Shared pathobiology identifies AMPK as a therapeutic target for obesity and autosomal dominant polycystic kidney disease
Bibliographic record
Abstract
Autosomal dominant polycystic kidney disease (ADPKD) is the most common Mendelian kidney disease, affecting approximately one in 1,000 births and accounting for 5% of end-stage kidney disease in developed countries. The pathophysiology of ADPKD is strongly linked to metabolic dysregulation, which may be secondary to defective polycystin function. Overweight and obesity are highly prevalent in patients with ADPKD and constitute an independent risk factor for progression. Recent studies have highlighted reduced AMP-activated protein kinase (AMPK) activity, increased mammalian target of rapamycin (mTOR) signaling, and mitochondrial dysfunction as shared pathobiology between ADPKD and overweight/obesity. Notably, mTOR and AMPK are two diametrically opposed sensors of energy metabolism that regulate cell growth and proliferation. However, treatment with the current generation of mTOR inhibitors is poorly tolerated due to their toxicity, making clinical translation difficult. By contrast, multiple preclinical and clinical studies have shown that pharmacological activation of AMPK provides a promising approach to treat ADPKD. In this narrative review, we summarize the pleiotropic functions of AMPK as a regulator of cellular proliferation, macromolecule metabolism, and mitochondrial biogenesis, and discuss the potential for pharmacological activation of AMPK to treat ADPKD and obesity-related kidney disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".