Novel application of multi-stimuli network inference to synovial fibroblasts of rheumatoid arthritis patients

BACKGROUND: Network inference of gene expression data is an important challenge in systems biology. Novel algorithms may provide more detailed gene regulatory networks (GRN) for complex, chronic inflammatory diseases such as rheumatoid arthritis (RA), in which activated synovial fibroblasts (SFBs) play a major role. Since the detailed mechanisms underlying this activation are still unclear, simultaneous investigation of multi-stimuli activation of SFBs offers the possibility to elucidate the regulatory effects of multiple mediators and to gain new insights into disease pathogenesis. METHODS: A GRN was therefore inferred from RA-SFBs treated with 4 different stimuli (IL-1 β, TNF- α, TGF- β, and PDGF-D). Data from time series microarray experiments (0, 1, 2, 4, 12 h; Affymetrix HG-U133 Plus 2.0) were batch-corrected applying ‘ComBat’, analyzed for differentially expressed genes over time with ‘Limma’, and used for the inference of a robust GRN with NetGenerator V2.0, a heuristic ordinary differential equation-based method with soft integration of prior knowledge. RESULTS: Using all genes differentially expressed over time in RA-SFBs for any stimulus, and selecting the genes belonging to the most significant gene ontology (GO) term, i.e., ‘cartilage development’, a dynamic, robust, moderately complex multi-stimuli GRN was generated with 24 genes and 57 edges in total, 31 of which were gene-to-gene edges. Prior literature-based knowledge derived from Pathway Studio or manual searches was reflected in the final network by 25/57 confirmed edges (44%). The model contained known network motifs crucial for dynamic cellular behavior, e.g., cross-talk among pathways, positive feed-back loops, and positive feed-forward motifs (including suppression of the transcriptional repressor OSR2 by all 4 stimuli. CONCLUSION: A multi-stimuli GRN highly concordant with literature data was successfully generated by network inference from the gene expression of stimulated RA-SFBs. The GRN showed high reliability, since 10 predicted edges were independently validated by literature findings post network inference. The selected GO term ‘cartilage development’ contained a number of differentiation markers, growth factors, and transcription factors with potential relevance for RA. Finally, the model provided new insight into the response of RA-SFBs to multiple stimuli implicated in the pathogenesis of RA, in particular to the ‘novel’ potent growth factor PDGF-D

Effects of rheumatoid arthritis associated transcriptional changes on osteoclast differentiation network in the synovium

Background Osteoclast differentiation in the inflamed synovium of rheumatoid arthritis (RA) affected joints leads to the formation of bone lesions. Reconstruction and analysis of protein interaction networks underlying specific disease phenotypes are essential for designing therapeutic interventions. In this study, we have created a network that captures signal flow leading to osteoclast differentiation. Based on transcriptome analysis, we have indicated the potential mechanisms responsible for the phenotype in the RA affected synovium. Method We collected information on gene expression, pathways and protein interactions related to RA from literature and databases namely Gene Expression Omnibus, Kyoto Encyclopedia of Genes and Genomes pathway and STRING. Based on these information, we created a network for the differentiation of osteoclasts. We identified the differentially regulated network genes and reported the signaling that are responsible for the process in the RA affected synovium. Result Our network reveals the mechanisms underlying the activation of the neutrophil cytosolic factor complex in connection to osteoclastogenesis in RA. Additionally, the study reports the predominance of the canonical pathway of NF-κB activation in the diseased synovium. The network also confirms that the upregulation of T cell receptor signaling and downregulation of transforming growth factor beta signaling pathway favor osteoclastogenesis in RA. To the best of our knowledge, this is the first comprehensive protein–protein interaction network describing RA driven osteoclastogenesis in the synovium. Discussion This study provides information that can be used to build models of the signal flow involved in the process of osteoclast differentiation. The models can further be used to design therapies to ameliorate bone destruction in the RA affected joints

