CDK5RAP2 loss-of-function causes premature cell senescence via the GSK3β/β-catenin-WIP1 pathway
Bibliographic record
Abstract
Abstract Developmental disorders characterized by small body size have been linked to CDK5RAP2 loss-of-function mutations, but the mechanisms underlying which remain obscure. Here, we demonstrate that knocking down CDK5RAP2 in human fibroblasts triggers premature cell senescence that is recapitulated in Cdk5rap2 an/an mouse embryonic fibroblasts and embryos, which exhibit reduced body weight and size, and increased senescence-associated (SA)-β-gal staining compared to Cdk5rap2 +/+ and Cdk5rap2 +/an embryos. Interestingly, CDK5RAP2-knockdown human fibroblasts show increased p53 Ser15 phosphorylation that does not correlate with activation of p53 kinases, but rather correlates with decreased level of the p53 phosphatase, WIP1. Ectopic WIP1 expression reverses the senescent phenotype in CDK5RAP2-knockdown cells, indicating that senescence in these cells is linked to WIP1 downregulation. CDK5RAP2 interacts with GSK3β, causing increased inhibitory GSK3β Ser9 phosphorylation and inhibiting the activity of GSK3β, which phosphorylates β-catenin, tagging β-catenin for degradation. Thus, loss of CDK5RAP2 decreases GSK3β Ser9 phosphorylation and increases GSK3β activity, reducing nuclear β-catenin, which affects the expression of NF-κB target genes such as WIP1. Consequently, loss of CDK5RAP2 or β-catenin causes WIP1 downregulation. Inhibition of GSK3β activity restores β-catenin and WIP1 levels in CDK5RAP2-knockdown cells, reducing p53 Ser15 phosphorylation and preventing senescence in these cells. Conversely, inhibition of WIP1 activity increases p53 Ser15 phosphorylation and senescence in CDK5RAP2-depleted cells lacking GSK3β activity. These findings indicate that loss of CDK5RAP2 promotes premature cell senescence through GSK3β/β-catenin downregulation of WIP1. Premature cell senescence may contribute to reduced body size associated with CDK5RAP2 loss-of-function.
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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".