Investigating the regulation of central metabolism as key to human health and disorders through the association of PASK, USF1 and ATXN2 with phenotypes and disorders in the All of Us database

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Metabolic dysregulation lies at the heart of most disorders, from hyperlipidemia and diabetes to cancer and neurodegenerative disorders. Sensory protein kinases, which sense cellular metabolites and regulate metabolism accordingly, lie at the heart of metabolic homeostasis. PAS kinase (PASK) is a nutrient sensing protein kinase that regulates partitioning of glucose to lipid production versus respiratory metabolism. PASK deficient mice are resistant to liver triglyceride accumulation and display increased respiration when on a high-fat or high-fat high-sugar diet. In addition, PASK deficient mice display altered insulin metabolism in several studies, with PASK alleles associated with Maturity Onset Diabetes of the Young (MODY) in a small familial study. Our long-term goal is to characterize the role of PASK in human disease, including the molecular pathways by which it regulates central metabolism. Our short-term goal described herein is to conduct the first large-scale analysis of PASK alleles (and alleles of its protein substrates) associated with human disease. The Grose lab has identified two PASK substrates associated with lipid and respiratory metabolism, namely Upstream Stimulatory Factor 1 (USF1) and Ataxin-2 (ATXN2), the primary focus of our current R15. Herein Dr. Julianne Grose, a molecular biologist, teams up with Dr. Mary Davis, a biomedical informaticist and human geneticist, 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 cancer and neurodegenerative disorders. The All of Us dataset makes this possible. All of Us provides phenotypes from electronic health records, basic vitals, surveys, exercise data (e.g. Fitbit) and COVID- 19 results, as well as whole genome sequencing. In our first Aim we will analyze common and rare variants in PASK, USF1, and ATXN2 compared to triglycerides, weight, cardiovascular measures, exercise levels and COVID-19 results. In our second Aim, we will perform a phenome-wide association study (PheWAS), in which variants in PASK, USF1, and ATXN2 will be regressed against phenotypes from electronic health record data. In addition to the wide variety of phenotypic data, 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, identifying both multigene effects due to ancestry and conserved effects common to humankind. Combined, the mechanistic results from our R15 and the informatic results from the supplement described herein further our progress towards holistic treatments and preventions for human disorders.