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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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. |
format | Online Article Text |
id | pubmed-10531486 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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