Relative persistence of AAV serotype 1 vector genomes in dystrophic muscle

The purpose of this study was to assess the behavior of pseudotyped recombinant adeno-associated virus type 1 (rAAV2/1) vector genomes in dystrophic skeletal muscle. A comparison was made between a therapeutic vector and a reporter vector by injecting the hindlimb in a mouse model of Limb Girdle Muscular Dystrophy Type 2D (LGMD-2D) prior to disease onset. We hypothesized that the therapeutic vector would establish long-term persistence through prevention of myofiber turnover. In contrast, the reporter vector genome copy number would diminish over time due to disease-associated muscle degradation

Tissue specific promoters improve specificity of AAV9 mediated transgene expression following intra-vascular gene delivery in neonatal mice

The AAV9 capsid displays a high natural affinity for the heart following a single intravenous (IV) administration in both newborn and adult mice. It also results in substantial albeit relatively lower expression levels in many other tissues. To increase the overall safety of this gene delivery method we sought to identify which one of a group of promoters is able to confer the highest level of cardiac specific expression and concurrently, which is able to provide a broad biodistribution of expression across both cardiac and skeletal muscle. The in vivo behavior of five different promoters was compared: CMV, desmin (Des), alpha-myosin heavy chain (α-MHC), myosin light chain 2 (MLC-2) and cardiac troponin C (cTnC). Following IV administration to newborn mice, LacZ expression was measured by enzyme activity assays. Results showed that rAAV2/9-mediated gene delivery using the α-MHC promoter is effective for focal transgene expression in the heart and the Des promoter is highly suitable for achieving gene expression in cardiac and skeletal muscle following systemic vector administration. Importantly, these promoters provide an added layer of control over transgene activity following systemic gene delivery

Elevated liver glycogenolysis mediates higher blood glucose during acute exercise in Barth syndrome

UNLABELLED: Barth syndrome (BTHS) is an X-linked recessive genetic disorder due to mutations in the Tafazzin (TAFAZZIN) gene that lead to cardiac and skeletal muscle mitochondrial dysfunction. Previous studies in humans with BTHS demonstrate that the defects in muscle mitochondrial oxidative metabolism result in an enhanced reliance on anaerobic metabolism during exercise to meet energy demands of muscular work. During exercise, the liver normally increases glucose production via glycogenolysis and gluconeogenesis to match the elevated rate of muscle glucose uptake and meet the ATP requirements of working muscle. However, the impact of Tafazzin deficiency on hepatic glucose production and the pathways contributing to hepatic glucose production during exercise is unknown. Therefore, the purpose of this study was to quantify in vivo liver gluconeogenesis and glycogenolysis in Tafazzin knockdown mice at rest and during acute exercise. METHODS: Male TAFAZZIN shRNA transgenic (TG) and wild-type (WT) mice completed exhaustive treadmill running protocols to test exercise tolerance. Mice underwent 2H- and 13C-stable isotope infusions at rest and during a 30-minute treadmill running bout to quantify hepatic glucose production and associated nutrient fluxes under sedentary conditions and during acute exercise. Circulating and tissue (skeletal muscle and liver) samples were obtained during and following exercise to assess static metabolite levels. RESULTS: TG mice reached exhaustion sooner during exhaustive treadmill running protocols and exhibited higher plasma lactate concentrations after exhaustive exercise compared to WT mice. Arterial glucose levels were comparable between genotypes at rest, but higher in TG mice compared to WT mice during exercise. Consistent with the higher blood glucose, TG mice showed increased endogenous glucose production owing to elevated glycogenolysis compared to WT mice during exercise. Total gluconeogenesis, gluconeogenesis from glycerol, gluconeogenesis from phosphoenolpyruvate, pyruvate cycling, total cataplerosis, and anaplerotic fluxes were similar between TG and WT mice at rest and during exercise. However, lactate dehydrogenase flux and TCA cycle fluxes trended higher in TG mice during exercise. Liver glycogen content in TG was higher in TG vs. controls. CONCLUSION: Our data in the Tafazzin knockdown mouse suggest that elevated anaerobic metabolism during rest and exercise previously reported in humans with BTHS are supported by the finding of higher hepatic glycogenolysis

Megf10 Deficiency Impairs Skeletal Muscle Stem Cell Migration and Muscle Regeneration

Biallelic loss-of-function MEGF10 mutations lead to MEGF10 myopathy, also known as early onset myopathy with areflexia, respiratory distress, and dysphagia (EMARDD). MEGF10 is expressed in muscle satellite cells, but the contribution of satellite cell dysfunction to MEGF10 myopathy is unclear. Myofibers and satellite cells were isolated and examined from Megf10 and wild-type mice. A separate set of mice underwent repeated intramuscular barium chloride injections. Megf10 muscle satellite cells showed reduced proliferation and migration, while Megf10 mouse skeletal muscles showed impaired regeneration. Megf10 deficiency is associated with impaired muscle regeneration, due in part to defects in satellite cell function. Efforts to rescue Megf10 deficiency will have therapeutic implications for MEGF10 myopathy and other inherited muscle diseases involving impaired muscle regeneration

