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Fetal and Neonatal Alloimmune Thrombocytopenia: Lessons Learned from Animal Models

2013· article· en· W2530516992 on OpenAlexaff
Heyu Ni

Bibliographic record

VenueBlood · 2013
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsNeonatal alloimmune thrombocytopeniaImmunologyFetusMedicineAntibodyPregnancyAntigenMiscarriageObstetricsBiologyGenetics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.041
GPT teacher head0.274
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2013
Admission routes1
Has abstractyes

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