Transforming growth factor β1 and laminin-111 cooperate in the induction of interleukin-16 expression in synovial fibroblasts from patients with rheumatoid arthritis

Integrated Analysis of Transcriptome Changes in Osteoarthritis: Gene Expression, Pathways and Alternative Splicing

OBJECTIVE

Osteoarthritis (OA) is the most prevalent joint disease characterized by the degeneration of articular cartilage and the remodeling of its underlying bones, resulting in pain and loss of function in the knees and hips. As far as we know, no curative treatments are available except for the joint replacement. The precise molecular mechanisms which are involved in the degradation of cartilage matrix and development of osteoarthritis are still unclear.

DESIGN

By analyzing RNA-seq data, we found the molecular changes at the transcriptome level such as alternative splicing, gene expression, and molecular pathways in OA knees cartilage.

RESULTS

Expression analysis have identified 457 differential expressed genes including 266 up-regulated genes such as TNFSF15, ST6GALNAC5, TGFBI, ASPM, and TYM, and 191 down-regulated genes such as ADM, JUN, IRE2, PIGA, and MAFF. Gene set enrichment analysis (GSEA) analysis identified down-regulated pathways related to translation, transcription, immunity, PI3K/AKT, and circadian as well as disturbed pathways related to extracellular matrix and collagen. Splicing analysis identified 442 differential alternative splicing events within 284 genes in osteoarthritis, including genes involved in extracellular matrix (ECM) and alternative splicing, and TIA1 was identified as a key regulator of these splicing events.

CONCLUSIONS

These findings provide insights into disease etiology, and offer favorable information to support the development of more effective interventions in response to the global clinical challenge of osteoarthritis.

Urine Proteomics and Renal Single Cell Transcriptomics Implicate IL-16 in Lupus Nephritis

OBJECTIVES

Current treatments are effective only in 30% of lupus nephritis patients emphasizing the need for novel therapeutic strategies. To develop mechanistic hypotheses and explore novel biomarkers, we analyzed the longitudinal urinary proteomic profiles in patients with lupus nephritis undergoing treatment.

METHODS

We quantified 1,000 urinary proteins in 30 patients with lupus nephritis at the time of the diagnostic renal biopsy and after 3, 6, and 12 months. The proteins and molecular pathways detected in the urine proteome were then analyzed with respect to baseline clinical features and longitudinal trajectories. The intrarenal expression of candidate biomarkers was evaluated using single cell transcriptomics of renal biopsies from lupus nephritis patients.

RESULTS

Our analysis revealed multiple biological pathways including chemotaxis, neutrophil activation, platelet degranulation, and extracellular matrix organization that could be noninvasively quantified and monitored in the urine. We identified 237 urinary biomarkers associated with lupus nephritis as compared to controls without SLE. IL-16, CD163, and TGF-β mirrored intrarenal nephritis activity. Response to treatment was paralleled by a reduction of urinary IL-16, a CD4 ligand with proinflammatory and chemotactic properties. Single cell RNA sequencing independently demonstrated that IL16 is the second most expressed cytokine by most infiltrating immune cells in lupus nephritis kidneys. IL-16 producing cells were found at key sites of kidney injury.

CONCLUSION

Urine proteomics may profoundly change the diagnosis and management of lupus nephritis by noninvasively monitor active intrarenal biological pathways. These findings implicate IL-16 in lupus nephritis pathogenesis designating it as a potentially treatable target and biomarker.

A cytokine protein-protein interaction network for identifying key molecules in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory disease of the synovial joints. Though the current RA therapeutics such as disease-modifying antirheumatic drugs (DMARDs), nonsteroidal anti-inflammatory drugs (NSAIDs) and biologics can halt the progression of the disease, none of these would either dramatically reduce or cure RA. So, the identification of potential therapeutic targets and new therapies for RA are active areas of research. Several studies have discovered the involvement of cytokines in the pathogenesis of this disease. These cytokines induce signal transduction pathways in RA synovial fibroblasts (RASF). These pathways share many signal transducers and their interacting proteins, resulting in the formation of a signaling network. In order to understand the involvement of this network in RA pathogenesis, it is essential to identify the key transducers and their interacting proteins that are part of this network. In this study, based on a detailed literature survey, we have identified a list of 12 cytokines that induce signal transduction pathways in RASF. For these cytokines, we have built a signaling network using the protein-protein interaction (PPI) data that was obtained from public repositories such as HPRD, BioGRID, MINT, IntAct and STRING. By combining the network centrality measures with the gene expression data from the RA related microarrays that are available in the open source Gene Expression Omnibus (GEO) database, we have identified 24 key proteins of this signaling network. Two of these 24 are already drug targets for RA, and of the remaining, 12 have direct PPI links to some of the current drug targets of RA. Therefore, these key proteins seem to be crucial in the pathogenesis of RA and hence might be treated as potential drug targets.

Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine-learning algorithm

Many breast cancer (BC) patients treated with aromatase inhibitors (AIs) develop aromatase inhibitor‐related arthralgia (AIA). Candidate gene studies to identify AIA risk are limited in scope. We evaluated the potential of a novel analytic algorithm (NAA) to predict AIA using germline single nucleotide polymorphisms (SNP) data obtained before treatment initiation. Systematic chart review of 700 AI‐treated patients with stage I‐III BC identified asymptomatic patients (n = 39) and those with clinically significant AIA resulting in AI termination or therapy switch (n = 123). Germline DNA was obtained and SNP genotyping performed using the Affymetrix UK BioBank Axiom Array to yield 695,277 SNPs. SNP clusters that most closely defined AIA risk were discovered using an NAA that sequentially combined statistical filtering and a machine‐learning algorithm. NCBI PhenGenI and Ensemble databases defined gene attribution of the most discriminating SNPs. Phenotype, pathway, and ontologic analyses assessed functional and mechanistic validity. Demographics were similar in cases and controls. A cluster of 70 SNPs, correlating to 57 genes, was identified. This SNP group predicted AIA occurrence with a maximum accuracy of 75.93%. Strong associations with arthralgia, breast cancer, and estrogen phenotypes were seen in 19/57 genes (33%) and were functionally consistent. Using a NAA, we identified a 70 SNP cluster that predicted AIA risk with fair accuracy. Phenotype, functional, and pathway analysis of attributed genes was consistent with clinical phenotypes. This study is the first to link a specific SNP/gene cluster to AIA risk independent of candidate gene bias.

Major involvement of bacterial components in rheumatoid arthritis and its accompanying oxidative stress, systemic inflammation and hypercoagulability

We review the evidence that infectious agents, including those that become dormant within the host, have a major role to play in much of the etiology of rheumatoid arthritis and the inflammation that is its hallmark. This occurs in particular because they can produce cross-reactive (auto-)antigens, as well as potent inflammagens such as lipopolysaccharide that can themselves catalyze further inflammagenesis, including via β-amyloid formation. A series of observables coexist in many chronic, inflammatory diseases as well as rheumatoid arthritis. They include iron dysregulation, hypercoagulability, anomalous morphologies of host erythrocytes, and microparticle formation. Iron dysregulation may be responsible for the periodic regrowth and resuscitation of the dormant bacteria, with concomitant inflammagen production. The present systems biology analysis benefits from the philosophical idea of "coherence," that reflects the principle that if a series of ostensibly unrelated findings are brought together into a self-consistent narrative, that narrative is thereby strengthened. As such, we provide a coherent and testable narrative for the major involvement of (often dormant) bacteria in rheumatoid arthritis.

Association of transforming growth factor-β1 T869C, G915C, and C509T gene polymorphisms with rheumatoid arthritis risk

