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
Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
BeauBrain Healthcare, Inc., Seoul, South Korea.
Neurology. 2025 Sep 23;105(6):e213954. doi: 10.1212/WNL.0000000000213954. Epub 2025 Aug 19.
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.
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 ε4 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.
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).
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.
识别β-淀粉样蛋白(Aβ)阳性对于选择早期阿尔茨海默病(AD)中Aβ靶向治疗的候选者至关重要。虽然Aβ正电子发射断层扫描(PET)准确,但成本高昂限制了其常规使用。血浆磷酸化tau217(p-tau217)检测提供了一种侵入性较小的选择,但也会产生额外费用。常用于认知评估的结构性脑磁共振成像(MRI)可以识别预测Aβ阳性的特征,且无需额外费用。我们评估了一种两阶段工作流程,该流程整合基于MRI的特征和血浆p-tau217,以有效预测早期AD中的Aβ PET阳性。
这项前瞻性队列研究纳入了来自韩国克服痴呆症和加速痴呆症研究注册库(K-ROAD;韩国)和阿尔茨海默病神经成像计划(ADNI;美国)队列的轻度认知障碍(MCI)或早期阿尔茨海默型痴呆(ATD)参与者。符合条件的参与者临床痴呆评定量表评分为0.5,同时拥有MRI、血浆p-tau217和Aβ PET数据。使用基于MRI的脑萎缩模式和载脂蛋白E(APOE)ε4状态开发了一种预测Aβ PET阳性的随机森林分类器。参与者被分为低风险、中风险和高风险组;仅对中风险个体进行血浆p-tau217检测。结果包括阳性预测值(PPV)、阴性预测值(NPV)和总体准确率。
共分析了807名K-ROAD参与者(中位年龄72.0岁,58.7%为女性)和230名ADNI参与者(中位年龄70.9岁,49.1%为女性)。采用95%灵敏度/特异度策略时,低风险组的NPV在K-ROAD队列中为94.7%(91.7%-97.7%),在ADNI队列中为99.0%(97.0%-100.0%)。高风险组的PPV在K-ROAD队列中为97.6%(95.9%-99.3%),在ADNI队列中为98.8%(96.5%-100.0%)。中风险组在K-ROAD队列中占参与者的33.3%,在ADNI队列中占20.9%。对中风险组进行血浆p-tau217检测,PPV在K-ROAD队列中为92.5%(88.7%-96.3%),在ADNI队列中为90.0%(79.0%-100.0%);NPV在K-ROAD队列中为83.1%(75.0%-91.2%),在ADNI队列中为83.3%(66.1%-100.0%)。总体工作流程准确率在K-ROAD队列中为94.2%(92.6%-95.8%),在ADNI队列中为96.5%(94.1%-98.9%)。
整合基于MRI的风险分层和血浆p-tau217检测的两阶段诊断工作流程准确识别了早期AD中Aβ PET阳性的个体,大幅减少了对额外生物标志物检测的需求。然而,与基线模型相比,适度的增量改善以及有限的种族和民族多样性可能会限制其可推广性。