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Key Points Epigenetic mechanisms are essential for immune cell differentiation and function, including the correct activation of B cells and T cells and inflammatory processes The dysregulation of epigenetic mechanisms in genetically predisposed individuals is associated with inflammatory rheumatic diseases Epigenome-wide association studies in genetically complex inflammatory rheumatic diseases have identified substantial correlations between epigenetic mechanisms and disease activity and severity Epigenetic dysregulation contributes to the clinical manifestations of monogenic autoinflammatory syndromes and can be used as a biomarker of response to treatment The systematic use of epigenomic screening will help to classify and identify novel biomarkers for personalized management of patients with inflammatory rheumatic diseases New inhibitors of epigenetic enzymes or upstream enzymes that are linked to the epigenetic control of immune function are likely to be tested in clinical trials for disease management Epigenetic alterations are increasingly being associated with the pathogenesis of inflammatory rheumatic diseases. In this Review, Ballestar and Li outline the current state of research into the role of epigenetics in such diseases and the possibility of epigenetic-targeting therapies. Over the past decade, awareness of the importance of epigenetic alterations in the pathogenesis of rheumatic diseases has grown in parallel with a general recognition of the fundamental role of epigenetics in the regulation of gene expression. Large-scale efforts to generate genome-wide maps of epigenetic modifications in different cell types, as well as in physiological and pathological contexts, illustrate the increasing recognition of the relevance of epigenetics. To date, although several reports have demonstrated the occurrence of epigenetic alterations in a wide range of inflammatory rheumatic conditions, epigenomic information is rarely used in a clinical setting. By contrast, several epigenetic biomarkers and treatments are currently in use for personalized therapies in patients with cancer. This Review highlights advances from the past 5 years in the field of epigenetics and their application to inflammatory rheumatic diseases, delineating the future lines of development for a rational use of epigenetic information in clinical settings and in personalized medicine. These advances include the identification of epipolymorphisms associated with clinical outcomes, DNA methylation as a contributor to disease susceptibility in rheumatic conditions, the discovery of novel epigenetic mechanisms that modulate disease susceptibility and the development of new epigenetic therapies.

Could temporal changes in DNA methylation patterns of rheumatoid arthritis (RA) synoviocytes provide insights into the progression of the disease? A study comparing synoviocyte DNA methylation profiles in early and long-standing RA suggests this might be the case, with potential implications for understanding and perhaps modulating RA progression.

Background:Primary Sjögren’s syndrome (pSS) is an autoimmune disease, known for its disabling effect and chronic course. One of the peculiar symptoms is the lachrymal glands dryness associated often but not limited to dry mouth, dental disorders, joint pain, fatigue, and, in severe cases, systemic complications. The most relevant clinical feature is the infiltration of lymphocytes within the salivary glands and the development of an autoimmune endocrinopathy that can overstimulate lymphocytes until the development of lymphoma in 5% of the patients. pSS treatments are limited, and a deeper disease understanding is mandatory. Recently, Soret et al1 proposed a novel classification of pSS patients, in line with the PRECISESADS project2, aiming to reclassify the autoimmune diseases based on their biology more than the clinical features.Objectives:The ‘interferon’ cluster 1 (C1), ‘healthy-like’ cluster 2 (C2), ‘lymphoid’ cluster 3 (C3) and ‘inflammatory’ cluster 4 (C4) are analysed with novel datasets and omics from the same patients of the Soret et al study, including RNA-seq data from B lymphocytes and metabolomics data from plasma and urine. The multi-omics data integration by the MOFA algorithm is applied to extract factors able to catch the common variance from the novel and older omics. This study aims to extend the previous work and identify metabolomics markers easily obtainable with routine analysis to classify new pSS patients and provide the best care.Methods:Bioinformatics analyses were performed on the PRECISESADS datasets, including transcriptomics, metabolomics, methylomics and clinical data from over 300 pSS patients. The B-cell transcriptome was analysed using DESeq and GSEA. Plasma and urine metabolomics peak changes were quantified, statistically tested, and annotated using the Ceu Mass Mediator database. Common