Search

Systemic lupus erythematosus (SLE) is a complex autoimmune disease, characterised by a breakdown of immune tolerance and the development of autoantibodies against nucleic self-antigens. Immunometabolism is a rapidly expanding scientific field investigating the metabolic programming of cells of the immune system. During the normal immune response, extensive reprogramming of cellular metabolism occurs, both to generate adenosine triphosphate (ATP) and facilitate protein synthesis, and also to manage cellular stress. Major pathways upregulated include glycolysis, oxidative phosphorylation (OXPHOS), the tricarboxylic acid (TCA) cycle, and the pentose phosphate pathway (PPP), among others. Metabolic reprogramming also occurs to aid resolution of inflammation. Immune cells of both patients with SLE and lupus-prone mice are characterised by metabolic abnormalities resulting in an altered functional and inflammatory state. Recent studies have described how metabolic reprogramming occurs in many cell populations in SLE, particularly CD4+ T cells, for example favouring a glycolytic profile by overactivation of the mechanistic target of rapamycin (mTOR) pathway. These advances have led to an increased understanding of the metabolic changes affecting the inflammatory profile of T and B cells, monocytes, dendritic cells, neutrophils, and how they contribute to autoimmunity and SLE pathogenesis. In the current review, we aim to summarise recent advances in the field of immunometabolism involved in SLE, and how these could potentially lead to new therapeutic strategies in the future.

Type I interferons have been suspected for decades to have a crucial role in the pathogenesis of systemic lupus erythematosus (SLE). Evidence has now overturned several long-held assumptions about how type I interferons are regulated and cause pathological conditions, providing a new view of SLE pathogenesis that resolves longstanding clinical dilemmas. This evidence includes data on interferons in relation to genetic predisposition and epigenetic regulation. Importantly, data are now available on the role of interferons in the early phases of the disease and the importance of non-haematopoietic cellular sources of type I interferons, such as keratinocytes, renal tubular cells, glial cells and synovial stromal cells, as well as local responses to type I interferons within these tissues. These local effects are found not only in inflamed target organs in established SLE, but also in histologically normal skin during asymptomatic preclinical phases, suggesting a role in disease initiation. In terms of clinical application, evidence relating to biomarkers to characterize the type I interferon system is complex, and, notably, interferon-blocking therapies are now licensed for the treatment of SLE. Collectively, the available data enable us to propose a model of disease pathogenesis that invokes the unique value of interferon-targeted therapies. Accordingly, future approaches in SLE involving disease reclassification and preventative strategies in preclinical phases should be investigated.

Keratinocyte-mediated interferon production in nonlesional skin drives activation of CD16 + dendritic cells and is associated with cutaneous inflammation in lupus (Billi et al. ).

