Research Projects Directory

Research Projects Directory

815 active projects

This information was updated 10/28/2021

Information about each project within the Researcher Workbench is available in the Research Projects Directory below. Approved researchers provide their project’s research purpose, description, populations of interest, and more. This information helps All of Us ensure transparency on the type of research being conducted.

At this time, all listed projects are using data in the Registered Tier. The Registered Tier contains individual-level data from electronic health records, surveys, physical measurements, and wearables. Personal identifiers have been removed from these data to protect participant privacy.

Note: Researcher Workbench users provide information about their research projects independently. Views expressed in the Research Projects Directory belong to the relevant users and do not necessarily represent those of the All of Us Research Program. Information in the Research Projects Directory is also cross-posted on AllofUs.nih.gov in compliance with the 21st Century Cures Act.

BMIF 6300 Course Practice Workspace

Exploring the characteristics of participants who have responded to the COPE survey to better understand the impact of COVID-19

Scientific Questions Being Studied

Exploring the characteristics of participants who have responded to the COPE survey to better understand the impact of COVID-19

Project Purpose(s)

  • Educational

Scientific Approaches

We will build an analytical dataset using the cohort builder + concept set selector, and we will use Python or R to run descriptive analyses.

Anticipated Findings

Summary results (e.g., number of participants, demographic characteristics, etc...) of participants who have responded to the COPE survey

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Collaborators:

  • Adrienne Roman - Project Personnel, Vanderbilt University Medical Center
  • Hiral Master - Project Personnel, All of Us Program Operational Use

Health Disparities Experienced by Adults with ASD

We plan to identify challenges in treating adults with autism spectrum disorder (ASD) in the medical system, and identify what conditions these individuals are at risk for. This will be accomplished by looking at the variety of variables provided within…

Scientific Questions Being Studied

We plan to identify challenges in treating adults with autism spectrum disorder (ASD) in the medical system, and identify what conditions these individuals are at risk for. This will be accomplished by looking at the variety of variables provided within the All of Us research program

Specific scientific questions include:
1. How does treatment (i.e., medical appointments, labs, procedures) differ between adults with and without ASD?
2. Are individuals with ASD more likely to experience certain comorbidities, and if so, are they being treated equally as those without ASD?

Our study aim is to assess if and how patients with a diagnosis of ASD are treated differently when they present to healthcare settings with respect to medications, imaging, or invasive procedures with a goal to empower both patients and health care workers.

Project Purpose(s)

  • Educational

Scientific Approaches

The ASD cohort was created by searching for patients who are noted as having one of the following conditions: autism spectrum disorder, autistic disorder, infantile autism, active infantile autism, or residual infantile autism in their medical record, and/or responding "yes" to a survey question, "Has a doctor or health care provider ever told you that you have autism spectrum disorder?" Within these criteria, 999 individuals with ASD have been identified. In our first pass with the AoU dataset we will select features from literature such as comorbidities that have been shown to be significantly associated with ASD. We will also include demographic information since this is a potential confound that has impacts on healthcare outcomes . Our data-driven approach will be centered around leveraging machine learning models to discriminate between ASD and non-ASD patients. We will then identify what indicators drive the differences in the clinical trajectories of these two cohorts.

Anticipated Findings

In the United States, ASD has been estimated to have a prevalence as high as 2.2% amongst US adults. Within healthcare there are countless stories of individuals with ASD getting treated differently in a hospital, having to deal with a misunderstanding of the diagnosis between patients and providers, and an overall sentiment that the system has failed to adapt to the needs of those with ASD. Adults with ASD have a higher prevalence of chronic medical conditions and mental health disorders compared to neurotypical adults. Thus, individuals with ASD are more likely to need healthcare and affiliated resources over their lifespan. Examining the differences in clinical trajectories and experiences by adults with and without ASD will help us build a more complete story about what drives health disparities in ASD patients at the clinic and provide insights into strategies to remedy them.

Demographic Categories of Interest

  • Disability Status

Research Team

Owner:

  • Rohini Patel - Research Fellow, University of California, San Diego
  • Molly Wilkinson - Graduate Trainee, University of California, San Diego
  • David Laub - Graduate Trainee, University of California, San Diego

TandemRepeats_SCZ

Tandem repeats are prevalent throughout the genome and prone to high frequency of mutation, categorized as short tandem repeats (STRs) with motif lengths of 1-6bp, and variable number tandem repeats (VNTRs) with longer motif lengths, >7bp, repeated in tandem. In…

Scientific Questions Being Studied

Tandem repeats are prevalent throughout the genome and prone to high frequency of mutation, categorized as
short tandem repeats (STRs) with motif lengths of 1-6bp, and variable number tandem repeats (VNTRs) with
longer motif lengths, >7bp, repeated in tandem. In addition to length variations of common frequency, some TRs
also exhibit rare variation, extreme changes in length. TR variations are known to underlie about 40 Mendelian,
monogenic disorders, that are primarily brain-specific, for example the trinucleotide, poly(CAG) repeat disorders, of Huntington’s
Disease and spinocerebellar ataxia.

