Comparative Study

. 2025 Dec 1;50(12):1120-1129.

doi: 10.1097/RLU.0000000000006088. Epub 2025 Sep 1.

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

Sohyun Yim¹, Yuna Gu^{1

2}, Heekyung Kang¹, Daeun Shin¹, Hyemin Jang³, Heejin Yoo¹, Henrik Zetterberg^{4

5

6

7

8

9}, Kaj Blennow^{4

5

10

11}, Fernando Gonzalez-Ortiz^{4

5}, Nicholas J Ashton^{4

12

13

14}, Michael W Weiner^{15

16

17

18}, Theresa A Day¹⁹, Eun Hye Lee¹, Duk L Na¹, Hee Jin Kim^{1

2

20

20}, Sung Hoon Kang²¹, Ko Woon Kim²², Yeo Jin Kim²³, Yeshin Kim²⁴, Jaeho Kim²⁵, Min Young Chun^{26

27}, Na Yeon Jung²⁸, Soo Hyun Cho²⁹, Jun Pyo Kim¹, Jihwan Yun³⁰, Sang Won Seo^{1

2

20

20}; K-ROAD study groups

Affiliations

¹ Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.
² Department of Health Sciences and Technology, SAIHST, Sungkyunkwan UniversitySeoul, Republic of Korea.
³ Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Jongno-gu, Seoul, Republic of Korea.
⁴ Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
⁵ Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg; Sahlgrenska University Hospital, Mölndal, Sweden.
⁶ Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK.
⁷ UK Dementia Research Institute at UCL; Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London, UK.
⁸ Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China.
⁹ Wisconsin Alzheimer Disease Research Center, Department of Neurology, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI.
¹⁰ Paris Brain Institute (ICM), Department of Neurology, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France.
¹¹ Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China.
¹² Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
¹³ NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia, South London and Maudsley NHS Foundation Trust, London, UK.
¹⁴ Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway.
¹⁵ Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA.
¹⁶ Department of Medicine, University of California, San Francisco, CA.
¹⁷ Department of Psychiatry, University of California, San Francisco, CA.
¹⁸ Department of Neurology, University of California, San Francisco, CA.
¹⁹ Lilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN.
²⁰ Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea.
²¹ Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
²² Department of Neurology, Jeonbuk National University Medical School and Hospital, Jeonju, Republic of Korea.
²³ Department of Neurology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea.
²⁴ Department of Neurology, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Republic of Korea.
²⁵ Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea.
²⁶ Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea.
²⁷ Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, Republic of Korea.
²⁸ Department of Neurology, Pusan National University Yangsan Hospital, Research Institute for Convergence of Biomedical Science and Technology, Yangsan, Republic of Korea.
²⁹ Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Republic of Korea.
³⁰ Department of Neurology, Kyung Hee University College of Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea.

PMID: 40910876
PMCID: PMC12617315
DOI: 10.1097/RLU.0000000000006088

Comparative Study

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

Sohyun Yim et al. Clin Nucl Med. 2025.

. 2025 Dec 1;50(12):1120-1129.

doi: 10.1097/RLU.0000000000006088. Epub 2025 Sep 1.

Authors

Affiliations

¹ Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, Republic of Korea.
² Department of Health Sciences and Technology, SAIHST, Sungkyunkwan UniversitySeoul, Republic of Korea.
³ Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Jongno-gu, Seoul, Republic of Korea.
⁴ Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
⁵ Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg; Sahlgrenska University Hospital, Mölndal, Sweden.
⁶ Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK.
⁷ UK Dementia Research Institute at UCL; Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London, UK.
⁸ Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China.
⁹ Wisconsin Alzheimer Disease Research Center, Department of Neurology, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI.
¹⁰ Paris Brain Institute (ICM), Department of Neurology, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France.
¹¹ Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China.
¹² Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
¹³ NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia, South London and Maudsley NHS Foundation Trust, London, UK.
¹⁴ Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway.
¹⁵ Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA.
¹⁶ Department of Medicine, University of California, San Francisco, CA.
¹⁷ Department of Psychiatry, University of California, San Francisco, CA.
¹⁸ Department of Neurology, University of California, San Francisco, CA.
¹⁹ Lilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN.
²⁰ Alzheimer's Disease Convergence Research Center, Samsung Medical Center, Seoul, Republic of Korea.
²¹ Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
²² Department of Neurology, Jeonbuk National University Medical School and Hospital, Jeonju, Republic of Korea.
²³ Department of Neurology, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Republic of Korea.
²⁴ Department of Neurology, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Republic of Korea.
²⁵ Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea.
²⁶ Department of Neurology, Yonsei University College of Medicine, Seoul, Republic of Korea.
²⁷ Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, Republic of Korea.
²⁸ Department of Neurology, Pusan National University Yangsan Hospital, Research Institute for Convergence of Biomedical Science and Technology, Yangsan, Republic of Korea.
²⁹ Department of Neurology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Republic of Korea.
³⁰ Department of Neurology, Kyung Hee University College of Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea.

