bioRxivBioinformaticsPreprint
Identification of Key Pathways and Genes in Dementia via Integrated Bioinformatics Analysis
Basavaraj Mallikarjunayya VastradiD, Chanabasayya Mallikarjunayya VastradiD
Abstract
To provide a better understanding of dementia at the molecular level, this study aimed to identify the genes and key pathways associated with dementia by using integrated bioinformatics analysis. Based on the expression profiling by high throughput sequencing dataset GSE153960 derived from the Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) between patients with dementia and healthy controls were identified. With DEGs, we performed a series of functional enrichment analyses. Then, a protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network was constructed, analyzed and visualized, with which the hub genes miRNAs and TFs nodes were screened out. Finally, validation of hub genes was performed by using receiver operating characteristic curve (ROC) analysis. A total of 948 DEGs were screened out, among which 475 genes were up regulated; while 473 were down regulated. Functional enrichment analyses indicated that DEGs were mainly involved in defense response, ion transport, neutrophil degranulation and neuronal system. The hub genes (CDK1, TOP2A, MAD2L1, RSL24D1, CDKN1A, NOTCH3, MYB, PWP2, WNT7B and HSPA12B) were identified from PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. We identified a series of key genes along with the pathways that were most closely related with dementia initiation and progression. Our results provide a more detailed molecular mechanism for the advancement of dementia, shedding light on the potential biomarkers and therapeutic targets.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 1
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Bioinformatics analyses of significant genes, related pathways and candidate prognostic biomarkers in Alzheimer disease
Basavaraj Mallikarjunayya Vastrad, Chanabasayya Mallikarjunayya Vastrad·bioRxiv·May 6, 2021
- Identification of candidate biomarkers and signaling pathways associated with Alzheimer's disease using bioinformatics analysis of next generation sequencing data
Basavaraj Mallikarjunayya Vastrad, Chanabasayya Mallikarjunayya Vastrad·bioRxiv·Dec 3, 2024
- Identification of key genes and signaling pathway in the pathogenesis of Huntington's disease via bioinformatics and next generation sequencing data analysis
Basavaraj Mallikarjunayya Vastrad, Chanabasayya Mallikarjunayya Vastrad·Egyptian Journal of Medical Human GeneticsPeer-reviewed·Mar 4, 2025
- Bioinformatics and next generation sequencing data analysis to identify key genes and pathways influencing in Parkinson's disease
Basavaraj Mallikarjunayya Vastrad, Chanabasayya Mallikarjunayya Vastrad·Genome Instability & DiseasePeer-reviewed·May 16, 2025
- Identification of candidate biomarkers and pathways associated with multiple sclerosis using bioinformatics and next generation sequencing data analysis
Basavaraj Mallikarjunayya Vastrad, Shivaling Pattanashetti, Chanabasayya Mallikarjunayya Vastrad·bioRxiv·Dec 5, 2023
- Dementia risk genes engage gene networks poised to tune the immune response towards chronic inflammatory states
Jessica E. Rexach, Vivek Swarup, … Daniel H. Geschwind·bioRxiv·Apr 4, 2019