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      Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder

      research-article
      1 , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 7 , 8 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 17 , 19 , 20 , 17 , 21 , 15 , 16 , 22 , 23 , 14 , 18 , 20 , 24 , 25 , 26 , 14 , 15 , 16 , 22 , 7 , 18 , 8 , 14 , 1 , *
      Frontiers in Psychiatry
      Frontiers Media S.A.
      pharmacogenomics, polygenic score, personality traits, major depression, antidepressants, selective serotonin reuptake inhibitors

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          Abstract

          Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD). Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs) derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs). In addition, we performed meta-analyses of genome-wide association studies (GWASs) on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529) and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865). The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p < 0.05 across P T thresholds in both cohorts. A significant association was also found between the PGS for conscientiousness and SSRIs treatment response in the PGRN-AMPS sample. In the cross-trait GWAS meta-analyses, we identified eight loci associated with (a) SSRIs response and conscientiousness near YEATS4 gene and (b) SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs.

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          Most cited references50

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders

            Chi-Hua Chen and colleagues report a GWAS for five personality traits and identify four loci associated with extraversion and two associated with neuroticism at genome-wide significance. They find that the five personality traits are genetically correlated and identify genetic correlations between personality traits and psychiatric disorders.
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              The genetic overlap between mood disorders and cardiometabolic diseases: a systematic review of genome wide and candidate gene studies

              Meta-analyses of genome-wide association studies (meta-GWASs) and candidate gene studies have identified genetic variants associated with cardiovascular diseases, metabolic diseases and mood disorders. Although previous efforts were successful for individual disease conditions (single disease), limited information exists on shared genetic risk between these disorders. This article presents a detailed review and analysis of cardiometabolic diseases risk (CMD-R) genes that are also associated with mood disorders. First, we reviewed meta-GWASs published until January 2016, for the diseases ‘type 2 diabetes, coronary artery disease, hypertension’ and/or for the risk factors ‘blood pressure, obesity, plasma lipid levels, insulin and glucose related traits’. We then searched the literature for published associations of these CMD-R genes with mood disorders. We considered studies that reported a significant association of at least one of the CMD-R genes and ‘depression’ or ‘depressive disorder’ or ‘depressive symptoms’ or ‘bipolar disorder’ or ‘lithium treatment response in bipolar disorder’, or ‘serotonin reuptake inhibitors treatment response in major depression’. Our review revealed 24 potential pleiotropic genes that are likely to be shared between mood disorders and CMD-Rs. These genes include MTHFR, CACNA1D, CACNB2, GNAS, ADRB1, NCAN, REST, FTO, POMC, BDNF, CREB, ITIH4, LEP, GSK3B, SLC18A1, TLR4, PPP1R1B, APOE, CRY2, HTR1A, ADRA2A, TCF7L2, MTNR1B and IGF1. A pathway analysis of these genes revealed significant pathways: corticotrophin-releasing hormone signaling, AMPK signaling, cAMP-mediated or G-protein coupled receptor signaling, axonal guidance signaling, serotonin or dopamine receptors signaling, dopamine-DARPP32 feedback in cAMP signaling, circadian rhythm signaling and leptin signaling. Our review provides insights into the shared biological mechanisms of mood disorders and cardiometabolic diseases.
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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
                06 March 2018
                2018
                : 9
                : 65
                Affiliations
                [1] 1Discipline of Psychiatry, School of Medicine, University of Adelaide , Adelaide, SA, Australia
                [2] 2Northern Adelaide Local Health Network, Mental Health Services , Adelaide, SA, Australia
                [3] 3Epidemiology Branch, Division of Intramural Population Health Research, National Institute of Child Health and Human Development, National Institutes of Health , Bethesda, MD, United States
                [4] 4HSL Institute for Aging Research, Harvard Medical School , Boston, MA, United States
                [5] 5Program for Quantitative Genomics, Harvard School of Public Health , Boston, MA, United States
                [6] 6Broad Institute of MIT and Harvard , Cambridge, MA, United States
                [7] 7Biomedical Data Science, Stanford University , Stanford, CA, United States
                [8] 8Department of Health Sciences Research, Mayo Clinic , Rochester, NY, United States
                [9] 9Department of Bioengineering, Stanford University , Stanford, CA, United States
                [10] 10Department of Psychiatry and Psychotherapy, University of Muenster , Muenster, Germany
                [11] 11Department of Clinical Pharmacology, University Göttingen , Göttingen, Germany
                [12] 12Department of Psychiatry, Taipei Medical University-Shuangho Hospital , New Taipei City, Taiwan
                [13] 13Department of Psychiatry and Psychotherapy, Faculty of Medicine, University of Freiburg , Freiburg, Germany
                [14] 14Department of Psychiatry and Psychology, Mayo Clinic , Rochester, NY, United States
                [15] 15Department of Psychiatry, Taipei Veterans General Hospital , Taipei, Taiwan
                [16] 16Division of Psychiatry, School of Medicine, National Yang-Ming University , Taipei, Taiwan
                [17] 17Department of Psychiatry, Faculty of Medicine and Life Sciences, University of Tampere , Tampere, Finland
                [18] 18Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic Rochester , Rochester, MN, United States
                [19] 19Department of Psychiatry, Seinäjoki Hospital District , Seinäjoki, Finland
                [20] 20Department of Neuropsychiatry, Kansai Medical University , Osaka, Japan
                [21] 21Department of Psychiatry, Tampere University Hospital , Tampere, Finland
                [22] 22RIKEN Center for Integrative Medical Sciences , Kanagawa, Japan
                [23] 23Department of Pharmacy, Hyogo University of Health Sciences , Hyogo, Japan
                [24] 24Center for Neuropsychiatric Research, National Health Research Institutes , Miaoli, Taiwan
                [25] 25Center for Medical Genetics Research, Rajanukul Institute, Department of Mental Health, Ministry of Public Health Bangkok , Bangkok, Thailand
                [26] 26Research Division Federal Institute for Drugs and Medical Devices , Bonn, Germany
                Author notes

                Edited by: Stefan Borgwardt, University of Basel, Switzerland

                Reviewed by: Ju Wang, Tianjin Medical University, China; Kurt Leroy Hoffman, Autonomous University of Tlaxcala, Mexico

                *Correspondence: Bernhard T. Baune, bernhard.baune@ 123456adelaide.edu.au

                Specialty section: This article was submitted to Molecular Psychiatry, a section of the journal Frontiers in Psychiatry

                Article
                10.3389/fpsyt.2018.00065
                5845551
                29559929
                cc1a46ba-16af-4296-b253-53666c30e4b3
                Copyright © 2018 Amare, Schubert, Tekola-Ayele, Hsu, Sangkuhl, Jenkins, Whaley, Barman, Batzler, Altman, Arolt, Brockmöller, Chen, Domschke, Hall-Flavin, Hong, Illi, Ji, Kampman, Kinoshita, Leinonen, Liou, Mushiroda, Nonen, Skime, Wang, Kato, Liu, Praphanphoj, Stingl, Bobo, Tsai, Kubo, Klein, Weinshilboum, Biernacka and Baune.

                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 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.

                History
                : 08 December 2017
                : 19 February 2018
                Page count
                Figures: 3, Tables: 2, Equations: 0, References: 67, Pages: 11, Words: 8108
                Categories
                Psychiatry
                Original Research

                Clinical Psychology & Psychiatry
                pharmacogenomics,polygenic score,personality traits,major depression,antidepressants,selective serotonin reuptake inhibitors

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