ENDOCANNABINOID-BASED NANOPARTICLES TARGETED TO THE SYNOVIUM FOR THE TREATMENT OF ARTHRITIS

Chronic inflammatory joint disease represents an emerging public health issue, occupying a sizeable proportion of the adult population in the industrialized world. Recently, there has been a resurgence of interest in marijuana and its natural and synthetic derivatives, cannabinoid receptor agonists and antagonists, as well as chemically related compounds, for their therapeutic potential as both an anti-inflammatory and analgesic. Whilst the benefits of endocannabinoid-based treatments appear promising, very few studies have investigated the use of the self-assembled nanoparticles (NPs) for targeted drug delivery. In this study, the nanostructure mesophase behaviour of a series of mixed monoethanolamide lipids of oleoylethanolamide (OEA) and linoylethanolamide (LEA) into higher order NP structures for the encapsulation and delivery of drugs was investigated. In addition to drug encapsulation, active targeting through the conjugation of a synovium-targeting peptide, HAP-1, to the surface of these NP’s was used to facilitate selective accumulation of therapeutic agents the inflamed joint. The inhibitory cytokine effects of these targeted NPs was demonstrated in vitro, and in vivo using an adjuvant induced arthritis model of inflammation. The ability to deliver endocannabinoid based NPs to specific sites of the body mediating pharmacological endocannabinoid-like effects to influence key physiological pathways, provides a novel drug delivery system and medicinal potential to treat many diseases in many fields of medicine in which inflammation is a key feature of the disease

Differential effects of anti-TNF therapies for inflammatory arthritides on immune responses to Mycobacterium tuberculosis

Tumour necrosis factor (TNF) antagonists have revolutionised the management of rheumatoid arthritis (RA) and other inflammatory diseases. This success is partly tempered by substantially increased risk of granulomatous infectious diseases, particularly tuberculosis (TB). In this thesis I sought new insights into the mechanisms by which TNF blockade leads to an increased incidence of TB. In a new analysis of data collected by the British Society of Rheumatology Biologics Registry, I confirmed that anti-TNF therapy leads to reactivation of latent TB infection, rather than increasing the risk of new TB infection, consistent with published literature. I derived and validated four separate context-specific transcriptional modules representing TNF inducible gene expression in macrophages, keratinocytes and whole blood. I used these modules to quantify TNF bioactivity in clinical samples from RA patients responding to anti TNF therapies or treated with methotrexate only. As expected, anti-TNF therapy was associated with attenuated expression of the TNF modules in whole blood following ex vivo stimulation. However, anti-TNF therapy had no effect on TNF module expression and therefore TNF function, at the site of acute cell mediated immune responses in vivo, modelled by the tuberculin skin test. These data are consistent with a model in which anti-TNF therapies do not reach sufficient concentration within tissues to block TNF responses in an acute inflammatory challenge. Rather, my data suggest that anti TNF therapies mediate their therapeutic and adverse effects by regulating TNF activity at foci of chronic inflammation or by alternative non-canonical pathways. Finally I tested the hypothesis that anti-TNF therapy may inhibit cellular restriction of mycobacteria in human macrophage cultures. Using an in vitro model of human monocyte-derived macrophages, I established a new method to quantify fluorescent mycobacterial load both inside and outside cells, and showed that TNF blockade in this model did not have a significant impact on mycobacterial growth

