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.

The multitude and abundance of macrophage-derived mediators in rheumatoid arthritis and their paracrine/autocrine effects identify macrophages as local and systemic amplifiers of disease. Although uncovering the etiology of rheumatoid arthritis remains the ultimate means to silence the pathogenetic process, efforts in understanding how activated macrophages influence disease have led to optimization strategies to selectively target macrophages by agents tailored to specific features of macrophage activation. This approach has two advantages: (a) striking the cell population that mediates/amplifies most of the irreversible tissue destruction and (b) sparing other cells that have no (or only marginal) effects on joint damage.

Introduction: Rheumatoid arthritis (RA) is a chronic inflammatory and destructive joint disease characterized by overexpression of pro-inflammatory/pro-destructive genes and other activating genes (for example, proto-oncogenes) in the synovial membrane (SM). The gene expression in disease is often characterized by significant inter-individual variances via specific synchronization/desynchronization of gene expression. To elucidate the contribution of the variance to the pathogenesis of disease, expression variances were tested in SM samples of RA patients, osteoarthritis (OA) patients, and normal controls (NCs).Method: Analysis of gene expression in RA, OA, and NC samples was carried out using Affymetrix U133A/B oligonucleotide arrays, and the results were validated by real-time reverse transcription-polymerase chain reaction. For the comparison between RA and NC, 568 genes with significantly different variances in the two groups (P≤ 0.05; Bonferroni/Holm corrected Brown-Forsythe version of the Levene test) were selected. For the comparison between RA and OA, 333 genes were selected. By means of theKyoto Encyclopedia of Genes and Genomes, the pathways/complexes significantly affected by higher gene expression variances were identified in each group.Results: Ten pathways/complexes significantly affected by higher gene expression variances were identified in RA compared with NC, including cytokine–cytokine receptor interactions, the transforming growth factor-beta pathway, and anti-apoptosis. Compared with OA, three pathways with significantly higher variances were identified in RA (for example, B-cell receptor signaling and vascular endothelial growth factor signaling). Functionally, the majority of the identified pathways are involved in the regulation of inflammation, proliferation, cell survival, and angiogenesis.Conclusion: In RA, a number of disease-relevant or even disease-specific pathways/complexes are characterized by broad intra-group inter-individual expression variances. Thus, RA pathogenesis in different individuals may depend to a lesser extent on common alterations of the expression of specific key genes, and rather on individual-specific alterations of different genes resulting in common disturbances of key pathways.

Genome-wide gene expression was comparatively investigated in early-passage rheumatoid arthritis (RA) and osteoarthritis (OA) synovial fibroblasts (SFBs; n = 6 each) using oligonucleotide microarrays; mRNA/protein data were validated by quantitative PCR (qPCR) and western blotting and immunohistochemistry, respectively. Gene set enrichment analysis (GSEA) of the microarray data suggested constitutive upregulation of components of the transforming growth factor (TGF)-β pathway in RA SFBs, with 2 hits in the top 30 regulated pathways. The growth factor TGF-β1, its receptor TGFBR1, the TGF-β binding proteins LTBP1/2, the TGF-β-releasing thrombospondin 1 (THBS1), the negative effector SkiL, and the smad-associated molecule SARA were upregulated in RA SFBs compared to OA SFBs, whereas TGF-β2 was downregulated. Upregulation of TGF-β1 and THBS1 mRNA (both positively correlated with clinical markers of disease activity/severity) and downregulation of TGF-β2 mRNA in RA SFBs were confirmed by qPCR. TGFBR1 mRNA (only numerically upregulated in RA SFBs) and SkiL mRNA were not differentially expressed. At the protein level, TGF-β1 showed a slightly higher expression, and the signal-transducing TGFBR1 and the TGF-β-activating THBS1 a significantly higher expression in RA SFBs than in OA SFBs. Consistent with the upregulated TGF-β pathway in RA SFBs, stimulation with TGF-β1 resulted in a significantly enhanced expression of matrix-metalloproteinase (MMP)-11 mRNA and protein in RA SFBs, but not in OA SFBs. In conclusion, RA SFBs show broad, constitutive alterations of the TGF-β pathway. The abundance of TGF-β, in conjunction with an augmented mRNA and/or protein expression of TGF-β-releasing THBS1 and TGFBR1, suggests a pathogenetic role of TGF-β-induced effects on SFBs in RA, for example, the augmentation of MMP-mediated matrix degradation/remodeling.

Introduction: Mesenchymal stem cells (MSC) are highly attractive for use in cartilage regeneration. To date, MSC are usually recruited from subchondral bone marrow using microfracture. Recent data suggest that isolated cells from adult human articular cartilage, which express the combination of the cell-surface markers CD105 and CD166, are multi-potent mesenchymal progenitor cells (MPC) with characteristics similar to MSC. MPC within the cartilage matrix, the target of tissue regeneration, may provide the basis for in situ regeneration of focal cartilage defects. However, there is only limited information concerning the presence/abundance of CD105⁺/CD166⁺ MPC in human articular cartilage. The present study therefore assessed the relative percentage and particularly the zonal distribution of cartilage MPC using the markers CD105/CD166. Methods: Specimens of human osteoarthritic (OA; n = 11) and normal (n = 3) cartilage were used for either cell isolation or immunohistochemistry. Due to low numbers, isolated cells were expanded for 2 weeks and then analyzed by flow cytometry (FACS) or immunofluorescence in chamber slides for the expression of CD105 and CD166. Following immunomagnetic separation of CD166⁺/^- OA cells, multi-lineage differentiation assays were performed. Also, the zonal distribution of CD166⁺ cells within the matrix of OA and normal cartilage was analyzed by immunohistochemistry. Results: FACS analysis showed that 16.7 ± 2.1% (mean ± SEM) of OA and 15.3 ± 2.3 of normal chondrocytes (n.s.) were CD105⁺/CD166⁺ and thus carried the established MPC marker combination. Similarly, 13.2% ± 0.9% and 11.7 ± 2.1 of CD105⁺/CD166⁺cells, respectively, were identified by immunofluorescence in adherent OA and normal chondrocytes. The CD166⁺ enriched OA cells showed a stronger induction of the chondrogenic phenotype in differentiation assays than the CD166⁺ depleted cell population, underlining the chondrogenic potential of the MPC. Strikingly, CD166⁺ cells in OA and normal articular cartilage sections (22.1 ± 1.7% and 23.6% ± 1.4%, respectively; n.s.) were almost exclusively located in the superficial and middle zone. Conclusions: The present results underline the suitability of CD166 as a biomarker to identify and, in particular, localize and/or enrich resident MPC with a high chondrogenic potential in human articular cartilage. The percentage of MPC in both OA and normal cartilage is substantially higher than previously reported, suggesting a yet unexplored reserve capacity for regeneration.