Plasma osteoprotegerin is related to carotid and peripheral arterial disease, but not to myocardial ischemia in type 2 diabetes mellitus

<p>Abstract</p> <p>Background</p> <p>Cardiovascular disease (CVD) is frequent in type 2 diabetes mellitus patients due to accelerated atherosclerosis. Plasma osteoprotegerin (OPG) has evolved as a biomarker for CVD. We examined the relationship between plasma OPG levels and different CVD manifestations in type 2 diabetes.</p> <p>Methods</p> <p>Type 2 diabetes patients without known CVD referred consecutively to a diabetes clinic for the first time (n = 305, aged: 58.6 ± 11.3 years, diabetes duration: 4.5 ± 5.3 years) were screened for carotid arterial disease, peripheral arterial disease, and myocardial ischemia by means of carotid artery ultrasonography, peripheral ankle and toe systolic blood pressure measurements, and myocardial perfusion scintigraphy (MPS). In addition, plasma OPG concentrations and other CVD-related markers were measured.</p> <p>Results</p> <p>The prevalence of carotid arterial disease, peripheral arterial disease, and myocardial ischemia was 42%, 15%, and 30%, respectively. Plasma OPG was significantly increased in patients with carotid and peripheral arterial disease compared to patients without (p < 0.001, respectively), however, this was not the case for patients with myocardial ischemia versus those without (p = 0.71). When adjusted for age, HbA1c and U-albumin creatinine ratio in a multivariate logistic regression analysis, plasma OPG remained strongly associated with carotid arterial disease (adjusted OR: 2.12; 95% CI: 1.22-3.67; p = 0.008), but not with peripheral arterial disease or myocardial ischemia.</p> <p>Conclusions</p> <p>Increased plasma OPG concentration is associated with carotid and peripheral arterial disease in patients with type 2 diabetes, whereas no relation is observed with respect to myocardial ischemia on MPS. The reason for this discrepancy is unknown.</p> <p>Trial registration number</p> <p>at <url>http://www.clinicaltrial.gov</url>: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00298844">NCT00298844</a></p

Effective brilliance amplification in neutron propagation-based phase contrast imaging

Propagation-based neutron phase-contrast tomography was demonstrated on an insect sample, using the ISIS pulsed spallation source. In our proof-of-concept low-fluence experiment the tomogram with Paganin-type phase-retrieval filter applied exhibited an effective net boost of $23\pm 1$ in the signal-to-noise ratio as compared to an attenuation-based tomogram, implying an effective boost in neutron brilliance of well over two orders of magnitude. The phase-retrieval filter applies to monochromatic as well as poly-energetic neutron beams. Expressions are provided for the optimal phase-contrast geometry as well as conditions for the validity of the method. The underpinning theory is derived under the assumption of the sample being composed of a single material, but this can be generalized. The effective boost in brilliance may be employed to give reduced acquisition time, or may instead be used to keep exposure times fixed while improving contrast and spatial resolution

Genome-Wide Analysis of DNA Methylation Differences in Muscle and Fat from Monozygotic Twins Discordant for Type 2 Diabetes

Background: Monozygotic twins discordant for type 2 diabetes constitute an ideal model to study environmental contributions to type 2 diabetic traits. We aimed to examine whether global DNA methylation differences exist in major glucose metabolic tissues from these twins. Methodology/Principal Findings: Skeletal muscle (n = 11 pairs) and subcutaneous adipose tissue (n = 5 pairs) biopsies were collected from 53-80 year-old monozygotic twin pairs discordant for type 2 diabetes. DNA methylation was measured by microarrays at 26,850 cytosine-guanine dinucleotide (CpG) sites in the promoters of 14,279 genes. Bisulfite sequencing was applied to validate array data and to quantify methylation of intergenic repetitive DNA sequences. The overall intra-pair variation in DNA methylation was large in repetitive (LINE1, D4Z4 and NBL2) regions compared to gene promoters (standard deviation of intra-pair differences: 10% points vs. 4% points, P<0.001). Increased variation of LINE1 sequence methylation was associated with more phenotypic dissimilarity measured as body mass index (r = 0.77, P = 0.007) and 2-hour plasma glucose (r = 0.66, P = 0.03) whereas the variation in promoter methylation did not associate with phenotypic differences. Validated methylation changes were identified in the promoters of known type 2 diabetes-related genes, including PPARGC1A in muscle (13.9+/-6.2% vs. 9.0+/-4.5%, P = 0.03) and HNF4A in adipose tissue (75.2+/-3.8% vs. 70.5+/-3.7%, P<0.001) which had increased methylation in type 2 diabetic individuals. A hypothesis-free genome-wide exploration of differential methylation without correction for multiple testing identified 789 and 1,458 CpG sites in skeletal muscle and adipose tissue, respectively. These methylation changes only reached some percentage points, and few sites passed correction for multiple testing. Conclusions/Significance: Our study suggests that likely acquired DNA methylation changes in skeletal muscle or adipose tissue gene promoters are quantitatively small between type 2 diabetic and non-diabetic twins. The importance of methylation changes in candidate genes such as PPARGC1A and HNF4A should be examined further by replication in larger samples

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

The rumen microbial metagenome associated with high methane production in cattle

Acknowledgements The Rowett Institute of Nutrition and Health and SRUC are funded by the Rural and Environment Science and Analytical Services Division (RESAS) of the Scottish Government. The project was supported by Defra and the DA funded Agricultural Greenhouse Gas Inventory Research Platform, the Technology Strategy Board (Project No: TP 5903–40240) and the Biotechnology and Biological Sciences Research Council (BBSRC; BB/J004243/1, BB/J004235/1). Our thanks are due to the excellent support staff at the SRUC Beef and Sheep Research Centre, Edinburgh, and to Silvia Ramos Garcia for help in interrogating the data. MW and RR contributed equally to the paper and should be considered as joint last authors.Peer reviewedPublisher PD