Subtypes of brain change in aging and their associations with cognition and Alzheimer's disease biomarkers.

Structural brain changes underly cognitive changes in older age and contribute to inter-individual variability in cognition. Here, we assessed how changes in cortical thickness, surface area, and subcortical volume, are related to cognitive change in cognitively unimpaired older adults using structural magnetic resonance imaging (MRI) data-driven clustering. Specifically, we tested (1) which brain structural changes over time predict cognitive change in older age (2) whether these are associated with core cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers phosphorylated tau (p-tau) and amyloid-ß (Aß42), and (3) the degree of overlap between clusters derived from different structural features. In total 1899 cognitively healthy older adults (50 - 93 years) were followed up to 16 years with neuropsychological and structural MRI assessments, a subsample of which (n = 612) had CSF p-tau and Aß42 measurements. We applied Monte-Carlo Reference-based Consensus clustering to identify subgroups of older adults based on structural brain change patterns over time. Four clusters for each brain feature were identified, representing the degree of longitudinal brain decline. Each brain feature provided a unique contribution to brain aging as clusters were largely independent across modalities. Cognitive change and baseline cognition were best predicted by cortical area change, whereas higher levels of p-tau and Aß42 were associated with changes in subcortical volume. These results provide insights into the link between changes in brain morphology and cognition, which may translate to a better understanding of different aging trajectories.

Evidence for widespread alterations in cortical microstructure after 32 h of sleep deprivation.

Cortical microstructure is influenced by circadian rhythm and sleep deprivation, yet the precise underpinnings of these effects remain unclear. The ratio between T1-weighted and T2-weighted magnetic resonance images (T1w/T2w ratio) has been linked to myelin levels and dendrite density and may offer novel insight into the intracortical microstructure of the sleep deprived brain. Here, we examined intracortical T1w/T2w ratio in 41 healthy young adults (26 women) before and after 32 h of either sleep deprivation (n = 18) or a normal sleep-wake cycle (n = 23). Linear models revealed significant group differences in T1w/T2w ratio change after 32 h in four clusters, including bilateral effects in the insular, cingulate, and superior temporal cortices, comprising regions involved in attentional, auditory and pain processing. Across clusters, the sleep deprived group showed an increased T1w/T2w ratio, while the normal sleep-wake group exhibited a reduced ratio. These changes were not explained by in-scanner head movement, and 95% of the effects across clusters remained significant after adjusting for cortical thickness and hydration. Compared with a normal sleep-wake cycle, 32 h of sleep deprivation yields intracortical T1w/T2w ratio increases. While the intracortical changes detected by this study could reflect alterations in myelin or dendritic density, or both, histological analyses are needed to clarify the precise underlying cortical processes.

Sleep and sleep deprivation differentially alter white matter microstructure: A mixed model design utilising advanced diffusion modelling.

Sleep deprivation influences several critical functions, yet how it affects human brain white matter (WM) is not well understood. The aim of the present work was to investigate the effect of 32 hours of sleep deprivation on WM microstructure compared to changes observed in a normal sleep-wake cycle (SWC). To this end, we utilised diffusion weighted imaging (DWI) including the diffusion tensor model, diffusion kurtosis imaging and the spherical mean technique, a novel biophysical diffusion model. 46 healthy adults (23 sleep deprived vs 23 with normal SWC) underwent DWI across four time points (morning, evening, next day morning and next day afternoon, after a total of 32 hours). Linear mixed models revealed significant group × time interaction effects, indicating that sleep deprivation and normal SWC differentially affect WM microstructure. Voxel-wise comparisons showed that these effects spanned large, bilateral WM regions. These findings provide important insight into how sleep deprivation affects the human brain.

Evidence for wakefulness-related changes to extracellular space in human brain white matter from diffusion-weighted MRI.

Recently, several magnetic resonance imaging (MRI) studies have reported time-of-day effects on brain structure and function. Due to the possibility that time-of-day effects reflect mechanisms of circadian regulation, the aim of this prospective study was to assess these effects while under strict experimental control of variables that might influence biological clocks, such as caffeine intake and exposure to blue-emitting light. In addition, the current study assessed whether time-of-day effects were driven by changes to extracellular space, by including estimations of non-Gaussian diffusion metrics obtained from diffusion kurtosis imaging, white matter tract integrity and the spherical mean technique, in addition to conventional diffusion tensor imaging -derived parameters. Participants were 47 healthy adults who underwent diffusion-weighted imaging in the morning and evening of the same day. Morning and evening scans were compared using voxel-wise tract based spatial statistics and permutation testing. A day of wakefulness was associated with widespread increases in fractional anisotropy, indices of kurtosis and indices of the axonal water fraction. In addition, wakefulness was associated with widespread decreases in radial diffusivity, both in the single compartment and in extra-axonal space. These results suggest that an increase in the intra-axonal space relative to the extra-axonal volume underlies time-of-day effects in human white matter, which is in line with activity-induced reductions to the extracellular volume. These findings provide important insight into possible mechanisms driving time-of-day effects in MRI.