Asthma is the most common chronic illness in childhood and it is widely recognized that there is a major genetic component to asthma susceptibility. Genome-wide association studies, relying on the """"""""common disease, common variant"""""""" model of disease, have identified common variants in more than 15 genes significantly associated with asthma or related phenotypes. While the majority of these findings have been replicated, the risk conferred by any one of these variants is low (typical OR <1.7). Thus, there is a significant portion of the genetic component attributed to asthma development and severity that has not been accounted for, termed """"""""missing heritability."""""""" This missing heritability problem is not unique to asthma and has been recognized for the majority of common diseases. It has been proposed that rare variants may be an important, yet unexplored, player in common diseases and may in fact explain some of the strong associations that have not yet yielded causative variants. Here, we hypothesize a model whereby individual families are segregating """"""""family-specific"""""""" mutations contributing to asthma susceptibility. In contrast to the majority of rare Mendelian disorders where only one causative mutation is required for disease, we hypothesize that at least one family- specific mutation is necessary, but not sufficient for diseas development within individuals in the family. It is only when these private mutations occur in the context of common asthma susceptibility variants that the disease will develop. This application utilizes a family-based whole-exome sequencing strategy to identify family-specific variants segregating with asthma and study the distribution of functional variants across all known asthma genes. We will take advantage of the family-based nature of several studies conducted at the Center for Perinatal, Pediatric and Environmental Epidemiology by selecting asthmatic probands from the children that had asthma phenotype information collected in one of the original studies. We propose to re-contact asthma families with at least two asthmatic children and one non-asthmatic child to collect blood for DNA, update the asthma phenotype information in the parents and children, and conduct family-based whole-exome sequencing analyses. We will identify family-specific mutations using whole-exome sequencing of half of the families in the study and then perform a family-based association analysis to identify genes containing multiple family-specific variants associated with asthma. We will then sequence the genes identified in this discovery exome sequencing data in the other half of the asthma families to validate these findings. Finally, we will look across the frequency spectrum of variants in our whole-exome data to determine if asthma patients have more functional variants in known asthma genes than their non-asthmatic relatives.
Asthma is the most common chronic illness in childhood and in addition to environmental exposure, it is widely recognized that there is a major genetic component to asthma susceptibility. Here we plan to identify functional genetic variants by sequencing the protein coding regions of the genome in families with multiple children with asthma. This will help us to gain a better understanding of the biology of asthma and may one day lead to improved treatments for asthma.
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|Salinas, Yasmmyn D; Wang, Zuoheng; DeWan, Andrew T (2018) Statistical Analysis of Multiple Phenotypes in Genetic Epidemiologic Studies: From Cross-Phenotype Associations to Pleiotropy. Am J Epidemiol 187:855-863|
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