POS1431 CIRCULATING CD14+ MONOCYTES DISPLAY A PRO-MIGRATORY AND PRO-INFLAMMATORY PHENOTYPE IN INTERSTITIAL LUNG DISEASE ASSOCIATED WITH RHEUMATOID ARTHRITIS
Notice bibliographique
Résumé
Background: Interstitial lung diseases (ILD) represent a group of heterogeneous pulmonary fibrotic diseases often associated with rheumatoid arthritis (RA). The lack of reliable diagnostic or prognostic biomarkers, standardised treatments, and poor prognosis, as well as disease heterogeneity (usual interstitial pneumonia (UIP) and non-specific interstitial pneumonitis (NSIP)) represent a substantial clinical challenge, which can have a major impact on patient wellbeing. This is further confounded by the current knowledge gap in disease pathogenesis. Current evidence suggests an important role of the myeloid compartment both in RA and ILD, particularly in idiopathic pulmonary fibrosis (IPF). Both circulating monocytes and tissue resident macrophages have been shown to contribute to disease pathogenesis by driving and maintaining inflammation in synovial tissue in RA as well as in both chronic (IPF) and acute (COVID-19) lung disease [1, 2, 3]. Objectives: The aim of our study was to analyse the transcriptional profiles of circulating monocytes in people living with RA-ILD (both UIP and NSIP) to better understand their role in disease pathogenesis compared to healthy controls and people living with RA without ILD and ILD without RA (both UIP and NSIP). Methods: We included 39 patients in the analysis (13 RA, 10 RA ILD UIP, 8 RA ILD NSIP and 8 age and sex matched HC). CD14+ Monocytes were isolated from peripheral blood mononuclear cells using a magnetic negative selection kit with CD16 depletion. We then performed RNA sequencing on the samples. Results: There were no significant differences between groups in terms of disease duration, disease activity, conventional synthetic and biologic DMARDs and glucocorticoid dose. Circulating monocytes in RA-ILD UIP display a different transcriptomic profile compared to HC (Figure 1) and RA-ILD NSIP. Interestingly, expression of several chemokines facilitating tissue migration including CCL2 (Figure 2) and CCL7 were increased in RA-ILD UIP monocytes; compared to age and sex matched HC, RA, and RA-ILD NSIP. In addition, monocytes displayed increased capability to recruit other immune cells such as neutrophils and T cells as evidenced by the increased expression of CXCL16, CXCL1, CXCL2 , and CXCL3 . Finally, monocytes in RA-ILD displayed a pro inflammatory phenotype, as demonstrated by the increased expression of IL6, LIF, HIF1A, S100A10, S100A11, ADAMTS1 . Figure 1Principal component analysis reveals global differences in transcriptomic profiles between HC and RA-ILD UIP patients. Figure 2Circulating monocytes in RA-ILD UIP display increased CCL2 expression priming them to be trafficked to tissues, compared to RA and HC. Conclusion: Circulating monocytes in RA-ILD, particularly UIP, display differential transcriptomic profiles linked to key trafficking and inflammatory genes. This suggests that these cells are primed to migrate to tissues such as joints and the lungs. Utilising this specific phenotypic state as a disease stratifying biomarker would provide therapeutic avenues to explore and improve our understanding of the pathogenesis of both RA and ILD. REFERENCES: [1] Joy GM, Arbiv OA, Wong CK, Lok SD, Adderley NA, Dobosz KM, Johannson KA, Ryerson CJ. Prevalence, imaging patterns and risk factors of interstitial lung disease in connective tissue disease: a systematic review and meta-analysis. Eur Respir Rev. 2023 Mar 8;32(167):220210. doi: 10.1183/16000617.0210-2022. PMID: 36889782; PMCID: PMC10032591. [2] Poole, Jill A. et al. "Expansion of distinct peripheral blood myeloid cell subpopulations in patients with rheumatoid arthritis-associated interstitial lung disease." International immunopharmacology 127 (2023): 111330. [3] Sullivan, D.I., Ascherman, D.P. Rheumatoid Arthritis-Associated Interstitial Lung Disease (RA-ILD): Update on Prevalence, Risk Factors, Pathogenesis, and Therapy. Curr Rheumatol Rep 26, 431–449 (2024). https://doi.org/10.1007/s11926-024-01155-8 Acknowledgements: NIL . Disclosure of Interests: Lynn Stewart: None declared, Kieran Woolcock: None declared, Mario Ferraioli: None declared, Bruno Crestani BMS, GSK, SANOFI, Menarini, Boehringer Ingelheim, Abbvie, Astra Zeneca, Chiesi, GSK, Boehringer Ingelheim, Boehringer Ingelheim, Roche, Sanofi, Philippe Dieudé: None declared, Marie-Pierre Debray: None declared, Esther Ebstein: None declared, Madeleine Jaillet: None declared, Pierre-Antoine Juge: None declared, Victoria Keillor: None declared, Andrew Tong: None declared, Emily Smith: None declared, David Anderson: None declared, Aurelie Najm: None declared. © 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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».