Inhibition of Branched‐Chain Ketoacid Dehydrogenase Kinase (BDK) Attenuates BCKA Induced Suppression of Insulin‐Stimulated Glucose Uptake in Muscle Cells
Bibliographic record
Abstract
Objective Plasma levels of branched‐chain amino acids (BCAAs) and their metabolites, branched‐chain ketoacids (BCKAs) are increased in insulin resistance, a condition that can lead to type 2 diabetes mellitus (T2DM). BCAA catabolic enzymes are downregulated in diabetes and obesity in skeletal muscle. We previously showed that leucine and KIC suppressed insulin‐stimulated glucose uptake in L6 myotubes. We have also shown that knocking down branched‐chain ketoacid dehydrogenase (BCKD), an enzyme that decarboxylates BCKAs, suppressed insulin‐stimulated glucose uptake. The objective of this study was to analyze the effect of increasing BCAA catabolism on measures of insulin sensitivity. We hypothesized that upregulating BCAA catabolism increases insulin‐stimulated glucose transport and attenuates BCKA induced insulin resistance. Methods L6 myotubes were starved of serum‐ and amino acids with vehicle (DMSO) or BDK inhibitor BT2 supplementation for 3 hours. Then myotubes were supplemented with or without BCKAs (200 uM) for 30 minutes. After, cells were incubated with or without insulin (100 nM) for 20 minutes. They were then harvested for immunoblotting or used for glucose transport assay. Results BDK inhibition had no effect on insulin‐stimulated glucose uptake. BCKAs suppressed insulin‐stimulated glucose uptake by 31% in control cells (p>0.05; n=3); this suppression was attenuated in cells in which BDK was inhibited. BDK inhibition also reduced KIC‐induced IRS‐1 Ser612 and S6K1 Thr389 phosphorylation by 28% and 60% respectively but had no effect on Akt Ser473 phosphorylation. Conclusions BDK inhibition attenuated BCKA‐induced suppression of insulin‐stimulated glucose uptake, suggesting that BCAA metabolism may be implicated in the pathogenesis of insulin resistance, and is worth further investigation.
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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 | 0.001 |
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".