Expression of a pathogen-response program in peripheral blood cells defines a subgroup of Rheumatoid Arthritis patients

Role of IFN-α in Rheumatoid Arthritis

PURPOSE OF REVIEW

Type 1 interferons (IFN-I) are of increasing interest across a wide range of autoimmune rheumatic diseases. Historically, research into their role in rheumatoid arthritis (RA) has been relatively neglected, but recent work continues to highlight a potential contribution to RA pathophysiology.

RECENT FINDINGS

We emphasise the importance of disease stage when examining IFN-I in RA and provide an overview on how IFN-I may have a direct role on a variety of relevant cellular functions. We explore how clinical trajectory may be influenced by increased IFN-I signalling, and also, the limitations of scores composed of interferon response genes. Relevant environmental triggers and inheritable RA genetic risk relating to IFN-I signalling are explored with emphasis on intriguing data potentially linking IFN-I exposure, epigenetic changes, and disease relevant processes. Whilst these data cumulatively illustrate a likely role for IFN-I in RA, they also highlight the knowledge gaps, particularly in populations at risk for RA, and suggest directions for future research to both better understand IFN-I biology and inform targeted therapeutic strategies.

IFI44 is an immune evasion biomarker for SARS-CoV-2 and Staphylococcus aureus infection in patients with RA

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic of severe coronavirus disease 2019 (COVID-19). Staphylococcus aureus is one of the most common pathogenic bacteria in humans, rheumatoid arthritis (RA) is among the most prevalent autoimmune conditions. RA is a significant risk factor for SARS-CoV-2 and S. aureus infections, although the mechanism of RA and SARS-CoV-2 infection in conjunction with S. aureus infection has not been elucidated. The purpose of this study is to investigate the biomarkers and disease targets between RA and SARS-CoV-2 and S. aureus infections using bioinformatics analysis, to search for the molecular mechanisms of SARS-CoV-2 and S. aureus immune escape and potential drug targets in the RA population, and to provide new directions for further analysis and targeted development of clinical treatments.

Methods

The RA dataset (GSE93272) and the S. aureus bacteremia (SAB) dataset (GSE33341) were used to obtain differentially expressed gene sets, respectively, and the common differentially expressed genes (DEGs) were determined through the intersection. Functional enrichment analysis utilizing GO, KEGG, and ClueGO methods. The PPI network was created utilizing the STRING database, and the top 10 hub genes were identified and further examined for functional enrichment using Metascape and GeneMANIA. The top 10 hub genes were intersected with the SARS-CoV-2 gene pool to identify five hub genes shared by RA, COVID-19, and SAB, and functional enrichment analysis was conducted using Metascape and GeneMANIA. Using the NetworkAnalyst platform, TF-hub gene and miRNA-hub gene networks were built for these five hub genes. The hub gene was verified utilizing GSE17755, GSE55235, and GSE13670, and its effectiveness was assessed utilizing ROC curves. CIBERSORT was applied to examine immune cell infiltration and the link between the hub gene and immune cells.

Results

A total of 199 DEGs were extracted from the GSE93272 and GSE33341 datasets. KEGG analysis of enrichment pathways were NLR signaling pathway, cell membrane DNA sensing pathway, oxidative phosphorylation, and viral infection. Positive/negative regulation of the immune system, regulation of the interferon-I (IFN-I; IFN-α/β) pathway, and associated pathways of the immunological response to viruses were enriched in GO and ClueGO analyses. PPI network and Cytoscape platform identified the top 10 hub genes: RSAD2, IFIT3, GBP1, RTP4, IFI44, OAS1, IFI44L, ISG15, HERC5, and IFIT5. The pathways are mainly enriched in response to viral and bacterial infection, IFN signaling, and 1,25-dihydroxy vitamin D3. IFI44, OAS1, IFI44L, ISG15, and HERC5 are the five hub genes shared by RA, COVID-19, and SAB. The pathways are primarily enriched for response to viral and bacterial infections. The TF-hub gene network and miRNA-hub gene network identified YY1 as a key TF and hsa-mir-1-3p and hsa-mir-146a-5p as two important miRNAs related to IFI44. IFI44 was identified as a hub gene by validating GSE17755, GSE55235, and GSE13670. Immune cell infiltration analysis showed a strong positive correlation between activated dendritic cells and IFI44 expression.

Conclusions

IFI144 was discovered as a shared biomarker and disease target for RA, COVID-19, and SAB by this study. IFI44 negatively regulates the IFN signaling pathway to promote viral replication and bacterial proliferation and is an important molecular target for SARS-CoV-2 and S. aureus immune escape in RA. Dendritic cells play an important role in this process. 1,25-Dihydroxy vitamin D3 may be an important therapeutic agent in treating RA with SARS-CoV-2 and S. aureus infections.

