Utrecht University

About: Utrecht University is a education organization based out in Utrecht, Utrecht, Netherlands. It is known for research contribution in the topics: Population & Context (language use). The organization has 58176 authors who have published 139351 publications receiving 6214282 citations. The organization is also known as: UU & Universiteit Utrecht.

Amazonia Through Time: Andean Uplift, Climate Change, Landscape Evolution, and Biodiversity

Abstract: The Amazonian rainforest is arguably the most species-rich terrestrial ecosystem in the world, yet the timing of the origin and evolutionary causes of this diversity are a matter of debate. We review the geologic and phylogenetic evidence from Amazonia and compare it with uplift records from the Andes. This uplift and its effect on regional climate fundamentally changed the Amazonian landscape by reconfiguring drainage patterns and creating a vast influx of sediments into the basin. On this “Andean” substrate, a region-wide edaphic mosaic developed that became extremely rich in species, particularly in Western Amazonia. We show that Andean uplift was crucial for the evolution of Amazonian landscapes and ecosystems, and that current biodiversity patterns are rooted deep in the pre-Quaternary.

Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis

Abstract: By combining genome-wide association data from 8,130 individuals with type 2 diabetes (T2D) and 38,987 controls of European descent and following up previously unidentified meta-analysis signals in a further 34,412 cases and 59,925 controls, we identified 12 new T2D association signals with combined P<5x10(-8). These include a second independent signal at the KCNQ1 locus; the first report, to our knowledge, of an X-chromosomal association (near DUSP9); and a further instance of overlap between loci implicated in monogenic and multifactorial forms of diabetes (at HNF1A). The identified loci affect both beta-cell function and insulin action, and, overall, T2D association signals show evidence of enrichment for genes involved in cell cycle regulation. We also show that a high proportion of T2D susceptibility loci harbor independent association signals influencing apparently unrelated complex traits.

Prevalence of mental disorders in Europe: Results from the European Study of the Epidemiology of Mental Disorders (ESEMeD) project

Abstract: Objective: To describe the 12-month and lifetime prevalence rates of mood, anxiety and alcohol disorders in six European countries. Method: A representative random sample of non-institutionalized inhabitants from Belgium, France, Germany, Italy, the Netherlands and Spain aged 18 or older (n = 21425) were interviewed between January 2001 and August 2003. DSM-IV disorders were assessed by lay interviewers using a revised version of the Composite International Diagnostic Interview (WMH-CIDI). Results: Fourteen per cent reported a lifetime history of any mood disorder, 13.6% any anxiety disorder and 5.2% a lifetime history of any alcohol disorder. More than 6% reported any anxiety disorder, 4.2% any mood disorder, and 1.0% any alcohol disorder in the last year. Major depression and specific phobia were the most common single mental disorders. Women were twice as likely to suffer 12-month mood and anxiety disorders as men, while men were more likely to suffer alcohol abuse disorders. Conclusion: ESEMeD is the first study to highlight the magnitude of mental disorders in the six European countries studied. Mental disorders were frequent, more common in female, unemployed, disabled persons, or persons who were never married or previously married. Younger persons were also more likely to have mental disorders, indicating an early age of onset for mood, anxiety and alcohol disorders.

Binary Interaction Dominates the Evolution of Massive Stars

Abstract: The presence of a nearby companion alters the evolution of massive stars in binary systems, leading to phenomena such as stellar mergers, x-ray binaries, and gamma-ray bursts. Unambiguous constraints on the fraction of massive stars affected by binary interaction were lacking. We simultaneously measured all relevant binary characteristics in a sample of Galactic massive O stars and quantified the frequency and nature of binary interactions. More than 70% of all massive stars will exchange mass with a companion, leading to a binary merger in one-third of the cases. These numbers greatly exceed previous estimates and imply that binary interaction dominates the evolution of massive stars, with implications for populations of massive stars and their supernovae.

Large recurrent microdeletions associated with schizophrenia

Abstract: Reduced fecundity, associated with severe mental disorders, places negative selection pressure on risk alleles and may explain, in part, why common variants have not been found that confer risk of disorders such as autism, schizophrenia and mental retardation. Thus, rare variants may account for a larger fraction of the overall genetic risk than previously assumed. In contrast to rare single nucleotide mutations, rare copy number variations (CNVs) can be detected using genome-wide single nucleotide polymorphism arrays. This has led to the identification of CNVs associated with mental retardation and autism. In a genome-wide search for CNVs associating with schizophrenia, we used a population-based sample to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring. The 66 de novo CNVs identified were tested for association in a sample of 1,433 schizophrenia cases and 33,250 controls. Three deletions at 1q21.1, 15q11.2 and 15q13.3 showing nominal association with schizophrenia in the first sample (phase I) were followed up in a second sample of 3,285 cases and 7,951 controls (phase II). All three deletions significantly associate with schizophrenia and related psychoses in the combined sample. The identification of these rare, recurrent risk variants, having occurred independently in multiple founders and being subject to negative selection, is important in itself. CNV analysis may also point the way to the identification of additional and more prevalent risk variants in genes and pathways involved in schizophrenia.