Research Projects Directory

Research Projects Directory

3,097 active projects

This information was updated 11/27/2022

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.

54 projects have 'alzheimer' in the scientific questions being studied description
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Alzheimer's Disease resilience

We aim to identify a subgroup of healthy individuals with a high risk of developing Alzheimer’s Disease (AD) based on high-throughput genetics data. This subgroup of AD-resilient individuals will be further studied with the final goal of detecting other genetic…

Scientific Questions Being Studied

We aim to identify a subgroup of healthy individuals with a high risk of developing Alzheimer’s Disease (AD) based on high-throughput genetics data. This subgroup of AD-resilient individuals will be further studied with the final goal of detecting other genetic factors or environmental/social variables associated with resilience.

Project Purpose(s)

  • Disease Focused Research (Alzheimer's Disease)
  • Population Health
  • Social / Behavioral
  • Ancestry

Scientific Approaches

We will first select a cohort with high-throughput Single Nucleotide Polymorphisms (SNPs) data; then, we will exclude individuals with AD diagnosis and any other type of dementia using ICD-codes (total: 29 codes) and four medications (Galantamine, Rivastigmine, Memantine, and Donepezil). Individuals included in the study cohort will be from both sexes, any ethnicity, and at least 60 years old. The first group will be selected based on the APO E4/E4 genotype, which increases the risk by approximately eight to twelvefold. The second group will be selected among the individuals with a higher AD polygenic risk scores (PRS) computed from Genome-Wide Association Studies (GWAS). All the group samples will be stratified by ethnicity due to the different genetic risks of APOE and AD-associated SNPs used for the PRS.

Anticipated Findings

We aim to find variables associated with AD resilience. The non-genetic protective factors will be used to increase the knowledge of modifiable risk factors and focus on improving lifestyle conditions aiming to reduce AD risk. The genetic factor will be used to develop genetic testing for screening for early detection of individuals at high AD risk to plan proper early pharmacological treatment and non-drug interventions (e.g., memory training and physical exercise programs).

Demographic Categories of Interest

  • Others

Data Set Used

Controlled Tier

Research Team

Owner:

  • Ignazio Piras - Early Career Tenure-track Researcher, Translational Genomics Research Institute
  • Donald Saner - Project Personnel, Banner Health

APOE and hypercholesterol

Variants in the Apolipoprotein E (APOE) have been shown to have differential risk for conditions such as Alzheimer's disease and cardiovascular disease. This workspace will assess the feasibility of a large APOE association study by summarizing the APOE genotypes, hypercholesterolemia…

Scientific Questions Being Studied

Variants in the Apolipoprotein E (APOE) have been shown to have differential risk for conditions such as Alzheimer's disease and cardiovascular disease. This workspace will assess the feasibility of a large APOE association study by summarizing the APOE genotypes, hypercholesterolemia and demographics.

Project Purpose(s)

  • Educational
  • Ancestry

Scientific Approaches

The two rsIDs for APOE genotyping (rs429358 and rs7412) will be extracted from AllOfUs Hail tables. Data will be summarized into the defined APOE genotypes (ε2, ε3, ε4) and associated with hypercholesterolemia status. Hypercholesterolemia will be defined by the SNOMED code "E78.0 - Pure hypercholesterolemia". Summary statistics for APOE association will be stratified by age, sex and declared race/ethnicity.

Anticipated Findings

The study hopes to find similar statics as has been found in the UKBiobank cohort, with the addition of higher diversity. The summary statistics of these findings will be used as preliminary data to propose a larger cohort study.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Sevda Molani - Research Fellow, Institute for Systems Biology
  • Ehsan Alipour - Graduate Trainee, University of Washington

Underdiagnosis of Dementias

The national prevalence of Alzheimer’s disease is estimated to be 11% in individuals over 65 years old and 1.5-2.0 times higher in underrepresented racial and ethnic groups including Black and Hispanic/Latinx. In real world medical care based on prior studies…

Scientific Questions Being Studied

The national prevalence of Alzheimer’s disease is estimated to be 11% in individuals over 65 years old and 1.5-2.0 times higher in underrepresented racial and ethnic groups including Black and Hispanic/Latinx. In real world medical care based on prior studies and our work, less than half of patients with dementia have been formally diagnosed and significantly more so in underrepresented racial and ethnic groups. Our scientific questions are:
1. Are dementias underdiagnosed in the electronic health record (EHR) compared to population estimates?
2. What are the risk factors for patients to not be formally diagnosed with dementias?
3. How do the underdiagnosis and risk factors differ across racial and ethnic groups?

We hypothesize dementias are underdiagnosed the EHR, more so in underrepresented racial and ethnic groups, and that risk factors include demographics, comorbidities, medications, and healthcare access.

Project Purpose(s)

  • Disease Focused Research (dementia)
  • Population Health

Scientific Approaches

We will define dementia as probable based on ICD codes and possible based on a combination of ICD codes, medication use and personal medical history. We will calculate the prevalence of dementias across racial and ethnic group compared to population estimates. We will compare risk factors of patients who have probable dementia versus possible dementia using logistic regression correcting for demographics. Risk factors tested will include drug exposures, lab measurement, demographics, health access, and other survey questions. We will compare risk factors across racial and ethnic groups.

