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.


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)


2589-0042 (eISSN)

Vol. 24 11 103222


Medicinsk genetik

Bioinformatik och systembiologi






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