Integration of population level ‘omics data to target cardiometabolic disease
- Research Opportunity
- PhD students, Honours students
- Department / Centre
- Baker Department of Cardiometabolic Health
- Baker Heart and Diabetes Institute
|Professor Peter Meiklefirstname.lastname@example.org||85321770||Personal web page|
|Dr Corey Gilesemail@example.com||Personal web page|
Summary Development of a plasma lipid profiling test to enable the early detection of patients at increased risk of type 2 diabetes and coronary artery disease. In addition we will develop methods to monitor treatment. Identification of individuals prior to the development of disease will enable early intervention and will have a profound effect on the health of the Australian population.
Type 2 diabetes and coronary artery disease are major causes of morbidity and mortality in Australia. A number of lipids and lipoproteins have been identified as useful indicators and predictors of both type 2 diabetes and atherosclerosis (i.e. cholesterol, HDL, triglycerides). However, these provide only a restricted picture and a limited interpretation of the disease risk/status of an individual. It is now becoming clear that many other lipid types are altered during disease onset and progression and it is likely that some/many of these are involved in disease pathogenesis. We have an ongoing program of method development and biomarker discovery to identify and validate new lipid biomarkers of disease
In this project we will use our novel lipidomic approach to generate lipid profiles from patient cohorts at different stages of disease to identify those lipids and lipid profiles that are specifically associated with disease onset and progression.
We hypothesize that: the major differences in the plasma lipid profiles between healthy and type 2 diabetes or coronary artery disease precede the clinical presentation and so will be useful to predict disease outcomes.
The specific aims are to:
1) Perform plasma lipid profiling on patient cohorts that have been clinically phenotyped (type 2 diabetes or coronary artery disease).
2) Determine the plasma lipid profiles that are correlated with the burden of disease and use this to develop predictive models to identify individuals at increased risk of a disease onset and progression.
This project is suitable for an Honours or PhD student and will focus on bioinformatic/statistical modelling with human clinical/population cohorts to investigate the relationship between lipid metabolism and cardiometabolic diseases.
School Research Themes
PhD students, Honours students
Students who are interested in joining this project will need to consider their elegibility as well as other requirements before contacting the supervisor of this research
For further information about this research, please contact a supervisor.
Department / Centre
Research NodeBaker Heart and Diabetes Institute
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