Variability of sleep stage scoring in late midlife and early old age

peer reviewedSleep stage scoring can lead to important inter-expert variability. Although likely, whether this issue is amplified in older populations, which show alterations of sleep electrophysiology, has not been thoroughly assessed. Algorithms for automatic sleep stage scoring may appear ideal to eliminate inter-expert variability. Yet, variability between human experts and algorithm sleep stage scoring in healthy older individuals has not been investigated. Here, we aimed to compare stage scoring of older individuals and hypothesized that variability, whether between experts or considering the algorithm, would be higher than usually reported in the literature. Twenty cognitively normal and healthy late midlife individuals’ (61 ± 5 years; 10 women) night-time sleep recordings were scored by two experts from different research centres and one algorithm. We computed agreements for the entire night (percentage and Cohen's κ) and each sleep stage. Whole-night pairwise agreements were relatively low and ranged from 67% to 78% (κ, 0.54–0.67). Sensitivity across pairs of scorers proved lowest for stages N1 (8.2%–63.4%) and N3 (44.8%–99.3%). Significant differences between experts and/or algorithm were found for total sleep time, sleep efficiency, time spent in N1/N2/N3 and wake after sleep onset (p ≤ 0.005), but not for sleep onset latency, rapid eye movement (REM) and slow-wave sleep (SWS) duration (N2 + N3). Our results confirm high inter-expert variability in healthy aging. Consensus appears good for REM and SWS, considered as a whole. It seems more difficult for N3, potentially because human raters adapt their interpretation according to overall changes in sleep characteristics. Although the algorithm does not substantially reduce variability, it would favour time-efficient standardization

Using quantitative magnetic resonance imaging to track cerebral alterations in multiple sclerosis brain: A longitudinal study

peer reviewedIntroduction: Quantitative MRI quantifies tissue microstructural properties and supports the characterization of cerebral tissue damages. With an MPM protocol, 4 parameter maps are constructed: MTsat, PD, R1 and R2*, reflecting tissue physical properties associated with iron and myelin contents. Thus, qMRI is a good candidate for in vivo monitoring of cerebral damage and repair mechanisms related to MS. Here, we used qMRI to investigate the longitudinal microstructural changes in MS brain. Methods: Seventeen MS patients (age 25-65, 11 RRMS) were scanned on a 3T MRI, in two sessions separated with a median of 30 months, and the parameters evolution was evaluated within several tissue classes: NAWM, NACGM and NADGM, as well as focal WM lesions. An individual annual rate of change for each qMRI parameter was computed, and its correlation to clinical status was evaluated. For WM plaques, three areas were defined, and a GLMM tested the effect of area, time points, and their interaction on each median qMRI parameter value. Results: Patients with a better clinical evolution, that is, clinically stable or improving state, showed positive annual rate of change in MTsat and R2* within NAWM and NACGM, suggesting repair mechanisms in terms of increased myelin content and/or axonal density as well as edema/inflammation resorption. When examining WM lesions, qMRI parameters within surrounding NAWM showed microstructural modifications, even before any focal lesion is visible on conventional FLAIR MRI. Conclusion: The results illustrate the benefit of multiple qMRI data in monitoring subtle changes within normal appearing brain tissues and plaque dynamics in relation with tissue repair or disease progression. Emilie Lommers and Christophe Phillips equally contributed to the work

Positive Effect of Cognitive Reserve on Episodic Memory, Executive and Attentional Functions Taking Into Account Amyloid-Beta, Tau, and Apolipoprotein E Status

peer reviewedStudies exploring the simultaneous influence of several physiological and environmental factors on domain-specific cognition in late middle-age remain scarce. Therefore, our objective was to determine the respective contribution of modifiable risk/protective factors (cognitive reserve and allostatic load) on specific cognitive domains (episodic memory, executive functions, and attention), taking into account non-modifiable factors [sex, age, and genetic risk for Alzheimer’s disease (AD)] and AD-related biomarker amount (amyloid-beta and tau/neuroinflammation) in a healthy late-middle-aged population. One hundred and one healthy participants (59.4 ± 5 years; 68 women) were evaluated for episodic memory, executive and attentional functioning via neuropsychological test battery. Cognitive reserve was determined by the National Adult Reading Test. The allostatic load consisted of measures of lipid metabolism and sympathetic nervous system functioning. The amyloid-beta level was assessed using positron emission tomography in all participants, whereas tau/neuroinflammation positron emission tomography scans and apolipoprotein E genotype were available for 58 participants. Higher cognitive reserve was the main correlate of better cognitive performance across all domains. Moreover, age was negatively associated with attentional functioning, whereas sex was a significant predictor for episodic memory, with women having better performance than men. Finally, our results did not show clear significant associations between performance over any cognitive domain and apolipoprotein E genotype and AD biomarkers. This suggests that domain-specific cognition in late healthy midlife is mainly determined by a combination of modifiable (cognitive reserve) and non-modifiable factors (sex and age) rather than by AD biomarkers and genetic risk for AD.Cognitive Fitness in Aging stud

