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A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer’s Disease Diagnosis Using Targeted Proteomics and Machine Learning

As disease-modifying therapies are now available for Alzheimer’s disease (AD), accessible, accurate and affordable biomarkers to support diagnosis are urgently needed. We sought to develop a mass spectrometry-based urine test as a high-throughput screening tool for diagnosing AD. We collected urine...

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Autores principales: Hällqvist, Jenny, Pinto, Rui C., Heywood, Wendy E., Cordey, Jonjo, Foulkes, Alexander J. M., Slattery, Catherine F., Leckey, Claire A., Murphy, Eimear C., Zetterberg, Henrik, Schott, Jonathan M., Mills, Kevin, Paterson, Ross W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10531486/
https://www.ncbi.nlm.nih.gov/pubmed/37762058
http://dx.doi.org/10.3390/ijms241813758
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author Hällqvist, Jenny
Pinto, Rui C.
Heywood, Wendy E.
Cordey, Jonjo
Foulkes, Alexander J. M.
Slattery, Catherine F.
Leckey, Claire A.
Murphy, Eimear C.
Zetterberg, Henrik
Schott, Jonathan M.
Mills, Kevin
Paterson, Ross W.
author_facet Hällqvist, Jenny
Pinto, Rui C.
Heywood, Wendy E.
Cordey, Jonjo
Foulkes, Alexander J. M.
Slattery, Catherine F.
Leckey, Claire A.
Murphy, Eimear C.
Zetterberg, Henrik
Schott, Jonathan M.
Mills, Kevin
Paterson, Ross W.
author_sort Hällqvist, Jenny
collection PubMed
description As disease-modifying therapies are now available for Alzheimer’s disease (AD), accessible, accurate and affordable biomarkers to support diagnosis are urgently needed. We sought to develop a mass spectrometry-based urine test as a high-throughput screening tool for diagnosing AD. We collected urine from a discovery cohort (n = 11) of well-characterised individuals with AD (n = 6) and their asymptomatic, CSF biomarker-negative study partners (n = 5) and used untargeted proteomics for biomarker discovery. Protein biomarkers identified were taken forward to develop a high-throughput, multiplexed and targeted proteomic assay which was tested on an independent cohort (n = 21). The panel of proteins identified are known to be involved in AD pathogenesis. In comparing AD and controls, a panel of proteins including MIEN1, TNFB, VCAM1, REG1B and ABCA7 had a classification accuracy of 86%. These proteins have been previously implicated in AD pathogenesis. This suggests that urine-targeted mass spectrometry has potential utility as a diagnostic screening tool in AD.
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spelling pubmed-105314862023-09-28 A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer’s Disease Diagnosis Using Targeted Proteomics and Machine Learning Hällqvist, Jenny Pinto, Rui C. Heywood, Wendy E. Cordey, Jonjo Foulkes, Alexander J. M. Slattery, Catherine F. Leckey, Claire A. Murphy, Eimear C. Zetterberg, Henrik Schott, Jonathan M. Mills, Kevin Paterson, Ross W. Int J Mol Sci Article As disease-modifying therapies are now available for Alzheimer’s disease (AD), accessible, accurate and affordable biomarkers to support diagnosis are urgently needed. We sought to develop a mass spectrometry-based urine test as a high-throughput screening tool for diagnosing AD. We collected urine from a discovery cohort (n = 11) of well-characterised individuals with AD (n = 6) and their asymptomatic, CSF biomarker-negative study partners (n = 5) and used untargeted proteomics for biomarker discovery. Protein biomarkers identified were taken forward to develop a high-throughput, multiplexed and targeted proteomic assay which was tested on an independent cohort (n = 21). The panel of proteins identified are known to be involved in AD pathogenesis. In comparing AD and controls, a panel of proteins including MIEN1, TNFB, VCAM1, REG1B and ABCA7 had a classification accuracy of 86%. These proteins have been previously implicated in AD pathogenesis. This suggests that urine-targeted mass spectrometry has potential utility as a diagnostic screening tool in AD. MDPI 2023-09-06 /pmc/articles/PMC10531486/ /pubmed/37762058 http://dx.doi.org/10.3390/ijms241813758 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hällqvist, Jenny
Pinto, Rui C.
Heywood, Wendy E.
Cordey, Jonjo
Foulkes, Alexander J. M.
Slattery, Catherine F.
Leckey, Claire A.
Murphy, Eimear C.
Zetterberg, Henrik
Schott, Jonathan M.
Mills, Kevin
Paterson, Ross W.
A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer’s Disease Diagnosis Using Targeted Proteomics and Machine Learning
title A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer’s Disease Diagnosis Using Targeted Proteomics and Machine Learning
title_full A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer’s Disease Diagnosis Using Targeted Proteomics and Machine Learning
title_fullStr A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer’s Disease Diagnosis Using Targeted Proteomics and Machine Learning
title_full_unstemmed A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer’s Disease Diagnosis Using Targeted Proteomics and Machine Learning
title_short A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer’s Disease Diagnosis Using Targeted Proteomics and Machine Learning
title_sort multiplexed urinary biomarker panel has potential for alzheimer’s disease diagnosis using targeted proteomics and machine learning
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10531486/
https://www.ncbi.nlm.nih.gov/pubmed/37762058
http://dx.doi.org/10.3390/ijms241813758
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