Inverse Association Between Obesity and Antinuclear Antibodies in Women
Bibliographic record
Abstract
tionship between positive ANA titer and obesity in women, and the absence of this relationship in men (Table 1).In multivariate analyses to contrast ANA-negative persons against ANA-positive participants in whom the titer was ≥ 1/80, the inverse association between ANA titer and obesity in women was stronger (odds ratio further from the null value) than in models that included ANA titers ≥ 1/40 (Table 1).This inverse relationship we found between ANA and obesity in women from the general population has not been reported previously.Improvements in nutritional status have been paralleled by an increase in the susceptibility to autoimmune diseases 6,7 .Given that leptin accelerates the onset or progression of some autoimmune diseases, and that it also stimulates the secretion of autoantibodies in vitro 8 , it might be predicted that obesity and elevated leptin concentrations would be associated with an increase in ANA.However, we found no such association in men, and in contrast to our expectations, in women we observed that leptin concentration and obesity correlated inversely with ANA.This finding was bolstered by the fact that the association became stronger at higher ANA titers.One possible explanation for the low prevalence of ANA in women with overweight or obesity is related to the lack of response to leptin in obese individuals.Obesity in humans presents hyperleptinemia together with both central and peripheral resistance to the action of this hormone.Leptin resistance has been well documented 9 : as BMI increases, the diminishing response to leptin can impair ANA production by B lymphocytes.To understand why the inverse relationship between obesity and ANA titer appears only in women, we may speculate whether sex hormones play a role in leptin resistance 10 .The main limitation of our study is its cross-sectional design; this prevents us from establishing a causal relationship for the variables we analyzed.The main strength of our study, in contrast, lies in the large sample of individuals drawn randomly from the general population.We conclude that in women in the general population there is an inverse association between positive ANA titer and obesity defined on the basis of anthropometric criteria or serum leptin concentration.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".