ANTI-Β2GLYCOPROTEIN I-INDUCED NEUTROPHIL EXTRACELLULAR TRAPS CAUSE ENDOTHELIAL ACTIVATION
Notice bibliographique
Résumé
O001 / #144 Topic:AS03 - Antiphospholipid Syndrome SCIENTIFIC HYBRID SESSION: BASIC TRACK PRESENTATIONS - OUTSTANDING ABSTRACT PRESENTATIONS 23-05-2025 9:00 AM - 10:00 AM Background/Purpose Neutrophil extracellular traps (NETs) formation – NETosis – involvement in antiphospholipid syndrome (APS) pathogenesis is known, but the role of anti-β2glycoprotein I antibodies (aβ2GPI)-induced NETs in triggering a procoagulant and proinflammatory phenotype in endothelial cells (EC) remains to be evaluated. This study investigated whether aβ2GPI-induced NET can activate ECs and whether aβ2GPI-induced NET and phorbol myristate acetate (PMA)-induced NET have different proteomic profiles. Methods Healthy donors (HD) neutrophils were stimulated with aβ2GPI isolated from a pool of primary APS patient sera by affinity chromatography, normal human IgG or PMA. NETs were stained with antineutrophil elastase and DAPI, and the ability of aβ2GPI to bind NETs and inhibit DNA degradation was investigated. Following aβ2GPI, aβ2GPI-induced NET and PMA-induced NET stimuli, we evaluated EC activation investigating ICAM-1 (Intra-Cellular Adhesion Molecule 1), VCAM-1 (Vascular Cell Adhesion Molecule 1) and tissue factor (TF) expression using flow cytometry; and EC dysfunction analyzing extracellular microvesicles (EMVs) release via flow cytometry and NanoSight analysis. Mass spectrometry-based proteomics was performed on aβ2GPI-induced NET and PMA-induced NET. Results Unlike normal IgG, aβ2GPI induced NETosis and bound to NETs by colocalizing with the neutrophil elastase signal at 93.6 % without preventing NET degradation. Compared with unstimulated EC, aβ2GPI-induced NET triggered a robust expression of TF, VCAM and ICAM in EC with a change-fold MFI of 6 (SE 0.1), 4.2 (SE 0.09), 2.3 (SE 0.09). VCAM-1 and ICAM-1 were higher expressed in EA.hy926 treated with aβ2GPI-induced NET than those treated with aβ2GPI (p < 0.0001 in all instances) (Figure 1). aβ2GPI induced a significant increase in EMVs compared to untreated samples and those treated with NETs. Fifty-six proteins were identified, 7 resulted upregulated in aβ2GPI-induced NET and downregulated in PMA-induced ones. GO enrichment analysis revealed that proteins upregulated in aβ2GPI-induced NET were enriched for ubiquitin protein ligase binding and SLC2A4 translocation to the plasma membrane. Notably, triosphosphate isomerase 1 (TPI1), 14-3-3 epsilon protein (YWHAE) and tubulin alpha-1B (TUBA1B) proteins, upregulated in aβ2GPI-induced NET, showed functional relationships among themselves at network analysis that were distinct from other proteins, indicating unique interconnections within some aβ2GPI-induced NET proteins that differentiate them from PMA-induced NET proteins (Figure 2). Figure 1. Endothelial cells activation by aβ2GPI IgG-induced NETs. Figure 2. Proteomic analysis of aβ2GPI and PMA-induced NETs. Conclusions Taken together, these results emphasize that NETs from aβ2GPI and PMA are different in both composition and biological function. In conclusion, our findings describe how aβ2GPI-induced NET amplify endothelial cell activation and TF induction, unveiling a novel mechanism connecting the process of NETosis to thrombotic pathogenesis in APS.
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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) | 0,010 | 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 ».