ABSTRACT
A case of a 61-year-old woman with hemichorea associated with nonketotic hyperglycemia is reported. The typical presentation of this disease is nonketotic hyperglycemia, hemichorea, hyper-intense signal on T1-weighted magnetic resonance imaging (MRI) and high-density on computed tomography (CT) in the contralateral striatum. With good glycemic control, the clinical symptoms disappeared.
Subject(s)
Basal Ganglia Diseases/etiology , Chorea/etiology , Diabetes Mellitus, Type 2/complications , Hyperglycinemia, Nonketotic/complications , Basal Ganglia Diseases/diagnostic imaging , Basal Ganglia Diseases/pathology , Chorea/diagnostic imaging , Chorea/pathology , Diabetes Mellitus, Type 2/therapy , Female , Humans , Hyperglycinemia, Nonketotic/therapy , Magnetic Resonance Imaging , Middle Aged , Putamen/diagnostic imaging , Putamen/pathology , Tomography, X-Ray ComputedABSTRACT
Type 2 diabetes (T2D) can be prevented in pre-diabetic individuals with impaired glucose tolerance (IGT). Here, we have used a metabolomics approach to identify candidate biomarkers of pre-diabetes. We quantified 140 metabolites for 4297 fasting serum samples in the population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort. Our study revealed significant metabolic variation in pre-diabetic individuals that are distinct from known diabetes risk indicators, such as glycosylated hemoglobin levels, fasting glucose and insulin. We identified three metabolites (glycine, lysophosphatidylcholine (LPC) (18:2) and acetylcarnitine) that had significantly altered levels in IGT individuals as compared to those with normal glucose tolerance, with P-values ranging from 2.4×10(-4) to 2.1×10(-13). Lower levels of glycine and LPC were found to be predictors not only for IGT but also for T2D, and were independently confirmed in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort. Using metabolite-protein network analysis, we identified seven T2D-related genes that are associated with these three IGT-specific metabolites by multiple interactions with four enzymes. The expression levels of these enzymes correlate with changes in the metabolite concentrations linked to diabetes. Our results may help developing novel strategies to prevent T2D.