Regulation of type I interferon signature by VGLL3 in the fibroblast-like synoviocytes of rheumatoid arthritis patients via targeting the Hippo pathway

Background

The upregulation of interferon (IFN)-stimulated genes induced by type I IFNs (namely type I IFN signature) in rheumatoid arthritis (RA) patients had implications in early diagnosis and prediction of therapy responses. However, factors that modulate the type I IFN signature in RA are largely unknown. In this study, we aim to explore the involvement of VGLL3, a homologue of the vestigial-like gene in Drosophila and a putative regulator of the Hippo pathway, in the modulation of type I IFN signature in the fibroblast-like synoviocytes (FLS) of RA patients.

Methods

FLS were isolated from RA and osteoarthritis (OA) patients. Expression of VGLL3 in the synovial tissues and FLS was analyzed by immunohistochemistry and PCR. RNA sequencing was performed in RA-FLS upon VGLL3 overexpression. The expression of IFN-stimulated genes was examined by PCR and Western blotting.

Results

VGLL3 was upregulated in the RA synovium and RA-FLS compared to OA. Overexpression of VGLL3 promoted the expression of IFN-stimulated genes in RA-FLS. The expression of STAT1 and MX1 was also upregulated in RA synovium compared to OA and was associated with the expression of VGLL3 in RA and OA patients. VGLL3 promoted the IRF3 activation and IFN-β1 expression in RA-FLS. Increased IFN-β1 induced the expression of IFN-stimulated genes in RA-FLS in an autocrine manner. VGLL3 also modulated the expression of the Hippo pathway molecules WWTR1 and AMOTL2, which mediated the regulation of IRF3 activation and IFN-β1 production by VGLL3 in RA-FLS.

Conclusions

VGLL3 drives the IRF3-induced IFN-β1 expression in RA-FLS by inhibiting WWTR1 expression and subsequently promotes the type I IFN signature expression in RA-FLS through autocrine IFN-β1 signaling.

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.

Pentosan polysulfate sodium prevents functional decline in chikungunya infected mice by modulating growth factor signalling and lymphocyte activation

Chikungunya virus (CHIKV) is an arthropod-borne virus that causes large outbreaks world-wide leaving millions of people with severe and debilitating arthritis. Interestingly, clinical presentation of CHIKV arthritides have many overlapping features with rheumatoid arthritis including cellular and cytokine pathways that lead to disease development and progression. Currently, there are no specific treatments or vaccines available to treat CHIKV infections therefore advocating the need for the development of novel therapeutic strategies to treat CHIKV rheumatic disease. Herein, we provide an in-depth analysis of an efficacious new treatment for CHIKV arthritis with a semi-synthetic sulphated polysaccharide, Pentosan Polysulfate Sodium (PPS). Mice treated with PPS showed significant functional improvement as measured by grip strength and a reduction in hind limb foot swelling. Histological analysis of the affected joint showed local inflammation was reduced as seen by a decreased number of infiltrating immune cells. Additionally, joint cartilage was protected as demonstrated by increased proteoglycan staining. Using a multiplex-immunoassay system, we also showed that at peak disease, PPS treatment led to a systemic reduction of the chemokines CXCL1, CCL2 (MCP-1), CCL7 (MCP-3) and CCL12 (MCP-5) which may be associated with the reduction in cellular infiltrates. Further characterisation of the local effect of PPS in its action to reduce joint and muscle inflammation was performed using NanoString™ technology. Results showed that PPS altered the local expression of key functional genes characterised for their involvement in growth factor signalling and lymphocyte activation. Overall, this study shows that PPS is a promising treatment for alphaviral arthritis by reducing inflammation and protecting joint integrity.

Type I interferon detection in autoimmune diseases: challenges and clinical applications

INTRODUCTION

Accumulating data highlights that the dysregulation of type I interferon (IFN) pathways plays a central role in the pathogenesis of several systemic and organ-specific autoimmune diseases. Advances in understanding the role of type I IFNs in these disorders can lead to targeted drug development as well as establishing potential disease biomarkers.

AREAS COVERED

Here, we summarize current knowledge regarding the role of type I IFNs in the major systemic, as well as organ-specific, autoimmune disorders, including prominent inflammatory CNS disorders like multiple sclerosis.

EXPERT OPINION

Type I IFN involvement and its clinical associations in a wide spectrum of autoimmune diseases represents a promising area for research aiming to unveil common pathogenetic pathways in systemic and organ-specific autoimmunity.

Next-Generation Sequencing Profiles of the Methylome and Transcriptome in Peripheral Blood Mononuclear Cells of Rheumatoid Arthritis

Using next-generation sequencing to decipher methylome and transcriptome and underlying molecular mechanisms contributing to rheumatoid arthritis (RA) for improving future therapies, we performed methyl-seq and RNA-seq on peripheral blood mononuclear cells (PBMCs) from RA subjects and normal donors. Principal component analysis and hierarchical clustering revealed distinct methylation signatures in RA with methylation aberrations noted across chromosomes. Methylation alterations varied with CpG features and genic characteristics. Typically, CpG islands and CpG shores were hypermethylated and displayed the greatest methylation variance. Promoters were hypermethylated and enhancers/gene bodies were hypomethylated, with methylation variance associated with expression variance. RA genetically associated genes preferentially displayed differential methylation and differential expression or interacted with differentially methylated and differentially expressed genes. These differentially methylated and differentially expressed genes were enriched with several signaling pathways and disease categories. 10 genes (CD86, RAB20, XAF1, FOLR3, LTBR, KCNH8, DOK7, PDGFA, PITPNM2, CELSR1) with concomitantly differential methylation in enhancers/promoters/gene bodies and differential expression in B cells were validated. This integrated analysis of methylome and transcriptome identified novel epigenetic signatures associated with RA and highlighted the interaction between genetics and epigenetics in RA. These findings help our understanding of the pathogenesis of RA and advance epigenetic studies in regards to the disease.

