THU0251 IMMUNOPHENOTYPIC CLUSTERS OF SLE PATIENTS REVEAL SUBGROUPS WITH SEVERE DISEASE RESISTANT TO CONVENTIONAL THERAPY

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