Anticipated Findings

We expect to find that dementias are underdiagnosed the EHR, more so in underrepresented racial and ethnic groups, and that risk factors for underdiagnosis include demographics, comorbidities, medications, and healthcare access, which will differ across racial and ethnic groups. These findings may lead to racially and ethnically specific strategies to improve the early and appropriate diagnosis of dementias, which can initiate multi-disciplinary care and treatment.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Registered Tier

Research Team

Owner:

  • Tim Chang - Early Career Tenure-track Researcher, University of California, Los Angeles
  • Samantha Shah - Project Personnel, University of California, Los Angeles
  • Joy Fu - Graduate Trainee, University of California, Los Angeles

AD full

Alzheimer’s disease (AD) is a leading cause of dementia and neurological disability in the aging population. For the proposed project, we will examine the associations between genetic, environmental, demographic and clinical factors and functional outcomes in people with Alzheimer’s disease.

Scientific Questions Being Studied

Alzheimer’s disease (AD) is a leading cause of dementia and neurological disability in the aging population. For the proposed project, we will examine the associations between genetic, environmental, demographic and clinical factors and functional outcomes in people with Alzheimer’s disease.

Project Purpose(s)

  • Disease Focused Research (Alzheimer's disease)
  • Educational

Scientific Approaches

In the proposed project, we will test the hypothesis that meaningful genetic, environmental, demographic and clinical factors can predict AD functional outcomes and disease trajectory. We will also examine how social determinants of health influence AD functional outcomes and disease trajectory. We will utilize data from the All of Us database with at least one of the International Classification of Disease (ICD) diagnosis codes for AD and related dementia.

Anticipated Findings

We anticipate that integrating genetic, environmental, demographic and clinical factors will predict AD functional outcomes and disease trajectory and these outcomes will differ by sex, race, ethnicity, and socioeconomic status.

Demographic Categories of Interest

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

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Richard Boyce - Mid-career Tenured Researcher, University of Pittsburgh
  • Olga Kravchenko - Research Fellow, University of Pittsburgh
  • Bamidele Ajisogun - Graduate Trainee, University of Pittsburgh

ALDH2

Alcohol consumption is a risk factor for many chronic diseases, including some cancers, type 2 diabetes, and Alzheimer’s disease. Individuals with a specific variant of the aldehyde dehydrogenase 2 gene (ALDH2*2) are at higher risk of many of these diseases.…

Scientific Questions Being Studied

Alcohol consumption is a risk factor for many chronic diseases, including some cancers, type 2 diabetes, and Alzheimer’s disease. Individuals with a specific variant of the aldehyde dehydrogenase 2 gene (ALDH2*2) are at higher risk of many of these diseases. Given that ALDH2*2 is the most common single genetic variation in humans and that more than half of all American adults drink alcohol, an opportunity is present for targeted chronic disease risk reduction in a large number of Americans. However, in order to design effective public health strategies, such as targeted intervention programs, a better understanding of current alcohol consumption behaviors and associated factors, overall and stratified by ALDH2 genotype, is needed. This study aims to characterize the alcohol consumption behaviors among participants in the All of Us Research Program and examine factors that may be related to the behaviors, overall and by ALDH2 genotype.

Project Purpose(s)

  • Population Health
  • Social / Behavioral
  • Ancestry

Scientific Approaches

We will analyze data from the All of Us Research Program database regarding alcohol consumption behaviors, ALDH2 genotype (rs671), demographics, personal and family health history, socioeconomic factors, lifestyle factors, and social determinants of health. All participants with informative data for rs671 will be included in the study. These data sets will be from surveys, physical measurements, and the genomic data set. Statistical analyses will be done using R or python. We will examine relationships between these factors and alcohol consumption using Fisher’s exact test (categorical variables) and the Kruskal-Wallis test (continuous variables), overall and stratified by ALDH2 genotype and potentially other factors, for example, demographics.

Anticipated Findings

We hypothesize that alcohol consumption behaviors will be associated with factors including demographics, personal and family health history, socioeconomic factors, lifestyle factors, and social determinants of health, with ALDH2 genotype and potentially other factors. While a limited number of U.S. studies among university students have shown that ALDH2*2 homozygotes tend to avoid alcohol, many ALDH2 heterozygotes do consume alcohol, albeit at lower levels. There have been no studies examining alcohol consumption behaviors by ALDH2 genotype conducted outside the university setting in the U.S. The All of Us Research Program presents a valuable source of data from study participants across the U.S. which would enable the study of alcohol consumption behaviors in the context of genomics.

Demographic Categories of Interest

  • Race / Ethnicity

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Jacqueline Kim - Other, University of California, Irvine
  • Hester Nguyen - Undergraduate Student, University of California, Irvine

Dementia-Alzheimer's-CRP

Do CRP levels change with age in dementia/Alzheimer's patients as opposed to controls? Associations have shown that these protein levels are increased in Alzheimer's patients, and this will help answer whether patients' CRP levels are elevated naturally or if it…

Scientific Questions Being Studied

Do CRP levels change with age in dementia/Alzheimer's patients as opposed to controls? Associations have shown that these protein levels are increased in Alzheimer's patients, and this will help answer whether patients' CRP levels are elevated naturally or if it is something that happens over time as a result of the disease progression.

