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Liu C, Gershon ES. Endophenotype 2.0: updated definitions and criteria for endophenotypes of psychiatric disorders, incorporating new technologies and findings. Transl Psychiatry 2024; 14:502. [PMID: 39719446 PMCID: PMC11668880 DOI: 10.1038/s41398-024-03195-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2024] [Revised: 11/28/2024] [Accepted: 12/05/2024] [Indexed: 12/26/2024] Open
Abstract
Recent genetic studies have linked numerous loci to psychiatric disorders. However, the biological pathways that connect these genetic associations to psychiatric disorders' specific pathophysiological processes are largely unclear. Endophenotypes, first defined over five decades ago, are heritable traits, independent of disease state that are associated with a disease, encompassing a broad range of neurophysiological, biochemical, endocrinological, neuroanatomical, cognitive, and neuropsychological characteristics. Considering the advancements in genetics and genomics over recent decades, we propose a revised definition of endophenotypes as 'genetically influenced phenotypes linked to disease or treatment characteristics and their related events.' We also updated endophenotype criteria to include (1) reliable measurement, (2) association with the disease or its related events, and (3) genetic mediation. 'Genetic mediation' is introduced to differentiate between causality and pleiotropic effects and allows non-linear relationships. Furthermore, this updated Endophenotype 2.0 framework expands to encompass genetically regulated responses to disease-related factors, including environmental risks, illness progression, treatment responses, and resilience phenotypes, which may be state-dependent. This broadened definition paves the way for developing new endophenotypes crucial for genetic analyses in psychiatric disorders. Integrating genetics, genomics, and diverse endophenotypes into multi-dimensional mechanistic models is vital for advancing our understanding of psychiatric disorders. Crucially, elucidating the biological underpinnings of endophenotypes will enhance our grasp of psychiatric genetics, thereby improving disease risk prediction and treatment approaches.
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Affiliation(s)
- Chunyu Liu
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY, USA.
- School of Life Sciences, Central South University, Changsha, China.
| | - Elliot S Gershon
- Departments of Psychiatry and Human Genetics, The University of Chicago, Chicago, IL, USA.
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2
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Fleischmann E, Dalkner N, Fellendorf FT, Bengesser SA, Lenger M, Birner A, Queissner R, Platzer M, Tmava-Berisha A, Maget A, Wagner-Skacel J, Stross T, Schmiedhofer F, Smolle S, Painold A, Reininghaus EZ. The Big Five as Predictors of Cognitive Function in Individuals with Bipolar Disorder. Brain Sci 2023; 13:brainsci13050773. [PMID: 37239245 DOI: 10.3390/brainsci13050773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 04/02/2023] [Accepted: 05/02/2023] [Indexed: 05/28/2023] Open
Abstract
The connection between cognitive function and the "Big Five" personality traits (openness, conscientiousness, extraversion, agreeableness, and neuroticism) in the general population is well known; however, studies researching bipolar disorder (BD) are scarce. Therefore, this study aimed to investigate the Big Five as predictors of executive function, verbal memory, attention, and processing speed in euthymic individuals with BD (cross-sectional: n = 129, including time point t1; longitudinal: n = 35, including t1 and t2). Participants completed the NEO Five-Factor Inventory, the Color and Word Interference Test, the Trail Making Test, the d2 Test of Attention Revised, and the California Verbal Learning Test. The results showed a significant negative correlation between executive function and neuroticism at t1. Changes in cognitive function between t1 and t2 did not correlate with and could not be predicted by the Big Five at t1. Additionally, worse executive function at t2 was predicted by higher neuroticism and lower conscientiousness at t1, and high neuroticism was a predictor of worse verbal memory at t2. The Big Five might not strongly impact cognitive function over short periods; however, they are significant predictors of cognitive function. Future studies should include a higher number of participants and more time in between points of measurement.
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Affiliation(s)
- Eva Fleischmann
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Nina Dalkner
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Frederike T Fellendorf
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Susanne A Bengesser
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Melanie Lenger
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Armin Birner
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Robert Queissner
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Martina Platzer
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Adelina Tmava-Berisha
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Alexander Maget
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Jolana Wagner-Skacel
- Department of Medical Psychology and Psychotherapy, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Tatjana Stross
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Franziska Schmiedhofer
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Stefan Smolle
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Annamaria Painold
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
| | - Eva Z Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University of Graz, 8036 Graz, Styria, Austria
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3
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R Kelsoe J. Polygenic Polarity in Bipolar Disorder. Am J Psychiatry 2023; 180:177-178. [PMID: 36855878 DOI: 10.1176/appi.ajp.20230040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Affiliation(s)
- John R Kelsoe
- Department of Psychiatry, University of California, San Diego
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4
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Ortelbach N, Rote J, Dingelstadt AML, Stolzenburg A, Koenig C, O'Malley G, Quinlivan E, Fiebig J, Pfeiffer S, König B, Simhandl C, Bauer M, Pfennig A, Stamm TJ. The big five model in bipolar disorder: a latent profile analysis and its impact on longterm illness severity. Int J Bipolar Disord 2022; 10:1. [PMID: 35041119 PMCID: PMC8766615 DOI: 10.1186/s40345-021-00248-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 12/16/2021] [Indexed: 12/12/2022] Open
Abstract
Background Using a personality typing approach, we investigated the relationship between personality profiles and the prediction of longterm illness severity in patients with bipolar disorder (BD). While previous research suggests associations between BD and traits from the NEO-FFI profiles, the current study firstly aimed to identify latent classes of NEO-FFI profiles, and, secondly, to examine their impact on the longterm prognosis of BD. Methods Based on the NEO-FFI profiles of 134 euthymic patients diagnosed with BD (64.2% female, mean age = 44.3 years), successive latent profile analyses were conducted. Subsequently, a subsample (n = 80) was examined prospectively by performing multiple regression analysis of the latent classes to evaluate the longitudinal course of the disease (mean: 54.7 weeks) measured using a modified Morbidity Index. Results The latent profile analyses suggested a 3-class model typifying in a resilient (n = 68, 51%), vulnerable (n = 55, 41%) and highly vulnerable (n = 11, 8%) class. In the regression analysis, higher vulnerability predicted a higher longterm Morbidity Index (R2 = 0.28). Conclusions Subgroups of patients with BD share a number of discrete personality features and their illness is characterized by a similar clinical course. This knowledge is valuable in a variety of clinical contexts including early detection, intervention planning and treatment process.
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Affiliation(s)
- Niklas Ortelbach
- Department of Educational Science and Psychology, Free University of Berlin, Berlin, Germany
| | - Jonas Rote
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany
| | - Alice Mai Ly Dingelstadt
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Anna Stolzenburg
- Department of Psychology, Brandenburg Medical School Theodor Fontane, Fehrbelliner Straße 38, 16816, Neuruppin, Germany
| | - Cornelia Koenig
- Department of Psychology, Brandenburg Medical School Theodor Fontane, Fehrbelliner Straße 38, 16816, Neuruppin, Germany
| | - Grace O'Malley
- Department of Psychology, Brandenburg Medical School Theodor Fontane, Fehrbelliner Straße 38, 16816, Neuruppin, Germany.,Department of Pediatrics, Division of Oncology and Hematology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Esther Quinlivan
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jana Fiebig
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Steffi Pfeiffer
- Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany
| | | | - Christian Simhandl
- Bipolar Center, Wiener Neustadt, Austria.,Faculty of Medicine, Sigmund Freud University Vienna, Vienna, Austria
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany
| | - Andrea Pfennig
- Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany
| | - Thomas J Stamm
- Department of Psychology, Brandenburg Medical School Theodor Fontane, Fehrbelliner Straße 38, 16816, Neuruppin, Germany. .,Schloss Luetgenhof Hospital, Centre for Personal Medicine, Psychosomatics and Psychotherapy, Dassow, Mecklenburg-Western Pomerania, Germany.
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Ren Z, Liu C, Meng J, Liu Q, Shi L, Wu X, Song L, Qiu J. Effects of the Openness to Experience Polygenic Score on Cortical Thickness and Functional Connectivity. Front Neurosci 2021; 14:607912. [PMID: 33505240 PMCID: PMC7829912 DOI: 10.3389/fnins.2020.607912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 12/09/2020] [Indexed: 11/16/2022] Open
Abstract
Openness to experience (OTE) has relatively stable and heritable characteristics. Previous studies have used candidate gene approaches to explore the genetic mechanisms of OTE, but genome-wide polygenic scores have a greater genetic effect than other genetic analysis methods, and previous studies have never examined the potential effect of OTE on this cumulative effect at the level of the brain mechanism. In the present study, we aim to explore the associations between polygenic scores (PGSs) of OTE and brain structure and functions. First, the results of PGSs of OTE at seven different thresholds were calculated in a large Chinese sample (N = 586). Then, we determined the associations between PGSs of OTE and cortical thickness and functional connectivity. The results showed that PGSs of OTE was negatively correlated with the thickness of the fusiform gyrus, and PGSs of OTE were negatively associated with the functional connectivity between the left intraparietal sulcus (IPS) and the right posterior occipital lobe. These findings may suggest that the brain structure of fusiform gyrus and brain functions of IPS and posterior occipital lobe are partly regulated by OTE-related genetic factors.
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Affiliation(s)
- Zhiting Ren
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Cheng Liu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Jie Meng
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Qiang Liu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Liang Shi
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Xinran Wu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Li Song
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China
- Faculty of Psychology, Southwest University (SWU), Chongqing, China
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6
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Cortical surface area alterations shaped by genetic load for neuroticism. Mol Psychiatry 2020; 25:3422-3431. [PMID: 30185937 DOI: 10.1038/s41380-018-0236-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 07/22/2018] [Accepted: 07/31/2018] [Indexed: 01/24/2023]
Abstract
Neuroticism has been shown to act as an important risk factor for major depressive disorder (MDD). Genetic and neuroimaging research has independently revealed biological correlates of neurotic personality including cortical alterations in brain regions of high relevance for affective disorders. Here we investigated the influence of a polygenic score for neuroticism (PGS) on cortical brain structure in a joint discovery sample of n = 746 healthy controls (HC) and n = 268 MDD patients. Findings were validated in an independent replication sample (n = 341 HC and n = 263 MDD). Subgroup analyses stratified for case-control status and analyses of associations between neurotic phenotype and cortical measures were carried out. PGS for neuroticism was significantly associated with a decreased cortical surface area of the inferior parietal cortex, the precuneus, the rostral cingulate cortex and the inferior frontal gyrus in the discovery sample. Similar associations between PGS and surface area of the inferior parietal cortex and the precuneus were demonstrated in the replication sample. Subgroup analyses revealed negative associations in the latter regions between PGS and surface area in both HC and MDD subjects. Neurotic phenotype was negatively correlated with surface area in similar cortical regions including the inferior parietal cortex and the precuneus. No significant associations between PGS and cortical thickness were detected. The morphometric overlap of associations between both PGS and neurotic phenotype in similar cortical regions closely related to internally focused cognition points to the potential relevance of genetically shaped cortical alterations in the development of neuroticism.
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Antioch I, Ilie OD, Ciobica A, Doroftei B, Fornaro M. Preclinical Considerations about Affective Disorders and Pain: A Broadly Intertwined, yet Often Under-Explored, Relationship Having Major Clinical Implications. MEDICINA (KAUNAS, LITHUANIA) 2020; 56:E504. [PMID: 32992963 PMCID: PMC7600172 DOI: 10.3390/medicina56100504] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 09/16/2020] [Accepted: 09/23/2020] [Indexed: 12/11/2022]
Abstract
Background: Pain, a distinctive undesirable experience, encompasses several different and fluctuating presentations across varying mood disorders. Therefore, the present narrative review aimed to shed further light on the matter, accounting for both experimental animal models and clinical observations about major depressive disorder (MDD) pathology. Method: Major databases were inquired from inception until April 2016 for records about MDD and pain. Results: Pain and MDD are tightly associated with each other in a bi-directional fashion. Several cross-sectional and retrospective studies indicated a high presence of pain in the context of mood disorders, including MDD (up to 65%), but also increased prevalence rates in the case of mood disorders documented among people with a primary diagnosis of either psychological or somatic pain (prevalence rates exceeding 45%). The clinical implications of these observations suggest the need to account for mood and pain manifestations as a whole rather than distinct entities in order to deliver more effective interventions. Limitations: Narrative review, lack of systematic control groups (e.g., people with the primary diagnosis at review, but not the associated comorbidity as a study) to allow reliable comparisons. Prevalence rates and clinical features associated with pain varied across different studies as corresponding operational definitions did. Conclusions: Pain may have a detrimental effect on the course of mood disorders-the opposite holds. Promoting a timely recognition and management of such an often neglected comorbidity would therefore represent a primary goal toward the delivery of effective, multi-disciplinary care.
