DOP08 Transcriptional signatures of blood derived immune cells associated with disease location-based heterogeneity in IBD
Notice bibliographique
Résumé
Abstract Background Disease location is a prominent axis of heterogeneity in Inflammatory Bowel Disease (IBD) with many implications. Using genome-wide profiling of the transcriptome of monocytes and CD4+ T cells isolated and purified from whole blood, we aimed to identify molecular signatures and mechanisms associated with different locations among IBD patients. Methods Blood was collected from 125 IBD patients (87 CD, 38 UC) with endoscopy-proven active disease (presence of ulcerations). Cell separation and fluorescence activated cell sorting were performed to separate the monocyte and CD4+ T cell fractions, from which RNA was subsequently isolated and sequenced (Illumina HiSeq 4000NGS). We used different supervised and unsupervised approaches (differential expression, pathway based data integration, latent factor based models, regularized generalized canonical correlation analysis and co-expression networks) to interpret the differences in the gene expression datasets of monocytes and CD4+ T cells from patients with different disease locations (Montreal classification). Functional enrichment analysis was performed using the ReactomePA package. Regulatory relationships and therapeutic relevance information were retrieved from the ChEA3 and the OpenTargets resources respectively. Comparison with single-cell and bulk-derived gene expression signatures from other auto-immune diseases were performed using the ADEX resource. Results Highly variant disease-location (DL)-associated genes (FDR <= 0.1) in monocytes and CD4+ T cells were identified using latent factor based unsupervised models. These genes were known to be involved in IBD pathogenesis and/or intestinal inflammation. Additional supervised analysis revealed significant differences in CD4+ T cells between ileal CD patients and UC patients. RAF-independent MAPK-activation pathway and FOXO-mediated transcriptional pathway (downregulated in UC patients) were over-represented (FDR <= 0.05) among the features distinguishing ileal CD and UC patients based on signature sets derived from the above-mentioned multiple approaches. Of note was the finding that 12.5% of the DL associated co-expression modules were also annotated as IBD drug targets. Based on gene expression signature from bulk and single-cell sources, the DL associated genes were found to be active in many other auto-immune diseases such as rheumatoid arthritis, systemic sclerosis, Sjögren’s syndrome, type 1 diabetes and Systemic lupus erythematosus, suggesting their role in mediating immune malfunctions. Conclusion We identified signaling pathways and transcription factors which could drive the expression differences observed in the circulating immune cells between ileal CD and UC patients.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 ».