Monogenic diabetes: An evidence-based clinical approach.

Abstract

Monogenic diabetes is a heterogeneous disorder characterized by hyperglycemia arising from defects in a single gene. Maturity-onset diabetes of the young (MODY) is the most common type with 14 subtypes, each linked to specific mutations affecting insulin synthesis, secretion and glucose regulation. Common traits across MODY subtypes include early-onset diabetes, a family history of autosomal dominant diabetes, lack of features of insulin resistance, and absent islet cell autoimmunity. Many cases are misdiagnosed as type 1 and type 2 diabetes mellitus. Biomarkers and scoring systems can help identify candidates for genetic testing. GCK-MODY, a common subtype, manifests as mild hyperglycemia and doesn't require treatment except during pregnancy. In contrast, mutations in HNF4A, HNF1A, and HNF1B genes lead to progressive beta-cell failure and similar risks of complications as type 2 diabetes mellitus. Neonatal diabetes mellitus (NDM) is a rare form of monogenic diabetes that usually presents within the first six months. Half of the cases are lifelong, while others experience transient remission. Permanent NDM is most commonly due to activating mutations in genes encoding the adenosine triphosphate-sensitive potassium channel (KCNJ11 or ABCC8) and can be transitioned to sulfonylurea after confirmation of diagnosis. Thus, in many cases, monogenic diabetes offers an opportunity to provide precision treatment. The scope has broadened with next-generation sequencing (NGS) technologies, replacing older methods like Sanger sequencing. NGS can be for targeted gene panels, whole-exome sequencing (WES), or whole-genome sequencing. Targeted gene panels offer specific information efficiently, while WES provides comprehensive data but comes with bioinformatic challenges. The surge in testing has also led to an increase in variants of unknown significance (VUS). Deciding whether VUS is disease-causing or benign can be challenging. Computational models, functional studies, and clinical knowledge help to determine pathogenicity. Advances in genetic testing technologies offer hope for improved diagnosis and personalized treatment but also raise concerns about interpretation and ethics.