AMPK activation protects from neuronal dysfunction and vulnerability across nematode, cellular and mouse models of Huntington's disease
Bibliographic record
Abstract
The adenosine monophosphate activated kinase protein (AMPK) is an evolutionary-conserved protein important for cell survival and organismal longevity through the modulation of energy homeostasis. Several studies suggested that AMPK activation may improve energy metabolism and protein clearance in the brains of patients with vascular injury or neurodegenerative disease. However, in Huntington's disease (HD), AMPK may be activated in the striatum of HD mice at a late, post-symptomatic phase of the disease, and high-dose regiments of the AMPK activator 5-aminoimidazole-4-carboxamide ribonucleotide may worsen neuropathological and behavioural phenotypes. Here, we revisited the role of AMPK in HD using models that recapitulate the early features of the disease, including Caenorhabditis elegans neuron dysfunction before cell death and mouse striatal cell vulnerability. Genetic and pharmacological manipulation of aak-2/AMPKα shows that AMPK activation protects C. elegans neurons from the dysfunction induced by human exon-1 huntingtin (Htt) expression, in a daf-16/forkhead box O-dependent manner. Similarly, AMPK activation using genetic manipulation and low-dose metformin treatment protects mouse striatal cells expressing full-length mutant Htt (mHtt), counteracting their vulnerability to stress, with reduction of soluble mHtt levels by metformin and compensation of cytotoxicity by AMPKα1. Furthermore, AMPK protection is active in the mouse brain as delivery of gain-of-function AMPK-γ1 to mouse striata slows down the neurodegenerative effects of mHtt. Collectively, these data highlight the importance of considering the dynamic of HD for assessing the therapeutic potential of stress-response targets in the disease. We postulate that AMPK activation is a compensatory response and valid approach for protecting dysfunctional and vulnerable neurons in HD.
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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".