Research Projects Directory

Research Projects Directory

11,984 active projects

This information was updated 6/23/2024

The Research Projects Directory includes information about all projects that currently exist in the Researcher Workbench to help provide transparency about how the Workbench is being used. Each project specifies whether Registered Tier or Controlled Tier data are used.

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.

369 projects have 'COVID' in the scientific questions being studied description
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ABO Systematic Review

Research questions: 1) Can our novel ABO blood typing algorithm using genetic data be used effectively to extensively type ABO subtypes from whole genome sequencing and array data in a diverse cohort? 2) Will a SNP approach for ABO blood…

Scientific Questions Being Studied

Research questions:

1) Can our novel ABO blood typing algorithm using genetic data be used effectively to extensively type ABO subtypes from whole genome sequencing and array data in a diverse cohort?
2) Will a SNP approach for ABO blood typing be concordant with available serotype?
3) What disease association ABO blood types can be replicated using the AllofUs dataset?
4) What novel disease associations, if any, with ABO blood types can be identified in a diverse cohort?

Relevance: Genomic variation in RBC and antigens is associated with a myriad of conditions. The ABO locus alone is associated with many conditions including venous thromboembolism (VTE), pancreatic cancer, malaria, and COVID-19. Furthermore, it is not common practice to extensively type beyond the traditional ABO blood groups, and the studies that do so are primarily done in individuals of European ancestry. Thus, we seek to do the first PheWAS on extensively typed RBC antigens and to do so in a diverse cohort.

Project Purpose(s)

  • Disease Focused Research (red blood cell (RBC) antigen-associated diseases)

Scientific Approaches

We plan to employ a blood typing algorithm to extensively type RBC antigens from 1) whole genome sequencing and 2) array data in the AllofUs cohort, and compare the two outcomes. Then, we plan to employ the phenome-wide association study (PheWAS) approach to identify associations between RBC antigen types and other clinical phenotypes. PheWAS will be carried out using multivariable linear regression and logistic regressions with ABO blood groups with our novel ABO blood type. For example, in the case of the ABO blood group, ABO blood subtypes (A101, A102, Aw01, B101, etc.) will act as the independent variable and phenotypes, derived from participant provided information (PPI) electronic health records (EHR), as the dependent variable. Initial models will include adjustments for age, gender, and race/ethnicity. Differential associations by race/ethnicity, gender, and sex will also be evaluated.

Anticipated Findings

This proposed project aims to test our novel ABO blood typing algorithm on WGS and array data in the diverse AllofUs cohort. We also aim to replicate known RBC-disease associations as well as identify any novels ones that may be identified within a diverse cohort.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Kiana Martinez - Research Fellow, University of Arizona
  • Jason Karnes - Early Career Tenure-track Researcher, University of Arizona

Collaborators:

  • Anthony Vicenti - Project Personnel, University of Arizona
  • Sadaf Raoufi - Graduate Trainee, University of Arizona
  • Rudramani Pokhrel - Other, University of Arizona
  • Jason Giles - Research Fellow, University of Arizona
  • Ehsan Khajouei - Project Personnel, University of Arizona
  • Andrew Klein - Graduate Trainee, University of Arizona

Impact of COVID-19 on the Hispanic Community

This Workspace will be used for the “Impact of COVID-19 on the Hispanic Community” Driver Project, that will go beyond validation and result in novel findings. The study aims to replicate findings from the following articles: “COVID-19 Pandemic: Disparate Health…

Scientific Questions Being Studied

This Workspace will be used for the “Impact of COVID-19 on the Hispanic Community” Driver Project, that will go beyond validation and result in novel findings. The study aims to replicate findings from the following articles: “COVID-19 Pandemic: Disparate Health Impact on the Hispanic/Latinx Population in the United States” (Gil et al. 2020), “Life in the Time of COVID-19: a Case Study of Community Health” (Schelly 2021), “Racial/Ethnic Disparities In COVID-19 Exposure Risk, Testing, And Cases At The Subcounty Level In California” (Reitsma et al. 2021), that shed light on how COVID-19 has disproportionately affected the Hispanic community in the United States. We will focus on replicating the findings as they relate to the social determinants of health (SDOH) such as income, education, coexisting medical conditions such as obesity and diabetes, lack of access to health care, language barriers, working conditions, and living conditions.

Project Purpose(s)

  • Social / Behavioral

Scientific Approaches

1. Has the Hispanic community been disproportionately affected by COVID-19?
What is the impact COVID-19 has had on the U.S. Hispanic Community?

2. What role have social determinants of health, such as income, education, and access to health care, played in the disproportionate effect of COVID-19 on the Hispanic community?

Anticipated Findings

We expect that the Hispanic cohort in the All of Us Research Program reflects the disproportionate effect of COVID-19 on the Hispanic community found in the aforementioned articles. We expect to see that a large proportion of Hispanics will have had COVID-19, or known someone who did, or lack access to healthcare facilities in the event of a COVID-19 infection, based on COPE Survey findings. These findings would reinforce the importance of taking social determinants of health into account when creating policy relating to access to health care and safety net programs for the Hispanic community in the United States.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

Impact of COVID-19 on the Hispanic Community - Dataset v7

This Workspace will be used for the “Impact of COVID-19 on the Hispanic Community” Driver Project, that will go beyond validation and result in novel findings. The study aims to replicate findings from the following articles: “COVID-19 Pandemic: Disparate Health…

Scientific Questions Being Studied

This Workspace will be used for the “Impact of COVID-19 on the Hispanic Community” Driver Project, that will go beyond validation and result in novel findings. The study aims to replicate findings from the following articles: “COVID-19 Pandemic: Disparate Health Impact on the Hispanic/Latinx Population in the United States” (Gil et al. 2020), “Life in the Time of COVID-19: a Case Study of Community Health” (Schelly 2021), “Racial/Ethnic Disparities In COVID-19 Exposure Risk, Testing, And Cases At The Subcounty Level In California” (Reitsma et al. 2021), that shed light on how COVID-19 has disproportionately affected the Hispanic community in the United States. We will focus on replicating the findings as they relate to the social determinants of health (SDOH) such as income, education, coexisting medical conditions such as obesity and diabetes, lack of access to health care, language barriers, working conditions, and living conditions.

