The PREDICT T1D Study group

Plasma RNA Evaluation for Diagnosing Incident risk of Clinical Type 1 Diabetes The PREDICT T1D group represents a collaborative effort between clinicians, consumers, researchers, academics, data scientists, bioinformaticians and engineers across seven countries, united by their interests in focusing on assessing the potential of microRNA-based biomarkers for Type 1 Diabetes (T1D). The study assesses a set of RNA molecules (called microRNAs) that the investigators discovered and validated in multi-national (multi-context) cohorts on individuals without, at-risk or with T1D. A brief introduction to microRNAs is provided in the figure below:
Read about our preprint, tweet, comment and connect with us through this link: or read the preprint on Research Square. Identifying biomarkers of functional β-cell loss is critical in risk stratification for Type 1 Diabetes (T1D). We report a microRNA-based dynamic (responsive to environment) risk score developed using multi-center, multi-ethnic/country (“multi-context”) cohorts. Discovery (wet-lab and dry-lab) analysis identified 50 microRNAs that were measured across n=2,204 individuals from four contexts (4C=AUS/Australia, DNK/Denmark, HKG/Hong Kong SAR China, IND/India). A microRNA-based dynamic risk score (DRS) was generated (DRS4C), which effectively stratified individuals with/without T1D. Generative artificial intelligence (GAI) was used to create an enhanced (e)DRS4C that showed AUC >0.84 on an independent Validation set (n=313) from AUS, IND and NZL and predicted future exogenous-insulin requirement in islet transplantation recipients from Canada (CAN). In another T1D therapy, this microRNA signature stratified 1-year response to imatinib based on their profile at the study baseline. Utilizing machine learning and GAI, this study identified and validated a microRNA-based DRS for T1D stratification and treatment efficacy prediction. Also read our related article on T1D biomarkers: Joglekar M, Kaur S, Pociot F and Hardikar A (2024) Lancet D&E The PREDICT T1D study group collaborators contributing to this work are listed in the preprint. Future publications will have an updated list of all contributing researchers/collaborators.