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Enregistrement W4411410478 · doi:10.1016/j.ard.2025.06.771

POS1423 ALTERATIONS IN INNATE IMMUNE POPULATIONS DURING SYSTEMIC AUTOIMMUNE RHEUMATIC DISEASE DEVELOPMENT

2025· article· en· W4411410478 sur OpenAlexaff
Claudio Ucciferri, Carine M. Nassar, Sindhu R. Johnson, Zahi Touma, Zareen Ahmad, Dennisse Bonilla, Linda T. Hiraki, Arthur Bookman, Tracy L. McGaha, Igor Jurišica, Joan Wither

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiqueImmunodeficiency and Autoimmune Disorders
Établissements canadiensHospital for Sick ChildrenUniversity of TorontoUniversity Health NetworkPrincess Margaret Cancer CentreToronto Western HospitalMount Sinai HospitalKrembil Foundation
Organismes subventionnairesnon disponible
Mots-clésMedicineInnate immune systemImmunologyRheumatic diseaseAutoimmune diseaseImmune systemDiseaseRheumatologyRheumatoid arthritisAntibodyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Background: Systemic autoimmune rheumatic diseases (SARD) are a group of chronic diseases characterized by the presence of anti-nuclear antibodies (ANAs). However, ANAs cannot reliably be used as a diagnostic tool because a subset of healthy women are ANA + (~20%) and the majority of these individuals will not progress to SARD. Why some individuals progress while others remain asymptomatic is unknown. Previous work suggests that monocytes/dendritic cells (DCs) may support immunological disturbances observed in SARD, including a shift toward a T helper (Th) 17 cell phenotype with a concurrent decrease in Tregs. Objectives: To evaluate functional alterations in innate immune populations during SARD development. Methods: Experiments have been completed to examine the composition of innate immune cells in PBMCs using CITE-Seq. Samples were used from 5 ANA - healthy controls, 11 ANA + asymptomatic (5 progressors sampled prior to progression, 6 non-progressors) and 8 early SARD patients (4 Systemic Lupus Erythematosus, 4 Sjogren's disease). Five million freshly thawed PBMCs were depleted of T and B cells by negative selection, and stained with a panel of oligo-conjugated antibodies for the identification of DC/monocyte populations. 9000 cells were sequenced at a depth of 50000 reads for gene expression and 5000 reads for CITE-Seq. Results: Using both gene and surface protein expression, we identified 11 distinct DC and monocyte populations (Figure 1A). Proportional analysis revealed an expansion of non-classical and activated non-classical monocytes in progressor and SARD patients (Figure 1B). SARD patients also exhibited higher proportions of cDC3s, VCAN+ monocytes and MME+ DCs than ANA + individuals regardless of progression status (Figure 1B), suggesting a role for these cells in active disease. Comparing asymptomatic ANA + individuals, we found that classical, intermediate, and non-classical monocytes were expanded in progressors while cDC1s, cDC2s and pDCs were expanded in non-progressors (Figure 1B). Differential gene expression analysis showed high expression of interferon (IFN) stimulated genes in progressors and SARD patients (Figure 1C), implicating these pro-inflammatory cytokines in the transition to SARD. Interestingly, non-progressors exclusively had elevated expression of heat shock proteins and CD52 (Figure 1C), which have been shown to promote immunologic tolerance and may play a role in preventing progression to SARD. In contrast, progressors had elevated HLA expression (Figure 1C), suggesting enhanced antigen presentation capacity. These differences in gene expression were observed across cell types (intermediate monocytes are shown as representative cells due to their role in antigen presentation in Figure 1C). Pathway analysis confirmed that genes associated with T cell activation are increased in the innate immune populations of progressors and genes associated with the heat shock response are increased in non-progressors. Notably, non-progressors with high levels of IFN-induced gene expression had low levels of heat shock proteins and HLA expression, but elevated levels of CD52, suggesting that the reported ability of high levels of IFN to promote development of SARD may be due to in part that an altered ability to support T cell tolerance. Several genes were differentially expressed between progressors and SARD (Figure 1C), potentially highlighting distinct roles for genes in initiating and driving disease. Figure 1 A ) UMAP of 11 annotated monocyte and DC clusters . B ) Proportional analysis showing each cluster for control, non-progressor, progressor and SARD groups. Data was normalized to account for differences in cell counts per cluster and per patient sample. C ) Heatmap showing differentially expressed genes in intermediate monocytes as a representative cell cluster. Similar trends were seen in the remaining cell types. Red arrows indicate genes of interest that are differentially expressed between progressor and SARD groups. Blue bars indicate differentially expressed genes between progressors and non-progressors. Conclusion: Our data reveals differences in proportions and gene expression between progressors, non-progressors and SARD patients. Importantly, ANA + progressors show expanded monocyte populations and functional differences compared to non-progressors prior to progression, highlighting immune disturbances even in the asymptomatic, pre-clinical stage of SARD. The results provide insight into the immune mechanisms that drive progression from asymptomatic autoimmunity to disease in SARD. REFERENCES: NIL . Acknowledgements: NIL . Disclosure of Interests: 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 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)0,000
score de la tête « metaresearch » (Gemma)0,000
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,013

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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 Opus0,022
Tête enseignante GPT0,278
Écart entre enseignants0,255 · 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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Même revueAnnals of the Rheumatic DiseasesMême sujetImmunodeficiency and Autoimmune DisordersTravaux en français237 207