Project Purpose(s)

  • Social / Behavioral

Scientific Approaches

1. Has the Hispanic community been disproportionately affected by COVID-19?
What is the impact COVID-19 has had on the U.S. Hispanic Community?

2. What role have social determinants of health, such as income, education, and access to health care, played in the disproportionate effect of COVID-19 on the Hispanic community?

Anticipated Findings

We expect that the Hispanic cohort in the All of Us Research Program reflects the disproportionate effect of COVID-19 on the Hispanic community found in the aforementioned articles. We expect to see that a large proportion of Hispanics will have had COVID-19, or known someone who did, or lack access to healthcare facilities in the event of a COVID-19 infection, based on COPE Survey findings. These findings would reinforce the importance of taking social determinants of health into account when creating policy relating to access to health care and safety net programs for the Hispanic community in the United States.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

  • Kyle Melin - Mid-career Tenured Researcher, University of Puerto Rico Medical Sciences
  • William Agyapong - Project Personnel, University of Texas at El Paso

Myalgic Encephalopathy, fibromyalgic, long COVID19

CSF/ME can often be misdiagnosed for a condition with shared presentation (e.g., fibromyalgia, chronic pain syndrome, post-viral fatigue syndrome). We hypothesise the trio of conditions, ME/CSF, Fibromyalgia, and Long COVID-19, plus their comorbidities, share causal pathways (biological mechanisms) and that…

Scientific Questions Being Studied

CSF/ME can often be misdiagnosed for a condition with shared presentation (e.g., fibromyalgia, chronic pain syndrome, post-viral fatigue syndrome). We hypothesise the trio of conditions, ME/CSF, Fibromyalgia, and Long COVID-19, plus their comorbidities, share causal pathways (biological mechanisms) and that these can be discovered using genetic and novel causal inference methods. This raises the possibility that these may not represent distinct clinical entities but disparate phenotypical expressions of the same disease. We will investigate:
1) The patterns of co-occurrence in the US population,
2) The risk factors shared between the diseases,
3) The shared genetics between the diseases, highlighting potentially modifiable mechanisms associated with the onset of ME/CSF.

Project Purpose(s)

  • Disease Focused Research (chronic fatigue syndrome)
  • Population Health
  • Ancestry

Scientific Approaches

We will perform genome-wide analyses for ME/CSF, Fibromyalgia and post-viral fatigue syndrome and additional long-term conditions using defined clinical code lists and the REGENIE software. We will use LD-score regression to estimate pairwise genetic correlations between the trio of conditions and additional long-term conditions with significance set at a false discovery rate (FDR) of 5%. We will investigate the role of common risk factors (e.g. blood pressure and BMI) in explaining the shared genetics between disease pairs (using partial LDSC). We will use causal inference methods (Mendelian Randomization) to confirm which modifiable risk factors drive comorbidities. We will use fine mapping and colocalization methods to identify specific shared causal variants, and bioinformatics databases to gain insight into common disease biology.

Anticipated Findings

This study will help understand the specific and shared causes of ME/CSF, fibromyalgia and long COVID19, and their interplay with common comorbidities. This new knowledge addresses current gaps in evidence and will help formulate new strategies and interventions for preventing or delaying the onset and managing these chronic illnesses affecting the population. The project should provide new ideas for prevention and management, tailored for specific patient needs, by applying the now well-established tools of genetic association in large populations to reveal causation and identify drug targets.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

DB7 of CRS study

What are some of the significant characteristics of Covid 19 patients who lost sense of smell. Why important: to understand the potential cause of the loss of smell for Covid 19 Patients.

Scientific Questions Being Studied

What are some of the significant characteristics of Covid 19 patients who lost sense of smell.
Why important: to understand the potential cause of the loss of smell for Covid 19 Patients.

Project Purpose(s)

  • Disease Focused Research (covid 19)
  • Methods Development

Scientific Approaches

Build ML models to discover the potentail patterns for the Covid 19 patients who had smell lose

Anticipated Findings

Find significant features that can predict the smell lose for Covid 19 patients and potentially guide the recovery process of the patients

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Renjie Hu - Early Career Tenure-track Researcher, University of Houston
  • Meher Gajula - Graduate Trainee, University of Houston

Collaborators:

  • Tania Banerjee - Early Career Tenure-track Researcher, University of Houston
  • Thamer Alnazzal - Graduate Trainee, University of Houston
  • Roshan Dongre - Graduate Trainee, Houston Methodist Research Institute
  • Khoa Nguyen - Student, University of Houston
  • Najm Khan - Graduate Trainee, Rutgers, The State University of New Jersey
  • Koyal Ansingkar - Graduate Trainee, Houston Methodist Research Institute
  • Jagan Mohan Reddy Dwarampudi - Graduate Trainee, University of Houston
  • Faizaan Khan - Graduate Trainee, Houston Methodist Research Institute
  • Ying Lin - Early Career Tenure-track Researcher, University of Houston
  • Aatin Dhanda - Graduate Trainee, Rutgers, The State University of New Jersey
  • lichang zhu - Graduate Trainee, University of Houston
  • Boaz Adikaibe - Undergraduate Student, University of Houston

RECOVER

We are trying to understand the gaps in current aspects of long COVID in recent research and development efforts. In the form of a meta-analysis, we aim to identify current gaps in this space to highlight a need for further…

Scientific Questions Being Studied

We are trying to understand the gaps in current aspects of long COVID in recent research and development efforts. In the form of a meta-analysis, we aim to identify current gaps in this space to highlight a need for further investment.

