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<p>This study aimed to explore and identify novel genes and signaling pathways that contribute to the progression of dementia to improve prognosis. Next-generation sequencing (NGS) dataset (GSE153960) was screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were screened using the limma R bioconductor package. Then, the gene ontology (GO) and REACTOME pathway enrichment analyses were performed, and the protein–protein interaction (PPI) network and modules were constructed and analyzed. Then, miRNet database and NetworkAnalyst database were used to predict the microRNAs (miRNAs) and upstream transcriptional factors (TFs), Finally, validation of hub genes was performed by using empirical ROC curve receiver operating characteristic curve (ROC) analysis. There were 948 DEGs (475 upregulated and 873 downregulated) identified from 263 post-mortem tissue samples of dementia and 277 post-mortem tissue samples of normal controls. The GO and REACTOME pathway enrichment analyses of DEGs were mainly enriched in defense response, ion transport, neutrophil degranulation, and neuronal system. Top Ten hub genes (namely, CDK1, TOP2A, MAD2L1, RSL24D1, CDKN1A, NOTCH3, MYB, PWP2, WNT7B, and HSPA12B) were obtained via PPI network and module analysis result. The miRNAs-genes network showed that has-let-7&#xa0;g might play an important role in the common mechanisms between osteoporosis and atherosclerosis. The miRNA-hub regulatory gene network and TF-hub regulatory gene network showed that hsa-mir-1248, hsa-mir-6886-5p, MLLT1, and BCL11B might play an important role in the molecular mechanism of dementia. Analysis of NGS dataset and ROC analysis presents a successful approach to uncover the risk hub genes and prognostic markers of dementia. Our study identified four risk- and prognostic-related gene signatures, including CDK1, TOP2A, MAD2L1, RSL24D1, CDKN1A, NOTCH3, MYB, PWP2, WNT7B, and HSPA12B. These genes contribute a new perspective to improve the diagnostic, prognostic, and therapeutic outcomes of dementia.</p>

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Identification of Key Pathways and Genes in Dementia via Integrated Bioinformatics Analysis

  • 期刊论文

  • 发表日期：

    2025年8月11日

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  • Basavaraj Vastrad,
  • Chanabasayya Vastrad

摘要

This study aimed to explore and identify novel genes and signaling pathways that contribute to the progression of dementia to improve prognosis. Next-generation sequencing (NGS) dataset (GSE153960) was screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were screened using the limma R bioconductor package. Then, the gene ontology (GO) and REACTOME pathway enrichment analyses were performed, and the protein–protein interaction (PPI) network and modules were constructed and analyzed. Then, miRNet database and NetworkAnalyst database were used to predict the microRNAs (miRNAs) and upstream transcriptional factors (TFs), Finally, validation of hub genes was performed by using empirical ROC curve receiver operating characteristic curve (ROC) analysis. There were 948 DEGs (475 upregulated and 873 downregulated) identified from 263 post-mortem tissue samples of dementia and 277 post-mortem tissue samples of normal controls. The GO and REACTOME pathway enrichment analyses of DEGs were mainly enriched in defense response, ion transport, neutrophil degranulation, and neuronal system. Top Ten hub genes (namely, CDK1, TOP2A, MAD2L1, RSL24D1, CDKN1A, NOTCH3, MYB, PWP2, WNT7B, and HSPA12B) were obtained via PPI network and module analysis result. The miRNAs-genes network showed that has-let-7 g might play an important role in the common mechanisms between osteoporosis and atherosclerosis. The miRNA-hub regulatory gene network and TF-hub regulatory gene network showed that hsa-mir-1248, hsa-mir-6886-5p, MLLT1, and BCL11B might play an important role in the molecular mechanism of dementia. Analysis of NGS dataset and ROC analysis presents a successful approach to uncover the risk hub genes and prognostic markers of dementia. Our study identified four risk- and prognostic-related gene signatures, including CDK1, TOP2A, MAD2L1, RSL24D1, CDKN1A, NOTCH3, MYB, PWP2, WNT7B, and HSPA12B. These genes contribute a new perspective to improve the diagnostic, prognostic, and therapeutic outcomes of dementia.