Use of high-resolution metabolomics for the identification of metabolic signals associated with traffic-related air pollution.
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ABSTRACT:
SUBMITTER: Liang D
PROVIDER: S-EPMC6414207 | biostudies-literature | 2018 Nov
REPOSITORIES: biostudies-literature
Publications
Use of high-resolution metabolomics for the identification of metabolic signals associated with traffic-related air pollution.
Liang Donghai D Moutinho Jennifer L JL Golan Rachel R Yu Tianwei T Ladva Chandresh N CN Niedzwiecki Megan M Walker Douglas I DI Sarnat Stefanie Ebelt SE Chang Howard H HH Greenwald Roby R Jones Dean P DP Russell Armistead G AG Sarnat Jeremy A JA
Environment international 20180807
<h4>Background</h4>High-resolution metabolomics (HRM) is emerging as a sensitive tool for measuring environmental exposures and biological responses. The aim of this analysis is to assess the ability of high-resolution metabolomics (HRM) to reflect internal exposures to complex traffic-related air pollution mixtures.<h4>Methods</h4>We used untargeted HRM profiling to characterize plasma and saliva collected from participants in the Dorm Room Inhalation to Vehicle Emission (DRIVE) study to identi ...[more]
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Project description:BackgroundSubstantial research has investigated the adverse effects of traffic-related air pollutants (TRAP) on human health. Convincing associations between TRAP and respiratory and cardiovascular diseases are known, but the underlying biological mechanisms are not well established. High-resolution metabolomics (HRM) is a promising platform for untargeted characterization of molecular mechanisms between TRAP and health indexes.ObjectivesWe examined metabolic perturbations associated with short-term exposures to TRAP, including carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), fine particulate matter (PM2.5), organic carbon (OC), and elemental carbon (EC) among 180 participants of the Center for Health Discovery and Well-Being (CHDWB), a cohort of Emory University-affiliated employees.MethodsA cross-sectional study was conducted on baseline visits of 180 CHDWB participants enrolled during 2008-2012, in whom HRM profiling was determined in plasma samples using liquid chromatography-high-resolution mass spectrometry with positive and negative electrospray ionization (ESI) modes. Ambient pollution concentrations were measured at an ambient monitor near downtown Atlanta. Metabolic perturbations associated with TRAP exposures were assessed following an untargeted metabolome-wide association study (MWAS) framework using feature-specific Tobit regression models, followed by enriched pathway analysis and chemical annotation.ResultsSubjects were predominantly white (76.1%) and non-smokers (95.6%), and all had at least a high school education. In total, 7821 and 4123 metabolic features were extracted from the plasma samples by the negative and positive ESI runs, respectively. There are 3421 features significantly associated with at least one air pollutant by negative ion mode, and 1691 features by positive ion mode. Biological pathways enriched by features associated with the pollutants are primarily involved in nucleic acids damage/repair (e.g., pyrimidine metabolism), nutrient metabolism (e.g., fatty acid metabolism), and acute inflammation (e.g., histidine metabolism and tyrosine metabolism). NO2 and EC were associated most consistently with these pathways. We confirmed the chemical identity of 8 metabolic features in negative ESI and 2 features in positive ESI, including metabolites closely linked to oxidative stress and inflammation, such as histamine, tyrosine, tryptophan, and proline.ConclusionsWe identified a range of ambient pollutants, including components of TRAP, associated with differences in the metabolic phenotype among the cohort of 180 subjects. We found Tobit models to be a robust approach to handle missing data among the metabolic features. The results were encouraging of further use of HRM and MWAS approaches for characterizing molecular mechanisms underlying exposure to TRAP.
