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Goltermann J, Winter NR, Meinert S, Sindermann L, Lemke H, Leehr EJ, Grotegerd D, Winter A, Thiel K, Waltemate L, Breuer F, Repple J, Gruber M, Richter M, Teckentrup V, Kroemer NB, Brosch K, Meller T, Pfarr JK, Ringwald KG, Stein F, Heindel W, Jansen A, Kircher T, Nenadić I, Dannlowski U, Opel N, Hahn T. Resting-state functional connectivity patterns associated with childhood maltreatment in a large bicentric cohort of adults with and without major depression. Psychol Med 2023; 53:4720-4731. [PMID: 35754405 PMCID: PMC10388325 DOI: 10.1017/s0033291722001623] [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: 11/08/2021] [Revised: 03/11/2022] [Accepted: 05/13/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Childhood maltreatment (CM) represents a potent risk factor for major depressive disorder (MDD), including poorer treatment response. Altered resting-state connectivity in the fronto-limbic system has been reported in maltreated individuals. However, previous results in smaller samples differ largely regarding localization and direction of effects. METHODS We included healthy and depressed samples [n = 624 participants with MDD; n = 701 healthy control (HC) participants] that underwent resting-state functional MRI measurements and provided retrospective self-reports of maltreatment using the Childhood Trauma Questionnaire. A-priori defined regions of interest [ROI; amygdala, hippocampus, anterior cingulate cortex (ACC)] were used to calculate seed-to-voxel connectivities. RESULTS No significant associations between maltreatment and resting-state connectivity of any ROI were found across MDD and HC participants and no interaction effect with diagnosis became significant. Investigating MDD patients only yielded maltreatment-associated increased connectivity between the amygdala and dorsolateral frontal areas [pFDR < 0.001; η2partial = 0.050; 95%-CI (0.023-0.085)]. This effect was robust across various sensitivity analyses and was associated with concurrent and previous symptom severity. Particularly strong amygdala-frontal associations with maltreatment were observed in acutely depressed individuals [n = 264; pFDR < 0.001; η2partial = 0.091; 95%-CI (0.038-0.166)). Weaker evidence - not surviving correction for multiple ROI analyses - was found for altered supracallosal ACC connectivity in HC individuals associated with maltreatment. CONCLUSIONS The majority of previous resting-state connectivity correlates of CM could not be replicated in this large-scale study. The strongest evidence was found for clinically relevant maltreatment associations with altered adult amygdala-dorsolateral frontal connectivity in depression. Future studies should explore the relevance of this pathway for a maltreated subgroup of MDD patients.
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Affiliation(s)
- Janik Goltermann
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Nils Ralf Winter
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Susanne Meinert
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
- University of Münster, Institute for Translational Neuroscience, Münster, Germany
| | - Lisa Sindermann
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Hannah Lemke
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Elisabeth J. Leehr
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Dominik Grotegerd
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Alexandra Winter
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Katharina Thiel
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Lena Waltemate
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Fabian Breuer
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Jonathan Repple
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Marius Gruber
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Maike Richter
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Vanessa Teckentrup
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Nils B. Kroemer
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
- Department of Psychiatry & Psychotherapy, University of Bonn, Bonn, Germany
| | - Katharina Brosch
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Tina Meller
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | | | | | - Frederike Stein
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Walter Heindel
- University of Münster, Department of Clinical Radiology, Münster, Germany
| | - Andreas Jansen
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Udo Dannlowski
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Nils Opel
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
- University of Münster, Interdisciplinary Centre for Clinical Research (IZKF), Münster, Germany
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Tim Hahn
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
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Li X, Xu M, Jiang R, Li X, Calhoun VD, Zhou X, Sui J. ICA-based Individualized Differential Structure Similarity Networks for Predicting Symptom Scores in Adolescents with Major Depressive Disorder. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-5. [PMID: 38082692 DOI: 10.1109/embc40787.2023.10340456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Major depressive disorder (MDD) is a complex mood disorder characterized by persistent and overwhelming depression. Previous studies have identified large scale structural brain alterations in MDD, yet most are group analyses with atlas-parcellated anatomical regions. Here we proposed a method to measure individual difference by independent component analysis (ICA)-based individual difference structural similarity network (IDSSN). This approach provided a data-adaptive, atlas-free solution that can be applied to new individual subjects. Specifically, we constructed individualized whole-brain structural covariance networks based on network perturbation approach using spatially constrained ICA. First, a set of benchmark independent components (ICs) were generated using gray matter volume (GMV) from all healthy controls. Then individual heterogeneity was obtained by calculating differences and other similarity metrics between ICs derived from "each one patient + all controls" and the benchmark ICs, resulting in 32 imaging features and structural similarity networks for each patient, which can be used for predicting multiple clinical symptoms. We estimated IDSSN for 189 adolescent MDD patients aged 10-20 years and compared them to 112 healthy adolescents. We tested their predictability of the Hamilton Anxiety Scale , the 17-item Hamilton Depression Scale and six clinical syndromes using connectome-based predictive modeling. The prediction results showed that ICA-based IDSSN features reveal more disease-specific information than those using other brain templates. We also found that depression-associated networks mainly involved the default-mode network and visual network. In conclusion, our study proposed an adaptive method that improves the ability to detect GMV deviations and specificity between one individual patient and healthy groups, providing a new perspectives and insights for evaluating individual-level clinical heterogeneity based on brain structures.
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203
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León BE, Peyton L, Essa H, Wieden T, Marion N, Childers WE, Abou-Gharbia M, Choi DS. A novel monobactam lacking antimicrobial activity, MC-100093, reduces sex-specific ethanol preference and depressive-like behaviors in mice. Neuropharmacology 2023; 232:109515. [PMID: 37001726 PMCID: PMC10144181 DOI: 10.1016/j.neuropharm.2023.109515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 02/24/2023] [Accepted: 03/21/2023] [Indexed: 03/30/2023]
Abstract
Several β-lactam derivatives upregulate astrocytic glutamate transporter type 1expression and are known to improve measures in models of mood and alcohol use disorders (AUD) through normalizing glutamatergic states. However, long-term, and high doses of β-lactams may cause adverse side effects for treating mood disorders and AUD. Studies suggest that MC-100093, a novel β-lactam lacking antimicrobial activity, rescues GLT1 expression. Thus, we sought to investigate whether MC-100093 improves affective behaviors and reduces voluntary ethanol drinking. We intraperitoneally administered MC-100093 (50 mg/kg) or vehicle once per day to C57BL/6J male and female mice (8-10 weeks old) over 6 days. We employed the open field test and the elevated plus maze to examine the effect of MC-100093 on anxiety-like behaviors. We assayed MC-100093's effects on depressive-like behaviors using the tail suspension and forced swim tests. Next, utilizing a separate cohort of male and female C57BL6 mice, we assessed the effects MC100093 treatment on voluntary ethanol drinking utilizing the 2-bottle choice continuous access drinking paradigm. After screening and selecting high-drinking mice, we systematically administered MC-100093 (50 mg/kg) or vehicle to the high-drinking mice over 6 days. Overall, we found that MC-100093 treatment resulted in sex-specific pharmacological effects with female mice displaying reduced innate depressive-like behaviors during the tail suspension and force swim testing juxtaposed with male treated mice who displayed no changes in tail suspension and a paradoxical increased depressive-like behavior during the forced swim testing. Additionally, we found that MC100093 treatment reduced female preference for 10% EtOH during the 2-bottle choice continuous access drinking with no effects of MC100093 treatment detected in male mice. Overall, this data suggests sex-specific regulation of innate depressive-like behavior and voluntary EtOH drinking by MC100093 treatment. Western blot analysis of the medial prefrontal cortex and hippocampus revealed no changes in male or female GLT1 protein abundance relative to GAPDH.
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Affiliation(s)
- Brandon Emanuel León
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN, 55905, USA; Regenerative Sciences Program, Center for Regenerative Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Lee Peyton
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN, 55905, USA
| | - Hesham Essa
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN, 55905, USA
| | - Tia Wieden
- Neuroscience Program, Mayo Clinic College of Medicine and Science, MN, 55905, USA
| | - Nicole Marion
- Neuroscience Program, Mayo Clinic College of Medicine and Science, MN, 55905, USA
| | - Wayne E Childers
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, PA, 19140, USA
| | - Magid Abou-Gharbia
- Department of Pharmaceutical Sciences, Temple University School of Pharmacy, Philadelphia, PA, 19140, USA
| | - Doo-Sup Choi
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic College of Medicine and Science, Rochester, MN, 55905, USA; Neuroscience Program, Mayo Clinic College of Medicine and Science, MN, 55905, USA; Department of Psychiatry and Psychology, Mayo Clinic College of Medicine and Science, Rochester, MN, 59905, USA.
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204
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Ma H, Yuan J, Wang Y, Zhang D, Ding Y, Zhang X, Li K, Yang J. ComBat harmonization of radiomics features to improve the diagnostic accuracy of major depressive disorder and subthreshold depression in adolescents with brain multiscale structural MRI. Asian J Psychiatr 2023; 86:103681. [PMID: 37352757 DOI: 10.1016/j.ajp.2023.103681] [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] [Received: 05/08/2023] [Revised: 06/15/2023] [Accepted: 06/19/2023] [Indexed: 06/25/2023]
Affiliation(s)
- Huan Ma
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Kunming 650018, China; Department of Psychiatry, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, China
| | - Jing Yuan
- Department of Psychiatry, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, China
| | - Yao Wang
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Kunming 650018, China
| | - Dafu Zhang
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Kunming 650018, China
| | - Yingying Ding
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Kunming 650018, China
| | - Xiaoyong Zhang
- Clinical Science, Philips Healthcare, Chengdu 610000, China
| | - Kun Li
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Kunming 650018, China.
| | - Jianzhong Yang
- Department of Psychiatry, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, China.
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205
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Musaelyan K, Horowitz MA, McHugh S, Szele FG. Fluoxetine Can Cause Epileptogenesis and Aberrant Neurogenesis in Male Wild-Type Mice. Dev Neurosci 2023; 46:158-166. [PMID: 37302394 DOI: 10.1159/000531478] [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: 09/27/2022] [Accepted: 05/05/2023] [Indexed: 06/13/2023] Open
Abstract
Antidepressants in general, and fluoxetine in particular, increase adult hippocampal neurogenesis (AHN) in mice. Here we asked how the antidepressant fluoxetine affects behavior and AHN in a corticosterone model of depression. In three groups of adult male C57BL/6j mice, we administered either vehicle (VEH), corticosterone (CORT) treatment to induce a depression-like state, or corticosterone plus a standard dose of fluoxetine (CORT+FLX). Following treatment, mice performed the open field test, the novelty suppressed feeding (NSF) test, and the splash test. Neurogenesis was assessed by means of immunohistochemistry using BrdU and neuronal maturation markers. Unexpectedly, 42% of the CORT+FLX-treated mice exhibited severe weight loss, seizures, and sudden death. As expected, the CORT-treated group had altered behaviors compared to the VEH group, but the CORT+FLX mice that survived did not show any behavioral improvement compared to the CORT group. Antidepressants generally increase neurogenesis and here we also found that compared to CORT mice, CORT+FLX mice that survived had a significantly greater density of BrdU+, BrdU+DCX+, and BrdU+NeuN+ cells, suggesting increased neurogenesis. Moreover, the density of BrdU+NeuN+ cells was increased in an aberrant location, the hilus, of CORT+FLX mice, similar to previous studies describing aberrant neurogenesis following seizures. In conclusion, fluoxetine could induce considerable adverse effects in wild-type mice, including seizure-like activity. Fluoxetine-induced neurogenesis increases could be related to this activity; therefore, proneurogenic effects of fluoxetine and other antidepressants, especially in the absence of any behavioral therapeutic effects, should be interpreted with caution.
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Affiliation(s)
- Ksenia Musaelyan
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Mark A Horowitz
- Research and Development Department, North East London NHS Foundation Trust, Ilford, UK
- Department of Psychiatry, University College London, London, UK
| | - Stephen McHugh
- Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Francis G Szele
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
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206
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Wang K, Hu Y, Yan C, Li M, Wu Y, Qiu J, Zhu X. Brain structural abnormalities in adult major depressive disorder revealed by voxel- and source-based morphometry: evidence from the REST-meta-MDD Consortium. Psychol Med 2023; 53:3672-3682. [PMID: 35166200 DOI: 10.1017/s0033291722000320] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
BACKGROUND Neuroimaging studies on major depressive disorder (MDD) have identified an extensive range of brain structural abnormalities, but the exact neural mechanisms associated with MDD remain elusive. Most previous studies were performed with voxel- or surface-based morphometry which were univariate methods without considering spatial information across voxels/vertices. METHODS Brain morphology was investigated using voxel-based morphometry (VBM) and source-based morphometry (SBM) in 1082 MDD patients and 990 healthy controls (HCs) from the REST-meta-MDD Consortium. We first examined group differences in regional grey matter (GM) volumes and structural covariance networks between patients and HCs. We then compared first-episode, drug-naïve (FEDN) patients, and recurrent patients. Additionally, we assessed the effects of symptom severity and illness duration on brain alterations. RESULTS VBM showed decreased GM volume in various regions in MDD patients including the superior temporal cortex, anterior and middle cingulate cortex, inferior frontal cortex, and precuneus. SBM returned differences only in the prefrontal network. Comparisons between FEDN and recurrent MDD patients showed no significant differences by VBM, but SBM showed greater decreases in prefrontal, basal ganglia, visual, and cerebellar networks in the recurrent group. Moreover, depression severity was associated with volumes in the inferior frontal gyrus and precuneus, as well as the prefrontal network. CONCLUSIONS Simultaneous application of VBM and SBM methods revealed brain alterations in MDD patients and specified differences between recurrent and FEDN patients, which tentatively provide an effective multivariate method to identify potential neurobiological markers for depression.
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Affiliation(s)
- KangCheng Wang
- School of Psychology, Shandong Normal University, Jinan, Shandong, China
| | - YuFei Hu
- School of Psychology, Shandong Normal University, Jinan, Shandong, China
| | - ChaoGan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- International Big-Data Center for Depression Research, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - MeiLing Li
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA
| | - YanJing Wu
- Faculty of Foreign Languages, Ningbo University, Ningbo, Zhejiang, China
| | - Jiang Qiu
- Faculty of Psychology, Southwest University, Chongqing 400716, China
| | - XingXing Zhu
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
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207
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Tian YE, Di Biase MA, Mosley PE, Lupton MK, Xia Y, Fripp J, Breakspear M, Cropley V, Zalesky A. Evaluation of Brain-Body Health in Individuals With Common Neuropsychiatric Disorders. JAMA Psychiatry 2023; 80:567-576. [PMID: 37099313 PMCID: PMC10134046 DOI: 10.1001/jamapsychiatry.2023.0791] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 02/15/2023] [Indexed: 04/27/2023]
Abstract
Importance Physical health and chronic medical comorbidities are underestimated, inadequately treated, and often overlooked in psychiatry. A multiorgan, systemwide characterization of brain and body health in neuropsychiatric disorders may enable systematic evaluation of brain-body health status in patients and potentially identify new therapeutic targets. Objective To evaluate the health status of the brain and 7 body systems across common neuropsychiatric disorders. Design, Setting, and Participants Brain imaging phenotypes, physiological measures, and blood- and urine-based markers were harmonized across multiple population-based neuroimaging biobanks in the US, UK, and Australia, including UK Biobank; Australian Schizophrenia Research Bank; Australian Imaging, Biomarkers, and Lifestyle Flagship Study of Ageing; Alzheimer's Disease Neuroimaging Initiative; Prospective Imaging Study of Ageing; Human Connectome Project-Young Adult; and Human Connectome Project-Aging. Cross-sectional data acquired between March 2006 and December 2020 were used to study organ health. Data were analyzed from October 18, 2021, to July 21, 2022. Adults aged 18 to 95 years with a lifetime diagnosis of 1 or more common neuropsychiatric disorders, including schizophrenia, bipolar disorder, depression, generalized anxiety disorder, and a healthy comparison group were included. Main Outcomes and Measures Deviations from normative reference ranges for composite health scores indexing the health and function of the brain and 7 body systems. Secondary outcomes included accuracy of classifying diagnoses (disease vs control) and differentiating between diagnoses (disease vs disease), measured using the area under the receiver operating characteristic curve (AUC). Results There were 85 748 participants with preselected neuropsychiatric disorders (36 324 male) and 87 420 healthy control individuals (40 560 male) included in this study. Body health, especially scores indexing metabolic, hepatic, and immune health, deviated from normative reference ranges for all 4 neuropsychiatric disorders studied. Poor body health was a more pronounced illness manifestation compared to brain changes in schizophrenia (AUC for body = 0.81 [95% CI, 0.79-0.82]; AUC for brain = 0.79 [95% CI, 0.79-0.79]), bipolar disorder (AUC for body = 0.67 [95% CI, 0.67-0.68]; AUC for brain = 0.58 [95% CI, 0.57-0.58]), depression (AUC for body = 0.67 [95% CI, 0.67-0.68]; AUC for brain = 0.58 [95% CI, 0.58-0.58]), and anxiety (AUC for body = 0.63 [95% CI, 0.63-0.63]; AUC for brain = 0.57 [95% CI, 0.57-0.58]). However, brain health enabled more accurate differentiation between distinct neuropsychiatric diagnoses than body health (schizophrenia-other: mean AUC for body = 0.70 [95% CI, 0.70-0.71] and mean AUC for brain = 0.79 [95% CI, 0.79-0.80]; bipolar disorder-other: mean AUC for body = 0.60 [95% CI, 0.59-0.60] and mean AUC for brain = 0.65 [95% CI, 0.65-0.65]; depression-other: mean AUC for body = 0.61 [95% CI, 0.60-0.63] and mean AUC for brain = 0.65 [95% CI, 0.65-0.66]; anxiety-other: mean AUC for body = 0.63 [95% CI, 0.62-0.63] and mean AUC for brain = 0.66 [95% CI, 0.65-0.66). Conclusions and Relevance In this cross-sectional study, neuropsychiatric disorders shared a substantial and largely overlapping imprint of poor body health. Routinely monitoring body health and integrated physical and mental health care may help reduce the adverse effect of physical comorbidity in people with mental illness.