Schizophrenia (SCZ) is a psychiatric disorder that affects approximately 1% of the population worldwide, with
heritability estimated up to 80%. To date, a systematic investigation of the role of TRs in schizophrenia has
not yet been conducted, partly owing to technical limitations in genotyping tandem repeats, as well as lack of
access to large-scale, sequenced schizophrenia cohorts.

Project Purpose(s)

  • Disease Focused Research (Schizophrenia)
  • Ancestry

Scientific Approaches

The current project aims to apply recently developed, next-generation sequence based TR profiling tools to whole genome sequenced
(WGS) data within NIH All of Us, comparing individuals with schizophrenia to neurotypical controls, to identify variation in short tandem repeats (STRs) and variable number tandem repeats (VNTRs), that may contribute to schizophrenia genetic risk. We will initially restrict analysis of common variation to schizophrenia GWAS-positive loci. We will functionally annotate and prioritize rare variation by genomic location (i.e. coding regions, splice sites, UTRs and promoter regions).

Anticipated Findings

We anticipate identifying rare STR variation associated with schizophrenia case status, identified in schizophrenia cases but not typical neurotypical controls.
In addition, we anticipate identifying common STR and VNTR variation associated with schizophrenia.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age

Research Team

Owner:

  • Rebecca Birnbaum - Early Career Tenure-track Researcher, Icahn School of Medicine at Mount Sinai

Depression Fitbit Study

Major depressive disorder (MDD) is known to result in changes in physical activity, fidgeting/restlessness, energy levels, and sleep patterns. It has also been established that most MDD patients have recurrent episodes, separated by periods of "remission" that may last 2…

Scientific Questions Being Studied

Major depressive disorder (MDD) is known to result in changes in physical activity, fidgeting/restlessness, energy levels, and sleep patterns. It has also been established that most MDD patients have recurrent episodes, separated by periods of "remission" that may last 2 months or more. The purpose of this study is to assess the ability of the Fitbit data of 1) longitudinally distinguish individuals based on diagnostic severity, and 2) longitudinally distinguish between additional modifiers. We will focus primarily on daily activity (steps) data, and sleep data (once available).

Project Purpose(s)

  • Disease Focused Research (major depressive disorder)
  • Social / Behavioral

Scientific Approaches

We will build datasets and cohorts of individuals meeting the MDD diagnostic criteria, as well as subsets for severity and additional modifiers. We will perform time series analysis of the Fitbit data with machine learning models, and assess their performance in the above questions. We will look specifically for trends and patterns in the time series Fitbit data that may be unique to the MDD group, or subsets.

Anticipated Findings

Consumer-grade technology has been pushing into the field of health and wellness. While previous studies have evaluated the performance of wearables in psychiatric and cardiovascular diseases, none have the sample sizes or data collection lengths made possible by the All of Us. We know that MDD comes with it changes in physical activity, and positive results may reinforce the role of wearable technology as a confirmatory step in the diagnostic process. Null results, on the other hand, will highlight the unique challenges of consumer health-related technologies, especially as these devices are becoming more and more common.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Depression Fitbit Study - V4 Archive

Major depressive disorder (MDD) is known to result in changes in physical activity, fidgeting/restlessness, energy levels, and sleep patterns. It has also been established that most MDD patients have recurrent episodes, separated by periods of "remission" that may last 2…

Scientific Questions Being Studied

Major depressive disorder (MDD) is known to result in changes in physical activity, fidgeting/restlessness, energy levels, and sleep patterns. It has also been established that most MDD patients have recurrent episodes, separated by periods of "remission" that may last 2 months or more. The purpose of this study is to assess the ability of the Fitbit data of 1) longitudinally distinguish individuals based on diagnostic severity, and 2) longitudinally distinguish between additional modifiers. We will focus primarily on daily activity (steps) data, and sleep data (once available).

Project Purpose(s)

  • Disease Focused Research (major depressive disorder)
  • Social / Behavioral

Scientific Approaches

We will build datasets and cohorts of individuals meeting the MDD diagnostic criteria, as well as subsets for severity and additional modifiers. We will perform time series analysis of the Fitbit data with machine learning models, and assess their performance in the above questions. We will look specifically for trends and patterns in the time series Fitbit data that may be unique to the MDD group, or subsets.

Anticipated Findings

Consumer-grade technology has been pushing into the field of health and wellness. While previous studies have evaluated the performance of wearables in psychiatric and cardiovascular diseases, none have the sample sizes or data collection lengths made possible by the All of Us. We know that MDD comes with it changes in physical activity, and positive results may reinforce the role of wearable technology as a confirmatory step in the diagnostic process. Null results, on the other hand, will highlight the unique challenges of consumer health-related technologies, especially as these devices are becoming more and more common.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Gordon Ye - Undergraduate Student, University of California, San Diego

AYA Cancer Survivors - Updated

I am examining the All of Us data to understand patient-provider communication patterns among adolescent/young adult (AYA) cancer survivors. Prior research shows AYA survivors are at risk of disengaging in their care as they transition from pediatric to adult care…

Scientific Questions Being Studied

I am examining the All of Us data to understand patient-provider communication patterns among adolescent/young adult (AYA) cancer survivors. Prior research shows AYA survivors are at risk of disengaging in their care as they transition from pediatric to adult care settings. Evidence suggests high-quality communication with providers is protective against this disengagement. The questions I hope to answer include: (1) Are there patterns in patient-provider communication by patient age? and (2) What additional factors may be related to patient-provider communication? With the answers to these questions, there may be opportunities for improving healthcare engagement among AYA cancer survivors.

