Regulatory role of cathepsin L in induction of nuclear laminopathy in Alzheimer’s disease
Bibliographic record
Abstract
Experimental and clinical therapies in the field of Alzheimer's disease (AD) have focused on elimination of extracellular amyloid beta aggregates or prevention of cytoplasmic neuronal fibrillary tangles formation, yet these approaches have been generally ineffective. Interruption of nuclear lamina integrity, or laminopathy, is a newly identified concept in AD pathophysiology. Unraveling the molecular players in the induction of nuclear lamina damage may lead to identification of new therapies. Here, using 3xTg and APP/PS1 mouse models of AD, and in vitro model of amyloid beta42 (Aβ42) toxicity in primary neuronal cultures and SH-SY5Y neuroblastoma cells, we have uncovered a key role for cathepsin L in the induction of nuclear lamina damage. The applicability of our findings to AD pathophysiology was validated in brain autopsy samples from patients. We report that upregulation of cathepsin L is an important process in the induction of nuclear lamina damage, shown by lamin B1 cleavage, and is associated with epigenetic modifications in AD pathophysiology. More importantly, pharmacological targeting and genetic knock out of cathepsin L mitigated Aβ42 induced lamin B1 degradation and downstream structural and molecular changes. Affirming these findings, overexpression of cathepsin L alone was sufficient to induce lamin B1 cleavage. The proteolytic activity of cathepsin L on lamin B1 was confirmed using mass spectrometry. Our research identifies cathepsin L as a newly identified lamin B1 protease and mediator of laminopathy observed in AD. These results uncover a new aspect in the pathophysiology of AD that can be pharmacologically prevented, raising hope for potential therapeutic interventions.
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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) | 0.001 | 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".