Alzheimer’s Disease Severity is Not Significantly Associated with Short Sleep: Survey by Actigraphy on 208 Mild and Moderate Alzheimer’s Disease Patients

2016 ◽  
Vol 55 (1) ◽  
pp. 321-331 ◽  
Author(s):  
Damien Leger ◽  
Maxime Elbaz ◽  
Alexandre Dubois ◽  
Stéphane Rio ◽  
Hocine Mezghiche ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Severity ◽  
Short Sleep

Increased isoprostane biosynthesis in alzheimer's disease: Correlation of a specific non invasive index of lipid peroxidation with disease severity

2000 ◽  
Vol 21 ◽  
pp. 220 ◽  
Author(s):  
Domenico Pratico ◽  
Christopher C. Clark ◽  
Virginia M-Y. Lee ◽  
John Q. Trojanowski ◽  
Garret A. FitzGerald
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Lipid Peroxidation ◽  
Disease Severity ◽  
Non Invasive

scholarly journals Group-level progressive alterations in brain connectivity patterns revealed by diffusion-tensor brain networks across severity stages in Alzheimer’s disease

2017 ◽  
Author(s):  
J. Rasero ◽  
C. Alonso-Montes ◽  
I. Diez ◽  
L. Olabarrieta-Landa ◽  
L. Remaki ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Disease Severity ◽  
Diffusion Tensor ◽  
Brain Networks ◽  
Stage Ii ◽  
Group Level ◽  
The Brain

AbstractAlzheimer’s disease (AD) is a chronically progressive neurodegenerative disease highly correlated to aging. Whether AD originates by targeting a localized brain area and propagates to the rest of the brain across disease-severity progression is a question with an unknown answer. Here, we aim to provide an answer to this question at the group-level by looking at differences in diffusion-tensor brain networks. In particular, making use of data from Alzheimer's Disease Neuroimaging Initiative (ADNI), four different groups were defined (all of them matched by age, sex and education level): G1 (N1=36, healthy control subjects, Control), G2 (N2=36, early mild cognitive impairment, EMCI), G3 (N3=36, late mild cognitive impairment, LMCI) and G4 (N4=36, AD). Diffusion-tensor brain networks were compared across three disease stages: stage I 3(Control vs EMCI), stage II (Control vs LMCI) and stage III (Control vs AD). The group comparison was performed using the multivariate distance matrix regression analysis, a technique that was born in genomics and was recently proposed to handle brain functional networks, but here applied to diffusion-tensor data. The results were three-fold: First, no significant differences were found in stage I. Second, significant differences were found in stage II in the connectivity pattern of a subnetwork strongly associated to memory function (including part of the hippocampus, amygdala, entorhinal cortex, fusiform gyrus, inferior and middle temporal gyrus, parahippocampal gyrus and temporal pole). Third, a widespread disconnection across the entire AD brain was found in stage III, affecting more strongly the same memory subnetwork appearing in stage II, plus the other new subnetworks,including the default mode network, medial visual network, frontoparietal regions and striatum. Our results are consistent with a scenario where progressive alterations of connectivity arise as the disease severity increases and provide the brain areas possibly involved in such a degenerative process. Further studies applying the same strategy to longitudinal data are needed to fully confirm this scenario.

scholarly journals Research on the Glial–Lymphatic System and Its Relationship With Alzheimer’s Disease

2021 ◽  
Vol 15 ◽  
Author(s):  
Danhua Ding ◽  
Xinyu Wang ◽  
Qianqian Li ◽  
Lanjun Li ◽  
Jun Wu
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Severity ◽  
Interstitial Fluid ◽  
Lymphatic System ◽  
Pathological Change ◽  
Vital Role ◽  
Aquaporin 4 ◽  
Β Amyloid ◽  
The Brain

Metabolic waste clearance is essential to maintain body homeostasis, in which the lymphatic system plays a vital role. Conversely, in recent years, studies have identified the glial–lymphatic system in the brain, which primarily comprises the inflow of fluid along the para-arterial space. Aquaporin-4 mediates the convection of interstitial fluid in the brain and outflow along the paravenous space. β-Amyloid deposition is a characteristic pathological change in Alzheimer’s disease, and some studies have found that the glial–lymphatic system plays an important role in its clearance. Thus, the glial–lymphatic system may influence Alzheimer’s disease severity and outcome; therefore, this review summarizes the current and available research on the glial–lymphatic system and Alzheimer’s disease.

The Association between Alzheimer's Disease Severity as measured by RMBPC and Caregiver-reported Outcomes

2013 ◽  
Vol 21 (3) ◽  
pp. S133-S134
Author(s):  
Michael Durkin ◽  
Shaloo Gupta ◽  
Deborah Freedman ◽  
Jonathan Chapnick ◽  
Sonali Shah
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Severity

scholarly journals 1152 Genetic Risk Of Alzheimer’S Disease Is Linked To Short Sleep Duration

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A439-A439
Author(s):  
Y Leng ◽  
K Yaffe ◽  
S Ackley ◽  
M Glymour ◽  
W Brenowitz
Keyword(s):  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Sleep Duration ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Genetic Ancestry ◽  
European Ancestry ◽  
Short Sleep Duration ◽  
Short Sleep

Abstract Introduction Sleep disturbances including short sleep duration are common in older adults, especially in those with Alzheimer’s disease (AD). However, it is unclear to what extent sleep duration is a manifestation of AD disease process. We examined whether genetic variants related to AD influence sleep duration in middle-aged and older adults and estimated the causal effects of AD on sleep duration using a mendelian randomization (MR) analysis. Methods We examined 406,687 UK Biobank participants with Caucasian genetic ancestry who self-reported sleep duration at baseline (2006-2010). Sleep duration was assessed by asking: “About how many hours sleep do you get in every 24 hours? (please include naps).” A genetic risk score for AD (AD-GRS) was calculated as a weighted sum of 23 previously identified AD-related single nucleotide polymorphisms in individuals of European ancestry. We evaluated whether AD-GRS predicted sleep duration using linear regression, adjusting for age, sex and principle components for genetic ancestry. We also stratified the analysis by age at baseline (≤55y or >55y) and conducted a MR analysis to estimate the effect of AD (ICD-9/10 codes for AD/dementia diagnosis) on sleep duration. Results The participants (aged 56.91±8.00y) had an average sleep duration of 7.2 (Standard deviation [SD]=1.1) hours and AD-GRS of 0.11 (SD=0.40) (range: -1.15~1.85). Higher AD-GRS score predicted shorter sleep duration (b= -0.013, 95%CI:-0.022,-0.005), mainly among those aged over 55y (b= -0.023, 95%CI:-0.034,-0.012) and not in those 55y or younger (b= 0.006, 95%CI:-0.012,0.013); p for interaction by age=0.02. MR analysis using AD-GRS as an instrumental variable suggested that AD was associated with 1.76 hrs (b=-1.76, -2.62~ -0.90) shorter sleep duration in those aged >55y. Conclusion Using a novel analytical approach, we found that higher genetic risk for AD predicted shorter sleep duration among older adults. This suggests shared genetic pathways; the biologic processes that lead to AD may also affect sleep duration. Support Dr. Leng received support from the National Institute on Aging (NIA) 1K99AG056598, and from GBHI, Alzheimer’s Association, and Alzheimer’s Society (GBHI ALZ UK-19-591141).

Sign in / Sign up

Export Citation Format

Share Document