Longitudinal selenium status in healthy British adults: assessment using biochemical and molecular biomarkers

Human selenium (Se) requirements are currently based on biochemical markers of Se status. In rats, tissue glutathione peroxidase-1 (Gpx1) mRNA levels can be used effectively to determine Se requirements; blood Gpx1 mRNA levels decrease in Se-deficient rats, so molecular biology-based markers have potential for human nutrition assessment. To study the efficacy of molecular biology markers for assessing Se status in humans, we conducted a longitudinal study on 39 subjects (age 45 +/- 11) in Reading, UK. Diet diaries (5 day) and blood were obtained from each subject at 2, 8, 17 and 23 weeks, and plasma Se, glutathione peroxidase (Gpx3) enzyme activity, and selenoprotein mRNA levels were determined. There were no significant longitudinal effects on Se biomarkers. Se intake averaged 48 +/- 14 mu g/d. Plasma Se concentrations averaged 1.13 +/- 0.16 mu mol/l. Plasma Se v. energy-corrected Se intake (ng Se/kJ/d) was significantly correlated, but neither Gpx3 activity v. Se intake (ng Se/kJ/d) nor Gpx3 activity v. plasma Se was significantly correlated. Collectively, this indicates that subjects were on the plateaus of the response curves. Selenoprotein mRNAs were quantitated in total RNA isolated from whole blood, but mRNA levels for Gpx1, selenoprotein H, and selenoprotein W (all highly regulated by Se in rodents), as well selenoprotein P, Gpx3, and phospholipid hydroperoxide glutathione peroxidase were also not significantly correlated with plasma Se. Thus selenoprotein molecular biomarkers, as well as traditional biochemical markers, are unable to further distinguish differences in Se status in these Se replete subjects. The efficacy of molecular biomarkers to detect Se deficiency needs to be tested in Se-deficient populations.

Molecular and phenotypic characterization of a mouse model of oculopharyngeal muscular dystrophy reveals severe muscular atrophy restricted to fast glycolytic fibres

Oculopharyngeal muscular dystrophy (OPMD) is an adult-onset disorder characterized by ptosis, dysphagia and proximal limb weakness. Autosomal-dominant OPMD is caused by a short (GCG)8–13 expansions within the first exon of the poly(A)-binding protein nuclear 1 gene (PABPN1), leading to an expanded polyalanine tract in the mutated protein. Expanded PABPN1 forms insoluble aggregates in the nuclei of skeletal muscle fibres. In order to gain insight into the different physiological processes affected in OPMD muscles, we have used a transgenic mouse model of OPMD (A17.1) and performed transcriptomic studies combined with a detailed phenotypic characterization of this model at three time points. The transcriptomic analysis revealed a massive gene deregulation in the A17.1 mice, among which we identified a significant deregulation of pathways associated with muscle atrophy. Using a mathematical model for progression, we have identified that one-third of the progressive genes were also associated with muscle atrophy. Functional and histological analysis of the skeletal muscle of this mouse model confirmed a severe and progressive muscular atrophy associated with a reduction in muscle strength. Moreover, muscle atrophy in the A17.1 mice was restricted to fast glycolytic fibres, containing a large number of intranuclear inclusions (INIs). The soleus muscle and, in particular, oxidative fibres were spared, even though they contained INIs albeit to a lesser degree. These results demonstrate a fibre-type specificity of muscle atrophy in this OPMD model. This study improves our understanding of the biological pathways modified in OPMD to identify potential biomarkers and new therapeutic targets.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

Background Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers (“biomarkers”) of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10–20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2–10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.