3.1 Identification of Differentially Expressed Genes (DEGs)
In the cerebral cortex tissue, 2598 DEGs were screened, including 2362 up-regulated DEGs and 236 down-regulated DEGs. In the blood, 1442 DEGs were screened, including 540 up-regulated DEGs and 902 down-regulated DEGs. The volcano map in Figure 1A-B displays the general distribution of these genes, and expression of the top 30 up-regulation DEGs and the top 30 down-regulation DEGs of two kinds of samples were showed in the heatmap in Figure 1C-D.
3.2 GO Term Enrichment Analysis and KEGG Pathway Analysis
We applied the DAVID online tool and the KOBAS online tool to cluster the GO protein function and the KEGG signal pathway of the DEGs of HIBD. As shown in GO analysis results (Figure 2A-B,only the top 30 items of gene enrichment were shown), DEGs in cerebral cortex tissue cell samples were mainly enriched in biological processes such as cell signal transduction, transcription regulation, redox response, inflammatory response, immune response, cell proliferation, cell apoptosis, drug response and multicellular biological development; DEGs in blood samples were mainly enriched in biological processes such as redox reaction, inflammation, angiogenesis, multicellular biological development, cell morphology regulation, transmembrane transport, positive regulation of the MAPK cascade, and positive regulation of the Notch signaling pathway. KEGG enrichment results showed(Figure 2C-D, only showing the top 30 items of gene enrichment): DEGs in cerebral cortex tissue cell samples were mainly in metabolic signaling pathways, cancer pathways, cytokine-cytokine receptor interactions, PI3K-Akt signaling pathway,neural active ligand-receptor interaction pathway, MAPK signaling pathway,Rap1 signaling pathway,chemokine signaling pathway, and infection-related signaling pathways; DEGs in blood samples were mainly enriched in metabolic signaling pathways, cancer pathways, neuroactive ligand-receptor interaction pathways, PI3K-Akt signaling pathways, endocytosis, Rap signaling pathways, calcium signaling pathways, and infection-related signaling pathways. Other results are in the supplementary materials
In general, the enrichment results of GO and KEGG of DEGs in the cerebral cortex tissue and DEGs in whole blood are related to hypoxic-ischemic brain injury, and both involve inflammation, immunity and apoptosis.
3.3 Common DEGs identified in the cerebral cortex tissue and blood of HIBD cases
There were 86 genes overlapping between DEGs in the cerebral cortex tissue with HIBD and DEGs in whole blood with HIBD. As shown in Figure 3, these 86 common DEGs included 67 up-regulation and 19 down-regulation.The biological processes that these common DEGs mainly involved inflammation and immunity (Figure 4A, only showing the top 15 items in terms of gene enrichment), including participation in neutrophils, macrophage-mediated inflammation, platelet activation, inflammatory cells activation,participates in immune response, regulation of lymphocyte differentiation. Cross-examination of common DEGs and GO biological process terms showed (Figure 4B) that some genes related to inflammation were also enriched in immune-related biological processes, indicating that these genes may be related to the inflammation-immune damage mechanism in HIBD.The enrichment results of cellular components and molecular functions (Figure 4C) showed that the cellular components of common DEGs were mainly enriched in plasma membrane, extracellular body, cytoskeleton, extracellular zone, cell surface, extracellular space, and oscillating cilia; molecular functions mainly included binding to phosphotyrosine, phosphatase, interleukin-1, serine endopeptidase activity, phospholipase D activity, interleukin-1 receptor activity. Similarly, common DEGs were significantly enriched in the KEGG pathway (Figure 4D, showing the signal pathway with FDR<0.05), mainly involving microbial infection, natural killer cell-mediated cytotoxicity, osteoclast differentiation, cancer pathway, FcεRI signaling pathways, complement and coagulation cascade pathways, hematopoietic cell spectrum, neuroactive ligand receptor interaction, Rap1 signaling pathway.
3.4 Construction of protein-protein interaction (PPI) network, identification of central genes and key modules
PPI network of 86 common DEGs was constructed(Figure 5A) , including 50 nodes and 89 edges. Network topology analysis was applied to arrange the nodes according to the degree of connection. The larger the Degree, the larger the dot.Then, according to the 5 centrality methods (Figure 5B), We determined 10 common genes (ITGAM, SYK, PLD1, KLRD1, NCKAP1L, EGR1, MAPK3, TYROBP, HMOX1, IL1R1) among the first 20 nodes as central genes. Then we performed subnet module analysis (filter criteria: Degree Cutoff=3, node score=0.2, K-core=2, Max Depth=100). Two key modules were obtained (Cluster1=3.70, Cluster2=2.80) (Figure 5C-D), and they contained 8 DEGs, which contained 4 central genes (red).DAVID and KOBAS databases were used for the enrichment analysis of GO and KEGG pathways for 8 DEGs in these two modules.The results showed (Table 2.): The GO-BP of these two modules GO mainly involved integrin-mediated signaling pathways, positive regulation of chemokine biosynthesis, and response to hypoxia;The results of KEGG mainly involved HIF-1 signaling pathway, hepatocellular carcinoma, Rap1 signaling pathway, neomycin, kanamycin and gentamicin biosynthesis, galactose metabolism, etc.
3.5 Validation of key central genes and determination of hematologic/immune system tissue-specific biomarker genes
Using Genecards database to identify 10 central genes, it was found that 7 central genes may be related to HIBD, and no related reports were found for the other 3 genes.Intersecting these 7 genes with the genes of 2 modules to get 4 genes. It was confirmed in the Biogps database that all 4 genes were clearly expressed in the hematologic/immune system, and these genes were defined as HIBD hematologic/immune system tissue specificity potential biomarkers (Table 3).In this study, 32 samples in the GSE12137 data set (hypoxia model of early cortical progenitor cells) were used to verify 4 potential biomarkers, and it was found that two potential biomarkers were significantly up-regulated.The box plots of the two genes (Figure 6A-B) were clearly differentially expressed in the hypoxia model of cortical progenitors cells; the ROC curve (Figure 6C-D) showed that the two genes have good performance in identifying cases and controls(AUCEGR1=0.8398,AUCHMOX1=0.9063).In addition, a literature search was conducted on ITGAM and TYROBP that have not been verified by the data set, and related studies (qt-PCR test) showed that ITGAM and TYROBP were significantly expressed in the brain tissue of the hypoxic-ischemic brain injury model[25].This study believed that these 4 genes may be specific potential biomarker genes for the diagnosis of hematologic/immune system in HIBD.Especially, EGR1 and HMOX1 may have a diagnostic effect on early HIBD
3.6 Prediction of transcription factors and miRNAs of key central genes
According to the comprehensive ranking of multiple sub-databases in the CHEPA3 database, the top 10 potential transcription factors with higher scores are selected to construct an interaction network (Figure 7A).In the mirDIP database, we set the credibility parameter to very high, and obtained at least 88 miRNAs predicted by 7 sub-databases (Figure 7B).9 key transcription factors (TFEC, SPI1, CEBPE, HLX, ZNF438, ZNF641, CEBPB, ELF4, LYL1) and 3 key miRNAs (hsa-miR-218-5p, hsa-miR-217, hsa-miR-377-3p) were screened according to the topoisomeric method,and their interactive network may be a potential key regulatory pathway in the pathogenesis of HIBD.