Project Purpose(s)

  • Population Health

Scientific Approaches

We aim to analyze EHR datasets to find similarities among specific sub-domains and identify gaps in specific research initiatives. To this end, we will use standard clustering and natural language processing (NLP) approaches to accomplish our research objectives.

Anticipated Findings

We anticipate finding under-researched domains in the healthcare, drug development, and infectious disease spaces that have yet to be exhaustively investigated. We hope to inform the scientific community of these fundings to encourage downstream investment and initiatives in these spaces.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Longitudinal serum cytokines and health outcomes in COVID-19 patients

How longitudinal serum cytokines (IL-6, IL-10, CRP etc.) is associated with intubation among COVID-19 patients? Understanding how longitudinal serum cytokines like IL-6, IL-10, and CRP correlate with severe outcomes in COVID-19 patients is critical. These cytokines are pivotal in immune…

Scientific Questions Being Studied

How longitudinal serum cytokines (IL-6, IL-10, CRP etc.) is associated with intubation among COVID-19 patients?
Understanding how longitudinal serum cytokines like IL-6, IL-10, and CRP correlate with severe outcomes in COVID-19 patients is critical. These cytokines are pivotal in immune response and their levels can indicate cytokine storm, which worsens inflammation and tissue damage. Tracking these markers over time helps predict disease severity and outcomes such as respiratory failure or death. This knowledge aids in timely intervention and personalized treatment, potentially improving patient outcomes amid the pandemic.

Project Purpose(s)

  • Disease Focused Research (COVID-19)
  • Population Health

Scientific Approaches

We are using a retrospective cohort study design to examine factors associated with intubation in COVID-19 patients.
Dependent Variable: Binary variable indicating whether intubation occurred (1) or did not occur (0).
Independent Variables: Demographics: Age, sex, race, and ethnicity.
Physical Measurements: BMI and pregnancy status.
Biomarkers: D-dimer, Interleukin-6 (IL-6), IL-10, CRP. Collect biomarker data at specific times relative to the diagnosis of COVID-19.
COVID Vaccine Status: Document vaccination status and dates.
Drug: Record medications administered and their timing relative to COVID-19 diagnosis.

Repeated measures logistic regression will be performed to assess the relationship between the biomarkers and intubation status. Adjusted odds ratios (aOR) will be reported with their 95% confidence intervals. We will also examine potential interaction effects potential interactions between independent variables (e.g., biomarkers and demographics).

Anticipated Findings

We anticipate to reveal that elevated levels of biomarkers such as D-dimer, IL-6, IL-10, and CRP are significantly associated with increased odds of intubation. This could underscore the role of systemic inflammation and coagulopathy in disease severity. In the meantime, the we also would like to know the impact of demographic factors that older age, male sex, and specific racial or ethnic groups are more prone to requiring intubation, highlighting demographic disparities in COVID-19 outcomes.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

  • Weize Wang - Project Personnel, Florida International University

Aleena Summer 2024 Project

This workspace will investigate the relationship between COVID-19 infection and the new onset of mental health conditions including anxiety and depression after infection. We hope to determine whether there is a meaningful association between COVID-19 infection and the incidence of…

Scientific Questions Being Studied

This workspace will investigate the relationship between COVID-19 infection and the new onset of mental health conditions including anxiety and depression after infection. We hope to determine whether there is a meaningful association between COVID-19 infection and the incidence of these conditions in participants with no EHR-documented history before infection.

Project Purpose(s)

  • Disease Focused Research (COVID-19, Depression, Anxiety)
  • Educational

Scientific Approaches

We will ascertain diagnoses and time deltas from participant EHR. We will incorporate covariates from PPI (sex at birth, education, race, income, etc...) and potentially from COPE and other follow-up surveys. We will generate descriptive statistics and conduct logistic regression and Cox Proportional Hazards regression using R.

Anticipated Findings

Based on our review of the literature, we think it is possible that we could find a positive association between COVID-19 infection and new onset of anxiety and/or depression. However, we would not be able to discern whether this is due to some real biological mechanism or if the relationship is mediated by personal/socioeconomic variables beyond the scope of this dataset. In other words, we won't be able to tell whether COVID-19 infection somehow predisposes a person to a new mental health disorder, or if the experience of life in a pandemic-era context (which entailed loss of livelihood, alienation, grief, and uncertainty for many) is a greater contributor to the condition. This investigation will be a good start, however, and it is an interesting exercise for this student.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Aleena Syed - Undergraduate Student, University of Chicago

Covid Vaccine Uptake CT

The primary purpose of using All of Us data is to investigate health behaviors, outcomes, access, and disparities in populations. Epidemiologic characterization of covid vaccination uptake among All of Us participants. We plan to explore demographic differences in covid vaccine…

Scientific Questions Being Studied

The primary purpose of using All of Us data is to investigate health behaviors, outcomes, access, and disparities in populations. Epidemiologic characterization of covid vaccination uptake among All of Us participants. We plan to explore demographic differences in covid vaccine uptake, the association between covid vaccination and usual source of care, and the association between the presence of existing morbidities and covid vaccine uptake.