IRF4 and IRGs Delineate Clinically Relevant Gene Expression Signatures in Systemic Lupus Erythematosus and Rheumatoid Arthritis

Introduction: Overactivation of the type I interferon (IFN) signature has been observed in several systemic autoimmune conditions, such as Systemic Lupus Erythematosus (SLE) or Rheumatoid Arthritis (RA). Impaired control of Interferon-Responding Genes (IRGs) expression by their regulatory mechanisms, including Interferon Regulatory Factors (IRFs), may underlie these findings and it may explain the heterogeneity observed among these conditions. In the present study we aimed to evaluate the associations between IRF4 gene expression and those of IRGs in SLE and RA patients to gain insight about its links with the IFN signature as well as to explore the potential clinical relevance of these associations.

Methods: The gene expression of IRF4 and IRGs (IFI44, IFI44L, IFI6, and MX1) in peripheral blood was analyzed in 75 SLE patients, 98 RA patients, and 28 healthy controls. A group of 13 biological-naïve RA patients was prospectively followed upon TNFα-blockade. The associations among IRF4 and IRGs were evaluated by principal component analyses (PCA), correlations and network analyses. Publicly available datasets were used for replication.

Results: A broad activation of IRGs was observed in autoimmune patients, although certain heterogeneity can be distinguished, whereas IRF4 was only upregulated in RA. The differential expression of IRF4 in RA was then confirmed in publicly available gene expression datasets. PCA revealed different associations among IRF4 and IRGs in each condition, which was later confirmed by correlation and network analyses. Cluster analysis identified 3 gene expression signatures on the basis of IRF4 and IRGs expression which were differentially used by SLE and RA patients. Cluster III was associated with markers of disease severity in SLE patients. Cluster II, hallmarked by IRF4 upregulation, was linked to clinical stage and mild disease course in RA. TNFα-blockade led to changes in the association between IRF4 and IRGs, whereas increasing IRF4 expression was associated with a good clinical outcome in RA.

Conclusions: The differential expression of IRF4 and IRGs observed in SLE and RA can delineate gene expression signatures associated with clinical features and treatment outcomes. These results support a clinically-relevant phenomenon of shaping of the IFN signature by IRF4 in autoimmune patients.

Heterogeneity of the Type I Interferon Signature in Rheumatoid Arthritis: A Potential Limitation for Its Use As a Clinical Biomarker

INTRODUCTION

An increased expression of interferon (IFN)-responding genes (IRGs), the so-called IFN signature, has been reported in rheumatoid arthritis (RA). However, some controversy exists concerning its clinical relevance. The main aim of this study is to evaluate whether quantitative and qualitative differences in the activation of the IFN pathway may account for these findings.

METHODS

The expression of IFN-induced protein 44 (IFI44), IFN-induced protein 44 like (IFI44L), IFN alpha inducible protein 6, and MX dynamin-like GTPase 1 (MX1) was determined in peripheral blood in 98 RA patients (IFI6) and 28 controls. RA patients were classified into groups according to their clinical stage and treatments received: very early RA (VERA), biological disease-modifying antirheumatic drug (bDMARD) naive, and bDMARD. An additional group of 13 RA patients candidates for tumor necrosis factor alpha (TNFα) blockade was also recruited. The associations among IRGs were evaluated by network and principal component analyses.

RESULTS

The expression of all IRGs was increased in RA to different levels. The IFN score was increased in all RA groups (VERA, bDMARD-naïve, and bDMARD), but important differences in their degree of activation and in the relationships among IRGs were observed. The IFN score correlated with the accumulated disease activity score 28-joints, and it was found to be a predictor of clinical outcome in VERA. No differences in the IFN score were observed between the bDMARD-naive and bDMARD groups, but opposite associations with the clinical parameters were noted. Interestingly, the correlations among IRGs delineate different pictures between these two groups. The IFN score at baseline predicted poor clinical outcome upon TNFα blockade. Although no absolute changes in the IFN score were found, TNFα-blockade shifted the associations among IRGs.

CONCLUSION

A certain heterogeneity within the IFN signature can be recognized in RA, depending on the clinical stage. The structure of the IFN signature may be a potential explanation for the controversy in this field and must be considered to decipher its clinical relevancein RA.

Do Type I Interferons Link Systemic Autoimmunities and Metabolic Syndrome in a Pathogenetic Continuum?

