Murine Model of Fetal and Neonatal Alloimmune Thrombocytopenia Mediated by Anti-GPIb α Versus Anti-β3 Integrin Antibodies.
Bibliographic record
Abstract
Abstract Fetal and neonatal alloimmune thrombocytopenia (FNAITP) is a life-threatening bleeding disorder which results from maternal anti-platelet antibodies that cross the placenta and destroy fetal platelets. In most cases FNAITP is mediated by anti-β3 integrin antibodies, whereas reported cases of anti-GPIbα mediated FNAITP are rare. This difference can not be solely explained by the frequency of their respective polymorphisms. It is unclear whether this is due to:the GPIbα antigen being less immunogenic, resulting in less maternal antibody generation during pregnancy, oranti-GPIbα antibodies mediating a less severe pathology, resulting in a reduced number of reported cases. To study the immunogenecity and antibody response to the GPIbα antigen, GPIbα deficient mice (GPIbα−/−, Black Swiss background) were transfused with wild-type (WT) platelets. No detectable anti-GPIbα IgG antibody was induced even after 8 transfusions (108 platelets/transfusion). This clearly differs from the immune response generated in β3 integrin deficient (β3−/−, BALB/c background) mice, in which anti-β3 integrin antibody can be easily detected after 2–4 WT platelet transfusions. This suggested that the MHC complex in Black Swiss mice might not be able to present the GPIbα antigen. We thus introduced the BALB/c background to the GPIbα−/− mice via backcrossing these mice with BALB/c mice for 9 generations (F9). To further minimize genetic background differences, the F9 BALB/c GPIbα−/− mice were bred with F9 BALB/c β3−/− mice to generate heterozygous BALB/c GPIbα+/− and β3+/− mice. These mice were subsequently used to generate littermate GPIbα−/− or β3−/− mice for the following studies. We found that BALB/c GPIbα−/− mice are immunoresponsive to the GPIbα antigen, but antibody titers after 2 and 4 platelet transfusions were significantly lower than those seen with the anti-β3 integrin model (1:50 & 1:200 vs 1:400 & 1:3200 respectively, P<0.05). We then established a FNAITP model with these GPIbα−/− mice and compared it with syngeneic background β3−/− mice. Naïve (Group I) or 2-time-platelet-immunized (Group II) female GPIbα−/− or β3−/− mice were bred with WT male mice. In Group I, neonatal platelet counts after the first delivery were normal and no maternal antibody was detected for both groups. After the third delivery, GPIbα+/− pups did not have any bleeding disorders and the maternal antibody was also negative. In contrast, 14.3% of β3+/− pups were stillborn or had subcutaneous bleeding and maternal antibody was detected. In Group II, 8 pups were delivered from a GPIbα−/− female and 2 of them have minor intestinal and subcutaneous bleeding. 10 pups were delivered from 2 β3−/− female mice and 6 of them were stillborn. Of these dead pups, there was 1 case of intracranial hemorrhage and 2 immature pups. When the anti-GPIbα antibody level was increased via 4 platelet transfusions, a GPIbα−/− female had a miscarriage and severe FNAITP was observed. Our preliminary data suggested that fewer FNAITP cases reported with alloantibodies against GPIbα might not be due to the severity of FNAITP caused by this antibody, but is more likely because GPIbα is less immunogenic with a limited repertoire of MHC in pregnant women.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".