SHP2 drives inflammation-triggered insulin resistance by reshaping tissue macrophage populations
Bibliographic record
Abstract
Insulin resistance is a key event in type 2 diabetes onset and a major comorbidity of obesity. It results from a combination of fat excess-triggered defects, including lipotoxicity and metaflammation, but the causal mechanisms remain difficult to identify. Here, we report that hyperactivation of the tyrosine phosphatase SHP2 found in Noonan syndrome (NS) led to an unsuspected insulin resistance profile uncoupled from altered lipid management (for example, obesity or ectopic lipid deposits) in both patients and mice. Functional exploration of an NS mouse model revealed this insulin resistance phenotype correlated with constitutive inflammation of tissues involved in the regulation of glucose metabolism. Bone marrow transplantation and macrophage depletion improved glucose homeostasis and decreased metaflammation in the mice, highlighting a key role of macrophages. In-depth analysis of bone marrow-derived macrophages in vitro and liver macrophages showed that hyperactive SHP2 promoted a proinflammatory phenotype, modified resident macrophage homeostasis, and triggered monocyte infiltration. Consistent with a role of SHP2 in promoting inflammation-driven insulin resistance, pharmaceutical SHP2 inhibition in obese diabetic mice improved insulin sensitivity even better than conventional antidiabetic molecules by specifically reducing metaflammation and alleviating macrophage activation. Together, these results reveal that SHP2 hyperactivation leads to inflammation-triggered metabolic impairments and highlight the therapeutical potential of SHP2 inhibition to ameliorate insulin resistance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".