The central pathogenetic role of type I interferons (IFNs) in several systemic autoimmune diseases is well established. Recent studies have also discovered a similar crucial role of type I IFNs in different components of metabolic disorders. Self nucleic acid-driven Toll-like receptor (TLR) activation in plasmacytoid dendritic cells (pDCs) and type I IFN induction appear to be the key initiating events shared by most of these autoimmune and metabolic diseases. Further strengthening this link, many patients with systemic autoimmunities also present with metabolic disorders. This concurrence of autoimmunities and metabolic disorders may be explained by a single pathogenetic continuum, and suggests shared targets for potential new therapies.

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.

Type I interferon response gene expression in established rheumatoid arthritis is not associated with clinical parameters

Background

A peripheral blood interferon (IFN) signature (i.e., elevated type I interferon response gene [IRG] expression) has been described in a subset of patients with rheumatoid arthritis (RA). In the present study, we systematically assessed the association between this IRG expression and clinical parameters.

Methods

Expression of 19 IRGs was determined in peripheral blood from 182 consecutive patients with RA and averaged into an IFN score per individual. Correlation and unpaired analyses were performed on the complete patient group. The analyses were internally validated by using an algorithm to randomize the patient group 1000 times into two equally sized sets, and then analyses were performed on both sets.

Results

Associations were assessed between IFN score and disease duration, 28-joint Disease Activity Score and its components, the occurrence of erosions and nodules, autoantibody positivity, and immunosuppressive treatment. This analysis revealed lower IFN scores in patients using hydroxychloroquine, prednisone, and/or sulfasalazine, but it did not show significant associations between the other parameters and the IFN score. Selecting patients who were not treated with hydroxychloroquine, prednisone, and/or sulfasalazine (n = 95) did not reveal any significant associations either.

Conclusions

IRG expression in RA is affected by immunosuppressive treatment with prednisone, hydroxychloroquine, and/or sulfasalazine, but it is not evidently associated with other clinical parameters. Hence, the IFN signature appears to describe a subgroup of patients with RA but does not seem to reflect disease activity.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-016-1191-y) contains supplementary material, which is available to authorized users.

Effect of prednisone on type I interferon signature in rheumatoid arthritis: consequences for response prediction to rituximab

Introduction

Elevated type I interferon (IFN) response gene (IRG) expression has proven clinical relevance in predicting rituximab non-response in rheumatoid arthritis (RA). Interference between glucocorticoids (GCs) and type I IFN signaling has been demonstrated in vitro. Since GC use and dose are highly variable among patients before rituximab treatment, the aim of this study was to determine the effect of GC use on IRG expression in relation to rituximab response prediction in RA.

Methods

In two independent cohorts of 32 and 182 biologic-free RA patients and a third cohort of 40 rituximab-starting RA patients, peripheral blood expression of selected IRGs was determined by microarray or quantitative real-time polymerase chain reaction (qPCR), and an IFN-score was calculated. The baseline IFN-score was tested for its predictive value towards rituximab response in relation to GC use using receiver operating characteristics (ROC) analysis in the rituximab cohort. Patients with a decrease in disease activity score (∆DAS28) >1.2 after 6 months of rituximab were considered responders.

Results

We consistently observed suppression of IFN-score in prednisone users (PREDN⁺) compared to non-users (PREDN⁻). In the rituximab cohort, analysis on PREDN⁻ patients (n = 13) alone revealed improved prediction of rituximab non-response based on baseline IFN-score, with an area under the curve (AUC) of 0.975 compared to 0.848 in all patients (n = 40). Using a group-specific IFN-score cut-off for all patients and PREDN⁻ patients alone, sensitivity increased from 41% to 88%, respectively, combined with 100% specificity.

Conclusions

Because of prednisone-related suppression of IFN-score, higher accuracy of rituximab response prediction was achieved in PREDN⁻ patients. These results suggest that the IFN-score-based rituximab response prediction model could be improved upon implementation of prednisone use.

Type I IFNs as biomarkers in rheumatoid arthritis: towards disease profiling and personalized medicine

RA (rheumatoid arthritis) is a chronic rheumatic condition hallmarked by joint inflammation and destruction by self-reactive immune responses. Clinical management of RA patients is often hampered by its heterogeneous nature in both clinical presentation and outcome, thereby highlighting the need for new predictive biomarkers. In this sense, several studies have recently revealed a role for type I IFNs (interferons), mainly IFNα, in the pathogenesis of a subset of RA patients. Genetic variants associated with the type I IFN pathway have been linked with RA development, as well as with clinical features. Moreover, a role for IFNα as a trigger for RA development has also been described. Additionally, a type I IFN signature has been associated with the early diagnosis of RA and clinical outcome prediction in patients undergoing biological drug treatment, two challenging issues for decision-making in the clinical setting. Moreover, these cytokines have been related to endothelial damage and vascular repair failure in different autoimmune disorders. Therefore, together with chronic inflammation and disease features, they could probably account for the increased cardiovascular disease morbidity and mortality of these patients. The main aim of the present review is to provide recent evidence supporting a role for type I IFNs in the immunopathology of RA, as well as to analyse their possible role as biomarkers for disease management.

