An autoantibody targeting glycated IgG is associated with elevated serum immune complexes in rheumatoid arthritis (RA)
Bibliographic record
Abstract
Advanced glycation end-products (AGE) play a role in diabetes complications and in RA. An autoantibody to IgG-AGE has been shown to correlate with RA disease activity. Thus we sought to analyse serum immune complexes (IC) and AGE-modified proteins in Caucasians and North American Indians to see if the presence of anti-IgG-AGE influenced their composition. Polyethylene glycol precipitation of IC from the serum of anti-IgG-AGE-positive or -negative RA patients, and healthy and diabetic controls were examined. Concentrations of circulating IC were highest in anti-IgG-AGE+ RA patients, followed by anti-IgG-AGE- RA patients, which were greater than healthy controls. IC amounts in the Ojibwe were consistently higher than in Caucasians. Affinity purification of AGE-modified proteins from IC and immunoblotting with antibodies against Ig gamma and mu heavy chains, kappa and lambda light chains, and AGE Nepsilon(carboxymethyl)lysine and imidazolone yielded similar results: anti-AGE+ RA patients had elevated levels relative to those without the autoantibody. Levels in both RA groups were higher than in controls. Glycated albumin amounts followed a similar distribution, but were not influenced by the presence of anti-AGE antibodies. A heavily glycated kappa-chain was present primarily in IC from anti-IgG-AGE+ patients. These studies indicate that anti-AGE antibodies have a direct impact on the accumulation of IgG-AGE but not glycated albumin, and may block the normal clearance of IgG-AGE through AGE receptors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".