John G. Wesseling

The type I IFN signature as a biomarker of preclinical rheumatoid arthritis

Objectives To validate the presence and demonstrate the clinical value of the type I interferon (IFN)-signature during arthritis development. Method In 115 seropositive arthralgia patients who were followed for the development of arthritis (Amsterdam Reade cohort), and 25 presymptomatic individuals who developed rheumatoid arthritis (RA) later, and 45 population-based controls (Northern Sweden cohort), the expression levels of 7 type I IFN response genes were determined with multiplex qPCR and an IFN-score was calculated. The diagnostic performance of the IFN-score was evaluated using Cox regression and Receiver Operating Characteristics (ROC)-curve analysis. Results In 44 of the 115 at-risk individuals (38%) from the Amsterdam Reade cohort, arthritis developed after a median period of 8 months (IQR 5–13). Stratification of these individuals based on the IFN-score revealed that 15 out of 25 IFNhigh individuals converted to arthritis, compared with 29 out of 90 IFNlow individuals (p=0.011). In the Northern Sweden cohort, the level of the IFN-score was also significantly increased in presymptomatic individuals who developed RA compared with population-based controls (p=0.002). Cox regression analysis of the Amsterdam Reade cohort showed that the hazard ratio (HR) for development of arthritis was 2.38 (p=0.008) for IFNhigh at-risk individuals after correction for anticitrullinated protein antibodies (ACPA) and rheumatoid factor (RF). The ROC-curve area under the curve (AUC) for the IFN-score combined with ACPA and RF in the prediction of arthritis was 78.5% (p=0.0001, 95% CI 0.70 to 0.87). Conclusions The results demonstrated clinical utility for the IFN-signature as a biomarker in the prediction of arthritis development.

Physiological evidence for diversification of IFNα- and IFNβ-mediated response programs in different autoimmune diseases

BackgroundActivation of the type I interferon (IFN) response program is described for several autoimmune diseases, including systemic lupus erythematosus (SLE), multiple sclerosis (MS), myositis (IIM) and rheumatoid arthritis (RA). While IFNα contributes to SLE pathology, IFNβ therapy is often beneficial in MS, implying different immunoregulatory roles for these IFNs. This study was aimed to investigate potential diversification of IFNα-and IFNβ-mediated response programs in autoimmune diseases.MethodsPeripheral blood gene expression of 23 prototypical type I IFN response genes (IRGs) was determined in 54 healthy controls (HCs), 69 SLE (47 test, 22 validation), 149 IFNβ-treated MS (71 test, 78 validation), 160 untreated MS, 78 IIM and 76 RA patients. Patients with a type I IFN signature were selected for analysis.ResultsWe identified IFNα- and IFNβ-specific response programs (GC-A and GC-B, respectively) in SLE and IFNβ-treated MS patients. Concordantly, the GC-A/GC-B log-ratio was positive for all SLE patients and negative for virtually all IFNβ-treated MS patients, which was confirmed in additional cohorts. Applying this information to other autoimmune diseases, IIM patients displayed positive GC-A/GC-B log-ratios, indicating predominant IFNα activity. The GC-A/GC-B log-ratio in RA was lower and approached zero in part of the patients, implying relative importance of both clusters. Remarkably, GC-A/GC-B log-ratios appeared most heterogeneous in untreated MS; half of the patients displayed GC-A dominance, whereas others showed GC-B dominance or log-ratios near zero.ConclusionsOur findings show diversification of the type I IFN response in autoimmune diseases, suggesting different pathogenic roles of the type I IFNs.

B cell signature contributes to the prediction of RA development in patients with arthralgia.

Early recognition followed by treatment of rheumatoid arthritis (RA) helps to maintain joint integrity and functional capacity,1 suggesting it may be beneficial to intervene in patients with arthralgia before RA develops. Anticitrullinated protein antibodies (ACPA) and rheumatoid factor (RF) are established predictive markers,2 ,3 but only 20–40% of ACPA and/or RF positive patients with arthralgia develop RA within 2 years.4 Recently, we have demonstrated that the type I interferon (IFN) signature correctly identifies 52% of patients with arthralgia who will develop RA within 2 years.5 ,6 Our previous study suggested that a B cell related gene signature was associated with protection against arthritis development,6 and could aid in the prediction of arthritis development. We therefore studied the clinical value of the B cell signature, comprising CD19, CD20, CD79α and CD79β, for the prediction of arthritis development in an independent cohort of 115 ACPA and/or RF positive patients with arthralgia followed for median 22 months5 and explored the phenotypical nature of this B cell signature. In total, 44 patients (38%) developed arthritis (defined as one or more swollen joints) within 2 years. Of these, 4 patients had undifferentiated arthritis and 40 patients fulfilled the 2010 American College of Rheumatology (ACR)/ European League Against Rheumatism (EULAR) criteria for RA. Patients were stratified into B cellhigh …

