Identification of pivotal markers in vascular dementia based on proteomics data

The aim of this study was to analyze protein expression profiles of vascular dementia (VaD) subjects for investigating the underlying therapeutic markers.

Protein expression profile data were acquired from a quantitative clinical proteomic study, including 10 nondemented elderly controls and 10 age-matched VaD subjects. Differentially expressed proteins (DEPs) were identified between VaD subjects and controls, followed by function prediction using DAVID (Database for Annotation, Visualization, and Integrated Discovery). Then, a protein-protein interaction (PPI) network was constructed by comparing it with the STRING (Search Tool for the Retrieval of Interacting Genes) database, and the pathway crosstalk analysis was conducted based on overlapping PPI network and enriched pathways. Furthermore, the subpathway was screened and analyzed by the iSubpathwayMiner package in R.

A total of 144 DEPs were screened from VaD subjects and the controls. They were significantly enriched in many pathways. High-degree proteins were detected in the PPI network, such as ATP5B (ATP synthase subunit β). Furthermore, 'metabolic pathways' and 'Alzheimer's disease' were the significant pathways screened in the crosstalk analysis. At last, upregulated proteins were enriched in 2 subpathways of 1 pathway, while downregulated proteins were enriched in 162 subpathways of 36 pathways.

By analyzing the differential expressions of proteins, the potential underlying therapeutic markers and mechanism of VaD might be elucidated.