Research Projects Directory

Research Projects Directory

15,222 active projects

This information was updated 1/28/2025

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.

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11 projects have 'Long COVID' in the project title
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The impact of Long COVID on complex daily routines

About 30% of adults who have survived COVID-19 experience new symptoms that make it harder for them to fulfill their normal roles and routines. This collection of symptoms is sometimes called "post-acute sequelae of COVID-19 (PASC)" by researchers, or "Long…

Scientific Questions Being Studied

About 30% of adults who have survived COVID-19 experience new symptoms that make it harder for them to fulfill their normal roles and routines. This collection of symptoms is sometimes called "post-acute sequelae of COVID-19 (PASC)" by researchers, or "Long COVID" by patients. People with long COVID may benefit from rehabilitation, but because it is a new disease we don't yet know enough about how to rehabilitate people safely and effectively. We want to know whether All of Us participants with symptoms of long COVID experience daily activity restrictions, are getting rehabilitation therapies like occupational, physical, and speech/language therapy, and whether there are things that increase the risk of impairment.

Project Purpose(s)

  • Disease Focused Research (Long COVID-19 (or Post-acute sequelae of COVID-19, "PASC"))

Scientific Approaches

We will analyze v.7 data on participants who have had a COVID-19 infection, and use methods that tell us whether they are likely to have long COVID, whether the tools (e.g. tests and surveys) used to identify their impairments are working, and whether they've been referred for therapy. We will select participants who, since their COVID-19 illness, have been diagnosed with long COVID specifically or with "clusters" or groups of symptoms/disorders that have been found in previous population-based studies of long COVID. Then we will explore whether these groups are similar or different from those in the previous studies, and see how likely they are to get a referral for therapies that might help them get back to their daily routines. We might also compare them to people without COVID-19 to determine whether the group with long COVID is very different in other ways that matter to health, like socioeconomic situation, insurance, or social connectedness.

Anticipated Findings

From this study, we aim to show how likely All of Us participants with COVID-19 are to experience long COVID symptoms that restrict what they can do, whether rehabilitation recommendations are followed, and whether there are factors that increase or decrease the likelihood of having trouble in daily routines and/or getting rehabilitation. We hope that this will help focus future research on the way long COVID affects participation in meaningful aspects of life, and how rehabilitation can help. Ultimately, this knowledge can help us develop rehabilitation programs for people with long COVID so that they can get back to the things that matter to them.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Emma Freisberg - Undergraduate Student, University of Wisconsin, Madison
  • Maria Rosario Marin Marmol kilrain - Project Personnel, All of Us Program Operational Use
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Angela Long COVID Fall 2024

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:

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Replication and validation of combinatorial genetic risk factors for long COVID

Long COVID is a debilitating chronic condition that has affected over 100 million people globally. Despite considerable global research, traditional genetic studies have identified a single gene linked to long COVID, with little insight into the mechanisms underlying this complex…

Scientific Questions Being Studied

Long COVID is a debilitating chronic condition that has affected over 100 million people globally. Despite considerable global research, traditional genetic studies have identified a single gene linked to long COVID, with little insight into the mechanisms underlying this complex heterogeneous disease. Using PrecisionLife’s unique combinatorial approach to analyzing complex, chronic diseases, Taylor et al. (2023) identified 73 genetic associations with long COVID, including mechanistic differences between different patient subgroups. These genetic associations are reflected in combinatorial disease signatures, i.e., combinations of SNP genotypes that are significantly over- or under-enriched in long COVID patients. This study aims to replicate and validate those signatures in a diverse patient population. Validated signatures will then be used as the basis for a clinical decision support tool that can be used to stratify patients based on genetic risk and mechanistic subcategorization.

Project Purpose(s)

  • Disease Focused Research (Long COVID)
  • Methods Development
  • Ancestry

Scientific Approaches

For each Long COVID disease signature from Taylor et al. (2023), we will generate summary statistics (e.g., # cases & controls, odds ratio, p-value) to evaluate the overall degree of replication in a patient cohort comprised of long COVID patients and healthy controls. Signatures with odds ratio <1 will be flagged as non-replicating. We will also test whether the count of disease signatures possessed by each patient is significantly associated with case-control status. This test will be repeated in ancestry-specific cohorts to identify potential challenges for health equity.
For each signature, we will evaluate the contribution of each component SNP to disease risk by comparing the odds ratio for patients with the full signature to the odds ratio for patients with the broader signature excluding the focal SNP. SNPs will be removed from the signature when the odds ratio of the latter exceeds the former. This refinement process will be repeated using a 5-fold cross validation approach.

Anticipated Findings

The main output of this study will be a set of combinatorial disease signatures that are associated with elevated risk of Long COVID in multiple datasets. Each signature will be paired with summary statistics (e.g., odds ratio, p-value), allowing us to assess the identify and annotate signatures that are individually significant. We expect to further demonstrate that a risk score based on the cumulative effects of refined signatures is significantly correlated with prevalence of long COVID and that this correlation is significant in all broad ancestry groups and not just patients with European ancestry.

Validated signatures will be further clustered based on shared mechanistic hypotheses as identified in the Taylor et al. (2023) manuscript. We expect to demonstrate that these signatures can be used to stratify the population, opening potential for precision medicine-based treatment of long COVID.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

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Duplicate of Angela Long COVID Fall 2024

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:

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Long COVID

I will be looking into Long COVID data to see if there are links to any treatments as I am a patient researcher.

Scientific Questions Being Studied

I will be looking into Long COVID data to see if there are links to any treatments as I am a patient researcher.

