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Plasma proteins predict conversion to dementia from prodromal disease

BACKGROUND: The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia. METHODS: Three multicenter cohorts of cognitively hea...

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Autores principales: Hye, Abdul, Riddoch-Contreras, Joanna, Baird, Alison L., Ashton, Nicholas J., Bazenet, Chantal, Leung, Rufina, Westman, Eric, Simmons, Andrew, Dobson, Richard, Sattlecker, Martina, Lupton, Michelle, Lunnon, Katie, Keohane, Aoife, Ward, Malcolm, Pike, Ian, Zucht, Hans Dieter, Pepin, Danielle, Zheng, Wei, Tunnicliffe, Alan, Richardson, Jill, Gauthier, Serge, Soininen, Hilkka, Kłoszewska, Iwona, Mecocci, Patrizia, Tsolaki, Magda, Vellas, Bruno, Lovestone, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4240530/
https://www.ncbi.nlm.nih.gov/pubmed/25012867
http://dx.doi.org/10.1016/j.jalz.2014.05.1749
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author Hye, Abdul
Riddoch-Contreras, Joanna
Baird, Alison L.
Ashton, Nicholas J.
Bazenet, Chantal
Leung, Rufina
Westman, Eric
Simmons, Andrew
Dobson, Richard
Sattlecker, Martina
Lupton, Michelle
Lunnon, Katie
Keohane, Aoife
Ward, Malcolm
Pike, Ian
Zucht, Hans Dieter
Pepin, Danielle
Zheng, Wei
Tunnicliffe, Alan
Richardson, Jill
Gauthier, Serge
Soininen, Hilkka
Kłoszewska, Iwona
Mecocci, Patrizia
Tsolaki, Magda
Vellas, Bruno
Lovestone, Simon
author_facet Hye, Abdul
Riddoch-Contreras, Joanna
Baird, Alison L.
Ashton, Nicholas J.
Bazenet, Chantal
Leung, Rufina
Westman, Eric
Simmons, Andrew
Dobson, Richard
Sattlecker, Martina
Lupton, Michelle
Lunnon, Katie
Keohane, Aoife
Ward, Malcolm
Pike, Ian
Zucht, Hans Dieter
Pepin, Danielle
Zheng, Wei
Tunnicliffe, Alan
Richardson, Jill
Gauthier, Serge
Soininen, Hilkka
Kłoszewska, Iwona
Mecocci, Patrizia
Tsolaki, Magda
Vellas, Bruno
Lovestone, Simon
author_sort Hye, Abdul
collection PubMed
description BACKGROUND: The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia. METHODS: Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays. RESULTS: Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%). CONCLUSIONS: We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints.
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spelling pubmed-42405302014-11-25 Plasma proteins predict conversion to dementia from prodromal disease Hye, Abdul Riddoch-Contreras, Joanna Baird, Alison L. Ashton, Nicholas J. Bazenet, Chantal Leung, Rufina Westman, Eric Simmons, Andrew Dobson, Richard Sattlecker, Martina Lupton, Michelle Lunnon, Katie Keohane, Aoife Ward, Malcolm Pike, Ian Zucht, Hans Dieter Pepin, Danielle Zheng, Wei Tunnicliffe, Alan Richardson, Jill Gauthier, Serge Soininen, Hilkka Kłoszewska, Iwona Mecocci, Patrizia Tsolaki, Magda Vellas, Bruno Lovestone, Simon Alzheimers Dement Featured Article BACKGROUND: The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia. METHODS: Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays. RESULTS: Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%). CONCLUSIONS: We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints. John Wiley & Sons, Ltd 2014-11 /pmc/articles/PMC4240530/ /pubmed/25012867 http://dx.doi.org/10.1016/j.jalz.2014.05.1749 Text en © 2014 The Authors https://creativecommons.org/licenses/by/3.0/This work is licensed under a Creative Commons Attribution 3.0 Unported License (https://creativecommons.org/licenses/by/3.0/) .
spellingShingle Featured Article
Hye, Abdul
Riddoch-Contreras, Joanna
Baird, Alison L.
Ashton, Nicholas J.
Bazenet, Chantal
Leung, Rufina
Westman, Eric
Simmons, Andrew
Dobson, Richard
Sattlecker, Martina
Lupton, Michelle
Lunnon, Katie
Keohane, Aoife
Ward, Malcolm
Pike, Ian
Zucht, Hans Dieter
Pepin, Danielle
Zheng, Wei
Tunnicliffe, Alan
Richardson, Jill
Gauthier, Serge
Soininen, Hilkka
Kłoszewska, Iwona
Mecocci, Patrizia
Tsolaki, Magda
Vellas, Bruno
Lovestone, Simon
Plasma proteins predict conversion to dementia from prodromal disease
title Plasma proteins predict conversion to dementia from prodromal disease
title_full Plasma proteins predict conversion to dementia from prodromal disease
title_fullStr Plasma proteins predict conversion to dementia from prodromal disease
title_full_unstemmed Plasma proteins predict conversion to dementia from prodromal disease
title_short Plasma proteins predict conversion to dementia from prodromal disease
title_sort plasma proteins predict conversion to dementia from prodromal disease
topic Featured Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4240530/
https://www.ncbi.nlm.nih.gov/pubmed/25012867
http://dx.doi.org/10.1016/j.jalz.2014.05.1749
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