Our mission is to discover better diagnostic markers, predictors, and therapies for cardiometabolic disease
as obesity-driven metabolic diseases are the major drivers of atherosclerotic
cardiovascular disease in the modern era.
What impact will this research have?
Obesity-related diseases are the major health challenges of our generation. Obesity-driven type 2 diabetes has dramatically increased in prevalence in Australia and other Western countries in the last few decades. Alarmingly, in the last decade alone, highly-populous developing countries like India and China have seen type 2 diabetes reach epidemic proportions. In fact, the WHO described the increase of type 2 diabetes in China as “explosive”, where 114 million people have type 2 diabetes and 500 million people (almost 50% of all adults) have prediabetes.
Clearly, there is an urgent global need for better ways to detect and treat type 2 diabetes. One of the cornerstones of treatment of type 2 diabetes is early intervention. In this context, our discovery of a new molecule that independently predicts diabetes 12 years before diagnosis has huge clinical potential to facilitate intervention well before overt onset of diabetes and its attendant complications such as cardiovascular disease. Furthermore, by detailing the entire pathway controlling levels of this molecule, we can now determine if this pathway can treat type 2 diabetes.
Current projects and goals
Obesity-driven metabolic disease such as insulin resistance, diabetes, fatty liver disease, hyperlipidaemia, and hypertension are the major drivers of atherosclerotic cardiovascular disease in the modern era. This trend is continuing despite the best primary prevention efforts. These complex diseases are the consequence of gene-environment interactions, and to truly understand the various levels of dysregulation, both genomic data and environmental data must be captured. We probe carefully-phenotyped patient cohorts using genome scanning and metabolomic profiling to discover novel disease markers that may have clinical utility, e.g., by providing better diagnostic markers of disease, and allowing earlier intervention by predicting future disease. Furthermore, integration of genetic and metabolomic data allows delineation of disease pathways, which we then study in animal and cell models of disease. This allows us to determine disease-specific functional regulation, and potential for therapeutic intervention.