Genetic and Immune Predictors for Hypersensitivity Syndrome to Antiepileptic Drugs
Notice bibliographique
Résumé
Abstract Hypersensitivity syndrome reactions (HSR) to antiepileptic drugs (AED) are associated with severe clinical cutaneous adverse reactions (SCAR).Our aims are: to assess HSRs to AEDs using the in vitro lymphocyte toxicity assay (LTA) in patients who manifested HSRs clinically, to correlate LTA results with the clinical syndrome, to correlate LTA results with the human leukocyte antigen (HLA) allele B*1502 (HLA-B*1502) positivity in a Han Chinese-Canadian population, and to determine the cytokine network in this population. HSR patients developed fever and cutaneous eruptions in the presence or absence of organ involvement within 8 weeks of exposure to carbamazepine (CBZ), phenytoin (PHY) or lamotrigine (LTG). Control patients received AEDs without presenting HSR. We investigated 10 CBZ-HSR (4 presented with Stevens-Johnson syndrome (SJS)), 24 CBZ-controls, 10 PHY-HSR (4 presented with drug-induced liver injury (DILI)), 24 PHY-controls, 6 LTG-HSR (1 SJS and 1 DILI) and 24 LTG-controls. There were 30 Han Chinese individuals (14 HSR patients and 16 controls) in our cohort. LTA toxicity greater than 12.5%&177;2.5% was considered positive. Differences among groups were determined by analysis of variance. In addition, we measured cytokine secretion in the patient sera between 1 month and 3 years after the event. All Han Chinese individuals and 30% of Caucasians were genotyped for HLA-B*1502.A perfect correlation (r=0.92) was observed between positive LTA and clinical diagnosis of DILI and SJS/toxic epidermal necrolysis (TEN). HLA-B*1502 positivity in Han Chinese is a predictor of CBZ-HSR and PHY-HSR. HLA-B*1502-negative Han Chinese receiving only CBZ or a combination of CBZ-PHY tolerated the drug(s) clinically, presenting negative CBZ-LTA and PHY-LTA. However, 3 patients presenting negative CBZ-LTA and PHY-LTA, as well as negative HLA-B*1502, showed positive LTG-LTA (38%, 28% and 25%, respectively), implying that they should not be prescribed LTG. Three patients had LTA positive to both PHY and CBZ, and 3 others had LTA positive to both PHY and LTG. Clinically, all six patients presented HSR to both drugs that they tested positive to (cross-reactivity). Patients were grouped based on the clinical presentation of their symptoms as only rash and fever or a triad that characterizes "true" HSR (rash, fever and DILI or SJS/TEN). Levels of pro-inflammatory cytokines were significantly higher in patient sera compared to control sera. More specifically, the highest levels of tumor necrosis factor (TNF)-&x03B1; was measured in patients presenting "true" HSR, as were the apoptotic markers Fas, caspase 8 activity and M30. We concluded that LTA is sensitive for DILI and SJS/TEN regardless of drug or ethnicity. HSR prediction will prevent AED-induced morbidity. In Han Chinese, HLA-B*1502 positivity is a predictor for CBZ-HSR and PHY-HSR. Its negativity does not predict a negative LTG-HSR. There is cross-reactivity between AEDs. Additionally, T-cell cytokines and chemokines control the pathogenesis of SJS/TEN and DILI, contributing to apoptotic processes in the liver and in the skin.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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) | 0,003 | 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 ».