Combined MRI and 31P-MRS Investigations of the ACTA1(H40Y) Mouse Model of Nemaline Myopathy Show Impaired Muscle Function and Altered Energy Metabolism

Nemaline myopathy (NM) is the most common disease entity among non-dystrophic skeletal muscle congenital diseases. Mutations in the skeletal muscle α-actin gene (ACTA1) account for ∼25% of all NM cases and are the most frequent cause of severe forms of NM. So far, the mechanisms underlying muscle weakness in NM patients remain unclear. Additionally, recent Magnetic Resonance Imaging (MRI) studies reported a progressive fatty infiltration of skeletal muscle with a specific muscle involvement in patients with ACTA1 mutations. We investigated strictly noninvasively the gastrocnemius muscle function of a mouse model carrying a mutation in the ACTA1 gene (H40Y). Skeletal muscle anatomy (hindlimb muscles and fat volumes) and energy metabolism were studied using MRI and ³¹Phosphorus magnetic resonance spectroscopy. Skeletal muscle contractile performance was investigated while applying a force-frequency protocol (from 1–150 Hz) and a fatigue protocol (80 stimuli at 40 Hz). H40Y mice showed a reduction of both absolute (−40%) and specific (−25%) maximal force production as compared to controls. Interestingly, muscle weakness was associated with an improved resistance to fatigue (+40%) and an increased energy cost. On the contrary, the force frequency relationship was not modified in H40Y mice and the extent of fatty infiltration was minor and not different from the WT group. We concluded that the H40Y mouse model does not reproduce human MRI findings but shows a severe muscle weakness which might be related to an alteration of intrinsic muscular properties. The increased energy cost in H40Y mice might be related to either an impaired mitochondrial function or an alteration at the cross-bridges level. Overall, we provided a unique set of anatomic, metabolic and functional biomarkers that might be relevant for monitoring the progression of NM disease but also for assessing the efficacy of potential therapeutic interventions at a preclinical level.     

Prediction Errors in Learning Drug Response from Gene Expression Data – Influence of Labeling,Sample Size,and Machine Learning Algorithm

Model-based prediction is dependent on many choices ranging from the sample collection and prediction endpoint to the choice of algorithm and its parameters. Here we studied the effects of such choices, exemplified by predicting sensitivity (as IC50) of cancer cell lines towards a variety of compounds. For this, we used three independent sample collections and applied several machine learning algorithms for predicting a variety of endpoints for drug response. We compared all possible models for combinations of sample collections, algorithm, drug, and labeling to an identically generated null model. The predictability of treatment effects varies among compounds, i.e. response could be predicted for some but not for all. The choice of sample collection plays a major role towards lowering the prediction error, as does sample size. However, we found that no algorithm was able to consistently outperform the other and there was no significant difference between regression and two- or three class predictors in this experimental setting. These results indicate that response-modeling projects should direct efforts mainly towards sample collection and data quality, rather than method adjustment.     

Complications of Antiretroviral Therapy Initiation in Hospitalised Patients with HIV-Associated Tuberculosis

Background

HIV-associated tuberculosis is a common coinfection in Sub-Saharan Africa, which causes high morbidity and mortality. A sub-set of HIV-associated tuberculosis patients require prolonged hospital admission, during which antiretroviral therapy initiation may be required. The aim of this study was to document the causes of clinical deterioration of hospitalised patients with HIV-associated tuberculosis starting antiretroviral therapy in order to inform healthcare practice in low- to middle-income countries.

Methods

Prospective, observational cohort study of adult inpatients with HIV-associated tuberculosis starting antiretroviral therapy in a dedicated tuberculosis hospital in Cape Town, South Africa. Causes of clinical deterioration and outcome were recorded in the first 12 weeks of antiretroviral therapy. Patients with rifampicin-resistant tuberculosis were excluded.

Results

Between May 2009 and November 2010, 112 patients (60% female), with a median age of 32 years were enrolled. At baseline the median CD4 count was 55 cells/mm³ (IQR 31–106) and HIV viral load 5.6 log copies/mL. All patients had significant comorbidity: 82% were bed-bound, 65% had disseminated tuberculosis and 27% had central nervous system tuberculosis. Seventy six patients (68%) developed 144 clinical events after starting antiretroviral therapy. TB-IRIS, hospital-acquired infections and significant drug toxicities occurred in 42%, 20.5% and 15% of patients respectively. A new opportunistic disease occurred in 15% of patients and a thromboembolic event in 8%. Mortality during the 12 week period was 10.6%.

Conclusions

High rates of TB-IRIS, hospital-acquired infections and drug toxicities complicate the course of patients with HIV-associated tuberculosis starting antiretroviral therapy in hospital. Despite the high morbidity, mortality was relatively low. Careful clinical management and adequate resources are needed in hospitalised HIV-TB patients in the 1^st three months following ART initiation.     

