Research Projects Directory

Genomics of infectious disease susceptibility

Despite increasing evidence of the role of host genetics in infectious diseases, most genomics studies have been limited to a few pathogens (HIV infection, TB, malaria, viral hepatitis, and recently COVID-19) and populations of European ancestry. We aim to narrow…

Scientific Questions Being Studied

Despite increasing evidence of the role of host genetics in infectious diseases, most genomics studies have been limited to a few pathogens (HIV infection, TB, malaria, viral hepatitis, and recently COVID-19) and populations of European ancestry. We aim to narrow this gap by expanding the repertoire of studies to all infectious diseases for which we have at least 50 case numbers in All of Us and to diverse genetic ancestries.

Project Purpose(s)

Disease Focused Research (disease by infectious agent)
Population Health
Ancestry

Scientific Approaches

In brief, we will: Perform common and rare variant testing using All of Us genotyping and exome-sequencing data respectively. We aim to use SAIGE to conduct variant testing to understand genomic loci contributing to infectious disease susceptibility. Diseases will be defined on the basis of PhecodeX definitions, which are derived from ICD10 and ICD9 codes. For increased statistical power we will conduct a similar analysis on BioMe and Pan UK Biobank and subsequently meta-analyze the results with results from All of Us.

Anticipated Findings

Overall, leveraging the combined cohort from all three biobanks would enable us to discover novel associations in previously unexplored disease and understudied populations which paves the way to develop risk prediction scores and new therapies. Utilizing diverse biobanks will allow us to map ancestry-specific markers that influence infectious disease susceptibility. Our results will contribute not only to infectious disease research but also to the broader mission of supporting diversity in genomics. The completion of this project will open multiple routes for future exploration including scope for development of targeted preventive measures and personalized therapeutics and prophylactics.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Abhijith Biji - Graduate Trainee, Icahn School of Medicine at Mount Sinai

Collaborators:

Samira Asgari - Early Career Tenure-track Researcher, Icahn School of Medicine at Mount Sinai
jane Brown - Research Assistant, Icahn School of Medicine at Mount Sinai

Hampton Research hub_covid_study

Background: COVID-19 infection scars the lungs with the potential for lung tissue scarring. Scarring causes restrictive lung impairment. Long-term pulmonary sequelae of COVID-19 include: Research Question: What is the Association between COVID-19 infection and lung function impairment among apparently healthy…

Scientific Questions Being Studied

Background:
COVID-19 infection scars the lungs with the potential for lung tissue scarring. Scarring causes restrictive lung impairment.
Long-term pulmonary sequelae of COVID-19 include:

Research Question: What is the Association between COVID-19 infection and lung function impairment among apparently healthy adults?

Aims of the study:
1. To investigate the association between COVID-19 infection and lung function impairment among apparently healthy adults.
2. Estimate the magnitude of the association between COVID-19 infection and lung function impairment among apparently healthy adults.

Project Purpose(s)

Disease Focused Research (severe acute respiratory syndrome)
Population Health
Social / Behavioral
Educational

Scientific Approaches

Participants
Selection Criteria
Inclusion: Adult (above 18 years)

Exclusion: history of acute lung disease; history of chronic lung diseases;

Measurements
Outcome: Lung function impairment

Exposure: History of COVID-19

Covariates: Physical activity level, severity of COVID infection, frequency of infection, vaccination status, race, gender, smoking status, residential zip code, health insurance information, education, income bracket, blood pressure, previous hospitalization, comorbidity,

Anticipated Findings

Our findings will
1. Show the influence of previous covid infections on lung infection impairments.
2. Help to identify individuals at risk of chronic lung disease
3. Evaluate predictors of severe lung impairment among individuals with COVID-19 infection

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Joseph Aneke - Early Career Tenure-track Researcher, Hampton 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:

Aaron Abend - Senior Researcher, Autoimmune Registry

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

Duplicate of Discrimination, Depression, Suicide

As part of a grad school course, we plan to look at the association of everyday discrimination during COVID with depressive and suicidal symptoms.

Scientific Questions Being Studied

As part of a grad school course, we plan to look at the association of everyday discrimination during COVID with depressive and suicidal symptoms.