Project Purpose(s)

  • Disease Focused Research (Dimentia/Alzheimer's)

Scientific Approaches

Datasets - AOU phenotyping and lab data Research methods and tools - clean and summarize lab data for CRP - average by decile of age and disease status and plot in R.

Anticipated Findings

I anticipate that CRP levels will be elevated in Alzheimer's after disease progression. This would help answer cause and effect of the two

Demographic Categories of Interest

  • Age

Data Set Used

Registered Tier

Research Team

Owner:

Alzheimer's Disease

Are blood traits such as neutrophil to lymphocyte ratio associated with Alzheimer's Disease? Neutrophil to lymphocyte ratio has been shown to be associated with Alzheimer's Disease but it is not known whether this association will replicate in the All of…

Scientific Questions Being Studied

Are blood traits such as neutrophil to lymphocyte ratio associated with Alzheimer's Disease? Neutrophil to lymphocyte ratio has been shown to be associated with Alzheimer's Disease but it is not known whether this association will replicate in the All of Us dataset.

Project Purpose(s)

  • Disease Focused Research (Alzheimer's disease)

Scientific Approaches

The main approach will use a cox proportional hazards model while adjusted for covariates such as age and sex.

Anticipated Findings

Based on the previous literature, it is anticipated that neutrophil to lymphocyte ratio will be associated with Alzheimer's Disease in the All of Us cohort. These findings may allow for a better understanding of Alzheimer's Disease.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Collaborators:

  • Bjoernar Tuftin - Project Personnel, University of North Carolina, Chapel Hill

Alzheimer's Disease

Recent research has shown that APEO4 causes damage to the blood-brain barrier decades before sign of cognitive decline. We are interested if there are any associations between Alzheimer's and other brain-related diseases, such as stroke, multiple sclerosis, and stroke. Further,…

Scientific Questions Being Studied

Recent research has shown that APEO4 causes damage to the blood-brain barrier decades before sign of cognitive decline. We are interested if there are any associations between Alzheimer's and other brain-related diseases, such as stroke, multiple sclerosis, and stroke. Further, we are interested in if APOE4 is associated with other brain-related diseases besides Alzheimer's.

Project Purpose(s)

  • Educational

Scientific Approaches

We are going to analyze survey data to see if patients diagnosed with Alzheimer's have a history of stroke, epilepsy, and multiple sclerosis. We will also analyze genomic data to see if there are associations between APOE4 and these brain-related diseases.

Anticipated Findings

We are curious if APOE4 might have a correlation with other diseases in addition to Alzheimer's diseases. We seek to understand the full impact of APOE4 on human health.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

Environmental Exposure, Epigenetics, and Health Outcomes

Our research question is: How does exposure to adverse social and natural environmental conditions impact human health outcomes through epigenetic changes? Subsequent questions are: In which populations do we see the highest associations between exposure and epigenetic changes? In which…

Scientific Questions Being Studied

Our research question is: How does exposure to adverse social and natural environmental conditions impact human health outcomes through epigenetic changes? Subsequent questions are: In which populations do we see the highest associations between exposure and epigenetic changes? In which populations do we see the highest associations between epigenetic changes and poor health outcomes? To what extent do we see these epigenetic changes being reversed, and what lifestyle factors are associated with that?

This research will have key implications for chronic disease: a top cause of mortality in vulnerable U.S populations. This paper explores the mechanisms by which the SDOH impact health outcomes. Epigenetic mechanisms have been closely linked cardiovascular disease, type II diabetes, and Alzheimer’s disease–the three chronic diseases with the highest prevalence globally. Specifically, studying inflammation in the genotype dataset will connect this research directly to chronic disease.

Project Purpose(s)

  • Population Health
  • Social / Behavioral
  • Ancestry

Scientific Approaches

This project will have a longitudinal, natural experiment design as we plan to look at changes from the initial questionnaire to the follow-up.. We will control for various demographic, social, and genetic factors to infer causality.

We will use data from the EHR domains, genomics, physical measurements and the survey categories of family health history, SDOH, overall health, and lifestyle to examine factors influencing participants' health outcomes.

We will use R to analyze the data. We will calculate descriptive, bivariate, and inferential statistics to describe the population and measure outcomes of interest. The focus is on multivariate, fixed effects regression, with basic and augmented models. The study will include two main regressions, A) estimating the effects of environmental exposure on gene expression, and B) estimating the effects of changes in gene expression on health outcomes.

The outcome measures are epigenetic changes and mental and physical health outcomes.

Anticipated Findings

We hypothesize that degree of exposure to adverse environmental conditions will have a positive association with extent and severity of epigenetic changes. Additionally, we hypothesize that these epigenetic changes will be positively associated with extent and severity of poor physical and mental health outcomes. We expect to find that these effects are mitigated by upward socioeconomic mobility.

This research project fills a gap in the current literature by analyzing epigenetic data through a social science lens and combining epigenetic information with environmental exposure in populations with similar genetic information. Applying social science methods to this topic increases the external validity of this research because it combines field-based data with laboratory data. While much social science public health research analyzes associations between SDOH and health outcomes, this paper looks to examine the biological pathways by which these associations occur.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Gender Identity
  • Sexual Orientation
  • Income Level

Data Set Used

Controlled Tier

Research Team

Owner:

AD

Alzheimer’s disease (AD) is a leading cause of dementia and neurological disability in the aging population. For the proposed project, we will examine the associations between genetic, environmental, demographic and clinical factors and functional outcomes in people with Alzheimer’s disease.

