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Hashimoto N, Okada N, Fukunaga M, Nemoto K, Miura K, Matsumoto J, Ishikawa S, Narita H, Morita K, Yasuda Y, Kamishikiryo T, Harada K, Yamamoto M, Ohi K, Matsubara T, Hirano Y, Okada G, Tha KK, Abe O, Onitsuka T, Kawasaki Y, Ozaki N, Kasai K, Hashimoto R. Lithium and valproate affect subcortical brain volumes in individuals with bipolar disorder: Mega-analysis of 235 individuals. J Affect Disord 2025; 381:115-120. [PMID: 40189070 DOI: 10.1016/j.jad.2025.04.019] [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: 05/07/2024] [Revised: 11/01/2024] [Accepted: 04/02/2025] [Indexed: 04/10/2025]
Abstract
INTRODUCTION The mega-analysis conducted by the ENIGMA Bipolar Disorder Working Group revealed significant volume increment effects of lithium on the hippocampus in individual with bipolar disorder. However, the study did not assess other medications and other subcortical regions. METHODS Data of 235 individuals with bipolar disorder were taken from a mega-analysis conducted by the COCORO consortium in Japan. The effects of psychotropic prescriptions (lithium, valproate, antipsychotics, antidepressants, benzodiazepines) were assessed using a linear mixed-effects model with volumes of subcortical structures as dependent variables, and age, sex, intracranial volume, duration of illness, and psychotropic prescriptions as independent variables; the type of protocol was incorporated as a random effect. RESULTS Prescriptions of lithium was associated with larger left amygdala volume (Effect size (ES, Cohen's d) = 0.36, p = 0.001). Prescriptions of valproate was associated with smaller left amygdala volume (ES = -0.45, p = 0.001), and larger bilateral ventricle volumes (ES = 0.68, p < 0.001 (left), ES = 0.70, p < 0.001 (right)). Prescriptions of antipsychotics were associated with larger left globus pallidus volume (ES = 0.33, p = 0.014) and smaller left hippocampus volume (ES = -0.33, p = 0.024). Prescriptions of benzodiazepines were associated with smaller left lateral ventricle (ES = -0.40, p = 0.029). Prescriptions of antidepressants were associated with smaller right accumbens volume (ES = -0.22, p = 0.043), bilateral caudate volumes (ES = -0.38, p = 0.013 (left), ES = -0.25, p = 0.050 (right)) and right putamen volume (ES = -0.23, p = 0.024). CONCLUSION We confirmed the association between prescription of valproate and smaller amygdala and larger lateral ventricle volumes in a large sample for the first time. Large sample size, uniform data collection methodology, and robust statistical analysis are strengths of the current study.
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Affiliation(s)
- Naoki Hashimoto
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan.
| | - Naohiro Okada
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; The International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), Tokyo, Japan
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Aichi, Japan
| | - Kiyotaka Nemoto
- Department of Psychiatry, Institute of Medicine, University of Tsukuba, Ibaraki, Japan
| | - Kenichiro Miura
- Division of Cerebral Integration, National Institute for Physiological Sciences, Aichi, Japan; Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Junya Matsumoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Shuhei Ishikawa
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan
| | - Hisashi Narita
- Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan
| | - Kentaro Morita
- Department of Rehabilitation, University of Tokyo Hospital, Tokyo, Japan
| | - Yuka Yasuda
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan; Life Grow Brilliant Mental Clinic, Medical Corporation Foster, Osaka, Japan
| | | | - Kenichiro Harada
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, Yamaguchi, Japan
| | - Maeri Yamamoto
- Department of Psychiatry, Graduate School of Medicine, Nagoya University, Aichi, Japan
| | - Kazutaka Ohi
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan; Department of General Internal Medicine, Kanazawa Medical University, Ishikawa, Japan
| | - Toshio Matsubara
- Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, Yamaguchi, Japan
| | - Yoji Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; Department of Psychiatry, Division of Clinical Neuroscience, Faculty of Medicine, University of Miyazaki, Miyazaki, Japan
| | - Go Okada
- Department of Psychiatry and Neuroscience, Hiroshima University, Hiroshima, Japan
| | - Khin K Tha
- Department of Diagnostic Imaging, Hokkaido University Faculty of Medicine, Hokkaido, Japan; Global Center for Biomedical Science and Engineering, Hokkaido University Faculty of Medicine, Hokkaido, Japan
| | - Osamu Abe
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | | | - Yasuhiro Kawasaki
- Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan
| | - Norio Ozaki
- Department of Psychiatry, Graduate School of Medicine, Nagoya University, Aichi, Japan; Pathophysiology of Mental Disorders, Graduate School of Medicine, Nagoya University, Aichi, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; The International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), Tokyo, Japan; University of Tokyo Institute for Diversity & Adaptation of Human Mind (UTIDAHM), Tokyo, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan; Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, Japan
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Valizadeh P, Jannatdoust P, Ghadimi DJ, Tahamtan M, Darmiani K, Shahsavarhaghighi S, Rezaei S, Aarabi MH, Cattarinussi G, Sambataro F, Nosari G, Delvecchio G. The association between C-reactive protein and neuroimaging findings in mood disorders: A review of structural and diffusion MRI studies. J Affect Disord 2025; 381:643-658. [PMID: 40189071 DOI: 10.1016/j.jad.2025.03.175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2024] [Revised: 03/27/2025] [Accepted: 03/29/2025] [Indexed: 04/19/2025]
Abstract
BACKGROUND Mood disorders, including major depressive disorder (MDD) and bipolar disorder (BD), often share structural brain alterations, which may be linked to peripheral inflammation. In this regard, C-Reactive Protein (CRP) has been associated with these alterations. This review explores the relationship between CRP levels and neuroimaging findings in mood disorders using structural and diffusion Magnetic Resonance Imaging (MRI). METHODS Following PRISMA guidelines, a systematic search was conducted through Scopus, PubMed, Web of Science, and Embase before September 2024, focusing on studies evaluating associations between CRP levels and structural and/or microstructural brain alterations in mood disorders. RESULTS The present systematic review included 20 studies examining the associations between peripheral CRP levels or DNA methylation-based CRP (DNAm CRP) signatures and structural brain alterations in mood disorders. Findings showed considerable variability; however, consistent patterns emerged, linking higher CRP levels to reduced grey matter volumes and cortical thinning, particularly in the prefrontal cortex (PFC), hippocampus, entorhinal cortex, insula, and caudate. Diffusion-based imaging consistently indicated reduced white matter integrity, with significant effects in key tracts such as the internal capsule, cingulum bundle, and corpus callosum (CC). CONCLUSIONS Overall, these findings suggest that systemic inflammation, reflected by elevated CRP or DNAm CRP, contributes to structural alterations indicative of neurodegeneration and compromised axonal integrity in mood disorders. Discrepancies among studies highlight potential influences of disease severity, treatment history, and distinct inflammatory mediators. Future research employing standardized imaging protocols and longitudinal designs is essential to clarify inflammation's mechanistic roles and identify reliable biomarkers of structural brain alterations in mood disorders.
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Affiliation(s)
- Parya Valizadeh
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Payam Jannatdoust
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Delaram J Ghadimi
- School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammadreza Tahamtan
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Science, Tehran, Iran
| | - Kimia Darmiani
- School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Sahar Rezaei
- Department of Radiology, Medical School, Tabriz University of Medical Sciences, Tabriz, Iran
| | | | - Giulia Cattarinussi
- Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center (PNC), University of Padova, Padova, Italy
| | - Fabio Sambataro
- Department of Neuroscience, University of Padova, Padova, Italy; Padova Neuroscience Center (PNC), University of Padova, Padova, Italy
| | - Guido Nosari
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
| | - Giuseppe Delvecchio
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
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Haq SU, Ling W, Aqib AI, Danmei H, Aleem MT, Fatima M, Ahmad S, Gao F. Exploring the intricacies of antimicrobial resistance: Understanding mechanisms, overcoming challenges, and pioneering innovative solutions. Eur J Pharmacol 2025; 998:177511. [PMID: 40090539 DOI: 10.1016/j.ejphar.2025.177511] [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: 11/15/2024] [Revised: 03/07/2025] [Accepted: 03/14/2025] [Indexed: 03/18/2025]
Abstract
Antimicrobial resistance (AMR) poses a growing global threat. This review examines AMR from diverse angles, tracing the story of antibiotic resistance from its origins to today's crisis. It explores the rise of AMR, from its historical roots to the urgent need to counter this escalating menace. The review explores antibiotic classes, mechanisms, resistance profiles, and genetics. It details bacterial resistance mechanisms with illustrative examples. Multidrug-resistant bacteria spotlight AMR's resilience. Modern AMR control offers hope through precision medicine, stewardship, combination therapy, surveillance, and international cooperation. Converging traditional and innovative treatments presents an exciting frontier as novel compounds seek to enhance antibiotic efficacy. This review calls for global unity and proactive engagement to address AMR collectively, emphasizing the quest for innovative solutions and responsible antibiotic use. It underscores the interconnectedness of science, responsibility, and action in combatting AMR. Humanity faces a choice between antibiotic efficacy and obsolescence. The call is clear: unite, innovate, and prevail against AMR.
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Affiliation(s)
- Shahbaz Ul Haq
- Department of Pharmacology, Shantou University Medical College, Shantou, 515041, China.
| | - Wang Ling
- Key Laboratory of New Animal Drug Project, Gansu Province, Key Laboratory of Veterinary Pharmaceutical Development, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agriculture Sciences, Lanzhou, 730050, China
| | - Amjad Islam Aqib
- Department of Medicine, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, 63100, Pakistan
| | - Huang Danmei
- Department of Pharmacology, Shantou University Medical College, Shantou, 515041, China
| | - Muhammad Tahir Aleem
- Department of Pharmacology, Shantou University Medical College, Shantou, 515041, China
| | - Mahreen Fatima
- Faculty of Biosciences, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, 63100, Pakistan
| | - Saad Ahmad
- Engineering & Technology Research Center of Traditional Chinese Veterinary Medicine of Gansu Province, Lanzhou Institute of Husbandry and Pharmaceutical Sciences of Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Fenfei Gao
- Department of Pharmacology, Shantou University Medical College, Shantou, 515041, China.
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Fortea L, Ortuño M, De Prisco M, Oliva V, Albajes-Eizagirre A, Fortea A, Madero S, Solanes A, Vilajosana E, Yao Y, Del Fabro L, Solé E, Verdolini N, Farré-Colomés A, Serra-Blasco M, Picó-Pérez M, Lukito S, Wise T, Carlisi C, Arnone D, Kempton MJ, Hauson AO, Wollman S, Soriano-Mas C, Rubia K, Norman L, Fusar-Poli P, Mataix-Cols D, Valentí M, Via E, Cardoner N, Solmi M, Zhang J, Pan P, Shin JI, Fullana MA, Vieta E, Radua J. Atlas of Gray Matter Volume Differences Across Psychiatric Conditions: A Systematic Review With a Novel Meta-Analysis That Considers Co-Occurring Disorders. Biol Psychiatry 2025; 98:76-90. [PMID: 39491638 DOI: 10.1016/j.biopsych.2024.10.020] [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: 02/06/2024] [Revised: 10/04/2024] [Accepted: 10/21/2024] [Indexed: 11/05/2024]
Abstract
BACKGROUND Regional gray matter volume (GMV) differences between individuals with mental disorders and comparison participants may be confounded by co-occurring disorders. To disentangle disorder-specific GMV correlates, we conducted a large-scale multidisorder meta-analysis using a novel approach that explicitly models co-occurring disorders. METHODS We systematically reviewed voxel-based morphometry studies indexed in PubMed and Scopus up to January 2023 that compared adults with major mental disorders (anorexia nervosa, schizophrenia spectrum, anxiety, bipolar, major depressive, obsessive-compulsive, and posttraumatic stress disorders plus attention-deficit/hyperactivity, autism spectrum, and borderline personality disorders) with comparison participants. Two authors independently extracted data and assessed quality using the Newcastle-Ottawa Scale. We derived GMV correlates for each disorder using: 1) a multidisorder meta-analysis that accounted for all co-occurring mental disorders simultaneously and 2) separate standard meta-analyses for each disorder in which co-occurring disorders were ignored. We assessed the alterations' extent, intensity (effect size), and specificity (interdisorder correlations and transdiagnostic alterations) for both approaches. RESULTS We included 433 studies (499 datasets) involving 19,718 patients and 16,441 comparison participants (51% female, ages 20-67 years). We provide GMV correlate maps for each disorder using both approaches. The novel approach, which accounted for co-occurring disorders, produced GMV correlates that were more focal and disorder specific (less correlated across disorders and fewer transdiagnostic abnormalities). CONCLUSIONS This work offers the most comprehensive atlas of GMV correlates across major mental disorders. Modeling co-occurring disorders yielded more specific correlates, supporting this approach's validity. The atlas NIfTI maps are available online.