Project Purpose(s)

Population Health
Social / Behavioral
Educational

Scientific Approaches

We will use the COVID-19 Participant Experience (COPE) survey and the Patient Health Questionnaire (PHQ-9). We will conduct mixed effects modeling and lagged analyses. We may also conduct mediation analyses.

Anticipated Findings

We anticipate that people who experience higher levels of discrimination will be more likely to have increased symptoms of depression and suicidality.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Sarah Lee - Graduate Trainee, University of Massachusetts Medical School
Inbar Plaut - Research Fellow, University of Massachusetts Medical School

Collaborators:

Alexander Wilkins - Other, University of Massachusetts Medical School

Discrimination, Depression, Suicide

As part of a grad school course, we plan to look at the association of everyday discrimination during COVID with depressive and suicidal symptoms.

Scientific Questions Being Studied

As part of a grad school course, we plan to look at the association of everyday discrimination during COVID with depressive and suicidal symptoms.

Project Purpose(s)

Population Health
Social / Behavioral
Educational

Scientific Approaches

We will use the COVID-19 Participant Experience (COPE) survey and the Patient Health Questionnaire (PHQ-9). We will conduct mixed effects modeling and lagged analyses. We may also conduct mediation analyses.

Anticipated Findings

We anticipate that people who experience higher levels of discrimination will be more likely to have increased symptoms of depression and suicidality.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Sarah Lee - Graduate Trainee, University of Massachusetts Medical School

Collaborators:

Inbar Plaut - Research Fellow, University of Massachusetts Medical School
Alexander Wilkins - Other, University of Massachusetts Medical School

Materials and Methods COVID-19

During our research, we plan to utilize Genome-wide Association studies (GWAS). This is a powerful approach to identify genetic variants associated with specific traits or diseases. Researchers can analyze large datasets comprising the genomes of individuals with severe COVID-19 symptoms…

Scientific Questions Being Studied

During our research, we plan to utilize Genome-wide Association studies (GWAS). This is a powerful approach to identify genetic variants associated with specific traits or diseases. Researchers can analyze large datasets comprising the genomes of individuals with severe COVID-19 symptoms compared to those with mild or asymptomatic cases to pinpoint genetic variations linked to susceptibility.

Project Purpose(s)

Educational

Scientific Approaches

During our research, we plan to utilize Genome-wide Association studies (GWAS). This is a powerful approach to identify genetic variants associated with specific traits or diseases. Researchers can analyze large datasets comprising the genomes of individuals with severe COVID-19 symptoms compared to those with mild or asymptomatic cases to pinpoint genetic variations linked to susceptibility.

Anticipated Findings

During our research, we plan to utilize Genome-wide Association studies (GWAS). This is a powerful approach to identify genetic variants associated with specific traits or diseases. Researchers can analyze large datasets comprising the genomes of individuals with severe COVID-19 symptoms compared to those with mild or asymptomatic cases to pinpoint genetic variations linked to susceptibility.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

David Santana - Undergraduate Student, Arizona State University

Bonus project

How does genetic variation among individuals influence susceptibility to severe covid-19 symptoms and long-term health outcomes?

Scientific Questions Being Studied

How does genetic variation among individuals influence susceptibility to severe covid-19 symptoms and long-term health outcomes?

Project Purpose(s)

Population Health
Educational
Ancestry

Scientific Approaches

Genome-wide Association Studies (GWAS): GWAS is a powerful approach to identify genetic variants associated with specific traits or diseases. Researchers can analyze large datasets comprising the genomes of individuals with severe COVID-19 symptoms compared to those with mild or asymptomatic cases to pinpoint genetic variations linked to susceptibility.

Anticipated Findings

identify specific genes responsible for its virulence, transmission, and interaction with the human immune system

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

madison maria - Undergraduate Student, Arizona State University

Social distancing and mental health

During the COVID-19 pandemic, social distancing emerged as a crucial public health measure. While effective in reducing transmissions, it inadvertently placed strains on mental health. This study examines how two coping mechanisms—increased media consumption and maintenance of social connections—moderate the…

Scientific Questions Being Studied

During the COVID-19 pandemic, social distancing emerged as a crucial public health measure. While effective in reducing transmissions, it inadvertently placed strains on mental health. This study examines how two coping mechanisms—increased media consumption and maintenance of social connections—moderate the adverse impacts of social distancing on mental health. We will conduct regression and moderation analyses using data from the All of Us research program, one of the most diverse health databases in history.
H1: Increased social distancing correlates with worse mental health.
RQ1: Does heightened media consumption moderate the relationship between social distancing and mental health?
RQ2: Does maintaining social connections moderate the relationship between social distancing and mental health?