sources of variation among all the databases were identified using the MOFA integration analysis for each cluster, and the factor tested to be significantly discriminant to CTRLs. The clustering was performed in B-cell, plasma and urine data by linear discriminant analysis (LDA).Results:The B cell transcriptome highlighted the clusters C1 and C3 as the most affected by the interferon pathway, while C2 and C4 showed few differences compared to CTRLs. The cluster C4, marked by lymphopenia, had a low contribution of B lymphocytes in driving this patient cluster. Glycosylation genes (GALNTL6, MGAT3 and ENOSF1) contributed to the C2 and C4 differences among the clusters, while C1 and C3 by interferon signalling. Metabolomics analysis shed light on differences only in the plasma C1 cluster, where Lysophosphatidylcholine (LysoPC), phosphatidylinositol (PI) and neutral sphingolipids were upregulated, together with metabolites related to protein and nucleotide degradation. All clusters had a MOFA factor linked to interferon except the C2, where a single significant factor driven by B cell genes was associated with epigenetic modifications. Cluster 4 showed a factor associated with apoptosis in line with the lymphopenia, and carnitine complex showed a protective role in C1, C3, and C4 clusters, always contributing against their phenotype. LDA unveiled the drivers of the cluster differences, including interferon for B lymphocytes and cholines-associated lipids and phosphatidylinositol for plasma.Conclusion:This study provided novel details about the clustering of pSS patients observed in other studies1,2. B lymphocytes in cluster C4 showed little difference compared to CTRLs, while glycosylation, interferon signalling and epigenetics are proposed as drivers in B cell alteration in the other Sjogren clusters. PI, choline lipids and carnitine were identified in plasma as discriminant markers in the pSS clustering prediction, making them promising for their easy clinical measurement.REFERENCES:[1] Soret, P. A new molecular classification to drive precision treatment strategies in primary Sjögren’s syndrome. Nat Commun 12, 3523 (2021).[2] Barturen, G. et al. Integrative Analysis Reveals a Molecular Stratification of Systemic Autoimmune Diseases. Arthritis Rheumatol. Hoboken NJ 73, 1073–1085 (2021).Acknowledgements:NIL.Disclosure of Interests:CRISTIAN IPERI: None declared, Alvaro Fernández-Ochoa: None declared, Jacques-Olivier Pers: None declared, Nathan Foulquier: None declared, Guillermo Barturen: None declared, Marta Alarcon-Riquelme As part of the public European project PRECISESADS from the Innovative Medicines Initiative Joint Undertaking under Grant Agreement Number 115565. Innovative Health initiative from the European Union with in-kind contributions from the pharmaceutical industry (Sanofi, Roche, GSK, BMS, Novartis, Janssen, Tekada, Astra Zeneca and Pfizer. Payments are within the project and only BMS has made direct payments to her institution for personnel., Divi Cornec: None declared, Anne Bordron: None declared, Christophe Jamin: None declared.

Background:Sjögren’s disease (SjD) presents an unmet medical challenge as there is currently no cure. Despite advances in understanding the immunopathogenesis of SjD, there is still a pressing need to identify novel biomarkers and therapeutic targets, for better patient stratification and personalized treatment.Objectives:To create a fully-detailed molecular interaction map (MIM) including all the signalling and molecular pathways implicated in SjD pathogenesis. To create a large-scale mechanistic model to enable in silico simulations of perturbations including drug interventions, and the generation of hypothesis-driven predictions.Methods:Differential expression analysis was performed on blood samples from SjD patients vs controls on 3 datasets: the publicly available GSE51092 and the accessible via the NECESSITY consortium UKPSSR and PRECISEADS datasets. GSE51092 contains transcriptomic data of 190 SjD patients and 32 controls, UKPSSR of 151 SjD patients and 29 controls, and PRECISESADS, RNASeq data for 304 SjD patients and 341 controls. Pathway enrichment analysis was subsequently performed using GSEA and the Reactome pathway database[1,2]. Additional literature-based evidence was used to develop a molecular interaction map, combining the results of the previous analytical steps. The SjD specific map was then converted into a Boolean model using the CaSQ tool[3]. Logic rules based on Boolean algebra are used to describe every interaction between the molecular entities.Results:Our analysis unveiled a set of differentially expressed genes (DEG) and related pathways associated with immune dysregulation and inflammatory responses in SjD. We obtained a total of 1625 DEG, 725 DEG from PRECISESADS, 1161 DEG from GSE51092 and 239 DEG from UKPSSR, with 25 DEG common for all three datasets. Nine common DEG were associated with Interferon signalling. Twenty-one