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Affiliation(s)
- Iulia Antioch
- Department of Research, Faculty of Biology, “Alexandru Ioan Cuza” University, Carol I Avenue, no 11, 700505 Iasi, Romania; (I.A.); (O.-D.I.)
| | - Ovidiu-Dumitru Ilie
- Department of Research, Faculty of Biology, “Alexandru Ioan Cuza” University, Carol I Avenue, no 11, 700505 Iasi, Romania; (I.A.); (O.-D.I.)
| | - Alin Ciobica
- Department of Research, Faculty of Biology, “Alexandru Ioan Cuza” University, Carol I Avenue, no 11, 700505 Iasi, Romania; (I.A.); (O.-D.I.)
| | - Bogdan Doroftei
- Faculty of Medicine, University of Medicine and Pharmacy “Grigore T. Popa”, University Street, no 16, 700115 Iasi, Romania
| | - Michele Fornaro
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University, New York, NY 10027, USA;
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Gordovez FJA, McMahon FJ. The genetics of bipolar disorder. Mol Psychiatry 2020; 25:544-559. [PMID: 31907381 DOI: 10.1038/s41380-019-0634-7] [Citation(s) in RCA: 152] [Impact Index Per Article: 30.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 11/22/2019] [Accepted: 12/11/2019] [Indexed: 12/11/2022]
Abstract
Bipolar disorder (BD) is one of the most heritable mental illnesses, but the elucidation of its genetic basis has proven to be a very challenging endeavor. Genome-Wide Association Studies (GWAS) have transformed our understanding of BD, providing the first reproducible evidence of specific genetic markers and a highly polygenic architecture that overlaps with that of schizophrenia, major depression, and other disorders. Individual GWAS markers appear to confer little risk, but common variants together account for about 25% of the heritability of BD. A few higher-risk associations have also been identified, such as a rare copy number variant on chromosome 16p11.2. Large scale next-generation sequencing studies are actively searching for other alleles that confer substantial risk. As our understanding of the genetics of BD improves, there is growing optimism that some clear biological pathways will emerge, providing a basis for future studies aimed at molecular diagnosis and novel therapeutics.
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Affiliation(s)
- Francis James A Gordovez
- Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Department of Health and Human Services, National Institutes of Health, Bethesda, MD, USA.,College of Medicine, University of the Philippines Manila, 1000, Ermita, Manila, Philippines
| | - Francis J McMahon
- Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Department of Health and Human Services, National Institutes of Health, Bethesda, MD, USA.
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9
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Genetic risk factors and gene–environment interactions in adult and childhood attention-deficit/hyperactivity disorder. Psychiatr Genet 2019; 29:63-78. [DOI: 10.1097/ypg.0000000000000220] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
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10
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Lehto K, Karlsson I, Lundholm C, Pedersen NL. Genetic risk for neuroticism predicts emotional health depending on childhood adversity. Psychol Med 2019; 49:260-267. [PMID: 29576022 DOI: 10.1017/s0033291718000715] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Existing evidence for gene × environment interaction (G × E) in neuroticism largely relies on candidate gene studies, although neuroticism is highly polygenic. This study aimed to investigate the long-term associations between polygenic risk scores for neuroticism (PRSN), objective childhood adversity and their interplay on emotional health aspects such as neuroticism itself, depressive symptoms, anxiety symptoms, loneliness and life satisfaction. METHODS The sample consisted of reared-apart (TRA) and reared-together (TRT) middle- and old age twins (N = 699; median age at separation = 2). PRSN were created under nine p value cut-off thresholds (pT-s) and the pT with the highest degree of neuroticism variance explained was chosen for subsequent analyses. Linear regressions were used to assess the associations between PRSN, childhood adversity (being reared apart) and emotional health. G × E was further investigated using a discordant twin design. RESULTS PRSN explained up to 1.7% (pT < 0.01) of phenotypic neuroticism in the total sample. Analyses across two separation groups revealed substantial heterogeneity in the variance explained by PRSN; 4.3% was explained in TRT, but almost no effect was observed in TRA. Similarly, PRSN explained 4% and 1.7% of the variance in depressive symptoms and loneliness, respectively, only in TRT. A significant G × E interaction was identified for depressive symptoms. CONCLUSIONS By taking advantage of a unique sample of adopted twins, we demonstrated the presence of G × E in neuroticism and emotional health using PRSN and childhood adversity. Our results may indicate that genome-wide association studies are detecting genetic main effects associated with neuroticism, but not those susceptible to early environmental influences.
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Affiliation(s)
- Kelli Lehto
- Department of Medical Epidemiology and Biostatistics,Karolinska Institutet,Nobels väg 12A,171 77,Stockholm,Sweden
| | - Ida Karlsson
- Department of Medical Epidemiology and Biostatistics,Karolinska Institutet,Nobels väg 12A,171 77,Stockholm,Sweden
| | - Cecilia Lundholm
- Department of Medical Epidemiology and Biostatistics,Karolinska Institutet,Nobels väg 12A,171 77,Stockholm,Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics,Karolinska Institutet,Nobels väg 12A,171 77,Stockholm,Sweden
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Polygenic risk for schizophrenia and associated brain structural changes: A systematic review. Compr Psychiatry 2019; 88:77-82. [PMID: 30529765 DOI: 10.1016/j.comppsych.2018.11.014] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 10/22/2018] [Accepted: 11/27/2018] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Genome wide association studies (GWAS) of schizophrenia allow the generation of Polygenic Risk Scores (PRS). PRS can be used to determine the contribution to altered brain structures in this disorder, which have been well described. However, findings from studies using PRS to predict brain structural changes in schizophrenia have been inconsistent. We therefore performed a systematic review to determine the association between schizophrenia PRS and brain structure. METHODS Following PRISMA systematic review guidelines, databases were searched for literature using key search terms. Inclusion criteria for the discovery sample required case-control schizophrenia GWAS summary statistics from European populations. The target sample was required to be of European ancestry, and have brain structure and genotype information. Quality assessment of the publications was conducted using the Mixed Methods Appraisal Tool for quantitative non-randomised studies. MAIN FINDINGS A total of seven studies were found to be eligible for review. Five studies found no significant association and two studies found a significant association of schizophrenia PRS with total brain, reduced white matter volume, and globus pallidus volume. However, the latter studies were conducted using smaller discovery (ncases = 9394 ncontrols = 12,462) and target samples compared to the studies with substantially larger discovery (ncases = 33,636 ncontrols = 43,008) and target samples where no association was observed. Taken together, the results suggest that schizophrenia PRS are not significantly associated with brain structural changes in this disorder. CONCLUSIONS The lack of significant association between schizophrenia PRS and brain structural changes may indicate that intermediate phenotypes other than brain structure should be the focus of future work. Alternatively, however, the lack of association found here may point to limitations of the current evidence-base, and so point to the need for future better powered studies.
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12
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Chalmer MA, Esserlind AL, Olesen J, Hansen TF. Polygenic risk score: use in migraine research. J Headache Pain 2018; 19:29. [PMID: 29623444 PMCID: PMC5887014 DOI: 10.1186/s10194-018-0856-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Accepted: 03/21/2018] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The latest Genome-Wide Association Study identified 38 genetic variants associated with migraine. In this type of studies the significance level is very difficult to achieve (5 × 10- 8) due to multiple testing. Thus, the identified variants only explain a small fraction of the genetic risk. It is expected that hundreds of thousands of variants also confer an increased risk but do not reach significance levels. One way to capture this information is by constructing a Polygenic Risk Score. Polygenic Risk Score has been widely used with success in genetics studies within neuropsychiatric disorders. The use of polygenic scores is highly relevant as data from a large migraine Genome-Wide Association Study are now available, which will form an excellent basis for Polygenic Risk Score in migraine studies. RESULTS Polygenic Risk Score has been used in studies of neuropsychiatric disorders to assess prediction of disease status in case-control studies, shared genetic correlation between co-morbid diseases, and shared genetic correlation between a disease and specific endophenotypes. CONCLUSION Polygenic Risk Score provides an opportunity to investigate the shared genetic risk between known and previously unestablished co-morbidities in migraine research, and may lead to better and personalized treatment of migraine if used as a clinical assistant when identifying responders to specific drugs. Polygenic Risk Score can be used to analyze the genetic relationship between different headache types and migraine endophenotypes. Finally, Polygenic Risk Score can be used to assess pharmacogenetic effects, and perhaps help to predict efficacy of the Calcitonin Gene-Related Peptide monoclonal antibodies that soon become available as migraine treatment.
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Affiliation(s)
- Mona Ameri Chalmer
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark.
| | - Ann-Louise Esserlind
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark
| | - Jes Olesen
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark
| | - Thomas Folkmann Hansen
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark
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13
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Weger M, Sandi C. High anxiety trait: A vulnerable phenotype for stress-induced depression. Neurosci Biobehav Rev 2018; 87:27-37. [DOI: 10.1016/j.neubiorev.2018.01.012] [Citation(s) in RCA: 119] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 01/14/2018] [Accepted: 01/21/2018] [Indexed: 11/25/2022]
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14
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Chen Q, Ursini G, Romer AL, Knodt AR, Mezeivtch K, Xiao E, Pergola G, Blasi G, Straub RE, Callicott JH, Berman KF, Hariri AR, Bertolino A, Mattay VS, Weinberger DR. Schizophrenia polygenic risk score predicts mnemonic hippocampal activity. Brain 2018; 141:1218-1228. [PMID: 29415119 PMCID: PMC5888989 DOI: 10.1093/brain/awy004] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2017] [Revised: 11/10/2017] [Accepted: 11/21/2017] [Indexed: 01/01/2023] Open
Abstract
The use of polygenic risk scores has become a practical translational approach to investigating the complex genetic architecture of schizophrenia, but the link between polygenic risk scores and pathophysiological components of this disorder has been the subject of limited research. We investigated in healthy volunteers whether schizophrenia polygenic risk score predicts hippocampal activity during simple memory encoding, which has been proposed as a risk-associated intermediate phenotype of schizophrenia. We analysed the relationship between polygenic risk scores and hippocampal activity in a discovery sample of 191 unrelated healthy volunteers from the USA and in two independent replication samples of 76 and 137 healthy unrelated participants from Europe and the USA, respectively. Polygenic risk scores for each individual were calculated as the sum of the imputation probability of reference alleles weighted by the natural log of odds ratio from the recent schizophrenia genome-wide association study. We examined hippocampal activity during simple memory encoding of novel visual stimuli assessed using blood oxygen level-dependent functional MRI. Polygenic risk scores were significantly associated with hippocampal activity in the discovery sample [P = 0.016, family-wise error (FWE) corrected within Anatomical Automatic Labeling (AAL) bilateral hippocampal-parahippocampal mask] and in both replication samples (P = 0.033, FWE corrected within AAL right posterior hippocampal-parahippocampal mask in Bari sample, and P = 0.002 uncorrected in the Duke Neurogenetics Study sample). The relationship between polygenic risk scores and hippocampal activity was consistently negative, i.e. lower hippocampal activity in individuals with higher polygenic risk scores, consistent with previous studies reporting decreased hippocampal-parahippocampal activity during declarative memory tasks in patients with schizophrenia and in their healthy siblings. Polygenic risk scores accounted for more than 8% of variance in hippocampal activity during memory encoding in discovery sample. We conclude that polygenic risk scores derived from the most recent schizophrenia genome-wide association study predict significant variability in hippocampal activity during memory encoding in healthy participants. Our findings validate mnemonic hippocampal activity as a genetic risk associated intermediate phenotype of schizophrenia, indicating that the aggregate neurobiological effect of schizophrenia risk alleles converges on this pattern of neural activity.awy004media15749593779001.
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Affiliation(s)
- Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, 855 North Wolfe Street, MD, USA
| | - Gianluca Ursini
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, 855 North Wolfe Street, MD, USA
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Adrienne L Romer
- Laboratory of NeuroGenetics, Department of Psychology and Neurosicence, Duke University, Durham, NC, USA
| | - Annchen R Knodt
- Laboratory of NeuroGenetics, Department of Psychology and Neurosicence, Duke University, Durham, NC, USA
| | - Karleigh Mezeivtch
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, 855 North Wolfe Street, MD, USA
| | - Ena Xiao
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, 855 North Wolfe Street, MD, USA
| | - Giulio Pergola
- Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari, Bari, Italy
| | - Giuseppe Blasi
- Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari, Bari, Italy
| | - Richard E Straub
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, 855 North Wolfe Street, MD, USA
| | - Joseph H Callicott
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Karen F Berman
- Clinical and Translational Neuroscience Branch, National Institute of Mental Health Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Ahmad R Hariri
- Laboratory of NeuroGenetics, Department of Psychology and Neurosicence, Duke University, Durham, NC, USA
| | - Alessandro Bertolino
- Group of Psychiatric Neuroscience, Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari, Bari, Italy
| | - Venkata S Mattay
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, 855 North Wolfe Street, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, 855 North Wolfe Street, MD, USA
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD USA
- Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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15
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Sanchez-Roige S, Gray JC, MacKillop JK, Chen CH, Palmer AA. The genetics of human personality. GENES, BRAIN, AND BEHAVIOR 2018; 17:e12439. [PMID: 29152902 PMCID: PMC7012279 DOI: 10.1111/gbb.12439] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Revised: 10/12/2017] [Accepted: 11/07/2017] [Indexed: 12/13/2022]
Abstract
Personality traits are the relatively enduring patterns of thoughts, feelings and behaviors that reflect the tendency to respond in certain ways under certain circumstances. Twin and family studies have showed that personality traits are moderately heritable, and can predict various lifetime outcomes, including psychopathology. The Research Domain Criteria characterizes psychiatric diseases as extremes of normal tendencies, including specific personality traits. This implies that heritable variation in personality traits, such as neuroticism, would share a common genetic basis with psychiatric diseases, such as major depressive disorder. Despite considerable efforts over the past several decades, the genetic variants that influence personality are only beginning to be identified. We review these recent and increasingly rapid developments, which focus on the assessment of personality via several commonly used personality questionnaires in healthy human subjects. Study designs covered include twin, linkage, candidate gene association studies, genome-wide association studies and polygenic analyses. Findings from genetic studies of personality have furthered our understanding about the genetic etiology of personality, which, like neuropsychiatric diseases themselves, is highly polygenic. Polygenic analyses have showed genetic correlations between personality and psychopathology, confirming that genetic studies of personality can help to elucidate the etiology of several neuropsychiatric diseases.
