Australian Centre for Precision Health

Available as: Honours, Master of Research or PhD

Associate Professor Hong Lee

The genomic era provides a realistic opportunity for precision health and medicine n which individuals are classified into high or low-risk sub-groups based on profiles that incorporate information from genomic risk factors. Precision health based on genetic risk prediction can be applied at an early stage. It may be possible to predict future disease risk at birth, with potential to predict, intervene and prevent progression to the disease. In this project, we will investigate a number of novel approaches to increase the accuracy of genomic prediction. We will also estimate economic benefits from reduced treatment coses in an intervention program implementing novel genetic risk prediction approaches. The outcomes of this project will be of great significance to the prospects of using genetic information for personalised precision medicine. This project will be suitable for a high achieving student who has a interest in complex statistical modeling, and in developing related skills with an application to disease prevention. Some specific topics are:

1. Understanding the genetic architecture of complex diseases by gene-environment interaction
2. Polygenic Risk Scores for Prediction of Complex Traits and Diseases
3. Developing a mobile application for polygenetic disease risk prediction
4. Genome-transcriptome analyses 

Available as Master of Research and PhD

Professor Elina Hyppönen

The Nutritional and Genetic Epidemiology Group has several opportunities for Master of Research and PhD projects in the broad area of "Precision Health". Projects are suited for health professionals, keen to obtain high caliber research training and to continue professional development by acquiring skills for assessing large pools of information from the viewpoint of an individual patient.

Studies are based on large datasets with detailed information on genetics, lifestyle and health. Examples given below, but come and discuss, there may be some flexibility in tailoring the area of focus to suit your interests.

• Diet and cancer: establishing genetic evidence for a causal association
• Gene-environment interaction in cancer
• phemone-wide study of nutrition and physical activity on health

Available as: Master of Research and PhD

Dr Vijay Suppiah

Medications used in the treatment of many conditions do not always work for every patient. One of the factors that determine this variability in treatment outcomes, such as response and adverse effects, is the patient's genetic make-up. This effect is then multiplied once multiple medications are added to the mix. This project aims to elucidate the role of pharmacogenomics in patients who take multiple medications for the treatment of multiple conditions. 

Available as: Master of Research

Dr Terry Boyle

This project will use data from a cohort of 500 cancer survivors (breast cancer, colon cancer and non-Hodgkin lymphoma). Baseline assessment in 2013-14 involved collection of sleep quality/duration, sedentary time and physical activity (assessed with an accelerometer), clinical, demographic and lifestyle factors, and patient-reported outcomes (health-related quality of life, fatigue, depression, cognitive functioning and unmet needs). Follow-up data on patient-reported outcomes was collected in 2017.

Potential projects include:

1. Examining associations between sleep, sedentary and active behaviors and changes in patient-reported outcomes
2. Investigating determinants of poorer patient-reported outcomes and unmet needs.

Available as: Honours, Master of Research or PhD

Dr Beben Benyamin

The broad aim of the research project is to understand the aetiology and biological mechanism underlying complex traits and diseases, such as schizophrenia and motor neuron disease through the use and development of advanced statistical methods applied to high throughput genomics and clinical data.

Some examples of available student projects are:

1. The application of statistical genomic methods on large-scale ‘omics’ (e.g. genomics, epigenomics, transcriptomics) data to understand the causes of neuropsychiatric diseases, such as motor neuron disease or schizophrenia
2. Trans-ethnic genomic analyses to dissect the transferability of genomic findings in European samples into other populations, such as Asians
3. Mendelian randomization methods to infer the causal roles of modifiable risk factors (such as smoking) on complex diseases
4. Using genome-wide genotype data to dissect the heterogeneity of complex diseases.

It is now recognised that with the availability of big omics and health data, the major limiting factor is the availability of highly trained scientists who can ask the right questions and are equipped with the appropriate specialised computing and statistical genomic capabilities.

By studying with our group, you will have opportunities: to learn or develop the latest statistical genomic methods applied to large scale omics data, learn to analyse big data in genomics using computer program, and equip yourself with the rare set of skills required in the era of personalised and precision health.