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. 2025 Jan 16;26(2):740.
doi: 10.3390/ijms26020740.

Genetic Structure of Hereditary Forms of Diabetes Mellitus in Russia

Affiliations

Genetic Structure of Hereditary Forms of Diabetes Mellitus in Russia

Ildar R Minniakhmetov et al. Int J Mol Sci. .

Abstract

Analyzing the genetic architecture of hereditary forms of diabetes in different populations is a critical step toward optimizing diagnostic and preventive algorithms. This requires consideration of regional and population-specific characteristics, including the spectrum and frequency of pathogenic variants in targeted genes. As part of this study, we used a custom-designed NGS panel to screen for mutations in 28 genes associated with the pathogenesis of hereditary diabetes mellitus in 506 unrelated patients from Russia. The study identified 180 pathogenic or likely pathogenic variants across 13 genes (GCK, HNF1A, HNF1B, HNF4A, ABCC8, INS, INSR, KCNJ11, PAX4, PDX1, ZFP57, BLK, WFS1), representing 46.44% of the analyzed cohort (235 individuals). The glucokinase gene (GCK) had the highest number of identified variants, with 111 variants detected in 161 patients, 20 of which were identified for the first time. In the tissue-specific transcription factor genes HNF1A, HNF4A, and HNF1B, 34 variants were found in 38 patients, including 13 that were previously unreported. Seventeen variants were identified in the ABCC8 gene, which encodes the ATP-binding cassette transporter 8 of subfamily C, each found in a different patient; four of these were novel discoveries. Nine pathogenic or likely pathogenic variants were identified in the insulin gene (INS) and its receptor gene (INSR), including four previously unreported variants. Additionally, we identified 10 previously unreported variants in six other genes among 11 patients. Variants in the genes GCK, HNF1A, HNF1B, HNF4A, ABCC8, INS, and INSR were the main contributors to the genetic pathogenesis of hereditary diabetes mellitus in the Russian cohort. These findings enhance our understanding of the molecular mechanisms underlying the disease and provide a solid basis for future studies aimed at improving diagnostic accuracy and advancing personalized therapeutic strategies. This knowledge provides a foundation for developing region-specific genetic testing algorithms and personalized therapeutic strategies, which are critical for future initiatives in precision medicine.

Keywords: diabetes mellitus; maturity onset diabetes of the young; neonatal diabetes.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The percentage distribution of different types of genetic variants in the GCK gene in the patient cohort. Missense mutations are the most common, while a large deletion is a single variant identified in this gene.
Figure 2
Figure 2
The distribution of genetic variants in the studied cohort of patients for the GCK gene. Genetic variants were identified in all exons except exon 1. The highest number of genetic variants was found in exons 7 and 9. No pathogenic or likely pathogenic mutations were identified in exon 1. Variants identified for the first time are highlighted with an orange frame. Missense variants are highlighted in black, nonsense variants in blue, frameshift variants in purple, splicing variants in red, and deletions in green.
Figure 3
Figure 3
The percentage distribution of different types of genetic variants in the HNF1A gene in the patient cohort. Missense mutations are the most common.
Figure 4
Figure 4
The distribution of genetic variants in the studied cohort of patients for the HNF1A gene. Genetic variants were identified in 8 out of 10 exons. The highest number of genetic variants was found in exon 2. Variants identified for the first time are highlighted with an orange frame. Missense variants are highlighted in black, nonsense variants in blue, frameshift variants in purple, and deletions in green.

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