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Affiliation(s)
- Ye Ella Tian
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, Melbourne Medical School, the University of Melbourne, Melbourne, Victoria, Australia
| | - Maria A. Di Biase
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, Melbourne Medical School, the University of Melbourne, Melbourne, Victoria, Australia
| | - Philip E. Mosley
- Clinical Brain Networks Group, Queensland Institute of Medical Research Berghofer Medical Institute, Brisbane, Queensland, Australia
- Queensland Brain Institute, Brisbane, Queensland, Australia
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation Health and Biosecurity, Brisbane, Queensland, Australia
| | - Michelle K. Lupton
- Queensland Institute of Medical Research Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ying Xia
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation Health and Biosecurity, Brisbane, Queensland, Australia
| | - Jurgen Fripp
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation Health and Biosecurity, Brisbane, Queensland, Australia
| | - Michael Breakspear
- Discipline of Psychiatry, College of Health, Medicine and Wellbeing, the University of Newcastle, Newcastle, New South Wales, Australia
- School of Psychological Sciences, College of Engineering, Science and Environment, the University of Newcastle, Newcastle, New South Wales, Australia
| | - Vanessa Cropley
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, Melbourne Medical School, the University of Melbourne, Melbourne, Victoria, Australia
| | - Andrew Zalesky
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, Melbourne Medical School, the University of Melbourne, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, Faculty of Engineering and Information Technology, the University of Melbourne, Melbourne, Victoria, Australia
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Matsumoto J, Ito S, Yamazaki R, Nemoto K, Fukunaga M, Kodaka F, Takano H, Hasegawa N, Miura K, Hashimoto R. No changes in cerebral cortical and subcortical structures before and after SARS-CoV-2 infection: Case reports of a patient with schizophrenia and a patient with major depressive disorder. PCN REPORTS : PSYCHIATRY AND CLINICAL NEUROSCIENCES 2023; 2:e108. [PMID: 38868134 PMCID: PMC11114259 DOI: 10.1002/pcn5.108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/16/2023] [Accepted: 05/19/2023] [Indexed: 06/14/2024]
Affiliation(s)
- Junya Matsumoto
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaJapan
| | - Satsuki Ito
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaJapan
- Department of Developmental and Clinical Psychology, The Division of Human Developmental Sciences, Graduate School of Humanity and SciencesOchanomizu UniversityTokyoJapan
| | - Ryuichi Yamazaki
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaJapan
- Department of PsychiatryThe Jikei University School of MedicineTokyoJapan
| | - Kiyotaka Nemoto
- Department of Psychiatry, Faculty of MedicineUniversity of TsukubaTsukubaJapan
| | - Masaki Fukunaga
- Division of Cerebral IntegrationNational Institute for Physiological SciencesOkazakiJapan
| | - Fumitoshi Kodaka
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaJapan
- Department of PsychiatryThe Jikei University School of MedicineTokyoJapan
| | - Harumasa Takano
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaJapan
- Department of Clinical NeuroimagingIntegrative Brain Imaging Center, National Center of Neurology and PsychiatryKodairaJapan
| | - Naomi Hasegawa
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaJapan
| | - Kenichiro Miura
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaJapan
| | - Ryota Hashimoto
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaJapan
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Wang YB, Song NN, Ding YQ, Zhang L. Neural plasticity and depression treatment. IBRO Neurosci Rep 2023; 14:160-184. [PMID: 37388497 PMCID: PMC10300479 DOI: 10.1016/j.ibneur.2022.09.001] [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: 05/31/2022] [Revised: 07/29/2022] [Accepted: 09/01/2022] [Indexed: 12/08/2022] Open
Abstract
Depression is one of the most common mental disorders, which can lead to a variety of emotional problems and even suicide at its worst. As this neuropsychiatric disorder causes the patients to suffer a lot and function poorly in everyday life, it is imposing a heavy burden on the affected families and the whole society. Several hypotheses have been proposed to elucidate the pathogenesis of depression, such as the genetic mutations, the monoamine hypothesis, the hypothalamic-pituitary-adrenal (HPA) axis hyperactivation, the inflammation and the neural plasticity changes. Among these models, neural plasticity can occur at multiple levels from brain regions, cells to synapses structurally and functionally during development and in adulthood. In this review, we summarize the recent progresses (especially in the last five years) on the neural plasticity changes in depression under different organizational levels and elaborate different treatments for depression by changing the neural plasticity. We hope that this review would shed light on the etiological studies for depression and on the development of novel treatments.
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Affiliation(s)
- Yu-Bing Wang
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center) and Department of Anatomy, Histology and Embryology, Tongji University School of Medicine, Shanghai 200092, China
| | - Ning-Ning Song
- Department of Laboratory Animal Science, Fudan University, Shanghai 200032, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudfan University, Shanghai 200032, China
| | - Yu-Qiang Ding
- Department of Laboratory Animal Science, Fudan University, Shanghai 200032, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudfan University, Shanghai 200032, China
| | - Lei Zhang
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center) and Department of Anatomy, Histology and Embryology, Tongji University School of Medicine, Shanghai 200092, China
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Cullen B, Gameroff MJ, Ward J, Bailey MES, Lyall DM, Lyall LM, MacSweeney N, Murphy E, Sangha N, Shen X, Strawbridge RJ, van Dijk MT, Zhu X, Smith DJ, Talati A, Whalley HC, Cavanagh J, Weissman MM. Cognitive Function in People With Familial Risk of Depression. JAMA Psychiatry 2023; 80:610-620. [PMID: 37074691 PMCID: PMC10116387 DOI: 10.1001/jamapsychiatry.2023.0716] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 02/16/2023] [Indexed: 04/20/2023]
Abstract
Importance Cognitive impairment in depression is poorly understood. Family history of depression is a potentially useful risk marker for cognitive impairment, facilitating early identification and targeted intervention in those at highest risk, even if they do not themselves have depression. Several research cohorts have emerged recently that enable findings to be compared according to varying depths of family history phenotyping, in some cases also with genetic data, across the life span. Objective To investigate associations between familial risk of depression and cognitive performance in 4 independent cohorts with varied depth of assessment, using both family history and genetic risk measures. Design, Setting, and Participants This study used data from the Three Generations at High and Low Risk of Depression Followed Longitudinally (TGS) family study (data collected from 1982 to 2015) and 3 large population cohorts, including the Adolescent Brain Cognitive Development (ABCD) study (data collected from 2016 to 2021), National Longitudinal Study of Adolescent to Adult Health (Add Health; data collected from 1994 to 2018), and UK Biobank (data collected from 2006 to 2022). Children and adults with or without familial risk of depression were included. Cross-sectional analyses were conducted from March to June 2022. Exposures Family history (across 1 or 2 prior generations) and polygenic risk of depression. Main Outcomes and Measures Neurocognitive tests at follow-up. Regression models were adjusted for confounders and corrected for multiple comparisons. Results A total of 57 308 participants were studied, including 87 from TGS (42 [48%] female; mean [SD] age, 19.7 [6.6] years), 10 258 from ABCD (4899 [48%] female; mean [SD] age, 12.0 [0.7] years), 1064 from Add Health (584 [49%] female; mean [SD] age, 37.8 [1.9] years), and 45 899 from UK Biobank (23 605 [51%] female; mean [SD] age, 64.0 [7.7] years). In the younger cohorts (TGS, ABCD, and Add Health), family history of depression was primarily associated with lower performance in the memory domain, and there were indications that this may be partly associated with educational and socioeconomic factors. In the older UK Biobank cohort, there were associations with processing speed, attention, and executive function, with little evidence of education or socioeconomic influences. These associations were evident even in participants who had never been depressed themselves. Effect sizes between familial risk of depression and neurocognitive test performance were largest in TGS; the largest standardized mean differences in primary analyses were -0.55 (95% CI, -1.49 to 0.38) in TGS, -0.09 (95% CI, -0.15 to -0.03) in ABCD, -0.16 (95% CI, -0.31 to -0.01) in Add Health, and -0.10 (95% CI, -0.13 to -0.06) in UK Biobank. Results were generally similar in the polygenic risk score analyses. In UK Biobank, several tasks showed statistically significant associations in the polygenic risk score analysis that were not evident in the family history models. Conclusions and Relevance In this study, whether assessed by family history or genetic data, depression in prior generations was associated with lower cognitive performance in offspring. There are opportunities to generate hypotheses about how this arises through genetic and environmental determinants, moderators of brain development and brain aging, and potentially modifiable social and lifestyle factors across the life span.
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Affiliation(s)
- Breda Cullen
- School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Marc J. Gameroff
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
- Division of Translational Epidemiology, New York State Psychiatric Institute, New York
| | - Joey Ward
- School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Mark E. S. Bailey
- School of Molecular Biosciences, University of Glasgow, Glasgow, United Kingdom
| | - Donald M. Lyall
- School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Laura M. Lyall
- School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Niamh MacSweeney
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Eleanor Murphy
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
- Division of Translational Epidemiology, New York State Psychiatric Institute, New York
| | - Natasha Sangha
- School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Rona J. Strawbridge
- School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
- Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden
| | - Milenna T. van Dijk
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
- Division of Translational Epidemiology, New York State Psychiatric Institute, New York
| | - Xingxing Zhu
- School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Daniel J. Smith
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ardesheer Talati
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
- Division of Translational Epidemiology, New York State Psychiatric Institute, New York
| | - Heather C. Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Jonathan Cavanagh
- School of Infection and Immunity, University of Glasgow, Glasgow, United Kingdom
| | - Myrna M. Weissman
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York
- Division of Translational Epidemiology, New York State Psychiatric Institute, New York
- Mailman School of Public Health, Columbia University, New York, New York
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Vargas TG, Mittal VA. Brain morphometry points to emerging patterns of psychosis, depression, and anxiety vulnerability over a 2-year period in childhood. Psychol Med 2023; 53:3322-3334. [PMID: 37323064 PMCID: PMC10276191 DOI: 10.1017/s0033291721005304] [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] [Indexed: 11/06/2022]
Abstract
BACKGROUND Gray matter morphometry studies have lent seminal insights into the etiology of mental illness. Existing research has primarily focused on adults and then, typically on a single disorder. Examining brain characteristics in late childhood, when the brain is preparing to undergo significant adolescent reorganization and various forms of serious psychopathology are just first emerging, may allow for a unique and highly important perspective of overlapping and unique pathogenesis. METHODS A total of 8645 youth were recruited as part of the Adolescent Brain and Cognitive Development study. Magnetic resonance imaging scans were collected, and psychotic-like experiences (PLEs), depressive, and anxiety symptoms were assessed three times over a 2-year period. Cortical thickness, surface area, and subcortical volume were used to predict baseline symptomatology and symptom progression over time. RESULTS Some features could possibly signal common vulnerability, predicting progression across forms of psychopathology (e.g. superior frontal and middle temporal regions). However, there was a specific predictive value for emerging PLEs (lateral occipital and precentral thickness), anxiety (parietal thickness/area and cingulate), and depression (e.g. parahippocampal and inferior temporal). CONCLUSION Findings indicate common and distinct patterns of vulnerability for varying forms of psychopathology are present during late childhood, before the adolescent reorganization, and have direct relevance for informing novel conceptual models along with early prevention and intervention efforts.
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Affiliation(s)
- Teresa G Vargas
- Northwestern University, Swift Hall 102, 2029 Sheridan Road, Evanston, IL 60201, USA
| | - Vijay A Mittal
- Northwestern University, Swift Hall 102, 2029 Sheridan Road, Evanston, IL 60201, USA
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Rohrsetzer F, Balardin JB, Picon F, Sato JR, Battel L, Viduani A, Manfro PH, Yoon L, Kohrt BA, Fisher HL, Mondelli V, Swartz JR, Kieling C. An MRI-based morphometric and structural covariance network study of Brazilian adolescents stratified by depression risk. REVISTA BRASILEIRA DE PSIQUIATRIA (SAO PAULO, BRAZIL : 1999) 2023; 45. [PMID: 37243979 PMCID: PMC10668308 DOI: 10.47626/1516-4446-2023-3037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 03/29/2023] [Indexed: 05/29/2023]
Abstract
OBJECTIVE To explore differences in regional cortical morphometric structure between adolescents at risk for depression or with current depression. METHODS We analyzed cross-sectional structural neuroimaging data from a sample of 150 Brazilian adolescents classified as low-risk (n=50) or high-risk for depression (n=50) or with current depression (n=50) through a vertex-based approach with measurements of cortical volume, surface area and thickness. Differences between groups in subcortical volumes and in the organization of networks of structural covariance were also explored. RESULTS No significant differences in brain structure between groups were observed in whole-brain vertex-wise cortical volume, surface area or thickness. Also, no significant differences in subcortical volume were observed between risk groups. In relation to the structural covariance network, there was an indication of an increase in the hippocampus betweenness centrality index in the high-risk group network compared to the low-risk and current depression group networks. However, this result was only statistically significant when applying false discovery rate correction for nodes within the affective network. CONCLUSION In an adolescent sample recruited using an empirically based composite risk score, no major differences in brain structure were detected according to the risk and presence of depression.
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Affiliation(s)
- Fernanda Rohrsetzer
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Serviço de Psiquiatria da Infância e Adolescência, Hospital de Clínicas de Porto Alegre, UFRGS, Porto Alegre, RS, Brazil
| | - Joana Bisol Balardin
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Serviço de Psiquiatria da Infância e Adolescência, Hospital de Clínicas de Porto Alegre, UFRGS, Porto Alegre, RS, Brazil
| | - Felipe Picon
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Serviço de Psiquiatria da Infância e Adolescência, Hospital de Clínicas de Porto Alegre, UFRGS, Porto Alegre, RS, Brazil
| | - João Ricardo Sato
- Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, São Paulo, SP, Brazil
| | - Lucas Battel
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Serviço de Psiquiatria da Infância e Adolescência, Hospital de Clínicas de Porto Alegre, UFRGS, Porto Alegre, RS, Brazil
| | - Anna Viduani
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Serviço de Psiquiatria da Infância e Adolescência, Hospital de Clínicas de Porto Alegre, UFRGS, Porto Alegre, RS, Brazil
| | - Pedro Henrique Manfro
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Serviço de Psiquiatria da Infância e Adolescência, Hospital de Clínicas de Porto Alegre, UFRGS, Porto Alegre, RS, Brazil
| | - Leehyun Yoon
- Department of Human Ecology, University of California, Davis, CA, USA
| | - Brandon A. Kohrt
- Division of Global Mental Health, Department of Psychiatry, School of Medicine and Health Sciences, The George Washington University, Washington, DC, USA
| | - Helen L. Fisher
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Economic and Social Research Council, Centre for Society and Mental Health, King’s College London, London, United Kingdom
| | - Valeria Mondelli
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- National Institute for Health Research Mental Health, Biomedical Research Centre, South London and Maudsley National Health Service Foundation Trust, King’s College London, London, United Kingdom
| | - Johnna R. Swartz
- Department of Human Ecology, University of California, Davis, CA, USA
| | - Christian Kieling
- Departamento de Psiquiatria e Medicina Legal, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
- Serviço de Psiquiatria da Infância e Adolescência, Hospital de Clínicas de Porto Alegre, UFRGS, Porto Alegre, RS, Brazil
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Neuchat EE, Bocklud BE, Kingsley K, Barham WT, Luther PM, Ahmadzadeh S, Shekoohi S, Cornett EM, Kaye AD. The Role of Alpha-2 Agonists for Attention Deficit Hyperactivity Disorder in Children: A Review. Neurol Int 2023; 15:697-707. [PMID: 37218982 DOI: 10.3390/neurolint15020043] [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: 04/14/2023] [Revised: 05/08/2023] [Accepted: 05/15/2023] [Indexed: 05/24/2023] Open
Abstract
INTRODUCTION Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders, characterized by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), which is marked by symptoms such as inappropriate levels of inattention, hyperactivity, and impulsivity that can affect academic, social, and personal functioning in children and adolescents. This review summarizes clinical trials demonstrating the effectiveness of Alpha-2 agonists in reducing symptoms of inattention, hyperactivity, and impulsivity in children with ADHD. Studies were identified through a systematic search of PubMed and Cochrane databases. However, these medications' long-term safety and efficacy remain uncertain, with a lack of data on their effects on growth, cardiovascular function, and other adverse events. Further studies are required to determine these medications' optimal dose and treatment duration. METHODS Medications that target the noradrenergic system, such as Alpha-2 agonists, have been increasingly used as a treatment option for ADHD, with guanfacine and clonidine being two of the most commonly used medications. They function by selectively targeting Alpha-2 adrenergic receptors in the brain leading to improved attention and reduced hyperactivity and impulsivity symptoms in children with ADHD. RESULTS Clinical trials have demonstrated the effectiveness of Alpha-2 agonists in treating ADHD in children by reducing symptoms of inattention, hyperactivity, and impulsivity. However, these medications' long-term safety and efficacy still need to be completely understood. Due to a lack of information on the effects of Alpha-2 agonists on growth, cardiovascular function, and other long-term adverse events, more studies must investigate the optimal dose and treatment duration for these medications. CONCLUSIONS Despite these concerns, Alpha-2 agonists remain a valuable treatment option for ADHD in children, especially those unable to tolerate stimulant medications or who have coexisting conditions such as tic disorders. Future research should continue to explore the safety and efficacy of Alpha-2 agonists in the long term. In conclusion, Alpha-2 agonists show promise as a treatment for ADHD in children; however, the safety and efficacy of these drugs in the long term are not yet completely understood. Additional studies are required to investigate the optimal dose and treatment duration for these medications in their use as a treatment for this debilitating disease.
