Sleep, rest-activity rhythms and white matter in older adults at risk for cognitive decline and dementia

There is a significant body of evidence demonstrating alterations in sleep and circadian rhythms in ageing, with more prominent changes seen in older adults who are at risk for cognitive decline. White matter alterations have also been implicated in ageing with more pronounced and widespread changes seen in this at-risk cohort. Despite the convergence of evidence, there is currently limited understanding of the relationship between sleep-wake functioning, white matter alterations and risk factors for cognitive decline. This thesis aims to address this limitation investigating relationships between these factors using objective measures of sleep-wake functioning and advanced white matter analysis methods.

A systematic review of the literature revealed a small number of studies investigating associations between objective sleep-wake measures and white matter. There was significant variation in the sleep-wake measures assessed and importantly, no previous studies included participants experiencing subjective or objective cognitive decline. The next study investigated associations between non-parametric actigraphy measures and tract-specific white matter lesions (WMLs), revealing novel associations between regional WML burden 24-hour rhythm stability, overnight activity and onset time of the least active period. Following this, advanced analysis of diffusion weighted imaging was used to assess relationship between rest-activity rhythms and white matter micro-architecture beyond discrete WMLs. This study not only demonstrated associations between restactivity rhythms and properties of major cortico-subcortical and association white matter tracts, but also revealed moderating effects of clinical risk factors for cognitive decline on the relationship between rest-activity rhythms and white matter micro-architecture. The final empirical study shifted focus from rest-activity rhythms to overnight sleep microarchitecture to determine whether sleep spindle and slow-wave activity were related to white matter connectivity derived from state-of-the-art white matter fibre tracking and tractogram optimisation methods. This study revealed, for the first time, that white matter connectivity of select white matter tracts was associated with sleep spindle activity, with differential relationships identi?ed between clinical syndromes and specific white matter tracts.

The findings reported in this study advance understanding of the relationship between sleep-wake functioning and white matter properties in older adults at risk for cognitive decline. Taken together, they demonstrate that white matter may represent a common neurobiological substrate that underpins sleep-wake alterations in this population.