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13C tracing in synaptosomes reveals that SGLT2 inhibition with dapagliflozin prevents metabolic deficits in the 5X-FAD model of Alzheimer's Disease

Mekkittikul, M.; Zhu, C.; Danna, B. T.; Zuo, X.; Rios, A.; Yang, K.; Villanueva, M.; Agarwal, D.; Castro, D.; Gu, X.; Strofs, A. R.; Shirihai, O. S.; Stiles, L.; Frautschy, S. A.; Oscarsson, J.; Esterline, R. L.; Cole, G. M.; Divakaruni, A. S.

2025-05-03 biochemistry
10.1101/2025.04.30.651373 bioRxiv
Show abstract

Metabolic dysfunction is linked to several forms of age-related neurodegeneration including Alzheimers Disease (AD), and targeting brain energy metabolism is an increasingly attractive mode of therapeutic intervention. However, commonly used in vitro methods to identify specific metabolic pathways of interest in preclinical models of neurodegenerative disease have considerable limitations. They are prone to subselection of sample material, unable to identify cell type-specific effects, or cannot identify metabolic defects upstream of mitochondria. Here we address these challenges by validating a method for stable isotope tracing with isolated synaptic nerve terminals, or synaptosomes. We further applied this approach to study glucose metabolism in synaptosomes isolated from the 5X-FAD mouse model of AD treated with the antidiabetic sodium-glucose linked transporter-2 (SGLT-2) inhibitor Dapagliflozin. Treatment with Dapagliflozin preserved steady-state levels of synaptosomal metabolites and enrichment from labeled glucose into citrate that was reduced in the 5X-FAD model. These changes correlated with trends towards improved spatial working memory but not amyloid burden. The results highlight the utility of stable isotope tracing in synaptosomes to identify precise sites of metabolic dysfunction and mechanisms of action for metabolic drug candidates in preclinical models of neurodegeneration.

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