Project Purpose(s)

Population Health
Social / Behavioral

Scientific Approaches

We plan to use the COVID-19 Participant Experience survey, part of the All of Us research program (NIH, 2024).
We plan to conduct regression and moderating analyses.

Measures
Demographic factors (e.g., age, gender, ethnicity, education) were included in the study.

Social distancing was assessed by asking participants’ social habits in the last five days, including frequency of staying at home, attending large social gatherings, wearing a facemask/covering, and social interactions with people outside their home.

Mental health was assessed by asking participants how often they felt nervous, anxious, on edge, down, depressed, or hopeless over the last two weeks.

Increased media consumption was measured by asking participants whether they were increasing watching, reading, or listening to news stories, including social media.

Maintaining social connections was measured by asking participants whether they were connecting with others, including talking with people they trust.

Anticipated Findings

This study will reveal the role of two communication-related coping behaviors in either amplifying or alleviating the adverse effects of social distancing on mental health. Findings will contribute to the health communication literature and provide valuable insights for developing communication strategies to address the crises posed by infectious disease outbreaks.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Cindy Chen - Teacher/Instructor/Professor, Sam Houston State University

Collaborators:

Promethi Das Deep - Graduate Trainee, Sam Houston State University
Alexandra Andrews - Undergraduate Student, Sam Houston State University

Heart Disease

We are intending to study the effects of COVID 19 on heart disease between male and female young adults (18-24).

Scientific Questions Being Studied

We are intending to study the effects of COVID 19 on heart disease between male and female young adults (18-24).

Project Purpose(s)

Disease Focused Research (heart disease)
Population Health
Educational
Methods Development
Control Set
Ancestry

Scientific Approaches

We are going to seek the trends on patients that contracted COVID19 that has also been diagnosed of heart disease and see if there are any significant risks that it imposed on these male and female young adults (18-24).

Anticipated Findings

We anticipate that COVID 19 has a significant effect on the male and female young adults (18-25) that have already been diagnosed with heart disease. We hope that our findings can identify what the extent of COVID 19 has affected the individual's immune system as well as the extent of how it worsens their current condition.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Francis Xavier Malinao - Undergraduate Student, Arizona State University

Collaborators:

nikka encinas - Undergraduate Student, Arizona State University

Disparities in Surgical Care

During the COVID-19 recovery phase, did the demographics of patients presenting for and receiving surgical care shift disparately? The COVID-19 pandemic caused dramatic shifts in surgical and procedural care, with many hospitals acutely limiting elective surgeries/procedures to reduce exposures. However,…

Scientific Questions Being Studied

During the COVID-19 recovery phase, did the demographics of patients presenting for and receiving surgical care shift disparately? The COVID-19 pandemic caused dramatic shifts in surgical and procedural care, with many hospitals acutely limiting elective surgeries/procedures to reduce exposures. However, after the pandemic, hospitals rapidly restored surgical volume to meet the backlog of cases, entering recovery phases. The impact of SDOH on access to care is increasingly recognized across a range of surgeries and procedures, and the pandemic accentuated SDOH, with Black and Latinx Americans in particular suffering disproportionate infection/mortality rates. While surgical volume recovered during the COVID-19 recovery phase, the impact of pandemic-induced changes in access to surgical care during the recovery phase has not been well described. By understanding if any demographic changes exist, health systems can develop strategies to ensure equitable access to elective surgical care.

Project Purpose(s)

Population Health

Scientific Approaches

Our analysis will focus on the All of Us database and Social Determinants of Health surveys. We will use statistical software packages in R and Python, including libraries like Pandas, NumPy, and SciPy, or SAS for data manipulation, analysis, and visualization. We will also use machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch for implementing machine learning algorithms to detect significant predictors. We will also aim to use geospatial analysis tools like ArcGIS or QGIS to investigate neighborhood-level factors. We will use the United States Census Bureau 2014–2018 American Community Survey 5–year Estimates were used to determine ZIP code median income. We may also incorporate area deprivation index information into our study.