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Affiliation(s)
- Lydia Fortea
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Department of Medicine, University of Barcelona, Institute of Neuroscience, Barcelona, Spain.
| | - Maria Ortuño
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Department of Medicine, University of Barcelona, Institute of Neuroscience, Barcelona, Spain
| | - Michele De Prisco
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Department of Medicine, University of Barcelona, Institute of Neuroscience, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain; Bipolar and Depressive Disorders Unit, Hospital Clínic, Barcelona, Spain
| | - Vincenzo Oliva
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Department of Medicine, University of Barcelona, Institute of Neuroscience, Barcelona, Spain; Bipolar and Depressive Disorders Unit, Hospital Clínic, Barcelona, Spain; Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | | | - Adriana Fortea
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Department of Medicine, University of Barcelona, Institute of Neuroscience, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain; Psychiatric and Psychology Service, Hospital Clínic, Barcelona, Spain
| | - Santiago Madero
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Schizophrenia Unit, Hospital Clínic, Barcelona, Spain
| | - Aleix Solanes
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain
| | - Enric Vilajosana
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain
| | - Yuanwei Yao
- Department of Psychology, The University of Hong Kong, Hong Kong SAR, China; Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Lorenzo Del Fabro
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Eduard Solé
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain
| | - Norma Verdolini
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Department of Medicine, University of Barcelona, Institute of Neuroscience, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain; Bipolar and Depressive Disorders Unit, Hospital Clínic, Barcelona, Spain; Local Health Unit Umbria 1, Department of Mental Health, Mental Health Center of Perugia, Perugia, Italy
| | - Alvar Farré-Colomés
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health, Medical Faculty of Mannheim, Heidelberg University, Mannheim, Germany
| | - Maria Serra-Blasco
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain; eHealth ICOnnecta't Program and Psycho-Oncology Service, Institut Català d'Oncologia, L'Hospitalet de Llobregat, Spain; Psycho-oncology and Digital Health Group, Health Services Research in Cancer, Institut d'Investigació Biomèdica de Bellvitge, L'Hospitalet del Llobregat, Spain
| | - Maria Picó-Pérez
- Live and Health Sciences Research Institute, University of Minho, Braga, Portugal; ICVS/3B's, PT Government Associate Laboratory, Braga, Guimarães, Portugal; Departamento de Psicología Básica, Universitat Jaume I, Castelló de la Plana, Spain
| | - Steve Lukito
- Department of Child and Adolescent Psychiatry, Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, United Kingdom
| | - Toby Wise
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neurosciences, King's College London, London, United Kingdom
| | - Christina Carlisi
- Department of Child and Adolescent Psychiatry, Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, United Kingdom; Division of Psychology and Language Sciences, University College London, London, United Kingdom
| | - Danilo Arnone
- Centre for Affective Disorders, Psychological Medicine, King's College London, London, United Kingdom; Department of Psychiatry, University of Ottawa, Ottawa, Ontario, Canada; Department of Mental Health, The Ottawa Hospital, Ottawa, Ontario, Canada
| | - Matthew J Kempton
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neurosciences, King's College London, London, United Kingdom; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Alexander Omar Hauson
- Clinical Psychology PhD Program, California School of Professional Psychology, San Diego, California; Department of Psychiatry, University of California, San Diego, California
| | - Scott Wollman
- Clinical Psychology PhD Program, California School of Professional Psychology, San Diego, California
| | - Carles Soriano-Mas
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain; Department of Psychiatry, Bellvitge Biomedical Research Institute, Barcelona, Spain; Department of Social Psychology and Quantitative Psychology, Institute of Neurosciences, Universitat de Barcelona, Barcelona, Spain
| | - Katya Rubia
- Department of Child and Adolescent Psychiatry, Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, United Kingdom
| | - Luke Norman
- Department of Child and Adolescent Psychiatry, Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, United Kingdom; Department of Psychiatry, University of Michigan, Ann Arbor, Michigan
| | - Paolo Fusar-Poli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Early Psychosis: Interventions and Clinical-Detection (EPIC) Lab., Department of Psychosis Studies, Institute of Psychiatry, Psychology, London, United Kingdom; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy; Outreach and Support in South London Service, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - David Mataix-Cols
- Department of Clinical Neuroscience, Center for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden; Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
| | - Marc Valentí
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Department of Medicine, University of Barcelona, Institute of Neuroscience, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain; Bipolar and Depressive Disorders Unit, Hospital Clínic, Barcelona, Spain
| | - Esther Via
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain; Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Narcis Cardoner
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain; Sant Pau Mental Health Group, Institut d'Investigació Biomèdica Sant Pau, Hospital de la Sant Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
| | - Marco Solmi
- Department of Psychiatry, University of Ottawa, Ottawa, Ontario, Canada; Regional Centre for the Treatment of Eating Disorders and On Track: The Champlain First Episode Psychosis Program, Department of Mental Health, The Ottawa Hospital, Ottawa, Ontario, Canada; Ottawa Hospital Research Institute Clinical Epidemiology Program, University of Ottawa, Ottawa, Ontario, Canada; Department of Child and Adolescent Psychiatry, Charité - Universitätsmedizin, Berlin, Germany
| | - Jintao Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Pinglei Pan
- Department of Neurology, Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Affiliated Yancheng Hospital of Southeast University, Yancheng, China
| | - Jae Il Shin
- Department of Pediatrics, Yonsei University College of Medicine, Seoul, South Korea; Severance Underwood Meta-Research Center, Institute of Convergence Science, Yonsei University, Seoul, South Korea
| | - Miquel A Fullana
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain; Psychiatric and Psychology Service, Hospital Clínic, Barcelona, Spain
| | - Eduard Vieta
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Department of Medicine, University of Barcelona, Institute of Neuroscience, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain; Bipolar and Depressive Disorders Unit, Hospital Clínic, Barcelona, Spain; Psychiatric and Psychology Service, Hospital Clínic, Barcelona, Spain
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi I Sunyer, Barcelona, Spain; Department of Medicine, University of Barcelona, Institute of Neuroscience, Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, Madrid, Spain.
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Liang S, Gao Y, Palaniyappan L, Song XM, Zhang T, Han JF, Tan ZL, Li T. Transcriptional substrates of cortical thickness alterations in anhedonia of major depressive disorder. J Affect Disord 2025; 379:118-126. [PMID: 40044088 DOI: 10.1016/j.jad.2025.03.003] [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: 08/12/2024] [Revised: 02/26/2025] [Accepted: 03/01/2025] [Indexed: 03/14/2025]
Abstract
BACKGROUND Anhedonia is a core symptom of major depressive disorder (MDD), which has been shown to be associated with abnormalities in cortical morphology. However, the correlation between cortical thickness (CT) changes with anhedonia in MDD and gene expression remains unclear. METHODS We investigated the link between brain-wide gene expression and CT correlates of anhedonia in individuals with MDD, using 7 Tesla neuroimaging and a publicly available transcriptomic dataset. The interest-activity score was used to evaluation MDD with high anhedonia (HA) and low anhedonia (LA). Nineteen patients with HA, nineteen patients with LA, and twenty healthy controls (HC) were enrolled. We investigated CT alterations of anhedonia subgroups relative to HC and related cortical gene expression, enrichment and specific cell types. We further used Neurosynth and von Economo-Koskinas atlas to assess the meta-analytic cognitive functions and cytoarchitectural variation associated with anhedonia-related cortical changes. RESULTS Both patient subgroups exhibited widespread CT reduction, with HA manifesting more pronounced changes. Gene expression related to anhedonia had significant spatial correlations with CT differences. Transcriptional signatures related to anhedonia-associated cortical thinning were connected to mitochondrial dysfunction and enriched in adipogenesis, oxidative phosphorylation, mTORC1 signaling pathways, involving neurons, astrocytes, and oligodendrocytes. These CT alterations were significantly correlated with meta-analytic terms involving somatosensory processing and pain perception. HA had reduced CT within the somatomotor and ventral attention networks, and in agranular cortical regions. LIMITATIONS These include measuring anhedonia using interest-activity score and employing a cross-sectional design. CONCLUSIONS This study sheds light on the molecular basis underlying gene expression associated with anhedonia in MDD, suggesting directions for targeted therapeutic interventions.
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Affiliation(s)
- Sugai Liang
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, School of Medicine, Zhejiang University, Hangzhou 310013, China
| | - Yuan Gao
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, School of Medicine, Zhejiang University, Hangzhou 310013, China; Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou 310027, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec H4H1R3, Canada.; Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A5C1, Canada; Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario N6A5K8, Canada
| | - Xue-Mei Song
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, School of Medicine, Zhejiang University, Hangzhou 310013, China; Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou 310027, China
| | - Tian Zhang
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, School of Medicine, Zhejiang University, Hangzhou 310013, China
| | - Jin-Fang Han
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, School of Medicine, Zhejiang University, Hangzhou 310013, China
| | - Zhong-Lin Tan
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, School of Medicine, Zhejiang University, Hangzhou 310013, China.
| | - Tao Li
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, School of Medicine, Zhejiang University, Hangzhou 310013, China; Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 310000, China; NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310063, China.
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Tarmati V, Sepe A, Accoto A, Conversi D, Laricchiuta D, Panuccio A, Canterini S, Fiorenza MT, Cabib S, Orsini C. Genotype-dependent functional role of the anterior and posterior paraventricular thalamus in pavlovian conditioned approach. Psychopharmacology (Berl) 2025; 242:1275-1289. [PMID: 39663249 DOI: 10.1007/s00213-024-06726-2] [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: 05/06/2024] [Accepted: 11/25/2024] [Indexed: 12/13/2024]
Abstract
RATIONALE The specific location of deviations from normative models of brain function varies considerably across individuals with the same diagnoses. However, as pathological processes are distributed across interconnected systems, this heterogeneity of individual brain deviations may also reveal similarities and differences between disorders. The paraventricular nucleus of the thalamus (PVT) is a potential switcher to various behavioral responses where functionally distinct cell types exist across its antero-posterior axis. OBJECTIVES This study aimed to test the hypothesis that genotype-dependent differences in the anterior and posterior PVT subregions (aPVT and pPVT) are involved in the Sign-tracking (ST) behavior expressed by C57BL/6J (C57) and DBA/2J (DBA) inbred mice. METHODS Based on previous findings, male mice of the two strains were tested at ten weeks of age. The density of c-Fos immunoreactivity along the antero-posterior axis of PVT was assessed following the expression of ST behavior. Selective excitotoxic lesions of the aPVT or the pPVT by the NMDA infusion were performed prior to development of ST behavior. Finally, the distribution of neuronal populations expressing the Drd2 and Gal genes (D2R + and Gal +) was measured by in situ hybridization (ISH). RESULTS The involvement of PVT subregions in ST behavior is strain-specific, as aPVT is crucial for ST acquisition in DBA mice while pPVT is crucial for C57 mice. Despite similar antero-posterior distribution of D2R + and Gal + neurons, density of D2R + neurons differentiate aPVT in C57 and DBA mice. CONCLUSIONS These genotype-dependent results offer valuable insights into the nuanced organization of brain networks and individual variability in behavioral responses.
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Affiliation(s)
- Valeria Tarmati
- Department of Psychology, Sapienza University of Rome, Rome, Italy.
| | - Andrea Sepe
- PhD Program in Behavioral Neuroscience, Department of Psychology, Sapienza University of Rome, Rome, Italy
| | | | - David Conversi
- Department of Psychology, Sapienza University of Rome, Rome, Italy
| | - Daniela Laricchiuta
- Department of Philosophy, Social Sciences & Education, University of Perugia, Perugia, Italy
| | | | - Sonia Canterini
- Department of Psychology, Sapienza University of Rome, Rome, Italy
| | | | - Simona Cabib
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Fondazione Santa Lucia IRCCS, Rome, Rome, Italy
| | - Cristina Orsini
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Fondazione Santa Lucia IRCCS, Rome, Rome, Italy
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7
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Kraus A, Dohm K, Borgers T, Goltermann J, Grotegerd D, Winter A, Thiel K, Flinkenflügel K, Schürmeyer N, Hahn T, Langer S, Kircher T, Nenadić I, Straube B, Jamalabadi H, Alexander N, Jansen A, Stein F, Brosch K, Usemann P, Teutenberg L, Thomas-Odenthal F, Meinert S, Dannlowski U. Brain structural correlates of an impending initial major depressive episode. Neuropsychopharmacology 2025; 50:1176-1185. [PMID: 40074869 PMCID: PMC12089404 DOI: 10.1038/s41386-025-02075-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2024] [Revised: 01/20/2025] [Accepted: 02/17/2025] [Indexed: 03/14/2025]
Abstract
Neuroimaging research has yet to elucidate whether reported gray matter volume (GMV) alterations in major depressive disorder (MDD) exist already before the onset of the first episode. Recruitment of presently healthy individuals with a subsequent transition to MDD (converters) is extremely challenging but crucial to gain insights into neurobiological vulnerability. Hence, we compared converters to patients with MDD and sustained healthy controls (HC) to distinguish pre-existing neurobiological markers from those emerging later in the course of depression. Combining two clinical cohorts (n = 1709), voxel-based morphometry was utilized to analyze GMV of n = 45 converters, n = 748 patients with MDD, and n = 916 HC in a region-of-interest approach and exploratory whole-brain. By contrasting the subgroups and considering both remission state and reported recurrence at a 2-year clinical follow-up, we stepwise disentangled effects of (1) vulnerability, (2) the acute depressive state, and (3) an initial vs. a recurrent episode. Analyses revealed higher amygdala GMV in converters relative to HC (ptfce-FWE = 0.037, d = 0.447) and patients (ptfce-FWE = 0.005, d = 0.508), remaining significant when compared to remitted patients with imminent recurrence. Lower GMV in the dorsolateral prefrontal cortex (ptfce-FWE < 0.001, d = 0.188) and insula (ptfce-FWE = 0.010, d = 0.186) emerged in patients relative to HC but not to converters, driven by patients with acute MDD. By examining one of the largest available converter samples in psychiatric neuroimaging, this study allowed a first determination of neural markers for an impending initial depressive episode. Our findings suggest a temporary vulnerability, which in combination with other common risk factors might facilitate prediction and in turn improve prevention of depression.
