Prediction of Therapeutic Responses to Tocilizumab in Patients With Rheumatoid Arthritis: Biomarkers Identified by Analysis of Gene Expression in Peripheral Blood Mononuclear Cells Using Genome-Wide DNA Microarray

Multi-omics landscape of Interferon-stimulated gene OASL reveals a potential biomarker in pan-cancer: from prognosis to tumor microenvironment

Background

OASL (Oligoadenylate Synthetase-Like), an interferon-induced protein in the OAS family, plays a significant role in anti-viral response. Studies have demonstrated its association with prognosis of certain tumors. However, the mechanism through which OASL affects tumors is unclear. A systemic pan-cancer study of OASL needs to be illustrated.

Methods

Analysis of OASL expression across 33 tumors was conducted utilizing TCGA, GTEx and CPTAC databases. COX and Log-Rank regressions were employed to calculate the prognosis. We validated the impact of OASL on apoptosis, migration, and invasion in pancreatic cancer cell lines. Moreover, we employed seven algorithms in bulk data to investigate the association of OASL expression and immune cell infiltration within tumor immune microenvironment (TIME) and ultimately validated at single-cell transcriptome level.

Results

We discovered elevated expression of OASL and its genetic heterogeneity in certain tumors, which link closely to prognosis. Validation experiments were conducted in PAAD and confirmed these findings. Additionally, OASL regulates immune checkpoint ligand such as programmed death ligand 1 (PD-L1), through IFN-γ/STAT1 and IL-6/JAK/STAT3 pathways in tumor cells. Meanwhile, OASL affects macrophages infiltration in TIME. By these mechanisms OASL could cause dysfunction of cytotoxic T lymphocytes (CTLs) in tumors.

Discussion

Multi-omics analysis reveals OASL as a prognostic and immunological biomarker in pan-cancer.

CCR4 predicts the efficacy of abatacept in rheumatoid arthritis patients through the estimation of Th17 and Treg cell abundance

OBJECTIVES

Predicting the efficacy of biological disease-modifying antirheumatic drugs is challenging. In this study, we aimed to explore markers that predict the efficacy of abatacept in rheumatoid arthritis (RA) patients.

METHODS

Thirty RA patients receiving abatacept were recruited, and peripheral blood mononuclear cells from the participants were subjected to DNA microarray analysis. The expression of CC chemokine receptor 4 (CCR4), which was selected by the result of DNA microarray, was determined by flow cytometry in 16 newly diagnosed treatment-naïve RA patients. CCR4 expression on each helper T-cell subset was also measured.

RESULTS

CCR4 was upregulated in the abatacept responder. The expression levels of CCR4 were significantly correlated with the improvement of the Clinical Disease Activity Index. CCR4 expression was predominantly observed in CD4+ T cells in peripheral blood mononuclear cells. The percentage of CCR4-expressing CD4+ T cells was significantly higher in RA patients than in healthy individuals. Interestingly, Th17 and Treg cells expressed high levels of CCR4 compared to non-Th17-related helper T cells.

CONCLUSIONS

CCR4 is a Th17- and Treg-related gene, and the high CCR4 expression in peripheral blood samples may predict the efficacy of abatacept in RA.

Genomic Profiling for Predictive Treatment Strategies in Fibrotic Interstitial Lung Disease

Idiopathic pulmonary fibrosis (IPF) has traditionally been considered the archetype of progressive fibrotic interstitial lung diseases (f-ILDs), but several other f-ILDs can also manifest a progressive phenotype. Integrating genomic signatures into clinical practice for f-ILD patients may help to identify patients predisposed to a progressive phenotype. In addition to the risk of progressive pulmonary fibrosis, there is a growing body of literature examining how pharmacogenomics influences treatment response, particularly regarding the efficacy and safety profiles of antifibrotic and immunomodulatory agents. In this narrative review, we discuss current studies in IPF and other forms of pulmonary fibrosis, including systemic autoimmune disorders associated ILDs, sarcoidosis and hypersensitivity pneumonitis. We also provide insights into the future direction of research in this complex field.

Five-year follow-up of patients with difficult-to-treat rheumatoid arthritis

OBJECTIVES

To elucidate the long-term outcomes of patients with difficult-to-treat rheumatoid arthritis (D2T RA).

METHODS

We collected data on the clinical course of patients who had been identified as D2T RA in 2018 until 2023. We stratified the patients according to outcomes at the last visit: resolved D2T RA, persistent D2T RA, and mortality. We compared their clinical characteristics and investigated the predictive factors for the resolution of D2T RA or mortality. Furthermore, we investigated the impact of the causes of D2T RA identified in 2018, multidrug resistance, comorbidities, and socioeconomic factors on outcomes in 2023.

RESULTS

Of 173 patients identified as D2T RA in 2018, 150 were included in the analysis. Among them, D2T RA was resolved in 67 (45%), 75 (50%) remained as D2T RA, and 8 (5%) died. Patients with resolved D2T RA were significantly younger at the latest visit (p= 0.02), had a higher proportion of treatment changes during five years (p= 0.002), and had a higher proportion of interleukin-6 receptor inhibitors use in 2023 (p= 0.04) than those in patients with persistent D2T RA or those who died. D2T RA resolved in 38% of patients with multidrug resistance, mainly with treatment changes. Rheumatic disease comorbidity index and glucocorticoid dose escalation were independent risk factors for mortality (odds ratio [OR], 3.50; p= 0.02 and OR, 31.9; p= 0.002, respectively).

CONCLUSION

Further modifications in RA treatment are useful for resolving D2T RA. Multiple comorbidities and glucocorticoid use are associated with mortality.

Towards Personalized Medicine in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic, incurable, multisystem, inflammatory disease characterized by synovitis and extra-articular features. Although several advanced therapies targeting inflammatory mechanisms underlying the disease are available, no advanced therapy is universally effective. Therefore, a ceiling of treatment response is currently accepted where no advanced therapy is superior to another. The current challenge for medical research is the discovery and integration of predictive markers of drug response that can be used to personalize medicine so that the patient is started on "the right drug at the right time". This review article summarizes our current understanding of predicting response to anti-rheumatic drugs in RA, obstacles impeding the development of personalized medicine approaches and future research priorities to overcome these barriers.

Revealing the changes in signaling pathways caused by tofacitinib in patients with rheumatoid arthritis through RNA sequencing and the correlation with clinical parameters

OBJECTIVES

The current study is to accelerate the understanding of how tofacitinib works in patients with rheumatoid arthritis (RA) due to the lack of relevant information.

METHOD

We selected ten patients with active RA and obtained the expression profile for their peripheral blood mononuclear cells before and after the tofacitinib treatment by RNA sequencing. The gene set enrichment analysis was conducted, and the significantly enriched gene sets were identified. The hub gene highly correlated with clinical parameters in the gene set was selected. We constructed the weighted gene co-expression network, linked modules with clinical indicators, and screened hub genes. The expression of representative hub genes was validated by real-time quantitative PCR (qPCR).

RESULTS

Gene set interferon (IFN) α and IFN β signaling was the most significantly down-regulated after tofacitinib treatment. In this gene set, genes Oas2 and Oasl showed a significant positive correlation with morning stiffness. In co-expression network, gene Vgll3 from the violet module with the highest correlation coefficient, was positively correlated with morning stiffness. Among them, Oasl and Vgll3 have shown significant down-regulation in qPCR validation.

