장혜민 (서울아산병원 신경과) | 한빛사논문 > 한빛사

한빛사논문

조회63

서울아산병원 신경과

CV File

JAMA Neurol., Feb 02 2026, | https://doi.org/10.1001/jamaneurol.2025.5530 Plasma Phosphorylated Tau 217 Cutoffs for Amyloid Pathology and Kidney Function, Body Mass Index, and Anemia

Jihwan Yun, MD, PhD¹; Jungah Lee, MSc²; Daeun Shin, MD, MSc³; Eun Hye Lee, MD, PhD³; Jun Pyo Kim, MD, PhD³; Hongki Ham, MSc^2,3,8,9; Yuna Gu, MSc^3,7; Min Young Chun, MD, PhD^4,5; Sung Hoon Kang, MD, PhD⁶; Hee Jin Kim, MD, PhD^2,3,7,8; Duk L. Na, MD, PhD^3,10; Ko Woon Kim, MD, PhD¹¹; Si Eun Kim, MD, PhD¹²; Yeshin Kim, MD, PhD¹³; Jaeho Kim, MD, PhD¹⁴; Na-Yeon Jung, MD, PhD¹⁵; Yeo Jin Kim, MD, PhD¹⁶; Soo Hyun Cho, MD, PhD¹⁷; Jin San Lee, MD, PhD¹; Seonghyeon Kim, MD³; Henrik Zetterberg, MD, PhD^{18,19,20,21,22,23}; Kaj Blennow, MD, PhD^20,21,24,25; Fernando Gonzalez-Ortiz, MD, MSc^18,19; Nicholas J. Ashton, PhD^18,26,27,28; Joel B. Braunstein, MD, MBA²⁹; Philip B. Verghese, PhD²⁹; Tim West, PhD²⁹; Matthew R. Meyer, PhD²⁹; Sang Won Seo, MD, PhD^2,3,7,8,9; Hyemin Jang, MD, PhD³⁰; for the K-ROAD Study Groups

¹Department of Neurology, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, Republic of Korea
²Alzheimer’s Disease Convergence Research Center, Samsung Medical Center, Seoul, South Korea
³Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Gangnam-gu, Seoul, South Korea
⁴Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
⁵Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea
⁶Department of Neurology, Korea University Guro Hospital, Korea University College of Medicine, Seoul, South Korea
⁷Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
⁸Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
⁹Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, South Korea
¹⁰Happymind Clinic, Seoul, South Korea
¹¹Department of Neurology, Jeonbuk National University Medical School and Hospital, Jeonju, Korea
¹²Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan, Korea
¹³Department of Neurology, Kangwon National University College of Medicine, Chuncheon-si, Gangwon-do, Korea
¹⁴Department of Neurology, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea
¹⁵Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Korea
¹⁶Department of Neurology, Kangdong Sacred Heart Hospital, Seoul, Republic of Korea
¹⁷Department of Neurology, Chonnam National University Medical School and Chonnam National University Hospital, Gwangju, Korea
¹⁸Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
¹⁹Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
²⁰Department of Neurodegenerative Disease, University College London Institute of Neurology, London, United Kingdom
²¹UK Dementia Research Institute at University College London, London, United Kingdom
²²Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
²³Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin–Madison, Madison
²⁴Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
²⁵Neurodegenerative 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
²⁶Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King’s College London, London, United Kingdom
²⁷NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, United Kingdom
²⁸Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
²⁹C2N Diagnostics LLC, St Louis, Missouri
³⁰Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea

Drs Jang and Seo contributed equally to this article as co–corresponding authors.
Corresponding Authors: Hyemin Jang, MD, PhD, ; Sang Won Seo, MD, PhD

Abstract

Importance: Plasma phosphorylated p-tau 217 levels vary with biological factors such as kidney dysfunction, body mass index (BMI), and anemia. It remains unclear whether a biological subgroup-specific optimal cutoff or a double-cutoff strategy could enhance diagnostic accuracy and cost efficiency beyond the standard single cutoff.

Objective: To compare the diagnostic and economic performance of 3 plasma p-tau217 classification strategies for detecting amyloid-β (Aβ) positivity: standard single cutoff, subgroup-specific optimal cutoff, and double cutoff.

Design, setting, and participants: This cohort study was a multicenter cross-sectional study conducted from 2016 to 2023; analyses were completed in 2025. Participants were recruited from multiple memory clinics and community-based cohorts. All participants had amyloid positron emission tomography (PET) imaging, clinical evaluation, and p-tau217 testing with measures of estimated glomerular filtration rate (eGFR), BMI, and hemoglobin. Measurements of p-tau217 were made using UGOT Simoa and Roche Elecsys, and the %p-tau217 ratio was assessed using a tau multianalyte assay (C2N Diagnostics LLC).

Exposures: Kidney function (chronic kidney disease [CKD], eGFR <60 mL/min/1.73 m2; advanced CKD, eGFR <45 mL/min/1.73 m2), underweight (BMI <18.5), obesity (BMI ≥27.5), and anemia (hemoglobin <12 g/dL in women, <13 g/dL in men).

Main outcomes and measures: Plasma p-tau217 concentration; standard single cutoff, optimal cutoffs, and double cutoff for Aβ positivity (Centiloid ≥25.5); accuracy; and cost-effectiveness estimated from false-positive, false-negative, and confirmatory imaging costs.

Results: A total of 2571 participants were analyzed with UGOT, 1578 with Roche, and 304 with the C2N %p-tau217 ratio. The mean (SD) age was similar across cohorts (71.3 [8.6] years in the UGOT cohort, 71.3 [8.5] years in the Roche cohort, and 71.8 [7.8] years in the C2N cohort); there were 1633 (63.5%), 1006 (63.8%), and 191 (62.8%) women and 938 (36.5%), 572 (36.2%), and 113 (37.2%) men, respectively. In the UGOT cohort, the optimal cutoff improved diagnostic accuracy compared with the standard single cutoff, particularly in CKD and anemia (CKD: from 0.65; 95% CI, 0.57-0.72; to 0.83; 95% CI, 0.76-0.89; anemia: from 0.80; 95% CI, 0.76-0.84; to 0.86; 95% CI, 0.82-0.90), with consistent findings in the Roche cohort. In all biological subgroups, the double-cutoff strategy also increased accuracy relative to the single cutoff and reduced false classifications but yielded 12% to 39% intermediate results. When compared directly, the optimal cutoff provided higher accuracy than the double cutoff for CKD while lowering total diagnostic costs. For anemia, the double cutoff showed slightly higher accuracy but required confirmatory PET in up to 25% of cases, offsetting its economic advantage. In obesity, the double cutoff remained superior for both diagnostic accuracy and cost efficiency.

Conclusions and relevance: This study found that both the optimal cutoff and the double-cutoff strategy outperformed the standard single cutoff, each showing distinct strengths across subgroups. These findings support biologically informed thresholds to improve diagnostic accuracy and cost efficiency when implementing plasma p-tau217.

논문정보

형식Research article
게재일2026년 02월 (BRIC 등록일 2026-02-04)
연구진국내(교신)+국외 연구진
분야 의약학 > 신경의학

장혜민 님 전체 논문보기

연구자 ID

댓글 작성 로그인

CV 열람하기

연락처 보기