Project Purpose(s)

  • Population Health

Scientific Approaches

The Covid Minute Survey, Healthcare Access & Utilization Survey, The Basics Survey, and the Personal and Family Health History Survey will be used in this project. Rate/odds ratios will be used to characterize differences between groups.

Anticipated Findings

Epidemiologic characterization of covid vaccination uptake among All of Us participants will assist in future analysis of covid vaccine uptake among participants and in an effort to reduce health disparities and improve health equity in underrepresented populations

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Dysphagia/Dysphonia Project

There is limited research on the association of dysphagia and dysphonia in Otolaryngology-Head and Neck surgery research. Dysphagia is a medical condition for difficulty in swallowing. Dysphonia is defined as a condition with an abnormal voice, typically being described as…

Scientific Questions Being Studied

There is limited research on the association of dysphagia and dysphonia in Otolaryngology-Head and Neck surgery research. Dysphagia is a medical condition for difficulty in swallowing. Dysphonia is defined as a condition with an abnormal voice, typically being described as horse, breathy, or raspy. During the COVID-19 pandemic, patients after contracting the disease exhibited increasing symptoms of dysphagia and dysphonia, resulting in worse health outcomes. Those in the fields of communication sciences and disorders saw an increase in cases related to dysphagia and dysphonia, which makes it an opportune time to look more
into the association between these two conditions. Our research will help answer if there is an association between dysphagia and dysphonia and address the prevalence of these conditions in the All of Us dataset.

Project Purpose(s)

  • Population Health

Scientific Approaches

The All of Us dataset will be used to see if there is an association between dysphonia and dysphagia. Using a nested, matched, case-control study, we will develop a multivariable logistic regression model using R. We will identify individuals with dysphonia and dysphagia using SNOMED codes. The demographics will be sourced from the survey data, and the model will be control-matched by age, sex, ethnicity, and race using nearest-neighbor propensity score matching with replacement. To compare rates of comorbidities between cases and controls, we will use Pearson’s chi-squared test for the categorical variables and a one-way ANOVA for continuous variables. We will consider two-sided P<.05 to be significant.

Anticipated Findings

We expect to see an increased odds ratio of dysphagia in patients with dysphonia. Our findings will contribute to past research related to dysphonia, including a past study that found a higher dysphagia occurrence in patients with adductor spasmodic dysphonia after botulinum toxin injections. 1

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Robin Zhao - Undergraduate Student, Cornell University

V7 ARI Workspace - 4-21-23

We now have 4 goals in our research. This workspace is for goals 1 through 3. We have created a new workspace for Goal #4. 1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the…

Scientific Questions Being Studied

We now have 4 goals in our research. This workspace is for goals 1 through 3. We have created a new workspace for Goal #4.

1. Determine prevalence of autoimmune diseases, individually and as a class of disease, in the US.

2. Determine comorbidity of autoimmune diseases, including statistics on comorbidity of other autoimmune diseases and non-autoimmune diseases for each autoimmune disease.

3. Determine the impact of COVID-19 on the autoimmune and autoinflammatory disease population. This work will be conducted in parallel with work we are doing at University of Southern California under an IRB there.

4. Explore the genomic component of autoimmune diseases, particularly among patients with more than one autoimmune disease, so that the underlying mechanisms of disease among these diseases can be better understood.

Project Purpose(s)

  • Disease Focused Research (Autoimmune diseases)
  • Population Health
  • Ancestry

Scientific Approaches

We will create three data sets for analysis:

1. A list of diseases rated in the following ways:

a. Evidence Class
i. Strong evidence it is autoimmune
ii. Moderate evidence it is autoimmune
iii. Weak evidence for autoimmunity
iv. A comorbidity of autoimmune disease
v. Symptom or symptom set with no known mechanism

b. Autoinflammatory versus autoimmune flag

c. “Not always autoimmune” flag – to indicate diseases that could have alternative mechanisms of cause

2. A list of patients, anonymized, with socioeconomic, geographic and other data that would be of interest to patients and public health officials to understand which communities are affected by these diseases
3. Outcomes data for patients over time assessing quality of life using PROMIS metrics

Anticipated Findings

The current NIH estimate of 23.5 million people with autoimmune disease was a guess by a knowledgable clinician, but has no scientific support. As a consequence, there are numerous figures in the public sphere and nobody knows which one is correct.

Many reports say autoimmune diseases are on the increase, but since the number is unknown, it is impossible to say whether this is a public health issue or not. Having a methodology that can be used to recompute the number of people with autoimmune disease will help us understand if these reports are true.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Collaborators:

  • Francis Ratsimbazafy - Other, All of Us Program Operational Use
  • Jun Qian - Other, All of Us Program Operational Use
  • Jeremy Harper - Senior Researcher, Autoimmune Registry
  • Jeffrey Green - Project Personnel, Autoimmune Registry
  • Ingrid He - Project Personnel, Autoimmune Registry
  • Emily Holladay - Project Personnel, Autoimmune Registry
  • Chenchal Subraveti - Project Personnel, All of Us Program Operational Use
  • Boyd Ingalls - Project Personnel, Autoimmune Registry
  • Adnaan Jhetam - Project Personnel, Autoimmune Registry
  • Alexander Burrows - Research Assistant, Autoimmune Registry
  • Jagannadha Avasarala - Other, University of Kentucky

T2D and CVD Outcomes Among Black and Hispanic Populations

The specific scientific research question is: How does type 2 diabetes (T2D) and cardiovascular disease (CVD) affect Black and Hispanic populations in the United States and how does it differ between those with and without COVID-19 and in different regions…

Scientific Questions Being Studied

The specific scientific research question is: How does type 2 diabetes (T2D) and cardiovascular disease (CVD) affect Black and Hispanic populations in the United States and how does it differ between those with and without COVID-19 and in different regions of the United States? These questions will be assessed by investigating:
a. Is there greater prevalence of T2D and CVD outcomes among Black and Hispanic populations with COVID-19 and in different regions of the United States?
b. Are there genetic susceptibilities to T2D, CVD, and COVID-19 among Black and Hispanic populations that impact outcomes and vary by geographic region?

