ANTI-TRIM72 Autoantibodies IN SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS AND A LUPUS MOUSE MODEL WITH MYOCARDITIS COMPROMISE MEMBRANE REPAIR IN CARDIOMYOCYTES POTENTIALLY CONTRIBUTING TO CARDIOVASCULAR DISEASE PROGRESSION
Notice bibliographique
Résumé
PV008 / #647 Poster Topic: AS02 - Animal Models Background/Purpose Systemic Lupus Erythematosus (SLE) is a chronic autoimmune disease that causes inflammation in many of the body’s tissues, including the heart. Recent studies attribute almost 50% of mortality in lupus patients to cardiovascular (CV) disease after the first 10 years. A significant prevalence of myocardial inflammation in SLE patients has been recognized across the age spectrum confirming the presence of myocarditis in up to 40% of lupus patients. Understanding the pathogenic mechanisms that drive CV disease in SLE patients is essential for its management and for developing new therapeutic approaches. Our studies and others link reduced plasma membrane repair with development of CV disease. Given the importance of the membrane barrier function in preventing exposure of intracellular antigens to the extracellular space where they could act as autoantigens, compromised membrane repair may be a contributory mechanism to SLE pathogenesis. Previous studies have linked the Tripartite Motif (TRIM) family of E3 ubiquitin ligase proteins to membrane repair and as autoantigens in lupus. Our recently published work identified TRIM72 as a new autoantigen in myositis patients and our current studies indicate this may be the case in lupus as well. Given the potential contribution of membrane repair to the development of lupus-associated myocarditis and the role of TRIM72 in membrane repair, we hypothesized that defects in membrane repair are critical in the pathogenesis of lupus myocarditis leading to aberrant exposure of membrane repair proteins to the extracellular space and these autoantibodies create a positive-feedback loop that causes further exposure of intracellular antigens that contributes to the progression of lupus myocarditis pathogenesis. Methods A custom anti-TRIM72 antibody ELISA was used to quantify serum levels of circulating TRIM72 antibodies in mouse and human samples. Multiphoton confocal laser microscopy was used to measure the dynamics of membrane repair in vitro. Single nuclei (sn) RNAseq of NZM2410 mouse hearts was performed on young, middle and old aged mice. Partek™ Flow™ software was used to QC, normalize and analyze the transcriptomic expression data. Results We demonstrate that anti-TRIM72 autoantibodies are elevated in both SLE patient serum diagnosed with myocarditis and serum of NZM2410 mice with myocarditis. A polyclonal antibody against TRIM72, as well as both SLE patient serum and NZM2410 serum containing TRIM72 antibodies compromise membrane repair in vitro. snRNAseq revealed that cardiomyocytes are reduced and fibroblasts increase as NZM2410 mice age. Specific CV disease pathways are enriched in cells of aged hearts of NZM2410 mice as compared to young mice. Genes linked to lupus disease pathology are differentially expressed in immune cells (Figure). Subcluster analysis of specific cell populations, eg, cardiomyocytes, fibroblasts, etc. revealed several cell types and gene expression profiles associated with development of SLE myocarditis. Figure. Transcriptomic analysis of cardiac tissue reveals multiple differentially expressed genes linked to lupus. A partial list of statistically significant differentially expressed genes in immune cells is shown. Conclusions The plasma membrane repair protein TRIM72 is an autoantigen in SLE-associated myocarditis and potentially contributes to disease pathogenesis. We demonstrate the presence of TRIM72 antibodies in SLE patients that can compromise membrane repair in cardiomyocytes in vitro. Transcriptomics of cardiac tissue. Ongoing studies will examine if these defects could lead to membrane repair protein exposure to the extracellular space causing the production of additional autoantibodies which contribute to a vicious cycle that exacerbates SLE pathology.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,002 |
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 ».