Position title: Associate Director, Metabolomics Core; Assistant Professor of Biochemistry
We use mass spectrometry based lipidomics to study the regulation of metabolic disease by lipid signaling. We use both mice as a model organism and plasma from human population studies to explore the impact of lipid signaling on physiology and energy expenditure. In our mouse research we combine RNA-seq and lipidomic datasets to identify novel transcriptional regulators of lipid metabolism. We have been able to identify novel regulators of plasmalogens, bismonoacylglycerophosphates, and specific species of triacylglycerols. Increases in these various lipids are associated with type 2 diabetes in humans. In our human population studies we are identifying novel biomarkers of metabolic syndrome in diverse populations. In collaboration with Chris Coe, we began assessing plasma lipid changes in the Midlife in the US (MIDUS) human population study using untargeted lipidomics. Through correlation analysis, we were able to observe that current clinical markers of metabolic disease were poor predictive markers of glucose homeostasis and cardiovascular health in African American populations. Using machine learning on plasma lipidomics MIDUS participants, we were able to identify that arachidonic acid containing lipids and markers of inflammation were predictive markers of metabolic disease. We are performing targeted assessment of these lipid markers in a second human population study the Survey of the Health of Wisconsin (SHOW).