Miranda Sharp
Graduate Trainee, Brigham Young University
1 active project
Metabolism v7 mfd
Scientific Questions Being Studied
Metabolic diseases are a global epidemic. They occur when cells allocate too many of their primary resources towards one pathway, such as lipid production, at the expense of other crucial pathways, such as energy production. Understanding how cells control the pivotal point of allocating glucose towards lipid or energy production is key to developing effective treatments for these and other common metabolic diseases. PAS kinase (PASK) is a nutrient sensing protein kinase that regulates this critical metabolic node of lipid versus respiratory metabolism. PASK controls many of the hallmark pathways associated with heart disease, diabetes, cancer, and even neurodegenerative disease yet little is known about PASK alleles associated with human disease. Herein we propose to conduct the first large-scale analysis to identify PASK alleles associated with human disease.
Project Purpose(s)
- Ancestry
Scientific Approaches
Analyze common and rare variants in USF1, ATXN2, and PASK compared to triglycerides, weight, cardiovascular measures, exercise levels and COVID-19 results.
Perform a phenome-wide association study (PheWAS) with common and rare variants in USF1, ATXN2, and PASK. Common variants in each of these three genes will be regressed against phenotypes from electronic health record data.
Anticipated Findings
We target PASK as well as two of its substrates for our study. Due to their regulation of the critical node of glucose partitioning to lipid versus respiratory metabolism, we propose to uncover the influence of PASK, USF1, and ATXN2 variants on a variety of human phenotypes and classes of disease, from hyperlipidemia and diabetes to neurodegenerative disorders using the All of Us dataset.
In addition to the wide variety of phenotypic data that will aid in understanding the influence of variation in cellular respiration and triglyceride levels, the ancestral diversity represented by the individuals in the dataset will allow us to identify patterns and variants that differ or are similar across ancestry, defining effects common to humankind while opening further studies on multigene, secondary variants.
Demographic Categories of Interest
This study will not center on underrepresented populations.
Data Set Used
Controlled TierResearch Team
Owner:
- Miranda Sharp - Graduate Trainee, Brigham Young University
- Mary Davis - Early Career Tenure-track Researcher, Brigham Young University
- Lydia Howell - Graduate Trainee, Brigham Young University
- Kylee Bates - Undergraduate Student, Brigham Young University
- Christian Betteridge - Undergraduate Student, Brigham Young University
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