Exposure to air pollution is an established risk factor for asthma, reduced lung function as well as inflammatory and oxidative processes which are in turn linked with obesity and diabetes. Risk for these adverse outcomes begins early in childhood and well-documented racial/ethnic differences and social disparities render minority children especially vulnerable, yet these populations are underrepresented in the literature. Analysis for truly representative effect estimates should consider a wide array of genetic, social and environmental factors, biologic pathways from exposure to disease, with consideration for causal mediators and interactions. Mediation and interaction analysis can also aid in determining the transportability of estimated effects from one population to another. However, estimation and interpretability of target parameters in mediation analysis is complicated by issues such as mediator-outcome interactions, non-linearities, and exposure-induced confounding, which cannot be addressed using traditional regression approaches. My long-term career goals are to assess optimal interventions on environmental health risk factors that best reduce overall risk in populations of interest. I will utilize advanced epidemiologic methods maximinzing internal validity and efficiency of estimation of target. I will expand on existing methods for estimation of effects in the presence of time varying exposures and covariates as well as exposure-induced mediator outcome confounding (estimation of controlled direct effects and the randomized intervention analogues for the natural direct and indirect effects) which cannot be addressed with traditional regression approaches. The proposed methodology will be suitable for assessment of potential interventions on continuous exposures, which will be especially beneficial in the area of environmental epidemiology. In Aims 1 & 2 of this proposal I will use these proposed methods to assess direct, indirect and total effects of air pollution exposures on risk of asthma, overall lung function and metabolic syndrome, within a counterfactual framework. I am well suited to perform the proposed research based on 1) my past experience in environmental health and advanced methods and counterfactual approaches 2) the exceprional interdisciplinary mentoring team I have assembled and 3) the unique research opportunity offered by the datasets in the proposal, comprised largely of minority children. This proposed study will enable me to quantify mediated effects of air pollution exposures in especially vulnerable populations. I will be advised by a world-class team of mentors to expand my expertise in integrating advanced epidemiologic methods with causal inference applications (e.g., machine learning and efficient estimators of causal inference parameters) in environmental epidemiological studies; epigenetic and exposomic factors as potential modifiers or mediators of effect; and health disparities and social factors associated with environmental exposures. The proposed research and training will enable me to establish an independent career as a leader in intervention assessment and causal inference in environmental epidemiology

Asthma is a multifactorial disease with environmental and genetic contributions. We demonstrated that the harm caused by early-life exposures to air pollution and tobacco varies among different racial/ethnic groups. Our recent genome-wide association studies have identified both shared and ethnic-specific genetic risk factors for asthma and asthma-related traits. Our findings imply that both genes and early-life environmental exposures are important contributors to asthma susceptibility in minority children. We hypothesize that racial/ethnic differences in asthma susceptibility are due to gene-environment interactions resulting from early-life exposure to air pollution and tobacco. We will use existing genome-wide SNP genotypes and two distinct but complimentary approaches-admixture mapping and novel genome-wide GxE interaction scanning methods-to investigate the relationship between genetics, early-life air pollution and tobacco smoke exposures, and asthma risk. Specific Aim 1: Ancestry by environment interaction analysis of asthma in minority children. We will use genome-wide estimates of local chromosomal ancestry (African, European, and Native American) to perform an admixture mapping by environment (AxE) scan in 6,536 Latino and African American children from across the U.S. We will fine map AxE interaction peaks by performing targeted GxE analyses of genotyped and imputed SNPs from CAAPA and the Thousand Genomes Project. Results will be replicated using similar outcomes and exposures in the Mexico City Childhood Asthma Study (MCCAS). Specific Aim 2: Genome-wide by environment (GxE) interaction analysis of asthma in ethnically diverse children with and without asthma. We will use a novel two-step analytical method to perform a genome-wide scan at 38.9 million SNPs for GxE interactions with air pollution and tobacco smoke exposure. Scans will be performed in our combined resource of 8,138 children, as well as within Latino, European, and African American subgroups. Results will be replicated using similar outcomes and exposures in MCCAS.

