GAS6 and AXL promote insulin resistance by rewiring insulin signaling and increasing insulin receptor trafficking to endosomes
Bibliographic record
Abstract
ABSTRACT Growth-arrest specific 6 (GAS6) is a secreted protein that acts as a ligand for TAM receptors (TYRO3, AXL and MERTK). In humans, GAS6 circulating levels and genetic variations in GAS6 are associated with hyperglycemia and increased risk of type 2 diabetes. However, the mechanisms by which GAS6 influences glucose metabolism are not understood. Here, we show that Gas6 deficiency in mice increases insulin sensitivity and protects from diet-induced insulin resistance. Conversely, increasing GAS6 circulating levels is sufficient to reduce insulin sensitivity in vivo . GAS6 inhibits the activation of the insulin receptor (IR) and reduces insulin response in muscle cells in vitro and in vivo. Mechanistically, AXL and IR fom a complex, while GAS6 reprograms signaling pathways downstream of IR. This results in increased IR endocytosis following insulin treatment. This study contributes to a better understanding of the cellular and molecular mechanisms by which GAS6 and AXL influence insulin sensitivity. ARTICLE HIGHLIGHTS GAS6 deficient mice are characterized by improved glucose tolerance, increased insulin sensitivity and are protected from diet-induced insulin resistance. The GAS6 receptor AXL is expressed in muscle cells and forms a complex with the insulin receptor. GAS6 reprograms insulin signaling by modulating the phosphorylation of proteins implicated in endocytosis, vesicle-mediated transport, and membrane trafficking. AXL and GAS6 promotes insulin receptor endocytosis following insulin treatment.
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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 | 0.001 |
| 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".