| Title: | Genome-wide association and pleiotropy studies of subphenotypes of respiratory diseases |
| Lead Institution: | University of Arizona |
| Principal investigator: | Dr Xingnan Li |
Application 66320
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About
Chronic obstructive pulmonary disease (COPD) is a major cause of global morbidity and mortality, affecting ~328 million people worldwide. Currently, there is no cure for COPD. Although, in general, individuals who smoke heavily are more likely to develop COPD, it can still affect individuals with little or no smoking history. Likewise, not all subjects with a significant history of smoking develop COPD. Therefore, more research is needed to understand the biological basis of this common disease. Asthma is a common inflammatory airways disease, which affects more than 300 million people worldwide. It is often considered a disease of childhood which may or may persist throughout adult life. However, there are a significant subset of patients with adult onset. Major advances in therapy have been made. Although conventional drugs are effective for most of the patients with mild-to-moderate asthma; they do not cure the disease. However, standard therapies are less effective in patients with difficult-to-treat or severe asthma and often require very expensive biologic therapies. Both asthma and COPD are heterogeneous diseases, i.e., multiple subphenotypes with distinct molecular mechanisms exist that require different treatment approaches. There are many studies worldwide on the genetics of asthma and COPD; however, the majority of these studies have a relatively small number of patients making it very difficult to identify subphenotypes in these common heterogeneous diseases. Genetic studies, including studies using UKBiobank data, have identified more than 100 genes associated with asthma susceptibility or COPD susceptibility, however, very few genetic studies have focused on underlying subphenotypes of asthma or COPD. In this study, we are going to identify genes associated with subphenotypes of respiratory diseases and investigate genetic causes of various diseases in relationship to respiratory diseases. Using biostatistic and bioinformatic approaches, we will strive to reveal the genetics of the underlying clinical heterogeneity of respiratory diseases. This will expand our understanding of the biology of respiratory diseases in relationship to other common diseases. Identification of the genetics and the role of subphenotypes of respiratory diseases will lead to more precise approaches to treat both asthma and COPD.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 9721 | Genetic relationships between high blood eosinophil count, asthma susceptibility, and asthma severity | Huashi Li (+1) | 2023 | Journal of Asthma |
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