Background: SLE may be stratified according to a range of different immune assessments but the relationships between these are less well defined. MASTERPLANS is an MRC-funded consortium that seeks to identify immunophenotypic subgroups of patients that predict response to therapy. Objectives: Our objective here was to analyse a clinically well-phenotyped patients using a suite of immune assessments and identify inter-relationships between these features as well as subgroups of patients who may differ in response to therapy. Methods: 143 SLE patients were evaluated for clinical phenotype using BILAG-2004, autoantibodies using radioimmunoprecipitation (IP, University of Bath), two interferon scores (IFN-Score-A and IFN-Score-B), flow cytometry for major circulating immune cell subsets, as well as the surface protein expression of tetherin on each subset, a cell-specific assay for IFN response. Unsupervised hierarchical clustering was used to define autoantibody subgroups. IFN scores (reflected dCT) were compared between the groups using multivariate models. Other variables were compared using Kruskal-Wallis test with pairwise comparisons. Results: Using IP, 141 patients could be divided into five subgroups: U1RNP/Sm+ only (n=23), Ro60+ only (n=8), U1RNP/Sm+Ro60+ (n=6), Ro60+Ro52+La+ (n=11), Ro52+ (n=16) and other ANA (n=77). Antibody subgroups was strongly associated with IFN-Score-A (F=4.39, p=0.001). Expression was lowest for “other ANA”, intermediate for single antibody groups, and highest with multiple positive antibodies. Multivariate linear regression, including interaction terms between antibody types, revealed that Ro60 and U1RNP/Sm were the independent predictors of IFN-Score-A level (p=0.051 and 0.009 respectively). There was no association between autoantibody status and IFN-Score-B (F=0.973, p=0.438). In flow cytometry, the U1RNP/Sm group was notable for significantly lower numbers of CD4-T-cells and memory-B-cells. Memory -B-cells were also lower in antibody-positive groups compared to “other ANA”. Tetherin expression was increased in antibody positive groups, but to a similar extent on most cell subsets. Memory B cell tetherin was significantly higher in the groups with multiple positive antibodies. U1RNP/Sm+ was associated with renal involvement (p=0.004). Mucocutaneous involvement was greater in the Ro60+Ro52+La+ group (p=0.037). Conclusion: This cohort revealed relationships between immune features. U1RNP/Sm antibody was notable for defining a group of patients with a cluster of immune abnormalities, including the greatest elevation of IFN activity, greater abnormalities on flow cytometry and clinical renal involvement. This was independent to the IFN-Score-B high status that predicts better clinical response to rituximab (presented elsewhere at this conference). Future work in MASTERPLANS will investigate the significance of these subgroups for response to therapy. Disclosure of Interests: Marta Aguilar-Zamora: None declared, Hui Lu: None declared, Zoe Betteridge: None declared, Katie Dutton: None declared, Md Yuzaiful Md Yusof: None declared, Antonios Psarras: None declared, The MASTERPLANS Consortium. : None declared, Neil McHugh: None declared, Edward Vital Grant/research support from: He has received honoraria and research grant support from Roche, GSK and AstraZeneca.

Background Cognitive dysfunction is a common problem in autoimmune connective tissue diseases such as SLE that can be screened for using the Montreal Cognitive Assessment (MoCA). The causes of cognitive dysfunction are poorly understood. They may include immune-mediated neurological dysfunction (which should be targeted using immunosuppression) or traditional cardiovascular risk factors (which may be treated as in non-SLE patients). The purpose of this study was to explore these counter-hypotheses in patients with established autoimmune disease by analysing conventional measures of autoimmunity, cardiovascular risk, as well as validated scores for interferon status. Since cumulative organ damage and toxicity of therapy may affect these patients, we also included a cohort of At Risk individuals as previously described.1 Methods We assessed three cohorts: (1) patients with established AI-CTD (SLE, Sjogrens syndrome or undifferentiated CTD >12 months); (2) at risk individuals referred to secondary care due to ANA +and symptoms suggestive of AI-CTD less than 12 months duration; (3) age and sex matched healthy controls. Cognitive dysfunction was tested using the MoCA. Cardiovascular risk was assessed by recording diabetes, hypertension, previous angina or AMI, atrial fibrillation and cholesterol. Type I interferon activity was assessed using a validated two-score system for IFN status previously described.2 Results As expected, the number of patients with an abnormal MOCA score was greater in AI-CTD and At-Risk individuals than in the healthy controls (HC: 20%; At Risk: 39%; SLE: 34%). Also as expected, the IFN scores varied significantly between these groups (p=0.046, F=4.66). We compared parameters between individuals with normal and abnormal MoCA scores within each group and in all groups. Results are shown in table 1. In patients with an AI-CTD, the cognitive function assessed wasnt associated to any of the immune-related but associated with the presence of a cardiovascular risk factor (p=0.04) while CD was associated with anxiety and depression in at risk individuals (p=0.047). A relationship between CD and level of education, gender and current work was also observed. Conclusions In this exploratory study we identified an association between conventional cardiovascular risk factors and cognitive dysfunction. However there was no association between any of the immune parameters and MoCA score. Prevention of cognitive dysfunction in SLE should focus on early identification and treatment of cardiovascular risk. Funding Source(s): None References Md Yusof, et al. ARD 2018. El-Sherbiny, et al. Sci Rep 2018.

