Abstract
BACKGROUND: Obesity is an epidemic and systemic metabolic disease that seriously endangers human health. This study aimed to understand the transcriptomic characteristics of the blood of metabolically unhealthy obesity (MUO) and provide insight into the target genes of differently expressed microRNAs in the occurrence and development of MUO. METHODS: The GSE146869, GSE145412, GSE23561, and GSE169290 datasets were analyzed to understand the transcriptome characteristics of the blood of MUO and provide insights into the target genes of differently expressed microRNAs (DEMs) in MUO. Functional and pathway enrichment analyses and gene interaction network analyses were performed to profile the function of differentially expressed genes (DEGs). In addition, miRNet 2.0, TransmiR v2.0, RNA22, TargetScan 7.2, miRDB, and miRWalk databases were used to predict the target genes of effective microRNAs. RESULTS: A total of 189 co-DEGs were identified in at least two datasets. The 156 co-upregulated genes were enriched into 29 biological process (BP) terms and 12 KEGG pathways. Among the 29 BP terms, the immune- and metabolism-related BP terms were enriched. The 33 co-downregulated genes were enriched into two BP terms, including apoptotic process and regulation of the apoptotic process, with no KEGG pathway. The hub genes EGF, STAT3, IL1B, PF4, SELP, and ITGA2B in the gene interaction network might play important roles in abnormal BP in MUO. Among the 19 DEMs identified in the blood of the MUO group by the GSE169290 dataset, 18 microRNAs targeted 85 genes as risk factors in MUO. CONCLUSION: A network consisting of 18 microRNAs and 85 target genes might serve as a risk factor for metabolically unhealthy obesity.