Tam Tran

National Institutes of Health (NIH)

7 active projects

CAC - NIAID - Dr. Guerrerio - Loeys-Dietz syndrome

Collaboration between CAC and Drs. Pam Guerrerio (NIAID) and Tony Guerrerio (Johns Hopkins). They research Loeys-Dietz syndrome (LDS), food and environmental allergies in LDS, and potential modifiers of disease in LDS. The RPC is developing collaboration with them, but some…

Scientific Questions Being Studied

Collaboration between CAC and Drs. Pam Guerrerio (NIAID) and Tony Guerrerio (Johns Hopkins). They research Loeys-Dietz syndrome (LDS), food and environmental allergies in LDS, and potential modifiers of disease in LDS.

The RPC is developing collaboration with them, but some interesting questions came up that we all thought the Cohort Analytics Core could potentially help with.

Some possible ideas that were discussed:

1: Incidence of variants in LDS related genes
2: PheWAS for LDS related genes/variants
3: Potential to identify modifiers of disease that may be able to be further investigated through reverse phenotyping

Project Purpose(s)

  • Disease Focused Research (Loeys-Dietz syndrome)

Scientific Approaches

For CAC, we will utilize our tools on AOU Researcher Workbench to look at variants of genes of interest (e.g., TGFBR1, TGFBR2, SMAD3, TGFB2, TGFB3, SMAD2) and potentially do genome/phenome wide association studies as well as other potential genetic analyses.

Anticipated Findings

Dr. Guerrero would like to see associations of risk variants and disease outcome in AoU data. We will look at some genes of interests and might focus on certain variants of these genes.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Tam Tran - Other, National Institutes of Health (NIH)

CAC - NEI - Dr.Hufnagel - TYR PheWAS

This workspace is for collaboration work between the Cohort Data Analytics Core (CDAC) with Dr. Hufnagel at National Eye Institute. The CDAC will assist Dr. Hufnagel on technical analysis on AoU Research Workbench. Dr. Hufnagel is interested in TYR SNP…

Scientific Questions Being Studied

This workspace is for collaboration work between the Cohort Data Analytics Core (CDAC) with Dr. Hufnagel at National Eye Institute. The CDAC will assist Dr. Hufnagel on technical analysis on AoU Research Workbench.

Dr. Hufnagel is interested in TYR SNP R402Q, which is the anchor SNP of the phenotype of interest, and other SNPs that exist in cis with R402Q that could exacerbate the phenotype, such as S192Y.

Project Purpose(s)

  • Disease Focused Research (iris hypopigmentation related to TYR R402Q SNP)

Scientific Approaches

The main approach is to look at statistics and phenotypes of interested cohorts bearing specific TYR SNPs, and run PheWAS for SNPs of interest.

Anticipated Findings

The anticipated findings is to be able to find out the relationships between phenotypes and different TYR genotypes, especially those with double alternative variants of both R402Q and other SNPs.

This is a rare genotype/disease and the large and diverse population of AoU could help this research greatly. Any information gain from this study should be very valuable in studying this genetic disease.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Tam Tran - Other, National Institutes of Health (NIH)

Type 2 Diabetes GWAS Demo

This notebook will be used to practice building cohort using big query and then run a GWAS analysis with Hail. The case study will focus on type 2 diabetes. The main purpose is learning the mentioned methods.

Scientific Questions Being Studied

This notebook will be used to practice building cohort using big query and then run a GWAS analysis with Hail. The case study will focus on type 2 diabetes. The main purpose is learning the mentioned methods.

Project Purpose(s)

  • Educational

Scientific Approaches

Data will be selected using big query following Type 2 Diabetes algorithm on PheKB. Selected data will then be used for GWAS analysis with Hail on Google Cloud.

Anticipated Findings

Anticipated findings would be showing relevant SNPs associated with type 2 diabetes as the results of GWAS analysis. This case study is only to learn using big query and Hail.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Tam Tran - Other, National Institutes of Health (NIH)

Collaborators:

  • Huan Mo - Research Fellow, National Institutes of Health (NIH)
  • Tracey Ferrara - Project Personnel, National Institutes of Health (NIH)
  • Jian Dai - Project Personnel, National Institutes of Health (NIH)
  • Slavina Goleva - Research Fellow, National Institutes of Health (NIH)
  • David Schlueter - Research Fellow, National Institutes of Health (NIH)
  • Chenjie Zeng - Research Fellow, National Institutes of Health (NIH)
  • Ariel Williams - Research Fellow, National Institutes of Health (NIH)
  • Anav Babbar - Other, National Institutes of Health (NIH)

_TCT_Demos_

1. Socio-Economic Metrics: How to retrieve participants' socio-economic data from the CDR. 2. Observation Date: How to query and plot an observation date using survey completion date as example. 3. Demographics: Examples of how to query and plot participant demographic…

Scientific Questions Being Studied

1. Socio-Economic Metrics: How to retrieve participants' socio-economic data from the CDR.
2. Observation Date: How to query and plot an observation date using survey completion date as example.
3. Demographics: Examples of how to query and plot participant demographic data.
4. Death Cause: How to retrieve and plot deceased participants' death causes.

Project Purpose(s)

  • Educational
  • Methods Development
  • Other Purpose (This is a workspace to keep demo notebooks for reference purpose.)

