Elliot Outland
Project Personnel, Vanderbilt University Medical Center
1 active project
Duplicate of Demo - PheWAS Smoking
Scientific Questions Being Studied
As a demonstration project, this study will present the results of Phenome-Wide Association Studies (PheWAS) to show how the various sources of data contained within All of Us research dataset can be used to inform scientific discovery. We will perform separate PheWAS studies with smoking status as the independent variable. Specific questions include:
1. How can one implement a PheWAS within the All of Us Researcher Workbench?
2. How can one use heterogeneous data sources within the All of Us dataset to explore disease associations using self-reported exposures (Participant Provided Information, or “PPI”) and exposures captured in the electronic medical record (EHR).
Project Purpose(s)
- Methods Development
- Other Purpose (This work is a result of an All of Us Research Program Demonstration Project. The projects are efforts by the Program designed to meet the program's goal of ensuring the quality and utility of the Research Hub as a resource for accelerating discovery in science and medicine. This work was reviewed and overseen by the All of Us Research Program Science Committee and the Data and Research Center to ensure compliance with program policy, including policies for acceptable data access and use.)
Scientific Approaches
As a method for assessing the health burden of smoking on potential observed phenotypes, we implement a Phenome-Wide Association study. A Phenome-wide association study consists of an array of association tests over an indexed representation of the human phenome. In this analysis, we will conduct PheWAS for EHR derived smoking and PPI derived smoking exposures included in the All of Us research dataset. We will be representing "Smoking Exposure” in three ways:
EHR Smoking ICD Billing Codes
Participant Provided Information (PPI) Smoking lifetime 100 cigarettes yes/no
Participant Provided Information (PPI) Smoking lifetime smoking everyday
To perform PheWAS, we will map ICD representations of disease to a common vocabulary of PheCodes. We then use Jupyter Notebooks to create reusable functions to perform PheWAS and generate Manhattan Plots to summarize associations.
Anticipated Findings
For this study, we anticipate that we will be able to replicate known disease associations with smoking exposure. This will serve to demonstrate the quality, utility, and diversity of the All of Us data and tools and the power of gathering multiple data sources for a single phenotype, providing researchers options for study design and validation. Importantly the entire pheWAS package is made available for reuse by researchers in the Workbench, for new hypothesis generation.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Registered Tier
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