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Related Concept Videos

Alzheimer Disease l: Introduction01:29

Alzheimer Disease l: Introduction

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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...
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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...
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Dementia l: Introduction01:22

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Dementia is an acquired, progressive syndrome characterized by a decline in multiple cognitive domains severe enough to impair daily functioning and reduce independence. Although memory loss is a central feature, the diagnosis requires additional deficits involving language, executive function, visuospatial skills, judgment, calculation, or abstract reasoning. These cognitive impairments reflect underlying neurodegenerative or vascular processes that gradually disrupt neuronal networks...
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Alzheimer Disease ll: Pathophysiology01:23

Alzheimer Disease ll: Pathophysiology

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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...
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Alzheimer's Disease: Treatment01:22

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Alzheimer's Disease (AD), a neurodegenerative disorder, is pathologically identified by amyloid plaques and neurofibrillary tangles composed of tau protein. AD pharmacotherapy aims to manage cognitive symptoms, delay disease progression, and treat behavioral symptoms. The treatment is primarily symptomatic and palliative, with no definitive disease-modifying therapy available. Cholinesterase inhibitors, including donepezil (Aricept), rivastigmine (Exelon), and galantamine (Razadyne), are...
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Dementia01:30

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Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
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Updated: May 2, 2026

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
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Identifying Alzheimer's Disease Progression Subphenotypes Via a Graph-based Framework Using Electronic Health

Yu Huang1,2, Jie Xu3, Zhengkang Fan3

  • 1Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN 46202, USA.

Journal of Healthcare Informatics Research
|May 1, 2026
PubMed
Summary
This summary is machine-generated.

Alzheimer's disease (AD) progression varies significantly between individuals. This study identified four distinct subphenotypes of AD progression from mild cognitive impairment (MCI) to AD, offering new insights for personalized patient care.

Keywords:
Alzheimer’s diseaseDisease progression subphenotypingElectronic health recordsGraph neural networkReal-world data

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Area of Science:

  • Neuroscience
  • Medical Informatics
  • Computational Biology

Background:

  • Alzheimer's disease (AD) neurodegeneration exhibits significant heterogeneity.
  • Identifying distinct disease progression pathways is crucial for effective diagnosis, treatment, and prevention strategies.
  • Current understanding often overlooks the diverse trajectories of cognitive decline.

Purpose of the Study:

  • To identify and characterize distinct Alzheimer's disease (AD) progression subphenotypes.
  • To analyze progression pathways from mild cognitive impairment (MCI) to AD using real-world data.
  • To develop a novel computational framework for delineating neurodegenerative subphenotypes.

Main Methods:

  • Development of a novel framework combining graph neural networks (GNNs) and time series clustering.
  • Application of the framework to a large cohort of 2,525 patients with MCI and AD from electronic health records (EHRs).
  • Analysis of clinical patterns and progression times associated with identified subphenotypes.

Main Results:

  • Identification of four distinct MCI-to-AD progression subphenotypes.
  • Characterization of unique clinical patterns within each subphenotype.
  • Quantification of average MCI-to-AD progression times, ranging from 805 to 1,236 days, highlighting significant variability.

Conclusions:

  • Alzheimer's disease (AD) progression is not uniform but follows heterogeneous pathways.
  • The proposed GNN-based framework offers an explainable, data-driven method for subphenotyping AD progression.
  • Findings provide actionable insights for healthcare informatics and personalized clinical management of AD patients.