Identification of core gene networks and hub genes associated with progression of non-alcoholic fatty liver disease by RNA sequencing

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Non-alcoholic fatty liver disease (NAFLD) progresses because of the interaction between numerous genes. Thus, we carried out a weighted gene coexpression network analysis to identify core gene networks and key genes associated with NAFLD progression.


We enrolled 39 patients with mild NAFLD (fibrosis stages 0–2) and 21 with advanced NAFLD (fibrosis stages 3–4). Total RNA was extracted from frozen liver biopsies, and sequenced to capture a large dynamic range of expression levels.


A total of 1777 genes differentially expressed between mild and advanced NAFLD (q-value <0.05) clustered into four modules. One module was enriched for genes that encode cell surface or extracellular matrix proteins, and are involved in cell adhesion, proliferation, and signaling. This module formed a scale-free network containing four hub genes (PAPLN, LBH, DPYSL3, and JAG1) overexpressed in advanced NAFLD. PAPLN is a component of the extracellular matrix, LBH and DPYSL3 are reported to be tumor suppressors, and JAG1 is tumorigenic. Another module formed a random network, and was enriched for genes that accumulate in the mitochondria. These genes were downregulated in advanced NAFLD, reflecting impaired mitochondrial function. However, the other two modules did not form unambiguous networks. KEGG analysis indicated that 71 differentially expressed genes were involved in “pathways in cancer”. Strikingly, expression of half of all differentially expressed genes was inversely correlated with methylation of CpG sites (q-value <0.05). Among clinical parameters, serum type IV collagen 7 s was most strongly associated with the epigenetic status in NAFLD.


Newly identified core gene networks suggest that the NAFLD liver undergoes mitochondrial dysfunction and fibrosis, and acquires tumorigenic potential epigenetically. Our data provide novel insights into the pathology and etiology of NAFLD progression, and identify potential targets for diagnosis and treatment.

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