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Affiliation(s)
- Elisa E Neuchat
- School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, LA 71103, USA
| | - Brooke E Bocklud
- School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, LA 71103, USA
| | - Kali Kingsley
- School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, LA 71103, USA
| | - William T Barham
- School of Medicine, Louisiana State University Health Sciences Center at New Orleans, New Orleans, LA 70112, USA
| | - Patrick M Luther
- School of Medicine, Louisiana State University Health Sciences Center at Shreveport, Shreveport, LA 71103, USA
| | - Shahab Ahmadzadeh
- Department of Anesthesiology, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Highway, Shreveport, LA 71103, USA
| | - Sahar Shekoohi
- Department of Anesthesiology, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Highway, Shreveport, LA 71103, USA
| | - Elyse M Cornett
- Department of Anesthesiology, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Highway, Shreveport, LA 71103, USA
| | - Alan D Kaye
- Department of Anesthesiology, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Highway, Shreveport, LA 71103, USA
- Department of Pharmacology, Toxicology, and Neurosciences, Louisiana State University Health Sciences Center at Shreveport, 1501 Kings Highway, Shreveport, LA 71103, USA
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Förster K, Grotegerd D, Dohm K, Lemke H, Enneking V, Meinert S, Redlich R, Heindel W, Bauer J, Kugel H, Suslow T, Ohrmann P, Carballedo A, O'Keane V, Fagan A, Doolin K, McCarthy H, Kanske P, Frodl T, Dannlowski U. Association of hospitalization with structural brain alterations in patients with affective disorders over nine years. Transl Psychiatry 2023; 13:170. [PMID: 37202406 DOI: 10.1038/s41398-023-02452-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 04/17/2023] [Accepted: 04/25/2023] [Indexed: 05/20/2023] Open
Abstract
Repeated hospitalizations are a characteristic of severe disease courses in patients with affective disorders (PAD). To elucidate how a hospitalization during a nine-year follow-up in PAD affects brain structure, a longitudinal case-control study (mean [SD] follow-up period 8.98 [2.20] years) was conducted using structural neuroimaging. We investigated PAD (N = 38) and healthy controls (N = 37) at two sites (University of Münster, Germany, Trinity College Dublin, Ireland). PAD were divided into two groups based on the experience of in-patient psychiatric treatment during follow-up. Since the Dublin-patients were outpatients at baseline, the re-hospitalization analysis was limited to the Münster site (N = 52). Voxel-based morphometry was employed to examine hippocampus, insula, dorsolateral prefrontal cortex and whole-brain gray matter in two models: (1) group (patients/controls)×time (baseline/follow-up) interaction; (2) group (hospitalized patients/not-hospitalized patients/controls)×time interaction. Patients lost significantly more whole-brain gray matter volume of superior temporal gyrus and temporal pole compared to HC (pFWE = 0.008). Patients hospitalized during follow-up lost significantly more insular volume than healthy controls (pFWE = 0.025) and more volume in their hippocampus compared to not-hospitalized patients (pFWE = 0.023), while patients without re-hospitalization did not differ from controls. These effects of hospitalization remained stable in a smaller sample excluding patients with bipolar disorder. PAD show gray matter volume decline in temporo-limbic regions over nine years. A hospitalization during follow-up comes with intensified gray matter volume decline in the insula and hippocampus. Since hospitalizations are a correlate of severity, this finding corroborates and extends the hypothesis that a severe course of disease has detrimental long-term effects on temporo-limbic brain structure in PAD.
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Affiliation(s)
- Katharina Förster
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Verena Enneking
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Ronny Redlich
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychology, University of Halle, Halle, Germany
| | - Walter Heindel
- Department of Radiology, University of Münster and University Hospital Münster, Münster, Germany
| | - Jochen Bauer
- Department of Radiology, University of Münster and University Hospital Münster, Münster, Germany
| | - Harald Kugel
- Department of Radiology, University of Münster and University Hospital Münster, Münster, Germany
| | - Thomas Suslow
- Department of Psychosomatic Medicine and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany
| | | | - Angela Carballedo
- Department of Psychiatry & Trinity College Institute of Neuroscience, University Dublin, Dublin, Ireland
| | - Veronica O'Keane
- Department of Psychiatry & Trinity College Institute of Neuroscience, University Dublin, Dublin, Ireland
| | - Andrew Fagan
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Kelly Doolin
- Department of Psychiatry & Trinity College Institute of Neuroscience, University Dublin, Dublin, Ireland
| | - Hazel McCarthy
- Department of Psychiatry & Trinity College Institute of Neuroscience, University Dublin, Dublin, Ireland
| | - Philipp Kanske
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Thomas Frodl
- Department of Psychiatry & Trinity College Institute of Neuroscience, University Dublin, Dublin, Ireland
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital Aachen, RWTH University Aachen, Aachen, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.
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Klingbeil J, Brandt ML, Stockert A, Baum P, Hoffmann KT, Saur D, Wawrzyniak M. Associations of lesion location, structural disconnection, and functional diaschisis with depressive symptoms post stroke. Front Neurol 2023; 14:1144228. [PMID: 37265471 PMCID: PMC10231644 DOI: 10.3389/fneur.2023.1144228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Accepted: 04/20/2023] [Indexed: 06/03/2023] Open
Abstract
Introduction Post-stroke depressive symptoms (PSDS) are common and relevant for patient outcome, but their complex pathophysiology is ill understood. It likely involves social, psychological and biological factors. Lesion location is a readily available information in stroke patients, but it is unclear if the neurobiological substrates of PSDS are spatially localized. Building on previous analyses, we sought to determine if PSDS are associated with specific lesion locations, structural disconnection and/or localized functional diaschisis. Methods In a prospective observational study, we examined 270 patients with first-ever stroke with the Hospital Anxiety and Depression Scale (HADS) around 6 months post-stroke. Based on individual lesion locations and the depression subscale of the HADS we performed support vector regression lesion-symptom mapping, structural-disconnection-symptom mapping and functional lesion network-symptom-mapping, in a reanalysis of this previously published cohort to infer structure-function relationships. Results We found that depressive symptoms were associated with (i) lesions in the right insula, right putamen, inferior frontal gyrus and right amygdala and (ii) structural disconnection in the right temporal lobe. In contrast, we found no association with localized functional diaschisis. In addition, we were unable to confirm a previously described association between depressive symptom load and a network damage score derived from functional disconnection maps. Discussion Based on our results, and other recent lesion studies, we see growing evidence for a prominent role of right frontostriatal brain circuits in PSDS.
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Affiliation(s)
- Julian Klingbeil
- Neuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - Max-Lennart Brandt
- Neuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - Anika Stockert
- Neuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - Petra Baum
- Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - Karl-Titus Hoffmann
- Department of Neuroradiology, University of Leipzig Medical Center, Leipzig, Germany
| | - Dorothee Saur
- Neuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - Max Wawrzyniak
- Neuroimaging Laboratory, Department of Neurology, University of Leipzig Medical Center, Leipzig, Germany
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Xia Y, Sun H, Hua L, Dai Z, Wang X, Tang H, Han Y, Du Y, Zhou H, Zou H, Yao Z, Lu Q. Spontaneous beta power, motor-related beta power and cortical thickness in major depressive disorder with psychomotor disturbance. Neuroimage Clin 2023; 38:103433. [PMID: 37216848 PMCID: PMC10209543 DOI: 10.1016/j.nicl.2023.103433] [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: 04/06/2023] [Revised: 05/05/2023] [Accepted: 05/11/2023] [Indexed: 05/24/2023]
Abstract
INTRODUCTION The psychomotor disturbance is a common symptom in patients with major depressive disorder (MDD). The neurological mechanisms of psychomotor disturbance are intricate, involving alterations in the structure and function of motor-related regions. However, the relationship among changes in the spontaneous activity, motor-related activity, local cortical thickness, and psychomotor function remains unclear. METHOD A total of 140 patients with MDD and 68 healthy controls performed a simple right-hand visuomotor task during magnetoencephalography (MEG) scanning. All patients were divided into two groups according to the presence of psychomotor slowing. Spontaneous beta power, movement-related beta desynchronization (MRBD), absolute beta power during movement and cortical characteristics in the bilateral primary motor cortex were compared using general linear models with the group as a fixed effect and age as a covariate. Finally, the moderated mediation model was tested to examine the relationship between brain metrics with group differences and psychomotor performance. RESULTS The patients with psychomotor slowing showed higher spontaneous beta power, movement-related beta desynchronization and absolute beta power during movement than patients without psychomotor slowing. Compared with the other two groups, significant decreases were found in cortical thickness of the left primary motor cortex in patients with psychomotor slowing. Our moderated mediation model showed that the increased spontaneous beta power indirectly affected impaired psychomotor performance by abnormal MRBD, and the indirect effects were moderated by cortical thickness. CONCLUSION These results suggest that patients with MDD have aberrant cortical beta activity at rest and during movement, combined with abnormal cortical thickness, contributing to the psychomotor disturbance observed in this patient population.
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Affiliation(s)
- Yi Xia
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hao Sun
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China
| | - Lingling Hua
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing 210096, China
| | - Xiaoqin Wang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hao Tang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Yinglin Han
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Yishan Du
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hongliang Zhou
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Haowen Zou
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China
| | - Zhijian Yao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing 210096, China.
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Zugman A, Alliende L, Medel V, Bethlehem RA, Seidlitz J, Ringlein G, Arango C, Arnatkevičiūtė A, Asmal L, Bellgrove M, Benegal V, Bernardo M, Billeke P, Bosch-Bayard J, Bressan R, Busatto G, Castro M, Chaim-Avancini T, Compte A, Costanzi M, Czepielewski L, Dazzan P, de la Fuente-Sandoval C, Di Forti M, Díaz-Caneja C, María Díaz-Zuluaga A, Du Plessis S, Duran F, Fittipaldi S, Fornito A, Freimer N, Gadelha A, Gama C, Garani R, Garcia-Rizo C, Gonzalez Campo C, Gonzalez-Valderrama A, Guinjoan S, Holla B, Ibañez A, Ivanovic D, Jackowski A, Leon-Ortiz P, Lochner C, López-Jaramillo C, Luckhoff H, Massuda R, McGuire P, Miyata J, Mizrahi R, Murray R, Ozerdem A, Pan P, Parellada M, Phahladira L, Ramirez-Mahaluf J, Reckziegel R, Reis Marques T, Reyes-Madrigal F, Roos A, Rosa P, Salum G, Scheffler F, Schumann G, Serpa M, Stein D, Tepper A, Tiego J, Ueno T, Undurraga J, Undurraga E, Valdes-Sosa P, Valli I, Villarreal M, Winton-Brown T, Yalin N, Zamorano F, Zanetti M, Winkler A, Pine D, Evans-Lacko S, Crossley N. Country-level gender inequality is associated with structural differences in the brains of women and men. Proc Natl Acad Sci U S A 2023; 120:e2218782120. [PMID: 37155867 PMCID: PMC10193926 DOI: 10.1073/pnas.2218782120] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 03/15/2023] [Indexed: 05/10/2023] Open
Abstract
Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women's brains and provide initial evidence for neuroscience-informed policies for gender equality.
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Affiliation(s)
- André Zugman
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch (E & D), National Institute of Mental Health, National Institutes of Health, BethesdaMD20894
| | - Luz María Alliende
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago8330077, Chile
- Department of Psychology, Northwestern University, Evanston, IL60208
| | - Vicente Medel
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago7941169, Chile
| | - Richard A.I. Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, CambridgeCB2 8AH, United Kingdom
- Department of Psychology, University of Cambridge, CambridgeCB2 3EB, United Kingdom
| | - Jakob Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA19104
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children’s Hospital of Philadelphia, Philadelphia, PA19104
- Penn-Children’s Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA19104
| | - Grace Ringlein
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch (E & D), National Institute of Mental Health, National Institutes of Health, BethesdaMD20894
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), School of Medicine, Universidad Complutense, Madrid28009, Spain
| | - Aurina Arnatkevičiūtė
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC3168, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, VIC3168, Australia
| | - Laila Asmal
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town7602, South Africa
| | - Mark Bellgrove
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC3168, Australia
| | - Vivek Benegal
- Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka560029, India
| | - Miquel Bernardo
- Barcelona Clinic Schizophrenia Unit, Hospital Clínic de Barcelona, Departament de Medicina, Institut de Neurociències (UBNeuro), Universitat de Barcelona (UB), Institut d’Investigacions Biomèdiques, August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), Instituto de Salud Carlos III (ISCIII), Barcelona08036, Spain
| | - Pablo Billeke
- Laboratorio de Neurociencia Social y Neuromodulación, Centro de Investigación en Complejidad Social (neuroCICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago7610658, Chile
| | - Jorge Bosch-Bayard
- McGill Centre for Integrative Neuroscience, Ludmer Centre for Neuroinformatics and Mental Health, Montreal Neurological Institute, Montreal, QCH3A 2B4, Canada
- McGill University, Montreal, QCH3A 2B4, Canada
| | - Rodrigo Bressan
- Interdisciplinary Laboratory in Clinical Neuroscience (LiNC), Department of Psychiatry, Federal University of São Paulo, São Paulo04039-032, Brazil
| | - Geraldo F. Busatto
- Departamento e Instituto de Psiquiatria, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo05403-903, Brazil
| | - Mariana N. Castro
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (INAAC), Fleni-Consejo Nacional de Investigaciones Científicas y Técnicas Neurosciences Institute (INEU), Ciudad Autónoma de Buenos AiresC1428, Argentina
- Department of Psychiatry and Mental Health, School of Medicine, University of Buenos Aires, Ciudad Autónoma de Buenos AiresC1114AAD, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ciudad Autónoma de Buenos AiresC1033AAJ, Argentina
| | - Tiffany Chaim-Avancini
- Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas, Faculdade de Medicina Universidade de São Paulo (HCFMUSP), Faculdade de Medicina Universidade de São Paulo, São PauloSP05403-903, Brazil
| | - Albert Compte
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona08036, Spain
| | - Monise Costanzi
- Laboratory of Molecular Psychiatry, Centro de Pesquisa Clínica, Hospital de Clínicas de Porto Alegre, Porto AlegreRS90035-007, Brazil
| | - Leticia Czepielewski
- Laboratory of Molecular Psychiatry, Centro de Pesquisa Clínica, Hospital de Clínicas de Porto Alegre, Porto AlegreRS90035-007, Brazil
- Programa de Pós-Graduação em Psicologia, Instituto Psicologia, Universidade Federal do Rio Grande do Sul, Porto AlegreRS90040-060, Brazil
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, LondonSE5 8AF, United Kingdom
| | - Camilo de la Fuente-Sandoval
- Laboratory of Experimental Psychiatry, Direction of Research, Instituto Nacional de Neurología y Neurocirugía, Mexico City14269, Mexico
| | - Marta Di Forti
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, LondonSE5 8AF, United Kingdom
- National Institute for Health Research (NIHR), Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King’s College London, LondonSE5 8AZ, United Kingdom
| | - Covadonga M. Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), School of Medicine, Universidad Complutense, Madrid28009, Spain
| | - Ana María Díaz-Zuluaga
- Department of Psychiatry, Faculty of Medicine, University of Antioquia, Medellín050011, Colombia
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior Los Angeles, University of California Los Angeles (UCLA), Los Angeles, CA90024
| | - Stefan Du Plessis
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town7602, South Africa
- South African Medical Research Council (SA MRC), Genomics of Brain Disorders Unit, Cape Town7505, South Africa
| | - Fabio L. S. Duran
- Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas, Faculdade de Medicina Universidade de São Paulo (HCFMUSP), Faculdade de Medicina Universidade de São Paulo, São PauloSP05403-903, Brazil
| | - Sol Fittipaldi
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago7941169, Chile
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Victoria, Ciudad Autónoma de Buenos AiresB1644BID, Argentina
- Global Brain Health Institute (GBHI), Trinity College Dublin (TCD), DublinDO2 PN40, Ireland
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA94158
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC3168, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, VIC3168, Australia
| | - Nelson B. Freimer
