Journal Article

DZNE-2025-01198

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Comparison of amyloid chronicity and EYO in autosomal dominant Alzheimer's disease.

Wisch, J. K. ; McKay, N. S. ; Zammit, M. ; Christian, B. T. ; Schultz, S. A. ; Millar, P. R. ; Ryan, N. S. ; Cash, D. M. ; Belder, C. R. S. ; Chrem, P. ; Cruchaga, C. ; Ibanez, L. ; Jucker, M.DZNE* ; Yakushev, I. ; Day, G. S. ; Murphy, M. ; Llibre-Guerra, J. ; Aguillon, D. ; Roh, J. H. ; Xiong, C. ; Wang, G. ; Li, Y. ; Schindler, S. E. ; Jack, C. ; McDade, E. ; Bateman, R. J. ; Benzinger, T. L. S. ; Ances, B. M. ; Networ, D. I. A. (Collaboration Author) ; Betthauser, T. ; Gordon, B.

2025
Wiley Hoboken, NJ

This record in other databases:    

Please use a persistent id in citations: doi:10.1002/alz.70812

Abstract: Preclinical Alzheimer's disease (AD) can be described relative to biomarker positivity onset time.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.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.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.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.

Keyword(s): Humans (MeSH) ; Alzheimer Disease: genetics (MeSH) ; Alzheimer Disease: diagnostic imaging (MeSH) ; Alzheimer Disease: pathology (MeSH) ; Alzheimer Disease: metabolism (MeSH) ; Male (MeSH) ; Female (MeSH) ; Positron-Emission Tomography (MeSH) ; Middle Aged (MeSH) ; Age of Onset (MeSH) ; Longitudinal Studies (MeSH) ; Aged (MeSH) ; Biomarkers (MeSH) ; Disease Progression (MeSH) ; Amyloid: metabolism (MeSH) ; Amyloid beta-Peptides: metabolism (MeSH) ; Alzheimer's disease ; biomarkers ; genetic causes of Alzheimer's disease ; numeric methods ; Biomarkers ; Amyloid ; Amyloid beta-Peptides

---

Contributing Institute(s):

1. Cell Biology of Neurological Diseases (AG Jucker)

Research Program(s):

1. 352 - Disease Mechanisms (POF4-352) (POF4-352)

Appears in the scientific report 2025

---

Database coverage:
; ; ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; DEAL Wiley ; Essential Science Indicators ; IF >= 10 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

---