Background SLE may be stratified according to a range of different immune assessments but the relationships between these are less well defined. MASTERPLANS is an MRC-funded consortium that seeks to identify immunophenotypic subgroups of patients that predict response to therapy. Our objective here was to analyse a clinically well-phenotyped patients using a suite of immune assessments and identify inter-relationships between these features as well as subgroups of patients who may differ in response to therapy. Methods 143 SLE patients were evaluated for clinical phenotype using BILAG-2004, autoantibodies using radioimmunoprecipitation (IP, University of Bath), two interferon scores (IFN-Score-A and IFN-Score-B), flow cytometry for major circulating immune cell subsets, as well as the surface protein expression of tetherin on each subset, a cell-specific assay for IFN response. Unsupervised hierarchical clustering was used to define autoantibody subgroups. IFN scores (reflected dCT) were compared between the groups using multivariate models. Other variables were compared using Kruskal-Wallis test with pairwise comparisons. Results Using IP, 141 patients could be divided into five subgroups: U1RNP/Sm+only (n=23), Ro60 +only (n=8), U1RNP/Sm+Ro60+ (n=6), Ro60 +Ro52+La+(n=11), Ro52+ (n=16) and other ANA (n=77). Antibody subgroups was strongly associated with IFN-Score-A (F=4.39, p=0.001). Expression was lowest for other ANA, intermediate for single antibody groups, and highest with multiple positive antibodies. Multivariate linear regression, including interaction terms between antibody types, revealed that Ro60 and U1RNP/Sm were the independent predictors of IFN-Score-A level (p=0.051 and 0.009 respectively). There was no association between autoantibody status and IFN-Score-B (F=0.973, p=0.438). In flow cytometry, the U1RNP/Sm group was notable for significantly lower numbers of CD4-T-cells and memory-B-cells. Memory -B-cells were also lower in antibody-positive groups compared to other ANA. Tetherin expression was increased in antibody positive groups, but to a similar extent on most cell subsets. Memory B cell tetherin was significantly higher in the groups with multiple positive antibodies. U1RNP/Sm+was associated with renal involvement (p=0.004). Mucocutaneous involvement was greater in the Ro60 +Ro52+La+ group (p=0.037). Conclusions This cohort revealed relationships between immune features. U1RNP/Sm antibody was notable for defining a group of patients with a cluster of immune abnormalities, including the greatest elevation of IFN activity, greater abnormalities on flow cytometry and clinical renal involvement. This was independent to the IFN-Score-B high status that predicts better clinical response to rituximab (presented elsewhere at this conference). Future work in MASTERPLANS will investigate the significance of these subgroups for response to therapy. Funding Source(s): Medical Research Council, National Institute for Health Research

Background Rituximab is used for resistant SLE but clinical response varies. Although biomarkers of time to relapse have been validated, there are few biomarkers to predict initial response. Interferon status may predict response to rituximab and anti-TNF in RA. We previously validated two interferon-stimulated gene expression scores (IFN-Score-A and IFN-Score-B) that improved prediction of clinical outcomes in SLE. IFN-Score-A included most commonly reported ISGs and predicted flares and glucocorticoid requirements. IFN-Score-B included ISGs that respond to multiple IFN subtypes and predicted development of SLE in At-Risk individuals. Diagnosis of SLE was associated with both scores, while only IFN-Score-B was elevated in RA. The British Society for Rheumatology Biologics Registry (BILAG-BR) collects data and samples for rituximab-treated patients in the UK. MASTERPLANS is an MRC-funded consortium to identify predictors of response. Methods This is a preliminary analysis of the first rituximab-treated patients in the BILAG-BR with complete data. Patients were recruited if they were starting a first cycle of rituximab for active SLE (BILAG A or 2xBILAG B) despite previous cyclophosphamide or mycophenolate mofetil. Disease activity was measured using BILAG-2004. Clinical response was defined as improvement by ≥1 grade in active BILAG-2004 systems with no worsening in other systems. Whole blood was collected into TEMPUS tubes and RNA extracted. IFN-Scores were measured using a custom Taqman array as previously described, normalised to PP1A [El Sherbiny et al. Sci Rep 2018]. Multivariate logistic regression was used to test IFN-Scores and baseline clinical covariates as predictors of BILAG response at 6 months. Results Samples were available from 147 patients, of whom 84 had complete baseline and 6 month clinical data available and were included in this analysis. 40/84 (47.6%) patients had BILAG response at 6 months. In univariate and multivariate analysis, high IFN-Score-B expression was significantly associated with clinical response (see table 1). Conclusions This preliminary analysis suggests that assessment of IFN activity has a role in prediction of response to rituximab. A novel IFN score (Score B) was more predictive than classic ISGs (Score A). These results add to a body of work showing that IFN-Score-B predicts clinically significant outcomes independently of overall IFN activity. Future work will analyse this biomarker in a larger cohort of patients and integrate with other putative clinical and biological predictors of response. Funding Source(s): Medical Research Council, National Institute of Health Research

