3.1 Identification of DEGs in AD and SZ
After normalization, the mean gene expression values for each sample in AD and SZ were fundamental equal. By limma package (Version 3.26.9),2281 DEGs, including 601 upregulated and 1680 downregulated DEGs, were identified in GSE58793 (SZ)(Figure.1.a). While in GSE5281 (AD) 2769 DEGs, including 1437 upregulated and 1332 downregulated DEGs, were identified(Figure.1.b). Then we mapped these top 50 differentially expressed genes into heatmaps to assess the differences in expression between disease group and control group (Figure.1.c). As shown in (Figure.1.d), 613 overlapping of DEGs were found in SZ and AD, including 222 co-upregulated DEGs and 391 co-downregulated DEGs.
3.2. Functional annotation of DEGs
Then we explore the potentially altered functional characteristics associated with the DEGs in AD and SCZ, and Gene Ontology (GO) analysis was carried out for the differences in the biological processes between the disease group and the control group in AD and SCZ respectively.
In AD, genes upregulated in the disease group were major involved in protein modification, including regulation of chromatin organization, positive regulation of histone deacetylation, regulation of histone modification, and positive regulation of protein deacetylation. In contrast, downregulated genes in the AD disease group were tiedly related to metabolic process, including ATP metabolic process, cellular respiration, RNA catabolic process and regulation of mRNA metabolic/cellular amino acid metabolic process. Moreover, most of the positively related genes were enriched in KEGG terms including long-term depression, long-term potentiation. And the negatively correlated genes were enriched within the citrate cycle (TCA cycle), biosynthesis of amino acids, and amyotrophic lateral sclerosis. Next, validation was carried out by GSEA analyses, showing highly expressed genes that were significantly associated with long-term depression and estrogen signaling pathway, long-term potentiation, dopaminergic synapse, and Amoebiasis. The low expression gene group was significantly associated with oxidative phosphorylation, Huntington disease, proteasome, Parkinson disease, carbon metabolism, metabolic pathways, and Amyotrophic lateral sclerosis.
In SCZ, genes upregulated and downregulated in the GO terms and the KEGG pathways are shown as Fig. 3. Our GSEA analysis results indicated that the low expression genes were distinctly enriched in pathways of neurodegeneration disease, including AD, prion disease, Huntington disease(HD), Amyotrophic lateral sclerosis(ALS).
Further, we conducted the KEGG pathway and GO enrichment analysis of the 222 co-upregulated and 391 co-downregulated DEGs to study the functions of the 613 overlapping genes. And 222 overlapping co-upregulated genes within the biological processes (BP) were found closely related to the regulation of chromatin organization, positive regulation of histone deacetylation, regulation of histone modification, positive regulation of protein deacetylation, and regulation of protein-containing complex assembly. (Table 1) (Figure.2a). The BP of the 391 co-downregulated DEGs was primarily related to the regulation and activation of the innate immune response, ATP metabolic process, anaphase-promoting complex-dependent catabolic process, antigen processing and presentation of exogenous peptide antigen and regulation of stem cell differentiation. (Table 2) (Figure.2b). Moreover, in the KEGG pathway enrichment analysis, positively related co-DEGs were enriched within the MAPK signaling,cancer and the mTOR signaling pathways (Figure.2.c), while the negatively correlated genes were enriched within pathways of multiple neurodegeneration disease, AD,HD, ALS included(Table 3) (Figure.2d).
3.3 PPI Network Construction and Hub Genes Identification
Overlapping genes were analyzed by PPI network, 222 co-upregulated DEGs and 391 co-downregulated DEGs were established using the STRING database. In PPI networks, hub genes were defined as genes with stronger interactions with numerous other genes. And hub genes are potential drivers of the pathology of the diseases. In order to screen hub genes among all the DEGs via the MCC scores, cytoHubba plugin for Cytoscape was used. Interestingly, all these 10 hub genes got from screening were downregulated co-DEGs (Figure.3). And proteasome subunit alpha 5 (PSMA5), proteasome subunit beta 7 (PSMB7), proteasome 26S subunit, non-ATPase 12 (PSMD12), proteasome subunit alpha 1 (PSMA1), proteasome 26S subunit, ATPase 3 (PSMC3), proteasome 26S subunit, non-ATPase 4 (PSMD4), proteasome subunit beta 3 (PSMB3), proteasome subunit beta 1 (PSMB1), proteasome 26S subunit, non-ATPase 1 (PSMD1), and proteasome subunit alpha 7 (PSMA7) are the top 10 genes with the highest MCC sores, respectively .
3.4 GO Enrichment Analysis of the hub genes
All ten hub genes are downregulated DEGs both in SCZ and AD. Using the R package clusterprofiler. And among those genes, the top 10 GO terms were primarily related to the regulation of hematopoietic stem cell differentiation, regulation of cellular amino acid metabolic process, TAP-dependent,antigen processing and presentation of exogenous peptide antigen via MHC class I, antigen processing and presentation of exogenous peptide antigen via MHC class I, regulation of cellular amine metabolic process, regulation of transcription from RNA polymerase II promoter in response to hypoxia, anaphase-promoting complex-dependent catabolic process, regulation of hematopoietic progenitor cell or stem cell differentiation, and SCF-dependent proteasomal ubiquitin-dependent protein catabolic process. (Figure.4) (Table 4).