Traumatic brain injury results in a state of metabolic dysfunction with dynamic changes in oxidative metabolism and glucose consumption. A more comprehensive understanding of the metabolic derangements beyond changes in glucose utilization is currently lacking. We propose to use mass spectrometry to analyze the metabolome - the complete set of primary and secondary products of cellular metabolism - in a murine model of concussion. This approach will characterize hundreds of metabolites simultaneously, including those involved in glucose metabolism (including glycolysis and gluconeogenesis), essential fatty acids and their derivatives, vitamins and amino acids, Krebs cycle components, oxidative stress and lipid peroxidation pathway markers, inflammatory mediators, lipid metabolites (including those involved in fatty acid synthesis, triacylglycerol synthesis, phospholipids and membrane components), among others. We will use a published mouse model of repetitive mild concussion developed in our lab that results in robust cognitive deficits, in order to study the association between cognitive dysfunction and metabolomic derangements.
In Aim 1, we will compare the metabolome at both acute (1 day) and intermediate (6 week) time points post- injury to define the evolution of metabolic compensation. We will also compare the metabolome at two different levels of injury severity.
In Aim 2, we will study how a second injury within the vulnerable period alters the time course of resolution of metabolic changes. We will correlate our analysis of brain metabolites with serum metabolomic data to determine whether metabolic dysfunction of the brain can be monitored in peripheral blood. These studies will expand our current knowledge of post-concussive metabolic derangement and provide insight into potential biomarkers of metabolic recovery, as well as potential therapeutic targets to reduce neurological sequelae of repetitive concussion.
The proposed studies could impact public health in the short term by yielding important information regarding metabolic derangements that are present and associated with the vulnerable time period after concussion traumatic brain injury. In the long term, data generated from this exploratory application could generate new targets for therapy for people with one or more concussions to prevent or reduce long term cognitive dysfunction.