CONCLUSIONS

Our results highlighted the role of type I IFN, mainly including IFN α and IFN β, in the pathogenesis of RA and action for tofacitinib, and provided a new entry point for further elucidating the mechanism of morning stiffness. Key Points • Gene set IFN α and IFN β signaling was the most significantly down-regulated after tofacitinib treatment in RA patients. • Gene Oasl and Vgll3 were correlated with morning stiffness and significantly down-regulated due to the action of tofacitinib. • Type I IFN system was highlighted in the action of tofacitinib.

Pathophysiology and stratification of treatment-resistant rheumatoid arthritis

Early diagnosis and timely therapeutic intervention are clinical challenges of rheumatoid arthritis (RA), especially for treatment-resistant or difficult-to-treat patients. Little is known about the immunological mechanisms involved in refractory RA. In this review, we summarize previous research findings on the immunological mechanisms of treatment-resistant RA. Genetic prediction of treatment-resistant RA is challenging. Patients with and without anti-cyclic citrullinated peptide autoantibodies are considered part of distinct subgroups, especially regarding long-term clinical prognosis and treatment responses. B cells, T cells and other immune cells and fibroblasts are of pathophysiological importance and are associated with treatment responses. Finally, we propose a new hypothesis that stratifies patients with RA into two subgroups with distinct immunological pathologies based on our recent immunomics analysis of RA. One RA subgroup with a favorable prognosis is characterized by increased interferon signaling. Another subgroup with a worse prognosis is characterized by enhanced acquired immune responses. Increases in dendritic cell precursors and diversified autoreactive anti-modified protein antibodies may have pathophysiological roles, especially in the latter subgroup. These findings that improve treatment response predictions might contribute to future precision medicine for RA.

B cell subsets-related biomarkers and molecular pathways for systemic lupus erythematosus by transcriptomics analyses

BACKGROUND

Systemic lupus erythematosus (SLE), an autoimmune disease, is characterised by B-cell abnormalities and a loss of tolerance that can produce autoantibody. However, the imperative genes and molecular pathways involved in the change of B cell populations remain unclear.

METHODS

The expression of B cell subsets between SLE and healthy controls (HCs) was detected based on micro-array transcriptome data. The Weighted Gene Co-Expression Network Analysis (WGCNA) further revealed the co-expression modules of naïve and memory B cells. Whereafter, we performed the functional enrichment analysis, Protein-protein interaction (PPI) networks construction and feature selection to screen hub genes. Ultimately, we recruited SLE patients and HCs from the Second Hospital of Shanxi Medical University and further verified these genes in transcriptome sequencing samples.

RESULTS

Total of 1087 SLE patients and 86 HCs constituted in the study. Compared to HCs, the levels of peripheral naïve B cells of SLE patients decreased, while memory B cells increased. WGCNA identified two modules with the highest correlation for the subsequent analysis. The purple module was primarily in connection with naïve B cells, and the GO analysis indicated that these genes were mainly abundant in B cell activation. The blue module relevant to memory B cells was most significantly enriched in the "defence response to virus" correlation pathway. Then we screened six hub genes by PPI and feature selection. Finally, four biomarkers (IFI27, IFITM1, MX2, IRF7) were identified by transcriptome sequencing verification.

CONCLUSION

Our study identified hub genes and key pathways associated with the naïve and memory B cells respectively, which may offer novel insights into the behaviours of B cells and the pathogenesis of SLE.

2022 EULAR points to consider for the measurement, reporting and application of IFN-I pathway activation assays in clinical research and practice

BACKGROUND

Type I interferons (IFN-Is) play a role in a broad range of rheumatic and musculoskeletal diseases (RMDs), and compelling evidence suggests that their measurement could have clinical value, although testing has not progressed into clinical settings.

OBJECTIVE

To develop evidence-based points to consider (PtC) for the measurement and reporting of IFN-I assays in clinical research and to determine their potential clinical utility.

METHODS

EULAR standardised operating procedures were followed. A task force including rheumatologists, immunologists, translational scientists and a patient partner was formed. Two systematic reviews were conducted to address methodological and clinical questions. PtC were formulated based on the retrieved evidence and expert opinion. Level of evidence and agreement was determined.

RESULTS

Two overarching principles and 11 PtC were defined. The first set (PtC 1-4) concerned terminology, assay characteristics and reporting practices to enable more consistent reporting and facilitate translation and collaborations. The second set (PtC 5-11) addressed clinical applications for diagnosis and outcome assessments, including disease activity, prognosis and prediction of treatment response. The mean level of agreement was generally high, mainly in the first PtC set and for clinical applications in systemic lupus erythematosus. Harmonisation of assay methodology and clinical validation were key points for the research agenda.

CONCLUSIONS

IFN-I assays have a high potential for implementation in the clinical management of RMDs. Uptake of these PtC will facilitate the progress of IFN-I assays into clinical practice and may be also of interest beyond rheumatology.

TAp63, a methotrexate target in CD4+ T cells, suppresses Foxp3 expression and exacerbates autoimmune arthritis

Methotrexate (MTX) is a standard, first-line therapy for rheumatoid arthritis (RA); however, its precise mechanisms of action other than antifolate activity are largely unknown. We performed DNA microarray analyses of CD4+ T cells in patients with RA before and after MTX treatment and found that TP63 was the most significantly downregulated gene after MTX treatment. TAp63, an isoform of TP63, was highly expressed in human IL-17-producing Th (Th17) cells and was suppressed by MTX in vitro. Murine TAp63 was expressed at high levels in Th cells and at lower levels in thymus-derived Treg cells. Importantly, TAp63 knockdown in murine Th17 cells ameliorated the adoptive transfer arthritis model. RNA-Seq analyses of human Th17 cells overexpressing TAp63 and those with TAp63 knockdown identified FOXP3 as a possible TAp63 target gene. TAp63 knockdown in CD4+ T cells cultured under Th17 conditions with low-dose IL-6 increased Foxp3 expression, suggesting that TAp63 balances Th17 cells and Treg cells. Mechanistically, TAp63 knockdown in murine induced Treg (iTreg) cells promoted hypomethylation of conserved noncoding sequence 2 (CNS2) of the Foxp3 gene and enhanced the suppressive function of iTreg cells. Reporter analyses revealed that TAp63 suppressed the activation of the Foxp3 CNS2 enhancer. Collectively, TAp63 suppresses Foxp3 expression and exacerbates autoimmune arthritis.

Immunomics analysis of rheumatoid arthritis identified precursor dendritic cells as a key cell subset of treatment resistance

OBJECTIVES

Little is known about the immunology underlying variable treatment response in rheumatoid arthritis (RA). We performed large-scale transcriptome analyses of peripheral blood immune cell subsets to identify immune cells that predict treatment resistance.

METHODS

We isolated 18 peripheral blood immune cell subsets of 55 patients with RA requiring addition of new treatment and 39 healthy controls, and performed RNA sequencing. Transcriptome changes in RA and treatment effects were systematically characterised. Association between immune cell gene modules and treatment resistance was evaluated. We validated predictive value of identified parameters for treatment resistance using quantitative PCR (qPCR) and mass cytometric analysis cohorts. We also characterised the identified population by synovial single cell RNA-sequencing analysis.

RESULTS

Immune cells of patients with RA were characterised by enhanced interferon and IL6-JAK-STAT3 signalling that demonstrate partial normalisation after treatment. A gene expression module of plasmacytoid dendritic cells (pDC) reflecting the expansion of dendritic cell precursors (pre-DC) exhibited strongest association with treatment resistance. Type I interferon signalling was negatively correlated to pre-DC gene expression. qPCR and mass cytometric analysis in independent cohorts validated that the pre-DC associated gene expression and the proportion of pre-DC were significantly higher before treatment in treatment-resistant patients. A cluster of synovial DCs showed both features of pre-DC and pro-inflammatory conventional DC2s.