Scientific Questions Being Studied

Alzheimer’s disease (AD) is a leading cause of dementia and neurological disability in the aging population. For the proposed project, we will examine the associations between genetic, environmental, demographic and clinical factors and functional outcomes in people with Alzheimer’s disease.

Project Purpose(s)

  • Disease Focused Research (Alzheimer's disease)
  • Educational

Scientific Approaches

In the proposed project, we will test the hypothesis that meaningful genetic, environmental, demographic and clinical factors can predict AD functional outcomes and disease trajectory. We will also examine how social determinants of health influence AD functional outcomes and disease trajectory. We will utilize data from the All of Us database with at least one of the International Classification of Disease (ICD) diagnosis codes for AD and related dementia.

Anticipated Findings

We anticipate that integrating genetic, environmental, demographic and clinical factors will predict AD functional outcomes and disease trajectory and these outcomes will differ by sex, race, ethnicity, and socioeconomic status.

Demographic Categories of Interest

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

Data Set Used

Registered Tier

Research Team

Owner:

Alzheimer's Disease

Females are two-thirds as likely to develop Alzheimer's disease compared to males. Also, females also tend to have earlier onset and more severe symptoms. Whether that prevalence results from increased longevity or genetic differences remains to be understood. We want…

Scientific Questions Being Studied

Females are two-thirds as likely to develop Alzheimer's disease compared to males. Also, females also tend to have earlier onset and more severe symptoms. Whether that prevalence results from increased longevity or genetic differences remains to be understood. We want to perform association analysis for Alzheimer's disease-related phenotypes in a diverse population to explore genetic architecture using All of Us research dataset, with a particular focus on the previously-overlooked sex-specific effects. We seek to understand the reason behind these sex biases in Alzheimer's disease to improve health care and resolve health disparities.

We will consider the following questions:

1) Which variants are associated with Alzheimer’s disease?

2) Which variants have different effects on Alzheimer’s disease between sexes?

3) We will narrow down the list of causal variants using state-of-the-art methods.

We will publish our results as a scientific paper, and release GWAS summary statistics

Project Purpose(s)

  • Disease Focused Research (Alzheimer's disease)

Scientific Approaches

We plan to use marginal regression models such as logistic mixed regression for a binary outcome (in REGENIE) on All of Us genetics data. Phenotypes of interest are late-onset Alzheimer’s disease & other types of Alzheimer’s disease. We plan to define our phenotype based on known ICD-9 (331.0) & ICD-10 codes (G30).
1) Phenotype definition: We will try to retrieve both genetics data & phenotype data based on our established pipelines (in Liu et al) and uniformly process the data.
2) GWAS analysis: We will perform GWAS analysis for each sub-trait of interest and combine the results to perform meta-analysis. We will adjust sex, age, and 10 principal components as covariates in association analysis.
3) Sex-stratified effects and the X-chromosome: We will investigate the role of X chromosome in AD, generate sex stratified results, & perform downstream analysis such as variant annotation, among others.
We plan to use R, Python, Plink, REGENIE, and other commonly used tools.

Anticipated Findings

For this analysis, we would expect to see novel variants/genes associated with Alzheimer's phenotypes, especially those with effects showing sex differences. We expect to find: 1) potential variants or genes associated with Alzheimer's disease. 2) genetic factors' contribution to Alzheimer's disease in a sex-specific manner. 3) more accurate genetic effect estimation when we conduct sex-stratified analysis. 4) A detailed pipeline for performing similar analyses will be available to researchers within the Researcher Workbench for All of Us to enhance reproducibility. Our developed methods will benefit future research of a similar kind.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Education Level

Data Set Used

Controlled Tier

Research Team

Owner:

  • Jeniece Regan - Graduate Trainee, Pennsylvania State University, College of Medicine
  • Avantika Diwadkar - Graduate Trainee, Pennsylvania State University, College of Medicine

Alzheimer's disease APOe variants

By using the data, I hope to find answers on Alzheimer's disease progression in American Indian communities, specifically in the women ages 65 years or older. This research will be looking into the Apolipoprotein variants E2, E3, and E4 within…

Scientific Questions Being Studied

By using the data, I hope to find answers on Alzheimer's disease progression in American Indian communities, specifically in the women ages 65 years or older. This research will be looking into the Apolipoprotein variants E2, E3, and E4 within the American Indian populations and comparing the information to other ethnic groups. This research will investigate specific tribes within the United States by certain demographic areas. Many tribal elders use natural botanical plants from their environments for treatment of illnesses and diseases. I will explore the data to see what types of plants from the various areas have been researched or studied.

Project Purpose(s)

  • Educational
  • Ancestry

Scientific Approaches

The data sets I plan to use will be the Alzheimer's disease in populations 65 years or older and compare the ethnicities and specifically in American Indian populations.

