The Arkansas Integrative Metabolic Research Center (AIMRC) will host Heyjun Park, an assistant professor of international health at the Johns Hopkins Bloomberg School of Public Health, at 10:45 a.m. Wednesday, Oct. 22, in Bell Engineering 2267. Park's research identifies biological and behavioral markers linked to heart disease, diabetes and pregnancy outcomes, using multi-omics data and wearable health technologies.

Abstract: This talk highlights how precision nutrition can be advanced by integrating multi-omics data and real-time digital biomarkers to improve metabolic health, particularly in individuals at risk for type 2 diabetes. Using machine learning, habitual dietary patterns, especially those rich in refined carbohydrates, were identified and shown to be associated with host metabolism through gut microbial mediation. Moreover, individuals with insulin resistance exhibited weaker correlations among diet, metabolites and gut microbiome, suggesting impaired metabolic responsiveness. This talk also emphasizes the use of digital biomarkers from continuous glucose monitors (CGM) and wearables to capture daily lifestyle rhythms. Notably, integrated prediction models showed that distinct sets of lifestyle behaviors (diet, physical activity and sleep) predicted specific metabolic subphenotypes such as insulin resistance and incretin dysfunction. Together, these findings support a framework for developing targeted, omics-informed lifestyle interventions tailored to individual metabolic and behavioral phenotypes.

Biography: Park earned her Ph.D. in nutritional sciences from Cornell University and completed her clinical dietetic internship training at the University of California, San Francisco Medical Center. After earning the registered dietitian (RD) credential, Park pursued her postdoctoral research training in the Department of Genetics at Stanford University. During her doctoral studies at Cornell, her research focused on vitamin D status and metabolism among women in different reproductive states (i.e., pregnancy and lactation) and their relationship with bone health outcomes in both mothers and fetuses. Her postdoctoral research at Stanford was focused on using a big data approach to examine the impact of longitudinal dietary habits (nutrient and food group intakes, as well as meal timing) on glucose metabolism in individuals at risk for metabolic syndrome, including type 2 diabetes. Her current research focuses on identifying molecular and behavioral biomarkers associated with cardiometabolic disease risk and adverse pregnancy/birth outcomes through the use of multi-omics profiling, such as metabolome and microbiome data, in combination with wearable technologies (e.g., continuous glucose monitoring, actigraphy).

This event is supported by NIGMS of the National Institutes of Health under award number P20GM139768. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Please contact Kimberley Fuller, fullerk@uark.edu, for more information.

For those unable to attend in person, this seminar will also be available via Zoom.