| S-EPMC7855798 | biostudies-literature
Project description:PurposeTo investigate the association between exposure to traffic-related air pollution and use of spectacles (as a surrogate measure for myopia) in schoolchildren.MethodsWe analyzed the impact of exposure to NO2 and PM2.5 light absorbance at home (predicted by land-use regression models) and exposure to NO2 and black carbon (BC) at school (measured by monitoring campaigns) on the use of spectacles in a cohort of 2727 schoolchildren (7-10 years old) in Barcelona (2012-2015). We conducted cross-sectional analyses based on lifelong exposure to air pollution and prevalent cases of spectacles at baseline data collection campaign as well as longitudinal analyses based on incident cases of spectacles use and exposure to air pollution during the three-year period between the baseline and last data collection campaigns. Logistic regression models were developed to quantify the association between spectacles use and each of air pollutants adjusted for relevant covariates.ResultsAn interquartile range increase in exposure to NO2 and PM2.5 absorbance at home was respectively associated with odds ratios (95% confidence intervals (CIs)) for spectacles use of 1.16 (1.03, 1.29) and 1.13 (0.99, 1.28) in cross-sectional analyses and 1.15 (1.00, 1.33) and 1.23 (1.03, 1.46) in longitudinal analyses. Similarly, odds ratio (95% CIs) of spectacles use associated with an interquartile range increase in exposures to NO2 and black carbon at school was respectively 1.32 (1.09, 1.59) and 1.13 (0.97, 1.32) in cross-sectional analyses and 1.12 (0.84, 1.50) and 1.27 (1.03, 1.56) in longitudinal analyses. These findings were robust to a range of sensitivity analyses that we conducted.ConclusionWe observed increased risk of spectacles use associated with exposure to traffic-related air pollution. These findings require further confirmation by future studies applying more refined outcome measures such as quantified visual acuity and separating different types of refractive errors.
| S-EPMC5378327 | biostudies-literature
Project description:BACKGROUND:Traffic-related air pollution has been linked to multiple adverse pregnancy outcomes. However, few studies have examined pregnancy loss, targeting losses identified by hospital records, a large limitation as it does not capture events not reported to the medical system. METHODS:We used a novel variation of the time-series design to determine the association, and identify the critical window of vulnerability, between week-to-week traffic-related air pollution and conceptions resulting in live births, using nitrogen dioxide (NO2) as a traffic emissions tracer. We used information from all live births recorded at Beth Israel Deaconess Medical Center in Boston, MA (2000-2013) and all live births in Tel Aviv District, Israel (2010-2013). RESULTS:In Boston (68,969 live births), the strongest association was during the 15th week of gestation; for every 10 ppb of NO2 increase during that week, we observed a lower rate of live births (rate ratio [RR] = 0.87; 95% confidence interval [CI], 0.78, 0.97), using live birth-identified conceptions to infer pregnancy losses. In the Tel Aviv District (95,053 live births), the strongest estimate was during the 16th gestational week gestation (RR = 0.82; 95% CI, 0.76, 0.90 per 10 ppb of NO2). CONCLUSIONS:Using weekly conceptions ending in live birth rather than identified pregnancy losses, we comprehensively analyzed the relationship between air pollution and all pregnancy loss throughout gestation. The observed results, with remarkable similarity in two independent locations, suggest that higher traffic-related air pollution levels are associated with pregnancy loss, with strongest estimates between the 10th and 20th gestational weeks.