Project Purpose(s)

  • Disease Focused Research (cancer)
  • Population Health
  • Social / Behavioral

Scientific Approaches

First, I will identify a cohort of AYA cancer survivors within the All of Us data. I will explore options for dividing the cohort by age group. It is likely that cell sizes will be too small for reporting aggregated data. As such, I will also explore dividing the cohort by age at diagnosis. If data permits, I will examine differences in access and healthcare utilization.

Anticipated Findings

Taking into account guidelines for transitioning into adult care, I anticipate patient-provider communication to be stronger among older cohorts of AYA survivors compared to younger cohorts. If the contrary is observed, further investigation into communication patterns is needed and may better inform transition practices for AYA survivors.

Demographic Categories of Interest

  • Access to Care

Research Team

Owner:

  • Karen Llave - Graduate Trainee, University of California, Irvine

Pathways to Adverse Perinatal and Birth Outcomes Among Ethnic Minorities

There are remarkable racial disparities in perinatal and birth outcomes in the US. For example, African American women experience higher rates of perinatal mood and anxiety disorders and preterm birth/low birthweight compared to Caucasian American women. Environmental stress (e.g., racial…

Scientific Questions Being Studied

There are remarkable racial disparities in perinatal and birth outcomes in the US. For example, African American women experience higher rates of perinatal mood and anxiety disorders and preterm birth/low birthweight compared to Caucasian American women. Environmental stress (e.g., racial discrimination, SES), biological dysregulation (e.g., cortisol), unhealthy behaviors (e.g. lack of exercise), or inadequate coping resources (e.g., low social support) have been found to be risk factors for these adverse perinatal and birth outcomes. We want to investigate how these risk factors independently or interactively predict adverse outcomes for ethnically diverse women.

Project Purpose(s)

  • Disease Focused Research (perinatal mood and anxiety disorders, preterm birth, low birthweight)
  • Population Health
  • Social / Behavioral
  • Educational
  • Control Set

Scientific Approaches

We plan to analyze the data among pregnant and postpartum women that includes Overall Health, Lifestyle, COPE Survey, Lab Measurements, and Medical Records through the National Institutes of Health All of Us Research Program.

Anticipated Findings

We anticipate that environmental stress and/or biological dysregulation will lead to adverse perinatal and birth outcomes with mediators/moderators including health behaviors and coping resources in ethnically diverse women.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Jasmine Wang - Undergraduate Student, University of California, Irvine

Duplicate of SARS-CoV-2 infection Project

The proposed study seeks to investigate the associations between SARS-CoV-2 and the development of diabetes. The primary hypothesis is SARS-CoV-2 will be a risk factor for the onset of diabetes. The secondary hypothesis is that SARS-CoV-2 is a predisposing factor…

Scientific Questions Being Studied

The proposed study seeks to investigate the associations between SARS-CoV-2 and the development of diabetes. The primary hypothesis is SARS-CoV-2 will be a risk factor for the onset of diabetes. The secondary hypothesis is that SARS-CoV-2 is a predisposing factor for other chronic diseases. Additionally, the proposed study will explore if SARS-CoV-2 is associated with other hormone/endocrine conditions (e.g., hyperthyroidism), mental health or substance use of conditions (e.g., alcohol use disorder), and cancer (e.g., kidney cancer, lung cancer, pancreatic cancer). Findings have clinical implications for prevention (e.g., vaccines), screenings, and treatments, post SARS-CoV-2 infection. Moreover, the impact of SARS-CoV-2 will disproportionately impact underserved populations whom are at an increased risk for chronic conditions (e.g., diabetes, cardiovascular, pulmonary).

Project Purpose(s)

  • Disease Focused Research (SARS-CoV-2)

Scientific Approaches

We will explore associations between SARS-CoV-2 infections and the incidence of diabetes with a focus on underserved patient populations. This study will also explore other associations affecting the incidence of SARS-CoV-2 infections and co-morbidities. The analysis will employ exploratory methods of data analysis such as association plots, heatmaps, and descriptive statistics. Following the exploratory analysis, generalized linear models will explore the associations further while controlling for patient characteristics and other factors. Multiplicity corrections will control the incidence of type I errors and ensure replicability of research results. The data will include information on past SARS-CoV-2 infections, type I and II diabetes, demographic characteristics, and other hormone/endocrine conditions, mental health or substance use conditions, and cancer. Data will be stratified to assess the change in risk of these conditions for underserved patient populations.

