Regional Brain Differences in Cortical Thickness, Surface Area and Subcortical Volume in Individuals with Williams Syndrome

Williams syndrome (WS) is a rare genetic neurodevelopmental disorder characterized by increased non-social anxiety, sensitivity to sounds and hypersociability. Previous studies have reported contradictory findings with regard to regional brain variation in WS, relying on only one type of morphological measure (usually volume) in each study. The present study aims to contribute to this body of literature and perhaps elucidate some of these discrepancies by examining concurrent measures of cortical thickness, surface area and subcortical volume between WS subjects and typically-developing (TD) controls. High resolution MRI scans were obtained on 31 WS subjects and 50 typically developing control subjects. We derived quantitative regional estimates of cortical thickness, cortical surface area, and subcortical volume using FreeSurfer software. We evaluated between-group ROI differences while controlling for total intracranial volume. In post-hoc exploratory analyses within the WS group, we tested for correlations between regional brain variation and Beck Anxiety Inventory scores. Consistent with our hypothesis, we detected complex patterns of between-group cortical variation, which included lower surface area in combination with greater thickness in the following cortical regions: post central gyrus, cuneus, lateral orbitofrontal cortex and lingual gyrus. Additional cortical regions showed between-group differences in one (but not both) morphological measures. Subcortical volume was lower in the basal ganglia and the hippocampus in WS versus TD controls. Exploratory correlations revealed that anxiety scores were negatively correlated with gray matter surface area in insula, OFC, rostral middle frontal, superior temporal and lingual gyrus. Our results were consistent with previous reports showing structural alterations in regions supporting the socio-affective and visuospatial impairments in WS. However, we also were able to effectively capture novel and complex patterns of cortical differences using both surface area and thickness. In addition, correlation results implicate specific brain regions in levels of anxiety in WS, consistent with previous reports investigating general anxiety disorders in the general population

The effects of tea extracts on proinflammatory signaling

BACKGROUND: Skin toxicity is a common side effect of radiotherapy for solid tumors. Its management can cause treatment gaps and thus can impair cancer treatment. At present, in many countries no standard recommendation for treatment of skin during radiotherapy exists. In this study, we explored the effect of topically-applied tea extracts on the duration of radiation-induced skin toxicity. We investigated the underlying molecular mechanisms and compared effects of tea extracts with the effects of epigallocatechin-gallate, the proposed most-active moiety of green tea. METHODS: Data from 60 patients with cancer of the head and neck or pelvic region topically treated with green or black tea extracts were analyzed retrospectively. Tea extracts were compared for their ability to modulate IL-1β, IL-6, IL-8, TNFα and PGE(2 )release from human monocytes. Effects of tea extracts on 26S proteasome function were assessed. NF-κB activity was monitored by EMSAs. Viability and radiation response of macrophages after exposure to tea extracts was measured by MTT assays. RESULTS: Tea extracts supported the restitution of skin integrity. Tea extracts inhibited proteasome function and suppressed cytokine release. NF-κB activity was altered by tea extracts in a complex, caspase-dependent manner, which differed from the effects of epigallocatechin-gallate. Additionally, both tea extracts, as well as epigallocatechin-gallate, slightly protected macrophages from ionizing radiation CONCLUSION: Tea extracts are an efficient, broadly available treatment option for patients suffering from acute radiation-induced skin toxicity. The molecular mechanisms underlying the beneficial effects are complex, and most likely not exclusively dependent on effects of tea polyphenols such as epigallocatechin-gallate

Rule based classifier for the analysis of gene-gene and gene-environment interactions in genetic association studies

<p>Abstract</p> <p>Background</p> <p>Several methods have been presented for the analysis of complex interactions between genetic polymorphisms and/or environmental factors. Despite the available methods, there is still a need for alternative methods, because no single method will perform well in all scenarios. The aim of this work was to evaluate the performance of three selected rule based classifier algorithms, RIPPER, RIDOR and PART, for the analysis of genetic association studies.</p> <p>Methods</p> <p>Overall, 42 datasets were simulated with three different case-control models, a varying number of subjects (300, 600), SNPs (500, 1500, 3000) and noise (5%, 10%, 20%). The algorithms were applied to each of the datasets with a set of algorithm-specific settings. Results were further investigated with respect to a) the Model, b) the Rules, and c) the Attribute level. Data analysis was performed using WEKA, SAS and PERL.</p> <p>Results</p> <p>The RIPPER algorithm discovered the true case-control model at least once in >33% of the datasets. The RIDOR and PART algorithm performed poorly for model detection. The RIPPER, RIDOR and PART algorithm discovered the true case-control rules in more than 83%, 83% and 44% of the datasets, respectively. All three algorithms were able to detect the attributes utilized in the respective case-control models in most datasets.</p> <p>Conclusions</p> <p>The current analyses substantiate the utility of rule based classifiers such as RIPPER, RIDOR and PART for the detection of gene-gene/gene-environment interactions in genetic association studies. These classifiers could provide a valuable new method, complementing existing approaches, in the analysis of genetic association studies. The methods provide an advantage in being able to handle both categorical and continuous variable types. Further, because the outputs of the analyses are easy to interpret, the rule based classifier approach could quickly generate testable hypotheses for additional evaluation. Since the algorithms are computationally inexpensive, they may serve as valuable tools for preselection of attributes to be used in more complex, computationally intensive approaches. Whether used in isolation or in conjunction with other tools, rule based classifiers are an important addition to the armamentarium of tools available for analyses of complex genetic association studies.</p