ObjectiveType I interferon (IFN-I) responses are broadly associated with autoimmune disease including SLE. Given the cardinal role of autoantibodies in SLE, we investigated whether a B lineage cell-specific IFN assay might correlate with SLE activity.MethodsB cells and PBMCs were stimulated with IFN-I and IFN-II. Gene expression was scrutinised for pathway-related membrane protein expression. A flow-cytometric assay for tetherin (CD317), an IFN-induced protein ubiquitously expressed on leucocytes, was validated in vitro then clinically against SLE diagnosis, plasmablast expansion, and BILAG-2004 score in a discovery cohort (156 SLE; 30 RA; 22 healthy controls). A second longitudinal validation cohort of 80 patients was also evaluated for SLE flare prediction.ResultsIn vitro, a close cell-specific and dose-responsive relationship between IFN-I responsive genes and cell surface tetherin in all immune subsets existed. Tetherin expression was selectively responsive to the IFN-I compared to IFN-II and -III. In the discovery cohort memory B-cell tetherin was best associated with diagnosis (SLE/HC: effect size=0.11, p=0.003;SLE/RA: effect size=0.17, pConclusionMemory B cell surface tetherin, a reflection of cell-specific IFN response in a convenient flow cytometric assay, was associated with SLE diagnosis, disease activity and predicted flares better than other cell subsets or whole blood assays in independent validation cohorts.

Systemic Sclerosis (SSc) is an autoimmune disorder characterized by microvascular injury and diffuse fibrosis of the skin and internal organs. While macrovascular disease and higher risk for cardiovascular events are well documented in other systemic rheumatic diseases such as rheumatoid arthritis and systemic lupus erythematosus, the presence and extent of atherosclerosis among patients with SSc is yet to be established. Primary cardiac involvement, due to impairment of coronary microvascular circulation and myocardial fibrosis, considerably affects prognosis and life expectancy of individuals with SSc, representing one of the leading causes of death in this population. On the other hand the existence and prevalence of atherosclerotic coronary disease remains an issue of debate as studies comparing structural and morphological markers of atherosclerosis and cardiovascular events between SSc patients and the general population have yielded controversial results. The aim of this review is to summarize recent literature about the prevalence of cardiovascular disease in SSc, review the surrogate markers of CVD that have been evaluated and examine whether common pathogenic mechanisms exist between SSc and macrovascular disease.