| S-EPMC6269216 | biostudies-literature
Project description:Autism is a heterogeneous disorder with genetic and environmental factors likely contributing to its origins. Examination of hazardous pollutants has suggested the importance of air toxics in the etiology of autism, yet little research has examined its association with local levels of air pollution using residence-specific exposure assignments.To examine the relationship between traffic-related air pollution, air quality, and autism.This population-based case-control study includes data obtained from children with autism and control children with typical development who were enrolled in the Childhood Autism Risks from Genetics and the Environment study in California. The mother's address from the birth certificate and addresses reported from a residential history questionnaire were used to estimate exposure for each trimester of pregnancy and first year of life. Traffic-related air pollution was assigned to each location using a line-source air-quality dispersion model. Regional air pollutant measures were based on the Environmental Protection Agency's Air Quality System data. Logistic regression models compared estimated and measured pollutant levels for children with autism and for control children with typical development.Case-control study from California.A total of 279 children with autism and a total of 245 control children with typical development.Crude and multivariable adjusted odds ratios (AORs) for autism.Children with autism were more likely to live at residences that had the highest quartile of exposure to traffic-related air pollution, during gestation (AOR, 1.98 [95% CI, 1.20-3.31]) and during the first year of life (AOR, 3.10 [95% CI, 1.76-5.57]), compared with control children. Regional exposure measures of nitrogen dioxide and particulate matter less than 2.5 and 10 ?m in diameter (PM2.5 and PM10) were also associated with autism during gestation (exposure to nitrogen dioxide: AOR, 1.81 [95% CI, 1.37-3.09]; exposure to PM2.5: AOR, 2.08 [95% CI, 1.93-2.25]; exposure to PM10: AOR, 2.17 [95% CI, 1.49-3.16) and during the first year of life (exposure to nitrogen dioxide: AOR, 2.06 [95% CI, 1.37-3.09]; exposure to PM2.5: AOR, 2.12 [95% CI, 1.45-3.10]; exposure to PM10: AOR, 2.14 [95% CI, 1.46-3.12]). All regional pollutant estimates were scaled to twice the standard deviation of the distribution for all pregnancy estimates.Exposure to traffic-related air pollution, nitrogen dioxide, PM2.5, and PM10 during pregnancy and during the first year of life was associated with autism. Further epidemiological and toxicological examinations of likely biological pathways will help determine whether these associations are causal.
| S-EPMC4019010 | biostudies-literature
Project description:BackgroundAmbient air pollution exposure has been associated with dementia. Additionally, epidemiologic evidence supports associations between air pollution and diabetes as well as diabetes and dementia. Thus, an indirect pathway between air pollution and dementia may exist through metabolic dysfunction.ObjectiveTo investigate whether local traffic-related air pollution (TRAP) influences incident dementia and cognitive impairment, non-dementia (CIND) in a cohort of older Mexican Americans. We also assess how much of this estimated effect might be mediated through type 2 diabetes (T2DM).MethodsIn a 10-year, prospective study of Latinos (n = 1,564), we generated TRAP-NOx as a surrogate for pollution from local traffic sources at participants' residences during the year prior to enrollment. We used Cox proportional hazards modeling and mediation analysis to estimate the effects of TRAP-NOx on dementia and/or CIND and indirect pathways operating through T2DM.ResultsHigher TRAP-NOx was associated with incident dementia (HR = 1.55 for the highest versus lower tertiles, 95% CI = 1.04, 2.55). Higher TRAP-NOx was also associated with T2DM (OR = 1.62, 95% CI = 1.27, 2.05); furthermore, T2DM was associated with dementia (HR = 1.94, 95% CI = 1.42, 2.66). Mediation analysis indicated that 20% of the estimated effect of TRAP-NOx on dementia/CIND was mediated through T2DM.ConclusionOur results suggest that exposure to local traffic-related air pollution is associated with incident dementia. We also estimated that 20% of this effect is mediated through T2DM. Thus, ambient air pollution might affect brain health via direct damage as well as through indirect pathways related to diabetes and metabolic dysfunction.