A1.7 Interferon and B-Cell Gene Signatures Contribute to Diagnosis of Pre-Clinical Rheumatoid Arthritis

Background/Objective Early diagnosis of the preclinical phase of rheumatoid arthritis (pre-RA) allows timely start of treatment with the potential to prevent disease progression. It is known that antibodies against citrullinated proteins (ACPA) and rheumatoid factor (RF) have diagnostic value to identify pre-RA. However, since only 20–40% of ACPA+/RF+ arthralgia patients develop arthritis within 5 years, better prognostic markers are needed. Recently, we demonstrated involvement of interferon (IFN) response and B-cell gene signatures in pre-RA. The objective is to demonstrate the value of these signatures to diagnose pre-RA. Methods Peripheral blood (Paxgene) was collected from 115 ACPA+/RF+ arthralgia patients who were clinically followed for arthritis development, one or more swollen joints, with a mean follow-up time of 23 months (IQR 12–30). An IFN and B-cell score was calculated based on 7 Type I IFN response genes and 3 B-cell related genes, respectively, measured by multiplex qPCR. Cox regression analysis and Receiver Operating Characteristic (ROC)-curve analysis were used to demonstrate prognostic and diagnostic significance. Results Out of 115 arthralgia patients 44 developed arthritis after a median time of 8 months (IQR 5–13). Stratification of these individuals based on the IFN score revealed that 60% of the IFNhigh patients converted to arthritis compared to 32% in IFNlow patients (P = 0.011). For the B-cell signature, 58% in B-celllow patients developed arthritis, compared to 33% of B-cellhigh patients (P = 0.020). Combined analysis revealed a significant high risk for arthritis development in IFNhigh/B-celllow patients (80%, hazard ratio (HR) 6.22, P = 0.003) and a low risk for IFNlow/B-cellhigh patients (26%, HR 0.16, P = 0.003). To demonstrate clinical utility a ROC-curve was constructed of ACPA+/RF+ alone and in combination with both signatures. The area under the curve reached 0.619 (P = 0.032, CI 0.514–0.724) for ACPA+/RF+ and increased to 0.803 (P = 0.0001, CI 0.718–0.888) with IFN and B-cell signatures included. The sensitivity to diagnose pre-RA increased from 16% to 52% when both signatures are included, with a cut-off of 94% specificity. Conclusions These findings demonstrate the clinical value of IFN and B-cell gene signatures as biomarkers for the diagnosis of pre-RA. This research was supported by the Center for Translational Molecular Medicine (CTMM) consortium “TRACER”.

A6.12 Physiological evidence for diversification of IFNα- and IFNβ-mediated response programs in different autoimmune diseases

Background and objectives Upregulation of type I IFN response genes is described for several autoimmune diseases, including systemic lupus erythematosus (SLE), multiple sclerosis (MS), myositis (IIM) and rheumatoid arthritis (RA). While IFNα contributes to SLE pathology, IFNβ therapy is beneficial in MS, implying different immunoregulatory roles for these IFNs. This study aimed to investigate potential diversification of IFNα-and IFNβ-mediated response programs in autoimmune diseases. Materials and methods Peripheral blood gene expression of 23 prototypical type I IFN response genes (IRGs) was determined in healthy controls (HCs, n = 54), SLE (n = 47), IFNβ-treated MS (n = 71), untreated MS (n = 160), IIM (n = 78) and RA patients (n = 76). An IFN score was calculated and patients with a type I IFN signature (IFN score >mean+2SD in HC) were selected for analysis. Results We identified IFNα- and IFNβ-specific response programs by comparing IRG expression in SLE (IFNα-mediated) and IFNβ-treated MS patients. Statistical testing revealed increased expression of 5 IRGs in SLE (Gene cluster (GC-)A, p ≤ 0.006) and 13 IRGs in IFNβ-treated MS (Gene cluster (GC-)B, p ≤ 0.044). Concordantly, the GC-A/GC-B log-ratio was positive for all SLE patients and negative for virtually all IFNβ-treated MS patients. Applying this information to other autoimmune diseases, IIM patients displayed positive GC-A/GC-B log-ratios, indicating predominant IFNα activity. The GC-A/GC-B log-ratios in RA were lower and approached zero in part of the patients, implying relative importance of both clusters. Remarkably, GC-A/GC-B log-ratios appeared most heterogeneous in IFNβ-naive MS; half of the patients displayed GC-A dominance, whereas others showed GC-B dominance or log-ratios near zero. We confirmed these results for SLE, RA and MS using two public microarray datasets containing 22 SLE patients, 112 RA patients, 58 IFNβ-treated MS patients and 62 untreated MS patients. Exploring functional differences between GC-A and GC-B genes revealed enrichment of the ISGF3-binding response element ISRE and IRF8 binding sites only in GC-B, suggesting that IFNβ is more potent in activating these transcription factors than IFNα. Conclusions Conclusively, we demonstrated that type I IFN signatures in autoimmune diseases appear less uniform than generally assumed. The diversification of the type I IFN response in autoimmune diseases suggests different pathogenic roles of the type I IFNs.

