Reported sleep duration reveals segmentation of the adult life-course into three phases.

Classically the human life-course is characterized by youth, middle age and old age. A wide range of biological, health and cognitive functions vary across this life-course. Here, using reported sleep duration from 730,187 participants across 63 countries, we find three distinct phases in the adult human life-course: early adulthood (19-33yrs), mid-adulthood (34-53yrs), and late adulthood (54+yrs). They appear stable across culture, gender, education and other demographics. During the third phase, where self-reported sleep duration increases with age, cognitive performance, as measured by spatial navigation, was found to have an inverted u-shape relationship with reported sleep duration: optimal performance peaks at 7 hours reported sleep. World-wide self-reported sleep duration patterns are geographically clustered, and are associated with economy, culture, and latitude.

The sleep and circadian problems of Huntington's disease: when, why and their importance.

INTRODUCTION: Mounting evidence supports the existence of an important feedforward cycle between sleep and neurodegeneration, wherein neurodegenerative diseases cause sleep and circadian abnormalities, which in turn exacerbate and accelerate neurodegeneration. If so, sleep therapies bear important potential to slow progression in these diseases. FINDINGS: This cycle is challenging to study, as its bidirectional nature renders cause difficult to disentangle from effect. Likewise, well-controlled intervention studies are often impractical in the setting of established neurodegenerative disease. It is this that makes understanding sleep and circadian abnormalities in Huntington's disease (HD) important: as a monogenic fully penetrant neurodegenerative condition presenting in midlife, it provides a rare opportunity to study sleep and circadian abnormalities longitudinally, prior to and throughout disease manifestation, and in the absence of confounds rendered by age and comorbidities. It also provides potential to trial sleep therapies at a preclinical or early disease stage. Moreover, its monogenic nature facilitates the development of transgenic animal models through which to run parallel pre-clinical studies. HD, therefore, provides a key model condition through which to gain new insights into the sleep-neurodegeneration interface. CONCLUSIONS: Here, we begin by summarising contemporary knowledge of sleep abnormalities in HD, and consider how well these parallel those of Alzheimer's and Parkinson's as more common neurodegenerative conditions. We then discuss what is currently known of the sleep-neurodegeneration cyclical relationship in HD. We conclude by outlining key directions of current and future investigation by which to advance the sleep-neurodegeneration field via studies in HD.

Modelling the natural history of Huntington's disease progression.

BACKGROUND: The lack of reliable biomarkers to track disease progression is a major problem in clinical research of chronic neurological disorders. Using Huntington's disease (HD) as an example, we describe a novel approach to model HD and show that the progression of a neurological disorder can be predicted for individual patients. METHODS: Starting with an initial cohort of 343 patients with HD that we have followed since 1995, we used data from 68 patients that satisfied our filtering criteria to model disease progression, based on the Unified Huntington's Disease Rating Scale (UHDRS), a measure that is routinely used in HD clinics worldwide. RESULTS: Our model was validated by: (A) extrapolating our equation to model the age of disease onset, (B) testing it on a second patient data set by loosening our filtering criteria, (C) cross-validating with a repeated random subsampling approach and (D) holdout validating with the latest clinical assessment data from the same cohort of patients. With UHDRS scores from the past four clinical visits (over a minimum span of 2 years), our model predicts disease progression of individual patients over the next 2 years with an accuracy of 89-91%. We have also provided evidence that patients with similar baseline clinical profiles can exhibit very different trajectories of disease progression. CONCLUSIONS: This new model therefore has important implications for HD research, most obviously in the development of potential disease-modifying therapies. We believe that a similar approach can also be adapted to model disease progression in other chronic neurological disorders.

Correlation of visuospatial memory ability with right parietal EEG spindling during sleep.

Individual differences in human sleep EEG spindling were shown to be associated with psychometric measures of cognitive ability. Previous results revealed a frequency- and region specificity of this effect, suggesting that only fast, but not slow spindle-related oscillatory activity over the frontal region correlated with cognitive performance. Our aim is to test the hypothesis that region-specific spindle-type oscillatory activity is related to specific cognitive abilities reflecting the cortical localization of the corresponding cognitive function. The visuospatial abilities are the focus of the present report. Nineteen healthy volunteers were tested with the Rey-Osterrieth Complex Figure (ROCF) test and memory performances correlated with the spindle analysis of the second night's polysomnographic recordings. Correlations were age-corrected and subjected to descriptive data analysis. ROCF recall performances at 3 and 30 minutes delay, correlated positively and significantly with fast sleep spindle density measured over the right parietal area. No significant relationship between recognition performance and sleep EEG variables emerged. Slow spindle density did not correlate with test performances. Our findings converge with other data suggesting the involvement of right parietal functioning in visuospatial abilities. Moreover, these results support the hypothesis that region-specific differences in fast sleep spindling could be markers of specific neuropsychological performances.