ArticleActa diabetologica2026
Search for the most precise diagnosis of monogenic diabetes - the usefulness of short-read NGS method in molecular testing in Polish patients.
Article in Acta diabetologica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Despite years of experience from scientific teams around the world, diagnosing the cause of monogenic diabetes (MD) remains a challenge, mainly due to the proper definition of the patients' phenotype and the multitude of molecular causes. Our goal was to present the results of the efforts to make the molecular diagnosis of patients with suspected MD as precise as possible from the last few years of our Rare Disease Center for Children and Adolescents and Diabetogenetics using the NGS (Next Generation Sequencing) method. We used a targeted NGS panel and whole exome sequencing (WES) data. The study group consisted of 644 individuals, including 501 patients who were referred from 17 Polish diabetes centers with suspected MD and who were diagnosed between January 2020 and December 2023, as well as their 143 family members. The median age for the patients was 14 years (IQR: 9-18). Overall, MD was confirmed by identifying the causative genetic variant in 43.3% of probands. We identified causative variants in 16 genes, most commonly in GCK and HNF1A (85.7%), mainly of the SNV (single nucleotide variant) type, and CNV variants in the GCK and HNF1B genes (1.4%). Using WES data, we could also identify the 17q12 syndrome in one patient. The subgroups of MD and unresolved patients differed in regard to age of clinical and genetic diagnosis (p = 0.00714 and p = 0.00004), birth weight (p = 0.00255), BMI (p = 0.00075), and HbA1c (p = 0.00001). Analysis of WES data (44%) and targeted gene panels (43%) provided similar results in successful diagnosis of MD. However, WES data offer a more complete molecular picture for the diagnosis of MD, especially for large rearrangements, and allow for kinship and ethnicity analysis, which can expand the scope of the diagnosis.
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