Introduction: Exposure to ambient nitrogen dioxide (NO 2 ) is associated with adverse respiratory and cardiovascular outcomes. Supplementation of omega-3 polyunsaturated fatty acids (PUFA) has shown health benefits against exposure to air pollution. Hypothesis: Dietary omega-3 PUFA intake offers cardiovascular and respiratory benefits against short-term exposure to ambient NO 2 in healthy adults. Methods: Sixty-two healthy participants were enrolled into low or high omega-3 groups based on their habitual dietary omega-3 PUFA intake. Each participant was repeatedly assessed for blood lipids, markers of coagulation and fibrinolysis, vascular function, heart rate variability (HRV), and lung function up to five times separated by at least 7 days between October 2016 and September 2019. Daily ambient NO 2 concentrations were obtained from nearby air quality monitoring stations. The associations between NO 2 concentrations and the measured biomarkers were evaluated using the linear mixed-effects models stratified by the omega-3 intake levels. Results: In the high omega-3 group, an IQR increase in NO 2 concentrations was associated with reductions in total cholesterol at lag2 [-2.6% (-4.4, -0.9)], LDL at lag2 [-3.1% (-5.5, -0.7)], and HDL at lag1 [-2.4% (-4.4, -0.3)] and lag2 [-2.0% (-3.8, -0.1)]; increases in flow-mediated dilatation of brachial artery at lag1[5.7% (0.1, 11.2)] and lag2 [5.7% (0.8, 10.6)]; decreases in plasma levels of endothelin-1at lag3 [-25.6% (-50.0, -1.2)] and lag4 [-22.9% (-45.9, -0.01)]; decreased high frequency (HFn) of HRV [-7.2% (-13.6, -0.8)] and increased LF/HF ratio [13.4% (0.2, 28.3)] at lag3; as well as increased lung function. In the low omega-3 group, blood lipids, vascular function biomarkers and lung function were not significantly associated with NO 2 exposure. However, NO 2 exposure was associated with elevations in coagulation markers (von Willebrand Factor and D-dimer) and a decrease in very-low frequency of HRV at lag0 in the low omega-3 group. Conclusions: The results imply that high dietary omega-3 PUFA intake may offer benefits to cardiovascular and respiratory health in response to exposure to low-level ambient NO 2 in healthy adults. THIS ABSTRACT OF A PROPOSED PRESENTATION DOES NOT NECESSARILY REFLECT EPA POLICY.

Background/Aim: Untargeted metabolomics enable the exploration of pathways that are affected by environmental respiratory exposures. However, traditional analyses of such data analyze each feature separately, ignoring interactions between features and reducing power. Independent component analysis (ICA) is a machine learning method that uncovers hidden patterns in data and has found widespread application in the analysis of medical imaging, video surveillance, and financial data. We propose that applying ICA to untargeted metabolomics data can alleviate the limitations of traditional feature-by-feature analyses. Methods: We applied ICA to approximately 25,000 untargeted metabolomic features measured in brachial lavage fluid (BALF) collected from 15 healthy participants who experienced separate exposures to Cl2 gas and clean air. We estimated a total of 7 components using ICA. We compared our results to traditional feature-by-feature analyses. Results: In the traditional analyses, no features remained significant after a false discovery rate (FDR) correction. Of the 7 ICA components, 3 showed statistically significant differences, assessed using paired t-tests, in expression between the two conditions (Cl vs. clean air). These three components (t-statistics: 2.4, 7.2, and 12.2) remain significant after FDR correction. Annotation of detected metabolites in these components suggests variations in oxidative stress-related metabolites, including methionine (an important anti-oxidant) and oxidized fatty acids in the Cl¬2 exposure compared with the clean air exposure. Other features in these components showed a negative mass defect, which is consistent with the presence of halogenated compounds that may form through chlorine nucleophilic substitution. These ICA components were not associated with the age or sex of the participants. Conclusions: Our results suggest Cl2 exposure influences the lung metabolome and demonstrate the value of using machine learning methods to uncover biological response to respiratory exposures. Disclaimer: The views in this abstract belong to the authors and are not necessarily those of the U.S. Environmental Protection Agency.

