Poor Self-Reported Sleep is Related to Regional Cortical Thinning in Aging but not Memory Decline-Results From the Lifebrain Consortium

Poor sleep and decreased cortical thickness in veterans with mild traumatic brain injury and post-traumatic stress disorder

BACKGROUND

Poor sleep quality has been associated with changes in brain volume among veterans, particularly those who have experienced mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD). This study sought to investigate (1) whether poor sleep quality is associated with decreased cortical thickness in Iraq and Afghanistan war veterans, and (2) whether these associations differ topographically depending on the presence or absence of mTBI and PTSD.

METHODS

A sample of 440 post-9/11 era U.S. veterans enrolled in the Translational Research Center for Traumatic Brain Injury and Stress Disorders study at VA Boston, MA from 2010 to 2022 was included in the study. We examined the relationship between sleep quality, as measured by the Pittsburgh Sleep Quality Index (PSQI), and cortical thickness in veterans with mTBI (n = 57), PTSD (n = 110), comorbid mTBI and PTSD (n = 129), and neither PTSD nor mTBI (n = 144). To determine the topographical relationship between subjective sleep quality and cortical thickness in each diagnostic group, we employed a General Linear Model (GLM) at each vertex on the cortical mantle. The extent of topographical overlap between the resulting statistical maps was assessed using Dice coefficients.

RESULTS

There were no significant associations between PSQI and cortical thickness in the group without PTSD or mTBI (n = 144) or in the PTSD-only group (n = 110). In the mTBI-only group (n = 57), lower sleep quality was significantly associated with reduced thickness bilaterally in frontal, cingulate, and precuneus regions, as well as in the right parietal and temporal regions (β = -0.0137, P < 0.0005). In the comorbid mTBI and PTSD group (n = 129), significant associations were observed bilaterally in frontal, precentral, and precuneus regions, in the left cingulate and the right parietal regions (β = -0.0094, P < 0.0005). Interaction analysis revealed that there was a stronger relationship between poor sleep quality and decreased cortical thickness in individuals with mTBI (n = 186) compared to those without mTBI (n = 254) specifically in the frontal and cingulate regions (β = -0.0077, P < 0.0005).

CONCLUSIONS

This study demonstrates a significant relationship between poor sleep quality and lower cortical thickness primarily within frontal regions among individuals with both isolated mTBI or comorbid diagnoses of mTBI and PTSD. Thus, if directionality is established in longitudinal and interventional studies, it may be crucial to consider addressing sleep in the treatment of veterans who have sustained mTBI.

Sex differences in the association of sleep spindle density and cognitive performance among community-dwelling middle-aged and older adults with obstructive sleep apnea

Recent studies have found associations between obstructive sleep apnea and cognitive decline. The underlying mechanisms are still unclear. Here, we investigate the associations between changes in micro-architecture, specifically sleep spindles, and cognitive function in community-dwelling middle-aged and older adults, some with obstructive sleep apnea, with a focus on sex differences. A total of 125 voluntary participants (mean age 66.0 ± 6.4 years, 64 females) from a larger cohort (participants of the Brain in Motion Studies I and II) underwent 1 night of in-home polysomnography and a neuropsychological battery (sleep and cognitive testing were conducted within 2 weeks of each other). A semi-automatic computerized algorithm was used to score polysomnography data and detect spindle characteristics in non-rapid eye movement Stages 2 and 3 in both frontal and central electrodes. Based on their apnea-hypopnea index, participants were divided into those with no obstructive sleep apnea (apnea-hypopnea index < 5 per hr, n = 21), mild obstructive sleep apnea (5 ≥ apnea-hypopnea index < 15, n = 47), moderate obstructive sleep apnea (15 ≥ apnea-hypopnea index < 30, n = 34) and severe obstructive sleep apnea (apnea-hypopnea index ≥ 30, n = 23). There were no significant differences in spindle characteristics between the four obstructive sleep apnea severity groups. Spindle density and percentage of fast spindles were positively associated with some verbal fluency measures on the cognitive testing. Sex might be linked with these associations. Biological sex could play a role in the associations between spindle characteristics and some verbal fluency measures. Obstructive sleep apnea severity was not found to be a contributing factor in this non-clinical community-dwelling cohort.

