On Glucose Metabolism in Patients with the m.3243A>G Mutation

Background: The m.3243A>G mutation in mitochondrial DNA is the most common cause for mitochondrial diabetes. In addition, unexpected deaths related to the m.3243A>G associate with encephalopathy and cardiomyopathy. Failing mitochondrial respiratory chain in neurons, myocytes and beta cells is considered to underlie the multiorgan manifestations of the m.3243A>G. Aims: The primary aim of the study was to characterize the organ-specific glucose metabolism in patients with m.3243A>G and secondly, to study patients with or without signs of diabetes, cardiomyopathy or encephalopathy. The insulin-stimulated glucose metabolism in brain, heart, skeletal muscle, adipose tissue and liver were measured with 2-deoxy-2-[18F]fluoro-α-D-glucose in 15 patients and 14 controls. Brain oxygen metabolism was assessed with [15O]oxygen and insulin secretion was modelled based on oral glucose tolerance test. Results: The glucose oxidation in brain was globally decreased in patients with or without clinical encephalopathy. The insulin-stimulated glucose influx to skeletal muscle and adipose tissue was decreased in patients with or without diabetes as the hepatic glucose metabolism was normal. Impaired beta cell function and myocardial glucose uptake were associated with the high m.3243A>G heteroplasmy. Conclusions: This cross-sectional study suggests that: 1) The ability of insulin to stimulate glucose metabolism in skeletal muscle and adipose tissue is weakened before the beta cell failure results in mitochondrial diabetes. 2) Glucose oxidation defect is detected in otherwise unaffected cerebral regions in patients with the m.3243A>G, thus it likely precedes the clinical encephalopathy. 3) Uneconomical glucose hypometabolism during hyperinsulinemia contributes to the cardiac vulnerability in patients with high m.3243A>G heteroplasmy

Markov Random Fields in Cancer Mutation Dependencies

Even though a large amount of evidence would suggest that PP2A serine/threonine protein phosphatase acts as a tumour suppressor the genomics data to support this claim is limited. We fit a sparse binary Markov random field with individual sample's total mutational frequency as an additional covariate to model the dependencies between the mutations occurring in the PP2A encoding genes. We utilize the data from recent large scale cancer genomics studies, where the whole genome from a human tumour biopsy has been analysed. Our results show a complex network of interactions between the occurrence of mutations in our twenty examined genes. According to our analysis the mutations occurring in the genes PPP2R1A, PPP2R3A, and PPP2R2B are identified as the key mutations. These genes form the core of the network of conditional dependency between the mutations in the investigated twenty genes. Additionally, we note that the mutations occurring in PPP2R4 seem to be more influential in samples with higher number of total mutations. The mutations occurring in the set of genes suggested by our results has been shown to contribute to the transformation of human cells. We conclude that our evidence further supports the claim that PP2A acts as a tumour suppressor and restoring PP2A activity is an appealing therapeutic strategy.