Background:Biomarkers to predict response to rituximab include plasmablasts and, in the current MASTERPLANS consortium, Sm/U1RNP antibodies and high expression of IFN Score B (a subset of interferon-stimulated genes that predict more clinical outcomes than a classic interferon signature). The relationships amongst these biomarkers and their association with response to conventional therapies are less well described.Objectives:To analyse the inter-relationships amongst immune biomarkers in two independent SLE cohorts in association with disease activity and stage of therapeutic pathway.Methods:CONVAS is a cohort of unselected SLE patients; data available include current and historic disease activity, use of biologic therapy, flow cytometry, gene expression (IFN Score A and IFN Score B), and immunoprecipitation for autoantibodies (n=91). BILAG-BR is a British registry study for SLE patients commencing biologics; data available include current and historic disease activity, gene expression (IFN Score A and IFN Score B) and immunoprecipitation for autoantibodies (n=112). In both cohorts, biologics were only prescribed to patients with active disease (BILAG 1 x A or 2 x B) and failure of either cyclophosphamide or mycophenolate. Given the mixture of continuous and categorical variables, data were clustered using Gower distance and Partitioning Around Medioids. K was chosen using silhouette coefficient and clusters visualised with t-Distributed Stochastic Neighbor Embedding (t-SNE).Results:There were 6 clusters. In rituximab-naïve patients:Sm/U1RNP+, Ro60-, highest IFN Score A, low CD4+T cells, low NK cells, high plasmablastsSm/U1RNP-, Ro60+, medium IFN Score A, low CD4+T cells, high NK cells, high plasmablastsSm/U1RNP-, Ro60-, lowest IFN Score A, high CD4+T cells, low NK cells, low plasmablastsOther antibody subtypes and flow cytometric markers did not improve the accuracy of clustering. In rituximab-treated patients, 3 equivalent clusters for antibody subtypes and IFN Score A were observed but differentiated due to flow cytometry findings, as expected after rituximab treatment. Overall, the patients in the cluster defined by Sm/U1RNP antibodies and high IFN Score A were notable for a higher rate of prior disease activity in the renal, neurological and general BILAG domains (Table 1).Table 1 :Clinical features in unselected SLE patients (CONVAS)System affected (ever)Sm/U1RNP & high IFN Score A (n=27)Other(n=92)pvalueGeneral14/27 (52%)24/92 (26%)0.02Mucocutaneous23/27 (85%)73/92 (79%)0.50Neuro10/27 (37%)17/92 (19%)0.04MSK25/27 (93%)83/92 (90%)0.71Cardiorespiratory9/27 (33%)20/92 (22%)0.22Renal12/27 (44%)15/92 (16%)0.005Haematology25/27 (93%)67/92 (73%)0.03Analysis of autoantibody status and interferon scores only in BILAG-BR confirmed similar clustering. Across both cohorts, the prevalence of the Sm/U1RNP and high IFN Score A cluster was associated with inadequate response to conventional immunosuppressive treatment (Table 2).Table 2 :Prevalence according to stage of therapyTreatment groupSm/U1RNP & high IFN Score AOtherpvalueAntimalarial or conventional IS-treated(CONVAS) (n=90)16/90 (17.8%)74/90 (82%)0.02Conventional IS inadequate response,Previous rituximab (CONVAS) (n=38)14/38 (36.8%)24/38 (63.2%)Conventional IS inadequate response,starting rituximab (BILAG-BR) (n=163)51/163 (31.2%)112/163 (68.7%)N/AConclusion:A cluster of 23% of unselected SLE patients had more severe immune abnormalities, more severe clinical disease activity and were less likely to be maintained on conventional therapies, with twice as many requiring biologic therapy. Other data in MASTERPLANS have demonstrated that Sm/U1RNP antibodies and IFN Scores predict better response to rituximab. This subgroup of patients may therefore be more appropriate for first-line biologic therapy.Disclosure of Interests:Antonios Psarras: None declared, Danyang Li: None declared, Adewonuola Alase: None declared, Zoe Wigston: None declared, Ian Bruce Grant/research support from: Genzyme, Sanofi, GSK, UCB, Consultant of: Eli Lilly, AstraZeneca, Iltoo, Merck Serono, Neil McHugh: None declared, Edward Vital Grant/research support from: AstraZeneca, Roche/Genentech, and Sandoz, Consultant of: AstraZeneca, GSK, Roche/Genentech, and Sandoz, Speakers bureau: Becton Dickinson and GSK