Project Purpose(s)

  • Educational

Scientific Approaches

I will be looking into Long COVID data to see if there are links to any treatments as I am a patient researcher.

Anticipated Findings

I will be looking into Long COVID data to see if there are links to any treatments as I am a patient researcher.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Jon Douglas - Graduate Trainee, University of Texas at Austin
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Long COVID

I will be experimenting with the Long COVID datasets, EHR data, etc to try to understand various questions on symptoms, treatments, and potentially novel therapeutic usage.

Scientific Questions Being Studied

I will be experimenting with the Long COVID datasets, EHR data, etc to try to understand various questions on symptoms, treatments, and potentially novel therapeutic usage.

Project Purpose(s)

  • Disease Focused Research (Long COVID)
  • Population Health
  • Social / Behavioral
  • Educational
  • Drug Development
  • Ancestry

Scientific Approaches

I will use various techniques I am learning in my AI for Healthcare class at UT Austin. Mostly NLP, SQL, and other visualization techniques to interpret EHR data.

Anticipated Findings

I'm not sure yet. I have to look at the data. I would like to better understand common symptoms, treatments, and any novel usage of covid-19 therapeutics and outcomes.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age

Data Set Used

Registered Tier

Research Team

Owner:

  • Jon Douglas - Graduate Trainee, University of Texas at Austin
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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:

Collaborators:

  • Angela Choi - Undergraduate Student, University of Chicago
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Duplicate of 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:

  • Angela Choi - Undergraduate Student, University of Chicago
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Contrastive Learning - Long COVID Recovery

The purpose of this workspace is to benchmark a novel robust contrastive learning algorithm using the established long covid dataset. We will pull additional control data and attempt to identify long covid cases using our contrastive learning methods.

Scientific Questions Being Studied

The purpose of this workspace is to benchmark a novel robust contrastive learning algorithm using the established long covid dataset. We will pull additional control data and attempt to identify long covid cases using our contrastive learning methods.

Project Purpose(s)

  • Disease Focused Research (Long COVID)
  • Methods Development

Scientific Approaches

To achieve this objective, data science workflows were used to apply ML algorithms on the Researcher Workbench. This effort allowed an expansion in the number of participants used to evaluate the ML models used to identify risk of PASC/Long COVID and also serve to validate the efforts of one team and providing insight to other teams. These models were implemented within the All of Us Controlled Tier data (C2022Q2R2), which was last refreshed on June 22, 2022. We intend to provide a step-by-step guide for the implementation of N3C's ML Model for identification of PASC/Long COVID Phenotype in the All of Us dataset.

Anticipated Findings

We intend to provide a step-by-step guide for the implementation of N3C's ML Model for identification of PASC/Long COVID Phenotype in the All of Us dataset. We will do the same with our novel contrastive learning methods.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Arush Ramteke - Undergraduate Student, University of California, Los Angeles
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Impact of long COVID on surgical outcomes

Long Covid is a significant health care burden. During COVID a meaningful pause was placed on elective surgery. We have emerged from the pandemic with a number of a patients being impacted by longCOVID. Understanding the impacts on recovery are…

Scientific Questions Being Studied

Long Covid is a significant health care burden. During COVID a meaningful pause was placed on elective surgery. We have emerged from the pandemic with a number of a patients being impacted by longCOVID. Understanding the impacts on recovery are important for planning. First we will identify the clinical (seeking care) and societal burden (impacted with long COVID but did not seek care for this) of long COVID and the number of surgical procedures being performed. We will determine in peri-operative outcomes are impacted. Examples of outcomes include length of stay, complications post operatively and readmission rate.

Project Purpose(s)

  • Disease Focused Research (Long Covid impacts on surgical recovery)
  • Control Set
  • Ancestry

Scientific Approaches

We will use questionnaires, demographic data, and ICD10 cm codes to determine the extent of Long Covid across a number of domains. We wish to understand if there is a difference in health care utilization in participants in All of US compared to clinical cohorts from local EHR data. This is an initial exploration of the data set to better understand the fields available and better understand the prevalence of the condition in this population. As understanding of the dataset grows we will seek to better understand risk factors for the development of the condition including potential genomic predictors. We will need a control cohort of patients which match baseline characteristics.

Anticipated Findings

We hypothesize that patients with longCOVID experience worse perioperative outcomes compared to those who do not have long COVID.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Access to Care

Data Set Used

Controlled Tier

Research Team

Owner:

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Long COVID

Our team at Massachusetts General Hospital developed more refined definitions for using structured data to determine long COVID subtypes. Given the heterogenous nature of long COVID and that the definition casts a wide net, we wanted to implement more specific…

Scientific Questions Being Studied

Our team at Massachusetts General Hospital developed more refined definitions for using structured data to determine long COVID subtypes. Given the heterogenous nature of long COVID and that the definition casts a wide net, we wanted to implement more specific research definitions in order to explore the genetic underpinnings of the disease. We plan to use the refined phenotypes in the AllofUs dataset to see if there are specific genetic abnormalities that are associated with developing specific long COVID subtypes.

Project Purpose(s)

  • Disease Focused Research (Long COVID)

Scientific Approaches

We will used structured data found in the electronic health records of patients in AllofUs to identify patients with likely long COVID. Once they are identiied we will apply our validated algorithm on the cohort to increase the odds that the patients being assessed have specific long COVID outcomes. Than we will perform GWAS to see fi the specific subtypes are associated with particular single nucleotide polymorphisms.

Anticipated Findings

We hope that by using our more refined definitions and applying them to the large and diverse AllofUs patient dataset, we will be able to identify specific genetic polymorphisms that may increase the likelihood of developing long COVID.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

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