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior Los Angeles, University of California Los Angeles (UCLA), Los Angeles, CA90024
| | - Ary Gadelha
- Interdisciplinary Laboratory in Clinical Neuroscience (LiNC), Department of Psychiatry, Federal University of São Paulo, São Paulo04039-032, Brazil
| | - Clarissa S. Gama
- Laboratory of Molecular Psychiatry, Centro de Pesquisa Clínica, Hospital de Clínicas de Porto Alegre, Porto AlegreRS90035-007, Brazil
- Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Hospital de Clinicas de Porto Alegre, Porto Alegre, RS90035903, Brazil
| | - Ranjini Garani
- Integrated Program in Neuroscience, McGill University, Montreal, QuebecH3A 1A12B4Canada
| | - Clemente Garcia-Rizo
- Barcelona Clinic Schizophrenia Unit, Hospital Clínic de Barcelona, Departament de Medicina, Institut de Neurociències (UBNeuro), Universitat de Barcelona (UB), Institut d’Investigacions Biomèdiques, August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), Instituto de Salud Carlos III (ISCIII), Barcelona08036, Spain
| | - Cecilia Gonzalez Campo
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ciudad Autónoma de Buenos AiresC1033AAJ, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Victoria, Ciudad Autónoma de Buenos AiresB1644BID, Argentina
| | - Alfonso Gonzalez-Valderrama
- Early Intervention Program, Instituto Psiquiátrico Dr. J. Horwitz Barak, Santiago8431621, Chile
- School of Medicine, Universidad Finis Terrae, Santiago7501015, Chile
| | - Salvador Guinjoan
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ciudad Autónoma de Buenos AiresC1033AAJ, Argentina
- Laureate Institute for Brain Research, Tulsa, OK74136
| | - Bharath Holla
- Department of Integrative Medicine, NIMHANS, Bengaluru, Karnataka560029, India
- Accelerator Program for Discovery in Brain disorders using Stem cells, Department of Psychiatry, NIMHANS, Bengaluru, Karnataka560029, India
| | - Agustín Ibañez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago7941169, Chile
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ciudad Autónoma de Buenos AiresC1033AAJ, Argentina
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Victoria, Ciudad Autónoma de Buenos AiresB1644BID, Argentina
- Global Brain Health Institute (GBHI), Trinity College Dublin (TCD), DublinDO2 PN40, Ireland
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA94158
| | - Daniza Ivanovic
- Laboratorio de Neurociencia Social y Neuromodulación, Centro de Investigación en Complejidad Social (neuroCICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago7610658, Chile
| | - Andrea Jackowski
- Department of Psychiatry, Universidade Federal de São Paulo, São Paulo04038-000, Brazil
- Department of Education, Information and Communications Technology (ICT) and Learning, Østfold University College, Halden1757, Norway
| | - Pablo Leon-Ortiz
- Laboratory of Experimental Psychiatry, Direction of Research, Instituto Nacional de Neurología y Neurocirugía, Mexico City14269, Mexico
| | - Christine Lochner
- South African Medical Research Council (SA MRC) Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Stellenbosch7505, South Africa
| | - Carlos López-Jaramillo
- Department of Psychiatry, Faculty of Medicine, University of Antioquia, Medellín050011, Colombia
| | - Hilmar Luckhoff
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town7602, South Africa
| | - Raffael Massuda
- Department of Psychiatry, Universidade Federal do Paraná (UFPR), CuritibaPR 80060-000, Brazil
| | - Philip McGuire
- Department of Psychiatry, University of Oxford, OxfordOX3 7JX, United Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), University of Oxford, OxfordOX3 9DU, United Kingdom
- NIHR Oxford Health Biomedical Research Centre, OxfordOX3 7JX, United Kingdom
- Oxford HealthNational Health Service (NHS), Foundation Trust, OxfordOX4 4XN, United Kingdom
| | - Jun Miyata
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto606-8507, Japan
| | - Romina Mizrahi
- Integrated Program in Neuroscience, McGill University, Montreal, QuebecH3A 1A12B4Canada
- Clinical and Translational Sciences Lab, McGill University, Douglas Mental Health University Institute, Montreal, QCH4A 1R3, Canada
- Department of Psychiatry, McGill University,Montreal, QCH3A 1A1, Canada
| | - Robin Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, LondonSE5 8AF, United Kingdom
| | - Aysegul Ozerdem
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MinnesotaMN55905
| | - Pedro M. Pan
- Interdisciplinary Laboratory in Clinical Neuroscience (LiNC), Department of Psychiatry, Federal University of São Paulo, São Paulo04039-032, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents, São Paulo04038-000, Brazil
| | - Mara Parellada
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Instituto de Investigación Sanitaria Gregorio Marañón (IISGM), Centro de Investigación Biomédica en Red Salud Mental (CIBERSAM), School of Medicine, Universidad Complutense, Madrid28009, Spain
| | - Lebogan Phahladira
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town7602, South Africa
| | - Juan P. Ramirez-Mahaluf
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago8330077, Chile
| | - Ramiro Reckziegel
- Laboratory of Molecular Psychiatry, Centro de Pesquisa Clínica, Hospital de Clínicas de Porto Alegre, Porto AlegreRS90035-007, Brazil
| | - Tiago Reis Marques
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, LondonSE5 8AF, United Kingdom
| | - Francisco Reyes-Madrigal
- Laboratory of Experimental Psychiatry, Direction of Research, Instituto Nacional de Neurología y Neurocirugía, Mexico City14269, Mexico
| | - Annerine Roos
- South African Medical Research Council (SA MRC) Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town7925, South Africa
| | - Pedro Rosa
- Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas, Faculdade de Medicina Universidade de São Paulo (HCFMUSP), Faculdade de Medicina Universidade de São Paulo, São PauloSP05403-903, Brazil
| | - Giovanni Salum
- Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Hospital de Clinicas de Porto Alegre, Porto Alegre, RS90035903, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents, São Paulo04038-000, Brazil
| | - Freda Scheffler
- South African Medical Research Council (SA MRC) Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town7925, South Africa
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai200433, China
- PONS-Centre, Charité Mental Health, Dept of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin10117, Germany
| | - Mauricio Serpa
- Departamento e Instituto de Psiquiatria, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo05403-903, Brazil
| | - Dan J. Stein
- South African Medical Research Council (SA MRC) Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town7925, South Africa
| | - Angeles Tepper
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago8330077, Chile
| | - Jeggan Tiego
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, VIC3168, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, VIC3168, Australia
| | - Tsukasa Ueno
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto606-8507, Japan
- Integrated Clinical Education Center, Kyoto University Hospital, Kyoto606-8397, Japan
| | - Juan Undurraga
- Early Intervention Program, Instituto Psiquiátrico Dr. J. Horwitz Barak, Santiago8431621, Chile
- Department of Neurology and Psychiatry, Faculty of Medicine, Clínica Alemana Universidad del DesarrolloVitacura, Santiago7650568, Chile
| | - Eduardo A. Undurraga
- Escuela de Gobierno, Pontificia Universidad Católica de Chile, Santiago7820436, Chile
- Research Center for Integrated Disaster Risk Management (CIGIDEN), Santiago7820436, Chile
- Canadian Institute for Advanced Research (CIFAR), Azrieli Global Scholars Program, CIFAR, Toronto, ONM5G 1M1, Canada
| | - Pedro Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu610054, China
- Centro de Neurociencias de Cuba, La Habana11600, Cuba
| | - Isabel Valli
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona08036, Spain
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, LondonSE5 8AF, United Kingdom
| | - Mirta Villarreal
- Grupo de Investigación en Neurociencias Aplicadas a las Alteraciones de la Conducta (INAAC), Fleni-Consejo Nacional de Investigaciones Científicas y Técnicas Neurosciences Institute (INEU), Ciudad Autónoma de Buenos AiresC1428, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ciudad Autónoma de Buenos AiresC1033AAJ, Argentina
- Department of Physics, Universidad de Buenos Aires, Ciudad Autónoma deBuenos AiresC1428EGA, Argentina
| | - Toby T. Winton-Brown
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC3004, Australia
- Department of Psychiatry, Alfred Health, Melbourne, VIC3004, Australia
| | - Nefize Yalin
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, LondonSE5 8AF, United Kingdom
- South London and Maudsley National Health Service (NHS), Foundation Trust, LondonSE5 8AZ, United Kingdom
| | - Francisco Zamorano
- Unidad de Imágenes Cuantitativas Avanzadas, Departamento de Imágenes, Clínica Alemana de Santiago, Universidad del Desarrollo, Santiago7650568, Chile
- Facultad de Ciencias para el Cuidado de la Salud, Universidad San Sebastián, Santiago7510602, Chile
| | - Marcus V. Zanetti
- Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas, Faculdade de Medicina Universidade de São Paulo (HCFMUSP), Faculdade de Medicina Universidade de São Paulo, São PauloSP05403-903, Brazil
- Hospital Sírio-Libanês, São Paulo01308-050, Brazil
| | | | - Anderson M. Winkler
- Department of Human Genetics, University of Texas Rio Grande Valley, Brownsville, Texas TX78520
| | - Daniel S. Pine
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch (E & D), National Institute of Mental Health, National Institutes of Health, BethesdaMD20894
| | - Sara Evans-Lacko
- Care Policy and Evaluation Centre, School of Economics and Political Science, LondonWC2A 2AE, United Kingdom
| | - Nicolas A. Crossley
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago8330077, Chile
- Department of Psychiatry, University of Oxford, OxfordOX3 7JX, United Kingdom
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Ahmad Hariza AM, Mohd Yunus MH, Murthy JK, Wahab S. Clinical Improvement in Depression and Cognitive Deficit Following Electroconvulsive Therapy. Diagnostics (Basel) 2023; 13:diagnostics13091585. [PMID: 37174977 PMCID: PMC10178332 DOI: 10.3390/diagnostics13091585] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/17/2023] [Accepted: 04/24/2023] [Indexed: 05/15/2023] Open
Abstract
Electroconvulsive therapy (ECT) is a long-standing treatment choice for disorders such as depression when pharmacological treatments have failed. However, a major drawback of ECT is its cognitive side effects. While numerous studies have investigated the therapeutic effects of ECT and its mechanism, much less research has been conducted regarding the mechanism behind the cognitive side effects of ECT. As both clinical remission and cognitive deficits occur after ECT, it is possible that both may share a common mechanism. This review highlights studies related to ECT as well as those investigating the mechanism of its outcomes. The process underlying these effects may lie within BDNF and NMDA signaling. Edema in the astrocytes may also be responsible for the adverse cognitive effects and is mediated by metabotropic glutamate receptor 5 and the protein Homer1a.
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Affiliation(s)
- Ahmad Mus'ab Ahmad Hariza
- Department of Physiology, Faculty of Medicine, UKM Medical Centre, Jalan Yaacob Latiff, Bandar Tun Razak, Kuala Lumpur 56000, Malaysia
| | - Mohd Heikal Mohd Yunus
- Department of Physiology, Faculty of Medicine, UKM Medical Centre, Jalan Yaacob Latiff, Bandar Tun Razak, Kuala Lumpur 56000, Malaysia
| | - Jaya Kumar Murthy
- Department of Physiology, Faculty of Medicine, UKM Medical Centre, Jalan Yaacob Latiff, Bandar Tun Razak, Kuala Lumpur 56000, Malaysia
| | - Suzaily Wahab
- Department of Psychiatry, Faculty of Medicine, UKM Medical Centre, Jalan Yaacob Latiff, Bandar Tun Razak, Kuala Lumpur 56000, Malaysia
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Mendes SL, Pinaya WHL, Pan PM, Jackowski AP, Bressan RA, Sato JR. Generalizability of 3D CNN models for age estimation in diverse youth populations using structural MRI. Sci Rep 2023; 13:6886. [PMID: 37106035 PMCID: PMC10140022 DOI: 10.1038/s41598-023-33920-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 04/20/2023] [Indexed: 04/29/2023] Open
Abstract
Recently, several studies have investigated the neurodevelopment of psychiatric disorders using brain data acquired via structural magnetic resonance imaging (sMRI). These analyses have shown the potential of sMRI data to provide a relatively precise characterization of brain structural biomarkers. Despite these advances, a relatively unexplored question is how reliable and consistent a model is when assessing subjects from other independent datasets. In this study, we investigate the performance and generalizability of the same model architecture trained from distinct datasets comprising youths in diverse stages of neurodevelopment and with different mental health conditions. We employed models with the same 3D convolutional neural network (CNN) architecture to assess autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), brain age, and a measure of dimensional psychopathology, the Child Behavior Checklist (CBCL) total score. The investigated datasets include the Autism Brain Imaging Data Exchange II (ABIDE-II, N = 580), Attention Deficit Hyperactivity Disorder (ADHD-200, N = 922), Brazilian High-Risk Cohort Study (BHRCS, N = 737), and Adolescent Brain Cognitive Development (ABCD, N = 11,031). Models' performance and interpretability were assessed within each dataset (for diagnosis tasks) and inter-datasets (for age estimation). Despite the demographic and phenotypic differences of the subjects, all models presented significant estimations for age (p value < 0.001) within and between datasets. In addition, most models showed a moderate to high correlation in age estimation. The results, including the models' brain regions of interest (ROI), were analyzed and discussed in light of the youth neurodevelopmental structural changes. Among other interesting discoveries, we found that less confounded training datasets produce models with higher generalization capacity.
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Affiliation(s)
- Sergio Leonardo Mendes
- Center of Mathematics, Computing, and Cognition, Universidade Federal Do ABC, Rua Arcturus N. 03, São Bernardo Do Campo, SP, 09606-070, Brazil
| | | | - Pedro Mario Pan
- Escola Paulista de Medicina, Universidade Federal de São Paulo, R. Maj. Maragliano (UNIFESP), 241-Vila Mariana, São Paulo, SP, 04017-030, Brazil
| | - Andrea Parolin Jackowski
- Escola Paulista de Medicina, Universidade Federal de São Paulo, R. Maj. Maragliano (UNIFESP), 241-Vila Mariana, São Paulo, SP, 04017-030, Brazil
- Department of Education, ICT and Learning, Østfold University College, Halden, Norway
| | - Rodrigo Affonseca Bressan
- Escola Paulista de Medicina, Universidade Federal de São Paulo, R. Maj. Maragliano (UNIFESP), 241-Vila Mariana, São Paulo, SP, 04017-030, Brazil
| | - João Ricardo Sato
- Center of Mathematics, Computing, and Cognition, Universidade Federal Do ABC, Rua Arcturus N. 03, São Bernardo Do Campo, SP, 09606-070, Brazil
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Hu Y, Zhao C, Zhao H, Qiao J. Abnormal functional connectivity of the nucleus accumbens subregions mediates the association between anhedonia and major depressive disorder. BMC Psychiatry 2023; 23:282. [PMID: 37085792 PMCID: PMC10122393 DOI: 10.1186/s12888-023-04693-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 03/17/2023] [Indexed: 04/23/2023] Open
Abstract
BACKGROUND The nucleus accumbens (Nac) is a crucial brain region in the pathophysiology of major depressive disorder (MDD) patients with anhedonia. However, the relationship between the functional imaging characteristics of Nac subregions and anhedonia remains unclear. Thus, this study aimed to investigate the role of resting-state functional connectivity (rsFC) of the Nac subregions between MDD and anhedonia. METHODS We performed resting-state functional magnetic resonance imaging (fMRI) to measure the rsFC of Nac subregions in 55 MDD patients and 30 healthy controls (HCs). A two-sample t test was performed to determine the brain regions with varying rsFC among Nac subregions between groups. Then, correlation analyses were carried out to investigate the relationships between the aberrant rsFC of Nac subregions and the severity of anhedonia. Furthermore, we constructed a mediation model to explain the role of the aberrant rsFC of Nac subregions between MDD and the severity of anhedonia. RESULTS Compared with the HC group, decreased rsFC of Nac subregions with regions of the prefrontal cortex, insula, lingual gyrus, and visual association cortex was observed in MDD patients. In the MDD group, the rsFC of the right Nac shell-like subregions with the middle frontal gyrus (MFG)/superior frontal gyrus (SFG) was correlated with consummatory anhedonia, and the rsFC of the Nac core-like subdivisions with the inferior frontal gyrus (IFG)/insula and lingual gyrus/visual association cortex was correlated with anticipatory anhedonia. More importantly, the functional alterations in the Nac subregions mediated the association between anhedonia and depression. CONCLUSIONS The present findings suggest that the functional alteration of the Nac subregions mediates the association between MDD and anhedonia, which provides evidence for the hypothesis that MDD patients have neurobiological underpinnings of reward systems that differ from those of HCs.
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Affiliation(s)
- Yanqin Hu
- Department of Psychiatry, First Clinical College, Xuzhou Medical University, Xuzhou, 221000, China
| | - Chaoqi Zhao
- Department of Psychiatry, First Clinical College, Xuzhou Medical University, Xuzhou, 221000, China
| | - Houfeng Zhao
- Department of Psychiatry, the Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, 221000, China.
- Department of Medical Psychology, Second Clinical College, Xuzhou Medical University, Xuzhou, 221000, China.
| | - Juan Qiao
- Department of Psychiatry, the Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, 221000, China.
- Department of Medical Psychology, Second Clinical College, Xuzhou Medical University, Xuzhou, 221000, China.
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Hatch KS, Gao S, Ma Y, Russo A, Jahanshad N, Thompson PM, Adhikari BM, Bruce H, Van der Vaart A, Sotiras A, Kvarta MD, Nichols TE, Schmaal L, Hong LE, Kochunov P. Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease. Hum Brain Mapp 2023; 44:2636-2653. [PMID: 36799565 PMCID: PMC10028678 DOI: 10.1002/hbm.26235] [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: 11/10/2022] [Revised: 01/30/2023] [Accepted: 02/01/2023] [Indexed: 02/18/2023] Open
Abstract
Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD.
