Chen Ruijuan, Yi Yuanjing, Xiao Wenbiao, Zhong Bowen, Zhang Le, Zeng Yi
Department of Geriatrics, Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Department of Emergency, Central South University Xiangya School of Medicine Affiliated Haikou Hospital, Haikou, Hainan, China.
Front Aging Neurosci. 2023 Jan 25;15:1070854. doi: 10.3389/fnagi.2023.1070854. eCollection 2023.
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).
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.
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.
Our results suggested that urine proteins enable detection of VD from AD and VC, which may provide an opportunity for intervention.
本研究旨在通过液相色谱串联质谱法（LC-MS/MS）鉴定血管性痴呆（VD）潜在的尿液生物标志物，并阐明其疾病相关机制。
对3组尿液样本进行LC-MS/MS蛋白质组学分析，包括14例VD患者、9例阿尔茨海默病（AD）患者和21例正常对照（NC）。通过Proteome Discoverer软件搜索质谱数据，定性和定量分析蛋白质丰度，进行组间比较，结合使用基因本体论（GO）的生物信息学分析和使用京都基因与基因组百科全书（KEGG）的通路串扰分析，并进行文献检索，最终可全面确定VD的差异表达蛋白（DEP），并通过受试者工作特征（ROC）曲线方法进一步定量分析。
蛋白质组学研究结果显示，与NC组和AD组患者相比，VD患者存在定量变化；在鉴定出的4699种尿液蛋白质中，分别有939种和1147种蛋白质在VD与NC组和AD组比较时显示出独特的定量变化，其中包括484种重叠的常见DEP。然后，通过ROC曲线方法确认了KEGG数据库中命名的10种独特蛋白质（包括PLOD3、SDCBP、SRC、GPRC5B、TSG101/STP22/VPS23、THY1/CD90、PLCD、CDH16、NARS/asnS、AGRN）。
我们的结果表明，尿液蛋白质能够区分VD与AD和VC，这可能为干预提供机会。
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