Acute pulmonary and inflammatory response in young adults following a scripted car commute

Golan, Rachel; Ladva, Chandresh N; Greenwald, Roby; Krall, Jenna R.; Raysoni, Amit U.; Kumari, Priya; Winquist, Andrea; Flanders, W. Dana; Liang, Donghai; Sarnat, Jeremy A.

doi:10.1007/s11869-017-0530-8

Cited by 18 publications

(27 citation statements)

References 54 publications

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“…The ACE study was a longitudinal panel of 60 participants conducted in Atlanta, GA from 2011 to 2013. The design, participant characteristics, and exclusion criteria have been previously discussed [ 17 – 19 ]. This analysis focuses on a subset of 49 participants within the complete panel for which plasma samples were available.…”

Section: Methodsmentioning

confidence: 99%

“…In-vehicle and clinic pollutant sampling was conducted during the exposure period as described previously [ 20 ] with characterizations previously published [ 17 ]. We focused on particulate matter and specific particulate components with the potential to elicit oxidative stress in humans.…”

Section: Methodsmentioning

confidence: 99%

“…Sampling and targeted biomarker analysis are outlined in detail elsewhere [ 17 ]. Briefly, a panel of inflammatory and oxidative stress markers was collected at multiple time points before and after each commute.…”

Section: Methodsmentioning

confidence: 99%

“…The present analysis leverages extensive measurement collected within a scripted, longitudinal panel of car commuters and novel HRM profiling to investigate potential perturbations of the plasma metabolome following exposures to TRP. The Atlanta Commuters Exposure (ACE) panel study included a targeted examination of oxidative stress and inflammation for a suite of cardiovascular and respiratory outcomes associated with on-road traffic exposures during morning rush hour car commutes in Atlanta, GA [ 17 , 18 ]. In-vehicle exposures to PM 2.5 , its components, and noise were measured for 60 participants along with repeated biological sampling of numerous heart, lung, and inflammation-related endpoints.…”

Section: Introductionmentioning

confidence: 99%

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Particulate metal exposures induce plasma metabolome changes in a commuter panel study

et al. 2018

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IntroductionAdvances in liquid chromatography-mass spectrometry (LC-MS) have enabled high-resolution metabolomics (HRM) to emerge as a sensitive tool for measuring environmental exposures and corresponding biological response. Using measurements collected as part of a large, panel-based study of car commuters, the current analysis examines in-vehicle air pollution concentrations, targeted inflammatory biomarker levels, and metabolomic profiles to trace potential metabolic perturbations associated with on-road traffic exposures.MethodsA 60-person panel of adults participated in a crossover study, where each participant conducted a highway commute and randomized to either a side-street commute or clinic exposure session. In addition to in-vehicle exposure characterizations, participants contributed pre- and post-exposure dried blood spots for 2-hr changes in targeted proinflammatory and vascular injury biomarkers and 10-hr changes in the plasma metabolome. Samples were analyzed on a Thermo QExactive MS system in positive and negative electrospray ionization (ESI) mode. Data were processed and analyzed in R using apLCMS, xMSanalyzer, and limma. Features associated with environmental exposures or biological endpoints were identified with a linear mixed effects model and annotated through human metabolic pathway analysis in mummichog.ResultsHRM detected 10-hr perturbations in 110 features associated with in-vehicle, particulate metal exposures (Al, Pb, and Fe) which reflect changes in arachidonic acid, leukotriene, and tryptophan metabolism. Two-hour changes in proinflammatory biomarkers hs-CRP, IL-6, IL-8, and IL-1β were also associated with 10-hr changes in the plasma metabolome, suggesting diverse amino acid, leukotriene, and antioxidant metabolism effects. A putatively identified metabolite, 20-OH-LTB4, decreased after in-vehicle exposure to particulate metals, suggesting a subclinical immune response.ConclusionsAcute exposures to traffic-related air pollutants are associated with broad inflammatory response, including several traditional markers of inflammation.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Particulate metal exposures induce plasma metabolome changes in a commuter panel study

et al. 2018

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“…Recent epidemiologic studies have documented increased health risks from exposure to atmospheric particulate matter (PM) (Anderson et al 2012;Beelen et al 2014;Pelucchi et al 2009;Shah et al 2013;Hart et al 2015;Heinrich et al 2013;Weuve et al 2012;Stieb et al 2012;Rich et al 2018;Golan et al 2018) for a variety of health outcomes, including nonaccidental mortality, cardiovascular disease mortality, lung cancer, neurocognitive functioning, and effects on reproduction. Studies using proxy measures for exposure to trafficrelated air pollution have generally reported health effects larger than those for the mass concentration of PM < 2.5 μm (PM 2.5 ) or PM < 10 μm (PM 10 ) in aerodynamic diameter (Brugge et al 2013;Gehring et al 2006;Hoffmann et al 2007;Puett et al 2011;Puett et al 2014;Schikowski et al 2005).…”

Section: Introductionmentioning

confidence: 99%

Application and validation of a line-source dispersion model to estimate small scale traffic-related particulate matter concentrations across the conterminous US

Yanosky

Fisher

Liao

et al. 2018

Air Qual Atmos Health

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Numerous studies document increased health risks from exposure to traffic and traffic-related particulate matter (PM). However, many studies use simple exposure metrics to represent traffic-related PM, and/or are limited to small geographic areas over relatively short (e.g., 1 year) time periods. We developed a modeling approach for the conterminous US from 1999 to 2011 that applies a line-source Gaussian plume dispersion model using several spatially and/or temporally varying inputs (including daily meteorology) to produce high spatial resolution estimates of primary near-road traffic-related PM levels. We compared two methods of spatially averaging traffic counts: spatial smoothing generalized additive models and kernel density. Also, we evaluated and validated the output from the line-source dispersion modeling approach in a spatio-temporal model of 24-h average PM < 2.5 μm (PM 2.5 ) elemental carbon (EC) levels. We found that spatial smoothing of traffic count point data performed better than a kernel density approach. Predictive accuracy of the spatio-temporal model of PM 2.5 EC levels was moderate for 24-h averages (cross-validation (CV) R 2 = 0.532) and higher for longer averaging times (CV R 2 = 0.707 and 0.795 for monthly and annual averages, respectively). PM 2.5 EC levels increased monotonically with line-source dispersion model output. Predictive accuracy was higher when the spatio-temporal model of PM 2.5 EC included line-source dispersion model output compared to distance to road terms. Our approach provides estimates of primary traffic-related PM levels with high spatial resolution across the conterminous US from 1999 to 2011. Spatio-temporal model predictions describe 24-h average PM 2.5 EC levels at unmeasured locations well, especially over longer averaging times.

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Environmental toxicology: air

Schwela

2020

Information Resources in Toxicology

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Acute pulmonary and inflammatory response in young adults following a scripted car commute

Cited by 18 publications

References 54 publications

Particulate metal exposures induce plasma metabolome changes in a commuter panel study

Particulate metal exposures induce plasma metabolome changes in a commuter panel study

Application and validation of a line-source dispersion model to estimate small scale traffic-related particulate matter concentrations across the conterminous US

Environmental toxicology: air

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