Plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairment

Abstract INTRODUCTION Previous studies have examined the predictive accuracy of plasma amyloid beta (Aβ) biomarkers in clinical cohorts. However, their accuracy for predicting amyloid‐positive patients in community‐based cohorts is unclear. This study aimed to determine the predictive accuracy of Aβ...

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Main Authors: Takuya Ataka, Noriyuki Kimura, Naoki Kaneko, Teruaki Masuda, Yosuke Takeuchi, Kenichi Yabuuchi, Takeshi Mizukami, Tsukasa Takeuchi, Temmei Ito, Hideaki Tasai, Takehiko Miyagawa, Shunya Hanai, Shinichi Iwamoto, Etsuro Matsubara
Format: Article
Language:English
Published: Wiley 2024-10-01
Series:Alzheimer’s & Dementia: Translational Research & Clinical Interventions
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Online Access:https://doi.org/10.1002/trc2.70008
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author Takuya Ataka
Noriyuki Kimura
Naoki Kaneko
Teruaki Masuda
Yosuke Takeuchi
Kenichi Yabuuchi
Takeshi Mizukami
Tsukasa Takeuchi
Temmei Ito
Hideaki Tasai
Takehiko Miyagawa
Shunya Hanai
Shinichi Iwamoto
Etsuro Matsubara
author_facet Takuya Ataka
Noriyuki Kimura
Naoki Kaneko
Teruaki Masuda
Yosuke Takeuchi
Kenichi Yabuuchi
Takeshi Mizukami
Tsukasa Takeuchi
Temmei Ito
Hideaki Tasai
Takehiko Miyagawa
Shunya Hanai
Shinichi Iwamoto
Etsuro Matsubara
author_sort Takuya Ataka
collection DOAJ
description Abstract INTRODUCTION Previous studies have examined the predictive accuracy of plasma amyloid beta (Aβ) biomarkers in clinical cohorts. However, their accuracy for predicting amyloid‐positive patients in community‐based cohorts is unclear. This study aimed to determine the predictive accuracy of Aβ precursor protein 669‐711/Aβ1‐42, Aβ1‐40/1‐42 and their composite biomarkers for brain amyloid deposition or the clinical progression in community‐dwelling older adults with mild cognitive impairment (MCI). METHODS This prospective cohort study was conducted from August 2015 to September 2019. Subsequently, the participants underwent follow‐up cognitive assessments up to 8 years after the start of the study. Blood samples were collected from older adults aged ≥ 65 years with MCI at baseline. Plasma Aβ biomarkers were analyzed using immunoprecipitation‐mass spectrometry. The accuracy of plasma biomarkers for brain amyloid status was evaluated using receiver operating characteristic curve analysis. Relationships between comorbidities and plasma Aβ markers were examined using multiple linear regression analysis. Associations of plasma biomarkers with clinical conversion to Alzheimer's disease (AD) dementia were evaluated using Kaplan‒Meier curves. RESULTS The participants included 107 patients (57 [53.3%] females, median age: 76.0 [72.0–80.0] years). Plasma biomarkers correlated with cortical amyloid uptake (ρ = 0.667–0.754). The composite biomarker had the best area under the curve (0.943, 95% confidence interval [CI]: 0.901 to 0.985) for predicting amyloid positivity. Apolipoprotein ε4 status showed significant correlations with increased plasma amyloid biomarker levels. Participants with high composite biomarker levels at baseline had a greater risk of conversion to AD dementia (hazard ratio 10.74, 95% CI: 3.51 to 32.84, P < 0.001). The higher composite biomarker was associated with a faster rate of cognitive decline (ρ = −0.575, P < 0.001). DISCUSSION Plasma Aβ composite biomarker may serve as a surrogate measure for amyloid deposition and a predictor of disease progression in a community‐based cohort. Highlights Plasma amyloid beta (Aβ) biomarkers correlated with 11C‐Pittsburgh compound B uptake, mainly in the frontal/parietotemporal cortices and posterior cingulate gyrus. The amyloid composite biomarker can predict amyloid positron emission tomography positivity with a high area under the curve of 0.943 in a community‐based mild cognitive impairment cohort. The higher amyloid composite biomarker at baseline was significantly associated with worsening Mini‐Mental State Examination score and a high risk for developing Alzheimer's disease (AD) dementia over 8 years. The amyloid composite biomarker can predict clinical progression to AD dementia with a high area under the curve of 0.860. Apolipoprotein E ε4 status influenced the plasma Aβ biomarker levels.