Anticipated Findings

The primary hypothesis is SARS-CoV-2 will be a risk factor for the onset of diabetes. The secondary hypothesis is that SARS-CoV-2 is a predisposing factor for other chronic diseases. Additionally, the proposed study will explore if SARS-CoV-2 is associated with other hormone/endocrine conditions (e.g., hyperthyroidism), mental health or substance use of conditions (e.g., alcohol use disorder), and cancer (e.g., kidney cancer, lung cancer, pancreatic cancer). Findings have clinical implications for prevention (e.g., vaccines), screenings, and treatments, post SARS-CoV-2 infection.

Demographic Categories of Interest

  • Race / Ethnicity
  • Income Level

Research Team

Owner:

  • Eric Diaz - Undergraduate Student, University of Texas at El Paso

Duplicate of Duplicate of Mendelian diseases DX

We are studying the phenotypic burdens of diseases among patients with diagnoses of mendelian diseases across multiple racial groups.

Scientific Questions Being Studied

We are studying the phenotypic burdens of diseases among patients with diagnoses of mendelian diseases across multiple racial groups.

Project Purpose(s)

  • Disease Focused Research (Mendelian diseases)
  • Methods Development

Scientific Approaches

We will include all participants. We will compare the diseases profiles of participants with ICD codes or other concepts of genetic diagnosis of mendelian diseases.

Anticipated Findings

We hope to understand the burden of diseases in these patients, particularly among non-white ancestral groups.

Demographic Categories of Interest

  • Race / Ethnicity

Research Team

Owner:

  • Chenjie Zeng - Research Fellow, National Institutes of Health (NIH)

Retinal Vein Occlusion and associated risk factors

To assess for risk factors for retinal vein occlusion (RVO) among participants in the NIH All of Us database, particularly social risk factors that have not been well-studied, including substance use.

Scientific Questions Being Studied

To assess for risk factors for retinal vein occlusion (RVO) among participants in the NIH All of Us database, particularly social risk factors that have not been well-studied, including substance use.

Project Purpose(s)

  • Disease Focused Research (retinal vein occlusion)

Scientific Approaches

Data will be extracted regarding demographics, co-morbidities, income, housing, insurance, and substance use. Opioid use will be defined by relevant diagnosis and prescription codes, with prescription use >30 days. Controls will be sampled at a 4:1 control to case ratio from a pool of individuals >18 years of age without a diagnosis of RVO and proportionally matched to the demographic distribution of the 2019 U.S. census. We will use multivariable logistic regression to identify medical and social determinants significantly associated with RVO. Statistical significance will be defined as p<0.05.

Anticipated Findings

Understanding RVO risk factors is important for primary prevention and improving visual outcomes. Several studies have demonstrated an increasing prevalence of RVO with age, but little consensus has been reached regarding associations with race and/or ethnicity. Other studies exploring medical risk factors have shown strong associations with hypertension, hyperlipidemia, diabetes mellitus, glaucoma and cigarette smoking. However, the majority of these studies were conducted on small populations limited to individuals identifying as Asian or white. Few studies have investigated associations with substance use outside of cigarettes and alcohol. The opioid epidemic began in the early 2000s, and as of 2019, more than 1.6 million Americans suffer from opioid use disorder. Given that long term opioid use increases risk of cardiovascular events such as myocardial infarction, an investigation into whether opioid use increases risk of retinal vascular disease, such as RVO, is warranted

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

BINF6300 Course Practice Workspace [Group 2]

For BMIF6300

Scientific Questions Being Studied

For BMIF6300

Project Purpose(s)

  • Educational

Scientific Approaches

For BMIF6300

Anticipated Findings

For BMIF6300

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Chemoprevention in CRC and Breast Ca

Previous studies have shown that the drugs metformin, statins and aspirin all may have chemoprotective effects on cancer. However, other studies have shown that the effects are mitigated when other variables and accounted for. The research in animal models have…

Scientific Questions Being Studied

Previous studies have shown that the drugs metformin, statins and aspirin all may have chemoprotective effects on cancer. However, other studies have shown that the effects are mitigated when other variables and accounted for. The research in animal models have shown that there is a mechanistic reasoning behind the drug eliciting chemoprotective effects. Some studies have suggested that statins and metformin make work together to assert their effect. To date most of the studies have been in predominant population with European ancestry. Our primary goal is to determine if there is a chemoprotective effect seen with metformin, statins and aspirin. The secondary goal is to determine how these drugs in combination may change this relationship. These studies have predominant focused on colorectal and breast cancer.

Project Purpose(s)

  • Population Health

Scientific Approaches

For this study we will first determine if in the dataset we find any correlation between the drugs and prevention of colorectal or breast cancer. Then we plan to create a model to control for patient factors that may influence the relationship between the medication and cancer. Finally, we will create a model to determine how the medication may influence each other’s effect. To do this we will need to look at all patients that have electronic medical records data available. We will make a control set of adults that are 50 years old or older at the current time and have not taken metformin, statin or aspirin. We will then identify patients 50years old or older that have taken individually or in combination: metformin, statins and aspirin.

