Circadian rhythmicity during pre- and early-plaques stages of AD
Research has demonstrated that alterations in sleep rhythm precede cognitive alterations in AD [39, 40]. We investigated if alterations in circadian rhythm were present at pre-plaque (4M) and early-plaque (6M) stages in a rat model (TgF344-AD) that recapitulates the main hallmarks of AD such as Aß plaques, tau tangles and cognitive impairment. Overall circadian rhythmicity was intact at both pre- and early plaque stages of AD in TgF344-AD rats, where the total amount of sleep was higher in the inactive phase than in the active phase, similar to what was observed in wildtype (WT) rats (Fig. 2A). However, small alterations in circadian rhythmicity were observed in TgF344-AD rats, mainly during REM sleep. A significant age*genotype interaction was observed in the total time spent in REM sleep, where a significantly decreased amount of REM sleep was observed in the TgF344-AD rats at the pre-plaque stage with respect to WT littermates. Total REM time was significantly increased at the early-plaque stage in both groups (Fig. 2A, Suppl. Table 1, 2). Significant age effects were observed in the total time spent in REM and NREM during the inactive phase, where NREM sleep is increased and REM sleep is decreased at the early-plaque stage, irrespective of genotype (Fig. 2A, Suppl. Table 1). No significant age or genotype effects were observed in the percentage time spent in REM and NREM during the active phase (Fig. 2A, Suppl. Table 1).
Next, 24-hour acquisitions were divided into 3-hour epochs and the percentage time spent in each state across each epoch was plotted (Fig. 2B,C). Significant age*genotype interactions were observed during the inactive phase in NREM sleep (Fig. 2B, Suppl. Table 3). TgF344-AD rats showed an increased time spent in NREM between Z6-Z9 at the pre-plaque stage compared to age-matched WT rats, while the time spent in NREM between Z9-Z12 was significantly lower (Fig. 2B, Suppl. Table 4).When comparing the time spent in REM across 3-hour epochs, significant genotype effects were observed during the active period, demonstrating decreased time spent in REM between Z18- Z21, and an increased time spent in REM between Z21- Z24 in TgF344-AD rats (Fig. 2C, Suppl. Table 3). In addition, significant age effects were observed for two 3-hour epochs during the inactive phase (Z9-12, Z12-15), demonstrating decreased REM time in 6-month-old rats compared to 4-month-old animals irrespective of genotype. These results demonstrate subtle alterations in circadian rhythm were present at the pre- and early-plaque stages of AD in TgF344-AD rats.
Figure 2: Circadian rhythm in TgF344-AD rats. A) Percentage time spent in NREM and REM during the total 24-hour acquisition and during the active and inactive phases. B-C). Percentage time spent in NREM (B) or REM (C) during 3-hour epochs. On the x-axis, Zeitgeber time (Z) is represented. Between Z0 and Z12, lights are on, between Z12 and Z24, lights are off (Grey shading). Bars demonstrate the mean +/- SEM across animals within each group, whereas dots represent subject values. Dark shading on the x-axis represents the active phase, when lights are turned off. Abbreviations: WT = wildtype, Tg = TgF344-AD, Z = Zeitgeber. * = p < 0.05, ** = p < 0.01, *** = p < 0.001
Sleep fragmentation during NREM sleep
During aging, sleep architecture changes towards more awakenings and decreased bout length. Therefore, mean NREM bout length was evaluated. Age effects were observed across the whole 24-hour period as well as during the active and inactive period, demonstrating decreased NREM bout lengths at the early-plaque stage, irrespective of genotype (Fig. 3A, Suppl. Table 5). Next all the bout lengths of all subjects were combined in one cumulative probability plot, that demonstrated no significant differences in NREM bout length in TgF344-AD rats at pre- and early-plaque stages of AD (ppre−plaque = 0.1109, pearly−plaque = 0.4706) (Fig. 3B, Suppl. Figure 1).