Subjective sleep more predictive of global cognitive function than objective sleep in older adults: A specification curve analysis

OBJECTIVES

Sleep is associated with cognitive function in older adults. In the current study, we examined this relationship from subjective and objective perspectives, and determined the robustness and dimensional specificity of the associations using a comprehensive modelling approach.

METHODS

Multiple dimensions of subjective (sleep quality and daytime sleepiness) and objective sleep (sleep stages, sleep parameters, sleep spindles, and slow oscillations), as well as subjectively reported and objectively measured cognitive function were collected from 55 older adults. Specification curve analysis was used to examine the robustness of correlations for the effects of sleep on cognitive function.

RESULTS

Robust associations were found between sleep and objectively measured cognitive function, but not with subjective cognitive complaints. In addition, subjective sleep showed robust and consistent associations with global cognitive function, whereas objective sleep showed a more domain-specific association with episodic memory. Specifically, subjective sleep quality and daytime sleepiness correlated with global cognitive function, and objective sleep parameters correlated with episodic memory.

CONCLUSIONS

Overall, associations between sleep and cognitive function in older adults depend on how they are measured and which specific dimensions of sleep and domains of cognitive function are considered. It highlights the importance of focusing on specific associations to ameliorate the detrimental effects of sleep disturbance on cognitive function in later life.

Impaired sleep is associated with tau deposition on 18F-flortaucipir PET and accelerated cognitive decline, accounting for medications that affect sleep

BACKGROUND

Impaired sleep is commonly associated with Alzheimer's disease (AD), although the underlying mechanisms remain unclear. Furthermore, the moderating effects of sleep-affecting medications, which have been linked to AD pathology, are incompletely characterized. Using data from the Alzheimer's Disease Neuroimaging Initiative, we investigated whether a medical history of impaired sleep, informant-reported nighttime behaviors, and sleep-affecting medications are associated with beta-amyloid and tau deposition on PET and cognitive change, cross-sectionally and longitudinally.

METHODS

We included 964 subjects with 18F-florbetapir PET scans. Measures of sleep impairment and medication use were obtained from medical histories and the Neuropsychiatric Inventory Questionnaire. Multivariate models, adjusted for covariates, were used to assess associations among sleep-related features, beta-amyloid and tau, and cognition. Cortical tau deposition, categorized by Braak stage, was assessed using the standardized uptake value peak alignment (SUVP) method on 18F-flortaucipir PET.

RESULTS

Medical history of sleep impairment was associated with greater baseline tau in the meta-temporal, Braak 1, and Braak 4 regions (p = 0.04, p < 0.001, p = 0.025, respectively). Abnormal nighttime behaviors were also associated with greater baseline tau in the meta-temporal region (p = 0.024), and greater cognitive impairment, cross-sectionally (p = 0.007) and longitudinally (p < 0.001). Impaired sleep was not associated with baseline beta-amyloid (p > 0.05). Short-term use of selective serotonin reuptake inhibitors and benzodiazepines slightly weakened the sleep-tau relationship.

CONCLUSIONS

Sleep impairment was associated with tauopathy and cognitive decline, which could be linked to increased tau secretion from neuronal hyperactivity. Clinically, our results help identify high-risk individuals who could benefit from sleep-related interventions aimed to delay cognitive decline and AD.

Deficient sleep, altered hypothalamic functional connectivity, depression and anxiety in cigarette smokers

Background

Deficient sleep is implicated in nicotine dependence as well as depressive and anxiety disorders. The hypothalamus regulates the sleep-wake cycle and supports motivated behavior, and hypothalamic dysfunction may underpin comorbid nicotine dependence, depression and anxiety. We aimed to investigate whether and how the resting state functional connectivities (rsFCs) of the hypothalamus relate to cigarette smoking, deficient sleep, depression and anxiety.

Methods

We used the data of 64 smokers and 198 age- and sex-matched adults who never smoked, curated from the Human Connectome Project. Deficient sleep and psychiatric problems were each assessed with Pittsburgh Sleep Quality Index (PSQI) and Achenbach Adult Self-Report. We processed the imaging data with published routines and evaluated the results at a corrected threshold, all with age, sex, and the severity of alcohol use as covariates.

