David Schlueter

Research Fellow, NIH

11 active projects

Duplicate of Erwin Update: DJS: Duplicate of JAMA PheWAS Final Review 07-06-2021

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…

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).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

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 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).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

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.

Research Team

Owner:

Erwin Update: DJS: Duplicate of JAMA PheWAS Final Review 07-06-2021

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…

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).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

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 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).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

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.

Research Team

Owner:

Collaborators:

  • Ariel Williams - Research Fellow, National Institutes of Health (NIH)

Duplicate of Fitbit Data Obesity Project

We intend on exploring how continuously monitored measurements correlate with obesity measures in the AoU cohort.

Scientific Questions Being Studied

We intend on exploring how continuously monitored measurements correlate with obesity measures in the AoU cohort.

Project Purpose(s)

  • Disease Focused Research (morbid obesity)

Scientific Approaches

We first intend on extracting fitbit data as obesity phenotypes and define appropriate cohorts accordingly. Next we will use statistical analyses to explore the relationships between physical activity and obesity.

Anticipated Findings

We expect to see significant correlation between fitbit usage and obesity. We also expect to see fluctuations in measurement to be reflected in BMI measurement.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Fitbit Data Obesity Project

We intend on exploring how continuously monitored measurements correlate with obesity measures in the AoU cohort.

Scientific Questions Being Studied

We intend on exploring how continuously monitored measurements correlate with obesity measures in the AoU cohort.

Project Purpose(s)

  • Disease Focused Research (morbid obesity)

Scientific Approaches

We first intend on extracting fitbit data as obesity phenotypes and define appropriate cohorts accordingly. Next we will use statistical analyses to explore the relationships between physical activity and obesity.

Anticipated Findings

We expect to see significant correlation between fitbit usage and obesity. We also expect to see fluctuations in measurement to be reflected in BMI measurement.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

DJS: Duplicate of JAMA PheWAS Final Review 07-06-2020

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…

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).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

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 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).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

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.

Research Team

Owner:

Erwin Update: DJS: Duplicate of JAMA PheWAS Final Review 05-21-2020

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…

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).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

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 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).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

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.

Research Team

Owner:

Collaborators:

  • Andrea Ramirez - Other, All of Us Program Operational Use
  • Jianglin Feng - Other, University of Arizona
  • Jason Karnes - Early Career Tenure-track Researcher, University of Arizona
  • Chenjie Zeng - Research Fellow, National Institutes of Health (NIH)

Duplicate of How to Work with All of Us Survey Data

We recommend that all researchers explore the notebooks in this workspace to learn the basics of All of Us Program Data. What should you expect? By running the notebooks in this workspace, you should get familiar with how to query…

Scientific Questions Being Studied

We recommend that all researchers explore the notebooks in this workspace to learn the basics of All of Us Program Data.

What should you expect?
By running the notebooks in this workspace, you should get familiar with how to query PPI questions/surveys, what the frequencies of answers for each question in each PPI module are.

Project Purpose(s)

  • Educational
  • Methods Development
  • Other Purpose (This is an All of Us Tutorial Workspace created by the Researcher Workbench Support team. It is meant to provide instruction for key Researcher Workbench components and All of Us data representation.)

Scientific Approaches

Not available.

Anticipated Findings

By reading and running the notebooks in this Tutorial Workspace, researchers will learn the following:
- how to query the survey data,
- how to summarize PPI modules, and questions.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Duplicate of How to Work with All of Us Survey Data

We recommend that all researchers explore the notebooks in this workspace to learn the basics of All of Us Program Data. What should you expect? By running the notebooks in this workspace, you should get familiar with how to query…

Scientific Questions Being Studied

We recommend that all researchers explore the notebooks in this workspace to learn the basics of All of Us Program Data.

What should you expect?
By running the notebooks in this workspace, you should get familiar with how to query PPI questions/surveys, what the frequencies of answers for each question in each PPI module are.

Project Purpose(s)

  • Educational
  • Methods Development
  • Other Purpose (This is an All of Us Tutorial Workspace created by the Researcher Workbench Support team. It is meant to provide instruction for key Researcher Workbench components and All of Us data representation.)

Scientific Approaches

Not available.

Anticipated Findings

By reading and running the notebooks in this Tutorial Workspace, researchers will learn the following:
- how to query the survey data,
- how to summarize PPI modules, and questions.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Duplicate of Phenotype - Depression

The Notebooks in this Workspace can be used to implement well-known phenotype algorithms in one’s own research.

Scientific Questions Being Studied

The Notebooks in this Workspace can be used to implement well-known phenotype algorithms in one’s own research.

Project Purpose(s)

  • Educational
  • Methods Development
  • Other Purpose (This is an All of Us Phenotype Library Workspace created by the Researcher Workbench Support team. It is meant to demonstrate the implementation of key phenotype algorithms within the All of Us Research Program cohort.)

Scientific Approaches

Not Applicable

Anticipated Findings

By reading and running the Notebooks in this Phenotype Library Workspace, researchers can implement the following phenotype algorithms:

This Workspace contains an implementation of a phenotype algorithm for depression: This algorithm was obtained from the eMERGE network. Citation: TBA. KPWA/UW. Depression. PheKB; 2018 Available from: https://phekb.org/phenotype/1095

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

DJS: Duplicate of JAMA PheWAS Final Review 05-21-2020

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…

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).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

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 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).”

There is no pre-specified hypothesis. It is important to determine if PheWAS can be conducted within the All of Us workbench

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.

Research Team

Owner:

DJS: Duplicate of Final MASTER: PheWAS Phase I Demo Update 2020

Show PheWAS tools in the AOU Environment

Scientific Questions Being Studied

Show PheWAS tools in the AOU Environment

Project Purpose(s)

  • Methods Development

Scientific Approaches

We will implement phenome wide association study.

Anticipated Findings

That PheWAS will work.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

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Request a Review of this Research Project

You can request that the All of Us Resource Access Board (RAB) review a research purpose description if you have concerns that this research project may stigmatize All of Us participants or violate the Data User Code of Conduct in some other way. To request a review, you must fill in a form, which you can access by selecting ‘request a review’ below.