Postgraduate Studies Projects

Supervisor: Dr. Jeremy Jowett
Phone: 8532 1775
Email: jeremy.jowett@bakeridi.edu.au
 

Gene & Biomarker Discovery in Type 2 Diabetes

If you have a look around you will have noticed that there is great diversity among the people you see and meet. Some of these biological differences are easy to discern like height and eye colour, while others are of a more subtle nature and may not be immediately apparent like athletic ability and intelligence. This great diversity in our species also extends to our level of predisposition to development of disease. Most common diseases like type 2 diabetes, obesity and cardiovascular disease are “complex” meaning that an individual’s risk is influenced not only by heritable factors (i.e. genes or family history) but also by the environment in which we live.

Unfortunately the prevalence of type 2 diabetes and obesity continues to increase in both developed and developing countries presenting a major public health issue impacting a wide variety of social and economic measures not least of which is the personal health burden & suffering.  The number of affected individuals with type 2 diabetes worldwide is currently estimated at 246 million with a predicted increase to 380 million by 2025 (Diabetes Annual 2006).

The genomics and systems biology laboratory is working toward providing a better understanding of the process that causes obesity and diabetes by identifying disease-predisposing genes, their products and how those products interact with other elements in the cell; and, in turn, how the cell’s function is affected by these genes in its physiological role within the body.  Understanding this process will aid in the development of more accurate diagnostic tests and lead to improved therapeutic drugs which will ameliorate cure or prevent the development of obesity, type 2 diabetes and related metabolic conditions.

project 1 - Investigation of the mechanism of action of novel genes influencing HDL cholesterol homeostasis

Many epidemiological studies have shown that a low serum level of high density lipoprotein cholesterol (HDL-C) is a strong independent risk factor for development of cardiovascular disease (CVD) including atherogenesis and coronary heart disease. Major influences on low HDL-C levels include obesity, smoking, sedentary behaviour, type 2 diabetes and genetic factors, with the latter inherited risk contributing to 50% of the total natural variation. Current therapies to raise HDL-C levels include nicotinic acid, fibrates and statins, however they rise to a variable degree and it is uncertain whether any reduction in risk is conferred. Therefore there is an urgent need for new HDL-C raising therapies. The lack of therapeutic options is predominantly due to the complex regulatory pathways influencing HDL-C homeostasis including regulatory enzymes, cell surface receptors and apoproteins that regulate serum levels. All are subject to the influences of genetic variation. It is important therefore to fully understand the mechanisms responsible for the regulation of HDL-C levels and to develop multiple strategies to target its level at various molecular nodes.

We have combined genomic, transcriptomic and functional genetic analyses to identify novel genes involved in HDL-C homeostasis in a large human family cohort. We provide compelling evidence that these genes that influence plasma levels of HDL-C. Collectively the expression levels of these genes account for 5.5% of the naturally occurring variation in HDL-C levels. Given the large number and diversity of complex pathways that regulate HDL-C, identification of controllers of 5.5% of the variation of HDL-C represents a significant finding. We have also identified loci that are causal and control expression levels of each of these genes using Genome Wide Association (GWAS) and expression levels as a quantitative phenotypic trait.

This project will investigate the mechanism of action linking these genes to HDL-C homeostasis. Initially the biological consequences of modulation (over-expression and knockdown) in tissue culture models of HDL-C production, remodelling and catabolism will be investigated. Next the upstream genes that were found to control the expression levels of these genes will be validated using functional assays (knockdown/over-expression). These validation studies in tissue culture and animal model systems will increase our understanding of the HDL-C homeostasis mechanisms and reveal multiple new potential therapeutic targets for development of interventions. This will lead to significant improvements in clinical care strategies to combat the rising incidence of cardiovascular disease and reduce its impact on morbidity and mortality in the population.

Project 2 - Novel Biomarkers to Predict Development of Type 2 Diabetes

The development of most common chronic diseases is influenced by heritable genetic factors that increase or decrease an individual's propensity to develop disease. The identification and measurement of biomarkers that are influenced by these factors forms the basis upon which to quantify an individual's risk of disease and allow preventive action to be undertaken that may prevent disease onset and/or progression. Additionally, knowledge of the nature of these physiological perturbations may reveal novel modalities for therapeutic intervention. Despite extensive efforts, the use of proteomics based analysis has failed to identify new predictive biomarkers potentially due to insufficient sensitivity and limitations in throughput of current protein screening technologies. We have generated a large gene expression profiling database in humans, that we have used to discover novel biomarkers for assessing the risk of progression of normal glucose tolerant individuals to type 2 diabetes. Our proof of principle data resulted in discovery of circulating proteins not previously linked to diabetes that is involved in inflammation. Our data show that it is a significant predictor of progression to type 2 diabetes and carries independent predictive ability to existing measures in the current best prediction models including glucose, insulin and BMI.

This project will focus on the identification of predictive biomarkers by developing functional assays (such as ELISA), and validating the candidate biomarkers in plasma samples from two unique and valuable cohorts; the Mauritius longitudinal epidemiology cohort and the San Antonio Family Heart Study. An exciting aspect of working with these cohorts is that powerful genetic linkage analysis, genome wide association and transcript expression profiling can be undertaken through computer analysis to formulate hypotheses around mechanism of action of control and consequence. Depending upon the scope of the project these can then be tested directly in cell culture models and established biological assays. We also have in our lab the latest technologies (siRNA, microarray based profiling and molecular pathway analysis) to assist in validation of the new hypotheses.

Ultimately, this will improve risk determination for type 2 diabetes and allow intervention at an early stage to reduce the chance of increased morbidity and mortality associated with undiagnosed hyperglycemia.  This would have major benefits for not only the individual but also the public health management issue of the epidemic.

Project 3 - Identification of Novel Genes Influencing Development of Type 2 Diabetes

Changes in human behaviour and lifestyle over the last century have resulted in a dramatic increase in the incidence of Type 2 Diabetes Mellitus (T2D) worldwide in part driven by increased obesity. Once diagnosed, currently available therapies are inadequate to control disease progression and there are few new therapeutics in the development pipeline due to our limited understanding of the molecular pathogenesis. The complex etiology of T2D is thought to involve environmental and genetic risk factors. A substantial effort has been made to identify the underlying genetic basis of the familial predisposition in order to improve the current understanding of disease mechanisms and identify novel targets for therapeutic development.

This project will use next generation DNA sequence technology (NGS) to identify all genetic variation in a specific region within a cohort which has been successfully piloted in our facility. Comprehensive knowledge of all variation will allow full genetic dissection of the segregating variants contributing to the linkage signal and guarantee identification of the causative gene(s). This project will focus on cataloguing all the genetic variation in the Mauritius Family Cohort at chromosome 12q24 using the NGS technology and then variants associated with glucose will be genotyped in the whole cohort and confirmation of linkage signal using conditional linkage analysis.  Finally, validation experiments using in vitro model systems of glucose homeostasis will also be applied to confirm a role of the candidate genes. Ultimately these findings will translate to improved understanding of the molecular mechanisms of disease leading to novel and more specific therapeutics acting on new physiological pathways and the potential to control disease progression in afflicted individuals.