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. 2022 Mar 14;11(6):987.
doi: 10.3390/cells11060987.

Key Genes and Biochemical Networks in Various Brain Regions Affected in Alzheimer's Disease

Morteza Abyadeh  1   2 , Nahid Tofigh  2 , Saeedeh Hosseinian  3 , Mafruha Hasan  4 , Ardeshir Amirkhani  5 , Matthew J Fitzhenry  5 , Veer Gupta  6 , Nitin Chitranshi  7 , Ghasem H Salekdeh  8 , Paul A Haynes  8   9 , Vivek Gupta  7 , Koorosh Shahpasand  2 , Mehdi Mirzaei  7
Affiliations

Key Genes and Biochemical Networks in Various Brain Regions Affected in Alzheimer's Disease

Morteza Abyadeh et al. Cells. .

Abstract

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.

Keywords: Alzheimer’s disease; GABAergic synapse pathway; differentially expressed genes; retrograde endocannabinoid signaling.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(A) Number of down and up-regulated robust genes in each brain region; (B) upset plot indicates the overlap of robust differentially expressed genes with either increased or decreased abundance in different brain regions; DEGs, differentially expressed genes; CB, cerebellum; FC, frontal cortex; HPC, hippocampus; EC, entorhinal cortex; TC, temporal cortex.
Figure 2
Figure 2
Venn diagram of KEGG pathway enrichment analysis on (A) Up-regulated and (B) Down-regulated pathways based on adjusted p-value. TC, temporal cortex; FC, frontal cortex; EC, entorhinal cortex; HPC, hippocampus; CB, cerebellum.
Figure 3
Figure 3
Functional interaction networks analyzed by the String Cytoscape plug-in. (A) PPI network of genes related to GABAergic synapse pathway (red), retrograde endocannabinoid signaling (green), morphine (blue) and nicotine (orange). (B) In addiction, PRKACB (red), PRKCB (orange) and GABRA1 (yellow) found the top hub genes based on the MCC algorithm.
Figure 4
Figure 4
Transcription factors and miRNAs analyses. (A,B) results represent Venn diagram analysis for the top five miRNAs and the three TFs that interact with the robust DEGs of the GABAergic synapse pathway. (C,D) show Venn diagram analysis and the top five miRNAs and the TFs interacting with the robust DEGs involved in retrograde endocannabinoid signaling.
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