Determinants of disease-specific survival in patients with and without metastatic pheochromocytoma and paraganglioma

BACKGROUND: Pheochromocytomas and paragangliomas (PPGLs) have a heterogeneous prognosis, the basis of which remains unclear. We, therefore, assessed disease-specific survival (DSS) and potential predictors of progressive disease in patients with PPGLs and head/neck paragangliomas (HNPGLs) according to the presence or absence of metastases. METHODS: This retrospective study included 582 patients with PPGLs and 57 with HNPGLs. DSS was assessed according to age, location and size of tumours, recurrent/metastatic disease, genetics, plasma metanephrines and methoxytyramine. RESULTS: Among all patients with PPGLs, multivariable analysis indicated that apart from older age (HR = 5.4, CI = 2.93-10.29, P < 0.0001) and presence of metastases (HR = 4.8, CI = 2.41-9.94, P < 0.0001), shorter DSS was also associated with extra-adrenal tumour location (HR = 2.6, CI = 1.32-5.23, P = 0.0007) and higher plasma methoxytyramine (HR = 1.8, CI = 1.11-2.85, P = 0.0170) and normetanephrine (HR = 1.8, CI = 1.12-2.91, P = 0.0160). Among patients with HNPGLs, those with metastases presented with longer DSS compared to patients with metastatic PPGLs (33.4 versus 20.2 years, P < 0.0001) and only plasma methoxytyramine (HR = 13, CI = 1.35-148, P = 0.0380) was an independent predictor of DSS. For patients with metastatic PPGLs, multivariable analysis revealed that apart from older age (HR = 6.2, CI = 3.20-12.20, P < 0.0001), shorter DSS was associated with the presence of synchronous metastases (HR = 4.9, CI = 2.78-8.80, P < 0.0001), higher plasma methoxytyramine (HR = 2.4, CI = 1.44-4.14, P = 0.0010) and extensive metastatic burden (HR = 2.1, CI = 1.07-3.79, P = 0.0290). CONCLUSIONS: DSS among patients with PPGLs/HNPGLs relates to several presentations of the disease that may provide prognostic markers. In particular, the independent associations of higher methoxytyramine with shorter DSS in patients with HNPGLs and metastatic PPGLs suggest the utility of this biomarker to guide individualized management and follow-up strategies in affected patients

Prediction of metastatic pheochromocytoma and paraganglioma: a machine learning modelling study using data from a cross-sectional cohort

BACKGROUND Pheochromocytomas and paragangliomas have up to a 20% rate of metastatic disease that cannot be reliably predicted. This study prospectively assessed whether the dopamine metabolite, methoxytyramine, might predict metastatic disease, whether predictions might be improved using machine learning models that incorporate other features, and how machine learning-based predictions compare with predictions made by specialists in the field. METHODS In this machine learning modelling study, we used cross-sectional cohort data from the PMT trial, based in Germany, Poland, and the Netherlands, to prospectively examine the utility of methoxytyramine to predict metastatic disease in 267 patients with pheochromocytoma or paraganglioma and positive biochemical test results at initial screening. Another retrospective dataset of 493 patients with these tumors enrolled under clinical protocols at National Institutes of Health (00-CH-0093) and the Netherlands (PRESCRIPT trial) was used to train and validate machine learning models according to selections of additional features. The best performing machine learning models were then externally validated using data for all patients in the PMT trial. For comparison, 12 specialists provided predictions of metastatic disease using data from the training and external validation datasets. FINDINGS Prospective predictions indicated that plasma methoxytyramine could identify metastatic disease at sensitivities of 52% and specificities of 85%. The best performing machine learning model was based on an ensemble tree classifier algorithm that used nine features: plasma methoxytyramine, metanephrine, normetanephrine, age, sex, previous history of pheochromocytoma or paraganglioma, location and size of primary tumours, and presence of multifocal disease. This model had an area under the receiver operating characteristic curve of 0·942 (95% CI 0·894-0·969) that was larger (p<0·0001) than that of the best performing specialist before (0·815, 0·778-0·853) and after (0·812, 0·781-0·854) provision of SDHB variant data. Sensitivity for prediction of metastatic disease in the external validation cohort reached 83% at a specificity of 92%. INTERPRETATION Although methoxytyramine has some utility for prediction of metastatic pheochromocytomas and paragangliomas, sensitivity is limited. Predictive value is considerably enhanced with machine learning models that incorporate our nine recommended features. Our final model provides a preoperative approach to predict metastases in patients with pheochromocytomas and paragangliomas, and thereby guide individualised patient management and follow-up. FUNDING Deutsche Forschungsgemeinschaft