A Novel Method to Improve T1D Risk Prediction Using Genetic Information

Genetic studies have identified numerous gene regions related to T1D susceptibility. However, very few of these gene regions can help predict the disease because their individual relationship to T1D susceptibility is very small. In this study, the investigators utilized children from the BABYDIAB study, a longitudinal study examining the natural history of islet autoimmunity and T1D in 1650 children born to a mother or father with T1D. Periodically, blood samples were taken from children to identify various factors leading to a diagnosis of T1D. In this pilot study, the investigators showed that a combination of 12 T1D susceptibility gene regions could better identify risk for T1D in close relatives, and in particular they were specific for T1D when combined with certain genetic markers of the immune system functioning. They further provide a method of rating various combinations of these genes to provide multiple levels of T1D disease risk stratification. This pilot study shows that susceptibility genes for T1D can be used in a combined manner to improve the T1D susceptibility risk stratification for individuals. This approach may be able to be further improved upon, using more sophisticated analyses and by adding data from additional cohorts.

Ramifications for Individuals with T1D:
If this concept is further developed with additional studies, it may be possible to greatly improve our ability to assess an individual’s genetic risk for developing T1D. Such tools will help better identify individuals most appropriate for various prevention therapies being developed.

JDRF Involvement:
JDRF supported this study through a Strategic Research Agreement to Dr. Anette-G. Ziegler.

Investigators and Institutions:
This study was led by Dr. Anette-G. Ziegler at the Institute of Diabetes Research, Helmholtz Zentrum München.

Reference:
Winkler C, Krumsiek J, Lempainen J, Achenbach P, Grallert H, Giannopoulou E, Bunk M, Theis FJ, Bonifacio E, Ziegler AG. (2012) A strategy for combining minor genetic susceptibility genes to improve prediction of disease in type 1 diabetes. Genes Immun. 2012 Oct;13(7):549-55. doi: 10.1038/gene.2012.36. Epub 2012 Aug 30.