Dataset Information

Metabolomics analysis of a mouse model for chronic exposure to ambient PM2.5.

ABSTRACT: Chronic ambient fine particulate matter (PM2.5) exposure correlates with various adverse health outcomes. Its impact on the circulating metabolome-a comprehensive functional readout of the interaction between an organism's genome and environment-has not however been fully understood. This study thus performed metabolomics analyses using a chronic PM2.5 exposure mouse model. C57Bl/6J mice (female) were subjected to inhalational concentrated ambient PM2.5 (CAP) or filtered air (FA) exposure for 10 months. Their sera were then analyzed by liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). These analyses identified 2570 metabolites in total, and 148 of them were significantly different between FA- and CAP-exposed mice. The orthogonal partial least-squares discriminant analysis (OPLS-DA) and heatmap analyses displayed evident clustering of FA- and CAP-exposed samples. Pathway analyses identified 6 perturbed metabolic pathways related to amino acid metabolism. In contrast, biological characterization revealed that 71 differential metabolites were related to lipid metabolism. Furthermore, our results showed that CAP exposure increased stress hormone metabolites, 18-oxocortisol and 5a-tetrahydrocortisol, and altered the levels of circadian rhythm biomarkers including melatonin, retinal and 5-methoxytryptophol.

SUBMITTER: Xu Y

PROVIDER: S-EPMC6536002 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Metabolomics analysis of a mouse model for chronic exposure to ambient PM2.5.

Xu Yanyi Y Wang Wanjun W Zhou Ji J Chen Minjie M Huang Xingke X Zhu Yaning Y Xie Xiaoyun X Li Weihua W Zhang Yuhao Y Kan Haidong H Ying Zhekang Z

Environmental pollution (Barking, Essex : 1987) 20190201

Chronic ambient fine particulate matter (PM2.5) exposure correlates with various adverse health outcomes. Its impact on the circulating metabolome-a comprehensive functional readout of the interaction between an organism's genome and environment-has not however been fully understood. This study thus performed metabolomics analyses using a chronic PM2.5 exposure mouse model. C57Bl/6J mice (female) were subjected to inhalational concentrated ambient PM2.5 (CAP) or ...[more]

PMID: 30823350

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Project description:Using a case-crossover study design and conditional logistic regression, we compared the relative odds of transmural (full-wall) myocardial infarction (MI) calculated using exposure surrogates that account for human activity patterns and the indoor transport of ambient PM(2.5) with those calculated using central-site PM(2.5) concentrations to estimate exposure to PM(2.5) of outdoor origin (exposure to ambient PM(2.5)). Because variability in human activity and indoor PM(2.5) transport contributes exposure error in epidemiologic analyses when central-site concentrations are used as exposure surrogates, we refer to surrogates that account for this variability as "refined" surrogates. As an alternative analysis, we evaluated whether the relative odds of transmural MI associated with increases in ambient PM(2.5) is modified by residential air exchange rate (AER), a variable that influences the fraction of ambient PM(2.5) that penetrates and persists indoors. Use of refined exposure surrogates did not result in larger health effect estimates (ORs=1.10-1.11 with each interquartile range (IQR) increase), narrower confidence intervals, or better model fits compared with the analysis that used central-site PM(2.5). We did observe evidence for heterogeneity in the relative odds of transmural MI with residential AER (effect-modification), with residents of homes with higher AERs having larger ORs than homes in lower AER tertiles. For the level of exposure-estimate refinement considered here, our findings add support to the use of central-site PM(2.5) concentrations for epidemiological studies that use similar case-crossover study designs. In such designs, each subject serves as his or her own matched control. Thus, exposure error related to factors that vary spatially or across subjects should only minimally impact effect estimates. These findings also illustrate that variability in factors that influence the fraction of ambient PM(2.5) in indoor air (e.g., AER) could possibly bias health effect estimates in study designs for which a spatiotemporal comparison of exposure effects across subjects is conducted.