Figure 3: NREM Fragmentation in TgF344-AD rats. A) Mean NREM bout lengths during 24h (left), during the active period (lights off, middle) and inactive period (lights on, right). Bars represent the mean +/- SEM. ANOVA analysis was performed to test for statistical differences. B) Cumulative probability plots of sleep bout lengths for each group. The left panel shows the cumulative distribution of NREM bouts during the pre-plaque stage, while the right plot show the early-plaque stage. Kolmogorov-Smirnov tests (FDR p < 0.05) were performed to evaluate if distributions were significantly different. s = seconds, WT = wildtype, Tg = TgF344-AD, h = hour. ** = p < 0.01, *** = p < 0.001.
Alterations in oscillatory activity during NREM sleep
Most of the studies on sleep in AD have focused on alterations during NREM sleep. Aβ and hyperphosphorylated Tau have been known to interfere with synaptic function, hence inducing altered oscillatory activity during NREM sleep, which in turn is linked to cognitive symptoms of AD [8, 41]. When investigating the oscillatory power during NREM sleep in TgF344-AD rats, a significant age effect was observed in the delta band, demonstrating a decreased power at the early-plaque stage in both groups (Fig. 4A,B, Suppl. Table 6). In addition, significant age effects were detected in the fast gamma band, showing an increase in the power of these frequencies over time. However, no significant genotype effects were observed in the power across different frequency bands during NREM sleep.
During NREM sleep, SWR which are fast oscillatory events in the CA1 regions of the hippocampus, are considered a hallmark of memory replay and are therefore suggested to play a role in memory consolidation [42]. To investigate if SWR activity was already altered at pre-plaque and early-plaque stages of AD in the TgF344-AD rats, SWR were extracted (Fig. 4C, cfr. Materials and Methods) and several characteristics were examined. No significant genotype or age effects were observed for the power of the SWR (Fig. 4D, Suppl. Table 7). A significant age*genotype interaction was observed in the peak spectral frequency (PSF) of the SWR oscillations (Fig. 4E, Suppl. Table 7,8). Post-hoc analysis demonstrated a significant age effect in the TgF344-AD rats where the PSF decreased with age, an effect that was absent in the WT littermates. The duration of SWR has been associated with memory performance [43]. A significantly increased duration of SWR was observed in the TgF344-AD rats, irrespective of age (Fig. 4F, Suppl. Table 5). Histograms of the relative frequency for each duration of SWR demonstrates a skewed distribution (Fig. 4G). All SWR events were divided into short ripples (< 60 ms), medium ripples (60–100 ms) and long ripples (> 100 ms) [43]. Statistical analysis demonstrates a decreased fraction of short ripples, and an increased fraction of long ripples (Fig. 4H, Suppl. Table 9) in the TgF344-AD rats, demonstrating that the relative number of long duration ripples is increased at pre- and early-plaque stages of AD in the TgF344-AD rats (Fig. 4H).
Figure 4: Power and sharp wave-ripple activity during NREM sleep in TgF344-AD rats and wildtype littermates. A) Mean normalized power spectra during. Shading indicates SEM across the group. B) Averaged normalized power across distinct frequency bands of interest (+/- SEM). C)Illustrative sharp wave-ripple (SWR) of a wildtype (WT) and TgF344-AD (Tg) rat. Trace shows filtered data (120-250Hz) of the ripple, while the bottom time-frequency plot demonstrates the frequency and power of the ripple. D-F) Bar plots demonstrating the mean power (D), peak spectral frequency (E) and duration (F) of SWR. G-H) Histograms showing the group average relative frequency of each duration of SWR at 4 months (left) and 6 months (right).. H) Bar plots showing the ratio of short ripples (left) and long ripples (right) vs all ripples. Bar plots show mean +/- SEM, whereas dots represent subject values. gen = genotype, WT = wildtype, Tg = TgF344-AD, HFO = high frequency oscillations, ms = millisecond, SWR = sharp wave-ripple, PSF = peak spectral frequency, Hz = Herz, V = Volt. * = p < 0.05, ** = p < 0.01
E/I imbalance in TgF344-AD rats
SWR events are induced by a delicate interaction between excitatory neurons and GABAergic interneurons that, if disrupted, can lead to pathological forms of activity which leads to memory impairments [24, 44–46]. Therefore, we aimed to evaluate if altered excitatory or inhibitory balance could be attributing to the altered SWR activity observed in TgF344-AD rats. Analysis of the excitatory/inhibitory balance (ratio between glutamatergic and GABA-ergic synapses) revealed significant age effects in the CA1 layer of the hippocampus demonstrating an increased excitation and/or decreased inhibition at the pre-plaque stage in both groups (Fig. 5B, Suppl. Table 10). Interestingly, a significantly decreased excitation and/or increased inhibition was observed in the dentate gyrus (DG) in the TgF344-AD rats irrespective of age (Fig. 5B, Suppl. Table 10).