Background:We previously reported results from the first 118 “At-Risk” of autoimmune connective tissue disease (AI-CTD) individuals (i.e. ANA positivity, non-specific symptoms of ≤1 year and treatment naïve). At 1 year, 16% progressed to meet classification criteria for an AI-CTD. This was predicted by high baseline interferon (IFN) Score B and family history of RMD[1].However, some may have progressed at later time points, or had clinically significant disease despite not meeting diagnostic criteria. Longer term outcomes, baseline and follow up flow cytometry biomarkers were never reported.Objectives:(i)Describe detailed analysis of 3-year follow-up data of the At-Risk cohort(ii)Evaluate flow cytometric biomarkers as predictors of these outcomes(iii)Analyse follow up biomarkersMethods:We conducted a prospective observational longitudinal study of At-Risk individuals in Leeds (n=150). Patients were assessed at baseline, then annually for 3 years. Depending on diagnostic criteria and need for therapy, patients were grouped as follows:Absolute non-progressors (no clinical diagnostic criteria)Undifferentiated CTD (U-CTD) (≥1 clinical criteria at baseline persisting at follow-up but not meeting criteria). This group was subdivided into those who required treatment with an immunosuppressant (IS) excluding antimalarials and those who did notYear 1 progressors (meeting criteria for an RMD by 1 year)Late progressors (meeting criteria for AI-CTD beyond 1 year follow-up).Bloods were analysed at baseline and 1 year for two IFN-stimulated gene expression scores previously described[2], monocytes and subsets of B and T cells using flow cytometry. Association between clinical criteria, biomarkers at baseline and long term outcomes were tested using ANOVA.Results:3 year follow up data was available in 147/150 patients. Outcomes were: Absolute non-progressors: 63/147 (43%); U-CTD: 54/147 (37%); Year 1 progressors: 21/147 (14%) [SLE=18; pSS=3]; Late progressors (in years 1-2): 9/147 (6%) [SLE=7; pSS=2]. None progressed or required IS initiation beyond the first 2 years of follow-up. In U-CTD group, 7/54 (13%) were prescribed an IS.This work describes a larger group of 36/147 (24%) At-Risk individuals who developed clinically significant disease (CSD: progressors or need for IS) versus clinically non-significant disease (CNSD: absolute non-progressors or UCTD not needing IS).Analysis of baseline biomarkers between CSD and CNSD confirmed a significant difference in IFN Score B (mean difference -0.74, p = 0.027), but not IFN Score A (mean difference -0.68, p = 0.15). In flow cytometry analysis, there was also a significant difference in percentage monocytes (mean difference -4.09, p = 0.004) but no other subset. Absence of clinical criteria at baseline did not predict clinical outcome, and no one clinical criterion had greater predictive value.In follow up samples we noted a significant reduction in expression of IFN Score B in both groups, regardless of whether they received antimalarials or IS therapy.Conclusion:Here we report findings of a larger group of 24% At-Risk individuals who developed CSD (progressors and patients who did not meet criteria but needed IS therapy). These results provide a more complex picture of IFN activity in the initiation of SLE than previously suspected. First, we confirm that a specific subset of ISGs rather than a classic IFN signature predicts progression. Second, the reduction in IFN-Score-B in both groups suggests that IFN Score B activity is a transient phenomenon, playing a greater role in disease initiation than in disease maintenance.References:[1]Md Yusof MY, Psarras A, El-Sherbiny YM, et al. Prediction of autoimmune connective tissue disease in an at-risk cohort: prognostic value of a novel two-score system for interferon status. Ann Rheum Dis. 2018 Oct;77(10):1432-1439.[2]El-Sherbiny YM, Psarras A, Md Yusof MY, et al. A novel two score system for interferon status segregates autoimmune diseases and correlateswith clinical features. Sci Rep. 2018 Apr 11;8(1):5793.Disclosure of Interests:Sabih-Ul Hassan: None declared, Zoe Wigston: None declared, Antonios Psarras: None declared, Katie Dutton: None declared, Md Yuzaiful Md Yusof: None declared, Edward Vital Grant/research support from: AstraZeneca, Roche/Genentech, and Sandoz, Consultant of: AstraZeneca, GSK, Roche/Genentech, and Sandoz, Speakers bureau: Becton Dickinson and GSK

