Dirk Pohlers

TGF-β and fibrosis in different organs — molecular pathway imprints

The action of transforming-growth-factor (TGF)-beta following inflammatory responses is characterized by increased production of extracellular matrix (ECM) components, as well as mesenchymal cell proliferation, migration, and accumulation. Thus, TGF-beta is important for the induction of fibrosis often associated with chronic phases of inflammatory diseases. This common feature of TGF-related pathologies is observed in many different organs. Therefore, in addition to the description of the common TGF-beta-pathway, this review focuses on TGF-beta-related pathogenetic effects in different pathologies/organs, i. e., arthritis, diabetic nephropathy, colitis/Crohns disease, radiation-induced fibrosis, and myocarditis (including their similarities and dissimilarities). However, TGF-beta exhibits both exacerbating and ameliorating features, depending on the phase of disease and the site of action. Due to its central role in severe fibrotic diseases, TGF-beta nevertheless remains an attractive therapeutic target, if targeted locally and during the fibrotic phase of disease.

Constitutive upregulation of the transforming growth factor-β pathway in rheumatoid arthritis synovial fibroblasts

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.

Identification of intra-group, inter-individual, and gene-specific variances in mRNA expression profiles in the rheumatoid arthritis synovial membrane.

IntroductionRheumatoid 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).MethodAnalysis 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 the Kyoto Encyclopedia of Genes and Genomes, the pathways/complexes significantly affected by higher gene expression variances were identified in each group.ResultsTen 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.ConclusionIn 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.

Liposomal encapsulation enhances and prolongs the anti-inflammatory effects of water-soluble dexamethasone phosphate in experimental adjuvant arthritis

IntroductionThe objective of this study was to evaluate the efficacy of intravenous (i.v.) injection of liposomally encapsulated dexamethasone phosphate (DxM-P) in comparison to free DxM-P in rats with established adjuvant arthritis (AA). This study focused on polyethylene glycol (PEG)-free liposomes, to minimize known allergic reactions caused by neutral PEG-modified (PEG-ylated) liposomes.MethodsEfficacy was assessed clinically and histologically using standard scores. Non-specific and specific immune parameters were monitored. Activation of peritoneal macrophages was analyzed via cytokine profiling. Pharmacokinetics/biodistribution of DxM in plasma, synovial membrane, spleen and liver were assessed via mass spectrometry.ResultsLiposomal DxM-P (3 × 1 mg/kg body weight; administered intravenously (i.v.) on Days 14, 15 and 16 of AA) suppressed established AA, including histological signs, erythrocyte sedimentation rate, white blood cell count, circulating anti-mycobacterial IgG, and production of interleukin-1beta (IL-1β) and IL-6 by peritoneal macrophages. The suppression was strong and long-lasting. The clinical effects of liposomal DxM-P were dose-dependent for dosages between 0.01 and 1.0 mg/kg. Single administration of 1 mg/kg liposomal DxM-P and 3 × 1 mg/kg of free DxM-P showed comparable effects consisting of a partial and transient suppression. Moreover, the effects of medium-dose liposomal DxM-P (3 × 0.1 mg/kg) were equal (in the short term) or superior (in the long term) to those of high-dose free DxM-P (3 × 1 mg/kg), suggesting a potential dose reduction by a factor between 3 and 10 by liposomal encapsulation. For at least 48 hours after the last injection, the liposomal drug achieved significantly higher levels in plasma, synovial membrane, spleen and liver than the free drug.ConclusionsThis new PEG-free formulation of macrophage-targeting liposomal DxM-P considerably reduces the dose and/or frequency required to treat AA, with a potential to enhance or prolong therapeutic efficacy and limit side-effects also in the therapy of rheumatoid arthritis. Depot and/or recirculation effects in plasma, inflamed joint, liver, and spleen may contribute to this superiority of liposomally encapsulated DxM-P.

In vitro model for the analysis of synovial fibroblast-mediated degradation of intact cartilage.

