Gene expression network analyses in response to air pollution exposures in the trucking industry.
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ABSTRACT:
SUBMITTER: Chu JH
PROVIDER: S-EPMC5093980 | biostudies-literature | 2016 Nov
REPOSITORIES: biostudies-literature
Publications
Gene expression network analyses in response to air pollution exposures in the trucking industry.
Chu Jen-Hwa JH Hart Jaime E JE Chhabra Divya D Garshick Eric E Raby Benjamin A BA Laden Francine F
Environmental health : a global access science source 20161103 1
<h4>Background</h4>Exposure to air pollution, including traffic-related pollutants, has been associated with a variety of adverse health outcomes, including increased cardiopulmonary morbidity and mortality, and increased lung cancer risk.<h4>Methods</h4>To better understand the cellular responses induced by air pollution exposures, we performed genome-wide gene expression microarray analysis using whole blood RNA sampled at three time-points across the work weeks of 63 non-smoking employees at ...[more]
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Project description:To investigate the cellular responses induced by air pollution exposures, we performed genome-wide gene expression microarray analysis using whole blood RNA sampled at three time-points across the work weeks of 63 non-smoking employees in the trucking industry. Our objective was to identify the genes and gene networks differentially activated in response to micro-environmental measures of occupational exposure to three pollutants: PM2.5 (particulate matter ≤ 2.5 microns in diameter) and elemental carbon (EC) and organic carbon (OC).
2016-07-08 | GSE83864 | GEO
Project description:Few epidemiologic studies have evaluated the effects of air pollution on the risk of Parkinson disease (PD).We investigated the associations of long-term residential concentrations of ambient particulate matter (PM) < 10 ?m in diameter (PM10) and < 2.5 ?m in diameter (PM2.5) and nitrogen dioxide (NO2) in relation to PD risk.Our nested case-control analysis included 1,556 self-reported physician-diagnosed PD cases identified between 1995 and 2006 and 3,313 controls frequency-matched on age, sex, and race. We geocoded home addresses reported in 1995-1996 and estimated the average ambient concentrations of PM10, PM2.5, and NO2 using a national fine-scale geostatistical model incorporating roadway information and other geographic covariates. Air pollutant exposures were analyzed as both quintiles and continuous variables, adjusting for matching variables and potential confounders.We observed no statistically significant overall association between PM or NO2 exposures and PD risk. However, in preplanned subgroup analyses, a higher risk of PD was associated with higher exposure to PM10 (ORQ5 vs. Q1 = 1.65; 95% CI: 1.11, 2.45; p-trend = 0.02) among women, and with higher exposure to PM2.5 (ORQ5 vs. Q1 = 1.29; 95% CI: 0.94, 1.76; p-trend = 0.04) among never smokers. In post hoc analyses among female never smokers, both PM2.5 (ORQ5 vs. Q1 = 1.79; 95% CI: 1.01, 3.17; p-trend = 0.05) and PM10 (ORQ5 vs. Q1 = 2.34; 95% CI: 1.29, 4.26; p-trend = 0.01) showed positive associations with PD risk. Analyses based on continuous exposure variables generally showed similar but nonsignificant associations.Overall, we found limited evidence for an association between exposures to ambient PM10, PM2.5, or NO2 and PD risk. The suggestive evidence that exposures to PM2.5 and PM10 may increase PD risk among female never smokers warrants further investigation. Citation: Liu R, Young MT, Chen JC, Kaufman JD, Chen H. 2016. Ambient air pollution exposures and risk of Parkinson disease. Environ Health Perspect 124:1759-1765;?http://dx.doi.org/10.1289/EHP135.