| S-EPMC7591265 | biostudies-literature
Project description:BackgroundA recent meta-analysis suggested evidence for an effect of exposure to ambient air pollutants on risk of certain congenital heart defects. However, few studies have investigated the effects of traffic-related air pollutants with sufficient spatial accuracy.ObjectivesWe estimated associations between congenital anomalies and exposure to traffic-related air pollution in Barcelona, Spain.MethodCases with nonchromosomal anomalies (n = 2,247) and controls (n = 2,991) were selected from the Barcelona congenital anomaly register during 1994-2006. Land use regression models from the European Study of Cohorts for Air Pollution Effects (ESCAPE), were applied to residential addresses at birth to estimate spatial exposure to nitrogen oxides and dioxide (NOx, NO2), particulate matter with diameter ? 10 ?m (PM10), 10-2.5 ?m (PMcoarse), ? 2.5 ?m (PM2.5), and PM2.5 absorbance. Spatial estimates were adjusted for temporal trends using data from routine monitoring stations for weeks 3-8 of each pregnancy. Logistic regression models were used to calculate odds ratios (ORs) for 18 congenital anomaly groups associated with an interquartile-range (IQR) increase in exposure estimates.ResultsIn spatial and spatiotemporal exposure models, we estimated statistically significant associations between an IQR increase in NO2 (12.2 ?g/m3) and coarctation of the aorta (ORspatiotemporal = 1.15; 95% CI: 1.01, 1.31) and digestive system defects (ORspatiotemporal = 1.11; 95% CI: 1.00, 1.23), and between an IQR increase in PMcoarse (3.6 ?g/m3) and abdominal wall defects (ORspatiotemporal = 1.93; 95% CI: 1.37, 2.73). Other statistically significant increased and decreased ORs were estimated based on the spatial model only or the spatiotemporal model only, but not both.ConclusionsOur results overall do not indicate an association between traffic-related air pollution and most groups of congenital anomalies. Findings for coarctation of the aorta are consistent with those of the previous meta-analysis.CitationSchembari A, Nieuwenhuijsen MJ, Salvador J, de Nazelle A, Cirach M, Dadvand P, Beelen R, Hoek G, Basagaña X, Vrijheid M. 2014. Traffic-related air pollution and congenital anomalies in Barcelona. Environ Health Perspect 122:317-323;?http://dx.doi.org/10.1289/ehp.1306802.
| S-EPMC3948033 | biostudies-literature
Project description:While many studies have evaluated the association between acute childhood leukemia and environmental factors, knowledge is limited. Ambient air pollution has been classified as a Group 1 carcinogen, but studies have not established whether traffic-related air pollution is associated with leukemia. The goal of our study was to determine if children with acute leukemia had higher odds of exposure to traffic-related air pollution at birth compared to controls.We conducted a case-control study using the Oklahoma Central Cancer Registry to identify cases of acute leukemia in children diagnosed before 20 years of age between 1997 and 2012 (n=307). Controls were selected from birth certificates and matched to cases on week of birth (n=1013). Using a novel satellite-based land-use regression model of nitrogen dioxide (NO2) and estimating road density based on the 2010 US Census, we evaluated the association between traffic-related air pollution and childhood leukemia using conditional logistic regression.The odds of exposure to the fourth quartile of NO2 (11.19-19.89ppb) were similar in cases compared to controls after adjustment for maternal education (OR: 1.08, 95% CI: 0.75, 1.55). These estimates were stronger among children with acute myeloid leukemia (AML) than acute lymphoid leukemia, with a positive association observed among urban children with AML (4th quartile odds ratio: 5.25, 95% confidence interval: 1.09, 25.26). While we observed no significant association with road density, male cases had an elevated odds of exposure to roads at 500m from the birth residence compared to controls (OR: 1.39, 95% CI: 0.93, 2.10), which was slightly attenuated at 750m.Although we observed no association overall between NO2 or road density, this was the first study to observe an elevated odds of exposure to NO2 among children with AML compared to controls suggesting further exploration of traffic-related air pollution and AML is warranted.
