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Combined risk score predicts type 1 diabetes in children

An article published in Nature Medicine has demonstrated that a combined risk score improves type 1 diabetes (T1D) prediction in children.

T1D is an autoimmune disorder associated with substantial heritable risk, particularly from common human leukocyte antigen (HLA) variants. This disorder is a result of insulin deficiency caused by destruction of pancreatic islets. This occurs due to the presence of islet autoantibodies that appear early in life. Nevertheless, clinical diabetes can often take weeks or decades to appear and is often very difficult to predict. Ketoacidosis at onset of disease is common and is mostly prevented by effective autoantibody surveillance programmes. Nonetheless, the expense of frequent evaluations often limits public health adoption. In addition, preventative therapies applied before onset have rarely been feasible due to difficulty in identifying these patients.

Combined risk score

In this study, researchers from seven international sites developed a combined risk score (CRS). This score incorporates genetics, clinical factors (e.g. family history of diabetes) and islet autoantibody count. They followed 7,798 high-risk children closely from birth for over 9 years.

The team found that compared to autoantibodies alone, the CRS was able to dramatically improve T1D prediction in children. Most importantly, they found that CRS doubled the efficiency of population-based newborn screening programmes in preventing ketoacidosis. They also discovered that a combined approach enables accurate individualised risk estimates, which in turn can improve cost and feasibility of early intervention trials.

Lauric Ferrat, PhD, a postdoctoral research fellow at the University of Exeter Medical School, stated:

“At the moment, 40% of children who are diagnosed with type 1 diabetes have the severe complication of ketoacidosis. For the very young this is life-threatening, resulting in long intensive hospitalizations and in some cases even paralysis or death. Using our new combined approach to identify which babies will develop diabetes can prevent these tragedies, and ensure children are on the right treatment pathway earlier in life, meaning better health.”

The team believe that this new combined approach may also be applicable to other diseases that are identifiable in childhood which have a strong genetic component. Using a combined approach, also seen in polygenic risk scores, can provide more accurate predictions and subsequently lead to actionable and cost-effective measures in patient care.

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