A network-based approach reveals the dysregulated transcriptional regulation in non-alcoholic liver disease
Artikel i vetenskaplig tidskrift, 2021
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 genomescale 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.
Författare
Hong Yang
Kungliga Tekniska Högskolan (KTH)
Muhammad Arif
Kungliga Tekniska Högskolan (KTH)
Meng Yuan
Kungliga Tekniska Högskolan (KTH)
Xiangyu Li
Kungliga Tekniska Högskolan (KTH)
Koeun Shong
Kungliga Tekniska Högskolan (KTH)
Hasan Turkez
Atatürk Üniversitesi
Jens B Nielsen
Chalmers, Biologi och bioteknik, Systembiologi
BioInnovation Institute
Mathias Uhlen
Kungliga Tekniska Högskolan (KTH)
Jan Boren
Göteborgs universitet
C. Zhang
Kungliga Tekniska Högskolan (KTH)
Zhengzhou University
Adil Mardinoglu
King's College London
Kungliga Tekniska Högskolan (KTH)
iScience
25890042 (eISSN)
Vol. 24 11 103222Ämneskategorier
Medicinsk genetik
Bioinformatik och systembiologi
Genetik
DOI
10.1016/j.isci.2021.103222
PubMed
34712920