Alternative splicing in osteoclasts and Paget’s disease of bone
Bibliographic record
Abstract
BACKGROUND: Mutations in the SQSTM1/p62 gene have been reported in Paget's disease of bone (PDB), but they are not sufficient to induce the pagetic osteoclast (OC) phenotype. We hypothesized that specific RNA isoforms of OC-related genes may contribute to the overactivity of pagetic OCs, along with other genetic predisposing factors. METHODS: Alternative splicing (AS) events were studied using a PCR-based screening strategy in OC cultures from 29 patients with PDB and 26 healthy donors (HD), all genotyped for the p62P392L mutation. Primer pairs targeting 5223 characterized AS events were used to analyze relative isoform ratios on pooled cDNA from samples of the four groups (PDB, PDBP392L, HD, HDP392L). Of the 1056 active AS events detected in the screening analysis, 192 were re-analyzed on non-amplified cDNA from each subject of the whole cohort. RESULTS: This analysis led to the identification of six AS events significantly associated with PDB, but none with p62P392L. The corresponding genes included LGALS8, RHOT1, CASC4, USP4, TBC1D25, and PIDD. In addition, RHOT1 and LGALS8 genes were upregulated in pagetic OCs, as were CASC4 and RHOT1 genes in the presence of p62P392L. Finally, we showed that the proteins encoded by LGALS8, RHOT1, USP4, TBC1D25, and PIDD were expressed in human OCs. CONCLUSION: This study allowed the identification of hitherto unknown players in OC biology, and our findings of a differential AS in pagetic OCs may generate new concepts in the pathogenesis of 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 | 0.001 | 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 | 0.000 |
| 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".