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Grants
- This work is part of the German multicenter consortium “Neurobiology of Affective Disorders. A translational perspective on brain structure and function“, funded by the consortia grants from the German Research Foundation (Deutsche Forschungsgemeinschaft DFG; Forschungsgruppe/Research Unit FOR2107) FOR 2107 and SFB/TRR 393 (grant FOR2107 KI588/14-1, KI588/14-2, KI588/15-1, KI588/17-1, KI588/20-1, KI588/22-1 to TK, DA1151/5-1, DA1151/5-2, DA1151/6-1, DA1151/9-1, DA1151/10-1, DA1151/11-1 to UD, STR1146/18-1 to BS, NE2254/1-2, NE2254/2-1, NE2254/3-1, NE2254/4-1 to IN, JA1890/7-1, JA1890/7-2 to AJ, HA7070/2-2 to TH; grant SFB-TRR393, Projects A01 and S03 to TH, A02 and Z to TK, A02 and S02 to UD; A04 to SM, A04 and C02 to IN, B01 and INF to AJ, B03 and RTG to BS, B03 and S03 to HJ, B05 and S02 to NA, INF to FS), the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/022/22 to UD) and the “Innovative Medizinische Forschung“ (IMF) of the medical faculty Münster (grant ME122205 to SM; grant KO-121806 to KD).
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Affiliation(s)
- Anna Kraus
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tiana Borgers
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Kira Flinkenflügel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Navid Schürmeyer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Simon Langer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
| | - Nina Alexander
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
- Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Giessen, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.
- Institute for Translational Neuroscience, University of Münster, Münster, Germany.
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
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Song S, Wang S, Gao J, Zhu L, Zhang W, Wang Y, Wang D, Zhang D, Wang K. Predicting treatment response in individuals with major depressive disorder using structural MRI-based similarity features. BMC Psychiatry 2025; 25:540. [PMID: 40420009 PMCID: PMC12105223 DOI: 10.1186/s12888-025-06945-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2025] [Accepted: 05/07/2025] [Indexed: 05/28/2025] Open
Abstract
BACKGROUND Major Depressive Disorder (MDD) is a prevalent mental health condition with significant societal impact. Structural magnetic resonance imaging (sMRI) and machine learning have shown promise in psychiatry, offering insights into brain abnormalities in MDD. However, predicting treatment response remains challenging. This study leverages inter-brain similarity from sMRI as a novel feature to enhance prediction accuracy and explore disease mechanisms. The method's generalizability across adult and adolescent cohorts is also evaluated. METHODS The study included 172 participants. Based on remission status, 39 participants from the Hangzhou Dataset and 34 from the Jinan Dataset were selected for further analysis. Three methods were used to extract brain similarity features, followed by a statistical test for feature selection. Six machine learning classifiers were employed to predict treatment response, and their generalizability was tested using the Jinan Dataset. Group analyses between remission and non-remission groups were conducted to identify brain regions associated with treatment response. RESULTS Brain similarity features outperformed traditional metrics in predicting treatment outcomes, with the highest accuracy achieved by the model using these features. Between-group analyses revealed that the remission group had lower gray matter volume and density in the right precentral gyrus, but higher white matter volume (WMV). In the Jinan Dataset, significant differences were observed in the right cerebellum and fusiform gyrus, with higher WMV and density in the remission group. CONCLUSIONS This study demonstrates that brain similarity features combined with machine learning can predict treatment response in MDD with moderate success across age groups. These findings emphasize the importance of considering age-related differences in treatment planning to personalize care. TRIAL REGISTRATION Clinical trial number: not applicable.
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Affiliation(s)
- Sutao Song
- School of Information Science and Engineering, Shandong Normal University, Jinan, 250358, China.
| | - Songling Wang
- School of Information Science and Engineering, Shandong Normal University, Jinan, 250358, China
| | - Jingjing Gao
- School of Information Science and Engineering, Shandong Normal University, Jinan, 250358, China
| | - Lingkai Zhu
- School of Information Science and Engineering, Shandong Normal University, Jinan, 250358, China
| | - Wenxin Zhang
- School of Psychology, Shandong Normal University, Jinan, 250358, China
| | - Yan Wang
- Department of Psychiatry, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Donglin Wang
- Institutes of Psychological Sciences, College of Education, Hangzhou Normal University, Hangzhou, 311121, China
| | - Danning Zhang
- Shandong Mental Health Center, Shandong University, Jinan, Shandong, China.
| | - Kangcheng Wang
- School of Psychology, Shandong Normal University, Jinan, 250358, China.
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9
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Lin D, Ren Q, Ou Y, Li L, Peng D, Yang S. Neuroimaging studies of acupuncture for depressive disorder: a systematic review of published papers from 2014 to 2024. Front Psychiatry 2025; 16:1536660. [PMID: 40443752 PMCID: PMC12120174 DOI: 10.3389/fpsyt.2025.1536660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2024] [Accepted: 04/14/2025] [Indexed: 06/02/2025] Open
Abstract
Background Several neuroimaging studies have confirmed that acupuncture can elicit alterations in brain networks and regions associated with depressive disorder (DD). This review provides an overview of the methodologies and results of neuroimaging investigations into the efficacy of acupuncture in treating DD, with the intention of guiding future research objectives. Methods Neuroimaging studies of acupuncture for DD being published between February 2, 2014 and February 2, 2024, were gathered from PubMed, Cochrane Library, EMBASE, Web of Science, China National Knowledge Infrastructure, Chongqing VIP Database, WanFang Database, and Chinese Biomedical Literature Database. The methodological quality of the studies was assessed utilizing the Risk of Bias 2.0 and Risk of Bias in Non-Randomized Studies of Interventions tools. Following a qualitative analysis of the studies, relevant information regarding acupuncture interventions and brain imaging data was extracted. Results A total of 26 studies met the inclusion criteria. These studies featured a combined sample size of 1138 participants. All studies employed magnetic resonance imaging. Our findings indicate that acupuncture can affect neural activity in the cingulate gyrus, precuneus, insula, prefrontal lobe, etc. The neuroimaging results of most DD patients were correlated with the Hamilton Rating Scale for Depression scores. Conclusions The results of the current study indicate that acupuncture treatment may have a regulatory effect on the abnormal functioning of neural regions and networks in individuals diagnosed with DD. These networks are predominantly localized within various brain regions, including the default mode network, limbic system, emotion regulation and cognitive network, reward network, central executive network, salience network, and sensorimotor network. It is essential to conduct additional high-quality and multimodal neuroimaging research to expand upon these findings and elucidate the mechanisms by which acupuncture impacts patients with DD. Systematic Review Registration https://www.crd.york.ac.uk/prospero/, identifier CRD42023400557.
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Affiliation(s)
- Dezhi Lin
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Qiang Ren
- Department of Rheumatology and Immunology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Yangxu Ou
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Longlong Li
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Dezhong Peng
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Sha Yang
- School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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10
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Paris A, Amirthalingam G, Karania T, Foote IF, Dobson R, Noyce AJ, Marshall CR, Waters S. Depression and dementia: interrogating the causality of the relationship. J Neurol Neurosurg Psychiatry 2025; 96:573-581. [PMID: 39798961 DOI: 10.1136/jnnp-2024-334675] [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: 07/16/2024] [Accepted: 11/17/2024] [Indexed: 01/15/2025]
Abstract
BACKGROUND Depression is often cited as a major modifiable risk factor for dementia, though the relative contributions of a true causal relationship, reverse causality and confounding factors remain unclear. This study applied a subset of the Bradford Hill criteria for causation to depression and dementia including strength of effect, specificity, temporality, biological gradient and coherence. METHODS A total of 491 557 participants in UK Biobank aged between 40 and 69 at enrolment and followed up for a mean duration of 12.4 years were studied. Diagnoses of depression and dementia were ascertained from linked health records, self-reports and death certificate registration. Depressive symptoms were measured at enrolment using a combination of questions based on the Patient Health Questionnaire-9 depression screening questionnaire. Regional grey matter volumes were measured using T1-weighted MRI in 41 929 participants. RESULTS Depression was a strong risk factor for incident dementia with an OR of 1.76 (95% CI 1.63 to 1.90), a relationship which was found to be specific to depression rather than commonly proposed confounders. Depressive symptoms increased rapidly in the 10 years prior to dementia diagnosis. The severity of depressive symptoms showed a dose-response relationship with dementia risk. Depression at older ages correlated with reduced grey matter volume in an Alzheimer's pattern whereas younger onset depression was associated with reduced grey matter volume in the frontal lobes and cerebellum. CONCLUSIONS This study provides evidence that the link between depression and dementia is due to reverse causation with a smaller component of causation with clear evidence of both mechanisms driving the association.
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Affiliation(s)
- Alvar Paris
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Guru Amirthalingam
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Tasvee Karania
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Isabelle F Foote
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Ruth Dobson
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
- Department of Neurology, Barts Health NHS Trust, London, UK
| | - Alastair J Noyce
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
- Department of Neurology, Barts Health NHS Trust, London, UK
| | - Charles R Marshall
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
- Department of Neurology, Barts Health NHS Trust, London, UK
| | - Sheena Waters
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
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11
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Owen MJ, Bray NJ, Walters JTR, O'Donovan MC. Genomics of schizophrenia, bipolar disorder and major depressive disorder. Nat Rev Genet 2025:10.1038/s41576-025-00843-0. [PMID: 40355602 DOI: 10.1038/s41576-025-00843-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/10/2025] [Indexed: 05/14/2025]
Abstract
Schizophrenia, bipolar disorder and major depressive disorder - which are the most common adult disorders requiring psychiatric care - contribute substantially to premature mortality and morbidity globally. Treatments for these disorders are suboptimal, there are no diagnostic pathologies or biomarkers and their pathophysiologies are poorly understood. Novel therapeutic and diagnostic approaches are thus badly needed. Given the high heritability of psychiatric disorders, psychiatry has potentially much to gain from the application of genomics to identify molecular risk mechanisms and to improve diagnosis. Recent large-scale, genome-wide association studies and sequencing studies, together with advances in functional genomics, have begun to illuminate the genetic architectures of schizophrenia, bipolar disorder and major depressive disorder and to identify potential biological mechanisms. Genomic findings also point to the aetiological relationships between different diagnoses and to the relationships between adult psychiatric disorders and childhood neurodevelopmental conditions.
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Affiliation(s)
- Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK.
| | - Nicholas J Bray
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - James T R Walters
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Michael C O'Donovan
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
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12
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Whittle S, Rakesh D, Simmons JG, Schwartz O, Vijayakumar N, Allen NB. Prospective Associations Between Structural Brain Development and Onset of Depressive Disorder During Adolescence and Emerging Adulthood. Am J Psychiatry 2025:appiajp20240588. [PMID: 40329643 DOI: 10.1176/appi.ajp.20240588] [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] [Indexed: 05/08/2025]
Abstract
OBJECTIVE Brain structural alterations are consistently reported in depressive disorders, yet it remains unclear whether these alterations exist prior to disorder onset and thus may reflect a preexisting vulnerability. The authors investigated prospective adolescent neurodevelopmental risk markers for depressive disorder onset, using data from a 15-year longitudinal study. METHODS A community sample of 161 adolescents participated in neuroimaging assessments conducted during early (age 12), mid (age 16), and late (age 19) adolescence. Onsets of depressive disorders were assessed for the period spanning early adolescence through emerging adulthood (ages 12-27). Forty-six participants (28 female) experienced a first episode of a depressive disorder during the follow-up period; 83 participants (36 female) received no mental disorder diagnosis. Joint modeling was used to investigate whether brain structure (subcortical volume, cortical thickness, and surface area) or age-related changes in brain structure were associated with the risk of depressive disorder onset. RESULTS Age-related increases in amygdala volume (hazard ratio=3.01), and more positive age-related changes (i.e., greater thickening or attenuated thinning) of temporal (parahippocampal gyrus, hazard ratio=3.73; fusiform gyrus, hazard ratio=4.14), insula (hazard ratio=4.49), and occipital (lingual gyrus, hazard ratio=4.19) regions were statistically significantly associated with the onset of depressive disorder. CONCLUSIONS Relative increases in amygdala volume and temporal, insula, and occipital cortical thickness across adolescence may reflect disturbances in brain development, contributing to depression onset. This raises the possibility that prior findings of reduced gray matter in clinically depressed individuals instead reflect alterations that are caused by disorder-related factors after onset.
