Identifying MS4A6A+ macrophages as potential contributors to the pathogenesis of nonalcoholic fatty liver disease, periodontitis, and type 2 diabetes mellitus

Abstract

Purpose: Concrete epidemiological evidence has suggested the mutually-contributing effect respectively between nonalcoholic fatty liver disease (NAFLD), type 2 diabetes mellitus (T2DM), and periodontitis (PD); however, their shared crosstalk mechanism remains an open issue.

Method: The NAFLD, PD, and T2DM-related datasets were obtained from the NCBI GEO repository. Their common differentially expressed genes (DEGs) were identified and the functional enrichment analysis performed by the DAVID platform determined relevant biological processes and pathways. Then, the STRING database established a PPI network of such DEGs and topological analysis through Cytoscape 3.7.1 software along with the machine-learning analysis by the least absolute shrinkage and selection operator (LASSO) algorithm screened out hub characteristic genes. Their efficacy was validated by external datasets using the receiver operating characteristic (ROC) curve, and gene expression and location of the most robust one was determined using single-cell sequencing and immunohistochemical staining. Finally, the promising drugs were predicted through the CTD database, and the CB-DOCK 2 and Pymol platform mimicked molecular docking.

Result: Intersection of differentially expressed genes from three datasets identified 25 shared DEGs of the three diseases, which were enriched in MHC II-mediated antigen presenting process. PPI network and LASSO machine-learning analysis determined 4 feature genes, of which the MS4A6A gene mainly expressed by macrophages was the hub gene and key immune cell type. Molecular docking simulation chosen fenretinide as the most promising medicant for MS4A6A⁺ macrophages.

Conclusion: MS4A6A⁺ macrophages were suggested to be important immune-related mediators in the progression of NAFLD, PD, and T2DM pathologies.

Keywords: MS4A6A gene; Macrophages; Nonalcoholic fatty liver disease; Periodontitis; Type 2 diabetes mellitus.

Fig. 1

The flowchart of the study design *PD, periodontitis; NAFLD, nonalcoholic fatty liver disease; T2DM, type 2 diabetes mellitus; DEGs, differentially expressed genes; LASSO, least absolute shrinkage and selection operator; ROC, receiver operating characteristic curve.

Fig. 2

Identification of DEGs in PD, NAFLD, and T2DM-related datasets (A) Gene expression profiles in NAFLD-related GSE63067 and GSE164760 datasets. (B) Gene expression profiles in PD-related GSE10334 and GSE16134 datasets. (C) Gene expression profiles in T2DM-related GSE76894 and GSE76895 datasets. (D) Heatmaps showing the top fifty DEGs in the GSE63067 and GSE164760 datasets. (E) Heatmaps of the top fifty DEGs in the GSE10334 and GSE16134 datasets. (F) The heatmaps of the top fifty DEGs in the GSE76894 and GSE776895 datasets. (G) A Venn diagram showing 20 shared upregulated DEGs by GSE76895, GSE10334, and GSE164760 datasets. (H) A Venny diagram exhibiting 5 shared downregulated DEGs by GSE76895, GSE10334, and GSE164760 datasets. In A-C, the X-axis refers to log₂ |Foldchange| and the Y-axis represents -log₁₀(p value). The blue and red dots represent downregulated and upregulated DEGs, respectively. In D-F, the diagrams showing the results of a Two-way hierarchical clustering of all samples and the top fifty DEGs in each dataset. PD, periodontitis; NAFLD, nonalcoholic fatty liver disease; T2DM, type 2 diabetes mellitus; DEGs, differentially expressed genes.

Fig. 3

Functional enrichment analysis of these DEGs (A) DO analysis results of the 25 shared DEGs. (B) GO analysis results of the 25 shared DEGs, including terms of biological process (BP), molecular function (MF) and cellular component (CC). (C) The enriched GO terms of BP, CC, and MF, as shown in the circular diagram. (D) The KEGG and REACTOME pathway enrichment analyses results. (E) The PPI network of 25 shared DEGs built by the STRING database, which displayed the connections between 13 genes, with the threshold set as > 0.400 (F) The Circos track plot showing the locations of the hub module genes on chromosomes. (G) The correlations of the 13 genes in PD, NAFLD, and T2DM. The blue color indicates a positive correlation and the red color indicates the opposite. DEGs, differentially expressed genes; PD, periodontitis; NAFLD, nonalcoholic fatty liver disease; T2DM, type 2 diabetes mellitus.

Fig. 4

Identifying hub feature genes via the LASSO machine-learning algorithm (A) Hub modules of the PPI network selected by the cytoNCA and MCC algorithm of the cytoHubba plugins of Cytoscape software 3.7.1. Both modules contain the same 10 genes. (B) Predictions of gene expression locations of the 13 genes in the PPI network. Red indicates the expression by antigen-presenting cells; Blue refers to expression by bone marrow; Green indicates expression by the spleen. (C) Identification of the key feature genes of PD, NAFLD, and T2DM by the LASSO machine-learning algorithm. (D) Boxplots comparing the expression levels of these 4 preliminarily identified hub feature genes shared by PD, NAFLD, and T2DM, which showed lower expression levels of these 4 genes in pathologies in comparison to in healthy status. PD, periodontitis; NAFLD, nonalcoholic fatty liver disease; T2DM, type 2 diabetes mellitus; LASSO, least absolute shrinkage and selection operator.

Fig. 5

Validation of the efficacy of 4 hub feature genes (A) The ROC curves showing the diagnostic efficacy of these 4 genes in GSE164760, GSE10334, and GSE76895 datasets. (B) The ROC curves and violin plots showing the diagnostic efficacy and the expression level of the hub feature genes in GSE63067, GSE16134, and GSE76894 datasets, except for the CYTIP gene that is not matched in the GSE76894 validation dataset. (C) The correlations between the expression level of the MS4A6A gene and disease severity markers of PD, NAFLD, and T2DM. (CXCL8 for PD; NAS score for NAFLD; fasting glucose level for T2DM). PD, periodontitis; NAFLD, nonalcoholic fatty liver disease; T2DM, type 2 diabetes.

Fig. 6

Single-cell analysis and immunohistochemical staining data (A) Immunohistochemical staining graphs of the MS4A6A gene in various tissues. The graphs were acquired from the HPA database (https://www.proteinatlas.org/). Red arrows below indicate the expression site and level of the MS4A6A gene. (B) The single-cell RNA sequencing analysis showing cell types expressing the MS4A6A gene in PD, NAFLD, and T2DM. The results suggested a high and unique expression of the MS4A6A gene in macrophages. The orange color refers to its expression level and the darker the orange color is, the higher expression level of the MS4A6A gene. NAFLD, nonalcoholic fatty liver disease; T2DM, type 2 diabetes mellitus; PD, periodontitis.

Fig. 7

Intermolecular docking simulation results Intermolecular docking simulation results of the predicted drugs with MS4A6A protein.