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Affiliation(s)
- Kathryn S Hatch
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Alessandro Russo
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Bhim M Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Andrew Van der Vaart
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Aristeidis Sotiras
- Institute of Informatics, University of Washington, School of Medicine, St. Louis, Missouri, USA
- Department of Radiology, University of Washington, School of Medicine, St. Louis, Missouri, USA
| | - Mark D Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Thomas E Nichols
- Nuffield Department of Population Health of the University of Oxford, Oxford, UK
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- Orygen, Parkville, Australia
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
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Huang P, Chan SY, Ngoh ZM, Nadarajan R, Chong YS, Gluckman PD, Chen H, Fortier MV, Tan AP, Meaney MJ. Functional connectivity analysis of childhood depressive symptoms. Neuroimage Clin 2023; 38:103395. [PMID: 37031637 PMCID: PMC10120398 DOI: 10.1016/j.nicl.2023.103395] [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: 10/02/2022] [Revised: 03/26/2023] [Accepted: 03/27/2023] [Indexed: 04/09/2023]
Abstract
BACKGROUND Childhood depression is a highly distinct and prevalent condition with an unknown neurobiological basis. We wish to explore the resting state fMRI data in children for potential associations between neural connectivity and childhood depressive symptoms. METHODS A longitudinal birth cohort study with neuroimaging data obtained at 4.5, 6.0 and 7.5 years of age and the Children Depression Inventory 2 (CDI) administered between 8.5 and 10.5 years was used. The CDI score was used as the dependent variable and tested for correlation, both simple Pearson and network based statistic, with the functional connectivity values obtained from the resting state fMRI. Cross-validated permutation testing with a general linear model was used to validate that the identified functional connections were indeed implicated in childhood depression. RESULTS Ten functional connections and four brain regions (Somatomotor Area B, Temporoparietal Junction, Orbitofrontal Cortex and Insula) were identified as significantly associated with childhood depressive symptoms for girls at 6.0 and 7.5 years. No significant functional connections were found in girls at 4.5 years or for boys at any timepoint. Network based statistic and permutation testing confirmed these findings. CONCLUSIONS This study revealed significant sex-dependent associations of neural connectivity and childhood depressive symptoms. The regions identified are implicated in speech/language, social cognition and information integration and suggest unique pathways to childhood depressive symptoms.
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Affiliation(s)
- Pei Huang
- Singapore Institute for Clinical Sciences, Agency for Science and Technology, Singapore.
| | - Shi Yu Chan
- Singapore Institute for Clinical Sciences, Agency for Science and Technology, Singapore
| | - Zhen Ming Ngoh
- Singapore Institute for Clinical Sciences, Agency for Science and Technology, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ranjani Nadarajan
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences, Agency for Science and Technology, Singapore; Department of Obstetrics & Gynaecology, National University Hospital Singapore, Singapore
| | - Peter D Gluckman
- Singapore Institute for Clinical Sciences, Agency for Science and Technology, Singapore; Centre for Human Evolution, Adaptation and Disease, Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Helen Chen
- Department of Psychological Medicine, KK Women's and Children's Hospital, Singapore; Duke-National University of Singapore, Singapore
| | - Marielle V Fortier
- Singapore Institute for Clinical Sciences, Agency for Science and Technology, Singapore; Department of Diagnostic and Interventional Radiology, KK Women's and Children's Hospital, Singapore
| | - Ai Peng Tan
- Singapore Institute for Clinical Sciences, Agency for Science and Technology, Singapore; Department of Diagnostic Imaging, National University Hospital Singapore, Singapore
| | - Michael J Meaney
- Singapore Institute for Clinical Sciences, Agency for Science and Technology, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Brain - Body Initiative, Agency for Science and Technology, Singapore
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223
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Han S, Zheng R, Li S, Liu L, Wang C, Jiang Y, Wen M, Zhou B, Wei Y, Pang J, Li H, Zhang Y, Chen Y, Cheng J. Progressive brain structural abnormality in depression assessed with MR imaging by using causal network analysis. Psychol Med 2023; 53:2146-2155. [PMID: 34583785 DOI: 10.1017/s0033291721003986] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
BACKGROUND As a neuroprogressive illness, depression is accompanied by brain structural abnormality that extends to many brain regions. However, the progressive structural alteration pattern remains unknown. METHODS To elaborate the progressive structural alteration of depression according to illness duration, we recruited 195 never-treated first-episode patients with depression and 130 healthy controls (HCs) undergoing T1-weighted MRI scans. Voxel-based morphometry method was adopted to measure gray matter volume (GMV) for each participant. Patients were first divided into three stages according to the length of illness duration, then we explored stage-specific GMV alterations and the causal effect relationship between them using causal structural covariance network (CaSCN) analysis. RESULTS Overall, patients with depression presented stage-specific GMV alterations compared with HCs. Regions including the hippocampus, the thalamus and the ventral medial prefrontal cortex (vmPFC) presented GMV alteration at onset of illness. Then as the illness advanced, others regions began to present GMV alterations. These results suggested that GMV alteration originated from the hippocampus, the thalamus and vmPFC then expanded to other brain regions. The results of CaSCN analysis revealed that the hippocampus and the vmPFC corporately exerted causal effect on regions such as nucleus accumbens, the precuneus and the cerebellum. In addition, GMV alteration in the hippocampus was also potentially causally related to that in the dorsolateral frontal gyrus. CONCLUSIONS Consistent with the neuroprogressive hypothesis, our results reveal progressive morphological alteration originating from the vmPFC and the hippocampus and further elucidate possible details about disease progression of depression.
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Affiliation(s)
- Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Shuying Li
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Liang Liu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yu Jiang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Mengmeng Wen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jianyue Pang
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hengfen Li
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
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Dehestani N, Whittle S, Vijayakumar N, Silk TJ. Developmental brain changes during puberty and associations with mental health problems. Dev Cogn Neurosci 2023; 60:101227. [PMID: 36933272 PMCID: PMC10036507 DOI: 10.1016/j.dcn.2023.101227] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Revised: 02/28/2023] [Accepted: 03/08/2023] [Indexed: 03/11/2023] Open
Abstract
BACKGROUND Our understanding of the mechanisms relating pubertal timing to mental health problems via brain development remains rudimentary. METHOD Longitudinal data was sourced from ∼11,500 children from the Adolescent Brain Cognitive Development (ABCD) Study (age 9-13years). We built models of "brain age" and "puberty age" as indices of brain and pubertal development. Residuals from these models were used to index individual differences in brain development and pubertal timing, respectively. Mixed-effects models were used to investigate associations between pubertal timing and regional and global brain development. Mediation models were used to investigate the indirect effect of pubertal timing on mental health problems via brain development. RESULTS Earlier pubertal timing was associated with accelerated brain development, particularly of subcortical and frontal regions in females and subcortical regions in males. While earlier pubertal timing was associated with elevated mental health problems in both sexes, brain age did not predict mental health problems, nor did it mediate associations between pubertal timing and mental health problems. CONCLUSION This study highlights the importance of pubertal timing as a marker associated with brain maturation and mental health problems.
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Affiliation(s)
- Niousha Dehestani
- School of Psychology, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, VIC, Australia.
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, VIC, Australia
| | - Nandita Vijayakumar
- School of Psychology, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia; Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, VIC, Australia
| | - Timothy J Silk
- School of Psychology, Deakin University, 221 Burwood Highway, Burwood, VIC 3125, Australia; Developmental Imaging, Murdoch Children's Research Institute, Parkville 3052, Australia.
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225
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Jha MK, Chin Fatt C, Minhajuddin A, Mayes TL, Trivedi MH. Accelerated Brain Aging in Adults With Major Depressive Disorder Predicts Poorer Outcome With Sertraline: Findings From the EMBARC Study. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:462-470. [PMID: 36179972 PMCID: PMC10177666 DOI: 10.1016/j.bpsc.2022.09.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 09/09/2022] [Accepted: 09/20/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUND Major depressive disorder (MDD) may be associated with accelerated brain aging (higher brain age than chronological age). This report evaluated whether brain age is a clinically useful biomarker by checking its test-retest reliability using magnetic resonance imaging scans acquired 1 week apart and by evaluating the association of accelerated brain aging with symptom severity and antidepressant treatment outcomes. METHODS Brain age was estimated in participants of the EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study using T1-weighted structural magnetic resonance imaging (MDD n = 290; female n = 192; healthy control participants n = 39; female n = 24). Intraclass correlation coefficient was used for baseline-to-week-1 test-retest reliability. Association of baseline Δ brain age (brain age minus chronological age) with Hamilton Depression Rating Scale-17 and Concise Health Risk Tracking Self-Report domains (impulsivity, suicide propensity [measures: pessimism, helplessness, perceived lack of social support, and despair], and suicidal thoughts) were assessed at baseline (linear regression) and during 8-week-long treatment with either sertraline or placebo (repeated-measures mixed models). RESULTS Mean ± SD baseline chronological age, brain age, and Δ brain age were 37.1 ± 13.3, 40.6 ± 13.1, and 3.1 ± 6.1 years in MDD and 37.1 ± 14.7, 38.4 ± 12.9, and 0.6 ± 5.5 years in healthy control groups, respectively. Test-retest reliability was high (intraclass correlation coefficient = 0.98-1.00). Higher baseline Δ brain age in the MDD group was associated with higher baseline impulsivity and suicide propensity and predicted smaller baseline-to-week-8 reductions in Hamilton Depression Rating Scale-17, impulsivity, and suicide propensity with sertraline but not with placebo. CONCLUSIONS Brain age is a reliable and potentially clinically useful biomarker that can prognosticate antidepressant treatment outcomes.
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Affiliation(s)
- Manish K Jha
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Cherise Chin Fatt
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Abu Minhajuddin
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Taryn L Mayes
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Madhukar H Trivedi
- Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Psychiatry, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, Texas.
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Hou J, Liu S, van Wingen G. Increased subcortical brain activity in anxious but not depressed individuals. J Psychiatr Res 2023; 160:38-46. [PMID: 36773346 DOI: 10.1016/j.jpsychires.2023.02.013] [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: 08/22/2022] [Revised: 01/31/2023] [Accepted: 02/06/2023] [Indexed: 02/10/2023]
Abstract
BACKGROUND Anxiety and depressive symptoms usually co-occur. Neuroimaging abnormalities in patients with depression and anxiety disorders are therefore related to a combination of symptoms. Here, we used a large population study to select individuals with anxiety, depressive, or both anxiety and depressive symptoms to identify whether neuroimaging differences are unique or shared between anxiety and depressive symptoms. METHODS We selected four groups of 200 individuals (anxiety, depression, anxiety and depression, controls) from the UK Biobank, matched for age, sex, intelligence, and educational attainment (total N = 800). We extracted the amplitude of low frequency fluctuations (ALFF) from resting-state functional magnetic resonance imaging data, which indexes spontaneous neuronal activity. Group differences were assessed using permutation testing to correct for multiple comparisons, with age, sex, IQ, and head motion as covariates. RESULTS Compared to controls, anxious individuals had higher ALFF values in many subcortical brain regions including the striatum, thalamus, medial temporal lobe, midbrain, pons, as well as the cerebellum. Anxious individuals also showed higher ALFF in the hippocampus, parahippocampal gyrus, cerebellum, and pons compared to individuals with depressive symptoms. No significant differences were found for the depression and combined anxiety/depression groups. Post-hoc tests with largest possible samples showed comparable results in the anxiety group and in the combined group, but still no significant differences for the depression group. CONCLUSIONS Anxiety but not depressive symptoms were associated with increased subcortical activity during rest. This suggest that anxiety symptoms may have the largest contribution to the neuroimaging differences in individuals with depression and anxiety disorders.
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Affiliation(s)
- Jiangyun Hou
- Amsterdam UMC Location University of Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands; Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Shu Liu
- Amsterdam UMC Location University of Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands; Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Guido van Wingen
- Amsterdam UMC Location University of Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands; Amsterdam Neuroscience, Amsterdam, the Netherlands.
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Liu Y, Gao Y, Li M, Qin W, Xie Y, Zhao G, Wang Y, Yang C, Zhang B, Jing Y, Li J. Childhood sexual abuse related to brain activity abnormalities in right inferior temporal gyrus among major depressive disorder. Neurosci Lett 2023; 806:137196. [PMID: 36963746 DOI: 10.1016/j.neulet.2023.137196] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 03/15/2023] [Accepted: 03/20/2023] [Indexed: 03/26/2023]
Abstract
Regional brain activity abnormalities have been reported in major depressive disorder (MDD) with childhood trauma (CT). However, these findings were variable and equivocal. The present study aims to explore further the correlation between CT and the amplitude of low-frequency fluctuations (ALFF) alteration in MDD. In this study, we recruited 60 healthy controls (HCs) and 66 MDD patients to complete resting-state fMRI scans. All MDD patients were evaluated clinical symptoms and childhood trauma experience using the Hamilton Depression Rating Scale-17 (HDRS-17), the Hamilton Anxiety Scale (HAMA), and the Childhood Trauma Questionnaire (CTQ). Compared to HCs, MDD patients demonstrated significantly altered ALFF in the right middle occipital gyrus (MOG), bilateral inferior temporal gyrus (ITG), bilateral cerebellum posterior lobe, bilateral anterior cingulate gyrus (ACC), and bilateral superior frontal gyrus (SFG). More importantly, we found negative correlation between childhood sexual abuse (CSA) scores and ALFF value appeared mainly in the right ITG among MDD patients. After adjusting for covariates (age, gender, mean framewise displacement (FD), HRDS-17, and HAMA scores), this correlation remained significant. Meanwhile, ALFF in the right ITG could distinguish MDD patients with or without CSA (area under the curve (AUC) = 0.713). Our findings revealed that the regional brain activity abnormalities in the right ITG might be a potential biomarker for MDD patients with CSA.
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Affiliation(s)
- Yuan Liu
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Ying Gao
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Meijuan Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yingying Xie
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Guoshu Zhao
- The School of Medicine, Nankai University, Tianjin 300071, China
| | - Yuting Wang
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Chenghao Yang
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Bin Zhang
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Yifan Jing
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Jie Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China.
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228
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Bo T, Li J, Hu G, Zhang G, Wang W, Lv Q, Zhao S, Ma J, Qin M, Yao X, Wang M, Wang GZ, Wang Z. Brain-wide and cell-specific transcriptomic insights into MRI-derived cortical morphology in macaque monkeys. Nat Commun 2023; 14:1499. [PMID: 36932104 PMCID: PMC10023667 DOI: 10.1038/s41467-023-37246-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 03/06/2023] [Indexed: 03/19/2023] Open
Abstract
Integrative analyses of transcriptomic and neuroimaging data have generated a wealth of information about biological pathways underlying regional variability in imaging-derived brain phenotypes in humans, but rarely in nonhuman primates due to the lack of a comprehensive anatomically-defined atlas of brain transcriptomics. Here we generate complementary bulk RNA-sequencing dataset of 819 samples from 110 brain regions and single-nucleus RNA-sequencing dataset, and neuroimaging data from 162 cynomolgus macaques, to examine the link between brain-wide gene expression and regional variation in morphometry. We not only observe global/regional expression profiles of macaque brain comparable to human but unravel a dorsolateral-ventromedial gradient of gene assemblies within the primate frontal lobe. Furthermore, we identify a set of 971 protein-coding and 34 non-coding genes consistently associated with cortical thickness, specially enriched for neurons and oligodendrocytes. These data provide a unique resource to investigate nonhuman primate models of human diseases and probe cross-species evolutionary mechanisms.
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Affiliation(s)
- Tingting Bo
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Neuroscience Center, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Ganlu Hu
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
| | - Ge Zhang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, China
| | - Wei Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Qian Lv
- School of Psychological and Cognitive Sciences; Beijing Key Laboratory of Behavior and Mental Health; IDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Shaoling Zhao
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Junjie Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Meng Qin
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Xiaohui Yao
- Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao, Shandong, China
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, Heilongjiang, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, China.
| | - Guang-Zhong Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Zheng Wang
- School of Psychological and Cognitive Sciences; Beijing Key Laboratory of Behavior and Mental Health; IDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
- School of Biomedical Engineering, Hainan University, Haikou, Hainan, China.
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229
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Luppi AI, Singleton SP, Hansen JY, Bzdok D, Kuceyeski A, Betzel RF, Misic B. Transitions between cognitive topographies: contributions of network structure, neuromodulation, and disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.532981. [PMID: 36993597 PMCID: PMC10055141 DOI: 10.1101/2023.03.16.532981] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Patterns of neural activity underlie human cognition. Transitions between these patterns are orchestrated by the brain's network architecture. What are the mechanisms linking network structure to cognitively relevant activation patterns? Here we implement principles of network control to investigate how the architecture of the human connectome shapes transitions between 123 experimentally defined cognitive activation maps (cognitive topographies) from the NeuroSynth meta-analytic engine. We also systematically incorporate neurotransmitter receptor density maps (18 receptors and transporters) and disease-related cortical abnormality maps (11 neurodegenerative, psychiatric and neurodevelopmental diseases; N = 17 000 patients, N = 22 000 controls). Integrating large-scale multimodal neuroimaging data from functional MRI, diffusion tractography, cortical morphometry, and positron emission tomography, we simulate how anatomically-guided transitions between cognitive states can be reshaped by pharmacological or pathological perturbation. Our results provide a comprehensive look-up table charting how brain network organisation and chemoarchitecture interact to manifest different cognitive topographies. This computational framework establishes a principled foundation for systematically identifying novel ways to promote selective transitions between desired cognitive topographies.