Air pollution epidemiological studies of ambient fine particulate matter (PM2.5) and ozone (O3) often use outdoor concentrations from central-site monitors as exposure surrogates, which can add bias or uncertainty in health effect estimates. The goal of this study was to improve exposure assessments of ambient PM2.5 and O3 for a 10-year epidemiological study with 2,271 participants with coronary artery disease in central North Carolina called the Catheterization Genetics (CATHGEN) study. We developed an exposure modeling approach to estimate three tiers of individual-level exposure metrics for ambient PM2.5 and O3. We used a hybrid outdoor air quality model (based on satellite- and ground-based air pollution measurements, chemical transport and land-use models) linked to a residential air exchange rate model (based on building characteristics, indoor-outdoor temperatures, wind speed) and mass-balance infiltration model to determine residential air exchange rates (AER, Tier 1), infiltration factors (Finf, Tier 2), and indoor concentrations (Cin, Tier 3). For each of the 2,271 participant homes, we applied the exposure model to determine daily house-specific PM2.5 and O3 exposure metrics (Tiers 1-3) for the 365 days before each participant's cardiac catheterization date. The daily modeled exposure metrics for all 828,915 participant days showed considerable temporal and house-to-house variability of AER, Finf and Cout (Tiers 1-3). Our study demonstrates the ability to apply an outdoor air quality model linked to a residential infiltration model to determine individual-level ambient PM2.5 and O3 exposure metrics for a large, long-term epidemiological study, in support of improving risk estimation.

Background: Air pollution, particularly particulate matter less than 2.5 micrometers in diameter (PM2.5), is a significant risk factor for cardiovascular morbidity. Current studies have been primarily based on the general, typically healthy, population and there is limited information for individuals with pre-existing disease. We used the EPA CARES resource to examine the association between short-term PM2.5 exposure and heart rate (HR) in heart failure (HF) patients. Additionally, we examine potential effect modification by beta-blockers, a common medication class that modifies HR. Methods: We analyzed 3,048,856 heart rate (HR) measurements on 26,634 HF patients between January 2014 and December 2016, compiled using electronic health records from University of North Carolina affiliated hospitals. Satellite data, land use, and ground based monitoring were used to estimate daily average concentrations of PM2.5 at 1km resolution, and immediate (lag 0), delayed (lag 1 to 4), and 5 day moving average (5dMA) exposures at each primary address were computed. We used generalized additive mixed models to associate PM2.5 with HR while adjusting for age, sex, race, season, time-trend, daily temperature, and relative humidity, with a random intercept for individual. Results: PM2.5 exposure was associated with HR for lag 2 and 3 (beta = 0.006, CI = 0.002, 0.009; beta = 0.005, CI = 0.002, 0.010). Associations were stronger in individuals not taking beta-blocker medications at any time prior to HR measurement, with associations seen at all lags and strongest for 5dMA (beta = 0.086, CI = 0.073, 0.099). Conclusions: Elevated PM2.5 is associated with increased HR in HF patients. Associations are at best weak for the entire population, but strong and consistent across lags for measurements prior to beginning beta-blockers, suggesting that beta-blocker medication regimes may substantially attenuate effects of PM2.5 on HR. This abstract does not necessarily reflect the policies of the U.S. EPA.

TPS 681: Short-term health effects of air pollutants 1, Exhibition Hall, Ground floor, August 26, 2019, 3:00 PM - 4:30 PM Background: Heart failure (HF) is a severe form of cardiovascular disease which is increasing in prevalence. Mortality risks from elevlated ambient fine particulate matter (PM2.5) exposure are well characaterized for HF patients, but few studies have examined morbidity risks in the HF community. In particular, measures such as the days spent in hospital, which may correlate with quality of life and healthcare costs, have yet to be explored. Methods: Using the EPA CARES resource, we examined associations between annual average PM2.5 exposure (assessed at the primary residence at the time of initial HF diagnosis) and the total visits, number of emergency plus inpatient visits, and total days spent in hospital for 24,798 North Carolina resident HF patients (559,664 total visits, 7.7% inpatient or emergency) who resided <30 km from a PM2.5 monitor. The observation period was 7/1/2004 to 12/31/2016. Models were adjusted for age at diagnosis, sex, race, and socioeconomic status indicators extracted from the 2000 census. We used a quasipoisson model to model the total visits and inpatient plus emergency visits and a linear model for the log-transformed total days spent in hospital. Results: The average PM2.5 exposure was 10.2 µg/m3 (interquartile range 8.4-11.4 µg/m3). A 1 µg/m3 increase in PM2.5 exposure was associated with a 19% increase (95% confidence interval [CI] = 18-19%) in the total number of visits, an 11% increase (CI = 11-12%) in the number of inpatient and emergency visits, and a 4.4% increase (CI = 3.7-5.2%) in the total days spent in hospital. Conclusions: Elevated PM2.5 exposure is a significant morbidity risk factor for HF patients. Increases in the number of hospital visits and the days spent in hospital are likely related to quality of life as well as healthcare costs for HF patients. This abstract does not necessarily represent EPA policy.