Project Purpose(s)

  • Population Health
  • Social / Behavioral
  • Ancestry

Scientific Approaches

This study will include a cohort of Blacks, Hispanics, and non-Hispanic White participants aged 18 and older. Data included will include data from survey, electronic health records, physical measurements, and genetic data. Descriptive statistics will be calculated, and logistic regression will be used to assess odds ratios for associations. We will analyze common and rare variants from whole-genome sequencing data to control for genetic susceptibility to T2D and CVD.

Anticipated Findings

The anticipated findings from this study will provide a greater insight into the magnitude of the public health burden of COVID-19, T2D,a nd CVD among Blacks and Hispanics and will illustrate the differences in patient profiles and outcomes. Our goal is to make a significant impact in addressing T2D and CVD disparities among Blacks and Hispanics by quantifying the disproportionate effect of COVID-19 on Black and Hispanic T2D and CVD outcomes in different regions of the United States, thereby informing the need for more heath services among these populations The All of Us Research Program Workbench can provide a unique nationwide and U.S. State comparison on these associations.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Geography
  • Access to Care

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Yann Klimentidis - Mid-career Tenured Researcher, University of Arizona
  • Jason Karnes - Early Career Tenure-track Researcher, University of Arizona
  • Grace Leito - Graduate Trainee, University of Arizona
  • Anthony Vicenti - Project Personnel, University of Arizona

Long COVID

We will see if we can identify a cohort of AoU participants who meet the case definition of Long COVID as defined by Thaweethai et al, JAMA 2023. Long COVID is a currently public health concern and may continue to…

Scientific Questions Being Studied

We will see if we can identify a cohort of AoU participants who meet the case definition of Long COVID as defined by Thaweethai et al, JAMA 2023. Long COVID is a currently public health concern and may continue to be significant in the future. Identifying those who may have Long COVID in the AoU dataset will be an important first step toward follow up on their long-term health outcomes.

Project Purpose(s)

  • Disease Focused Research (Long COVID)

Scientific Approaches

Our work will be mainly descriptive. We will create a case definition using standard data builder queries to understand the N of those who may have long COVID, their comorbidities, and their sociodemographic characteristics.

Anticipated Findings

We anticipate that we will not be able to find the exact criteria outlined in Thaweethai et al, but that we will find significant overlap. We anticipate that using an amended case definition, we will be able to to find a cohort of participants with possible Long COVID.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Exploring Covid Vaccine Uptake

Epidemiologic characterization of covid vaccination uptake among All of Us participants. We plan to explore demographic differences in covid vaccine uptake, the association between covid vaccination and usual source of care, and the association between the presence of existing morbidities…

Scientific Questions Being Studied

Epidemiologic characterization of covid vaccination uptake among All of Us participants. We plan to explore demographic differences in covid vaccine uptake, the association between covid vaccination and usual source of care, and the association between the presence of existing morbidities and covid vaccine uptake.

Project Purpose(s)

  • Population Health

Scientific Approaches

The Covid Minute Survey, Healthcare Access & Utilization Survey, The Basics Survey, and the Personal and Family Health History Survey will be used in this project. Rate/odds ratios will be used to characterize differences between groups.

Anticipated Findings

Epidemiologic characterization of covid vaccination uptake among All of Us participants will assist in future analysis of covid vaccine uptake among participants and in an effort to reduce health disparities and improve health equity in underrepresented populations

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Collaborators:

  • Hui Wang - Project Personnel, University of Alabama

The Impact of COVID-19 on Health Equity and Vaccine Efficacy

This question is important for several reasons. Firstly, it addresses a critical gap in current scientific knowledge regarding the impact of COVID-19 on specific ethnic populations, particularly African-American patients. Understanding how the virus affects individuals from different racial backgrounds is…

Scientific Questions Being Studied

This question is important for several reasons. Firstly, it addresses a critical gap in current scientific knowledge regarding the impact of COVID-19 on specific ethnic populations, particularly African-American patients. Understanding how the virus affects individuals from different racial backgrounds is crucial for advancing population health and developing targeted interventions. Secondly, investigating the efficacy of vaccines in populations disproportionately affected by COVID-19, such as African-American patients with pre-existing cardiac conditions, is essential for ensuring equitable access to effective treatments.

Project Purpose(s)

  • Disease Focused Research (SARS-CoV-2 )
  • Population Health
  • Social / Behavioral
  • Drug Development
  • Methods Development
  • Control Set
  • Ancestry
  • Commercial
  • Ethical, Legal, and Social Implications (ELSI)

Scientific Approaches

Investigators will utilize both quantitative and qualitative research methods to address the research questions effectively. The primary datasets we aim to use will include demographic and medical records of African-American patients with pre-existing cardiac conditions who have been diagnosed with COVID-19. These datasets will offer valuable information about the impact of the virus on a specific ethnic population and its correlation with existing health conditions.