CONCLUSIONS

An increase in pre-DC in peripheral blood predicted RA treatment resistance. Pre-DC could have pathophysiological relevance to RA treatment response.

Optimal Selection of IFN-α-Inducible Genes to Determine Type I Interferon Signature Improves the Diagnosis of Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by the production of autoantibodies specific to self-molecules in the nucleus, cytoplasm, and cell surface. The diversity of serologic and clinical manifestations observed in SLE patients challenges the development of diagnostics and tools for monitoring disease activity. Elevated type I interferon signature (IFN- I) in SLE leads to dysregulation of innate and adaptive immune function, resulting in autoantibodies production. The most common method to determine IFN-I signature is measuring the gene expression of several IFN-α-inducible genes (IFIGs) in blood samples and calculating a score. Optimal selection of IFIGs improves the sensitivity, specificity, and accuracy of the diagnosis of SLE. We describe the mechanisms of the immunopathogenesis of IFN-I signature (IFNα production) and its clinical consequences in SLE. In addition, we explore the association between IFN-I signature, the presence of autoantibodies, disease activity, medical therapy, and ethnicity. We discuss the presence of IFN-I signature in some patients with other autoimmune diseases, including rheumatoid arthritis, systemic and multiple sclerosis, Sjogren’s syndrome, and dermatomyositis. Prospective studies are required to assess the role of IFIG and the best combination of IFIGs to monitor SLE disease activity and drug treatments.

Association between type I interferon pathway activation and clinical outcomes in rheumatic and musculoskeletal diseases: a systematic literature review informing EULAR points to consider

BACKGROUND

Type I interferons (IFN-I) contribute to a broad range of rheumatic and musculoskeletal diseases (RMDs). Compelling evidence suggests that the measurement of IFN-I pathway activation may have clinical value. Although several IFN-I pathway assays have been proposed, the exact clinical applications are unclear. We summarise the evidence on the potential clinical utility of assays measuring IFN-I pathway activation.

METHODS

A systematic literature review was conducted across three databases to evaluate the use of IFN-I assays in diagnosis and monitor disease activity, prognosis, response to treatment and responsiveness to change in several RMDs.

RESULTS

Of 366 screened, 276 studies were selected that reported the use of assays reflecting IFN-I pathway activation for disease diagnosis (n=188), assessment of disease activity (n=122), prognosis (n=20), response to treatment (n=23) and assay responsiveness (n=59). Immunoassays, quantitative PCR (qPCR) and microarrays were reported most frequently, while systemic lupus erythematosus (SLE), rheumatoid arthritis, myositis, systemic sclerosis and primary Sjögren's syndrome were the most studied RMDs. The literature demonstrated significant heterogeneity in techniques, analytical conditions, risk of bias and application in diseases. Inadequate study designs and technical heterogeneity were the main limitations. IFN-I pathway activation was associated with disease activity and flare occurrence in SLE, but their incremental value was uncertain. IFN-I pathway activation may predict response to IFN-I targeting therapies and may predict response to different treatments.

CONCLUSIONS

Evidence indicates potential clinical value of assays measuring IFN-I pathway activation in several RMDs, but assay harmonisation and clinical validation are urged. This review informs the EULAR points to consider for the measurement and reporting of IFN-I pathway assays.

Transcriptomic profile comparison of monocytes from rheumatoid arthritis patients in treatment with methotrexate, anti-TNFa, abatacept or tocilizumab

It is well documented that patients affected by rheumatoid arthritis (RA) have distinct susceptibility to the different biologic DMARDs available on the market, probably because of the many facets of the disease. Monocytes are deeply involved in the pathogenesis of RA and we therefore evaluated and compared the transcriptomic profile of monocytes isolated from patients on treatment with methotrexate alone or in combination with tocilizumab, anti-TNFα or abatacept and from healthy donors. Whole-genome transcriptomics yielded a list of regulated genes by Rank Product statistics and DAVID was then used for functional annotation enrichment analysis. Last, data were validated by qRT-PCR. Abatacept, tocilizumab and anti-TNFa cohorts were separately compared with methotrexate, leading to the identification of 78, 6, and 436 differentially expressed genes, respectively. The upper-most ranked genes were related to inflammatory processes and immune responses. Such an approach draws the genomic profile of monocytes in treated RA patients and lays the basis for finding gene signature for tailored therapeutic choices.

Pre-defined gene co-expression modules in rheumatoid arthritis transition towards molecular health following anti-TNF therapy

BACKGROUND

No reliable biomarkers to predict response to TNF inhibitors (TNFi) in RA patients currently exist. The aims of this study were to replicate changes in gene co-expression modules that were previously reported in response to TNFi therapy in RA; to test if changes in module expression are specific to TNFi therapy; and to determine whether module expression transitions towards a disease-free state in responding patients.

METHOD

Published transcriptomic data from the whole blood of disease-free controls (n = 10) and RA patients, treated with the TNFi adalimumab (n = 70) or methotrexate (n = 85), were studied. Treatment response was assessed using the EULAR response criteria following 3 or 6 months of treatment. Change in transcript expression between pre- and post-treatment was recorded for previously defined modules. Linear mixed models tested whether modular expression after treatment transitioned towards a disease-free state.

RESULTS

For 25 of the 27 modules, change in expression between pre- and post-treatment in the adalimumab cohort replicated published findings. Of these 25 modules, six transitioned towards a disease-free state by 3 months (P < 0.05), irrespective of clinical response. One module (M3.2), related to inflammation and TNF biology, significantly correlated with response to adalimumab. Similar patterns of modular expression, with reduced magnitude, were observed in the methotrexate cohort.

CONCLUSION

This study provides independent validation of changes in module expression in response to therapy in RA. However, these effects are not specific to TNFi. Further studies are required to determine whether specific modules could assist molecular classification of therapeutic response.

A systematic literature review informing the consensus statement on efficacy and safety of pharmacological treatment with interleukin-6 pathway inhibition with biological DMARDs in immune-mediated inflammatory diseases

Objectives

Informing an international task force updating the consensus statement on efficacy and safety of biological disease-modifying antirheumatic drugs (bDMARDs) selectively targeting interleukin-6 (IL-6) pathway in the context of immune-mediated inflammatory diseases.

Methods

A systematic literature research of all publications on IL-6 axis inhibition with bDMARDs published between January 2012 and December 2020 was performed using MEDLINE, EMBASE and Cochrane CENTRAL databases. Efficacy and safety outcomes were assessed in clinical trials including their long-term extensions and observational studies. Meeting abstracts from ACR, EULAR conferences and results on clinicaltrials.gov were taken into consideration.

Results

187 articles fulfilled the inclusion criteria. Evidence for positive effect of IL-6 inhibition was available in various inflammatory diseases such as rheumatoid arthritis, juvenile idiopathic arthritis, giant cell arteritis, Takayasu arteritis, adult-onset Still’s disease, cytokine release syndrome due to chimeric antigen receptor T cell therapy and systemic sclerosis-associated interstitial lung disease. Newcomers like satralizumab and anti-IL-6 ligand antibody siltuximab have expanded therapeutic approaches for Castleman’s disease and neuromyelitis optica, respectively. IL-6 inhibition did not provide therapeutic benefits in psoriatic arthritis, ankylosing spondylitis and certain connective tissue diseases. In COVID-19, tocilizumab (TCZ) has proven to be therapeutic in advanced disease. Safety outcomes did not differ from other bDMARDs, except higher risks of diverticulitis and lower gastrointestinal perforations. Inconsistent results were observed in several studies investigating the risk for infections when comparing TCZ to TNF-inhibitors.