Gene expression analysis in RA: towards personalized medicine

Gene expression has recently been at the forefront of advance in personalized medicine, notably in the field of cancer and transplantation, providing a rational for a similar approach in rheumatoid arthritis (RA). RA is a prototypic inflammatory autoimmune disease with a poorly understood etiopathogenesis. Inflammation is the main feature of RA; however, many biological processes are involved at different stages of the disease. Gene expression signatures offer management tools to meet the current needs for personalization of RA patients' care. This review analyses currently available information with respect to RA diagnostic, prognostic and prediction of response to therapy with a view to highlight the abundance of data, whose comparison is often inconclusive due to the mixed use of material source, experimental methodologies and analysis tools, reinforcing the need for harmonization if gene expression signatures are to become a useful clinical tool in personalized medicine for RA patients.

Identification of secreted phosphoprotein 1 gene as a new rheumatoid arthritis susceptibility gene

OBJECTIVE

To evaluate the contribution of the SPP1 rs11439060 and rs9138 polymorphisms, previously reported as autoimmune risk variants, in the rheumatoid arthritis (RA) genetic background according to anti-citrullinated protein antibodies (ACPAs) status of RA individuals.

METHODS

We analysed a total of 11,715 RA cases and 26,493 controls from nine independent cohorts; all individuals were genotyped or had imputed genotypes for SPP1 rs11439060 and rs9138. The effect of the SPP1 rs11439060 and rs9138 risk-allele combination on osteopontin (OPN) expression in macrophages and OPN serum levels was investigated.

RESULTS

We provide evidence for a distinct contribution of SPP1 to RA susceptibility according to ACPA status: the combination of ≥3 SPP1 rs11439060 and rs9138 common alleles was associated mainly with ACPA negativity (p=1.29×10(-5), ORACPA-negative 1.257 (1.135 to 1.394)) and less with ACPA positivity (p=0.0148, ORACPA-positive 1.072 (1.014 to 1.134)). The ORs between these subgroups (ie, ACPA-positive and ACPA-negative) significantly differed (p=7.33×10(-3)). Expression quantitative trait locus analysis revealed an association of the SPP1 risk-allele combination with decreased SPP1 expression in peripheral macrophages from 599 individuals. To corroborate these findings, we found an association of the SPP1 risk-allele combination and low serum level of secreted OPN (p=0.0157), as well as serum level of secreted OPN correlated positively with ACPA production (p=0.005; r=0.483).

CONCLUSIONS

We demonstrate a significant contribution of the combination of SPP1 rs11439060 and rs9138 frequent alleles to risk of RA, the magnitude of the association being greater in patients negative for ACPAs.

The physiologic increase in expression of some type I IFN-inducible genes during pregnancy is not associated with improved disease activity in pregnant patients with rheumatoid arthritis

During pregnancy, most patients with rheumatoid arthritis (RA) experience a spontaneous improvement in their condition. Since type I interferons (IFN) have immunomodulatory properties, we investigated whether type I IFN-inducible genes are upregulated in pregnant patients with RA. Peripheral blood mononuclear cells were evaluated using quantitative real-time polymerase chain reaction for type I IFN-inducible genes (IFI 35, IFI44, IFI44L, IFIT3, OAS1, and Siglec1) in patients with RA and healthy women during and after pregnancy as well as in nonpregnant controls. IFN-alpha and IFN-beta levels in sera of patients and healthy donors were analyzed by enzyme linked immunosorbent assay. It was found that healthy women did not show a change of gene expression levels from the second trimester until postpartum, yet some type I IFN-inducible genes were significantly upregulated in pregnant and postpartum women compared with nonpregnant individuals. In patients with RA, a pronounced upregulation of IFI35 and IFI44 at the second trimester and a peak expression of Siglec1 at the third trimester were observed. Pregnancy levels of IFI35 and IFI44 in patients with RA were higher than those of nonpregnant patients with RA. No significant association of gene expression levels with disease activity was found. In the sera of patients and healthy women, IFN-beta was undetectable and IFN-alpha levels remained stable throughout pregnancy and postpartum. Thus, pregnancy can give rise to an increased expression of type I IFN-inducible genes, reflecting an upregulation of the innate immune system. However, an association of type I IFN-inducible genes with pregnancy induced disease amelioration seems unlikely.

Interferons in autoimmune and inflammatory diseases: regulation and roles

Several lines of evidence strongly implicate type I interferons (IFN-α and β) and IFN-signaling in the pathogenesis of certain autoimmune inflammatory diseases. Accordingly, genome-wide association studies have identified polymorphisms in the type I IFN-signaling pathways. Other studies also indicate that a feed-forward loop of type I IFN production, which involves sensing of cytoplasmic nucleic acids by sensors, contributes to the development of immunopathology. In addition, a mutually positive regulatory feedback loop between type I IFNs and estrogen receptor-α may contribute to a gender bias, thus resulting in an increased production of type I IFNs and associated immunopathology in women. Increased levels of type I IFNs have numerous immunomodulatory functions for both the innate and adaptive immune responses. Given that the IFN-β also has some anti-inflammatory roles, identifying molecular links among certain genotypes, cytokine profiles, and associated phenotypes in patients with autoimmune inflammatory diseases is likely to improve our understanding of autoimmunity-associated pathogenesis and suboptimal outcomes following standard therapies.