Anticipated Findings

The anticipated findings should be higher for other ethnicities compared to American Indian populations. Also, the women are expected to be higher with Alzheimer's disease than men. For American Indian tribes, it will be beneficial to see if the women are at higher risk because most tribes are matrilineal and the women are the main teachers of cultures, traditions, language and histories.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Geography

Data Set Used

Controlled Tier

Research Team

Owner:

Duplicate of APOE and hypercholesterol

Variants in the Apolipoprotein E (APOE) have been shown to have differential risk for conditions such as Alzheimer's disease and cardiovascular disease. This workspace will assess the feasibility of a large APOE association study by summarizing the APOE genotypes, hypercholesterolemia…

Scientific Questions Being Studied

Variants in the Apolipoprotein E (APOE) have been shown to have differential risk for conditions such as Alzheimer's disease and cardiovascular disease. This workspace will assess the feasibility of a large APOE association study by summarizing the APOE genotypes, hypercholesterolemia and demographics.

Project Purpose(s)

  • Educational
  • Ancestry

Scientific Approaches

The two rsIDs for APOE genotyping (rs429358 and rs7412) will be extracted from AllOfUs Hail tables. Data will be summarized into the defined APOE genotypes (ε2, ε3, ε4) and associated with hypercholesterolemia status. Hypercholesterolemia will be defined by the SNOMED code "E78.0 - Pure hypercholesterolemia". Summary statistics for APOE association will be stratified by age, sex and declared race/ethnicity.

Anticipated Findings

The study hopes to find similar statics as has been found in the UKBiobank cohort, with the addition of higher diversity. The summary statistics of these findings will be used as preliminary data to propose a larger cohort study.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

The Impact of Alzheimer's disease in Latinx Populations

This research aims to calculate the fitness cost of Alzheimer's disease to high grandparent care, Latino/a communities. This research will take into consideration cultural, economic, and evolutionary factors in order to create a holistic model of the fitness impact on…

Scientific Questions Being Studied

This research aims to calculate the fitness cost of Alzheimer's disease to high grandparent care, Latino/a communities. This research will take into consideration cultural, economic, and evolutionary factors in order to create a holistic model of the fitness impact on a population when a grandmother gets Alzheimer's disease.

Project Purpose(s)

  • Educational

Scientific Approaches

The goal of this research will be to create a holistic model that shows the fitness impact of a grandmother getting Alzheimer's disease. Cultural factors such as high grandparent care and multigenerational households in Latino/a communities must be taken into account in the model. Evolutionary factors will be essential to the model in order to incorporate the grandmother effect and how grandmother’s generally increase fitness by caring for their offspring and allowing their daughters to have more children, indirectly increasing their own fitness. Genetic factors will be applied with the understanding of APOE and how an APOE4 homozygous individual will have a high chance of developing Alzheimer’s disease, allelic information could allow us to predict Alzheimer’s outcomes.

Anticipated Findings

I hope to find what the effect of Alzheimer's disease is on the Latinx community. I would like to figure out what this impact looks like so that better resources and tools can be allocated to help this community.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age

Data Set Used

Controlled Tier

Research Team

Owner:

A1C Project

We want to examine that if high A1C level is a risk factor for diagnosis of Alzheimer's' Disease. It's significant since the causes of AD are still mysterious for us.

Scientific Questions Being Studied

We want to examine that if high A1C level is a risk factor for diagnosis of Alzheimer's' Disease. It's significant since the causes of AD are still mysterious for us.

Project Purpose(s)

  • Educational

Scientific Approaches

We will apply simple scientific approaches, control-case experiments.
The datasets we will use contained A1C levels and test reports of AD/

Anticipated Findings

We want to examine that if high A1C level is a risk factor for diagnosis of Alzheimer's' Disease. It's significant since the causes of AD are still mysterious for us.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth

Data Set Used

Registered Tier

Research Team

Owner:

  • Yinyin Guan - Undergraduate Student, University of California, Davis

AD

Does neutrophil to lymphocyte ratio a risk factor for Alzheimer's disease? Investigating this association could help to identify patients at an increased risk for developing Alzheimer's disease and possibly allow for earlier treatment.

Scientific Questions Being Studied

Does neutrophil to lymphocyte ratio a risk factor for Alzheimer's disease? Investigating this association could help to identify patients at an increased risk for developing Alzheimer's disease and possibly allow for earlier treatment.

Project Purpose(s)

  • Disease Focused Research (Alzheimer's disease)

Scientific Approaches

The dataset will include All of Us participants with and without Alzheimer's disease and will include neutrophil to lymphocyte ratio and covariates such as age, sex, and cardiovascular risk factors. The analysis will involve logistic regression.

Anticipated Findings

The anticipated findings from the study based on the previous literature is that neutrophil to lymphocyte ratio will be associated with Alzheimer's disease.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Collaborators:

  • Laura Raffield - Other, University of North Carolina, Chapel Hill

Alzheimer's and ADHD Mendelian Randomization

What genetic connections, if any, do Alzheimer's Disease and ADHD have with each other? It's been shown in past studies that the primary and secondary kin of ADHD patients are more likely to develop Alzheimer's compared to other people. The…

Scientific Questions Being Studied

What genetic connections, if any, do Alzheimer's Disease and ADHD have with each other? It's been shown in past studies that the primary and secondary kin of ADHD patients are more likely to develop Alzheimer's compared to other people. The goal of this project is to see whether we can develop polygenic risk scores for each respective disease and determine if they can be used to predict the opposite disease phenotype.

