Distinct Pathophysiologic Pathways Support Stratification of Sjögren's Disease Based on Symptoms, Clinical, and Routine Biological Data
Year: 2024
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: Recently, three distinct phenotypes of patients with Sjögren disease (SjD) have been described based on cluster analysis: B cell active with low symptoms (BALS), high systemic activity (HSA), and low systemic activity with high symptoms (LSAHS). We aimed to assess whether these clusters were associated with distinct biomarkers and the prognostic value of interferon (IFN) signature. METHODS: The Assessment of Systemic Signs and Evolution in Sjögren's Syndrome cohort is a 20-year prospective cohort of patients with SjD. The following biomarkers were compared: IFN-α2, IFN-γ, CXCL10, CXCL13, BAFF, interleukin (IL)-7, fms-like tyrosine kinase 3 ligand, CCL19, and tumor necrosis factor receptor 2 (TNF-RII). IFN signature was assessed using transcriptomic analysis. We then compared systemic and symptomatic evolution, and the risk of new immunosuppressant prescription and of lymphoma, according to the IFN signature across the three clusters. RESULTS: A total of 395 patients (94% female, median age 53 [interquartile range 43-63] years) were included. Higher levels of CXCL13, IL-7, and TNF-RII were found in the BALS and HSA clusters compared with the LSAHS cluster. A high IFN signature was mainly found in the BALS cluster (57%, vs 48% and 38% in the HSA and LSAHS clusters, respectively). This IFN signature was mainly driven by type I IFN, with higher levels of IFN-α2. In the BALS cluster, a high IFN signature was associated with a higher risk of new immunosuppressant treatment (hazard ratio 9.38; 95% confidence interval 1.22-72.16). All lymphoma occurred in patients with high IFN signature. CONCLUSION: The three SjD clusters displayed distinct expressions of IFN signature and markers of T and B cell activation, confirming distinct pathophysiologic mechanisms. High IFN signature could predict systemic evolution in the BALS cluster.
Source: Arthritis & Rheumatology
DOI: 10.1002/art.43096
Authors: Yann Nguyen, Maxime Beydon, Jacques‐Eric Gottenberg, Jacques Morel, Aleth Perdriger, Emmanuelle Dernis, Divi Cornec, Valérie Devauchelle‐Pensec, Damien Sène, Philippe Dieudé, Marion Couderc, Anne‐Laure Fauchais, Claire Larroche, Olivier Vittecoq, Carine Salliot, Eric Hachulla, Véronique Le Guern, Xavier Mariette, Raphaèle Seror, Gaëtane Nocturne
Institutions: Inserm, Université Paris Cité, Université Paris-Saclay, Hôpital Beaujon, Assistance Publique – Hôpitaux de Paris, Bicêtre Hospital, Centre de Recherche Épidémiologie et Statistique, Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Centre National de la Recherche Scientifique, Université de Montpellier, Physiologie et Médecine Expérimentale du Coeur et des Muscles, Centre Hospitalier Universitaire de Montpellier, Centre Hospitalier Universitaire de Rennes, Université de Rennes, Université de Bretagne Occidentale, Centre Hospitalier Régional Universitaire de Brest, Université de Bretagne Occidentale, Hôpital Lariboisière, Hôpital Bichat-Claude-Bernard, Physiopathologie et Epidémiologie des Maladies Respiratoires, Université Clermont Auvergne, Centre Hospitalier Universitaire de Clermont-Ferrand, Centre Hospitalier Universitaire de Limoges, Université de Limoges, Hôpital Avicenne, Centre Hospitalier Universitaire de Rouen, Centre hospitalier universitaire d'Orléans, Université de Lille, Centre Hospitalier Universitaire de Lille, Institute for Translational Research in Inflammation, Hôpital Cochin
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4405800244