Anticipated Findings

This study will aim to examine whether the demographics of patients presenting and receiving elective surgical care shifted during the pandemic acute and recovery phases. As operating room volume was restored in the COVID-19 recovery phase, we expect to see that the demographics of patients presenting for and receiving surgical care shifted disparately among different race/ethnicity and socioeconomic groups.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Laleh Jalilian - Mid-career Tenured Researcher, University of California, Los Angeles

Collaborators:

Daniel Brannock - Senior Researcher, All of Us Researcher Academy/RTI International

Education exersice

How do SDOH influence individuals' mental well-being in the context of a public health crisis, such as the COVID-19 pandemic? Our primary objective is to accurately pinpoint individuals who are most susceptible to experiencing mental health issues based on specific…

Scientific Questions Being Studied

How do SDOH influence individuals' mental well-being in the context of a public health crisis, such as the COVID-19 pandemic?

Our primary objective is to accurately pinpoint individuals who are most susceptible to experiencing mental health issues based on specific social determinants of health. These determinants include but are not limited to, the safety of the neighborhood they live in, social support that they receive from their peers, discrimination that they may be subjected to, loneliness, and food insecurity. By identifying these factors, we can proactively anticipate and provide support to individuals at the highest risk of experiencing mental health challenges, especially during critical periods of vulnerability, such as those experienced during the COVID-19 pandemic. This project seeks to uplift and empower vulnerable communities, acknowledging the importance of a collective and compassionate response to mental health challenges in the face of adversity.

Project Purpose(s)

Disease Focused Research (Mental Health)
Population Health
Social / Behavioral

Scientific Approaches

Our approach involves a multi-step process to investigate how social determinants of health (SDoH) contribute to the worsening of mental health during a public health crisis. First, we will conduct a detailed descriptive data analysis to better understand the information and its characteristics. This will involve examining various factors that are available for participants, such as age, gender, socioeconomic status, and SDoH. After completing the descriptive analysis, we will implement linear mixed models to identify individuals at high risk of poor mental health outcomes overall and over time during the pandemic. Specifically, we will explore the relationship between these waves, SDoH, and mental health outcomes. This will allow us to better understand the impact of the pandemic on mental health and identify factors that may be contributing or aggravating to mental health decline.

Anticipated Findings

Our hypothesis is that social determinants of health (SDoH) have a significant impact on mental health, and that the effect is not limited to a single SDoH factor. Instead, we expect to see that a combination of these factors can contribute to the decline of participants' mental health. These factors may include socioeconomic status, access to healthcare, education, employment, housing, and social support. By analyzing the data collected, we hope to gain a better understanding of how multiple SDoH factors interact and affect mental health outcomes.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

yury garcia - Research Fellow, University of California, Davis
kuang li - Graduate Trainee, University of California, Davis

V7 ARI Genomics Workspace - 4-21-23

We now have 4 goals in our research - this workspace has been created specifically 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,…

Scientific Questions Being Studied

We now have 4 goals in our research - this workspace has been created specifically 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)
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
4. We will develop statistics analyzing the association of variants known to affect autoimmune diseases for specific diseases to see if those variants corelate with other autoimmune diseases.

Anticipated Findings

There are recognized associations between specific gene variants and some autoimmune diseases. We are going to explore whether those associations can be found in other autoimmune and autoinflammatory diseases. We hope this work can uncover the common mechanisms that underlie autoimmune conditions that appear to be unconnected but which are comorbid.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Aaron Abend - Senior Researcher, Autoimmune Registry

COVID-19 and Wearables CTDv6

Our primary goal is to understand the interaction between activity levels and the development, progression, and societal effects of COVID-19. These analyses will generate hypotheses guiding clinical and research interventions focused on activity and sleep to reduce morbidity and mortality…

Scientific Questions Being Studied

Our primary goal is to understand the interaction between activity levels and the development, progression, and societal effects of COVID-19. These analyses will generate hypotheses guiding clinical and research interventions focused on activity and sleep to reduce morbidity and mortality in patients seeking care.

