title: Discovering a critical transition state from nonalcoholic hepatosteatosis to nonalcoholic steatohepatitis by lipidomics and dynamical network biomarkers.
abstract: Nonalcoholic fatty liver disease (NAFLD) is a major risk factor for type 2 diabetes and metabolic syndrome. However, accurately differentiating nonalcoholic steatohepatitis (NASH) from hepatosteatosis remains a clinical challenge. We identified a critical transition stage (termed pre-NASH) during the progression from hepatosteatosis to NASH in a mouse model of high fat-induced NAFLD, using lipidomics and a mathematical model termed dynamic network biomarkers (DNB). Different from the conventional biomarker approach based on the abundance of molecular expressions, the DNB model exploits collective fluctuations and correlations of different metabolites at a network level. We found that the correlations between the blood and liver lipid species drastically decreased after the transition from steatosis to NASH, which may account for the current difficulty in differentiating NASH from steatosis based on blood lipids. Furthermore, most DNB members in the blood circulation, especially for triacylglycerol (TAG), are also identified in the liver during the disease progression, suggesting a potential clinical application of DNB to diagnose NASH based on blood lipids. We further identified metabolic pathways responsible for this transition. Our study suggests that the transition from steatosis to NASH is not smooth and the existence of pre-NASH may be partially responsible for the current clinical limitations to diagnose NASH. If validated in humans, our study will open a new avenue to reliably diagnose pre-NASH and achieve early intervention of NAFLD.
authors.affiliation: Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai 200031, China University of the Chinese Academy of Sciences, CAS, Beijing 100049, China.
authors.forename: Rina
authors.initials: R
authors.lastname: Sa
authors.affiliation: University of the Chinese Academy of Sciences, CAS, Beijing 100049, China Key Laboratory of Systems Biology, Innovation Center for Cell Signaling Network, Institute of Biochemistry and Cell Biology, SIBS, CAS, Shanghai 200031, China.
authors.forename: Wanwei
authors.initials: W
authors.lastname: Zhang
authors.affiliation: University of the Chinese Academy of Sciences, CAS, Beijing 100049, China Key Laboratory of Systems Biology, Innovation Center for Cell Signaling Network, Institute of Biochemistry and Cell Biology, SIBS, CAS, Shanghai 200031, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Ge
authors.affiliation: Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai 200031, China University of the Chinese Academy of Sciences, CAS, Beijing 100049, China.
authors.forename: Xinben
authors.initials: X
authors.lastname: Wei
authors.affiliation: Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai 200031, China.
authors.forename: Yunhua
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: Vanderbilt School of Medicine, Nashville, TN 37235, USA.
authors.forename: David R
authors.initials: DR
authors.lastname: Landzberg
authors.affiliation: Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai 200031, China.
authors.forename: Zhenzhen
authors.initials: Z
authors.lastname: Wang
authors.affiliation: Diabetes and Obesity Research Center, Sanford-Burnham Medical Research Institute, Orlando, FL 32827, USA.
authors.forename: Xianlin
authors.initials: X
authors.lastname: Han
authors.affiliation: University of the Chinese Academy of Sciences, CAS, Beijing 100049, China Key Laboratory of Systems Biology, Innovation Center for Cell Signaling Network, Institute of Biochemistry and Cell Biology, SIBS, CAS, Shanghai 200031, China School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China hyyin@sibs.ac.cn lnchen@sibs.ac.cn.
authors.forename: Luonan
authors.initials: L
authors.lastname: Chen
authors.affiliation: Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai 200031, China University of the Chinese Academy of Sciences, CAS, Beijing 100049, China School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing 100021, China hyyin@sibs.ac.cn lnchen@sibs.ac.cn.
authors.forename: Huiyong
authors.initials: H
authors.lastname: Yin
mesh_terms: D000818:Animals; D015415:Biomarkers / Q000378:metabolism*; D059305:Diet, High-Fat; D004195:Disease Models, Animal; D018450:Disease Progression; D053263:Gene Regulatory Networks; D050356:Lipid Metabolism; D008055:Lipids / Q000097:blood; D008099:Liver / Q000378:metabolism / Q000473:pathology; D008297:Male; D055432:Metabolomics / Q000379:methods*; D008810:Mice, Inbred C57BL; D065626:Non-alcoholic Fatty Liver Disease / Q000097:blood / Q000235:genetics / Q000378:metabolism*; D014280:Triglycerides / Q000378:metabolism
chemical_list: D015415:Biomarkers; D008055:Lipids; D014280:Triglycerides
keywords: dynamical network biomarkers; mass spectrometry lipidomics; nonalcoholic fatty liver disease (NAFLD); pre-NASH; systems biology