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Affiliation(s)
- Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
| | - Joshua C Gray
- Center for Deployment Psychology, Uniformed Services University, Bethesda, MD, 20814
| | - James K MacKillop
- Peter Boris Centre for Addictions Research, McMaster University/St. Joseph’s Healthcare Hamilton, Hamilton, ON L8N 3K7, Canada; Homewood Research Institute, Guelph, ON N1E 6K9, Canada
| | - Chi-Hua Chen
- Department of Radiology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
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Yüksel D, Dietsche B, Forstner AJ, Witt SH, Maier R, Rietschel M, Konrad C, Nöthen MM, Dannlowski U, Baune BT, Kircher T, Krug A. Polygenic risk for depression and the neural correlates of working memory in healthy subjects. Prog Neuropsychopharmacol Biol Psychiatry 2017. [PMID: 28624581 DOI: 10.1016/j.pnpbp.2017.06.010] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
INTRODUCTION Major depressive disorder (MDD) patients show impairments of cognitive functioning such as working memory (WM), and furthermore alterations during WM-fMRI tasks especially in frontal and parietal brain regions. The calculation of a polygenic risk score (PRS) can be used to describe the genetic influence on MDD, hence imaging genetic studies aspire to combine both genetics and neuroimaging data to identify the influence of genetic factors on brain functioning. We aimed to detect the effect of MDD-PRS on brain activation during a WM task measured with fMRI and expect healthy individuals with a higher PRS to be more resembling to MDD patients. METHOD In total, n=137 (80 men, 57 women, aged 34.5, SD=10.4years) healthy subjects performed a WM n-back task [0-back (baseline), 2-back and 3-back condition] in a 3T-MRI-tomograph. The sample was genotyped using the Infinium PsychArray BeadChip and a polygenic risk score was calculated for MDD using PGC MDD GWAS results. RESULTS A lower MDD risk score was associated with increased activation in the bilateral middle occipital gyri (MOG), the bilateral middle frontal gyri (MFG) and the right precentral gyrus (PCG) during the 2-back vs. baseline condition. Moreover, a lower PRS was associated with increased brain activation during the 3-back vs. baseline condition in the bilateral cerebellum, the right MFG and the left inferior parietal lobule. A higher polygenic risk score was associated with hyperactivation in brain regions comprising the right MFG and the right supplementary motor area during the 3-back vs. 2-back condition. DISCUSSION The results suggest that part of the WM-related brain activation patterns might be explained by genetic variants captured by the MDD-PRS. Furthermore we were able to detect MDD-associated activation patterns in healthy individuals depending on the MDD-PRS and the task complexity. Additional gene loci could contribute to these task-dependent brain activation patterns.
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Affiliation(s)
- Dilara Yüksel
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany.
| | - Bruno Dietsche
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Andreas J Forstner
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany; Institute of Human Genetics, University of Bonn, Bonn, Germany; Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland; Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Stephanie H Witt
- Discipline Department of Genetic Epidemiology, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Robert Maier
- Discipline Queensland Brain Institute, The University of Queensland, Australia
| | - Marcella Rietschel
- Discipline Department of Genetic Epidemiology, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Carsten Konrad
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Agaplesion Diakonieklinikum Rotenberg, Centre for Psychosocial Medicine, Elise-Averdieck-Straße 17, 27356 Rotenburg (Wümme), Germany
| | - Markus M Nöthen
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany; Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Udo Dannlowski
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Department of Psychiatry, University of Münster, Münster, Germany
| | - Bernhard T Baune
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, Australia
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
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Ohi K, Shimada T, Yasuyama T, Kimura K, Uehara T, Kawasaki Y. Spatial and temporal expression patterns of genes around nine neuroticism-associated loci. Prog Neuropsychopharmacol Biol Psychiatry 2017; 77:164-171. [PMID: 28433457 DOI: 10.1016/j.pnpbp.2017.04.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2017] [Revised: 04/14/2017] [Accepted: 04/18/2017] [Indexed: 12/20/2022]
Abstract
Neuroticism is a high-order personality trait. Individuals with higher neuroticism have increased risks of various psychiatric disorders and physical health outcomes. Neuroticism is related to physiological differences in the brain. A recent genome-wide association study identified nine distinct genomic loci that contribute to neuroticism. Brain development and function depend on the precise regulation of gene expression, which is differentially regulated across brain regions and developmental stages. Using multiple publicly available human post-mortem databases, we investigated, in brain and non-brain tissues and across several developmental life stages, the spatial and temporal expression patterns of genes arising from nine neuroticism-associated loci. Functional gene-network analysis for neuroticism-associated genes was performed. The spatial expression analysis revealed that the nearest genes (GRIK3, SRP9, KLHL2, PTPRD, ELAVL2, CRHR1 and CELF4) from index single-nucleotide polymorphisms (SNPs) at the nine loci were intensively enriched in the brain compared with their representation in non-brain tissues (p<1.56×10-3). The nearest genes associated with the glutamate receptor activity network consisted mainly of GRIK3 (FDR q=4.25×10-2). The temporal expression analysis revealed that the neuroticism-associated genes were divided into three expression patterns: KLHL2, CELF4 and CRHR1 were preferentially expressed during postnatal stages; PTPRD, ELAVL2 and MFHAS1 were expressed during prenatal stages; and the other three genes were not expressed during specific life stages. These findings suggest that the glutamate network might be a target for investigating the neurobiological mechanisms underlying susceptibilities to higher neuroticism and several psychiatric disorders and that neuroticism is mediated by genes specifically expressed in the brain during several developmental stages.
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Affiliation(s)
- Kazutaka Ohi
- Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan.
| | - Takamitsu Shimada
- Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan
| | - Toshiki Yasuyama
- Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan
| | - Kohei Kimura
- Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan
| | - Takashi Uehara
- Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan
| | - Yasuhiro Kawasaki
- Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan
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18
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Hayes JF, Osborn DPJ, Lewis G, Dalman C, Lundin A. Association of Late Adolescent Personality With Risk for Subsequent Serious Mental Illness Among Men in a Swedish Nationwide Cohort Study. JAMA Psychiatry 2017; 74:703-711. [PMID: 28538982 PMCID: PMC5710245 DOI: 10.1001/jamapsychiatry.2017.0583] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
IMPORTANCE Understanding of personality as an independent risk factor for serious mental illness (SMI) remains limited. Recently, overlap between the polygenic basis for specific personality traits and specific SMIs has been identified. OBJECTIVE To determine the association of the adolescent personality domains of social maturity, mental energy, and emotional stability with later diagnosis of SMI. DESIGN, SETTING, AND PARTICIPANTS This longitudinal cohort study enrolled Swedish male military conscripts aged 18 or 19 years from January 1, 1974, through December 31, 1997. The diagnosis of an SMI was extracted from the National Patient Register for all inpatient treatment episodes in Sweden from January 1, 1974, through December 31, 2011. Data were analyzed from May 3 to September 16, 2016. EXPOSURES Social maturity, mental energy, and emotional stability assessed at conscription interview. MAIN OUTCOMES AND MEASURES Inpatient diagnoses of bipolar disorder, schizoaffective disorder, schizophrenia, and other nonaffective psychoses occurring until December 31, 2011. RESULTS Of the 1 017 691 men included in the cohort, 4310 developed bipolar disorder; 784, schizoaffective disorder; 4823, schizophrenia; and 5013, other nonaffective psychoses. After adjustment, with use of mean scores as a reference, low social maturity (hazard ratio [HR], 1.61; 95% CI, 1.48-1.74), low mental energy (HR, 1.34; 95% CI, 1.24-1.44), and low emotional stability (HR, 1.51; 95% CI, 1.40-1.63) were inversely associated with schizophrenia in a dose-dependent fashion. Other nonaffective psychoses displayed a similar pattern. Bipolar disorder was associated with high (HR, 1.21; 95% CI, 1.09-1.35) and low (HR, 1.12; 95% CI, 1.01-1.25) social maturity and low emotional stability (HR, 1.62; 95% CI, 1.46-1.78). Schizoaffective disorder was associated with low emotional stability (HR, 1.53; 95% CI, 1.26-1.85). CONCLUSIONS AND RELEVANCE Emotional stability is inversely associated with all SMI. Bipolar disorder has a unique U-shaped association with social maturity. Premorbid personality may reflect subtle changes in cerebral function, may combine with symptoms and other neurocognitive deficits to influence illness presentation, and/or may be owing to shared genetic architecture.
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Affiliation(s)
- Joseph F. Hayes
- Division of Psychiatry, University College London, London, England
| | | | - Glyn Lewis
- Division of Psychiatry, University College London, London, England
| | - Christina Dalman
- Department of Public Health Sciences, Unit of Public Health Epidemiology, Karolinska Institute, Stockholm, Sweden
| | - Andreas Lundin
- Department of Public Health Sciences, Unit of Public Health Epidemiology, Karolinska Institute, Stockholm, Sweden
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19
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Bey K, Lennertz L, Riesel A, Klawohn J, Kaufmann C, Heinzel S, Grützmann R, Kathmann N, Wagner M. Harm avoidance and childhood adversities in patients with obsessive-compulsive disorder and their unaffected first-degree relatives. Acta Psychiatr Scand 2017; 135:328-338. [PMID: 28160276 DOI: 10.1111/acps.12707] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/16/2017] [Indexed: 01/05/2023]
Abstract
OBJECTIVE The etiology of obsessive-compulsive disorder (OCD) is assumed to involve interactions between genetically determined vulnerability factors and significant environmental features. Here, we aim to investigate how the personality trait harm avoidance and the experience of childhood adversities contribute to OCD. METHOD A total of 169 patients with OCD, 157 healthy comparison subjects, and 57 unaffected first-degree relatives of patients with OCD participated in the study. Harm avoidance was assessed using the Temperament and Character Inventory, and the severity of childhood adversities was measured with the Childhood Trauma Questionnaire. RESULTS Both patients with OCD and relatives showed elevated levels of harm avoidance compared to controls. Furthermore, patients exhibited significantly higher scores than relatives. This linear pattern was observed throughout all subscales of harm avoidance, and remained stable after controlling for the severity of depressive and obsessive-compulsive symptoms. With regard to childhood adversities, patients with OCD reported higher levels than relatives and controls. CONCLUSION Our results provide further evidence for a diathesis-stress model of OCD. While patients and unaffected relatives share elevated levels of harm avoidance, supporting the role of harm avoidance as an endophenotype of OCD, a heightened severity of childhood adversity was only observed in patients. The assumed biological underpinnings of these findings are discussed.
