Lupus and inflammatory bowel disease share a common set of microbiome features distinct from other autoimmune disorders.

autoimmune diseases lupus erythematosus, systemic machine learning spondylitis, ankylosing

Journal

Annals of the rheumatic diseases
ISSN: 1468-2060
Titre abrégé: Ann Rheum Dis
Pays: England
ID NLM: 0372355

Informations de publication

Date de publication:
18 Sep 2024
Historique:
received: 20 03 2024
accepted: 03 09 2024
medline: 20 9 2024
pubmed: 20 9 2024
entrez: 19 9 2024
Statut: aheadofprint

Résumé

This study aims to elucidate the microbial signatures associated with autoimmune diseases, particularly systemic lupus erythematosus (SLE) and inflammatory bowel disease (IBD), compared with colorectal cancer (CRC), to identify unique biomarkers and shared microbial mechanisms that could inform specific treatment protocols. We analysed metagenomic datasets from patient cohorts with six autoimmune conditions-SLE, IBD, multiple sclerosis, myasthenia gravis, Graves' disease and ankylosing spondylitis-contrasting these with CRC metagenomes to delineate disease-specific microbial profiles. The study focused on identifying predictive biomarkers from species profiles and functional genes, integrating protein-protein interaction analyses to explore effector-like proteins and their targets in key signalling pathways. Distinct microbial signatures were identified across autoimmune disorders, with notable overlaps between SLE and IBD, suggesting shared microbial underpinnings. Significant predictive biomarkers highlighted the diverse microbial influences across these conditions. Protein-protein interaction analyses revealed interactions targeting glucocorticoid signalling, antigen presentation and interleukin-12 signalling pathways, offering insights into possible common disease mechanisms. Experimental validation confirmed interactions between the host protein glucocorticoid receptor (NR3C1) and specific gut bacteria-derived proteins, which may have therapeutic implications for inflammatory disorders like SLE and IBD. Our findings underscore the gut microbiome's critical role in autoimmune diseases, offering insights into shared and distinct microbial signatures. The study highlights the potential importance of microbial biomarkers in understanding disease mechanisms and guiding treatment strategies, paving the way for novel therapeutic approaches based on microbial profiles. NCT02394964.

Identifiants

pubmed: 39299726
pii: ard-2024-225829
doi: 10.1136/ard-2024-225829
pii:
doi:

Banques de données

ClinicalTrials.gov
['NCT02394964']

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ on behalf of EULAR.

Déclaration de conflit d'intérêts

Competing interests: MAK received salary, consulting fees, honoraria or research funds from Eligo Biosciences, Enterome, Novartis, Roche, Genentech, Bristol-Meyers Squibb, Sanofi, and AbbVie, and holds a patent on the use of microbiota manipulations to treat immune-mediated diseases. HZ is both a salaried employee and a shareholder of Moderna.

Auteurs

Hao Zhou (H)

Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.

Diana Balint (D)

Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.

Qiaojuan Shi (Q)

Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA.

Tim Vartanian (T)

Weill Cornell Medicine, New York, New York, USA.

Martin A Kriegel (MA)

Department of Translational Rheumatology and Immunology, Institute of Musculoskeletal Medicine, Münster, Germany.
Section of Rheumatology and Clinical Immunology, University Hospital Münster, Münster, Germany.
Cells in Motion Interfaculty Centre, University of Münster, Münster, Germany.
Department of Immunobiology, Yale School of Medicine, New Haven, Connecticut, USA.

Ilana Brito (I)

Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York, USA ibrito@cornell.edu.

Classifications MeSH