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Minerva Medica 2019 December;110(6):499-506

DOI: 10.23736/S0026-4806.19.06053-1

Copyright © 2019 EDIZIONI MINERVA MEDICA

language: English

The utility of MODY Probability Calculator in probands of families with early-onset autosomal dominant diabetes from Poland

Jerzy HOHENDORFF 1, 2, Barbara ZAPALA 3, Agnieszka H. LUDWIG-SLOMCZYNSKA 4, Iwona SOLECKA 1, 2, Damian UCIEKLAK 1, 2, Bartlomiej MATEJKO 1, 2, Sandra MROZINSKA 1, 2, Maciej T. MALECKI 1, 2, Magdalena SZOPA 1, 2

1 Department of Metabolic Diseases, Jagiellonian University Medical College, Krakow, Poland; 2 Krakow University Hospital, Krakow, Poland; 3 Department of Clinical Biochemistry, Jagiellonian University Medical College, Krakow, Poland; 4 Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Krakow, Poland



BACKGROUND: Maturity-onset diabetes of the young (MODY) accounts for 1-2% of all diabetes cases. Unfortunately, circa 90% of MODY cases are misdiagnosed as type 1 or type 2 diabetes. A proper genetic diagnosis based on automatic sequencing is crucial for the use of a tailored treatment. However, this method is still expensive and, thus, patients’ selection for testing should be performed precisely. In 2012, an easy-to-use tool was developed in Exeter, UK, to support genetic testing for MODY in the British population. The aim of the study was to assess the utility of MODY Probability Calculator in probands from Polish families with early-onset autosomal dominant diabetes.
METHODS: We have performed a retrospective analysis of 155 probands who were qualified for genetic testing between 2006 and 2018. Probands were recruited for MODY testing based on the following criteria: 1) early age of diagnosis (≤35 years); 2) a positive, multigenerational family history of diabetes. Automatic sequencing, Sanger and, in case of initial negative results, new generation sequencing (NGS) of a set of 28 genes, were performed. MODY Probability was calculated on the website www.diabetesgenes.org.
RESULTS: The group of probands consisted of 64 GCK-, 37 HNF1A-, and three HNF4A-MODY patients and 51 NGS-negative subjects. The median positive predictive value (PPV) was 75.5% (95% CI: 75.5-75.5%), 49.4% (95% CI: 24.4-75.5%), 45.5% (95% CI: 21.0-75.5%) and 49.4% (95% CI: 32.9-75.5%) for GCK-, HNF1A-, HNF4A-MODY and NGS-negative, respectively. The discriminative accuracy, as expressed by AUC, of PPV between MODY and NGS negative groups was 0.62 (95% CI: 0.52-0.71) with the corresponding sensitivity of 71.2% and specificity of 51.0%.
CONCLUSIONS: In this highly pre-selected group of probands that were qualified for genetic testing based on clinical features, the use of MODY Probability Calculator would not substantially improve the patients’ selection process for genetic testing. Further efforts to improve this tool are desirable.


KEY WORDS: Probability; Sampling studies; Diagnostic errors; Human HNF1A protein; Human HNF4A protein

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