Long-term exposure to a mixture of industrial SO2, NO2, and PM2.5 and anti-citrullinated protein antibody positivity

• Main Authors: Naizhuo Zhao (Author), Audrey Smargiassi (Author), Marianne Hatzopoulou (Author), Ines Colmegna (Author), Marie Hudson (Author), Marvin J. Fritzler (Author), Philip Awadalla (Author), Sasha Bernatsky (Author)
• Format: Book
• Published: BMC, 2020-07-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12940-020-00637-3; 1476-069X
• Keywords: Anti-citrullinated protein antibodies (ACPA); Industrial air pollutants; Regional fine particles matter (PM2.5); Weighted quantile sum (WQS) regression; California puff (CALPUFF) model; Industrial medicine. Industrial hygiene; RC963-969; Public aspects of medicine; RA1-1270
• Source: Environmental Health, Vol 19, Iss 1, Pp 1-8 (2020)

Abstract Background Studies of associations between industrial air emissions and rheumatic diseases, or diseases-related serological biomarkers, are few. Moreover, previous evaluations typically studied individual (not mixed) emissions. We investigated associations between individual and combined exposures to industrial sulfur dioxide (SO2), nitrogen dioxide (NO2), and fine particles matter (PM2.5) on anti-citrullinated protein antibodies (ACPA), a characteristic biomarker for rheumatoid arthritis (RA). Methods Serum ACPA was determined for 7600 randomly selected CARTaGENE general population subjects in Quebec, Canada. Industrial SO2, NO2, and PM2.5 concentrations, estimated by the California Puff (CALPUFF) atmospheric dispersion model, were assigned based on residential postal codes at the time of sera collection. Single-exposure logistic regressions were performed for ACPA positivity defined by 20 U/ml, 40 U/ml, and 60 U/ml thresholds, adjusting for age, sex, French Canadian origin, smoking, and family income. Associations between regional overall PM2.5 exposure and ACPA positivity were also investigated. The associations between the combined three industrial exposures and the ACPA positivity were assessed by weighted quantile sum (WQS) regressions. Results Significant associations between individual industrial exposures and ACPA positivity defined by the 20 U/ml threshold were seen with single-exposure logistic regression models, for industrial emissions of PM2.5 (odds ratio, OR = 1.19, 95% confidence intervals, CI: 1.04-1.36) and SO2 (OR = 1.03, 95% CI: 1.00-1.06), without clear associations for NO2 (OR = 1.01, 95% CI: 0.86-1.17). Similar findings were seen for the 40 U/ml threshold, although at 60 U/ml, the results were very imprecise. The WQS model demonstrated a positive relationship between combined industrial exposures and ACPA positivity (OR = 1.36, 95% CI: 1.10-1.69 at 20 U/ml) and suggested that industrial PM2.5 may have a closer association with ACPA positivity than the other exposures. Again, similar findings were seen with the 40 U/ml threshold, though 60 U/ml results were imprecise. No clear association between ACPA and regional overall PM2.5 exposure was seen. Conclusions We noted positive associations between ACPA and industrial emissions of PM2.5 and SO2. Industrial PM2.5 exposure may play a particularly important role in this regard.