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Affiliation(s)
- Sarah Whittle
- Centre for Youth Mental Health, University of Melbourne, Parkville, Victoria, Australia (Whittle); Orygen, Parkville, Victoria, Australia (Whittle); Neuroimaging Department, Institute of Psychology, Psychiatry, and Neuroscience, King's College London (Whittle); Melbourne School of Psychological Sciences (Simmons) and Department of Psychiatry (Schwartz), University of Melbourne, Parkville, Victoria, Australia; Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Victoria, Australia (Vijayakumar); Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health, Geelong, Victoria, Australia (Vijayakumar); Department of Psychology, University of Oregon, Eugene (Allen)
| | - Divyangana Rakesh
- Centre for Youth Mental Health, University of Melbourne, Parkville, Victoria, Australia (Whittle); Orygen, Parkville, Victoria, Australia (Whittle); Neuroimaging Department, Institute of Psychology, Psychiatry, and Neuroscience, King's College London (Whittle); Melbourne School of Psychological Sciences (Simmons) and Department of Psychiatry (Schwartz), University of Melbourne, Parkville, Victoria, Australia; Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Victoria, Australia (Vijayakumar); Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health, Geelong, Victoria, Australia (Vijayakumar); Department of Psychology, University of Oregon, Eugene (Allen)
| | - Julian G Simmons
- Centre for Youth Mental Health, University of Melbourne, Parkville, Victoria, Australia (Whittle); Orygen, Parkville, Victoria, Australia (Whittle); Neuroimaging Department, Institute of Psychology, Psychiatry, and Neuroscience, King's College London (Whittle); Melbourne School of Psychological Sciences (Simmons) and Department of Psychiatry (Schwartz), University of Melbourne, Parkville, Victoria, Australia; Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Victoria, Australia (Vijayakumar); Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health, Geelong, Victoria, Australia (Vijayakumar); Department of Psychology, University of Oregon, Eugene (Allen)
| | - Orli Schwartz
- Centre for Youth Mental Health, University of Melbourne, Parkville, Victoria, Australia (Whittle); Orygen, Parkville, Victoria, Australia (Whittle); Neuroimaging Department, Institute of Psychology, Psychiatry, and Neuroscience, King's College London (Whittle); Melbourne School of Psychological Sciences (Simmons) and Department of Psychiatry (Schwartz), University of Melbourne, Parkville, Victoria, Australia; Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Victoria, Australia (Vijayakumar); Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health, Geelong, Victoria, Australia (Vijayakumar); Department of Psychology, University of Oregon, Eugene (Allen)
| | - Nandita Vijayakumar
- Centre for Youth Mental Health, University of Melbourne, Parkville, Victoria, Australia (Whittle); Orygen, Parkville, Victoria, Australia (Whittle); Neuroimaging Department, Institute of Psychology, Psychiatry, and Neuroscience, King's College London (Whittle); Melbourne School of Psychological Sciences (Simmons) and Department of Psychiatry (Schwartz), University of Melbourne, Parkville, Victoria, Australia; Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Victoria, Australia (Vijayakumar); Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health, Geelong, Victoria, Australia (Vijayakumar); Department of Psychology, University of Oregon, Eugene (Allen)
| | - Nicholas B Allen
- Centre for Youth Mental Health, University of Melbourne, Parkville, Victoria, Australia (Whittle); Orygen, Parkville, Victoria, Australia (Whittle); Neuroimaging Department, Institute of Psychology, Psychiatry, and Neuroscience, King's College London (Whittle); Melbourne School of Psychological Sciences (Simmons) and Department of Psychiatry (Schwartz), University of Melbourne, Parkville, Victoria, Australia; Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Victoria, Australia (Vijayakumar); Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health, Geelong, Victoria, Australia (Vijayakumar); Department of Psychology, University of Oregon, Eugene (Allen)
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13
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Yao J, Zhou Z, Tong Q, Li L, Wei J, Lu J, Hu S, Bao A, He H. Magnetic resonance imaging of postmortem human brain specimens: methodological considerations and prospects in psychoradiology. PSYCHORADIOLOGY 2025; 5:kkaf012. [PMID: 40395337 PMCID: PMC12090057 DOI: 10.1093/psyrad/kkaf012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2025] [Revised: 04/14/2025] [Accepted: 05/06/2025] [Indexed: 05/22/2025]
Abstract
Ex vivo magnetic resonance imaging (MRI) has revolutionized psychoradiological research by enabling detailed structural and pathological assessments of the brain in conditions ranging from psychiatric disorders to neurodegenerative diseases. By providing high-resolution images of postmortem brain tissue, ex vivo MRI overcomes several limitations inherent in in vivo imaging, offering unparalleled insights into the underlying pathophysiology of mental disorders. This review critically summarizes the state-of-the-art ex vivo MRI methodologies for neuroanatomical mapping and pathological characterization in psychoradiology, while also establishing standardized specimen processing protocols. Furthermore, we explore the prospects of application in ex vivo MRI in schizophrenia, major depressive disorder and bipolar disorder, highlighting its role in understanding neuroanatomical alterations, disease progression, and the validation of in vivo neuroimaging biomarkers.
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Affiliation(s)
- Junye Yao
- Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou 310027, China
- Clinical & Technical Support, Philips Healthcare, Shanghai 200072, China
| | - Zihan Zhou
- Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou 310027, China
- Stanford University Graduate School of Education, Department of Radiology, Stanford University, Stanford, CA 94305, USA
| | - Qiqi Tong
- Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou 310027, China
- Research Center for Data Hub and Security, Zhejiang Lab, Hangzhou 311121, China
| | - Lingyu Li
- Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou 310027, China
- Polytechnic Institute, Zhejiang University, Hangzhou 310015, China
| | - Jintao Wei
- Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou 310027, China
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Jing Lu
- Department of Psychiatry, the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China
| | - Shaohua Hu
- Department of Psychiatry, the First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310003, China
| | - Aimin Bao
- National Human Brain Bank for Health and Disease, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou 310058, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou 310027, China
- School of Physics, Zhejiang University, Hangzhou 310058, China
- State Key Laboratory of Brain-Machine Intelligence, Zhejiang University, Hangzhou 311121, China
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14
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Ping L, Chu Z, Zhou B, Sun D, Chu J, Xu J, Li Z, Zhang D, Cheng Y. Structural alterations after repetitive transcranial magnetic stimulation in depression and the link to neurotransmitter profiles. Asian J Psychiatr 2025; 107:104445. [PMID: 40117801 DOI: 10.1016/j.ajp.2025.104445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2024] [Revised: 03/04/2025] [Accepted: 03/08/2025] [Indexed: 03/23/2025]
Abstract
BACKGROUND Repetitive Transcranial Magnetic Stimulation (rTMS) is widely used to treat depression, showing good efficacy and tolerability. However, the neurobiological mechanisms of its antidepressant effects remain unclear. This study explores the potential impact of rTMS on brain structure in depressed patients and its link to neurotransmitter systems. METHODS Thirty-six MDD patients were randomized to receive 5 times per week for 3 weeks of active or sham rTMS targeting the dorsolateral prefrontal cortex (DLPFC) within a double-blind, sham-controlled trial. The Hamilton Depression Rating Scale-17 items (HAMD-17) was used to assess depressive symptoms at baseline and the end of 1 W, 2 W and 3 W after treatment. We analyzed the differences in efficacy between the two groups of patients at different time points, and the grey matter changes of the brain before and after treatment in both groups. In addition, we analyzed the spatial correlations between abnormal grey matter and the neurotransmitter receptors and transporters map. RESULTS Both the active and sham groups showed significant improvement in depression and anxiety symptoms following rTMS treatment, with the Active group demonstrating greater improvement. Additionally, the Active group exhibited increased grey matter volume in regions associated with the frontal-limbic network, and these changes were significantly correlated with the spatial distribution of D1 receptors. CONCLUSION This study suggests that rTMS targeting the left DLPFC produces antidepressant effects by enhancing structural plasticity in the frontal-limbic network, and that dopamine system modulation may underlie rTMS therapeutic effects. These findings provide insight into the neurobiological basis of rTMS for depression treatment.
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Affiliation(s)
- Liangliang Ping
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650032, China; Department of Psychiatry, Xiamen Xianyue Hospital, Xiamen, Fujian 361000, China; Xianyue Hospital Affiliated with Xiamen Medical College, Xiamen, Fujian 361000, China; Fujian Psychiatric Center, Xiamen, Fujian 361000, China; Fujian Clinical Research Center for Mental Disorders, Xiamen, Fujian 361000, China
| | - Zhaosong Chu
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, Guangdong 528000, China
| | - Biao Zhou
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650032, China
| | - Duo Sun
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650032, China
| | - Jiangmin Chu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650032, China
| | - Jian Xu
- Department of Rheumatology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan 650032, China
| | - Zhenhui Li
- Department of Radiology, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, Yunnan 650118, China
| | - Dafu Zhang
- Department of Radiology, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, Yunnan 650118, China.
| | - Yuqi Cheng
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310063, China.
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15
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Xian Z, Tian L, Yao Z, Cao L, Jia Z, Li G. Mechanism of N6-Methyladenosine Modification in the Pathogenesis of Depression. Mol Neurobiol 2025; 62:5484-5500. [PMID: 39551913 DOI: 10.1007/s12035-024-04614-6] [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: 04/14/2024] [Accepted: 11/05/2024] [Indexed: 11/19/2024]
Abstract
N6-methyladenosine (m6A) is one of the most common post-transcriptional RNA modifications, which plays a critical role in various bioprocesses such as immunological processes, stress response, cell self-renewal, and proliferation. The abnormal expression of m6A-related proteins may occur in the central nervous system, affecting neurogenesis, synapse formation, brain development, learning and memory, etc. Accumulating evidence is emerging that dysregulation of m6A contributes to the initiation and progression of psychiatric disorders including depression. Until now, the specific pathogenesis of depression has not been comprehensively clarified, and further investigations are warranted. Stress, inflammation, neurogenesis, and synaptic plasticity have been implicated as possible pathophysiological mechanisms underlying depression, in which m6A is extensively involved. Considering the extensive connections between depression and neurofunction and the critical role of m6A in regulating neurological function, it has been increasingly proposed that m6A may have an important role in the pathogenesis of depression; however, the results and the specific molecular mechanisms of how m6A methylation is involved in major depressive disorder (MDD) were varied and not fully understood. In this review, we describe the underlying molecular mechanisms between m6A and depression from several aspects including inflammation, stress, neuroplasticity including neurogenesis, and brain structure, which contain the interactions of m6A with cytokines, the HPA axis, BDNF, and other biological molecules or mechanisms in detail. Finally, we summarized the perspectives for the improved understanding of the pathogenesis of depression and the development of more effective treatment approaches for this disorder.
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Affiliation(s)
- Zhuohang Xian
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Liangjing Tian
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Zhixuan Yao
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Lei Cao
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Zhilin Jia
- West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Gangqin Li
- Department of Forensic Psychiatry, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, 610041, Sichuan, China.
