Fetal and Neonatal Alloimmune Thrombocytopenia: Lessons Learned from Animal Models
Notice bibliographique
Résumé
Abstract Fetal and neonatal alloimmune thrombocytopenia (FNAIT) is a severe alloimmune disorder that results from fetal/neonatal platelet opsonization by maternal antibodies, which cross the placenta and result in fetal/neonatal platelet destruction. The frequency of FNAIT has been estimated at 0.5-1.5/1,000 liveborn neonates. However, this number does not include fetuses that die from this disease, since the incidence of FNAIT miscarriage has not been adequately studied. Analogous to autoimmune thrombocytopenia (ITP), the major target antigens in FNAIT are the platelet GPIIIa (β3 integrin) and GPIbα. However, severe bleeding is much more frequent in FNAIT, particularly the occurrence of intracranial hemorrhage (ICH). It is not known why the reported incidence of FNAIT mediated by anti-GPIbα antibodies is at a much lower frequency when compared to ITP, and whether the severe bleeding tendency in FNAIT is due to β3 integrin expression on angiogenic vessels in the developing fetus, which are targeted by cross-reacting maternal anti-β3 integrin antibodies. To study the pathogenesis and to develop new strategies for prevention and treatment, we have established murine models of FNAIT using β3 integrin and GPIbα deficient (-/-) mice. We first transfused these deficient mice with wild-type (WT) platelets to induce anti-β3 or anti-GPIbα antibody responses; we then bred these immunized female mice with WT males, causing FNAIT in the offspring. We found that maternal antiplatelet antibody titer correlated with the severity of FNAIT. These two murine models have revealed fundamental differences between the pathogenesis of anti-β3 and anti-GPIbα-mediated FNAIT. In anti-β3-mediated FNAIT, we found severe thrombocytopenia, ICH, and miscarriage. We also found the impairment of angiogenesis, which may contribute to ICH and intrauterine growth retardation. In contrast, the anti-GPIbα-mediated model revealed a nonclassical form of FNAIT (e.g., miscarriage but not bleeding disorders in neonates). We found that anti-GPIbα antibodies caused thrombosis in the placentas and miscarriage in most pregnant mice, which may partially explain the rarity of anti-GPIbα-mediated FNAIT reported in humans. Despite these substantial differences, there are also similarities between anti-β3 and anti-GPIbα-mediated FNAIT, such as the role of the neonatal Fc receptor (FcRn). FcRn is important for serum IgG homeostasis and for IgG transportation across the placenta. Using FcRn-/- mice, we demonstrated that fetal (but not maternal) FcRn is required to transport maternal antibodies to the fetal circulation and is indispensable for FNAIT. Blocking FcRn with an anti-FcRn antibody markedly reduced the severity of both anti-β3 and anti-GPIbα-mediated FNAIT. This important finding may lead to the development of new therapies (e.g., anti-FcRn antibody) against FNAIT and other maternal pathogenic antibody-mediated fetal/neonatal diseases. These models of FNAIT have allowed us to investigate the efficacy and mechanism of action of several therapies, including the aforementioned anti-FcRn antibody as well as antibody-mediated immune suppression (AMIS) and intravenous IgG (IVIG). In β3-/- mice, prophylactic administration of anti-HPA-1a antibody or murine β3 antisera induced AMIS against human HPA-1a-positive or murine WT platelets, respectively. Importantly, AMIS induced by β3 antisera suppressed the antibody response, thrombocytopenia, and miscarriage in FNAIT mice. These findings support the hypothesis that anti-HPA-1a antibody administration to HPA-1a-negative women after delivery of an HPA-1a-positive child may prevent FNAIT in subsequent pregnancies. The efficacy of IVIG is inconsistent, sources are limited, and the mechanism of action is not fully understood. We demonstrated that IVIG ameliorated both anti-β3 and anti-GPIbα-mediated FNAIT. IVIG decreased antiplatelet antibodies in both maternal and neonatal circulations, fetal platelet clearance, bleeding, and fetal mortality. In summary, we have uncovered fundamental differences in the pathogenesis of anti-β3 and anti-GPIbα-mediated FNAIT and have greatly enhanced our understanding of emerging and existing therapies. We will continue to investigate the pathogenesis of FNAIT so that we may develop more tailored and accessible therapeutic strategies for patients. Disclosures: No relevant conflicts of interest to declare.
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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 | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».