Molecular and systems-level analyses reveal the emerging role of non-coding RNAs in liver diseases

  • Hao Wang

Student thesis: Doctoral ThesisDoctor of Philosophy


The liver is the largest solid organ in the human body, and functions to detoxify various chemicals, metabolize nutrients, and support almost every organ in the body. Thus, the liver is prone to many diseases. Non-alcoholic fatty liver disease (NAFLD), the most common liver disease, is an umbrella term for a range of conditions compromising hepatic steatosis, non-alcoholic steatohepatitis (NASH), fibrosis and cirrhosis without alcohol consumption, which may highly increase the risk of hepatocellular carcinoma, one of the leading causes of cancer-related death. Diabetes mellitus, one of the most common chronic diseases, has an intimate association with the onset of NAFLD. In addition, hepatic disease can cause the disordered metabolism of glucose, which is regarded as the pathophysiologic basis of diabetes in liver disease. MicroRNAs (miRNAs), the small and non-coding RNAs, are involved in various biological processes by regulating gene expression at transcriptional or translational levels. Ample studies have revealed that the aberrant levels of miRNAs strongly correlate with the pathogenesis of metabolic diseases. In addition, long non-coding RNAs (lncRNAs) have been regarded as co-operators of miRNAs, involving in the progression of diseases. However, the mechanistic role of miRNAs and miRNA-lncRNA-mRNA interplay in the development of the liver disease have not been investigated clearly. Therefore, my research aimed to determine the physiological and pathological roles of non-coding RNAs in the liver through molecular and bioinformatics approaches, in order to shed new light on the therapeutical potential of miRNAs in ameliorating liver diseases.

Thesis embargoed until 31 July 2025.
Date of AwardJul 2022
Original languageEnglish
Awarding Institution
  • Queen's University Belfast
SupervisorGary Hardiman (Supervisor) & Brian Green (Supervisor)


  • bioinformatics analysis
  • diabetes
  • HCC
  • miR29b
  • miR34a
  • miR378
  • lncRNAs
  • molecular analysis

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