CD248 promotes insulin resistance by binding to the insulin receptor and dampening its insulin-induced autophosphorylation
Bibliographic record
Abstract
BACKGROUND: In spite of new treatments, the incidence of type 2 diabetes (T2D) and its morbidities continue to rise. The key feature of T2D is resistance of adipose tissue and other organs to insulin. Approaches to overcome insulin resistance are limited due to a poor understanding of the mechanisms and inaccessibility of drugs to relevant intracellular targets. We previously showed in mice and humans that CD248, a pre/adipocyte cell surface glycoprotein, acts as an adipose tissue sensor that mediates the transition from healthy to unhealthy adipose, thus promoting insulin resistance. METHODS: Molecular mechanisms by which CD248 regulates insulin signaling were explored using in vivo insulin clamp studies and biochemical analyses of cells/tissues from CD248 knockout (KO) and wild-type (WT) mice with diet-induced insulin resistance. Findings were validated with human adipose tissue specimens. FINDINGS: Genetic deletion of CD248 in mice, overcame diet-induced insulin resistance with improvements in glucose uptake and lipolysis in white adipose tissue depots, effects paralleled by increased adipose/adipocyte GLUT4, phosphorylated AKT and GSK3β, and reduced ATGL. The insulin resistance of the WT mice could be attributed to direct interaction of the extracellular domains of CD248 and the insulin receptor (IR), with CD248 acting to block insulin binding to the IR. This resulted in dampened insulin-mediated autophosphorylation of the IR, with reduced downstream signaling/activation of intracellular events necessary for glucose and lipid homeostasis. INTERPRETATION: Our discovery of a cell-surface CD248-IR complex that is accessible to pharmacologic intervention, opens research avenues toward development of new agents to prevent/reverse insulin resistance. FUNDING: Funded by Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council of Canada (NSERC), Canada Foundations for Innovation (CFI), the Swedish Diabetes Foundation, Family Ernfors Foundation and Novo Nordisk Foundation.
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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) | 0.004 | 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".