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Enregistrement W4411427382 · doi:10.1016/j.ard.2025.05.264

OP0254 MICROBIOTA AND CLINICAL RESPONSES TO BIOLOGICAL TREATMENT IN AXIAL SPONDYLOARTHRITIS: INSIGHTS FROM 2 YEAR FOLLOW UP OF THE GESPIC COHORT

2025· article· en· W4411427382 sur OpenAlexaff
Valeria Ríos Rodríguez, M. Essex, Murat Torğutalp, Fabian Proft, H. Haibel, Mikhail Protopopov, Judith Rademacher, Britta Siegmund, Sofia K. Forslund, Denis Poddubnyy

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueSpondyloarthritis Studies and Treatments
Établissements canadiensToronto General HospitalToronto Western Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineAxial spondyloarthritisCohortCohort studyPhysical therapyAnkylosing spondylitisInternal medicineSacroiliitis

Résumé

récupéré en direct d'OpenAlex

Background: Increasing evidence suggest that gut microbiota may contribute to the pathogenesis of axial spondyloarthritis (axSpA), potentially through immune activation and systemic inflammation. It remains unclear how biological disease-modifying antirheumatic drugs (bDMARDs) influence the gut microbiota composition, and whether these changes impact differential treatment outcomes or hold prognostic value. Most existing data are cross-sectional or focused on short-term effects, highlighting a need for prospective longitudinal studies. Objectives: This study aimed to characterize the microbiota composition in patients with radiographic (r-)axSpA undergoing bDMARD therapy identifying microbial signatures predictive of treatment response and explore longitudinal shifts in the gut microbiota between responders and non-responders over a two-year period. Methods: Patients with r-axSpA from an extension arm of the German Spondyloarthritis Inception Cohort (GESPIC) were included in this analysis. Eligibility criteria included high disease activity despite prior intake of nonsteroidal anti-inflammatory drugs and have not received bDMARD therapy for at least three months prior enrollment. The choice of bDMARD therapy followed standard clinical practice at the discretion of the responsible rheumatologist. Disease activity (Axial Spondyloarthritis Disease Activity Score – ASDAS) was assessed at baseline and at each follow-up visit. Fecal samples were collected at baseline and yearly thereafter until year 2. Patients with chronic back pain without a diagnosis of inflammatory disease were included as a control group. Clinical response was defined as a change in ASDAS ≥2.0 points for major improvement (ASDAS-MI) and ≥ 1.1 points for clinically important improvement (ASDAS-CII). Shotgun metagenomic sequencing was performed on 247 fecal samples (62 patients and 62 controls), 237 of which passed quality control. Taxonomic profiling used the CHAMP TM pipeline, which leverages a comprehensive reference catalog of microbial genomes, annotated with GTDB (version r214). Species abundances were rarefied to a fixed number of signature gene counts to account for differences in sequencing depth. Associations with patient characteristics, treatment response, and longitudinal changes were analyzed using linear mixed-effect models, adjusted for baseline disease activity and false discovery rate (FDR) corrections. Results: Among the 62 patients included, 62.3% were male, with a mean age of 38.7 ± 10.7 years at baseline. The prevalence of HLA-B27 was 83.6% among patients and 7.9% among the controls. A total of 81.9% of patients were naïve to bDMARDs at baseline. Patients presented a mean ASDAS of 3.44 ± 0.78 at baseline. The largest decrease in ASDAS occurred between baseline and year 1, reaching clinical response rates of 37.7% for ASDAS-MI and 67.2% for ASDAS-CII at year 1. Alpha diversity showed no significant differences between responders and non-responders at any timepoint. However, non-responders had notably distinct microbiota profiles from other groups, especially at year 1 (Figure 1). Blautia A caecimuris was identified as the main negative predictor for treatment response, with a higher prevalence among non-responders. Higher baseline abundances associated with poor response to bDMARDs. Other species such as Bacteroides xylanisolvens and ER4 sp900317525 (of the Clostridia class) showed the opposite trend, associating with a good clinical response. Temporal changes in the gut microbiota species abundances revealed significant differences between bDMARD therapy responders and non-responders (according to CII) over the two-year period (Figure 2). The strongest microbial shifts were observed in non-responders, with significant increases in Prevotella rara, Dysosmobacter sp944387015, and Bacteroides xylanisolvens ; decreases were observed in Collinsella sp002391315, Bacteroides nordii, and Dysosmobacter faecalis . Interestingly, these species showed no significant changes in responders over the same time period, except for Prevotella rara (increased in responders) and Ventricola sp900542395 (decreased in responders). Conclusion: In this longitudinal analysis, non-responders to bDMARD therapy had distinct microbiota composition at baseline, and presented distinct species shift during treatment. Taxonomic shifts in responders were more subtle, although often in the opposite direction of non-responders. To develop more personalized treatment strategies in axSpA, the present study highlights how metagenomic sequencing is able to unravel persistent fecal signatures with potential prognostic value. REFERENCES: NIL . Acknowledgements: NIL . Disclosure of Interests: Valeria Rios Rodriguez AbbVie and Takeda, AbbVie, Eli Lily, Jannsen, UCB and Pfizer, Morgan Essex: None declared, Murat Torgutalp: None declared, Fabian Proft AbbVie, AMGEN, BMS, Celgene, Janssen, Hexal, Medscape, Moonlake, MSD, Pfizer and Roche, Novartis, Eli Lilly and UCB, Hildrun Haibel Abbvie, Novartis, Pfizer, Janssen, GSK, Sobi, UCB, Abbvie, UCB, Janssen, Sobi, Novartis, Pfizer, Sobi, Novartis, Pfizer, UCB, Alfasigma, Mikhail Protopopov: None declared, Judith Rademacher: None declared, Britta Siegmund AbbVie, AlfaSigma, BMS, CED Service GmbH, Dr. Falk Pharma, Eli Lilly, MSD, Ferring, Galapagos, Janssen, Pfizer, and Takeda, AbbVie, Abivax, Boehringer Ingelheim, Bristol Myers Squibb, Dr. Falk Pharma, Eli Lilly, Endpoint Health, Falk, Galapagos, Gilead, Janssen, Landos, Lilly, Materia Prima, PredictImmune, Pfizer, and Takeda, Pfizer, Sofia Forslund: None declared, Denis Poddubnyy AbbVie, Canon, DKSH, Eli Lilly, Janssen, MSD, Medscape, Novartis, Peervoice, Pfizer, and UCB, AbbVie, Biocad, Bristol-Myers Squibb, Eli Lilly, Janssen, Moonlake, Novartis, Pfizer, and UCB, AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, UCB. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,048
Tête enseignante GPT0,346
Écart entre enseignants0,298 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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