Plasma Phosphorylated Tau217–A Pivotal Plasma Biomarker for Predicting the Progression of Mild Cognitive Impairment to Alzheimer’s Disease: A Reanalysis of ADNI Data

INTRODUCTION: It remains uncertain whether plasma biomarkers can demonstrate reliable and robust prognostic performance in predicting progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia comparable to that of amyloid positron emission tomography (Aβ-PET) across different follow-up durations, and whether multi-plasma biomarker panels offer clinically meaningful incremental value over a core plasma biomarker. We aimed to identify the optimal plasma biomarker for differentiating MCI subjects who progressed to dementia (MCI-Converter) from those who did not (MCI-Nonconverter), and compare its discriminative performance with that of Aβ-PET and multi-plasma biomarker panels. METHODS: Based on follow-up diagnostic information, we included 47 MCI-Converters and 66 MCI-Nonconverters from Alzheimer's Disease Neuroimaging Initiative. Wilcoxon rank-sum tests, five-fold cross-validated logistic regression models, Cox proportional hazards models, Spearman correlations, and linear mixed-effects models (LMM) were applied to evaluate inter-group differences, discriminative performance, conversion risk, and correlations between plasma biomarkers and Aβ-PET measures, as well as longitudinal cognitive decline. Risk stratification analyses were further conducted using LMM by categorizing participants into low-, moderate-, and high-risk strata according to plasma phosphorylated tau 217 (p-tau217) two-cutpoints. RESULTS: P-tau217 demonstrated the most significant inter-group differences, the highest hazard ratio, and best distinguished MCI-Converters from MCI-Nonconverters, with its discriminative performance comparable to that of Aβ-PET measures and multi-plasma biomarker models. P-tau217 exhibited the strongest associations with global and domain-specific cognitive declines, as well as Aβ-PET. High-risk participants exhibited the fastest cognitive decline rate, with a positive predictive value (PPV) of 100% for Aβ-PET amyloid status and a PPV of 82.2% for MCI-Converters. Low-risk participants showed a negative predictive value (NPV) of 78.3% for Aβ-PET amyloid status and an NPV of 84.9% for MCI-Nonconverters. CONCLUSIONS: P-tau217 is the optimal and robust biomarker for predicting the conversion from MCI to AD dementia, thereby streamlining and promoting plasma biomarker - based prediction of MCI-to-dementia conversion.

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Journal
Journal of Clinical and Experimental Neuropsychology
Published
2026-05-12
DOI
https://doi.org/10.1080/13803395.2026.2671206
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
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article

Plasma Phosphorylated Tau217–A Pivotal Plasma Biomarker for Predicting the Progression of Mild Cognitive Impairment to Alzheimer’s Disease: A Reanalysis of ADNI Data

Huixuan Ma, P Y Wang, Jinxuan Guo, Ruina Li et al.
Journal of Clinical and Experimental Neuropsychology
Dementia and Cognitive Impairment Research
article

Plasma Phosphorylated Tau217–A Pivotal Plasma Biomarker for Predicting the Progression of Mild Cognitive Impairment to Alzheimer’s Disease: A Reanalysis of ADNI Data

Huixuan Ma, P Y Wang, Jinxuan Guo, Ruina Li, W Z Sun, Tong Cui, Qingyuan Sun, Qingjie Lian, Xiaodong Han, Alzheimer’s Disease Neuroimaging Initiative, Boye Wen, Jin Gong, Aidi Shan, Cuibai Wei
article en

Abstract

INTRODUCTION: It remains uncertain whether plasma biomarkers can demonstrate reliable and robust prognostic performance in predicting progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia comparable to that of amyloid positron emission tomography (Aβ-PET) across different follow-up durations, and whether multi-plasma biomarker panels offer clinically meaningful incremental value over a core plasma biomarker. We aimed to identify the optimal plasma biomarker for differentiating MCI subjects who progressed to dementia (MCI-Converter) from those who did not (MCI-Nonconverter), and compare its discriminative performance with that of Aβ-PET and multi-plasma biomarker panels. METHODS: Based on follow-up diagnostic information, we included 47 MCI-Converters and 66 MCI-Nonconverters from Alzheimer's Disease Neuroimaging Initiative. Wilcoxon rank-sum tests, five-fold cross-validated logistic regression models, Cox proportional hazards models, Spearman correlations, and linear mixed-effects models (LMM) were applied to evaluate inter-group differences, discriminative performance, conversion risk, and correlations between plasma biomarkers and Aβ-PET measures, as well as longitudinal cognitive decline. Risk stratification analyses were further conducted using LMM by categorizing participants into low-, moderate-, and high-risk strata according to plasma phosphorylated tau 217 (p-tau217) two-cutpoints. RESULTS: P-tau217 demonstrated the most significant inter-group differences, the highest hazard ratio, and best distinguished MCI-Converters from MCI-Nonconverters, with its discriminative performance comparable to that of Aβ-PET measures and multi-plasma biomarker models. P-tau217 exhibited the strongest associations with global and domain-specific cognitive declines, as well as Aβ-PET. High-risk participants exhibited the fastest cognitive decline rate, with a positive predictive value (PPV) of 100% for Aβ-PET amyloid status and a PPV of 82.2% for MCI-Converters. Low-risk participants showed a negative predictive value (NPV) of 78.3% for Aβ-PET amyloid status and an NPV of 84.9% for MCI-Nonconverters. CONCLUSIONS: P-tau217 is the optimal and robust biomarker for predicting the conversion from MCI to AD dementia, thereby streamlining and promoting plasma biomarker - based prediction of MCI-to-dementia conversion.

Journal of Clinical and Experimental Neuropsychology
Capital University (US), Capital Medical University (CN), Changchun University of Chinese Medicine (CN), Shandong First Medical University (CN), Beihang University (CN)
National Natural Science Foundation of China
Reduced inequalities
Openalex Percentile: Top 5%
Dementia and Cognitive Impairment Research
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