Application of nuclear magnetic resonance spectroscopy for the detection of metabolic changes in non-alcoholic fatty liver disease

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Saborano, Raquel (2019). Application of nuclear magnetic resonance spectroscopy for the detection of metabolic changes in non-alcoholic fatty liver disease. University of Birmingham. Ph.D.

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Abstract

The increasing rates of NAFLD worldwide are a major concern to healthcare providers leading to an arising need to study liver metabolism in health and disease. Metabolic analysis of specific biochemical processes by NMR spectroscopy allows detailed study of carbohydrate and lipid metabolism dysregulation in liver disease.

In order to identify the hepatic metabolic fingerprint at different stages of NAFLD I used in vitro, murine in vivo and human ex vivo models. Optimisation of NMR metabolic profiling and tracer-based studies using 13C-labelled precursors were performed using cell lines and primary cells. Furthermore, metabolic alterations that occur during disease progression were compared between an in vitro model of steatosis and human ex vivo liver samples. Flow cytometry, immunohistochemistry, qPCR and biochemical analysis were also used to confirm the extent of the liver injury during NAFLD progression.

Fructose supplementation led to accelerated obesity, hepatic steatosis and insulin resistance, as well as increased inflammation in my murine model. The use of 1D NMR-based metabolomics and 2D HSQC spectra to follow [U-13C] fructose confirmed selective enhancement of the glycolytic pathway and TCA cycle intermediates together with nucleotide production. Moreover, increase in the production of glycerol intermediates was observed, which drives de novo lipogenesis. Lastly, the inhibition of ketohexokinase activity in both the animal model and the ex vivo human perfusion system highlighted its potential as a therapeutic approach in NAFLD.

Hence, these findings demonstrate the relevance of using NMR metabolomics and tracer-based approaches to study metabolic changes in the context of human disease and provided detailed mechanistic information that can lead to the identification of novel diagnostic, prognostic and therapeutic tools.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):