Browsing by Issue Date, starting with "2015-02-05"
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- Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorderPublication . Maier, R.; Moser, G.; Chen, G.B.; Ripke, S; Cross-Disorder Working Group of the Psychiatric Genomics Consortium; Coryell, W.; Potash, J.B.; Scheftner, W.A.; Shi, J.; Weissman, M.M.; Hultman, C.M.; Landén, M.; Levinson, D.F.; Kendler, K.S.; Smoller, J.W.; Wray, N.R.; Lee, S.H.Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk
- Genome Sequencing of 10 Helicobacter pylori Pediatric Strains from Patients with Nonulcer Dyspepsia and Peptic Ulcer DiseasePublication . Nunes, Alexandra; Rocha, Raquel; Vale, Filipa F.; Vieira, Luís; Sampaio, Daniel A.; Dias, Ricardo; Gomes, João Paulo; Oleastro, MónicaWe present draft genome sequences of 10 Helicobacter pylori clinical strains isolated from children. This will be important for future studies of comparative genomics in order to better understand the virulence determinants underlying peptic ulcer disease.
- Water–Rock Interaction and Geochemical Processes in Surface Waters Influenced by Tailings Impoundments: Impact and Threats to the Ecosystems and Human Health in Rural Communities (Panasqueira Mine, central Portugal)Publication . Candeias, Carla; Ávila, Paula Freire; da Silva, Eduardo Ferreira; Durães, Nuno; Teixeira, João PauloThe present and past mining activity left several abandoned tailings and dams in the Panasqueira tin– tungsten mining area. Seasonal water samples and stream sediments were collected during two different periods (rainy and dry seasons) and analyzed for a wide range of major and trace elements, in order to define the present hydrochemical situation. Rain waters interact with the altered sulfides stored in the tailings which generate runoff waters with high metal concentrations. The waste material derived from the exploitation enhanced acidification and metal-releasing processes, due to the increase in the specific surface, which favors the oxidation of sulfide minerals. Acid drainage and high metal(loid)s (Cd, Fe, Mn, Zn, Cu, As) concentrations in solution were observed in waters leaching the Panasqueira tailing deposits. In dry season, generally the acidic waters, enriched in metals, evaporate progressively depositing sulfate efflorescences characteristic of acidic environments. The elements distribution in precipitated minerals helps in the interpretation of aqueous geochemical data. Aqueous concentrations may be attenuated by goethite, gibbsite, and/or ferrihydrite precipitation in the oxidation zone through adsorption processes. The use of these waters for human consumption and for irrigation represents a threat to humans as they have a potential carcinogenic risk, especially due to the As concentrations. The acid water precipitation is present on the stream sediments, with concentrations exceeding the toxicity limits. Stream sediments are good receptors of metals and metalloids transported by waters. The enrichment factor values, of heavy metal(loid)s from Casinhas stream and Zêzere river sediments, are extremely high in Ag, As, Cd, and Cu revealing enrichments for these potential toxic elements. Igeo values shows that samples are strongly to very strongly polluted for Ag, As, Bi, Cd, and Cu. According to the consensus-based SQGs, 80 % of the samples were classified at the level of great concern and adverse biological effects are to be expected frequently in this area.