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series Alzheimer’s & Dementia: Translational Research & Clinical Interventions
spelling doaj-art-252f30c56b5f45f1ab0c49fe27bdc9b12024-12-27T12:20:32ZengWileyAlzheimer’s & Dementia: Translational Research & Clinical Interventions2352-87372024-10-01104n/an/a10.1002/trc2.70008Plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairmentTakuya Ataka0Noriyuki Kimura1Naoki Kaneko2Teruaki Masuda3Yosuke Takeuchi4Kenichi Yabuuchi5Takeshi Mizukami6Tsukasa Takeuchi7Temmei Ito8Hideaki Tasai9Takehiko Miyagawa10Shunya Hanai11Shinichi Iwamoto12Etsuro Matsubara13Department of Neurology Faculty of Medicine Oita University Oita JapanDepartment of Neurology Faculty of Medicine Oita University Oita JapanKoichi Tanaka Mass Spectrometry Research Laboratory Shimadzu Corporation Kyoto JapanDepartment of Neurology Faculty of Medicine Oita University Oita JapanDepartment of Neurology Faculty of Medicine Oita University Oita JapanDepartment of Neurology Faculty of Medicine Oita University Oita JapanDepartment of Neurology Faculty of Medicine Oita University Oita JapanKoichi Tanaka Mass Spectrometry Research Laboratory Shimadzu Corporation Kyoto JapanEisai Co. Ltd. Tokyo JapanEisai Co. Ltd. Tokyo JapanEisai Co. Ltd. Tokyo JapanKoichi Tanaka Mass Spectrometry Research Laboratory Shimadzu Corporation Kyoto JapanKoichi Tanaka Mass Spectrometry Research Laboratory Shimadzu Corporation Kyoto JapanDepartment of Neurology Faculty of Medicine Oita University Oita JapanAbstract INTRODUCTION Previous studies have examined the predictive accuracy of plasma amyloid beta (Aβ) biomarkers in clinical cohorts. However, their accuracy for predicting amyloid‐positive patients in community‐based cohorts is unclear. This study aimed to determine the predictive accuracy of Aβ precursor protein 669‐711/Aβ1‐42, Aβ1‐40/1‐42 and their composite biomarkers for brain amyloid deposition or the clinical progression in community‐dwelling older adults with mild cognitive impairment (MCI). METHODS This prospective cohort study was conducted from August 2015 to September 2019. Subsequently, the participants underwent follow‐up cognitive assessments up to 8 years after the start of the study. Blood samples were collected from older adults aged ≥ 65 years with MCI at baseline. Plasma Aβ biomarkers were analyzed using immunoprecipitation‐mass spectrometry. The accuracy of plasma biomarkers for brain amyloid status was evaluated using receiver operating characteristic curve analysis. Relationships between comorbidities and plasma Aβ markers were examined using multiple linear regression analysis. Associations of plasma biomarkers with clinical conversion to Alzheimer's disease (AD) dementia were evaluated using Kaplan‒Meier curves. RESULTS The participants included 107 patients (57 [53.3%] females, median age: 76.0 [72.0–80.0] years). Plasma biomarkers correlated with cortical amyloid uptake (ρ = 0.667–0.754). The composite biomarker had the best area under the curve (0.943, 95% confidence interval [CI]: 0.901 to 0.985) for predicting amyloid positivity. Apolipoprotein ε4 status showed significant correlations with increased plasma amyloid biomarker levels. Participants with high composite biomarker levels at baseline had a greater risk of conversion to AD dementia (hazard ratio 10.74, 95% CI: 3.51 to 32.84, P < 0.001). The higher composite biomarker was associated with a faster rate of cognitive decline (ρ = −0.575, P < 0.001). DISCUSSION Plasma Aβ composite biomarker may serve as a surrogate measure for amyloid deposition and a predictor of disease progression in a community‐based cohort. Highlights Plasma amyloid beta (Aβ) biomarkers correlated with 11C‐Pittsburgh compound B uptake, mainly in the frontal/parietotemporal cortices and posterior cingulate gyrus. The amyloid composite biomarker can predict amyloid positron emission tomography positivity with a high area under the curve of 0.943 in a community‐based mild cognitive impairment cohort. The higher amyloid composite biomarker at baseline was significantly associated with worsening Mini‐Mental State Examination score and a high risk for developing Alzheimer's disease (AD) dementia over 8 years. The amyloid composite biomarker can predict clinical progression to AD dementia with a high area under the curve of 0.860. Apolipoprotein E ε4 status influenced the plasma Aβ biomarker levels.https://doi.org/10.1002/trc2.70008amyloidAlzheimer's diseasecomposite biomarkermild cognitive impairmentolder adult
spellingShingle Takuya Ataka
Noriyuki Kimura
Naoki Kaneko
Teruaki Masuda
Yosuke Takeuchi
Kenichi Yabuuchi
Takeshi Mizukami
Tsukasa Takeuchi
Temmei Ito
Hideaki Tasai
Takehiko Miyagawa
Shunya Hanai
Shinichi Iwamoto
Etsuro Matsubara
Plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairment
Alzheimer’s & Dementia: Translational Research & Clinical Interventions
amyloid
Alzheimer's disease
composite biomarker
mild cognitive impairment
older adult
title Plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairment
title_full Plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairment
title_fullStr Plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairment
title_full_unstemmed Plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairment
title_short Plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairment
title_sort plasma amyloid beta biomarkers predict amyloid positivity and longitudinal clinical progression in mild cognitive impairment
topic amyloid
Alzheimer's disease
composite biomarker
mild cognitive impairment
older adult
url https://doi.org/10.1002/trc2.70008
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