Validation study of existing gene expression signatures for anti-TNF treatment in patients with rheumatoid arthritis

So far, there are no means of identifying rheumatoid arthritis (RA) patients who will fail to respond to tumour necrosis factor blocking agents (anti-TNF), prior to treatment. We set out to validate eight previously reported gene expression signatures predicting therapy outcome. Genome-wide expression profiling using Affymetrix GeneChip Exon 1.0 ST arrays was performed on RNA isolated from whole blood of 42 RA patients starting treatment with infliximab or adalimumab. Clinical response according to EULAR criteria was determined at week 14 of therapy. Genes that have been reported to be associated with anti-TNF treatment were extracted from our dataset. K-means partition clustering was performed to assess the predictive value of the gene-sets. We performed a hypothesis-driven analysis of the dataset using eight existing gene sets predictive of anti-TNF treatment outcome. The set that performed best reached a sensitivity of 71% and a specificity of 61%, for classifying the patients in the current study. We successfully validated one of eight previously reported predictive expression profile. This replicated expression signature is a good starting point for developing a prediction model for anti-TNF treatment outcome that can be used in a daily clinical setting. Our results confirm that gene expression profiling prior to treatment is a useful tool to predict anti-TNF (non) response.

A personalized medicine approach to biologic treatment of rheumatoid arthritis: a preliminary treatment algorithm

RA is a syndrome consisting of different pathogenetic subsets in which distinct molecular mechanisms may drive common final pathways. Recent work has provided proof of principle that biomarkers may be identified predictive of the response to targeted therapy. Based on new insights, an initial treatment algorithm is presented that may be used to guide treatment decisions in patients who have failed one TNF inhibitor. Key questions in this algorithm relate to the question whether the patient is a primary vs a secondary non-responder to TNF blockade and whether the patient is RF and/or anti-citrullinated peptide antibody positive. This preliminary algorithm may contribute to more cost-effective treatment of RA, and provides the basis for more extensive algorithms when additional data become available.

Gene expression profiles from discordant monozygotic twins suggest that molecular pathways are shared among multiple systemic autoimmune diseases

INTRODUCTION

The objective of this study is to determine if multiple systemic autoimmune diseases (SAID) share gene expression pathways that could provide insights into pathogenic mechanisms common to these disorders.

METHODS

RNA microarray analyses (Agilent Human 1A(V2) 20K oligo arrays) were used to quantify gene expression in peripheral blood cells from 20 monozygotic (MZ) twin pairs discordant for SAID. Six affected probands with systemic lupus erythematosus (SLE), six with rheumatoid arthritis (RA), eight with idiopathic inflammatory myopathies (IIM), and their same-gendered unaffected twins, were enrolled. Comparisons were made between discordant twin pairs and these were also each compared to 40 unrelated control subjects (matched 2:1 to each twin by age, gender and ethnicity) using statistical and molecular pathway analyses. Relative quantitative PCR was used to verify independently measures of differential gene expression assessed by microarray analysis.

RESULTS

Probands and unrelated, matched controls differed significantly in gene expression for 104 probes corresponding to 92 identifiable genes (multiple-comparison adjusted P values < 0.1). Differentially expressed genes involved several overlapping pathways including immune responses (16%), signaling pathways (24%), transcription/translation regulators (26%), and metabolic functions (15%). Interferon (IFN)-response genes (IFI27, OASF, PLSCR1, EIF2AK2, TNFAIP6, and TNFSF10) were up-regulated in probands compared to unrelated controls. Many of the abnormally expressed genes played regulatory roles in multiple cellular pathways. We did not detect any probes expressed differentially in comparisons among the three SAID phenotypes. Similarly, we found no significant differences in gene expression when comparing probands to unaffected twins or unaffected twins to unrelated controls. Gene expression levels for unaffected twins appeared intermediate between that of probands and unrelated controls for 6535 probes (32% of the total probes) as would be expected by chance. By contrast, in unaffected twins intermediate ordering was observed for 84 of the 104 probes (81%) whose expression differed significantly between probands and unrelated controls.

CONCLUSIONS

Alterations in expression of a limited number of genes may influence the dysregulation of numerous, integrated immune response, cell signaling and regulatory pathways that are common to a number of SAID. Gene expression profiles in peripheral blood suggest that for genes in these critical pathways, unaffected twins may be in a transitional or intermediate state of immune dysregulation between twins with SAID and unrelated controls, perhaps predisposing them to the development of SAID given the necessary and sufficient environmental exposures.

