Hassanin, H. | bioRxiv Science

bioRxiv2025

Within and between sleep and cognition: associations in older community dwelling individuals

Cross sectional and interventional studies have demonstrated that sleep has a significant impact on waking brain function including alertness and cognitive performance. Few studies have assessed whether spontaneous night-to-night variation in sleep associates with variation in brain function within an individual. How this compares to the between-individual variation in sleep and cognition and their associations also remains largely unknown. These questions are of particular interest in the context of ageing because both sleep and cognitive abilities are altered in ageing. Furthermore, older people have been reported to be less sensitive to sleep loss. Here we investigated the relationship between sleep and cognition by quantifying associations between intraindividual variation in sleep and cognition as well as associations between interindividual variation in sleep and cognition in 35 cognitively intact older adults (70.8 {+/-} 4.9 years; mean {+/-} SD; 14 females) living in the community. Subjective and actigraphic sleep measures and daily digital assessments of cognition (nine cognitive tests; 19 variables) were obtained over a two-week period. The cognitive test battery probed a wide range of cognitive functions including reaction time, working memory, attention, and problem solving. Principal Component Analysis (PCA) identified four principal sleep components which were labelled Sleep Duration, Sleep Efficiency, Subjective Sleep Quality, and Nap-Effect. Mixed model analyses were conducted with mean and deviation-from-the-mean cognitive variables to quantify how inter- and intra-individual variation in sleep associated with inter and intra individual variation in cognition. Longer sleep duration was associated with faster reaction times in both the inter- and intra-individual analyses and with reduced errors in the inter-individual analyses. Higher sleep efficiency was associated with faster reaction times in both the intra- and inter-individual analyses. By contrast, aspects of cognition relating to learning, visual memory, verbal reasoning, and verbal fluency did not associate with sleep. The data show that in older people some aspects of waking function are sensitive to normal variation in sleep duration and efficiency which implies that interventions that target these aspects of sleep may be beneficial for waking function in ageing.

physiology↗

bioRxiv2024

Rhythmic variation in proteomics: challenges and opportunities for statistical power and biomarker identification

Time-of-day variation in the molecular profile of biofluids and tissues is a well-described phenomenon, but - especially for proteomics - is rarely considered in terms of the challenges this presents to reproducible biomarker identification. In this work we demonstrate these confounding issues using a small-scale proteomics analysis of male participants in a constant routine protocol following an 8-day laboratory study, in which sleep-wake, light-dark and meal timings were controlled. We provide a case study analysis of circadian and ultradian rhythmicity in proteins in the complement and coagulation cascades, as well as apolipoproteins, and demonstrate that rhythmicity increases the risk of Type II errors due to the reduction in statistical power from increased variance. For the proteins analysed herein we show that to maintain statistical power if chronobiological variation is not controlled for, n should be increased (by between 9% and 20%); failure to do so would increase {beta}, the chance of Type II error, from a baseline value of 20% to between 22% and 28%. Conversely, controlling for rhythmic time-of-day variation in study design offers the opportunity to improve statistical power and reduce the chances of Type II errors. Indeed, control of time-of-day sampling is a more cost-effective strategy than increasing sample sizes. We recommend that best practice in proteomics study design should account for temporal variation as part of sampling strategy where possible. Where this is impractical, we recommend that additional variance from chronobiological effects be considered in power calculations, that time of sampling be reported as part of study metadata, and that researchers reference any previously identified rhythmicity in biomarkers and pathways of interest. These measures would mitigate against both false and missed discoveries, and improve reproducibility, especially in studies looking at biomarkers, pathways or conditions with a known chronobiological component.

molecular biology↗