Clinical Genetics of Diabetes

Background/Objective: Pancreatic and duodenal homeobox 1 (PDX1) is a key transcription factor required for pancreatic development and maintenance of β-cell function. Genetic variants in PDX1 have been associated with monogenic forms of diabetes, including maturity-onset diabetes of the young type 4 (MODY4). However, the func-tional consequences of many reported non-synonymous single-nucleotide polymorphisms (nsSNPs) in PDX1 remain unclear. In this study, an integrated in silico approach was applied to systematically identify and characterize po-tentially deleterious nsSNPs in the PDX1 gene. Methods: Missense variants were retrieved from public databases and evaluated using multiple sequence- and structure-based prediction tools to assess functional impact, disease association, protein stability, and structural consequences. Variants considered deleterious were further examined through three-dimensional structural modeling and molecular dynamics simulation. Results: Several nsSNPs were identified with consistent predictions of pathogenicity, reduced protein stability, and pronounced structural and dynamic perturbations. Variants including R197G, Y170N, and T151K in the PDX1 Protein were considered the highest deleterious mutants. Conclusion: These findings will provide insight into the molecular mechanisms by which PDX1 mutations may contribute to β-cell dysfunction and diabetes development and offer a rational framework for prior-itizing variants for experimental validation and clinical interpretation. Full article

Diabetic kidney disease (DKD) affects a substantial proportion of individuals with diabetes mellitus and represents the leading cause of end-stage renal disease worldwide. Familial aggregation studies consistently demonstrate that genetic factors contribute significantly to DKD susceptibility beyond metabolic and hemodynamic determinants. The carnosine dipeptidase 1 (CNDP1) gene on chromosome 18q22.3 has emerged as a compelling susceptibility locus, with a trinucleotide (CTG) repeat polymorphism in exon 2 that encodes the Mannheim variant, which has demonstrated protective associations in selected populations. Individuals homozygous for the shorter (CTG)₅ allele exhibit reduced serum carnosinase-1 concentrations and activity, resulting in elevated tissue carnosine levels. Carnosine exerts multiple renoprotective effects, including antioxidant activity, inhibition of advanced glycation end-product formation, and attenuation of profibrotic signaling. Experimental models demonstrate that genetic or pharmacological reduction in carnosinase activity attenuates diabetic kidney injury. Early clinical studies of carnosine supplementation report improvements in albuminuria and oxidative stress markers, though available trials are limited in size, duration, and population scope. Therapeutic targeting of CNDP1 via carnosinase inhibition, therefore, represents a biologically grounded yet still emerging pharmacological strategy. This review synthesizes genetic, molecular, and translational evidence supporting CNDP1 as a model for genetics-informed therapeutic development in DKD, while highlighting important population-specific variation in allele frequencies that constrain universal clinical applicability. Full article

Gestational diabetes mellitus (GDM) is a prevalent pregnancy complication with significant short- and long-term consequences for mothers and offspring. While environmental factors, such as obesity and diet, contribute to the risk, genetic predisposition also plays a role in the pathogenesis of GDM. Genome-wide association studies have identified multiple susceptibility loci, including MTNR1B, CDKAL1, and IRS1, which represent mechanistically distinct pathways affecting β-cell function, insulin secretion, and peripheral insulin signaling. This review provides a unified mechanistic framework explaining why these three genes, despite individually modest effect sizes, offer complementary insights into GDM pathophysiology that extend beyond other established loci such as TCF7L2. We critically evaluate the current evidence for genetic risk scores in GDM prediction, acknowledging that their incremental predictive value beyond traditional clinical factors remains modest AUC improvement typically <0.05). The integration of genetic variants with epigenetic modifications is discussed, with careful attention to distinguishing causal mechanisms from correlative findings. We emphasize significant limitations in current research, including population stratification, winner’s curse effects, and the predominance of East Asian cohorts. While genetic insights may eventually inform risk stratification, substantial barriers remain before clinical implementation, including insufficient predictive accuracy, lack of cost-effectiveness data, and limited generalizability across diverse populations. Future directions include integrating multi-omics data, developing ethnically validated polygenic risk scores, and conducting pragmatic randomized controlled trials to establish the clinical utility of precision prevention strategies. Full article

