Study of whole-blood transcriptome of children with metabolically unhealthy obesity based on weighted gene co-expression network analysis
Wang Qingqing, Zhang Ruifeng, Ge Xing
1.Department of Nephrology and Rheumatology, XuzhouChildren's Hospital, Jiangsu, Xuzhou 221006, China; 2.College of Basic Medicine, Xuzhou Medical University, Jiangsu, Xuzhou 221004, China
Abstract: 【Abstract】 Objective To analyze the characteristics of the whole-blood transcriptome of children with metabolically unhealthy obesity (MUO) and metabolically healthy obesity (MHO), in order to find the biomarkers of MUO. Method The GSE146869 data set of Gene Expression Omnibus (GEO) database was used, including the whole-blood transcriptome sequencing data of 27 obese children (13 MHO children and 14 MUO children). The Limma package of R software was used to analyze the differentially expressed genes in the whole-blood cells. Bioinformatics methods such as gene ontology (GO) enrichment analysis, Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network analysis were used to explore the biological functions of differentially expressed genes. Weighted gene co-expression network analysis (WGCNA) was used to cluster differentially expressed genes into modules, and to explore biomarkers or potential therapeutic targets for MUO. Bioinformatics analysis and statistical analysis were performed by R software. Result There was no significant difference in gender, age, body mass index (BMI), systolic blood pressure, diastolic blood pressure, fasting blood glucose, insulin content and insulin resistance index between MHO group and MUO group (all P>0.05). Serum triglyceride, interleukin- 6 and tumor necrosis factor-α in MUO group was higher than that in MHO group (all P<0.05). Compared with the MHO group, 109 genes were up-regulated and 77 genes were down-regulated in the MUO group. The 186 differentially expressed genes were enriched into 46 GO entries and 3 KEGG pathways. Among the differentially expressed genes, cell division cycle 5 like (CDC5L), CTP synthase 1 (CTPS1) and major histocompatibility complex class Ⅰ-C (HLA-C) genes were the hub genes of PPI network map. In addition, WGCNA clustered 186 differentially expressed genes into 5 modules. In the cyan module, cleavage and polyadenylation specific factor 7 (CPSF7) was at the core and was the hub gene. Conclusion 186 differentially expressed genes and 5 modules can be used as potential targets for children with MUO, among which CDC5L, CTPS1, HLA-C and CPSF7 genes may play an essential role in the occurrence and development of MUO.
王青青 张锐锋 葛星. 基于加权基因共表达网络分析研究代谢异常型肥胖儿童的全血转录组特征[J]. 发育医学电子杂志, 2022, 10(3): 161-167.
Wang Qingqing, Zhang Ruifeng, Ge Xing. Study of whole-blood transcriptome of children with metabolically unhealthy obesity based on weighted gene co-expression network analysis. Journal of Developmental Medicine(Electronic Version), 2022, 10(3): 161-167.
2022, Vol. 10 
