Population health research to improve the future of health.

Australian Centre for Precision Health (ACPreH) brings together a multidisciplinary group of leading experts in genomics, population health and evidence translation to create the next generation of solutions for global health problems.

Our goals are to prevent disease before it strikes, and to create innovative solutions to address issues focused on health and wellbeing. We do this by developing ways to improve risk prediction and risk factor discovery, as well as disease screening and health education.

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Find out more about our latest research projects

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Find out how you can get involved with our research


What is Precision Health?

Precision health brings together our genome with our internal and external environment to improve strategies for early disease prevention, and to find innovative solutions for existing population level problems.




The Precision Health Model © Prof Elina Hyppönen 2018

Study with us

To prepare for the future of health, health professionals will need to become data specialists who are able to interpret large pools of information to tailor prevention and care for an individual.

In the future, health professionals will be increasingly expected to interpret large pools of information to tailor prevention and care for an individual. With the growing availability of consumer genotyping kits, this transition is already ongoing. We use big data to create the type of information that is required for improving disease prevention and care in the context of individual genetic makeup, and are committed to delivering postgraduate training in genomics and precision health to medical doctors, pharmacists, nutritionists or other health professionals hoping to upskill for the future. With us, you will also have the opportunity to develop skills to use novel technologies to support the delivery of healthcare and prevention.

Anwar Mulugeta: My PhD Story

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Lettie Pule: My PhD Story

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Available projects

  • Personalised precision health and medicine using statistical approaches based on whole-genome information minus-thick plus-thick

    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 
  • Disease Prevention with Precision: Identifying and Overcoming Individual Genetic Vulnerabilities minus-thick plus-thick

    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
  • Role of pharmacogenomics on multi-morbidity minus-thick plus-thick

    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. 

  • Determinants of adverse patient-reported outcomes in cancer survivors minus-thick plus-thick

    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.
  • Using large-scale genomic and other omics data to dissect the biology of complex traits and diseases minus-thick plus-thick

    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.

  • Using mixed reality and holographic technologies (iHealth) for delivery of smoking cessation treatment among patients admitted to hospital with tobacco-related illnesses minus-thick plus-thick

    Available as: Master of Research and PhD

    Associate Professor Kristin Carson-Chahhoud

    Establish a foundation for iHealth tools to aid delivery of smoking cessation treatment for patients admitted to hospital with smoking related illnesses. This will be achieved through two stages:

    1. Development of 3 iHealth smoking cessation resources for smartphone delivery, including one with augmented reality, one with virtual reality and one with holographic technology.
    2. Evaluation of the practicality and feasibility of these smoking cessation resources for use by smokers admitted to hospital with tobacco related illnesses, ex-smokers and health professionals via qualitative research including focus groups and one-on-one interviews.

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Australian Centre for Precision Health

Location Level 8 South SAHMRI Building, North Terrace, Adelaide