Autoimmune connective tissue diseases arise in a stepwise fashion from asymptomatic preclinical autoimmunity. Type I interferons (IFNs) have a crucial role in the progression to established autoimmune diseases such as systemic lupus erythematosus (SLE). However, their cellular source and regulation in disease initiation are unclear. The current paradigm suggests that plasmacytoid dendritic cells (pDCs) are activated in SLE contributing to excessive IFN production. Here, we show that in preclinical autoimmunity, established SLE, and primary Sjögren’s Syndrome, pDCs are not effector cells, but rather have lost their capacity for TLR-mediated IFN-α and TNF production and fail to induce T cell activation, independently of disease activity and blood IFN signature. In addition, pDCs present a transcriptional signature of cellular stress and senescence accompanied by increased telomere erosion. Instead, we demonstrate a marked enrichment of IFN signature in non-lesional skin in preclinical autoimmunity. In these individuals and SLE patients, type I IFNs were abundantly produced by keratinocytes in the absence of infiltrating leucocytes. These findings revise our understanding of the role of IFN in the initiation of human autoimmunity, with non-haematopoietic tissues perpetuating IFN responses, which in turn predict clinical disease. These data indicate potential therapeutic targets outside the conventional immune system for treatment and prevention.

Environmentally induced systemic sclerosis is a well-recognized condition, which is correlated with exposure to various chemical compounds or drugs. However, development of scleroderma-like disease after exposure to silicone has always been a controversial issue and, over time, it has triggered spirited debate whether there is a certain association or not. Herein, we report the case of a 35-year-old female who developed Raynaud’s phenomenon and, finally, systemic sclerosis shortly after silicone breast implantation surgery.

Background and objectives Type I interferons (IFN-I) are crucial to systemic lupus erythematosus (SLE) pathogenesis. However, IFN-I activity, as measured by interferon-stimulated gene (ISG) expression, has an unclear relationship with clinical features of disease. Incomplete lupus erythematosus (ILE) describes individuals who have new onset of features suggestive of SLE, but do not fulfil diagnostic criteria. Up to 20% of these patients eventually progress to SLE. The objective of this study is to compare ISG expression between patients with ILE and SLE to understand the role of IFN in onset of clinical features of SLE. Materials and methods Expression of 33 ISGs was measured using qPCR in PBMCs from individuals with SLE (n = 54), ILE (n = 27), and healthy controls (HC; n = 14). SLE was defined using 2012 ACR/SLICC criteria. ILE was defined as ANA +ve, 1–2 clinical ACR/SLICC criteria, and symptom duration Results FA on SLE patients indicated two factors explaining 80% of the data variance. In total, 16 and 14 genes loaded onto Factors F1 and F2 respectively. The majority of variability was explained by F1; however, F2 appeared more relevant to the presence of fully established SLE. F1 and F2 were significantly different between patient groups (p = 0.005 and p = 0.044 respectively). F1 was similarly high in both SLE [SLE:HC=4.22 (1.80, 9.88), p = 0.001] and ILE [ILE:HC=2.96 (1.20, 7.32), p = 0.019]. In contrast, F2 was increased only in SLE [SLE:HC=1.38 (0.95, 2.00), p = 0.086] but not in ILE [ILE:HC=1.02 (0.69, 1.51), p = 0.917]; a significant difference was observed between SLE and ILE patients [SLE:ILE=1.35 (1.04, 1.77), p = 0.026]. Conclusions IFN-I activity is present in ILE. However, the majority of measured ISG expression (F1) cannot distinguish ILE and SLE. F1 represents genes that distinguish healthy individuals, but show little variation at different stages of the disease development. We define a subset of ISGs (F2) whose expression is only increased in patients with confirmed clinical SLE. ISG expression is not unidimensional: qualitative differences in expression of distinct ISGs contribute to clinical progression after disease initiation.

