Comparative analysis of sleep architecture and circadian rhythms in senescence-accelerated mouse (SAM) P8 and R1 strains

Background: Sleep in older adults is characterized by fragmentation and reduced delta power in the electroencephalogram (EEG). Polysomnographic studies have demonstrated marked alterations in non-rapid eye movement (NREM) sleep architecture, including increased stage 1 sleep, fragmentation of stage 2, substantial reductions in stages 3 and 4, and a decrease in total rapid eye movement (REM) sleep, although its proportion relative to total sleep time remains unchanged. The senescence-accelerated mouse (SAM) strain is an inbred model exhibiting accelerated aging phenotypes. Among these, senescence-accelerated mouse prone 8 (SAMP8) displays early-onset learning deficits, immune dysfunction, and disruption of circadian rhythms. In contrast, senescence-accelerated mouse resistant 1 (SAMR1) serves as a normally aging control strain for SAMP models. In this study, circadian rhythms and sleep architecture in SAMP8 and SAMR1 mice were investigated to evaluate the utility of SAMP8 as a model for age-related sleep disorders.

Methods: Circadian rhythms were assessed by measuring locomotor activity in SAMP8 and SAMR1 mice from 1 to 5 months of age. At 6 months, animals were chronically implanted with EEG and electromyogram (EMG) electrodes to enable polysomnographic recording of sleep–wake states under isoflurane anesthesia. Vigilance states were automatically scored offline using SleepSign ver. 3 software based on EEG, EMG, and spontaneous locomotor activity, with data segmented into 10-second epochs. Group differences were analyzed using one-way analysis of variance (ANOVA) followed by Scheffé’s post hoc test. Power spectral analysis of EEG signals during NREM sleep was performed using fast Fourier transform (FFT) at a sampling rate of 128 Hz, generating spectra from 0 to 20 Hz with 1-Hz resolution.

Results: Analysis of circadian rhythms demonstrated that the ratio of locomotor activity during the 12-h dark period to that during the 12-h light period ranged from 3.7 to 5.4 in SAMR1 mice, whereas SAMP8 mice exhibited a lower ratio of 1.6 to 2.5, indicating a reduction in circadian amplitude in SAMP8. With respect to sleep architecture, both REM and NREM sleep durations were significantly reduced in SAMP8 compared with SAMR1. Furthermore, NREM sleep episodes were significantly shorter in SAMP8 mice, suggesting impaired sleep quality associated with increased fragmentation and instability of sleep states. FFT analysis further revealed a significant decrease in delta power during NREM sleep in SAMP8 relative to SAMR1.

Conclusions: These findings indicate that SAMP8 represents a valid model of age-related alterations in circadian rhythms and sleep, and may be useful for exploratory investigations of dietary components and potential therapeutic interventions that ameliorate sleep disturbances. Furthermore, this model provides a valuable platform for longitudinal and mechanistic studies aimed at elucidating the neural and molecular basis of sleep dysregulation, and may contribute to the identification of biomarkers and novel targets for the prevention and treatment of sleep disorders in the aging population.

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