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Hoy N, Lynch SJ, Waszczuk MA, Reppermund S, Mewton L. Transdiagnostic biomarkers of mental illness across the lifespan: A systematic review examining the genetic and neural correlates of latent transdiagnostic dimensions of psychopathology in the general population. Neurosci Biobehav Rev 2023; 155:105431. [PMID: 37898444 DOI: 10.1016/j.neubiorev.2023.105431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/26/2023] [Accepted: 10/21/2023] [Indexed: 10/30/2023]
Abstract
This systematic review synthesizes evidence from research investigating the biological correlates of latent transdiagnostic dimensions of psychopathology (e.g., the p-factor, internalizing, externalizing) across the lifespan. Eligibility criteria captured genomic and neuroimaging studies investigating general and/or specific dimensions in general population samples across all age groups. MEDLINE, Embase, and PsycINFO were searched for relevant studies published up to March 2023 and 46 studies were selected for inclusion. The results revealed several biological correlates consistently associated with transdiagnostic dimensions of psychopathology, including polygenic scores for ADHD and neuroticism, global surface area and global gray matter volume. Shared and unique associations between symptom dimensions are highlighted, as are potential age-specific differences in biological associations. Findings are interpreted with reference to key methodological differences across studies. The included studies provide compelling evidence that the general dimension of psychopathology reflects common underlying genetic and neurobiological vulnerabilities that are shared across diverse manifestations of mental illness. Substantive interpretations of general psychopathology in the context of genetic and neurobiological evidence are discussed.
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Affiliation(s)
- Nicholas Hoy
- The Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Sydney, Australia; Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia.
| | - Samantha J Lynch
- The Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Sydney, Australia; Department of Psychiatry, Université de Montréal, Montreal, Canada; Research Centre, CHU Sainte-Justine, Montreal, Canada
| | - Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, United States
| | - Simone Reppermund
- Centre for Healthy Brain Ageing, University of New South Wales, Sydney, Australia; Department of Developmental Disability Neuropsychiatry, University of New South Wales, Sydney, Australia
| | - Louise Mewton
- The Matilda Centre for Research in Mental Health and Substance Use, University of Sydney, Sydney, Australia
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Babineau V, Jolicoeur-Martineau A, Szekely E, Green CG, Sassi R, Gaudreau H, Levitan RD, Lydon J, Steiner M, O'Donnell KJ, Kennedy JL, Burack JA, Wazana A. Maternal prenatal depression is associated with dysregulation over the first five years of life moderated by child polygenic risk for comorbid psychiatric problems. Dev Psychobiol 2023; 65:e22395. [PMID: 37338256 DOI: 10.1002/dev.22395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 03/08/2023] [Accepted: 03/28/2023] [Indexed: 06/21/2023]
Abstract
Dysregulation is a combination of emotion, behavior, and attention problems associated with lifelong psychiatric comorbidity. There is evidence for the stability of dysregulation from childhood to adulthood, which would be more fully characterized by determining the likely stability from infancy to childhood. Early origins of dysregulation can further be validated and contextualized in association with environmental and biological factors, such as prenatal stress and polygenic risk scores (PRS) for overlapping child psychiatric problems. We aimed to determine trajectories of dysregulation from 3 months to 5 years (N = 582) in association with maternal prenatal depression moderated by multiple child PRS (N = 232 pairs with available PRS data) in a prenatal cohort. Mothers reported depression symptoms at 24-26 weeks' gestation and child dysregulation at 3, 6, 18, 36, 48, and 60 months. The PRS were for major depressive disorder, attention deficit hyperactivity disorder, cross disorder, and childhood psychiatric problems. Covariates were biological sex, maternal education, and postnatal depression. Analyses included latent classes and regression. Two dysregulation trajectories emerged: persistently low dysregulation (94%), and increasingly high dysregulation (6%). Stable dysregulation emerged at 18 months. High dysregulation was associated with maternal prenatal depression, moderated by PRS for child comorbid psychiatric problems. Males were at greater risk of high dysregulation.
