A systems biology approach towards child obesity and obesity-related diseases: integration of clinical, genetic, hormonal and NMR metabonomic factors

Abd Rahman, Shaffinaz (2015). A systems biology approach towards child obesity and obesity-related diseases: integration of clinical, genetic, hormonal and NMR metabonomic factors PhD Thesis, Institute for Molecular Bioscience, The University of Queensland. doi:10.14264/uql.2015.734

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Author Abd Rahman, Shaffinaz
Thesis Title A systems biology approach towards child obesity and obesity-related diseases: integration of clinical, genetic, hormonal and NMR metabonomic factors
School, Centre or Institute Institute for Molecular Bioscience
Institution The University of Queensland
DOI 10.14264/uql.2015.734
Publication date 2015-06-26
Thesis type PhD Thesis
Supervisor Gary M. Leong
Horst Joachim Schirra
David Hansen
Total pages 261
Language eng
Subjects 1103 Clinical Sciences
0604 Genetics
1101 Medical Biochemistry and Metabolomics
Formatted abstract
Systems biology has become a powerful scientific method using a more holistic perspective to tackle biological and biomedical research. Complex data obtained from different types of experiments using multiple interdisciplinary tools such as metabonomics and transcriptomics can be integrated and analysed to give a better understanding of the biological problem at hand.

This PhD thesis comprises closely related project parts that utilise tools of systems biology (NMR-based metabonomics, gene expression profiling, and multivariate analysis) to investigate how growth hormone deficiency (GHD) and obesity can cause alterations in metabolism of children and adolescence. In addition, method development of collecting and storage of human urine samples for NMR-based metabonomic studies were also investigated to aid in achieving accurate metabolic fingerprints.

The first project established a novel standard procedure of collection, storage and preservation of human urine samples to ensure the measurement of true metabolic fingerprints in NMR-based metabonomic studies. Human urine samples are susceptible to metabolite changes when left at room temperature for less than 24 hours even with the addition of different preservatives and I have successfully established the minimum requirements to maintain the stability of urine samples for 48 hours at room temperature.

Once a standard procedure of sample handling was established, a NMR-based metabonomics pilot study was performed in which the metabolic profiles of a growth hormone (GH)-deficient adolescent subject were tracked with NMR-based urinary metabonomics during five years of GH therapy . Detection of urinary metabolites related to GHD provided a clearer picture of the impact GH therapy has on metabolism. Metabonomics was able to differentiate the metabolic profiles of healthy controls from the GHD subject indicating that metabonomics has the capability to be utilised as a platform to identify the effects of GH treatment on metabolism in humans.

The main project of this PhD was a study of metabolic changes in children with obesity and used tools of systems biology such as NMR-based urinary metabonomics and peripheral blood mononuclear cell (PBMC) gene expression analysis to investigate samples collected as part of the KOALA childhood obesity program. Results from both metabonomics and gene expression profiling studies were combined with clinical data using multivariate analysis (O2PLS) to provide a clearer picture of how obesity can disrupt metabolism in children. The outcome(s) of this study support the utilisation of NMR-based metabonomics as a potential diagnostic and prognostic tool not only in the context of obesity, but make the technique also available for the study of other diseases. In addition, gene expression studies of PBMCs identified significant NRs and NR-dependent pathways that may improve our understanding of the underlying molecular mechanisms in metabolic dysfunction in obesity.

In summary, using tools of systems biology, a better understand can be achieved of how a disease or changes to body composition alter the metabolism of humans. In addition, by combining more than one type of ‘omics with multivariate analysis, one can obtain more information regarding the state of the subjects that could potentially be useful in predicting clinical risk factors for related diseases.
Keyword NMR
Chilldhood obesity
growth hormone
Nuclear Receptor
Multivariate Analysis

Document type: Thesis
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Created: Tue, 23 Jun 2015, 02:12:51 EST by Shaffinaz Abd Rahman on behalf of Scholarly Communication and Digitisation Service