Anticipated Findings

The anticipated findings from this study may provide crucial insights into the impact of COVID-19 on African-American patients with pre-existing cardiac conditions and its implications for vaccine efficacy and health disparities. We expect to uncover significant data regarding the prevalence, severity, and outcomes of COVID-19 within this specific population. Additionally, we anticipate gaining valuable information about the effectiveness of vaccines in reducing the burden of the virus and mitigating the impact on individuals with underlying cardiac conditions. Moreover, we aim to identify patterns and associations between demographic factors, health disparities, and the response to vaccination within this population.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

Covid-19 Research

We want to research the spread of COVID-19 and how it affects certain demographics within the All of Us research program. In addition we will look at its linkage to other diseases and its mental health impact.

Scientific Questions Being Studied

We want to research the spread of COVID-19 and how it affects certain demographics within the All of Us research program. In addition we will look at its linkage to other diseases and its mental health impact.

Project Purpose(s)

  • Educational

Scientific Approaches

We would use electronic healthcare data and surveys to move forward on our research. We would also be utilizing the analysis tools t create visualized date.

Anticipated Findings

We expect to see the impacts of Covid-19 on the mental health of patients who contracted the disease. This will help us understand how Covid impacted people and how it is spread by race.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Registered Tier

Research Team

Owner:

591_final_new

This project seeks to delve into the common Fitbit characteristics of patients with long COVID, including heart rate and physical activity.

Scientific Questions Being Studied

This project seeks to delve into the common Fitbit characteristics of patients with long COVID, including heart rate and physical activity.

Project Purpose(s)

  • Educational

Scientific Approaches

We will create a cohort of long COVID patients and obtain summary statistics about their demographic characteristics and Fitbit characteristics.

Anticipated Findings

We will obtain summary characteristics of long COVID patients in terms of heart rate and physical activity. Findings will be compared to findings from clinical intervention studies to better understand long COVID.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Code repository for GPH researchers (Allen W. built under S Cook)

Researcher have shown that there was an increase in discrimination some points of the COVID-19 pandemic. Many researchers have suggested a myriad of reasons why this may be. However, it remains unclear what the correlates and distribution of discrimination experiences…

Scientific Questions Being Studied

Researcher have shown that there was an increase in discrimination some points of the COVID-19 pandemic. Many researchers have suggested a myriad of reasons why this may be. However, it remains unclear what the correlates and distribution of discrimination experiences were for different groups of people. In addition, it is unknown how these experiences increased or decreased during high points in the pandemic. Lastly, it is unclear how social isolation and the disruption in human connection (e.g. with family, friends, etc.) may have been associated with the mental health effects of discrimination during the pandemic. This is of considerable public health significance because we must not only address the mental health needs of those in need, but understand the specific correlates of mental health, such as discrimination, to prevent such an uptick in mental health distress due to discrimination during the next pandemic.

Project Purpose(s)

  • Methods Development

Scientific Approaches

I plan on using the COPE data source from May 2020-February 2021 to examine changes in experiences of discrimination, social isolation, human connection, and mental health. I will utilize hierarchical linear models to asses random and fixed effects, as well as potential mediators and moderators. The COPE has questions related to discrimination experiences in each wave, family connections, social isolation, and mental health. I will also utilize the main survey to access basic sociodemographic information (e.g. race/ethnicity, age, socio economic status, etc.) to utilize as covariates in my analyses.

Anticipated Findings

Based on the extant research literature, I believe that we will find that there is a general uptick in perceived discrimination during COVID. In addition, we hypothesize that as discrimination experiences increase, so does poor mental health. We also hypothesize that social isolation will mediate the longitudinal relationship between perceived discrimination and perceive social isolation and perceived mental health. Lastly, we hypothesize a mediated-moderated model whereby those with perceived positive human connections who experience greater discrimination will report less social isolation and thus less poor mental health compared to those with perceived negative human connections who experience greater discrimination.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Yumeng Ma - Graduate Trainee, New York University
  • Yingzhu Chen - Graduate Trainee, New York University
  • Yuhan Cui - Graduate Trainee, New York University
  • Xinyue Du - Graduate Trainee, New York University
  • Yiwen Chen - Graduate Trainee, New York University
  • Hsing-Chun Wang - Graduate Trainee, New York University
  • Tingjia Shi - Graduate Trainee, New York University
  • Sixian Ju - Graduate Trainee, New York University
  • Sherry Wu - Graduate Trainee, New York University
  • Sydney Hagley-Alexander - Graduate Trainee, New York University
  • Sandy Carrillo-Argueta - Project Personnel, New York University
  • Rebecca Yu - Graduate Trainee, New York University
  • Jose Pagan - Late Career Tenured Researcher, New York University
  • Jingwen Lei - Graduate Trainee, New York University
  • Emma Risner - Graduate Trainee, New York University
  • Naiyue Liang - Graduate Trainee, New York University
  • Yu-Ju Wang - Graduate Trainee, New York University
  • Binyu Cui - Graduate Trainee, New York University
  • Antoneta Karaj - Graduate Trainee, New York University
  • Jingxuan Evelyn Ma - Graduate Trainee, New York University
  • Vivian Hsing-Chun Wang - Research Fellow, New York University, Grossman School of Medicine
  • Cindy Patippe - Graduate Trainee, New York University

WCUCOMAOUGroup5

This project aims to examine the heterogeneous health impacts of food insecurity in the diabetes mellitus type 2 (T2DM) population during the COVID-19 pandemic lockdown. Food insecurity is a public health concern for many reasons that are well documented. It…

Scientific Questions Being Studied

This project aims to examine the heterogeneous health impacts of food insecurity in the diabetes mellitus type 2 (T2DM) population during the COVID-19 pandemic lockdown. Food insecurity is a public health concern for many reasons that are well documented. It can be particularly burdensome for the T2DM population due to its need to access specific foods to adequately manage insulin levels. The lockdowns following the onset of the COVID-19 pandemic may have exacerbated pre-existing food insecurity or caused locations that previously had good food access to become “food deserts.” These factors will likely precipitate a change in dietary patterns, affecting glycemic control in T2DM patients. The paucity of such research focusing on US demographics, particularly in Mississippi, also underscores a need to investigate the link between food insecurity in COVID pandemic and diabetes management.

