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Related Concept Videos

Alzheimer Disease ll: Pathophysiology01:23

Alzheimer Disease ll: Pathophysiology

Alzheimer disease involves structural changes in the brain that begin long before symptoms appear. The most distinctive features are extracellular neuritic plaques and intracellular neurofibrillary tangles.Neuritic plaques form in the cerebral cortex and around blood vessels. These plaques contain a dense core of beta-amyloid (Aβ)—a toxic protein fragment that clumps outside neurons. The core is surrounded by damaged neuronal extensions, as well as reactive astrocytes and microglia. Abnormal...
Alzheimer Disease l: Introduction01:29

Alzheimer Disease l: Introduction

Alzheimer disease is a chronic, progressive, and irreversible neurodegenerative disorder and the most common cause of dementia in older adults. It leads to gradual neuronal loss, causing cognitive decline, behavioral changes, and loss of functional independence.Risk Factors and EtiologyThe disease is multifactorial. Age is the strongest risk factor, with prevalence doubling every 5 years after age 65. Genetic factors include mutations in genes such as APP, PSEN1, and PSEN2, which are associated...
Alzheimer's Disease: Overview01:26

Alzheimer's Disease: Overview

Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ and tau...

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Biomarker Identification for Gender Specificity of Alzheimer's Disease Based on the Glial Transcriptome Profiles
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Latent Factor Modeling Reveals Unexpected Spatial Heterogeneity in Human Alzheimer's Disease Brain Transcriptomes.

Rami Al-Ouran1,2,3, Chaozhong Liu2,3, Linhua Wang2,3

  • 1Department of Data Science and Artificial Intelligence, Al Hussein Technical University, Amman, Jordan.

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Alzheimer's disease (AD) exhibits complex heterogeneity. Latent factor modeling of AD brain RNA revealed distinct transcriptional groups, improving biomarker discovery by accounting for spatial variation.

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Published on: November 14, 2017

Area of Science:

  • Neuroscience
  • Genomics
  • Computational Biology

Background:

  • Alzheimer's disease (AD) presents significant molecular and cellular heterogeneity.
  • This complexity hinders the identification of reliable biomarkers and therapeutic targets for AD.

Purpose of the Study:

  • To characterize the transcriptional heterogeneity in Alzheimer's disease (AD) brain samples.
  • To identify underlying gene expression patterns and their relationship to disease characteristics.
  • To assess the impact of spatial variation on transcriptomic analysis in AD.

Main Methods:

  • Latent factor modeling applied to RNA sequencing data from approximately 2,500 human AD brain samples.
  • Analysis of gene expression profiles within identified transcriptional groups.
  • Evaluation of the effect of adjusting for a latent factor representing spatial variation on differential gene expression analysis.

Main Results:

  • Uncovered distinct transcriptional groups with unique gene expression profiles.
  • Identified associations with synaptic, neuronal, vascular, and protein processing pathways.
  • Demonstrated that the latent factor reflects spatial sampling variation.
  • Adjusting for the latent factor improved the identification of differentially expressed genes in AD samples.

Conclusions:

  • Spatial heterogeneity is a critical factor influencing transcriptomic variation in Alzheimer's disease (AD) brain.
  • Accounting for spatial variation enhances the discovery of disease-relevant gene expression changes.
  • Findings have significant implications for future research in AD and other neurological disorders.