Characterisation of dendritic cell subsets in inflammatory arthritis

The first part of this thesis examined by comparative analysis the phenotype, tissue distribution and functional profile of the human DC subsets, myeloid (m) DC and plasmacytoid (DC), in RA and PsA. This study demonstrated that circulating pDC and mDC are reduced in the peripheral blood (PB) of RA and PsA patients, but are accumulated to the inflammatory synovial fluid (SF) and synovial membrane (SM), commensurate with altered migration. Furthermore, it was demonstrated that the majority of pDC and mDC within the synovial compartment displayed a predominantly immature phenotype as identified by the low to absent expression of specific co-stimulation and maturation markers including CD80, CD83, CD86 and dendritic cell lysosome-associated membrane protein (DC-LAMP). However, pDC and mDC purified from SF underwent ex vivo phenotypic maturation and released cytokines to TLR stimulation at comparable levels to their normal PB purified counterparts. Commensurate with that observation, cytokine profiling of SM localized pDC and mDC revealed expression of the pro-inflammatory cytokines IL-12p70, IL-23p19, IL-15, IL-18 and IFN-α/β. Together these data indicated no apparent intrinsic cellular defect, suggesting that extrinsic factors in the local synovial environment may be culpable for inhibition of DC maturation. In addition mDC in SM expressed predominantly IL-12p70 and IL-23p19, suggesting a central role in the regulation and expansion of T cells, in particular Th17, which have been ascribed a pathologic role in arthritis. In contrast, pDC expressed predominantly IL-15 and IL-18, cytokines that can enhance IL-12 induced IFN-γ release and inhibit T cell apoptosis, thus indicating a role in the amplification and prolongation of inflammatory arthritis. Of particular interest it was demonstrated that pDC also expressed IFN-α/β in abundance. As pDC constituted the dominant DC subset in the SM in both RA and PsA, this may have pathological implications as IFN-α has been critically linked to pathology in other autoimmune diseases, including systemic lupus erythematosus (SLE) and, of particular import to PsA, psoriasis. In conclusion, these studies indicate that mDC and pDC possess multi-faceted roles in inflammatory arthritis, involved in both the initiation and perpetuation of arthritis, but also the potential suppression thereof. The data provide a firm basis upon which to build rational tolerance induction regimes in due course as the appropriate biological targeting agents become available in the clinical environment

Rheumatoid Arthritis Therapy Reappraisal

Rheumatoid Arthritis (RA) is a chronic inflammatory disease leading to joint inflammation and destruction. Treatment of RA includes the use of conventional (cs), biologic (b) disease-modifying anti-rheumatic drugs (DMARDs), and oral or intraarticular (IA) glucocorticoids (GCs). All different classes of drugs have shown to halt disease progression in clinical studies. In real life, a physician has more options than just adding or switching to a new ts/bDMARD if any kind of DMARDs has failed. They can modify or optimize the therapy with concomitant csDMARDs, and oral or IA-GC can be added to the treatment regimen. The EULAR states that therapeutic adjustment including the "optimization of csDMARDs dose or route of administration or intra-articular injections of GCs" is recommended. Thus, a new therapeutic agent can be embedded in a whole strategy with parallel optimization of the csDMARD and GC treatment. The idea of treating to target (T2T) for the treatment of RA patients has been around since the late 1990s. Many clinical studies (Ticora, BsSt, Camera) have demonstrated the superiority of a T2T approach. When I talk to physicians, I understand that most of them only rarely inject joints with GC. Therefore, I would like to create an issue on the T2T approach in reality including primary data, reviews, and real-life data demonstrating the general opinion and execution of T2T in treating RA

How to Predict Molecular Interactions between Species?