Project Purpose(s)

  • Disease Focused Research (type 2 diabetes mellitus)
  • Population Health

Scientific Approaches

We would like to investigate how food insecurity affected the Mississippi population during the peak COVID-19 social distancing period (Mar 2020 – Mar 2022). We will group diabetes patients into a food-secure group and a food-insecure group using answers from Social Determinants of Health survey. We will use HbA1c data from Feb 2018 to Feb 2020 for pre-COVID period as baseline and compare that with the data of the same patients from Mar 2020 to Mar 2022. We will also compare the eating behavior during COVID and medication adherence due to financial concerns between the two groups using additional survey questions. Demographic information such as race, sex, gender, education, employment, and income level from the Basics Survey will be used to control for confounding factors in the analysis and any statistically significant trends will be reported. Additionally, we would like to conduct a specific analysis focusing on the African-American patient population in Mississippi.

Anticipated Findings

We expect that patients with diabetes in the food insecure group experienced a greater increase in their HA1c and more diabetic complications than the those in the food secure group during COVID-19. The findings will aid in our understanding of rising HA1c levels in relation to food insecurity focusing on an underrepresented population in research and can shed light on disease prevention during a pandemic in such a vulnerable population. The outcome of our research may provide insights on reducing health disparity and improving health equity in an underrepresented population.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Daniel Thompson - Graduate Trainee, William Carey University

591_final

This project seeks to delve into the common Fitbit characteristics of patients with long COVID, including heart rate and physical activity,

Scientific Questions Being Studied

This project seeks to delve into the common Fitbit characteristics of patients with long COVID, including heart rate and physical activity,

Project Purpose(s)

  • Educational

Scientific Approaches

We will create a cohort of long COVID patients and obtain summary statistics about their demographic characteristics and Fitbit characteristics.

Anticipated Findings

We will obtain summary characteristics of long COVID patients in terms of heart rate and physical activity. Findings will be compared to findings from clinical intervention studies to better understand long COVID.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

T2DB and Food Insecurity

How did food insecurity affect Type 2 diabetes mellitus (T2DM) patients’ HbA1c levels and T2DM complication rates during the peak COVID-19 social distancing period (March 2020 - March 2022) in Mississippi? This project aims to examine the heterogeneous health impacts…

Scientific Questions Being Studied

How did food insecurity affect Type 2 diabetes mellitus (T2DM) patients’ HbA1c levels and T2DM complication rates during the peak COVID-19 social distancing period (March 2020 - March 2022) in Mississippi?
This project aims to examine the heterogeneous health impacts of food insecurity in the Type 2 diabetes mellitus (T2DM) population during the COVID-19 pandemic lockdown. Food insecurity is a public health concern for reasons that are well documented (Martin, 2023). It can be particularly burdensome for the T2DM population due to their need to access specific foods to adequately regulate insulin levels (Ippolito et al., 2016). The lockdowns following the onset of the COVID-19 pandemic may have exacerbated pre-existing food insecurity or caused locations that previously had good food access to become “food deserts.” These factors will likely precipitate a change in dietary patterns, affecting glycemic control in patients with T2DM.

Project Purpose(s)

  • Population Health

Scientific Approaches

We recognize the multifaceted psycho-social behavioral aspects influencing glycemic control in patients with T2DM, as well as the complex nature of the pathophysiology of T2DM, including how the population's predisposition to SARS-CoV-2 infection contributes to their poor glycemic levels (Lim et al., 2020). An understanding of these additional factors will help us identify and control the potential confounding variables in our study. The dependent variables we will compare between those two groups are the changes in HbA1c lab results and the rate of developing diabetic complications such as diabetic ketoacidosis, hyperglycemia, and diabetic neuropathy (please refer to ICD-10 codes below) between the pre and peak COVID-19 period. The HbA1c and the diabetic complication data are available in the Lab & Measurements section and the Condition section within the EHR Domain from All of Us, respectively.

Anticipated Findings

We hypothesize that patients with diabetes who are in the food-insecure group experienced a greater increase in their HbA1c and the number of diabetic complications than the food-secure group during COVID-19.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

Duplicate of Impact of COVID-19 on the Hispanic Community

This Workspace will be used for the “Impact of COVID-19 on the Hispanic Community” Driver Project, that will go beyond validation and result in novel findings. The study aims to replicate findings from the following articles: “COVID-19 Pandemic: Disparate Health…

Scientific Questions Being Studied

This Workspace will be used for the “Impact of COVID-19 on the Hispanic Community” Driver Project, that will go beyond validation and result in novel findings. The study aims to replicate findings from the following articles: “COVID-19 Pandemic: Disparate Health Impact on the Hispanic/Latinx Population in the United States” (Gil et al. 2020), “Life in the Time of COVID-19: a Case Study of Community Health” (Schelly 2021), “Racial/Ethnic Disparities In COVID-19 Exposure Risk, Testing, And Cases At The Subcounty Level In California” (Reitsma et al. 2021), that shed light on how COVID-19 has disproportionately affected the Hispanic community in the United States. We will focus on replicating the findings as they relate to the social determinants of health (SDOH) such as income, education, coexisting medical conditions such as obesity and diabetes, lack of access to health care, language barriers, working conditions, and living conditions.