Conclusion

IL-6 inhibition is effective for treatment of several inflammatory diseases with a safety profile that is widely comparable to other bDMARDs.

MX2: Identification and systematic mechanistic analysis of a novel immune-related biomarker for systemic lupus erythematosus

Background

Systemic lupus erythematosus (SLE) is an autoimmune disease that involves multiple organs. However, the current SLE-related biomarkers still lack sufficient sensitivity, specificity and predictive power for clinical application. Thus, it is significant to explore new immune-related biomarkers for SLE diagnosis and development.

Methods

We obtained seven SLE gene expression profile microarrays (GSE121239/11907/81622/65391/100163/45291/49454) from the GEO database. First, differentially expressed genes (DEGs) were screened using GEO2R, and SLE biomarkers were screened by performing WGCNA, Random Forest, SVM-REF, correlation with SLEDAI and differential gene analysis. Receiver operating characteristic curves (ROCs) and AUC values were used to determine the clinical value. The expression level of the biomarker was verified by RT‒qPCR. Subsequently, functional enrichment analysis was utilized to identify biomarker-associated pathways. ssGSEA, CIBERSORT, xCell and ImmuCellAI algorithms were applied to calculate the sample immune cell infiltration abundance. Single-cell data were analyzed for gene expression specificity in immune cells. Finally, the transcriptional regulatory network of the biomarker was constructed, and the corresponding therapeutic drugs were predicted.

Results

Multiple algorithms were screened together for a unique marker gene, MX2, and expression analysis of multiple datasets revealed that MX2 was highly expressed in SLE compared to the normal group (all P < 0.05), with the same trend validated by RT‒qPCR (P = 0.026). Functional enrichment analysis identified the main pathway of MX2 promotion in SLE as the NOD-like receptor signaling pathway (NES=2.492, P < 0.001, etc.). Immuno-infiltration analysis showed that MX2 was closely associated with neutrophils, and single-cell and transcriptomic data revealed that MX2 was specifically expressed in neutrophils. The NOD-like receptor signaling pathway was also remarkably correlated with neutrophils (r >0.3, P < 0.001, etc.). Most of the MX2-related interacting proteins were associated with SLE, and potential transcription factors of MX2 and its related genes were also significantly associated with the immune response.

Conclusion

Our study found that MX2 can serve as an immune-related biomarker for predicting the diagnosis and disease activity of SLE. It activates the NOD-like receptor signaling pathway and promotes neutrophil infiltration to aggravate SLE.

-Omic Approaches and Treatment Response in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an inflammatory disorder characterized by an aberrant activation of innate and adaptive immune cells. There are different drugs used for the management of RA, including disease-modifying antirheumatic drugs (DMARDs). However, a significant percentage of RA patients do not initially respond to DMARDs. This interindividual variation in drug response is caused by a combination of environmental, genetic and epigenetic factors. In this sense, recent -omic studies have evidenced different molecular signatures involved in this lack of response. The aim of this review is to provide an updated overview of the potential role of -omic approaches, specifically genomics, epigenomics, transcriptomics, and proteomics, to identify molecular biomarkers to predict the clinical efficacy of therapies currently used in this disorder. Despite the great effort carried out in recent years, to date, there are still no validated biomarkers of response to the drugs currently used in RA. -Omic studies have evidenced significant differences in the molecular profiles associated with treatment response for the different drugs used in RA as well as for different cell types. Therefore, global and cell type-specific -omic studies analyzing response to the complete therapeutical arsenal used in RA, including less studied therapies, such as sarilumab and JAK inhibitors, are greatly needed.

Lessons From Transcriptome Analysis of Autoimmune Diseases

Various immune cell types, including monocytes, macrophages, and adaptive immune T and B cells, play major roles in inflammation in systemic autoimmune diseases. However, the precise contribution of these cells to autoimmunity remains elusive. Transcriptome analysis has added a new dimension to biology and medicine. It enables us to observe the dynamics of gene expression in different cell types in patients with diverse diseases as well as in healthy individuals, which cannot be achieved with genomic information alone. In this review, we summarize how transcriptome analysis has improved our understanding of the pathological roles of immune cells in autoimmune diseases with a focus on the ImmuNexUT database we reported. We will also discuss the common experimental and analytical design of transcriptome analyses. Recently, single-cell RNA-seq analysis has provided atlases of infiltrating immune cells, such as pro-inflammatory monocytes and macrophages, peripheral helper T cells, and age or autoimmune-associated B cells in various autoimmune disease lesions. With the integration of genomic data, expression quantitative trait locus (eQTL) analysis can help identify candidate causal genes and immune cells. Finally, we also mention how the information obtained from these analyses can be used practically to predict patient prognosis.

Semaphorin 3G exacerbates joint inflammation through the accumulation and proliferation of macrophages in the synovium

Objectives

Methotrexate (MTX) is an anchor drug for the treatment of rheumatoid arthritis (RA). However, the precise mechanisms by which MTX stalls RA progression and alleviates the ensuing disease effects remain unknown. The aim of the present study was to identify novel therapeutic target molecules, the expression patterns of which are affected by MTX in patients with RA.

Methods

CD4⁺ T cells from 28 treatment-naïve patients with RA before and 3 months after the initiation of MTX treatment were subjected to DNA microarray analyses. The expression levels of semaphorin 3G, a differentially expressed gene, and its receptor, neuropilin-2, were evaluated in the RA synovium and collagen-induced arthritis synovium. Collagen-induced arthritis and collagen antibody-induced arthritis were induced in semaphorin3G-deficient mice and control mice, and the clinical score, histological score, and serum cytokines were assessed. The migration and proliferation of semaphorin 3G-stimulated bone marrow-derived macrophages were analyzed in vitro. The effect of local semaphorin 3G administration on the clinical score and number of infiltrating macrophages during collagen antibody-induced arthritis was evaluated.

Results

Semaphorin 3G expression in CD4⁺ T cells was downregulated by MTX treatment in RA patients. It was determined that semaphorin 3G is expressed in RA but not in the osteoarthritis synovium; its receptor neuropilin-2 is primarily expressed on activated macrophages. Semaphorin3G deficiency ameliorated collagen-induced arthritis and collagen antibody-induced arthritis. Semaphorin 3G stimulation enhanced the migration and proliferation of bone marrow-derived macrophages. Local administration of semaphorin 3G deteriorated collagen antibody-induced arthritis and increased the number of infiltrating macrophages.

Conclusions

Upregulation of semaphorin 3G in the RA synovium is a novel mechanism that exacerbates joint inflammation, leading to further deterioration, through macrophage accumulation.

The interferon gene signature as a clinically relevant biomarker in autoimmune rheumatic disease

The interferon gene signature (IGS) is derived from the expression of interferon-regulated genes and is classically increased in response to type I interferon exposure. A raised whole blood IGS has increasingly been reported in rheumatic diseases as sequencing technology has advanced. Although its role remains unclear, we explore how a raised IGS can function as a clinically relevant biomarker, independent of whether it is a bystander effect or a key pathological process. For example, a raised IGS can act as a diagnostic biomarker when predicting rheumatoid arthritis in patients with arthralgia and anti-citrullinated protein antibodies, or predicting systemic lupus erythematous (SLE) in those with antinuclear antibodies; a theragnostic biomarker when predicting response for patients receiving disease modifying therapy, such as rituximab in rheumatoid arthritis; a biomarker of disease activity (early rheumatoid arthritis, dermatomyositis, systemic sclerosis, SLE); or finally a predictor of clinical characteristics, such as lupus nephritis in SLE or disease burden in primary Sjögren's syndrome. A high IGS does not uniformly predict worse clinical phenotypes across all diseases, as demonstrated by a reduced disease burden in primary Sjögren's syndrome, nor does it predict a universally poorer response to all therapies, as shown in rheumatoid arthritis. This dichotomy highlights both the complexity of type I interferon signalling in vivo and the current lack of standardisation when calculating the IGS. The IGS as a biomarker warrants further exploration, with beneficial clinical applications anticipated in multiple rheumatic diseases.