| S-EPMC5089873 | biostudies-other
Project description:BackgroundAir pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data.MethodsWe analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated date of conception during 2002-2005 (n = 403,881). We predicted trimester-specific PM2.5 exposure using a complex spatiotemporal exposure model. To improve spatial compatibility, we restricted to mothers residing in counties with a PM2.5 monitor (n = 180,440). We accounted for additional measurement error via a nonparametric bootstrap.ResultsThird trimester PM2.5 exposure was associated with lower birth weight in the uncorrected (-2.4 g per 1 μg/m difference in exposure; 95% confidence interval [CI]: -3.9, -0.8) and bootstrap-corrected (-2.5 g, 95% CI: -4.2, -0.8) analyses. Results for the unrestricted analysis were attenuated (-0.66 g, 95% CI: -1.7, 0.35).ConclusionsThis study presents a novel application of measurement error correction for spatiotemporal air pollution exposures. Our results demonstrate the importance of spatial compatibility between monitor and subject locations and provide evidence of the association between air pollution exposure and birth weight.
| S-EPMC5378630 | biostudies-literature
Project description:Cohort studies in air pollution epidemiology aim to establish associations between health outcomes and air pollution exposures. Statistical analysis of such associations is complicated by the multivariate nature of the pollutant exposure data as well as the spatial misalignment that arises from the fact that exposure data are collected at regulatory monitoring network locations distinct from cohort locations. We present a novel clustering approach for addressing this challenge. Specifically, we present a method that uses geographic covariate information to cluster multi-pollutant observations and predict cluster membership at cohort locations. Our predictive k-means procedure identifies centers using a mixture model and is followed by multi-class spatial prediction. In simulations, we demonstrate that predictive k-means can reduce misclassification error by over 50% compared to ordinary k-means, with minimal loss in cluster representativeness. The improved prediction accuracy results in large gains of 30% or more in power for detecting effect modification by cluster in a simulated health analysis. In an analysis of the NIEHS Sister Study cohort using predictive k-means, we find that the association between systolic blood pressure (SBP) and long-term fine particulate matter (PM2.5) exposure varies significantly between different clusters of PM2.5 component profiles. Our cluster-based analysis shows that for subjects assigned to a cluster located in the Midwestern U.S., a 10 μg/m3 difference in exposure is associated with 4.37 mmHg (95% CI, 2.38, 6.35) higher SBP.
| S-EPMC5448716 | biostudies-literature
Project description:BACKGROUND:Maternal exposure to air pollution is associated with reduced fetal growth, but its relationship with expression of placental imprinted genes (important regulators of fetal growth) has not yet been studied. OBJECTIVES:To examine relationships between maternal residential air pollution and expression of placental imprinted genes in the Rhode Island Child Health Study (RICHS). METHODS:Women-infant pairs were enrolled following delivery between 2009 and 2013. We geocoded maternal residential addresses at delivery, estimated daily levels of fine particulate matter (PM2.5; n=355) and black carbon (BC; n=336) using spatial-temporal models, and estimated residential distance to nearest major roadway (n=355). Using linear regression models we investigated the associations between each exposure metric and expression of nine candidate genes previously associated with infant birthweight in RICHS, with secondary analyses of a panel of 108 imprinted genes expressed in the placenta. We also explored effect measure modification by infant sex. RESULTS:PM2.5 and BC were associated with altered expression for seven and one candidate genes, respectively, previously linked with birthweight in this cohort. Adjusting for multiple comparisons, we found that PM2.5 and BC were associated with changes in expression of 41 and 12 of 108 placental imprinted genes, respectively. Infant sex modified the association between PM2.5 and expression of CHD7 and between proximity to major roadways and expression of ZDBF2. CONCLUSIONS:We found that maternal exposure to residential PM2.5 and BC was associated with changes in placental imprinted gene expression, which suggests a plausible line of investigation of how air pollution affects fetal growth and development.
