Enhancer-gene rewiring in the pathogenesis of Quebec Platelet Disorder
Bibliographic record
Abstract
Quebec platelet disorder (QPD) is an autosomal dominant bleeding disorder with a unique, platelet-dependent, gain-of-function defect in fibrinolysis, without systemic fibrinolysis. The hallmark feature of QPD is a >100-fold overexpression of PLAU, specifically in megakaryocytes. This overexpression leads to a >100-fold increase in platelet stores of urokinase plasminogen activator (PLAU/uPA); subsequent plasmin-mediated degradation of diverse α-granule proteins; and platelet-dependent, accelerated fibrinolysis. The causative mutation is a 78-kb tandem duplication of PLAU. How this duplication causes megakaryocyte-specific PLAU overexpression is unknown. To investigate the mechanism that causes QPD, we used epigenomic profiling, comparative genomics, and chromatin conformation capture approaches to study PLAU regulation in cultured megakaryocytes from participants with QPD and unaffected controls. QPD duplication led to ectopic interactions between PLAU and a conserved megakaryocyte enhancer found within the same topologically associating domain (TAD). Our results support a unique disease mechanism whereby the reorganization of sub-TAD genome architecture results in a dramatic, cell-type-specific blood disorder phenotype.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
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".