Project Purpose(s)

Population Health
Social / Behavioral

Scientific Approaches

We will examine the relationship between daily activity (steps, activity intensity) over time and the prevalence of COVID-19. We will use the Fitbit data, EHR-curated diagnoses, laboratory values, quality of life survey results, and clinical outcomes (hospitalizations/mortality).

Anticipated Findings

We may find substantial variation in activity and disease prevalence/severity by socioeconomic status and/or location which would motivate studies/interventions to reduce these health disparities.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Runqi Yuan - Graduate Trainee, Vanderbilt University
Jeffrey Annis - Other, Vanderbilt University Medical Center

Collaborators:

Laleh Jalilian - Mid-career Tenured Researcher, University of California, Los Angeles
STACY DESINE - Project Personnel, Vanderbilt University Medical Center
Hiral Master - Project Personnel, All of Us Program Operational Use
Aymone Kouame - Other, All of Us Program Operational Use

AUD_MH_Genomics_v7_v2

Our scientific question is about the health disparity in alcohol use disorder (AUD), substance use disorder (SUD), and mental health, as well as the impact of the COVID pandemic on such health disparity. The COVID pandemic has been bringing financial,…

Scientific Questions Being Studied

Our scientific question is about the health disparity in alcohol use disorder (AUD), substance use disorder (SUD), and mental health, as well as the impact of the COVID pandemic on such health disparity. The COVID pandemic has been bringing financial, social, and psychological burdens, which are known risk factors for SUD and mental problems. Populations from minority groups, being socioeconomically disadvantaged, of younger ages, or with limited access to corresponding health care are at particularly higher risk of developing SUD or mental problems. Adolescents and young adults are also at higher risk. The understanding of how social determinants of health (SDoHs) are associated with the risk of new SUD and mental health problems will help better support the high-risk populations during and after the COVID pandemic.

Project Purpose(s)

Disease Focused Research (Alcohol use disorder, substance use disorder, and mental health )
Population Health
Social / Behavioral
Drug Development
Methods Development
Ancestry
Ethical, Legal, and Social Implications (ELSI)

Scientific Approaches

We plan to use the survey data, including the COVID-19 Participant Experience (COPE), the Basics, the Personal Medical History, the Family Heath History as well as the Conditions in EHR Domain data set and the genetics data to identify newly developed SUD and mental health issues occurred during the COVID-19 pandemics as well as SDoHs and other major risk factors. Logistic regression models will be used to identify the major risk factors. We will also explore whether graph artificial intelligence models can be used to disentangle the effects of SDoHs from other risk factors.

Anticipated Findings

We expect to quantitatively identify major risk factors, especially SDoHs, for AUD/SUD and for mental health issues. Such knowledge can help better understand the health disparity as well as impact of COVID on public health. A prediction model will also be developed to identify high-risk populations.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Jing Su - Early Career Tenure-track Researcher, Indiana University

Collaborators:

Yao Chen - Graduate Trainee, Indiana University
Chenxi Xiong - Graduate Trainee, Indiana University
Tae-Hwi An - Early Career Tenure-track Researcher, Indiana University
Shihui Jiang - Project Personnel, Indiana University
Netsanet Gebregziabher - Project Personnel, Indiana University
Baifang Zhang - Project Personnel, Indiana University
Haining Wang - Project Personnel, Indiana University
Jiangqiong Li - Project Personnel, Indiana University
Dongbing Lai - Project Personnel, Indiana University
Colin Hoffman - Project Personnel, Indiana University
Allison Gatz - Graduate Trainee, Indiana University
Chi Nguyen - Project Personnel, Indiana University

SJSU All of Us Research

How has depression rates changed after the pandemic among under represented groups? The research will expand on the Choi et al (2023) article looking at social support and depression during the global pandemic. By expanding on the study, we can…

Scientific Questions Being Studied

How has depression rates changed after the pandemic among under represented groups? The research will expand on the Choi et al (2023) article looking at social support and depression during the global pandemic. By expanding on the study, we can see if there was any significant changes or no change after COVID 19.

Project Purpose(s)

Social / Behavioral
Educational
Methods Development

Scientific Approaches

We will use the All of Us Research dataset in order to answer the question. We are specifically looking at the COPE survey dataset for our research question. We will use statistical analysis programs such as R in order to analyze the data.

