Heliyon (Feb 2024)

Identification of immune-associated genes in vascular dementia by integrated bioinformatics and inflammatory infiltrates

  • Fangchao Wu,
  • Junling Zhang,
  • Qian Wang,
  • Wenxin Liu,
  • Xinlei Zhang,
  • Fangli Ning,
  • Mengmeng Cui,
  • Lei Qin,
  • Guohua Zhao,
  • Di Liu,
  • Shi Lv,
  • Yuzhen Xu

Journal volume & issue
Vol. 10, no. 4
p. e26304

Abstract

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Objective: Dysregulation of the immune system plays a vital role in the pathological process of vascular dementia, and this study aims to spot critical biomarkers and immune infiltrations in vascular dementia employing a bioinformatics approach. Methods: We acquired gene expression profiles from the Gene Expression Database. The gene expression data were analyzed using the bioinformatics method to identify candidate immune-related central genes for the diagnosis of vascular dementia. and the diagnostic value of nomograms and Receiver Operating Characteristic (ROC) curves were evaluated. We also examined the role of the VaD hub genes. Using the database and potential therapeutic drugs, we predicted the miRNA and lncRNA controlling the Hub genes. Immune cell infiltration was initiated to examine immune cell dysregulation in vascular dementia. Results: 1321 immune genes were included in the combined immune dataset, and 2816 DEGs were examined in GSE122063. Twenty potential genes were found using differential gene analysis and co-expression network analysis. PPI network design and functional enrichment analysis were also done using the immune system as the main subject. To create the nomogram for evaluating the diagnostic value, four potential core genes were chosen by machine learning. All four putative center genes and nomograms have a solid diagnostic value (AUC ranged from 0.81 to 0.92). Their high confidence level became unquestionable by validating each of the four biomarkers using a different dataset. According to GeneMANIA and GSEA enrichment investigations, the pathophysiology of VaD is strongly related to inflammatory responses, drug reactions, and central nervous system degeneration. The data and Hub genes were used to construct a ceRNA network that includes three miRNAs, 90 lncRNA, and potential VaD therapeutics. Immune cells with varying dysregulation were also found. Conclusion: Using bioinformatic techniques, our research identified four immune-related candidate core genes (HMOX1, EBI3, CYBB, and CCR5). Our study confirms the role of these Hub genes in the onset and progression of VaD at the level of immune infiltration. It predicts potential RNA regulatory pathways control VaD progression, which may provide ideas for treating clinical disease.

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