A novel direct adenosine monophosphate kinase activator ameliorates disease progression in preclinical models of Autosomal Dominant Polycystic Kidney Disease
Bibliographic record
Abstract
Autosomal dominant polycystic kidney disease (ADPKD) mainly results from mutations in the PKD1 gene, which encodes polycystin 1. It is the most common inherited kidney disease and is characterized by a progressive bilateral increase in cyst number and size, often leading to kidney failure. The cellular energy sensor and regulator adenosine monophosphate stimulated protein kinase (AMPK) has been implicated as a promising new therapeutic target. To address this hypothesis, we determined the effects of a potent and selective clinical stage direct allosteric AMPK activator, PXL770, in canine and patient-derived 3D cyst models and an orthologous mouse model of ADPKD. PXL770 induced AMPK activation and dose-dependently reduced cyst growth in principal-like Madin-Darby Canine Kidney cells stimulated with forskolin and kidney epithelial cells derived from patients with ADPKD stimulated with desmopressin. In an inducible, kidney epithelium-specific Pkd1 knockout mouse model, PXL770 produced kidney AMPK pathway engagement, prevented the onset of kidney failure (reducing blood urea by 47%), decreased cystic index by 26% and lowered the kidney weight to body weight ratio by 35% compared to untreated control Pkd1 knockout mice. These effects were accompanied by a reduction of markers of cell proliferation (-48%), macrophage infiltration (-53%) and tissue fibrosis (-37%). Thus, our results show the potential of direct allosteric AMPK activation in the treatment of ADPKD and support the further development of PXL770 for this indication.
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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 | 0.002 |
| 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".