Results

Smokers vs. never smokers showed poorer sleep quality and greater severity of depression and anxiety. In smokers only, the total PSQI score, indicating more sleep deficits, was positively associated with hypothalamic rsFCs with the right inferior frontal/insula/superior temporal and postcentral (rPoCG) gyri. Stronger hypothalamus-rPoCG rsFCs were also associated with greater severity of depression and anxiety in smokers but not never smokers. Additionally, in smokers, the PSQI score completely mediated the relationships of hypothalamus-rPoCG rsFCs with depression and anxiety severity.

Conclusions

These findings associate hypothalamic circuit dysfunction to sleep deficiency and severity of depression and anxiety symptoms in adults who smoke. Future studies may investigate the roles of the hypothalamic circuit in motivated behaviors to better characterize the inter-related neural markers of smoking, deficient sleep, depression and anxiety.

Shorter self-reported sleep duration is associated with worse virtual spatial navigation performance in men

Sleep has been shown to impact navigation ability. However, it remains unclear how different sleep-related variables may be independently associated with spatial navigation performance, and as to whether gender may play a role in these associations. We used a mobile video game app, Sea Hero Quest (SHQ), to measure wayfinding ability in US-based participants. Wayfinding performance on SHQ has been shown to correlate with real-world wayfinding. Participants were asked to report their sleep duration, quality, daytime sleepiness and nap frequency and duration on a typical night (n = 766, 335 men, 431 women, mean age = 26.5 years, range = 18-59 years). A multiple linear regression was used to identify which self-reported sleep variables were independently associated with wayfinding performance. Shorter self-reported sleep durations were significantly associated with worse wayfinding performance in men only. Other self-reported sleep variables showed non-significant trends of association with wayfinding performance. When removing non-typical sleepers (< 6 or > 9 h of sleep on a typical night), the significant association between sleep duration and spatial navigation performance in men was no longer present. These findings from U.S.-based participants suggest that a longer self-reported sleep duration may be an important contributor to successful navigation ability in men.

FEMA: Fast and efficient mixed-effects algorithm for large sample whole-brain imaging data

The linear mixed-effects model (LME) is a versatile approach to account for dependence among observations. Many large-scale neuroimaging datasets with complex designs have increased the need for LME; however LME has seldom been used in whole-brain imaging analyses due to its heavy computational requirements. In this paper, we introduce a fast and efficient mixed-effects algorithm (FEMA) that makes whole-brain vertex-wise, voxel-wise, and connectome-wide LME analyses in large samples possible. We validate FEMA with extensive simulations, showing that the estimates of the fixed effects are equivalent to standard maximum likelihood estimates but obtained with orders of magnitude improvement in computational speed. We demonstrate the applicability of FEMA by studying the cross-sectional and longitudinal effects of age on region-of-interest level and vertex-wise cortical thickness, as well as connectome-wide functional connectivity values derived from resting state functional MRI, using longitudinal imaging data from the Adolescent Brain Cognitive DevelopmentSM Study release 4.0. Our analyses reveal distinct spatial patterns for the annualized changes in vertex-wise cortical thickness and connectome-wide connectivity values in early adolescence, highlighting a critical time of brain maturation. The simulations and application to real data show that FEMA enables advanced investigation of the relationships between large numbers of neuroimaging metrics and variables of interest while considering complex study designs, including repeated measures and family structures, in a fast and efficient manner. The source code for FEMA is available via: https://github.com/cmig-research-group/cmig_tools/.

The Relation of Sleep Characteristics and Cognitive Impairment in Community-Dwelling Middle-Aged and Older Adults: Ardakan Cohort Study on Aging (ACSA)

Introduction

The rise in the elderly population has brought attention to mild cognitive impairment (MCI). Sleep disorders also affect many older adults, indicating an important area of research for disturbed sleep and faster brain aging. This population-based study aimed to investigate the association of several sleep indicators with cognitive performance.

Methods

This cross-sectional study focused on adults over 50 in the Ardakan Cohort Study on Aging (ACSA). MCI was evaluated using the Mini-Mental State Examination (MMSE) and the Abbreviated Mental Test score (AMTS) in literate and illiterate individuals. Sleep characteristics were collected using the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale, and Berlin questionnaire. The logistic regression models were used to analyze the data.