The association of transforming growth factor-β1 (TGFβ1) is an important signaling pathway factor involving extracellular matrix regulation, and its gene polymorphisms with the risk of rheumatoid arthritis (RA) is currently still fiercely debated. Therefore, this meta-analysis was performed to determine if TGFβ1 T869C, G915C, and C509T gene polymorphisms correlate with the risk of developing RA. Association reports were identified from PubMed, Cochrane Library and CBM-disc (China Biological Medicine Database) on 1 May 2013, and eligible studies were recruited and synthesized to identifying patterns among study results. T869C TT genotype in the overall population was associated with increased RA risk (OR = 1.28, 95% CI: 1.02-1.60, p = 0.03). In the sub-group analysis, T869C TT genotype was shown to be a risk factor for RA, and T869C C allele or CC genotype a protective factor against RA disease in Asians, but these associations were not found in Caucasians. Furthermore, TGFβ1 C509T TT genotype was distinctly associated with RA susceptibility, but the T allele and CC genotype were not. TGFβ1 G915C gene polymorphism was not associated with RA susceptibility. In conclusion, the TT genotype of TGFβ1 T869C was associated with RA risk in the overall population and Asians. Furthermore, CC genotype or C allele was determined to be protective factors with respect to the RA risk in the overall population and Asians. Nonetheless, additional studies are required to firmly establish a correlation between the aforementioned polymorphisms and RA risk.

A candidate gene analysis of canine hypoadrenocorticism in 3 dog breeds

Canine hypoadrenocorticism is believed to be an immune-related condition. It is rare in the overall dog population but shows a breed-related predisposition with Standard poodles and Portuguese water dogs having a greater prevalence of the condition. It shares many similarities with human primary adrenal insufficiency and is believed to be a naturally occurring, spontaneous model for the human condition. Short haplotype blocks and low levels of linkage disequilibrium in the human genome mean that the identification of genetic contributors to the condition requires large sample numbers. Pedigree dogs have high linkage disequilibrium and long haplotypes within a breed, increasing the potential of identifying novel genes that contribute to canine genetic disease. We investigated 222 SNPs from 42 genes that have been associated or may be implicated in human Addison's disease. We conducted case-control analyses in 3 pedigree dog breeds (Labrador retriever: affected n = 30, unaffected = 76; Cocker Spaniel: affected n = 19, unaffected = 53; Springer spaniel: affected n = 26, unaffected = 46) and identified 8 associated alleles in genes COL4A4, OSBPL9, CTLA4, PTPN22, and STXBP5 in 3 pedigree breeds. Association with immune response genes PTPN22 and CTLA4 in certain breeds suggests an underlying immunopathogenesis of the disease. These results suggest that canine hypoadrenocorticism could be a useful model for studying comparative genetics relevant to human Addison's disease.

Markers of inflammation and bone remodelling associated with improvement in clinical response measures in psoriatic arthritis patients treated with golimumab

Objective

To determine serum biomarker associations with clinical response to golimumab treatment in patients with psoriatic arthritis (PsA).

Methods

GO–REVEAL was a randomised, placebo-controlled study of golimumab in patients with active PsA. Samples were collected from 100 patients at baseline, week 4 and week 14, and analysed for serum-based biomarkers and protein profiling (total 92 markers); data were correlated with clinical measures at week 14.

Results

Serum levels of a subset of proteins (apolipoprotein C III, ENRAGE, IL-16, myeloperoxidase, vascular endothelial growth factor, pyridinoline, matrix metalloproteinase 3, C-reactive protein (CRP), carcinoembryonic antigen, intercellular adhesion molecule 1 and macrophage inflammatory protein 1α) at baseline or week 4 were strongly associated with American College of Rheumatology 20% improvement (ACR20) response and/or disease activity score in 28 joints (DAS28) at week 14. A smaller subset of proteins was significantly associated with a 75% improvement in the psoriasis area and severity index score (PASI75) at week 14, (adiponectin, apolipoprotein CIII, serum glutamic oxaloacetic transaminase, and tumour necrosis factor α). Subsets of proteins were identified as potentially predictive of clinical response for each of the clinical measures, and the power of these biomarker panels to predict clinical response to golimumab treatment was stronger than for CRP alone.

Conclusions

This analysis provides insight into several panels of markers that may have utility in identifying PsA patients likely to have ACR20, DAS28, or PASI75 responses following golimumab treatment.

Association of serum markers with improvement in clinical response measures after treatment with golimumab in patients with active rheumatoid arthritis despite receiving methotrexate: results from the GO-FORWARD study

Introduction

The goal of this study was to identify serum markers that are modulated by treatment with golimumab with or without methotrexate (MTX) and are associated with clinical response.