pathways were identified with both GSEA and Reactome-based analysis. The building of the SjD MIM was performed based on literature search and the 21 identified pathways, from the data analysis. The MIM includes so far 16 pathways (5 present in the identified pathways and 11 literature-mined), comprising 187 species (genes, RNAs proteins) and 132 reactions. The SjD-specific Boolean model obtained after conversion of the SjD MIM, represents a more compact and fully executable version of the SjD molecular network, containing 111 nodes and 130 edges. In Sjögren-specific conditions the model is able to reproduce the activation of main inflammation pathways and predict the inflammatory response.Conclusion:We have built the first SjD-specific MIM integrating omic data analyses and information from literature-based evidence and pathway enrichment analysis. The current SjD map contains hallmark disease pathways and is constantly being enriched with data-driven highlighted pathways. The preliminary computational model based on the SjD map is able to reproduce inflammatory response scenarios, however further training is needed to improve performance and robustness.REFERENCES:[1] Fabregat, A. et al. The Reactome pathway Knowledgebase. Nucleic Acids Research 44, D481–D487 (2016).[2] Subramanian, A. et al. Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences 102, 15545–15550 (2005).[3] Aghamiri, S. S. et al. Automated inference of Boolean models from molecular interaction maps using CaSQ. Bioinformatics 36, 4473–4482 (2020).Figure 1.Data analysis revealed 1625 DEG from three different datasets of expression data in Sjögren patients. Pathway enrichment analysis using GSEA and Reactome database identified 21 common enriched pathways. These pathways along with literature-based search were used as the starting point for the building of the Sjögren molecular interaction map (MIM). The first version of the map consists of 187 biomolecules organized in 16 pathways (5 data-driven and 11 literature -mined) and has served as a template for the inference of a discrete computational model. The model comprises 111 biomolecules and 130 interactions.Acknowledgements:I express my gratitude to the NECESSITY consortium members for the materials they made available to me, which enabled me to carry out this research. I would also like to thank the doctoral school SDSV of Paris-Saclay University and Genopole for financing respectively my PhD studies and formations I followed.Disclosure of Interests:Sacha E Silva-Saffar: None declared, Jacques-Eric Gottenberg BMS, Pfizer, Lilly, Abbvie, AstraZeneca, Gilead, Galapagos, MSD, Roche-Chugai, Sanofi, UCB, Michele Bombardieri: None declared, Divi Cornec: None declared, Jacques-Olivier Pers: None declared, Marta Alarcon-Riquelme: None declared, Philippe MOINGEON Sanofi, Stallergenes, Servier, Michael Barnes: None declared, Sandra Ng: None declared, Wan-Fai Ng GlaxoSmithKline, MedImmune, Novartis and BMS, Abbvie, Resolves Therapeutics, Nascient, Xavier Mariette Sanofi, Servier, BMS, Gaetane Nocturne Amgen, Novartis, Anna Niarakis Sanofi.

ObjectivesChronic renal impairment remains a feared complication of lupus nephritis (LN). The present work aimed at identifying mechanisms and markers of disease severity in renal tissue samples from patients with LN.MethodsWe performed high-throughput transcriptomic studies (Illumina HumanHT-12 v4 Expression BeadChip) on archived kidney biopsies from 32 patients with LN and eight controls (pretransplant donors). Histological staging (glomerular and tubular scores) and immunohistochemistry experiments were performed on the same and on a replication set of 37 LN kidney biopsy samples.ResultsA group of LN samples was identified by unsupervised clustering studies based on their gene expression features, that is, the overexpression of transcripts involved in antigen presentation, T and B cell activation. These samples were characterised by a significantly lower estimated glomerular filtration rate (eGFR) at the time of biopsy (T0) compared with the other systemic lupus erythematosus samples. Yet, apparent disease duration at T0, double-stranded DNA antibody titres at T0 and other relevant characteristics (serum C3, proteinuria, histological scores, numbers of previous flares) were not different between groups.Immunohistochemistry studies confirmed the association between interstitial infiltration by adaptive immune effectors and decreased renal function in the same and in a replication group of LN kidney biopsies. This was associated with transcriptomic, histological and immunohistochemical evidence of renal tubular cell involvement.ConclusionInterstitial infiltration of LN kidney biopsies by adaptive immune effectors is associated with impaired renal tubular cell function and decreased eGFR. These results open new perspectives in evaluating and treating patients with LN, focusing on intrarenal mechanisms of immune cell activation.

