Autoantibodies to Thrombopoietin and the Thrombopoietin Receptor in Patients with Immune Thrombocytopenia
Notice bibliographique
Résumé
Abstract Background: Primary immune thrombocytopenia (ITP) is an autoimmune bleeding disorder caused by autoantibodies against platelet glycoproteins (GP). These autoantibodies are detected in only 40-60% of ITP patients even when sensitive techniques are used. Our understanding of the mechanisms of ITP is limited by the variability in clinical presentation, varied differences in treatment responses and the lack of reliable biomarkers. Several studies have exploited the possibilities of other immune-mediated mechanisms to account for low platelet counts in the absence of detectable antibodies. Thus, we hypothesized that other autoantibodies that target antigens involved in the platelet lifecycle can be important in ITP, such as thrombopoietin (TPO) and the thrombopoietin receptor (cMpl). The objective of this study was to evaluate the frequency and clinical significance of autoantibodies against TPO and cMpl in patients with ITP compared to patients with other thrombocytopenic disorders and healthy controls. Methods: We tested well-defined adult ITP patients with a platelet count less than 100 x109/L and ITP patients in remission (platelets > 100,000) all of whom had not received any immune-modulating treatments in the previous 3 months. We also tested patients with other immune-mediated platelet disorders, non-immune thrombocytopenia and healthy controls. Patients with immune-mediated platelet disorders had anti-phospholipid syndrome (APS); heparin induced thrombocytopenia (HIT); or thrombotic thrombocytopenic purpura (TTP). Patients with non-immune thrombocytopenia had hypersplenism with documented splenic enlargement; familial thrombocytopenia; or myelodysplastic syndrome. Samples were tested for circulating antibodies against TPO or cMpl using newly developed enzyme immunoassays (EIAs) and for antibodies against platelet glycoproteins (GPIIb/IIIa and GPIb/IX) using the antigen capture assay. Results: Among patients with active ITP, 36/42 (86%) had antibodies to TPO or c-Mpl: 4/42 (10%) had anti-TPO autoantibodies only and 5/42 (12%) had anti-cMpl autoantibodies only and 15/42 (36%) had both. Among patients with ITP in remission, 8/15 (53%) had autoantibodies to TPO or cMpl. Autoantibodies were not detected in healthy controls; however, all patients with non-immune thrombocytopenia had circulating autoantibodies to TPO or c-Mpl (10/10, 100%): 1/10 (10%) had anti-TPO autoantibodies only and 1/10 (10%) had anti-cMpl autoantibodies only and 8/10 (80%) had both. We also found antibodies against TPO and cMpl in patients with other immune-mediated platelet disorders. Among HIT patients (n=26), 73% had antibodies to TPO and 50% had antibodies to cMpl; among TTP patients (n=16), 31% had antibodies to TPO and 13% had antibodies to cMpl; and among APS patients (n=17), 29% had antibodies to TPO and 47% had antibodies to cMpl. Platelet bound antibodies to GPIIb/IIIa, GPIb/IX or both were detected in 18/42 (43%) active ITP samples; 6/15 (40%) remission ITP samples; and 2/10 (20%) patients with thrombocytopenia from non-immune causes. ITP patients with anti-TPO or anti-cMpl antibodies required fewer ITP therapies before remission was achieved compared with patients who had anti-GP autoantibodies. Conclusions: Testing the entire panel of autoantibodies that included anti-TPO, anti-cMpl and anti-GP, we were able to identify all patients with active ITP; however, we could not distinguish between patients with ITP and other thrombocytopenic syndromes. Disclosures Arnold: Novartis: Consultancy, Research Funding; Bristol Myers Squibb: Consultancy; UCB: Consultancy; Amgen: Consultancy, Research Funding.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».