Albuterol is the most commonly prescribed medication in the world for short-term relief of asthma symptoms, and functions to control these symptoms through relaxation of the airway smooth muscle. Response to albuterol varies widely between individuals and by race/ethnicity. Genome wide association studies (GWAS) have uncovered many loci associated with the genetic factors of asthma risk and the pharmacogenomics of albuterol response. However, these loci reside primarily in uncharacterized noncoding genomic regions, and the genetic basis of asthma and albuterol response remains largely unknown. I hypothesize that rare, population- specific variants inside gene regulatory elements active in airway smooth muscle cells contribute to racial/ethnic and interindividual differences in asthma severity and albuterol response. In order to test this hypothesis, I will build on my functional genomics training and add to them novel skills I will develop in the training phase of this proposal in cellular reprograming, CRISPR/Cas9 genome editing and quantitative trait loci (QTL) analysis. With these new skills, I will utilize functional genomic technologies of RNA-seq, ChIP-seq and ATAC-seq to characterize the gene expression and gene regulatory elements active in primary bronchial smooth muscle cells (BSMCs), generate a robust protocol for creation of induced pluripotent stem cell (iPSC) derived BSMCs, and characterize their gene regulatory environment relative to primary BSMCs (Aim K1).
This aim will provide an encyclopedia of active genes, pathways and regulatory elements in a critical cell type relevant to asthma and albuterol response. Through this aim, I will also provide the asthma research community with a well characterized protocol to create patient-specific, iPSC-derived BSMCs (iBSMCs) which could be used for individual genetic and drug assays. I will also identify variants that alter regulatory element activity and gene expression through differential enhancer assays and CRISPR/Cas9 genome editing followed by RNA-seq and ATAC-seq (Aim K2). In the independent phase of this project, I will create iBSMC lines from 100 asthmatic patients with deep genetic and phenotypic data relating to lung function and albuterol response. I will then use these iBSMC lines to carry out expression QTL and chromatin accessibility QTL mapping to identify genetic variants that alter gene expression and enhancer activity, contributing to asthma severity and albuterol response (Aim R1). Finally, I will functionally characterize these genomic variants for their general and ethnic-specific alterations to the gene regulatory environment through CRISPR/Cas9 genome editing of patient-specific iBSMCs and followed by RNA- seq and ATAC-seq (Aim K2). This study will advance our understanding of asthma and albuterol response by creating a functional annotation in a critical cell type and providing a model for carrying out functional experiments in cell lines derived from the patients themselves, thereby advancing precision medicine and improving asthma treatment outcomes. Through this proposed training and research, I will gain the necessary skills to achieve my ultimate career goal of leading a successful and independent research laboratory.

Public Health Relevance

Asthma affects 5% of children worldwide, is the most common chronic disease among children and is typically controlled with albuterol to relax the bronchial smooth muscle cells and open the airways. However, there are large differences between patients in asthma severity and albuterol response, thought to be due to genetic causes, the majority of which remain largely unknown. Here, I plan to use several genomic technologies on cells obtained from asthmatic patients with detailed clinical response and genetic data, to increase the functional understanding of the genetic factors that lead to differences in asthma severity and asthma drug response.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Transition Award (R00)
Project #
4R00HL135403-03
Application #
10044061
Study Section
Special Emphasis Panel (NSS)
Program Officer
Tigno, Xenia
Project Start
2017-09-01
Project End
2022-11-30
Budget Start
2019-12-01
Budget End
2020-11-30
Support Year
3
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Type
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118