A microRNA-based dynamic risk score for type 1 diabetes
Authors' conclusion
This study harnessed machine learning/generative artificial intelligence approaches, identifying and validating a miRNA-based DRS for T1D discrimination and treatment efficacy prediction.
Study context
- Population
- Individuals with and without T1D from four contexts (Australia, Denmark, Hong Kong SAR People's Republic of China, India)validation n = 662
- Participants
- 2,204 individuals
- Outcome
- Enhanced four-context miRNA-based DRS for T1D stratification in separate multicontext validation dataset
Methodological detailsmulticenter, multiethnic, multicountry, machine learning/generative artificial intelligence
- Multicenter
- Multiethnic
- Multicountry
- Machine learning/generative artificial intelligence
Performance
As reported in the abstract
AUC
0.84
Discovery identified microRNA (miRNAs) associated with functional β cell loss
50
Further findings
Prediction of future exogenous insulin requirement after islet transplantation · 1 hour of islet transplantation
- Enhanced dynamic risk score (DRS) accurately predicted future exogenous insulin requirement
Imatinib response in a clinical trial · 1 year
- Baseline miRNA signature, rather than clinical characteristics, distinguished drug responders from nonresponders
Original publication
A microRNA-based dynamic risk score for type 1 diabetes. Nat Med. Published 5 June 2025. doi:10.
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