Results

Overall, 3,380 literate and 1,558 illiterate individuals were included. In both groups, participants with MCI had a significantly higher PSQI global score (p < 0.05). Also, among the literate individuals, a significantly higher risk of having sleep-disordered breathing and poor sleep quality was observed in participants with MCI (p < 0.05). In illiterate individuals, higher sleep latency than 15 min increased odds of MCI (p < 0.05). However, after adjusting for all variables, only literate individuals with a sleep duration of more than 8 h had 66 percent increased odds of having MCI (p = 0.033).

Conclusion

Sleep duration might be associated with cognitive function in the older Iranian population. Our findings underscore the importance of considering sleep patterns in relation to cognitive health.

Differential effects of sleep on brain structure and metabolism at the preclinical stages of AD

INTRODUCTION

Poor sleep quality is associated with cognitive outcomes in Alzheimer's disease (AD). We analyzed the associations between self-reported sleep quality and brain structure and function in cognitively unimpaired (CU) individuals.

METHODS

CU adults (N = 339) underwent structural magnetic resonance imaging, lumbar puncture, and the Pittsburgh Sleep Quality Index (PSQI) questionnaire. A subset (N = 295) performed [18F] fluorodeoxyglucose positron emission tomography scans. Voxel-wise associations with gray matter volumes (GMv) and cerebral glucose metabolism (CMRGlu) were performed including interactions with cerebrospinal fluid (CSF) AD biomarkers status.

RESULTS

Poorer sleep quality was associated with lower GMv and CMRGlu in the orbitofrontal and cingulate cortices independently of AD pathology. Self-reported sleep quality interacted with altered core AD CSF biomarkers in brain areas known to be affected in preclinical AD stages.

DISCUSSION

Poor sleep quality may impact brain structure and function independently from AD pathology. Alternatively, AD-related neurodegeneration in areas involved in sleep-wake regulation may induce or worsen sleep disturbances. Highlights Poor sleep impacts brain structure and function independent of Alzheimer's disease (AD) pathology. Poor sleep exacerbates brain changes observed in preclinical AD. Sleep is an appealing therapeutic strategy for preventing AD.

No phenotypic or genotypic evidence for a link between sleep duration and brain atrophy

Short sleep is held to cause poorer brain health, but is short sleep associated with higher rates of brain structural decline? Analysing 8,153 longitudinal MRIs from 3,893 healthy adults, we found no evidence for an association between sleep duration and brain atrophy. In contrast, cross-sectional analyses (51,295 observations) showed inverse U-shaped relationships, where a duration of 6.5 (95% confidence interval, (5.7, 7.3)) hours was associated with the thickest cortex and largest volumes relative to intracranial volume. This fits converging evidence from research on mortality, health and cognition that points to roughly seven hours being associated with good health. Genome-wide association analyses suggested that genes associated with longer sleep for below-average sleepers were linked to shorter sleep for above-average sleepers. Mendelian randomization did not yield evidence for causal impacts of sleep on brain structure. The combined results challenge the notion that habitual short sleep causes brain atrophy, suggesting that normal brains promote adequate sleep duration-which is shorter than current recommendations.

Causal associations between sleep traits and brain structure: a bidirectional Mendelian randomization study

BACKGROUND

Emerging evidence suggests bidirectional causal relationships between sleep disturbance and psychiatric disorders, but the underlying mechanisms remain unclear. Understanding the bidirectional causality between sleep traits and brain imaging-derived phenotypes (IDPs) will help elucidate the mechanisms. Although previous studies have identified a range of structural differences in the brains of individuals with sleep disorders, it is still uncertain whether grey matter (GM) volume alterations precede or rather follow from the development of sleep disorders.

RESULTS

After Bonferroni correction, the forward MR analysis showed that insomnia complaint remained positively associated with the surface area (SA) of medial orbitofrontal cortex (β, 0.26; 95% CI, 0.15-0.37; P = 5.27 × 10-6). In the inverse MR analysis, higher global cortical SA predisposed individuals less prone to suffering insomnia complaint (OR, 0.89; 95%CI, 0.85-0.94; P = 1.51 × 10-5) and short sleep (≤ 6 h; OR, 0.98; 95%CI, 0.97-0.99; P = 1.51 × 10-5), while higher SA in posterior cingulate cortex resulted in a vulnerability to shorter sleep durations (β, - 0.09; 95%CI, - 0.13 to - 0.05; P = 1.21 × 10-5).