Anticipated Findings

We hope to find a positive correlation between the use of the medication and decreased cancer risk. This would contribute to the current literature because this study would be done on the most diverse population. This would add to the growing body of literature that these drugs may have chemoprotective effects.

Demographic Categories of Interest

  • Age

Research Team

Owner:

Sickle Cell Trait (SCT) Associated Clinical Outcomes

Sickle cell trait (SCT) is largely considered a benign carrier state; however, a growing body of research has found evidence on associated clinical complications. Our question is: What external and genetic factors increase the risk of developing clinical outcomes among…

Scientific Questions Being Studied

Sickle cell trait (SCT) is largely considered a benign carrier state; however, a growing body of research has found evidence on associated clinical complications. Our question is: What external and genetic factors increase the risk of developing clinical outcomes among SCT carriers? As our understanding of SCT continues to develop, accurately assessing possible related clinical complications and the factors that put carriers at higher risk of developing them will assist healthcare providers with counseling and treatment interventions for carriers.

Project Purpose(s)

  • Other Purpose (The primary purpose of this project is to identify differences in frequency of reported Sickle Cell Trait (SCT) associated clinical outcomes in a cohort of SCT and non-SCT carriers. In addition, this project aims to identify any external and genetic factors that may increase SCT-carriers’ risk of developing clinical outcomes. )

Scientific Approaches

In this study, electronic health records (EHRs) and surveys of identified SCT carriers will be analyzed to assess frequency of reported SCT associated clinical outcomes to help strengthen or refute current evidence on SCT association. High frequency of clinical outcomes with no reported association to SCT will also be accounted for. EHRs and surveys for a comparison group of All of Us participants that do not have SCT will also be assessed, to identify any significant differences in SCT associated clinical complication manifestation. Additionally, EHRs and surveys of both groups will be analyzed to determine history with external risk modifiers explored within SCT literature that may put carriers at higher risk of developing complications.

Anticipated Findings

We anticipate that our findings will strengthen current evidence on the association of certain clinical outcomes with SCT, as well as clarify the role of external factors in increasing the risk of developing complications. Overall, we hope that our findings will provide a better understanding of this carrier state, to improve genetic counseling and treatment for those living with sickle cell trait.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Hasmin Ramirez - Project Personnel, National Institutes of Health (NIH)

Work with All of Us Physical Measurements Data - Class Teaching

How to navigate around physical measurements?

Scientific Questions Being Studied

How to navigate around physical measurements?

Project Purpose(s)

  • Other Purpose (Testing and operations purposes)

Scientific Approaches

N/A

Anticipated Findings

N/A

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Hiral Master - Project Personnel, All of Us Program Operational Use

test migraine

This is an initial practice session with the AoU research workbench. no specific scientific question

Scientific Questions Being Studied

This is an initial practice session with the AoU research workbench. no specific scientific question

Project Purpose(s)

  • Methods Development
  • Other Purpose (initial experience in the research workbench environment. This is a place where I want to learn about the tools available her.)

Scientific Approaches

This is an initial practice session with the AoU research workbench. I will explore different methods using the examples provided

Anticipated Findings

This is an initial practice session with the AoU research workbench. I don't expect any specific findings from this initial trial

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

Social Determinants and Healthcare Access in Eye Conditions - v5 Dataset

We are planning to explore disparities in healthcare access and utilization for patients with eye conditions across different demographic groups. We would like to evaluate risk of developing advanced/severe disease in different eye conditions, and understand how social determinants contribute…

Scientific Questions Being Studied

We are planning to explore disparities in healthcare access and utilization for patients with eye conditions across different demographic groups. We would like to evaluate risk of developing advanced/severe disease in different eye conditions, and understand how social determinants contribute to this risk while adjusting for other known risk factors. We are also interested in understanding the availability of social determinants of health data in this data repository compared to EHR clinical data warehouses alone.

Project Purpose(s)

  • Population Health

Scientific Approaches

We will build cohorts of patients with various eye diseases (i.e. diabetic retinopathy, retinal vein occlusions, glaucoma, etc.). Then we will develop concept sets and extract data on outcomes (i.e. development of complications), as well as predictors including clinical data and social data. We will draw on survey data and EHR data within All of Us. When genomic data and wearable data become available, we are interested in evaluating those data sources as well. We will use statistical modeling and machine learning to generate predictive models.

