Identification and prediction of molecular factors associated with ischemic stroke: an integrative analysis of DEGs, TFs, and PPI networks

Abstract

Ischemic stroke (IS) is a complex neurological disorder characterized by the sudden disruption of blood flow to the brain, leading to severe and often irreversible damage. Despite advances in stroke management, the underlying molecular mechanisms and key factors involved in the development and progression of IS remain elusive. In recent years, the integration of high-throughput data analysis techniques has emerged as a powerful approach to unraveling the molecular intricacies of complex diseases. In this study, we comprehensively analyzed gene expression, protein-protein interactions (PPI), and gene regulatory networks to identify IS-associated molecular factors. We utilized publicly available datasets and employed bioinformatics tools to analyze the data. Our analysis revealed many differentially expressed genes (DEGs) in IS, with a predominant down-regulation of genes. Gene ontology (GO) analysis highlighted the involvement of various biological processes, including transcriptional regulation, cell cycle, immune system processes, and cell differentiation. These findings underscore the complexity of stroke pathology, involving dysregulated gene expression and disrupted cellular processes. Constructing PPI networks enabled us to identify specific subnetworks associated with critical biological processes relevant to stroke, such as nucleosome assembly, protein translation, glycosylation, protein folding, and mRNA splicing. These subnetworks provide insights into the dysregulated molecular mechanisms contributing to stroke progression. Furthermore, we focused on identifying differentially expressed transcription factors (DE-TFs) within the gene regulatory network. Several up-regulated DE-TFs, including E2F1, MYB, GFI1B, and NUCKS1, were identified, suggesting their potential involvement in the dysregulation of gene expression in IS.

Keywords: Gene expression; Gene regulatory networks; Ischemic stroke; Protein–protein interactions; Transcription factors.

Fig. 1

Gene ontology of the DEGs. The leading biological processes (BP) and KEGG related to a the top ten of BP, b the top ten of KEGG, c the top five of up-regulated DEGs BP, and d the top five of down-regulated DEGs BP are displayed. The number below the diagram indicates the number of genes involved in the process as a percentage of the total number of genes, and the number in front of the column indicates the number of genes involved in the process

Fig. 2

Gene ontology (GO) and DEGs. a Common genes among different biological processes. b Common genes among different KEGG

Fig. 3

Displays protein–protein interaction (PPI) networks with module annotations. The modules, identified through overlapping neighborhood expansion, are represented by colored nodes. The corresponding annotations for the modules are provided in the tables, with modules having p-values less than 0.05 being selected. In the network, modules are indicated by the color of the nodes. Larger-sized nodes indicate a higher degree of connectivity

Fig. 4

Gene regulatory networks. The node colors in red and blue are used to indicate up- and down-regulation, respectively. a IS TF network. b IS DE-TF network. TFs are transcription factors