Figure 5: Changes in E/I balance in TgF344-AD rats. A) Exemplary images of the glutamatergic (magenta) and GABA-ergic synapses (yellow) synapses in the CA1 layer of the hippocampus in wildtype littermates (WT) (left) and TgF344-AD rats (right) at 4 and 6 months of age. B Group-averaged vGLUT/vGAT ratio per region of interest. Bars represent the mean +/- SEM. ANOVA analysis was performed to test for statistical differences. DG = dentate gyrus, WT = wildtype, Tg = TgF344-AD, vGAT = vesicular GABA transporter, vGLUT = vesicular glutamate transporter, E/I = excitatory/inhibitory, gen = genotype. * = p < 0.05
REM sleep fragmentation
REM sleep is associated with local synaptic plasticity, consolidation of declarative memory and modulation of emotional memories [47–49]. Disruption of REM sleep has been associated with memory problems and emotional problems, such as increased anxiety, common symptoms observed in patients with AD [47, 49]. Therefore, we aimed to evaluate REM sleep disturbances at pre- and early-plaque stages of AD. Analysis of the mean REM bout length demonstrated age effects, where shorter REM bouts were observed at the early-plaque stage, when REM bout length was calculated over the entire 24h period and only during the active phase (Fig. 6A, Suppl. Table 11). Interestingly, when REM bout length was analyzed during the inactive phase, a significant age*genotype interaction was observed. Post-hoc analysis reveals a significant decrease in REM bout length in WT rats while aging, an effect that was absent in the TgF344-AD rats (Fig. 6A, Suppl. Table 12). When investigating the cumulative distribution of the REM bouts for each group separately, a significantly increased probability of shorter REM bouts was observed in TgF344-AD rats at the pre-plaque stage, but not at the early-plaque stage (Fig. 6, Suppl. Figure 2).
Figure 6: REM Fragmentation in TgF344-AD rats. A) Mean REM bout lengths during 24h (left), during the active period (lights off, middle) and inactive period (lights on, right). Bars represent the mean +/- SEM. ANOVA analysis was performed to test for statistical differences. B) Cumulative probability plots of sleep bout lengths for each group. The left panel shows the cumulative distribution of REM bouts during the pre-plaque stage, while the right plot shows the early-plaque stage. Kolmogorov-Smirnov tests (FDR p < 0.05) were performed to evaluate if distributions were significantly different. gen = genotype, WT = wildtype, Tg = TgF344-AD, s = seconds. * = p < 0.05, ** = p < 0.01
Alterations in oscillatory activity during REM sleep
Disruption of oscillatory activity during REM sleep has been observed at late stages of AD and has been proven to lead to memory deficits [50–52]. When investigating alterations in the power of hippocampal oscillations during REM sleep, a significant genotype effect was present in the fast gamma power, demonstrating a reduction in fast gamma oscillations in the TgF344-AD rats irrespective of age (Fig. 7A,B, Suppl. Table 13).
