Clinical studies

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. The final version is now accepted for publication and will be out shortly.  Follow this space for updates.

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 (consortium) authors contributing to this work are listed in the table below. Authors on the PREDICT T1D study are profiled below with links to their webpage.

PREDICT T1D - study leads

Prof. Anand Hardikar and Dr. Mugdha Joglekar planned this study whilst waiting for a weather-related delayed Qantas flight in 2009.  Although planning for this project began in 2009, the first major funding came in 2012 as an ARC Future Fellowship to Prof. Hardikar, generating basic research leads to future translational research fellowships and grants from Breakthrough T1D (formerly JDRF Australia and JDRFI) and The Leona M. and Harry B. Helmsley Charitable Trust. The refinement in protocols over the initial years, inclusion of generative AI-based workflows and the networking across over two dozen centers  led to the submission of this work to Nature Medicine. 
Collaborations are always welcome to further test the applicability of our microRNA-based signature in T1D. Any correspondance related to the PREDICT T1D study can be made via contacting the investigators directly (Prof. Anand Hardikar - is the Lead Principle Investigator for the study.  Dr. Mugdha Joglekar is a co-corresponding author on the study).  

Mugdha Joglekar

PREDICT T1D lead researcher

Anand Hardikar

Study PI - PREDICT T1D

#	PREDICT T1D Study group member name	Affiliation (Contribution to this study - current affiliation in the link)
1	Caroline Taylor, Maria Virginia Pereira E Cotta, Nirupa Sachithanandan	Diabetes & Islet Biology Group, O’Brien Institute and University of Melbourne, Australia
2	Charlotte Dong, Fahmida K Ema, Sathya Perera, Sarang Satoor,	Diabetes & Islet Biology Group, The University of Sydney, Camperdown, Australia
3	Pamela Acosta, Ritesh Chimoriya,	Macarthur Diabetes Endocrinology and Metabolism Service Camden and Campbelltown Hospital, Western Sydney University School of Medicine, Sydney, Australia.
4	Nirubasini Paramalingam, Chontiey Saxon	Telethon Kids Institute and Perth Children's Hospital, University of Western Australia, Perth, Australia
5	Indri Purwana, Saira Qureshi, Peter Senior	Alberta Diabetes Institute, University of Alberta, Edmonton, AB, Canada.
6	Gilles Guillemin	IPB University, Bogor, Indonesia
7	Sonia Isaacs	Virology Research Laboratory, Serology and Virology Division, NSW Health Pathology, Prince of Wales Hospital, Sydney, Australia
8	Thomas Loudovaris, Helen Thomas	St. Vincent's Institute, Fitzroy, Victoria, Australia
9	David Martin	Strathfield Private Hospital, Sydney, New South Wales, Australia
10	Jenny Gamble	Vascular Biology Program, Centenary Institute, Camperdown, NSW, Australia.
11	Yoon Hi Cho	The Children's Hospital at Westmead, Sydney, New South Wales, Australia
12	Suzette Coat	Discipline of Obstetrics & Gynecology and Robinson Research Institute, University of Adelaide, Adelaide, SA, Australia
13	David O’Neal	Department of Endocrinology, St Vincents Hospital, Melbourne, Australia
14	Martha Lappas	Obstetrics, Nutrition and Endocrinology Group, Department of Obstetrics and Gynaecology, University of Melbourne, Heidelberg, VIC, Australia
15	Sandy Shultz	Department of Neuroscience, School of Translational Medicine, Monash University, Australia
16	Stuart McDonald	Monash Trauma Group, Fluid Biomarker Research, Department of Neuroscience, School of S Medicine, Monash University, VIC, Australia
17	Elham Hosseini Beheshti, Georges Grau	School of Medical Sciences, The University of Sydney, Camperdown, NSW 2006, Australia
18	Andrzej Januszewski, Emma Scott	Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
19	Wayne J Hawthorne	The Centre for Transplant & Renal Research, Westmead Institute for Medical Research, Westmead, NSW, Australia
20	Amita Limaye, Ralph Bright	Macquarie Stem Cells Centres of Excellence, 21b Bathurst Street, Liverpool, NSW, Australia
21	Guozhi Jiang	Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China.
22	Dattatray Bhat, Aboli Bhalerao, Alma Baptist, Rucha Wagh, Smita Dhadge, Vidya Gokhale, Kalpana Jog, Tejas Limaye, Neelima Thuse,	Diabetes Unit, The King Edward Memorial Hospital, Pune, India
23	Rohan R Patil, Mahesh S Karandikar	Central Research Facility, Dr D. Y. Patil Medical College, Hospital and Research Centre, Pimpri, Pune, India.
24	Sharda Bapat	Healthcare Analytics, AlgoAnalytics, Pune, India.
25	Sheela Joglekar, Vinay Joglekar	Shree Seva Medical Foundation, Shirwal, India
26	Janet Rowan	National Women's Health, Auckland City Hospital and The University of Auckland, Auckland, New Zealand
27	Noha Lim	Immune Tolerance Network, Bethesda, MD, USA.

Credits: PREDICT T1D logo is designed and conceptualised by Aditi Hardikar. 