Artificial Intelligence Identifies T1D Risk Factors in Children

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T1DI Type 1 Data Intelligence logo

JDRF and IBM Research are collaborating to develop and apply world-class computing power to analyze years of global type 1 diabetes (T1D) data and identify factors leading to the onset of T1D in children, and a breakthrough publication is just out. Published in Diabetes Care, it is the first major clinical paper from this collaboration on identifying people at high risk for the disease.

The Type 1 Data Intelligence (T1DI) Study—the largest one of its kind for predictors of childhood T1D, created by IBM Research—combined the data from 5 studies in 4 countries. The datasets included measurements of autoantibodies—markers that are specific to T1D.

By analyzing the data, IBM Research found that the number of autoantibodies present in blood—the earliest time point in autoimmunity development—can reliably predict risk of T1D onset in young children for periods up to 10 to 15 years into the future.

For children with multiple autoantibodies, the risk of developing T1D is very high, about 90% over a 15-year period. Also, the younger the age at which children develop multiple autoantibodies, the greater the risk, peaking between 2-4 years of age.

JDRF-IBM Research has also shed new light on risk of T1D in single autoantibody-positive children. Their 15-year risk of T1D onset is markedly lower, just 30%, especially for children with only a single autoantibody and those remaining single after that.

Children who remain positive for only a single autoantibody, as well as having a low-risk genotype for T1D, have a substantially lower risk: Just about 12% overall, or about one third lower than those with high-risk genotypes.

Helping Identify At-Risk Children

These results not only pave the way for better understanding of risk factors for T1D, but may also help to develop guidelines for routine screening, monitoring, and management of at-risk children.

As well, T1D onset and initial diagnosis is often associated with life-threatening complications of diabetic ketoacidosis (DKA), increasing the importance of early detection. This is particularly valuable since research has shown reduced DKA rates in study participants who were routinely tested for development of autoantibodies and followed.

Our findings should also help inform screening programs—like the JDRF initiative, T1Detect—to identify high-risk individuals early as potential candidates for clinical trials, such as in the TrialNet consortium. This could benefit not only the children who participate, but also the entire T1D research community.

Two of the participating centers in the T1DI collaboration are in the United States: DAISY at the University of Colorado, Denver, and DEW-IT at the Pacific Northwest Research Institute in Seattle. The other three centers are in Europe: DiPiS, in Sweden at the Department of Clinical Sciences Malmö at Lund University CRC, and Skåne University Hospital in Malmö. The DIPP study was conducted at multiple locations in Finland: the Institute of Biomedicine and Centre for Population Health Research at the University of Turku, Department of Pediatrics at Turku University Hospital in Turku, University of Oulu and Oulu University Hospital, Department of Pediatrics, PEDEGO Research Unit, in Oulu; and in Germany, the BABYDIAB and BABYDIET studies were conducted at Helmholtz Zentrum München in Munich.