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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. ispartof: ARTHRITIS & RHEUMATOLOGY vol:73 issue:6 pages:1073-1085 ispartof: location:United States status: published

Objective Epigenetic modifications are dynamic and influence cellular disease activity. The aim of this study was to investigate global DNA methylation in peripheral blood mononuclear cells (PBMCs) of RA patients to clarify whether global DNA methylation pattern testing might be useful in monitoring disease activity as well as the response to therapeutics. Methods Flow cytometric measurement of 5-methyl-cytosine (5′-mC) was established using the cell line U937. In the subsequent prospective study, 62 blood samples were investigated, including 17 healthy donors and 45 RA patients at baseline and after 3 months of treatment with methotrexate, the IL-6 receptor inhibitor sarilumab, and Janus kinase inhibitors. Methylation status was assessed with an anti-5′-mC antibody and analysed in PBMCs and CD4+, CD8+, CD14+ and CD19+ subsets. Signal intensities of 5′-mC were correlated with 28-joint DASs with ESR and CRP (DAS28-ESR and DAS28-CRP). Results Compared with healthy individuals, PBMCs of RA patients showed a significant global DNA hypomethylation. Signal intensities of 5′-mC correlated with transcription levels of DNMT1, DNMT3B and MTR genes involved in methylation processes. Using flow cytometry, significant good correlations and linear regression values were achieved in RA patients between global methylation levels and DAS28-ESR values for PBMCs (r = −0.55, P = 0.002), lymphocytes (r = −0.57, P = 0.001), CD4+ (r = −0.57, P = 0.001), CD8+ (r = −0.54, P = 0.001), CD14+ (r = −0.49, P = 0.008) and CD19+ (r = −0.52, P = 0.004) cells. Conclusions The degree of global DNA methylation was found to be associated with disease activity. Based on this novel approach, the degree of global methylation is a promising biomarker for therapy monitoring and the prediction of therapy outcome in inflammatory diseases.

Background Clinical heterogeneity, a hallmark of systemic autoimmune diseases (SADs) impedes early diagnosis and effective treatment, issues that may be addressed if patients could be grouped into a molecular defined stratification. Methods With the aim of reclassifying SADs independently of the clinical diagnoses, unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data of 918 patients with 7 SADs and 263 healthy controls was undertaken. An inception cohort prospectively followed for 6 and 14 months was studied to validate the results in early cases and analyze if cluster assignment was modified with time. Results Four clusters were identified Three aberrant clusters were ‘acute phase inflammatory’, ‘T cell immunity’, and ‘interferon’, each including all diagnoses, were defined by genetic, clinical, serological and cellular features. A fourth cluster showed no specific molecular pattern, to which 74% of healthy controls clustered with patients. The inception cohort showed that most patients were either assigned always to the same cluster or moved from the healthy-like cluster to a single aberrant cluster resembling the relapsing-remitting dynamic of these diseases, showing that single aberrant molecular signatures characterize each individual patient. Conclusions Patients with SADs share molecular signatures and can be therefore stratified into three disease clusters differentiating each patient into a specific molecular disease pathway. Such assignment is stable with time. These results have important implications for understanding disease progression and therapy design marking a paradigm shift in our view of SADs. Acknowledgment This work has been supported through a grant from the Innovative Medicines Initiative Joint Undertaking No. 115565 and in-kind and in-cash contributions from the EFPIA partners. G.B. is supported by the Instituto de Salud Carlos III (ISCIII, Spanish Health Ministry), through the Sara Borrell subprogram (CD18/00153). The authors would like to particularly express their gratitude to the patients, nurses and many others who helped directly or indirectly in the consecution of this study.

SUMMARYBackgroundClinical heterogeneity, a hallmark of systemic autoimmune diseases (SADs) impedes early diagnosis and effective treatment, issues that may be addressed if patients could be grouped into a molecular defined stratification.MethodsWith the aim of reclassifying SADs independently of the clinical diagnoses, unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data of 918 patients with 7 SADs and 263 healthy controls was undertaken. In addition, an inception cohort was prospectively followed for 6 and 14 months to validate the results and analyze if cluster assignment changed or not with time.ResultsFour clusters were identified. Three clusters were aberrant, representing ‘inflammatory’, ‘lymphoid’, and ‘interferon’ patterns each including all diagnoses and defined by genetic, clinical, serological and cellular features. A fourth cluster showed no specific molecular pattern and accumulated also healthy controls. An independent inception cohort showed that with time, the molecular clusters remain stable, showing that single aberrant molecular signatures characterize each individual patient.ConclusionsPatients with SADs can be jointly stratified into three 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 therapy non-responsiveness marking a paradigm shift in the view of SADs.

