Mechanisms of hematopoietic clonal dominance in VEXAS syndrome
Bibliographic record
Abstract
Clonal dominance characterizes hematopoiesis during aging and increases susceptibility to blood cancers and common nonmalignant disorders. VEXAS syndrome is a recently discovered, adult-onset, autoinflammatory disease burdened by a high mortality rate and caused by dominant hematopoietic clones bearing somatic mutations in the UBA1 gene. However, pathogenic mechanisms driving clonal dominance are unknown. Moreover, the lack of disease models hampers the development of disease-modifying therapies. In the present study, we performed immunophenotype characterization of hematopoiesis and single-cell transcriptomics in a cohort of nine male patients with VEXAS syndrome, revealing pervasive inflammation across all lineages. Hematopoietic stem and progenitor cells (HSPCs) in patients are skewed toward myelopoiesis and acquire senescence-like programs. Humanized models of VEXAS syndrome, generated by inserting the causative mutation in healthy HSPCs through base editing, recapitulated proteostatic defects, cytological alterations and senescence signatures of patients' cells, as well as hematological and inflammatory disease hallmarks. Competitive transplantations of human UBA1-mutant and wild-type HSPCs showed that, although mutant cells are more resilient to the inflammatory milieu, probably through the acquisition of the senescence-like state, wild-type ones are progressively exhausted and overwhelmed by VEXAS clones, overall impairing functional hematopoiesis and leading to bone marrow failure. Our study unveils the mechanism of clonal dominance and provides models for preclinical studies and preliminary insights that could inform therapeutic strategies.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".