Utilizing Genetic Techniques to Understand Relationships Between Lung Disease and Comorbid Conditions

Abstract

The goal of this dissertation was to utilize genetic techniques to understand the relationships between lung cancer, COPD, and comorbid conditions using DNA biobanks linked to electronic health records. In the first aim, we used the Synthetic Derivative, a de-identified version of Vanderbilt University Medical Center’s EHR, to develop two phenotyping algorithms for COPD. The second aim focused on the relationship between COPD and MDD. In the final aim, we explored the role of genetics in the development of irAEs in individuals with lung cancer treated with PD-1/PD-L1 immunotherapy with or without combined CTLA-4 immunotherapy. Overall, this project contributes important knowledge to the fields of COPD and lung cancer research. COPD and lung cancer are major contributors to morbidity and mortality worldwide. By leveraging genetic tools, we were able to improve our understanding of these diseases, which will ultimately lead to better diagnostic, treatment, and prevention strategies.