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Steroids Are Less Effective In Treating Thrombocytopenia Caused by Immune Responses Against Platelet GPIbα: A Comparative Study Using Passive and Active ITP Models.

2010· article· en· W2979315362 on OpenAlexaff
Elisa Simpson, Guangheng Zhu, Conglei Li, Lingyan Zhu, Qingshu Zeng, John W. Semple, John Freedman, Heyu Ni

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsCanadian Blood ServicesUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsImmune thrombocytopeniaPlateletAntibodyAutoantibodyImmune systemImmunologyMonoclonal antibodyDexamethasoneSplenocyteMedicinePharmacologyInternal medicineChemistry

Abstract

fetched live from OpenAlex

Abstract Abstract 1433 Introduction: Immune thrombocytopenia (ITP) is a common autoimmune disorder in which autoantibodies are generated against a patient's platelets, leading to decreased platelet counts and bleeding diatheses. Autoantibodies in ITP mainly target platelet receptors GPIIbIIIa (αIIbβ3 integrin) and GPIbα. Current first-line therapy for ITP patients is steroids, while intravenous immunoglobulin (IVIG) is a common second-line therapy. However, not all patients are responsive and we lack useful exclusion criteria for steroid therapy. Appropriate identification of non-responsive patients would facilitate proper treatment and limit side effects. We previously showed anti-GPIbα (versus anti-GPIIbIIIa) mediated ITP is less responsive to IVIG (Blood. 2006;108(3):943-6). Our preliminary data from human patients also suggests that patients with anti-GPIbα antibodies are less responsive to steroids. However, these data need to be confirmed and mechanisms remain to be elucidated. Methods: To examine whether antibody specificity (GPIIbIIIa or GPIbα) correlates with responsiveness to steroids and determine the target immune cells for steroid action, we used two murine ITP models (passive antibody transfer model and active splenocyte transfer model (Blood. 2010;115:1247-53)). In both models, mice are treated with the corticosteroid Dexamethasone (DEX) and platelet counts are monitored. In the passive antibody transfer model: BALB/c or C57 mice were pretreated for 3 days with 0.1mg/kg, 1mg/kg, or 10 mg/kg of DEX prior to injection with our newly developed mouse-anti-mouse monoclonal antibodies (mAbs) targeting GPIIbIIIa or GPIbα. A second group of mice were treated with DEX 1 day following mAb injection (i.e. after becoming thrombocytopenic) and daily thereafter. In both groups, platelet counts were monitored for 4 consecutive days post mAb injection. In the active splenocyte transfer model: β3-/- and GPIbα-/- mice were immunized with wild-type (WT) platelets resulting in an antibody titer of >1:12,800. Purified splenocytes from immunized mice were transferred into syngeneic WT or SCID recipients, such that they developed ITP. Recipient mice were treated with 1mg/kg or 10 mg/kg of DEX starting 1 day after splenocyte transfer, and daily thereafter. Platelet counts were monitored. Results and Discussion: In the passive ITP model, irrespective of DEX dose, route of administration (i.p. or s.c.) or mouse strain, pretreatment with DEX was unable to ameliorate ITP induced by either anti-GPIIbIIIa or anti-GPIbα mAbs. In addition to pretreating with DEX, administration of DEX following ITP induction also appeared to be unable to ameliorate ITP induced by either anti-GPIIbIIIa or anti-GPIbα mAbs. Similar results were obtained in the passive model when using the corticosteroid Prednisolone in a different experimental setting. In the active splenocyte transfer model, we found that varying doses of DEX ameliorated ITP in mice engrafted with anti-GPIIbIIIa reactive splenocytes while untreated mice remained thrombocytopenic. Importantly, DEX failed to show a significant effect on ITP amelioration in mice engrafted with anti-GPIbα reactive splenocytes. Since the passive model involves exogenous administration of mAb, the effect of steroid treatment is largely limited to effects on the reticuloendothelial system (RES) and destruction of opsonized platelets. Conversely, the splenocyte transfer model allows for steroid effects on active immune responses (i.e. it may affect dendritic cells, T cells, B cells, etc.) in addition to the RES. As DEX was efficacious in only the splenocyte transfer model, this suggests steroids primarily affect upstream of the immune responses in ITP. Ongoing experiments involving depletion of CD4+, CD8+, or CD19+ splenocytes will help elucidate specific immune cells as targets of DEX. Conclusions: Our data clearly demonstrated that DEX ameliorated anti-GPIIbIIIa mediated ITP but was not significantly effective for amelioration of anti-GPIbα mediated ITP in the active splenocyte transfer model. We also demonstrated that steroid therapy failed in our passive ITP model. This finding is consistent with our preliminary data in human patients (patients with anti-GPIbα antibodies may be refractory to both IVIG and steroids). This may explain the clinical variability seen in response to steroids and lead to new diagnostic/therapeutic approaches. 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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.309
Teacher spread0.275 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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
Published2010
Admission routes1
Has abstractyes

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