Max A. Seibold, Ph.D. - US grants

? DESCRIPTION (provided by applicant): Asthma affects 5% of the world population. In the U.S., asthma death rates are four-fold higher in Latinos and African Americans compared to Whites. Latinos and African Americans have varying degrees of African, European, and Native American genetic ancestry. This genetic heterogeneity has important clinical implications. In fact, we demonstrated that we can improve the diagnosis of lung disease among African Americans by as much as 15% by including genetic measures of ancestry into clinical lung function prediction equations (NEJM). We improved upon our results by incorporating sub-continental Native American ancestry into clinical lung function prediction equations for Latinos (Science). We also demonstrated that exposure to air pollution is associated with increased asthma risk among Latino and African American children, and that this increase in risk was greatest among African American children (AJRCCM). Subsequently, we demonstrated that environmental and social risk factors cannot fully explain the correlation between genetic ancestry and asthma severity and lung function (JACI). Clearly, we demonstrated that ancestry plays a strong role in determining normal clinical measures such as lung function and asthma severity. We hypothesize that gene- environment interactions contribute to population differences in lung function and asthma severity following exposure to air pollution. Racial/ethnic differences in the frequency and composition of genetic variation likely play an important role in asthma severity. To test this hypothesis we recruited the largest gene-environment study of asthma among minority children in the U.S. (N > 10,000). Our goal is to use integrative genomics to identify gene-by-air pollution interactions that influence lung function and asthma severity in minority children. We will leverage existing 1,600 whole genome sequences with air pollution-induced gene expression in nasal airway epithelial cells (NECs) from children with mild and severe asthma. We will integrate individual-level whole genome sequencing data with precise cell-level genetic and exposure-response experiments. We will identify genetic risk factors and gene-environment interactions that contribute to asthma severity, and determine cellular response mechanisms that mediate poor lung function and severe asthma using NECs exposed to air pollution.

PROJECT SUMMARY/ABSTRACT Asthma prevalence in Puerto Ricans is 37% versus 12% for whites yet most studies have been conducted among the latter. This asthma burden extends to asthma morbidity and mortality, which are 2.4- and 4-fold higher among Puerto Ricans compared to whites, respectively. There is a strong association between severe, early-life viral respiratory illnesses and development of childhood recurrent wheeze and asthma. However, little is known about the mechanisms underlying these associations. Does airway dysfunction exist at birth and first manifest in early life as a severe illness in response to viral respiratory infections, and later as childhood asthma? Or does a severe, early-life respiratory illness injure a normal airway and precipitate asthma later in childhood? We will study Puerto Rican children to address these questions via three Specific Aims. Aim 1: Recruit a cohort of 3,000 newborns to longitudinally study the effects of early-life viral respiratory illnesses on nasal airway molecular endotype and risk for recurrent wheeze. We will collect yearly environmental, social, and clinical data on each participant and track all respiratory illnesses from birth to age 3. We will record severity and presence of wheezing in each child's illnesses and collect nasal swabs to determine the presence/type of virus associated with these illnesses. Aim 2: Identify viral and genetic determinants of severe early-life respiratory illnesses and whether the molecular state of the nasal airway epithelium at birth is predictive of these severe illnesses. We will perform transcriptomic and viral analyses on nasal airway swabs from subjects at birth and during respiratory illness. We will test if severe respiratory illnesses are associated with viral infection in general and/or infection with a specific viral species. We will use genome-wide genetic data to identify risk variants for severe early-life respiratory illnesses and variants influencing airway gene expression at birth and during illness (eQTLs). We will test for GxE interactions between top risk variants/eQTLs and infection with different viral species. We will also identify gene expression response to mild vs. severe early-life respiratory illnesses and determine if airway gene expression at birth is predictive of severe respiratory illness in early childhood. Aim 3: Determine the relationship between severity of early-life respiratory illness and post-illness but pre-asthma nasal airway gene expression profiles. We will perform transcriptomic and viral metagenomic analysis of nasal swabs collected from subjects at age 3. We will determine how severe respiratory illnesses affect the trajectory of airway gene expression profiles from birth to early childhood. Finally, we will determine if mild or severe respiratory illness in early life is predictive of recurrent wheeze at age 3. Our longitudinal birth cohort will [1] be the largest prospective study of minority infants, [2] provide novel and seminal information on genetic/viral risk factors for severe respiratory illnesses, and [3] identify airway endotypes that high-risk groups exhibit at birth and after respiratory illness, but prior to asthma onset. Our study will help to elucidate the relationship between early-life respiratory illness and asthma.

ABSTRACT Asthma is the most common chronic disease among children. Asthma prevalence, mortality, and drug response vary by race/ethnicity and genetic ancestry. In the U.S., asthma prevalence is highest among Puerto Ricans (36.5%), intermediate among African Americans (13.0%) and whites (12.1%), and lowest in Mexicans (7.5%). These disparities extend to asthma mortality, which is four-fold higher in Puerto Ricans and African Americans compared to Mexican Americans. Albuterol is the most commonly prescribed asthma medication in the world and is the mainstay of acute asthma management. Among low income and minority populations in the U.S., albuterol is often the only medication used regardless of asthma severity. Poor drug response contributes to racial/ethnic disparities in asthma morbidity and mortality. Disturbingly, Americans with the highest asthma prevalence and death rate also have the lowest drug response. Chronic albuterol use can decrease acute airway smooth muscle response to albuterol and increase airway inflammation through beta-agonist signaling in the airway epithelium, suggesting that chronic albuterol use may alter acute response through genomic and epigenomic modification of airway cells. Furthermore, acute bronchodilator drug response (BDR) to albuterol is a complex phenotype with an estimated heritability of 28.5%, indicating genetic factors contribute to BDR variability. Genome-wide and whole genome association analyses have revealed population-specific common and rare variants in non-coding regions of the genome associated with the extremes of BDR. The roles of genomic regulatory regions and population-specific variants in BDR have yet to be fully investigated. To this end, we have created an investigative system involving airway-specific cell types, patient-derived cells, and detailed clinical data to generate an encyclopedia of genes, regulatory regions, and pathways involved in BDR to albuterol. We will integrate RNA-seq, ChIP-seq, ATAC-seq, and whole genome sequencing data with detailed clinical data to identify trans-ethnic and population-specific variants contributing to differential expression and chromatin structure patterns in response to albuterol exposure. Furthermore, we will functionally characterize the regulatory regions that underlie acute and chronic albuterol BDR in multi-ethnic children with asthma using CRISPR-Cas9 activation/inhibition assays. These analyses will allow us to determine on a genomic scale the functional consequences of acute and chronic albuterol treatment on airway cells, and provide insight into potential targetable genes, regulatory elements, and pathways for improved asthma therapies in at-risk populations.