OP0020 Validation of gene signatures to predict rheumatoid arthritis development

Background Early recognition of development of rheumatoid arthritis (RA) allows timely start of treatment. It is known that antibodies against citrullinated proteins (ACPA) and rheumatoid factor (RF) have a predictive value for development of RA within 5 years. Since only 20-40% of ACPA+ and/or RF+ seropositive arthralgia patients develop arthritis, better prognostic markers are required. Recently, we reported gene signatures in the peripheral blood (PB), involving interferon (IFN) response gene activity and B-cell related genes, which are associated with the development of arthritis. Objectives The objective of this study is to validate the signatures of IFN response gene activity and B-cell related genes in independent cohorts. Methods PB samples of an independent group of 40 seropositive arthralgia patients from the Amsterdam Reade cohort who are clinically followed for arthritis development were analyzed for their IFN-response gene activity, defined as a score based on the average expression of 7 IFN-response genes. In addition PB mononuclear cells (MCs) of 22 pre-onset RA, 25 RA patients and 48 population based controls (PC) from the Medical Biobank of Northern Sweden (Umeå) were studied. FACS-analysis for B-cell markers expression was performed on PB from 87 seropositive arthralgia patients and 30 healthy controls (HC) from the Amsterdam Reade cohort. qPCR for B-cell markers expression was performed in 45 seropositive arthralgia patients and 6 HC from the Amsterdam Reade cohort. Results Of the 40 seropositive arthralgia patients analyzed for INF-scores, 19 developed arthritis within a median period of 11 months (IQR 9-28). Comparative analysis of INF-score high and low patients confirmed that an increased IFN-score is associated with conversion to arthritis (p=0.025). In addition, the IFN-score was measured in PBMC from RA, pre-onset RA patients and PC from the Medical Biobank of Northern Sweden. Comparative analyses between the groups revealed that both pre-onset RA patients as well as RA patients had significantly increased IFN-scores compared to HC (Mann-Whitney U test p=0.006 and p=0.008, respectively). Of the 87 seropositive arthralgia patients analyzed for B-cell marker expression, 22 developed arthritis within a median period to conversion of 11 months (IQR 5-13). Low B-cell markers expression was significantly associated with conversion to arthritis (p=0.01). An interim analysis with qPCR showed a strong trend towards decreased B-cell transcript markers and arthritis conversion (p=0.07). Conclusions These results provide evidence for the validation for a role of IFN-activity and low B-cell presence in the preclinical phase of RA. Further studies are aimed to demonstrate the diagnostic value of these markers. Acknowledgements This research was supported by the Center for Translational Molecular Medicine (CTMM) consortium “TRACER”. Disclosure of Interest None Declared

