Investigating associations between anti-nuclear antibody positivity and combined long-term exposures to NO2, O3, and PM2.5 using a Bayesian kernel machine regression approach

•We determined ANA using biobanked sera from a general population sample in Quebec.•Effects of exposures to NO2, O3, and PM2.5 on ANA were assessed by a BKMR method.•We compared the results obtained by the BKMR to standard logistic regression models.•Individual/mixed effects of exposures on ANA were...

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Published inEnvironment international Vol. 136; p. 105472
Main Authors Zhao, Naizhuo, Smargiassi, Audrey, Hudson, Marie, Fritzler, Marvin J., Bernatsky, Sasha
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.03.2020
Elsevier
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Online AccessGet full text
ISSN0160-4120
1873-6750
1873-6750
DOI10.1016/j.envint.2020.105472

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Abstract •We determined ANA using biobanked sera from a general population sample in Quebec.•Effects of exposures to NO2, O3, and PM2.5 on ANA were assessed by a BKMR method.•We compared the results obtained by the BKMR to standard logistic regression models.•Individual/mixed effects of exposures on ANA were not seen with either method. Air pollution has many adverse health effects, but the combined or synergistic effects of multiple ambient air pollutants on anti-nuclear antibodies (ANA, a serologic marker of systemic autoimmune rheumatic disease, SARDs) have never been assessed. To flexibly model ANA and individual and joint associations of long-term exposures to nitrogen dioxide (NO2), ozone (O3), and fine particles matter (PM2.5) using a Bayesian Kernel machine regression (BKMR) approach and to compare the results to those from individual logistic regressions. Serum ANA positivity was determined for randomly selected CARTaGENE general population subjects in Quebec, Canada. CARTaGENE is a public research platform created for investigating the associations of environmental, genomic, and lifestyle factors on chronic diseases. Ambient NO2, O3, and PM2.5 estimates, derived from ground-measurement and chemical-transport-model simulated concentrations, were assigned to subjects based on residential postal codes at the time of blood collection. Our models adjusted for age, sex, French Canadian origin, smoking, and family income. Concentrations of NO2, O3, and PM2.5 were closely correlated in space. In the 5485 CARTaGENE subjects studied, we did not see clear associations between NO2, PM2.5 or O3 and ANA positivity, with either the BKMR or logistic models. BKMR did not uncover associations between ANA positivity and individual levels or combined exposures of NO2, O3, and PM2.5; neither did simpler logistic models. Additional studies (in younger populations, in distinct race/ethnicity groups, and/or in jurisdictions with high air pollution levels) would be helpful to reinforce current findings.
AbstractList •We determined ANA using biobanked sera from a general population sample in Quebec.•Effects of exposures to NO2, O3, and PM2.5 on ANA were assessed by a BKMR method.•We compared the results obtained by the BKMR to standard logistic regression models.•Individual/mixed effects of exposures on ANA were not seen with either method. Air pollution has many adverse health effects, but the combined or synergistic effects of multiple ambient air pollutants on anti-nuclear antibodies (ANA, a serologic marker of systemic autoimmune rheumatic disease, SARDs) have never been assessed. To flexibly model ANA and individual and joint associations of long-term exposures to nitrogen dioxide (NO2), ozone (O3), and fine particles matter (PM2.5) using a Bayesian Kernel machine regression (BKMR) approach and to compare the results to those from individual logistic regressions. Serum ANA positivity was determined for randomly selected CARTaGENE general population subjects in Quebec, Canada. CARTaGENE is a public research platform created for investigating the associations of environmental, genomic, and lifestyle factors on chronic diseases. Ambient NO2, O3, and PM2.5 estimates, derived from ground-measurement and chemical-transport-model simulated concentrations, were assigned to subjects based on residential postal codes at the time of blood collection. Our models adjusted for age, sex, French Canadian origin, smoking, and family income. Concentrations of NO2, O3, and PM2.5 were closely correlated in space. In the 5485 CARTaGENE subjects studied, we did not see clear associations between NO2, PM2.5 or O3 and ANA positivity, with either the BKMR or logistic models. BKMR did not uncover associations between ANA positivity and individual levels or combined exposures of NO2, O3, and PM2.5; neither did simpler logistic models. Additional studies (in younger populations, in distinct race/ethnicity groups, and/or in jurisdictions with high air pollution levels) would be helpful to reinforce current findings.