CONCLUSIONS

Sleep habits not only result from but also contribute to alterations in brain structure, which may shed light on the possible mechanisms linking sleep behaviours with neuropsychiatric disorders, and offer new strategies for prevention and intervention in psychiatric disorders and sleep disturbance.

Maintaining brain health across the lifespan

Across the lifespan, the human body and brain endure the impact of a plethora of exogenous and endogenous factors that determine the health outcome in old age. The overwhelming inter-individual variance spans between progressive frailty with loss of autonomy to largely preserved physical, cognitive, and social functions. Understanding the mechanisms underlying the diverse aging trajectories can inform future strategies to maintain a healthy body and brain. Here we provide a comprehensive overview of the current literature on lifetime factors governing brain health. We present the growing body of evidence that unhealthy alimentary regime, sedentary behaviour, sleep pathologies, cardio-vascular risk factors, and chronic inflammation exert their harmful effects in a cumulative and gradual manner, and that timely and efficient intervention could promote healthy and successful aging. We discuss the main effects and interactions between these risk factors and the resulting brain health outcomes to follow with a description of current strategies aiming to eliminate, treat, or counteract the risk factors. We conclude that the detailed insights about modifiable risk factors could inform personalized multi-domain strategies for brain health maintenance on the background of increased longevity.

Is Short Sleep Bad for the Brain? Brain Structure and Cognitive Function in Short Sleepers

Many sleep less than recommended without experiencing daytime sleepiness. According to prevailing views, short sleep increases risk of lower brain health and cognitive function. Chronic mild sleep deprivation could cause undetected sleep debt, negatively affecting cognitive function and brain health. However, it is possible that some have less sleep need and are more resistant to negative effects of sleep loss. We investigated this using a cross-sectional and longitudinal sample of 47,029 participants of both sexes (20-89 years) from the Lifebrain consortium, Human Connectome project (HCP) and UK Biobank (UKB), with measures of self-reported sleep, including 51,295 MRIs of the brain and cognitive tests. A total of 740 participants who reported to sleep <6 h did not experience daytime sleepiness or sleep problems/disturbances interfering with falling or staying asleep. These short sleepers showed significantly larger regional brain volumes than both short sleepers with daytime sleepiness and sleep problems (n = 1742) and participants sleeping the recommended 7-8 h (n = 3886). However, both groups of short sleepers showed slightly lower general cognitive function (GCA), 0.16 and 0.19 SDs, respectively. Analyses using accelerometer-estimated sleep duration confirmed the findings, and the associations remained after controlling for body mass index, depression symptoms, income, and education. The results suggest that some people can cope with less sleep without obvious negative associations with brain morphometry and that sleepiness and sleep problems may be more related to brain structural differences than duration. However, the slightly lower performance on tests of general cognitive abilities warrants closer examination in natural settings.SIGNIFICANCE STATEMENT Short habitual sleep is prevalent, with unknown consequences for brain health and cognitive performance. Here, we show that daytime sleepiness and sleep problems are more strongly related to regional brain volumes than sleep duration. However, participants sleeping ≤6 h had slightly lower scores on tests of general cognitive function (GCA). This indicates that sleep need is individual and that sleep duration per se is very weakly if at all related brain health, while daytime sleepiness and sleep problems may show somewhat stronger associations. The association between habitual short sleep and lower scores on tests of general cognitive abilities must be further scrutinized in natural settings.

Purpose in life promotes resilience to age-related brain burden in middle-aged adults

BACKGROUND

Disease-modifying agents to counteract cognitive impairment in older age remain elusive. Hence, identifying modifiable factors promoting resilience, as the capacity of the brain to maintain cognition and function with aging and disease, is paramount. In Alzheimer's disease (AD), education and occupation are typical cognitive reserve proxies. However, the importance of psychological factors is being increasingly recognized, as their operating biological mechanisms are elucidated. Purpose in life (PiL), one of the pillars of psychological well-being, has previously been found to reduce the deleterious effects of AD-related pathological changes on cognition. However, whether PiL operates as a resilience factor in middle-aged individuals and what are the underlying neural mechanisms remain unknown.