Toward Overcoming Treatment Failure in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an autoimmune disorder characterized by inflammation and bone erosion. The exact mechanism of RA is still unknown, but various immune cytokines, signaling pathways and effector cells are involved. Disease-modifying antirheumatic drugs (DMARDs) are commonly used in RA treatment and classified into different categories. Nevertheless, RA treatment is based on a "trial-and-error" approach, and a substantial proportion of patients show failed therapy for each DMARD. Over the past decades, great efforts have been made to overcome treatment failure, including identification of biomarkers, exploration of the reasons for loss of efficacy, development of sequential or combinational DMARDs strategies and approval of new DMARDs. Here, we summarize these efforts, which would provide valuable insights for accurate RA clinical medication. While gratifying, researchers realize that these efforts are still far from enough to recommend specific DMARDs for individual patients. Precision medicine is an emerging medical model that proposes a highly individualized and tailored approach for disease management. In this review, we also discuss the potential of precision medicine for overcoming RA treatment failure, with the introduction of various cutting-edge technologies and big data.

The impact of sex on susceptibility to systemic lupus erythematosus and rheumatoid arthritis; a bioinformatics point of view

The unknown etiology of systemic autoimmune diseases, such as Systemic Lupus Erythematosus (SLE) and Rheumatoid Arthritis (RA), with a remarkable predominance of female, have prompted many researchers for unveiling the precise molecular mechanisms involved in this gender bias. In fact, depending on hormones and transcribed genes from sex chromosomes, at least, the initial mechanisms involved in pathogenesis might differ largely. With the aim of elucidating the above mechanisms, we have tried to specify the differentially expressed genes (DEGs) extracted from microarray libraries from both female and male SLE and RA patients. Subsequently, the androgen and estrogen receptor elements (ARE and ERE) among differentially expressed transcription factors (TFs) and the DEGs located on X or Y chromosomes have been determined. Moreover, the pathways regarding the common DEGs in both sexes are enriched. Our data revealed several ARE and ERE-containing genes (LCN2, LTF, RPL31, RPL9, RPS17, RPS24, RPS27L, S100A8, ABCA1, HIST1H2BD, ISG15, MAFB, GNLY, EVL, and HDC) to be associated with the related autoimmune disease and sex. Also, two DEGs (KDM5D and RPS4Y1) in SLE patients were determined to be on Y chromosome with one had been proved to be associated with autoantigens in SLE. Altogether, our data showed a number of plausible pathways in both autoimmune conditions together with the relevance of several sex-related genes in the mentioned diseases pathogenesis.

Possible Roles of tRNA Fragments, as New Regulatory ncRNAs, in the Pathogenesis of Rheumatoid Arthritis

Understanding the pathophysiology of rheumatoid arthritis (RA) has led to the successful development of molecule-targeted drugs for the treatment of RA. However, some RA patients are refractory to these treatments, suggesting that the pathological mechanism of the disease is not entirely understood. Genome and transcriptome analysis is essential for understanding the unknown pathophysiology of human diseases. Rapid and more comprehensive gene analysis technologies have revealed notable changes in the expression of coding RNA and non-coding RNA in RA patients. This review focuses on the current state of non-coding RNA research in relation to RA, especially on tRNA fragments. Interestingly, it has been found that tRNA fragments repress translation and are antiapoptotic. The association between tRNA fragments and various diseases has been studied, and this article reviews the possible role of tRNA fragments in RA.

Multi-omics approach to precision medicine for immune-mediated diseases

Recent innovation in high-throughput sequencing technologies has drastically empowered the scientific research. Consequently, now, it is possible to capture comprehensive profiles of samples at multiple levels including genome, epigenome, and transcriptome at a time. Applying these kinds of rich information to clinical settings is of great social significance. For some traits such as cardiovascular diseases, attempts to apply omics datasets in clinical practice for the prediction of the disease risk have already shown promising results, although still under way for immune-mediated diseases. Multiple studies have tried to predict treatment response in immune-mediated diseases using genomic, transcriptomic, or clinical information, showing various possible indicators. For better prediction of treatment response or disease outcome in immune-mediated diseases, combining multi-layer information together may increase the power. In addition, in order to efficiently pick up meaningful information from the massive data, high-quality annotation of genomic functions is also crucial. In this review, we discuss the achievement so far and the future direction of multi-omics approach to immune-mediated diseases.

Plasma interferon-alpha is associated with double-positivity for autoantibodies but is not a predictor of remission in early rheumatoid arthritis-a spin-off study of the NORD-STAR randomized clinical trial

BACKGROUND

The type I interferon (IFN) gene signature is present in a subgroup of patients with early rheumatoid arthritis (RA). Protein levels of IFNα have not been measured in RA and it is unknown whether they associate with clinical characteristics or treatment effect.

METHODS

Patients with early untreated RA (n = 347) were randomized to methotrexate combined with prednisone, certolizumab-pegol, abatacept, or tocilizumab. Plasma IFNα protein levels were determined by single molecular array (Simoa) before and 24 weeks after treatment initiation and were related to demographic and clinical factors including clinical disease activity index, disease activity score in 28 joints, swollen and tender joint counts, and patient global assessment.

RESULTS

IFNα protein positivity was found in 26% of the patients, and of these, 92% were double-positive for rheumatoid factor (RF) and anti-citrullinated protein antibodies (ACPA). IFNα protein levels were reduced 24 weeks after treatment initiation, and the absolute change was similar irrespective of treatment. IFNα protein positivity was associated neither with disease activity nor with achievement of CDAI remission 24 weeks after randomization.

CONCLUSION

IFNα protein positivity is present in a subgroup of patients with early RA and associates with double-positivity for autoantibodies but not with disease activity. Pre-treatment IFNα positivity did not predict remission in any of the treatment arms, suggesting that the IFNα system is distinct from the pathways of TNF, IL-6, and T-cell activation in early RA. A spin-off study of the NORD-STAR randomized clinical trial, NCT01491815 (ClinicalTrials), registered 12/08/2011, https://clinicaltrials.gov/ct2/show/NCT01491815 .

Pathological Mechanisms and Potential Therapeutic Targets of Pulmonary Arterial Hypertension: A Review

Pulmonary arterial hypertension (PAH) is a progressive cardiovascular disease characterized by pulmonary vasculature reconstruction and right ventricular dysfunction. The mortality rate of PAH remains high, although multiple therapeutic strategies have been implemented in clinical practice. These drugs mainly target the endothelin-1, prostacyclin and nitric oxide pathways. Management for PAH treatment includes improving symptoms, enhancing quality of life, and extending survival rate. Existing drugs developed to treat the disease have resulted in enormous economic and healthcare liabilities. The estimated cost for advanced PAH has exceeded $200,000 per year. The pathogenesis of PAH is associated with numerous molecular processes. It mainly includes germline mutation, inflammation, dysfunction of pulmonary arterial endothelial cells, epigenetic modifications, DNA damage, metabolic dysfunction, sex hormone imbalance, and oxidative stress, among others. Findings based on the pathobiology of PAH may have promising therapeutic outcomes. Hence, faced with the challenges of increasing healthcare demands, in this review, we attempted to explore the pathological mechanisms and alternative therapeutic targets, including other auxiliary devices or interventional therapies, in PAH. The article will discuss the potential therapies of PAH in detail, which may require further investigation before implementation.

