Genetics of diabetes

Abstract

Diabetes mellitus is a complicated disease characterized by a complex interplay of genetic, epigenetic, and environmental variables. It is one of the world's fastest-growing diseases, with 783 million adults expected to be affected by 2045. Devastating macrovascular consequences (cerebrovascular disease, cardiovascular disease, and peripheral vascular disease) and microvascular complications (like retinopathy, nephropathy, and neuropathy) increase mortality, blindness, kidney failure, and overall quality of life in individuals with diabetes. Clinical risk factors and glycemic management alone cannot predict the development of vascular problems; multiple genetic investigations have revealed a clear hereditary component to both diabetes and its related complications. In the twenty-first century, technological advancements (genome-wide association studies, next-generation sequencing, and exome-sequencing) have led to the identification of genetic variants associated with diabetes, however, these variants can only explain a small proportion of the total heritability of the condition. In this review, we address some of the likely explanations for this "missing heritability", for diabetes such as the significance of uncommon variants, gene-environment interactions, and epigenetics. Current discoveries clinical value, management of diabetes, and future research directions are also discussed.

Keywords: Type 1 diabetes, Type 2 diabetes, Gestational diabetes mellitus, Maturity-onset diabetes of young, Genome-wide association studies, Common variants, Rare variants

Core Tip: Diabetes pathogenesis encompasses genetic, epigenetic, and environmental variables and their interactions. To date, the examined common variations can explain just a small portion of the heritability of diabetes. Furthermore, the technique of integrating the associated variants as a type of genetic risk score does not accurately predict diabetes risk. As a result, the trend for genetic risk factors for diabetes is shifting from common to rare variants. Aside from genetic variables, systemic data from other transomics such as epigenomics, transcriptomics, proteomics, metabolomics, and metagenomics will contribute to a better understanding of genetic determinants in the progression of metabolic illnesses like diabetes. Technological, computational, and collaborative developments continue to uncover novel genetic diabetes risk factors. There are high prospects for tailored diabetes treatment in the future, based on increased knowledge of the molecular genetic profile of the patients.