Hällqvist, Jenny;
Pinto, Rui C;
Heywood, Wendy E;
Cordey, Jonjo;
Foulkes, Alexander JM;
Slattery, Catherine F;
Leckey, Claire A;
... Paterson, Ross W; + view all
(2023)
A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer’s Disease Diagnosis Using Targeted Proteomics and Machine Learning.
International Journal of Molecular Sciences
, 24
(18)
, Article 13758. 10.3390/ijms241813758.
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Abstract
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.
| Type: | Article |
|---|---|
| Title: | A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer’s Disease Diagnosis Using Targeted Proteomics and Machine Learning |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3390/ijms241813758 |
| Publisher version: | https://doi.org/10.3390/ijms241813758 |
| Language: | English |
| Additional information: | Copyright: © 2023 by the authors. 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/). |
| Keywords: | Alzheimer’s; urine; machine learning; biomarkers; proteomics; mass spectrometry; diagnosis |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Genetics and Genomic Medicine Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10177374 |
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