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Integrating MRI Volume and Plasma p-Tau217 for Amyloid Risk Stratification in Early-Stage Alzheimer Disease

Authors
 Yim, Sohyun  ;  Park, Seongbeom  ;  Lim, Kyoungyoon  ;  Kang, Heekyung  ;  Shin, Daeun  ;  Jo, Hyunjin  ;  Jang, Hyemin  ;  Weiner, Michael W.  ;  Zetterberg, Henrik  ;  Blennow, Kaj  ;  Gonzalez-Ortiz, Fernando  ;  Ashton, Nicholas J.  ;  Kang, Sung Hoon  ;  Yun, Jihwan  ;  Chun, Min Young  ;  Kim, Eun-Joo  ;  Kim, Hee Jin  ;  Na, Duk L.  ;  Kim, Jun Pyo  ;  Seo, Sang Won  ;  Kwak, Kichang 
Citation
 NEUROLOGY, Vol.105(6), 2025-09 
Article Number
 e213954 
Journal Title
NEUROLOGY
ISSN
 0028-3878 
Issue Date
2025-09
MeSH
Aged ; Aged, 80 and over ; Alzheimer Disease* / blood ; Alzheimer Disease* / diagnostic imaging ; Alzheimer Disease* / pathology ; Amyloid beta-Peptides* / metabolism ; Biomarkers / blood ; Brain* / diagnostic imaging ; Brain* / metabolism ; Brain* / pathology ; Cognitive Dysfunction / blood ; Cognitive Dysfunction / diagnostic imaging ; Cohort Studies ; Female ; Humans ; Magnetic Resonance Imaging* / methods ; Male ; Middle Aged ; Positron-Emission Tomography ; Prospective Studies ; Risk Assessment ; tau Proteins* / blood
Abstract
Background and ObjectivesIdentifying beta-amyloid (A beta) positivity is crucial for selecting candidates for A beta-targeted therapies in early-stage Alzheimer disease (AD). While A beta PET is accurate, its high cost limits routine use. Plasma p-tau217 testing offers a less invasive option but also incurs additional costs. Structural brain MRI, routinely used in cognitive assessments, can identify features predictive of A beta positivity without extra expense. We evaluated a 2-stage workflow integrating MRI-based features and plasma p-tau217 to efficiently predict A beta PET positivity in early-stage AD.MethodsThis prospective cohort study included participants with mild cognitive impairment (MCI) or early Alzheimer-type dementia (ATD) from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research (K-ROAD; Korea) and Alzheimer's Disease Neuroimaging Initiative (ADNI; US) cohorts. Eligible participants had a Clinical Dementia Rating score of 0.5, along with MRI, plasma p-tau217, and A beta PET data. A random forest classifier predicting A beta PET positivity was developed using MRI-based brain atrophy patterns and APOE epsilon 4 status. Participants were stratified into low-risk, intermediate-risk, and high-risk groups; plasma p-tau217 testing was performed only in intermediate-risk individuals. Outcomes included positive predictive value (PPV), negative predictive value (NPV), and overall accuracy.ResultsA total of 807 K-ROAD participants (median age 72.0 years, 58.7% female) and 230 ADNI participants (median age 70.9 years, 49.1% female) were analyzed. Using a 95% sensitivity/specificity strategy, the low-risk group demonstrated NPVs of 94.7% (91.7%-97.7%, K-ROAD) and 99.0% (97.0%-100.0%, ADNI). The high-risk group showed PPVs of 97.6% (95.9%-99.3%, K-ROAD) and 98.8% (96.5%-100.0%, ADNI). Intermediate-risk groups comprised 33.3% (K-ROAD) and 20.9% (ADNI) of participants. Plasma p-tau217 testing in intermediate-risk groups yielded PPVs of 92.5% (88.7%-96.3%, K-ROAD) and 90.0% (79.0%-100.0%, ADNI) and NPVs of 83.1% (75.0%-91.2%, K-ROAD) and 83.3% (66.1%-100.0%, ADNI). The overall workflow accuracy was 94.2% (92.6%-95.8%, K-ROAD) and 96.5% (94.1%-98.9%, ADNI).DiscussionThe 2-stage diagnostic workflow integrating MRI-based risk stratification and plasma p-tau217 testing accurately identified individuals with A beta PET positivity in early-stage AD, substantially reducing the need for additional biomarker testing. However, the generalizability may be limited by modest incremental improvement over baseline models and limited racial and ethnic diversity.
Files in This Item:
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DOI
10.1212/WNL.0000000000213954
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers
Yonsei Authors
Chun, Min Young(전민영) ORCID logo https://orcid.org/0000-0003-3731-6132
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/207618
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