USP53 Regulates Bone Homeostasis by Controlling Rankl Expression in Osteoblasts and Bone Marrow Adipocytes
Bibliographic record
Abstract
In the skeleton, osteoblasts and osteoclasts synchronize their activities to maintain bone homeostasis and integrity. Investigating the molecular mechanisms governing bone remodeling is critical and helps understand the underlying biology of bone disorders. Initially, we have identified the ubiquitin-specific peptidase gene (Usp53) as a target of the parathyroid hormone in osteoblasts and a regulator of mesenchymal stem cell differentiation. Mutations in USP53 have been linked to a constellation of developmental pathologies. However, the role of Usp53 in bone has never been visited. Here we show that Usp53 null mice have a low bone mass phenotype in vivo. Usp53 null mice exhibit a pronounced decrease in trabecular bone indices including trabecular bone volume (36%) and trabecular number (26%) along with an increase in trabecular separation (13%). Cortical bone parameters are also impacted, showing a reduction in cortical bone volume (12%) and cortical bone thickness (15%). As a result, the strength and mechanical bone properties of Usp53 null mice have been compromised. At the cellular level, the ablation of Usp53 perturbs bone remodeling, augments osteoblast-dependent osteoclastogenesis, and increases osteoclast numbers. Bone marrow adipose tissue volume increased significantly with age in Usp53-deficient mice. Usp53 null mice displayed increased serum receptor activator of NF-κB ligand (RANKL) levels, and Usp53-deficient osteoblasts and bone marrow adipocytes have increased expression of Rankl. Mechanistically, USP53 regulates Rankl expression by enhancing the interaction between VDR and SMAD3. This is the first report describing the function of Usp53 during skeletal development. Our results put Usp53 in display as a novel regulator of osteoblast-osteoclast coupling and open the door for investigating the involvement of USP53 in pathologies. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".