Type I interferon in organ-targeted autoimmune and inflammatory diseases

A significant role for IFNα in the pathogenesis of systemic lupus erythematosus is well supported, and clinical trials of anti-IFNα monoclonal antibodies are in progress in this disease. In other autoimmune diseases characterized by substantial inflammation and tissue destruction, the role of type I interferons is less clear. Gene expression analysis of peripheral blood cells from patients with rheumatoid arthritis and multiple sclerosis demonstrate an interferon signature similar to but less intense than that seen in patients with lupus. In both of those diseases, presence of the interferon signature has been associated with more significant clinical manifestations. At the same time, evidence supports an anti-inflammatory and beneficial role of IFNβ locally in the joints of patients with rheumatoid arthritis and in murine arthritis models, and many patients with multiple sclerosis show a clinical response to recombinant IFNβ. As can also be proposed for type I diabetes mellitus, type I interferon appears to contribute to the development of autoimmunity and disease progression in multiple autoimmune diseases, while maintaining some capacity to control established disease - particularly at local sites of inflammation. Recent studies in both rheumatoid arthritis and multiple sclerosis suggest that quantification of type I interferon activity or target gene expression might be informative in predicting responses to distinct classes of therapeutic agents.

A towards-multidimensional screening approach to predict candidate genes of rheumatoid arthritis based on SNP, structural and functional annotations

Background

According to the Genetic Analysis Workshops (GAW), hundreds of thousands of SNPs have been tested for association with rheumatoid arthritis. Traditional genome-wide association studies (GWAS) have been developed to identify susceptibility genes using a "most significant SNPs/genes" model. However, many minor- or modest-risk genes are likely to be missed after adjustment of multiple testing. This screening process uses a strict selection of statistical thresholds that aim to identify susceptibility genes based only on statistical model, without considering multi-dimensional biological similarities in sequence arrangement, crystal structure, or functional categories/biological pathways between candidate and known disease genes.

Methods

Multidimensional screening approaches combined with traditional statistical genetics methods can consider multiple biological backgrounds of genetic mutation, structural, and functional annotations. Here we introduce a newly developed multidimensional screening approach for rheumatoid arthritis candidate genes that considers all SNPs with nominal evidence of Bayesian association (BFLn > 0), and structural and functional similarities of corresponding genes or proteins.

Results

Our multidimensional screening approach extracted all risk genes (BFLn > 0) by odd ratios of hypothesis H₁ to H₀, and determined whether a particular group of genes shared underlying biological similarities with known disease genes. Using this method, we found 6614 risk SNPs in our Bayesian screen result set. Finally, we identified 146 likely causal genes for rheumatoid arthritis, including CD4, FGFR1, and KDR, which have been reported as high risk factors by recent studies. We must denote that 790 (96.1%) of genes identified by GWAS could not easily be classified into related functional categories or biological processes associated with the disease, while our candidate genes shared underlying biological similarities (e.g. were in the same pathway or GO term) and contributed to disease etiology, but where common variations in each of these genes make modest contributions to disease risk. We also found 6141 risk SNPs that were too minor to be detected by conventional approaches, and associations between 58 candidate genes and rheumatoid arthritis were verified by literature retrieved from the NCBI PubMed module.

Conclusions

Our proposed approach to the analysis of GAW16 data for rheumatoid arthritis was based on an underlying biological similarities-based method applied to candidate and known disease genes. Application of our method could identify likely causal candidate disease genes of rheumatoid arthritis, and could yield biological insights that not detected when focusing only on genes that give the strongest evidence by multiple testing. We hope that our proposed method complements the "most significant SNPs/genes" model, and provides additional insights into the pathogenesis of rheumatoid arthritis and other diseases, when searching datasets for hundreds of genetic variances.

Functional genomics and rheumatoid arthritis: where have we been and where should we go?

Studies in model organisms and humans have begun to reveal the complexity of the transcriptome. In addition to serving as passive templates from which genes are translated, RNA molecules are active, functional elements of the cell whose products can detect, interact with, and modify other transcripts. Gene expression profiling is the method most commonly used thus far to enrich our understanding of the molecular basis of rheumatoid arthritis in adults and juvenile idiopathic arthritis in children. The feasibility of this approach for patient classification (for example, active versus inactive disease, disease subsets) and improving prognosis (for example, response to therapy) has been demonstrated over the past 7 years. Mechanistic understanding of disease-related differences in gene expression must be interpreted in the context of interactions with transcriptional regulatory molecules and epigenetic alterations of the genome. Ongoing work regarding such functional complexities in the human genome will likely bring both insight and surprise to our understanding of rheumatoid arthritis.

Association of the response to tumor necrosis factor antagonists with plasma type I interferon activity and interferon-beta/alpha ratios in rheumatoid arthritis patients: a post hoc analysis of a predominantly Hispanic cohort

OBJECTIVE

Despite the substantial clinical efficacy of tumor necrosis factor alpha (TNFalpha) antagonist therapy in patients with rheumatoid arthritis (RA), some patients respond poorly to such agents. Since an interferon (IFN) signature is variably expressed among RA patients, we investigated whether plasma type I IFN activity might predict the response to TNF antagonist therapy.

