The recent development of disease-modifying therapies for type 1 diabetes, coupled with increased difficulty in diagnosing diabetes subtypes is reinforcing the need for accurate and cost-effective methods of identifying those at risk of developing the disease. Genetic risk scores may provide novel methods to help identify those at risk and to improve discrimination between subtypes of diabetes.
In the early 20th century, a type 1 diabetes (T1D) diagnosis was a death sentence. That is, until Fredrick Banting’s 1920 theory led to the isolation of insulin with John Macleod, Charles Best, and later, James Collip. By the end of January 1922, they successfully purified insulin and treated a 14-year-old boy. This breakthrough changed T1D from a fatal diagnosis into a manageable condition. At a meeting of the Association of American Physicians in May 1922, Macleod presented their paper, The effects produced on diabetes by extracts of pancreas,1 marking the first use of the word ‘insulin’ with a standing ovation. By 1923, insulin belonged to the world and was mass produced for the first time. Banting and Macleod shared the 1923 Nobel Prize in Physiology or Medicine, sharing their prize money with the other members of the group.
100 years since the discovery of insulin, many questions around T1D remain. Even with extensive research and investment, the complete mechanisms of T1D remain elusive. However, modern analytical methods have introduced novel understanding of the processes at work. While T1D is no longer a terminal prognosis, many studies have shown those with T1D are at increased risk of a range of comorbidities including micro- and macrovascular complications.2,3
T1D has traditionally been considered a disease of the young, whereas type 2 diabetes (T2D) has been classically associated with mature onset and high BMI. However, rising obesity rates in the young and increasing numbers of adult-onset T1D are making the identification of true T1D cases more and more difficult. Additionally, the development of disease-modifying therapies for T1D is reinforcing the need for accurate and cost-effective methods of stratifying those at the highest risk of developing T1D. The development of genetic risk scores (GRS), like those described here, may provide novel methods to help identify those at risk of T1D and to improve discrimination between subtypes of diabetes.
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