Poor Self-Reported Sleep is Related to Regional Cortical Thinning in Aging but not Memory Decline-Results From the Lifebrain Consortium

Abstract

We examined whether sleep quality and quantity are associated with cortical and memory changes in cognitively healthy participants across the adult lifespan. Associations between self-reported sleep parameters (Pittsburgh Sleep Quality Index, PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n = 2205, 4363 MRIs, 18-92 years). In additional analyses, we tested coherence with cell-specific gene expression maps from the Allen Human Brain Atlas, and relations to changes in memory performance. "PSQI # 1 Subjective sleep quality" and "PSQI #5 Sleep disturbances" were related to thinning of the right lateral temporal cortex, with lower quality and more disturbances being associated with faster thinning. The association with "PSQI #5 Sleep disturbances" emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. None of the sleep scales were related to a longitudinal change in episodic memory function, suggesting that sleep-related cortical changes were independent of cognitive decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.

Trial registration: ClinicalTrials.gov NCT01634841.

Keywords: aging; atrophy; cortex; sleep.

Figure 1

Effects of sleep on cortical thinning Clusters where PSQI #1 Subjective sleep quality and PSQI #5 Sleep disturbances were related to cortical thinning after corrections for multiple comparisons across space.

Figure 2

Age-interactions; left panels: clusters where PSQI #5 Sleep disturbances are significantly more strongly related to cortical thinning in older than younger adults. Average cortical thickness in the cluster in the right middle temporal gyrus—marked by the red asterisk—was extracted and used to illustrate the age-interactions in the right panels. Right panels: model predicted cortical thickness in the right middle temporal cluster in the left panel as a function of age, time, and amount of sleep disturbances (0: none, 3: severe). Participants reporting more sleep disturbances show more cortical thinning in the older age ranges but not in the younger. CIs around the curves were removed for improved viewing and are presented in the Supplementary Material, along with similar curves for the other three significant clusters. These plots are used for illustrating the effects in the surface analyses. Statistical analyses were conducted using age as a continuous variable.

Figure 3

Cortical thinning as a function of sleep disturbances and age; top panel: mean cortical thinning (mm/year) in the clusters with a significant effect of age × sleep on thickness change broken up by score on PSQI #5 Sleep disturbances and age group. Bottom panel: mean cortical thinning in the same regions as a function of score on PSQI #5 Sleep disturbances and age group. Error bars denote 1 SD.

Figure 4

Virtual histology; significantly higher expression of genes characteristic of specific cell types (oligodendrocytes and S1 pyramidal) in vertices where the age-related association between PSQI #5 Sleep disturbances and cortical thinning are the strongest (vertex-wise thickness effects from the age × time × sleep interaction; see surface plots in Figure 2). The black vertical lines represent the mean association, and the shaded area represents the empirical null distribution for each of the 9 cell types. The x-axes indicate the coefficients of correlation between the thinning and the gene expression profiles. The y-axes indicate the estimated probability density for the correlation coefficients. Panels, where the mean of the target ROIs is outside the null distribution 95% CI, are considered to show a correlation greater or smaller than predicted. See Allen et al. (2019) for the creation of raincloud plots.

Figure 5

Controlling for BMI; BMI did not affect the relationship between PSQI #5 Sleep disturbances and cortical thinning across age, as can be seen from the overlapping solid and dotted lines. Plotted effects are from Cluster B (Figure 3); see Supplementary Material for additional clusters. Note that the y-axes are fitted to each plot to facilitate the detection of possible differences between curves visually, and therefore vary between plots.

Figure 6

Controlling for depression; depressive symptoms did not affect the relationship between PSQI #5 Sleep disturbances and cortical thinning across age, as can be seen from the overlapping solid and dotted lines. Plotted effects are from Cluster B (Figure 3); see Supplementary Material for additional clusters. Note that the y-axes are fitted to each plot to facilitate the detection of possible differences between curves visually, and therefore vary between plots.