Chronic TNF in the aging microenvironment exacerbates <i>Tet2</i> loss-of-function myeloid expansion
Bibliographic record
Abstract
ABSTRACT: Somatic mutations in the TET2 gene occur more frequently with age, imparting an intrinsic hematopoietic stem cells (HSCs) advantage and contributing to a phenomenon termed clonal hematopoiesis of indeterminate potential (CHIP). Individuals with TET2-mutant CHIP have a higher risk of developing myeloid neoplasms and other aging-related conditions. Despite its role in unhealthy aging, the extrinsic mechanisms driving TET2-mutant CHIP clonal expansion remain unclear. We previously showed an environment containing tumor necrosis factor (TNF) favors TET2-mutant HSC expansion in vitro. We therefore postulated that age-related increases in TNF also provide an advantage to HSCs with TET2 mutations in vivo. To test this hypothesis, we generated mixed bone marrow chimeric mice of old wild-type (WT) and TNF-/- genotypes reconstituted with WT CD45.1+ and Tet2-/- CD45.2+ HSCs. We show that age-associated increases in TNF dramatically increased the expansion of Tet2-/- cells in old WT recipient mice, with strong skewing toward the myeloid lineage. This aberrant myelomonocytic advantage was mitigated in old TNF-/- recipient mice, suggesting that TNF signaling is essential for the expansion Tet2-mutant myeloid clones. Examination of human patients with rheumatoid arthritis with clonal hematopoiesis revealed that hematopoietic cells carrying certain mutations, including in TET2, may be sensitive to reduced TNF bioactivity following blockade with adalimumab. This suggests that targeting TNF may reduce the burden of some forms of CHIP. To our knowledge, this is the first evidence to demonstrate that TNF has a causal role in driving TET2-mutant CHIP in vivo. These findings highlight TNF as a candidate therapeutic target to control TET2-mutant CHIP.
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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".