Anticipated Findings

The anticipated findings will be that depression rates will be significantly lower after the pandemic. This gives insight on depression rates after the pandemic and show if anything changed years after the global crisis.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Kyle Amores - Graduate Trainee, San Jose State University

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:

Thamer Alnazzal - Graduate Trainee, University of Houston
Roshan Dongre - Graduate Trainee, Houston Methodist Research Institute
Najm Khan - Graduate Trainee, Rutgers, The State University of New Jersey
lichang zhu - Graduate Trainee, University of Houston
Faizaan Khan - Graduate Trainee, Houston Methodist Research Institute
Ying Lin - Early Career Tenure-track Researcher, University of Houston
Boaz Adikaibe - Undergraduate Student, University of Houston
Aatin Dhanda - Graduate Trainee, Rutgers, The State University of New Jersey
Sai Phani Ram Popuri - Graduate Trainee, University of Houston
Muyun Lu - Graduate Trainee, University of Houston

COPE Survey Data Tutorial Example

This workspace is meant for me to familiarize how this application works. I will be following the tutorials provided from All of Us to understand how to utilize this platform to conduct and analyze research. The notebooks explores multiple questions…

Scientific Questions Being Studied

This workspace is meant for me to familiarize how this application works. I will be following the tutorials provided from All of Us to understand how to utilize this platform to conduct and analyze research. The notebooks explores multiple questions across the following 17 survey topics: - Social Distancing Experiences - COVID-19 Related Symptoms - COVID-19 Related Impact - COVID-19 Related Testing - COVID-19 Related Treatment - Vaccine Perceptions - General Well-Being - Basic Information - Social Support - Anxiety - Mood - Stress - Physical Activity - Loneliness - Substance Use - Resilience - Discrimination.

Project Purpose(s)

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

Scientific Approaches

I am exploring the notebooks in this workspace to learn the basics of All of Us Program Data. By running the notebooks in this workspace, I should get familiar with how to query the COPE questions/surveys, what the frequencies of answers for each question in the module are.

Anticipated Findings

By reading and running the notebooks in this Tutorial Workspace, I will attempt to learn the following: how to query the COPE survey data in Python and R. This will help me to query and include COPE survey data into their own projects.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Anshika Jaiswal - Undergraduate Student, San Jose State University

Duplicate of Covid-19 vaccine uptake among cancer survivors V

The purpose of the study is to evaluate the modifiable, multilevel factors associated with COVID-19 vaccine uptake among cancer survivors from the All of Us dataset.

Scientific Questions Being Studied

The purpose of the study is to evaluate the modifiable, multilevel factors associated with COVID-19 vaccine uptake among cancer survivors from the All of Us dataset.

Project Purpose(s)

Disease Focused Research (cancer)
Population Health
Social / Behavioral

Scientific Approaches

A cohort of cancer survivors will be from using the database. Various survey questions will aid in answering our research aims. In addition, the covid-19 survey questionnaires will also be used to determine our outcome of interest.

Anticipated Findings

Multilevel factors are anticipated to be associated with vaccine uptake and hesitance. These results can help to identify specific characteristics of cancer survivors that make them more or less likely to experience vaccine hesitancy and inform efforts to target, adapt and tailor interventions to their needs.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Angel Arizpe - Graduate Trainee, University of Southern California

Collaborators:

Katelyn Queen - Graduate Trainee, University of Southern California
Alberto Carvajal Jr - Graduate Trainee, University of Southern California
Albert Farias - Early Career Tenure-track Researcher, University of Southern California

Duplicate of Homeless project(Data- V7)-Final_after_error

To find the Correlation of different previous disease history with Covid-19 hospitalization among homeless people.

Scientific Questions Being Studied

To find the Correlation of different previous disease history with Covid-19 hospitalization among homeless people.

Project Purpose(s)

Educational

Scientific Approaches

I want to apply various machine learning ,data analysis and statistical technique so That I can find out correlation of different previous disease history with Covid-19 hospitalization among homeless people.

Anticipated Findings

I have found that COPD, smoking history and certain diseases play a pivotal role in Covid-19 hospitalizations.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

J M Imtinan Uddin - Graduate Trainee, University of Tennessee, Chattanooga

Homeless project(Data- V7)-Final

To find the Correlation of different previous disease history with Covid-19 hospitalization among homeless people.