Heterogeneity in the links between sleep arousals, amyloid-beta and cognition

peer reviewedBACKGROUND. Tight relationships between sleep quality, cognition and amyloid-beta (Aβ) accumulation, a hallmark of Alzheimer’s disease (AD) neuropathology, emerge in the literature. Sleep arousals become more prevalent with ageing and are considered to reflect poorer sleep quality. Yet, heterogeneity in arousals has been suggested while their associations with Aβ and cognition are not established. METHODS. We recorded undisturbed night-time sleep with EEG in 101 healthy individuals in late midlife (50-70y), devoid of cognitive and sleep disorders. We classified spontaneous arousals according to their association with muscular tone increase (M+/M-) and sleep stage transition (T+/T-). We assessed cortical Aβ burden over earliest affected regions via PET imaging, and cognition via extensive neuropsychological testing. RESULTS. Arousal types differed in their oscillatory composition in theta and beta EEG bands. Furthermore, T+M- arousals, which interrupt sleep continuity, were positively linked to Aβ burden (p=.0053, R²β*=0.08). By contrast, more prevalent T-M+ arousals, upholding sleep continuity, were associated with lower Aβ burden (p=.0003, R²β*=0.13), and better cognition, particularly over the attentional domain (p<.05, R²β*≥0.04). CONCLUSION. Contrasting with what is commonly accepted, we provide empirical evidence that arousals are diverse and differently associated with early AD-related neuropathology and cognition. This suggests that sleep arousals, and their coalescence with other brain oscillations during sleep, may actively contribute to the beneficial functions of sleep. This warrants re-evaluation of age-related sleep changes and suggests that spontaneous arousals could constitute a marker of favourable brain and cognitive health trajectories

Cognitive efficiency in late midlife is linked to lifestyle characteristics and allostatic load

We investigated whether cognitive fitness in late midlife is associated with physiological and psychological factors linked to increased risk of age-related cognitive decline. Eighty-one healthy late middle-aged participants (mean age: 59.4 y; range: 50-69 y) were included. Cognitive fitness consisted of a composite score known to be sensitive to early subtle cognitive change. Lifestyle factors (referenced below as cognitive reserve factors; CRF) and affective state were determined through questionnaires, and sleep-wake quality was also assessed through actimetry. Allostatic load (AL) was determined through a large range of objective health measures. Generalized linear mixed models, controlling for sex and age, revealed that higher cognitive reserve and lower allostatic load are related to better cognitive efficiency. Crystallized intelligence, sympathetic nervous system functioning and lipid metabolism were the only sub-fields of CRF and AL to be significantly associated with cognition. These results show that previous lifestyle characteristics and current physiological status are simultaneously explaining variability in cognitive abilities in late midlife. Results further encourage early multimodal prevention programs acting on both of these modifiable factors to preserve cognition during the aging process

Good sleep, healthy ageing

Most people in the world probably know little to nothing about the third of their life they spend asleep. I will try to fix this by giving you a general overview of the mechanisms that regulate sleep, explaining why sleep is important, and how it changes throughout life. I'll throw in a few interesting anecdotes to try and not bore you... to sleep

Increased cortical excitability and reduced brain response propagation during attentional lapses

Modern lifestyle curtails sleep and increases nighttime work and leisure activities. This has a deleterious impact on vigilance and attention, exacerbating chances of committing attentional lapses, with potential dramatic outcomes. A full characterization of the brain mechanisms associated with lapses is still lacking. Here, we investigated the brain signature of attentional lapses and assessed whether cortical excitability and brain response propagation were modified during lapses and whether these modifications changed with aging. We compared electroencephalogram (EEG) responses to transcranial magnetic stimulation (TMS) during lapse and no-lapse periods while performing a continuous attentional/vigilance task at night, after usual bedtime. Data were collected in healthy younger (N=12; 18-30 y) and older individuals (N=12; 50- 70 y) of both sexes. Amplitude and slope of the first component of the TMS-Evoked Potential (TEP) and Response Scattering (ReSc) were used to assess cortical excitability and brain response propagation, respectively. In line with our predictions, TEP during lapses was characterized by larger amplitude and slope. We further found that ReSc over the cortical surface was lower during lapses. Importantly, cortical excitability increase and response propagation decrease during lapse did not significantly differ between age groups. These results demonstrate that attentional lapses are associated with transient increase of excitability, and decrease in response propagation and effective connectivity. This pattern is similar to what is observed during sleep, suggesting that lapses reflect a sleep-like phenomenon. These findings could contribute to develop models aimed to predicting and preventing lapses in real life situations

Increased cortical excitability but stable effective connectivity index during attentional lapses.

Modern lifestyle curtails sleep and increases night-time work and leisure activities. This has a deleterious impact on vigilance and attention, exacerbating chances of committing attentional lapses, with potential dramatic outcomes. Here, we investigated the brain signature of attentional lapses and assessed whether cortical excitability and brain response propagation were modified during lapses and whether these modifications changed with aging. We compared electroencephalogram (EEG) responses to transcranial magnetic stimulation (TMS) during lapse and no-lapse periods while performing a continuous attentional/vigilance task at night, after usual bedtime. Data were collected in healthy younger (N=12; 18-30 y) and older individuals (N=12; 50-70 y) of both sexes. The amplitude and slope of the first component of the TMS-Evoked Potential (TEP) were larger during lapses. In contrast, TMS response scattering over the cortical surface, as well as EEG response complexity, did not significantly vary between lapse and no-lapse periods. Importantly, despite qualitative differences, age did not significantly affect any of the TMS-EEG measures. These results demonstrate that attentional lapses are associated with a transient increase of cortical excitability. This initial change is not associated with detectable changes in subsequent effective connectivity - as indexed by response propagation - and are not markedly different between younger and older adults. These findings could contribute to develop models aimed to predicting and preventing lapses in real life situations