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. EXPECTED OUTCOMES: We will identify genes and genetic loci whereby gene-environment interactions play an important role in asthma etiology, and thus retrieve part of the missing heritability of asthma. We will identify significant shared and ethnic specific gene-environment interactions, which will further our understanding of racial/ethnic differences in asthma susceptibility.

Public Health Relevance

Genetic and early-life environmental exposures are important contributors of asthma risk. Some racial/ethnic groups are more susceptible than others to developing asthma following early-life exposure to air pollution and tobacco smoke. Our goal is to untangle how the interplay between genetics and early-life exposures to air pollution and tobacco explain racial/ethnic differences in asthma risk among Latino and African American children. Our results will fill knowledge gaps about asthma risk and help reduce asthma health disparities.

National Institute of Health (NIH)
National Institute of Environmental Health Sciences (NIEHS)
Exploratory/Developmental Grants (R21)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-HDM-R (50))
Program Officer
Mcallister, Kimberly A
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of California San Francisco
Internal Medicine/Medicine
Schools of Medicine
San Francisco
United States
Zip Code
Spear, Melissa L; Hu, Donglei; Pino-Yanes, Maria et al. (2018) A genome-wide association and admixture mapping study of bronchodilator drug response in African Americans with asthma. Pharmacogenomics J :
Zeiger, Andrew M; White, Marquitta J; Eng, Celeste et al. (2018) Genetic Determinants of Telomere Length in African American Youth. Sci Rep 8:13265
Mangul, Serghei; Yang, Harry Taegyun; Strauli, Nicolas et al. (2018) ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues. Genome Biol 19:36
Levin, Albert M; Gui, Hongsheng; Hernandez-Pacheco, Natalia et al. (2018) Integrative approach identifies corticosteroid response variant in diverse populations with asthma. J Allergy Clin Immunol :
Sun, Xiaobo; Gao, Jingjing; Jin, Peng et al. (2018) Optimized distributed systems achieve significant performance improvement on sorted merging of massive VCF files. Gigascience 7:
Mak, Angel C Y; White, Marquitta J; Eckalbar, Walter L et al. (2018) Whole-Genome Sequencing of Pharmacogenetic Drug Response in Racially Diverse Children with Asthma. Am J Respir Crit Care Med 197:1552-1564
Park, Danny S; Eskin, Itamar; Kang, Eun Yong et al. (2018) An ancestry-based approach for detecting interactions. Genet Epidemiol 42:49-63
Moss, Lilit C; Gauderman, William J; Lewinger, Juan Pablo et al. (2018) Using Bayes model averaging to leverage both gene main effects and G?×? E interactions to identify genomic regions in genome-wide association studies. Genet Epidemiol :
Neophytou, Andreas M; Oh, Sam S; White, Marquitta J et al. (2018) Secondhand smoke exposure and asthma outcomes among African-American and Latino children with asthma. Thorax 73:1041-1048
Ritz, Beate R; Chatterjee, Nilanjan; Garcia-Closas, Montserrat et al. (2017) Lessons Learned From Past Gene-Environment Interaction Successes. Am J Epidemiol 186:778-786

Showing the most recent 10 out of 23 publications