TPS 682: Long-term health effects of air pollutants 2, Exhibition Hall, Ground floor, August 27, 2019, 3:00 PM - 4:30 PM Background: Traffic is a primary source of urban air pollution exposure, and is associated with adverse health outcomes. There is limited information on the impact of exposure to traffic on mortality for individuals with pre-existing disease. We used the EPA CARES resource to examine the relationship between residential proximity to traffic, the distance between the primary residence and the nearest major roadway (DTR), and mortality in heart failure (HF) patients. Methods: The study cohort comprised 30,599 North Carolina (NC) residents diagnosed with HF between 2004 and 2016, who did not reside in a group home or institutional residence. Cox proportional hazards models were used to determine the association between all-cause mortality and DTR while adjusting for age, sex, race, and socioeconomic status indicators measured at the census block group: median household income, median home value, urbanicity, percent households below poverty line, and percent households receiving public assistance. Results are given in as the hazard ratio (HR) per 1 km decrease in DTR and the associated 95% confidence interval (CI). Results: In the central, more urban counties of NC (Durham, Wake, Orange, and Chatham), DTR was associated with mortality in HF patients (HR = 1.17, CI = 1.01, 1.35). The association was weaker in the entire state (HR = 1.05, CI = 0.95, 1.17), and not observed when restricting to the 96 counties outside of central NC (HR = 0.95, CI = 0.82, 1.11). The association was stronger in men than women, and in Caucasians than African-Americans. Conclusions: Residential proximity to traffic may be a significant mortality risk factor for HF patients in urban areas. With increasing urban density and HF prevalence in developed nations, it is important to understand, monitor, and communicate environmental traffic-related environmental health risks. This abstract does not necessarily reflect the policies of the U.S. EPA.

TPS 701: Spatial determinants of population health, Exhibition Hall, Ground floor, August 27, 2019, 3:00 PM - 4:30 PM Background: Heart failure (HF) is a major public health concern in the USA with high mortality. Although neighborhood-level socioeconomic status (NSES) is associated with adverse health outcomes in the general community, it is unclear if NSES is associated with mortality in HF patients. Methods: We used electronic health records from 30,060 heart failure patients seen at a University of North Carolina-affiliated hospital between July 1, 2004 and December 31, 2016. We created indicators for NSES using Ward's hierarchical clustering of ten Census-based measures assessed at the block group level, yielding seven neighborhood clusters across North Carolina (NC). We conducted Cox proportional hazards analysis, adjusting for age, sex, and race, to evaluate differential hazards of mortality across the seven clusters. Results: We assigned participants to one of seven clusters based on NSES and urbanicity: urban low-NSES (97% urban, n=3162), urban middle-low-NSES (91% urban, n=5078), urban middle-high-NSES (98% urban, n=2127), urban high-NSES (96% urban, n=5510), rural low-NSES (8% urban, n=2705), rural middle-NSES (13% urban, n=8258), and suburban high-NSES (85% urban, n=3220, referent). Compared to the suburban high-NSES cluster, hazards of mortality for HF patients were elevated in the urban middle-high-NSES (HR 1.14, 95% Confidence Interval [CI] 1.03-1.22), rural middle-NSES (HR 1.13, 95% CI 1.05-1.19), and rural low-NSES (HR 1.11, 95% CI 1.01-1.20) clusters. Hazard ratios were less elevated among urban middle-low-NSES (HR 1.08, 95% CI 0.99-1.15), urban low-NSES (HR 1.06, 95% CI 0.96-1.14), and urban high-NSES (HR 1.06, 95% CI 0.97-1.13) clusters. Conclusions: Among HF patients, hazards of mortality were generally more elevated for residents of traditionally understudied rural neighborhood clusters, compared to more urban clusters. Residents of the urban middle-high-NSES cluster had a more elevated hazard than other urban clusters, suggesting that additional factors in this cluster may contribute to mortality. This abstract does not necessarily reflect EPA policies.

