ArticleFrontiers in aging neuroscience2023
Urinary protein biomarkers based on LC-MS/MS analysis to discriminate vascular dementia from Alzheimer's disease in Han Chinese population.
Article in Frontiers in aging neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 9 citations in OpenAlex.
- Identification of molecular subtypes of dementia by using blood-proteins interaction-aware graph propagational network.Briefings in bioinformatics · 2024Article
- Identification of novel diagnostic panel for mild cognitive impairment and Alzheimer's disease: findings based on urine proteomics and machine learning.Alzheimer's research & therapy · 2023Article
- A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning.International journal of molecular sciences · 2023Article
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aimed to identify the potential urine biomarkers of vascular dementia (VD) and unravel the disease-associated mechanisms by applying Liquid chromatography tandem-mass spectrometry (LC-MS/MS). Methods: LC-MS/MS proteomic analysis was applied to urine samples from 3 groups, including 14 patients with VD, 9 patients with AD, and 21 normal controls (NC). By searching the MS data by Proteome Discoverer software, analyzing the protein abundances qualitatively and quantitatively, comparing between groups, combining bioinformatics analysis using Gene Ontology (GO) and pathway crosstalk analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG), and literature searching, the differentially expressed proteins (DEPs) of VD can be comprehensively determined at last and were further quantified by receiver operating characteristic (ROC) curve methods. Results: The proteomic findings showed quantitative changes in patients with VD compared to patients with NC and AD groups; among 4,699 identified urine proteins, 939 and 1,147 proteins displayed quantitative changes unique to VD vs. NC and AD, respectively, including 484 overlapped common DEPs. Then, 10 unique proteins named in KEGG database (including PLOD3, SDCBP, SRC, GPRC5B, TSG101/STP22/VPS23, THY1/CD90, PLCD, CDH16, NARS/asnS, AGRN) were confirmed by a ROC curve method. Conclusion: Our results suggested that urine proteins enable detection of VD from AD and VC, which may provide an opportunity for intervention.
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