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Affiliation(s)
- K Bey
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - L Lennertz
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - A Riesel
- Department of Psychology, Humboldt University of Berlin, Berlin, Germany
| | - J Klawohn
- Department of Psychology, Humboldt University of Berlin, Berlin, Germany
| | - C Kaufmann
- Department of Psychology, Humboldt University of Berlin, Berlin, Germany
| | - S Heinzel
- Department of Psychology, Humboldt University of Berlin, Berlin, Germany.,Clinical Psychology and Psychotherapy, Freie Universität Berlin, Berlin, Germany
| | - R Grützmann
- Department of Psychology, Humboldt University of Berlin, Berlin, Germany
| | - N Kathmann
- Department of Psychology, Humboldt University of Berlin, Berlin, Germany
| | - M Wagner
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
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20
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Whalley HC, Adams MJ, Hall LS, Clarke TK, Fernandez-Pujals AM, Gibson J, Wigmore E, Hafferty J, Hagenaars SP, Davies G, Campbell A, Hayward C, Lawrie SM, Porteous DJ, Deary IJ, McIntosh AM. Dissection of major depressive disorder using polygenic risk scores for schizophrenia in two independent cohorts. Transl Psychiatry 2016; 6:e938. [PMID: 27801894 PMCID: PMC5314119 DOI: 10.1038/tp.2016.207] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Accepted: 08/30/2016] [Indexed: 12/20/2022] Open
Abstract
Major depressive disorder (MDD) is known for its substantial clinical and suspected causal heterogeneity. It is characterized by low mood, psychomotor slowing and increased levels of the personality trait neuroticism; factors also associated with schizophrenia (SCZ). It is possible that some cases of MDD may have a substantial genetic loading for SCZ. The presence of SCZ-like MDD subgroups would be indicated by an interaction between MDD status and polygenic risk of SCZ on cognitive, personality and mood measures. Here, we hypothesized that higher SCZ polygenic risk would define larger MDD case-control differences in cognitive ability, and smaller differences in distress and neuroticism. Polygenic risk scores (PRSs) for SCZ and their association with cognitive variables, neuroticism, mood and psychological distress were estimated in a large population-based cohort (Generation Scotland: Scottish Family Health Study, GS:SFHS). The individuals were divided into those with, and without, depression (n=2587 and n=16 764, respectively) to test for the interactions between MDD status and schizophrenia risk. Replication was sought in UK Biobank (UKB; n=6049 and n=27 476 cases and controls, respectively). In both the cohorts, we found significant interactions between SCZ-PRS and MDD status for measures of psychological distress (βGS=-0.04, PGS=0.014 and βUKB=-0.09, PUKB⩽0.001 for GS:SFHS and UKB, respectively) and neuroticism (βGS=-0.04, PGS=0.002 and βUKB=-0.06, PUKB=0.023). In both the cohorts, there was a reduction of case-control differences on a background of higher genetic risk of SCZ. These findings suggest that depression on a background of high genetic risk for SCZ may show attenuated associations with distress and neuroticism. This may represent a causally distinct form of MDD more closely related to SCZ.
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Affiliation(s)
- H C Whalley
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - M J Adams
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - L S Hall
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - T-K Clarke
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - A M Fernandez-Pujals
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - J Gibson
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - E Wigmore
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - J Hafferty
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - S P Hagenaars
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - A Campbell
- Centre for Genetics and Molecular Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - C Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - S M Lawrie
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - D J Porteous
- Centre for Genetics and Molecular Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - A M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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Abstract
Approximately half of the variation in wellbeing measures overlaps with variation in personality traits. Studies of non-human primate pedigrees and human twins suggest that this is due to common genetic influences. We tested whether personality polygenic scores for the NEO Five-Factor Inventory (NEO-FFI) domains and for item response theory (IRT) derived extraversion and neuroticism scores predict variance in wellbeing measures. Polygenic scores were based on published genome-wide association (GWA) results in over 17,000 individuals for the NEO-FFI and in over 63,000 for the IRT extraversion and neuroticism traits. The NEO-FFI polygenic scores were used to predict life satisfaction in 7 cohorts, positive affect in 12 cohorts, and general wellbeing in 1 cohort (maximal N = 46,508). Meta-analysis of these results showed no significant association between NEO-FFI personality polygenic scores and the wellbeing measures. IRT extraversion and neuroticism polygenic scores were used to predict life satisfaction and positive affect in almost 37,000 individuals from UK Biobank. Significant positive associations (effect sizes <0.05%) were observed between the extraversion polygenic score and wellbeing measures, and a negative association was observed between the polygenic neuroticism score and life satisfaction. Furthermore, using GWA data, genetic correlations of −0.49 and −0.55 were estimated between neuroticism with life satisfaction and positive affect, respectively. The moderate genetic correlation between neuroticism and wellbeing is in line with twin research showing that genetic influences on wellbeing are also shared with other independent personality domains.
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22
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Kao CF, Chen HW, Chen HC, Yang JH, Huang MC, Chiu YH, Lin SK, Lee YC, Liu CM, Chuang LC, Chen CH, Wu JY, Lu RB, Kuo PH. Identification of Susceptible Loci and Enriched Pathways for Bipolar II Disorder Using Genome-Wide Association Studies. Int J Neuropsychopharmacol 2016; 19:pyw064. [PMID: 27450446 PMCID: PMC5203756 DOI: 10.1093/ijnp/pyw064] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Accepted: 07/11/2016] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND This study aimed to identify susceptible loci and enriched pathways for bipolar disorder subtype II. METHODS We conducted a genome-wide association scan in discovery samples with 189 bipolar disorder subtype II patients and 1773 controls, and replication samples with 283 bipolar disorder subtype II patients and 500 controls in a Taiwanese Han population using Affymetrix Axiom Genome-Wide CHB1 Array. We performed single-marker and gene-based association analyses, as well as calculated polygeneic risk scores for bipolar disorder subtype II. Pathway enrichment analyses were employed to reveal significant biological pathways. RESULTS Seven markers were found to be associated with bipolar disorder subtype II in meta-analysis combining both discovery and replication samples (P<5.0×10-6), including markers in or close to MYO16, HSP90AB3P, noncoding gene LOC100507632, and markers in chromosomes 4 and 10. A novel locus, ETF1, was associated with bipolar disorder subtype II (P<6.0×10-3) in gene-based association tests. Results of risk evaluation demonstrated that higher genetic risk scores were able to distinguish bipolar disorder subtype II patients from healthy controls in both discovery (P=3.9×10-4~1.0×10-3) and replication samples (2.8×10-4~1.7×10-3). Genetic variance explained by chip markers for bipolar disorder subtype II was substantial in the discovery (55.1%) and replication (60.5%) samples. Moreover, pathways related to neurodevelopmental function, signal transduction, neuronal system, and cell adhesion molecules were significantly associated with bipolar disorder subtype II. CONCLUSION We reported novel susceptible loci for pure bipolar subtype II disorder that is less addressed in the literature. Future studies are needed to confirm the roles of these loci for bipolar disorder subtype II.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | - Ru-Band Lu
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan (Dr Kao, Mr Lee, and Dr Kuo); Department of Agronomy, College of Agriculture & Natural Resources, National Chung Hsing University, Taichung, Taiwan (Dr Kao); National Center for Genome Medicine, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan (Mrs Chen, Dr Yang, Dr Chen, and Dr Wu); Department of Psychiatry & Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwan (Dr Chen); Department of Nursing, Cardinal Tien Junior College of Healthcare & Management, Yilan, Taiwan (Dr Chuang); Department of Psychiatry, School of Medicine, Taipei Medical University, Taipei, Taiwan (Drs Huang, Chiu, and Lin); Department of Psychiatry, Taipei City Psychiatric Center, Taipei, Taiwan (Dr Huang); Department of Psychiatry, Wan Fang Medical Center, Taipei, Taiwan (Dr Chiu); Department of Psychiatry, Taipei City Hospital and Psychiatric Center, Taipei, Taiwan (Dr Lin); Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan (Dr Liu); Department of Psychiatry, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan (Dr Liu); Department of Psychiatry, National Cheng Kung University and Hospital, Tainan, Taiwan (Dr Lu); Research Center for Genes, Environment and Human Health, National Taiwan University, Taipei, Taiwan (Dr Kuo).
| | - Po-Hsiu Kuo
- Department of Public Health & Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan (Dr Kao, Mr Lee, and Dr Kuo); Department of Agronomy, College of Agriculture & Natural Resources, National Chung Hsing University, Taichung, Taiwan (Dr Kao); National Center for Genome Medicine, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan (Mrs Chen, Dr Yang, Dr Chen, and Dr Wu); Department of Psychiatry & Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwan (Dr Chen); Department of Nursing, Cardinal Tien Junior College of Healthcare & Management, Yilan, Taiwan (Dr Chuang); Department of Psychiatry, School of Medicine, Taipei Medical University, Taipei, Taiwan (Drs Huang, Chiu, and Lin); Department of Psychiatry, Taipei City Psychiatric Center, Taipei, Taiwan (Dr Huang); Department of Psychiatry, Wan Fang Medical Center, Taipei, Taiwan (Dr Chiu); Department of Psychiatry, Taipei City Hospital and Psychiatric Center, Taipei, Taiwan (Dr Lin); Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan (Dr Liu); Department of Psychiatry, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan (Dr Liu); Department of Psychiatry, National Cheng Kung University and Hospital, Tainan, Taiwan (Dr Lu); Research Center for Genes, Environment and Human Health, National Taiwan University, Taipei, Taiwan (Dr Kuo).
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23
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Gale CR, Hagenaars SP, Davies G, Hill WD, Liewald DCM, Cullen B, Penninx BW, Boomsma DI, Pell J, McIntosh AM, Smith DJ, Deary IJ, Harris SE. Pleiotropy between neuroticism and physical and mental health: findings from 108 038 men and women in UK Biobank. Transl Psychiatry 2016; 6:e791. [PMID: 27115122 PMCID: PMC4872414 DOI: 10.1038/tp.2016.56] [Citation(s) in RCA: 73] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2015] [Revised: 01/15/2016] [Accepted: 03/05/2016] [Indexed: 12/14/2022] Open
Abstract
People with higher levels of neuroticism have an increased risk of several types of mental disorder. Higher neuroticism has also been associated, less consistently, with increased risk of various physical health outcomes. We hypothesised that these associations may, in part, be due to shared genetic influences. We tested for pleiotropy between neuroticism and 17 mental and physical diseases or health traits using linkage disequilibrium regression and polygenic profile scoring. Genetic correlations were derived between neuroticism scores in 108 038 people in the UK Biobank and health-related measures from 14 large genome-wide association studies (GWASs). Summary information for the 17 GWASs was used to create polygenic risk scores for the health-related measures in the UK Biobank participants. Associations between the health-related polygenic scores and neuroticism were examined using regression, adjusting for age, sex, genotyping batch, genotyping array, assessment centre and population stratification. Genetic correlations were identified between neuroticism and anorexia nervosa (rg=0.17), major depressive disorder (rg=0.66) and schizophrenia (rg=0.21). Polygenic risk for several health-related measures were associated with neuroticism, in a positive direction in the case of bipolar disorder, borderline personality, major depressive disorder, negative affect, neuroticism (Genetics of Personality Consortium), schizophrenia, coronary artery disease, and smoking (β between 0.009-0.043), and in a negative direction in the case of body mass index (β=-0.0095). A high level of pleiotropy exists between neuroticism and some measures of mental and physical health, particularly major depressive disorder and schizophrenia.
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Affiliation(s)
- C R Gale
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
| | - S P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - W D Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - D C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - B Cullen
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - B W Penninx
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ inGeest, Amsterdam, The Netherlands
| | - International Consortium for Blood Pressure GWAS, CHARGE Consortium Aging and Longevity Group
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
- Department of Psychiatry, EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ inGeest, Amsterdam, The Netherlands
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
- Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - D I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - J Pell
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - D J Smith
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
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24
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van den Berg SM, de Moor MHM, Verweij KJH, Krueger RF, Luciano M, Arias Vasquez A, Matteson LK, Derringer J, Esko T, Amin N, Gordon SD, Hansell NK, Hart AB, Seppälä I, Huffman JE, Konte B, Lahti J, Lee M, Miller M, Nutile T, Tanaka T, Teumer A, Viktorin A, Wedenoja J, Abdellaoui A, Abecasis GR, Adkins DE, Agrawal A, Allik J, Appel K, Bigdeli TB, Busonero F, Campbell H, Costa PT, Smith GD, Davies G, de Wit H, Ding J, Engelhardt BE, Eriksson JG, Fedko IO, Ferrucci L, Franke B, Giegling I, Grucza R, Hartmann AM, Heath AC, Heinonen K, Henders AK, Homuth G, Hottenga JJ, Iacono WG, Janzing J, Jokela M, Karlsson R, Kemp JP, Kirkpatrick MG, Latvala A, Lehtimäki T, Liewald DC, Madden PAF, Magri C, Magnusson PKE, Marten J, Maschio A, Mbarek H, Medland SE, Mihailov E, Milaneschi Y, Montgomery GW, Nauck M, Nivard MG, Ouwens KG, Palotie A, Pettersson E, Polasek O, Qian Y, Pulkki-Råback L, Raitakari OT, Realo A, Rose RJ, Ruggiero D, Schmidt CO, Slutske WS, Sorice R, Starr JM, St Pourcain B, Sutin AR, Timpson NJ, Trochet H, Vermeulen S, Vuoksimaa E, Widen E, Wouda J, Wright MJ, Zgaga L, Porteous D, Minelli A, Palmer AA, Rujescu D, et alvan den Berg SM, de Moor MHM, Verweij KJH, Krueger RF, Luciano M, Arias Vasquez A, Matteson LK, Derringer J, Esko T, Amin N, Gordon SD, Hansell NK, Hart AB, Seppälä I, Huffman JE, Konte B, Lahti J, Lee M, Miller M, Nutile T, Tanaka T, Teumer A, Viktorin A, Wedenoja J, Abdellaoui A, Abecasis GR, Adkins DE, Agrawal A, Allik J, Appel K, Bigdeli TB, Busonero F, Campbell H, Costa PT, Smith GD, Davies G, de Wit H, Ding J, Engelhardt BE, Eriksson JG, Fedko IO, Ferrucci L, Franke B, Giegling I, Grucza R, Hartmann AM, Heath AC, Heinonen K, Henders AK, Homuth G, Hottenga JJ, Iacono WG, Janzing J, Jokela M, Karlsson R, Kemp JP, Kirkpatrick MG, Latvala A, Lehtimäki T, Liewald DC, Madden PAF, Magri C, Magnusson PKE, Marten J, Maschio A, Mbarek H, Medland SE, Mihailov E, Milaneschi Y, Montgomery GW, Nauck M, Nivard MG, Ouwens KG, Palotie A, Pettersson E, Polasek O, Qian Y, Pulkki-Råback L, Raitakari OT, Realo A, Rose RJ, Ruggiero D, Schmidt CO, Slutske WS, Sorice R, Starr JM, St Pourcain B, Sutin AR, Timpson NJ, Trochet H, Vermeulen S, Vuoksimaa E, Widen E, Wouda J, Wright MJ, Zgaga L, Porteous D, Minelli A, Palmer AA, Rujescu D, Ciullo M, Hayward C, Rudan I, Metspalu A, Kaprio J, Deary IJ, Räikkönen K, Wilson JF, Keltikangas-Järvinen L, Bierut LJ, Hettema JM, Grabe HJ, Penninx BWJH, van Duijn CM, Evans DM, Schlessinger D, Pedersen NL, Terracciano A, McGue M, Martin NG, Boomsma DI. Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium. Behav Genet 2016; 46:170-82. [PMID: 26362575 PMCID: PMC4751159 DOI: 10.1007/s10519-015-9735-5] [Show More Authors] [Citation(s) in RCA: 103] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2014] [Accepted: 08/10/2015] [Indexed: 11/26/2022]
Abstract
Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion.
