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

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dc.contributor.authorYim, Sohyun-
dc.contributor.authorPark, Seongbeom-
dc.contributor.authorLim, Kyoungyoon-
dc.contributor.authorKang, Heekyung-
dc.contributor.authorShin, Daeun-
dc.contributor.authorJo, Hyunjin-
dc.contributor.authorJang, Hyemin-
dc.contributor.authorWeiner, Michael W.-
dc.contributor.authorZetterberg, Henrik-
dc.contributor.authorBlennow, Kaj-
dc.contributor.authorGonzalez-Ortiz, Fernando-
dc.contributor.authorAshton, Nicholas J.-
dc.contributor.authorKang, Sung Hoon-
dc.contributor.authorYun, Jihwan-
dc.contributor.authorChun, Min Young-
dc.contributor.authorKim, Eun-Joo-
dc.contributor.authorKim, Hee Jin-
dc.contributor.authorNa, Duk L.-
dc.contributor.authorKim, Jun Pyo-
dc.contributor.authorSeo, Sang Won-
dc.contributor.authorKwak, Kichang-
dc.date.accessioned2025-10-17T08:00:49Z-
dc.date.available2025-10-17T08:00:49Z-
dc.date.created2025-10-30-
dc.date.issued2025-09-
dc.identifier.issn0028-3878-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/207618-
dc.description.abstractBackground 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.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherLippincott Williams & Wilkins-
dc.relation.isPartOfNEUROLOGY-
dc.relation.isPartOfNEUROLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAged-
dc.subject.MESHAged, 80 and over-
dc.subject.MESHAlzheimer Disease* / blood-
dc.subject.MESHAlzheimer Disease* / diagnostic imaging-
dc.subject.MESHAlzheimer Disease* / pathology-
dc.subject.MESHAmyloid beta-Peptides* / metabolism-
dc.subject.MESHBiomarkers / blood-
dc.subject.MESHBrain* / diagnostic imaging-
dc.subject.MESHBrain* / metabolism-
dc.subject.MESHBrain* / pathology-
dc.subject.MESHCognitive Dysfunction / blood-
dc.subject.MESHCognitive Dysfunction / diagnostic imaging-
dc.subject.MESHCohort Studies-
dc.subject.MESHFemale-
dc.subject.MESHHumans-
dc.subject.MESHMagnetic Resonance Imaging* / methods-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHPositron-Emission Tomography-
dc.subject.MESHProspective Studies-
dc.subject.MESHRisk Assessment-
dc.subject.MESHtau Proteins* / blood-
dc.titleIntegrating MRI Volume and Plasma p-Tau217 for Amyloid Risk Stratification in Early-Stage Alzheimer Disease-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Neurology (신경과학교실)-
dc.contributor.googleauthorYim, Sohyun-
dc.contributor.googleauthorPark, Seongbeom-
dc.contributor.googleauthorLim, Kyoungyoon-
dc.contributor.googleauthorKang, Heekyung-
dc.contributor.googleauthorShin, Daeun-
dc.contributor.googleauthorJo, Hyunjin-
dc.contributor.googleauthorJang, Hyemin-
dc.contributor.googleauthorWeiner, Michael W.-
dc.contributor.googleauthorZetterberg, Henrik-
dc.contributor.googleauthorBlennow, Kaj-
dc.contributor.googleauthorGonzalez-Ortiz, Fernando-
dc.contributor.googleauthorAshton, Nicholas J.-
dc.contributor.googleauthorKang, Sung Hoon-
dc.contributor.googleauthorYun, Jihwan-
dc.contributor.googleauthorChun, Min Young-
dc.contributor.googleauthorKim, Eun-Joo-
dc.contributor.googleauthorKim, Hee Jin-
dc.contributor.googleauthorNa, Duk L.-
dc.contributor.googleauthorKim, Jun Pyo-
dc.contributor.googleauthorSeo, Sang Won-
dc.contributor.googleauthorKwak, Kichang-
dc.identifier.doi10.1212/WNL.0000000000213954-
dc.relation.journalcodeJ02340-
dc.identifier.eissn1526-632X-
dc.identifier.pmid40829110-
dc.contributor.alternativeNameChun, Min Young-
dc.contributor.affiliatedAuthorChun, Min Young-
dc.identifier.scopusid2-s2.0-105013825071-
dc.identifier.wosid001553674200001-
dc.citation.volume105-
dc.citation.number6-
dc.identifier.bibliographicCitationNEUROLOGY, Vol.105(6), 2025-09-
dc.identifier.rimsid90035-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordPlusMILD COGNITIVE IMPAIRMENT-
dc.subject.keywordPlusMEDIAL TEMPORAL-LOBE-
dc.subject.keywordPlusASSOCIATION WORKGROUPS-
dc.subject.keywordPlusDIAGNOSTIC GUIDELINES-
dc.subject.keywordPlusNATIONAL INSTITUTE-
dc.subject.keywordPlusBETA-
dc.subject.keywordPlusATROPHY-
dc.subject.keywordPlusTAU-
dc.subject.keywordPlusRECOMMENDATIONS-
dc.subject.keywordPlusDEMENTIA-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalWebOfScienceCategoryClinical Neurology-
dc.relation.journalResearchAreaNeurosciences & Neurology-
dc.identifier.articlenoe213954-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers

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