Air pollution has many adverse health effects, but the combined or synergistic effects of multiple ambient air pollutants on anti-nuclear antibodies (ANA, a serologic marker of systemic autoimmune rheumatic disease, SARDs) have never been assessed.BACKGROUNDAir pollution has many adverse health effects, but the combined or synergistic effects of multiple ambient air pollutants on anti-nuclear antibodies (ANA, a serologic marker of systemic autoimmune rheumatic disease, SARDs) have never been assessed.To flexibly model ANA and individual and joint associations of long-term exposures to nitrogen dioxide (NO2), ozone (O3), and fine particles matter (PM2.5) using a Bayesian Kernel machine regression (BKMR) approach and to compare the results to those from individual logistic regressions.OBJECTIVETo flexibly model ANA and individual and joint associations of long-term exposures to nitrogen dioxide (NO2), ozone (O3), and fine particles matter (PM2.5) using a Bayesian Kernel machine regression (BKMR) approach and to compare the results to those from individual logistic regressions.Serum ANA positivity was determined for randomly selected CARTaGENE general population subjects in Quebec, Canada. CARTaGENE is a public research platform created for investigating the associations of environmental, genomic, and lifestyle factors on chronic diseases. Ambient NO2, O3, and PM2.5 estimates, derived from ground-measurement and chemical-transport-model simulated concentrations, were assigned to subjects based on residential postal codes at the time of blood collection. Our models adjusted for age, sex, French Canadian origin, smoking, and family income.METHODSSerum ANA positivity was determined for randomly selected CARTaGENE general population subjects in Quebec, Canada. CARTaGENE is a public research platform created for investigating the associations of environmental, genomic, and lifestyle factors on chronic diseases. Ambient NO2, O3, and PM2.5 estimates, derived from ground-measurement and chemical-transport-model simulated concentrations, were assigned to subjects based on residential postal codes at the time of blood collection. Our models adjusted for age, sex, French Canadian origin, smoking, and family income.Concentrations of NO2, O3, and PM2.5 were closely correlated in space. In the 5485 CARTaGENE subjects studied, we did not see clear associations between NO2, PM2.5 or O3 and ANA positivity, with either the BKMR or logistic models.RESULTSConcentrations of NO2, O3, and PM2.5 were closely correlated in space. In the 5485 CARTaGENE subjects studied, we did not see clear associations between NO2, PM2.5 or O3 and ANA positivity, with either the BKMR or logistic models.BKMR did not uncover associations between ANA positivity and individual levels or combined exposures of NO2, O3, and PM2.5; neither did simpler logistic models. Additional studies (in younger populations, in distinct race/ethnicity groups, and/or in jurisdictions with high air pollution levels) would be helpful to reinforce current findings.CONCLUSIONSBKMR did not uncover associations between ANA positivity and individual levels or combined exposures of NO2, O3, and PM2.5; neither did simpler logistic models. Additional studies (in younger populations, in distinct race/ethnicity groups, and/or in jurisdictions with high air pollution levels) would be helpful to reinforce current findings.
Air pollution has many adverse health effects, but the combined or synergistic effects of multiple ambient air pollutants on anti-nuclear antibodies (ANA, a serologic marker of systemic autoimmune rheumatic disease, SARDs) have never been assessed.To flexibly model ANA and individual and joint associations of long-term exposures to nitrogen dioxide (NO₂), ozone (O₃), and fine particles matter (PM₂.₅) using a Bayesian Kernel machine regression (BKMR) approach and to compare the results to those from individual logistic regressions.Serum ANA positivity was determined for randomly selected CARTaGENE general population subjects in Quebec, Canada. CARTaGENE is a public research platform created for investigating the associations of environmental, genomic, and lifestyle factors on chronic diseases. Ambient NO₂, O₃, and PM₂.₅ estimates, derived from ground-measurement and chemical-transport-model simulated concentrations, were assigned to subjects based on residential postal codes at the time of blood collection. Our models adjusted for age, sex, French Canadian origin, smoking, and family income.Concentrations of NO₂, O₃, and PM₂.₅ were closely correlated in space. In the 5485 CARTaGENE subjects studied, we did not see clear associations between NO₂, PM₂.₅ or O₃ and ANA positivity, with either the BKMR or logistic models.BKMR did not uncover associations between ANA positivity and individual levels or combined exposures of NO₂, O₃, and PM₂.₅; neither did simpler logistic models. Additional studies (in younger populations, in distinct race/ethnicity groups, and/or in jurisdictions with high air pollution levels) would be helpful to reinforce current findings.