METHODS

Data was obtained from 624 middle-aged adults (mean age 53.71 ± 6.9; 303 women) from the Barcelona Brain Health Initiative cohort. Individuals with lower (LP; N = 146) and higher (HP; N = 100) PiL rates, according to the division of this variable into quintiles, were compared in terms of cognitive status, a measure reflecting brain burden (white matter lesions; WMLs), and resting-state functional connectivity, examining system segregation (SyS) parameters using 14 common brain circuits.

RESULTS

Neuropsychological status and WMLs burden did not differ between the PiL groups. However, in the LP group, greater WMLs entailed a negative impact on executive functions. Subjects in the HP group showed lower SyS of the dorsal default-mode network (dDMN), indicating lesser segregation of this network from other brain circuits. Specifically, HP individuals had greater inter-network connectivity between specific dDMN nodes, including the frontal cortex, the hippocampal formation, the midcingulate region, and the rest of the brain. Greater functional connectivity in some of these nodes positively correlated with cognitive performance.

CONCLUSION

Expanding previous findings on AD pathology and advanced age, the present results suggest that higher rates of PiL may promote resilience against brain changes already observable in middle age. Furthermore, having a purposeful life implies larger functional integration of the dDMN, which may potentially reflect greater brain reserve associated to better cognitive function.

Associations between self-reported sleep patterns and health, cognition and amyloid measures: results from the Wisconsin Registry for Alzheimer's Prevention

Previous studies suggest associations between self-reported sleep problems and poorer health, cognition, Alzheimer's disease pathology and dementia-related outcomes. It is important to develop a deeper understanding of the relationship between these complications and sleep disturbance, a modifiable risk factor, in late midlife, a time when Alzheimer's disease pathology may be accruing. The objectives of this study included application of unsupervised machine learning procedures to identify distinct subgroups of persons with problematic sleep and the association of these subgroups with concurrent measures of mental and physical health, cognition and PET-identified amyloid. Dementia-free participants from the Wisconsin Registry for Alzheimer's Prevention (n = 619) completed sleep questionnaires including the Insomnia Severity Index, Epworth Sleepiness Scale and Medical Outcomes Study Sleep Scale. K-means clustering analysis identified discrete sleep problem groups who were then compared across concurrent health outcomes (e.g. depression, self-rated health and insulin resistance), cognitive composite indices including episodic memory and executive function and, in a subset, Pittsburgh Compound B PET imaging to assess amyloid burden. Significant omnibus tests (P < 0.05) were followed with pairwise comparisons. Mean (SD) sample baseline sleep assessment age was 62.6 (6.7). Cluster analysis identified three groups: healthy sleepers [n = 262 (42.3%)], intermediate sleepers [n = 229 (37.0%)] and poor sleepers [n = 128 (20.7%)]. All omnibus tests comparing demographics and health measures across sleep groups were significant except for age, sex and apolipoprotein E e4 carriers; the poor sleepers group was worse than one or both of the other groups on all other measures, including measures of depression, self-reported health and memory complaints. The poor sleepers group had higher average body mass index, waist-hip ratio and homeostatic model assessment of insulin resistance. After adjusting for covariates, the poor sleepers group also performed worse on all concurrent cognitive composites except working memory. There were no differences between sleep groups on PET-based measures of amyloid. Sensitivity analyses indicated that while different clustering approaches resulted in different group assignments for some (predominantly the intermediate group), between-group patterns in outcomes were consistent. In conclusion, distinct sleep characteristics groups were identified with a sizable minority (20.7%) exhibiting poor sleep characteristics, and this group also exhibited the poorest concurrent mental and physical health and cognition, indicating substantial multi-morbidity; sleep group was not associated with amyloid PET estimates. Precision-based management of sleep and related factors may provide an opportunity for early intervention that could serve to delay or prevent clinical impairment.

