Association of autoantibodies with the IFN signature and NETosis in patients with systemic lupus erythematosus.

Autoantibodies Interferon signature NETosis Patient stratification Systemic lupus erythematosus

Journal

Journal of translational autoimmunity
ISSN: 2589-9090
Titre abrégé: J Transl Autoimmun
Pays: Netherlands
ID NLM: 101759413

Informations de publication

Date de publication:
Dec 2024
Historique:
received: 20 05 2024
revised: 11 06 2024
accepted: 15 06 2024
medline: 19 7 2024
pubmed: 19 7 2024
entrez: 19 7 2024
Statut: epublish

Résumé

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by a variety of disease symptoms and an unpredictable clinical course. To improve treatment outcome, stratification based on immunological manifestations commonly seen in patients with SLE such as autoantibodies, type I interferon (IFN) signature and neutrophil extracellular trap (NET) release may help. It is assumed that there is an association between these immunological phenomena, since NET release induces IFN production and IFN induces autoantibody formation via B-cell activation. Here we studied the association between autoantibodies, the IFN signature, NET release, and clinical manifestations in patients with SLE. We performed principal component analysis (PCA) and hierarchical clustering of 57 SLE-related autoantibodies in 25 patients with SLE. We correlated each autoantibody to the IFN signature and NET inducing capacity. We observed two distinct clusters: one cluster contained mostly patients with a high IFN signature. Patients in this cluster often present with cutaneous lupus, and have higher anti-dsDNA concentrations. Another cluster contained a mix of patients with a high and low IFN signature. Patients with high and low NET inducing capacity were equally distributed between the clusters. Variance between the clusters is mainly driven by antibodies against histones, RibP2, RibP0, EphB2, RibP1, PCNA, dsDNA, and nucleosome. In addition, we found a trend towards increased concentrations of autoantibodies against EphB2, RibP1, and RNP70 in patients with an IFN signature. We found a negative correlation of NET inducing capacity with anti-FcER (r = -0.530; p = 0.007) and anti-PmScl100 (r = -0.445; p = 0.03). We identified a subgroup of patients with an IFN signature that express increased concentrations of antibodies against DNA and RNA-binding proteins, which can be useful for further patient stratification and a more targeted therapy. We did not find positive associations between autoantibodies and NET inducing capacity. Our study further strengthens the evidence of a correlation between RNA-binding autoantibodies and the IFN signature.

Identifiants

pubmed: 39027720
doi: 10.1016/j.jtauto.2024.100246
pii: S2589-9090(24)00016-9
pmc: PMC11254743
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100246

Informations de copyright

© 2024 The Authors.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Ellen D Kaan (ED)

Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Oncode Institute, Utrecht, the Netherlands.

Tammo E Brunekreef (TE)

Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Julia Drylewicz (J)

Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Lucas L van den Hoogen (LL)

Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Maarten van der Linden (M)

Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Helen L Leavis (HL)

Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Jacob M van Laar (JM)

Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Michiel van der Vlist (M)

Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Oncode Institute, Utrecht, the Netherlands.

Henny G Otten (HG)

Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Maarten Limper (M)

Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Classifications MeSH