Field:

  • Genomics
  • Paediatrics

Location:  UQDI

Type of student:  Both types will be considered (i.e. flexible with project)

Type of work:

  • Statistical analysis
  • Systematic review

Project Information: 

Type-1 diabetes (T1D) is a chronic autoimmune disease that leads to the destruction and dysfunction of the insulin producing beta cells. T1D affects more than 1.3 million people in Australia at a huge societal cost. The clinical presentation of T1D is preceded by a prodromal period that can last from months to years post birth and is characterised by the production of islet autoantibodies or seroconversion, reflecting loss of immune tolerance to beta cells. The factors that trigger T1D onset are largely unknown, but are believed to be a combination of environmental and genetic cues. Over the last decade, significant advances in T1D research have occurred through studying HLA-high risk individuals at familial risk of T1D into cohorts followed from birth, with concomitant exploration of biomarkers associated with preclinical development of autoantibodies and eventual progression to T1D. Our vision is that a better understanding of T1D progression mechanisms can be established by integrating the huge resource of the heterogeneous data that is available from preclinical studies of T1D development. Such an approach will predict T1D onset and uncover therapeutic strategies that prevent or suppress these pathogenic autoimmune responses in the subjects at highest risk for “disease interception'. Through successful collaborations, we have access to longitudinal microarray data from German BABYDIET, the US DAISY and Finnish DIPP study cohorts from individuals who are at risk of T1D. Some of these individuals progressed to develop T1D. By using this huge resource of data, we aim to find differentially expressed genes in children at risk of T1D. We also aim to link clinical and gene expression data by developing probabilistic models would predict T1D onset.

Required skills: Computer programming, mathematics and biology.

Desired skillls: Interest and experience in Matlab or R

Prerequisite skills: Knowledge of statistical tests

Supervisor

Dr Ahmed Mehdi

JDRF Research Fellow
UQ Diamantina Institute