Insulin resistance in skeletal muscle is a major risk factor for the development of type 2 diabetes in women with polycystic ovary syndrome (PCOS). In patients with type 2 diabetes, insulin resistance in skeletal muscle is associated with abnormalities in insulin signaling, fatty acid metabolism, and mitochondrial oxidative phosphorylation (OXPHOS). In PCOS patients, the molecular mechanisms of insulin resistance are, however, less well characterized. To identify biological pathways of importance for the pathogenesis of insulin resistance in PCOS, we compared gene expression in skeletal muscle of metabolically characterized PCOS patients (n = 16) and healthy control subjects (n = 13) using two different approaches for global pathway analysis: gene set enrichment analysis (GSEA 1.0) and gene map annotator and pathway profiler (GenMAPP 2.0). We demonstrate that impaired insulin-stimulated total, oxidative and nonoxidative glucose disposal in PCOS patients are associated with a consistent downregulation of OXPHOS gene expression using GSEA and GenMAPP analysis. Quantitative real-time PCR analysis validated these findings and showed that reduced levels of peroxisome proliferator–activated receptor γ coactivator α (PGC-1α) could play a role in the downregulation of OXPHOS genes in PCOS. In these women with PCOS, the decrease in OXPHOS gene expression in skeletal muscle cannot be ascribed to obesity and diabetes. This supports the hypothesis of an early association between insulin resistance and impaired mitochondrial oxidative metabolism, which is, in part, mediated by reduced PGC-1α levels. These abnormalities may contribute to the increased risk of type 2 diabetes observed in women with PCOS.

The most common genetic cause of neonatal diabetes and hyperinsulinism is pathogenic variants in ABCC8 and KCNJ11. These genes encode the subunits of the β‐cell ATP‐sensitive potassium channel, a key component of the glucose‐stimulated insulin secretion pathway. Mutations in the two genes cause dysregulated insulin secretion; inactivating mutations cause an oversecretion of insulin, leading to congenital hyperinsulinism, whereas activating mutations cause the opposing phenotype, diabetes. This review focuses on variants identified in ABCC8 and KCNJ11, the phenotypic spectrum and the treatment implications for individuals with pathogenic variants.

In this study, a second case of hyperinsulinemic hypoglycemia due to activation of glucokinase is reported. The 14-year-old proband had a history of neonatal hypoglycemia, treated with diazoxide. He was admitted with coma and convulsions due to nonketotic hypoglycemia. His BMI was 34 kg/m², and his fasting blood glucose ranged from 2.1 to 2.7 mmol/l, associated with inappropriately high serum levels of insulin, C-peptide, and proinsulin. An oral glucose tolerance test (OGTT) showed exaggerated responses of these peptides followed by profound hypoglycemia. Treatment with diazoxide and chlorothiazide was effective. His mother never had clinical hypoglycemic symptoms, even though her fasting blood glucose ranged from 2.9 to 3.5 mmol/l. Increases in serum insulin, C-peptide, and proinsulin in response to an OGTT suggested a lower threshold for glucose-stimulated insulin release (GSIR). Screening for mutations in candidate genes revealed a heterozygous glucokinase mutation in exon 10, substituting valine for alanine at codon 456 (A456V) in the proband and his mother. The purified recombinant glutathionyl S-transferase fusion protein of the A456V glucokinase revealed a decreased glucose S_0.5 (the concentration of glucose needed to achieve the half-maximal rate of phosphorylation) from 8.04 (wild-type) to 2.53 mmol/l. The mutant’s Hill coefficient was decreased, and its maximal specific activity k_cat was increased. Mathematical modeling predicted a markedly lowered GSIR threshold of 1.5 mmol/l. The theoretical and practical implications are manifold and significant.

In recent years, several genes have been causally associated with epilepsy. However, making a genetic diagnosis in a patient can still be difficult, since extensive phenotypic and genetic heterogeneity has been observed in many monogenic epilepsies. This study aimed to analyze the genetic basis of a wide spectrum of epilepsies with age of onset spanning from the neonatal period to adulthood. A gene panel targeting 46 epilepsy genes was used on a cohort of 216 patients consecutively referred for panel testing. The patients had a range of different epilepsies from benign neonatal seizures to epileptic encephalopathies (EEs). Potentially causative variants were evaluated by literature and database searches, submitted to bioinformatic prediction algorithms, and validated by Sanger sequencing. If possible, parents were included for segregation analysis. We identified a presumed disease-causing variant in 49 (23%) of the 216 patients. The variants were found in 19 different genes including SCN1A, STXBP1, CDKL5, SCN2A, SCN8A, GABRA1, KCNA2, and STX1B. Patients with neonatal-onset epilepsies had the highest rate of positive findings (57%). The overall yield for patients with EEs was 32%, compared to 17% among patients with generalized epilepsies and 16% in patients with focal or multifocal epilepsies. By the use of a gene panel consisting of 46 epilepsy genes, we were able to find a disease-causing genetic variation in 23% of the analyzed patients. The highest yield was found among patients with neonatal-onset epilepsies and EEs.