| S-EPMC4874884 | biostudies-literature
Project description:BACKGROUND: Traffic-related air pollution is related with asthma, and this association may be modified by genetic factors. OBJECTIVES: We investigated the role of genetic polymorphisms potentially modifying the association between home outdoor levels of modeled nitrogen dioxide and asthma. METHODS: Adults from 13 cities of the second European Community Respiratory Health Survey (ECRHS II) were included (n = 2,920), for whom both DNA and outdoor NO(2) estimates were available. Home addresses were geocoded and linked to modeled outdoor NO(2) estimates, as a marker of local traffic-related pollution. We examined asthma prevalence and evaluated polymorphisms in genes involved in oxidative stress pathways [gluthatione S-transferases M1 (GSTM1), T1 (GSTT1), and P1 (GSTP1) and NAD(P)H:quinine oxidoreductase (NQO1)], inflammatory response [tumor necrosis factor alpha (TNFA)], immunologic response [Toll-like receptor 4 (TLR4)], and airway reactivity [adrenergic receptor beta2 (ADRB2)]. RESULTS: The association between modeled NO(2) and asthma prevalence was significant for carriers of the most common genotypes of NQO1 rs2917666 [odds ratio (OR) = 1.54; 95% confidence interval (CI), 1.10-2.24], TNFA rs2844484 (OR = 2.02; 95% CI, 1.30-3.27). For new-onset asthma, the effect of NO(2) was significant for the most common genotype of NQO1 rs2917666 (OR = 1.52; 95% CI, 1.09-2.16). A significant interaction was found between NQO1 rs2917666 and NO(2) for asthma prevalence (p = 0.02) and new-onset asthma (p = 0.04). CONCLUSIONS: Genetic polymorphisms in the NQO1 gene are related to asthma susceptibility among persons exposed to local traffic-related air pollution. This points to the importance of antioxidant pathways in the protection against the effects of air pollution on asthma.
| S-EPMC2799467 | biostudies-literature
Project description:BackgroundWe conducted a meta-analysis to evaluate the association between traffic-related air pollution and lung cancer in order to provide evidence for control of traffic-related air pollution.MethodsSeveral databases were searched for relevant studies up to December 2013. The quality of articles obtained was evaluated by the Strengthening the Reporting of Observational Studies in Epidemiology checklist. Statistical analysis, including pooling effective sizes and confidential intervals, was performed.ResultsA total of 1106 records were obtained through the database and 36 studies were included in our analysis. Among the studies included, 14 evaluated the association between ambient exposure to traffic-related air pollution and lung cancer and 22 studies involved occupational exposure to air pollution among professional drivers. Twenty-two studies were marked A level regarding quality, 13 were B level, and one was C level. Exposure to nitrogen dioxide (meta-odds ratio [OR]: 1.06, 95% confidence interval [CI]: 0.99-1.13), nitrogen oxide (meta-OR: 1.04, 95% CI: 1.01-1.07), sulfur dioxide (meta-OR: 1.03, 95% CI: 1.02-1.05), and fine particulate matter (meta-OR: 1.11, 95% CI: 1.00-1.22) were positively associated with a risk of lung cancer. Occupational exposure to air pollution among professional drivers significantly increased the incidence (meta-OR: 1.27, 95% CI: 1.19-1.36) and mortality of lung cancer (meta-OR: 1.14, 95% CI: 1.04-1.26).ConclusionExposure to traffic-related air pollution significantly increased the risk of lung cancer.
| S-EPMC4448375 | biostudies-literature
Project description:Land use regression (LUR) models rely on air pollutant measurements for their development, and are therefore limited to recent periods where such measurements are available. Here we propose an approach to overcome this gap and calculate LUR models several decades before measurements were available. We first developed a LUR model for NOx using annual averages of NOx at all available air quality monitoring sites in Israel between 1991 and 2011 with time as one of the independent variables. We then reconstructed historical spatial data (e.g., road network) from historical topographic maps to apply the model's prediction to each year from 1961 to 2011. The model's predictions were then validated against independent estimates about the national annual NOx emissions from on-road vehicles in a top-down approach. The model's cross validated R2 was 0.74, and the correlation between the model's annual averages and the national annual NOx emissions between 1965 and 2011 was 0.75. Information about the road network and population are persistent predictors in many LUR models. The use of available historical data about these predictors to resolve the spatial variability of air pollutants together with complementary national estimates on the change in pollution levels over time enable historical reconstruction of exposures.
| S-EPMC4763339 | biostudies-literature