FINE PARTICULATE MATTER AIR POLLUTION AND ANTINUCLEAR ANTIBODY POSITIVITY: THE ONTARIO HEALTH STUDY
Bibliographic record
Abstract
PV075 / #90 Poster Topic: AS10 - Environment and SLE Background/Purpose Air pollution has been increasingly linked to systemic autoimmune rheumatic diseases (SARDs), but studies of fine particulate matter (PM2.5) and SARD-related serologic biomarkers are limited. In this study, we aimed to assess exposure to ambient PM2.5 and antinuclear antibodies (ANA) in the general population. Methods We used data and sera from the Ontario Health Study (OHS), which has enrolled 225,000 general population residents of the province of Ontario in Canada. Serum samples from 3548 subjects (collected at enrollment between 2010-2013) were randomly selected from the OHS database/biorepository. Indirect immunofluorescence assay on Hep-2 cells assessed ANA titers (>1:160, >1:320, >1:640, and >1:1280). Annual mean ambient PM2.5 levels for the 5-year period before sera collection were assigned based on subjects’ 6-digit residential postal codes. Our multivariable logistic regression models computed adjusted odds ratios (ORs) for ANA positivity, comparing the highest (fourth) quartile to the lowest (first) quartile in terms of ambient PM2.5. We adjusted for sex, age, race/ethnicity, smoking, and the Rurality Index of Ontario (to characterize subjects’ urban/rural status). Results Of the 3548 subjects, 2215 (62.4%) were female and 3131 (88.2%) were white. Mean age at serum collection was 54.7 (standard deviation 9.5) years. Multivariate analyses showed females were more likely to be ANA positive than males (Table 1). Comparing the highest vs lowest quartile PM2.5 exposure, the adjusted OR for ANA positivity related to a titer of ≥1:160 was 1.04 (95% CI 0.75-1.44), while for a titer of ≥1:320 the aOR was 1.14 (95% CI 0.77-1.68), for a titer of ≥1:640 the aOR was 1.67 (95% CI 0.99-2.82) and for a titer of ≥1:1280 the aOR was 2.33 (95% CI 1.11-4.91) (Table 2). Table 1. Antinuclear positivity in Ontario Health Study general population subjects* Table 2. Adjusted odds, OR (95% confidence interval, CI) for ANA* positivity for ambient fine particulate matter (PM 2.5 , comparing highest to lowest quartile) adjusting for sex, age, race/ethnicity, smoking, and the Rurality Index of Ontario, RIO Conclusions Our analyses suggested relationships between PM2.5 exposure and ANA positivity which were most prominent at highest titers. This strengthens the argument for systemic immune system effects of air pollution, which could in turn lead to autoimmune disease.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".