Promising clinical tools for specific Alzheimer disease diagnosis from plasma pTau217 and ApoE genotype in a cognitive disorder unit

Abstract Alzheimer’s disease (AD) diagnosis relies on cerebrospinal fluid (CSF) biomarkers or amyloid PET. Alternatives for AD diagnosis from blood samples are needed to develop a fully-automated early-diagnosis approach, potentially implemented in a cognitive disorder unit. Plasma p-Tau217 was dete...

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Main Authors: Lourdes Álvarez-Sánchez, Carmen Peña-Bautista, Laura Ferré-González, Ángel Balaguer, Julián Luis Amengual, Miguel Baquero, Consuelo Cháfer-Pericás
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-01511-3
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author Lourdes Álvarez-Sánchez
Carmen Peña-Bautista
Laura Ferré-González
Ángel Balaguer
Julián Luis Amengual
Miguel Baquero
Consuelo Cháfer-Pericás
author_facet Lourdes Álvarez-Sánchez
Carmen Peña-Bautista
Laura Ferré-González
Ángel Balaguer
Julián Luis Amengual
Miguel Baquero
Consuelo Cháfer-Pericás
author_sort Lourdes Álvarez-Sánchez
collection DOAJ
description Abstract Alzheimer’s disease (AD) diagnosis relies on cerebrospinal fluid (CSF) biomarkers or amyloid PET. Alternatives for AD diagnosis from blood samples are needed to develop a fully-automated early-diagnosis approach, potentially implemented in a cognitive disorder unit. Plasma p-Tau217 was determined in patients diagnosed with AD (n = 134) or non-AD (n = 132), from CSF biomarkers (Aβ42/Aβ40). A logistic regression model was developed. The predictive performance was assessed using a training set (70% of data) and internally validated with a test set (30% of data) and 1000 iterations. A nomogram and a double cut-off strategy were proposed to visualize the model results, and stratify patients (AD, non-AD, uncertain), respectively. The model (plasma p-Tau217, ApoE, age) showed satisfactory performance (AUC 0.94, sensitivity 0.85, specificity 0.89); so, together with the corresponding nomogram, it could be applied in specialized clinical contexts. The model including only plasma p-Tau217 (AUC 0.93, sensitivity 0.72, specificity 0.96) would be a useful approach in less specialized clinics. The corresponding two-cut-off strategy for the first model were as AD probability (< 0.41 non-AD, > 0.57 AD). This study provided clinical tools (nomogram, double cut-off) for identifying Aβ positivity at a cognitive disorder unit, which would lead to reduce the CSF analysis.
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spelling doaj-art-f81443b1d43b476b80ed4c6847e895d72025-08-20T03:53:12ZengNature PortfolioScientific Reports2045-23222025-05-0115111310.1038/s41598-025-01511-3Promising clinical tools for specific Alzheimer disease diagnosis from plasma pTau217 and ApoE genotype in a cognitive disorder unitLourdes Álvarez-Sánchez0Carmen Peña-Bautista1Laura Ferré-González2Ángel Balaguer3Julián Luis Amengual4Miguel Baquero5Consuelo Cháfer-Pericás6Alzheimer’s Disease Research Group, Instituto de Investigación Sanitaria La FeAlzheimer’s Disease Research Group, Instituto de Investigación Sanitaria La FeAlzheimer’s Disease Research Group, Instituto de Investigación Sanitaria La FePlataforma de Big Data, IA y Bioestadística, Instituto de Investigación Sanitaria La FePlataforma de Big Data, IA y Bioestadística, Instituto de Investigación Sanitaria La FeAlzheimer’s Disease Research Group, Instituto de Investigación Sanitaria La FeAlzheimer’s Disease Research Group, Instituto de Investigación Sanitaria La FeAbstract Alzheimer’s disease (AD) diagnosis relies on cerebrospinal fluid (CSF) biomarkers or amyloid PET. Alternatives for AD diagnosis from blood samples are needed to develop a fully-automated early-diagnosis approach, potentially implemented in a cognitive disorder unit. Plasma p-Tau217 was determined in patients diagnosed with AD (n = 134) or non-AD (n = 132), from CSF biomarkers (Aβ42/Aβ40). A logistic regression model was developed. The predictive performance was assessed using a training set (70% of data) and internally validated with a test set (30% of data) and 1000 iterations. A nomogram and a double cut-off strategy were proposed to visualize the model results, and stratify patients (AD, non-AD, uncertain), respectively. The model (plasma p-Tau217, ApoE, age) showed satisfactory performance (AUC 0.94, sensitivity 0.85, specificity 0.89); so, together with the corresponding nomogram, it could be applied in specialized clinical contexts. The model including only plasma p-Tau217 (AUC 0.93, sensitivity 0.72, specificity 0.96) would be a useful approach in less specialized clinics. The corresponding two-cut-off strategy for the first model were as AD probability (< 0.41 non-AD, > 0.57 AD). This study provided clinical tools (nomogram, double cut-off) for identifying Aβ positivity at a cognitive disorder unit, which would lead to reduce the CSF analysis.https://doi.org/10.1038/s41598-025-01511-3Alzheimer diseaseBiomarkersPlasmaDiagnosisPredictive modelValidation
spellingShingle Lourdes Álvarez-Sánchez
Carmen Peña-Bautista
Laura Ferré-González
Ángel Balaguer
Julián Luis Amengual
Miguel Baquero
Consuelo Cháfer-Pericás
Promising clinical tools for specific Alzheimer disease diagnosis from plasma pTau217 and ApoE genotype in a cognitive disorder unit
Scientific Reports
Alzheimer disease
Biomarkers
Plasma
Diagnosis
Predictive model
Validation
title Promising clinical tools for specific Alzheimer disease diagnosis from plasma pTau217 and ApoE genotype in a cognitive disorder unit
title_full Promising clinical tools for specific Alzheimer disease diagnosis from plasma pTau217 and ApoE genotype in a cognitive disorder unit
title_fullStr Promising clinical tools for specific Alzheimer disease diagnosis from plasma pTau217 and ApoE genotype in a cognitive disorder unit
title_full_unstemmed Promising clinical tools for specific Alzheimer disease diagnosis from plasma pTau217 and ApoE genotype in a cognitive disorder unit
title_short Promising clinical tools for specific Alzheimer disease diagnosis from plasma pTau217 and ApoE genotype in a cognitive disorder unit
title_sort promising clinical tools for specific alzheimer disease diagnosis from plasma ptau217 and apoe genotype in a cognitive disorder unit
topic Alzheimer disease
Biomarkers
Plasma
Diagnosis
Predictive model
Validation
url https://doi.org/10.1038/s41598-025-01511-3
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