Background Dendritic cells (DCs) have a pivotal role in the pathogenesis of systemic lupus erythematosus (SLE). Reduced numbers of blood DCs and the accumulation of DCs at inflammatory sites have been observed in SLE. One crucial feature of DCs is their ability to migrate. Objective To analyse the maturation/activation state and the migratory capacity of different DC precursor subsets in SLE to further elucidate their role in autoimmunity. Methods Plasmacytoid DCs (pDCs), myeloid DCs (mDCs) and monocytes from patients with SLE, healthy volunteers and healthy volunteers immunised with tetanus/diphtheria were examined by flow cytometry for expression of subset-specific antigens (BDCA-2, CD11c, CD14, HLA-DR), activation/maturation markers (CD83, CD86, CD40, BLyS) and chemokine receptors (CCR1, CCR5, CCR7, ChemR23). Additionally, migratory capacity to chemokine receptors was investigated in vitro using the chemokines RANTES, CCL19 and chemerin. Results SLE monocytes and mDCs had higher CD86 and B-lymphocyte stimulatory factor (BLyS) expression levels. ChemR23 expression was lower in SLE pDCs and mDCs. Basal and CCL19-specific migration levels were higher in SLE pDCs. Altered DC function in SLE had no correlative changes in chemokine receptor expression, whereas immunisation-induced blood DC migration patterns in healthy donors were accompanied by changes in chemokine receptor expression. Conclusions The phenotypic and migratory disturbances observed in SLE blood DCs could result in altered distribution of DCs in peripheral tissues, contributing to dysregulated immune responses and autoimmunity.

Background and objectives The "Molecular Reclassification to Find Clinically Useful Biomarkers for Systemic Autoimmune Diseases" (PRECISESADS) IMI project will study 2,500 individuals affected by SADs into clusters of molecular, instead of clinical entities. Among extensive OMICS approaches, patients will get flow cytometry analyses using 9 panels of Abs, containing 8 different multi-stained markers, that will be performed in 11 various centres equipped with different flow cytometers (Canto II, Aria III, Fortessa, Verse, Navios or Gallios). The aim of this work was to establish a method to harmonised all the cytometers to be able to compared the overall data. Materials and methods VersaComp capture beads (Beckman Coulter) were used for the mirroring of the 11 flow cytometers. Rainbow 8 - peak beads (Beckman Coulter) were used to settle internal quality control for each machine. Duraclone tubes (Beckman Coulter) containing dried Ab cocktail were used for the multi-colour staining of the blood samples. Results A Navios has been chosen as the internal reference to fix the MFIs of the 8 different fluorochrome-conjugated Abs (FITC, PE, PC5.5, PC7, APC, APC-AF750, PB and KrO) using the VersaComp Ab capture beads. The 10 other centres have then fixed their own PMT values to reach the same MFIs using the same conjugated Abs. Thereafter, each centre acquired the Rainbow 8 - peak beads to determine their own internal QC. One blood sample has been dispatched in all centres and has been concomitantly stained with the Duraclone tubes (Beckman Coulter) . Frequencies of cell subsets and MFIs of markers have been compared and found similar between centres. Conclusions The prerequisite of the integration of the flow cytometry informations in bioinformatical and biostatistical analyses of the OMICS data is a fine inter-cytometer harmonisation. This procedure has been succesfully achieved getting a very close sensitivity for all flow cytometers. The inclusion of patients can now be confidently performed, knowing that the comparison of the flow cytometry data will be workable. Identification of specific molecular signatures in patients with SADs should finally enable clinicians to tailor individual therapies. (This work has received support from EU/EFPIA Innovative Medicines Initiative Joint Undertaking PRECISESADS grant n°115565).