Regulation of gene expression by MF63, a selective inhibitor of microsomal PGE synthase 1 (mPGES1) in human osteoarthritic chondrocytes

Background and Purpose

mPGES1 catalyses the production of PGE₂, the most abundant prostanoid related to inflammation and pain in arthritis. mPGES1 is suggested to be a safer and more selective drug target in inflammatory conditions compared to the COX enzymes inhibited by NSAIDs. In the present study, we investigated the effects of the selective mPGES1 inhibitor MF63 on gene expression in primary human chondrocytes from patients with osteoarthritis (OA).

Experimental Approach

Chondrocytes were isolated from articular cartilage obtained from osteoarthritis patients undergoing knee replacement surgery. The effects of MF63 were studied in the primary chondrocytes with RNA‐sequencing based genome‐wide expression analysis. The main results were confirmed with qRT‐PCR and compared with the effects of the NSAID ibuprofen. Functional analysis was performed with the GO database and interactions between the genes were studied with STRING.

Key Results

MF63 enhanced the expression of multiple metallothionein 1 (MT1) isoforms as well as endogenous antagonists of IL‐1 and IL‐36. The expression of IL‐6, by contrast, was down‐regulated. These genes were also essential in functional and interaction network analyses. The effects of MF63 were consistent in qRT‐PCR analysis, whereas the effects of ibuprofen overlapped only partly with MF63. There were no evident findings of catabolic effects by MF63.

Conclusion and Implications

Metallothionein 1 has been suggested to have anti‐inflammatory and protective effects in cartilage. Up‐regulation of the antagonists of IL‐1 superfamily and down‐regulation of the pro‐inflammatory cytokine IL‐6 also support novel anti‐inflammatory and possibly disease‐modifying effects of mPGES1 inhibitors in arthritis.

RNA Identification of PRIME Cells Predicting Rheumatoid Arthritis Flares

BACKGROUND

Rheumatoid arthritis, like many inflammatory diseases, is characterized by episodes of quiescence and exacerbation (flares). The molecular events leading to flares are unknown.

METHODS

We established a clinical and technical protocol for repeated home collection of blood in patients with rheumatoid arthritis to allow for longitudinal RNA sequencing (RNA-seq). Specimens were obtained from 364 time points during eight flares over a period of 4 years in our index patient, as well as from 235 time points during flares in three additional patients. We identified transcripts that were differentially expressed before flares and compared these with data from synovial single-cell RNA-seq. Flow cytometry and sorted-blood-cell RNA-seq in additional patients were used to validate the findings.

RESULTS

Consistent changes were observed in blood transcriptional profiles 1 to 2 weeks before a rheumatoid arthritis flare. B-cell activation was followed by expansion of circulating CD45-CD31-PDPN+ preinflammatory mesenchymal, or PRIME, cells in the blood from patients with rheumatoid arthritis; these cells shared features of inflammatory synovial fibroblasts. Levels of circulating PRIME cells decreased during flares in all 4 patients, and flow cytometry and sorted-cell RNA-seq confirmed the presence of PRIME cells in 19 additional patients with rheumatoid arthritis.

CONCLUSIONS

Longitudinal genomic analysis of rheumatoid arthritis flares revealed PRIME cells in the blood during the period before a flare and suggested a model in which these cells become activated by B cells in the weeks before a flare and subsequently migrate out of the blood into the synovium. (Funded by the National Institutes of Health and others.).

IMMUNOINFLAMMATORY RHEUMATIC DISEASES ASSOCIATED WITH TYPE I INTERFERON: NEW EVIDENCE

Immunoinflammatory rheumatic diseases (IIRDs) are a large group of pathological conditions with impaired immunological tolerance to autogenous tissues, leading to inflammation and irreversible organ damage. The review discusses current ideas on the role of type I interferons in the immunopathogenesis of IIRDs, primarily systemic lupus erythematosus, and new possibilities for personalized therapy.

Dynamics of the Type I Interferon Response During Immunosuppressive Therapy in Rheumatoid Arthritis

Objective: The type I interferon (IFN) response in rheumatoid arthritis (RA) has been extensively studied in relation to therapy with biological DMARDs (bDMARDs). However, the effect of conventional synthetic (cs)DMARDs and glucocorticoids (GCs) on IFN response gene (IRG) expression remains largely unknown, even though csDMARDS are used throughout all disease phases, including simultaneously with biologic therapy. This study was aimed to determine the dynamics of IFN response upon immunosuppressive treatment. Methods: Whole blood was collected in PAXgene tubes from 35 RA patients who received either COBRA therapy (combination of prednisone, initially 60 mg, methotrexate and sulfasalazine) (n = 14) or COBRA-light therapy (prednisone, initially 30 mg, and methotrexate) (n = 21). Expression of 10 IRGs was determined by real-time PCR at baseline (T0), after 4 weeks (T4), and 13 weeks (T13) of treatment. IRG selection was based on the differential presence of transcription factor binding sites (TFBS), in order to study the therapy effect on different pathway components involved in IFN signaling. Results: Seven of the 10 IRGs displayed significant changes during treatment (p ≤ 0.016). These 7 IRGs all displayed a particularly pronounced decrease between T0 and T4 (≥1.6-fold, p ≤ 0.0059). The differences between IRG sensitivity to the treatment appeared related to the presence of TFBS for STAT1 and IRF proteins within the genes. The extent of the decreases between T0 and T4 was similar for the COBRA- and COBRA-light-treated group, despite the differences in drug combination and doses in those groups. Between T4 and T13, however, IRG expression in the COBRA-light-treated group displayed a significant increase, whereas it remained stable or decreased even further in most COBRA-treated patients (comparison of mean fold changes, p = 0.011). A significant association between IRG dynamics and clinical response to therapy was not detected. Conclusions: Immunosuppressive treatment with csDMARDs, in this case a combination of prednisolone, methotrexate and sulfasalazine, substantially downregulates the IFN response in RA patients. The dynamics of this downregulation were partly dependent on the presence of TFBS within the IRGs and the combination and dosages of agents, but they were irrespective of the clinical response to therapy.

Profiling of Gene Expression Biomarkers as a Classifier of Methotrexate Nonresponse in Patients With Rheumatoid Arthritis

Objective

Approximately 30–40% of rheumatoid arthritis (RA) patients who are initially started on low‐dose methotrexate (MTX) will not benefit from the treatment. To date, no reliable biomarkers of MTX inefficacy in RA have been identified. The aim of this study was to analyze whole blood samples from RA patients at 2 time points (pretreatment and 4 weeks following initiation of MTX), to identify gene expression biomarkers of the MTX response.

Methods

RA patients who were about to commence treatment with MTX were selected from the Rheumatoid Arthritis Medication Study. Using European League Against Rheumatism (EULAR) response criteria, 42 patients were categorized as good responders and 43 as nonresponders at 6 months following the initation of MTX treatment. Data on whole blood transcript expression were generated, and supervised machine learning methods were used to predict a EULAR nonresponse. Models in which transcript levels were included were compared to models in which clinical covariates alone (e.g., baseline disease activity, sex) were included. Gene network and ontology analysis was also performed.