Numerous epidemiological studies have shown the adverse effects of traffic-related air pollution (TRAP) exposure on asthma and related inflammatory phenotypes in children and adults. Although genome-wide association studies (GWAS) have identified variants associated with asthma, there has been limited success in identifying genes that modulate susceptibility to TRAP exposure. We propose an innovative genetics approach in mice and humans to identify novel variants that interact with TRAP to affect immunoregulatory endophenotypes and risk of childhood asthma. Specific Aim 1 will determine the immunoregulatory responses of ~150 mouse strains from the Hybrid Mouse Diversity Panel (HMDP) to diesel exhaust particles (DEP), a model traffic-related pollutant. Mice will undergo a 2-week intranasal exposure protocol after which cellular immunoregulatory phenotypes will be determined in lung and spleen. The relationship between these traits to lung function will also be assessed. We will use these data to carry out a gene-environment (GxE) GWAS to identify loci that influence immunoregulation through interactions with DEP exposure. In preliminary studies with ~40 HMDP strains, we observed ~10-fold variability in immunoregulatory endophenotypes and identified 2 loci on chromosomes 4 and 16 that exhibited highly suggestive association with pulmonary Treg frequency. Notably, previous GWAS have identified the corresponding loci on human chromosomes 1 and 3, respectively, as being associated with childhood asthma-related phenotypes. These preliminary findings are consistent with our hypothesis that genetic background modulates the response to TRAP and support the use of our proposed integrative genetics approach to identify novel asthma susceptibility loci. In Specific Aim 2, we will use synteny mapping to identify loci that affect asthma-related phenotypes in children through GxE interactions. This will be accomplished by leveraging already existing genetic, exposure, and clinical data in 4 large cohorts. First, we will use GWAS results from the Children's Health Study (CHS) to determine whether regions of the human genome that are syntenic to those identified the HMDP interact with TRAP exposure to affect asthma-related traits. Loci exhibiting GxE interactions will be replicated in the Genetics o Asthma in Latino Americans (GALA) I & II and Study of African Americans, Asthma, Genes, & Environments (SAGE) II cohorts. For loci exhibiting consistent GxE interactions, we will leverage already existing biological samples in these cohorts to investigate methylation at the FoxP3 promoter and FoxP3 mRNA levels, as surrogate measures of Treg function/frequency. Importantly, the clinical phenotypes and estimates of TRAP exposure are highly comparable in these 4 cohorts, thus increasing the likelihood of identifying and validating true GxE loci. The integrative genomics approaches proposed herein could lead to a better understanding of the interrelationships between genes, environmental exposures, immunoregulatory endophenotypes, and asthma, which could have important clinical, epidemiological, and translational implications for developing novel treatment strategies.

Asthma is caused by the interaction of genetic and environmental factors. In the U.S., asthma prevalence, morbidity and mortality are highest in Puerto Ricans, intermediate in Dominicans and Cubans, and lowest in Mexicans and Central Americans. There are many potential explanations for this observation, including place of birth, acculturation, early life exposures and genetic predisposition. Latinos are admixed and share varying proportions of African, Native American and European ancestry. The mixed ancestry of Latinos provides unique opportunities in epidemiological and genetic studies of complex traits and may be useful in untangling complex gene-environment (G x E) interactions in disease susceptibility. We hypothesize that ancestry will modify the association between environmental risk factors and asthma prevalence and severity. We propose to investigate whether individual ancestry, genetic factors, and environmental risk factors interact to influence asthma and asthma-related traits among several Latino ethnic groups. We will collect a well-characterized sample of Latino asthmatics (n = 2000) and clinic-based controls (n = 2000), age 8-21 years, from the Bronx, NY, Chicago, IL, San Francisco, CA, Houston, TX and Puerto Rico. This application has three specific aims. 1) We will test the hypothesis that genetic ancestry interacts with environmental/demographic risk factors to modify asthma risk and asthma-related phenotypes in Latinos of high risk Puerto Rican, intermediate risk Dominican, and low risk Central American and Mexican ethnicities. 2) We will genotype fifty candidate genes that may be involved in G x E interactions relevant to asthma. We will test whether there are ethnic-specific G x E interactions that differentially affect asthma risk, severity and pharmacologic response among Latino ethnic groups. 3) We will determine whether migration and acculturation are associated with asthma and severe asthma. Place of birth and length of stay in the U.S. are indicators of migration and acculturation. We will test the hypotheses that these indicators are associated with asthma and asthma severity. We will also test the hypothesis that place of birth and length of stay in the U.S. interact with ancestry, environmental, clinical and demographic risk factors to modify their associations with asthma and asthma severity among Latinos.