METHODS

RA patients (n = 35), the majority of whom were Hispanic, from a single center were evaluated before and after initiation of TNF antagonist therapy. As controls, 12 RA patients from the same center who were not treated with a TNF antagonist were studied. Plasma type I IFN activity was measured using a reporter cell assay, and disease status was assessed using the Disease Activity Score in 28 joints (DAS28). Levels of interleukin-1 receptor antagonist (IL-1Ra) were determined in baseline plasma samples using a commercial enzyme-linked immunosorbent assay. The clinical response was classified according to the European League Against Rheumatism criteria for improvement in RA.

RESULTS

Plasma type I IFN activity at baseline was significantly associated with clinical response (odds ratio 1.36 [95% confidence interval 1.05-1.76], P = 0.020), with high baseline IFN activity associated with a good response. Changes in DAS28 scores were greater among patients with a baseline plasma IFNbeta/alpha ratio >0.8 (indicating elevated plasma IFNbeta levels). Consistent with the capacity of IFNbeta to induce IL-1Ra, elevated baseline IL-1Ra levels were associated with better therapeutic outcomes (odds ratio 1.82 [95% confidence interval 1.1-3.29], P = 0.027).

CONCLUSION

The plasma type I IFN activity, the IFNbeta/alpha ratio, and the IL-1Ra level were predictive of the therapeutic response in TNF antagonist-treated RA patients, indicating that these parameters might define clinically meaningful subgroups of RA patients with distinct responses to therapeutic agents.

Type I interferons have no major influence on humoral autoimmunity in rheumatoid arthritis

OBJECTIVE

Type I IFNs have recently been implicated in autoantibody-mediated diseases such as SLE. As half the RA patients display a type I IFN(high) signature, we investigated in a pilot study if type I IFN determines the autoantibody response in RA.

METHODS

Serum and peripheral blood cells were obtained from 52 RA patients, with paired samples before and after infliximab treatment in 21 patients. Additional samples were collected from 8 anti-citrullinated protein antibody (ACPA)-positive individuals without arthritis and from 10 ACPA-negative healthy controls. The type I IFN signature was determined by peripheral blood cell gene expression analysis and quantitative RT-PCR. ACPA IgG and IgM, RF IgM, anti-nucleosome IgM and anti-dsDNA were measured by ELISA.

RESULTS

The type I IFN signature was not related to the presence and titers of ACPA and RF during active disease. TNF blockade induced a similar rise of ANAs, and a similar decrease in RF titers in both groups. ACPA IgG and IgM levels appeared to be down-modulated only in the type I IFN(low) group. These changes were independent of the changes in type I IFN response gene activity after TNF blockade. Furthermore, the ACPA response in individuals without arthritis and inflammation was not related to an increase of type I IFN.

CONCLUSIONS

In this explorative study, type I IFN signature does not appear to have a major impact on the humoral autoimmune response in RA. Replication of these data remains warranted.

Predicting the development of RA in patients with early undifferentiated arthritis

The rapidity with which bone and cartilage damage occurs in patients with rheumatoid arthritis (RA), and the increasing body of evidence for the effectiveness of early intervention in RA, mean that there is a great need for approaches to accurately predict the development of RA in patients with early undifferentiated arthritis. We will review developments in the prediction of outcome on the basis of clinical and laboratory features, including measures of anti-citrullinated protein/peptide antibody status. Although accurate predictions are possible in the majority of patients using recently developed predictive algorithms which utilize clinical and serological variables, there remains a group of patients for whom it is very difficult to predict the development of RA. The utility of new strategies for prediction will be discussed, including recently discovered genetic associations of RA, an assessment of material from the primary site of pathology (the joint), and assessment using the highly sensitive imaging modalities of ultrasound and magnetic resonance imaging.

Transcription profiling of rheumatic diseases

Rheumatic diseases are a diverse group of disorders. Most of these diseases are heterogeneous in nature and show varying responsiveness to treatment. Because our understanding of the molecular complexity of rheumatic diseases is incomplete and criteria for categorization are limited, we mainly refer to them in terms of group averages. The advent of DNA microarray technology has provided a powerful tool to gain insight into the molecular complexity of these diseases; this technology facilitates open-ended survey to identify comprehensively the genes and biological pathways that are associated with clinically defined conditions. During the past decade, encouraging results have been generated in the molecular description of complex rheumatic diseases, such as rheumatoid arthritis, systemic lupus erythematosus, Sjögren syndrome and systemic sclerosis. Here, we describe developments in genomics research during the past decade that have contributed to our knowledge of pathogenesis, and to the identification of biomarkers for diagnosis, patient stratification and prognostication.

Use and misuse of the gene ontology annotations

The Gene Ontology (GO) project is a collaboration among model organism databases to describe gene products from all organisms using a consistent and computable language. GO produces sets of explicitly defined, structured vocabularies that describe biological processes, molecular functions and cellular components of gene products in both a computer- and human-readable manner. Here we describe key aspects of GO, which, when overlooked, can cause erroneous results, and address how these pitfalls can be avoided.