Vincent Lam
Research Fellow, National Institutes of Health (NIH)
8 active projects
Exploring the Landscape of Health Disparities in All of Us
Scientific Questions Being Studied
The goal of this project is to develop an interactive web browser with which All of Us researchers can conveniently view group-specific prevalences
and inter-group prevalence differences for hundreds of diseases.
Project Purpose(s)
- Methods Development
Scientific Approaches
The interactive web browser will be developed using the Shiny package in R. ICD codes will be extracted from All of Us EHR data and converted to
phecodes for the purpose of designating cases and controls. Case and control counts will be used to make prevalence calculations.
Anticipated Findings
The interactive web browser will allow All of Us researchers to swiftly identify health disparities related to their disease(s) of interest,
accelerating the process of forming health disparities-related research questions.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Vincent Lam - Research Fellow, National Institutes of Health (NIH)
Collaborators:
- Jeff Kramer - Undergraduate Student, Georgia Institute of Technology
Smoking and Genetic Ancestry
Scientific Questions Being Studied
We seek to determine how genetic ancestry is associated with smoking behavior among individuals identifying as Hispanic or Latino in the All of Us cohort.
Project Purpose(s)
- Ancestry
Scientific Approaches
We will be performing GWAS using Hail, admixture regression using multivariable logistic regression in R, and other related genetic / genomic analyses.
Anticipated Findings
We expect to see smoking behavior vary across individuals of different Hispanic / Latino subcontinental ancestry fractions.
Demographic Categories of Interest
- Race / Ethnicity
Data Set Used
Controlled TierResearch Team
Owner:
- Vincent Lam - Research Fellow, National Institutes of Health (NIH)
Collaborators:
- Sonali Gupta - Research Assistant, National Institutes of Health (NIH)
- Somayeh Hooshmand - Research Fellow, National Heart, Lung, and Blood Institute (NIH - NHLBI)
- Amanda Hinerman - Project Personnel, National Heart, Lung, and Blood Institute (NIH - NHLBI)
iSDI vs zSDI
Scientific Questions Being Studied
The aim of this study is to determine whether individual or area-specific socioeconomic status (SES) influences disease risk in different ways and whether these two forms of SES interact to influence disease risk.
Project Purpose(s)
- Social / Behavioral
Scientific Approaches
We plan to use Brokamp et. al.'s community-level deprivation index as a metric for area-level SES (zSDI) and our own individual-level deprivation index (iSDI) as a metric for individual SES. We plan to use the stats package in R for logistic regression.
Anticipated Findings
We expect to see differences in how the two types of SES affect disease risk and we expect them to interact. Our study's findings could inform decisions on whether to focus on area or individual SES in epidemiological studies and whether to consider one type of SES in the context of the other.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierThe comorbid landscape of health disparities in the All of Us Research Project
Scientific Questions Being Studied
The purpose of this study is to determine how comorbidities differ by race / ethnicity across the All of Us participant cohort.
Project Purpose(s)
- Population Health
Scientific Approaches
Machine learning classifiers from scikitlearn will be used to test how well race / ethnicity can be predicted from an individual's particular set of comorbities.
Anticipated Findings
It is expected that specific comorbidities will be more prevalent among minority populations. Such results would inform public efforts to combat race-based health disparities.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Vincent Lam - Research Fellow, National Institutes of Health (NIH)
Collaborators:
- Sonali Gupta - Research Assistant, National Institutes of Health (NIH)
Hispanic / Latino Analyses
Scientific Questions Being Studied
The goal of this study is to study the intra-ethnic health disparities among Hispanic participants in the All of Us cohort. Specifically, we would like to see how racial identity and Hispanic ethnicity interact, as well as how genetic ancestry and Hispanic ethnicity interact to influence disease risk, using T2D as our disease of interest.
Project Purpose(s)
- Disease Focused Research (Type 2 Diabetes)
- Ancestry
Scientific Approaches
We plan to use the glm function in the stats package in R to model interaction effects between racial identity and Hispanic ethnicity, as well as the interaction effects between genetic ancestry and Hispanic ethnicity.