Background and objectives Type I interferons (IFN-I) have diverse effects on immune cell populations in SLE, Measuring IFN-I using whole blood interferon-stimulated gene (ISG) expression does not completely explain clinical features of SLE. Objective: develop a cell-specific assay using a surface protein encoded by an ISG ( BST2 ). This would allow convenient analysis of IFN response in individual populations to improve immunophenotyping of SLE patients. Materials and methods PBMCs from 133 SLE patientsand 19 healthy controls (HC) were analysed by flow cytometry for cell surface BST2 protein on each immune cell subset. Cells were FACS-sorted into naive and memory B-cells, plasmablasts, CD3 + T-cells, NK-cells and monocytes in 12 SLE patients and 16 healthy controls. Expression of BST2, as well as 32 other ISGs, were measured using qPCR. Results Analysis of sorted cells confirmed that surface BST2 is a valid cell-specific IFN assay. BST2 expression correlated with BST2 surface protein within each immune subset: naive B-cells (r = 0.63, p = 0.009); memory B-cells (r = 0.78, p We next used surface BST2 to compare IFN activity of each subset with clinical features in 133 patients. A significant correlation between the PBMC 33-gene IFN score and surface BST2 for each cell subset (all p BST2 was significantly higher in SLE than HC on naive and memory B-cells (p = 0.004, p = 0.003), plasmablasts (p = 0.047), T cells (p = 0.043), but not different on monocytes (p = 0.406). Association of disease activity (total BILAG) with BST2 on naive and memory B-cells (Tau-a = 0.23 and 0.22 respectively) was substantive and approximately twice as strong as monocytes and T-cells (Tau-a = 0.12 and 0.14). A similar pattern was seen for anti-dsDNA titre, with no association with monocyte BST-2 (Tau-a = 0.07) but a substantive association for memory B cell BST-2 (Tau-a = 0.18). Conclusion IFN-I response differs in cell subsets. This can be measured in a fast, cost-effective, convenient assay using flow cytometric analysis of surface BST2. Our results show that IFN activity measured on B cells is more clinically relevant than on other cell populations.

Background Dysfunction of peripheral immune tolerance against self antigens is a critical factor in the pathogenesis of neuropsychiatric systemic lupus erythematosus (NPSLE) and is mainly mediated by T regulatory cells (Tregs). Objectives Aim of the present study was the evaluation of Tregs and related cytokines (IL-6, IL-10, TGF-β) in regard to disease activity in NPSLE patients. Methods Twenty patients (17 females, 3 males, mean age 44.9±14.1 years, mean disease duration 87.2±63.4 months) were included. CD4+CD25 high FOXP3+ Tregs were assessed by triple color flow cytometry in 88 peripheral blood samples (26 active, 62 inactive disease). IL-6, IL-10 and TGF-β were evaluated by ELISA in 36 serum samples (18 active, 18 inactive disease). Disease activity was determined using SLEDAI (SLE Disease Activity Index). Statistics were performed by Student9s t-test; p Results Tregs were significantly lower in active NPSLE (0.57±0.17% of CD4+ T cells vs 1.05±0.39%, absolute numbers 4.6±3.4 vs 9.3±6.6 cells/mm 3 , p p =0.005). On the contrary, IL-10 levels were not differentiated (4.5±3.2pg/ml vs 2.75±3.77pg/ml, p =0.224), while TGF-β was marginally lower in active disease (20064±5495pg/ml vs 25770±9282pg/ml, p =0.103). Conclusions Peripheral Tregs are lower in active NPSLE, in parallel with higher IL-6 and lower TGF-β levels. Impairment of the IL-6/TGF-β axis probably plays an important role in disease pathogenesis. Disclosure of Interest None declared DOI 10.1136/annrheumdis-2014-eular.3813