Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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...
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...
Human Genetics01:28

Human Genetics

Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
Dementia l: Introduction01:22

Dementia l: Introduction

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...
Alzheimer's Disease: Treatment01:22

Alzheimer's Disease: Treatment

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Undiagnosed dementia and mortality among older adults in the United States and Brazil: A cross-national cohort study.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same author

Frequent in dementia, deadliest without it: delirium and mortality in hospitalised older adults.

Age and ageing·2026
Same author

Patterns of Daily Administration of Psychoactive Drug Classes for Distress Behavior in Dementia.

Journal of the American Medical Directors Association·2026
Same author

Using Natural Language Processing to Improve Fall Documentation in VA Nursing Home Residents.

Journal of the American Medical Directors Association·2026
Same author

An Updated Mortality and Community Discharge Prognostic Model for Older Adults Admitted to Skilled Nursing Facilities for Post-Acute Care.

Journal of the American Medical Directors Association·2026
Same author

Geriatric Syndromes and Mortality Among Hospitalized Older Adults.

JAMA network open·2026

Related Experiment Video

Updated: May 27, 2026

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
09:38

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Predicting Alzheimer's risk: why and how?

Deborah E Barnes1, Sei J Lee

  • 1Department of Psychiatry, University of California at San Francisco, San Francisco, CA, USA. deborah.barnes@ucsf.edu.

Alzheimer'S Research & Therapy
|December 1, 2011
PubMed
Summary

Predicting Alzheimer's disease (AD) risk requires models that account for mortality and the full preclinical period. Current strategies lack accuracy by not differentiating AD progression from other causes of death.

Area of Science:

  • Neurology
  • Gerontology
  • Biostatistics

Background:

  • Alzheimer's disease (AD) pathology begins 10-20 years before symptom onset, driving interest in early risk prediction.
  • Current AD risk prediction strategies use biomarkers, neuroimaging, and risk factors but have moderate accuracy.
  • Existing models fail to incorporate mortality, hindering differentiation between AD development and death from other causes.

Discussion:

  • Accurate AD risk prediction is crucial for targeted preventive treatments, maximizing benefits and minimizing harms.
  • A key limitation of current strategies is the lack of simultaneous modeling of AD risk and mortality.
  • The full preclinical period (10-20 years) and a comprehensive range of predictive variables remain underexplored.

Key Insights:

More Related Videos

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

Quantitative 3D In Silico Modeling (q3DISM) of Cerebral Amyloid-beta Phagocytosis in Rodent Models of Alzheimer's Disease
09:33

Quantitative 3D In Silico Modeling (q3DISM) of Cerebral Amyloid-beta Phagocytosis in Rodent Models of Alzheimer's Disease

Published on: December 26, 2016

Related Experiment Videos

Last Updated: May 27, 2026

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
09:38

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

Quantitative 3D In Silico Modeling (q3DISM) of Cerebral Amyloid-beta Phagocytosis in Rodent Models of Alzheimer's Disease
09:33

Quantitative 3D In Silico Modeling (q3DISM) of Cerebral Amyloid-beta Phagocytosis in Rodent Models of Alzheimer's Disease

Published on: December 26, 2016

  • Developing AD risk prediction models that explicitly account for mortality is essential.
  • Integrating diverse data sources (biomarkers, imaging, risk factors) over the entire preclinical phase is necessary.
  • Sophisticated modeling techniques, like hidden Markov models, can combine multi-cohort data for improved prediction.

    • Outlook:

    • Future AD risk prediction algorithms must simultaneously model AD and mortality risks across the preclinical spectrum.
    • Consideration of potential harms and benefits is critical when identifying and treating high-risk individuals.
    • Advancements in predictive modeling are needed to refine prognostic accuracy for Alzheimer's disease.