Project Purpose(s)

  • Ancestry

Scientific Approaches

My hope is to use a consortium of GWAS studies for each respective disease and develop polygenic risk scores for both. After which, I intend to use the genetic dataset in All of Us to determine whether we can respectively predict both disease types with each PRS. This Mendelian Randomization would be used to help us discover what genes might be linked between diseases.

Anticipated Findings

The findings would tell us what, if any, genes are linked between the diseases. Knowing this information can help us track the onset of Alzheimer's Disease in ADHD patients and work to discover ways to prevent such occurrences.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth
  • Gender Identity
  • Sexual Orientation
  • Disability Status

Data Set Used

Controlled Tier

Research Team

Owner:

  • Ryan Colby - Undergraduate Student, Brigham Young University

alzheimers-liver-project

The goal of this project is to uncover novel early biomarkers and generate prediction models for Alzheimer’s disease (AD) based on race/ethnicity or dietary habits. The hypothesis is that metabolic dysfunction and diet-associated health issues are predictors for cognitive impairment…

Scientific Questions Being Studied

The goal of this project is to uncover novel early biomarkers and generate prediction models for Alzheimer’s disease (AD) based on race/ethnicity or dietary habits. The hypothesis is that metabolic dysfunction and diet-associated health issues are predictors for cognitive impairment in a race/ethnicity-specific manner. We propose using medical data obtained from 6 University of California Medical Centers to generate prediction models for AD development based on metabolic disease diagnoses and clinical test results, differentiating by race and ethnicity as well as gender. The long-term objective is to aggressively treat and prevent metabolic diseases prevalent among differing ethnicities, leading to AD prevention.

Project Purpose(s)

  • Disease Focused Research (Alzheimer's disease and Liver diseases)

Scientific Approaches

The inclusion criteria are patients who are 65-95 years old with and without AD based on ICD-10 code (International Classification of Diseases).
Diseases that affect liver functions (alcoholic, toxic, failure, chronic hepatitis, fibrosis, cirrhosis, inflammation, malignancy, i.e., liver cancer of any types, autoimmune, Wilson’s Disease), Type 2 diabetes melilotus (T2DM), cardiovascular disease, as well as nicotine or alcohol dependence will be included for risk predictions. Demographic data and clinical tests that will be included are birth sex, BMI, age at menopause (or hot flash symptom, hemoglobin A1C, glucose blood/urine tests, erythrocyte sedimentation rate, plasma viscosity, liver function panels, comprehensive metabolic panels, blood count, lipid panels, urinalysis, C reactive protein, and prothrombin time to generate prediction models. All of those are possible indicators of metabolic dysfunction.

Anticipated Findings

We expect to generate good prediction models and to be able to quantify the importance of metabolic clinical features for AD identification. If the learned model is not sufficiently accurate on held-back data, we will retrain the models from scratch using more domain knowledge to reduce the complexity of the prediction tasks. We will also explore the possibility of using a similar dataset to pre-train a model or to select appropriate features. If the data does not match with the known National data, we will look into patient population and barriers to access within the UC system. The benchmarks for success are measured by: (1) the identification of disparities in AD as well as metabolic diseases in the UC system; (2) the generation of good models for predicting AD based on race and ethnicity.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Sex at Birth

Data Set Used

Controlled Tier

Research Team

Owner:

Identification of novel genetic variants affecting Alzheimer’s disease

Alzheimer’s disease (AD) is a neurodegenerative disease, which affects around 0.10% of people in the United States aged 65 years or older. It is important to find genetic variants which are associated with AD and affect AD. Here, we will…

Scientific Questions Being Studied

Alzheimer’s disease (AD) is a neurodegenerative disease, which affects around 0.10% of people in the United States aged 65 years or older. It is important to find genetic variants which are associated with AD and affect AD. Here, we will use the Multivariable Information Theory-based dependence Search Tool (MIST) software we implemented to see how the software runs using the AD datasets in All of Us. We will also check how the UK Biobank results (which we already have) compare to the ones with All of Us. In addition, we will apply methods described in the MIST software and compare with standard statistical methods using the AD datasets in All of Us.

It has been suggested that the APOE4 genetic variant affects AD. It is important to find new genetic dependencies by identifying genes and/or genetic variants that modify this well-known APOE4 genetic variant.

Project Purpose(s)

  • Methods Development

Scientific Approaches

Here, we will use research methods and tools such as the Multivariable Information Theory-based dependence Search Tool (MIST) software as well as standard statistical methods (e.g., linear models and other existing software packages) to establish novel genes and/or genetic variants that have relationships among variables in the All of Us datasets.

The MIST software is a new software package we developed, which performs the joint probability density for many variables and then carry out the entropy-based measures implemented to identify the functional dependencies among variables. The MIST software utilizes a novel symmetric measure of functional dependence we developed, which is based on Information Theory.

Also, we will use the Alzheimer’s disease (AD) datasets in All of Us. The All of Us results for AD will be compared to the ones with UK Biobank (which we already have).

