Maturity-onset diabetes of the young (MODY) is a group of monogenic disorders of β-cell function which causes diabetes in young adults. Diagnosing MODY is important as the different subtypes have distinct first line treatments, e.g. low dose sulphonylureas in HNF1A mutations while no treatment is required in GCK mutations. This can lead to treatment changes including discontinuing insulin therapy. First degree family members can also be offered diabetes screening and genetic testing. However, there are considerable challenges in differentiating MODY from type 1 and type 2 diabetes and this means that an estimated 8090% of cases in the UK are undiagnosed and on average there is a delay of around 15 years after diagnosis of diabetes before a genetic diagnosis is established.
Finding economic, widely-available non-genetic biomarkers that can be used for screening to find those at high risk of MODY would be greatly advantageous. This lecture describes the recent progress that has been made in this area.
One approach to finding biomarkers is to use the fact that the transcription factor mutations that cause the commonest forms of MODY have extra-pancreatic manifestations not shared by type 1 or type 2 diabetes. Looking at hepatic genes regulated by HNF1A has lead to the identification that highly-sensitive C-reactive protein (hsCRP) is lower in HNF1A-MODY than in all other kinds of diabetes and non-diabetic individuals. Using hsCRP to differentiate HNF1A-MODY from type 2 diabetes diagnosed before 45 years has a sensitivity and specificity both around 80% and an area under the receiver operated characteristic curve of >0.8, indicating a good discriminative test. A model including simple clinical characteristics can improve this further.
Simple pathophysiological features can also form the basis for selection for genetic testing e.g. presence of C-peptide indicating endogenous insulin secretion can be a marker to differentiate MODY cases from those assumed to have type 1 diabetes.
The results of a novel discovery experiment using metabonomics to identify putative MODY biomarkers will also be presented.