Project description:Background & aimsExisting evidence suggests that long-term exposure to ambient fine particulate pollution (PM2.5) may increase metabolic dysfunction-associated fatty liver disease (MAFLD) risk. However, there is still limited evidence on the association of PM2.5 constituents with MAFLD. Therefore, this study explores the associations between the five main chemical constituents of PM2.5 and MAFLD to provide more explicit information on the liver exposome.MethodsA total of 76,727 participants derived from the China Multi-Ethnic Cohort, a large-scale epidemic survey in southwest China, were included in this study. Multiple linear regression models were used to estimate the pollutant-specific association with MAFLD. Weighted quantile sum regression was used to evaluate the joint effect of the pollutant-mixture on MAFLD and identify which constituents contribute most to it.ResultsThree-year exposure to PM2.5 constituents was associated with a higher MAFLD risk and more severe liver fibrosis. Odds ratios for MAFLD were 1.480, 1.426, 1.294, 1.561, 1.618, and 1.368 per standard deviation increase in PM2.5, black carbon, organic matter, ammonium, sulfate, and nitrate, respectively. Joint exposure to the five major chemical constituents was also positively associated with MAFLD (odds ratio 1.490, 95% CI 1.360-1.632). Nitrate contributed most to the joint effect of the pollutant-mixture. Further stratified analyses indicate that males, current smokers, and individuals with a high-fat diet might be more susceptible to ambient PM2.5 exposure than others.ConclusionsLong-term exposure to PM2.5 and its five major chemical constituents may increase the risk of MAFLD. Nitrate might contribute most to MAFLD, which may provide new clues for liver health. Males, current smokers, and participants with high-fat diets were more susceptible to these associations.Impact and implicationsThis large-scale epidemiologic study explored the associations between constituents of fine particulate pollution (PM2.5) and metabolic dysfunction-associated fatty liver disease (MAFLD), and further revealed which constituents play a more important role in increasing the risk of MAFLD. In contrast to previous studies that examined the effects of PM2.5 as a whole substance, this study carefully explored the health effects of the individual constituents of PM2.5. These findings could (1) help researchers to identify the specific particles responsible for hepatotoxicity, and (2) indicate possible directions for policymakers to efficiently control ambient air pollution, such as targeting the sources of nitrate pollution.

Project description:BackgroundStudies on the extent to which long-term exposure to ambient particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5) contributes to adult mortality in India are few, despite over 99% of Indians being exposed to levels that the World Health Organization (WHO) considers unsafe.ObjectiveWe conducted a retrospective cohort study within the Million Death Study (MDS) to provide the first-ever quantification of national mortality from exposure to PM2.5 in India from 1999 to 2014.MethodsWe calculated relative risks (RRs) by linking a total of ten 3-y intervals of satellite-based estimated PM2.5 exposure to deaths 3 to 5 y later in over 7,400 small villages or urban blocks covering a total population of 6.8 million. We applied using a model-based geostatistical model, adjusted for individual age, sex, and year of death; smoking prevalence, rural/urban residency, area-level female illiteracy, languages, and spatial clustering and unit-level variation.ResultsPM2.5 exposure levels increased from 1999 to 2014, particularly in central and eastern India. Among 212,573 deaths at ages 15-69 y, after spatial adjustment, we found a significant RR of 1.09 [95% credible interval (CI): 1.04, 1.14] for stroke deaths per 10-μg/m3 increase in PM2.5 exposure, but no significant excess for deaths from chronic respiratory disease and ischemic heart disease (IHD), all nonaccidental causes, and total mortality (after excluding stroke). Spatial adjustment attenuated the RRs for chronic respiratory disease and IHD but raised those for stroke. The RRs were consistent in various sensitivity analyses with spatial adjustment, including stratifying by levels of solid fuel exposure, by sex, and by age group, addition of climatic variables, and in supplementary case-control analyses using injury deaths as controls.DiscussionDirect epidemiological measurements, despite inherent limitations, yielded associations between mortality and long-term PM2.5 inconsistent with those reported in earlier models used by the WHO to derive estimates of PM2.5 mortality in India. The modest RRs in our study are consistent with near or null mortality effects. They suggest suitable caution in estimating deaths from PM2.5 exposure based on MDS results and even more caution in extrapolating model-based associations of risk derived mostly from high-income countries to India. https://doi.org/10.1289/EHP9538.

Dataset Information

Metabolomics analysis of a mouse model for chronic exposure to ambient PM2.5.

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Metabolomics analysis of a mouse model for chronic exposure to ambient PM<sub>2.5</sub>.

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