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      Childhood Adversity Moderates the Effects of HTR2A Epigenetic Regulatory Polymorphisms on Rumination

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          Abstract

          The serotonin system has been suggested to moderate the association between childhood maltreatment and rumination, with the latter in its turn reported to be a mediator in the depressogenic effect of childhood maltreatment. Therefore, we investigated whether the associations of two epigenetic regulatory polymorphisms in the HTR2A serotonin receptor gene with Ruminative Responses Scale rumination and its two subtypes, brooding and reflection, are moderated by childhood adversity (derived from the Childhood Trauma Questionnaire) among 1,501 European white adults. We tested post hoc whether the significant associations are due to depression. We also tested the replicability of the significant results within the two subsamples of Budapest and Manchester. We revealed two significant models: both the association of methylation site rs6311 with rumination and that of miRNA binding site rs3125 (supposed to bind miR-1270, miR-1304, miR-202, miR-539 and miR-620) with brooding were a function of childhood adversity, and both interaction findings were significantly present both in the never-depressed and in the ever-depressed group. Moreover, the association of rs3125 with brooding could be replicated across the separate subsamples, and remained significant even when controlling for lifetime depression and the Brief Symptom Inventory depression score. These findings indicate the crucial importance of involving stress factors when considering endophenotypes and suggest that brooding is a more promising endophenotype than a broader measure of rumination. Transdiagnostic relevance of the brooding endophenotype and the potential of targeting epigenetic regulatory polymorphisms of HTR2A in primary and secondary prevention of depression and possibly of other disorders are also discussed.

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          Most cited references 62

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          Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach

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            Reciprocal relations between rumination and bulimic, substance abuse, and depressive symptoms in female adolescents.

            The authors examined the reciprocal relations between rumination and symptoms of depression, bulimia, and substance abuse with longitudinal data from 496 female adolescents. Rumination predicted future increases in bulimic and substance abuse symptoms, as well as onset of major depression, binge eating, and substance abuse. Depressive and bulimic, but not substance abuse, symptoms predicted increases in rumination. Rumination did not predict increases in externalizing symptoms, providing evidence for the specificity of effects of rumination, although externalizing symptoms predicted future increases in rumination. Results suggest rumination may contribute to the etiology of depressive, bulimic, and substance abuse pathology and that the former two disturbances may foster increased rumination. Results imply that it might be beneficial for prevention programs to target this cognitive vulnerability. (c) 2007 APA, all rights reserved.
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              Common features of microRNA target prediction tools

              The human genome encodes for over 1800 microRNAs (miRNAs), which are short non-coding RNA molecules that function to regulate gene expression post-transcriptionally. Due to the potential for one miRNA to target multiple gene transcripts, miRNAs are recognized as a major mechanism to regulate gene expression and mRNA translation. Computational prediction of miRNA targets is a critical initial step in identifying miRNA:mRNA target interactions for experimental validation. The available tools for miRNA target prediction encompass a range of different computational approaches, from the modeling of physical interactions to the incorporation of machine learning. This review provides an overview of the major computational approaches to miRNA target prediction. Our discussion highlights three tools for their ease of use, reliance on relatively updated versions of miRBase, and range of capabilities, and these are DIANA-microT-CDS, miRanda-mirSVR, and TargetScan. In comparison across all miRNA target prediction tools, four main aspects of the miRNA:mRNA target interaction emerge as common features on which most target prediction is based: seed match, conservation, free energy, and site accessibility. This review explains these features and identifies how they are incorporated into currently available target prediction tools. MiRNA target prediction is a dynamic field with increasing attention on development of new analysis tools. This review attempts to provide a comprehensive assessment of these tools in a manner that is accessible across disciplines. Understanding the basis of these prediction methodologies will aid in user selection of the appropriate tools and interpretation of the tool output.
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                Author and article information

                Contributors
                Journal
                Front Psychiatry
                Front Psychiatry
                Front. Psychiatry
                Frontiers in Psychiatry
                Frontiers Media S.A.
                1664-0640
                14 June 2019
                2019
                : 10
                Affiliations
                1Department of Pharmacodynamics, Faculty of Pharmacy, Semmelweis University , Budapest, Hungary
                2NAP-2-SE New Antidepressant Target Research Group, Hungarian Brain Research Program, Semmelweis University , Budapest, Hungary
                3MTA-SE Neuropsychopharmacology and Neurochemistry Research Group, Hungarian Academy of Sciences, Semmelweis University , Budapest, Hungary
                4Department of Psychiatry and Psychotherapy, Kutvolgyi Clinical Centre, Semmelweis University , Budapest, Hungary
                5SE-NAP 2 Genetic Brain Imaging Migraine Research Group, Hungarian Brain Research Program, Semmelweis University , Budapest, Hungary
                6Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester , Manchester, United Kingdom
                7Manchester Academic Health Sciences Centre , Manchester, United Kingdom
                8Greater Manchester Mental Health NHS Foundation Trust , Manchester, United Kingdom
                Author notes

                Edited by: Divya Mehta, Queensland University of Technology, Australia

                Reviewed by: Ludwig Stenz, Université de Genève, Switzerland; Gabriel R. Fries, University of Texas Health Science Center at Houston, United States

                *Correspondence: Nora Eszlari, eszlari.nora@ 123456pharma.semmelweis-univ.hu

                This article was submitted to Behavioral and Psychiatric Genetics, a section of the journal Frontiers in Psychiatry

                Article
                10.3389/fpsyt.2019.00394
                6588047
                Copyright © 2019 Eszlari, Petschner, Gonda, Baksa, Elliott, Anderson, Deakin, Bagdy and Juhasz

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                Page count
                Figures: 5, Tables: 3, Equations: 0, References: 72, Pages: 13, Words: 6969
                Categories
                Psychiatry
                Original Research

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