Broad Views of Non-alcoholic Fatty Liver Disease
Introductory text in journal, 2018

Multi-omics multi-tissue data are used to interpret genome-wide association study results from mice to identify key driver genes of non-alcoholic fatty liver disease. Non-alcoholic fatty liver disease (NAFLD) is the accumulation of fat (steatosis) in the liver due to causes other than excessive alcohol consumption. The disease may progress to more severe forms of liver diseases, including non-alcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma. In this issue of Cell Systems, Krishnan et al. (2018) reveal mechanisms underlying NAFLD by generating multi-omics data using liver and adipose tissues obtained from the Hybrid Mouse Diversity Panel, consisting of 113 mouse strains with various degrees of NAFLD. The study identified key driver genes of NAFLD that can be used in the development of efficient treatment strategies and illustrates the potential utility of systematic analysis of multi-layer biological networks. Multi-omics multi-tissue data are used to interpret genome-wide association study results from mice to identify key driver genes of non-alcoholic fatty liver disease. Non-alcoholic fatty liver disease (NAFLD) is the accumulation of fat (steatosis) in the liver due to causes other than excessive alcohol consumption. The disease may progress to more severe forms of liver diseases, including non-alcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma. In this issue of Cell Systems, Krishnan et al. (2018) reveal mechanisms underlying NAFLD by generating multi-omics data using liver and adipose tissues obtained from the Hybrid Mouse Diversity Panel, consisting of 113 mouse strains with various degrees of NAFLD. The study identified key driver genes of NAFLD that can be used in the development of efficient treatment strategies and illustrates the potential utility of systematic analysis of multi-layer biological networks.

Author

Adil Mardinoglu

Royal Institute of Technology (KTH)

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Mathias Uhlen

Royal Institute of Technology (KTH)

Jan Borén

University of Gothenburg

Cell Systems

2405-4712 (eISSN)

Vol. 6 1 37-51.e9

Subject Categories

Medical Genetics

Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)

Genetics

DOI

10.1016/j.cels.2018.01.004

More information

Latest update

7/5/2018 2