TPS 651: Air pollution exposure modeling 1, Exhibition Hall, Ground floor, August 27, 2019, 3:00 PM - 4:30 PM To better understand exposure to air pollutants and their potential for adverse health effects, it is important to account for time spent in different indoor and outdoor locations, and the air pollutant concentrations in those locations. Currently available exposure models require substantial technical exposure modeling expertise, and near real-time exposure predictions are not possible since large and diverse input data must be collected, organized, and processed. To address these limitations, we developed TracMyAir, an iPhone application (App) that automatically estimates exposures (24 h average) to ambient PM2.5 and ozone based on several sources of input data available from iPhones, including: near real-time ambient air pollution measurements from local monitors, local weather, user's locations, and building characteristics of the user's home. TracMyAir uses an exposure model that accounts for time spent in different indoor and outdoor locations, and building-specific attenuation of ambient PM2.5 and ozone when indoors. In central North Carolina, we evaluated the App's ability to automatically obtain real-time measurements (1 h averages across previous 24 h) for (1) ambient PM2.5 and ozone concentrations from the nearest official air quality monitoring station, and (2) temperature and wind speed from the nearest weather station. We evaluated the App at various locations across the region, which has four air monitoring stations and two weather stations. The App successfully obtained real-time data from all the stations, and always selected the station closest to the iPhone location. We also performed a sensitivity analysis, which showed that the modeled exposures varied substantially with changes in daily home operating conditions (window opening, air cleaner usage), indoor-outdoor temperature differences, and time spent outdoors. The App is being applied for two epidemiological studies in central North Carolina. TracMyAir could also be used to develop public health strategies for individuals at elevated risk.

OPS 28: Green space and biomarkers, Room 417, Floor 4, August 27, 2019, 4:30 PM - 5:30 PM Background/Aim. Neighborhood characteristics have been shown to impact cardiometabolic risk, yet few studies have examined the relationship of residential area to the cardiometabolic epigenome. Using DNA methylation data, geocoded residence, and medical history from a cohort of patients referred for cardiac catheterization, we examined the cross-sectional relationship of neighborhood with residents' epigenome. Methods. Using 11 U.S. Census socioeconomic variables, we used hierarchical clustering to group 444 block groups in Wake, Durham & Orange counties (North Carolina, USA) into 5 clusters. We randomly selected ~112 participants from each cluster for DNA methylation analysis of blood (N=563). Candidate loci were previously associated with high sensitivity C-reactive protein (hsCRP; 218 loci), a cardiometabolic biomarker. For each locus, we carried out an analysis of variance comparison of full and reduced mixed models, including and excluding a categorical term for cluster, respectively. Models were adjusted for age, sex, race, smoking, blood cell counts, and technical covariates. In sensitivity analyses, we also assessed independence from cardiometabolic outcomes. The relationship of each census variable with loci, found to be associated with neighborhood cluster, were assessed via linear mixed models. P-values were multiple test corrected using false discovery rate (FDR). Results. Of 218 candidate loci, 10 and 39 were associated at FDR<0.10 and p<0.05, respectively, with neighborhood cluster in a concerted pattern. Further, univariate analysis of census variables with these 39 candidate loci revealed that increased urbanicity, decreased owner-occupied housing, and increased poverty at the block group level were associated with a DNA methylation profile that is consistent with increased expression of hsCRP. Conclusion. Our results suggest that neighborhood socioeconomic profile may shape a remarkably lock-step profile of inflammatory DNA methylation. This abstract does not necessarily represent EPA policy.

