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

Quality of life assessment in patients with HNF1A-MODY and GCK-MODY.

AIM: The impact of maturity onset diabetes of the young (MODY) on quality of life (QoL) has never been examined. We assessed disease impact on QoL among patients with HNF1A-MODY and GCK mutation carrier status. METHODS: The study included 80 patients with HNF1A-MODY and 89 GCK gene mutation carriers. We also examined 128 type 1 diabetes (T1DM) patients for comparison. Diabetes-specific QoL was assessed using the Audit of Diabetes Dependent Quality of Life questionnaire. RESULTS: HNF1A-MODY and GCK-MODY groups had similar mean age (41.7 vs. 38.0 years, respectively) and BMI (24.1 vs. 24.3 kg/m2), whereas T1DM patients were on average younger (34.2 years) with similar BMI (25.0 kg/m2). Less than a third of GCK mutation carriers were on pharmacotherapy (n = 20, 31%), while the majority of HNF1A mutation carriers used oral drugs or insulin (n = 66, 82.5%). While current QoL was similar across the three groups (p = 0.66), two other major indices-the impact of diabetes on QoL and the average weighted impact (AWI)-differed among them (p < 0.001 for both comparisons). The impact of diabetes on patient QoL and AWI observed in both MODY groups was smaller than in T1DM. Etiological diagnosis of diabetes and a diagnosis of retinopathy were the only independent factors influencing the impact of diabetes on QoL and AWI in regression analysis. In HNF1A-MODY, all three major indices of QoL were more heavily influenced for patients on insulin in comparison to other treatment sub-groups. CONCLUSION: MODY has a smaller negative impact on QoL compared to T1DM. Mode of treatment further stratifies QoL decline for HNF1A-MODY subjects.

Circulating ghrelin level is higher in HNF1A-MODY and GCK-MODY than in polygenic forms of diabetes mellitus.

Ghrelin is a hormone that regulates appetite. It is likely to be involved in the pathophysiology of varying forms of diabetes. In animal studies, the ghrelin expression was regulated by the hepatocyte nuclear factor 1 alpha (HNF1A). Mutations of the HNF1A gene cause maturity onset diabetes of the young (MODY). We aimed to assess the circulating ghrelin levels in HNF1A-MODY and in other types of diabetes and to evaluate its association with HNF1A mutation status. Our cohort included 46 diabetic HNF1A gene mutation carriers, 55 type 2 diabetes (T2DM) subjects, 42 type 1 diabetes (T1DM) patients, and 31 glucokinase (GCK) gene mutation carriers with diabetes as well as 51 healthy controls. Plasma ghrelin concentration was measured using the immunoenzymatic assay with polyclonal antibody against the C-terminal fragment of its acylated and desacylated forms. Ghrelin concentrations were 0.75 ± 0.32, 0.70 ± 0.21, 0.50 ± 0.20, and 0.40 ± 0.16 ng/ml in patients with HNF1A-MODY, GCK-MODY, T1DM, and T2DM, respectively. The ghrelin levels were higher in HNF1A-MODY and GCK-MODY than in T1DM and T2DM (p < 0.001 for all comparisons) but lower than in non-diabetic controls (1.02 ± 0.29 ng/ml, p < 0.001 for both comparisons). In the multivariate linear model, the differences between both MODY groups and common diabetes types remained significant. Analysis by a HNF1A mutation type indicated that ghrelin concentration is similar in patients with different types of sequence differences. Plasma ghrelin level is higher in HNF1A-MODY and GCK-MODY than in the common polygenic forms of diabetes.

Assessment of insulin sensitivity in adults with permanent neonatal diabetes mellitus due to mutations in the KCNJ11 gene encoding Kir6.2.

Activating mutations in the KCNJ11 gene encoding the Kir6.2 subunit of ATP-sensitive potassium channel have been described in patients with permanent neonatal diabetes mellitus (PNDM). The main pathophysiological feature of PNDM associated with Kir6.2 mutations is a profound defect in insulin secretion. However, the expression of Kir6.2 protein is not limited to beta-cells; it also includes skeletal muscles, heart, brain, and peripheral nerves. Thus, the hypothesis that Kir6.2 mutations may influence insulin sensitivity in humans seems justified. Moreover, this notion is additionally supported by an animal model of Kir6.2 knock-out mice. Four adult carriers of a Kir6.2 mutation from the Polish population (mean age 31.5 years, range 20-50) were available for this study that aimed to evaluate their insulin sensitivity by the hyperinsulinemic euglycemic clamp technique. Three subjects carried the R201H mutation and one patient was a carrier of the K170N mutation. In addition, eight healthy volunteers with normal glucose tolerance were examined for comparison (mean age 31.0 years, range 20-41). The mean M value, i.e. the amount of metabolized glucose, for PNDM cases equaled 4.49 mg/(kg x min) (range 2.76-6.66) and was significantly lower than in the control group (9.64 mg/(kg x min), range 4.59-18.00). This observation suggests that impaired insulin sensitivity, in addition to profoundly decreased insulin secretion, contributes to the clinical picture of PNDM resulting from mutations in the Kir6.2 gene. An additional factor that might influence insulin sensitivity in our diabetes patients is glucose toxicity that may have appeared due to poor metabolic control prior to the examination (mean HbA1c = 8.95%). The intriguing question to be answered in the future is whether an improvement in insulin action could be seen following the transfer of Kir6.2 mutation carriers to sulphonylurea compounds.