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Arcego DM, Buschdorf JP, O'Toole N, Wang Z, Barth B, Pokhvisneva I, Rayan NA, Patel S, de Mendonça Filho EJ, Lee P, Tan J, Koh MX, Sim CM, Parent C, de Lima RMS, Clappison A, O'Donnell KJ, Dalmaz C, Arloth J, Provençal N, Binder EB, Diorio J, Silveira PP, Meaney MJ. A Glucocorticoid-Sensitive Hippocampal Gene Network Moderates the Impact of Early-Life Adversity on Mental Health Outcomes. Biol Psychiatry 2024; 95:48-61. [PMID: 37406925 DOI: 10.1016/j.biopsych.2023.06.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 04/15/2023] [Accepted: 06/20/2023] [Indexed: 07/07/2023]
Abstract
BACKGROUND Early stress increases the risk for psychiatric disorders. Glucocorticoids are stress mediators that regulate transcriptional activity and morphology in the hippocampus, which is implicated in the pathophysiology of multiple psychiatric conditions. We aimed to establish the relevance of hippocampal glucocorticoid-induced transcriptional activity as a mediator of the effects of early life on later psychopathology in humans. METHODS RNA sequencing was performed with anterior and posterior hippocampal dentate gyrus from adult female macaques (n = 12/group) that were chronically treated with betamethasone (glucocorticoid receptor agonist) or vehicle. Coexpression network analysis identified a preserved gene network in the posterior hippocampal dentate gyrus that was strongly associated with glucocorticoid exposure. The single nucleotide polymorphisms in the genes in this network were used to create an expression-based polygenic score in humans. RESULTS The expression-based polygenic score significantly moderated the association between early adversity and psychotic disorders in adulthood (UK Biobank, women, n = 44,519) and on child peer relations (ALSPAC [Avon Longitudinal Study of Parents and Children], girls, n = 1666 for 9-year-olds and n = 1594 for 11-year-olds), an endophenotype for later psychosis. Analyses revealed that this network was enriched for glucocorticoid-induced epigenetic remodeling in human hippocampal cells. We also found a significant association between single nucleotide polymorphisms from the expression-based polygenic score and adult brain gray matter density. CONCLUSIONS We provide an approach for the use of transcriptomic data from animal models together with human data to study the impact of environmental influences on mental health. The results are consistent with the hypothesis that hippocampal glucocorticoid-related transcriptional activity mediates the effects of early adversity on neural mechanisms implicated in psychiatric disorders.
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Affiliation(s)
- Danusa Mar Arcego
- Douglas Research Centre, Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Centre, McGill University, Montreal, Quebec, Canada.
| | - Jan-Paul Buschdorf
- Translational Neuroscience Program, Singapore Institute for Clinical Sciences, Singapore, Republic of Singapore
| | - Nicholas O'Toole
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Centre, McGill University, Montreal, Quebec, Canada
| | - Zihan Wang
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Centre, McGill University, Montreal, Quebec, Canada
| | - Barbara Barth
- Douglas Research Centre, Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Irina Pokhvisneva
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Centre, McGill University, Montreal, Quebec, Canada
| | | | - Sachin Patel
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Centre, McGill University, Montreal, Quebec, Canada
| | | | - Patrick Lee
- Translational Neuroscience Program, Singapore Institute for Clinical Sciences, Singapore, Republic of Singapore
| | - Jennifer Tan
- Translational Neuroscience Program, Singapore Institute for Clinical Sciences, Singapore, Republic of Singapore
| | - Ming Xuan Koh
- Translational Neuroscience Program, Singapore Institute for Clinical Sciences, Singapore, Republic of Singapore
| | - Chu Ming Sim
- Translational Neuroscience Program, Singapore Institute for Clinical Sciences, Singapore, Republic of Singapore
| | - Carine Parent
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Centre, McGill University, Montreal, Quebec, Canada
| | | | - Andrew Clappison
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Centre, McGill University, Montreal, Quebec, Canada
| | - Kieran J O'Donnell
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Centre, McGill University, Montreal, Quebec, Canada; Yale Child Study Center, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Carla Dalmaz
- Department of Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Janine Arloth
- Department Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Nadine Provençal
- Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada; BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada
| | - Elisabeth B Binder
- Department Genes and Environment, Max Planck Institute of Psychiatry, Munich, Germany
| | - Josie Diorio
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Centre, McGill University, Montreal, Quebec, Canada
| | - Patrícia Pelufo Silveira
