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1. Sleep Disorders and Cognitive Aging Among Cognitively Impaired Versus Unimpaired Older Adults

   https://doi.org/10.1093/geront/gnad152  

   Lee, Soomi ; Nelson, Monica E. ; Hamada, Fumiko ; Wallace, Meredith L. ; Andel, Ross ; Buxton, Orfeu M. ; Almeida, David M. ; Lyketsos, Constantine ; Small, Brent J. ; Gaugler, ed., Joseph E. ( November 2023 , The Gerontologist)

   Sleep disorders often predict or co-occur with cognitive decline. Yet, little is known about how the relationship unfolds among older adults at risk for cognitive decline. To examine the associations of sleep disorders with cognitive decline in older adults with unimpaired cognition or impaired cognition (mild cognitive impairment and dementia).

   A total of 5,822 participants (Mage = 70) of the National Alzheimer’s Coordinating Center database with unimpaired or impaired cognition were followed for 3 subsequent waves. Four types of clinician-diagnosed sleep disorders were reported: sleep apnea, hyposomnia/insomnia, REM sleep behavior disorder, or “other.” Cognition over time was measured by the Montreal Cognitive Assessment (MoCA) or an estimate of general cognitive ability (GCA) derived from scores based on 12 neuropsychological tests. Growth curve models were estimated adjusting for covariates.

   In participants with impaired cognition, baseline sleep apnea was related to better baseline MoCA performance (b = 0.65, 95% confidence interval [95% CI] = [0.07, 1.23]) and less decline in GCA over time (b = 0.06, 95% CI = [0.001, 0.12]). Baseline insomnia was related to better baseline MoCA (b = 1.54, 95% CI = [0.88, 2.21]) and less decline in MoCA over time (b = 0.56, 95% CI = [0.20, 0.92]). Furthermore, having more sleep disorders (across the 4 types) at baseline predicted better baseline MoCA and GCA, and less decline in MoCA and GCA over time. These results were only found in those with impaired cognition and generally consistent when using self-reported symptoms of sleep apnea or insomnia.

   Participants with sleep disorder diagnoses may have better access to healthcare, which may help maintain cognition through improved sleep.

    

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2. Cerebellar atrophy and its contribution to cognition in frontotemporal dementias

   https://doi.org/10.1002/ana.25271  

   Chen, Yu ; Kumfor, Fiona ; Landin‐Romero, Ramon ; Irish, Muireann ; Hodges, John R. ; Piguet, Olivier ( August 2018 , Annals of Neurology)

   Increasing evidence suggests that cerebellar damage impacts on cognitive functions. Frontotemporal dementias (FTDs) are neurodegenerative brain conditions, primarily affecting the frontal and/or temporal lobe. Three main phenotypes are recognized, each with a distinct clinical and cognitive profile: behavioral‐variant FTD (bvFTD), semantic dementia (SD), and progressive nonfluent aphasia (PNFA). The severity of cerebellar changes and their relation to cognition in FTD, however, remain unclear. This study aimed to establish cerebellar gray matter changes on magnetic resonance imaging (MRI) and their relation to profiles of cognitive deficits in FTD subtypes.

   Ninety‐six FTD patients (45 bvFTD, 28 SD, and 23 PNFA), meeting current clinical diagnostic criteria, and 35 age‐, sex‐, and education‐matched controls underwent brain MRI and cognitive assessment. Cerebral and cerebellar gray matter integrity were investigated using voxel‐based morphometry.

   Compared with controls, widespread bilateral cerebellar changes were observed in all FTD subtypes, with the greatest atrophy present in bvFTD. Significant associations were found between cerebellar integrity and cognitive performance in attention and working memory in bvFTD, visuospatial function in SD, and language‐motor function in PNFA. Bilateral atrophy of crus and lobule VI were most commonly associated with cognitive deficits, irrespective of FTD phenotype.

   This study is the first to identify distinct patterns of cerebellar atrophy across FTD syndromes, which in turn relate to discrete cognitive dysfunctions, after accounting for the effect of cerebral atrophy. These findings extend our understanding of the cerebellum and point to its involvement across an array of processes beyond the domain of motor function. Ann Neurol 2018;83:98–109

    

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3. Dementia detection from brain activity during sleep

   https://doi.org/10.1093/sleep/zsac286  

   Ye, Elissa M. ; Sun, Haoqi ; Krishnamurthy, Parimala V. ; Adra, Noor ; Ganglberger, Wolfgang ; Thomas, Robert J. ; Lam, Alice D. ; Westover, M. Brandon ( November 2022 , Sleep)

   Dementia is a growing cause of disability and loss of independence in the elderly, yet remains largely underdiagnosed. Early detection and classification of dementia can help close this diagnostic gap and improve management of disease progression. Altered oscillations in brain activity during sleep are an early feature of neurodegenerative diseases and be used to identify those on the verge of cognitive decline.