IntroductionActivated synovial fibroblasts are thought to play a major role in the destruction of cartilage in chronic, inflammatory rheumatoid arthritis (RA). However, profound insight into the pathogenic mechanisms and the impact of synovial fibroblasts in the initial early stages of cartilage destruction is limited. Hence, the present study sought to establish a standardised in vitro model for early cartilage destruction with native, intact cartilage in order to analyse the matrix-degrading capacity of synovial fibroblasts and their influence on cartilage metabolism.MethodsA standardised model was established by co-culturing bovine cartilage discs with early-passage human synovial fibroblasts for 14 days under continuous stimulation with TNF-α, IL-1β or a combination of TNF-α/IL-1β. To assess cartilage destruction, the co-cultures were analysed by histology, immunohistochemistry, electron microscopy and laser scanning microscopy. In addition, content and/or neosynthesis of the matrix molecules cartilage oligomeric matrix protein (COMP) and collagen II was quantified. Finally, gene and protein expression of matrix-degrading enzymes and pro-inflammatory cytokines were profiled in both synovial fibroblasts and cartilage.ResultsHistological and immunohistological analyses revealed that non-stimulated synovial fibroblasts are capable of demasking/degrading cartilage matrix components (proteoglycans, COMP, collagen) and stimulated synovial fibroblasts clearly augment chondrocyte-mediated, cytokine-induced cartilage destruction. Cytokine stimulation led to an upregulation of tissue-degrading enzymes (aggrecanases I/II, matrix-metalloproteinase (MMP) 1, MMP-3) and pro-inflammatory cytokines (IL-6 and IL-8) in both cartilage and synovial fibroblasts. In general, the activity of tissue-degrading enzymes was consistently higher in co-cultures with synovial fibroblasts than in cartilage monocultures. In addition, stimulated synovial fibroblasts suppressed the synthesis of collagen type II mRNA in cartilage.ConclusionsThe results demonstrate for the first time the capacity of synovial fibroblasts to degrade intact cartilage matrix by disturbing the homeostasis of cartilage via the production of catabolic enzymes/pro-inflammatory cytokines and suppression of anabolic matrix synthesis (i.e., collagen type II). This new in vitro model may closely reflect the complex process of early stage in vivo destruction in RA and help to elucidate the role of synovial fibroblasts and other synovial cells in this process, and the molecular mechanisms involved in cartilage degradation.

Zwitterionic poly(2-oxazoline)s as promising candidates for blood contacting applications

We report the synthesis of highly hemo- and cytocompatible zwitterionic 2-oxazoline-based poly(sulfobetaine)s and poly(carboxybetaine)s, which demonstrate beneficial anticoagulant activity. The polymers were obtained by thiol–ene photoaddition of a tertiary amine-containing thiol onto an alkene-containing precursor copoly(2-oxazoline), followed by betainization with 1,3-propansultone and β-propiolactone. The polymers and their intermediates were characterized by means of 1H NMR spectroscopy and size exclusion chromatography. The influence of the zwitterionic polymers on the aggregation and hemolysis of erythrocytes, the whole blood viscosity, the platelet and complement activation as well as the blood coagulation has been studied in detail. In addition, the cytotoxicity of the materials has been evaluated. It was found that the zwitterionic POx show no negative interactions with blood. Moreover, anticoagulant activity via the intrinsic and/or the common coagulation pathway was observed. The high hemocompatibility and the low cytotoxicity as well as the beneficial anticoagulant activity of the presented zwitterionic poly(2-oxazoline)s demonstrate their potential for the use in biomedical applications.

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

IntroductionDiscrimination 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.MethodsThree 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.ResultsThe 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.ConclusionFirst-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.

Expression of cytokine mRNA and protein in joints and lymphoid organs during the course of rat antigen-induced arthritis

Cytokine expression was assessed during antigen-induced arthritis (AIA) in synovial membrane (SM), inguinal lymph node (LN), and spleen using competitive RT-PCR and sandwich ELISA. In the SM, early elevations of IL-1β and IL-6 mRNA (by 6 hours; 450- and 200-fold, respectively) correlated with the joint swelling; a 6-fold increase in tumor necrosis factor α (TNFα) was not significant. Not only IL-2 and IFN-γ (which increased 10,000-fold and 200-fold, respectively), but also IL-5 and IL-10, increased acutely (6 hours – day 1; 3-fold and 35-fold, respectively) in the SM. In general, the protein levels in the SM for IL-1β, IL-6, TNFα, IFN-γ, IL-4, and IL-10 (increase from 4-fold to 15-fold) matched the course of mRNA expression. In the inguinal LN, there were early mRNA elevations of IL-6 (a 2.5-fold increase by 6 hours, which correlated positively with the joint swelling) and IL-2 (4-fold by 6 hours), as well as later rises of IL-4 and IL-5 (2.5- and 4-fold, respectively, by day 3). No significant elevations of the corresponding proteins in this tissue were observed, except for IL-1β (by day 6) and IL-10 (by day 1). In the spleen, there were significant mRNA elevations at 6 hours of IL-1β (1.5-fold), IL-6 (4-fold; positively correlated with the joint swelling), IFN-γ (3-fold), and IL-2 (7- to 10-fold). IL-5 and IL-10 (2- and 3-fold, respectively) peaked from 6 hours to day 3 in the spleen. Increases of the corresponding proteins were significant in comparison with day 0 only in the case of IL-2 (day 6). By day 6 (transition to the chronic phase), the mRNA for cytokines declined to or below prearthritis levels in all the tissues studied except for IL-1β in the SM and IL-6 in the spleen. AIA is thus characterized by four phenomena: early synovial activation of macrophages, T helper (Th)1-like, and Th2-like cells; late, well-segregated Th2-like responses in the inguinal LN; late, overlapping Th1-like/Th2-like peaks in the spleen; and chronic elevation of synovial IL-1β mRNA and spleen IL-6 mRNA.

