61 research outputs found

    On the justification of intergroup violence: The roles of procedural justice, police legitimacy and group identity in attitudes towards violence among indigenous people

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    Objective Why do people justify intergroup violence? In this paper we examine attitudes towards violence perpetrated by indigenous activists to claim for rights and violence by pólice officers against indigenous people. We assess the role that perceived pólice legitimacy, procedurally just policing towards the indigenous minority group and group identity play in the justification of intergroup violence. Method We present findings from two surveys (Study 1, n=1493, Study 2, n=198) and an experiment (Study 3, n=76) conducted among indigenous people in Chile. Studies 1 and 2 measure perceptions of police procedural justice towards indigenous people. Study 3 manipulates the fairness with which police officers treat indigenous people. Effects of procedural justice on police legitimacy (Studies 2 and 3) and attitudes towards violence for social change and social control (Studies 1-3) are analyzed. Result Higher perceptions of procedurally just policing towards indigenous people predict more support for police violence and less support for violence perpetrated by indigenous activists. These effects are mediated by perceived police legitimacy and moderated by identification with the minority group. Among people who identify strongly with their indigenous group, perceiving high procedural justice predicts greater police legitimacy, greater support for police violence, and lesser support for violence perpetrated by indigenous activists

    Genetic predictors of risk and resilience in psychiatric disorders: A cross-disorder genome-wide association study of functional impairment in major depressive disorder, bipolar disorder, and schizophrenia

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    Functional impairment is one of the most enduring, intractable consequences of psychiatric disorders and is both familial and heritable. Previous studies have suggested that variation in functional impairment can be independent of symptom severity. Here we report the first genome-wide association study (GWAS) of functional impairment in the context of major mental illness. Participants of European-American descent (N=2,246) were included from three large treatment studies of bipolar disorder (STEP-BD) (N=765), major depressive disorder (STAR*D) (N=1091), and schizophrenia (CATIE) (N=390). At study entry, participants completed the SF-12, a widely-used measure of health-related quality of life. We performed a GWAS and pathway analysis of the mental and physical components of health-related quality of life across diagnosis (~1.6 million single nucleotide polymorphisms), adjusting for psychiatric symptom severity. Psychiatric symptom severity was a significant predictor of functional impairment, but it accounted for less than one-third of the variance across disorders. After controlling for diagnostic category and symptom severity, the strongest evidence of genetic association was between variants in ADAMTS16 and physical functioning (p=5.87 × 10−8). Pathway analysis did not indicate significant enrichment after correction for gene clustering and multiple testing. This study illustrates a phenotypic framework for examining genetic contributions to functional impairment across psychiatric disorders

    Using C. elegans to decipher the cellular and molecular mechanisms underlying neurodevelopmental disorders

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    Prova tipográfica (uncorrected proof)Neurodevelopmental disorders such as epilepsy, intellectual disability (ID), and autism spectrum disorders (ASDs) occur in over 2 % of the population, as the result of genetic mutations, environmental factors, or combination of both. In the last years, use of large-scale genomic techniques allowed important advances in the identification of genes/loci associated with these disorders. Nevertheless, following association of novel genes with a given disease, interpretation of findings is often difficult due to lack of information on gene function and effect of a given mutation in the corresponding protein. This brings the need to validate genetic associations from a functional perspective in model systems in a relatively fast but effective manner. In this context, the small nematode, Caenorhabditis elegans, presents a good compromise between the simplicity of cell models and the complexity of rodent nervous systems. In this article, we review the features that make C. elegans a good model for the study of neurodevelopmental diseases. We discuss its nervous system architecture and function as well as the molecular basis of behaviors that seem important in the context of different neurodevelopmental disorders. We review methodologies used to assess memory, learning, and social behavior as well as susceptibility to seizures in this organism. We will also discuss technological progresses applied in C. elegans neurobiology research, such as use of microfluidics and optogenetic tools. Finally, we will present some interesting examples of the functional analysis of genes associated with human neurodevelopmental disorders and how we can move from genes to therapies using this simple model organism.The authors would like to acknowledge Fundação para a Ciência e Tecnologia (FCT) (PTDC/SAU-GMG/112577/2009). AJR and CB are recipients of FCT fellowships: SFRH/BPD/33611/2009 and SFRH/BPD/74452/2010, respectively

    Introduction to the SPARC Reanalysis Intercomparison Project (S-RIP) and overview of the reanalysis systems

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    The climate research community uses atmospheric reanalysis data sets to understand a wide range of processes and variability in the atmosphere, yet different reanalyses may give very different results for the same diagnostics. The Stratosphere–troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP) is a coordinated activity to compare reanalysis data sets using a variety of key diagnostics. The objectives of this project are to identify differences among reanalyses and understand their underlying causes, to provide guidance on appropriate usage of various reanalysis products in scientific studies, particularly those of relevance to SPARC, and to contribute to future improvements in the reanalysis products by establishing collaborative links between reanalysis centres and data users. The project focuses predominantly on differences among reanalyses, although studies that include operational analyses and studies comparing reanalyses with observations are also included when appropriate. The emphasis is on diagnostics of the upper troposphere, stratosphere, and lower mesosphere. This paper summarizes the motivation and goals of the S-RIP activity and extensively reviews key technical aspects of the reanalysis data sets that are the focus of this activity. The special issue The SPARC Reanalysis Intercomparison Project (S-RIP) in this journal serves to collect research with relevance to the S-RIP in preparation for the publication of the planned two (interim and full) S-RIP reports

    Analysis of shared heritability in common disorders of the brain

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    ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders
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