PMID: 40910876
PMCID: PMC12617315
DOI: 10.1097/RLU.0000000000006088

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-tau217 MSD 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.

Figures

**FIGURE 1**
Representative images of amyloid PET, tau PET, cortical thickness, and hippocampal volume. A, Representative 18F-florbetaben (FBB) PET images showing a negative case without β-amyloid (Aβ) deposition and a positive case with significant Aβ deposition. B, Representative 18F-flortaucipir (FTP) PET images showing a negative case without tau deposition and a positive case with tau deposition across neocortex. C, Axial images from 3D T1-weighted MRI showing a case with relatively preserved cortical thickness and a case with markedly reduced cortical thickness. D, Coronal images from 3D T1-weighted MRI showing a case with relatively preserved hippocampal structure and a case with marked hippocampal atrophy.

**FIGURE 2**
**A–G**, Prognostic performances of plasma biomarkers for predicting cognitive decline. The standardized regression coefficient (β) and P-values are computed using linear regression with the annualized change in the MMSE score as the dependent variable, adjusted by age, sex, years of education, and *APOE* ε4 status. The black lines indicate the regression line, and the error bands denote the 95% CIs. The y-axis represents the annualized change in MMSE, and the x-axis shows baseline plasma biomarker levels, measured in pg/mL for all biomarkers except Aβ42/40. Aβ indicates β-amyloid; APOE, apolipoprotein E; GFAP, glial fibrillary acidic protein; MMSE, Mini-Mental State Examination; MSD, Meso Scale Discovery; NfL, neurofilament light chain; p-tau, phosphorylated-tau.

**FIGURE 3**
**A–G**, Prognostic performances of imaging biomarkers for predicting cognitive decline. The standardized regression coefficient (β) and P-values are computed using linear regression with the annualized change in the MMSE score as the dependent variable, adjusted by age, sex, years of education, and *APOE* ε4 status. The black lines indicate the regression line, and the error bands denote the 95% Cls. The y-axis represents the annualized change in MMSE, and the x-axis shows baseline imaging biomarker levels: klunk CL for amyloid PET, SUVR for tau PET, mm³ for hippocampal volume, and mm for cortical thickness. APOE indicates apolipoprotein E; klunk CL, klunk Centiloid; MMSE, Mini-Mental State Examination; MTL, medial temporal lobe; meta, meta-temporal; NEO, neo-temporal; TP, temporoparietal; SUVR, standardized uptake value ratios.

**FIGURE 4**
Annualized MMSE change explained (adjusted R²) in plasma and imaging biomarker cohorts. Age, sex, *APOE ε4* status, and education years were included as covariates. Aβ indicates β-amyloid; APOE, apolipoprotein E; Cth, cortical thickness; klunk CL, klunk Centiloid; MMSE, Mini-Mental State Examination; Meta, flortaucipir SUVR in the meta-temporal ROI; MTA, medial temporal lobe atrophy; MTL, flortaucipir SUVR in the medial temporal ROI; NEO, flortaucipir SUVR in the neo-temporal ROI; NfL, neurofilament light chain; p-tau, phosphorylated-tau; ROI, region of interest; SUVR, standardized uptake value ratios, TP, flortaucipir SUVR in the temporoparietal ROI.

See this image and copyright information in PMC

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

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

Authors

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Abstract

Conflict of interest statement

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