Background In Systemic Lupus Erythematosus (SLE) various compartments of the immune system are altered. Type I interferon (IFN) produced by plasmacytoid dendritic cells seems to play a central role. The expression of Sialic Acid–Binding Ig-like Lectin 1 (Siglec-1) on monocytes is a cytometrically measurable surrogate parameter for type I IFN and has been shown to correlate with disease activity in SLE. Increased B cell activation is also characteristic for active SLE. Frequencies of CD27 ++ plasmablasts in peripheral blood are known to be higher in patients with active disease. Type I IFN can promote T cell dependent and independent B cell activation. Objectives To investigate the combined measurement of Siglec-1 expression and plasmablast frequencies as biomarkers for disease activity in human SLE. Methods After informed consent heparinised blood samples along with clinical and paraclinical data were collected from 12 SLE patients. After red cell lysis FACS staining was performed with fluorescent antibodies against CD14, CD3, CD19, CD20, CD27, CD138 and Siglec-1 plus isotype control. Cells were collected and measured using a BD™ LSR II flow cytometer. Data were analysed using FLOWJO analysis software. For Siglec-1 expression on CD14 + monocytes a ratio was calculated dividing the median fluorescence intensity (MFI) value of Siglec-1 stained by the MFI of isotype control stained cells. Plasmablast frequencies where calculated by gating on mononuclear cells according to forward and sideward scatter, further gating on CD19 + CD3 - cells and than on CD20 - CD27 ++ or CD20 - CD138 + cells, respectively. Results Siglec-1 expression correlated negatively with serum complement (C3) but not with SLEDAI or anti double stranded DNA (dsDNA) antibody titers using the non parametric Spearman test. Both, frequencies of CD20 - CD27 ++ and frequencies of CD20 - CD138 + cells correlated negatively with serum complement and positively with SLEDAI but not with dsDNA antibody titers. This was the case for frequencies in CD19 + B cells as well as in lymphocytes. Furthermore, Siglec-1 expression correlated positively with plasmablast frequencies, again for both, CD20 - CD27 ++ and CD20 - CD138 + cells. Conclusions All measured parameters (Siglec-1 in monocytes, CD20 - CD27 ++ CD19+ cells and CD20 - CD138 + CD19+ cells) seem to be suitable as additional disease activity markers in SLE. The reliability of the single markers and combinations should, of course, be studied in a bigger cohort, and also under various treatment conditions. The correlation of Siglec-1 expression with plasmablast frequencies is a further hint to pathogenetic relations between type I interferon and B cell activation. References Biesen R, Demir C, Barkhudarova F, Grun JR, Steinbrich-Zollner M, Backhaus M, Haupl T, Rudwaleit M, Riemekasten G, Radbruch A, Hiepe F, Burmester GR, Grutzkau A. Sialic acid-binding Ig-like lectin 1 expression in inflammatory and resident monocytes is a potential biomarker for monitoring disease activity and success of therapy in systemic lupus erythematosus. Arthritis Rheum. 2008 Apr;58(4):1136-45. Jacobi AM, Odendahl M, Reiter K, Bruns A, Burmester GR, Radbruch A, Valet G, Lipsky PE, Dorner T. Correlation between circulating CD27high plasma cells and disease activity in patients with systemic lupus erythematosus. Arthritis Rheum. 2003 May;48(5):1332-42. Disclosure of Interest None Declared

Objectives: The analysis of annotated transcripts from genome-wide expression studies may help to understand the pathogenesis of complex diseases, such as systemic sclerosis (SSc). We performed a whole blood (WB) transcriptome analysis on RNA collected in the context of the European PRECISESADS project, aiming at characterising the pathways that differentiate SSc from controls and that are reproducible in geographically diverse populations. Methods: Samples from 162 patients and 252 controls were collected in RNA stabilisers. Cases and controls were divided into a discovery (n=79+163; Southern Europe) and validation cohort (n=83+89; Central-Western Europe). RNA sequencing was performed by an Illumina assay. Functional annotations of Reactome pathways were performed with the Functional Analysis of Individual Microarray Expression (FAIME) algorithm. In parallel, immunophenotyping of 28 circulating cell populations was performed. We tested the presence of differentially expressed genes/pathways and the correlation between absolute cell counts and RNA transcripts/FAIME scores in regression models. Results significant in both populations were considered as replicated. Results: Overall, 15 224 genes and 1277 functional pathways were available; of these, 99 and 225 were significant in both sets. Among replicated pathways, we found a deregulation in type-I interferon, Toll-like receptor cascade, tumour suppressor p53 protein function, platelet degranulation and activation. RNA transcripts or FAIME scores were jointly correlated with cell subtypes with strong geographical differences; neutrophils were the major determinant of gene expression in SSc-WB samples. Conclusions: We discovered a set of differentially expressed genes/pathways validated in two independent sets of patients with SSc, highlighting a number of deregulated processes that have relevance for the pathogenesis of autoimmunity and SSc., This work was supported by eU/eFPia/innovative Medicines initiative Joint Undertaking PrecisesaDs Grant no. 115 565.