The goal of this proposed research is to determine to what extent asthma risk in African American (AA) subjects is modified by environmental exposure risk factors. Recent studies have identified genetic and environmental exposure factors that contribute to asthma risk; however, the extent to which these factors explain a person's risk to asthma remains largely unknown. Our long-term goal is to develop a program of study that would lead to an in-depth understanding of the complex interplay between genetic ancestry and environmental causes of asthma among AA children, and establish the utility of this information to predict and reduce asthma risk in AA children. Despite advances in asthma care, AAs are four times more likely to be hospitalized and seven times more likely to die from asthma than non-AAs. AAs have a mixed parental genome contribution with varying proportion of ancestry from African and European descents. We plan to search for specific genomic regions of unusually high African or European ancestry to identify chromosomal segments that are likely to interact with environmental exposure asthma risk factors. We hypothesize that ancestry and environmental exposure risk factors are critical in asthma risk.
Three Specific Aims are proposed to test our hypothesis and achieve our proposed plan:
Aim 1) Determine the genetic ancestry and conduct admixture mapping of AA asthmatic children using a multi-ethnic genotyping array;
Aim 2) Identify interactions between local ancestry and environmental exposure risk factors in modifying asthma risk;
and Aim 3) Replicate the most promising ancestry-specific and A:E interacting 6000 SNPs and develop a genetic ancestry risk score (GARS) to potentially explain a significant portion of asthma risk. To complete these aims we will analyze genetic, environmental exposure factors, clinical and epidemiologic data from the Cincinnati Children's Hospital Medical Center pediatric repository cohorts and Cincinnati BioBank. This research will improve our understanding of the interplay between ancestry and environmental exposure factors (traffic, cigarette smoke, mold) that modify asthma risk. Using a unique ancestry-based study design, we are particularly well positioned to develop a roadmap to unravel the relative contributions of genetic and environmental exposure variances and uncover the etiology of asthma in minority children. Predicting the development or progression of asthma is one of the ultimate aims of our research. 1

Public Health Relevance

The overall goal of this project is to decipher the genetic and environmental exposure determinants of childhood asthma by carrying out a 1) multi-ethnic genotyping array that contains SNP sets that are tailored towards African American (AA) ancestry, 2) admixture mapping analysis in well-phenotyped (n=3,000) admixed AA children, ancestry-environmental exposure interactions, and 3) replicate the top 6,000 SNPs in 2,000 samples and use the replicated variants to develop a genetic ancestry risk score (GARS) to predict asthma risk (n=3,000). Genetic ancestry interacts with environmental exposures to modify asthma risk, and the analysis of ancestry in the context of an environmental exposure framework has significant potential to more efficiently uncover variants that affect asthma susceptibility. Any success with ancestry-specific variant identification and development of risk alleles in the form of GARS in asthma can lead to important translational research of considerable public health significance and will likely motivate similar approaches for other common complex diseases.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project (R01)
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Infectious Diseases, Reproductive Health, Asthma and Pulmonary Conditions Study Section (IRAP)
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Gan, Weiniu
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Cincinnati Children's Hospital Medical Center
Independent Hospitals
United States
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Ding, Lili; Li, Dan; Wathen, Michael et al. (2018) African ancestry is associated with cluster-based childhood asthma subphenotypes. BMC Med Genomics 11:51
Gautam, Yadu; Altaye, Mekibib; Xie, Changchun et al. (2017) AdmixPower: Statistical Power and Sample Size Estimation for Mapping Genetic Loci in Admixed Populations. Genetics 207:873-882
Harding, Kimberly; Mersha, Tesfaye B; Pham, Phuong-Thu et al. (2017) Health Disparities in Kidney Transplantation for African Americans. Am J Nephrol 46:165-175
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