Abstract

INTRODUCTION: Preclinical Alzheimer's disease (AD) can be described relative to biomarker positivity onset time. METHODS: We estimated time from amyloid positivity (A+) using sampled iterative local approximation (SILA) in a longitudinal autosomal dominant AD (ADAD) sample (N = 379) with amyloid positron emission tomography. We compared (1) predicted age at A+ to imputed age, (2) estimated age at A+ to estimated age at symptom onset, and (3) variance in cognitive performance explained. RESULTS: Mean error between imputed and SILA-estimated age at A+ (N = 26) was 1.15 years. Age at A+ explained 39% of estimated years to symptom onset (EYO) variance. Time from A+ explained 19% of cognitive composite variance and 14% of Clinical Dementia Rating Sum of Boxes CDR-SB variance; EYO explained 43% and 57%, respectively. DISCUSSION: SILA estimates A+ age in ADAD with reasonably good accuracy. SILA-estimated time from A+ describes the start of pathology, but the time from A+ onset to symptoms is variable in ADAD and better described by EYO. Highlights: Amyloid chronicity predicts a 14-year preclinical AD phase in ADAD. SILA accurately estimates age at A+ (MAE < 2 years). EYO outperforms chronicity in predicting symptom onset. APP mutation carriers show atypical amyloid accumulation. Chronicity models help reveal AD heterogeneity in preclinical stages.

Original languageEnglish
Article numbere70812
JournalAlzheimer's and Dementia
Volume21
Issue number10
DOIs
StatePublished - Oct 2025

Keywords

  • Alzheimer's disease
  • biomarkers
  • genetic causes of Alzheimer's disease
  • numeric methods

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