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Posts Tagged ‘Cognitive decline’


Sleep quality, amyloid and cognitive decline

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

β-amyloid disrupts human NREM slow waves and related hippocampus-dependent memory consolidation

Bryce A ManderShawn M MarksJacob W VogelVikram RaoBrandon LuJared M SaletinSonia Ancoli-IsraelWilliam J Jagust & Matthew P Walker

Nature Neuroscience 18, 1051–1057 (2015)    http://dx.doi.org:/10.1038/nn.4035

 

Independent evidence associates β-amyloid pathology with both non-rapid eye movement (NREM) sleep disruption and memory impairment in older adults. However, whether the influence of β-amyloid pathology on hippocampus-dependent memory is, in part, driven by impairments of NREM slow wave activity (SWA) and associated overnight memory consolidation is unknown. Here we show that β-amyloid burden in medial prefrontal cortex (mPFC) correlates significantly with the severity of impairment in NREM SWA generation. Moreover, reduced NREM SWA generation was further associated with impaired overnight memory consolidation and impoverished hippocampal-neocortical memory transformation. Furthermore, structural equation models revealed that the association between mPFC β-amyloid pathology and impaired hippocampus-dependent memory consolidation was not direct, but instead statistically depended on the intermediary factor of diminished NREM SWA. By linking β-amyloid pathology with impaired NREM SWA, these data implicate sleep disruption as a mechanistic pathway through which β-amyloid pathology may contribute to hippocampus-dependent cognitive decline in the elderly.

 

Figure 1: Aβ, NREM SWA and memory retention measures in three sample subjects.

A[beta], NREM SWA and memory retention measures in three sample subjects.

(ad) [11C]PIB-PET DVR images demonstrating Aβ deposition (a), NREM SWA and associated localized slow wave source (in arbitrary units) (b), proportion of NREM SWA 0.6–1 Hz at FZ and CZ derivations (c) and overnight memory retention (lon…

 

Figure 2: Associations between Aβ, NREM SWA and memory retention measures.

Associations between A[beta], NREM SWA and memory retention measures.

Associations between natural logarithm–transformed, [11C]PIB-PET DVR–measured mPFC Aβ deposition, mPFC relative SWA, mPFC SW density and overnight memory retention. (ad) Interaction plots of two-way, repeated measures ANCOVAs. Aβ burde…

 

Sleep disruptions similar to jet lag linked to memory and learning problems

http://www.kurzweilai.net/sleep-disruptions-similar-to-jet-lag-linked-to-memory-and-learning-problems

Add good sleep habits to regular exercise and a healthy diet to maximize good memory, scientists advise
October 29, 2015

Chemical changes in brain cells caused by disturbances in the body’s day-night cycle may lead to the learning and memory loss associated with Alzheimer’s disease, according to a University of California, Irvine (UCI) study.

People with Alzheimer’s often have problems with sleeping or may experience changes in their slumber schedule. Scientists do not completely understand why these disturbances occur.

“The issue is whether poor sleep accelerates the development of Alzheimer’s disease or vice versa,” said UCI biomedical engineering professor Gregory Brewer, affiliated with UCI’s Institute for Memory Impairments and Neurological Disorders. “It’s a chicken-or-egg dilemma, but our research points to disruption of sleep as the accelerator of memory loss.”

Inducing jet lag in mice causes low glutathione levels

To examine the link between learning and memory and circadian disturbances, his team altered normal light-dark patterns, with an eight-hour shortening of the dark period every three days for two groups of mice: young mouse models of Alzheimer’s disease (mice genetically modified to have AD symptoms) and normal mice.

The resulting jet lag greatly reduced activity in both sets of mice. The researchers found that in water maze tests, the AD mouse models had significant learning impairments that were absent in the AD mouse models not exposed to light-dark variations or in normal mice with jet lag. However, memory three days after training was impaired in both types of mice.

In follow-up tissue studies, they saw that jet lag caused a decrease in glutathione levels in the brain cells of all the mice. But these levels were much lower in the AD mouse models and corresponded to poor performance in the water maze tests. Glutathione is a major antioxidant that helps prevent damage to essential cellular components.

Glutathione deficiencies produce redox changes in brain cells. Redox reactions involve the transfer of electrons, which leads to alterations in the oxidation state of atoms and may affect brain metabolism and inflammation.

Brewer pointed to the accelerated oxidative stress as a vital component in Alzheimer’s-related learning and memory loss and noted that potential drug treatments could target these changes in redox reactions.

“This study suggests that clinicians and caregivers should add good sleep habits to regular exercise and a healthy diet to maximize good memory,” he said.

Study results appear online in the Journal of Alzheimer’s Disease.

AD has emerged as a global public health issue, currently estimated to affect 4.4% of persons 65 years old and 22% of those aged 90 and older, with an estimated 5.4 million Americans affected, according to the paper.