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16
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Bohman H, Låftman SB, Alaie I, Ssegonja R, Jonsson U. Adult mental health outcomes of adolescent depression and co-occurring alcohol use disorder: a longitudinal cohort study. Eur Child Adolesc Psychiatry 2025; 34:1649-1659. [PMID: 39470789 PMCID: PMC12122575 DOI: 10.1007/s00787-024-02596-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 10/09/2024] [Indexed: 11/01/2024]
Abstract
Depression and alcohol use disorder (AUD) are frequently co-occurring in adolescence, which often goes undetected in routine care. While this may potentially compromise treatment effectiveness and lead to a less favourable long-term prognosis, few longitudinal studies have followed this group into adulthood. The aim of this study was to explore the risk for adult depression, anxiety disorders, suicidality, and AUD in adolescents with concurrent depression and AUD. The study was based on the Uppsala Longitudinal Adolescent Depression Study (ULADS), a Swedish prospective cohort study. Diagnostic interviews were conducted in adolescence (age 16-17) and adulthood (around age 30). Adolescents with concurrent depression and AUD (n = 38) were compared with peers having only depression (n = 189) or neither of the conditions (n = 144). Logistic regression was used to calculate adjusted odds ratios (aORs) with 95% confidence intervals (CIs). Adolescents with concurrent depression and AUD were more likely than their non-affected peers to experience adult depressive episodes (aOR, 5.33; 95% CI, 2.22-12.83), anxiety disorders (4.05; 1.77-9.27), suicidality (5.37; 2.28-12.66), and AUD (7.68; 2.59-22.81). Notably, 34% of adolescents with both depression and AUD subsequently experienced both these conditions as adults, compared to 7% of adolescents with only depression. Adolescents suffering only from depression were less likely than those with both conditions to experience suicidality (0.44; 0.21-0.95) and AUD in adulthood (0.18; 0.07-0.44). These findings underscore the clinical imperative to identify adolescents with this comorbidity. Recognition of the poor long-term prognosis can inform targeted interventions for this vulnerable group, ultimately improving health and well-being throughout the life course.
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Affiliation(s)
- Hannes Bohman
- Uppsala University, Uppsala, Sweden.
- Karolinska Institutet, Stockholm, Sweden.
| | | | - Iman Alaie
- Uppsala University, Uppsala, Sweden
- Karolinska Institutet, Stockholm, Sweden
| | | | - Ulf Jonsson
- Uppsala University, Uppsala, Sweden
- Karolinska Institutet, Stockholm, Sweden
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17
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Li ZY, Fei CJ, Yin RY, Kang JJ, Ma Q, He XY, Wu XR, Zhao YJ, Zhang W, Liu WS, Wu BS, Yang L, Zhu Y, Feng JF, Yu JT, Cheng W. Whole exome sequencing identified six novel genes for depressive symptoms. Mol Psychiatry 2025; 30:1925-1936. [PMID: 39472661 DOI: 10.1038/s41380-024-02804-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 10/17/2024] [Accepted: 10/18/2024] [Indexed: 04/24/2025]
Abstract
Previous genome-wide association studies of depression have primarily focused on common variants, limiting our comprehensive understanding of the genetic architecture. In contrast, whole-exome sequencing can capture rare coding variants, helping to explore the phenotypic consequences of altering protein-coding genes. Here, we conducted a large-scale exome-wide association study on 296,199 participants from the UK Biobank, assessing their depressive symptom scores through the Patient Health Questionnaire-4. We identified 22 genes associated with depressive symptoms, including 6 newly discovered genes (TRIM27, UBD, SVOP, ADGRB2, IRF2BPL, and ANKRD12). Both ontology enrichment analysis and plasma proteomics association analysis consistently revealed that the identified genes were associated with immune responses. Furthermore, we identified associations between these genes and brain regions related to depression, such as anterior cingulate cortex and orbitofrontal cortex. Additionally, phenome-wide association analysis demonstrated that TRIM27 and UBD were associated with neuropsychiatric, cognitive, biochemistry, and inflammatory traits. Our findings offer new insights into the potential mechanisms and genetic architecture of depressive symptoms.
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Affiliation(s)
- Ze-Yu Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Chen-Jie Fei
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Rui-Ying Yin
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Ju-Jiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Qing Ma
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Xiao-Yu He
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Xin-Rui Wu
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Yu-Jie Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Wei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Wei-Shi Liu
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Liu Yang
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Ying Zhu
- Institutes of Brain Science, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Jin-Tai Yu
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China.
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18
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Chen C, Liu Y, Sun Y, Jiang W, Yuan Y, Qing Z. Abnormal structural covariance network in major depressive disorder: Evidence from the REST-meta-MDD project. Neuroimage Clin 2025; 46:103794. [PMID: 40328096 DOI: 10.1016/j.nicl.2025.103794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2025] [Revised: 04/27/2025] [Accepted: 04/29/2025] [Indexed: 05/08/2025]
Abstract
BACKGROUND Major depressive disorder (MDD) is a common mental illness associated with brain morphological abnormalities. Although extensive studies have examined gray matter volume (GMV) changes in MDD, inconsistencies persist in reported findings. In the current study, we employed source-based morphometry (SBM) and structural covariance network (SCN) analyses to a large multi-center sample from the REST-meta-MDD database, aiming to characterize robust results of structural abnormalities in MDD. METHODS We analyzed 798 MDD patients and 974 healthy controls (HCs) from the REST-meta-MDD consortium. Voxel-based morphometry was applied to generate GMV maps. SBM was used to adaptively parcellate brain into different components, and SCN was constructed based on SBM components. Volume scores in each component and SCNs between the components were both compared between MDD and HC groups, as well as between first-episode drug-naive (FEDN) and recurrent MDD subgroups. RESULTS SBM identified 20 stable components. Three components encompassing the middle temporal gyrus, middle orbitofrontal gyrus and superior frontal gyrus exhibited volumetric differences between the MDD and HC groups. Volume differences were observed in the cingulate cortex and medial frontal gyrus between the FEDN and recurrent groups. SCN analysis revealed 9 aberrant pairs in MDD vs. HCs, and 7 pairs in FEDN vs. recurrent groups. All aberrant component pairs in the SCN implicated the prefrontal cortex. CONCLUSIONS These findings demonstrated brain structural deficits in MDD, and highlighted the prefrontal cortex as a central hub of SCN alterations. Our findings advance the understanding of MDD's neural mechanisms and suggest directions for diagnostic research.
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Affiliation(s)
- Changmin Chen
- School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China
| | - Yuhan Liu
- School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China
| | - Yu Sun
- School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China; Joint Research Center for Biomedical Engineering, Southeast University-University of Birmingham, Nanjing 210096, China
| | - Wenhao Jiang
- Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Jiangsu Provincial Key Laboratory of Brain Science and Medicine, Southeast University, Nanjing 210009, China
| | - Yonggui Yuan
- Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Jiangsu Provincial Key Laboratory of Brain Science and Medicine, Southeast University, Nanjing 210009, China
| | - Zhao Qing
- School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China; Shing-Tung Yau Center, Southeast University, Nanjing 210096, China; Joint Research Center for Biomedical Engineering, Southeast University-University of Birmingham, Nanjing 210096, China.
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19
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Goes FS, Collado-Torres L, Zandi PP, Huuki-Myers L, Tao R, Jaffe AE, Pertea G, Shin JH, Weinberger DR, Kleinman JE, Hyde TM. Large-scale transcriptomic analyses of major depressive disorder reveal convergent dysregulation of synaptic pathways in excitatory neurons. Nat Commun 2025; 16:3981. [PMID: 40295477 PMCID: PMC12037741 DOI: 10.1038/s41467-025-59115-4] [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: 01/28/2025] [Accepted: 04/10/2025] [Indexed: 04/30/2025] Open
Abstract
Major Depressive Disorder (MDD) is a common, complex disorder that is a leading cause of disability worldwide and a significant risk factor for suicide. In this study, we have performed the largest molecular analysis of MDD in postmortem human brains (846 samples across 458 individuals) in the subgenual Anterior Cingulate Cortex (sACC) and the Amygdala, two regions central to mood regulation and the pathophysiology of MDD. We found extensive expression differences, particularly at the level of specific transcripts, with prominent enrichment for genes associated with the vesicular functioning, the postsynaptic density, GTPase signaling, and gene splicing. We find associated transcriptional features in 107 of 243 genome-wide significant loci for MDD and, through integrative analyses, highlight convergence of genetic risk, gene expression, and network-based analyses on dysregulated glutamatergic signaling and synaptic vesicular functioning. Together, these results provide an initial mechanistic understanding of MDD and highlight potential targets for novel drug discovery.
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Affiliation(s)
- Fernando S Goes
- Department of Psychiatry and Behavioral Sciences, Stanley and Elizabeth Star Precision Medicine Center of Excellence in Mood Disorders, Johns Hopkins School of Medicine, Baltimore, MD, USA.
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Leonardo Collado-Torres
- The Lieber Institute for Brain Development, Baltimore, MD, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Peter P Zandi
- Department of Psychiatry and Behavioral Sciences, Stanley and Elizabeth Star Precision Medicine Center of Excellence in Mood Disorders, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Ran Tao
- The Lieber Institute for Brain Development, Baltimore, MD, USA
| | - Andrew E Jaffe
- The Lieber Institute for Brain Development, Baltimore, MD, USA
- Department of Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Geo Pertea
- The Lieber Institute for Brain Development, Baltimore, MD, USA
| | - Joo Heon Shin
- The Lieber Institute for Brain Development, Baltimore, MD, USA
| | - Daniel R Weinberger
- The Lieber Institute for Brain Development, Baltimore, MD, USA
- Department of Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joel E Kleinman
- Department of Psychiatry and Behavioral Sciences, Stanley and Elizabeth Star Precision Medicine Center of Excellence in Mood Disorders, Johns Hopkins School of Medicine, Baltimore, MD, USA
- The Lieber Institute for Brain Development, Baltimore, MD, USA
| | - Thomas M Hyde
- The Lieber Institute for Brain Development, Baltimore, MD, USA.
- Department of Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD, USA.
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
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20
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Kumar K, Liao Z, Kopal J, Moreau C, Ching CRK, Modenato C, Snyder W, Kazem S, Martin CO, Bélanger AM, Fontaine VK, Jizi K, Boen R, Huguet G, Saci Z, Kushan L, Silva AI, van den Bree MBM, Linden DEJ, Owen MJ, Hall J, Lippé S, Dumas G, Draganski B, Almasy L, Thomopoulos SI, Jahanshad N, Sønderby IE, Andreassen OA, Glahn DC, Raznahan A, Bearden CE, Paus T, Thompson PM, Jacquemont S. Cortical differences across psychiatric disorders and associated common and rare genetic variants. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.04.16.25325971. [PMID: 40321288 PMCID: PMC12047953 DOI: 10.1101/2025.04.16.25325971] [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: 05/11/2025]
Abstract
Genetic studies have identified common and rare variants increasing the risk for neurodevelopmental and psychiatric disorders (NPDs). These risk variants have also been shown to influence the structure of the cerebral cortex. However, it is unknown whether cortical differences associated with genetic variants are linked to the risk they confer for NPDs. To answer this question, we analyzed cortical thickness (CT) and surface area (SA) for common and rare variants associated with NPDs, in ~33000 individuals from the general population and clinical cohorts, as well as ENIGMA summary statistics for 8 NPDs. Rare and common genetic variants increasing risk for NPDs were preferentially associated with total SA, while NPDs were preferentially associated with mean CT. Larger effects on mean CT, but not total SA, were observed in NPD medicated subgroups. At the regional level, genetic variants were preferentially associated with effects in sensorimotor areas, while NPDs showed higher effects in association areas. We show that schizophrenia- and bipolar-disorder-associated SNPs show positive and negative effect sizes on SA suggesting that their aggregated effects cancel out in additive polygenic models. Overall, CT and SA differences associated with NPDs do not relate to those observed across individual genetic variants and may be linked with critical non-genetic factors, such as medication and the lived experience of the disorder.
