Background Recent diabetes subclassifications have improved the differentiation between patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus despite several overlapping features, yet without considering genetic forms of diabetes. We sought to facilitate the identification of monogenic diabetes by creating a new tool that we validated in a pediatric maturity-onset diabetes of the young (MODY) cohort.
Methods We first created the DIAgnose MOnogenic DIAbetes (DIAMODIA) criteria based on the pre-existing, but incomplete, MODY calculator. This new score is composed of four strong and five weak criteria, with patients having to display at least one weak and one strong criterion.
Results The effectiveness of the DIAMODIA criteria was evaluated in two patient cohorts, the first consisting of patients with confirmed MODY diabetes (n=34) and the second of patients with T1DM (n=390). These DIAMODIA criteria successfully detected 100% of MODY patients. Multiple correspondence analysis performed on the MODY and T1DM cohorts enabled us to differentiate MODY patients from T1DM. The three most relevant variables to distinguish a MODY from T1DM profile were: lower insulin-dose adjusted A1c score ≤9, glycemic target-adjusted A1c score ≤4.5, and absence of three anti-islet cell autoantibodies.
Conclusion We validated the DIAMODIA criteria, as it effectively identified all monogenic diabetes patients (MODY cohort) and succeeded to differentiate T1DM from MODY patients. The creation of this new and effective tool is likely to facilitate the characterization and therapeutic management of patients with atypical diabetes, and promptly referring them for genetic testing which would markedly improve clinical care and counseling, as well.
Monogenic diabetes, including maturity-onset diabetes of the young, neonatal diabetes, and other rare forms of diabetes, results from a single gene mutation. It has been estimated to represent around 1% to 6% of all diabetes. With the advances in genome sequencing technology, it is possible to diagnose more monogenic diabetes cases than ever before. In Korea, 11 studies have identified several monogenic diabetes cases, using Sanger sequencing and whole exome sequencing since 2001. The recent largest study, using targeted exome panel sequencing, found a molecular diagnosis rate of 21.1% for monogenic diabetes in clinically suspected patients. Mutations in glucokinase (GCK), hepatocyte nuclear factor 1α (HNF1A), and HNF4A were most commonly found. Genetic diagnosis of monogenic diabetes is important as it determines the therapeutic approach required for patients and helps to identify affected family members. However, there are still many challenges, which include a lack of simple clinical criterion for selecting patients for genetic testing, difficulties in interpreting the genetic test results, and high costs for genetic testing. In this review, we will discuss the latest updates on monogenic diabetes in Korea, and suggest an algorithm to screen patients for genetic testing. The genetic tests and non-genetic markers for accurate diagnosis of monogenic diabetes will be also reviewed.
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