   Our observational cross-sectional study used a clinical dataset of 10 784 polysomnography from 8044 participants. Sleep macro- and micro-structural features were extracted from the electroencephalogram (EEG). Microstructural features were engineered from spectral band powers, EEG coherence, spindle, and slow oscillations. Participants were classified as dementia (DEM), mild cognitive impairment (MCI), or cognitively normal (CN) based on clinical diagnosis, Montreal Cognitive Assessment, Mini-Mental State Exam scores, clinical dementia rating, and prescribed medications. We trained logistic regression, support vector machine, and random forest models to classify patients into DEM, MCI, and CN groups.

   For discriminating DEM versus CN, the best model achieved an area under receiver operating characteristic curve (AUROC) of 0.78 and area under precision-recall curve (AUPRC) of 0.22. For discriminating MCI versus CN, the best model achieved an AUROC of 0.73 and AUPRC of 0.18. For discriminating DEM or MCI versus CN, the best model achieved an AUROC of 0.76 and AUPRC of 0.32.

   Our dementia classification algorithms show promise for incorporating dementia screening techniques using routine sleep EEG. The findings strengthen the concept of sleep as a window into neurodegenerative diseases.

    

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4. Sleep duration and brain MRI measures: Results from the SOL‐INCA MRI study

   https://doi.org/10.1002/alz.13451  

   González, Kevin A. ; Tarraf, Wassim ; Stickel, Ariana M. ; Kaur, Sonya ; Agudelo, Christian ; Redline, Susan ; Gallo, Linda C. ; Isasi, Carmen R. ; Cai, Jianwen ; Daviglus, Martha L. ; et al ( September 2023 , Alzheimer's & Dementia)

   Sleep duration has been associated with dementia and stroke. Few studies have evaluated sleep pattern–related outcomes of brain disease in diverse Hispanics/Latinos.

   The SOL‐INCA (Study of Latinos‐Investigation of Neurocognitive Aging) magnetic resonance imaging (MRI) study recruited diverse Hispanics/Latinos (35–85 years) who underwent neuroimaging. The main exposure was self‐reported sleep duration. Our main outcomes were total and regional brain volumes.

   The final analytic sample includedn = 2334 participants. Increased sleep was associated with smaller brain volume (β_{total_brain} = −0.05,p < 0.01) and consistently so in the 50+ subpopulation even after adjusting for mild cognitive impairment status. Sleeping >9 hours was associated with smaller gray (β_{combined_gray} = −0.17,p < 0.05) and occipital matter volumes (β_{occipital_gray} = −0.18,p < 0.05).

   We found that longer sleep duration was associated with lower total brain and gray matter volume among diverse Hispanics/Latinos across sex and background. These results reinforce the importance of sleep on brain aging in this understudied population.

   Longer sleep was linked to smaller total brain and gray matter volumes.

   Longer sleep duration was linked to larger white matter hyperintensities (WMHs) and smaller hippocampal volume in an obstructive sleep apnea (OSA) risk group.

   These associations were consistent across sex and Hispanic/Latino heritage groups.

    

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5. Reduced White Matter Integrity and Deficits in Neuropsychological Functioning in Adults With Autism Spectrum Disorder

   https://doi.org/10.1002/aur.2271  

   Haigh, Sarah M. ; Keller, Timothy A. ; Minshew, Nancy J. ; Eack, Shaun M. ( February 2020 , Autism Research)

   Autism spectrum disorder (ASD) is currently viewed as a disorder of cortical systems connectivity, with a heavy emphasis being on the structural integrity of white matter tracts. However, the majority of the literature to date has focused on children with ASD. Understanding the integrity of white matter tracts in adults may help reveal the nature of ASD pathology in adulthood and the potential contributors to cognitive impairment. This study examined white matter water diffusion using diffusion tensor imaging in relation to neuropsychological measures of cognition in a sample of 45 adults with ASD compared to 20 age, gender, and full‐scale‐IQ‐matched healthy volunteers. Tract‐based spatial statistics were used to assess differences in diffusion along white matter tracts between groups using permutation testing. The following neuropsychological measures of cognition were assessed: processing speed, attention vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition. Results indicated that fractional anisotropy (FA) was significantly reduced in adults with ASD in the anterior thalamic radiation (P= 0.022) and the right cingulum (P= 0.008). All neuropsychological measures were worse in the ASD group, but none of the measures significantly correlated with reduced FA in either tract in the adults with ASD or in the healthy volunteers. Together, this indicates that the tracts that are the most impacted in autism may not be (at least directly) responsible for the behavioral deficits in ASD.Autism Res2020, 13: 702–714. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

   White matter tracts are the data cables in the brain that efficiently transfer information, and damage to these tracts could be the cause for the abnormal behaviors that are associated with autism. We found that two long‐range tracts (the anterior thalamic radiation and the cingulum) were both impaired in autism but were not directly related to the impairments in behavior. This suggests that the abnormal tracts and behavior are the effects of another underlying mechanism.

    

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