Scientific Questions Being Studied

To find the Correlation of different previous disease history with Covid-19 hospitalization among homeless people.

Project Purpose(s)

Educational

Scientific Approaches

I want to apply various machine learning ,data analysis and statistical technique so That I can find out correlation of different previous disease history with Covid-19 hospitalization among homeless people.

Anticipated Findings

I have found that COPD, smoking history and certain diseases play a pivotal role in Covid-19 hospitalizations.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

J M Imtinan Uddin - Graduate Trainee, University of Tennessee, Chattanooga
Hong Qin - Mid-career Tenured Researcher, University of Tennessee, Chattanooga

Collaborators:

Mohammad Aman Ullah Al Amin - Graduate Trainee, University of Tennessee, Chattanooga

Vaccine and cancer

Our research focuses on evaluating the impact of viral vaccines, such as COVID-19 and influenza vaccines, on immunocompromised patients, primarily those with cancer. We aim to explore whether these vaccinations can significantly enhance their immune responses, thus reducing their susceptibility…

Scientific Questions Being Studied

Our research focuses on evaluating the impact of viral vaccines, such as COVID-19 and influenza vaccines, on immunocompromised patients, primarily those with cancer. We aim to explore whether these vaccinations can significantly enhance their immune responses, thus reducing their susceptibility to diseases and the need for infection-related treatments. This question is critically important as it directly influences future treatment protocols for immunocompromised individuals, offering a potential pathway to improve their quality of life and health outcomes. Understanding how vaccines affect these patients' immunity will provide valuable insights into tailoring healthcare strategies to better protect this vulnerable population against infectious diseases, thereby contributing to both scientific knowledge and public health advancements.

Project Purpose(s)

Disease Focused Research (cancer)

Scientific Approaches

Our study will utilize a comprehensive scientific approach involving the extraction of Electronic Health Records (EHR) data from the All of Us Research Program, focusing on cancer patients undergoing cancer treatments like chemotherapy and radiotherapy. We will assess the impact of viral vaccine administration on mortality rates, antibiotic usage rates, and hospitalization rates among these patients. Our research methodology includes rigorous statistical analysis, employing tests such as the T-test to examine the data for significant differences between vaccinated and unvaccinated groups. For data analysis and visualization, we will utilize Jupyter Notebooks within the All of Us Workbench environment. This toolset will enable us to efficiently process large datasets and perform complex analyses, facilitating a deeper understanding of the vaccines' effects on immunocompromised patients, which is essential for improving their healthcare outcomes.

Anticipated Findings

Our anticipated findings aim to demonstrate whether viral vaccinations can significantly enhance the immune response in cancer patients, potentially leading to a decrease in infection rates, lower antibiotic usage, and reduced hospitalization rates. Should our research confirm that viral vaccinations effectively bolster immunity in this vulnerable population, it could revolutionize treatment protocols for immunocompromised patients. By providing concrete evidence of the benefits of vaccinations for cancer patients, our study would contribute significantly to the body of scientific knowledge, aiding healthcare professionals in devising more effective treatment strategies. Ultimately, this could improve the overall health outcomes and quality of life for cancer patients, marking a substantial advancement in immunotherapy and preventive medicine.

Demographic Categories of Interest

Data Set Used

Registered Tier

Research Team

Owner:

Rui Yin - Early Career Tenure-track Researcher, University of Florida
Hongru Zhao - Research Assistant, University of Florida

Duplicate of Long-COVID AoU Project

1. Develop novel software tools to identify long COVID patients from EHR and integrate EHR, survey, and wearable sensor data for these patients. 2. Study the relationships between digital biomarkers from wearable sensor related to long COVID and the rate…

Scientific Questions Being Studied

1. Develop novel software tools to identify long COVID patients from EHR and integrate EHR, survey, and wearable sensor data for these patients.
2. Study the relationships between digital biomarkers from wearable sensor related to long COVID and the rate of long COVID complications in the EHR

Project Purpose(s)

Disease Focused Research (long COVID)
Methods Development

Scientific Approaches

Data integration, Result interpretation and statistical analysis and correlation between long COVID biomarkers and complications in EHR will be used. EHR data, wearable sensor data, and survey data from AoU will be used for this study

Anticipated Findings

We anticipate to provide a set of tools for future EHR data analysis in the AoU workbench and our findings can contribute to assessing the risk of long COVID.