Phase-amplitude coupling (PAC) is an electrophysiological phenomenon where the amplitude of fast oscillations is modulated by the phase of slower oscillations. Theta-driven modulation of gamma oscillations during REM sleep has been implicated in memory processing and has been demonstrated to be an important mechanism of synaptic plasticity and synaptic homeostasis [51, 53]. Alterations in synaptic function could impair theta-gamma coupling, therefore we evaluated PAC during REM sleep. First, the main frequencies modulated by theta frequencies were analyzed using a comodulogram. Mean comodulograms were plotted which demonstrate modes of coupling between theta frequencies (6.5-9 Hz) and fast gamma in all groups (80–100 Hz) (Fig. 7C). Interestingly, strong coupling was observed between theta (6.5-9 Hz) and slow gamma oscillations (30–45 Hz) mainly in 4-month-old TgF344-AD rats.
Next, to evaluate the strength of the theta-gamma coupling, a time-resolved PAC analysis was performed (Fig. 7C,D, Suppl. Table 14). A significant age*genotype interaction was observed in the coupling between theta and slow gamma frequencies. Post-hoc analysis revealed increased coupling strength in TgF344-AD rats during the pre-plaque stage, which was restored to WT levels at the early-plaque stage (Fig. 7D, Suppl. Table 15). When evaluating the coupling between theta and fast gamma frequencies, a significantly decreased coupling strength was present in the TgF344-AD rats, irrespective of age (Fig. 7E, Suppl. Table 14). Moreover, a significant age effect was observed, demonstrating an increase in the strength of PAC in the 6-month-old rats, which is mainly driven by an increasing MI in the TgF344-AD rats over time, suggesting a partial recovery of PAC in TgF344-AD rats at the early-plaque stage.
Figure 7: Power and theta-gamma coupling in TgF344-AD rats during REM sleep. A) Mean normalized power spectra. Shading indicates SEM across the group. B) Averaged normalized power across distinct frequency bands of interest (+/- SEM). C) Comodulogram averaged across subjects demonstrating main frequencies of coupling. Color bar indicates the strength of the modulation index at different frequencies of theta (x-axis) and gamma (y-axis). D) Mean (+/- SEM) MI across subjects between theta-frequencies (6.5-9Hz) and slow gamma frequencies (30-45Hz). Dots represent subject MI values. E) Mean (+/- SEM) MI across subjects between theta frequencies (6.5-9HZ) and fast gamma frequencies 80-110Hz. Dots represent subject MI values. gen = genotype, Tg = TgF344-AD, WT = wildtype, MI = modulation index, Hz = Hertz. * = p < 0.05, *** = p < 0.001
Cholinergic synapses in the hippocampus
Cholinergic dysfunction has been implicated to occur at early stages of AD. REM sleep and PAC are heavily dependent on cholinergic signaling [12, 54–57]. To evaluate if the observed alterations in REM bout length and theta-gamma coupling could be attributed to alterations in cholinergic function, histological analysis of cholinergic synapses in the hippocampus was performed (Fig. 8A). When statistically comparing the abundance of cholinergic synapses, significant genotype*age effects were observed in the DG and in the CA1 (Fig. 8A, Suppl. Table 16). Cholinergic synaptic density in the CA1 region and DG was paradoxically increased at 6-months of age in TgF344-AD rats compared to WT littermates. Moreover, a significant increase in cholinergic synapses was observed over time in the TgF344-AD rats in both hippocampal regions, which was absent in WT littermates (Fig. 8B, Suppl. Table 17).
Figure 8: Increased number of cholinergic synapses in hippocampus during early-plaque stage. A) Exemplary images of cholinergic synapses (grey) in the CA1 layer of the hippocampus in wildtype littermates (WT) (left) and TgF344-AD rats (right) at the pre-, and early-plaque stage of AD. B) Group-averaged numbers of cholinergic synapses per region of interest. Bars represent the mean +/- SEM. Dots represent subject MI values. ANOVA analysis was performed to test for statistical differences. DG = dentate gyrus, TG = TgF344-AD, gen = genotype. *** = p < 0.001