Results

Based on the ratio of transcript values (i.e., the difference in log₂‐transformed expression values between 4 weeks of treatment and pretreatment), a highly predictive classifier of MTX nonresponse was developed using L2‐regularized logistic regression (mean ± SEM area under the receiver operating characteristic [ROC] curve [AUC] 0.78 ± 0.11). This classifier was superior to models that included clinical covariates (ROC AUC 0.63 ± 0.06). Pathway analysis of gene networks revealed significant overrepresentation of type I interferon signaling pathway genes in nonresponders at pretreatment (P = 2.8 × 10⁻²⁵) and at 4 weeks after treatment initiation (P = 4.9 × 10⁻²⁸).

Conclusion

Testing for changes in gene expression between pretreatment and 4 weeks post–treatment initiation may provide an early classifier of the MTX treatment response in RA patients who are unlikely to benefit from MTX over 6 months. Such patients should, therefore, have their treatment escalated more rapidly, which would thus potentially impact treatment pathways. These findings emphasize the importance of a role for early treatment biomarker monitoring in RA patients started on MTX.

Transcriptome analysis of peripheral blood from patients with rheumatoid arthritis: a systematic review

In the era of precision medicine, transcriptome analysis of whole gene expression is an essential technology. While DNA microarray has a limited dynamic range and a problem of background hybridization, RNA sequencing (RNA-seq) has a broader dynamic range and a lower background signal that increase the sensitivity and reproducibility. While transcriptome analyses in rheumatoid arthritis (RA) have generally focused on whole peripheral blood mononuclear cells (PBMC), analyses of detailed cell subsets have an increased need for understanding the pathophysiology of disease because the involvement of CD4⁺ T cells in the pathogenesis of RA has been established. Transcriptome analysis of detailed CD4⁺ T cell subsets or neutrophils shed new light on the pathophysiology of RA. There are several analyses about the effect of biological treatment. Many studies report the association between type I interferon signature gene expression and response to therapy.

Discovery of Key Genes in Dermatomyositis Based on the Gene Expression Omnibus Database

The aim of this study was to identify biomarkers of dermatomyositis (DM). The analysis was conducted by retrieving DM-related cDNA microarray data sets from public databases. Gene ontology, Kyoto encyclopedia of genes and genomes, and protein-protein interaction analyses were performed, together with quantitative PCR-based detection of biomarkers in muscle tissue after stimulation with serum from patients with DM or healthy controls. Our analysis of five microarray data sets identified 20 common differentially expressed genes that are closely associated with DM. PCR analysis showed that mRNAs of IFITM2, LY6E, DDX58, and IFI6 were expressed at significantly higher levels in the muscle tissue of patients with DM than in normal muscle tissues. These mRNAs were also upregulated in human skeletal muscle cells stimulated with the serum from patients with DM. The results of integrated analyses of the DM microarray data and the mRNA levels of genes showed significant differences between the muscle tissues of DM patients and controls, which could indicate key pathogenic genes and novel therapeutic targets for DM.

The plasma biomarker soluble SIGLEC-1 is associated with the type I interferon transcriptional signature, ethnic background and renal disease in systemic lupus erythematosus

Background

The molecular heterogeneity of autoimmune and inflammatory diseases has been one of the main obstacles to the development of safe and specific therapeutic options. Here, we evaluated the diagnostic and clinical value of a robust, inexpensive, immunoassay detecting the circulating soluble form of the monocyte-specific surface receptor sialic acid binding Ig-like lectin 1 (sSIGLEC-1).

Methods

We developed an immunoassay to measure sSIGLEC-1 in small volumes of plasma/serum from systemic lupus erythematosus (SLE) patients (n = 75) and healthy donors (n = 504). Samples from systemic sclerosis patients (n = 99) were studied as an autoimmune control. We investigated the correlation between sSIGLEC-1 and both monocyte surface SIGLEC-1 and type I interferon-regulated gene (IRG) expression. Associations of sSIGLEC-1 with clinical features were evaluated in an independent cohort of SLE patients (n = 656).

Results

Plasma concentrations of sSIGLEC-1 strongly correlated with expression of SIGLEC-1 on the surface of blood monocytes and with IRG expression in SLE patients. We found ancestry-related differences in sSIGLEC-1 concentrations in SLE patients, with patients of non-European ancestry showing higher levels compared to patients of European ancestry. Higher sSIGLEC-1 concentrations were associated with lower serum complement component 3 and increased frequency of renal complications in European patients, but not with the SLE Disease Activity Index clinical score.

Conclusions

Our sSIGLEC-1 immunoassay provides a specific and easily assayed marker for monocyte–macrophage activation, and interferonopathy in SLE and other diseases. Further studies can extend its clinical associations and its potential use to stratify patients and as a secondary endpoint in clinical trials.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1649-1) contains supplementary material, which is available to authorized users.

A novel gene-expression-signature-based model for prediction of response to Tripterysium glycosides tablet for rheumatoid arthritis patients

Background

Approximately 30% of rheumatoid arthritis (RA) patients treated with Tripterysium glycosides (TG) tablets fail to achieve clinical improvement, implying the essentiality of predictive biomarkers and tools. Herein, we aimed to identify possible biomarkers predictive of therapeutic effects of TG tablets in RA.

Methods

Gene expression profile in peripheral blood mononuclear cells obtained from a discovery cohort treated with TG tablets was detected by Affymetrix EG1.0 arrays. Then, a list of candidate gene biomarkers of response to TG tablets were identified by integrating differential expression data analysis and gene signal transduction network analysis. After that, a partial-least-squares (PLS) model based on the expression levels of the candidate gene biomarkers in RA patients was constructed and evaluated using a validation cohort.

Results

Six candidate gene biomarkers (MX1, OASL, SPINK1, CRK, GRAPL and RNF2) were identified to be predictors of TG therapy. Following the construction of a PLS-based model using their expression levels in peripheral blood, both the 5-fold cross-validation and independent dataset validations showed the high predictive efficiency of this model, and demonstrated a distinguished improvement of the PLS-model based on six candidate gene biomarkers’ expression in combination over the commonly used clinical and inflammatory parameters, as well as the gene biomarkers alone, in predicting RA patients’ response to TG tablets.

Conclusions

This hypothesis-generating study identified MX1, OASL, SPINK1, CRK, GRAPL and RNF2 as novel targets for RA therapeutic intervention, and the PLS model based on the expression levels of these candidate biomarkers may have a potential prognostic value in RA patients treated with TG tablets.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1549-9) contains supplementary material, which is available to authorized users.

[Upcoming value of gene expression analysis in rheumatology]

Rheumatoid arthritis (RA) is a chronic inflammatory disease of unknown etiology, which involves disturbance in immune system signaling pathway functions, damage of other tissues, pain and joint destruction. Modern treatment attempts to improve pathophysiological and biochemical mechanisms damaged by the disease. However, due to the RA patient heterogeneity personalized approach to treatment is required; the choice of personalized treatment is complicated by the variability of patient's response to treatment. Gene expression analysis might serve a tool for the disease control and therapy personification for inhibition of inflammation and pain as well as for prevention of joint destruction.

A Novel Circulating miRNA-Based Model Predicts the Response to Tripterysium Glycosides Tablets: Moving Toward Model-Based Precision Medicine in Rheumatoid Arthritis

Accumulating clinical evidence show that not all rheumatoid arthritis (RA) patients benefit to the same extent from a Tripterygium wilfordii Hook F (TwHF)-based therapy-Tripterysium glycosides tablets (TG tablets), which emphasizes the need of predictive biomarkers and tools for drug response. Herein, we integrated TG tablets' response-related miRNA and mRNA expression profiles obtained from the clinical cohort-based microarray, miRNA target prediction, miRNA-target gene coexpression, as well as gene-gene interactions, to identify four candidate circulating miRNA biomarkers that were predictive of response to TG tablets. Moreover, we applied the support vector machines (SVM) algorithm to construct the prediction model for the treatment outcome of TG tablets based on the levels of the candidate miRNA biomarkers, and also confirmed its good performance via both 5-fold cross-validation and the independent clinical cohort validations. Collectively, this circulating miRNA-based biomarker model may assist in screening the responsive RA patients to TG tablets and thus potentially benefit individualized therapy of RA in a daily clinical setting.

