Dataset Information

Exposure to Fine Particulate Air Pollution Causes Vascular Insulin Resistance by Inducing Pulmonary Oxidative Stress.

ABSTRACT:

Background

Epidemiological evidence suggests that exposure to ambient air fine particulate matter (PM2.5) increases the risk of developing type 2 diabetes and cardiovascular disease. However, the mechanisms underlying these effects of PM2.5 remain unclear.

Objectives

We tested the hypothesis that PM2.5 exposure decreases vascular insulin sensitivity by inducing pulmonary oxidative stress.

Methods

Mice fed control (10-13% kcal fat) and high-fat (60% kcal fat, HFD) diets, treated with 4-hydroxy-2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPOL) or mice overexpressing lung-specific extracellular superoxide dismutase (ecSOD) were exposed to HEPA-filtered air or to concentrated PM2.5 (CAP) for 9 or 30 days, and changes in systemic and organ-specific insulin sensitivity and inflammation were measured.

Results

In control diet-fed mice, exposure to CAP for 30 days decreased insulin-stimulated Akt phosphorylation in lung, heart, and aorta but not in skeletal muscle, adipose tissue, and liver and did not affect adiposity or systemic glucose tolerance. In HFD-fed mice, 30-day CAP exposure suppressed insulin-stimulated endothelial nitric oxide synthase (eNOS) phosphorylation in skeletal muscle and increased adipose tissue inflammation and systemic glucose intolerance. In control diet-fed mice, a 9-day CAP exposure was sufficient to suppress insulin-stimulated Akt and eNOS phosphorylation and to decrease I?B? (inhibitor of the transcription factor NF-?B levels in the aorta. Treatment with the antioxidant TEMPOL or lung-specific overexpression of ecSOD prevented CAP-induced vascular insulin resistance and inflammation.

Conclusions

Short-term exposure to PM2.5 induces vascular insulin resistance and inflammation triggered by a mechanism involving pulmonary oxidative stress. Suppression of vascular insulin signaling by PM2.5 may accelerate the progression to systemic insulin resistance, particularly in the context of diet-induced obesity. Citation: Haberzettl P, O'Toole TE, Bhatnagar A, Conklin DJ. 2016. Exposure to fine particulate air pollution causes vascular insulin resistance by inducing pulmonary oxidative stress. Environ Health Perspect 124:1830-1839;?http://dx.doi.org/10.1289/EHP212.

SUBMITTER: Haberzettl P

PROVIDER: S-EPMC5132639 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Publications

Exposure to Fine Particulate Air Pollution Causes Vascular Insulin Resistance by Inducing Pulmonary Oxidative Stress.

Haberzettl Petra P O'Toole Timothy E TE Bhatnagar Aruni A Conklin Daniel J DJ

Environmental health perspectives 20160429 12

<h4>Background</h4>Epidemiological evidence suggests that exposure to ambient air fine particulate matter (PM2.5) increases the risk of developing type 2 diabetes and cardiovascular disease. However, the mechanisms underlying these effects of PM2.5 remain unclear.<h4>Objectives</h4>We tested the hypothesis that PM2.5 exposure decreases vascular insulin sensitivity by inducing pulmonary oxidative stress.<h4>Methods</h4>Mice fed control (10-13% kcal fat) and high-fat (60% kcal fat, HFD) diets, tre ...[more]

PMID: 27128347

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Project description:Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.

Dataset Information

Exposure to Fine Particulate Air Pollution Causes Vascular Insulin Resistance by Inducing Pulmonary Oxidative Stress.

Background

Objectives

Methods

Results

Conclusions

Publications

Exposure to Fine Particulate Air Pollution Causes Vascular Insulin Resistance by Inducing Pulmonary Oxidative Stress.

Similar Datasets

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