Overview of Clinical Genetics of Diabetes Mellitus

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This review discusses the genetic basis of diabetes mellitus, including polygenic forms like T1D and T2D and monogenic subtypes, and the development of polygenic risk scores for improved prediction and classification.

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Abstract

Diabetes mellitus is characterized by elevated blood sugar due to absolute or relative insulin deficiency. Diabetes is broadly classified into 2 major forms: type 1 diabetes mellitus (T1D) and type 2 diabetes mellitus (T2D). It is known also that other categories of diabetes exist, and this includes gestational diabetes, monogenic causes, rare syndromes, and iatrogenic causes. Most cases of T1D and T2D are polygenic with environmental triggers. T1D often results from autoimmune destruction of pancreatic beta cells leading to absolute insulin deficiency. T2D is associated with obesity, insulin resistance with relative insulin deficiency. Genetic studies have focused on the identification of loci associated with increased susceptibility to diabetes. Early studies showed linkage between T1D and several HLA susceptibility loci on chromosome 6. The HLA haplotypes DR3 (DQb1*201) and/or DR4 (DQb1*302) are susceptibility alleles and the DR2 (DQb1*602) is considered a protective allele for development of T1D. Genome-wide association studies (GWAS) have identified more than 100 HLA- and non-HLA loci that increase susceptibility to T1D; many of these loci have small effects to the phenotype and are relevant to autoimmunity. Some of the notable genes for T1D are INS, PTPN22, CTLA4. Regarding T2D risk, thousands of gene variants that are common and contribute small effects have also been identified through GWAS, but the rarer variants may confer significant risk to an individual’s risk. The usefulness of individual variants for genetic counseling in diabetes has been limited in the clinical setting in the past until the development of polygenic risk scores (PRS) and partitioned polygenic risk scores (PPRS) statistics derived from GWAS. PRS and PPRS are statistical methods that combine multiple disease-modifying variants obtained from GWAS to predict and classify diabetes. These scores use the cumulative effect of hundreds to millions of variants generated from GWAS to compute an individual’s relative risk. Currently more than 100 variants for T1D and over 1000 variants for T2D are utilized in risk analysis of diabetes. Continued investment in global consortia such as the Type 1 Diabetic Genetics Consortium (T1DGC), National Institute of Diabetes and Kidney Diseases (NIDDK), and the Wellcome Trust Case-Control Consortium (WTCCC) in genetic variant mapping will help identify genes involved in pathophysiologic pathways involved in insulin secretion and signaling, and provide insight into new targets for prediction, prevention and treatment of diabetes. Monogenic diabetes comprises several clinical dysglycemic disorders that include neonatal diabetes, maturity-onset diabetes of the young (MODY), and several genetic syndromes that have diabetes either as an associated finding and/or complication. Some of the monogenic diabetes gene variants have incomplete penetrance and variable expressivity leading to different ages of onset and variable presentation even within the same family. Hence some patients with these conditions have been previously diagnosed as having T1D or T2D. Monogenic disorders follow Mendelian inheritance patterns so genetic counseling is relatively straightforward. Counseling for forms of diabetes due to maternally inherited mitochondrial cytopathies such MELAS and Kearne-Sayres syndrome are not straight-forward due to heteroplasmy. Clearer definition of diabetes phenotypes, development of powerful statistical methodologies, use of next-generation sequencing applications to interrogate the genome, incorporation of epigenetic mechanisms and accurate curation of gene variants, will help us realize application of genomic medicine and inform diabetes care.

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last seen: 2026-05-20T01:45:00.602351+00:00
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License: CC-BY-4.0