Demographic Categories of Interest

Data Set Used

Controlled Tier

Research Team

Owner:

Michael Hung - Project Personnel, Scripps Research
Ethan Dinh-Luong - Project Personnel, Scripps Research

Collaborators:

Kalyani Kottilil - Project Personnel, Scripps Research

Link Between Smoking/Vaping and Sleep Apneas

The goal of this research is to examine the vaping/smoking habits among those diagnosed with sleep apnea during the COVID-19 pandemic. The research is important because there is not much literature exploring the topic especially with how novel vaping is.…

Scientific Questions Being Studied

The goal of this research is to examine the vaping/smoking habits among those diagnosed with sleep apnea during the COVID-19 pandemic. The research is important because there is not much literature exploring the topic especially with how novel vaping is. I hope to be able to show the importance of the topic.

Project Purpose(s)

Population Health

Scientific Approaches

I plan to use descriptive statistics to establish a potential link between smoking/vaping and sleep apnea.

Anticipated Findings

I anticipate to find a statistically significant link between smoking/vaping and sleep apneas. This will encourage the topic to be explore further so more direct links can be established.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Elijah Johnson - Graduate Trainee, Meharry Medical College

surveys, and genetic predictors of post-COVID phenotypes. v7

The coronavirus disease 2019 (COVID-19) pandemic continues to evolve, with more than 400 million confirmed cases worldwide over numerous waves. Although most COVID-19 patients ultimately recover, many survivors have persistent symptoms or develop new medical problems after recovery. With hundreds…

Scientific Questions Being Studied

The coronavirus disease 2019 (COVID-19) pandemic continues to evolve, with more than 400 million confirmed cases worldwide over numerous waves. Although most COVID-19 patients ultimately recover, many survivors have persistent symptoms or develop new medical problems after recovery. With hundreds of millions potentially at risk for long-term adverse health effects, there is a pressing need to efficiently identify new medical problems occurring among COVID-19 survivors and to understand their biological underpinnings. This study will identify patients in the All of Us Research Program who have been tested for the SARS-CoV-2 virus to identify medical conditions (phenotypes) occurring in patients after clinical COVID-19. Then, using genetic information available for these patients, we will identify genetic variants associated with the new post-COVID-19 medical phenotypes.

Project Purpose(s)

Disease Focused Research (Long COVID-19)

Scientific Approaches

This project will use a phenome-wide association study (PheWAS) approach to identify new post-acute COVID-19 diagnoses. PheWAS is high-throughput informatics framework initially developed to examine the effects of genetic variation on a wide range of physiological and clinical outcomes using electronic health records (EHR) data. PheWAS is simple and has a well-documented R package, facilitating easy dissemination of study design and harmonization of analytical methods across institutions. PheWAS also has previously been used to identify clinical risk factors for hospitalization among patients acutely infected with COVID-19.

Anticipated Findings

This study will assess how genetic differences contribute to development of medical problems after recovery from COVID-19, and ultimately improve our understanding of the "Long-COVID" syndrome.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Christopher Guardo - Project Personnel, Vanderbilt University Medical Center

Collaborators:

Srushti Gangireddy - Project Personnel, Vanderbilt University Medical Center

COVID + Eye

Determine the impact of the COVID-19 pandemic on ocular diseases, such as any changes resulted from the pandemic.

Scientific Questions Being Studied

Determine the impact of the COVID-19 pandemic on ocular diseases, such as any changes resulted from the pandemic.

Project Purpose(s)

Population Health

Scientific Approaches

Analyze the database to analyze and determine whether there are more ocular diseases that come with the pandemic, will use R to analyze All of Us database.

Anticipated Findings

Find whether there is an increase in ocular diseases, general or specific, as a result of the pandemic to guide treatment and/or diagnosis in this post-pandemic era.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Keer Zhang - Graduate Trainee, University of California, Los Angeles
Caleb Tan - Graduate Trainee, Loma Linda University Health

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