Understanding the Need for Sleep to Improve Cognition

The restorative function of sleep is shaped by its duration, timing, continuity, subjective quality, and efficiency. Current sleep recommendations specify only nocturnal duration and have been largely derived from sleep self-reports that can be imprecise and miss relevant details. Sleep duration, preferred timing, and ability to withstand sleep deprivation are heritable traits whose expression may change with age and affect the optimal sleep prescription for an individual. Prevailing societal norms and circumstances related to work and relationships interact to influence sleep opportunity and quality. The value of allocating time for sleep is revealed by the impact of its restriction on behavior, functional brain imaging, sleep macrostructure, and late-life cognition. Augmentation of sleep slow oscillations and spindles have been proposed for enhancing sleep quality, but they inconsistently achieve their goal. Crafting bespoke sleep recommendations could benefit from large-scale, longitudinal collection of objective sleep data integrated with behavioral and self-reported data.

The association of sleep and cortical thickness in mild cognitive impairment

We investigated whether device-measured sleep parameters are associated with cortical thickness in older adults with probable mild cognitive impairment (MCI). We performed a cross-sectional, exploratory analysis of sleep and structural MRI data. Sleep data were collected with MotionWatch8© actigraphy over 7 days. We computed average and variability for sleep duration, sleep efficiency, and fragmentation index. T1-weighted MRI scans were used to measure cortical thickness in FreeSurfer. We employed surface-based analysis to determine the association between sleep measures and cortical thickness, adjusting for age, sex, Montreal Cognitive Assessment (MoCA) score, and sleep medication use. Our sample included 113 participants (age = 73.1 [5.7], female = 72 [63.7 %]). Higher fragmentation index variability predicted lower cortical thickness in the left superior frontal gyrus (cluster size = 970.9 mm², cluster-wise p = 0.017, cortical thickness range = 2.1 mm² to 3.0 mm²), adjusting for age, sex, MoCA, and sleep medication. Our results suggest that higher variability in sleep fragmentation, an indicator of irregular sleep pattern, is linked to lower cortical thickness. Future longitudinal studies are needed to determine the directionality of these associations.

Unveiling the neuroimaging-genetic intersections in the human brain

PURPOSE OF REVIEW

The prevalence of new public datasets of brain-wide and single-cell transcriptome data has created new opportunities to link neuroimaging findings with genetic data. The aim of this study is to present the different methodological approaches that have been used to combine this data.

RECENT FINDINGS

Drawing from various sources of open access data, several studies have been able to correlate neuroimaging maps with spatial distribution of brain expression. These efforts have enabled researchers to identify functional annotations of related genes, identify specific cell types related to brain phenotypes, study the expression of genes across life span and highlight the importance of selected brain genes in disease genetic networks.

SUMMARY

New transcriptome datasets and methodological approaches complement current neuroimaging work and will be crucial to improve our understanding of the biological mechanism that underlies many neurological conditions.

Human Brain Resilience: A Call to Action

At present, resilience refers to a highly heterogeneous concept with ill-defined determinants, mechanisms, and outcomes. This call for action argues for the need to define resilience as a person-centered multidimensional metric, informed by a dynamic lifespan perspective and combining observational and interventional experimental studies to identify specific neural markers and correlated behavioral measures. The coronavirus disease 2019 (COVID-19) pandemic highlights the urgent need of such an effort with the ultimate goal of defining a new vital sign, an individual index of resilience, as a life-long metric with the capacity to predict an individual's risk for disability in the face of a stressor, insult, injury, or disease. ANN NEUROL 2021.

The genetic organization of longitudinal subcortical volumetric change is stable throughout the lifespan

Development and aging of the cerebral cortex show similar topographic organization and are governed by the same genes. It is unclear whether the same is true for subcortical regions, which follow fundamentally different ontogenetic and phylogenetic principles. We tested the hypothesis that genetically governed neurodevelopmental processes can be traced throughout life by assessing to which degree brain regions that develop together continue to change together through life. Analyzing over 6000 longitudinal MRIs of the brain, we used graph theory to identify five clusters of coordinated development, indexed as patterns of correlated volumetric change in brain structures. The clusters tended to follow placement along the cranial axis in embryonic brain development, suggesting continuity from prenatal stages, and correlated with cognition. Across independent longitudinal datasets, we demonstrated that developmental clusters were conserved through life. Twin-based genetic correlations revealed distinct sets of genes governing change in each cluster. Single-nucleotide polymorphisms-based analyses of 38,127 cross-sectional MRIs showed a similar pattern of genetic volume–volume correlations. In conclusion, coordination of subcortical change adheres to fundamental principles of lifespan continuity and genetic organization.