TY - JOUR
T1 - Integrating MRI Volume and Plasma p-Tau217 for Amyloid Risk Stratification in Early-Stage Alzheimer Disease
AU - K-ROAD study and the Alzheimer’s Disease Neuroimaging Initiative
AU - Yim, Sohyun
AU - Park, Seongbeom
AU - Lim, Kyoungyoon
AU - Kang, Heekyung
AU - Shin, Daeun
AU - Jo, Hyunjin
AU - Jang, Hyemin
AU - Weiner, Michael W.
AU - Zetterberg, Henrik
AU - Blennow, Kaj
AU - Gonzalez-Ortiz, Fernando
AU - Ashton, Nicholas J.
AU - Kang, Sung Hoon
AU - Yun, Jihwan
AU - Chun, Min Young
AU - Kim, Eun Joo
AU - Kim, Hee Jin
AU - Na, Duk L.
AU - Kim, Jun Pyo
AU - Seo, Sang Won
AU - Kwak, Kichang
N1 - Publisher Copyright:
Copyright © 2025 The Author(s).
PY - 2025/9/23
Y1 - 2025/9/23
N2 - Background and Objectives Identifying β-amyloid (Aβ) positivity is crucial for selecting candidates for Aβ-targeted therapies in early-stage Alzheimer disease (AD). While Aβ 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 Aβ positivity without extra expense. We evaluated a 2-stage workflow integrating MRI-based features and plasma p-tau217 to efficiently predict Aβ PET positivity in early-stage AD. Methods This 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 Aβ PET data. A random forest classifier predicting Aβ PET positivity was developed using MRI-based brain atrophy patterns and APOE e4 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. Results A 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). Discussion The 2-stage diagnostic workflow integrating MRI-based risk stratification and plasma p-tau217 testing accurately identified individuals with Aβ 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.
AB - Background and Objectives Identifying β-amyloid (Aβ) positivity is crucial for selecting candidates for Aβ-targeted therapies in early-stage Alzheimer disease (AD). While Aβ 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 Aβ positivity without extra expense. We evaluated a 2-stage workflow integrating MRI-based features and plasma p-tau217 to efficiently predict Aβ PET positivity in early-stage AD. Methods This 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 Aβ PET data. A random forest classifier predicting Aβ PET positivity was developed using MRI-based brain atrophy patterns and APOE e4 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. Results A 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). Discussion The 2-stage diagnostic workflow integrating MRI-based risk stratification and plasma p-tau217 testing accurately identified individuals with Aβ 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.
UR - https://www.scopus.com/pages/publications/105013825071
U2 - 10.1212/WNL.0000000000213954
DO - 10.1212/WNL.0000000000213954
M3 - Article
C2 - 40829110
AN - SCOPUS:105013825071
SN - 0028-3878
VL - 105
JO - Neurology
JF - Neurology
IS - 6
M1 - e213954
ER -