Evolution in a Changing Environment

We propose a simple model for genetic adaptation to a changing environment, describing a fitness landscape characterized by two maxima. One is associated with “specialist” individuals that are adapted to the environment; this maximum moves over time as the environment changes. The other maximum is static, and represents “generalist” individuals not affected by environmental changes. The rest of the landscape is occupied by “maladapted” individuals. Our analysis considers the evolution of these three subpopulations. Our main result is that, in presence of a sufficiently stable environmental feature, as in the case of an unchanging aspect of a physical habitat, specialists can dominate the population. By contrast, rapidly changing environmental features, such as language or cultural habits, are a moving target for the genes; here, generalists dominate, because the best evolutionary strategy is to adopt neutral alleles not specialized for any specific environment. The model we propose is based on simple assumptions about evolutionary dynamics and describes all possible scenarios in a non-trivial phase diagram. The approach provides a general framework to address such fundamental issues as the Baldwin effect, the biological basis for language, or the ecological consequences of a rapid climate change.     

Effect of weight loss and exercise on angiogenic factors in the circulation and in adipose tissue in obese subjects

Background:

Vascular growth is a prerequisite for adipose tissue (AT) development and expansion. Some AT cytokines and hormones have effects on vascular development, like vascular endothelial growth factor (VEGF‐A), angiopoietin (ANG‐1), ANG‐2 and angiopoietin‐like protein‐4 (ANGPTL‐4).

Methods:

In this study, the independent and combined effects of diet‐induced weight loss and exercise on AT gene expression and proteins levels of those angiogenic factors were investigated. Seventy‐nine obese males and females were randomized to: 1. Exercise‐only (EXO; 12‐weeks exercise without diet‐restriction), 2. Hypocaloric diet (DIO; 8‐weeks very low energy diet (VLED) + 4‐weeks weight maintenance diet) and 3. Hypocaloric diet and exercise (DEX; 8‐weeks VLED + 4‐weeks weight maintenance diet combined with exercise throughout the 12 weeks). Blood samples and fat biopsies were taken before and after the intervention.

Results:

Weight loss was 3.5 kg in the EXO group and 12.3 kg in the DIO and DEX groups. VEGF‐A protein was non‐significantly reduced in the weight loss groups. ANG‐1 protein levels were significantly reduced 22‐25% after all three interventions (P < 0.01). The ANG‐1/ANG‐2 ratio was also decreased in all three groups (P < 0.05) by 27‐38%. ANGPTL‐4 was increased in the EXO group (15%, P < 0.05) and 9% (P < 0.05) in the DIO group. VEGF‐A, ANG‐1, and ANGPTL‐4 were all expressed in human AT, but only ANGPTL‐4 was influenced by the interventions.

Conclusions:

Our data show that serum VEGF‐A, ANG‐1, ANG‐2, and ANGPTL‐4 levels are influenced by weight changes, indicating the involvement of these factors in the obese state. Moreover, it was found that weight loss generally was associated with a reduced angiogenic activity in the circulation.     

DNAdigest and Repositive: Connecting the World of Genomic Data

There is no unified place where genomics researchers can search through all available raw genomic data in a way similar to OMIM for genes or Uniprot for proteins. With the recent increase in the amount of genomic data that is being produced and the ever-growing promises of precision medicine, this is becoming more and more of a problem. DNAdigest is a charity working to promote efficient sharing of human genomic data to improve the outcome of genomic research and diagnostics for the benefit of patients. Repositive, a social enterprise spin-out of DNAdigest, is building an online platform that indexes genomic data stored in repositories and thus enables researchers to search for and access a range of human genomic data sources through a single, easy-to-use interface, free of charge.     

Does AMH Reflect Follicle Number Similarly in Women with and without PCOS?

Context

Increased Anti-Mullerian Hormone in polycystic ovary syndrome, may be due to overactive follicles rather than reflect antral follicle count.

Objective

Does Anti-Mullerian Hormone reflect antral follicle count similarly in women with or without polycystic ovary syndrome or polycystic ovarian morphology?

Design

Cross-sectional, case-control.

Setting

Women who delivered preterm in 1999–2006. For each index woman, a woman with a term delivery was identified.

Patients

Participation rate was 69%. Between 2006–2008, 262 women were included, and diagnosed to have polycystic ovary syndrome, polycystic ovarian morphology or to be normal controls.

Intervention(s)

Blood tests, a clinical examination and vaginal ultrasound.

Main Outcome Measure(s)

Anti-Mullerian Hormone / antral follicle count -ratio, SHBG, androstenedione and insulin, to test potential influence on the Anti-Mullerian Hormone / antral follicle count -ratio.

Results

Mean Anti-Mullerian Hormone / antral follicle count ratio in women with polycystic ovary syndrome or polycystic ovarian morphology was similar to that of the controls (polycystic ovary syndrome: 1,2 p = 0,10 polycystic ovarian morphology: 1,2, p = 0,27 Controls 1,3). Anti-Mullerian Hormone showed a positive linear correlation to antral follicle count in all groups. Multivariate analysis did not change the results.

Conclusions

We confirmed the positive correlation between AMH and follicle count. Anti-Mullerian Hormone seems to be a reliable predictor of antral follicle count, independent of polycystic ovary syndrome diagnosis or ovarian morphology.