Novel and emerging therapeutic strategies for clonal haematopoiesis
Bibliographic record
Abstract
Clonal hematopoiesis (CH) arises when hematopoietic stem cells (HSC) acquire mutations that confer a competitive advantage over wild-type HSC, leading to their expansion in the bone marrow with clonal progeny that circulate in the blood and are most readily detected through peripheral blood sequencing. The prevalence of CH increases with age and is linked to a higher risk of hematologic malignancies and various non-malignant diseases, particularly atherosclerotic cardiovascular disease. CH is not merely a biomarker; it actively contributes to the pathogenesis of these age-related conditions. Therefore, targeting the expansion of mutant clones and their downstream effects offers an opportunity to prevent these adverse health outcomes. CH involves mutation-specific biological changes that sustain the abnormal HSC phenotype, including epigenetic dysregulation, aberrant inflammatory signaling, metabolic reprogramming, and altered intracellular signaling pathways. A deeper understanding of these processes has led to the development of targeted therapeutic approaches. This review addresses the practical challenges of implementing interventions against CH, focusing on balancing risk and benefit and selecting appropriate patients. It discusses emerging treatments targeting the pathogenic mechanisms in CH, such as epigenetic modulators, anti-inflammatory therapies, metabolic inhibitors, and signaling pathway inhibitors. We also highlight potential novel therapeutic strategies on the horizon, such as immune-based approaches for selective clonal elimination and gene-editing therapies to correct causative mutations. These advances reframe CH as a potentially modifiable condition rather than an inevitable consequence of aging, creating opportunities for early intervention before progression to overt disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".