Ketotic hypoglycemia in patients with Down syndrome.

BACKGROUND: Ketotic hypoglycemia (KH) without an identifiable underlying metabolic or hormonal disease is historically named idiopathic KH. The prevalence is unknown, but idiopathic KH is considered the most frequent cause of hypoglycemia beyond the neonatal period. KH in Down syndrome (DS) has not been reported. METHODS: We conducted a web-based survey on KH in DS through the non-profit patient organization Ketotic Hypoglycemia International. The responses were evaluated for consistency with KH by two authors. Two DS patient histories with documented KH were shared in more details. RESULTS: Survey data on 139 DS patients were obtained. After validation, 10 patients (7.2%) had reported episodes of documented hypoglycemia, ketosis, and/or symptoms compatible with KH beyond the neonatal period. Glucose concentrations ranged 1.2-2.9 mmol/L; betahydroxybutyrate was up to 5.5 mmol/L during hypoglycemia. One girl had trisomy 21 with no response to i.m. glucagon also had a heterozygous Xp22.23 deletion including GYG2, which protein, glycogenin 2, is a substrate for glycogen synthase. Treatment with extended release cornstarch was effective. CONCLUSION: This is the first demonstration of a possible high prevalence of KH in DS. Even though this finding needs to be confirmed in other research settings, identification of KH in DS could have a dramatic impact, as simple treatments with cornstarch, protein and frequent meals may prevent KH attacks and, analogous to other conditions with KH, improve growth, stamina and prevent overeating and obesity. GYG2 deletion may contribute to KH in DS, resembling glycogen storage disease type 0.

Case Reports of Pre-clinical Replication Studies in Metabolism and Diabetes.

Recent articles have highlighted the lack of reproducibility of data from scientific publications. Here we would argue that a better way to describe and also tackle this matter is to use the term "lack of robustness," since it points toward potential solutions. Presenting several case reports, we highlight examples with common underlying issues from Novo Nordisk's experience: animal model variability, reagent quality, and inter-lab variability. We discuss means to prevent these issues and argue for increased collaborative work and transparent manuscript revision procedures. Collectively, we believe these measures will help promote a more rapid and efficient self-corrective process in diabetes drug target research.

Complex multi-block analysis identifies new immunologic and genetic disease progression patterns associated with the residual ß-cell function 1 year after diagnosis of type 1 diabetes.

The purpose of the present study is to explore the progression of type 1 diabetes (T1D) in Danish children 12 months after diagnosis using Latent Factor Modelling. We include three data blocks of dynamic paraclinical biomarkers, baseline clinical characteristics and genetic profiles of diabetes related SNPs in the analyses. This method identified a model explaining 21.6% of the total variation in the data set. The model consists of two components: (1) A pattern of declining residual ß-cell function positively associated with young age, presence of diabetic ketoacidosis and long duration of disease symptoms (P = 0.0004), and with risk alleles of WFS1, CDKN2A/2B and RNLS (P = 0.006). (2) A second pattern of high ZnT8 autoantibody levels and low postprandial glucagon levels associated with risk alleles of IFIH1, TCF2, TAF5L, IL2RA and PTPN2 and protective alleles of ERBB3 gene (P = 0.0005). These results demonstrate that Latent Factor Modelling can identify associating patterns in clinical prospective data--future functional studies will be needed to clarify the relevance of these patterns.

[Future breakthroughs in medical treatment of age-related conditions]. / Fremtidige gennembrud inden for medicinsk behandling af aldersrelaterede sygdomme.

Significant progress in our understanding of age-related diseases including the metabolic syndrome, type 2 diabetes, arteriosclerosis and cancer have been achieved in recent years. Novel disease-causing mechanisms and, therefore, drug targets, include epigenetics, inflammation, telomeres, mitochondrial function, oxidative stress and sirtuins. There is a need for individualized treatments, and future medical interventions may be initiated in a primary preventive setting by targeting mechanisms similar to those influenced by calorie restriction and physical exercise.