<HashMap><database>panorama</database><scores/><additional><omics_type>Proteomics</omics_type><submitter>Jenny Hallqvist</submitter><species>Homo Sapiens</species><full_dataset_link>https://panoramaweb.org/AD_Urine_Proteomics.url</full_dataset_link><submitter_email>j.hallqvist@ucl.ac.uk</submitter_email><submitter_affiliation>Great Ormond Street Institute of Child Health, University College London</submitter_affiliation><sample_protocol></sample_protocol><repository>PanoramaPublic</repository><data_protocol></data_protocol><pubmed_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.</pubmed_abstract><pubmed_title>A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning.</pubmed_title><pubmed_authors>Hällqvist Jenny J, Pinto Rui C RC, Heywood Wendy E WE, Cordey Jonjo J, Foulkes Alexander J M AJM, Slattery Catherine F CF, Leckey Claire A CA, Murphy Eimear C EC, Zetterberg Henrik H, Schott Jonathan M JM, Mills Kevin K, Paterson Ross W RW</pubmed_authors></additional><is_claimable>false</is_claimable><name>A multiplexed urinary biomarker panel has potential for Alzheimer’s Disease Diagnosis using targeted proteomics and machine learning</name><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.</description><dates><publication>Mon May 04 00:00:00 BST 2026</publication></dates><accession>PXD044751</accession><cross_references><TAXONOMY>9606</TAXONOMY><pubmed>37762058</pubmed></cross_references></HashMap>