Journal
CELLS
Volume 11, Issue 6, Pages -Publisher
MDPI
DOI: 10.3390/cells11060987
Keywords
Alzheimer's disease; GABAergic synapse pathway; retrograde endocannabinoid signaling; differentially expressed genes
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Funding
- Perpetual Hillcrest Foundation
- Macquarie University
- National Health and Medical Research Council (NHMRC) Australia
- Ophthalmic Research Institute of Australia (ORIA)
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Alzheimer's disease is a complex neurodegenerative disorder that affects millions of people worldwide. Ageing is a major risk factor associated with the disease. Through gene expression data analysis, pathways and genes related to the disease were identified, providing a foundation for further research on the pathogenesis of Alzheimer's disease and potential therapeutic and diagnostic targets.
Alzheimer's disease (AD) is one of the most complicated progressive neurodegenerative brain disorders, affecting millions of people around the world. Ageing remains one of the strongest risk factors associated with the disease and the increasing trend of the ageing population globally has significantly increased the pressure on healthcare systems worldwide. The pathogenesis of AD is being extensively investigated, yet several unknown key components remain. Therefore, we aimed to extract new knowledge from existing data. Ten gene expression datasets from different brain regions including the hippocampus, cerebellum, entorhinal, frontal and temporal cortices of 820 AD cases and 626 healthy controls were analyzed using the robust rank aggregation (RRA) method. Our results returned 1713 robust differentially expressed genes (DEGs) between five brain regions of AD cases and healthy controls. Subsequent analysis revealed pathways that were altered in each brain region, of which the GABAergic synapse pathway and the retrograde endocannabinoid signaling pathway were shared between all AD affected brain regions except the cerebellum, which is relatively less sensitive to the effects of AD. Furthermore, we obtained common robust DEGs between these two pathways and predicted three miRNAs as potential candidates targeting these genes; hsa-mir-17-5p, hsa-mir-106a-5p and hsa-mir-373-3p. Three transcription factors (TFs) were also identified as the potential upstream regulators of the robust DEGs; ELK-1, GATA1 and GATA2. Our results provide the foundation for further research investigating the role of these pathways in AD pathogenesis, and potential application of these miRNAs and TFs as therapeutic and diagnostic targets.
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