Anticipated Findings
We currently hypothesize that racial identity will have a greater effect on disease outcome than ethnicity and that the impact that racial identity will have on disease outcome will vary between Hispanic and non-Hispanic participants. We also anticipate that the impact of ancestry on disease outcome will vary between Hispanic and non-Hispanic participants.
Demographic Categories of Interest
- Race / Ethnicity
Data Set Used
Controlled TierResearch Team
Owner:
- Vincent Lam - Research Fellow, National Institutes of Health (NIH)
- Sonali Gupta - Research Assistant, National Institutes of Health (NIH)
- Shivam Sharma - Graduate Trainee, Georgia Institute of Technology
Individual Level Deprivation Index
Scientific Questions Being Studied
We wish to develop an individual-level socioeconomic deprivation index in All of Us that can make up for limitations inherent in the place-based deprivation index that All of Us uses.
Project Purpose(s)
- Methods Development
Scientific Approaches
We plan to perform principal component analyses on different socioeconomic variables in the All of Us dataset and to perform statistical tests to see how such variables correlate.
Anticipated Findings
We expect to be able to develop an individual-level deprivation index that can provide researchers with a metric for deprivation to use in cases in which a place-based deprivation index may not be appropriate.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Vincent Lam - Research Fellow, National Institutes of Health (NIH)
Collaborators:
- Sonali Gupta - Research Assistant, National Institutes of Health (NIH)
Reproducing the results of a UK Biobank study on Type 2 Diabetes
Scientific Questions Being Studied
The study I am trying to replicate attempted to determine whether genetic ancestry and socioeconomic deprivation (SED) interact to affect one's risk of developing type 2 diabetes and whether this interaction varies depending on genetic ancestry type. Such insight may help inform future health interventions.
Project Purpose(s)
- Other Purpose (I am a research trainee trying to familiarize myself with both the All of Us workspace and working with All of Us data. To accomplish this, I will be attempting to replicate the results of a study conducted by my lab, which was published as an article titled "Socioeconomic deprivation and genetic ancestry interact to modify type 2 diabetes ethnic disparities in the United Kingdom". )
Scientific Approaches
Case / control cohorts will be made with individuals with type 2 diabetes and those without the disease, respectively. Analyses with be done in Python and R.
Anticipated Findings
The results are expected to those of the study I am attempting to replicate - socioeconomic deprivation is expected to increase the likelihood of developing type 2 diabetes among all demographic groups, but this effect is expected to be especially pronounced in individuals of African and Asian ancestry.
Demographic Categories of Interest
- Race / Ethnicity
- Access to Care
- Education Level
- Income Level
Data Set Used
Controlled TierResearch Team
Owner:
- Vincent Lam - Research Fellow, National Institutes of Health (NIH)
Collaborators:
- Sonali Gupta - Research Assistant, National Institutes of Health (NIH)
- Shivam Sharma - Graduate Trainee, Georgia Institute of Technology
- Robin Kee - Graduate Trainee, National Institutes of Health (NIH)
- Leonardo Marino-Ramirez - Senior Researcher, National Institutes of Health (NIH)
Ancestry-amplified effects of SED on T2D health disparities
Scientific Questions Being Studied
Observe how genetic ancestry and self-reported race influence the effect of socioeconomic deprivation (SED) on type 2 diabetes risk.
Project Purpose(s)
- Disease Focused Research (type 2 diabetes mellitus)
Scientific Approaches
A cohort will be created from All of Us data consisting participants for whom known race, ethnicity, age, and sex are available. Exploratory analyses, such as logistic regression, will be performed on the cohort in order to assess factors relevant to T2D risk, identify disparities, and observe how the effect of SED on T2D risk varies between racial / genetic ancestry groups.
Anticipated Findings
It is expected that there will be a positive correlation between SED and T2D risk, with this effect being particularly pronounced among Black and Hispanic Americans. This project would elucidate race-based T2D disparities in the United States while also yielding insight into what may be causing these disparities.
Demographic Categories of Interest
- Race / Ethnicity
Data Set Used
Controlled TierRequest a Review of this Research Project
You can request that the All of Us Resource Access Board (RAB) review a research purpose description if you have concerns that this research project may stigmatize All of Us participants or violate the Data User Code of Conduct in some other way. To request a review, you must fill in a form, which you can access by selecting ‘request a review’ below.
