Timely coupling of sleep spindles and slow waves linked to early amyloid-β burden and predicts memory decline

Sleep alteration is a hallmark of ageing and emerges as a risk factor for Alzheimer’s disease (AD). While the fine-tuned coalescence of sleep microstructure elements may influence age-related cognitive trajectories, its association with AD processes is not fully established. Here, we investigated whether the coupling of spindles and slow waves (SW) is associated with early amyloid-β (Aβ) brain burden, a hallmark of AD neuropathology, and cognitive change over 2 years in 100 healthy individuals in late-midlife (50–70 years; 68 women). We found that, in contrast to other sleep metrics, earlier occurrence of spindles on slow-depolarisation SW is associated with higher medial prefrontal cortex Aβ burden (p=0.014, r²β*=0.06) and is predictive of greater longitudinal memory decline in a large subsample (p=0.032, r²β*=0.07, N=66). These findings unravel early links between sleep, AD-related processes, and cognition and suggest that altered coupling of sleep microstructure elements, key to its mnesic function, contributes to poorer brain and cognitive trajectories in ageing.


Sample-size estimation
• You should state whether an appropriate sample size was computed when the study was being designed • You should state the statistical method of sample size computation and any required assumptions • If no explicit power analysis was used, you should describe how you decided what sample (replicate) size (number) to use Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission:

Replicates
• You should report how often each experiment was performed • You should include a definition of biological versus technical replication • The data obtained should be provided and sufficient information should be provided to indicate the number of independent biological and/or technical replicates • If you encountered any outliers, you should describe how these were handled • Criteria for exclusion/inclusion of data should be clearly stated • High-throughput sequence data should be uploaded before submission, with a private link for reviewers provided (these are available from both GEO and ArrayExpress) Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: We did not compute sample size prior to the study. As indicated in the methods section (p.21) : « Optimal sensitivity and power analyses in GLMM remain under investigation [e.g. 63]. We nevertheless computed a prior sensitivity analysis to get an indication of the minimum detectable effect size in our main analyses given our sample size. According to G*Power 3 (version 3.1.9.4)64 taking into account a power of .8, an error rate α of .025 (corrected for 2 tests), a sample size of 100 allowed us to detect small effect sizes r > .29 (2-sided; absolute values; confidence interval: .1 -.46; R² > .08, R² confidence interval: .01 -.21) within a linear multiple regression framework including 1 tested predictor (Aβ) and 2 covariates (age, sex)." The experiment was performed once for each individual (N=100) with no further replication. Exclusion criteria can be found in the methods section of the manuscript (p. 15). As indicated in the statistics section of the methods (p. 21), no outliers were detected/removed: "Cook's distance was used to assess the potential presence of outliers driving the associations, and as values ranged below 0.45 no datapoint was excluded from the analyses (a Cook's distant > 1 is typically considered to reflect outlier value)."

Statistical reporting • Statistical analysis methods should be described and justified
• Raw data should be presented in figures whenever informative to do so (typically when N per group is less than 10) • For each experiment, you should identify the statistical tests used, exact values of N, definitions of center, methods of multiple test correction, and dispersion and precision measures (e.g., mean, median, SD, SEM, confidence intervals; and, for the major substantive results, a measure of effect size (e.g., Pearson's r, Cohen's d) • Report exact p-values wherever possible alongside the summary statistics and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05.
Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: (For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
• Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied • Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Additional data files ("source data") • We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table • Where provided, these should be in the most useful format, and they can be uploaded as "Source data" files linked to a main figure or table • Include model definition files including the full list of parameters used • Include code used for data analysis (e.g., R, MatLab) • Avoid stating that data files are "available upon request" Please indicate the figures or tables for which source data files have been provided: Statistical analysis methods are detailed in the methods section (section about statistics -p. 20-21) and reminded in the results section. The regressions display raw data (Figure 2 and 3). Exact p-values are reported both in the text and on the displays. N/A (no experimental groups).
The data and analysis scripts supporting the results included in this manuscript are publicly available: https://gitlab.uliege.be/CyclotronResearchCentre/Public/fasst/slowwave-spindle-coupling-and-amyloid. The raw data of the study may be accessed after request to the corresponding author and local ethic committee, if relevant.