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| 001 | 281816 | ||
| 005 | 20251114102931.0 | ||
| 024 | 7 | _ | |a 10.1002/alz.70812 |2 doi |
| 024 | 7 | _ | |a pmid:41137622 |2 pmid |
| 024 | 7 | _ | |a 1552-5260 |2 ISSN |
| 024 | 7 | _ | |a 1552-5279 |2 ISSN |
| 037 | _ | _ | |a DZNE-2025-01198 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Wisch, Julie K |0 0000-0003-3624-2784 |b 0 |
| 245 | _ | _ | |a Comparison of amyloid chronicity and EYO in autosomal dominant Alzheimer's disease. |
| 260 | _ | _ | |a Hoboken, NJ |c 2025 |b Wiley |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1763031333_32671 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a ARTICLE |2 BibTeX |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 520 | _ | _ | |a 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. |
| 536 | _ | _ | |a 352 - Disease Mechanisms (POF4-352) |0 G:(DE-HGF)POF4-352 |c POF4-352 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: pub.dzne.de |
| 650 | _ | 7 | |a Alzheimer's disease |2 Other |
| 650 | _ | 7 | |a biomarkers |2 Other |
| 650 | _ | 7 | |a genetic causes of Alzheimer's disease |2 Other |
| 650 | _ | 7 | |a numeric methods |2 Other |
| 650 | _ | 7 | |a Biomarkers |2 NLM Chemicals |
| 650 | _ | 7 | |a Amyloid |2 NLM Chemicals |
| 650 | _ | 7 | |a Amyloid beta-Peptides |2 NLM Chemicals |
| 650 | _ | 2 | |a Humans |2 MeSH |
| 650 | _ | 2 | |a Alzheimer Disease: genetics |2 MeSH |
| 650 | _ | 2 | |a Alzheimer Disease: diagnostic imaging |2 MeSH |
| 650 | _ | 2 | |a Alzheimer Disease: pathology |2 MeSH |
| 650 | _ | 2 | |a Alzheimer Disease: metabolism |2 MeSH |
| 650 | _ | 2 | |a Male |2 MeSH |
| 650 | _ | 2 | |a Female |2 MeSH |
| 650 | _ | 2 | |a Positron-Emission Tomography |2 MeSH |
| 650 | _ | 2 | |a Middle Aged |2 MeSH |
| 650 | _ | 2 | |a Age of Onset |2 MeSH |
| 650 | _ | 2 | |a Longitudinal Studies |2 MeSH |
| 650 | _ | 2 | |a Aged |2 MeSH |
| 650 | _ | 2 | |a Biomarkers |2 MeSH |
| 650 | _ | 2 | |a Disease Progression |2 MeSH |
| 650 | _ | 2 | |a Amyloid: metabolism |2 MeSH |
| 650 | _ | 2 | |a Amyloid beta-Peptides: metabolism |2 MeSH |
| 700 | 1 | _ | |a McKay, Nicole S |b 1 |
| 700 | 1 | _ | |a Zammit, Matthew |b 2 |
| 700 | 1 | _ | |a Christian, Bradley T |b 3 |
| 700 | 1 | _ | |a Schultz, Stephanie A |b 4 |
| 700 | 1 | _ | |a Millar, Peter R |b 5 |
| 700 | 1 | _ | |a Ryan, Natalie S |b 6 |
| 700 | 1 | _ | |a Cash, David M |b 7 |
| 700 | 1 | _ | |a Belder, Christopher R S |b 8 |
| 700 | 1 | _ | |a Chrem, Patricio |b 9 |
| 700 | 1 | _ | |a Cruchaga, Carlos |b 10 |
| 700 | 1 | _ | |a Ibanez, Laura |b 11 |
| 700 | 1 | _ | |a Jucker, Mathias |0 P:(DE-2719)2000010 |b 12 |u dzne |
| 700 | 1 | _ | |a Yakushev, Igor |b 13 |
| 700 | 1 | _ | |a Day, Gregory S |b 14 |
| 700 | 1 | _ | |a Murphy, Mei |b 15 |
| 700 | 1 | _ | |a Llibre-Guerra, Jorge |b 16 |
| 700 | 1 | _ | |a Aguillon, David |b 17 |
| 700 | 1 | _ | |a Roh, Jee Hoon |b 18 |
| 700 | 1 | _ | |a Xiong, Chengjie |b 19 |
| 700 | 1 | _ | |a Wang, Guoqiao |b 20 |
| 700 | 1 | _ | |a Li, Yan |b 21 |
| 700 | 1 | _ | |a Schindler, Suzanne E |b 22 |
| 700 | 1 | _ | |a Jack, Cliff |b 23 |
| 700 | 1 | _ | |a McDade, Eric |b 24 |
| 700 | 1 | _ | |a Bateman, Randall J |b 25 |
| 700 | 1 | _ | |a Benzinger, Tammie L S |b 26 |
| 700 | 1 | _ | |a Ances, Beau M |b 27 |
| 700 | 1 | _ | |a Networ, Dominantly Inherited Alzheimer |b 28 |e Collaboration Author |
| 700 | 1 | _ | |a Betthauser, Tobey |b 29 |
| 700 | 1 | _ | |a Gordon, Brian |b 30 |
| 773 | _ | _ | |a 10.1002/alz.70812 |g Vol. 21, no. 10, p. e70812 |0 PERI:(DE-600)2201940-6 |n 10 |p e70812 |t Alzheimer's and dementia |v 21 |y 2025 |x 1552-5260 |
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