A novel cause of type 1 von Willebrand disease: impaired exocytosis of Weibel-Palade bodies due to biallelic <i>MADD</i> variants
Bibliographic record
Abstract
ABSTRACT: The regulated secretion of von Willebrand factor (VWF) from Weibel-Palade bodies (WPBs) in endothelial cells is fundamental to hemostasis. This process relies on recruiting Rab GTPases and their effectors to the WPB membrane, with the guanine nucleotide exchange factor MAPK-activating death domain (MADD) playing a central role. Biallelic variants in MADD lead to a pleiotropic neurological and developmental disorder that can include bleeding abnormalities. This study investigates the impact of pathogenic MADD variants on VWF secretion using patient-derived endothelial cells. We isolated endothelial colony-forming cells (ECFCs) from 3 pediatric patients with biallelic MADD variants and unaffected heterozygous family members. All patients exhibited low VWF plasma levels (22-30 IU/dL). Proteomic analysis of patient-derived ECFCs revealed an absence of MADD peptides, reduced VWF, and downregulation of proteins involved in the exocytotic machinery, including Rab3D and the Rab3/27 effector Slp4-a. Functional assays demonstrated diminished Rab27A and Rab3D activity and their failure to localize to WPBs in patient cells. Biochemical and live-imaging studies showed that histamine-induced VWF and VWF propeptide secretion were significantly reduced in patient cells due to delayed and reduced degranulation of WPBs. Our findings demonstrate the critical role of MADD in maintaining the secretion competence of WPBs and the magnitude of VWF secretion by regulating the recruitment of the endothelial exocytotic machinery. This study highlights the in vivo significance of WPB exocytosis in maintaining plasma VWF levels and establishes MADD as the first causal gene for quantitative von Willebrand disease in patients without pathogenic VWF variants.
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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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".