Friend or Foe? Defining the Role of Glutamate in Aging and Alzheimer's Disease

Abstract

Aging is a naturally occurring decline of physiological processes and biological pathways that affects both the structural and functional integrity of the body and brain. These physiological changes reduce motor skills, executive function, memory recall, and processing speeds. Aging is also a major risk factor for multiple neurodegenerative disorders including Alzheimer's disease (AD). Identifying a biomarker, or biomarkers, that signals the transition from physiological to pathological aging would aid in earlier therapeutic options or interventional strategies. Considering the importance of glutamate signaling in synaptic plasticity, motor movement, and cognition, this neurotransmitter serves as a juncture between cognitive health and disease. This article discusses glutamatergic signaling during physiological aging and the pathological changes observed in AD patients. Findings from studies in mouse models of successful aging and AD are reviewed and provide a biological context for this transition. Finally, current techniques to monitor brain glutamate are highlighted. These techniques may aid in elucidating time-point specific therapeutic windows to modify disease outcome.

Keywords: amyloid—beta; biomarker; excitotoxcity; geroscience; growth hormone receptor knockout; hippocampus; neurodegenerative disease; neuroimaging.

FIGURE 1

Glutamate dynamics in APP/PS1 and C57BL/6J mice at 12 months. The figures were created using control 12–15 months male C57BL/6J (white) and APP/PS1 (gray) mice across multiple datasets (Hascup E. R. et al., 2019; Hascup K. N. et al., 2019; Hascup et al., 2020a). Graphs depict violin plots with median (blue line) and quartiles (red line). (A) Basal glutamate levels were measured in the CA1, CA3, and the DG of the hippocampus using a microelectrode array (MEA). (B) Glutamate release rate was calculated using the change in amplitude between the maximal response and baseline over the duration (s) to reach maximal response after stimulation. (C) Average glutamate release was determined using the maximal change after stimulation from baseline. (D) Glutamate clearance followed first-order-rate kinetics. A logarithmic slope for glutamate concentration decay (k₋₁) versus time (s⁻¹) is estimated using regression analysis (R² ≥ 0.9) to determine the uptake rate. (E) T₈₀ refers to the duration of time needed for 80% of the maximal glutamate signal to be cleared from the extracellular space. A two tailed t-test was used to compare genotypes in each hippocampal subregion. **p < 0.01, ***p < 0.001, ****p < 0.0001; n = 36–47.