Objective
Type 1 diabetes (T1D) involves destruction of insulin-producing cells. Current clinical tests, although useful to diagnose T1D, cannot accurately predict future T1D as they measure blood-based molecules that arise following the destruction of insulin producing cells. Through this study, we aim to validate the use of a novel test (just like a pregnancy test or similar to a Covid rapid antigen test) that will offer the capacity to measure a different class of blood-based molecules, which can help predict T1D progression. Early detection can help delay or even prevent diabetes.
Background Rationale
Unlike other (monogenic) forms of diabetes that are diagnosed/predicted with genetic analyses, type 1 diabetes (T1D) is a multifactorial disease. Although biochemical (autoantibody) measurements are currently used in clinical risk-stratification of T1D, antibodies themselves are a consequence of underlying pre-existent pathology. Genetics and/or family history is important in T1D prediction. However, 90% of individuals diagnosed with T1D do not have a family history of T1D, and genetics i.e. differences in our DNA, although important, are what we are born with and do not change over lifetime. Research that we and others have carried out has demonstrated that a set of biomarkers (called microRNAs) can be useful in identifying the dynamic changes in blood profiles leading to T1D. We also have a novel “Rapid PCR test” (similar to Covid Rapid Antigen Test), that enables to measure circulating microRNAs within minutes. Successful completion of this project will enable the validation of this novel technology in type 1 diabetes.
Description of Project
Although a strong genetic link is known to be associated in the development of Type 1 diabetes (T1D), it is well known that 90% of individuals who develop T1D do not have a family history of T1D. Thus, genetic factors alone do not fully explain future T1D risk. Currently, T1D is clinically diagnosed using autoantibodies, but autoantibodies themselves are a consequence of the underlying pre-existent pathology. There has been a growing need to identify biomarkers that are associated with and predictive of the molecular changes leading to T1D. We and others have demonstrated that small RNA molecules (called microRNAs) regulate the development and function of insulin-producing cells. We now present a unique opportunity to assess microRNAs using a Rapid PCR test that can profile T1D-associated microRNAs (patent through previous work with JDRF) in retrospective as well as prospective clinical samples. Study outcomes will help validate a low-cost population screening tool that captures the dynamic changes leading to T1D. With most samples already collected and available from multi-ethnic study cohorts, we present a unique opportunity to use this novel (NanoChip) Rapid PCR test technology. MicroRNA-based biomarker identification, validation and analysis in this unique low-costs, population screening ready NanoChip, is a strength of our proposal. With the availability of immune-modulatory therapies that can delay clinical onset of T1D, the need of accurate predictive biomarkers, such as ours, is imminent. A microRNA-based screening test would be particularly life changing for children where the diagnosis of T1D before 10 years of age is associated with a 16-year reduction in life expectancy.
Anticipated Outcome
This research is anticipated to validate a novel microRNA profiling technology that can predict the risk of T1D within minutes. It will provide a means for expanding collaborative links across several other T1D studies, broadened the ease and reliability of measuring dynamic molecular biomarkers in T1D, whilst retaining robust quality control (QC) and data integrity through machine learning workflows that are already identified and established by the team. A low cost of goods sold (COGS) is anticipated once mass production is engaged. This would facilitate a clear pathway to population screening using microRNA for T1D prediction. Since microRNAs are important regulators (as well as biomarkers), the test can be integrated with telehealth to provide a smartphone app that could translate the risk nomogram to explicable information for the end user. Collaborations would be worked in discussion with key researchers, industry partners, stakeholders and consumers.
Relevance to T1D
The recently completed trial of a drug (eg. anti-CD3 monoclonal antibody, teplizumab), demonstrated that treatment with teplizumab in Stage 2 T1D delayed the onset of insulin dependence (Stage 3 T1D) by an average of two years. A further six immunotherapies in addition to teplizumab have shown modest efficacy in delaying beta-cell death (C-peptide/insulin loss) in individuals newly diagnosed with T1D.
Initiating immune-modulatory therapies earlier in high-risk populations when little to no β-cell damage has occurred may further delay or even prevent the requirement for future exogenous insulin. This would be particularly life-changing for children as the diagnosis of T1D before 10 years of age is associated with a 16-year reduction in life expectancy . It is, therefore, timely to validate the predictive power of microRNA biomarkers (and other available data on neonatal metabolites) in predicting islet autoimmunity.