Hyperlipidemia-associated specific modules and hub genes revealed by integrative methods of WGCNA and MetaDE

This study aimed to screen the specific modules and hub genes of hyperlipidemia.

Three microarray datasets (GSE3059, GSE1010 and GSE13985) were obtained from the Gene Expression Omnibus database. Weighted Gene Co-expression Network Analysis (WGCNA) was used to screen stable gene modules across the three datasets. The MetaDE method was used to screen differentially expressed genes (DEGs) based on GSE1010 and GSE13985 datasets. The Cytoscape software was utilized for protein-protein interaction (PPI) network visualization, and the DAVID was employed to perform Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis on the DEG nodes in the interaction network.

Based on the WGCNA algorithm, eleven hyperlipidemia-related modules were screened, and a total of 1,149 DEGs were screened by the metaDE method. 288 overlapping genes were used to establish a PPI network. Finally, a total of four overlapping KEGG pathways were obtained, including Fc gamma R-mediated phagocytosis (ARPC1A, GAB2, LYN, HCK, RAF1, WAS), chemokine signalling pathway (LYN, PTK2B, HCK, GRK6, GRK3, RAF1, CXCR2, JAK3, FOXO3, WAS), endocytosis (CHMP2A, CHMP1B, RAB5C, VPS45, TGFBR2, GRK6, GRK3, CXCR2) and natural killer cell-mediated cytotoxicity (TNFRSF10C, PTK2B, ICAM2, RAF1, FCGR3B, SH3BP2). The hub genes such as RAF1, GRK3 and CXCR2, might be potential genetic biomarkers of hyperlipidemia.

This study identified the critical pathways and hub genes associated with hyperlipidemia. In particular, these critical pathways may help clarify the pathogenesis of hyperlipidemia, and the hub genes may become new biomarkers and therapeutic target for hyperlipidemia.