Mood Influences the Concordance of Subjective and Objective Measures of Sleep Duration in Older Adults

Objective/Background: Sleep plays a central role in maintaining health and cognition. In most epidemiologic studies, sleep is evaluated by self-report questionnaires but several reports suggest that these evaluations might be less accurate than objective measures such as polysomnography or actigraphy. Determinants of the discrepancy between objective and subjective measures remain to be investigated. The aim of this pilot-study was to examine the role of mood states in determining the discrepancy observed between objective and subjective measures of sleep duration in older adults.Patients/Methods: Objective sleep quantity and quality were recorded by actigraphy in a sample of 45 elderly subjects over at least three consecutive nights. Subjective sleep duration and supplementary data, such as mood status and memory, were evaluated using Ecological Momentary Assessment (EMA).Results: A significant discrepancy was observed between EMA and actigraphic measures of sleep duration (p<0.001). The magnitude of this difference was explained by the patient’s mood status (p=0.020). No association was found between the magnitude of this discrepancy and age, sex, sleep quality or memory performance.Conclusion: The discrepancy classically observed between objective and subjective measures of sleep duration can be explained by mood status at the time of awakening. These results have potential implications for epidemiologic and clinical studies examining sleep as a risk factor for morbidity or mortality

Activity/rest cycle and disturbances of structural backbone of cerebral networks in aging.

OBJECTIVE: Although aging is associated with alterations of both activity/rest cycle and brain structure, few studies have evaluated associations between these processes. The aim of this study was to examine relationship between activity/rest cycle quality and brain structural integrity in aging subjects by exploring both grey and white matter compartments. MATERIAL AND METHODS: Fifty-eight elderly subjects (76±0.5 years; 41% female) without dementia, sleep disorders and medications were included in the analysis. Actigraphy was used to measure parameters of activity/rest cycle (24-h amplitude, 24-h fragmentation and 24-h stability) and sleep (total sleep time and sleep fragmentation) over a minimal period of 5 days. Whole brain linear regression analyses were performed on grey matter volumes maps using voxel based morphometry and on white matter integrity using tract based statistics analyses. RESULTS: A lower 24-h amplitude and a higher sleep fragmentation were independently associated with a reduction of white matter integrity in models including age and gender as covariates. The association between 24-h amplitude and white matter integrity decreased but remained significant in a model accounted for sleep fragmentation, indicating a specific effect of 24-h cycle disturbances. No association with grey matter volumes was observed. CONCLUSION: In elderly, not only sleep but also 24-h cycle disturbances were associated with altered structural connectivity. This alteration of structural backbone networks related to activity/rest cycle disturbances in aging might constitute a cerebral frailty factor for the development of cognitive impairment

Genetic Variants For Head Size Share Genes and Pathways With Cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer

Structural progression of Alzheimer’s disease over decades: the MRI staging scheme

International audienceAbstract The chronological progression of brain atrophy over decades, from pre-symptomatic to dementia stages, has never been formally depicted in Alzheimer’s disease. This is mainly due to the lack of cohorts with long enough MRI follow-ups in cognitively unimpaired young participants at baseline. To describe a spatiotemporal atrophy staging of Alzheimer’s disease at the whole-brain level, we built extrapolated lifetime volumetric models of healthy and Alzheimer’s disease brain structures by combining multiple large-scale databases (n = 3512 quality controlled MRI from 9 cohorts of subjects covering the entire lifespan, including 415 MRI from ADNI1, ADNI2 and AIBL for Alzheimer’s disease patients). Then, we validated dynamic models based on cross-sectional data using external longitudinal data. Finally, we assessed the sequential divergence between normal aging and Alzheimer’s disease volumetric trajectories and described the following staging of brain atrophy progression in Alzheimer’s disease: (i) hippocampus and amygdala; (ii) middle temporal gyrus; (iii) entorhinal cortex, parahippocampal cortex and other temporal areas; (iv) striatum and thalamus and (v) middle frontal, cingular, parietal, insular cortices and pallidum. We concluded that this MRI scheme of atrophy progression in Alzheimer’s disease was close but did not entirely overlap with Braak staging of tauopathy, with a ‘reverse chronology’ between limbic and entorhinal stages. Alzheimer’s disease structural progression may be associated with local tau accumulation but may also be related to axonal degeneration in remote sites and other limbic-predominant associated proteinopathies

Multimodal Hippocampal Subfield Grading For Alzheimer's Disease Classification.