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Affiliation(s)
- Stéphanie M van den Berg
- Department of Research Methodology, Measurement and Data-Analysis (OMD), Faculty of Behavioural, Management, and Social Sciences, University of Twente, PO Box 217, 7500 AE, Enschede, The Netherlands.
| | - Marleen H M de Moor
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
- Department of Clinical Child and Family Studies, VU University Amsterdam, Amsterdam, The Netherlands
- Department of Methods, VU University Amsterdam, Amsterdam, The Netherlands
| | - Karin J H Verweij
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Department of Developmental Psychology and EMGO Institute for Health and Care Research, VU University Amsterdam, Amsterdam, The Netherlands
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, USA
| | - Michelle Luciano
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Alejandro Arias Vasquez
- Donders Institute for Cognitive Neuroscience, Radboud University Nijmegen, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
- Department of Human Genetics, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | | | - Jaime Derringer
- Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | - Amy B Hart
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Tampere, Finland
| | - Jennifer E Huffman
- MRC Human Genetics Unit, MRC IGMM, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Bettina Konte
- Department of Psychiatry, University of Halle, Halle, Germany
| | - Jari Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Minyoung Lee
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Mike Miller
- Department of Psychology, University of Minnesota, Minneapolis, USA
| | - Teresa Nutile
- Institute of Genetics and Biophysics "A. Buzzati-Traverso" - CNR, Naples, Italy
| | | | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Alexander Viktorin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juho Wedenoja
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Abdel Abdellaoui
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Goncalo R Abecasis
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Daniel E Adkins
- Pharmacotherapy & Outcomes Science, Virginia Commonwealth University, Richmond, VA, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Jüri Allik
- Department of Psychology, University of Tartu, Tartu, Estonia
- Estonian Academy of Sciences, Tallinn, Estonia
| | - Katja Appel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Timothy B Bigdeli
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Fabio Busonero
- Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, Italy
| | - Harry Campbell
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Paul T Costa
- Behavioral Medicine Research Center, Duke University School of Medicine, Durham, NC, USA
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Gail Davies
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Harriet de Wit
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, USA
| | - Jun Ding
- Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Barbara E Engelhardt
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Johan G Eriksson
- Folkhälsan Research Center, Helsinki, Finland
- National Institute for Health and Welfare (THL), Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Unit of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Vasa Central Hospital, Vaasa, Finland
| | - Iryna O Fedko
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | | | - Barbara Franke
- Donders Institute for Cognitive Neuroscience, Radboud University Nijmegen, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
- Department of Human Genetics, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Ina Giegling
- Department of Psychiatry, University of Halle, Halle, Germany
| | - Richard Grucza
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Andrew C Heath
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Kati Heinonen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | | | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, USA
| | - Joost Janzing
- Department of Psychiatry, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Markus Jokela
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - John P Kemp
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
- Translational Research Institute, University of Queensland Diamantina Institute, Brisbane, Australia
| | - Matthew G Kirkpatrick
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, USA
| | - Antti Latvala
- Department of Public Health, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Tampere, Finland
| | - David C Liewald
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Pamela A F Madden
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Chiara Magri
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jonathan Marten
- MRC Human Genetics Unit, MRC IGMM, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Andrea Maschio
- Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, Italy
| | - Hamdi Mbarek
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Department of Biotechnology, University of Tartu, Tartu, Estonia
| | - Yuri Milaneschi
- Department of Psychiatry, EMGO+ Institute, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | | | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Michel G Nivard
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Klaasjan G Ouwens
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Aarno Palotie
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Erik Pettersson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ozren Polasek
- Department of Public Health, Faculty of Medicine, University of Split, Split, Croatia
| | - Yong Qian
- Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Laura Pulkki-Råback
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Anu Realo
- Department of Psychology, University of Tartu, Tartu, Estonia
| | - Richard J Rose
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics "A. Buzzati-Traverso" - CNR, Naples, Italy
| | - Carsten O Schmidt
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Wendy S Slutske
- Department of Psychological Sciences and Missouri Alcoholism Research Center, University of Missouri, Columbia, MO, USA
| | - Rossella Sorice
- Institute of Genetics and Biophysics "A. Buzzati-Traverso" - CNR, Naples, Italy
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Beate St Pourcain
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
- School of Oral and Dental Sciences, University of Bristol, Bristol, UK
- School of Experimental Psychology, University of Bristol, Bristol, UK
| | - Angelina R Sutin
- National Institute on Aging, NIH, Baltimore, MD, USA
- College of Medicine, Florida State University, Tallahassee, FL, USA
| | - Nicholas J Timpson
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Holly Trochet
- MRC Human Genetics Unit, MRC IGMM, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Sita Vermeulen
- Department of Human Genetics, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Eero Vuoksimaa
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Jasper Wouda
- Department of Research Methodology, Measurement and Data-Analysis (OMD), Faculty of Behavioural, Management, and Social Sciences, University of Twente, PO Box 217, 7500 AE, Enschede, The Netherlands
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | | | - Lina Zgaga
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Department of Public Health and Primary Care, Trinity College Dublin, Dublin, Ireland
| | - David Porteous
- Medical Genetics Section, Centre for Genomics and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, The University of Edinburgh, Edinburgh, UK
| | - Alessandra Minelli
- Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Abraham A Palmer
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, USA
| | - Dan Rujescu
- Department of Psychiatry, University of Halle, Halle, Germany
| | - Marina Ciullo
- Institute of Genetics and Biophysics "A. Buzzati-Traverso" - CNR, Naples, Italy
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC IGMM, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Igor Rudan
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Estonian Academy of Sciences, Tallinn, Estonia
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare (THL), Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Katri Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - James F Wilson
- MRC Human Genetics Unit, MRC IGMM, Western General Hospital, University of Edinburgh, Edinburgh, UK
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | | | - Laura J Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - John M Hettema
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, HELIOS Hospital Stralsund, Stralsund, Germany
| | - Brenda W J H Penninx
- Department of Psychiatry, EMGO+ Institute, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - David M Evans
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - David Schlessinger
- Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Antonio Terracciano
- Folkhälsan Research Center, Helsinki, Finland
- National Institute on Aging, NIH, Baltimore, MD, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, USA
- Institute of Public Health, University of Southern Denmark, Odense, Denmark
| | | | - Dorret I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
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25
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Wang Y, Sun N, Liu Z, Li X, Yang C, Zhang K. Psychosocial mechanisms of serotonin transporter's genetic polymorphism in susceptibility to major depressive disorder: mediated by trait coping styles and interacted with life events. Am J Transl Res 2016; 8:1281-1292. [PMID: 27158415 PMCID: PMC4846972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2015] [Accepted: 01/29/2016] [Indexed: 06/05/2023]
Abstract
The mechanism of 5-HTT genetic polymorphisms related susceptibility of major depressive disorder (MDD) has not been fully understood. Two hundred MDD patients and 199 control subjects were included. A model of two binary logistical regressions with and without controlling for different psychosocial variables, was applied to investigate the possible mediation effects of psychosocial factors in contribution of 5-HTT polymorphisms in MDD development. These psychosocial variables included personality, trait coping style, life events and social support. Then, contribution of interactions between 5-HTT polymorphisms and psychosocial factors in MDD was investigated by a stepwise logistical approach. The results indicated a significant association of 5-HTT LPR with the MDD indicence, but not of VNTR genotype variances with the MDD incidence without counting effects of psychosocial factors. The ss genotype of LPR demonstrated 2.50 (95% CI: 1.11-5.62) times higher odds to develop MDD than ll genotype (p=0.026). After including psychosocial variables, the odds ratio of 5-HTT LPR ss to ll genotype dropped to 1.30 times (95% CI: 0.41-4.10) and became non-significant (p=0.658). While psychosocial variables all showed significant contributions to MDD susceptibility. Our data suggested an intermediator role of this psychosocial variable in LPR genetic pathogenesis of MDD. Whereas, 5-HTT VNTR could significantly affect MDD outcome by interacting with life events (p=0.043). In conclusion, 5-HTT LPR and VNTR polymorphisms could affect MDD susceptibility through mediation by trait coping styles and interaction with severe life events, respectively. The genetic information of 5-HTT can be potentially helpful for diagnosis and further therapy.
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Affiliation(s)
- Yanfang Wang
- Department of Psychiatry, First Hospital of Shanxi Medical University Taiyuan 030001, Shanxi Province, China
| | - Ning Sun
- Department of Psychiatry, First Hospital of Shanxi Medical University Taiyuan 030001, Shanxi Province, China
| | - Zhifen Liu
- Department of Psychiatry, First Hospital of Shanxi Medical University Taiyuan 030001, Shanxi Province, China
| | - Xinrong Li
- Department of Psychiatry, First Hospital of Shanxi Medical University Taiyuan 030001, Shanxi Province, China
| | - Chunxia Yang
- Department of Psychiatry, First Hospital of Shanxi Medical University Taiyuan 030001, Shanxi Province, China
| | - Kerang Zhang
- Department of Psychiatry, First Hospital of Shanxi Medical University Taiyuan 030001, Shanxi Province, China
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Smoller JW. The Genetics of Stress-Related Disorders: PTSD, Depression, and Anxiety Disorders. Neuropsychopharmacology 2016; 41:297-319. [PMID: 26321314 PMCID: PMC4677147 DOI: 10.1038/npp.2015.266] [Citation(s) in RCA: 281] [Impact Index Per Article: 31.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Revised: 08/05/2015] [Accepted: 08/26/2015] [Indexed: 02/06/2023]
Abstract
Research into the causes of psychopathology has largely focused on two broad etiologic factors: genetic vulnerability and environmental stressors. An important role for familial/heritable factors in the etiology of a broad range of psychiatric disorders was established well before the modern era of genomic research. This review focuses on the genetic basis of three disorder categories-posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and the anxiety disorders-for which environmental stressors and stress responses are understood to be central to pathogenesis. Each of these disorders aggregates in families and is moderately heritable. More recently, molecular genetic approaches, including genome-wide studies of genetic variation, have been applied to identify specific risk variants. In this review, I summarize evidence for genetic contributions to PTSD, MDD, and the anxiety disorders including genetic epidemiology, the role of common genetic variation, the role of rare and structural variation, and the role of gene-environment interaction. Available data suggest that stress-related disorders are highly complex and polygenic and, despite substantial progress in other areas of psychiatric genetics, few risk loci have been identified for these disorders. Progress in this area will likely require analysis of much larger sample sizes than have been reported to date. The phenotypic complexity and genetic overlap among these disorders present further challenges. The review concludes with a discussion of prospects for clinical translation of genetic findings and future directions for research.