Scientific Approaches

The notebooks are demonstrations of different useful methods to study data on AoU. The methods are varied, e.g. GWAS, PheWAS, BigQuery, etc.

Anticipated Findings

By reading and running the notebooks in this Tutorial Workspace, you will understand the following: All of Us data are made available in two Curated Data Repository: the Registered Tier and Controlled Tier. The latter was subject to more relaxed privacy rules relative to the Registered Tier. As a result, you can expect to find more concept ids in certain data types such as EHR and Survey.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Tam Tran - Other, National Institutes of Health (NIH)

Collaborators:

  • Huan Mo - Research Fellow, National Institutes of Health (NIH)

StellarPGx demo

Exploring the possibility to use StellarPGx package (https://github.com/SBIMB/StellarPGx) to study CYP2D6 on AoU. This is mainly for trying out to see what works and what would not work on AoU technically.

Scientific Questions Being Studied

Exploring the possibility to use StellarPGx package (https://github.com/SBIMB/StellarPGx) to study CYP2D6 on AoU. This is mainly for trying out to see what works and what would not work on AoU technically.

Project Purpose(s)

  • Educational

Scientific Approaches

We would use a small sample of genomic data to test the functions of StellarPGx package.

Description from StellarPGx github:

StellarPGx: Calling star alleles in highly polymorphic pharmacogenes by leveraging genome graph-based variant detection.
Model gene: CYP2D6

Other CYP450 genes supported: CYP2A6, CYP2B6, CYP2C19, CYP2C9, CYP2C8, CYP3A4, CYP3A5, CYP1A1, CYP1A2, CYP2E1, CYP4F2

Non-CYP450 genes supported: CYPOR (POR)

StellarPGx is built using Nextflow, a workflow management system that facilitates parallelisation, scalability, reproducibility and portability of pipelines via Docker and Singularity technologies.

Anticipated Findings

This is mainly for tool exploration purpose, there is no specific research goals or anticipated findings.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Tam Tran - Other, National Institutes of Health (NIH)

Collaborators:

  • Huan Mo - Research Fellow, National Institutes of Health (NIH)
  • Chenjie Zeng - Research Fellow, National Institutes of Health (NIH)

Iris Hypopigmentation PheWAS Demo

A demo on AoU to learn about iris hypopigmentation.

Scientific Questions Being Studied

A demo on AoU to learn about iris hypopigmentation.

Project Purpose(s)

  • Disease Focused Research (iris hypopigmentation)

Scientific Approaches

A demo on AoU to learn about iris hypopigmentation.

Anticipated Findings

A demo on AoU to learn about iris hypopigmentation.

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Tam Tran - Other, National Institutes of Health (NIH)

Collaborators:

  • Tracey Ferrara - Project Personnel, National Institutes of Health (NIH)
  • Onajia Stubblefield - Graduate Trainee, National Institutes of Health (NIH)
  • Huan Mo - Research Fellow, National Institutes of Health (NIH)
  • Jian Dai - Project Personnel, National Institutes of Health (NIH)
  • Jacob Keaton - Other, National Institutes of Health (NIH)
  • Slavina Goleva - Research Fellow, National Institutes of Health (NIH)
  • David Schlueter - Research Fellow, National Institutes of Health (NIH)
  • Chenjie Zeng - Research Fellow, National Institutes of Health (NIH)
  • Ariel Williams - Research Fellow, National Institutes of Health (NIH)
  • Anav Babbar - Other, National Institutes of Health (NIH)

Duplicate of Role of pathogenic alleles in a general population

Pathogenic variants (alleles) of genes are diagnosed with ACMG criteria and reported in ClinVar. However, although each of these alleles are very rare (as one of the ACMG diagnostic criteria) in the population, each healthy person may carry multiple of…

Scientific Questions Being Studied

Pathogenic variants (alleles) of genes are diagnosed with ACMG criteria and reported in ClinVar. However, although each of these alleles are very rare (as one of the ACMG diagnostic criteria) in the population, each healthy person may carry multiple of pathogenic variants due to the large number of kinds of these variants across the human genome. Also, most of these pathogenic variants were discovered from patients with diseases and the penetrance of the phenotypes can be over-estimated. In this study, we will survey the carriers of these pathogenic variants in the general population and understand their true phenotypes in an unbiased cohort. Particularly, we are interested in pathogenic variants that are associated with malignant hyperthermia during anesthesia .

Project Purpose(s)

  • Disease Focused Research (malignant hyperthermia)
  • Drug Development
  • Methods Development

Scientific Approaches

Data: Whole genome sequencing and phenotype.
Methods: GWAS, PheWAS, Reversed Phenotyping, Phenomic risk scores.
We will first identified individuals who carries the pathogenic alleles, and perform PheWAS and reversed phenotyping to evaluate the behaviors of these alleles in an unbiased population. We will also validate phenomic risk scores (PheRS) to predict the carrier status of these pathogenic alleles.

Anticipated Findings

1. The prevalence of the carrier status of pathogenic alleles.
2. The phenotype impacts of these alleles in the general population
3. Validation of PheRS

Demographic Categories of Interest

This study will not center on underrepresented populations.

Data Set Used

Controlled Tier

Research Team

Owner:

  • Tam Tran - Other, National Institutes of Health (NIH)
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