Chronic diseases are long-term health conditions that persist over an extended period, often for a person’s entire life. Genetic predisposition plays a role in many chronic diseases which includes liver, kidney, cardiovascular disease, diabetes, arthritis and obesity. The Chronic Disease Genomics program explores how genetic information can be used to improve the diagnosis and treatment of chronic diseases leading to better outcomes for patients. Many chronic diseases are currently treated in the same way for all patients; the Program aims to use genomic information to personalise treatments to achieve the best outcomes for each individual, guided by information from the patient’s own genome.
Program Leader: Associate Professor Shivashankar Hiriyur Nagaraj
With a PhD in Bioinformatics and over 15 years’ experience in diverse research projects encompassing Genomics, Computational Biology, and Transfusion. A/Prof Nagaraj is a talented mid-career researcher whose experience is a natural fit for the proposed study. His interdisciplinary knowledge and skills provide him with a strong foundation and capability to undertake cutting-edge research at QUT. The skills of his group are diverse and across computer science, software engineering, statistics and biology with a strong specialisation in next-generation sequencing (NGS), one of the most powerful technologies of modern biology. Importantly, he has developed industrial-grade software to solve complex problems in Genomics and to serve biomedical community. This initial design will serve as a foundation for further product development. His research has been published in leading international journals including Nature, Nature Genetics, Genome Research, and PNAS. His research has been continually funded by fellowships ever since the receipt of his PhD in 2009. He has been recently awarded $1.6M through MRFF Genomics Health Futures Mission for defining Genomic architecture of chronic disease in Australia’s First Peoples. He has been leading Indigenous Genomics projects since 2017 which includes blood group study and Tiwi Genetic study. He has additionally pioneered Pharmacogenomic studies by identifying variants associated with drug responses and adverse reactions in Tiwi population.