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Affiliation(s)
- Vanessa Babineau
- Department of Obstetrics and Gynecology, Columbia University, New York, New York, USA
| | | | - Eszter Szekely
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | | | - Roberto Sassi
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada
| | - Hélène Gaudreau
- Department of Psychiatry, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - Robert D Levitan
- Campbell Family Mental Health Research Institute, Center for Addiction and Mental Health, Toronto, Ontario, Canada
| | - John Lydon
- Department of Psychology, McGill University, Montreal, Quebec, Canada
| | - Meir Steiner
- Women's Health Concerns Clinic, St-Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
| | - Kieran J O'Donnell
- Department of Obstetrics, Gynecology and Reproductive Sciences, Yale School of Medicine, New Haven, USA
| | - James L Kennedy
- Campbell Family Mental Health Research Institute, Center for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Jacob A Burack
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Ashley Wazana
- Institute of Community and Family Psychiatry, Jewish General Hospital, Montreal, Quebec, Canada
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Dattani S, Sham PC, Jermy BS, Coleman JRI, Howard DM, Lewis CM. Common and rare variant associations with latent traits underlying depression, bipolar disorder, and schizophrenia. Transl Psychiatry 2023; 13:46. [PMID: 36746926 PMCID: PMC9902570 DOI: 10.1038/s41398-023-02324-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 01/07/2023] [Accepted: 01/18/2023] [Indexed: 02/08/2023] Open
Abstract
Genetic studies in psychiatry have primarily focused on the effects of common genetic variants, but few have investigated the role of rare genetic variants, particularly for major depression. In order to explore the role of rare variants in the gap between estimates of single nucleotide polymorphism (SNP) heritability and twin study heritability, we examined the contribution of common and rare genetic variants to latent traits underlying psychiatric disorders using high-quality imputed genotype data from the UK Biobank. Using a pre-registered analysis, we used items from the UK Biobank Mental Health Questionnaire relevant to three psychiatric disorders: major depression (N = 134,463), bipolar disorder (N = 117,376) and schizophrenia (N = 130,013) and identified a general hierarchical factor for each that described participants' responses. We calculated participants' scores on these latent traits and conducted single-variant genetic association testing (MAF > 0.05%), gene-based burden testing and pathway association testing associations with these latent traits. We tested for enrichment of rare variants (MAF 0.05-1%) in genes that had been previously identified by common variant genome-wide association studies, and genes previously associated with Mendelian disorders having relevant symptoms. We found moderate genetic correlations between the latent traits in our study and case-control phenotypes in previous genome-wide association studies, and identified one common genetic variant (rs72657988, minor allele frequency = 8.23%, p = 1.01 × 10-9) associated with the general factor of schizophrenia, but no other single variants, genes or pathways passed significance thresholds in this analysis, and we did not find enrichment in previously identified genes.
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Affiliation(s)
- Saloni Dattani
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Department of Psychiatry, Li Ka Shing (LKS) Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China.
| | - Pak C Sham
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
- Department of Psychiatry, State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China
- Centre for PanorOmic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Bradley S Jermy
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Jonathan R I Coleman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - David M Howard
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King's College London, London, UK
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Gillett AC, Jermy BS, Lee SH, Pain O, Howard DM, Hagenaars SP, Hanscombe KB, Coleman JRI, Lewis CM. Exploring polygenic-environment and residual-environment interactions for depressive symptoms within the UK Biobank. Genet Epidemiol 2022; 46:219-233. [PMID: 35438196 PMCID: PMC9541465 DOI: 10.1002/gepi.22449] [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: 08/06/2021] [Revised: 02/04/2022] [Accepted: 03/15/2022] [Indexed: 11/10/2022]
Abstract
Substantial advances have been made in identifying genetic contributions to depression, but little is known about how the effect of genes can be modulated by the environment, creating a gene-environment interaction. Using multivariate reaction norm models (MRNMs) within the UK Biobank (N = 61294-91644), we investigate whether the polygenic and residual variance components of depressive symptoms are modulated by 17 a priori selected covariate traits-12 environmental variables and 5 biomarkers. MRNMs, a mixed-effects modelling approach, provide unbiased polygenic-covariate interaction estimates for a quantitative trait by controlling for outcome-covariate correlations and residual-covariate interactions. A continuous depressive symptom variable was the outcome in 17 MRNMs-one for each covariate trait. Each MRNM had a fixed-effects model (fixed effects included the covariate trait, demographic variables, and principal components) and a random effects model (where polygenic-covariate and residual-covariate interactions are modelled). Of the 17 selected covariates, 11 significantly modulate deviations in depressive symptoms through the modelled interactions, but no single interaction explains a large proportion of phenotypic variation. Results are dominated by residual-covariate interactions, suggesting that covariate traits (including neuroticism, childhood trauma, and BMI) typically interact with unmodelled variables, rather than a genome-wide polygenic component, to influence depressive symptoms. Only average sleep duration has a polygenic-covariate interaction explaining a demonstrably nonzero proportion of the variability in depressive symptoms. This effect is small, accounting for only 1.22% (95% confidence interval: [0.54, 1.89]) of variation. The presence of an interaction highlights a specific focus for intervention, but the negative results here indicate a limited contribution from polygenic-environment interactions.
