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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Ltd
2014
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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. |
format | Online Article Text |
id | pubmed-4240530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | John Wiley & Sons, Ltd |
record_format | MEDLINE/PubMed |
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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