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Affiliation(s)
- Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Genetic and Environmental Stability of Neuroticism From Adolescence to Adulthood. Twin Res Hum Genet 2015; 18:746-54. [DOI: 10.1017/thg.2015.80] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Longitudinal studies of neuroticism have shown that, on average, neuroticism scores decrease from adolescence to adulthood. The heritability of neuroticism is estimated between 0.30 and 0.60 and does not seem to vary greatly as a function of age. Shared environmental effects are rarely reported. Less is known about the role of genetic and environmental influences on the rank order stability of neuroticism in the period from adolescence to adulthood. We studied the stability of neuroticism in a cohort sequential (classical) twin design, from adolescence (age 14 years) to young adulthood (age 32 years). A genetic simplex model that was fitted to the longitudinal neuroticism data showed that the genetic stability of neuroticism was relatively high (genetic correlations between adjacent age bins >0.9), and increased from adolescence to adulthood. Environmental stability was appreciably lower (environmental correlations between adjacent age bins were between 0.3 and 0.6). This low stability was largely due to age-specific environmental variance, which was dominated by measurement error. This attenuated the age-to-age environmental correlations. We constructed an environmental covariance matrix corrected for this error, under the strong assumption that all age-specific environmental variance is error variance. The environmental (co)variance matrix corrected for attenuation revealed highly stable environmental influences on neuroticism (correlations between adjacent age bins were between 0.7 and 0.9). Our results indicate that both genetic and environmental influences have enduring effects on individual differences in neuroticism.
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Abstract
Genetic factors account for up to 80% of the liability for schizophrenia and bipolar disorder. Genome-wide association studies (GWAS) have successfully identified several single nucleotide polymorphisms (SNPs) and genes associated with increased risk for both disorders. Single SNP analyses alone do not address the overall genomic or polygenic architecture of psychiatric disorders as the amount of phenotypic variation explained by each GWAS-supported SNP is small whereas the number of SNPs/regions underlying risk for illness is thought to be very large. The polygenic risk score models the aggregate effect of alleles associated with disease status present in each individual and allows us to utilise the power of large GWAS to be applied robustly in small samples. Here we make the case that risk prediction, intervention and personalised medicine can only benefit with the inclusion of polygenic risk scores in imaging genetics research.
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Affiliation(s)
- Danai Dima
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gerome Breen
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK National Institute of Health Research (NIHR) Biomedical Research Centre for Mental Health, South London and Maudsley National Health Service (NHS) Trust, London, UK
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29
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de Moor MH, van den Berg SM, Verweij KJ, Krueger RF, Luciano M, Vasquez AA, Matteson LK, Derringer J, Esko T, Amin N, Gordon SD, Hansell NK, Hart AB, Seppälä I, Huffman JE, Konte B, Lahti J, Lee M, Miller M, Nutile T, Tanaka T, Teumer A, Viktorin A, Wedenoja J, Abecasis GR, Adkins DE, Agrawal A, Allik J, Appel K, Bigdeli TB, Busonero F, Campbell H, Costa PT, Smith GD, Davies G, de Wit H, Ding J, Engelhardt BE, Eriksson JG, Fedko IO, Ferrucci L, Franke B, Giegling I, Grucza R, Hartmann AM, Heath AC, Heinonen K, Henders AK, Homuth G, Hottenga JJ, Janzing J, Jokela M, Karlsson R, Kemp JP, Kirkpatrick MG, Latvala A, Lehtimäki T, Liewald DC, Madden PA, Magri C, Magnusson PK, Marten J, Maschio A, Medland SE, Mihailov E, Milaneschi Y, Montgomery GW, Nauck M, Ouwens KG, Palotie A, Pettersson E, Polasek O, Qian Y, Pulkki-Råback L, Raitakari OT, Realo A, Rose RJ, Ruggiero D, Schmidt CO, Slutske WS, Sorice R, Starr JM, Pourcain BS, Sutin AR, Timpson NJ, Trochet H, Vermeulen S, Vuoksimaa E, Widen E, Wouda J, Wright MJ, Zgaga L, Scotland G, Porteous D, Minelli A, Palmer AA, Rujescu D, Ciullo M, Hayward C, Rudan I, et alde Moor MH, van den Berg SM, Verweij KJ, Krueger RF, Luciano M, Vasquez AA, Matteson LK, Derringer J, Esko T, Amin N, Gordon SD, Hansell NK, Hart AB, Seppälä I, Huffman JE, Konte B, Lahti J, Lee M, Miller M, Nutile T, Tanaka T, Teumer A, Viktorin A, Wedenoja J, Abecasis GR, Adkins DE, Agrawal A, Allik J, Appel K, Bigdeli TB, Busonero F, Campbell H, Costa PT, Smith GD, Davies G, de Wit H, Ding J, Engelhardt BE, Eriksson JG, Fedko IO, Ferrucci L, Franke B, Giegling I, Grucza R, Hartmann AM, Heath AC, Heinonen K, Henders AK, Homuth G, Hottenga JJ, Janzing J, Jokela M, Karlsson R, Kemp JP, Kirkpatrick MG, Latvala A, Lehtimäki T, Liewald DC, Madden PA, Magri C, Magnusson PK, Marten J, Maschio A, Medland SE, Mihailov E, Milaneschi Y, Montgomery GW, Nauck M, Ouwens KG, Palotie A, Pettersson E, Polasek O, Qian Y, Pulkki-Råback L, Raitakari OT, Realo A, Rose RJ, Ruggiero D, Schmidt CO, Slutske WS, Sorice R, Starr JM, Pourcain BS, Sutin AR, Timpson NJ, Trochet H, Vermeulen S, Vuoksimaa E, Widen E, Wouda J, Wright MJ, Zgaga L, Scotland G, Porteous D, Minelli A, Palmer AA, Rujescu D, Ciullo M, Hayward C, Rudan I, Metspalu A, Kaprio J, Deary IJ, Räikkönen K, Wilson JF, Keltikangas-Järvinen L, Bierut LJ, Hettema JM, Grabe HJ, van Duijn CM, Evans DM, Schlessinger D, Pedersen NL, Terracciano A, McGue M, Penninx BW, Martin NG, Boomsma DI. Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder. JAMA Psychiatry 2015; 72:642-50. [PMID: 25993607 PMCID: PMC4667957 DOI: 10.1001/jamapsychiatry.2015.0554] [Show More Authors] [Citation(s) in RCA: 191] [Impact Index Per Article: 19.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63,000 participants (including MDD cases). OBJECTIVES To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD. DESIGN, SETTING, AND PARTICIPANTS Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63,661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014. MAIN OUTCOMES AND MEASURES Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts. RESULTS A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P = 9.26 × 10-9 in the discovery meta-analysis). This association was not replicated (P = .32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P = 2.38 × 10-8). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09 × 10-12 < P < .05) and MDD (4.02 × 10-9 < P < .05) in the 2 other cohorts. CONCLUSIONS AND RELEVANCE This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism.
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Affiliation(s)
- Marleen H.M. de Moor
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
- Department of Clinical Child and Family Studies, VU University Amsterdam, Amsterdam, The Netherlands
- Department of Methods, VU University Amsterdam, Amsterdam, The Netherlands
| | - Stéphanie M. van den Berg
- Department of Research Methodology, Measurement and Data-Analysis, University of Twente, Enschede, The Netherlands
| | - Karin J.H. Verweij
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Australia
- Department of Developmental Psychology and EMGO Institute for Health and Care Research, VU University Amsterdam, Amsterdam, The Netherlands
| | | | - Michelle Luciano
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Alejandro Arias Vasquez
- Donders Institute for Cognitive Neuroscience, Radboud University Nijmegen, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
- Department of Human Genetics, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | | | - Jaime Derringer
- Department of Psychology, University of Illinois at Urbana-Champaign, Champaign IL, USA
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Scott D. Gordon
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Australia
| | | | - Amy B. Hart
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Finland
| | - Jennifer E. Huffman
- MRC Human Genetics, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, Scotland, UK
| | - Bettina Konte
- Department of Psychiatry, University of Halle, Halle, Germany
| | - Jari Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Minyoung Lee
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Mike Miller
- Department of Psychology, University of Minnesota, Minneapolis, USA
| | - Teresa Nutile
- Institute of Genetics and Biophysics “A. Buzzati-Traverso” – CNR, Naples, Italy
| | | | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Alexander Viktorin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juho Wedenoja
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki, Finland
| | - Goncalo R. Abecasis
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Daniel E. Adkins
- Pharmacotherapy & Outcomes Science, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jüri Allik
- Department of Psychology, University of Tartu, Tartu, Estonia
- Estonian Academy of Sciences, Tallinn, Estonia
| | - Katja Appel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Timothy B. Bigdeli
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Fabio Busonero
- Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, Italy
| | - Harry Campbell
- Centre for Population Health Sciences, Medical School, University of Edinburgh, Edinburgh, UK
| | - Paul T. Costa
- Behavioral Medicine Research Center, Duke University School of Medicine, Durham NC, USA
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Gail Davies
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Harriet de Wit
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, USA
| | - Jun Ding
- Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore MD USA
| | | | - Johan G. Eriksson
- Folkhälsan Research Center, Helsinki, Finland
- National Institute for Health and Welfare (THL), Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Unit of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Vasa Central Hospital, Vasa, Finland
| | - Iryna O. Fedko
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | | | - Barbara Franke
- Donders Institute for Cognitive Neuroscience, Radboud University Nijmegen, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
- Department of Human Genetics, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Ina Giegling
- Department of Psychiatry, University of Halle, Halle, Germany
| | - Richard Grucza
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | | | - Andrew C. Heath
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Kati Heinonen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Anjali K. Henders
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Australia
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Germany
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Joost Janzing
- Department of Psychiatry, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Markus Jokela
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - John P. Kemp
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia
| | | | - Antti Latvala
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare (THL), Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Finland
| | - David C. Liewald
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Pamela A.F. Madden
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Chiara Magri
- Department of Molecular and Translational Medicine, University of Brescia, Italy
| | - Patrik K.E. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jonathan Marten
- MRC Human Genetics, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, Scotland, UK
| | - Andrea Maschio
- Istituto di Ricerca Genetica e Biomedica (IRGB), CNR, Monserrato, Italy
| | - Sarah E. Medland
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Australia
| | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Department of Biotechnology, University of Tartu, Tartu, Estonia
| | - Yuri Milaneschi
- Department of Psychiatry, EMGO+ Institute, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | | | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Klaasjan G. Ouwens
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Aarno Palotie
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, University of Helsinki, Finland
| | - Erik Pettersson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ozren Polasek
- Department of Public Health, Faculty of Medicine, University of Split, Faculty of Medicine, University of Split, Split, Croatia
| | - Yong Qian
- Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore MD USA
| | - Laura Pulkki-Råback
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Olli T. Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Anu Realo
- Department of Psychology, University of Tartu, Tartu, Estonia
| | - Richard J. Rose
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Daniela Ruggiero
- Institute of Genetics and Biophysics “A. Buzzati-Traverso” – CNR, Naples, Italy
| | - Carsten O. Schmidt
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Wendy S. Slutske
- Department of Psychological Sciences and Missouri Alcoholism Research Center, University of Missouri, Columbia, Missouri, USA
| | - Rossella Sorice
- Institute of Genetics and Biophysics “A. Buzzati-Traverso” – CNR, Naples, Italy
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh
- Geriatric Medicine Royal Victoria Hospital, Edinburgh, UK
| | - Beate St Pourcain
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
- School of Oral and Dental Sciences, University of Bristol, Bristol, UK
- School of Experimental Psychology, University of Bristol, Bristol, UK
| | - Angelina R. Sutin
- National Institute on Aging, NIH, Baltimore, MD, USA
- College of Medicine, Florida State University, Tallahassee, FL, USA
| | - Nicholas J. Timpson
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Holly Trochet
- MRC Human Genetics, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, Scotland, UK
| | - Sita Vermeulen
- Department of Human Genetics, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
- Department for Health Evidence, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Eero Vuoksimaa
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki, Finland
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, University of Helsinki, Finland
| | - Jasper Wouda
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
- Department of Research Methodology, Measurement and Data-Analysis, University of Twente, Enschede, The Netherlands
| | | | - Lina Zgaga
- Centre for Population Health Sciences, Medical School, University of Edinburgh, Edinburgh, UK
- Department of Public Health and Primary Care, Trinity College Dublin, Dublin, Ireland
| | - Generation Scotland
- Generation Scotland, A Collaboration between the University Medical Schools and NHS, Aberdeen, Dundee, Edinburgh and Glasgow, UK
| | - David Porteous
- Medical Genetics Section, The University of Edinburgh, Centre for Genomics and Experimental Medicine, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK
| | - Alessandra Minelli
- Department of Molecular and Translational Medicine, University of Brescia, Italy
| | - Abraham A. Palmer
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, USA
| | - Dan Rujescu
- Department of Psychiatry, University of Halle, Halle, Germany
| | - Marina Ciullo
- Institute of Genetics and Biophysics “A. Buzzati-Traverso” – CNR, Naples, Italy
| | - Caroline Hayward
- MRC Human Genetics, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, Scotland, UK
| | - Igor Rudan
- Centre for Population Health Sciences, Medical School, University of Edinburgh, Edinburgh, UK
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Estonian Academy of Sciences, Tallinn, Estonia
| | - Jaakko Kaprio
- Department of Public Health, Hjelt Institute, University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare (THL), Helsinki, Finland
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, University of Helsinki, Finland
| | - Ian J. Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Katri Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - James F. Wilson
- Centre for Population Health Sciences, Medical School, University of Edinburgh, Edinburgh, UK
| | | | - Laura J. Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - John M. Hettema
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, HELIOS Hospital Stralsund, Stralsund, Germany
| | - Cornelia M. van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - David M. Evans
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia
| | - David Schlessinger
- Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore MD USA
| | - Nancy L. Pedersen
- Institute of Genetics and Biophysics “A. Buzzati-Traverso” – CNR, Naples, Italy
| | - Antonio Terracciano
- Folkhälsan Research Center, Helsinki, Finland
- College of Medicine, Florida State University, Tallahassee, FL, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, USA
- Institute of Public Health, University of Southern Denmark, Odense, Denmark
| | - Brenda W.J.H. Penninx
- Department of Psychiatry, EMGO+ Institute, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | | | - Dorret I. Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
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30
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Kim HN, Kim BH, Cho J, Ryu S, Shin H, Sung J, Shin C, Cho NH, Sung YA, Choi BO, Kim HL. Pathway analysis of genome-wide association datasets of personality traits. GENES BRAIN AND BEHAVIOR 2015; 14:345-56. [PMID: 25809424 DOI: 10.1111/gbb.12212] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2014] [Revised: 03/05/2015] [Accepted: 03/10/2015] [Indexed: 12/31/2022]
Abstract
Although several genome-wide association (GWA) studies of human personality have been recently published, genetic variants that are highly associated with certain personality traits remain unknown, due to difficulty reproducing results. To further investigate these genetic variants, we assessed biological pathways using GWA datasets. Pathway analysis using GWA data was performed on 1089 Korean women whose personality traits were measured with the Revised NEO Personality Inventory for the 5-factor model of personality. A total of 1042 pathways containing 8297 genes were included in our study. Of these, 14 pathways were highly enriched with association signals that were validated in 1490 independent samples. These pathways include association of: Neuroticism with axon guidance [L1 cell adhesion molecule (L1CAM) interactions]; Extraversion with neuronal system and voltage-gated potassium channels; Agreeableness with L1CAM interaction, neurotransmitter receptor binding and downstream transmission in postsynaptic cells; and Conscientiousness with the interferon-gamma and platelet-derived growth factor receptor beta polypeptide pathways. Several genes that contribute to top-ranked pathways in this study were previously identified in GWA studies or by pathway analysis in schizophrenia or other neuropsychiatric disorders. Here we report the first pathway analysis of all five personality traits. Importantly, our analysis identified novel pathways that contribute to understanding the etiology of personality traits.