Anticipated Findings

We anticipate that there may be differential risk for developing complications based on disparities in healthcare access and utilization for patients with eye conditions.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Geography
  • Disability Status
  • Access to Care
  • Education Level
  • Income Level

Research Team

Owner:

  • Terrence Lee - Graduate Trainee, University of California, San Diego
  • Sally Baxter - Research Fellow, University of California, San Diego
  • John McDermott - Graduate Trainee, University of California, San Diego
  • Grace Ahn - Graduate Trainee, University of California, San Diego
  • Gordon Ye - Undergraduate Student, University of California, San Diego
  • Alison Chan - Graduate Trainee, University of California, San Diego
  • Bita Shahrvini - Graduate Trainee, University of California, San Diego
  • Bharanidharan Radha Saseendrakumar - Project Personnel, University of California, San Diego
  • Arash Delavar - Graduate Trainee, University of California, San Diego

Collaborators:

  • Priyanka Soe - Project Personnel, University of California, San Diego
  • Mahasweta Nayak - Undergraduate Student, University of California, San Diego
  • Cecilia Vallejos - Undergraduate Student, University of California, San Diego

MDD Assay SNPs

The goal of this workspace is to get acquainted with the workspace while exploring medical features related to major depressive disorder, and, when available, utilize ~1000 single letters of genotyped genomes to see if they can predict major depressive disorder…

Scientific Questions Being Studied

The goal of this workspace is to get acquainted with the workspace while exploring medical features related to major depressive disorder, and, when available, utilize ~1000 single letters of genotyped genomes to see if they can predict major depressive disorder in a sex-specific fashion, based on experimental work done regarding possible roles of variants at these genetic positions.

Project Purpose(s)

  • Ancestry

Scientific Approaches

Polygenic scoring using genotypes at MDD SNPs deemed functional in gene-regulatory assays to determine if genotypes at these variants explain. Data: genotypes for ~1000 single positions with common variants and EHR psych diagnoses and meds.

Anticipated Findings

The hope would be that these polygenic scores provide greater explanation of variance in disease/non-disease status than existing polygenic scores, which rely in part on genotypes imputed in either the panel's study or in the cohort the score is being applied to. In addition, having vetted these variants for differences in function between alleles should narrow the scope of detection to variants that even have potential to exert their hypothesized biological effects underlying disease risk.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Bernie Mulvey - Graduate Trainee, Washington University in St. Louis

WSWM Study

I will use this workbench to to explore the lived experiences of women who have sex with women and men (WSWM) and the connection between their relationship dynamics and sexual practices, in relation to HIV risk. Looking at the relationship…

Scientific Questions Being Studied

I will use this workbench to to explore the lived experiences of women who have sex with women and men (WSWM) and the connection between their relationship dynamics and sexual practices, in relation to HIV risk. Looking at the relationship dynamics of WSWM (i.e. self-esteem, power, and intimate partner violence) may help gain insight on the sexual risk behaviors of WSWM’s that exist in those relationships, and how they may be related to increased HIV risk. Identifying these dynamics and behaviors may inform future clinical cultural competence interventions which address the problem associated with the phenomena of sexual practices within WSWM relationships, and increased HIV risk within these relationships, which result from unprotected sex.

Project Purpose(s)

  • Population Health
  • Social / Behavioral

Scientific Approaches

I plan to conduct a qualitative study, using a phenomenological approach. Participant qualification will be deemed by completion of a participant inclusion survey. All study questions will be answered in a virtual interview format (i.e. Zoom).

Anticipated Findings

This study was designed to address the limited research that currently exists on HIV prevention and testing interventions for women who have sex with women, to also include interactions with men. The anticipated findings from the study intend to identify which dynamics of participant relationships (i.e self-esteem, power) may contribute to sexual decision making. The intent is to identify patterns in sexual decision making and consequent sexual-risk taking behaviors that may increase risk in contracting or transmitting HIV.

Demographic Categories of Interest

  • Race / Ethnicity
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Others

Research Team

Owner:

  • DaJaneil McCree - Early Career Tenure-track Researcher, University of Michigan

Cardiovascular Disease

Our research is focused on exploring patients with various cardiovascular diseases and analyze how different medications are being used to treat these diseases within the All of Us dataset. This research will also focus on exploring how rural populations are…

Scientific Questions Being Studied

Our research is focused on exploring patients with various cardiovascular diseases and analyze how different medications are being used to treat these diseases within the All of Us dataset. This research will also focus on exploring how rural populations are treated in comparison to the urban population to determine any differences in the course of treatment and to determine if a patients treatment in an urban vs rural setting can impact a patients healthcare. We are exploring the hypothesize that while similar medications are being utilized, the limited access to healthcare in a rural setting has an increase in disease progression and the need for additional medications.

Project Purpose(s)

  • Disease Focused Research (cardiovascular system disease)

Scientific Approaches

For this study, we will utilize algorithms in the All of Us data to determine the various medications being prescribed for different cardiovascular diseases and for individuals in urban vs rural populations. We will determine if the medications being used vary based upon a urban vs rural setting for different cardiovascular diseases and how these medications are being used during disease progression.

Anticipated Findings

We anticipate that with the available data sets from the different sites across the country, that similar medications will be utilized in urban and rural setting; however, with the limited access to healthcare in a rural setting has an increase in disease progression and the need for additional medications to help control a patients disease progression. This research will hopefully highlight the importance continued care to slow or limit disease progression.

