Researchers developed new method to better predict onset of type 1 diabetes among infants

The research efforts, released in the journal Nature Medicine, unveiled a new test capable of better predicting T1D risk.

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Researchers at the University of Exeter developed a combined risk score involving clinical, genetic, and immunological factors to predict future type 1 diabetes (T1D) risk among children.

Their research efforts, released in the journal Nature Medicine, unveiled a new test capable of better predicting T1D risk, based on an examination of more than 7,000 high-risk children.

According to researchers, the participants were followed since birth for a span of nine years and was associated with The Environmental Determinants of Diabetes in the Young (TEDDY) study.

The data from that study was utilized for the development of a new approach using multiple factors influencing the risk of T1D among children.

“We sought accurate, cost-effective estimation of future T1D risk by developing a combined risk score incorporating both fixed and variable factors (genetic, clinical and immunological) in 7,798 high-risk children followed closely from birth for 9.3 years,” the co-authors explained in their findings.

“Compared with autoantibodies alone, the combined model dramatically improves T1D prediction at ≥2 years of age over horizons up to 8 years of age, doubles the estimated efficiency of population-based newborn screening to prevent ketoacidosis, and enables individualized risk estimates for better prevention trial selection,” the co-authors determined.

The new approach significantly improved the prediction of type 1 diabetes among the participants, also increasing identification to help prevent the onset of ketoacidosis.

“We’re really excited by these findings,” said William Hagopian, co-author of the study.

“They suggest that the routine heel prick testing of babies done at birth, could go a long way towards preventing early sickness as well as predicting which children will get type 1 diabetes years later. We’re now putting this to the test in a trial in Washington State. We hope it will ultimately be used internationally to identify the condition as early as possible, and to power efforts to prevent the disease.”

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