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Genome­Environment Interactions in Type 1 Diabetes


Generating solutions




Competition III

Genome Centre(s)



Project Leader(s)

Fiscal Year Project Launched


Project Description

Type 1 Diabetes (T1D) is a complex disease often arising in childhood in which the immune system destroys the insulin producing cells of the pancreas. Insulin is a crucial hormone in sugar and fat metabolism. Despite insulin therapy, T1D greatly increases the probability of heart attack, stroke, blindness and limb amputation, as well as shortened life expectancy. T1D afflicts some 200,000 Canadians and is caused by multiple genetic risk factors and currently unknown environmental factors. Now an innovative research project is investigating the interactions of genetic risks and environmental factors underlying T1D.

Jayne Danska, Senior Scientist at Toronto’s Hospital for Sick Children and Professor in the Faculty of Medicine at the University of Toronto, and Andrew Macpherson, Canada Research Chair in mucosal immunology at McMaster University, are project leaders of GenomeEnvironment Interactions in Type 1 Diabetes.

This project aims to understand the genetic control of T1D in humans and rodent models, and to study the role of exposure to common intestinal bacteria in regulating immune system development and how such exposures affect the probability that persons at genetic risk of T1D will develop the disease.

By identifying genetic variants and bacterial exposure associated with T1D, this project is expected to discover new genetic markers, and to identify environmental exposures to intestinal bacteria that modify inherited T1D risk.

Canada has the third highest rate of T1D in the world and the incidence is rising. T1D accounts for 10% of cases of all diabetes cases, and costs the Canadian healthcare system $1.32 billion in 2002 and is projected to rise to $1.6 billion by 2010. This project aims to decrease the disease burden and increase the quality of life and life expectancy of persons with T1D and their families.

Moreover, discoveries from this research project are expected to have implications for a number of other autoimmune disease states, such as multiple sclerosis, inflammatory bowel disease and rheumatoid arthritis.

Integrated GE3LS Research: Genome-environment interactions in Type 1 diabetes: Attitudes of Adults and Adolescents to Predictive Genetic Testing for Diabetes

GE3LS Project Leaders: Aideen Moore and Andrew Paterson, The Hospital for Sick Children


Recent research advances mean that Research Ethics Boards (REBs) are now reviewing protocols that involve predictive genetic testing in children. While issues surrounding predictive genetic testing are clear in adults, there remain significant problems regarding the ethics of predictive testing in children. Further information on the acceptability and impact of predictive testing in children and adolescents and their families is required so as to allow REBs to better quantify risks and benefits of such studies.

The objectives of our research study include :

  1. Examine the views of first-degree relatives of diabetics to predictive testing for type 1 diabetes as compared to the nondiabetic population.
  2. Determine the views of first degree relatives of diabetics as compared to the general population, relating to studies on gene-environment interaction for Type 1 Diabetes (T1D).
  3. Examine the views of children and young adolescents who are able to provide assent.
  4. Determine the effect of having a child with T1D on parent’s perceived risk to other children and impact on anxiety levels and family functioning.

This information should help to guide investigators, REB members and research participants on the key elements that need to be included in consent forms for research in T1D that includes predictive testing. Many other childhood diseases, including asthma and Crohn’s disease, are now understood to involve genome-environment interactions. Information gained in the GE3LS component of our project will be generalisable to many other disorders and will be very important as other large population-based predictive studies are undertaken.