Henry Taylor
Graduate Trainee, National Human Genome Research Institute (NIH-NHGRI)
2 active projects
Trans-ancestry analysis of Type 2 Diabetes (v2)
Scientific Questions Being Studied
Previous genetic studies have successfully identified >240 loci associated with type 2 diabetes (T2D). However, many of the identified loci lie in non-coding regions of the genome, masking the underlying “effector gene”. Additionally, these studies were primarily performed in individuals of European and East Asian ancestry. As genetic findings are integrated into the clinic, this limited genetic understanding threatens to exacerbate existing health disparities among non-European communities disproportionately suffering from T2D and T2D-related health complications. Expanding our genetic understanding into non-European ancestries is essential as these studies will mitigate such health disparities and improve our ability to identify causal loci and mechanisms. In this study, I will leverage the diversity found within All of Us to perform a trans-ancestry genetic analysis of T2D, identifying likely causal variants and evaluating their potential for clinical utility.
Project Purpose(s)
- Disease Focused Research (type 2 diabetes mellitus)
- Drug Development
- Ancestry
Scientific Approaches
Using well-established techniques in statistical genetics, I will (1) conduct a genome wide association study of common variants, as well as other forms of genetic variation (e.g., rare variants, copy number variations), to identify trans-ancestry and ancestry-specific disease-associated loci, (2) use statistical and functional fine-mapping techniques to identify the likely causal variants at disease-associated loci, validating my findings with experimental approaches, and (3) evaluate the clinical utility of my findings through polygenic scores (PGSs) and screening for potential targets of drug repurposing. For these analyses, I will use all participants with genetic data (whole genome and SNP-array). I will develop a phenotypic algorithm to classify participants into T2D cases and controls based on previously published work in electronic health records.
Anticipated Findings
Genetic studies of T2D have already provided valuable insight into disease pathophysiology. However, the vast majority of these studies have been performed in European and East Asian ancestries, threatening to exacerbate existing health disparities in populations carrying a disproportionate disease burden as genetics enters the clinic through preventative and therapeutic interventions. In the present study, I aim to address these shortcomings by leveraging the diversity found within All of Us to expand our genetic understanding of T2D. Based on the prior success of similar studies, I expect to identify many rare and common T2D-associated loci that are shared across ancestries as well as ancestry-specific. Combined with experimental and computational approaches, I will use these results to identify variants that are likely causal for T2D, propose the mechanism by which these variants contribute to T2D risk, and propose ways to translate my findings into clinical intervention strategies.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Henry Taylor - Graduate Trainee, National Human Genome Research Institute (NIH-NHGRI)
Trans-ancestry analysis of Type 2 Diabetes
Scientific Questions Being Studied
Previous genetic studies have successfully identified >240 loci associated with type 2 diabetes (T2D). However, many of the identified loci lie in non-coding regions of the genome, masking the underlying “effector gene”. Additionally, these studies were primarily performed in individuals of European and East Asian ancestry. As genetic findings are integrated into the clinic, this limited genetic understanding threatens to exacerbate existing health disparities among non-European communities disproportionately suffering from T2D and T2D-related health complications. Expanding our genetic understanding into non-European ancestries is essential as these studies will mitigate such health disparities and improve our ability to identify causal loci and mechanisms. In this study, I will leverage the diversity found within All of Us to perform a trans-ancestry genetic analysis of T2D, identifying likely causal variants and evaluating their potential for clinical utility.
Project Purpose(s)
- Disease Focused Research (type 2 diabetes mellitus)
- Drug Development
- Ancestry
Scientific Approaches
Using well-established techniques in statistical genetics, I will (1) conduct a genome wide association study of common variants, as well as other forms of genetic variation (e.g., rare variants, copy number variations), to identify trans-ancestry and ancestry-specific disease-associated loci, (2) use statistical and functional fine-mapping techniques to identify the likely causal variants at disease-associated loci, validating my findings with experimental approaches, and (3) evaluate the clinical utility of my findings through polygenic scores (PGSs) and screening for potential targets of drug repurposing. For these analyses, I will use all participants with genetic data (whole genome and SNP-array). I will develop a phenotypic algorithm to classify participants into T2D cases and controls based on previously published work in electronic health records.
Anticipated Findings
Genetic studies of T2D have already provided valuable insight into disease pathophysiology. However, the vast majority of these studies have been performed in European and East Asian ancestries, threatening to exacerbate existing health disparities in populations carrying a disproportionate disease burden as genetics enters the clinic through preventative and therapeutic interventions. In the present study, I aim to address these shortcomings by leveraging the diversity found within All of Us to expand our genetic understanding of T2D. Based on the prior success of similar studies, I expect to identify many rare and common T2D-associated loci that are shared across ancestries as well as ancestry-specific. Combined with experimental and computational approaches, I will use these results to identify variants that are likely causal for T2D, propose the mechanism by which these variants contribute to T2D risk, and propose ways to translate my findings into clinical intervention strategies.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Henry Taylor - Graduate Trainee, National Human Genome Research Institute (NIH-NHGRI)
Collaborators:
- Huan Mo - Research Fellow, National Human Genome Research Institute (NIH-NHGRI)
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