Switching From Insulin to Sulfonylurea in Diabetes Associated With Variants in MODY Genes

Maturity onset diabetes in the young (MODY) is characterised by monogenic diabetes due to beta-cell dysfunction, with typical onset of diabetes before age of 25 years. There are 14 known forms of MODY, ranging from rather common to extremely rare. About 1% of patients in the Norwegian Childhood Diabetes registry may have disease causing MODY mutations, according to a study recently published by the investigator's group and others. MODY associated mutations in the transcription factors HNF1A, HNF4A, and HNF1B leads to activation of the potassium channel causing depolarisation of the beta-cell membrane, which is crucial for excretion of insulin. By treating patients with HNF1A-MODY, HNF4A-MODY, and HNF1B-MODY with sulfonylurea class of drugs, these channels will close, causing depolarisation of the beta-cell membrane, and release of insulin. Hence, these patients can often stop insulin treatment when they are treated with sulfonylurea class drugs. Due to high throughput sequencing, a number of rare variants in these genes have been discovered. In many cases, bioinformatic tools are not sufficient to correctly classify these variants. In the present study, we intend to identify rare variants in the HNF1A, HNF4A, and HNF1B genes in patients with insulin dependent diabetes identified through the Norwegian Childhood Diabetes registry or the Norwegian MODY Registry with possibly disease causing HNF1A, HNF4A, or HNF1B mutations with sulfonylurea to see if they can reduce or even stop insulin treatment, and regulate their diabetes with sulfonylurea only. All variants will be investigated by bioinformatics tools as well as functional assays (tests for DNA-binding, transcriptional activation, nuclear localisation, protein expression). Primary endpoints are efficacy of sulfonylurea treatment measured by insulin requirement or not and level of HbA1c. Secondary endpoints are tolerance of sulfonylurea and effect on insulin secretion by oral and intravenous glucose tolerance tests. Bioinformatics and functional characterisation will be compared with success to reach primary endpoints.