RATIONALE: Polymorphisms in the oxidative stress gene GSTM1 have demonstrated that GSTM1null individuals have greater ozone-induced decrements in lung function and benefit more from antioxidant supplementation from pollutant-induced health effects. Ozone exposure is known to induce decrements in pulmonary function and cause elevated % PMNs in the airways. METHODS: Thirty four (27 healthy, 7 allergic asthmatics) subjects were exposed to 0.4 ppm ozone for 2 hrs with moderate intermittent exercise in a controlled chamber. Sputum endpoints, pulmonary function and flow cytometric markers of sputum monocyte function were evaluated at pre exposure baseline and 6 hr post exposure. All subjects were genotyped for GSTM1 and were stratified according to GSTM1 sufficient (N = 17) or GSTM1null (N = 17). RESULTS: Preliminary data: The FEV1 response following ozone was identical for both GSTM1 and GSTM1null groups (17% mean fall vs. baseline). However, compared to the GSTM sufficient group, the GSTM1null group had a significantly greater increase from pre exposure baseline in % PMNs (33 ± 4% null vs. 20 ± 3%) and a lesser decrease in % monocytes (20 ± 3%null vs 32 ± 4%) in the airways. CONCLUSIONS: GSTM1null individuals do not appear to have greater pulmonary function decline following ozone exposure. However, this gene polymorphism does modify the effect of ozone exposure on the relative proportion of airway neutrophils and monocytes. Together, these observations suggest that the reported increased risk of GSTM1 null persons to adverse effects of ozone likely derive from differences in pollutant induced inflammatory cell populations in the airway.

Although molds have demonstrated the ability to induce allergic asthma-like responses in mouse models, their role in human disease is unclear. This study was undertaken to provide insight into the prevalence of human IgE-reactivity and identify the target mold protein(s). The study objectives were 1) to identify mold extracts that are bound by IgE in serum from human asthmatics, 2) to describe the protein profile of this reactivity and 3) to compare humans and mouse IgE-reactive protein profiles. Human sera were collected from thirty-three individuals (11 adults and 22 children) with persistent asthma, living within a 30-mile radius of Chapel Hill, North Carolina under an UNC-CH IRB approved protocol. The sera were screened for IgE-reactivity against selected indoor mold extracts by dot blot analysis. The resulting chemiluminescent signal was quantified by densitometry. To identify the IgE-binding proteins in the extracts, Western blot analysis was performed using strongly reactive sera. These protein profiles were compared to those identified with extract-specific mouse serum IgE. The dot blot screening demonstrated variability among individuals and within an individual's level of IgE-responsiveness to mold extracts. Subsequently, Western blots revealed IgE-reactive protein profiles that were similar to those detected using mouse serum. The quantity/quality of mold-reactive IgE varies among individuals. Additionally, this variability extends to an individual's reactivity against different mold extracts. Current data suggest that both mouse and human immune systems are generally reactive to the same mold proteins. (This abstract does not reflect EPA policy.)