GEIRA: gene-environment and gene–gene interaction research application

The GEIRA (Gene-Environment and Gene–Gene Interaction Research Application) algorithm and subsequent program is dedicated to genome-wide gene-environment and gene–gene interaction analysis. It implements concepts of both additive and multiplicative interaction as well as calculations based on dominant, recessive and co-dominant genetic models, respectively. Estimates of interactions are incorporated in a single table to make the output easily read. The algorithm is coded in both SAS and R. GEIRA is freely available to non-commercial users at http://www.epinet.se. Additional information, including user’s manual and example datasets is available online at http://www.epinet.se

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Comparative Linkage Meta-Analysis Reveals Regionally-Distinct, Disparate Genetic Architectures: Application to Bipolar Disorder and Schizophrenia

New high-throughput, population-based methods and next-generation sequencing capabilities hold great promise in the quest for common and rare variant discovery and in the search for ”missing heritability.” However, the optimal analytic strategies for approaching such data are still actively debated, representing the latest rate-limiting step in genetic progress. Since it is likely a majority of common variants of modest effect have been identified through the application of tagSNP-based microarray platforms (i.e., GWAS), alternative approaches robust to detection of low-frequency (1–5% MAF) and rare (<1%) variants are of great importance. Of direct relevance, we have available an accumulated wealth of linkage data collected through traditional genetic methods over several decades, the full value of which has not been exhausted. To that end, we compare results from two different linkage meta-analysis methods—GSMA and MSP—applied to the same set of 13 bipolar disorder and 16 schizophrenia GWLS datasets. Interestingly, we find that the two methods implicate distinct, largely non-overlapping, genomic regions. Furthermore, based on the statistical methods themselves and our contextualization of these results within the larger genetic literatures, our findings suggest, for each disorder, distinct genetic architectures may reside within disparate genomic regions. Thus, comparative linkage meta-analysis (CLMA) may be used to optimize low-frequency and rare variant discovery in the modern genomic era

Influence of the Environment on Participation in Social Roles for Young Adults with Down Syndrome

Background: The concept of disability is now understood as a result of the interaction between the individual, features related to impairment, and the physical and social environment. It is important to understand these environmental influences and how they affect social participation. The purpose of this study is to describe the social participation of young adults with Down syndrome and examine its relationship with the physical and social environment. Methods: Families ascertained from the Down syndrome ‘Needs Opinion Wishes’ database completed questionnaires during 2011. The questionnaires contained two parts, young person characteristics and family characteristics. Young adults’ social participation was measured using the Assessment of Life Habits (LIFE-H) and the influences of environmental factors were measured by the Measure of the Quality of the Environment (MQE). The analysis involved descriptive statistics and linear and logistic regression. Results: Overall, participation in daily activities was higher (mean 6.45) than in social roles (mean 5.17) (range 0 to 9). When the physical and/or social environment was reported as a facilitator, compared to being no influence or a barrier, participation in social roles was greater (coef 0.89, 95%CI 0.28, 1.52, coef 0.83, 95%CI 0.17, 1.49, respectively). The relationships between participation and both the physical (coef 0.60, 95% CI -0.40, 1.24) and social (coef 0.20, 95%CI -0.47, 0.87) environments were reduced when age, gender, behavior and functioning in ADL were taken into account. Conclusion: We found that young adults’ participation in social roles was influenced more by the physical environment than by the social environment, providing a potentially modifiable avenue for intervention

A role for CETP TaqIB polymorphism in determining susceptibility to atrial fibrillation: a nested case control study

BACKGROUND: Studies investigating the genetic and environmental characteristics of atrial fibrillation (AF) may provide new insights in the complex development of AF. We aimed to investigate the association between several environmental factors and loci of candidate genes, which might be related to the presence of AF. METHODS: A nested case-control study within the PREVEND cohort was conducted. Standard 12 lead electrocardiograms were recorded and AF was defined according to Minnesota codes. For every case, an age and gender matched control was selected from the same population (n = 194). In addition to logistic regression analyses, the multifactor-dimensionality reduction (MDR) method and interaction entropy graphs were used for the evaluation of gene-gene and gene-environment interactions. Polymorphisms in genes from the Renin-angiotensin, Bradykinin and CETP systems were included. RESULTS: Subjects with AF had a higher prevalence of electrocardiographic left ventricular hypertrophy, ischemic heart disease, hypertension, renal dysfunction, elevated levels of C-reactive protein (CRP) and increased urinary albumin excretion as compared to controls. The polymorphisms of the Renin-angiotensin system and Bradykinin gene did not show a significant association with AF (p > 0.05). The TaqIB polymorphism of the CETP gene was significantly associated with the presence of AF (p < 0.05). Using the MDR method, the best genotype-phenotype models included the combination of micro- or macroalbuminuria and CETP TaqIB polymorphism, CRP >3 mg/L and CETP TaqIB polymorphism, renal dysfunction and the CETP TaqIB polymorphism, and ischemic heart disease and CETP TaqIB polymorphism (1000 fold permutation testing, P < 0.05). Interaction entropy graph showed that the combination of albuminuria and CETP TaqIB polymorphism removed the most entropy. CONCLUSION: CETP TaqIB polymorphism is significantly associated with the presence of AF in the context of micro- or macroalbuminuria, elevated C-reactive protein, renal dysfunction, and ischemic heart disease

Anxiety Disorders in Williams Syndrome Contrasted with Intellectual Disability and the General Population: A Systematic Review and Meta-Analysis

Individuals with specific genetic syndromes associated with intellectual disability (ID), such as Williams syndrome (WS), are at increased risk for developing anxiety disorders. A systematic literature review identified sixteen WS papers that could generate pooled prevalence estimates of anxiety disorders for WS. A meta-analysis compared these estimates with prevalence estimates for the heterogeneous ID population and the general population. Estimated rates of anxiety disorders in WS were high. WS individuals were four times more likely to experience anxiety than individuals with ID, and the risk was also heightened compared to the general population. The results provide further evidence of an unusual profile of high anxiety in WS