Focus
Authors: Scott L. Friedman
Journal: Journal of Hepatology (2011)

The field of hepatology, like all medical disciplines, has greatly benefited from the development of model systems. These include cell culture models (primary cells and cell lines), disease and genetic models in fish, rodents and higher organisms, and mathematical models in humans. Three studies in this issue of Journal of Hepatology nicely illustrate the power and pitfalls of model systems in advancing our understanding of human liver disease. The study by Dubuquoy et al. examines the regulation of the PNPLA3 gene (also called ‘adiponutrin’), by two important metabolic rheostats, the transcription factors SREBP-1c and ChREBP, which regulate lipid and carbohydrate metabolism, respectively. PNPLA3 was uncovered as an important clue to the pathogenesis of non-alcoholic fatty liver disease when a single nucleotide polymorphism, or sequence variant, was uncovered that is strongly associated with risk of NAFLD [[7]Romeo S. Kozlitina J. Xing C. Pertsemlidis A. Cox D. Pennacchio L.A. et al.Genetic variation in PNPLA3 confers susceptibility to nonalcoholic fatty liver disease.Nat Genet. 2008; 40: 1461-1465Crossref PubMed Scopus (2309) Google Scholar], and more recently with alcoholic liver disease as well [[10]Tian C. Stokowski R.P. Kershenobich D. Ballinger D.G. Hinds D.A. Variant in PNPLA3 is associated with alcoholic liver disease.Nat Genet. 2010; 42: 21-23Crossref PubMed Scopus (352) Google Scholar]. The initial association was discovered through a genome-wide association study, underscoring the strength of this unbiased large scale screening technique to discover hidden links to disease pathogenesis from genes not on the investigative radar. In the case of the PNPLA3 risk variant, the mechanism for conferring risk of disease by the SNP remains uncertain, but the variant protein lacks the ability to hydrolyze triglycerides to the same extent as the wild type protein [[2]He S. McPhaul C. Li J.Z. Garuti R. Kinch L. Grishin N.V. et al.A sequence variation (I148M) in PNPLA3 associated with nonalcoholic fatty liver disease disrupts triglyceride hydrolysis.J Biol Chem. 2010; 285: 6706-6715Crossref PubMed Scopus (472) Google Scholar]. The Dubuquoy study does not examine the role the PNPLA3 SNP, but instead attempts to position the protein within the context of known metabolic mediators by examining its regulation by SREPB-1c and ChREBP. To do so, the studies rely primarily on a mouse model in which PNPLA3 gene expression is tracked in mice following either dietary or genetic manipulation of lipid and carbohydrate homeostasis. Studies were also conducted in isolated mouse hepatocytes, and thereafter in immortalized human hepatocytes in culture. One problem with this approach, however, is that the pattern of PNPLA3 expression differs significantly between mouse and man, wherein mice have very low expression in normal liver while humans have high hepatic expression [[6]Romeo S. Huang-Doran I. Baroni M.G. Kotronen A. Unravelling the pathogenesis of fatty liver disease: patatin-like phospholipase domain-containing 3 protein.Curr Opin Lipidol. 2010; 21: 247-252Crossref PubMed Scopus (70) Google Scholar]. Indeed, the authors discovered that hepatic PNPLA3 is regulated by ChREBP in mouse but not in man. Moreover, most of the analyses rely on mRNA expression, even though there is significant post-translational regulation of PNPLA3 stability. Does this mean that the models in this study lack relevance to human disease? Not necessarily, and in fact the species difference in PNPLA3 regulation could represent a clue to the difference between rodent models of fatty liver disease and the human condition. However, failure to recognize the limitation of the rodent model could have led to over-extrapolation of its results to humans. Moreover, even the human experiments in this report are limited to two immortalized cell lines, so the models used are informative but not ideal, and the findings must still be validated in a more relevant human system. The study by Lu et al. adds a different wrinkle to the use of animal models, in this case to study hepatocellular carcinoma (HCC). The authors generated a very clever in vivo reporter system to detect the emergence of early HCC in mice by combined bioluminescence and PET imaging. To accomplish this goal, they inserted two reporter constructs – luciferase for bioluminescence detection and thymidylate kinase for PET imaging – downstream of the promoter for alpha fetoprotein (AFP) in the germline of knock-in mice to express these reporter genes in early HCC cells, which typically re-express AFP as they become cancerous. Using this approach, early tumor formation could be imaged in animals given diethylnitrosamine (DEN), a standard HCC-inducing toxin [[4]Naugler W.E. Sakurai T. Kim S. Maeda S. Kim K. Elsharkawy A.M. et al.Gender disparity in liver cancer due to sex differences in MyD88-dependent IL-6 production.Science. 