A network-based approach reveals the dysregulated transcriptional regulation in non-alcoholic fatty liver disease

Hong Yang, Muhammad Arif, Meng Yuan, Xiangyu Li, Koeun Shong, Hasan Türkez, Jens Nielsen, Mathias Uhlén, Jan Borén, Cheng Zhang*, Adil Mardinoglu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Non-alcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease worldwide. We performed network analysis to investigate the dysregulated biological processes in the disease progression and revealed the molecular mechanism underlying NAFLD. Based on network analysis, we identified a highly conserved disease-associated gene module across three different NAFLD cohorts and highlighted the predominant role of key transcriptional regulators associated with lipid and cholesterol metabolism. In addition, we revealed the detailed metabolic differences between heterogeneous NAFLD patients through integrative systems analysis of transcriptomic data and liver-specific genome-scale metabolic model. Furthermore, we identified transcription factors (TFs), including SREBF2, HNF4A, SREBF1, YY1, and KLF13, showing regulation of hepatic expression of genes in the NAFLD-associated modules and validated the TFs using data generated from a mouse NAFLD model. In conclusion, our integrative analysis facilitates the understanding of the regulatory mechanism of these perturbed TFs and their associated biological processes.

Original languageEnglish
Article number103222
JournaliScience
Volume24
Issue number11
DOIs
Publication statusPublished - 19 Nov 2021

Keywords

  • Gene network
  • Hepatology
  • Systems biology

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