BackgroundThe diagnosis of primary Sjögren Disease (SjD) is currently based on a combination of clinical, histological and biological findings [1]. Current thinking supports anti-Ro60 antibodies as the most specific serum marker, while the impact of anti-Ro52 remains unclear [2].ObjectivesThe aim of this study was to characterize the clinical, serological, biological, transcriptomic and interferon profiles of SjD patients according to their anti-Ro52 status and discuss the role of anti-Ro52 in the prognosis of SjD.MethodsSjD patients were recruited from the European PRECISESADS (378 patients) [3] and the independant Brittany DIApSS cohorts (160 patients) [4]. Four groups were defined: double negative (Ro52-/Ro60-), isolated anti-Ro52 positive (Ro52+), isolated anti-Ro60 positive (Ro60+), and double positive (Ro52+/Ro60+) patients. Clinical information, disease activity, and biological markers linked to disease severity were evaluated. Transcriptome data on whole blood by RNAseq and Type I and type II interferon signatures [5,6] were analyzed for PRECISESADS SjD patients.ResultsIn both cohorts, arthritis, parotidomegaly, and biological markers (hypergammaglobulinemia, rheumatoid factor and inflammation) [7] were significantly more frequent in the double positive group as compared to other groups. ESSDAI, a score representing systemic activity [8], was also significantly higher in double positive patients compared to the others. Transcriptome analysis demonstrated that anti-Ro52 positivity was associated with a strong interferon pathway activation as the lead cause to explain the clinical associations.ConclusionTaken together, these results suggest that SjD patients with anti-Ro52 positivity adopt a more severe phenotype as compared to their negative counterparts, independently of anti-Ro60 positivity.References[1]Brito-Zerón P, Baldini C, Bootsma H, Bowman SJ, Jonsson R, Mariette X, et al. Sjögren syndrome. Nat Rev Dis Primer. 2016 Jul 7;2(1):1–20.[2]Decker P, Moulinet T, Pontille F, Cravat M, De Carvalho Bittencourt M, Jaussaud R. An updated review of anti-Ro52 (TRIM21) antibodies impact in connective tissue diseases clinical management. Autoimmun Rev. 2022 Mar;21(3):103013.[3]Soret P, Le Dantec C, Desvaux E, Foulquier N, Chassagnol B, Hubert S, et al. A new molecular classification to drive precision treatment strategies in primary Sjögren’s syndrome. Nat Commun. 2021 Jun 10;12(1):3523.[4]Cornec D, Jousse-Joulin S, Pers JO, Marhadour T, Cochener B, Boisramé-Gastrin S, et al. Contribution of salivary gland ultrasonography to the diagnosis of Sjögren’s syndrome: toward new diagnostic criteria? Arthritis Rheum. 2013 Jan;65(1):216–25.[5]Kirou KA, Lee C, George S, Louca K, Papagiannis IG, Peterson MGE, et al. Coordinate overexpression of interferon-alpha-induced genes in systemic lupus erythematosus. Arthritis Rheum. 2004 Dec;50(12):3958–67.[6]Chiche L, Jourde-Chiche N, Whalen E, Presnell S, Gersuk V, Dang K, et al. Modular transcriptional repertoire analyses of adults with systemic lupus erythematosus reveal distinct type I and type II interferon signatures. Arthritis Rheumatol Hoboken NJ. 2014 Jun;66(6):1583–95.[7]Baldini C, Pepe P, Quartuccio L, Priori R, Bartoloni E, Alunno A, et al. Primary Sjögren’s syndrome as a multi-organ disease: impact of the serological profile on the clinical presentation of the disease in a large cohort of Italian patients. Rheumatology. 2014 May 1;53(5):839–44.[8]Brito-Zerón P, Kostov B, Solans R, Fraile G, Suárez-Cuervo C, Casanovas A, et al. Systemic activity and mortality in primary Sjögren syndrome: predicting survival using the EULAR-SS Disease Activity Index (ESSDAI) in 1045 patients. Ann Rheum Dis. 2016 Feb;75(2):348–55.Acknowledgements:NIL.Disclosure of InterestsNone Declared.