Batch correction of microarray data substantially improves the identification of genes differentially expressed in Rheumatoid Arthritis and Osteoarthritis

BackgroundBatch effects due to sample preparation or array variation (type, charge, and/or platform) may influence the results of microarray experiments and thus mask and/or confound true biological differences. Of the published approaches for batch correction, the algorithm “Combating Batch Effects When Combining Batches of Gene Expression Microarray Data” (ComBat) appears to be most suitable for small sample sizes and multiple batches.MethodsSynovial fibroblasts (SFB; purity > 98%) were obtained from rheumatoid arthritis (RA) and osteoarthritis (OA) patients (n = 6 each) and stimulated with TNF-α or TGF-β1 for 0, 1, 2, 4, or 12 hours. Gene expression was analyzed using Affymetrix Human Genome U133 Plus 2.0 chips, an alternative chip definition file, and normalization by Robust Multi-Array Analysis (RMA). Data were batch-corrected for different acquiry dates using ComBat and the efficacy of the correction was validated using hierarchical clustering.ResultsIn contrast to the hierarchical clustering dendrogram before batch correction, in which RA and OA patients clustered randomly, batch correction led to a clear separation of RA and OA. Strikingly, this applied not only to the 0 hour time point (i.e., before stimulation with TNF-α/TGF-β1), but also to all time points following stimulation except for the late 12 hour time point. Batch-corrected data then allowed the identification of differentially expressed genes discriminating between RA and OA. Batch correction only marginally modified the original data, as demonstrated by preservation of the main Gene Ontology (GO) categories of interest, and by minimally changed mean expression levels (maximal change 4.087%) or variances for all genes of interest. Eight genes from the GO category “extracellular matrix structural constituent” (5 different collagens, biglycan, and tubulointerstitial nephritis antigen-like 1) were differentially expressed between RA and OA (RA > OA), both constitutively at time point 0, and at all time points following stimulation with either TNF-α or TGF-β1.ConclusionBatch correction appears to be an extremely valuable tool to eliminate non-biological batch effects, and allows the identification of genes discriminating between different joint diseases. RA-SFB show an upregulated expression of extracellular matrix components, both constitutively following isolation from the synovial membrane and upon stimulation with disease-relevant cytokines or growth factors, suggesting an “imprinted” alteration of their phenotype.

Adapted Boolean network models for extracellular matrix formation

BackgroundDue to the rapid data accumulation on pathogenesis and progression of chronic inflammation, there is an increasing demand for approaches to analyse the underlying regulatory networks. For example, rheumatoid arthritis (RA) is a chronic inflammatory disease, characterised by joint destruction and perpetuated by activated synovial fibroblasts (SFB). These abnormally express and/or secrete pro-inflammatory cytokines, collagens causing joint fibrosis, or tissue-degrading enzymes resulting in destruction of the extra-cellular matrix (ECM).We applied three methods to analyse ECM regulation: data discretisation to filter out noise and to reduce complexity, Boolean network construction to implement logic relationships, and formal concept analysis (FCA) for the formation of minimal, but complete rule sets from the data.ResultsFirst, we extracted literature information to develop an interaction network containing 18 genes representing ECM formation and destruction. Subsequently, we constructed an asynchronous Boolean network with biologically plausible time intervals for mRNA and protein production, secretion, and inactivation. Experimental gene expression data was obtained from SFB stimulated by TGFβ1 or by TNFα and discretised thereafter. The Boolean functions of the initial network were improved iteratively by the comparison of the simulation runs to the experimental data and by exploitation of expert knowledge. This resulted in adapted networks for both cytokine stimulation conditions.The simulations were further analysed by the attribute exploration algorithm of FCA, integrating the observed time series in a fine-tuned and automated manner. The resulting temporal rules yielded new contributions to controversially discussed aspects of fibroblast biology (e.g., considerable expression of TNF and MMP9 by fibroblasts stimulation) and corroborated previously known facts (e.g., co-expression of collagens and MMPs after TNFα stimulation), but also revealed some discrepancies to literature knowledge (e.g., MMP1 expression in the absence of FOS).ConclusionThe newly developed method successfully and iteratively integrated expert knowledge at different steps, resulting in a promising solution for the in-depth understanding of regulatory pathways in disease dynamics. The knowledge base containing all the temporal rules may be queried to predict the functional consequences of observed or hypothetical gene expression disturbances. Furthermore, new hypotheses about gene relations were derived which await further experimental validation.