FRI0101 The value of gene signatures in the diagnosis of pre-clinical ra

Background Diagnosis of the preclinical phase of rheumatoid arthritis (RA) allows timely start of treatment with the potential to prevent disease progression. It is known that antibodies against citrullinated proteins (ACPA) and rheumatoid factor (RF) have diagnostic value to identify pre-clinical RA. However, since only 20-40% of ACPA+/RF+ arthralgia patients develop arthritis within 5 years, better prognostic markers are needed. Recently, we demonstrated involvement of Interferon (IFN) response and B-cell gene signatures in pre-clinical RA. Objectives The objective of this study is to demonstrate the diagnostic value of the IFN and B-cell gene signatures in the diagnosis of pre-clinical RA. Methods Peripheral blood (Paxgene) was collected from 115 ACPA+/RF+ arthralgia patients from the Jan van Breemen Research Institute | Reade Amsterdam. Patients where clinically followed for arthritis development, one or more swollen joints, with a mean follow-up time of 23 months (IQR 12-30). IFN response and B-cell related gene expression was measured by multiplex qPCRs. An IFN score was calculated based on 7 highly correlating Type I IFN response genes. A B-cell score was calculated based on three highly correlating B-cell related genes. Cut-off levels for the IFN and B-cell high or low definition were determined by the 85% specificity of the individual IFN and B-cell Receiver Operating Characteristics (ROC)-curves. Cox regression analysis and ROC-curve analysis were used to demonstrate prognostic and diagnostic significance. Results Out of 115 arthralgia patients 44 developed arthritis after a median time of 8 months (IQR 5-13). Stratification of these individuals based on the IFN score revealed that 60% of the IFNhigh patients converted to arthritis compared to 32% in IFNlow patients (P=0.011). For the B-cell signature, 58% in B-celllow patients developed arthritis, compared to 33% of B-cellhigh patients (P=0.020). Combined analysis revealed a significant high risk for arthritis development in IFNhigh/B-celllow patients (80%, hazard ratio (HR)(6.22, P=0.003) and a low risk for IFNlow/B-cellhigh patients (26%, HR 0.16, P=0.003). To demonstrate clinical utility a ROC-curve was constructed of ACPA+/RF+ alone and in combination with both signatures. The area under the curve reached 0.619 (P=0.032, C.I. 0.514-0.724) for ACPA+/RF+ and increased to 0.803 (P=0.0001, C.I. 0.718-0.888) with IFN and B-cell signatures included. The sensitivity to diagnose pre-clinical RA increased from 16% to 52% when both signatures are included, with a cut-off of 94% specificity. Conclusions These findings demonstrate the clinical value of IFN and B-cell gene signatures as biomarkers for the diagnosis of pre-clinical RA. Acknowledgements This research was supported by the Center for Translational Molecular Medicine (CTMM) consortium “TRACER”. Disclosure of Interest J. Lubbers Grant/research support from: CTMM TRACER, L. van de Stadt Grant/research support from: Dutch Arthritis Foundation, S. Vosslamber: None Declared, J. G. Wesseling Grant/research support from: CTMM TRACER, D. van Schaardenburg Grant/research support from: Dutch Arthritis Foundation, C. Verweij Grant/research support from: CTMM TRACER

Interferons overrule the TNF-induced proliferation of rheumatoid fibroblast-like synoviocytes

Objectives Tumour necrosis factor α (TNF-α) and interferons (IFNs), which are abundantly present in the rheumatoid synovium, are thought to exert two opposing effects on RA pathology. We studied the opposing effects of IFNs and TNF on the proliferative capacity of rheumatoid fibroblast-like synoviocytes (FLS). Methods IFN and/or TNF induced changes in FLS gene expression were measured by DNA-microarray analysis and data was analysed using Significance Analysis of Microarrays (SAM) and pathway analysis using PANTHER. Activation of STAT-1 was determined by immunofluorescence and real-time PCR. FLS proliferation was monitored by 3H-thymidine incorporation. Apoptosis was determined by staining with Annexin V and propidium iodide (PI). Staining with PI was also used to analyse cell cycle distribution. Expression of GADD45β mRNA was measured by real-time PCR. Results Gene expression profiling of IFN-stimulated rheumatoid FLS provided evidence for inhibition of cell cycle regulation. Accordingly, IFN stimulation resulted in a >50% decrease in DNA synthesis. The inhibitory effect was not due to induction of apoptosis but was shown to be the consequence of limited cell cycle progression due to accumulation of cells in G0/1 phase. The inhibitory effect overruled TNFα-induced cell cycle progression to G2/M phase and proliferation. This effect correlated with expression of the Growth-Arrest and DNA Damage-Inducible gene GADD45β. Conclusion These results indicate that IFN-induced inhibition of cell cycle progression in rheumatoid FLS overrules TNFα-induced proliferative effects. Funding This work has been supported by the EU Marie Curie Training Network (EURO-RA), the EU integrated program AUTOCURE, and CMSB (Netherlands Centre of Excellenc on Genomics Research)