteria and Visser algorithm) was similar with areas under the curve of 0.71-0.78 ('gold standard' methotrexate), 0.74-0.80 (gold standard expert opinion RA) and 0.63-0.67 (gold standard erosive disease after 3 years). The sensitivity of the 2010 ACR/EULAR criteria was highest with 0.85 (gold standard methotrexate). 86% of patients with RA and 51% of 'non-RA' patients according to the new criteria used methotrexate.
The 2010 ACR/EULAR criteria were slightly more sensitive, but otherwise performed similarly to the older criteria. A high percentage of 'non-RA' patients used methotrexate, the gold standard for RA. The ability of the new criteria to identify patients with erosive disease was low, possibly owing to the effect of intensive treatment.
Rituximab displays therapeutic benefits in the treatment of patients with rheumatoid arthritis (RA) resistant to tumor necrosis factor (TNF) blockade. However, the precise role of B cells in the pathogenesis of RA is still unknown. We undertook this study to investigate the global molecular effects of rituximab in synovial biopsy samples obtained from anti-TNF-resistant RA patients before and after administration of the drug.
Paired synovial biopsy samples were obtained from the affected knee of anti-TNF-resistant RA patients before (time 0) and 12 weeks after (time 12) initiation of rituximab therapy. Total RNA was extracted, labeled according to standard Affymetrix procedures, and hybridized on GeneChip HGU133 Plus 2.0 slides. Immunohistochemistry and quantitative real-time reverse transcriptase-polymerase chain reaction experiments were performed to confirm the differential expression of selected transcripts.
According to Student's paired t-tests, 549 of 54,675 investigated probe sets were differentially expressed between time 0 and time 12. Pathway analysis revealed that genes down-regulated between time 0 and time 12 were significantly enriched in immunoglobulin genes and genes involved in chemotaxis, leukocyte activation, and immune responses (Gene Ontology annotations). In contrast, genes up-regulated between time 0 and time 12 were significantly enriched in transcripts involved in cell development (Gene Ontology annotation) and wound healing (Gene Set Enrichment Analysis). At baseline, higher synovial expression of immunoglobulin genes was associated with response to therapy.
Rituximab displays unique effects on global gene expression profiles in the synovial tissue of RA patients. These observations open new perspectives in the understanding of the biologic effects of the drug and in the selection of patients likely to benefit from this therapy.
We previously demonstrated that baseline synovial overexpression of the interleukin-7 receptor α-chain (IL-7R) is associated with poor response to tumour necrosis factor (TNF) blockade in rheumatoid arthritis (RA). We found that IL-7R gene expression is induced in fibroblast-like synovial cells (FLS) by the addition of TNF-α, IL-1β and combinations of TNF-α+ IL-1β or TNF-α+ IL-17, thereby suggesting that these cytokines play a role in the resistance to TNF blockade in RA. Because FLS and CD4 T cells also produce a soluble form of IL-7R (sIL-7R), resulting from an alternative splicing of the full-length transcript, we wondered whether expression of sIL-7R is similarly regulated by pro-inflammatory cytokines. We also investigated whether sIL-7R is detectable in the serum of RA patients and associated with response to TNF blockade. RA FLS were cultured in the presence of pro-inflammatory cytokines and sIL-7R concentrations were measured in culture supernatants. Similarly, sIL-7R titres were measured in sera obtained from healthy individuals, early untreated RA patients with active disease and disease-modifying anti-rheumatic drug (DMARD)-resistant RA patients prior to initiation of TNF-blockade. Baseline serum sIL-7R titres were correlated with validated clinical measurements of disease activity. We found that exposure of RA FLS to pro-inflammatory cytokines (TNF-α, IL-1β and combinations of TNF-α and IL-1β or TNF-α and IL-17) induces sIL-7R secretion. Activated CD4 T cells also produce sIL-7R. sIL-7R serum levels are higher in RA patients as compared to controls. In DMARD-resistant patients, high sIL-7R serum concentrations are strongly associated with poor response to TNF-blockade. In conclusion, sIL-7R is induced by pro-inflammatory cytokines in RA FLS. sIL-7R could qualify as a new biomarker of response to therapy in RA.