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Genetic Differences in the Immediate Transcriptome Response to Stress Predict Risk-Related Brain Function and Psychiatric Disorders

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      Summary

      Depression risk is exacerbated by genetic factors and stress exposure; however, the biological mechanisms through which these factors interact to confer depression risk are poorly understood. One putative biological mechanism implicates variability in the ability of cortisol, released in response to stress, to trigger a cascade of adaptive genomic and non-genomic processes through glucocorticoid receptor (GR) activation. Here, we demonstrate that common genetic variants in long-range enhancer elements modulate the immediate transcriptional response to GR activation in human blood cells. These functional genetic variants increase risk for depression and co-heritable psychiatric disorders. Moreover, these risk variants are associated with inappropriate amygdala reactivity, a transdiagnostic psychiatric endophenotype and an important stress hormone response trigger. Network modeling and animal experiments suggest that these genetic differences in GR-induced transcriptional activation may mediate the risk for depression and other psychiatric disorders by altering a network of functionally related stress-sensitive genes in blood and brain.Video Abstract

      Highlights

      •SNPs in long-range enhancers alter the transcriptional response of GR target genes•These functional SNPs predict risk for psychiatric but not other medical disorders•These variants are associated with differential neural circuit responses to threat•GR transcripts are strongly co-expressed and regulated in the brain of animal models

      Abstract

      Using a stimulated eQTL approach, Arloth et al. show that common genetic variants that alter the initial transcriptome response to stress hormone receptor activation also cumulatively increase the risk for stress-related psychiatric disorders and predict a threat response from the amygdala.

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      PLINK: a tool set for whole-genome association and population-based linkage analyses.

      Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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        Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication.

        Little is known about lifetime prevalence or age of onset of DSM-IV disorders. To estimate lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the recently completed National Comorbidity Survey Replication. Nationally representative face-to-face household survey conducted between February 2001 and April 2003 using the fully structured World Health Organization World Mental Health Survey version of the Composite International Diagnostic Interview. Nine thousand two hundred eighty-two English-speaking respondents aged 18 years and older. Lifetime DSM-IV anxiety, mood, impulse-control, and substance use disorders. Lifetime prevalence estimates are as follows: anxiety disorders, 28.8%; mood disorders, 20.8%; impulse-control disorders, 24.8%; substance use disorders, 14.6%; any disorder, 46.4%. Median age of onset is much earlier for anxiety (11 years) and impulse-control (11 years) disorders than for substance use (20 years) and mood (30 years) disorders. Half of all lifetime cases start by age 14 years and three fourths by age 24 years. Later onsets are mostly of comorbid conditions, with estimated lifetime risk of any disorder at age 75 years (50.8%) only slightly higher than observed lifetime prevalence (46.4%). Lifetime prevalence estimates are higher in recent cohorts than in earlier cohorts and have fairly stable intercohort differences across the life course that vary in substantively plausible ways among sociodemographic subgroups. About half of Americans will meet the criteria for a DSM-IV disorder sometime in their life, with first onset usually in childhood or adolescence. Interventions aimed at prevention or early treatment need to focus on youth.
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          Biological Insights From 108 Schizophrenia-Associated Genetic Loci

          Summary Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here, we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain providing biological plausibility for the findings. Many findings have the potential to provide entirely novel insights into aetiology, but associations at DRD2 and multiple genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that play important roles in immunity, providing support for the hypothesized link between the immune system and schizophrenia.
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            Author and article information

            Affiliations
            [1 ]Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich 80804, Germany
            [2 ]Department of Psychology and Neuroscience, Institute for Genome Sciences and Policy, Duke University, Durham, NC 27708, USA
            [3 ]Department of Psychology, Washington University in St. Louis, St. Louis, MO 63130, USA
            [4 ]Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany
            [5 ]23andMe, Mountain View, CA 94043, USA
            [6 ]Technische Universität München, c/o Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Developmental Genetics, Neuherberg 85764, Germany
            [7 ]Deutsches Zentrum für Neurodegenerative Erkrankungen e. V. (DZNE), Site Munich, Munich 80336, Germany
            [8 ]Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA 30329, USA
            [9 ]Department of Neurology and Neurological Sciences, School of Medicine, Stanford University, Palo Alto, CA 94304, USA
            [10 ]Department of Stress Neurobiology and Neurogenetics, Max Planck Institute of Psychiatry, Munich 80804, Germany
            Author notes
            []Corresponding author binder@ 123456psych.mpg.de
            Contributors
            Journal
            Neuron
            Neuron
            Neuron
            Cell Press
            0896-6273
            1097-4199
            03 June 2015
            03 June 2015
            : 86
            : 5
            : 1189-1202
            26050039
            4490780
            S0896-6273(15)00473-0
            10.1016/j.neuron.2015.05.034
            © 2015 The Authors

            This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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            Neurosciences

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