While ambient air pollution has been implicated as a risk factor for asthma exacerbations, interpretation of findings from epidemiologic studies has been hampered by uncertainties in exposures and in the precise nature of the airway responses. The overall goal of the proposed study is to advance our understanding of the influence of diesel exhaust exposures in acute asthma exacerbations by linking innovative exposure and outcome measures. We propose to optimize and test a new miniature """"""""smart"""""""" personal sampling system for size- and composition-classified particulate matter, and to implement the system in a study of personal xposures and acute airway responses among children enrolled in CCCEH. The smart sampler will monitor personal exposures for 30 asthmatic and 30 non-asthmatic children ages 9/10 to DEP/BC (Diesel Exhaust Particulates-Black Carbon), multiple elements, and PM2.5 and will distinguish exposures occurring in three key environments (at home, at school and other/in-transit). For each child, we will collect a sequence of six 48-hour personal samples, timed to coincide with 2-week average home indoor and outdoor measurements proposed in project 1. We will quantify and compare personal exposures to DEP/BC at home, school, and other/transit, and will analyze the relationship between personal DEP/BC exposures and concurrently- measured home indoor/outdoor DEP/BC concentrations. Based on particle elemental composition, we also will analyze the extent to which personal PM2.5 exposures are driven by traffic-related particle emissions. At the completion of each 48-hour monitoring period, we will measure exhaled-breath biomarkers (cys- leukotrienes, NO, 8-isoprostane) and adenosine, lung function by spirometry, and respiratory symptoms (i.e., wheeze) for each of the 60 children. Statistical analyses and hypothesis testing will 1) determine the relative importance of home, school, and other/in-transit exposure environments for personal exposures, 2) test for acute effects of personal DEP/BC exposures on exhaled-breath 8-isoprostane, NO, pH, cys-leukotrienes and adenosine, and 3) determine whether average levels of these biomarkers vary across children as a function of asthma status and/or average DEP/BC exposure.
The aims and methods proposed here will both advance our understanding of acute airway effects of DEP/BC and complement the aims of the other projects.

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National Institute of Environmental Health Sciences (NIEHS)
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Columbia University (N.Y.)
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Bansal, Ravi; Peterson, Bradley S (2018) Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions. Magn Reson Imaging 49:101-115
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