Early-onset Alzheimer's Disease Phenotypes: Neuropsychology and Neural Networks

• Conditions: Logopenic Progressive Aphasia; Corticobasal Degeneration; Ideomotor Apraxia; Alzheimer Disease; Alzheimer Disease, Late Onset; Dementia, Alzheimer Type; Visuospatial/Perceptual Abilities; Posterior Cortical Atrophy; Primary Progressive Aphasia; Alzheimer Disease, Early Onset

• Registration Number: NCT03153371
• Lead Sponsor: University of California, Los Angeles

Brief Summary

This study attempts to identify two types of AD by using clinical and cognitive tasks and brain imaging. The subtypes of AD are separated into a "typical" group (memory loss) and a "variant" group (language, visuospatial, and other cognitive difficulties). Performance on the clinical tasks and brain imaging will be compared among the young-onset Alzheimer's disease group, a late-onset Alzheimer's disease group, and a control group.

Detailed Description

Unlike the usual late-onset Alzheimer's disease (LOAD), early-onset AD (EOAD), with onset before age 65, includes a high percentage of phenotypic variants. These non-familial, variants (vEOAD) present, not with progressive memory loss, but with language, visuospatial, or other cognitive difficulties. AD is now understood as a disorder that manifests with disturbed cognition reflecting disturbed neural networks. A multivariate analysis of neuropsychological tests, the "gold standard" for objectively defining neurocognitive impairments, coupled with structural and functional neuroimaging analysis of connectomes, can identify the neurocognitive-neural network profiles of vEOAD patients, compared to those with typical AD. This knowledge can increase our understanding of the heterogeneity of AD and how it causes disease.

This study hopes to show that vEOAD constitutes a "Type 2 AD", by (1) defining the neuropsychological components of Type 2 AD, and (2) understanding the anatomy and atrophy of the brains of vEOAD patients. Together, these components can outline the neurocognitive-neural network profile of Type 2 AD.

In addition to information that can help in the diagnosis and management of EOAD, this study can stimulate novel research into the reasons for this neurobiological heterogeneity in AD and could potentially lead to interventions based on alternate neurocognitive-neural network profiles.

Study Timeline

• Study Start: 2016-04-04
• Study First Submitted: 2017-04-27
• Study First Submitted QC: 2017-05-11
• Study First Posted: 2017-05-15
• Status Verified: 2020-04
• Last Update Submitted: 2020-04-25
• Last Update Posted: 2020-04-28
• Primary Completion: 2021-03-31
• Study Completion: 2022-03-31

Recruitment & Eligibility

• Status: UNKNOWN
• Sex: All
• Target Recruitment: 180

Inclusion Criteria

Not provided

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Exclusion Criteria

Not provided

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Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Alzheimer's disease Subtype	Performed at baseline	Neuropsychological testing results for use in a two-stage multivariate diagnostic method that combines the (weighted) test results in order to best discriminate Type 2 AD and typical AD.

Secondary Outcome Measures

Name	Time	Method
Brain atrophy in MRI - Magnetic Resonance Imaging of the brain	Performed at baseline visit	Images from initial MRI scan taken at baseline visit will be analyzed for atrophy and white matter tract integrity
Change in overall Neurological profile	Performed at baseline and 1-year follow-up visit	Change in performance on neurological tasks between baseline visit and follow-up visit.
Change in overall Neuropsychological profile	Performed at baseline and 1-year follow-up visit	Change in neuropsychological performance over time.

Trial Locations

Locations (1)

UCLA Department of Neurology; 🇺🇸 Los Angeles, California, United States