Background: Air pollution has many adverse health effects, but the combined or synergistic effects of multiple ambient air pollutants on anti-nuclear antibodies (ANA, a serologic marker of systemic autoimmune rheumatic disease, SARDs) have never been assessed. Objective: To flexibly model ANA and individual and joint associations of long-term exposures to nitrogen dioxide (NO2), ozone (O3), and fine particles matter (PM2.5) using a Bayesian Kernel machine regression (BKMR) approach and to compare the results to those from individual logistic regressions. Methods: Serum ANA positivity was determined for randomly selected CARTaGENE general population subjects in Quebec, Canada. CARTaGENE is a public research platform created for investigating the associations of environmental, genomic, and lifestyle factors on chronic diseases. Ambient NO2, O3, and PM2.5 estimates, derived from ground-measurement and chemical-transport-model simulated concentrations, were assigned to subjects based on residential postal codes at the time of blood collection. Our models adjusted for age, sex, French Canadian origin, smoking, and family income. Results: Concentrations of NO2, O3, and PM2.5 were closely correlated in space. In the 5485 CARTaGENE subjects studied, we did not see clear associations between NO2, PM2.5 or O3 and ANA positivity, with either the BKMR or logistic models. Conclusions: BKMR did not uncover associations between ANA positivity and individual levels or combined exposures of NO2, O3, and PM2.5; neither did simpler logistic models. Additional studies (in younger populations, in distinct race/ethnicity groups, and/or in jurisdictions with high air pollution levels) would be helpful to reinforce current findings. Keywords: Anti-nuclear antibodies (ANAs), Nitrogen dioxide (NO2), Ozone (O3), Fine particles matter (PM2.5), Bayesian kernel machine regression (BKMR)
ArticleNumber 105472
Author Hudson, Marie
Smargiassi, Audrey
Bernatsky, Sasha
Fritzler, Marvin J.
Zhao, Naizhuo
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  organization: Department of Medicine, McGill University, Montreal, QC, Canada
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  organization: Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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  givenname: Sasha
  surname: Bernatsky
  fullname: Bernatsky, Sasha
  email: sasha.bernatsky@mcgill.ca
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Keywords Fine particles matter (PM2.5)
Bayesian kernel machine regression (BKMR)
Anti-nuclear antibodies (ANAs)
Ozone (O3)
Nitrogen dioxide (NO2)
Language English
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Snippet •We determined ANA using biobanked sera from a general population sample in Quebec.•Effects of exposures to NO2, O3, and PM2.5 on ANA were assessed by a BKMR...
Air pollution has many adverse health effects, but the combined or synergistic effects of multiple ambient air pollutants on anti-nuclear antibodies (ANA, a...
Background: Air pollution has many adverse health effects, but the combined or synergistic effects of multiple ambient air pollutants on anti-nuclear...
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StartPage 105472
SubjectTerms adverse effects
air pollutants
air pollution
Anti-nuclear antibodies (ANAs)
antibodies
Bayesian kernel machine regression (BKMR)
Bayesian theory
blood sampling
chronic diseases
Fine particles matter (PM2.5)
genomics
lifestyle
logit analysis
nationalities and ethnic groups
nitrogen dioxide
Nitrogen dioxide (NO2)
ozone
Ozone (O3)
particulates
public research
Quebec
synergism
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Title Investigating associations between anti-nuclear antibody positivity and combined long-term exposures to NO2, O3, and PM2.5 using a Bayesian kernel machine regression approach
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