RESUMO
Context: The liver is both the largest metabolic and the largest immune organ and is closely related to the mechanisms of disease development. Clarifying the immune environment of the NAFLD liver to determine its interactions with biomarkers would be beneficial in exploring the mechanisms of disease development. Objective: The study aimed to identify biomarkers and immune cells associated with nonalcoholic fatty liver disease (NAFLD) and to analyze the correlation between key genes and immune cells in NAFLD, to improve the understanding of the mechanisms underlying NAFLD and provide potential therapeutic targets. Design: The research team performed a genetic study. Setting: The study took place at Qingdao, Shandong Province, China. Outcome Measures: The research team: (1) obtained the NAFLD-related datasets GSE63067, GSE48452, and GSE89632 from the Gene Expression Omnibus (GEO) database; (2) analyzed immune-cell infiltrates using single-sample gene set enrichment analysis (ssGSEA) to determine the hub immune cells; (3) selected the differentially expressed genes (DEGs) between the NAFLD and normal samples and screened them to identify the hub genes; (4) evaluated the efficiency of the hub genes using receiver operating characteristic (ROC) curves; and (5) analyzed the correlations between hub genes and immune cells. Results: The research team: (1) found 28 differential immune cells; (2) identified monocytes as the hub immune cells; (3) identified 55 DEGs; (4) comparing the top 10 genes, identified five hub genes: S100 calcium binding proteins A12 (S100A12), S100A9, S100A8, selectin L (SELL), and sex hormone binding globulin (SHBG); (5) for all five, the area under the ROC curve (AUC) was greater than 0.6-training set: AUCSA00A12 = 0.699, AUCSELL = 0.743, AUCS100A9 = 0.735, AUCSHBG = 0.752, and AUCS100A8 = 0.703; and validation set: AUCSA00A12 = 0.852, AUCSELL = 0.905, AUCS100A9 = 0.819, AUCSHBG = 0.830, and AUCS100A8 = 0.822; (6) negatively correlated SHBG with immune cells (P > .05, r=-0.09); and (7) positively correlated S100A12, S100A9, S100A8, and SELL with immune cells-rS100A8 = 0.40, rS100A9 = 0.50, rS100A12 = 0.38, and rSELL = 0.42, respectively. Conclusions: Based on bioinformatic analyses, the progression of NAFLD may involve monocytes through promotion of liver inflammation. The hub genes S100A12, S100A9, S100A8, SELL, and SHBG are potential biomarkers that may be useful as diagnostic tools or therapeutic targets for NAFLD.