Are Obesity-Related Insulin Resistance and Type 2 Diabetes Autoimmune Diseases?
Bibliographic record
Abstract
Obesity and associated insulin resistance predispose individuals to develop chronic metabolic diseases, such as type 2 diabetes and cardiovascular disease. Although these disorders affect a significant proportion of the global population, the underlying mechanisms of disease remain poorly understood. The discovery of elevated tumor necrosis factor-α in adipose tissue as an inducer of obesity-associated insulin resistance marked a new era of understanding that a subclinical inflammatory process underlies the insulin resistance and metabolic dysfunction that precedes type 2 diabetes. Advances in the field identified components of both the innate and adaptive immune response as key players in regulating such inflammatory processes. As antigen specificity is a hallmark of an adaptive immune response, its role in modulating the chronic inflammation that accompanies obesity and type 2 diabetes begs the question of whether insulin resistance and type 2 diabetes can have autoimmune components. In this Perspective, we summarize current data that pertain to the activation and perpetuation of adaptive immune responses during obesity and discuss key missing links and potential mechanisms for obesity-related insulin resistance and type 2 diabetes to be considered as potential autoimmune diseases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".