Abstract of Circadian Disruption Reveals a Correlation of an Oxidative GSH/GSSG Redox Shift with Learning and Impaired Memory in an Alzheimer’s Disease Mouse Model

It is unclear whether pre-symptomatic Alzheimer’s disease (AD) causes circadian disruption or whether circadian disruption accelerates AD pathogenesis. In order to examine the sensitivity of learning and memory to circadian disruption, we altered normal lighting phases by an 8 h shortening of the dark period every 3 days (jet lag) in the APPSwDI NOS2–/– model of AD (AD-Tg) at a young age (4-5 months), when memory is not yet affected compared to non-transgenic (non-Tg) mice. Analysis of activity in 12-12 h lighting or constant darkness showed only minor differences between AD-Tg and non-Tg mice. Jet lag greatly reduced activity in both genotypes during the normal dark time. Learning on the Morris water maze was significantly impaired only in the AD-Tg mice exposed to jet lag. However, memory 3 days after training was impaired in both genotypes. Jet lag caused a decrease of glutathione (GSH) levels that tended to be more pronounced in AD-Tg than in non-Tg brains and an associated increase in NADH levels in both genotypes. Lower brain GSH levels after jet lag correlated with poor performance on the maze. These data indicate that the combination of the environmental stress of circadian disruption together with latent stress of the mutant amyloid and NOS2 knockout contributes to cognitive deficits that correlate with lower GSH levels.

 

 

Reduced Metabolic Capacity in Aged Primary Retinal Pigment Epithelium (RPE) is Correlated with Increased Susceptibility to Oxidative Stress

Rohrer, M. Bandyopadhyay and C. Beeson.

Adv Exp Med Biol. 2016 Jan 1, 854: 793-8.

 

Relationships between mitochondrial content and bioenergetics with obesity, body composition and fat distribution in healthy older adults

S. Bharadwaj, D. J. Tyrrell, I. Leng, J. L. Demons, M. F. Lyles, J. J. Carr, B. J. Nicklas and A. J. Molina.

BMC Obes. 2015 Oct 6, 2: 40.

 

Mitochondrial Dysfunction in Diabetic Neuropathy: a Series of Unfortunate Metabolic Events

Fernyhough.

Curr Diab Rep. 2015 Nov 1, 15 (11): 89.

 

Small Molecules that Protect Mitochondrial Function from Metabolic Stress Decelerate Loss of Photoreceptor Cells in Murine Retinal Degeneration Models

Beeson, C. Lindsey, C. Nasarre, M. Bandyopadhyay, N. Perron and B. Rohrer.

Adv Exp Med Biol. 2016 Jan 1, 854: 449-54.

 

Reduced Metabolic Capacity in Aged Primary Retinal Pigment Epithelium (RPE) is Correlated with Increased Susceptibility to Oxidative Stress

Rohrer, M. Bandyopadhyay and C. Beeson.

Adv Exp Med Biol. 2016 Jan 1, 854: 793-8.

 

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Reporter: Aviva Lev-Ari, PhD, RN

MRI cortical thickness biomarker predicts AD-like CSF and cognitive decline in normal adults

Bradford C. Dickerson, MD and David A. Wolk, MD On behalf of the Alzheimer’s Disease Neuroimaging Initiative

Author Affiliations

From the Frontotemporal Dementia Unit, Department of Neurology, Massachusetts Alzheimer’s Disease Research Center, and Athinoula A. Martinos Center for Biomedical Imaging (B.C.D.), Massachusetts General Hospital and Harvard Medical School, Boston; and Department of Neurology, Alzheimer’s Disease Core Center, and Penn Memory Center (D.A.W.), University of Pennsylvania, Philadelphia.

Correspondence & reprint requests to Dr. Dickerson: bradd@nmr.mgh.harvard.edu

ABSTRACT

Objective: New preclinical Alzheimer disease (AD) diagnostic criteria have been developed using biomarkers in cognitively normal (CN) adults. We implemented these criteria using an MRI biomarker previously associated with AD dementia, testing the hypothesis that individuals at high risk for preclinical AD would be at elevated risk for cognitive decline.

Methods: The Alzheimer’s Disease Neuroimaging Initiative database was interrogated for CN individuals. MRI data were processed using a published set of a priori regions of interest to derive a single measure known as the AD signature (ADsig). Each individual was classified as ADsig-low (≥1 SD below the mean: high risk for preclinical AD), ADsig-average (within 1 SD of mean), or ADsig-high (≥1 SD above mean). A 3-year cognitive decline outcome was defined a priori using change in Clinical Dementia Rating sum of boxes and selected neuropsychological measures.

Results: Individuals at high risk for preclinical AD were more likely to experience cognitive decline, which developed in 21% compared with 7% of ADsig-average and 0% of ADsig-high groups (p = 0.03). Logistic regression demonstrated that every 1 SD of cortical thinning was associated with a nearly tripled risk of cognitive decline (p = 0.02). Of those for whom baseline CSF data were available, 60% of the high risk for preclinical AD group had CSF characteristics consistent with AD while 36% of the ADsig-average and 19% of the ADsig-high groups had such CSF characteristics (p = 0.1).

Conclusions: This approach to the detection of individuals at high risk for preclinical AD—identified in single CN individuals using this quantitative ADsig MRI biomarker—may provide investigators with a population enriched for AD pathobiology and with a relatively high likelihood of imminent cognitive decline consistent with prodromal AD.

 

Copyright © 2011 by AAN Enterprises, Inc.

http://www.neurology.org/content/early/2011/12/21/WNL.0b013e31823efc6c.abstract

 

 

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