AI reveals link between family history and type 1 diabetes risks
A new data-driven approach is offering insight into people with type 1 diabetes, who account for about 5-10% of all diabetes diagnoses.
The researchers gathered information through health informatics and applied artificial intelligence (AI) to better understand the disease.
In the study, they analyzed publicly available, real-world data from about 16,000 participants enrolled in the T1D Exchange Clinic Registry. By applying a contrast pattern mining algorithm, researchers were able to identify major differences in health outcomes among people living with type 1 diabetes who do or do not have an immediate family history of the disease.
The technique is exploratory in nature, says Chi-Ren Shyu, professor in the University of Missouri College of Engineering, who led the AI approach.
“Here we let the computer do the work of connecting millions of dots in the data to identify only major contrasting patterns between individuals with and without a family history of type 1 diabetes, and to do the statistical testing to make sure we are confident in our results,” says Shyu, director of the Institute for Data Science and Informatics (MUIDSI).
The analysis resulted in some unfamiliar findings, says Erin Tallon, a graduate student in the MUIDSI, and lead author of the paper in Diabetes Care.
“For instance, we found individuals in the registry who had an immediate family member with type 1 diabetes were more frequently diagnosed with hypertension, as well as diabetes-related nerve disease, eye disease, and kidney disease,” Tallon says.
“We also found a more frequent co-occurrence of these conditions in individuals who had an immediate family history of type 1 diabetes. Additionally, individuals who had an immediate family history of type 1 diabetes also more frequently had certain demographic characteristics.”
Tallon’s passion for this project began with a personal connection, and quickly grew as a result of her experience working as a nurse in an intensive critical care unit (ICU). She would often see patients with type 1 diabetes who were also dealing with other co-existing conditions such as kidney disease and high blood pressure.
