scholarly journals Donor specific transcriptomic analysis of Alzheimer’s disease associated hypometabolism highlights a unique donor, microglia, and ribosomal proteins

2019 ◽  
Author(s):  
Sejal Patel ◽  
Derek Howard ◽  
Alana Man ◽  
Deborah Schwartz ◽  
Joelle Jee ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebral Cortex ◽  
Glucose Utilization ◽  
Meta Analysis ◽  
Expression Patterns ◽  
Neurofibrillary Tangle ◽  
Brain Atlas ◽  
Angular Gyrus ◽  
Healthy Controls

AbstractAlzheimer’s disease (AD) starts decades before clinical symptoms appear. Low glucose utilization in regions of the cerebral cortex marks early AD and is clinically useful. To identify these regions, we conducted a voxel-wise meta-analysis of positron emission tomography studies that compared AD patients with healthy controls. This meta-analysis included 27 studies that assayed glucose utilization in 915 AD patients and 715 healthy controls. The resulting map marks hypometabolism in the posterior cingulate, middle frontal, angular gyrus, middle and inferior temporal regions. Using the Allen Human Brain Atlas, we identified genes with expression patterns associated with this hypometabolism pattern in the cerebral cortex. Of the six brains in the Atlas, one demonstrated a strong spatial association with the hypometabolism pattern. Previous neuropathological assessment of this brain from a 39-year-old male noted a neurofibrillary tangle in the entorhinal cortex. Using the transcriptomic data, we estimate lower proportions of neurons and more microglia in the hypometabolic regions when compared with the other five brains. Within this single brain, signal recognition particle (SRP)-dependent cotranslational protein targeting genes, which primarily encode cytosolic ribosome proteins, are highly expressed in the hypometabolic regions. Analyses of human and mouse data show that expression of these genes progressively increases across AD-associated states of microglial activation. In addition, genes involved in cell killing, chronic inflammation, ubiquitination, tRNA aminoacylation, and vacuole sorting are associated with the hypometabolism map. These genes suggest disruption of the protein life cycle and neuroimmune activation. Taken together, our molecular characterization of cortical hypometabolism reveals a molecular link to AD associated hypometabolism that may be relevant to preclinical stages.

scholarly journals Alzheimer’s Disease and Risk of Hip Fracture: A Meta-Analysis Study

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Yan Zhao ◽  
Liang Shen ◽  
Hong-Fang Ji
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Hip Fracture ◽  
Strong Predictor ◽  
Meta Analysis ◽  
The Elderly ◽  
Cochrane Library ◽  
Healthy Controls ◽  
Mineral Density ◽  
Hip Bmd

Background. Alzheimer's disease (AD) is the most common cause of dementia in the elderly population. Growing evidence supports that AD patients are at high risk for hip fracture, but the issue remains questionable. The purpose of the present study is to perform a meta-analysis to explore the association between AD and risk of hip fracture. Considering that bone mineral density (BMD) acts as a strong predictor of bone fracture, we also studied the hip BMD in AD patients.Methods. We searched all publications in Medline, SciVerse Scopus, and Cochrane Library published up to January 2012 about the association between AD and hip fracture or hip BMD.Results. There are 9 studies included in the meta-analysis. The results indicate that AD patients are at higher risk for hip fracture (OR and 95% CI fixed: ES = 2.58, 95% CI = [2.03, 3.14]; dichotomous data: summary OR = 1.80, 95% CI = [1.54, 2.11]) than healthy controls. Further meta-analysis showed that AD patients have a lower hip BMD (summary SMD = −1.12, 95% CI = [−1.34, −0.90]) than healthy controls.Conclusions. It was found that in comparison with healthy controls AD patients are at higher risk for hip fracture and have lower hip BMD.

scholarly journals Alzheimer’s disease clinical variants show distinct regional patterns of neurofibrillary tangle accumulation

2019 ◽  
Author(s):  
Cathrine Petersen ◽  
Amber L Nolan ◽  
Elisa de Paula França Resende ◽  
Alexander Ehrenberg ◽  
Salvatore Spina ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Hierarchical Clustering ◽  
Primary Motor Cortex ◽  
Regional Distribution ◽  
Neurofibrillary Tangle ◽  
Angular Gyrus ◽  
Braak Stage ◽  
Regional Patterns ◽  
Braak Staging