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Affiliation(s)
- Andrea I. Luppi
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | | | - Justine Y. Hansen
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Danilo Bzdok
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
- MILA, Quebec Artificial Intelligence Institute, Montréal, QC, Canada
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, U.S.A
| | - Richard F. Betzel
- Psychological and Brain Sciences, Indiana University, Bloomington, IN, U.S.A
| | - Bratislav Misic
- Montréal Neurological Institute, McGill University, Montréal, QC, Canada
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230
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Long X, Li L, Wang X, Cao Y, Wu B, Roberts N, Gong Q, Kemp GJ, Jia Z. Gray matter alterations in adolescent major depressive disorder and adolescent bipolar disorder. J Affect Disord 2023; 325:550-563. [PMID: 36669567 DOI: 10.1016/j.jad.2023.01.049] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 12/24/2022] [Accepted: 01/11/2023] [Indexed: 01/19/2023]
Abstract
BACKGROUND Gray matter volume (GMV) alterations in several emotion-related brain areas are implicated in mood disorders, but findings have been inconsistent in adolescents with major depressive disorder (MDD) or bipolar disorder (BD). METHODS We conducted a comprehensive meta-analysis of 35 region-of-interest (ROI) and 18 whole-brain voxel-based morphometry (VBM) MRI studies in adolescent MDD and adolescent BD, and indirectly compared the results in the two groups. The effects of age, sex, and other demographic and clinical scale scores were explored using meta-regression analysis. RESULTS In the ROI meta-analysis, right putamen volume was decreased in adolescents with MDD, while bilateral amygdala volume was decreased in adolescents with BD compared to healthy controls (HC). In the whole-brain VBM meta-analysis, GMV was increased in right middle frontal gyrus and decreased in left caudate in adolescents with MDD compared to HC, while in adolescents with BD, GMV was increased in left superior frontal gyrus and decreased in limbic regions compared with HC. MDD vs BD comparison revealed volume alteration in the prefrontal-limbic system. LIMITATION Different clinical features limit the comparability of the samples, and small sample size and insufficient clinical details precluded subgroup analysis or meta-regression analyses of these variables. CONCLUSIONS Distinct patterns of GMV alterations in adolescent MDD and adolescent BD could help to differentiate these two populations and provide potential diagnostic biomarkers.
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Affiliation(s)
- Xipeng Long
- Department of Nuclear Medicine, West China Hospital of Sichuan University, No. 37 GuoXue Xiang, Chengdu 610041, Sichuan, PR China; Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, PR China
| | - Lei Li
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, PR China; Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, PR China
| | - Xiuli Wang
- Department of Clinical Psychiatry, the Fourth People's Hospital of Chengdu, Chengdu 610041, Sichuan, PR China
| | - Yuan Cao
- Department of Nuclear Medicine, West China Hospital of Sichuan University, No. 37 GuoXue Xiang, Chengdu 610041, Sichuan, PR China
| | - Baolin Wu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, PR China; Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, PR China
| | - Neil Roberts
- The Queens Medical Research Institute (QMRI), School of Clinical Sciences, University of Edinburgh, Edinburgh, UK
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, PR China; Department of Radiology, West China Xiamen Hospital of Sichuan University, 699Jinyuan Xi Road, Jimei District, 361021 Xiamen, Fujian, PR China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Center (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
| | - Zhiyun Jia
- Department of Nuclear Medicine, West China Hospital of Sichuan University, No. 37 GuoXue Xiang, Chengdu 610041, Sichuan, PR China; Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, PR China.
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231
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Fang Q, Cai H, Jiang P, Zhao H, Song Y, Zhao W, Yu Y, Zhu J. Transcriptional substrates of brain structural and functional impairments in drug-naive first-episode patients with major depressive disorder. J Affect Disord 2023; 325:522-533. [PMID: 36657492 DOI: 10.1016/j.jad.2023.01.051] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 12/30/2022] [Accepted: 01/11/2023] [Indexed: 01/18/2023]
Abstract
BACKGROUND Despite remarkable success in identifying genetic risk factors for depression, there are still open questions about the exact genetic mechanisms underlying certain disease phenotypes, such as brain structural and functional impairments. METHODS Comprehensive multi-modal neuroimaging meta-analyses were conducted to examine changes in brain structure and function in drug-naive first-episode patients with major depressive disorder (DF-MDD). Combined with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were performed to identify genes whose expression related to these brain structural and functional changes, followed by a range of gene functional signature analyses. RESULTS Meta-analyses revealed gray matter atrophy in the insula, temporal pole, cerebellum and postcentral gyrus, and a complex pattern of hyper-function in the temporal pole and hypo-function in the cuneus/precuneus, angular gyrus and lingual gyrus in DF-MDD. Moreover, these brain structural and functional changes were spatially associated with the expression of 1194 and 1733 genes, respectively. Importantly, there were commonalities and differences in the two gene sets and their functional signatures including functional enrichment, specific expression, behavioral relevance, and constructed protein-protein interaction networks. LIMITATIONS The results merit further verification using a large sample of DF-MDD. CONCLUSIONS Our findings not only corroborate the polygenic nature of depression, but also suggest common and distinct genetic modulations of brain structural and functional impairments in this disorder.
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Affiliation(s)
- Qian Fang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Huanhuan Cai
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Ping Jiang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Han Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yu Song
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Wenming Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China.
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; Research Center of Clinical Medical Imaging, Anhui Province, Hefei 230032, China; Anhui Provincial Institute of Translational Medicine, Hefei 230032, China.
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232
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Yang H, Wu G, Li Y, Ma Y, Chen R, Pines A, Xu T, Sydnor VJ, Satterthwaite TD, Cui Z. Connectional Hierarchy in Human Brain Revealed by Individual Variability of Functional Network Edges. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.08.531800. [PMID: 36945479 PMCID: PMC10028904 DOI: 10.1101/2023.03.08.531800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
The human cerebral cortex is connected by intricate inter-areal wiring at the macroscale. The cortical hierarchy from primary sensorimotor to higher-order association areas is a unifying organizational principle across various neurobiological properties; however, previous studies have not clarified whether the connections between cortical regions exhibit a similar hierarchical pattern. Here, we identify a connectional hierarchy indexed by inter-individual variability of functional connectivity edges, which continuously progresses along a hierarchical gradient from within-network connections to between-network edges connecting sensorimotor and association networks. We found that this connectional hierarchy of variability aligns with both hemodynamic and electromagnetic connectivity strength and is constrained by structural connectivity strength. Moreover, the patterning of connectional hierarchy is related to inter-regional similarity in transcriptional and neurotransmitter receptor profiles. Using the Neurosynth cognitive atlas and cortical vulnerability maps in 13 brain disorders, we found that the connectional hierarchy of variability is associated with similarity networks of cognitive relevance and that of disorder vulnerability. Finally, we found that the prominence of this hierarchical gradient of connectivity variability declines during youth. Together, our results reveal a novel hierarchal organizational principle at the connectional level that links multimodal and multiscale human connectomes to individual variability in functional connectivity.
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Affiliation(s)
- Hang Yang
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Guowei Wu
- Chinese Institute for Brain Research, Beijing, 102206, China
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yaoxin Li
- Chinese Institute for Brain Research, Beijing, 102206, China
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Yiyao Ma
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Runsen Chen
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Adam Pines
- Psychiatry and Behavioral Sciences, Stanford School of Medicine, Stanford University, Stanford, California, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Valerie J. Sydnor
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D. Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing, 102206, China
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233
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Seitz-Holland J, Mulsant BH, Reynolds CF, Blumberger DM, Karp JF, Butters MA, Mendes-Silva AP, Vieira EL, Tseng G, Lenze EJ, Diniz BS. Major depression, physical health and molecular senescence markers abnormalities. NATURE. MENTAL HEALTH 2023; 1:200-209. [PMID: 39483500 PMCID: PMC11527398 DOI: 10.1038/s44220-023-00033-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 02/10/2023] [Indexed: 11/03/2024]
Abstract
Previous studies suggested the role of cellular senescence in late-life depression (LLD). However, it is unclear how this finding relates to common features of LLD, such as medical and cognitive problems. We applied factor analyses to an extensive battery of clinical variables in 426 individuals with LLD. Here we tested the relationship between these factors, age and sex, with an index of cellular senescence based on 22 senescence-associated secretory phenotype proteins. We found four factors: 'depression and anxiety severity', 'cognitive functioning', 'cardiovascular and cardiometabolic health' and 'blood pressure'. A higher senescence-associated secretory phenotype index was associated with poorer 'cognitive functioning' and 'cardiovascular and cardiometabolic health' but not with 'depression and anxiety severity'. These findings highlight the role of cellular senescence in poorer physical and cognitive health in LLD. They are consonant with the viewpoint that co-occurring medical burdens and their associated disabilities are part of a phenotype of accelerated ageing in LLD.
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Affiliation(s)
- Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Benoit H. Mulsant
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Charles F. Reynolds
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Daniel M. Blumberger
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Jordan F. Karp
- Department of Psychiatry, The University of Arizona College of Medicine, Tucson, AZ, USA
| | - Meryl A. Butters
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - Erica L. Vieira
- Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - George Tseng
- Department of Biostatistics, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA
| | - Eric J. Lenze
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Breno S. Diniz
- UConn Center on Aging, University of Connecticut, Farmington, CT, USA
- Department of Psychiatry, UConn School of Medicine, Farmington, CT, USA
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234
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Li M, Wu F, Cao Y, Jiang X, Kong L, Tang Y. Abnormal white matter integrity in Papez circuit in first-episode medication-naive adults with anxious depression: A combined voxel-based analysis and region of interest study. J Affect Disord 2023; 324:489-495. [PMID: 36610591 DOI: 10.1016/j.jad.2022.12.149] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 12/25/2022] [Accepted: 12/31/2022] [Indexed: 01/06/2023]
Abstract
BACKGROUND Anxious depression is one of the subtypes of major depressive disorder (MDD), usually defined as "patients with MDD and high levels of anxiety symptoms". Compared to non-anxious MDD (naMDD), patients with anxious MDD (aMDD) have more severe depressive symptoms and suicidal ideation, worse treatment outcomes and remission rates, and poorer prognosis. Current research suggests that the Papez circuit is an important brain structure closely related to emotion, memory, and cognition. This study applied DTI to explore the altered white matter integrity in Papez circuit of patients with aMDD. METHODS DTI data were acquired from 30 medication-naive outpatients with naMDD and 55 with aMDD and 88 demographically similar healthy control (HC) subjects. Voxel-based analysis (VBM) and region of interest (ROI) analysis were conducted to explore the significant difference of fractional anisotropy (FA) values among 3 groups. Pearson's correlations were performed to analyze the correlation between FA values and the score of HAMA-14 and HAMD-17. RESULTS We found that aMDD patients had significantly higher FA values in left fornix (belong to Papez circuit) and left posterior thalamic radiation and right anterior corona radiata (belong to limbic-thalamo-cortical circuitry) compared with HC. And there was variability in the white matter integrity in right posterior thalamic radiation (belong to limbic-thalamo-cortical circuitry) and left fornix (belong to Papez circuit) between aMDD and naMDD patients. LIMITATIONS The cross-sectional study and the population vary between aMDD group and naMDD group are limitations. CONCLUSIONS Abnormal white matter integrity in Papez circuit and Limbic-Thalamo-Cortical circuitry may play an important role in the neuropathology of aMDD and might help to identify aMDD.
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Affiliation(s)
- Mengxue Li
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China
| | - Feng Wu
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China
| | - Yang Cao
- Shenyang Mental Health Center, Shenyang 110168, Liaoning, China
| | - Xiaowei Jiang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China
| | - Lingtao Kong
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China.
| | - Yanqing Tang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang 110001, Liaoning, China
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235
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Constantinides C, Han LKM, Alloza C, Antonucci LA, Arango C, Ayesa-Arriola R, Banaj N, Bertolino A, Borgwardt S, Bruggemann J, Bustillo J, Bykhovski O, Calhoun V, Carr V, Catts S, Chung YC, Crespo-Facorro B, Díaz-Caneja CM, Donohoe G, Plessis SD, Edmond J, Ehrlich S, Emsley R, Eyler LT, Fuentes-Claramonte P, Georgiadis F, Green M, Guerrero-Pedraza A, Ha M, Hahn T, Henskens FA, Holleran L, Homan S, Homan P, Jahanshad N, Janssen J, Ji E, Kaiser S, Kaleda V, Kim M, Kim WS, Kirschner M, Kochunov P, Kwak YB, Kwon JS, Lebedeva I, Liu J, Mitchie P, Michielse S, Mothersill D, Mowry B, de la Foz VOG, Pantelis C, Pergola G, Piras F, Pomarol-Clotet E, Preda A, Quidé Y, Rasser PE, Rootes-Murdy K, Salvador R, Sangiuliano M, Sarró S, Schall U, Schmidt A, Scott RJ, Selvaggi P, Sim K, Skoch A, Spalletta G, Spaniel F, Thomopoulos SI, Tomecek D, Tomyshev AS, Tordesillas-Gutiérrez D, van Amelsvoort T, Vázquez-Bourgon J, Vecchio D, Voineskos A, Weickert CS, Weickert T, Thompson PM, Schmaal L, van Erp TGM, Turner J, Cole JH, Dima D, Walton E. Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium. Mol Psychiatry 2023; 28:1201-1209. [PMID: 36494461 PMCID: PMC10005935 DOI: 10.1038/s41380-022-01897-w] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 10/14/2022] [Accepted: 11/17/2022] [Indexed: 12/13/2022]
Abstract
Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.
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Affiliation(s)
| | - Laura K M Han
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
- Orygen, Parkville, VIC, Australia
- Department of Psychiatry, Amsterdam University Medical Centers, Vrije Universiteit and GGZ inGeest, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Linda Antonella Antonucci
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians Universität-Munich, Munich, Germany
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Rosa Ayesa-Arriola
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Nerisa Banaj
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Alessandro Bertolino
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Stefan Borgwardt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
- Department of Psychiatry, Psychosomatics and Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Jason Bruggemann
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Juan Bustillo
- Department of Psychiatry, University of New Mexico, Albuquerque, NM, USA
| | - Oleg Bykhovski
- Department of Psychiatry, Psychiatric University Hospital (UPK), University of Basel, Basel, Switzerland
- Division of Addiction Medicine, Centre Hospitalier des Quatre Villes, St. Cloud, France
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
| | - Vaughan Carr
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
- Department of Psychiatry, Monash University, Clayton, VIC, Australia
| | - Stanley Catts
- School of Medicine, University of Queensland, Herston, QLD, Australia
| | - Young-Chul Chung
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Department of Psychiatry, Jeonbuk National University Hospital, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Benedicto Crespo-Facorro
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Hospital Universitario Virgen del Rocío, IBiS-CSIC, Universidad de Sevilla, Seville, Spain
| | - Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Gary Donohoe
- Centre for Neuroimaging and Cognitive Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - Stefan Du Plessis
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
- Stellenbosch University Genomics of Brain Disorders Research Unit, South African Medical Research Council, Cape Town, South Africa
| | - Jesse Edmond
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Germany
| | - Robin Emsley
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Paola Fuentes-Claramonte
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain
| | - Foivos Georgiadis
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
| | - Melissa Green
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain
- Hospital Benito Menni CASM, Sant Boi de Llobregat, Catalonia, Spain
| | - Minji Ha
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Frans A Henskens
- School of Medicine & Public Health, The University of Newcastle, Newcastle, NSW, Australia
- Priority Research Centre for Health Behaviour, The University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Laurena Holleran
- Centre for Neuroimaging and Cognitive Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - Stephanie Homan
- Psychiatric University Hospital Zurich, Zurich, Switzerland
- Department of Experimental Psychopathology and Psychotherapy, University of Zurich, Zurich, Switzerland
| | - Philipp Homan
- Psychiatric University Hospital Zurich, Zurich, Switzerland
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, IiSGM, CIBERSAM, School of Medicine, Universidad Complutense, Madrid, Spain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
| | - Ellen Ji
- Psychiatric University Hospital Zurich, Zurich, Switzerland
| | - Stefan Kaiser
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland
| | | | - Minah Kim
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
| | - Woo-Sung Kim
- Department of Psychiatry, Jeonbuk National University, Medical School, Jeonju, Korea
- Research Institute of Clinical Medicine of Jeonbuk National University-Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Korea
| | - Matthias Kirschner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland
- Division of Adult Psychiatry, Department of Psychiatry, Geneva University Hospitals, Geneva, Switzerland
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Yoo Bin Kwak
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Jun Soo Kwon
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
| | | | - Jingyu Liu
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
- Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - Patricia Mitchie
- Hunter Medical Research Institute, Newcastle, NSW, Australia
- School of Psychological Sciences, University of Newcastle, Callaghan, NSW, Australia
| | - Stijn Michielse
- Department of Neurosurgery, School of Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - David Mothersill
- Centre for Neuroimaging and Cognitive Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
- Department of Psychology, School of Business, National College of Ireland, Dublin, Ireland
| | - Bryan Mowry
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- The Queensland Centre for Mental Health Research, The University of Queensland, Brisbane, QLD, Australia
| | - Víctor Ortiz-García de la Foz
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Carlton South, VIC, Australia
- Florey Institute of Neuroscience & Mental Health, Parkville, VIC, Australia
| | - Giulio Pergola
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Edith Pomarol-Clotet
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - Yann Quidé
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Paul E Rasser
- Hunter Medical Research Institute, Newcastle, NSW, Australia
- Priority Centre for Brain & Mental Health Research, The University of Newcastle, Newcastle, NSW, Australia
| | - Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, USA
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Raymond Salvador
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain
| | - Marina Sangiuliano
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
| | - Salvador Sarró
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Catalonia, Spain
| | - Ulrich Schall
- Hunter Medical Research Institute, Newcastle, NSW, Australia
- Priority Centre for Brain & Mental Health Research, The University of Newcastle, Newcastle, NSW, Australia
| | - André Schmidt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Pierluigi Selvaggi
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Filip Spaniel
- National Institute of Mental Health, Klecany, Czech Republic
- Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - David Tomecek
- National Institute of Mental Health, Klecany, Czech Republic
- Institute of Computer Science, Czech Academy of Sciences, Prague, Czech Republic
- Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | | | - Diana Tordesillas-Gutiérrez
- Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Santander, Spain
- Advanced Computation and e-Science, Instituto de Física de Cantabria CSIC, Santander, Spain
| | - Therese van Amelsvoort
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, The Netherlands
| | - Javier Vázquez-Bourgon
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Spain
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IDIVAL, School of Medicine, University of Cantabria, Santander, Spain
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Aristotle Voineskos
- Campbell Family Mental Health Research Institute, CAMH, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Cynthia S Weickert
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
- Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Thomas Weickert
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
- Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Lianne Schmaal
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA
| | - Jessica Turner
- Department of Psychology, Georgia State University, Atlanta, GA, USA
- Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - James H Cole
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Dementia Research Centre, Queen Square, Institute of Neurology, University College London, London, UK
| | - Danai Dima
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychology, School of Arts and Social Sciences, City, University of London, London, UK
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK.