Background:Sjögren’s disease (SjD) is a heterogenous autoimmune disease, with a wide range of symptoms, from dryness, fatigue, pain, to systemic manifestations, and an increased risk of lymphoma. Recently, three clusters of patients with SjD have been described based on unsupervised clustering analysis according to symptoms, clinical signs and biologic parameters: 1/ BA-LS (B-cell active with low symptoms); 2/ HSA (High systemic activity); 3/ LSA-HS (Low systemic activity with high symptoms). These findings suggest potential heterogeneity in pathophysiological mechanisms.Objectives:To investigate this hypothesis, we examined whether these three clusters were associated with distinct biomarkers.Methods:This study involved SjD patients meeting AECG criteria from the ASSESS cohort. The following biomarkers were measured in sera at the time of inclusion: for IFN pathways—IFN-alpha 2, IFN gamma, CXCL-10; for B cell activation—CXCL-13, BAFF, B2-microglobulin, FLT-3; for T cell activation—IL-7, CCL-19, TNF-RII. Additionally, the IFN signature was assessed using transcriptomic analysis. Kruskal-Wallis rank sum test was used to compare different clusters for continuous variables. Additionally, the risk of lymphoma and of new immunosuppressive drugs prescriptions were compared according to the IFN signature.Results:This analysis included 395 (94% female, median age 53 [43-63] years) patients from the ASSESS cohorts. The three clusters displayed differences in the IFN pathways (IFN signature), primarily driven by type I IFN (IFN-a2 level) elevated only in BA-LS and HSA clusters and not in the LSA-HS cluster (p=0.001). IFN gamma and CXCL-10 were not different between the 3 clusters.The same clusters that exhibit high level of type 1 IFN also had higher CXCL-13 levels (p=0.0032) reflecting B-cell activation, higher IL-7 (p=0.0042) and TNFRII (p<0.001) levels reflecting T-cell activation. Higher levels of FLT-3 were found in the HSA cluster. BAFF level was not different between the 3 clusters.Lastly, there were a trend indicating an increased risk of lymphoma in patients with positive IFN signature (HR 2.53; 95%CI 0.67–9.55), and an increased risk of immunosuppressant prescription during follow-up (HR 2.81; 95%CI 1.26-6.29).Conclusion:The two clusters BA-LS and HSA have a very distinct cytokine signature than the patients with LSA-HS. These two active clusters share a high type 1 IFN level, and elevated markers of both B-cell and T-cell activation. Patients from the BA-LS cluster being younger, it is likely that this cluster represent an earlier disease stage than HSA cluster. In order to go towards personalized medicine, work is in progress for deciphering patients in these two active clusters exhibiting one predominant pathways among type 1 IFN, B-cell and T-cell activation.REFERENCES:[1] Nguyen Y, Nocturne G, Henry J. Identification of distinct phenotypes of Sjögren disease by cluster analysis based on clinical and biological manifestations: data from the cross-sectional Paris-Saclay and the prospective ASSESS cohorts. Lancet Rheumatology 2024.Acknowledgements:The authors are indebted to all patients for their participation, and to all physicians who included patients in the Paris-Saclay and ASSESS cohorts. The Assessment of Systemic Signs and Evolution in Sjögren’s Syndrome (ASSESS) national multicenter prospective cohort was formed in 2006 with a French Ministry of Health grant (Programme Hospitalier de Recherche Clinique 2005 P060228). The ASSESS cohort is promoted by the French Society of Rheumatology and receives research grants from the French Society of Rheumatology.Disclosure of Interests:Yann Nguyen: None declared, Xavier Mariette Xavier Mariette received consulting fees from Astra Zeneca, Bristol Myer Squib, Galapagos, GSK, Novartis and Pfizer, Maxime Beydon: None declared, Divi Cornec: None declared, Jacques-Olivier Pers: None declared, Jacques MorelJacques Morel received honoraria from Abbvie, Boehringer Ingelheim, Biogen, Lilly, Mylan, Pfizer, Sanofi, Bristol Myers Squib, Fresenius Kabi, Galapagos, Medac, Novartis, Roche Chugai;,Jacques Morel received grants from Bristol Myers Squib, Fresenius Kabi, Lilly, Novartis, Pfizer, and Roche-Chugaï;, Aleth PERDRIGER: None declared, Emmanuelle Dernis Emmanuelle Dernis received consulting fees from BMS, Celgène, Lilly, MSD, Novartis, UCB; honoria for lectures from Abbvie, BMS, Janssen, Lilly, Medac, MSD, Novartis, Roche-Chugaï, Sanofi, UCB, Celgène, Amgen, Galapagos;, Valerie Devauchelle-Pensec: None declared, Damien Sene: None declared, Philippe Dieudé Philippe Dieudé received consulting fees from Pfizer, Roche Chugai, Bristol Myers Squibb, Abbvie, MSD., Philippe Dieudé received grants from Novartis, Marion Couderc: None declared, Anne-Laure Fauchais: None declared, Claire Larroche: None declared, Olivier Vittecoq: None declared, Carine Salliot Carine Salliot received Honoria from Novartis, Roche Chugaï, Eric Hachulla: None declared, Véronique Le Guern: None declared, Jacques-Eric Gottenberg Jacques-Eric Gottenberg consulting fees from Abbvie, Astra Zeneca, Sanofi, Lilly, Galapagos, Gilead, Roche Chugai, Pfizer, Bristol Myer Squib, MSD., Jacques-Eric Gottenberg received grants from Pfizer, Abbvie, Lilly, Raphaèle Seror Raphaèle Seror received consulting fees from GSK, Bristol Myer Squib, Boerhinger and Janssen; honoraria from GSK, Bristol Myer Squib, Boehringer, Amgen, Pfizer and Roche; travel fees from Amgen and GSK;, Gaetane Nocturne: None declared.