Acetyl-CoA carboxylase inhibition increases retinal pigment epithelial cell fatty acid flux and restricts apolipoprotein efflux
Bibliographic record
Abstract
Lipid-rich deposits called drusen accumulate under the retinal pigment epithelium (RPE) in the eyes of patients with age-related macular degeneration and Sorsby's fundus dystrophy (SFD). Drusen may contribute to photoreceptor degeneration in these blinding diseases. Stimulating β-oxidation of fatty acids could decrease the availability of lipid with which RPE cells generate drusen. Inhibitors of acetyl-CoA carboxylase (ACC) stimulate β-oxidation and diminish lipid accumulation in fatty liver disease. In this report, we test the hypothesis that an ACC inhibitor, Firsocostat, can diminish lipid deposition by RPE cells. We probed metabolism and cellular function in mouse RPE-choroid tissue and human RPE cells. We used 13 C 6 -glucose, 13 C 16 -palmitate, and gas chromatography–linked mass spectrometry to monitor effects of Firsocostat on glycolytic, Krebs cycle, and fatty acid metabolism. We quantified lipid abundance, apolipoprotein E levels, and vascular endothelial growth factor release using liquid chromatography–mass spectrometry, ELISAs, and immunostaining. RPE barrier function was assessed by trans-epithelial electrical resistance (TEER). Firsocostat-mediated ACC inhibition increases β-oxidation, decreases intracellular lipid levels, diminishes lipoprotein release, and increases TEER. When human serum or outer segments are used to stimulate lipoprotein release, fewer lipoproteins are released in the presence of Firsocostat. In a culture model of SFD, Firsocostat stimulates fatty acid oxidation, increases TEER, and decreases apolipoprotein E release. We conclude that Firsocostat remodels RPE metabolism and can limit lipid deposition. This suggests that ACC inhibition could be an effective strategy for diminishing pathologic drusen in the eyes of patients with age-related macular degeneration or SFD.
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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) | 0.001 | 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".