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236
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Kim J, Lee C, Kang Y, Kang W, Kim A, Tae WS, Ham BJ, Chang J, Han KM. Childhood Sexual Abuse and Cortical Thinning in Adults With Major Depressive Disorder. Psychiatry Investig 2023; 20:255-261. [PMID: 36990669 PMCID: PMC10064205 DOI: 10.30773/pi.2022.0314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 12/27/2022] [Indexed: 03/31/2023] Open
Abstract
OBJECTIVE A growing body of evidence reports on the effect of different types of childhood abuse on the structural and functional architecture of the brain. In the present study, we aimed to investigate the differences in cortical thickness according to specific types of childhood abuse between patients with major depressive disorder (MDD) and healthy controls (HCs). METHODS A total of 61 patients with MDD and 98 HCs were included in this study. All participants underwent T1-weighted magnetic resonance imaging, and the occurrence of childhood abuse was assessed using the Childhood Trauma Questionnaire. We investigated the association between whole-brain cortical thickness and exposure to any type of childhood abuse and specific type of childhood abuse in the total sample using the FreeSurfer software. RESULTS No significant difference was reported in the cortical thickness between the MDD and HC groups nor between the "any abuse" and "no abuse" groups. Compared to no exposure to childhood sexual abuse (CSA), exposure to CSA was significantly associated with cortical thinning in the left rostral middle frontal gyrus (p=0.00020), left (p=0.00240), right fusiform gyri (p=0.00599), and right supramarginal gyrus (p=0.00679). CONCLUSION Exposure to CSA may lead to cortical thinning of the dorsolateral prefrontal cortex, which is deeply involved in emotion regulation, to a greater extent than other types of childhood abuse.
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Affiliation(s)
- Jinyi Kim
- Department of Psychiatry, Seoul Metropolitan Eunpyeong Hospital, Seoul, Republic of Korea
| | - Changju Lee
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Youbin Kang
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Wooyoung Kang
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Aram Kim
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Woo-Suk Tae
- Brain Convergence Research Center, Korea University, Seoul, Republic of Korea
| | - Byung-Joo Ham
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
- Brain Convergence Research Center, Korea University, Seoul, Republic of Korea
| | - Jisoon Chang
- Department of Psychiatry, Seoul Metropolitan Eunpyeong Hospital, Seoul, Republic of Korea
| | - Kyu-Man Han
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
- Brain Convergence Research Center, Korea University, Seoul, Republic of Korea
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237
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Ge R, Sassi R, Yatham LN, Frangou S. Neuroimaging profiling identifies distinct brain maturational subtypes of youth with mood and anxiety disorders. Mol Psychiatry 2023; 28:1072-1078. [PMID: 36577839 PMCID: PMC10005933 DOI: 10.1038/s41380-022-01925-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 12/07/2022] [Accepted: 12/13/2022] [Indexed: 12/29/2022]
Abstract
Mood and anxiety disorders typically begin in adolescence and have overlapping clinical features but marked inter-individual variation in clinical presentation. The use of multimodal neuroimaging data may offer novel insights into the underlying brain mechanisms. We applied Heterogeneity Through Discriminative Analysis (HYDRA) to measures of regional brain morphometry, neurite density, and intracortical myelination to identify subtypes of youth, aged 9-10 years, with mood and anxiety disorders (N = 1931) compared to typically developing youth (N = 2823). We identified three subtypes that were robust to permutation testing and sample composition. Subtype 1 evidenced a pattern of imbalanced cortical-subcortical maturation compared to the typically developing group, with subcortical regions lagging behind prefrontal cortical thinning and myelination and greater cortical surface expansion globally. Subtype 2 displayed a pattern of delayed cortical maturation indicated by higher cortical thickness and lower cortical surface area expansion and myelination compared to the typically developing group. Subtype 3 showed evidence of atypical brain maturation involving globally lower cortical thickness and surface coupled with higher myelination and neural density. Subtype 1 had superior cognitive function in contrast to the other two subtypes that underperformed compared to the typically developing group. Higher levels of parental psychopathology, family conflict, and social adversity were common to all subtypes, with subtype 3 having the highest burden of adverse exposures. These analyses comprehensively characterize pre-adolescent mood and anxiety disorders, the biopsychosocial context in which they arise, and lay the foundation for the examination of the longitudinal evolution of the subtypes identified as the study sample transitions through adolescence.
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Affiliation(s)
- Ruiyang Ge
- Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.,Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Roberto Sassi
- Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.,Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.,BC Children's Hospital, Vancouver, BC, Canada
| | - Lakshmi N Yatham
- Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada.,Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Sophia Frangou
- Djavad Mowafaghian Centre for Brain Health, Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada. .,Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada. .,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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238
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Liu S, Abdellaoui A, Verweij KJH, van Wingen GA. Gene Expression has Distinct Associations with Brain Structure and Function in Major Depressive Disorder. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2205486. [PMID: 36638259 PMCID: PMC9982587 DOI: 10.1002/advs.202205486] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 12/07/2022] [Indexed: 06/17/2023]
Abstract
Major depressive disorder (MDD) is associated with structural and functional brain abnormalities. MDD as well as brain anatomy and function are influenced by genetic factors, but the role of gene expression remains unclear. Here, this work investigates how cortical gene expression contributes to structural and functional brain abnormalities in MDD. This work compares the gray matter volume and resting-state functional measures in a Chinese sample of 848 MDD patients and 749 healthy controls, and these case-control differences are then associated with cortical variation of gene expression. While whole gene expression is positively associated with structural abnormalities, it is negatively associated with functional abnormalities. This work observes the relationships of expression levels with brain abnormalities for individual genes, and found that transcriptional correlates of brain structure and function show opposite relations with gene dysregulation in postmortem cortical tissue from MDD patients. This work further identifies genes that are positively or negatively related to structural abnormalities as well as functional abnormalities. The MDD-related genes are enriched for brain tissue, cortical cells, and biological pathways. These findings suggest that distinct genetic mechanisms underlie structural and functional brain abnormalities in MDD, and highlight the importance of cortical gene expression for the development of cortical abnormalities.
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Affiliation(s)
- Shu Liu
- Amsterdam UMC locationUniversity of AmsterdamDepartment of PsychiatryAmsterdam Neuroscience, AmsterdamMeibergdreef 5Amsterdam1100 DDThe Netherlands
| | - Abdel Abdellaoui
- Amsterdam UMC locationUniversity of AmsterdamDepartment of PsychiatryAmsterdam Neuroscience, AmsterdamMeibergdreef 5Amsterdam1100 DDThe Netherlands
| | - Karin J. H. Verweij
- Amsterdam UMC locationUniversity of AmsterdamDepartment of PsychiatryAmsterdam Neuroscience, AmsterdamMeibergdreef 5Amsterdam1100 DDThe Netherlands
| | - Guido A. van Wingen
- Amsterdam UMC locationUniversity of AmsterdamDepartment of PsychiatryAmsterdam Neuroscience, AmsterdamMeibergdreef 5Amsterdam1100 DDThe Netherlands
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239
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Cao T, Pang JC, Segal A, Chen YC, Aquino KM, Breakspear M, Fornito A. Mode-based morphometry: A multiscale approach to mapping human neuroanatomy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.26.529328. [PMID: 36909539 PMCID: PMC10002616 DOI: 10.1101/2023.02.26.529328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/02/2023]
Abstract
Voxel-based morphometry (VBM) and surface-based morphometry (SBM) are two widely used neuroimaging techniques for investigating brain anatomy. These techniques rely on statistical inferences at individual points (voxels or vertices), clusters of points, or a priori regions-of-interest. They are powerful tools for describing brain anatomy, but offer little insights into the generative processes that shape a particular set of findings. Moreover, they are restricted to a single spatial resolution scale, precluding the opportunity to distinguish anatomical variations that are expressed across multiple scales. Drawing on concepts from classical physics, here we develop an approach, called mode-based morphometry (MBM), that can describe any empirical map of anatomical variations in terms of the fundamental, resonant modes--eigenmodes--of brain anatomy, each tied to a specific spatial scale. Hence, MBM naturally yields a multiscale characterization of the empirical map, affording new opportunities for investigating the spatial frequency content of neuroanatomical variability. Using simulated and empirical data, we show that the validity and reliability of MBM are either comparable or superior to classical vertex-based SBM for capturing differences in cortical thickness maps between two experimental groups. Our approach thus offers a robust, accurate, and informative method for characterizing empirical maps of neuroanatomical variability that can be directly linked to a generative physical process.
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Affiliation(s)
- Trang Cao
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, 762-772 Blackburn Rd, Clayton VIC 3168, Australia
| | - James C Pang
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, 762-772 Blackburn Rd, Clayton VIC 3168, Australia
| | - Ashlea Segal
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, 762-772 Blackburn Rd, Clayton VIC 3168, Australia
| | - Yu-Chi Chen
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, 762-772 Blackburn Rd, Clayton VIC 3168, Australia
| | - Kevin M Aquino
- School of Physics, University of Sydney, Physics Rd, Camperdown NSW 2006, Australia
| | - Michael Breakspear
- School of Psychological Sciences, University of Newcastle, University Dr, Callaghan NSW 2308, Australia
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, 762-772 Blackburn Rd, Clayton VIC 3168, Australia
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240
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Wang Z, Liu C, Dong Q, Xue G, Chen C. Polygenic risk score for five major psychiatric disorders associated with volume of distinct brain regions in the general population. Biol Psychol 2023; 178:108530. [PMID: 36858107 DOI: 10.1016/j.biopsycho.2023.108530] [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: 09/08/2022] [Revised: 02/23/2023] [Accepted: 02/25/2023] [Indexed: 03/03/2023]
Abstract
Risk genes and abnormal brain structural indices of psychiatric disorders have been extensively studied. However, whether genetic risk influences brain structure in the general population has been rarely studied. The current study enrolled 483 young Chinese adults, calculated their polygenic risk scores (PRS) for psychiatric disorders based on Psychiatric Genomics Consortium GWAS results, and examined the association between PRSs and brain volume. We found that PRSs were associated with the volume of many brain regions, with differences between PRS for different disorder, calculated at different threshold, and calculated using European or East Asian ancestry. Of them, the PRS for Major Depressive Disorder based on European ancestry was positively associated with right temporal gyrus; the PRS for schizophrenia based on East Asian ancestry was negatively associated with right precentral and postcentral gyrus; the PRS for schizophrenia based on European ancestry was positively associated with right superior temporal gyrus. All these brain regions are critical for corresponding disorders. However, no significant associations were found between PRS for Autism Spectrum Disorder / Bipolar Disorder and brain volume; and the association between PRS for Attention Deficit Hyperactivity Disorder at different thresholds and brain volume was inconsistent. These findings suggest distinct brain mechanisms underlying different psychiatric disorders.
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Affiliation(s)
- Ziyi Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Experimental School Attached to Haidian Teachers' Training College, Xiangshan Branch, Beijing, China
| | - Chang Liu
- Department of Psychology, Washington State University, Pullman, WA, USA
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Gui Xue
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chunhui Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
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241
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The role of brain structure in the association between pubertal timing and depression risk in an early adolescent sample (the ABCD Study®): A registered report. Dev Cogn Neurosci 2023; 60:101223. [PMID: 36870214 PMCID: PMC10009199 DOI: 10.1016/j.dcn.2023.101223] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 02/03/2023] [Accepted: 02/21/2023] [Indexed: 02/26/2023] Open
Abstract
BACKGROUND Earlier pubertal timing is associated with higher rates of depressive disorders in adolescence. Neuroimaging studies report brain structural associations with both pubertal timing and depression. However, whether brain structure mediates the relationship between pubertal timing and depression remains unclear. METHODS The current registered report examined associations between pubertal timing (indexed via perceived pubertal development), brain structure (cortical and subcortical metrics, and white matter microstructure) and depressive symptoms in a large sample (N = ∼5000) of adolescents (aged 9-13 years) from the Adolescent Brain Cognitive Development (ABCD) Study. We used three waves of follow-up data when the youth were aged 10-11 years, 11-12 years, and 12-13 years, respectively. We used generalised linear-mixed models (H1) and structural equation modelling (H2 & H3) to test our hypotheses. HYPOTHESES We hypothesised that earlier pubertal timing at Year 1 would be associated with increased depressive symptoms at Year 3 (H1), and that this relationship would be mediated by global (H2a-b) and regional (H3a-g) brain structural measures at Year 2. Global measures included reduced cortical volume, thickness, surface area and sulcal depth. Regional measures included reduced cortical thickness and volume in temporal and fronto-parietal areas, increased cortical volume in the ventral diencephalon, increased sulcal depth in the pars orbitalis, and reduced fractional anisotropy in the cortico-striatal tract and corpus callosum. These regions of interest were informed by our pilot analyses using baseline ABCD data when the youth were aged 9-10 years. RESULTS Earlier pubertal timing was associated with increased depressive symptoms two years later. The magnitude of effect was stronger in female youth and the association remained significant when controlling for parental depression, family income, and BMI in females but not in male youth. Our hypothesised brain structural measures did not however mediate the association between earlier pubertal timing and later depressive symptoms. CONCLUSION The present results demonstrate that youth, particularly females, who begin puberty ahead of their peers are at an increased risk for adolescent-onset depression. Future work should explore additional biological and socio-environmental factors that may affect this association so that we can identify targets for intervention to help these at-risk youth.
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242
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Sherif MA, Khalil MZ, Shukla R, Brown JC, Carpenter LL. Synapses, predictions, and prediction errors: A neocortical computational study of MDD using the temporal memory algorithm of HTM. Front Psychiatry 2023; 14:976921. [PMID: 36911109 PMCID: PMC9995817 DOI: 10.3389/fpsyt.2023.976921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 01/16/2023] [Indexed: 02/25/2023] Open
Abstract
Introduction Synapses and spines play a significant role in major depressive disorder (MDD) pathophysiology, recently highlighted by the rapid antidepressant effect of ketamine and psilocybin. According to the Bayesian brain and interoception perspectives, MDD is formalized as being stuck in affective states constantly predicting negative energy balance. To understand how spines and synapses relate to the predictive function of the neocortex and thus to symptoms, we used the temporal memory (TM), an unsupervised machine-learning algorithm. TM models a single neocortical layer, learns in real-time, and extracts and predicts temporal sequences. TM exhibits neocortical biological features such as sparse firing and continuous online learning using local Hebbian-learning rules. Methods We trained a TM model on random sequences of upper-case alphabetical letters, representing sequences of affective states. To model depression, we progressively destroyed synapses in the TM model and examined how that affected the predictive capacity of the network. We found that the number of predictions decreased non-linearly. Results Destroying 50% of the synapses slightly reduced the number of predictions, followed by a marked drop with further destruction. However, reducing the synapses by 25% distinctly dropped the confidence in the predictions. Therefore, even though the network was making accurate predictions, the network was no longer confident about these predictions. Discussion These findings explain how interoceptive cortices could be stuck in limited affective states with high prediction error. Connecting ketamine and psilocybin's proposed mechanism of action to depression pathophysiology, the growth of new synapses would allow representing more futuristic predictions with higher confidence. To our knowledge, this is the first study to use the TM model to connect changes happening at synaptic levels to the Bayesian formulation of psychiatric symptomatology. Linking neurobiological abnormalities to symptoms will allow us to understand the mechanisms of treatments and possibly, develop new ones.
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Affiliation(s)
- Mohamed A. Sherif
- Lifespan Physician Group, Department of Psychiatry and Human Behavior, The Warren Alpert Medical School of Brown University, Carney Institute for Brain Science, Norman Prince Neurosciences Institute, Providence, RI, United States
| | - Mostafa Z. Khalil
- Department of Psychiatry and Behavioral Health, Penn State Milton S. Hershey Medical Center, Penn State College of Medicine, Hershey, PA, United States
| | - Rammohan Shukla
- Department of Neurosciences, The University of Toledo College of Medicine and Life Sciences, Toledo, OH, United States
| | - Joshua C. Brown
- Department of Psychiatry and Human Behavior, The Warren Alpert Medical School of Brown University, Butler Hospital, Providence, RI, United States
| | - Linda L. Carpenter
- Department of Psychiatry and Human Behavior, The Warren Alpert Medical School of Brown University, Butler Hospital, Providence, RI, United States
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243
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Jog MA, Anderson C, Kubicki A, Boucher M, Leaver A, Hellemann G, Iacoboni M, Woods R, Narr K. Transcranial direct current stimulation (tDCS) in depression induces structural plasticity. Sci Rep 2023; 13:2841. [PMID: 36801903 PMCID: PMC9938111 DOI: 10.1038/s41598-023-29792-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 02/10/2023] [Indexed: 02/19/2023] Open
Abstract
Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique involving administration of well-tolerated electrical current to the brain through scalp electrodes. TDCS may improve symptoms in neuropsychiatric disorders, but mixed results from recent clinical trials underscore the need to demonstrate that tDCS can modulate clinically relevant brain systems over time in patients. Here, we analyzed longitudinal structural MRI data from a randomized, double-blind, parallel-design clinical trial in depression (NCT03556124, N = 59) to investigate whether serial tDCS individually targeted to the left dorso-lateral prefrontal cortex (DLPFC) can induce neurostructural changes. Significant (FWEc p < 0.05) treatment-related gray matter changes were observed with active high-definition (HD) tDCS relative to sham tDCS within the left DLPFC stimulation target. No changes were observed with active conventional tDCS. A follow-up analysis within individual treatment groups revealed significant gray matter increases with active HD-tDCS in brain regions functionally connected with the stimulation target, including the bilateral DLPFC, bilateral posterior cingulate cortex, subgenual anterior cingulate cortex, and the right hippocampus, thalamus and left caudate brain regions. Integrity of blinding was verified, no significant differences in stimulation-related discomfort were observed between treatment groups, and tDCS treatments were not augmented by any other adjunct treatments. Overall, these results demonstrate that serial HD-tDCS leads to neurostructural changes at a predetermined brain target in depression and suggest that such plasticity effects may propagate over brain networks.