ISEE-272 Introduction: No study has looked at fine versus coarse particle health effects on asthmatic children (PM2.5 vs. PM2.5-10). Few non-invasive biomarkers of asthma morbidity have been evaluated for their implementation into field epidemiological studies. We performed a panel study to address these scientific gaps. Aim: The purpose of this study was two-fold: 1.) to test biomarkers of asthma morbidity for their potential application in larger field epidemiological studies and 2.) to test the hypothesis that there were differences in persistent asthmatic children's responses to fine and coarse particulate air pollution. Methods: We performed a panel study of the health effects of PM<2.5 and PM2.5-10 on asthmatic children using an observation period, including peak particle season and excluding peak ozone season. From September 2003 through May 2004, we enrolled 28 persistent asthmatic children from the Chapel Hill area into a 6-week panel study. Each child was 8-18 years old and had one comprehensive clinical evaluation (2-3 hr), one panel enrollment (45 min.), and one panel completion (10 min.) visit at the US EPA's Human Studies Facility in Chapel Hill, North Carolina. The clinical evaluation included a medical history, vital signs, physical exam, spirometry, buccal swab, allergy skin test, nasal lavage, collection of exhaled breath condensates, exhaled nitric oxide measurement, urine collection, and blood draw. Children were provided with an electronic peak flow meter for twice daily peak expiratory flow assessment, and a personal digital assistant/mobile telephone for internet-based daily health diary collection, upon enrollment. Daily PM<2.5 and PM2.5-10 measurements were made concurrently using a centrally located dichotomous air sampler on the roof of the Human Studies Facility, from August 2003 through June 2004. Results: Most study children were moderate persistent asthmatics (18, 64%), with four severe persistent, five mild persistent, and only two mild intermittent. All 28 children completed the entire 6-week panel. Children were on study for an average of 42 days (+/− 1.8 days) with an 85% diary and 89% peak flow meter completion average. Eighteen of the 28 children consented to the blood draw (64%). The mean daily PM<2.5 and PM2.5-10 measurements were 11.3 (Interquartile range: 8.1) and 5.6 (Interquartile range: 4.6), respectively. A sub-group of 18 children had supplemental outdoor monitoring performed at their residence for up to five consecutive days. Particulate air pollution levels were consistently below the standards set by the USEPA. Conclusion: We successfully evaluated, enrolled, and retained persistent asthmatic children within a 6-week daily diary study with good compliance. This study demonstrates that persistent asthmatic children can provide reasonably complete daily diary and peak expiratory flow data for up to six weeks using the technology employed in our study. These findings do not necessarily represent United States Environmental Protection Agency policy.

ISEE-311 Introduction: Recent reports indicate that the elderly and those with cardiovascular disease are susceptible to fine and coarse particulate matter (PM 2.5, PM 2.5–10) exposures. Asthmatics are thought to be primarily affected via airway inflammation. We investigated whether markers of blood coagulation change in response to ambient PM. Methods: Twelve atopic adults with mild to moderate persistent asthma living in a 30 mile radius of the clinic were followed over a six week period, each with nine clinic visits. Daily ambient coarse (PM 2.5–10) and fine (PM 2.5) PM were measured separately for each 24 hour period using a Rupprecht & Patashnick (R&P) Partisol Plus 2025D dichotomous air sampler. Blood samples were analyzed for bloodcoagulation factors including plasminogen, fibrinogen, Von Willebrand factor, D-dimer, plasminogen activator inhibitor type 1 (PAI-1), Factor VII, and Factor IX. Linear mixed models controlling for within subject correlation and confounding were used to assess potential associations. Results: We found changes in ambient PM 2.5–10 were associated with plasminogen and fibrinogen levels in peripheral blood samples (p<0.018), after adjusting for the effects of age, gender, height, weight, and temperature. For a 10 SD unit increase in PM coarse concentration, a decrease of 0.13% in plasminogen and 0.53% in fibrinogen concentration were found. No such relationship was seen for PM 2.5. Other blood coagulation factors showed no such association. The mean concentration for PM 10 2.5–10 was 5.6 μg/m3 (0–15 μg/m3) and PM 2.5 12.4 μg/m3 (6–37 μg/m3). Conclusion: These data suggest that exposure to ambient levels of PM 2.5–10 affect certain molecules (plasminogen, fibrinogen) in the fibrinolytic pathway of blood clot formation in adult asthmatics. These findings do not necessarily represent EPA policy. Funding: EPA Cooperative Agreement 829522, NHLBI R01HL62624

We recently reported that baseline expression of circulating CD11b is associated with the magnitude of the neutrophil response following inhaled endotoxin. In this study, we examined whether circulating CD11b plays a similar role in the inflammatory response following inhaled ozone exposure. Twenty-two volunteers underwent controlled exposure to ozone (0.4 ppm, 2 h) and to clean air on two separate occasions. Induced sputum and peripheral blood were collected before and after exposure. Induced sputum collected from subjects exposed to ozone revealed marked neutrophilia and increased expression of mCD14 on airway macrophages and monocytes. Baseline CD11b expression on blood phagocytes correlated positively with ozone-induced neutrophil influx into the airways. In conclusion, in human volunteers, circulating CD11b predicts the magnitude of the airway neutrophil response following inhaled ozone exposure. Consequently, CD11b may be a useful biomarker for predicting susceptibility to airway neutrophilic inflammation caused by pollutants.