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Affiliation(s)
- Kuldeep Kumar
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
| | - Zhijie Liao
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
| | - Jakub Kopal
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Clara Moreau
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Claudia Modenato
- LREN - Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Switzerland
| | - Will Snyder
- Section on Developmental Neurogenomics, Human Genetics Branch, NIMH, NIH, Bethesda, MD, USA
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Sayeh Kazem
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
| | | | | | - Valérie K Fontaine
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
| | - Khadije Jizi
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
| | - Rune Boen
- Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, UCLA, Los Angeles, USA
| | - Guillaume Huguet
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
| | - Zohra Saci
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
| | - Leila Kushan
- Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, UCLA, Los Angeles, USA
| | - Ana I Silva
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, MN, USA
| | - Marianne B M van den Bree
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom
| | - David E J Linden
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom
- Mental Health and Neuroscience Research Institute, Maastricht University, Netherlands
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Jeremy Hall
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom
| | - Sarah Lippé
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
| | - Guillaume Dumas
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
| | - Bogdan Draganski
- LREN - Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Switzerland
- Neurology Department, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Inselspital, University of Bern, Bern, Switzerland
- University Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland
| | - Laura Almasy
- Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, PA, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Penn Medicine, PA, USA
- Department of Genetics, University of Pennsylvania, PA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Ida E Sønderby
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - David C Glahn
- Harvard Medical School, Department of Psychiatry, 25 Shattuck St, Boston, MA, USA
- Boston Children's Hospital, Tommy Fuss Center for Neuropsychiatric Disease Research, 300 Longwood Avenue, Boston, MA, USA
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, NIMH, NIH, Bethesda, MD, USA
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, UCLA, Los Angeles, USA
| | - Tomas Paus
- Centre de recherche CHU Sainte-Justine and University of Montreal, Canada
- Departments of Psychiatry and Neuroscience, University of Montreal, Montreal, Quebec, Canada
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
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21
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Zhang B, Wu B, Zhang X, Xie H, Ling Y, Zhao Z, Gan R, Qiu L, Mechelli A, Jia Z, Gong Q. Gray matter structural alterations in first-episode drug-naïve adolescents with major depressive disorder: a comprehensive morphological analysis study. Psychol Med 2025; 55:e113. [PMID: 40211094 DOI: 10.1017/s0033291725000790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/12/2025]
Abstract
BACKGROUND Major depressive disorder (MDD) tends to emerge during adolescence; however, neurobiological research in adolescents has lagged behind that in adults. This study aimed to characterize gray matter (GM) structural alterations in adolescents with MDD using comprehensive morphological analyses. METHODS This study included 93 adolescent MDD patients and 77 healthy controls. Voxel-based morphometry (VBM), deformation-based morphometry (DBM), and surface-based morphometry (SBM) methods were used to analyze GM morphological alterations in adolescent MDD patients. Sex-by-group and age-by-group interactions, as well as the relationships between altered GM structure and clinical characteristics were also analyzed. RESULTS Whole-brain VBM and DBM analyses revealed GM atrophy in the left thalamus and bilateral midbrain in adolescent MDD patients. Whole-brain SBM analysis revealed that adolescent MDD patients, relative to controls, showed decreased thickness in the left postcentral gyrus and left precentral gyrus; increased thickness in the bilateral superior temporal gyrus, left parahippocampal gyrus and right lateral orbitofrontal gyrus; and decreased fractal dimension in the right lateral occipital gyrus. A significant sex-by-group interaction effect was found in the fractal dimension of the left lateral occipital gyrus. The volume of the left thalamus and the thickness of the left superior temporal gyrus were correlated with the duration of disease in adolescent MDD patients. CONCLUSIONS This study suggested that adolescent MDD had GM morphological abnormalities in the frontal-limbic, subcortical, perceptual network and midbrain regions, with some morphological abnormalities associated with disease duration and sex differences. These findings provide new insight into the neuroanatomical substrates underlying adolescent MDD.
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Affiliation(s)
- Baoshuai Zhang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Institute of Radiology and Medical Imaging, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Baolin Wu
- Department of Radiology, Huaxi MR Research Center (HMRRC), Institute of Radiology and Medical Imaging, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Xun Zhang
- Department of Radiology, Huaxi MR Research Center (HMRRC), Institute of Radiology and Medical Imaging, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Hongsheng Xie
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Yanxin Ling
- Medical Imaging Center, The Second People's Hospital of Yibin, Yibin, China
| | - Ziru Zhao
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Ruoqiu Gan
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Lihua Qiu
- Medical Imaging Center, The Second People's Hospital of Yibin, Yibin, China
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Zhiyun Jia
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), Institute of Radiology and Medical Imaging, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Xiamen Key Laboratory of Psychoradiology and Neuromodulation, Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, China
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22
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Jiang Y, Chen Y, Zheng R, Zhou B, Wei Y, Li S, Han S, Zhang Y, Cheng J. Age-related abnormalities in brain functional and molecular neuroimaging signatures in first-episode depression. Prog Neuropsychopharmacol Biol Psychiatry 2025; 138:111330. [PMID: 40081563 DOI: 10.1016/j.pnpbp.2025.111330] [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: 12/12/2024] [Revised: 03/07/2025] [Accepted: 03/09/2025] [Indexed: 03/16/2025]
Abstract
Abnormalities in resting-state brain activity have been demonstrated in depression patients with different ages, yet the age-related changes in dynamics of brain activity in depression are still limited. Here, we investigated the impacts of age on dynamics of brain activity and the molecular architecture. Resting-state functional magnetic resonance images were obtained from 138 first-episode depression patients and 120 healthy volunteers. All the participants were classified into two age cohorts, including adolescents and adults. Two-way analysis of variance was performed to examine the effect of age on dynamic amplitude of low-frequency fluctuations (ALFF) in depression. Then, cross-modal correlation analyses between dynamic ALFF and neurotransmitter maps were established. Significant diagnosis-by-age interaction of dynamic ALFF was located in medial frontal gyrus, supplementary motor area, postcentral gyrus, paracentral lobule and rolandic operculum. Dynamic ALFF alterations in the diagnosis-by-age interaction effect were associated with serotonergic, dopaminergic, noradrenergic, and GABAergic systems. These findings highlight the interaction between depression and age in brain functional and molecular neuroimaging signatures, which may be useful for future treatment strategies of different ages of depression.
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Affiliation(s)
- Yu Jiang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou 450000, China
| | - Ying Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Shuying Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
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23
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Kochunov P, Adhikari BM, Keator D, Amen D, Gao S, Karcher NR, Labate D, Azencott R, Huang Y, Syed H, Ke H, Thompson PM, Wang DJJ, Mitchell BD, Turner JA, van Erp TG, Jahanshad N, Ma Y, Du X, Burroughs W, Chen S, Ma T, Soares JC, Hong LE. Functional vs Structural Cortical Deficit Pattern Biomarkers for Major Depressive Disorder. JAMA Psychiatry 2025:2832270. [PMID: 40172866 PMCID: PMC11966481 DOI: 10.1001/jamapsychiatry.2025.0192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2024] [Accepted: 01/01/2025] [Indexed: 04/04/2025]
Abstract
Importance Major depressive disorder (MDD) is a severe mental illness characterized more by functional rather than structural brain abnormalities. The pattern of regional homogeneity (ReHo) deficits in MDD may relate to underlying regional hypoperfusion. Capturing this functional deficit pattern provides a brain pattern-based biomarker for MDD that is linked to the underlying pathophysiology. Objective To examine whether cortical ReHo patterns provide a replicable biomarker for MDD that is more sensitive than reduced cortical thickness and evaluate whether the ReHo MDD deficit pattern reflects regional cerebral blood flow (RCBF) deficit patterns in MDD and whether a regional vulnerability index (RVI) thus constructed may provide a concise brain pattern-based biomarker for MDD. Design, Settings, and Participants The UK Biobank (UKBB) participants had ReHo and structural measurements. Participants from the Enhancing Neuroimaging Genetics Through Meta-Analysis (ENIGMA) Consortium were included for measuring the MDD structural cortical deficit pattern. The UKBB ReHo and ENIGMA cortical thickness effect sizes for MDD were used to test the deficit patterns in the Amish Connectome Project (ACP) with ReHo, structural, and RCBF data. Finally, the Ament Clinic Inc (ACI) sample had RCBF data measured using single-photon emission computed tomography. Data were analyzed from August 2021 to September 2024. Exposures ReHo and structural measurements. Results Included in this analysis were 4 datasets: (1) UKBB (N = 4810 participants; 2220 with recurrent MDD and 2590 controls; mean [SD] age, 63.0 [7.5] years; 1121 female [50%]), (2) ENIGMA (N = 10 115 participants; 2148 with MDD and 7957 healthy controls; mean [SD] age, 39.9 [10.0] years; 5927 female [59%]), (3) ACP (N = 204 participants; 68 with a lifetime diagnosis of MDD and 136 controls; mean [SD] age, 41.0 [14.5] years; 104 female [51%]), and (4) ACI (N = 372 participants; 296 with recurrent MDD and 76 controls; mean [SD] age, 45.3 [17.2] years; 189 female [51%]). MDD participants had lower cortical ReHo in the cingulum, superior temporal lobe, frontal lobe, and several other areas, with no significant differences in cortical thickness. The regional pattern of ReHo MDD effect sizes was significantly correlated with that of RCBF obtained from 2 independent datasets (Pearson r = 0.52 and Pearson r = 0.46; P < 10-4). ReHo and RCBF functional RVIs showed numerically stronger effect sizes (Cohen d = 0.33-0.90) compared with structural RVIs (Cohen d = 0.09-0.20). Elevated ReHo-based RVI-MDD values in individuals with MDD were associated with higher depression symptom severity across cohorts. Conclusions and Relevance Results of this case-control study suggest that the ReHo MDD deficit pattern reflected cortical hypoperfusion and was regionally specific in MDD. ReHo-based RVI may serve as a sensitive functional biomarker for MDD.
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Affiliation(s)
- Peter Kochunov
- Department of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston
| | - Bhim M. Adhikari
- Department of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston
| | - David Keator
- Amen Clinics Inc, Costa Mesa, California
- Department of Psychiatry and Human Behavior, University of California, Irvine
- Change Your Brain Change Your Life Foundation, Costa Mesa, California
| | - Daniel Amen
- Amen Clinics Inc, Costa Mesa, California
- Change Your Brain Change Your Life Foundation, Costa Mesa, California
| | - Si Gao
- Department of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston
| | - Nicole R. Karcher
- Department of Psychiatry, Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Demetrio Labate
- Departments of Mathematics, University of Houston, Houston, Texas
| | - Robert Azencott
- Departments of Mathematics, University of Houston, Houston, Texas
| | - Yewen Huang
- Departments of Mathematics, University of Houston, Houston, Texas
| | - Hussain Syed
- Departments of Mathematics, University of Houston, Houston, Texas
| | - Hongjie Ke
- Department of Biostatistics, University of Maryland College Park, College Park
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey
| | - Danny J. J. Wang
- Laboratory of Functional MRI Technology, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles
| | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, Maryland
| | - Jessica A. Turner
- Department of Psychiatry and Behavioral Science, The Ohio State University College of Medicine, Columbus
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine
- Center for the Neurobiology of Learning and Memory, University of California Irvine
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey
| | - Yizhou Ma
- Department of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston
| | - Xiaoming Du
- Department of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston
| | - William Burroughs
- Department of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston
| | - Shuo Chen
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore
| | - Tianzhou Ma
- Department of Biostatistics, University of Maryland College Park, College Park
| | - Jair C. Soares
- Department of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston
| | - L. Elliot Hong
- Department of Psychiatry and Behavioral Sciences, UTHealth Houston School of Behavioral Health Sciences, University of Texas Health Science Center at Houston, Houston
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24
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Yunzhi P, Mingjun Z, Yuqing C, Lin H, Weiqing H, Wenjian T, Danqing H, Jun Y, Yixing C, Xudong C. Spatial patterns of individual morphological deformation in schizophrenia: Putative cortical compensatory of unaffected sibling. Prog Neuropsychopharmacol Biol Psychiatry 2025; 138:111329. [PMID: 40090456 DOI: 10.1016/j.pnpbp.2025.111329] [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: 12/19/2024] [Revised: 03/05/2025] [Accepted: 03/09/2025] [Indexed: 03/18/2025]
Abstract
BACKGROUND Neuroimaging advancements have revealed morphological deformation across various indicators, illuminating the neuropathological origins of schizophrenia. However, consolidating the findings across indicators and assessing regional global deformation at individual-level poses a significant challenge. METHODS We propose individual morphological deformation index (IMDI) as potential biomarker for schizophrenia leveraging a distance algorithm that incorporates three key indicators (cortical thickness, gyrification, and volume), and applied it for 199 schizophrenia patients, 218 healthy controls, and 47 unaffected siblings. Additionally, we studied the relationships between polygenic risks, symptomology, cognition, social functioning and regional IMDI. RESULTS Our findings reveal significantly higher IMDI in specific brain regions (bilateral pars opercularis, lateral orbitofrontal, left superior parietal, right pars orbitalis, and superior temporal) in patients, demonstrating two distinct spatial patterns linked to either isolated indicator reduction or concurrent declines across multiple indicators. Notably, unaffected siblings exhibited higher IMDI than controls, primarily due to cortical volume expansion in the right pars opercularis and superior temporal regions. Patients with higher IMDI had more severe positive symptoms, impaired cognition, reduced social functioning and selfcare ability. Participants with higher polygenic scores showed higher IMDI specifically in left caudal middle frontal regions. CONCLUSIONS The proposed IMDI biomarker offers an objective, interpretable way to quantify global regional deformation and integrate disparate neuroimaging indicators. Our results indicate that schizophrenia-related cortical deformations encompass sensorimotor, attention, default mode, and frontoparietal networks, exhibiting at least two spatial patterns. Moreover, siblings may exhibit compensation in cortical volume. These insights offer a novel perspective on the neuroanatomical underpinnings of schizophrenia.