Demographic Categories of Interest

  • Age
  • Geography

Research Team

Owner:

  • Stephanie Giorno - Graduate Trainee, West Virginia School of Osteopathic Medicine
  • Olivia Giambra - Graduate Trainee, West Virginia School of Osteopathic Medicine
  • Nicholas Courtney - Graduate Trainee, West Virginia School of Osteopathic Medicine
  • Jacob Neumann - Mid-career Tenured Researcher, West Virginia School of Osteopathic Medicine
  • Cassandra Ross - Graduate Trainee, West Virginia School of Osteopathic Medicine

Adolescent depression

Our lab's (WebbsLab.com) research is focused on improving our understanding of the etiology and treatment of depression in adolescents (in particular focused on developing multivariable machine learning models to predict depressive symptom onset and treatment response to inform treatment recommendations).…

Scientific Questions Being Studied

Our lab's (WebbsLab.com) research is focused on improving our understanding of the etiology and treatment of depression in adolescents (in particular focused on developing multivariable machine learning models to predict depressive symptom onset and treatment response to inform treatment recommendations). This is our first time logging into the AllofUs research workbench to explore the available samples/cohorts and relevant variables.

Project Purpose(s)

  • Disease Focused Research (Depression)

Scientific Approaches

Datasets: adolescents with and without a depression diagnosis. Depressed adolescents receiving psychotherapy and/or pharmacotherapy.
Methods/tools: use of machine learning to predict depression onset and treatment response from baseline adolescent characteristics

Anticipated Findings

This will depend on the available samples/cohorts and relevant variables. Our first goal is to explore what the workbench has available. Ultimately the goal of our research is to develop predictive models that can inform which adolescents are at elevated risk of developing depressive symptoms or at risk of poor treatment response from a pharmacological or psychotherapeutic intervention.

Demographic Categories of Interest

  • Age

Research Team

Owner:

  • Christian Webb - Early Career Tenure-track Researcher, Mass General Brigham

oral cancer disparities

The goal of this project is to report on cancer and oral complications from cancer therapy related disparities and associated factors in the United States.

Scientific Questions Being Studied

The goal of this project is to report on cancer and oral complications from cancer therapy related disparities and associated factors in the United States.

Project Purpose(s)

  • Population Health

Scientific Approaches

We will identify diseases of interest using ICD-10 codes. Descriptive statistics and multivariate logistic regression will be used to identify possible association between diseases and risk factors and disparities.

Anticipated Findings

We hypothesize that certain populations may have less access to care and therefore worst outcomes when cancer and oral complications from cancer therapy are considered.

Demographic Categories of Interest

  • Race / Ethnicity
  • Sexual Orientation

Research Team

Owner:

  • Alessandro Villa - Mid-career Tenured Researcher, University of California, San Francisco
  • Brooke Warren - Graduate Trainee, University of California, San Francisco

Test - Work With Wearable Device Data

Testing and operational use

Scientific Questions Being Studied

Testing and operational use

Project Purpose(s)

  • Other Purpose (Testing and operational use)

Scientific Approaches

This Tutorial Workspace contains one Jupyter Notebook written in Python. The notebook contains information on how to extract and work with the current set of All of Us Fitbit data. What are the anticipated findings from the study? How would your findings contribute to the body of scientific knowledge in the field? By reading and running the notebook in this Tutorial Workspace, researchers will learn how to query information about steps, heart rate, and daily activity summary.

Anticipated Findings

By reading and running the notebook in this Tutorial Workspace, researchers will understand how to work with Fitbit CDR data from the workbench. They will learn how to query information about steps, heart rate, and daily activity summary.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Research Team

Owner:

  • Hiral Master - Project Personnel, All of Us Program Operational Use

Collaborators:

  • Francis Ratsimbazafy - Other, All of Us Program Operational Use

Investigation on Suicide in the COVID-19 pandemic

Outbreak of Coronavirus Disease 2019 (COVID-19) has caused a new psychological burden. Patient Health Questionnaire (PHQ-9) can be used to evaluate mood status, monitor changes in signs/symptoms of depression, and assess suicidal ideation. Here our study aims to describe the…

Scientific Questions Being Studied

Outbreak of Coronavirus Disease 2019 (COVID-19) has caused a new psychological burden. Patient Health Questionnaire (PHQ-9) can be used to evaluate mood status, monitor changes in signs/symptoms of depression, and assess suicidal ideation. Here our study aims to describe the basis statistics of PHQ-9 scores and its inferred depression or suicide risk for all participants in All of US COPE survey.

Project Purpose(s)

  • Disease Focused Research (Depression, Suicidal behaviors)

Scientific Approaches

PHQ-9 questions and answers will be retrieved for participants involved in six different time points. Response to each question will be converted to numeric scores (0, 1, 2, 3), and then summed up to derive the PHQ-9 total score. Participants missing any individual score were not included in this study. Depression levels will be categorized into 5 different ordinals according to their PHQ-9 total scores. Binary status of suicidal ideation will be defined using item-9 answer (i.e., yes for >0). Distributions of PHQ-9 total score, depression severity, and suicidal ideation status at each time session will be reported by descriptive statistics stratified by age, sex, and ancestry. Their changes across different time sessions were tested by Kruskal-Wallis (KW) test, Friedman test, or chi-square test. Multivariable analyses are going to be conducted by generalized linear mixed models.

