P109 The association between sleep microarchitecture and cognitive function in middle-aged and older men: A community-based study. (7th October 2021) - Parker, J; Melaku, Y; D'Rozario, A; Wittert, G; Martin, S; Toson, B; Catcheside, P; Lechat, B; Teare, A; Appleton, S; Adams, R; Vakulin, A
Abstract: Introduction: Sleep microarchitecture metrics determined by quantitative power spectral analysis (PSA) of the electroencephalogram (EEG) have been proposed as potential biomarkers of cognitive function. However, there remain no data from community-based samples. This study examined cross-sectional associations between sleep microarchitecture metrics determined by PSA and cognitive function outcomes in community-dwelling men. Methods: Men, Androgen, Inflammation, Lifestyle, Environment, and Stress (MAILES) study participants (n=477) underwent home-based polysomnography between 2010–2011. All-night EEG recordings were processed using PSA following exclusion of artefacts. MAILES participants also completed the inspection time task, Fuld object memory evaluation, and trail-making test A (TMT-A) and B (TMT-B). Multivariable linear regression models were used to determine the associations of sleep microarchitecture (relative spectral power) with cognitive function in the complete and age-stratified samples. Results: Power spectral densities in theta-alpha ranges during NREM and REM sleep were associated with worse TMT-A performance, whereas higher delta density was associated with better TMT-A performance in the complete sample and men ≥65 years (all p<0.05). Similar associations were observed with TMT-B performance in men ≥65 years. Furthermore, in men <65 years, higher sigma density during NREM sleep was associated with faster inspection time (B= -3.14, 95% CI [-6.00, -0.27], p=0.032), whereas in men ≥65 years, higher theta density during NREM sleep was associated with faster inspection time (B = -3.33, 95% CI [-6.65, -0.02], p=0.049). Discussion: PSA markers of sleep microarchitecture are independently associated with cognitive function. Longitudinal studies are needed to determine whether sleep microarchitecture metrics predict future cognitive dysfunction and decline.