Computational modeling of neurotransmitter cycling predicts human brain glutamate and GABA dynamics in response to administration of exogenous ketones

Abstract

Administration of ketones is used as a therapeutic option in multiple conditions, including epilepsy, mental health disorders, and brain aging. A proposed mechanism of action involves the modulation of glutamate and GABA, the brains primary excitatory and inhibitory neurotransmitters, which jointly regulate the excitatory-inhibitory balance. However, the precise mechanism by which ketones influence these neurotransmitters remains unclear. In this study, we hypothesize that ketones modulate glutamate and GABA through the pseudomalate-spartate shuttle (PMAS). To test this, we developed a computational model of neurotransmitter cycling centered on the PMAS, simulating the temporal dynamics and steady-state concentrations of glutamate and GABA as functions of ketone metabolism. We then compared the model outputs with MRS data from ketone administration experiments and found agreement with the model predictions, providing quantitative support for the model. Building on this agreement, we performed metabolic control analysis, which identified partial displacement of glucose metabolism through the PMAS as the dominant mechanism underlying the observed reductions in glutamate and GABA and revealed key enzymes that selectively modulate each neurotransmitter. Overall, the model provides researchers and clinicians with a framework for hypothesis testing and treatment optimization, while also serving as a foundation for future model expansions.