Branched-chain ketoacid overload inhibits insulin action in the muscle
Bibliographic record
Abstract
Branched-chain α-keto acids (BCKAs) are catabolites of branched-chain amino acids (BCAAs). Intracellular BCKAs are cleared by branched-chain ketoacid dehydrogenase (BCKDH), which is sensitive to inhibitory phosphorylation by BCKD kinase (BCKDK). Accumulation of BCKAs is an indicator of defective BCAA catabolism and has been correlated with glucose intolerance and cardiac dysfunction. However, it is unclear whether BCKAs directly alter insulin signaling and function in the skeletal and cardiac muscle cell. Furthermore, the role of excess fatty acids (FAs) in perturbing BCAA catabolism and BCKA availability merits investigation. By using immunoblotting and ultra-performance liquid chromatography MS/MS to analyze the hearts of fasted mice, we observed decreased BCAA-catabolizing enzyme expression and increased circulating BCKAs, but not BCAAs. In mice subjected to diet-induced obesity (DIO), we observed similar increases in circulating BCKAs with concomitant changes in BCAA-catabolizing enzyme expression only in the skeletal muscle. Effects of DIO were recapitulated by simulating lipotoxicity in skeletal muscle cells treated with saturated FA, palmitate. Exposure of muscle cells to high concentrations of BCKAs resulted in inhibition of insulin-induced AKT phosphorylation, decreased glucose uptake, and mitochondrial oxygen consumption. Altering intracellular clearance of BCKAs by genetic modulation of BCKDK and BCKDHA expression showed similar effects on AKT phosphorylation. BCKAs increased protein translation and mTORC1 activation. Pretreating cells with mTORC1 inhibitor rapamycin restored BCKA's effect on insulin-induced AKT phosphorylation. This study provides evidence for FA-mediated regulation of BCAA-catabolizing enzymes and BCKA content and highlights the biological role of BCKAs in regulating muscle insulin signaling and function.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".