Anticipated Findings

We anticipate the descriptive statistics, pairwise correlations, and multivariable model fitting results will tell us the trajectories of major depression disorder and suicidal behaviors in the COVID-19 pandemic. They will not only help to verify the known relationship between depression and gender or age, but also will provide new evidence of mood status changes along COVID-19 pandemic at both population and individual level.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Geography
  • Education Level

Research Team

Owner:

  • Hongsheng Gui - Early Career Tenure-track Researcher, Henry Ford Health System

Capstone Project

Although adverse drug reactions happens across many different drugs, it is especially common with clopidogrel, an oral antiplatelet drug; in 1997, the FDA approved clopidogrel but 30% of Caucasian patients have had a suboptimal response to therapy based on platelet…

Scientific Questions Being Studied

Although adverse drug reactions happens across many different drugs, it is especially common with clopidogrel, an oral antiplatelet drug; in 1997, the FDA approved clopidogrel but 30% of Caucasian patients have had a suboptimal response to therapy based on platelet function tests. The success rate of clopidogrel is lower in Asians, with 50-60% showing a higher risk of stroke and poor composite vascular outcome measures.
The purpose of this project is to perform retrospective case control study in order to find the effect of socioeconomic factors: patients’ education level, race and ethnicity, access to healthcare, income, on increased risk of bleeding or adverse drug reactions (ADRs) in patients.

Project Purpose(s)

  • Population Health
  • Social / Behavioral
  • Educational
  • Commercial

Scientific Approaches

We want to perform exploratory data analysis to find underlying patterns of individudal patterns and then combining it with other factors related to ADRs to look for possible correlation between ADRs in patients taking clopidogrel and SES factors.

Anticipated Findings

By finding the association between SES and ADR to clopidogrel, we could predict ADRs for patients planning to take this drug to avoid bleeding and other complications.

Demographic Categories of Interest

  • Age
  • Access to Care
  • Education Level
  • Income Level

Research Team

Owner:

Effects of Physical Activity on Health in Aging Latino Populations

The primary purpose of this study is to investigate the relationships between 1) individual characteristics (e.g., age, gender, etc.), 2) ethnicity, 3) physical activity, and 4) subjective/objective physical health. The data will be used to further understanding of the effects…

Scientific Questions Being Studied

The primary purpose of this study is to investigate the relationships between 1) individual characteristics (e.g., age, gender, etc.), 2) ethnicity, 3) physical activity, and 4) subjective/objective physical health. The data will be used to further understanding of the effects of antecedent characteristics on physical activity and health. Similarly, these data will help inform on the relationships between health and physical activity in aging individuals. Findings will concentrate on the context of ethnicity to contribute to research on aging ethnic minorities and marginalized populations.

The specific questions we aim to elucidate are as follows:
AIM 1. How do individual characteristics affect engagement in physical activity and subjective/objective health; how are these relationships affected by ethnicity?
AIM 2. What are the relationships between physical activity and subjective/objective health; how are these relationships affected by ethnicity?

Project Purpose(s)

  • Social / Behavioral
  • Educational
  • Other Purpose (Findings from this study may contribute to manuscripts for scientific journals and/or conference submissions. )

Scientific Approaches

Dataset development and analyses will utilize All of Us data and will occur in the researcher workbench. Data will be pulled from several All of Us datasets including: The Basics (e.g., demographic, ability, etc.), Overall Health (e.g., quality of life, everyday activities, etc.), Lifestyle (e.g., substance use), Personal Medical History (e.g., cardiovascular history), and Physical Measurements (e.g., height, weight, etc.). Normality tests, regression analyses and tests of correlation (e.g. chi-square analysis, Pearson correlation, etc.) will be utilized in analyses. Results will be reported in APA style.

Anticipated Findings

The objectives of this study are to inform on the relationships between individual characteristics, physical activity, and health, particularly in aging Latino adults. We anticipate that variables associated with increased cumulative disadvantage (e.g., race, gender, etc.) will disproportionally affect physical activity engagement and health; it is hypothesized that physical activity will positively impact health and vice versa, such that persons with more engagement are healthier. This contributes to ethnic, minority and marginalized peoples research by providing greater context for health and behavioral research by exploring both risk and protective factors. It may also serve to inform future meaningful interventions to improve health and activity in aging diverse populations.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age

Research Team

Owner:

  • Sarah Hubner - Graduate Trainee, University of Nebraska, Omaha

Collaborators:

  • Harlan Sayles - Project Personnel, University of Nebraska Medical Center
  • Julie Blaskewicz Boron - Mid-career Tenured Researcher, University of Nebraska, Omaha
  • Athena Ramos - Senior Researcher, University of Nebraska Medical Center
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