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Identification and Functional Characterization of a Novel 27bp Deletion in the Macroglycopeptide-Coding Region of the GPIbα Gene Resulting in Platelet-Type Von Willebrand Disease.

2004· article· en· W4254922035 on OpenAlexaff
Maha Othman, Hisham S. Elbatarny, Colleen Notley, Louise F. Lavender, Helen White, Christopher D. Byrne, Denise F. O’Shaughnessy, David Lillicrap

Bibliographic record

VenueBlood · 2004
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsQueen's University
Fundersnot available
KeywordsVon Willebrand diseasePlateletVon Willebrand factorRistocetinPlatelet membrane glycoproteinBleeding timePlatelet disorderImmunologyMolecular biologyChemistryInternal medicineMedicineBiologyPlatelet aggregation

Abstract

fetched live from OpenAlex

Abstract Platelet-type Von Willebrand disease (PT-VWD) is a rare autosomal dominant bleeding disorder. It results from an abnormally high affinity interaction between the platelet membrane glycoprotein Ib/IX/V complex and Von Willebrand factor (VWF), leading to characteristic platelet hyperaggregability. The condition shares most of the clinical and laboratory features of type 2B VWD and the final discrimination between these two diseases requires either platelet mixing studies or a molecular genetic approach. Five members of a British family with PT-VWD were studied; three affected and two unaffected. The proposita, had a long history of bleeding with recurrent epistaxis, postoperative and dental bleeding and menorrhagia. An initial series of hematological investigations lead to a diagnosis of type 2B VWD but a significant fall in her platelet count following therapy with a VWF/FVIII concentrate resulted in the consideration of PT-VWD as the correct diagnosis. This diagnosis was subsequently confirmed with appropriate FVIII and VWF assays. Affected individuals had VWF:Ag values in the range 0.34–0.47 U/mL, FVIII 0.45–0.64 U/mL and VWF:RCo ranging from 0.18–0.42 U/mL. These subjects showed loss of the HMW VWF multimers from plasma and enhanced ristocetin-induced platelet agglutination (RIPA). Also, washed normal platelets did not show enhanced RIPA when mixed with the patient’s plasma. On molecular genetic analysis of the GPIbα locus, the three affected family members were heterozygous for a 27 bp in-frame deletion (nucleotides 4374–4400). This corresponds to residues 421–429 in the macroglycopeptide region of GPIbα. This deletion was not identified in any of 50 normal controls. Flow cytometric quantitative analysis of the platelet GPIb/IX/V complex showed that the number of molecules for each of GPIb, GPIX and GPV, in each of the affected and non-affected family members fell within the normal range. Wild type (WT) GPIbα and the 27bp deletion mutant GPIba were then expressed in CHO b/IX cells. To examine the effect of the 27bp deletion on the conformation of the receptor, the cells were incubated with monoclonal antibodies that bind to different sites on GPIbα. We demonstrated that each of the three monoclonal antibodies bound WT and Mut GPIba to a similar extent and that the mutant protein was expressed at a normal level on the CHO cell surface. Finally, the effect of the 27bp deletion on VWF binding was analysed in CHO b/IX cells expressing the mutant and WT GPIbα receptor with 125I-VWF in the presence of varying ristocetin concentrations. We showed that the mutant receptor binds significantly more VWF than the WT GPIbα in the absence of ristocetin and also displays heightened sensitivity to low ristocetin concentrations compared to the WT cells. This study reports the first mutation resulting in PT-VWD that does not directly involve the VWF binding region of GPIbα. Our functional studies with the mutant receptor confirm that the deletion of 9 amino acids from the macroglycopeptide region of the protein enhances its interaction with VWF.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.019
GPT teacher head0.232
Teacher spread0.213 · 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 designObservational
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".

Quick stats

Citations5
Published2004
Admission routes1
Has abstractyes

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