The relationship between various measures of obesity and arterial stiffness in morbidly obese patients

<p>Abstract</p> <p>Background</p> <p>Obesity is associated with increased risk of cardiovascular disease. Arterial stiffness assessed by carotid femoral pulse wave velocity (PWV) is an independent predictor of cardiovascular morbidity and mortality. We aimed to investigate how various measures of body composition affect arterial stiffness.</p> <p>Methods</p> <p>This is an analysis of cross-sectional baseline data from a controlled clinical trial addressing changes in arterial stiffness after either surgery or lifestyle intervention in a population of morbidly obese patients. High-fidelity applanation tonometry (Millar^®, Sphygmocor^®) was used to measure pulse wave velocity (PWV). Carotid femoral PWV is a direct measure of arterial stiffness and is considered to be the gold standard method. The Inbody 720 Body Composition Analyzer was used for bioelectrical impedance analysis (BIA). Spearman's correlation, independent samples <it>t</it>-test, chi-square tests, Fisher's exact test and multiple linear regression analyses were used as statistical methods.</p> <p>Results</p> <p>A total of 133 patients (79 women), with a mean (SD) age of 43 (11) years were included in the study. Men had a significantly higher prevalence of obesity related comorbidities and significantly higher PWV, 9.1 (2.0) m/s vs. 8.1 (1.8) m/s, p = 0.003, than women. In the female group, PWV was positively correlated with WC, WHtR, BMI and visceral fat area. In the male group, PWV was negatively correlated with BMI. Multiple linear regression analysis showed that increasing BMI, WC, WHtR, visceral fat area and fat mass were independently associated with higher PWV in women, but not in men, after adjustment for age, hypertension and type 2 diabetes.</p> <p>Conclusion</p> <p>Most measures of general and abdominal obesity were predictors of arterial stiffness in female morbidly obese patients.</p> <p>Trial registration</p> <p>ClinicalTrials.gov Identifier <a href="http://www.clinicaltrials.gov/ct2/show/NCT00626964">NCT00626964</a></p

Acoelomorpha: earliest branching bilaterians or deuterostomes?

The Acoelomorpha is an animal group comprised by nearly 400 species of misleadingly inconspicuous flatworms. Despite this, acoelomorphs have been at the centre of a heated debate about the origin of bilaterian animals for 150 years. The animal tree of life has undergone major changes during the last decades, thanks largely to the advent of molecular data together with the development of more rigorous phylogenetic methods. There is now a relatively robust backbone of the animal tree of life. However, some crucial nodes remain contentious, especially the node defining the root of Bilateria. Some studies situate Acoelomorpha (and Xenoturbellida) as the sister group of all other bilaterians, while other analyses group them within the deuterostomes which instead suggests that the last common bilaterian ancestor directly gave rise to deuterostomes and protostomes. The resolution of this node will have a profound impact on our understanding of animal/bilaterian evolution. In particular, if acoelomorphs are the sister group to Bilateria, it will point to a simple nature for the first bilaterian. Alternatively, if acoelomorphs are deuterostomes, this will imply that they are the result of secondary simplification. Here, we review the state of this question and provide potential ways to solve this long-standing issue. Specifically, we argue for the benefits of (1) obtaining additional genomic data from acoelomorphs, in particular from taxa with slower evolutionary rates; (2) the development of new tools to analyse the data; and (3) the use of metagenomics or metatranscriptomics data. We believe the combination of these three approaches will provide a definitive answer as to the position of the acoelomorphs in the animal tree of life

Impact of Attention-Deficit/Hyperactivity Disorder (ADHD) on prescription dug spending for children and adolescents: increasing relevance of health economic evidence

<p>Abstract</p> <p>Background</p> <p>During the last decade, pharmaceutical spending for patients with attention-deficit-hyperactivity disorder (ADHD) has been escalating internationally.</p> <p>Objectives</p> <p>First, to estimate future trends of ADHD-related drug expenditures from the perspectives of the statutory health insurance (SHI; Gesetzliche Krankenversicherung, GKV) in Germany and the National Health Service (NHS) in England, respectively, for children and adolescents age 6 to 18 years. Second, to evaluate the budgetary impact on individual prescribers (child and adolescent psychiatrists and pediatricians treating patients with ADHD) in Germany.</p> <p>Methods</p> <p>A model was developed to predict plausible scenarios of future pharmaceutical expenditures for treatment of ADHD. Model inputs were derived from demographic and epidemiological data, a literature review of past spending trends, and an analysis of new pharmaceutical products in development for ADHD. Only products in clinical development phase III or later were considered. Uncertainty was addressed by way of scenario analysis. For each jurisdiction, five scenarios used different assumptions of future diagnosis prevalence, treatment prevalence, rates of adoption and unit costs of novel drugs, and treatment intensity.</p> <p>Results</p> <p>Annual ADHD pharmacotherapy expenditures for children and adolescents will further increase and may exceed €310 m (D; E: ₤78 m) in 2012 (2002: ~€21.8 m; ~₤7.0 m). During this period, overall drug spending by individual physicians may increase 2.3- to 9.5-fold, resulting from the multiplicative effects of four variables: increased number of diagnosed cases, growing acceptance and intensity of pharmacotherapy, and higher unit costs of novel medications.</p> <p>Discussion</p> <p>Even for an extreme low case scenario, a more than six-fold increase of pharmaceutical spending for children and adolescents is predicted over the decade from 2002 to 2012, from the perspectives of both the NHS in England and the GKV in Germany. This budgetary impact projection represents a partial analysis only because other expenditures are likely to rise as well, for instance those associated with physician services, including diagnosis and psychosocial treatment. Further to this, by definition budgetary impact analyses have little to nothing to say about clinical appropriateness and about value of money.</p> <p>Conclusion</p> <p>Providers of care for children and adolescents with ADHD should anticipate serious challenges related to the cost-effectiveness of interventions.</p

Формирование эмоциональной культуры как компонента инновационной культуры студентов

Homozygosity has long been associated with rare, often devastating, Mendelian disorders1 and Darwin was one of the first to recognise that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity, ROH), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3,4. Here we use ROH to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts and find statistically significant associations between summed runs of homozygosity (SROH) and four complex traits: height, forced expiratory lung volume in 1 second (FEV1), general cognitive ability (g) and educational attainment (nominal p<1 × 10−300, 2.1 × 10−6, 2.5 × 10−10, 1.8 × 10−10). In each case increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing convincing evidence for the first time that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5,6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein (LDL) cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p