Background: Diabetes mellitus is characterized by elevated blood sugar due to absolute or relative insulin deficiency. Diabetes is classified as type 1 (T1D) or type 2 diabetes (T2D), gestational diabetes, and other types, such as monogenic diabetes, exocrine pancreatic disorders, and medication-induced diabetes. Objectives: This review article provides an overview of diabetes genetics, covering polygenic, monogenic, and syndromic forms of the disorder with emphasis on aspects to help clinicians in diagnosis, management, and counseling, but also to foster valuable knowledge for diabetic researchers in identifying phenotypes that will help inform gene discovery. Key Findings: Most cases of T1D and T2D are polygenic with environmental triggers. T1D results from autoimmune destruction of pancreatic beta cells leading to absolute insulin deficiency. Genetic studies of T1D have focused on the identification of loci associated with increased susceptibility to T1D. Early studies showed a linkage between T1D and several human leukocyte antigen (HLA) susceptibility loci on chromosome 6. Genome-wide association studies (GWAS) have identified more than 100 HLA- and non-HLA loci that increase susceptibility to T1D. It has been well established that a substantial portion of the genetic risk for T1D is encoded in the HLA locus. The non-HLA loci INS, CTLA4, IL2RA, IFIH1, and PTPN22 make moderate contributions to T1D risk. Many other non-HLA loci have small effects to the phenotype and are relevant to autoimmunity, but they are yet to be identified. T2D, on the other hand, is associated with obesity and insulin resistance with relative insulin deficiency. Thousands of gene variants that are common and contribute small effects have also been identified through GWAS to contribute to T2D risk, but the rarer variants may confer significant risk to an individual’s risk. Common variants in the TCF7L2 locus consistently carry one of the largest risks associated with T2D with a reported 1.7-fold disease odds for homozygous carriers. The usefulness of individual variants for genetic counseling in the common forms of diabetes has been limited in clinical settings in the past. The development of polygenic risk scores (PRS) and partitioned polygenic risk scores (PPRS), statistics derived from GWAS, are being used to predict and classify diabetes. The performance of PRS and PPRS varies by ancestry and type of diabetes. The PRS performs better with T1D, with an area under the curve and receiver operating characteristics (AUC-ROC) ranging from 0.87 to 0.93, compared to 0.72–0.75 for T2D. The genetic architecture of T2D is markedly more polygenic than T1D, and the PPRS has been useful in assessing risk in that setting. Monogenic diabetes comprises several dysglycemic disorders that include neonatal diabetes, maturity-onset diabetes of the young (MODY), and other genetic syndromes that have diabetes either as an associated finding and/or as a 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. Many monogenic disorders follow Mendelian inheritance patterns, so genetic counseling is relatively straightforward if pathogenic variants are found to be inherited from a parent. Counseling for forms of diabetes due to maternally inherited mitochondrial cytopathies, such as MELAS and Kearns–Sayres syndrome, is not straightforward due to the occurrence of two or more populations of genetically distinct mitochondrial DNAs in the cells (heteroplasmy); the higher the percent of pathogenic variants in a cell or tissue, the greater the chance for affectation of disorder. Implications: Early stages of diabetes may be asymptomatic, and improvement in methodologies to identify individuals at high risk is important so prevention strategies can be targeted to susceptible individuals to slow or obviate the onset of disease and to minimize complications. Conclusions: Diabetes is a heterogeneous disorder, and accurate definition of phenotypes in the setting of non-syndromic and syndromic forms, development of powerful statistical methodologies, use of next-generation sequencing applications to interrogate the genome, incorporation of epigenetic mechanisms in statistical modeling and accurate curation of gene variants, will help us to realize application of genomic medicine and to inform diabetes care. Full article