Organisms constantly interact with other species through physical contact which leads to chan-ges on the molecular level, for example the transcriptome. These changes can be monitored forall genes, with the help of high-throughput experiments such as RNA-seq or microarrays. Theadaptation of the gene expression to environmental changes within cells is mediated throughcomplex gene regulatory networks. Often, our knowledge of these networks is incomplete. Netw-ork inference predicts gene regulatory interactions based on transcriptome data. An emergingapplication of high-throughput transcriptome studies are dual transcriptomics experiments. Here,the transcriptome of two or more interacting species is measured simultaneously. Based ona dual RNA-seq data set of murine dendritic cells infected with the fungal pathogen Candidaalbicans, the software tool NetGenerator was applied to predict an inter-species gene regulatorynetwork. To promote further investigations of molecular inter-species interactions, we recentlydiscussed dual RNA-seq experiments for host-pathogen interactions and extended the appliedtool NetGenerator (Schulze et al., 2015). The updated version of NetGenerator makes use ofmeasurement variances in the algorithmic procedure and accepts gene expression time seriesdata with missing values. Additionally, we tested multiple modeling scenarios regarding the stimulifunctions of the gene regulatory network. Here, we summarize the work by Schulze et al. (2015)and put it into a broader context. We review various studies making use of the dual transcriptomicsapproach to investigate the molecular basis of interacting species. Besides the application tohost-pathogen interactions, dual transcriptomics data are also utilized to study mutualistic andcommensalistic interactions. Furthermore, we give a short introduction into additional approachesfor the prediction of gene regulatory networks and discuss their application to dual transcriptomicsdata. We conclude that the application of network inference on dual-transcriptomics data is apromising approach to predict molecular inter-species interactions

Anti-citrulline immunity in rheumatoid arthritis : characterization of peptide-HLA interactions and CD4+ T cell responses

Rheumatoid Arthritis (RA) is a complex, systemic autoimmune disorder characterized by chronic inflammation in small joints in hands and feet. It is a common disease that if untreated leads to joint destruction, disability, comorbidities and a reduced lifespan. Both genetic and environmental factors contribute to disease pathogenesis that in the majority of patients is characterized by the occurrence of antibodies against citrullinated proteins (ACPA). The strong genetic association with certain MHC class II alleles led to autoreactive T cells being assigned a major role in the course of disease. Today, citrulline-specific CD4+ T cells are regarded the perfect target for antigen-specific immunotherapy and have so far been investigated in a handful of studies. The focus of this thesis was therefore to expand our knowledge of citrulline-reactive T cells with a specific emphasis on their phenotype as well as the interaction with their cognate peptide-HLA complexes on antigen-presenting cells. We have examined functional T cell responses to native and citrullinated epitopes derived from the candidate antigen α-enolase and compared their relevance in peripheral blood of patients with different RA-associated HLA-DR alleles. While HLA-DRB1*04:01 and *04:04 presented a similar set of peptides, a clear bias in functional responses towards citrullinated epitopes was observed in HLA-DRB1*04:01 patients. When analysing crystal structures of both native and citrullinated versions of two α-enolase epitopes in complex with HLADRB1* 04:01, we found the citrulline residues at peptide positions p-1 and p2, respectively. In both cases the citrulline was not involved in binding to the HLA molecule but instead pointed upwards readily available for interaction with the TCR. Particular recognition of these citrullinated epitopes by the T cells is thus based on the creation of neoantigens. Using HLA class II tetramer technology, we even detected cross-reactive T cells in some patients recognizing both native and citrullinated version of the epitope with citrulline at position p-1 implicating the existence of TCRs with different docking patterns towards these pHLA complexes. When comparing frequencies of T cells reactive to either of the two versions, we found memory T cells specific for the citrullinated version enriched in the synovial fluid compared to peripheral blood. Additionally, by successfully combining HLA class II tetramer sorting with single cell RNAsequencing, we could compare the transcriptional profile of citrulline- versus virus-specific CD4+ T cells in peripheral blood and synovial fluid of RA patients. Here, we repeatedly found genes associated with cytolytic and cytotoxic features upregulated in the citrulline-specific T cells both in blood and synovial fluid. Furthermore, we developed a multi-tetramer staining panel that allows the simultaneous assessment of multiple specificities making it applicable for longitudinal monitoring of T cells in clinical samples. Using this tool to examine the frequency and phenotype of T cells specific for eight citrullinated peptides from four RA candidate antigens, we could show that the frequencies of citrulline-specific CD4+ T cells in early RA patients decline upon disease improvement. In summary, our data demonstrate that autoreactive citrulline-specific T cells are present in RA patients both early and late in the disease course and that the breach of tolerance includes several non-related autoantigens