To disentangle how aging and Alzheimer’s pathology (amyloidosis, tauopathy) modulate behavioral and neurophysiological responses to systemic inflammation in mice.
Delirium is an acute neuropsychiatric disorder often triggered by acute systemic inflammation in patients with underlying brain vulnerability. Yet the relative contributions of vulnerabilities like aging and Alzheimer’s pathology remain unclear. We therefore evaluated whether predisposing vulnerabilities including amyloidosis, tauopathy, and aging, independently affect the effects of systemic inflammation on behavior and electrophysiology.
We studied three experimental groups: aged (15–22 months) vs. young (4–6 months) wild-type mice (WT), 5xFAD transgenic mice (amyloidosis model) vs. age-matched WT controls, and Tau PS19 transgenic mice (tauopathy model) vs. age-matched WT controls. Systemic inflammation was induced via 0.5 mg/kg intraperitoneal lipopolysaccharide (LPS); saline served as control. Mice were monitored continuously using home cage video for 72 hours post-injection. Behavioral endpoints included locomotion and nesting, analyzed using Camus, our custom video-based behavioral analysis pipeline. EEG/EMG was recorded to assess arousal patterns and slow-wave activity changes.
LPS-induced hypoactivity and nesting disruption across all groups was most severe and prolonged in Tau PS19 mice. EEG following LPS administration revealed disrupted circadian rhythmicity and a spectral shift towards lower frequencies (increased delta power), which was more evident during the dark phase.
Systemic inflammation reveals vulnerability-dependent susceptibility, with tauopathy (Tau PS19) emerging as a high-predisposition. Comparative analyses across aging, amyloidosis, and tauopathy highlight both shared and distinct behavioral and electrophysiological responses to LPS in mice. These results emphasize the importance of including dynamic vulnerability types into delirium models and provide a platform for mechanistic studies and targeted interventions. Ongoing work evaluates reliability, mechanisms, and recovery dynamics.