Presenilin-dependent regulation of tau pathology via the autophagy/proteasome pathway
Bibliographic record
Abstract
Abstract Autosomal dominant inherited mutations in the presenilin ( PS / PSEN ) genes cause early-onset familial Alzheimer’s disease (AD) by enhancing cerebral accumulation of amyloid-β (Aβ) and microtubule-associated protein tau, although the precise cellular mechanisms by which PS dysfunction drives neuronal tau pathology remain still unclear. Here, we investigated the mechanisms linking PS/γ-secretase-dependent tau pathology and autophagy by using molecular, imaging and pathological approaches in brains, fibroblasts and induced pluripotent stem cells (iPSCs)-derived neurons from mutant PSEN1 carriers, as well as in a novel tauopathy mouse model lacking PS in glutamatergic neurons. We found colocalization of phosphorylated tau with the autophagy marker p62 in the hippocampus of tauopathy patients with PSEN1 mutations, corticobasal degeneration and Pick’s disease. Remarkably, disrupted autophagic clearance of pathological tau was evidenced by increased autophagy markers and accumulation of total and AD-associated phosphorylated tau species (pTau 181, 202, 217) in hippocampal lysates and autophagosomes of familial AD-linked PSEN1 patients and PS -deficient tau transgenic mice. Human iPSC-derived neurons harboring the familial AD-linked PSEN1 G206D mutation are less sensitive to autophagy inhibition, reduce tau release and accumulate intracellular tau oligomers. Human primary fibroblasts from PSEN1 G206D and/or L286P carriers show elevated LC3 and autolysosomes indicating that these familial AD-linked PSEN1 mutations disrupt autophagy flux. PS is required for efficient autophagy-mediated tau degradation in neurons through a dual mechanism involving autophagy induction via blockage of Akt/PRAS40-dependent mTORC1 activation and promoting autophagosome/lysosome fusion. Surprisingly, pharmacological proteasome inhibition decreases tau accumulation in neurons by promoting tau release through a mechanism that requires functional PS. In conclusion, PS is required for autophagy/proteasome-mediated tau elimination in neurons, while familial AD-linked PSEN mutations cause progressive tau pathology by disrupting autophagy. These findings may impact on the development of new therapeutic targets for tauopathy dementias.
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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) | 0.000 | 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 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".