Project Purpose(s)

  • Social / Behavioral

Scientific Approaches

1. Has the Hispanic community been disproportionately affected by COVID-19?
What is the impact COVID-19 has had on the U.S. Hispanic Community?

2. What role have social determinants of health, such as income, education, and access to health care, played in the disproportionate effect of COVID-19 on the Hispanic community?

Anticipated Findings

We expect that the Hispanic cohort in the All of Us Research Program reflects the disproportionate effect of COVID-19 on the Hispanic community found in the aforementioned articles. We expect to see that a large proportion of Hispanics will have had COVID-19, or known someone who did, or lack access to healthcare facilities in the event of a COVID-19 infection, based on COPE Survey findings. These findings would reinforce the importance of taking social determinants of health into account when creating policy relating to access to health care and safety net programs for the Hispanic community in the United States.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

Medical Health Disparities

The research question I hope to answer is; "what are the factors that lead to medical health disparities in minority communities?" As a historian medical mistrust in African American communities are long documented from experimentations during slavery to the Tuskegee…

Scientific Questions Being Studied

The research question I hope to answer is; "what are the factors that lead to medical health disparities in minority communities?" As a historian medical mistrust in African American communities are long documented from experimentations during slavery to the Tuskegee and Covid 19 testing. This question is important because it will provide a glimpse into why people in minority communities specifically African American communities are neglected by some medical professionals, why they are misdiagnosed and over prescribed medication that conflicts with other prescribed medications. I would also like to look at what changes can be made to combat disparities and mistrust.

Project Purpose(s)

  • Educational

Scientific Approaches

I plan on looking at the datasets in the All of us Research portal pertaining to race, social economic background, medical information about illnesses that plague minority communities the most and the treatment based on race. I also plan to research the comfort level minorities feel with the medical profession. My plan is to focus on three deep south states Louisiana, Mississippi, Alabama.

Anticipated Findings

Anticipated findings are that most African Americans are not comfortable with medical professions because they feel like their life is being judged. They also mistrust people in the medical profession that are not from a similar racial background as them. These factors and more lead to medical mistrust and health disparities amongst minority groups.

Demographic Categories of Interest

  • Age
  • Geography
  • Education Level
  • Income Level

Data Set Used

Registered Tier

Research Team

Owner:

WCUCOMAOUGroup4

Which demographics became more susceptible to substance use disorders during the COVID-19 pandemic? This research question is important for many reasons. It can give public health officials inside into the groups that should be targeted for intervention and resource allocation,…

Scientific Questions Being Studied

Which demographics became more susceptible to substance use disorders during the COVID-19 pandemic? This research question is important for many reasons. It can give public health officials inside into the groups that should be targeted for intervention and resource allocation, or it can help formulate and expand preventative and treatment plans and programs for the groups most affected. In addition, with more information healthcare workers can respond faster to SUD. Identifying and addressing disparities in SUD can also promote social equity after the the pandemic may have exacerbated existing inequalities. The pandemic caused significant mental health challenges and by studying its impact on substance use disorders, researches can gain a more thorough understanding of the correlation between mental health crises and substance abuse.

Project Purpose(s)

  • Population Health
  • Social / Behavioral

Scientific Approaches

The AoU COPE survey will be used along with datasets on admission into hospitals, rehabs, and other facilities for substance use disorders.

Anticipated Findings

It is anticipated that the COVID-19 Pandemic did result in a rise in substance use disorders and the demographics that were hit the hardest would be the most likely to result in higher SUD rates. Minority groups and finically insecure people would have been the hardest hit and therefore anticipated to have higher SUD rates.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Geography
  • Disability Status
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Controlled Tier

Research Team

Owner:

Re-purposing Computable Phenotypes for Public Health Disease Surveillance

This study proposes a novel application for a well-established method of cohort identification in biomedical research, known as computable phenotyping, for EHR-based public health surveillance of chronic diseases. At the core of the proposed research study is the repurposing of…

Scientific Questions Being Studied

This study proposes a novel application for a well-established method of cohort identification in biomedical research, known as computable phenotyping, for EHR-based public health surveillance of chronic diseases. At the core of the proposed research study is the repurposing of already developed and validated EHR-based computable phenotyping algorithms for disease surveillance while assessing those algorithms’ transferability or portability to two national data repositories, All of Us Research Program and National COVID Cohort Collaborative (N3C), and establishing the concordance between repurposed computable phenotypes within and across two distinct data networks. The outcome measure for evaluating computable phenotype performance will be disease prevalence estimates.

Project Purpose(s)

  • Disease Focused Research (diabetes, depression, dementia, asthma, hypertension, breast cancer, lung cancer)
  • Population Health
  • Educational
  • Methods Development
  • Control Set

Scientific Approaches

EHR data will be used to apply algorithms designed for patient cohort identification from a number of large research networks (eMERGE/PheKB, PCORnet, OHDSI and MDPHnet ) to ascertain disease prevalence estimates for a number of chronic diseases and conditions. Performance of re-purposed algorithms will be compared within All of Us and between All of Us and N3C. Prevalence estimates will be validated against those from the most recent traditional national surveillance surveys (i.e. American Community Survey, NHANES, BRFSS).

Anticipated Findings

Using computable phenotyping algorithms for disease surveillance is a novel application. Re-using already developed and validated algorithms for disease surveillance is also a novel approach which would maximize the utility of resources spent in developing and validating each algorithm.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

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