Anticipated Findings

The anticipated findings from the study will be novel genes and/or genetic variants that modify the well-known APOE4 genetic variant. In the field, it has been shown that the APOE4 genetic variant affects Alzheimer’s disease (AD). It is important to identify new genes and/or genetic variants which modify this well-known APOE4 genetic variant affecting AD.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Eugene Lin - Mid-career Tenured Researcher, Pacific Northwest Research Institute

Alzheimer's Disease Analysis

We want to study the characteristics of Alzheimer's Disease patients through their medical data. Our goal is to perform early detection for neurodegeneration and discover potential drugs for the disease.

Scientific Questions Being Studied

We want to study the characteristics of Alzheimer's Disease patients through their medical data. Our goal is to perform early detection for neurodegeneration and discover potential drugs for the disease.

Project Purpose(s)

  • Disease Focused Research (Alzheimer's disease)
  • Drug Development
  • Methods Development
  • Control Set
  • Ancestry

Scientific Approaches

We will study the medical data of the patients including diagnosis, lab tests, demographics, medications, etc. We plan to apply Machine Learning (ML) techniques to solve this problem. Particularly, we are interested in applying traditional ML methods such as Logistic Regression, Support Vector Machine (SVM), Random Forest, etc. as baselines for our predictions. Then, we will develop deep learning methods to generate more accurate solutions to the problem.

Anticipated Findings

The anticipated findings will be early indicators of neurodegeneration, and a high-performance ML that can accurately predict the results while providing sufficient interpretation to help the clinician understand the rationale behind the solution.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

  • Yurui Cao - Graduate Trainee, University of Illinois at Urbana Champaign

Duplicate of Underdiagnosis of Dementias

The national prevalence of Alzheimer’s disease is estimated to be 11% in individuals over 65 years old and 1.5-2.0 times higher in underrepresented racial and ethnic groups including Black and Hispanic/Latinx. In real world medical care based on prior studies…

Scientific Questions Being Studied

The national prevalence of Alzheimer’s disease is estimated to be 11% in individuals over 65 years old and 1.5-2.0 times higher in underrepresented racial and ethnic groups including Black and Hispanic/Latinx. In real world medical care based on prior studies and our work, less than half of patients with dementia have been formally diagnosed and significantly more so in underrepresented racial and ethnic groups. Our scientific questions are:
1. Are dementias underdiagnosed in the electronic health record (EHR) compared to population estimates?
2. What are the risk factors for patients to not be formally diagnosed with dementias?
3. How do the underdiagnosis and risk factors differ across racial and ethnic groups?

We hypothesize dementias are underdiagnosed the EHR, more so in underrepresented racial and ethnic groups, and that risk factors include demographics, comorbidities, medications, and healthcare access.

Project Purpose(s)

  • Disease Focused Research (dementia)
  • Population Health

Scientific Approaches

We will define dementia as probable based on ICD codes and possible based on a combination of ICD codes, medication use and personal medical history. We will calculate the prevalence of dementias across racial and ethnic group compared to population estimates. We will compare risk factors of patients who have probable dementia versus possible dementia using logistic regression correcting for demographics. Risk factors tested will include drug exposures, lab measurement, demographics, health access, and other survey questions. We will compare risk factors across racial and ethnic groups.

Anticipated Findings

We expect to find that dementias are underdiagnosed the EHR, more so in underrepresented racial and ethnic groups, and that risk factors for underdiagnosis include demographics, comorbidities, medications, and healthcare access, which will differ across racial and ethnic groups. These findings may lead to racially and ethnically specific strategies to improve the early and appropriate diagnosis of dementias, which can initiate multi-disciplinary care and treatment.

Demographic Categories of Interest

  • Race / Ethnicity
  • Age
  • Access to Care
  • Education Level
  • Income Level

Data Set Used

Registered Tier

Research Team

Owner:

  • Samantha Shah - Project Personnel, University of California, Los Angeles

Duplicate of Preparing to Investigate the Genetics of NDDs in the AoU Cohort

Querying the AoU WGS data to quantify the statistical power of using the AoU cohort dataset to independently investigate the genetic architecture of neurodegenerative diseases such as Alzheimer’s Disease (AD), Parkinson’s Disease (PD), Frontotemporal Dementia (FTD), and other age-associated neurodegenerative…

Scientific Questions Being Studied

Querying the AoU WGS data to quantify the statistical power of using the AoU cohort dataset to independently investigate the genetic architecture of neurodegenerative diseases such as Alzheimer’s Disease (AD), Parkinson’s Disease (PD), Frontotemporal Dementia (FTD), and other age-associated neurodegenerative diseases.

Project Purpose(s)

  • Disease Focused Research (neurodegenerative disease, Ageing)
  • Ancestry

Scientific Approaches

We will use this workspace to become familiar with how to retrieve phenotypic and genomic data from the AoU cohort. Using Python and/or R (via JupyterNotebooks) we will perform a prospective statistical power analysis of the AoU dataset to determine the applicability of future, secondary analysis to help bridge the gap between genetic association and functional impact with methods such as GWAS, PheWAS, and Polygenic Risk Score (PRS). Additionally, our lab is interested in investigating the role of genetics in neurodegenerative diseases in underrepresented populations and therefore will investigate whether the diversity and size of the AoU cohort will allow us to perform population-specific analysis of the genetic contributions to neurodegenerative diseases.