ABSTRACTBackgroundNeurofibrillary tangle (NFT) pathology in Alzheimer’s disease (AD) follows a stereotypic progression well-characterized by Braak staging. However, some AD cases show deviations from the Braak staging scheme. In this study, we tested the hypothesis that these variations in the regional distribution of tau pathology are linked to heterogeneity in the clinical phenotypes of AD.MethodsWe included a clinicopathological cohort of ninety-four AD cases enriched for atypical clinical presentations. Subjects underwent apolipoprotein E (APOE) genotyping and neuropsychological testing. Main cognitive domains (executive, visuospatial, language, and memory function) were assessed using an established composite z-score. We assessed NFT density and distribution from thioflavin S fluorescent microscopy throughout four neocortical and two hippocampal regions. A mathematical algorithm classifying AD cases into typical, hippocampal sparing (HpSp), and limbic predominant (LP) subtypes based on regional NFT burden was compared to unbiased hierarchical clustering for cases with Braak stage > IV.ResultsPatients diagnosed with logopenic primary progressive aphasia showed significantly higher NFT density in the superior temporal gyrus relative to patients diagnosed with Alzheimer-type dementia (p = 0.0091), while patients with corticobasal syndrome showed significantly higher NFT density in the primary motor cortex (p = 0.0205). Hierarchical clustering identified three discrete clusters of patients characterized respectively by low overall NFT burden (n = 18), high overall burden (n = 30), and cortical-predominant burden (n = 24). A regionally specific effect was observed for visuospatial ability; higher NFT density in the angular gyrus (β = - 0.0921, p = 0.0099) and in the CA1 sector of the hippocampus (β = −0.0735, p = 0.0380) was significantly associated with more severe visuospatial dysfunction, modulated by age of death.ConclusionsOur results suggest domain-specific functional consequences of regional NFT accumulation. In particular, we observed focal aggregation of NFT density in clinically relevant regions among different clinical AD variants. Continued work to map the regionally specific clinical consequences of tau accumulation presents an opportunity to increase understanding of disease mechanisms underlying atypical clinical manifestations.

scholarly journals A multipredictor model to predict the conversion of mild cognitive impairment to Alzheimer’s disease by using a predictive nomogram

2019 ◽  
Vol 45 (2) ◽  
pp. 358-366 ◽  
Author(s):  
Kexin Huang ◽  
◽  
Yanyan Lin ◽  
Lifeng Yang ◽  
Yubo Wang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebral Cortex ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Structural Changes ◽  
Expression Patterns ◽  
Image Features ◽  
Predictive Tool ◽  
Clinical Factor

Abstract Predicting the probability of converting from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) is still a challenging task. This study aims at providing a personalized MCI-to-AD conversion estimation by using a multipredictor nomogram that integrates neuroimaging features, cerebrospinal fluid (CSF) biomarker, and clinical assessments. To do so, 290 MCI patients were collected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), of whom 76 has converted to AD and 214 remained with MCI. All subjects were randomly divided into a primary and validation cohort. Radiomics signature (Rad-sig) was obtained based on 17 cerebral cortex features selected by using Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Clinical factors and amyloid-beta peptide (Aβ) concentration were selected by using Spearman correlation between the converted and not-converted patients. Then, a nomogram that combines image features, clinical factor, and Aβ concentration was constructed and validated. Furthermore, we explored the associations between various predictors from the macro- to the microperspective by assessing gene expression patterns. Our results showed that the multipredictor nomogram (C-index 0.978 and 0.956 in both cohorts, respectively) outperformed the nomogram using either Rad-sig or Aβ concentration as individual predictors. Significant associations were found between neuropsychological scores, cerebral cortex features, Aβ levels, and underlying gene pathways. Our study may have a clinical impact as a powerful predictive tool for predicting the conversion probability of MCI and providing associations between cognitive impairment, structural changes, Aβ levels, and underlying biological patterns from the macro- to the microperspective.

scholarly journals Data-Driven Analysis of Age, Sex, and Tissue Effects on Gene Expression Variability in Alzheimer’s Disease

