Mozart's rhythm influence on Alzheimer's disease progression via modulation of pathological damage and cognition

Abstract

Rhythm perception is considered a conserved trait across species, and musical rhythm exposure (MRE) has been demonstrated to enhance cognitive functions in healthy individuals. Alzheimer's disease (AD), characterized by cognitive decline and pathological degeneration, may potentially be delayed by MRE. In this study, the APP/PS1 AD mouse model was exposed to Mozart's K.448 rhythm for six months, with APP/PS1 and wild-type C57BL/6J mice serving as controls. The Morris water maze test was employed to assess the impact of MRE on spatial learning and memory. Pathological damage was evaluated through amyloid-beta and phosphorylated tau levels. Additionally, hippocampal microglia activation, inflammatory markers, and gut microbiota composition were analyzed. The study revealed that MRE improves cognitive function, reduces amyloid plaque accumulation, suppresses microglial activation and neuroinflammation, and modulates gut microbiota composition. This suggests that MRE offers a promising non-pharmacological approach to slowing cognitive decline and pathological damage in AD.

Keywords: Behavioral neuroscience; Microbiome; Neuroscience.

Graphical abstract

Figure 1

MRE protected against impaired cognitive function in APP/PS1 mice (A) Schematic diagram of the animal experiments. (B) Derived from the fifth and sixth stanzas of Mozart K.448, the rhythm adjusts the pitch of the piece to the same level as the original piece of music. (C) The average escape latency time was calculated as the amount of time needed to locate the submerged platform at 3, 6, and 9 months in mice in the MWM task. (D) The number of platform crossings in the MWM probe trials (no platform). (E) The time the mice spent in the target quadrant area in the MWM probe trials (no platform). n = 8. The data are reported as the means ± S.E.M. The data were analyzed by one-way ANOVA with the LSD multiple comparison test. ∗p < 0.05, ∗∗p < 0.01.

Figure 2

MRE effectively inhibited the rapid accumulation of Aβ and p-Tau181 in APP/PS1 mice (A) The area of Aβ was evaluated by immunofluorescence in hippocampal slices. Scale bar: 200 μm. (B) The area of Aβ within the hippocampus is a percentage of the entire hippocampal area in the slice (n = 5–6). For each mouse, 2–3 brain slices were analyzed, and the average value was used for quantification. (C and D) The levels of Aβ1−40 and p-Tau181 in the serum of each group of mice (n = 4–6) were determined by ELISA. One sample from the WT group at 9 months of age exhibited hemolysis and was therefore excluded from the analysis. The data are reported as the means ± S.E.M. The data were analyzed by one-way ANOVA with the LSD multiple comparison test. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Figure 3

MRE maintained the microglial population in the hippocampus of APP/PS1 mice at a homeostatic level The number of microglia was evaluated by immunofluorescence in hippocampal CA1, CA3, and DG slices (A, C, and E), and the number of microglia in the corresponding regions is shown (B, D, and F). Scale bar: 50 μm. For each mouse, 2–3 brain slices were analyzed, and the average value was used for quantification. 5–6 mice per group. The data are reported as the means ± S.E.M. The data were analyzed by one-way ANOVA with the LSD multiple comparison test. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Figure 4

MRE effectively suppressed the rapid increase in peripheral inflammation in the APP/PS1 mice The expression levels of (A) IL-1, (B) IL-6, and (C) TNF-α in the serum of each group of mice (n = 4–6) were determined via ELISA. One sample from the WT group at 9 months of age exhibited hemolysis and was excluded from the analysis. The data are reported as the means ± S.E.M. The data were analyzed by one-way ANOVA with the LSD multiple comparison test. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Figure 5

MRE enhanced the diversity and altered the composition of gut microbes in APP/PS1 mice (A–D) Sobs, Chao1, and Ace account for the species richness or the number of species presented, and the PD-tree reflects the diversity of sample lineages combined with evolutionary distance. (E) PCoA plot based on the unweighted UniFrac index at the OTU level. (F) PLS-DA plot based on the unweighted UniFrac index at the OTU level. (G) ANOSIM test based on the unweighted UniFrac index at the OTU level. (H) Adonis (PERMANOVA) test based on the unweighted UniFrac index at the OTU level. (I) The most differentially abundant taxa in each group were identified by LDA scores generated from the LEfSe analysis. (J) Relative abundances of predominant bacteria at the family level in each group. n = 6. Data are shown as box-and-whisker plots median and interquartile range. Kruskal-Wallis rank-sum test. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.

Figure 6

MRE leading to the convergence of APP/PS1 mice toward WT mice (A) Correlations among all the detection indices, according to the Spearman correlation analysis. (B) The normalized values of each detection index at age 9 months. (C) The mean squared error distance for the test indices for each group of mice aged 9 months ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.