Integrative bioinformatics analysis of transcriptomic data sheds light on the molecular complexity of parkinson's disease and potential therapeutic targets

Qudsia Yousafi, Sawaira Asghar, Misbah Shaukat

Abstract


Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects millions of individuals worldwide, with an increasing prevalence in aging populations. In this study, we retrieved the mRNA expression dataset, GSE165082, for PD through GEOmnibus. Total of 220 downregulated and 354 upregulated genes were identified after data normalization. Functional annotation carried out by DAVID tools, revealed that these DEGs were mainly enriched in biological processes i.e., cell division and protein phosphorylation, and they were localized mostly cytoplasm and nucleus. Two molecular function protein binding and ATP binding were predominant.  Additionally KEGG pathway analysis highlighted their involvement in neurodegenerative, cancer, alzheimer's and coronavirus diseases. Armadillo-type fold and Armadillo-like helical domains were found by INTERPRO while TKc domain by SMART. Transcription factors IRF1 was predicted by FunRich tool. Upregulated genes were found expressed in 6 sites i.e., Palate, Ventral striatum, Pluripotent stem cells, Ganglia, Curtilage and Ciliary muscle. A protein-protein interaction network was constructed by using Cytoscape v 6.0. Ten hub genes EFI3A, RPL28, SMG8. UPF2, XAF1, IFITM1, IFIT3, LY63, IFI3 and LY6B were identified by Cytohubba. The expression patterns of hub genes across different organs and immune response cells using a heatmap and expression of EIF3 was found in almost all organs except liver. MicroRNA for were predicted by FunRich tool. Finally, we predicted microRNAs for RPL28, SMG8, UPF2 and EIF3a that could potentially regulate these hub genes, providing insights into post-transcriptional gene regulation. This comprehensive analysis contributes to our understanding of the molecular mechanisms underlying Parkinson's disease and provides a foundation for future research and therapeutic development in this complex and challenging condition.


Keywords


miRNA, gene ontology, hub genes, heat map, IRF1

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References


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DOI: https://doi.org/10.33865/wjb.009.01.1161

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