Frontiers in Genetics (Nov 2022)
Identification of polyunsaturated fatty acids related key modules and genes in metabolic dysfunction-associated fatty liver disease using WGCNA analysis
Abstract
Polyunsaturated fatty acids (PUFAs) play important roles in the aetiology and pathogenesis of metabolic dysfunction-associated fatty liver disease (MAFLD). However, the underlying molecular mechanisms are not understood. We analysed a public GEO dataset, GSE89632, to identify differentially expressed genes (DEGs) in MAFLD. Weighted gene coexpression network analysis (WGCNA) was used to reveal the core gene regulation network and to explore the PUFA-related hub genes in MAFLD. We experimentally verified these genes by quantitative reverse transcription PCR in high-fat diet (HFD)-fed mice. A total of 286 common DEGs (89 upregulated; 197 downregulated), mostly related to inflammatory and immune responses, were identified. Six modules were constructed using WGCNA, and 2 modules showed significant correlations with PUFAs. After combining these 2 modules with DEGs, the top 10 hub genes were identified. We further established a MAFLD mouse model with liver steatosis, as proved by HE and Oil Red O staining. Of the hub genes, ADAM metallopeptidase with thrombospondin type 1 motif 1 (adamts1) (p = 0.005) and transforming growth factor β3 (tgfβ3) (p < 0.001) showed significantly lower mRNA expression in MAFLD in vivo. adamts1 and tgfβ3 bridged PUFAs and MAFLD, which might be potential causative genes and therapeutic targets of MAFLD.
Keywords