Abstract
Alzheimer's disease (AD) a complex neurodegenerative disorder and the most common cause of dementia in older people. Recently computational approaches have been integrated with genomics to discover novel genes involved in pathogenesis as well as to understand their mechanism. In this study we analyzed RNA-Seq data from different brain regions of AD patients and compared them with healthy individuals. Quantitative analysis of AD and control samples helped to find out differentially expressed genes (DEGs). Gene enrichment and pathway analysis were also performed to explore additional knowledge about DEGs. Study about protein-protein interaction/gene interaction, hub genes and modules helped in identifying crucial genes. It was revealed that ACKR3, CXCR4, DACH1, CDC6, GMNC, PELI2, DPP4, HSPA1L and PCGF genes were downregulated while CHRM5, CYSTLTR2, DRD5, HTR2C, PTGFR, TACR3, TRHR, MAS1, CARTPTs, DDX3Y, KDMD5, SST, GALR1, NOV, SERPINE1, HLA-B, TRIM26, and BAG-6 genes were found to be upregulated in case of AD. Network analysis of DEGs helped in understanding key pathways involved in AD disease. The analytics revealed a connection between upregulated GPCRs, presence of Aβ granules and formation of Neurofibrillary tangles. It also provides a basis of identification of novel markers and therapeutic targets for Alzheimer's disease.
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