A Proinflammatory Cytokine Network Profile in Th1/Type 1 Effector B Cells Delineates a Common Group of Patients in Four Systemic Autoimmune Diseases.

OBJECTIVE: The effector T cell and B cell cytokine networks have been implicated in the pathogenesis of systemic autoimmune diseases, but the association of these cytokine networks with the heterogeneity of clinical manifestations and immune profiles has not been carefully examined. This study was undertaken to examine whether cytokine profiles can delineate distinct groups of patients in 4 systemic autoimmune diseases (systemic lupus erythematosus, Sjögren's syndrome, rheumatoid arthritis, and systemic sclerosis). METHODS: A total of 179 patients and 48 healthy volunteers were enrolled in the multicenter cross-sectional PRECISE Systemic Autoimmune Diseases (PRECISESADS) study. Multi-low-dimensional omics data (cytokines, autoantibodies, circulating immune cells) were examined. Coculture experiments were performed to test the impact of the cytokine microenvironment on T cell/B cell cross-talk. RESULTS: A proinflammatory cytokine profile defined by high levels of CXCL10, interleukin-6 (IL-6), IL-2, and tumor necrosis factor characterized a distinct group of patients in the 4 systemic autoimmune diseases. In each disease, this proinflammatory cluster was associated with a specific circulating immune cell signature, more severe disease, and higher levels of autoantibodies, suggesting an uncontrolled proinflammatory Th1 immune response. We observed in vitro that B cells reinforce Th1 differentiation and naive T cell proliferation, leading to the induction of type 1 effector B cells and IgG production. This process was associated with an increase in CXCL10, IL-6, IL-2, and interferon-γ production. CONCLUSION: This composite analysis brings new insights into human B cell functional heterogeneity based on T cell/B cell cross-talk, and proposes a better stratification of patients with systemic autoimmune diseases, suggesting that combined biomarkers would be of great value for the design of personalized treatments.

Integrative Analysis Reveals a Molecular Stratification of Systemic Autoimmune Diseases.

OBJECTIVE: Clinical heterogeneity, a hallmark of systemic autoimmune diseases, impedes early diagnosis and effective treatment, issues that may be addressed if patients could be classified into groups defined by molecular pattern. This study was undertaken to identify molecular clusters for reclassifying systemic autoimmune diseases independently of clinical diagnosis. METHODS: Unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data on 955 patients with 7 systemic autoimmune diseases and 267 healthy controls was undertaken. In addition, an inception cohort was prospectively followed up for 6 or 14 months to validate the results and analyze whether or not cluster assignment changed over time. RESULTS: Four clusters were identified and validated. Three were pathologic, representing "inflammatory," "lymphoid," and "interferon" patterns. Each included all diagnoses and was defined by genetic, clinical, serologic, and cellular features. A fourth cluster with no specific molecular pattern was associated with low disease activity and included healthy controls. A longitudinal and independent inception cohort showed a relapse-remission pattern, where patients remained in their pathologic cluster, moving only to the healthy one, thus showing that the molecular clusters remained stable over time and that single pathogenic molecular signatures characterized each individual patient. CONCLUSION: Patients with systemic autoimmune diseases can be jointly stratified into 3 stable disease clusters with specific molecular patterns differentiating different molecular disease mechanisms. These results have important implications for future clinical trials and the study of nonresponse to therapy, marking a paradigm shift in our view of systemic autoimmune diseases.

Standardization procedure for flow cytometry data harmonization in prospective multicenter studies.

One of the most challenging objective for clinical cytometry in prospective multicenter immunomonitoring trials is to compare frequencies, absolute numbers of leukocyte populations and further the mean fluorescence intensities of cell markers, especially when the data are generated from different instruments. Here, we describe an innovative standardization workflow to compare all data to carry out any large-scale, prospective multicentric flow cytometry analysis whatever the duration, the number or type of instruments required for the realization of such projects.

Multi-center harmonization of flow cytometers in the context of the European "PRECISESADS" project.

The innovative medicine initiative project called PRECISESADS will study 2.500 individuals affected by systemic autoimmune diseases (SADs) and controls. Among extensive OMICS approaches, multi-parameter flow cytometry analyses will be performed in eleven different centers. Therefore, the integration of all data in common bioinformatical and biostatistical investigations requires a fine mirroring of all instruments. We describe here the procedure elaborated to achieve this prerequisite. One flow cytometer chosen as reference instrument fixed the mean fluorescence intensities (MFIs) of 8 different fluorochrome-conjugated antibodies (Abs) using VersaComp Ab capture beads. The ten other centers adjusted their own PMT voltages to reach the same MFIs. Subsequently, all centers acquired Rainbow 8-peak beads data on a daily basis to follow the stability of their instrument overtime. One blood sample has been dispatched and concomitantly stained in all centers. Comparison of leukocytes frequencies and cell surface marker MFIs demonstrated the close sensitivity of all flow cytometers, allowing a multicenter analysis. The effective multi-center harmonization enables the constitution of a workable wide flow cytometry database for the identification of specific molecular signatures in individuals with SADs.