MECHANISMS PROTECTING MALES FROM DEVELOPMENT OF SLE
Notice bibliographique
Résumé
PV108 / #408 Poster Topic: AS12 - Genetics, Epigenetics, Transcriptomics Background/Purpose Among the autoimmune rheumatic diseases, the highest female prevalence is observed in SLE, suggesting that sex-related pathways are important contributors to disease pathogenesis. Several hypotheses have been presented to explain the extreme 9-10:1 female:male skewing of SLE, with a role for sex hormones, X chromosome dose, and incomplete X chromosome inactivation (XCI) currently dominating this field of research. We have taken a novel experimental approach by investigating the cellular and molecular factors that protect males from development of SLE. Our goal is to gain new understanding of the skewed sex-related occurrence of SLE, thereby identifying new therapeutic approaches. Methods The study groups included 15 females with SLE, 15 males with SLE, all from our longitudinal SLE cohort established at Hospital for Special Surgery, and 15 female and 15 male healthy donor subjects, well matched for age and ancestry with the SLE patients. RNA sequencing of PBMC was performed and data analyzed using principal component analysis (PCA) and determination of differentially expressed gene transcripts. Results PCA showed a larger difference in RNA transcripts between SLE males and healthy males than between SLE females and healthy females. Weighted gene co-expression analysis identified 24 groups of co-expressed and functionally related transcripts, with female and male SLE patients demonstrating considerable overlap of common disease-associated genes, including type I interferon-stimulated genes, neutrophil-related genes, and B cell/plasmablast transcripts. However, transcripts associated with the NF-kB and epidermal growth factor receptor pathways were expressed at a significantly higher level in SLE males than in healthy males, while those pathways were expressed at comparable levels between SLE and healthy donor females. In contrast, gene transcripts typically expressed in natural killer (NK) cells, including KLRK1, KLRC3, KLRC4 and CADM1 , were expressed at a significantly lower level in SLE males than in healthy males. In addition, several Y chromosome-encoded genes, namely KDMD5D , encoding a histone demethylase that is expressed in NK cells, and TXLNGY were expressed at a significantly lower level in SLE males than in healthy males (adjusted p < 0.01 for comparison with healthy males for both genes). Conclusions Our data suggest that NK cells may represent an important protective cell type that limits development of SLE in most males. Moreover, our data point to several Y chromosome-encoded genes that are decreased in expression in SLE males and may contribute to altered epigenetic regulation of immune system cells, including NK cells, leading to impaired control of autoimmunity and development of SLE in some males. Further characterization of these alterations in SLE males may identify novel approaches for limiting development or severity of SLE in both males and females.
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 | 0,000 | 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) | 0,004 | 0,001 |
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.
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 ».