Recent development in antihyperalgesic effect of phytochemicals: anti-inflammatory and neuro-modulatory actions

INTRODUCTION

Pain is an unpleasant sensation triggered by noxious stimulation. It is one of the most prevalent conditions, limiting productivity and diminishing quality of life. Non steroidal anti inflammatory drugs (NSAIDs) are widely used as pain relievers in present day practice as pain is mostly initiated due to inflammation. However, due to potentially serious side effects, long term use of these antihyperalgesic drugs raises concern. Therefore there is a demand to search novel medicines with least side effects. Herbal products have been used for centuries to reduce pain and inflammation, and phytochemicals are known to cause fewer side effects. However, identification of active phytochemicals of herbal medicines and clear understanding of the molecular mechanism of their action is needed for clinical acceptance.

MATERIALS AND METHODS

In this review, we have briefly discussed the cellular and molecular changes during hyperalgesia via inflammatory mediators and neuro-modulatory action involved therein. The review includes 54 recently reported phytochemicals with antihyperalgesic action, as per the literature available with PubMed, Google Scholar and Scopus.

CONCLUSION

Compounds of high interest as potential antihyperalgesic agents are: curcumin, resveratrol, capsaicin, quercetin, eugenol, naringenin and epigallocatechin gallate (EGCG). Current knowledge about molecular targets of pain and their regulation by these phytochemicals is elaborated and the scope of further research is discussed.

Classical IL-6 signaling: a promising therapeutic target for pulmonary arterial hypertension

Current therapies for pulmonary arterial hypertension (PAH) provide symptomatic relief and improve prognosis but fall short of improving long-term survival. There is emerging evidence for a role of inflammatory mediators, primarily IL-6, in the pathogenesis of PAH. However, the mechanisms by which IL-6 potentially affects PAH are unknown. In this issue of the JCI, Tamura, Phan, and colleagues identified ectopic upregulation of the membrane-bound IL-6 receptor (IL6R), indicating classical IL-6 signaling in the smooth muscle layer of remodeled vessels in human and experimental PAH. They performed a series of in vitro and in vivo experiments that provide deeper insights into the mechanisms of classical IL-6 signaling and propose interventions directed against IL6R as a potential therapeutic strategy for PAH.

Tocilizumab in the treatment of adult rheumatoid arthritis

Rheumatoid arthritis (RA) is the most prevalent immune-mediated chronic rheumatic disease and is associated with joint destruction and disability. Therapeutic strategies, including biological disease-modifying antirheumatic drugs (bDMARDs) have improved the prognosis and quality of life of RA patients. Tocilizumab (TCZ) is a humanized monoclonal antibody against IL-6 receptor licensed in 2009 that has demonstrated clinical efficacy in various adult RA populations. RA management guidelines and recommendations consider TCZ as one of the bDMARDS indicated after methotrexate or other conventional synthetic DMARDs and/or TNF inhibitors failure in adult RA. Of particular interest is the demonstration of its effectiveness in monotherapy in comparison with other bDMARDs. Recent observational studies have shown good results for the safety profile of TCZ with no new alert signals.

Right drug, right patient, right time: aspiration or future promise for biologics in rheumatoid arthritis?

Individualising biologic disease-modifying anti-rheumatic drugs (bDMARDs) to maximise outcomes and deliver safe and cost-effective care is a key goal in the management of rheumatoid arthritis (RA). Investigation to identify predictive tools of bDMARD response is a highly active and prolific area of research. In addition to clinical phenotyping, cellular and molecular characterisation of synovial tissue and blood in patients with RA, using different technologies, can facilitate predictive testing. This narrative review will summarise the literature for the available bDMARD classes and focus on where progress has been made. We will also look ahead and consider the increasing use of 'omics' technologies, the potential they hold as well as the challenges, and what is needed in the future to fully realise our ambition of personalised bDMARD treatment.

The clinical utility of gene expression examination in rheumatology

Rheumatoid arthritis (RA) is a chronic inflammatory disease with unknown etiology that affects various pathways within the immune system, involves many other tissues and is associated with pain and joint destruction. Current treatments fail to address pathophysiological and biochemical mechanisms involved in joint degeneration and the induction of pain. Moreover, RA patients are extremely heterogeneous and require specific treatments, the choice of which is complicated by the fact that not all patients equally respond to therapy. Gene expression analysis offer tools for patient management and personalization of patient’s care to meet individual needs in controlling inflammation and pain and delaying joint destruction.

Increased baseline RUNX2, caspase 3 and p21 gene expressions in the peripheral blood of disease-modifying anti-rheumatic drug-naïve rheumatoid arthritis patients are associated with improved clinical response to methotrexate therapy

OBJECTIVE

To investigate the potential of the baseline gene expression in the whole blood of disease-modifying anti-rheumatic drug-naïve rheumatoid arthritis (RA) patients for predicting the response to methotrexate (MTX) treatment.

METHODS

Twenty-six control subjects and 40 RA patients were examined. Clinical, immunological and radiographic parameters were assessed before and after 24 months of follow-up. The gene expressions in the whole blood were measured using real-time reverse transcription polymerase chain reaction. The protein concentrations in peripheral blood mononuclear cells were quantified using enzyme-linked immunosorbent assay. Receiver operating characteristic curve analyses were used to suggest thresholds that were associated with the prediction of the response.

RESULTS

Decreases in the disease activity at the end of the study were accompanied by significant increases in joint space narrowing score (JSN). Positive correlations between the expressions of the Unc-51-like kinase 1 (ULK1) and matrix metalloproteinase 9 (MMP-9) genes with the level of C-reactive protein and MMP-9 expression with Disease Activity Score of 28 joints (DAS28) and swollen joint count were noted at baseline. The baseline tumor necrosis factor (TNF)α gene expression was positively correlated with JSN at the end of the follow-up, whereas p21, caspase 3, and runt-related transcription factor (RUNX)2 were correlated with the ΔDAS28 values.

CONCLUSIONS

Our results suggest that the expressions of MMP-9 and ULK1 might be associated with disease activity. Increased baseline gene expressions of RUNX2, p21 and caspase 3 in the peripheral blood might predict better responses to MTX therapy.

Prediction of Response to Targeted Treatment in Rheumatoid Arthritis

Rheumatoid arthritis is an autoimmune syndrome presenting with chronic inflammation of the joints. Patients with the same diagnosis can present with different phenotypes. In some patients severe joint inflammation and early joint destruction are observed, whereas a milder phenotype can be seen in others. Conversely, patients with the same signs and symptoms may exhibit different immunological and molecular abnormalities. Since the introduction of early treatment in clinical practice, the treat to target principle, and new medicines such as biologic disease-modifying antirheumatic drugs, clinical remission can be achieved early in the disease course, albeit not in all patients. The clinical response and efficacy of biologic disease-modifying antirheumatic drugs vary among different individuals. Therefore, there is a need to develop a more personalized approach toward treatment to achieve rapid remission in every patient to prevent disability and restore and maintain quality of life, without unnecessary adverse effects, in a cost-effective manner. The latest data from explorative studies of predictive markers of response are discussed here, together with a preliminary treatment algorithm based on currently available knowledge.