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Affiliation(s)
- H-N Kim
- Department of Biochemistry, School of Medicine, Ewha Womans University, Seoul, Republic of Korea
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Walton E, Geisler D, Lee PH, Hass J, Turner JA, Liu J, Sponheim SR, White T, Wassink TH, Roessner V, Gollub RL, Calhoun VD, Ehrlich S. Prefrontal inefficiency is associated with polygenic risk for schizophrenia. Schizophr Bull 2014; 40:1263-71. [PMID: 24327754 PMCID: PMC4193692 DOI: 10.1093/schbul/sbt174] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Considering the diverse clinical presentation and likely polygenic etiology of schizophrenia, this investigation examined the effect of polygenic risk on a well-established intermediate phenotype for schizophrenia. We hypothesized that a measure of cumulative genetic risk based on additive effects of many genetic susceptibility loci for schizophrenia would predict prefrontal cortical inefficiency during working memory, a brain-based biomarker for the disorder. The present study combined imaging, genetic and behavioral data obtained by the Mind Clinical Imaging Consortium study of schizophrenia (n = 255). For each participant, we derived a polygenic risk score (PGRS), which was based on over 600 nominally significant single nucleotide polymorphisms, associated with schizophrenia in a separate discovery sample comprising 3322 schizophrenia patients and 3587 control participants. Increased polygenic risk for schizophrenia was associated with neural inefficiency in the left dorsolateral prefrontal cortex after covarying for the effects of acquisition site, diagnosis, and population stratification. We also provide additional supporting evidence for our original findings using scores based on results from the Psychiatric Genomics Consortium study. Gene ontology analysis of the PGRS highlighted genetic loci involved in brain development and several other processes possibly contributing to disease etiology. Our study permits new insights into the additive effect of hundreds of genetic susceptibility loci on a brain-based intermediate phenotype for schizophrenia. The combined impact of many common genetic variants of small effect are likely to better reveal etiologic mechanisms of the disorder than the study of single common genetic variants.
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Affiliation(s)
- Esther Walton
- Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Dresden University of Technology, Dresden, Germany
| | - Daniel Geisler
- Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Dresden University of Technology, Dresden, Germany
| | | | - Johanna Hass
- Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Dresden University of Technology, Dresden, Germany
| | | | - Jingyu Liu
- The Mind Research Network, Albuquerque, NM
| | - Scott R Sponheim
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN; Department of Psychiatry, University of Minnesota, Minneapolis, MN
| | - Tonya White
- Department of Child and Adolescent Psychiatry, Erasmus University, Rotterdam, Netherlands
| | | | - Veit Roessner
- Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Dresden University of Technology, Dresden, Germany
| | - Randy L Gollub
- Department of Psychiatry, Massachusetts General Hospital/Harvard Medical School, Boston, MA; MGH/MIT/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque, NM; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM
| | - Stefan Ehrlich
- Department of Child and Adolescent Psychiatry, University Hospital Carl Gustav Carus, Dresden University of Technology, Dresden, Germany; Department of Psychiatry, Massachusetts General Hospital/Harvard Medical School, Boston, MA; MGH/MIT/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA;
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Wray NR, Lee SH, Mehta D, Vinkhuyzen AAE, Dudbridge F, Middeldorp CM. Research review: Polygenic methods and their application to psychiatric traits. J Child Psychol Psychiatry 2014; 55:1068-87. [PMID: 25132410 DOI: 10.1111/jcpp.12295] [Citation(s) in RCA: 470] [Impact Index Per Article: 42.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/13/2014] [Indexed: 12/18/2022]
Abstract
BACKGROUND Despite evidence from twin and family studies for an important contribution of genetic factors to both childhood and adult onset psychiatric disorders, identifying robustly associated specific DNA variants has proved challenging. In the pregenomics era the genetic architecture (number, frequency and effect size of risk variants) of complex genetic disorders was unknown. Empirical evidence for the genetic architecture of psychiatric disorders is emerging from the genetic studies of the last 5 years. METHODS AND SCOPE We review the methods investigating the polygenic nature of complex disorders. We provide mini-guides to genomic profile (or polygenic) risk scoring and to estimation of variance (or heritability) from common SNPs; a glossary of key terms is also provided. We review results of applications of the methods to psychiatric disorders and related traits and consider how these methods inform on missing heritability, hidden heritability and still-missing heritability. FINDINGS Genome-wide genotyping and sequencing studies are providing evidence that psychiatric disorders are truly polygenic, that is they have a genetic architecture of many genetic variants, including risk variants that are both common and rare in the population. Sample sizes published to date are mostly underpowered to detect effect sizes of the magnitude presented by nature, and these effect sizes may be constrained by the biological validity of the diagnostic constructs. CONCLUSIONS Increasing the sample size for genome wide association studies of psychiatric disorders will lead to the identification of more associated genetic variants, as already found for schizophrenia. These loci provide the starting point of functional analyses that might eventually lead to new prevention and treatment options and to improved biological validity of diagnostic constructs. Polygenic analyses will contribute further to our understanding of complex genetic traits as sample sizes increase and as sample resources become richer in phenotypic descriptors, both in terms of clinical symptoms and of nongenetic risk factors.
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Affiliation(s)
- Naomi R Wray
- Queensland Brain Institute, The University of Queensland, St Lucia, Qld, Australia
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Vink JM, Hottenga JJ, de Geus EJC, Willemsen G, Neale MC, Furberg H, Boomsma DI. Polygenic risk scores for smoking: predictors for alcohol and cannabis use? Addiction 2014; 109:1141-51. [PMID: 24450588 PMCID: PMC4048635 DOI: 10.1111/add.12491] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2013] [Revised: 10/09/2013] [Accepted: 01/15/2014] [Indexed: 01/27/2023]
Abstract
BACKGROUND AND AIMS A strong correlation exists between smoking and the use of alcohol and cannabis. This paper uses polygenic risk scores to explore the possibility of overlapping genetic factors. Those scores reflect a combined effect of selected risk alleles for smoking. METHODS Summary-level P-values were available for smoking initiation, age at onset of smoking, cigarettes per day and smoking cessation from the Tobacco and Genetics Consortium (n between 22,000 and 70,000 subjects). Using different P-value thresholds (0.1, 0.2 and 0.5) from the meta-analysis, sets of 'risk alleles' were defined and used to generate a polygenic risk score (weighted sum of the alleles) for each subject in an independent target sample from the Netherlands Twin Register (n = 1583). The association between polygenic smoking scores and alcohol/cannabis use was investigated with regression analysis. RESULTS The polygenic scores for 'cigarettes per day' were associated significantly with the number of glasses alcohol per week (P = 0.005, R2 = 0.4-0.5%) and cannabis initiation (P = 0.004, R2 = 0.6-0.9%). The polygenic scores for 'age at onset of smoking' were associated significantly with 'age at regular drinking' (P = 0.001, R2 = 1.1-1.5%), while the scores for 'smoking initiation' and 'smoking cessation' did not significantly predict alcohol or cannabis use. CONCLUSIONS Smoking, alcohol and cannabis use are influenced by aggregated genetic risk factors shared between these substances. The many common genetic variants each have a very small individual effect size.
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Affiliation(s)
- Jacqueline M Vink
- Department of Biological Psychology, VU University, Amsterdam, the Netherlands; Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
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Disentangling the molecular genetic basis of personality: From monoamines to neuropeptides. Neurosci Biobehav Rev 2014; 43:228-39. [DOI: 10.1016/j.neubiorev.2014.04.006] [Citation(s) in RCA: 72] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2013] [Revised: 03/26/2014] [Accepted: 04/15/2014] [Indexed: 12/27/2022]
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36
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South SC, Krueger RF. Genetic strategies for probing conscientiousness and its relationship to aging. Dev Psychol 2014; 50:1362-76. [PMID: 23181432 PMCID: PMC3776017 DOI: 10.1037/a0030725] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Conscientiousness is an important trait for understanding healthy aging. The present article addresses how behavioral and molecular genetics methodologies can aid in furthering explicating the link between conscientiousness and aspects of health and well-being in later life. We review the etiology of conscientiousness documented by both quantitative and molecular genetics methods. We also discuss the ways behavior genetics can be used to continue to help refine the concept of conscientiousness and to help identify points of etiological overlap between conscientiousness and healthy aging outcomes. Phenotypic research has established nontrivial associations between conscientiousness and important outcomes, but behavior genetic methods can determine what the causal (genetic and environmental) mechanisms are behind these relationships. An empirical example of one of these techniques is provided using twin data from the Midlife in the United States (MIDUS) study. We demonstrate that conscientiousness moderates genetic and environmental influences on problem alcohol use, such that greater levels of conscientiousness buffer against the random effects of the environment. Finally, suggestions for future work in this area are discussed.
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Affiliation(s)
- Susan C South
- Department of Psychological Sciences, Purdue University
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37
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Leitsalu L, Haller T, Esko T, Tammesoo ML, Alavere H, Snieder H, Perola M, Ng PC, Mägi R, Milani L, Fischer K, Metspalu A. Cohort Profile: Estonian Biobank of the Estonian Genome Center, University of Tartu. Int J Epidemiol 2014; 44:1137-47. [PMID: 24518929 DOI: 10.1093/ije/dyt268] [Citation(s) in RCA: 272] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/03/2013] [Indexed: 01/05/2023] Open
Abstract
The Estonian Biobank cohort is a volunteer-based sample of the Estonian resident adult population (aged ≥18 years). The current number of participants-close to 52000--represents a large proportion, 5%, of the Estonian adult population, making it ideally suited to population-based studies. General practitioners (GPs) and medical personnel in the special recruitment offices have recruited participants throughout the country. At baseline, the GPs performed a standardized health examination of the participants, who also donated blood samples for DNA, white blood cells and plasma tests and filled out a 16-module questionnaire on health-related topics such as lifestyle, diet and clinical diagnoses described in WHO ICD-10. A significant part of the cohort has whole genome sequencing (100), genome-wide single nucleotide polymorphism (SNP) array data (20 000) and/or NMR metabolome data (11 000) available (http://www.geenivaramu.ee/for-scientists/data-release/). The data are continuously updated through periodical linking to national electronic databases and registries. A part of the cohort has been re-contacted for follow-up purposes and resampling, and targeted invitations are possible for specific purposes, for example people with a specific diagnosis. The Estonian Genome Center of the University of Tartu is actively collaborating with many universities, research institutes and consortia and encourages fellow scientists worldwide to co-initiate new academic or industrial joint projects with us.
