Daijiworld Media Network – Sydney
Sydney, Jun 7: In a groundbreaking development, researchers at Western Sydney University have created a cutting-edge AI-powered tool that can predict the risk of developing Type 1 diabetes (T1D) and assess responses to treatment—potentially transforming how the disease is diagnosed and managed.
The tool uses a novel Dynamic Risk Score (DRS4C) based on microRNAs—small molecules measured from blood samples—to provide a real-time picture of T1D progression risk. Unlike genetic testing, which offers a static view, DRS4C captures dynamic changes, enabling timely medical intervention.
“T1D risk prediction is critical, especially since early-onset T1D before age 10 can reduce life expectancy by up to 16 years. Accurate prediction helps us intervene sooner,” said Prof Anand Hardikar, lead investigator from the university's School of Medicine and Translational Health Research Institute.
Published in Nature Medicine, the study analysed nearly 6,000 samples from participants across India, Australia, Canada, Denmark, Hong Kong, New Zealand, and the US. The AI-enhanced tool was further validated in an independent group of 662 individuals. Remarkably, it could predict just one hour after therapy who would remain insulin-free.
Beyond T1D diagnosis, the tool also shows promise in distinguishing between type 1 and type 2 diabetes and predicting drug efficacy.
Dr Mugdha Joglekar, co-lead researcher, highlighted the tool’s advantage over genetic markers. “While genetic markers reveal a fixed lifetime risk, our dynamic risk score reflects real-time danger—like monitoring rising water during a flood rather than just knowing you live in a flood-prone area,” she explained.
The breakthrough promises timely, personalised, and stigma-free monitoring for those at risk of or already battling diabetes.