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Affiliation(s)
- Alexandra C Gillett
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Bradley S Jermy
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Sang Hong Lee
- Australian Centre for Precision Health, University of South Australia, SA, Adelaide, Australia.,UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia
| | - Oliver Pain
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - David M Howard
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Saskia P Hagenaars
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Ken B Hanscombe
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Jonathan R I Coleman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK.,Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King's College London, London, UK
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Kanarik M, Grimm O, Mota NR, Reif A, Harro J. ADHD co-morbidities: A review of implication of gene × environment effects with dopamine-related genes. Neurosci Biobehav Rev 2022; 139:104757. [PMID: 35777579 DOI: 10.1016/j.neubiorev.2022.104757] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 06/25/2022] [Accepted: 06/26/2022] [Indexed: 02/07/2023]
Abstract
ADHD is a major burden in adulthood, where co-morbid conditions such as depression, substance use disorder and obesity often dominate the clinical picture. ADHD has substantial shared heritability with other mental disorders, contributing to comorbidity. However, environmental risk factors exist but their interaction with genetic makeup, especially in relation to comorbid disorders, remains elusive. This review for the first time summarizes present knowledge on gene x environment (GxE) interactions regarding the dopamine system. Hitherto, mainly candidate (GxE) studies were performed, focusing on the genes DRD4, DAT1 and MAOA. Some evidence suggest that the variable number tandem repeats in DRD4 and MAOA may mediate GxE interactions in ADHD generally, and comorbid conditions specifically. Nevertheless, even for these genes, common variants are bound to suggest risk only in the context of gender and specific environments. For other polymorphisms, evidence is contradictory and less convincing. Particularly lacking are longitudinal studies testing the interaction of well-defined environmental with polygenic risk scores reflecting the dopamine system in its entirety.
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Affiliation(s)
- Margus Kanarik
- Chair of Neuropsychopharmacology, Institute of Chemistry, University of Tartu, Ravila 14A Chemicum, 50411 Tartu, Estonia
| | - Oliver Grimm
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University, Frankfurt, Germany
| | - Nina Roth Mota
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University, Frankfurt, Germany
| | - Jaanus Harro
- Chair of Neuropsychopharmacology, Institute of Chemistry, University of Tartu, Ravila 14A Chemicum, 50411 Tartu, Estonia; Psychiatry Clinic, North Estonia Medical Centre, Paldiski Road 52, 10614 Tallinn, Estonia.