| S-EPMC5623128 | biostudies-literature
Project description:BACKGROUND:Residential proximity to major roadways, and prenatal exposures to particulate matter <2.5??m (PM2.5) and ozone (O3) are linked to poor fetal outcomes but their relationship with childhood development is unclear. OBJECTIVES:We investigated whether proximity to major roadways, or prenatal and early-life exposures to PM2.5 and O3 increase the risk of early developmental delays. STUDY DESIGN:Prospective cohort. SETTINGS:New York State excluding New York City. PARTICIPANTS:4089 singletons and 1016 twins born between 2008 and 2010. EXPOSURES:Proximity to major roadway was calculated using road network data from the NY Department of Transportation. Concentrations of PM2.5 and O3 estimated by the Environmental Protection Agency Downscaler models were spatiotemporally linked to each child's prenatal and early-life addresses incorporating residential history, and locations of maternal work and day-care. OUTCOMES:Parents reported their children's development at ages 8, 12, 18, 24, 30 and 36 months in five domains using the Ages and Stages Questionnaire. Generalized mixed models estimated the relative risk (RR) and 95% CI for failing any developmental domain per 10 units increase in PM2.5 and O3, and for those living <1000?m away from a major roadway compared to those living further. Models adjusted for potential confounders. RESULTS:Compared to those >1000?m away from a major roadway, those resided 50-100?m [RR: 2.12 (1.00-4.52)] and 100-500?m [RR: 2.07 (1.02-4.22)] away had twice the risk of failing the communication domain. Prenatal exposures to both PM2.5 and ozone during various pregnancy windows had weak but significant associations with failing any developmental domain with effects ranging from 1.6% to 2.7% for a 10??g/m3 increase in PM2.5 and 0.7%-1.7% for a 10?ppb increase in ozone. Average daily postnatal ozone exposure was positively associated with failing the overall screening by 8 months [3.3% (1.1%-5.5%)], 12 months [17.7% (10.4%-25.5%)], and 30 months [7.6%, (1.3%-14.3%)]. Findings were mixed for postnatal PM2.5 exposures. CONCLUSIONS:In this prospective cohort study, proximity to major roadway and prenatal/early-life exposures to PM2.5 and O3 were associated with developmental delays. While awaiting larger studies with personal air pollution assessment, efforts to minimize air pollution exposures during critical developmental windows may be warranted.
| S-EPMC6541527 | biostudies-literature
Project description:ObjectiveStudies suggest that prenatal exposure to traffic-related air pollution (TRAP) may contribute to childhood obesity. While exact mechanisms for this association are unknown, circulating adipokines are hypothesized to contribute to early-life weight gain.MethodsThe Maternal and Child Health Study birth cohort included 136 women from the Los Angeles County + University of Southern California Medical Center. This study estimated prenatal residential TRAP exposure and used linear regression analysis to examine associations between adipokines with TRAP exposure and infant weight change (birth to 6 months).ResultsA one standard deviation (1-SD: 2 ppb) increase in prenatal non-freeway nitrogen oxides was associated with 33% (P = 0.01) higher leptin and 9% higher high molecular weight adiponectin levels (P = 0.07) in cord blood. Leptin levels were 71% higher in mothers who lived <75 m than those living >300 m from major roadways (P = 0.03). A 1-SD (10 ng mL-1 ) increase in leptin was associated with a significant increase in infant weight change in female infants (0.62 kg, P = 0.02) but not male infants (0.11 kg, P = 0.48).ConclusionsHigher TRAP exposures were associated with higher cord blood levels of leptin and high molecular weight adiponectin. These adipokines were associated with increased infant weight change in female infants, which may have implications for future obesity risk.