2007; 317: 121-124Crossref PubMed Scopus (1495) Google Scholar], without having to sacrifice the mice. This strategy enabled the investigators to study the kinetics of HCC development in real time. So in this example, disease dynamics rather than molecular mechanisms are the focus of their modeling effort. Still, the model could be combined with different genetically altered mice that lack or over-express candidate HCC related genes in order to interrogate the contributions of specific pathways. Interestingly, other elements of disease modeling are also represented by the Lu study. First, DEN is the mostly widely used method to generate HCC in mice. However, the tumors in this model arise in a non-fibrotic background, which is not representative of human HCCs, and, moreover, they lack the marked molecular heterogeneity that is typical of human HCC [[1]Chiang D.Y. Villanueva A. Hoshida Y. Peix J. Newell P. Minguez B. et al.Focal gains of VEGFA and molecular classification of hepatocellular carcinoma.Cancer Res. 2008; 68: 6779-6788Crossref PubMed Scopus (497) Google Scholar]. Second, the genetic background is a critical determinant of HCC development after DEN, and thus the investigators were required to backcross their mice from the C57Bl/6j-129Sv strain into the FVC3H background to facilitate tumor development. While in humans the presence of chronic liver disease and not host genetics is the most compelling risk for HCC development, it is also clear that host genetic determinants contribute to disease risk as well. For example, a polymorphism in the epidermal growth factor gene has been linked to HCC risk among patients with cirrhosis [[9]Tanabe K.K. Lemoine A. Finkelstein D.M. Kawasaki H. Fujii T. Chung R.T. et al.Epidermal growth factor gene functional polymorphism and the risk of hepatocellular carcinoma in patients with cirrhosis.JAMA. 2008; 299: 53-60Crossref PubMed Scopus (185) Google Scholar]. Thus, the Lu study nicely illustrates not only a model that employs novel imaging technology, but also the features of an experimental model of chemical carcinogenesis, as well as a model for genetic influences on cancer development. The third study by Drumright et al. exploits a different type of modeling – mathematical modeling – to explore predictors and effects of alcohol use on liver function tests in injection drug users with HCV infection. Specifically, part of their analysis relies on Markov modeling, a statistical method that models medical prognosis for clinical problems with ongoing risk [[8]Sonnenberg F.A. Beck J.R. Markov models in medical decision making: a practical guide.Med Decis Making. 1993; 13: 322-338Crossref PubMed Scopus (1986) Google Scholar]. The investigators have examined the impact of behavioral intervention on alcohol use in this population and linked this intervention to changes in liver function tests. The synergistic effect of excessive alcohol on fibrosis progression in chronic HCV is well known [[5]Poynard T. Bedossa P. Opolon P. Natural history of liver fibrosis progression in patients with chronic hepatitis C. The OBSVIRC, METAVIR, CLINIVIR, and DOSVIRC groups.Lancet. 1997; 349: 825-832Abstract Full Text Full Text PDF PubMed Scopus (2800) Google Scholar], and thus any intervention that might reduce alcohol use is worth considering in order to slow fibrosis progression. By exploiting the strengths of Markov modeling, the investigators reached several important conclusions. First, marijuana use, itself a determinant of accelerated fibrosis progression [[3]Hezode C. Roudot-Thoraval F. Nguyen S. Grenard P. Julien B. Zafrani E.S. et al.Daily cannabis smoking as a risk factor for progression of fibrosis in chronic hepatitis C.Hepatology. 2005; 42: 63-71Crossref PubMed Scopus (262) Google Scholar], also increased the return to alcohol use among those who had been abstinent. Second, effective intervention to stop alcohol use led to an improvement in serum transaminases, demonstrating for the first time a clear, positive impact on disease severity through behavioral intervention in this population. While the results may not be entirely surprising, they nonetheless reinforce the value of intervention efforts to reduce morbidity from alcohol use, which in the United States costs in excess of $185 million per year (http://www.niaaa.nih.gov/Resources/DatabaseResources/QuickFacts/EconomicData/Pages/cost8.aspx). Importantly, the conclusions might not have emerged without the application of sophisticated modeling. What do these three studies tell us with regard to models in liver disease? It is axiomatic to suggest that all models have strengths and weaknesses. Yet, from the data from each model emerges a thread that together weaves a tapestry of a human liver disease. The author did not have a relationship with the manufacturers of the drugs involved either in the past or present and did not receive funding from the manufacturers to carry out his research.