Interleukin-6 autoantibodies are involved in the pathogenesis of a subset of type 2 diabetes
Bibliographic record
Abstract
Interleukin-6 (IL6) is critically involved in inflammation and metabolism. About 1% of people produce IL6 autoantibodies (aAb-IL6) that impair IL6 signaling in vivo. We tested the hypothesis that the prevalence of such aAb-IL6 is increased in type 2 diabetic patients and that aAb-IL6 plays a direct role in causing hyperglycemia. In humans, the prevalence of circulating high-affinity neutralizing aAb-IL6 was 2.5% in the type 2 diabetic patients and 1% in the controls (odds ratio 2.5, 95% confidence interval 1.2-4.9, P=0.01). To test for the role of aAb-IL6 in causing hyperglycemia, such aAb-IL6 were induced in mice by a validated vaccination procedure. Mice with plasma levels of aAb-IL6 similar to the 2.5% type 2 diabetic patients developed obesity and impaired glucose tolerance (area under the curve (AUC) glucose, 2056+/-62 vs 1793+/-62, P=0.05) as compared with sham-vaccinated mice, when challenged with a high-fat diet. Mice with very high plasma levels of aAb-IL6 developed elevated fasting plasma glucose (mM, 4.8+/-0.4 vs 3.3+/-0.1, P<0.001) and impaired glucose tolerance (AUC glucose, 1340+/-38 vs 916+/-25, P<0.001) as compared with sham-control mice on normal chow. In conclusion, the prevalence of plasma aAb-IL6 at levels known to impair IL6 signaling in vivo is increased 2.5-fold in people with type 2 diabetes. In mice, matching levels of aAb-IL6 cause obesity and hyperglycemia. These data suggest that a small subset of type 2 diabetes may in part evolve from an autoimmune attack against IL6.
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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) | 0.001 | 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 | 0.000 |
| 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".