2018 ◽  
Author(s):  
Lavida R.K. Brooks ◽  
George I. Mias
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Meta Analysis ◽  
Tissue Type ◽  
Healthy Controls ◽  
Expression Data ◽  
Mitochondrial Translation ◽  
Microarray Expression Data ◽  
Microarray Expression

ABSTRACTAlzheimer’s disease (AD) has been categorized by the Centers for Disease Control and Prevention (CDC) as the 6thleading cause of death in the United States. AD is a significant health-care burden because of its increased occurrence (specifically in the elderly population) and the lack of effective treatments and preventive methods. With an increase in life expectancy, the CDC expects AD cases to rise to 15 million by 2060. Aging has been previously associated with susceptibility to AD, and there are ongoing efforts to effectively differentiate between normal and AD age-related brain degeneration and memory loss. AD targets neuronal function and can cause neuronal loss due to the buildup of amyloid-beta plaques and intracellular neurofibrillary tangles.Our study aims to identify temporal changes within gene expression profiles of healthy controls and AD subjects. We conducted a meta-analysis using publicly available microarray expression data from AD and healthy cohorts. For our meta-analysis, we selected datasets that reported donor age and gender, and used Affymetrix and Illumina microarray platforms (8 datasets, 2,088 samples). Raw microarray expression data were re-analyzed, and normalized across arrays. We then performed an analysis of variance, using a linear model that incorporated age, tissue type, sex, and disease state as effects, as well as study to account for batch effects, and including binary interaction between factors. Our results identified 3,735 statistically significant (Bonferroni adjusted p<0.05) gene expression differences between AD and healthy controls, which we filtered for biological effect (10% two-tailed quantiles of mean differences between groups) to obtain 352 genes. Interesting pathways identified as enriched comprised of neurodegenerative diseases pathways (including AD), and also mitochondrial translation and dysfunction, synaptic vesicle cycle and GABAergic synapse, and gene ontology terms enrichment in neuronal system, transmission across chemical synapses and mitochondrial translation.Overall our approach allowed us to effectively combine multiple available microarray datasets and identify gene expression differences between AD and healthy individuals including full age and tissue type considerations. Our findings provide potential gene and pathway associations that can be targeted to improve AD diagnostics and potentially treatment or prevention. (US).

scholarly journals Decreased Serum Brain-Derived Neurotrophic Factor (BDNF) Levels in Patients with Alzheimer’s Disease (AD): A Systematic Review and Meta-Analysis

2019 ◽  
Vol 20 (2) ◽  
pp. 257 ◽  
Author(s):  
Ted Ng ◽  
Cyrus Ho ◽  
Wilson Tam ◽  
Ee Kua ◽  
Roger Ho
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurotrophic Factor ◽  
Molecular Mechanisms ◽  
Meta Analysis ◽  
Brain Derived Neurotrophic Factor ◽  
Significant Heterogeneity ◽  
Healthy Controls ◽  
Healthy Control ◽  
Serum Bdnf

Findings from previous studies reporting the levels of serum brain-derived neurotrophic factor (BDNF) in patients with Alzheimer’s disease (AD) and individuals with mild cognitive impairment (MCI) have been conflicting. Hence, we performed a meta-analysis to examine the aggregate levels of serum BDNF in patients with AD and individuals with MCI, in comparison with healthy controls. Fifteen studies were included for the comparison between AD and healthy control (HC) (n = 2067). Serum BDNF levels were significantly lower in patients with AD (SMD: −0.282; 95% confidence interval [CI]: −0.535 to −0.028; significant heterogeneity: I2 = 83.962). Meta-regression identified age (p < 0.001) and MMSE scores (p < 0.001) to be the significant moderators that could explain the heterogeneity in findings in these studies. Additionally, there were no significant differences in serum BDNF levels between patients with AD and MCI (eight studies, n = 906) and between MCI and HC (nine studies, n = 5090). In all, patients with AD, but not MCI, have significantly lower serum BDNF levels compared to healthy controls. This meta-analysis confirmed the direction of change in serum BDNF levels in dementia. This finding suggests that a significant change in peripheral BDNF levels can only be detected at the late stage of the dementia spectrum. Molecular mechanisms, implications on interventional trials, and future directions for studies examining BDNF in dementia were discussed.

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