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Affiliation(s)
- Pan Yunzhi
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zhong Mingjun
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chen Yuqing
- Hunan College of Foreign Studies, Changsha, Hunan, China
| | - Han Lin
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Huang Weiqing
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Tan Wenjian
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Huang Danqing
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Yang Jun
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Cheng Yixing
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chen Xudong
- Department of Psychiatry, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
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25
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Koike S, Tanaka SC, Hayashi T. Beyond case-control study in neuroimaging for psychiatric disorders: Harmonizing and utilizing the brain images from multiple sites. Neurosci Biobehav Rev 2025; 171:106063. [PMID: 40020797 DOI: 10.1016/j.neubiorev.2025.106063] [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: 09/18/2024] [Revised: 01/15/2025] [Accepted: 02/09/2025] [Indexed: 03/03/2025]
Abstract
Recent magnetic resonance imaging (MRI) research has advanced our understanding of brain pathophysiology in psychiatric disorders. This progress necessitates re-evaluation of the diagnostic system for psychiatric disorders based on MRI-based biomarkers, with implications for precise clinical diagnosis and optimal therapeutics. To achieve this goal, large-scale multi-site studies are essential to develop a standardized MRI database, with the analysis of several thousands of images and the incorporation of new data. A critical challenge in these studies is to minimize sampling and measurement biases in MRI studies to accurately capture the diversity of disease-derived biomarkers. Various techniques have been employed to consolidate datasets from multiple sites in case-control studies. Traveling subject harmonization stands out as a powerful tool that can differentiate measurement bias from sample variety and sampling bias. A non-linear statistical model for a normative trajectory across the lifespan also strengthens the database to mitigate sampling bias from known factors such as age and sex. These approaches can enhance the alterations between psychiatric disorders and integrate new data and follow-up scans into existing life-course trajectory, enhancing the reliability of machine learning classification and subtyping. Although this approach has been developed using T1-weighted structural image features, future research may extend this framework to other modalities and measures. The required sample size and methodological establishment are needed for future investigations, leading to novel insights into the brain pathophysiology of psychiatric disorders and the development of optimal therapeutics for bedside clinical applications. Sharing big data and their findings also need to be considered.
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Affiliation(s)
- Shinsuke Koike
- University of Tokyo Institute for Diversity and Adaptation of Human Mind, The University of Tokyo, Tokyo 153-8902, Japan; Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo 153-8902, Japan; The International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo Institutes for Advanced Study (UTIAS), Tokyo 113-8654, Japan.
| | - Saori C Tanaka
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto 619-0288 Japan; Division of Information Science, Nara Institute of Science and Technology, Nara 630-0192, Japan
| | - Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Hyogo 351-0198, Japan; Department of Brain Connectomics, Kyoto University Graduate School of Medicine, Kyoto 606-8501, Japan
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26
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Sălcudean A, Bodo CR, Popovici RA, Cozma MM, Păcurar M, Crăciun RE, Crisan AI, Enatescu VR, Marinescu I, Cimpian DM, Nan AG, Sasu AB, Anculia RC, Strete EG. Neuroinflammation-A Crucial Factor in the Pathophysiology of Depression-A Comprehensive Review. Biomolecules 2025; 15:502. [PMID: 40305200 PMCID: PMC12024626 DOI: 10.3390/biom15040502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2025] [Revised: 03/26/2025] [Accepted: 03/27/2025] [Indexed: 05/02/2025] Open
Abstract
Depression is a multifactorial psychiatric condition with complex pathophysiology, increasingly linked to neuroinflammatory processes. The present review explores the role of neuroinflammation in depression, focusing on glial cell activation, cytokine signaling, blood-brain barrier dysfunction, and disruptions in neurotransmitter systems. The article highlights how inflammatory mediators influence brain regions implicated in mood regulation, such as the hippocampus, amygdala, and prefrontal cortex. The review further discusses the involvement of the hypothalamic-pituitary-adrenal (HPA) axis, oxidative stress, and the kynurenine pathway, providing mechanistic insights into how chronic inflammation may underlie emotional and cognitive symptoms of depression. The bidirectional relationship between inflammation and depressive symptoms is emphasized, along with the role of peripheral immune responses and systemic stress. By integrating molecular, cellular, and neuroendocrine perspectives, this review supports the growing field of immunopsychiatry and lays the foundation for novel diagnostic biomarkers and anti-inflammatory treatment approaches in depression. Further research in this field holds promise for developing more effective and personalized interventions for individuals suffering from depression.
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Affiliation(s)
- Andreea Sălcudean
- Department of Ethics and Social Sciences, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540142 Târgu Mureș, Romania; (A.S.); (M.-M.C.); (D.-M.C.)
| | - Cristina-Raluca Bodo
- Department of Ethics and Social Sciences, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540142 Târgu Mureș, Romania; (A.S.); (M.-M.C.); (D.-M.C.)
| | - Ramona-Amina Popovici
- Department of Management and Communication in Dental Medicine, Faculty of Dental Medicine, Victor Babes University of Medicine and Pharmacy of Timisoara, 9 Revolutiei 1989 Bv., 300070 Timisoara, Romania
| | - Maria-Melania Cozma
- Department of Ethics and Social Sciences, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540142 Târgu Mureș, Romania; (A.S.); (M.-M.C.); (D.-M.C.)
| | - Mariana Păcurar
- Orthodontic Department, Faculty of Dental Medicine, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540142 Târgu Mures, Romania;
| | | | - Andrada-Ioana Crisan
- Doctoral School, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540142 Târgu Mureș, Romania;
| | - Virgil-Radu Enatescu
- Department of Psychiatry, Faculty of Medicine, Victor Babes University of Medicine and Pharmacy of Timisoara, 300041 Timisoara, Romania;
| | - Ileana Marinescu
- Discipline of Psychiatry, Faculty of Medicine, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania;
| | - Dora-Mihaela Cimpian
- Department of Ethics and Social Sciences, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540142 Târgu Mureș, Romania; (A.S.); (M.-M.C.); (D.-M.C.)
| | - Andreea-Georgiana Nan
- First Department of Psychiatry, Clinical County Hospital of Targu Mures, 540142 Târgu Mureș, Romania; (A.-G.N.); (A.-B.S.)
| | - Andreea-Bianca Sasu
- First Department of Psychiatry, Clinical County Hospital of Targu Mures, 540142 Târgu Mureș, Romania; (A.-G.N.); (A.-B.S.)
| | - Ramona-Camelia Anculia
- Discipline of Occupational Medicine, Faculty of Medicine, Victor Babes University of Medicine and Pharmacy of Timisoara, 300041 Timișoara, Romania;
| | - Elena-Gabriela Strete
- Department of Psychiatry, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540142 Târgu Mureș, Romania;
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27
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Elfaki LA, Sharma B, Meusel LAC, So I, Colella B, Wheeler AL, Harris JE, Green REA. Examining anterior prefrontal cortex resting-state functional connectivity patterns associated with depressive symptoms in chronic moderate-to-severe traumatic brain injury. Front Neurol 2025; 16:1541520. [PMID: 40224311 PMCID: PMC11985445 DOI: 10.3389/fneur.2025.1541520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2024] [Accepted: 03/03/2025] [Indexed: 04/15/2025] Open
Abstract
In chronic moderate-to-severe TBI (msTBI), depression is one of the most common psychiatric consequences. Yet to date, there is limited understanding of its neural underpinnings. This study aimed to better understand this gap by examining seed-to-voxel connectivity in depression, with all voxel-wise associations seeded to the bilateral anterior prefrontal cortices (aPFC). In a secondary analysis of 32 patients with chronic msTBI and 17 age-matched controls acquired from the Toronto Rehab TBI Recovery Study database, the Personality Assessment Inventory Depression scale scores were used to group patients into an msTBI-Dep group (T ≥ 60; n = 13) and an msTBI-Non-Dep group (T < 60; n = 19). Resting-state fMRI scans were analyzed using seed-based connectivity analyses. F-tests, controlling for age and education, were used to assess differences in bilateral aPFC rsFC across the 3 groups. After nonparametric permutation testing, the left aPFC demonstrated significantly increased rsFC with the left (p = 0.041) and right (p = 0.013) fusiform gyri, the right superior temporal lobe (p = 0.032), and the right precentral gyrus (p = 0.042) in the msTBI-Dep group compared to controls. The msTBI-Non-Dep group had no significant rsFC differences with either group. To our knowledge, this study is the first to examine aPFC rsFC in a sample of patients with msTBI exclusively. Our preliminary findings suggest a role for the aPFC in the pathophysiology of depressive symptoms in patients with chronic msTBI. Increased aPFC-sensory/motor rsFC could be associated with vulnerability to depression post-TBI, a hypothesis that warrants further investigation.
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Affiliation(s)
- Layan A. Elfaki
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- The KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
| | - Bhanu Sharma
- Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
| | - Liesel-Ann C. Meusel
- The KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
| | - Isis So
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Brenda Colella
- The KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
| | - Anne L. Wheeler
- Neuroscience and Mental Health Program, The Hospital for Sick Children, Toronto, ON, Canada
- Physiology Department, University of Toronto, Toronto, ON, Canada
| | - Jocelyn E. Harris
- Faculty of Health Sciences, School of Rehabilitation Science, McMaster University, Hamilton, ON, Canada
| | - Robin E. A. Green
- The KITE Research Institute, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada
- Rehabilitation Sciences Institute, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
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28
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Wang Y, Wang B, Zhu D, Zheng W, Sheng Y. Revealing morphological fingerprints in perinatal brains using quasi-conformal mapping: occurrence and neurodevelopmental implications. Brain Imaging Behav 2025:10.1007/s11682-025-00998-8. [PMID: 40146450 DOI: 10.1007/s11682-025-00998-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/18/2025] [Indexed: 03/28/2025]
Abstract
The morphological fingerprint in the brain is capable of identifying the uniqueness of an individual. However, whether such individual patterns are present in perinatal brains, and which morphological attributes or cortical regions better characterize the individual differences of neonates remain unclear. In this study, we proposed a deep learning framework that projected three-dimensional spherical meshes of three morphological features (i.e., cortical thickness, mean curvature, and sulcal depth) onto two-dimensional planes through quasi-conformal mapping, and employed the ResNet18 and contrastive learning for individual identification. We used the cross-sectional structural MRI data of 461 infants, incorporating with data augmentation, to train the model and fine-tuned the parameters based on 41 infants who had longitudinal scans. The model was validated on a fold of 20 longitudinal scanned infant data, and remarkable Top1 and Top5 accuracies of 85.90% and 92.20% were achieved, respectively. The sensorimotor and visual cortices were recognized as the most contributive regions in individual identification. Moreover, morphological fingerprints successfully predicted the long-term development of cognition and behavior. Furthermore, the folding morphology demonstrated greater discriminative capability than the cortical thickness. These findings provided evidence for the emergence of morphological fingerprints in the brain at the beginning of the third trimester, which may hold promising implications for understanding the formation of individual uniqueness, and predicting long-term neurodevelopmental risks in the brain during early development.
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Affiliation(s)
- Ying Wang
- School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Boyang Wang
- School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Dalin Zhu
- Department of Medical Imaging Center, Gansu Maternity and Child-Care Hospital (Gansu Provincial Central Hospital), Lanzhou, China
| | - Weihao Zheng
- School of Information Science and Engineering, Lanzhou University, Lanzhou, China.
| | - Yucen Sheng
- School of Foreign Languages, Lanzhou Jiaotong University, Lanzhou, China.
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29
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Ivanović A, Petrović J, Stanić D, Nedeljković J, Ilić M, Jukić MM, Pejušković B, Pešić V. Single subanesthetic dose of ketamine exerts antioxidant and antidepressive-like effect in ACTH-induced preclinical model of depression. Mol Cell Neurosci 2025; 133:104006. [PMID: 40157469 DOI: 10.1016/j.mcn.2025.104006] [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: 08/11/2024] [Revised: 02/25/2025] [Accepted: 03/18/2025] [Indexed: 04/01/2025] Open
Abstract
Hyperactivity of the hypothalamic-pituitary-adrenal (HPA) axis and oxidative stress represent important mechanisms that have been implicated in etiopathology of depression. Although first antidepressants were introduced in clinical practice more than six decades ago, approximately 30 % of patients with a diagnosis of depression show treatment resistance. A noncompetitive N-methyl-d-aspartate receptor antagonist ketamine has shown promising rapid antidepressant effects and has been approved for treatment-resistant depression (TRD). In the present study, we investigated antioxidant and antidepressant-like activity of a single subanesthetic dose of ketamine (10 mg/kg, ip) in a rodent model of TRD induced by adrenocorticotropic hormone (10 μg ACTH/day, sc, 21 days). Behavioral assessment was performed, and plasma biomarkers of oxidative stress and DNA damage in peripheral blood lymphocytes (PBLs) were determined. We observed that ACTH produced depressive-like behavior and significant increase in superoxide anion (O2·-), advanced oxidation protein products (AOPP), malondialdehyde (MDA) and total oxidant status (TOS) in male Wistar rats. This effect was accompanied by reduced activity of antioxidant enzymes - superoxide dismutase (SOD) and paraoxonase1 (PON1) in plasma and increase in DNA damage in PBLs. In the described model of TRD, we have demonstrated antidepressant effects of ketamine for the first time. Our results reveal that ketamine was effective in reducing O2.-, AOPP, MDA and TOS, while enhancing SOD and PON1 activity in ACTH-rats. Collectively, our study sheds light on molecular mechanisms implicated in antioxidant activity of ketamine, thus incentivizing further investigation of its effects on ROS metabolism and antioxidant defenses in clinical trials, particularly in depression.
