Asthma affects over 300 million individuals worldwide. Asthma symptoms are tightly correlated with overall quality of life;persistent symptoms resulting in poor asthma control leads to disproportionate morbidity and cost. Genome-wide association studies have been extensively applied to the study of asthma susceptibility and lung function in asthma, but have yet to be applied in a systematic fashion to studies of self-reported symptoms in asthma. The major goal of this project is to thoroughly investigate the genetic origins of asthma symptoms via genome-wide association study. To accomplish this, we have specified three related but independent aims.
The first aim evaluates data from over 500,000 genetic markers for their association with symptoms as reported at the time of enrollment into a clinical trial or clinical cohort. The markers with the strongest evidence for association will be tested for replication in independent clinical cohorts.
The second aim seeks to understand the genetic basis for response of symptoms to drug treatment (pharmacogenetics). Instead of analyzing baseline symptoms, the change in symptoms as a response to inhaled corticosteroid medications will be the primary outcome phenotype for this aim, which will also use genome-wide association testing and replication methods.
Our final aim will be to develop a model, using both genotype and phenotypic characteristics, including demographic, psychosocial, and behavioral factors, to predict who is at greatest risk of developing persistent symptoms in asthma. Dozens to hundreds of genetic markers will be used to develop these predictive tests, which will be formulated and validated for both persistent symptoms and treatment response of symptoms. We believe that these findings will uncover the genetic basis for symptoms in asthma and lead to novel interventions to predict and alleviate this major health care problem.
Asthma affects an estimated 300 million individuals worldwide and accounts for approximately $20 billion in direct health care costs in the United States annually, with a disproportionate proportion of those costs allocated to uncontrolled, persistently symptomatic individuals. The identification of genetic variants that can be used as the basis of a prognostic test to predict which individuals will or will not demonstrate symptoms and respond to therapy has the potential to substantially decrease both morbidity and financial burden related to asthma as well as to improve the overall quality of life for subjects with asthma and their care providers.
|Qiu, Weiliang; Rogers, Angela J; Damask, Amy et al. (2014) Pharmacogenomics: novel loci identification via integrating gene differential analysis and eQTL analysis. Hum Mol Genet 23:5017-24|
|Park, Heung-Woo; Dahlin, Amber; Tse, Szeman et al. (2014) Genetic predictors associated with improvement of asthma symptoms in response to inhaled corticosteroids. J Allergy Clin Immunol 133:664-9.e5|
|Bolotin, Eugene; Armendariz, Angela; Kim, Kyungpil et al. (2014) Statin-induced changes in gene expression in EBV-transformed and native B-cells. Hum Mol Genet 23:1202-10|
|McGeachie, Michael J; Stahl, Eli A; Himes, Blanca E et al. (2013) Polygenic heritability estimates in pharmacogenetics: focus on asthma and related phenotypes. Pharmacogenet Genomics 23:324-8|