title: Transition from hepatic steatosis to steatohepatitis: unique microRNA patterns and potential downstream functions and pathways.
abstract: OBJECTIVE
  This study aimed to explore the unique miRNA responsible for transition from hepatic steatosis to steatohepatitis and to investigate the functions and pathways of their downstream targets.
  
  
  METHODS
  Microarray and stem-loop reverse transcription-polymerase chain reaction were utilized to detect dysregulated miRNA in a rat model. SAM, PAM and clustering analysis were jointly applied to calculate significantly changed miRNA. The targets of miRNA were predicted through web server "microrna." The functions and pathways of those predicted genes were analyzed using databases of Gene Ontology and KEGG by the web server "DAVID."
  
  
  RESULTS
  Fourteen upregulated and six downregulated miRNA were selected as an accurate molecular signature in distinguishing hepatic steatohepatitis from steatosis. Through Gene ontology, 499 and 287 enriched functional categories were found for the target genes of upregulated and downregulated miRNA, including ion homeostasis, protein transport and so on. Through KEGG, 46 and 41 enriched pathways were collected for the target genes of upregulated and downregulated miRNA, including apoptosis, fatty acid metabolism and so on. Analysis of common target genes of all downregulated miRNA revealed potential involvement of ion transport and the membrane structure in steatohepatitis.
  
  
  CONCLUSIONS
  We reported the dysregulated miRNA in transition from hepatic steatosis to steatohepatitis and showed potential clinical application in disease differentiation. This study provided data reservoir for miRNA exploration and revealed novel disease-specific Gene Ontology functions and KEGG pathways such as uncoupling-protein-guided membrane change. Our data contributes to further researches on the pathogenesis and treatment of non-alcoholic steatohepatitis.
authors.affiliation: Department of Gastroenterology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
authors.forename: Xi
authors.initials: X
authors.lastname: Jin
authors.forename: Yi-peng
authors.initials: YP
authors.lastname: Chen
authors.forename: Mei
authors.initials: M
authors.lastname: Kong
authors.forename: Lin
authors.initials: L
authors.lastname: Zheng
authors.forename: Yi-da
authors.initials: YD
authors.lastname: Yang
authors.forename: You-ming
authors.initials: YM
authors.lastname: Li
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D019295:Computational Biology; D030541:Databases, Genetic; D004195:Disease Models, Animal; D018450:Disease Progression; D005234:Fatty Liver / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D020869:Gene Expression Profiling / Q000379:methods; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D008099:Liver / Q000378:metabolism* / Q000473:pathology; D035683:MicroRNAs / Q000378:metabolism*; D020411:Oligonucleotide Array Sequence Analysis; D051381:Rats; D017207:Rats, Sprague-Dawley; D020133:Reverse Transcriptase Polymerase Chain Reaction
chemical_list: D035683:MicroRNAs