Numerous studies have proposed biomarkers based on magnetic resonance imaging (MRI) to detect and predict the risk of evolution toward Alzheimer's disease (AD). Most of these methods have focused on the hippocampus, which is known to be one of the earliest structures impacted by the disease. To date, patch-based grading approaches provide among the best biomarkers based on the hippocampus. However, this structure is complex and is divided into different subfields, not equally impacted by AD. Former in-vivo imaging studies mainly investigated structural alterations of these subfields using volumetric measurements and microstructural modifications with mean diffusivity measurements. The aim of our work is to improve the current classification performances based on the hippocampus with a new multimodal patch-based framework combining structural and diffusivity MRI. The combination of these two MRI modalities enables the capture of subtle structural and microstructural alterations. Moreover, we propose to study the efficiency of this new framework applied to the hippocampal subfields. To this end, we compare the classification accuracy provided by the different hippocampal subfields using volume, mean diffusivity, and our novel multimodal patch-based grading framework combining structural and diffusion MRI. The experiments conducted in this work show that our new multimodal patch-based method applied to the whole hippocampus provides the most discriminating biomarker for advanced AD detection while our new framework applied into subiculum obtains the best results for AD prediction, improving by two percentage points the accuracy compared to the whole hippocampus

Author Correction: Multimodal hippocampal subfield grading for Alzheimer's disease classification.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Night‐to‐night variability in sleep and amyloid beta burden in normal aging

Abstract INTRODUCTION Alzheimer's disease is associated with sleep disturbances and accumulation of cerebral amyloid beta. The objective was to examine whether actigraphy‐detected sleep parameters might be biomarkers for early amyloid burden. METHODS Participants underwent a week of actigraphy and an amyloid positron emission tomography (PET) scan. Sleep duration and continuity disruption (sleep fragmentation and nocturnal awakenings) were extracted and compared between amyloid‐positive and amyloid‐negative participants. Then multiple linear regressions were used between mean or night‐to‐night intra‐individual variability (standard deviation) of sleep parameters and brain amyloid burden in a voxel‐wise analysis. RESULTS Eighty‐six subjects were included (80.3 ± 5.4 years; 48.8% of women). Amyloid‐positive participants had a higher variability of sleep fragmentation compared to amyloid‐negative participants. This parameter was associated with a higher amyloid burden in the frontal and parietal regions, and in the precuneus, in the whole sample. DISCUSSION This study highlights the relevance of using variability in sleep continuity as a potential biomarker of early amyloid pathogenesis

Normal-Appearing White Matter Deteriorates over the Year After an Ischemic Stroke and Is Associated with Global Cognition

International audienceNormal-appearing white matter (NAWM) is a hub of plasticity, but data relating to its influence on post-ischemic stroke (IS) outcome remain scarce. The aim of this study was to evaluate the relationship between NAWM integrity and cognitive outcome after an IS. A longitudinal study was conducted including supra-tentorial IS patients. A 3-Tesla brain MRI was performed at baseline and 1 year, allowing the analyses of mean fractional anisotropy (FA) and mean diffusivity (MD) in NAWM masks, along with the volume of white matter hyperintensities (WMH) and IS. A Montreal Cognitive Assessment (MoCA), an Isaacs set test, and a Zazzo's cancellation task were performed at baseline, 3 months and 1 year. Mixed models were built, followed by Tract-based Spatial Statistics (TBSS) analyses. Ninety-five patients were included in the analyses (38% women, median age 69 ± 20). FA significantly decreased, and MD significantly increased between baseline and 1 year, while cognitive scores improved. Patients who decreased their NAWM FA more over the year had a slower cognitive improvement on MoCA (β = - 0.11, p = 0.05). The TBSS analyses showed that patients who presented the highest decrease of FA in various tracts of white matter less improved their MoCA performances, regardless of WMH and IS volumes, demographic confounders, and clinical severity. NAWM integrity deteriorates over the year after an IS, and is associated with a cognitive recovery slowdown. The diffusion changes recorded here in patients starting with an early preserved white matter structure could have long term impact on cognition

Microstructural Gray Matter Integrity Deteriorates After an Ischemic Stroke and Is Associated with Processing Speed

International audienceMicrostructural changes after an ischemic stroke (IS) have mainly been described in white matter. Data evaluating microstructural changes in gray matter (GM) remain scarce. The aim of the present study was to evaluate the integrity of GM on longitudinal data using mean diffusivity (MD), and its influence on post-IS cognitive performances. A prospective study was conducted, including supra-tentorial IS patients without pre-stroke disability. A cognitive assessment was performed at baseline and 1 year, including a Montreal Cognitive Assessment, an Isaacs set test, and a Zazzo cancelation task (ZCT): completion time and number of errors. A 3-T brain MRI was performed at the same two time-points, including diffusion tensor imaging for the assessment of GM MD. GM volume was also computed, and changes in GM volume and GM MD were evaluated, followed by the assessment of the relationship between these structural changes and changes in cognitive performances. One hundred and four patients were included (age 68.5 ± 21.5, 38.5% female). While no GM volume loss was observed, GM MD increased between baseline and 1 year. The increase of GM MD in left fronto-temporal regions (dorsolateral prefrontal cortex, superior and medial temporal gyrus, p < 0.05, Threshold-Free Cluster Enhancement, 5000 permutations) was associated with an increase time to complete ZCT, regardless of demographic confounders, IS volume and location, GM, and white matter hyperintensity volume. GM integrity deterioration was thus associated with processing speed slowdown, and appears to be a biomarker of cognitive frailty. This broadens the knowledge of post-IS cognitive impairment mechanisms