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Jermy BS, Glanville KP, Coleman JRI, Lewis CM, Vassos E. Exploring the genetic heterogeneity in major depression across diagnostic criteria. Mol Psychiatry 2021; 26:7337-7345. [PMID: 34290369 PMCID: PMC8872976 DOI: 10.1038/s41380-021-01231-w] [Citation(s) in RCA: 7] [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: 12/18/2020] [Revised: 07/02/2021] [Accepted: 07/06/2021] [Indexed: 02/05/2023]
Abstract
Major depressive disorder (MDD) is defined differently across genetic research studies and this may be a key source of heterogeneity. While previous literature highlights differences between minimal and strict phenotypes, the components contributing to this heterogeneity have not been identified. Using the cardinal symptoms (depressed mood/anhedonia) as a baseline, we build MDD phenotypes using five components-(1) five or more symptoms, (2) episode duration, (3) functional impairment, (4) episode persistence, and (5) episode recurrence-to determine the contributors to such heterogeneity. Thirty-two depression phenotypes which systematically incorporate different combinations of MDD components were created using the mental health questionnaire data within the UK Biobank. SNP-based heritabilities and genetic correlations with three previously defined major depression phenotypes were calculated (Psychiatric Genomics Consortium (PGC) defined depression, 23andMe self-reported depression and broad depression) and differences between estimates analysed. All phenotypes were heritable (h2SNP range: 0.102-0.162) and showed substantial genetic correlations with other major depression phenotypes (Rg range: 0.651-0.895 (PGC); 0.652-0.837 (23andMe); 0.699-0.900 (broad depression)). The strongest effect on SNP-based heritability was from the requirement for five or more symptoms (1.4% average increase) and for a long episode duration (2.7% average decrease). No significant differences were noted between genetic correlations. While there is some variation, the two cardinal symptoms largely reflect the genetic aetiology of phenotypes incorporating more MDD components. These components may index severity, however, their impact on heterogeneity in genetic results is likely to be limited.
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Affiliation(s)
- Bradley S. Jermy
- grid.13097.3c0000 0001 2322 6764Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK ,grid.37640.360000 0000 9439 0839NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Kylie P. Glanville
- grid.13097.3c0000 0001 2322 6764Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Jonathan R. I. Coleman
- grid.13097.3c0000 0001 2322 6764Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK ,grid.37640.360000 0000 9439 0839NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Cathryn M. Lewis
- grid.13097.3c0000 0001 2322 6764Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK ,grid.37640.360000 0000 9439 0839NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK ,grid.13097.3c0000 0001 2322 6764Department of Medical & Molecular Genetics, Faculty of Life Sciences and Medicine, King’s College London, London, UK
| | - Evangelos Vassos
- grid.13097.3c0000 0001 2322 6764Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK ,grid.37640.360000 0000 9439 0839NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
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Cai N, Choi KW, Fried EI. Reviewing the genetics of heterogeneity in depression: operationalizations, manifestations and etiologies. Hum Mol Genet 2020; 29:R10-R18. [PMID: 32568380 PMCID: PMC7530517 DOI: 10.1093/hmg/ddaa115] [Citation(s) in RCA: 74] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 06/05/2020] [Accepted: 06/08/2020] [Indexed: 02/06/2023] Open
Abstract
With progress in genome-wide association studies of depression, from identifying zero hits in ~16 000 individuals in 2013 to 223 hits in more than a million individuals in 2020, understanding the genetic architecture of this debilitating condition no longer appears to be an impossible task. The pressing question now is whether recently discovered variants describe the etiology of a single disease entity. There are a myriad of ways to measure and operationalize depression severity, and major depressive disorder as defined in the Diagnostic and Statistical Manual of Mental Disorders-5 can manifest in more than 10 000 ways based on symptom profiles alone. Variations in developmental timing, comorbidity and environmental contexts across individuals and samples further add to the heterogeneity. With big data increasingly enabling genomic discovery in psychiatry, it is more timely than ever to explicitly disentangle genetic contributions to what is likely 'depressions' rather than depression. Here, we introduce three sources of heterogeneity: operationalization, manifestation and etiology. We review recent efforts to identify depression subtypes using clinical and data-driven approaches, examine differences in genetic architecture of depression across contexts, and argue that heterogeneity in operationalizations of depression is likely a considerable source of inconsistency. Finally, we offer recommendations and considerations for the field going forward.
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Affiliation(s)
- Na Cai
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg 85764, Germany
| | - Karmel W Choi
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
- Stanley Center for Psychiatric Research, Broad Institute, Boston, MA 02142, USA
| | - Eiko I Fried
- Department of Psychology, Leiden University, Leiden 2333 AK, Netherlands
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