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 brain’s 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 alterations in the pseudo–malate–aspartate 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, which showed agreement with the model predictions, providing quantitative support for our proposed mechanism that ketones modulate neurotransmitters through the PMAS. Building on this consistency, we performed metabolic control analysis to identify key enzymes that modulate selectively glutamate and GABA. 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. Competing Interest Statement The authors have declared no competing interest.