- Douglas Research Centre, Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Ludmer Centre for Neuroinformatics and Mental Health, Douglas Research Centre, McGill University, Montreal, Quebec, Canada; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Republic of Singapore
| | - Michael J Meaney
- Douglas Research Centre, Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada; Translational Neuroscience Program, Singapore Institute for Clinical Sciences, Singapore, Republic of Singapore; Brain Body Initiative, Agency for Science, Technology and Research (A∗STAR), Singapore, Republic of Singapore; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Republic of Singapore
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Thomas M, Rakesh D, Whittle S, Sheridan M, Upthegrove R, Cropley V. The neural, stress hormone and inflammatory correlates of childhood deprivation and threat in psychosis: A systematic review. Psychoneuroendocrinology 2023; 157:106371. [PMID: 37651860 DOI: 10.1016/j.psyneuen.2023.106371] [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: 02/20/2023] [Revised: 07/20/2023] [Accepted: 08/18/2023] [Indexed: 09/02/2023]
Abstract
Childhood adversity increases the risk of developing psychosis, but the biological mechanisms involved are unknown. Disaggregating early adverse experiences into core dimensions of deprivation and threat may help to elucidate these mechanisms. We therefore systematically searched the literature investigating associations between deprivation and threat, and neural, immune and stress hormone systems in individuals on the psychosis spectrum. Our search yielded 74 articles, from which we extracted and synthesized relevant findings. While study designs were heterogeneous and findings inconsistent, some trends emerged. In psychosis, deprivation tended to correlate with lower global cortical volume, and some evidence supported threat-related variation in prefrontal cortex morphology. Greater threat exposure was also associated with higher C-reactive protein, and higher and lower cortisol measures. When examined, associations in controls were less evident. Overall, findings indicate that deprivation and threat may associate with partially distinct biological mechanisms in the psychosis spectrum, and that associations may be stronger than in controls. Dimensional approaches may help disentangle the biological correlates of childhood adversity in psychosis, but more studies are needed.
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Affiliation(s)
- Megan Thomas
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Australia.
| | - Divyangana Rakesh
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Australia; Neuroimaging Department, Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, United Kingdom
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Australia
| | - Margaret Sheridan
- Department of Psychology & Neuroscience, University of North Carolina, United States
| | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, United Kingdom; Early Intervention Service, Birmingham Women's and Children's NHS Foundation Trust, United Kingdom
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Australia
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Fan F, Tan S, Liu S, Chen S, Huang J, Wang Z, Yang F, Li CSR, Tan Y. Subcortical structures associated with childhood trauma and perceived stress in schizophrenia. Psychol Med 2023; 53:5654-5662. [PMID: 36154670 DOI: 10.1017/s0033291722002860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Childhood trauma influences the clinical features of schizophrenia. In this study, we examined how childhood trauma and perceived stress are associated with clinical manifestations and subcortical gray matter volumes (GMVs) in patients with schizophrenia. METHODS We recruited 127 patients with schizophrenia and 83 healthy controls for assessment of early childhood trauma, perceived stress, and clinical symptoms. With structural brain imaging, we identified the GMVs of subcortical structures and examined the relationships between childhood trauma, perceived stress, clinical symptoms, and subcortical GMVs. RESULTS Compared to controls, patients with schizophrenia showed higher levels of childhood trauma and perceived stress. Patients with schizophrenia showed significantly smaller amygdala and hippocampus GMVs as well as total cortical GMVs than age-matched controls. Childhood trauma score was significantly correlated with the severity of clinical symptoms, depression, perceived stress, and amygdala GMVs. Perceived stress was significantly correlated with clinical symptoms, depression, and hippocampus and amygdala GMVs. Further, the association between childhood trauma (emotional neglect) and stress coping ability was mediated by right amygdala GMV in patients with schizophrenia. CONCLUSIONS Patients with schizophrenia had more exposure to early-life trauma and poorer stress coping. Both childhood trauma and perceived stress were associated with smaller amygdala volumes. The relationship between early-life trauma and perceived stress was mediated by right amygdala GMV in patients with schizophrenia. These findings together suggest the long-term effects of childhood trauma on perceived stress and the subcortical volumetric correlates of the effects in schizophrenia.
