Identification of pathogenic GCK variants in patients with common type 2 diabetes can lead to discontinuation of pharmacological treatment.

Background: Functionally disruptive variants in the glucokinase gene (GCK) cause a form of mild non-progressive hyperglycemia, which does not require pharmacological treatment. A substantial proportion of patients with type 2 diabetes (T2D) carry GCK variants. We aimed to investigate whether carriers of rare GCK variants diagnosed with T2D have a glycemic phenotype and treatment response consistent with GCK-diabetes. Methods: Eight patients diagnosed with T2D from the Danish DD2 cohort who had previously undergone sequencing of GCK participated. Clinical examinations at baseline included an oral glucose tolerance test and continuous glucose monitoring. Carriers with a glycemic phenotype consistent with GCK-diabetes took part in a three-month treatment withdrawal. Results: Carriers of pathogenic and likely pathogenic variants had lower median fasting glucose and C-peptide levels compared to carriers of variants of uncertain significance and benign variants (median fasting glucose: 7.3 (interquartile range: 0.4) mmol/l vs. 9.5 (1.6) mmol/l, p = 0.04; median fasting C-peptide 902 (85) pmol/l vs. 1535 (295) pmol/l, p = 0.03). Four participants who discontinued metformin treatment and one diet-treated participant were reevaluated after three months. There was no deterioration of HbA1c or fasting glucose (median baseline HbA1c: 49 (3) vs. 51 (6) mmol/mol after three months, p = 0.4; median baseline fasting glucose: 7.3 (0.4) mmol/l vs. 7.0 (0.6) mmol/l after three months, p = 0.5). Participants did not consistently fulfill best practice guidelines for GCK screening nor clinical criteria for monogenic diabetes. Discussion: Carriers of pathogenic or likely pathogenic GCK variants identified by unselected screening in T2D should be reported, as they have a glycemic phenotype and treatment response consistent with GCK-diabetes. Variants of uncertain significance should be interpreted with care. Systematic genetic screening of patients with common T2D receiving routine care can lead to the identification and precise care of patients with misclassified GCK-diabetes who are not identifiable through common genetic screening criteria.

Glucose metabolism in children and adolescents: Population-based reference values and comparisons to children and adolescents enrolled in obesity treatment.

BACKGROUND: Alterations in glucose metabolism that lead to the development of metabolic and cardiovascular disease may begin already in childhood. OBJECTIVE: This study aims to generate pediatric age and sex-specific reference values for fasting concentrations of glucose, hemoglobin A1c (HbA1c), insulin, C-peptide, and homeostasis model assessment: insulin resistance (HOMA-IR) in Danish/North-European white children and adolescents from a population-based cohort and to compare values from children and adolescents with overweight/obesity with this reference. METHODS: The population- and obesity clinic-based cohorts consisted of 2451 and 1935 children and adolescents between 6 and 18 years of age. Anthropometric measurements and blood samples were obtained and percentile curves were calculated. RESULTS: In the population-based cohort, glucose, insulin, and HOMA-IR values increased before the expected onset of puberty (P < .05). Thereafter, all variables decreased in girls (P < .05) and HbA1c decreased in boys (P < .05). Concentrations of all measured markers of glucose metabolism were higher in the obesity clinic-based cohort than the population-based cohort (both sexes P < .001). Specifically, insulin and HOMA-IR continued to increase to 18 years in the clinic-based cohort, particularly among boys. CONCLUSIONS: Fasting glucose, insulin, and HOMA-IR change during childhood, making pediatric reference values essential for timely identification of derangements in glucose metabolism. Children and adolescents with obesity exhibit increased concentrations of these biomarkers.

Plasma Alkylresorcinols Reflect Gluten Intake and Distinguish between Gluten-Rich and Gluten-Poor Diets in a Population at Risk of Metabolic Syndrome.

BACKGROUND: Many patients with celiac disease experience difficulties in adherence to a gluten-free diet. Methods for testing compliance to a gluten-free diet are costly and cumbersome. Thus, a simple biomarker of gluten intake is needed in a clinical setting and will be useful for epidemiologic studies investigating wider effects of gluten intake. OBJECTIVE: The aim was to evaluate plasma total alkylresorcinol concentrations as a measure of gluten intake. METHODS: In this randomized, controlled, crossover intervention study in 52 Danish adults with features of the metabolic syndrome, we compared 8 wk of a gluten-rich and gluten-poor diet separated by a washout period of ≥6 wk. We measured fasting plasma concentrations of alkylresorcinols to determine if they reflected differences in gluten intake as a secondary outcome of the original study. In addition, we investigated in 118 Danish adults the cross-sectional association between self-reported gluten intake and plasma alkylresorcinols in the same and a similar study at baseline. We used mixed-model ANCOVA for examining treatment effects, a classification tree to determine compliance to the gluten-poor diet, and linear regression models for examining baseline correlation between plasma alkylresorcinol concentrations and gluten intake. RESULTS: Plasma total alkylresorcinols decreased more during the gluten-poor period (geometric mean: -124.8 nmol/L; 95% CI: -156.5, -93.0 nmol/L) than in the gluten-rich period (geometric mean: -31.8 nmol/L; 95% CI: -63.1, -0.4 nmol/L) (P < 0.001). On the basis of the plasma alkylresorcinol profile, we built a classification tree to objectively determine compliance and found an overall participant misclassification error of 3.9%. In the cross-sectional study we found a 5.6% (95% CI: 2.4%, 8.9%) increase in plasma total alkylresorcinols per 1-g increase in reported gluten intake (P < 0.001). CONCLUSION: We propose the use of plasma alkylresorcinols to monitor compliance to a gluten-free diet as well as to help investigations into the possible effects of gluten in the wider population. This trial was registered at www.clinicaltrials.gov as NCT017119913 and NCT01731366.

Lessons from whole-exome sequencing in MODYX families.

We report the first results from whole-exome sequencing performed in families with Maturity-Onset Diabetes of the Young without a known genetic cause of diabetes (MODYX). This next generation sequencing technique pointed out that routine testing of MODY needs constant awareness and regular re-evaluation of both clinical criteria and primer sequences.

Mutations in HNF1A result in marked alterations of plasma glycan profile.

A recent genome-wide association study identified hepatocyte nuclear factor 1-α (HNF1A) as a key regulator of fucosylation. We hypothesized that loss-of-function HNF1A mutations causal for maturity-onset diabetes of the young (MODY) would display altered fucosylation of N-linked glycans on plasma proteins and that glycan biomarkers could improve the efficiency of a diagnosis of HNF1A-MODY. In a pilot comparison of 33 subjects with HNF1A-MODY and 41 subjects with type 2 diabetes, 15 of 29 glycan measurements differed between the two groups. The DG9-glycan index, which is the ratio of fucosylated to nonfucosylated triantennary glycans, provided optimum discrimination in the pilot study and was examined further among additional subjects with HNF1A-MODY (n = 188), glucokinase (GCK)-MODY (n = 118), hepatocyte nuclear factor 4-α (HNF4A)-MODY (n = 40), type 1 diabetes (n = 98), type 2 diabetes (n = 167), and nondiabetic controls (n = 98). The DG9-glycan index was markedly lower in HNF1A-MODY than in controls or other diabetes subtypes, offered good discrimination between HNF1A-MODY and both type 1 and type 2 diabetes (C statistic ≥ 0.90), and enabled us to detect three previously undetected HNF1A mutations in patients with diabetes. In conclusion, glycan profiles are altered substantially in HNF1A-MODY, and the DG9-glycan index has potential clinical value as a diagnostic biomarker of HNF1A dysfunction.