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. 2021 Nov 5:12:768966.
doi: 10.3389/fimmu.2021.768966. eCollection 2021.

Expression of Immune Related Genes and Possible Regulatory Mechanisms in Alzheimer's Disease

Yanjun Lu  1 , Ke Li  2 , Yu Hu  3 , Xiong Wang  1
Affiliations

Expression of Immune Related Genes and Possible Regulatory Mechanisms in Alzheimer's Disease

Yanjun Lu et al. Front Immunol. .

Abstract

Immune infiltration of peripheral natural killer (NK) cells in the brain has been observed in Alzheimer's disease (AD). Immunity-related genes (IRGs) play an essential role in immune infiltration; however, the expression of IRGs and possible regulatory mechanisms involved in AD remain unclear. The peripheral blood mononuclear cells (PBMCs) single-cell RNA (scRNA) sequencing data from patients with AD were analyzed and PBMCs obtained from the ImmPort database were screened for cluster marker genes. IRG activity was calculated using the AUCell package. A bulk sequencing dataset of AD brain tissues was analyzed to explore common IRGs between PBMCs and the brain. Relevant regulatory transcription factors (TFs) were identified from the Human TFDB database. The protein-protein interaction network of key TFs were generated using the STRING database. Eight clusters were identified, including memory CD4 T, NKT, NK, B, DC, CD8 T cells, and platelets. NK cells were significantly decreased in patients with AD, while CD4 T cells were increased. NK and DC cells exhibited the highest IRG activity. GO and KEGG analyses of the scRNA and bulk sequencing data showed that the DEGs focused on the immune response. Seventy common IRGs were found in both peripheral NK cells and the brain. Seventeen TFs were associated with IRG expression, and the PPI network indicated that STAT3, IRF1, and REL were the hub TFs. In conclusion, we propose that peripheral NK cells may infiltrate the brain and contribute to neuroinflammatory changes in AD through bioinformatic analysis of scRNA and bulk sequencing data. Moreover, STAT3 may be involved in the transcriptional regulation of IRGs in NK cells.

Keywords: Alzheimer’s disease; NK cells; immune infiltration; immunity related genes; single-cell sequencing.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
scRNA analysis of PBMCs in AD. (A) The genes (features), counts, and mitochondrial gene percentage of each sample. (B) Correlation between genes and counts in each sample. (C) HVGs were colored in red, and the top 10 HVGs were labeled. (D) PCs selection using JackStraw function. (E) Heatmap of top 10 DEGs in each cluster. The top 10 DEGs were labeled in yellow color.
Figure 2
Figure 2
Marker gene expression of each cluster. (A) tSNE projection of 24,679 cells from all PBMCs. Different cell types were colored with unique colors. (B) tSNE projection of AD and NC groups, respectively. NK cells were labeled with ellipse tag, which were decreased in AD group. (C) Dot plot of cell type marker genes. Cell specific marker genes were selected according to previous study by Sinha D (11). The color of dots represents average expression, and size of dots represents average percent of cells expressing selected gene. (D) Violin plot depicts distributions of cell type marker genes in each cluster using density curves. The width of each violin plot corresponds with the frequency of cells with relevant gene expression level. (E) Cluster distribution in each sample. (F) Cluster distribution in AD and NC group. The percent of NK cluster was decreased in PBMC of AD group. * means, P < 0.05 compared with NC group.
Figure 3
Figure 3
IRG scores of PBMC cell clusters in AD. (A) Score of 212 screened IRGs. The threshold was chosen as 0.26. (B) t-SNE plots of IRG score in all clusters. NK and DC cells express more genes and exhibit higher AUC values. (C) GO analysis of DEGs in NK cluster. The top 10 GOs include neutrophil mediated immunity (GO:0002446), neutrophil degranulation (GO:0043312), neutrophil activation involved in immune response (GO:0002283), antigen processing and presentation of exogenous peptide antigen via MHC class I (GO:0042590), antigen processing and presentation of exogenous peptide antigen via MHC class I, TAP-dependent (GO:0002479), cytokine-mediated signaling pathway (GO:0019221), aerobic electron transport chain (GO:0019646), mitochondrial ATP synthesis coupled electron transport (GO:0042775), Fc-gamma receptor signaling pathway (Go:0038094), and cellular protein modification process (GO:0006464). (D) KEGG of DEGs in NK cluster. The top 10 KEGGs include Parkinson disease, Prion disease, Amyotrophic lateral sclerosis, Pathways of neurodegeneration, Huntington disease, Pathogenic Escherichia infection, Shigellosis, Salmonella infection, Proteasome, and Alzheimer’s disease.
Figure 4
Figure 4
DEGs of AD brain from GSE33000 dataset. (A) Volcano plot of DEGs (|logFC| > 0.03 and adjusted P value < 0.05). Up-regulated genes were colored in red and down-regulated genes were colored in blue. (B) Heatmap of top 100 up and top 100 down DEGs of GSE33000. (C) GO of DEGs in GSE33000. The top 10 GOs include neutrophil activation involved in immune response (GO:0002283), neutrophil degranulation (GO:0043312), neutrophil mediated immunity (GO:0002446), regulation of mRNA catabolic process (GO:0061013), regulation of cellular ketone metabolic process (GO:0010565), aerobic electron transport chain (GO:0019646), cellular protein modification process (GO:0006464), regulation of potassium ion transmembrane transport (GO:1901379), mitochondrial ATP synthesis coupled electron transport (GO:0042775), and negative regulation of extrinsic apoptotic signaling pathway (GO:2001237). (D) KEGG of DEGs in GSE33000. The top 10 KEGGs include Pathways in cancer, Focal adhesion, Non-alcoholic fatty liver disease, MAPK signaling pathway, Human T-cell leukemia virus 1 infection, Dopaminergic synapse, Kaposi sarcoma-associated herpesvirus infection, Glutamatergic synapse, Retrograde endocannabinoid signaling, and PI3K-Akt signaling pathway.
Figure 5
Figure 5
Common IRGs and relevant regulatory transcription factors. (A) Venn plot showed IRGs of NK cluster from PBMC in GSE181279 and IRGs in DEGs of AD brains in GES33000. A total of 70 common IRGs were found in both PBMC NK cluster and AD brains. (B) Dot plot of top 40 common IRGs in PBMCs. The red arrow dictates NK cluster from PBMC in GSE181279. (C) Venn plot showed TFs in NK cluster from PBMC in GSE181279, Human TF database, and TFs in DEG of AD brains in GES33000. (D) The expression of common TFs in DEG of GES33000. Up-regulated TFs were colored in purple, and down-regulated TFs were colored in green. (E) The expression of common TFs in AD PBMCs. (F) The PPI network of the common TFs illustrated using STRING. STAT3 serves as a hub gene.
Figure 6
Figure 6
scRNA analysis of NK cells in AD brain. (A) tSNE projection of 3,250 cells from all NK cells isolated from brain of AD mice. (B) Cluster distribution in each sample. (C) Dot plot of NK related genes. (D) Violin plot of NK related genes. (E) Score plot of cluster annotation by singleR package. (F) tSNE projection of annotated clusters.
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