Loss of presenilin function enhances tau phosphorylation and aggregation in mice
Bibliographic record
Abstract
Mutations in the presenilin (PS/PSEN) genes encoding the catalytic components of γ-secretase accelerate amyloid-β (Aβ) and tau pathologies in familial Alzheimer's disease (AD). Although the mechanisms by which these mutations affect Aβ are well defined, the precise role PS/γ-secretase on tau pathology in neurodegeneration independently of Aβ is largely unclear. Here we report that neuronal PS deficiency in conditional knockout (cKO) mice results in age-dependent brain atrophy, inflammatory responses and accumulation of pathological tau in neurons and glial cells. Interestingly, genetic inactivation of presenilin 1 (PS1) or both PS genes in mutant human Tau transgenic mice exacerbates memory deficits by accelerating phosphorylation and aggregation of tau in excitatory neurons of vulnerable AD brain regions (e.g., hippocampus, cortex and amygdala). Remarkably, neurofilament (NF) light chain (NF-L) and phosphorylated NF are abnormally accumulated in the brain of Tau mice lacking PS. Synchrotron infrared microspectroscopy revealed aggregated and oligomeric β-sheet structures in amyloid plaque-free PS-deficient Tau mice. Hippocampal-dependent memory deficits are associated with synaptic tau accumulation and reduction of pre- and post-synaptic proteins in Tau mice. Thus, partial loss of PS/γ-secretase in neurons results in temporal- and spatial-dependent tau aggregation associated with memory deficits and neurodegeneration. Our findings show that tau phosphorylation and aggregation are key pathological processes that may underlie neurodegeneration caused by familial AD-linked PSEN mutations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".