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livSYSiPS - The systems biology of network stress based on data generated from in vitro differentiated hepatocytes derived from individual-specific human iPS cells.


Non-alcoholic fatty liver disease comprises a broad spectrum of disease states ranging from manageable stress as in simple steatosis (S) to excessive stress as in steatohepatitis (SH). In contrast to simple steatosis which has a good prognosis and may be considered a stressed state of normal liver, SH may ultimately lead to liver cirrhosis and hepatocellular carcinoma, which are both diseased states. A major unsolved problem is the marked difference in the individuals? ability to deal with the stress, e.g. as observed in terms of risk to develop steatohepatitis and to progress to cirrhosis. These differences in susceptibility to SH and its progression to cirrhosis have been attributed to a complex interplay of genetic and environmental factors. The complex interplay of pathways involved in the pathogenesis of steatohepatitis have hindered the discovery of susceptibility and modifier genes. The concept underpinning this project is that the various environmental exposures and genetic factors affect many different molecules in many different ways, but have very similar effects on network function. Hence, shifting focus from individual genes to the networks in which they are embedded, might well lead to a much clearer understanding. Accordingly, the proposed project will adopt a systems biology approach to develop a computational model for S and SH based on transcriptomics, proteomics and metabolomics data generated from patient-specific iPS cells (induced Pluripotent Stem cells) differentiated into hepatocytes and exposed to various environmental stimuli. To achieve this goal we will reprogram fibroblast cultures derived from skin biopsies taken from patients into iPS cells employing virus-mediated transduction of the transcription factors-OCT4, SOX2, KlF4 and c-MYC. The knowledge gained from these studies will be invaluable for the early means of identifying drugs that cause side effects in patients and most importantly for understanding the molecular (genes and associated signalling pathways) mechanisms underlying the etiology of simple steatosis and steatohepatitis.


Project partners:

James Adjaye Project Coordinator)
MPI for Molecular Genetics, DE
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Kurt Zatloukal
Medical University of Graz, AT

Hans Westerhoff
Manchester Interdisciplinary Biocentre (MIB), UK

Christian Regenbrecht
Comprehensive Cancer Center Charité, DE

Ivano Bertini
Magnetic Resonance Center (CERM), IT

Ulrike Korf
German Cancer Research Center (DKFZ), DE

George Church
Harvard University Medical School, USA