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Affiliation(s)
- Mayank A Jog
- Department of Neurology, University of California Los Angeles (UCLA), Los Angeles, CA, 90095, USA.
| | - Cole Anderson
- Diagnostic Imaging Sciences Center, University of Washington, Seattle, WA, 98195, USA
| | - Antoni Kubicki
- Department of Neurology, University of California Los Angeles (UCLA), Los Angeles, CA, 90095, USA
| | - Michael Boucher
- Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, 90095, USA
| | - Amber Leaver
- Department of Radiology, Northwestern University, Evanston, IL, 60208, USA
| | - Gerhard Hellemann
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Marco Iacoboni
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, CA, 90095, USA
| | - Roger Woods
- Department of Neurology, University of California Los Angeles (UCLA), Los Angeles, CA, 90095, USA
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, CA, 90095, USA
| | - Katherine Narr
- Department of Neurology, University of California Los Angeles (UCLA), Los Angeles, CA, 90095, USA
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, CA, 90095, USA
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244
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Glahn DC. Editorial: Irritable Imaging: Interpreting Null Results in Psychiatric Neuroimaging. J Am Acad Child Adolesc Psychiatry 2023; 62:130-132. [PMID: 36427758 DOI: 10.1016/j.jaac.2022.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 11/15/2022] [Indexed: 11/23/2022]
Abstract
There is a growing appreciation that clinically impairing irritability is an important transdiagnostic symptom among children and adolescents with mental illness. Severe irritability, defined by frequent, developmentally inappropriate temper outbursts and low frustration tolerance, is one of the most common reasons that youths are referred for psychiatric evaluation and care.1 Although chronic irritability is the primary symptom in disruptive mood dysregulation disorder, the symptom is common in a diverse set of DSM-5 diagnoses, including major depressive disorder, autism spectrum disorder, oppositional defiant disorder, bipolar disorder, and generalized anxiety disorder.1 Given that clinically impairing irritability is often predictive of poor outcomes in childhood and worse clinical course in adulthood, a concerted effort is being made to refine the definition of this symptom and determine if severe irritability could be better understood and treated as an independent diagnosis.1.
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Affiliation(s)
- David C Glahn
- Tommy Fuss Center for Neuropsychiatric Disease Research, Boston Children's Hospital, Boston, Massachusetts, and Harvard Medical School, Boston, Massachusetts.
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245
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Murck H, Lehr L, Jezova D. A viewpoint on aldosterone and BMI related brain morphology in relation to treatment outcome in patients with major depression. J Neuroendocrinol 2023; 35:e13219. [PMID: 36539978 DOI: 10.1111/jne.13219] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 11/06/2022] [Accepted: 11/15/2022] [Indexed: 11/21/2022]
Abstract
An abundance of knowledge has been collected describing the involvement of neuroendocrine parameters in major depression. The hypothalamic-pituitary-adrenocortical (HPA) axis regulating cortisol release has been extensively studied; however, attempts to target the HPA axis pharmacologically to treat major depression have failed. This review focuses on the importance of the adrenocortical stress hormone aldosterone, which is released by adrenocorticotropic hormone and angiotensin, and the mineralocorticoid receptor (MR) in depression. Depressed patients, in particular those with atypical depression, have signs of central hyperactivation of the aldosterone sensitive MR, potentially as a consequence of a reactive aldosterone release induced by low blood pressure and as a result of low sensitivity of peripheral MR. This is reflected in reduced heart rate variability, increased salt appetite and sleep changes in this group of patients. In addition, enlarged brain ventricles, compressed corpus callosum and changes of the choroid plexus are associated with increased aldosterone (in relation to cortisol). Furthermore, subjects with these features often show obesity. These characteristics are related to a worse antidepressant treatment outcome. Alterations in choroid plexus function as a consequence of increased aldosterone levels, autonomic dysregulation, metabolic changes and/or inflammation may be involved. The characterization of this regulatory system is in its early days but may identify new targets for therapeutic interventions.
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Affiliation(s)
- Harald Murck
- Philipps-University Marburg, Marburg, Germany
- Murck-Neuroscience LLC Westfield, Westfield, NJ, USA
| | - Lisa Lehr
- Department of Nephrology, Klinikum Rechts der Isar, Technical University Munich, Munich, Germany
| | - Daniela Jezova
- Slovak Academy of Sciences, Biomedical Research Center, Institute of Experimental Endocrinology, Bratislava, Slovakia
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Xue K, Guo L, Zhu W, Liang S, Xu Q, Ma L, Liu M, Zhang Y, Liu F. Transcriptional signatures of the cortical morphometric similarity network gradient in first-episode, treatment-naive major depressive disorder. Neuropsychopharmacology 2023; 48:518-528. [PMID: 36253546 PMCID: PMC9852427 DOI: 10.1038/s41386-022-01474-3] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 09/15/2022] [Accepted: 10/05/2022] [Indexed: 02/02/2023]
Abstract
Recent studies have shown that major depressive disorder (MDD) is accompanied by alterations in functional and structural network gradients. However, whether changes are present in the cortical morphometric similarity (MS) network gradient, and the relationship between alterations of the gradient and gene expression remains largely unknown. In this study, the MS network was constructed, and its gradient was calculated in 71 patients with first-episode, treatment-naive MDD, and 69 demographically matched healthy controls. Between-group comparisons were performed to investigate abnormalities in the MS network gradient, and partial least squares regression analysis was conducted to explore the association between gene expression profiles and MS network gradient-based alternations in MDD. We found that the gradient was primarily significantly decreased in sensorimotor regions in patients with MDD compared with healthy controls, and increased in visual-related regions. In addition, the altered principal MS network gradient in the left postcentral cortex and right lingual cortex exhibited significant correlations with symptom severity. The abnormal gradient pattern was spatially correlated with the brain-wide expression of genes enriched for neurobiologically relevant pathways, downregulated in the MDD postmortem brain, and preferentially expressed in different cell types and cortical layers. These results demonstrated alterations of the principal MS network gradient in MDD and suggested the molecular mechanisms for structural alternations underlying MDD.
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Affiliation(s)
- Kaizhong Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Wenshuang Zhu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Sixiang Liang
- Tianjin Anding Hospital, Tianjin, 300222, China
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, 100088, China
| | - Qiang Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Lin Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Mengge Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yong Zhang
- Tianjin Anding Hospital, Tianjin, 300222, China.
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
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Luo Q, Chen J, Li Y, Lin X, Yu H, Lin X, Wu H, Peng H. Cortical thickness and curvature abnormalities in patients with major depressive disorder with childhood maltreatment: Neural markers of vulnerability? Asian J Psychiatr 2023; 80:103396. [PMID: 36508912 DOI: 10.1016/j.ajp.2022.103396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/07/2022] [Accepted: 11/12/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Childhood maltreatment has been related to various disadvantageous lifetime outcomes. However, the brain structural alterations that occur in major depressive disorder (MDD) patients with childhood maltreatment are incompletely investigated. METHODS We extensively explored the cortical abnormalities including cortical volume, surface area, thickness, sulcal depth, and curvature in maltreated MDD patients. Twoway ANOVA was performed to distinguish the effects of childhood maltreatment and depression on structural abnormalities. Partial correlation analysis was performed to explore the relationship between childhood maltreatment and cortical abnormalities. Moreover, we plotted the receiver operating characteristic curve to examine whether the observed cortical abnormalities could be used as neuro biomarkers to identify maltreated MDD patients. RESULTS We reach the following findings: (i) relative to MDD without childhood maltreatment, MDD patients with childhood maltreatment existed increased cortical curvature in inferior frontal gyrus; (ii) compared to HC without childhood maltreatment, decreased cortical thickness was observed in anterior cingulate cortex and medial prefrontal cortex in MDD patients with childhood maltreatment; (iii) we confirmed the inseparable relationship between cortical curvature alterations in inferior frontal gyrus as well as childhood maltreatment; (iv) cortical curvature abnormality in inferior frontal gyrus could be applied as neural biomarker for clinical identification of MDD patients with childhood maltreatment. CONCLUSIONS Childhood maltreatment have a significant effects on cortical thickness and curvature abnormalities involved in inferior frontal gyrus, anterior cingulate cortex and medial prefrontal cortex, constituting the vulnerability to depression.
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Affiliation(s)
- Qianyi Luo
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Juran Chen
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Yuhong Li
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Xinyi Lin
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Huiwen Yu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Xiaohui Lin
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China
| | - Huawang Wu
- Department of Radiology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China.
| | - Hongjun Peng
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China.
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Cortical profiles of numerous psychiatric disorders and normal development share a common pattern. Mol Psychiatry 2023; 28:698-709. [PMID: 36380235 DOI: 10.1038/s41380-022-01855-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 10/19/2022] [Accepted: 10/24/2022] [Indexed: 11/16/2022]
Abstract
The neurobiological bases of the association between development and psychopathology remain poorly understood. Here, we identify a shared spatial pattern of cortical thickness (CT) in normative development and several psychiatric and neurological disorders. Principal component analysis (PCA) was applied to CT of 68 regions in the Desikan-Killiany atlas derived from three large-scale datasets comprising a total of 41,075 neurotypical participants. PCA produced a spatially broad first principal component (PC1) that was reproducible across datasets. Then PC1 derived from healthy adult participants was compared to the pattern of CT differences associated with psychiatric and neurological disorders comprising a total of 14,886 cases and 20,962 controls from seven ENIGMA disease-related working groups, normative maturation and aging comprising a total of 17,697 scans from the ABCD Study® and the IMAGEN developmental study, and 17,075 participants from the ENIGMA Lifespan working group, as well as gene expression maps from the Allen Human Brain Atlas. Results revealed substantial spatial correspondences between PC1 and widespread lower CT observed in numerous psychiatric disorders. Moreover, the PC1 pattern was also correlated with the spatial pattern of normative maturation and aging. The transcriptional analysis identified a set of genes including KCNA2, KCNS1 and KCNS2 with expression patterns closely related to the spatial pattern of PC1. The gene category enrichment analysis indicated that the transcriptional correlations of PC1 were enriched to multiple gene ontology categories and were specifically over-represented starting at late childhood, coinciding with the onset of significant cortical maturation and emergence of psychopathology during the prepubertal-to-pubertal transition. Collectively, the present study reports a reproducible latent pattern of CT that captures interregional profiles of cortical changes in both normative brain maturation and a spectrum of psychiatric disorders. The pubertal timing of the expression of PC1-related genes implicates disrupted neurodevelopment in the pathogenesis of the spectrum of psychiatric diseases emerging during adolescence.
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Huang X, Lai S, Lu X, Wang Y, Zhang Y, Chen G, Chen P, Ye K, Duan M, Song K, Zhong S, Jia Y. Cognitive dysfunction and neurometabolic alternations in major depressive disorder with gastrointestinal symptoms. J Affect Disord 2023; 322:180-186. [PMID: 36372125 DOI: 10.1016/j.jad.2022.10.036] [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: 07/09/2022] [Revised: 10/12/2022] [Accepted: 10/20/2022] [Indexed: 11/13/2022]
Abstract
BACKGROUND Brain biochemical abnormalities have been associated with major depressive disorder (MDD) and cognitive impairments. However, the cognitive performance and neurometabolic alterations of MDD patients accompanied by gastrointestinal (GI) symptoms remain to be elucidated. We aimed to reveal the features and correlation between cognitive impairments and brain biochemical abnormalities of depressed patients with GI symptoms. METHODS Fifty MDD patients with GI symptoms (GI group), 46 patients without GI symptoms (NGI group) and 50 demographically matched healthy controls (HCs) underwent Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) assessments. In addition, proton magnetic resonance spectroscopy (1H-MRS) was used to obtain ratios of N-acetyl aspartate to creatine (NAA/Cr) and choline-containing compounds to creatine (Cho/Cr) in the thalamus, putamen and anterior cingulate cortex (ACC). Finally, association analysis was conducted to investigate the relationships of these measurements. RESULTS Compared to HCs, participants in both the GI and NGI groups had significantly reduced performance in the six MCCB cognitive domains (all p < 0.05), except for reasoning and problem solving. Higher Cho/Cr ratios in the right thalamus (p < 0.05) and lower NAA/Cr ratios in the left putamen (p < 0.05) were found in the NGI group than in the GI group. The severity of GI symptoms was negatively correlated with Cho/Cr ratios in the right ACC (r = -0.288, p = 0.037). In addition, the T-scores of visual learning were negatively correlated with NAA/Cr ratios in the right ACC (r = -0.443, p = 0.001) and right thalamus (r = -0.335, p = 0.015). CONCLUSION Our findings suggest that MDD patients with GI symptoms may exhibit greater neurometabolic alternations than those without GI symptoms, while both show similar cognitive dysfunction. In addition, neurometabolic alterations in the ACC and thalamus may underlie the neural basis of GI symptoms and cognitive impairment in MDD.
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Affiliation(s)
- Xiaosi Huang
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Shunkai Lai
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Xiaodan Lu
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Yiliang Zhang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Pan Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Kaiwei Ye
- School of Management, Jinan University, Guangzhou 510316, China
| | - Manying Duan
- School of Management, Jinan University, Guangzhou 510316, China
| | - Kailin Song
- School of Management, Jinan University, Guangzhou 510316, China
| | - Shuming Zhong
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China.
| | - Yanbin Jia
- Department of Psychiatry, First Affiliated Hospital of Jinan University, Guangzhou 510630, China.
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Lima-Filho R, Fortuna JS, Cozachenco D, Isaac AR, Lyra e Silva N, Saldanha A, Santos LE, Ferreira ST, Lourenco MV, De Felice FG. Brain FNDC5/Irisin Expression in Patients and Mouse Models of Major Depression. eNeuro 2023; 10:ENEURO.0256-22.2023. [PMID: 36697257 PMCID: PMC9927507 DOI: 10.1523/eneuro.0256-22.2023] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 01/16/2023] [Accepted: 01/19/2023] [Indexed: 01/27/2023] Open
Abstract
Major depressive disorder (MDD) is a major cause of disability in adults. MDD is both a comorbidity and a risk factor for Alzheimer's disease (AD), and regular physical exercise has been associated with reduced incidence and severity of MDD and AD. Irisin is an exercise-induced myokine derived from proteolytic processing of fibronectin type III domain-containing protein 5 (FNDC5). FNDC5/irisin is reduced in the brains of AD patients and mouse models. However, whether brain FNDC5/irisin expression is altered in depression remains elusive. Here, we investigate changes in fndc5 expression in postmortem brain tissue from MDD individuals and mouse models of depression. We found decreased fndc5 expression in the MDD prefrontal cortex, both with and without psychotic traits. We further demonstrate that the induction of depressive-like behavior in male mice by lipopolysaccharide decreased fndc5 expression in the frontal cortex, but not in the hippocampus. Conversely, chronic corticosterone administration increased fndc5 expression in the frontal cortex, but not in the hippocampus. Social isolation in mice did not result in altered fndc5 expression in either frontal cortex or hippocampus. Finally, fluoxetine, but not other antidepressants, increased fndc5 gene expression in the mouse frontal cortex. Results indicate a region-specific modulation of fndc5 in depressive-like behavior and by antidepressant in mice. Our finding of decreased prefrontal cortex fndc5 expression in MDD individuals differs from results in mice, highlighting the importance of carefully interpreting observations in mice. The reduction in fndc5 mRNA suggests that decreased central FNDC5/irisin could comprise a shared pathologic mechanism between MDD and AD.
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Affiliation(s)
- Ricardo Lima-Filho
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, 21941-902, Rio de Janeiro RJ, Brazil
| | - Juliana S. Fortuna
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, 21941-902, Rio de Janeiro RJ, Brazil
| | - Danielle Cozachenco
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, 21941-902, Rio de Janeiro RJ, Brazil
| | - Alinny R. Isaac
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, 21941-902, Rio de Janeiro RJ, Brazil
| | - Natalia Lyra e Silva
- Centre for Neurosciences Studies, Departments of Biomedical and Molecular Sciences, and Psychiatry, Queen’s University, Kingston, Ontario K7L 3N6, Canada
| | - Alice Saldanha
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, 21941-902, Rio de Janeiro RJ, Brazil
| | - Luis E. Santos
- Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, 21941-902, Rio de Janeiro RJ, Brazil
| | - Sergio T. Ferreira
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, 21941-902, Rio de Janeiro RJ, Brazil
- Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, 21941-902, Rio de Janeiro RJ, Brazil
- D’Or Institute for Research and Education, Rio de Janeiro RJ, 22281-100, Brazil
| | - Mychael V. Lourenco
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, 21941-902, Rio de Janeiro RJ, Brazil
| | - Fernanda G. De Felice
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, 21941-902, Rio de Janeiro RJ, Brazil
- Centre for Neurosciences Studies, Departments of Biomedical and Molecular Sciences, and Psychiatry, Queen’s University, Kingston, Ontario K7L 3N6, Canada
- D’Or Institute for Research and Education, Rio de Janeiro RJ, 22281-100, Brazil
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