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Using subjective cognitive decline to identify high global amyloid in community-based samples: A cross-cohort study
Rachel F Buckley1,2,3,4, Sietske Sikkes5,6, Victor L Villemagne7,8
1The Florey Institute, The University of Melbourne, Melbourne, Victoria, Australia.
Subjective cognitive decline (SCD) aids in identifying individuals with high beta-amyloid (Aβ) levels, reducing the need for positron emission tomography scans in clinical trials for Alzheimer's disease research.
Area of Science:
- Neuroscience
- Clinical Trials
- Biomarkers
Background:
- Alzheimer's disease (AD) clinical trials require efficient recruitment of individuals with specific biomarkers.
- Beta-amyloid (Aβ) positivity is a key criterion for enrolling participants in many AD trials.
- Subjective cognitive decline (SCD) is being investigated as a potential early indicator of AD pathology.
Purpose of the Study:
- To evaluate the effectiveness of subjective cognitive decline (SCD) in identifying individuals with elevated beta-amyloid (Aβ) levels.
- To determine if SCD can reduce the number of Aβ positron emission tomography (PET) scans needed for clinical trial recruitment.
- To assess the impact of SCD, apolipoprotein E (APOE) genotype, and sex on Aβ positivity.
Main Methods:
- Analysis of three independent cohorts comprising 890 clinically normal individuals.
- Dichotomization of SCD status from a single question.
- Logistic regression modeling to classify Aβ positivity based on SCD, APOE ε4 status, sex, and age.
Main Results:
- SCD was associated with a 1.58-fold increased odds of being Aβ+ compared to non-SCD.
- Female APOE ε4 carriers with SCD showed significantly higher odds of Aβ+ (OR=3.34).
- Incorporating SCD reduced Aβ PET scan requirements by 13% (9% if APOE ε4 status was known).
Conclusions:
- Subjective cognitive decline (SCD) is a valuable tool for classifying individuals with high Aβ burden, independent of APOE genotype.
- Collecting SCD information is a practical strategy for targeting recruitment in AD clinical trials.
- SCD may help identify individuals on an early Alzheimer's disease trajectory.
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