New Delhi: A team of researchers has developed an AI-based approach to predict whether a person with type 2 diabetes will develop kidney disease, a frequent and dangerous complication of diabetes. Published in Nature Communications, the study by Sanford Burnham Priebis in the US and researchers from the Chinese University of Hong Kong may help doctors prevent or better manage kidney disease in people with type 2 diabetes.
Kevin Yip, Professor and Director of Bioinformatics, said, “Our team has demonstrated that by combining clinical data with state-of-the-art technology, it is possible to develop computational models to help clinicians optimize type 2 diabetes treatment. ” Sanford Burnham in Prebis.
The new algorithm relies on measuring a process called DNA methylation, which occurs when subtle changes accumulate in our DNA. DNA methylation can encode important information about which genes are being turned on and off, and can be easily measured through a blood test.
“Our computational model can use methylation markers from a blood sample to predict both current kidney function and how the kidneys will function in the future, which means that existing methods for evaluating a patient’s risk for kidney disease It can be easily implemented with Yip said.
The researchers developed their model using detailed data from more than 1,200 patients with type 2 diabetes in the Hong Kong Diabetes Register. They also tested their model on a separate group of 326 Native Americans with type 2 diabetes, which helped ensure that their approach could predict kidney disease in different populations.
“This study highlights the unique strength of the Hong Kong Diabetes Register and its enormous potential to spur further discoveries to improve our understanding of diabetes and its complications,” says study co-author Juliana Chan, a professor in the FRCP Department. Are. Medicine and Medicine at the Chinese University of Hong Kong, who established the Hong Kong Diabetes Register more than two decades ago.
The researchers are currently working to further refine their model. They are also expanding the application of their approach to look at other questions about human health and disease such as determining why some people with cancer do not respond well to certain treatments.