| S-EPMC5934325 | biostudies-literature
Project description:Previous studies have suggested an association between particulate air pollution and cardiovascular disease, but the mechanism is still unclear.We examined the association between workplace exposure to vehicle-related particles and cardiovascular disease related systemic inflammatory markers, C-reactive protein (hs-CRP), soluble intercellular adhesion molecule-1 (sICAM-1), and interleukin-6 (IL-6) in 137 trucking terminal workers (non-drivers) in the U.S. trucking industry.We visited two large trucking terminals in 2009 and measured vehicle-related elemental carbon (EC), organic carbon (OC), and particulate matter with aerodynamic diameter ?2.5µm (PM2.5), for 5 days consecutively at the main work areas. Each participant provided a blood sample and completed a health questionnaire during the sampling period. Individual workplace exposure level was calculated by 12-h time weighted moving averages based on work shift. The association between each blood marker and exposure to each pollutant during 0-12, 12-24, 24-36, and 36-48h before the blood draw was examined by multivariable regression analyses.In general, OC and EC had a positive association with sICAM-1, especially for exposure periods 12-24 (lag12-24) and 24-36 (lag24-36)h prior to blood draw [?=54.9 (95%CI: 12.3-97.5) for lag12-24 and ?=46.5 (95%CI: 21.2-71.8) for lag12-24; change in sICAM-1 (in ng/mL) corresponding to an IQR increase in OC]. A similar pattern was found for EC and PM2.5. We did not find an association between measured pollutants up to 48h before blood draw and hs-CRP or IL-6.In this group of healthy workers, short-term exposure to vehicle-related air pollutants may be associated with sICAM-1. Our findings may be dependent on the exposure period studied.
| S-EPMC4874883 | biostudies-literature
Project description:Due to their lack of repair capacity mitochondria are critical targets for environmental toxicants. We studied genes and pathways reflecting mitochondrial responses to short- and medium-term PM10 exposure.Whole genome gene expression was measured in peripheral blood of 98 adults (49% women). We performed linear regression analyses stratified by sex and adjusted for individual and temporal characteristics to investigate alterations in gene expression induced by short-term (week before blood sampling) and medium-term (month before blood sampling) PM10 exposure. Overrepresentation analyses (ConsensusPathDB) were performed to identify enriched mitochondrial associated pathways and gene ontology sets. Thirteen Human MitoCarta genes were measured by means of quantitative real-time polymerase chain reaction (qPCR) along with mitochondrial DNA (mtDNA) content in an independent validation cohort (n = 169, 55.6% women).Overrepresentation analyses revealed significant pathways (p-value <0.05) related to mitochondrial genome maintenance and apoptosis for short-term exposure and to the electron transport chain (ETC) for medium-term exposure in women. For men, medium-term PM10 exposure was associated with the Tri Carbonic Acid cycle. In an independent study population, we validated several ETC genes, including UQCRH and COX7C (q-value <0.05), and some genes crucial for the maintenance of the mitochondrial genome, including LONP1 (q-value: 0.07) and POLG (q-value: 0.04) in women.In this exploratory study, we identified mitochondrial genes and pathways associated with particulate air pollution indicating upregulation of energy producing pathways as a potential mechanism to compensate for PM-induced mitochondrial damage.
| S-EPMC5563023 | biostudies-other
Project description:Commuting in automobiles can contribute substantially to total traffic-related air pollution (TRAP) exposure, yet measuring commuting exposures for studies of health outcomes remains challenging. To estimate real-world TRAP exposures, we developed and evaluated the robustness of a scripted drive protocol on the NJ Turnpike and local roads between April 2007 and October 2014. Study participants were driven in a car with closed windows and open vents during morning rush hours on 190 days. Real-time measurements of PM2.5, PNC, CO, and BC, and integrated samples of NO2, were made in the car cabin. Exposure measures included in-vehicle concentrations on the NJ Turnpike and local roads and the differences and ratios of these concentrations. Median in-cabin concentrations were 11 ?g/m3 PM2.5, 40 000 particles/cm3, 0.3 ppm CO, 4 ?g/m3 BC, and 20.6 ppb NO2. In-cabin concentrations on the NJ Turnpike were higher than in-cabin concentrations on local roads by a factor of 1.4 for PM2.5, 3.5 for PNC, 1.0 for CO, and 4 for BC. Median concentrations of NO2 for full rides were 2.4 times higher than ambient concentrations. Results were generally robust relative to season, traffic congestion, ventilation setting, and study year, except for PNC and PM2.5, which had secular and seasonal trends. Ratios of concentrations were more stable than differences or absolute concentrations. Scripted drives can be used for generating reasonably consistent in-cabin increments of exposure to traffic-related air pollution.
| S-EPMC5019181 | biostudies-literature