Evaluation of classical and novel autoantibodies for the diagnosis of Primary Biliary Cholangitis-Autoimmune Hepatitis Overlap Syndrome (PBC-AIH OS)
Notice bibliographique
Résumé
BACKGROUND AND AIMS: Up to 20% of Primary Biliary Cholangitis (PBC) patients are estimated to have features that overlap with Autoimmune Hepatitis (AIH). Patients with PBC-AIH overlap syndrome (PBC-AIH OS) have been reported to exhibit suboptimal responses to ursodeoxycholic acid therapy, and are more likely to progress to cirrhosis. Anti-double stranded DNA (anti-dsDNA) and anti-p53 have been previously suggested to be potential autoantibodies for identifying patients with PBC-AIH OS. In our well defined PBC patient cohorts, a comprehensive assessment of various classical and novel autoantibodies was evaluated for their utility in identifying PBC-AIH OS patients. METHODS: PBC-AIH OS was classified according to the Paris criteria and PBC as per the European Association for the Study of the Liver guidelines. Biobanked serum samples from 197 patients at the University of Calgary Liver Unit and the University of Alberta were analyzed for classical and novel autoantibodies. Anti-dsDNA was measured by the Crithidia luciliae immunofluorescence (CLIFT) assay (1:20 dilution) and chemiluminescence (CIA: QUANTA Flash®, Inova Diagnostics, San Diego). Anti-p53, anti-Ro52/TRIM21, anti-YB 1, anti-GW182, anti-Ge-1, and anti-Ago 2 were measured by either an addressable laser bead immunoassay (ALBIA) or line immunoassay (LIA). Autoantibodies against MIT3, gp210, sp100, LKM1, SLA, and the novel autoantibodies Hexokinase-1 (HK-1), and Kelch like protein 12 (KLHL-12) were measured using QUANTA Lite® ELISA assays. We applied non-parametric methods to compare the biomarkers frequencies between study groups. We used multivariate adjusted models and AUROC to compare the diagnostic accuracy of the different autoantibodies alone or in combination with serum biochemistry. RESULTS: 16 out of 197 PBC patients (8.1%) were classified as PBC-AIH OS. Compared to PBC patients, PBC-AIH OS patients were similar in age (median: 59 vs. 63, P = 0.21) and female predominance (94% vs. 89%, P = 1.00). Anti-dsDNA-by CLIFT (37.5% in PBC-AIH OS vs 9.9% in PBC alone, P <0.01) was the only autoantibody associated with PBC-AIH OS; a finding consistent with previous reports. Significant elevation in serum ALT (62 IU/L in PBC-AIH OS vs 37 IU/L in PBC alone, P < 0.01), and serum IgG (17.6 g/L in OS vs 12.1 g/L in PBC alone, P <0.01) were observed in patients with PBC-AIH OS receiving medical/immunosuppressive therapy. In a multivariate model, positive anti-dsDNA by CLIFT, ALT and IgG were significant predictors of PBC-AIH OS with an area under the receiver operator curve (AUROC) value of 0.84. CONCLUSIONS: Consistent with previous findings, the presence of anti-dsDNA by CLIFT is associated with PBC-AIH OS. Contrary to previous reports, anti-p53 was not associated with PBC-AIH OS. Our comprehensive evaluation of various classical and novel autoantibody biomarkers including Ro52/TRIM21, anti-p53, anti-KLHL-12 and anti-HK-1 were not significantly associated with PBC-AIH OS. Our findings highlight the ongoing need for the research and development of new autoantibody biomarkers to aid in the diagnosis of PBC-AIH OS.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| 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) | 0,000 | 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 tête enseignante, 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 ».