Anticipated Findings

We expect to find that the size of the AoU cohort will have the statistical power necessary to perform our desired secondary analysis.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Eve Gardner - Project Personnel, Van Andel Research Institute

MCI Project

Mild cognitive impairment (MCI) is a decline of mental function. It falls between the expected decline of normal aging, and the more serious decline of dementia. It increases a person’s risk of Alzheimer’s disease and other forms of dementia. The…

Scientific Questions Being Studied

Mild cognitive impairment (MCI) is a decline of mental function. It falls between the expected decline of normal aging, and the more serious decline of dementia. It increases a person’s risk of Alzheimer’s disease and other forms of dementia.

The goal of our analysis is aiming to develop a risk scoring system for the prediction of the conversion of cognitively normal people into patients with Mild Cognitive Impairment (MCI) to provide a reliable tool for the prevention of MCI.

Project Purpose(s)

  • Disease Focused Research (Mild Cognitive Impairment )
  • Population Health
  • Methods Development

Scientific Approaches

We may use statistical models including Least Absolute Shrinkage and Selection Operator (LASSO) regression, logistic regression, correlation analysis, Cox proportional hazards regression analysis, etc. to develop a scoring system to determine the risk of a person to have MCI.

Anticipated Findings

We will investigate risk factors associated with mild cognitive impairment (MCI) like gender, race, diabetes, etc., and develop risk score to that allows physician to determine the risk of developing MCI in populations 45+. Our anticipated findings can help in the early detection of MCI. Patients with suspected MCI should undergo a comprehensive history and physical examination at an earlier age to distinguish MCI from normal aging or dementia.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Registered Tier

Research Team

Owner:

Preparing to Investigate the Genetics of NDDs in the AoU Cohort

Querying the AoU WGS data to quantify the statistical power of using the AoU cohort dataset to independently investigate the genetic architecture of neurodegenerative diseases such as Alzheimer’s Disease (AD), Parkinson’s Disease (PD), Frontotemporal Dementia (FTD), and other age-associated neurodegenerative…

Scientific Questions Being Studied

Querying the AoU WGS data to quantify the statistical power of using the AoU cohort dataset to independently investigate the genetic architecture of neurodegenerative diseases such as Alzheimer’s Disease (AD), Parkinson’s Disease (PD), Frontotemporal Dementia (FTD), and other age-associated neurodegenerative diseases.

Project Purpose(s)

  • Disease Focused Research (neurodegenerative disease, Ageing)
  • Ancestry

Scientific Approaches

We will use this workspace to become familiar with how to retrieve phenotypic and genomic data from the AoU cohort. Using Python and/or R (via JupyterNotebooks) we will perform a prospective statistical power analysis of the AoU dataset to determine the applicability of future, secondary analysis to help bridge the gap between genetic association and functional impact with methods such as GWAS, PheWAS, and Polygenic Risk Score (PRS). Additionally, our lab is interested in investigating the role of genetics in neurodegenerative diseases in underrepresented populations and therefore will investigate whether the diversity and size of the AoU cohort will allow us to perform population-specific analysis of the genetic contributions to neurodegenerative diseases.

Anticipated Findings

We expect to find that the size of the AoU cohort will have the statistical power necessary to perform our desired secondary analysis.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Eve Gardner - Project Personnel, Van Andel Research Institute

Itch and Dementia

Itch is a common clinical phenomenon which worsens with age, and up to one-third of elderly patients report clinically significant itch with moderate impact on their quality of life. Itch and neurological conditions including Alzheimer’s disease are also significantly associated…

Scientific Questions Being Studied

Itch is a common clinical phenomenon which worsens with age, and up to one-third of elderly patients report clinically significant itch with moderate impact on their quality of life. Itch and neurological conditions including Alzheimer’s disease are also significantly associated in aging humans. For example, bullous pemphigoid – a pruritic autoimmune skin disorder whose incidence rises with age – increases the odds of dementia by 10-fold (95% confidence interval 5.4-17.8]). The association between age-related non-neoplastic skin conditions and neurological disorders can be due to shared risk factors (e.g., aging, exposure) or upstream pathophysiology (systemic inflammation, inflammaging), but studies dissecting these potential mechanistic relationships are lacking. In this study, I intend to evaluate the association between dementia and pruritus in an aging population.

Project Purpose(s)

  • Disease Focused Research (dementia)

Scientific Approaches

I will use descriptive statistics to characterize pruritic skin diseases in patients with and without dementia including demographic information, inflammatory skin diseases, dementia subtypes, other comorbid medical conditions, and use of specific medications that have been associated with the development of dementia in prior literature (e.g. sedating anti-histamines). I will use basic statistical techniques to assess these relationships including chi-squared analyses, t-tests, Pearson correlation coefficients, and linear multivariable linear regression models.

Anticipated Findings

I anticipate that these analyses will demonstrate an association between dementia and pruritus, measured by presence/absence of pruritic inflammatory skin diseases. These data will be used to inform future studies on these associations as well as alternative therapeutic options for patients with dementia and itch.

Demographic Categories of Interest

  • Age

Data Set Used

Registered Tier

Research Team

Owner:

  • Emily Cole - Early Career Tenure-track Researcher, Emory University
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