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Affiliation(s)
- Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Shuping Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Shibo Liu
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Song Chen
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Junchao Huang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Zhiren Wang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Fude Yang
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Yunlong Tan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, P. R. China
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Salminen LE, Tubi MA, Bright J, Thomopoulos SI, Wieand A, Thompson PM. Sex is a defining feature of neuroimaging phenotypes in major brain disorders. Hum Brain Mapp 2022; 43:500-542. [PMID: 33949018 PMCID: PMC8805690 DOI: 10.1002/hbm.25438] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 12/12/2022] Open
Abstract
Sex is a biological variable that contributes to individual variability in brain structure and behavior. Neuroimaging studies of population-based samples have identified normative differences in brain structure between males and females, many of which are exacerbated in psychiatric and neurological conditions. Still, sex differences in MRI outcomes are understudied, particularly in clinical samples with known sex differences in disease risk, prevalence, and expression of clinical symptoms. Here we review the existing literature on sex differences in adult brain structure in normative samples and in 14 distinct psychiatric and neurological disorders. We discuss commonalities and sources of variance in study designs, analysis procedures, disease subtype effects, and the impact of these factors on MRI interpretation. Lastly, we identify key problems in the neuroimaging literature on sex differences and offer potential recommendations to address current barriers and optimize rigor and reproducibility. In particular, we emphasize the importance of large-scale neuroimaging initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analyses consortium, the UK Biobank, Human Connectome Project, and others to provide unprecedented power to evaluate sex-specific phenotypes in major brain diseases.
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Affiliation(s)
- Lauren E. Salminen
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Meral A. Tubi
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Joanna Bright
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Sophia I. Thomopoulos
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Alyssa Wieand
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
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Sämann PG, Iglesias JE, Gutman B, Grotegerd D, Leenings R, Flint C, Dannlowski U, Clarke‐Rubright EK, Morey RA, Erp TG, Whelan CD, Han LKM, Velzen LS, Cao B, Augustinack JC, Thompson PM, Jahanshad N, Schmaal L. FreeSurfer
‐based segmentation of hippocampal subfields: A review of methods and applications, with a novel quality control procedure for
ENIGMA
studies and other collaborative efforts. Hum Brain Mapp 2020; 43:207-233. [PMID: 33368865 PMCID: PMC8805696 DOI: 10.1002/hbm.25326] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 11/26/2020] [Accepted: 12/13/2020] [Indexed: 12/11/2022] Open
Abstract
Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013–12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi‐)genetics. Finally, we highlight points where FreeSurfer‐based hippocampal subfield studies may be optimized.
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Affiliation(s)
| | - Juan Eugenio Iglesias
- Centre for Medical Image Computing University College London London UK
- The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital/Harvard Medical School Boston Massachusetts US
- Computer Science and AI Laboratory (CSAIL), Massachusetts Institute of Technology (MIT) Cambridge Massachusetts US
| | - Boris Gutman
- Department of Biomedical Engineering Illinois Institute of Technology Chicago USA
| | | | - Ramona Leenings
- Department of Psychiatry University of Münster Münster Germany
| | - Claas Flint
- Department of Psychiatry University of Münster Münster Germany
- Department of Mathematics and Computer Science University of Münster Germany
| | - Udo Dannlowski
- Department of Psychiatry University of Münster Münster Germany
| | - Emily K. Clarke‐Rubright
- Brain Imaging and Analysis Center, Duke University Durham North Carolina USA
- VISN 6 MIRECC, Durham VA Durham North Carolina USA
| | - Rajendra A. Morey
- Brain Imaging and Analysis Center, Duke University Durham North Carolina USA
- VISN 6 MIRECC, Durham VA Durham North Carolina USA
| | - Theo G.M. Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior University of California Irvine California USA
- Center for the Neurobiology of Learning and Memory University of California Irvine Irvine California USA
| | - Christopher D. Whelan
- Imaging Genetics Center Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Los Angeles California USA
| | - Laura K. M. Han
- Department of Psychiatry Amsterdam University Medical Centers, Vrije Universiteit and GGZ inGeest, Amsterdam Neuroscience Amsterdam The Netherlands
| | - Laura S. Velzen
- Orygen Parkville Australia
- Centre for Youth Mental Health The University of Melbourne Melbourne Australia
| | - Bo Cao
- Department of Psychiatry, Faculty of Medicine & Dentistry University of Alberta Edmonton Canada
| | - Jean C. Augustinack
- The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital/Harvard Medical School Boston Massachusetts US
| | - Paul M. Thompson
- Imaging Genetics Center Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Los Angeles California USA
| | - Neda Jahanshad
- Imaging Genetics Center Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Los Angeles California USA
| | - Lianne Schmaal
- Orygen Parkville Australia
- Centre for Youth Mental Health The University of Melbourne Melbourne Australia
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