Specific loss of adipocyte CD248 improves metabolic health via reduced white adipose tissue hypoxia, fibrosis and inflammation
Bibliographic record
Abstract
BACKGROUND: A positive energy balance promotes white adipose tissue (WAT) expansion which is characterized by activation of a repertoire of events including hypoxia, inflammation and extracellular matrix remodelling. The transmembrane glycoprotein CD248 has been implicated in all these processes in different malignant and inflammatory diseases but its potential impact in WAT and metabolic disease has not been explored. METHODS: The role of CD248 in adipocyte function and glucose metabolism was evaluated by omics analyses in human WAT, gene knockdowns in human in vitro differentiated adipocytes and by adipocyte-specific and inducible Cd248 gene knockout studies in mice. FINDINGS: CD248 is upregulated in white but not brown adipose tissue of obese and insulin-resistant individuals. Gene ontology analyses showed that CD248 expression associated positively with pro-inflammatory/pro-fibrotic pathways. By combining data from several human cohorts with gene knockdown experiments in human adipocytes, our results indicate that CD248 acts as a microenvironmental sensor which mediates part of the adipose tissue response to hypoxia and is specifically perturbed in white adipocytes in the obese state. Adipocyte-specific and inducible Cd248 knockouts in mice, both before and after diet-induced obesity and insulin resistance/glucose intolerance, resulted in increased microvascular density as well as attenuated hypoxia, inflammation and fibrosis without affecting fat cell volume. This was accompanied by significant improvements in insulin sensitivity and glucose tolerance. INTERPRETATION: CD248 exerts detrimental effects on WAT phenotype and systemic glucose homeostasis which may be reversed by suppression of adipocyte CD248. Therefore, CD248 may constitute a target to treat obesity-associated co-morbidities.
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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 | 0.000 |
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".