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Affiliation(s)
- Liis Leitsalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Toomas Haller
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Divisions of Endocrinology, Boston Children's Hospital, Boston, MA, USA, Department of Genetics, Harvard Medical School, Boston, MA, USA, Broad Institute of Harvard and MIT, Cambridge, MA, US
| | | | - Helene Alavere
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Harold Snieder
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Department of Epidemiology, University of Groningen, Groningen, The Netherlands
| | - Markus Perola
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Public Health Genomics Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland, University of Helsinki, Institute for Molecular Medicine, Helsinki, Finland
| | - Pauline C Ng
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Genome Institute of Singapore, Singapore and
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia, Estonian Biocentre, Tartu, Estonia
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Ligthart L, Hottenga JJ, Lewis CM, Farmer AE, Craig IW, Breen G, Willemsen G, Vink JM, Middeldorp CM, Byrne EM, Heath AC, Madden PAF, Pergadia ML, Montgomery GW, Martin NG, Penninx BWJH, McGuffin P, Boomsma DI, Nyholt DR. Genetic risk score analysis indicates migraine with and without comorbid depression are genetically different disorders. Hum Genet 2014; 133:173-86. [PMID: 24081561 PMCID: PMC3947136 DOI: 10.1007/s00439-013-1370-8] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2013] [Accepted: 09/22/2013] [Indexed: 01/20/2023]
Abstract
Migraine and major depressive disorder (MDD) are comorbid, moderately heritable and to some extent influenced by the same genes. In a previous paper, we suggested the possibility of causality (one trait causing the other) underlying this comorbidity. We present a new application of polygenic (genetic risk) score analysis to investigate the mechanisms underlying the genetic overlap of migraine and MDD. Genetic risk scores were constructed based on data from two discovery samples in which genome-wide association analyses (GWA) were performed for migraine and MDD, respectively. The Australian Twin Migraine GWA study (N = 6,350) included 2,825 migraine cases and 3,525 controls, 805 of whom met the diagnostic criteria for MDD. The RADIANT GWA study (N = 3,230) included 1,636 MDD cases and 1,594 controls. Genetic risk scores for migraine and for MDD were used to predict pure and comorbid forms of migraine and MDD in an independent Dutch target sample (NTR-NESDA, N = 2,966), which included 1,476 MDD cases and 1,058 migraine cases (723 of these individuals had both disorders concurrently). The observed patterns of prediction suggest that the 'pure' forms of migraine and MDD are genetically distinct disorders. The subgroup of individuals with comorbid MDD and migraine were genetically most similar to MDD patients. These results indicate that in at least a subset of migraine patients with MDD, migraine may be a symptom or consequence of MDD.
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Affiliation(s)
- Lannie Ligthart
- Department of Biological Psychology, VU University, van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands,
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Tansey KE, Guipponi M, Domenici E, Lewis G, Malafosse A, O'Donovan M, Wendland JR, Lewis CM, McGuffin P, Uher R. Genetic susceptibility for bipolar disorder and response to antidepressants in major depressive disorder. Am J Med Genet B Neuropsychiatr Genet 2014; 165B:77-83. [PMID: 24339138 DOI: 10.1002/ajmg.b.32210] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2013] [Accepted: 10/15/2013] [Indexed: 11/07/2022]
Abstract
The high heterogeneity of response to antidepressant treatment in major depressive disorder (MDD) makes individual treatment outcomes currently unpredictable. It has been suggested that resistance to antidepressant treatment might be due to undiagnosed bipolar disorder or bipolar spectrum features. Here, we investigate the relationship between genetic susceptibility for bipolar disorder and response to treatment with antidepressants in MDD. Polygenic scores indexing risk for bipolar disorder were derived from the Psychiatric Genomics Consortium Bipolar Disorder whole genome association study. Linear regressions tested the effect of polygenic risk scores for bipolar disorder on proportional reduction in depression severity in two large samples of individuals with MDD, treated with antidepressants, NEWMEDS (n=1,791) and STAR*D (n=1,107). There was no significant association between polygenic scores for bipolar disorder and response to treatment with antidepressants. Our data indicate that molecular measure of genetic susceptibility to bipolar disorder does not aid in understanding non-response to antidepressants.
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Genome-wide association study implicates a novel RNA gene, the lincRNA AC068718.1, as a risk factor for post-traumatic stress disorder in women. Psychoneuroendocrinology 2013; 38:3029-38. [PMID: 24080187 PMCID: PMC3844079 DOI: 10.1016/j.psyneuen.2013.08.014] [Citation(s) in RCA: 95] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2013] [Revised: 08/27/2013] [Accepted: 08/29/2013] [Indexed: 11/22/2022]
Abstract
Posttraumatic stress disorder (PTSD) is a common and debilitating mental disorder with a particularly high burden for women. Emerging evidence suggests PTSD may be more heritable among women and evidence from animal models and human correlational studies suggest connections between sex-linked biology and PTSD vulnerability, which may extend to the disorder's genetic architecture. We conducted a genome-wide association study (GWAS) of PTSD in a primarily African American sample of women from the Detroit Neighborhood Health Study (DNHS) and tested for replication in an independent cohort of primarily European American women from the Nurses Health Study II (NHSII). We genotyped 413 DNHS women - 94 PTSD cases and 319 controls exposed to at least one traumatic event - on the Illumina HumanOmniExpress BeadChip for >700,000 markers and tested 578 PTSD cases and 1963 controls from NHSII for replication. We performed a network-based analysis integrating data from GWAS-derived independent regions of association and the Reactome database of functional interactions. We found genome-wide significant association for one marker mapping to a novel RNA gene, lincRNA AC068718.1, for which we found suggestive evidence of replication in NHSII. Our network-based analysis indicates that our top GWAS results were enriched for pathways related to telomere maintenance and immune function. Our findings implicate a novel RNA gene, lincRNA AC068718.1, as risk factor for PTSD in women and add to emerging evidence that non-coding RNA genes may play a crucial role in shaping the landscape of gene regulation with putative pathological effects that lead to phenotypic differences.
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Saunders EF, Novick DM, Fernandez-Mendoza J, Kamali M, Ryan KA, Langenecker SA, Gelenberg AJ, McInnis MG. Sleep quality during euthymia in bipolar disorder: the role of clinical features, personality traits, and stressful life events. Int J Bipolar Disord 2013; 1:16. [PMID: 25505683 PMCID: PMC4230686 DOI: 10.1186/2194-7511-1-16] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2013] [Accepted: 08/16/2013] [Indexed: 11/16/2022] Open
Abstract
Background Poor sleep quality is known to precede the onset of mood episodes and to be associated with poor treatment outcomes in bipolar disorder (BD). We sought to identify modifiable factors that correlate with poor sleep quality in BD independent of residual mood symptoms. Methods A retrospective analysis was conducted to assess the association between the Pittsburgh Sleep Quality Index and clinical variables of interest in euthymic patients with DSM-IV BD (n = 119) and healthy controls (HC; n = 136) participating in the Prechter Longitudinal Study of Bipolar Disorder. Multivariable linear regression models were constructed to investigate the relationship between sleep quality and demographic and clinical variables in BD and HC participants. A unified model determined independent predictors of sleep quality. Results and discussion Euthymic participants with BD and HC differed in all domains. The best fitting unified multivariable model of poor sleep quality in euthymic participants with BD included rapid cycling (β = .20, p = .03), neuroticism (β = .28, p = 2 × 10−3), and stressful life events (β = .20, p = .02). Poor sleep quality often persists during euthymia and can be a target for treatment. Clinicians should remain vigilant for treating subjective sleep complaints independent of residual mood symptoms in those sensitive to poor sleep quality, including individuals with high neuroticism, rapid cycling, and recent stressful life events. Modifiable factors associated with sleep quality should be targeted directly with psychosocial or somatic treatment. Sleep quality may be a useful outcome measure in BD treatment studies.
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Affiliation(s)
- Erika Fh Saunders
- University of Illinois at Chicago, Chicago, IL 60612 USA ; University of Illinois at Chicago, Chicago, IL 60612 USA ; University of Illinois at Chicago, Chicago, IL 60612 USA
| | - Danielle M Novick
- University of Illinois at Chicago, Chicago, IL 60612 USA ; University of Illinois at Chicago, Chicago, IL 60612 USA ; University of Illinois at Chicago, Chicago, IL 60612 USA
| | - Julio Fernandez-Mendoza
- University of Illinois at Chicago, Chicago, IL 60612 USA ; University of Illinois at Chicago, Chicago, IL 60612 USA
| | - Masoud Kamali
- University of Illinois at Chicago, Chicago, IL 60612 USA ; University of Illinois at Chicago, Chicago, IL 60612 USA
| | - Kelly A Ryan
- University of Illinois at Chicago, Chicago, IL 60612 USA ; University of Illinois at Chicago, Chicago, IL 60612 USA
| | - Scott A Langenecker
- University of Illinois at Chicago, Chicago, IL 60612 USA ; University of Illinois at Chicago, Chicago, IL 60612 USA ; University of Illinois at Chicago, Chicago, IL 60612 USA
| | | | - Melvin G McInnis
- University of Illinois at Chicago, Chicago, IL 60612 USA ; University of Illinois at Chicago, Chicago, IL 60612 USA
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Enaw JOE, Smith AK. Biomarker Development for Brain-Based Disorders: Recent Progress in Psychiatry. ACTA ACUST UNITED AC 2013; 1:7. [PMID: 25110721 DOI: 10.13188/2332-3469.1000006] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Biomarkers are biological measures that are indicative of a specific disorder, its severity or response to treatment. They are widely used in many areas of medicine, but biomarker development for brain-based disorders lags behind. Using examples from the field of psychiatry, this article reviews the concepts of biomarkers, challenges to their development and the recent progress along those lines. In addition to discussing historical biomarker candidates such as cortisol or catecholamine levels, we include progress from recent genetic, epigenetic, proteomic, neuroimaging and EEG studies. Successful identification of biomarkers will advance the field of psychiatry towards the goal of biological tests for diagnosis, symptom management and treatment response.
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Affiliation(s)
- James O Ebot Enaw
- Department of Psychiatry & Behavioral Sciences, Emory University, School of Medicine, Atlanta, GA, USA
| | - Alicia K Smith
- Department of Psychiatry & Behavioral Sciences, Emory University, School of Medicine, Atlanta, GA, USA
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Luciano M, Huffman JE, Arias-Vásquez A, Vinkhuyzen AAE, Middeldorp CM, Giegling I, Payton A, Davies G, Zgaga L, Janzing J, Ke X, Galesloot T, Hartmann AM, Ollier W, Tenesa A, Hayward C, Verhagen M, Montgomery GW, Hottenga JJ, Konte B, Starr JM, Vitart V, Vos PE, Madden PAF, Willemsen G, Konnerth H, Horan MA, Porteous DJ, Campbell H, Vermeulen SH, Heath AC, Wright A, Polasek O, Kovacevic SB, Hastie ND, Franke B, Boomsma DI, Martin NG, Rujescu D, Wilson JF, Buitelaar J, Pendleton N, Rudan I, Deary IJ. Genome-wide association uncovers shared genetic effects among personality traits and mood states. Am J Med Genet B Neuropsychiatr Genet 2012; 159B:684-95. [PMID: 22628180 PMCID: PMC3795298 DOI: 10.1002/ajmg.b.32072] [Citation(s) in RCA: 62] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2012] [Accepted: 05/03/2012] [Indexed: 12/27/2022]
Abstract
Measures of personality and psychological distress are correlated and exhibit genetic covariance. We conducted univariate genome-wide SNP (~2.5 million) and gene-based association analyses of these traits and examined the overlap in results across traits, including a prediction analysis of mood states using genetic polygenic scores for personality. Measures of neuroticism, extraversion, and symptoms of anxiety, depression, and general psychological distress were collected in eight European cohorts (n ranged 546-1,338; maximum total n = 6,268) whose mean age ranged from 55 to 79 years. Meta-analysis of the cohort results was performed, with follow-up associations of the top SNPs and genes investigated in independent cohorts (n = 527-6,032). Suggestive association (P = 8 × 10(-8)) of rs1079196 in the FHIT gene was observed with symptoms of anxiety. Other notable associations (P < 6.09 × 10(-6)) included SNPs in five genes for neuroticism (LCE3C, POLR3A, LMAN1L, ULK3, SCAMP2), KIAA0802 for extraversion, and NOS1 for general psychological distress. An association between symptoms of depression and rs7582472 (near to MGAT5 and NCKAP5) was replicated in two independent samples, but other replication findings were less consistent. Gene-based tests identified a significant locus on chromosome 15 (spanning five genes) associated with neuroticism which replicated (P < 0.05) in an independent cohort. Support for common genetic effects among personality and mood (particularly neuroticism and depressive symptoms) was found in terms of SNP association overlap and polygenic score prediction. The variance explained by individual SNPs was very small (up to 1%) confirming that there are no moderate/large effects of common SNPs on personality and related traits.
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Affiliation(s)
- Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
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