The C3a Anaphylatoxin Receptor Is a Key Mediator of Insulin Resistance and Functions by Modulating Adipose Tissue Macrophage Infiltration and Activation
Bibliographic record
Abstract
OBJECTIVE: Significant new data suggest that metabolic disorders such as diabetes, obesity, and atherosclerosis all posses an important inflammatory component. Infiltrating macrophages contribute to both tissue-specific and systemic inflammation, which promotes insulin resistance. The complement cascade is involved in the inflammatory cascade initiated by the innate and adaptive immune response. A mouse genomic F2 cross biology was performed and identified several causal genes linked to type 2 diabetes, including the complement pathway. RESEARCH DESIGN AND METHODS: We therefore sought to investigate the effect of a C3a receptor (C3aR) deletion on insulin resistance, obesity, and macrophage function utilizing both the normal-diet (ND) and a diet-induced obesity mouse model. RESULTS: We demonstrate that high C3aR expression is found in white adipose tissue and increases upon high-fat diet (HFD) feeding. Both adipocytes and macrophages within the white adipose tissue express significant amounts of C3aR. C3aR(-/-) mice on HFD are transiently resistant to diet-induced obesity during an 8-week period. Metabolic profiling suggests that they are also protected from HFD-induced insulin resistance and liver steatosis. C3aR(-/-) mice had improved insulin sensitivity on both ND and HFD as seen by an insulin tolerance test and an oral glucose tolerance test. Adipose tissue analysis revealed a striking decrease in macrophage infiltration with a concomitant reduction in both tissue and plasma proinflammatory cytokine production. Furthermore, C3aR(-/-) macrophages polarized to the M1 phenotype showed a considerable decrease in proinflammatory mediators. CONCLUSIONS: Overall, our results suggest that the C3aR in macrophages, and potentially adipocytes, plays an important role in adipose tissue homeostasis and insulin resistance.
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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) | 0.000 | 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) | 0.002 | 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".