The p62 P392L Mutation Linked to Paget’s Disease Induces Activation of Human Osteoclasts
Bibliographic record
Abstract
Mutations of the gene encoding p62/SQSTM1 have been described in Paget's disease of bone (PDB), identifying p62 as an important player in osteoclast signaling. We investigated the phenotype of osteoclasts differentiated from peripheral blood monocytes obtained from healthy donors or PDB patients, all genotyped for the presence of a mutation in the p62 ubiquitin-associated domain. The cohort included PDB patients carrying or not the p62 P392L mutation and healthy donors carrying or not this mutation. Osteoclasts from PDB patients were more numerous, contained more nuclei, were more resistant to apoptosis, and had a greater ability to resorb bone than their normal counterparts, regardless of whether the p62 mutation was present or not. A strong increase in p62 expression was observed in PDB osteoclasts. The presence of the p62(P392L) gene in cells from healthy carriers conferred a unique, intermediate osteoclast phenotype. In addition, we report that two survival-promoting kinases, protein kinase Czeta and phosphoinositide-dependent protein kinase 1, were associated with p62 in response to receptor activator of NF-kappaB ligand (RANKL) stimulation in controls and before RANKL was added in PDB osteoclasts. In transfected osteoclasts derived from cord blood monocytes, the p62 P392L mutation contributed to increased activation of kinases protein kinase Czeta/lambda and phosphoinositide-dependent protein kinase 1, along with basal activation of NF-kappaB, independently of RANKL stimulation. These findings clearly indicate that the overexpression of p62 in PDB patients induces important shifts in the pathways activated by RANKL and up-regulates osteoclast functions. Moreover, the most-commonly reported p62 mutation, P392L, certainly contributes to the overactive state of osteoclasts in PDB.
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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 | 0.000 | 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) | 0.002 | 0.001 |
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".