Anav Babbar
National Human Genome Research Institute (NIH-NHGRI)
5 active projects
Hypothyroidism genomics v7
Scientific Questions Being Studied
In previous work, certain genetic variants were found to be associated with hypothyroidism using techniques such as GWAS and PheWAS. Current work will leverage the diversity of the All of Us data to replicate and confirm the association between those variants and hypothyroidism, and possibly identify new variants that are associated with hypothyroidism.
Project Purpose(s)
- Disease Focused Research (hypothyroidism)
- Ancestry
Scientific Approaches
Will use All of Us genetic data and genomic techniques such as GWAS/PheWAS to identify genomic variants that are associated with hypothyroidism. Tools used include Python, R, Hail, SQL, etc.
Anticipated Findings
We seek to replicate and confirm previously identified variants associated with hypothyroidism, while possibly identifying new variants that could become targets of further study to understand the disease process of hypothyroidism. The diversity of the All of Us dataset may allow us to find these new variants.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Anav Babbar - Other, National Human Genome Research Institute (NIH-NHGRI)
Collaborators:
- Ariel Williams - Research Fellow, National Human Genome Research Institute (NIH-NHGRI)
CYP2C19 Clopidogrel Response - v7
Scientific Questions Being Studied
Will use controlled tier data to identify association between CYP2C19 variants, clopidogrel usage, and rate of cardiac/clotting events post-MI/PCI.
Project Purpose(s)
- Disease Focused Research (Post-MI/PCI Clopidogrel interaction with CYP2C19 variants)
Scientific Approaches
WGS sequencing to identify participants with CYP2C19 variants;
EHR data to identify participants with hx MI/PCI/stenting;
Kaplan meier survival analysis
PheWAS
Anticipated Findings
Anticipate identifying how CYP2C19 variants interact with clopidogrel response post-MI/PCI with hopes of further clarifying role of CYP2C19 variants in drug processing and risk post-MI/stent
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierHypothyroidism genomics
Scientific Questions Being Studied
In previous work, certain genetic variants were found to be associated with hypothyroidism using techniques such as GWAS and PheWAS. Current work will leverage the diversity of the All of Us data to replicate and confirm the association between those variants and hypothyroidism, and possibly identify new variants that are associated with hypothyroidism.
Project Purpose(s)
- Disease Focused Research (hypothyroidism)
- Ancestry
Scientific Approaches
Will use All of Us genetic data and genomic techniques such as GWAS/PheWAS to identify genomic variants that are associated with hypothyroidism. Tools used include Python, R, Hail, SQL, etc.
Anticipated Findings
We seek to replicate and confirm previously identified variants associated with hypothyroidism, while possibly identifying new variants that could become targets of further study to understand the disease process of hypothyroidism. The diversity of the All of Us dataset may allow us to find these new variants.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Ariel Williams - Research Fellow, National Human Genome Research Institute (NIH-NHGRI)
- Anav Babbar - Other, National Human Genome Research Institute (NIH-NHGRI)
Collaborators:
- Huan Mo - Research Fellow, National Human Genome Research Institute (NIH-NHGRI)
- Tam Tran - Other, National Human Genome Research Institute (NIH-NHGRI)
- Slavina Goleva - Research Fellow, National Human Genome Research Institute (NIH-NHGRI)
- David Schlueter - Research Fellow, National Human Genome Research Institute (NIH-NHGRI)
- Chenjie Zeng - Research Fellow, National Human Genome Research Institute (NIH-NHGRI)
- Bennett Waxse - Research Fellow, National Institute of Allergy and Infectious Diseases (NIH - NIAID)
- Anas Awan - Project Personnel, National Human Genome Research Institute (NIH-NHGRI)
CYP2C19 Clopidogrel Response
Scientific Questions Being Studied
Will use controlled tier data to identify association between CYP2C19 variants, clopidogrel usage, and rate of cardiac/clotting events post-MI/PCI.
Project Purpose(s)
- Disease Focused Research (Post-MI/PCI Clopidogrel interaction with CYP2C19 variants)
Scientific Approaches
WGS sequencing to identify participants with CYP2C19 variants;
EHR data to identify participants with hx MI/PCI/stenting;
Kaplan meier survival analysis
PheWAS
Anticipated Findings
Anticipate identifying how CYP2C19 variants interact with clopidogrel response post-MI/PCI with hopes of further clarifying role of CYP2C19 variants in drug processing and risk post-MI/stent
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled Tierneural nets for gwas analysis
Scientific Questions Being Studied
Can we leverage deep learning to interrogate variant-phenotype relationships to a deeper extent than logistic regression allows? Will deep learning allow enhanced prediction of disease compared to PRS?
Project Purpose(s)
- Methods Development
- Ancestry
Scientific Approaches
Bigquery - query EHR data to build phenotype
Hail - Access WGS data
Tensorflow/keras - build deep learning neural net to predict phenotype from variants
Anticipated Findings
We hope to identify a novel way of analyzing WGS and phenotype data in order to improve identification of complex variant-variant relationships as well as potentially improve understanding of how multiple pathologies interact.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierRequest a Review of this Research Project
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