Analysis of Potential Genes and Pathways Involved in the Pathogenesis of Acne by Bioinformatics

Abstract

Acne is the eighth most frequent disease worldwide. Inflammatory response runs through all stages of acne. It is complicated and is involved in innate and adaptive immunity. This study aimed to explore the candidate genes and their relative signaling pathways in inflammatory acne using data mining analysis. Microarray data GSE6475 and GSE53795, including 18 acne lesion tissues and 18 matched normal skin tissues, were obtained. Differentially expressed genes (DEGs) were filtered and subjected to functional and pathway enrichment analyses. Protein-protein interaction (PPI) network and module analyses were also performed based on the DEGs. In this work, 154 common DEGs, including 145 upregulated and 9 downregulated, were obtained from two microarray profiles. Gene Ontology and pathway enrichment of DEGs were clustered using significant enrichment analysis. A PPI network containing 110 nodes/DEGs was constructed, and 31 hub genes were obtained. Four modules in the PPI network, which mainly participated in chemokine signaling pathway, cytokine-cytokine receptor interaction, and Fc gamma R-mediated phagocytosis, were extracted. In conclusion, aberrant DEGs and pathways involved in acne pathogenesis were identified using bioinformatic analysis. The DEGs included FPR2, ITGB2, CXCL8, C3AR1, CXCL1, FCER1G, LILRB2, PTPRC, SAA1, CCR2, ICAM1, and FPR1, and the pathways included chemokine signaling pathway, cytokine-cytokine receptor interaction, and Fc gamma R-mediated phagocytosis. This study could serve as a basis for further understanding the pathogenesis and potential therapeutic targets of inflammatory acne.

Figure 1

Identification of DEGs from two datasets GSE6475 and GSE53795 using the online tool GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/). The threshold for filtering DEGs is P<0.05 and [log⁡FC] ≥ 1. Different colors indicate different datasets. The cross part represents the common DEGs. (a) Common upregulated DEGs of the two datasets. (b) Common downregulated DEGs of the two datasets.

Figure 2

Volcano plot of gene expression in microarray data GSE6475 (a) and GSE53795 (b), with a threshold of P<0.05 and [log⁡FC] ≥ 1 for filtering DEGs. Teal represents downregulated genes, purple represents upregulated genes, and yellow means no significant DEGs. UP, upregulated DEGs; DW, downregulated DEGs; NoDiff, non-differentially expressed genes.

Figure 3

GO and KEGG pathway enrichment analyses of the upregulated DEGs in acne. (a) Significant enriched GO terms in molecular function. (b) Significant enriched GO terms in cellular component. (c) Significant enriched GO terms in biological process. (d) Significant KEGG pathway enrichment for the upregulated DEGs in acne. Count, number of DEGs.

Figure 4

PPI networks of the common DEGs and module analysis. (a) The PPI network contained 110 nodes and 365 edges; four parts of PPI network encompassed by four circles represented four modules filtered by app MCODE in Cytoscape. (b)–(e) represent modules 1–4, respectively, which were extracted from the PPI network. Green represents the upregulated genes, and red represents the downregulated genes.