Asthma disproportionately affects underrepresented minorities, and is a complex disease where the interplay between genetic factors and environmental exposures controls susceptibility. Airway epithelial cells are critical in the development of allergic airway inflammation, represent the first line of defense against environmental stimuli, and the nasal airway epithelium has been shown to mirror the bronchial epithelium morphologically and functionally. Genome-wide association studies (GWAS) have been successful in identifying genes associated with increased risk of asthma, but there is a substantial gap between single nucleotide polymorphism (SNP) associations discovered by GWAS and understanding how these loci control disease. Because nearly all of the asthma GWAS associations to date involve SNPs in intergenic or intronic regions, it seems likely that polymorphism markers in regulatory elements may account for a large portion of the missing heritability. It is also increasingly clear that epigenetic mechanisms may be causal for asthma, and studies suggest that SNPs are likely to affect both gene expression and methylation independently of one another; thus, both transcriptome and methylation data can independently be informative for defining functional genes. We recently completed whole genome sequencing (WGS) on 1,100 African Caribbean asthmatics and non- asthmatics, extensively phenotyped and followed participants for >20 years, living in a homogeneous, well- characterized environment, comprising the Barbados Asthma Genetics Study. Currently a subset is being recruited as part of the NIH-supported parent grant to characterize the transcriptome of peripheral blood CD4+ T cells, and perform an expression Quantitative Trait Locus (eQTL) study combining WGS and transcriptomic data. To test the hypothesis that genetic determinants confer risk to asthma, and expressed variation in the transcriptome and methylome of the nasal epithelium may mediate the relationship between genotype, phenotype and environment, we propose to integrate one of the most comprehensive WGS databases on an African ancestry population with next-generation sequencing technology (RNA-Seq) and eQTL mapping to elucidate how genetic variation controls differ in quantitative levels of gene expression of nasal airway epithelial cells.
The specific aims of this application build upon the infrastructure of an ongoing program, and include the following: (i) identify cis- and trans-effects of variants identified in the transcriptome for isolated nasal epithelial cells from atopic asthmatics; (ii) identify eQTL patterns from nasal epithelial cells specific to atopic asthma; and (iii) identify DNA methylation changes associated with atopic asthma in the nasal airway epithelium, followed by an unbiased QTL analyses on the methylome (meQTL) and integrating novel eQTLs and meQTLs from transcript expression and methylation, respectively, to determine whether these QTLs identified in airway epithelial cells contribute to asthma risk. These studies should substantially advance our understanding of the molecular basis for asthma.

Public Health Relevance

Most gene poylmorphisms associated with asthma found by genome-wide association studies (GWAS) involve intergenic and non-coding variants which are unlikely to directly control disease risk. Expression quantitative trait locus (eQTL) mapping is an approach to detect non-coding variation in regulatory elements controlling complex biological processes. We will test whether polymorphisms control asthma by regulating gene transcription and methylation patterns in nasal airway epithelial cells using data from 600 African Caribbean asthmatics and non-asthmatic controls from Barbados, measuring the relationship between genotype, phenotype and environment.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI132476-03
Application #
9851798
Study Section
Infectious Diseases, Reproductive Health, Asthma and Pulmonary Conditions Study Section (IRAP)
Program Officer
Dong, Gang
Project Start
2018-02-01
Project End
2023-01-31
Budget Start
2020-02-01
Budget End
2021-01-31
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Colorado Denver
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
041096314
City
Aurora
State
CO
Country
United States
Zip Code
80045