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. 2025 Sep 1.
doi: 10.1097/RLU.0000000000006088. Online ahead of print.

Prognostic Value of A/T/N Biomarkers: Comparing Plasma and Imaging Modalities in Alzheimer Disease

Affiliations

Prognostic Value of A/T/N Biomarkers: Comparing Plasma and Imaging Modalities in Alzheimer Disease

Sohyun Yim et al. Clin Nucl Med. .

Abstract

Background: Alzheimer disease (AD) is characterized by amyloid-β plaques (A), tau tangles (T), and neurodegeneration (N), collectively defining the ATN framework. While imaging biomarkers are well-established, the prognostic value of plasma biomarkers in predicting cognitive decline remains underexplored. This study compares plasma and imaging A/T/N biomarkers in predicting cognitive decline and evaluate the impact of combining biomarkers across modalities.

Patients and methods: We conducted a longitudinal study using K-ROAD cohort participants who underwent at least 2 cognitive assessments. All participants had plasma biomarker testing (Aβ ratio, p-tau181, p-tau231, p-tau217, NfL), and a subset with imaging biomarker assessments (Aβ PET, tau PET, structural MRI) formed an imaging subcohort. Multiple linear regression models identified the most predictive markers within each modality and evaluated the effect of combining A/T/N biomarkers.

Results: Among 1,614 plasma cohort and 130 imaging subcohort participants, tau markers demonstrated the strongest predictive value. p-tau217MSD outperforming other plasma biomarkers, and the neo-temporal ROI showing the highest predictive power among imaging biomarkers. In plasma-based model, adding neurodegeneration markers to combination of amyloid and tau biomarkers improved the performance. In imaging-based models, same strategy decreased the performance, suggesting that combinations of amyloid and tau PET captures the most relevant prognostic information.

Conclusions: Imaging biomarkers, particularly tau PET, show superior prognostic accuracy compared with plasma biomarkers, whereas plasma biomarkers offer advantages in combination models through neurodegeneration markers. These findings underscore the complementary roles of plasma and imaging biomarkers and emphasize the need for tailored strategies for prognostic modeling in AD.

Keywords: ATN framework; alzheimer disease; imaging biomarkers; plasma biomarkers; prediction of cognitive decline; prognostic modeling.

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Conflict of interest statement

Conflicts of interest and sources of funding: S.W.S. is supported by a grant of the Korea Dementia Research Project through the Korea Dementia Research Center (KDRC), funded by the Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea (RS-2020-KH106434), Future Medicine 20*30 Project of the Samsung Medical Center [#SMX1250081], the “Korea National Institute of Health” research project (2024-ER1003-01), the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2019-NR040057), Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.RS-2021-II212068, Artificial Intelligence Innovation Hub), and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: RS-2025-02223212). H.J. is supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare and Ministry of science and ICT, Republic of Korea (grant number: RS-2022-KH125667) and a grant of the Korea Dementia Research Project through the Korea Dementia Research Center (KDRC), funded by the Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea (RS-2020-KH107436). H.Z. is a Wallenberg scholar and a distinguished professor at the Swedish Research Council supported by grants from the Swedish Research Council (#2023-00356, #2022-01018, and #2019-02397), European Union’s Horizon Europe research and innovation program under grant agreement No 101053962, Swedish State Support for Clinical Research (#ALFGBG-71320), Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862), AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C, #ADSF-21-831377-C, and #ADSF-24-1284328-C), Bluefield Project, Cure Alzheimer’s Fund, Olav Thon Foundation, Erling-Persson Family Foundation, Familjen Rönströms Stiftelse, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270), European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), European Union Joint Programme – Neurodegenerative Disease Research (JPND2021-00694), National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre, and the UK Dementia Research Institute at UCL (UKDRI-1003). K.B. is supported by the Swedish Research Council (#2017-00915 and #2022-00732), Swedish Alzheimer Foundation (#AF-930351, #AF-939721, #AF-968270, and #AF-994551), Hjärnfonden, Sweden (#FO2017-0243 and #ALZ2022-0006), Swedish state under the agreement between the Swedish government and the County Councils, ALF-agreement (#ALFGBG-715986 and #ALFGBG-965240), European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236), Alzheimer’s Association 2021 Zenith Award (ZEN-21-848495), Alzheimer’s Association 2022–2025 Grant (SG-23-1038904 QC), La Fondation Recherche Alzheimer (FRA), Paris, France, Kirsten and Freddy Johansen Foundation, Copenhagen, Denmark, and Familjen Rönströms Stiftelse, Stockholm, Sweden. Avid Radiopharmaceuticals, Inc., a wholly owned subsidiary of Eli Lilly and Company, enabled the use of the 18F-flortaucipir tracer by providing a precursor, but did not provide direct funding and was not involved in data analysis or interpretation. He has served as a consultant and on advisory boards for Abbvie, AC Immune, ALZPath, AriBio, BioArctic, Biogen, Eisai, Lilly, Moleac Pte. Ltd, Novartis, Ono Pharma, Prothena, Roche Diagnostics, and Siemens Healthineers; has served on data monitoring committees for Julius Clinical and Novartis; has delivered lectures, produced educational materials, and participated in educational programs for AC Immune, Biogen, Celdara Medical, Eisai and Roche Diagnostics; and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program, outside the work presented in this paper. H.Z. has served at scientific advisory boards and/or as a consultant for Abbvie, Acumen, Alector, Alzinova, ALZPath, Amylyx, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, Merry Life, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Red Abbey Labs, reMYND, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, has delivered lectures in symposia sponsored by Alzecure, Biogen, Cellectricon, Fujirebio, Lilly, Novo Nordisk, and Roche, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work). N.J.A. has received consulting fees from Quanterix, and has also received payments for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Alamar Biosciences, Biogen, Eli-Lilly, and Quanterix. He is listed as an inventor on a patent application (Application No.: PCT/US2024/037834, WSGR Docket No. 58484-709.601) related to methods for remote blood collection, extraction, and analysis of neuro biomarkers; serves on the advisory board for Biogen, TargetALS, and TauRx; and receives payments for this role. D.L.N. and S.W.S. are co-founders of BeauBrain Healthcare, Inc.

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