Methods

Sera were collected at weeks 0 and 4 from a total of 336 patients (training dataset, n = 100; test dataset, n = 236) from the GO-FORWARD study of patients with active rheumatoid arthritis despite MTX. Patients were randomly assigned to receive placebo plus MTX; golimumab, 100 mg plus placebo; golimumab, 50 mg plus MTX; or golimumab, 100 mg plus MTX. Subcutaneous injections were administered every 4 weeks. Samples were tested for select inflammatory, bone, and cartilage markers and for protein profiling using multianalyte profiles.

Results

Treatment with golimumab with or without MTX resulted in significant decreases in a variety of serum proteins at week 4 as compared with placebo plus MTX. The American College of Rheumatology (ACR) 20, ACR 50, and Disease Activity Score (DAS) 28 responders showed a distinct biomarker profile compared with nonresponding patients.

Conclusions

ACR 20 and ACR 50 responders among the golimumab/golimumab + MTX-treated patients had a distinct change from baseline to week 4 in serum protein profile as compared with nonresponders. Some of these changed markers were also associated with multiple clinical response measures and improvement in outcome measures in golimumab/golimumab + MTX-treated patients. Although the positive and negative predictive values of the panel of markers were modest, they were stronger than C-reactive protein alone in predicting clinical response to golimumab.

Trial registration

http://ClinicalTrials.gov identification number: NCT00264550.

Rheumatoid arthritis progression mediated by activated synovial fibroblasts

Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by synovial hyperplasia and progressive joint destruction. Rheumatoid arthritis synovial fibroblasts (RASFs) are leading cells in joint erosion and contribute actively to inflammation. RASFs show an activated phenotype that is independent of the inflammatory environment and requires the combination of several factors. Although new aspects regarding RASF activation via matrix degradation products, epigenetic modifications, inflammatory factors, Toll-like receptor (TLR) activation and others have recently been uncovered, the primary pathophysiological processes in early arthritis leading to permanent activation are mostly unknown. Here, we review new findings regarding RASF activation and their altered behavior that contribute to matrix destruction and inflammation as well as their potential to spread RA.

Laminin-111: a potential therapeutic agent for Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) still needs effective treatments, and myoblast transplantation (MT) is considered as an approach to repair damaged skeletal muscles. DMD is due to the complete loss of dystrophin from muscles. The lack of link between the contracting apparatus and the extracellular matrix leads to frequent damage to the sarcolemma triggering muscle fiber necrosis. Laminins are major proteins in the extracellular matrix. Laminin-111 is normally present in skeletal and cardiac muscles in mice and humans but only during embryonic development. In this study, we showed that intramuscular injection of laminin-111 increased muscle strength and resistance in mdx mice. We also used laminin-111 as a coadjuvant in MT, and we showed this protein decreased considerably the repetitive cycles of degeneration, inflammatory reaction, and regeneration. Moreover, MT is significantly improved. To explain the improvement, we confirmed with the same myoblast cell batch that laminin-111 improves proliferation and drastically increases migration in vitro. These results are extremely important because DMD could be treated only by the injection of a recombinant protein, a simple and safe therapy to prevent loss of muscle function. Moreover, the improvement in MT would be significant to treat the muscles of DMD patients who are already weak.

Green tea polyphenol epigallocatechin-3-gallate: inflammation and arthritis. [corrected]

A number of factors including inflammation and oxidative stress are believed to play a role in the development of chronic joint diseases. Green tea has become a popular drink and is consumed throughout the world. Extracts of green tea and polyphenols present therein have been shown to inhibit the inflammatory responses in vitro in different cell types and the development of arthritis in animal model studies. There is considerable evidence that (-)-epigallocatechin-3-gallate (EGCG), the predominant green tea polyphenol which mimic its effects, inhibits enzyme activities and signal transduction pathways that play important roles in inflammation and joint destruction in arthritis. After oral consumption EGCG become bioavailable and proteomic studies suggest that EGCG may directly interact with a large set of protein targets and alter the physiological response of the cells. Taken together these and other studies identify and support the use of EGCG as a possible chemopreventive agent with a potential to inhibit the development of arthritis. Here we review the biological effects of EGCG in an attempt to understand its pivotal molecular targets that directly affect the inflammation and joint destruction process for prevention and/or for the development of new therapeutics for arthritis in humans.