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Affiliation(s)
- Ana Ivanović
- Department of Physiology, University of Belgrade, Faculty of Pharmacy, Vojvode Stepe 450, 11121 Belgrade, Serbia
| | - Jelena Petrović
- Department of Physiology, University of Belgrade, Faculty of Pharmacy, Vojvode Stepe 450, 11121 Belgrade, Serbia
| | - Dušanka Stanić
- Department of Physiology, University of Belgrade, Faculty of Pharmacy, Vojvode Stepe 450, 11121 Belgrade, Serbia.
| | - Jelena Nedeljković
- Department of Physiology, University of Belgrade, Faculty of Pharmacy, Vojvode Stepe 450, 11121 Belgrade, Serbia
| | - Miloš Ilić
- Department of Physiology, University of Belgrade, Faculty of Pharmacy, Vojvode Stepe 450, 11121 Belgrade, Serbia
| | - Marin M Jukić
- Department of Physiology, University of Belgrade, Faculty of Pharmacy, Vojvode Stepe 450, 11121 Belgrade, Serbia; Pharmacogenetics Section, Department of Physiology and Pharmacology, Karolinska Institutet, Solna, Sweden
| | - Bojana Pejušković
- Institute of Mental Health, School of Medicine, University of Belgrade, Palmotićeva 37, 11000 Belgrade, Serbia
| | - Vesna Pešić
- Department of Physiology, University of Belgrade, Faculty of Pharmacy, Vojvode Stepe 450, 11121 Belgrade, Serbia
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30
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Bayer J, van Velzen L, Pozzi E, Davey C, Han L, Bauduin S, Bauer J, Benedetti F, Berger K, Bonnekoh L, Brosch K, Bülow R, Couvy-Duchesne B, Cullen K, Dannlowski U, Dima D, Dohm K, Evans J, Fu C, Fuentes-Claramonte P, Godlewska B, Goltermann J, Gonul A, Goya-Maldonado R, Grabe H, Groenewold N, Grotegerd D, Gruber O, Hahn T, Hall G, Hamilton J, Harrison B, Hatton S, Hermesdorf M, Hickie I, Ho T, Jahanshad N, Jansen A, Jamieson A, Kamishikiryo T, Kircher T, Klimes-Dougan B, Krämer B, Kraus A, Krug A, Leehr E, Leenings R, Li M, McIntosh A, Medland S, Meinert S, Melloni E, Mwangi B, Nenadić I, Okada G, Oudega M, Portella M, Rodríguez E, Romaniuk L, Rosa P, Sacchet M, Salvador R, Sämann P, Shinzato H, Sim K, Simulionyte E, Soares J, Stein D, Stein F, Stolicyn A, Straube B, Strike L, Teutenberg L, Thomas-Odenthal F, Thomopoulos S, Usemann P, van der Wee N, Völzke H, Wagenmakers M, Walter M, Whalley H, Whittle S, Winter N, Wittfeld K, Wu M, Yang T, Zarate C, Zunta-Soares G, Thompson P, Veltman D, Marquand A, Schmaal L. Dissecting heterogeneity in cortical thickness abnormalities in major depressive disorder: a large-scale ENIGMA MDD normative modelling study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.17.643677. [PMID: 40166143 PMCID: PMC11956935 DOI: 10.1101/2025.03.17.643677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
Abstract
Importance Major depressive disorder (MDD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology, which may obscure identification of structural brain abnormalities in MDD. To explore this, we used normative modeling to index regional patterns of variability in cortical thickness (CT) across individual patients. Objective To use normative modeling in a large dataset from the ENIGMA MDD consortium to obtain individualised CT deviations from the norm (relative to age, sex and site) and examine the relationship between these deviations and clinical characteristics. Design setting and participants A normative model adjusting for age, sex and site effects was trained on 35 CT measures from FreeSurfer parcellation of 3,181 healthy controls (HC) from 34 sites (40 scanners). Individualised z-score deviations from this norm for each CT measure were calculated for a test set of 2,119 HC and 3,645 individuals with MDD. For each individual, each CT z-score was classified as being within the normal range (95% of individuals) or within the extreme range (2.5% of individuals with the thinnest or thickest cortices). Main outcome measures Z-score deviations of CT measures of MDD individuals as estimated from a normative model based on HC. Results Z-score distributions of CT measures were largely overlapping between MDD and HC (minimum 92%, range 92-98%), with overall thinner cortices in MDD. 34.5% of MDD individuals, and 30% of HC individuals, showed an extreme deviation in at least one region, and these deviations were widely distributed across the brain. There was high heterogeneity in the spatial location of CT deviations across individuals with MDD: a maximum of 12% of individuals with MDD showed an extreme deviation in the same location. Extreme negative CT deviations were associated with having an earlier onset of depression and more severe depressive symptoms in the MDD group, and with higher BMI across MDD and HC groups. Extreme positive deviations were associated with being remitted, of not taking antidepressants and less severe symptoms. Conclusions and relevance Our study illustrates a large heterogeneity in the spatial location of CT abnormalities across patients with MDD and confirms a substantial overlap of CT measures with HC. We also demonstrate that individualised extreme deviations can identify protective factors and individuals with a more severe clinical picture.
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Affiliation(s)
- J.M.M Bayer
- Donders Institute for Brain, Cognition and Behaviour, the Netherlands
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia Australia
- Orygen, Parkville, VIC
- Radboudumc, Nijmegen, the Netherlands
| | - L.S van Velzen
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia Australia
- Orygen, Parkville, VIC
| | - E Pozzi
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia Australia
- Orygen, Parkville, VIC
| | - C Davey
- Department of Psychiatry, The University of Melbourne, Australia
| | - L.K.M Han
- Amsterdam UMC, location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | | | - J Bauer
- University Clinic for Radiology, University of Muenster, Germany
| | - F Benedetti
- Division of Neuroscience, IRCCS Sar Raffaele Scientific Institute, Milan, Italy
| | - K Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Germany
| | - L.M Bonnekoh
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy University of Münster, Germany
| | - K Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - R Bülow
- University Medicine Greifswald Institute for Radiology and Neuroradiology, Germany
| | - B Couvy-Duchesne
- Institute for Molecular Bioscience, the University of Queensland, St Lucia, QLD, Australia
- Sorbonne University, Paris Brain Institute - ICM, France
- CNRS, Inria, Inserm, AP-HP, France
- Hôpital de la Pitié Salpêtrière, F-75013, Paris, France
| | - K.R Cullen
- University of Minnesota, Minneapolis, Minnesota, USA
| | - U Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - D Dima
- Department of Psychology, School of Health and Psychological Sciences, City, University of London, London
- UK Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - K Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | | | - C.H.Y Fu
- Centre for Affective Disorders, King’s College London Department of Psychology, University of East London
| | - P Fuentes-Claramonte
- FIDMAG Germanes Hospitalaries Research Foundation, Barcelona, Spain CIBERSAM, ISCIII, Madrid, Spain
| | - B.R Godlewska
- Departement of Psychiatry, University of Oxford, UK
- Oxford Health NHS Foundation Trust, Oxford, UK
| | - J Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - A Gonul
- Ege University School of Medicine Department of Psychiatry, Turkey
| | - R Goya-Maldonado
- Laboratory of Systems Neuroscience and Imaging in Psychiatry (SNIP-Lab), Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - H.J Grabe
- University Medicine Greifswald, Germany
| | - N.A Groenewold
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - D Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - O Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Germany
| | - T Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - G.B Hall
- Dept of Psychology, Neuroscience & Behaviour, McMaster University, Ontario, USA
| | - J Hamilton
- Department of Biological and Medical Psychology; University of Bergen; Bergen, Norway
| | - B.J Harrison
- Department of Psychiatry, The University of Melbourne, Australia
| | | | - M Hermesdorf
- Institute of Epidemiology and Social Medicine, University of Münster, Germany
| | | | - T.C Ho
- Department of Psychology, University of California, Los Angeles Brain Research Institute and Interdepartmental Graduate Program in Neuroscience, University of California, Los Angeles, USA
| | - N Jahanshad
- Mark and Mary Stevens Neuroimaging and Informatics Institute Department of Biomedical Engineering, USA
| | - A Jansen
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - A.J Jamieson
- Department of Psychiatry, The University of Melbourne, Australia
| | | | - T Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | | | - B Krämer
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Germany
| | - A Kraus
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - A Krug
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Germany
| | - E.J Leehr
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - R Leenings
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - M Li
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - A McIntosh
- Division of Psychiatry, Centre for Clinical Brain Science, University of Edinburgh
| | - S.E Medland
- Queensland Institute of Medical Research, Queensland, Australia
| | - S Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - E Melloni
- Division of Neuroscience, IRCCS Sar Raffaele Scientific Institute, Milan, Italy
| | - B Mwangi
- Center of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, the University of Texas Health Science Cetner at Houston, USA
| | - I Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - G Okada
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health Sciences, Hiroshima University, Japan
| | - M. Oudega
- Amsterdam UMC, location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
- GGZinGeest, Specialized Mental Health Care, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Mood Anxiety Psychosis Sleep & Stress program, Amsterdam, the Netherlands
- Amsterdam Public Health, Mental Health program, Amsterdam, the Netherlands
| | - M.J Portella
- Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau) Universitat Autònoma de Barcelona (UAB) Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Spain
| | - E Rodríguez
- FIDMAG Germanes Hospitalaries Research Foundation, Barcelona, Spain CIBERSAM, ISCIII, Madrid, Spain
| | - L Romaniuk
- Division of Psychiatry, Centre for Clinical Brain Science, University of Edinburgh
| | - P.G. Rosa
- PLaboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Bazil
| | - M.D Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - R Salvador
- FIDMAG Germanes Hospitalaries Research Foundation, Barcelona, Spain CIBERSAM, ISCIII, Madrid, Spain
| | - P.G Sämann
- Max Planck Institute of Psychiatry, Munich, Germany
| | - H Shinzato
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health Science, Hiroshima University, Hiroshima, Japan Department of Neuropsychiatry, Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - K Sim
- Institute of Mental Health, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - E Simulionyte
- Section for Experimental Psychopathology and Neuroimaging, Department of Psychiatry, University of Heidelberg, Heidelberg, Germany
| | - J.C Soares
- Center of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, the University of Texas Health Science Cetner at Houston, USA
| | - D.J Stein
- SAMRC Unit on Risk & Resilience in Mental Disorders, Dept of Psychiatry & Neuroscience Institute, University of Cape Town. South Afrika
| | - F Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - A Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Science, University of Edinburgh
| | - B Straube
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
- Germany Center for Mind, Brain and Behavior - CMBB, Marburg, Germany
| | - L.T Strike
- Brain and Mental Health, QIMR Berghofer Medical Research Institute, Brisbane, Australia School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - L Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - F Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - S.I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA,USA
| | - P Usemann
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - N.J.A van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands Leiden Institute for Brain and Cognition, Leiden University Medical Center, The Netherlands
| | - H Völzke
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA,USA
| | - M. Wagenmakers
- GGZinGeest, Specialized Mental Health Care, Amsterdam, the Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, Noord Holland 1081 HV, The Netherlands
| | - M Walter
- Insititute for Community Medicine, University Medicine Greifswald, Germany
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Germany German Center for Mental Health (DZPG), partner site Halle-Jena-Magdeburg, Germany
- Germany Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany
| | - H.C Whalley
- Division of Psychiatry, Centre for Clinical Brain Science, University of Edinburgh
| | - S Whittle
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia Australia
- Orygen, Parkville, VIC
| | - N.R Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - K Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - M Wu
- Center of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, the University of Texas Health Science Cetner at Houston, USA
| | - T.T Yang
- Department of Psychiatry and Behavioral Sciences Division of Child and Adolescent Psychiatry University of California at San Francisco (UCSF), USA
| | - C.A Zarate
- National Institute of Mental Health, USA
| | - G.B Zunta-Soares
- Center of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, the University of Texas Health Science Cetner at Houston, USA
| | | | - D.J Veltman
- Dept. Psychiatry, Amsterdam UMC, Amsterdam, the Netherlands
| | - A.F Marquand
- Donders Institute for Brain, Cognition and Behaviour, the Netherlands
- Radboudumc, Nijmegen, the Netherlands
| | - L Schmaal
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia Australia
- Orygen, Parkville, VIC
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31
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Zhang Y, Yang T, Jin X, Huang J, Li Z, Huang C, Luo X, He Y, Cui X. Time-frequency and functional connectivity analysis in drug-naive adolescents with depression based on electroencephalography using a visual cognitive task: A comparative study. J Child Psychol Psychiatry 2025. [PMID: 40098279 DOI: 10.1111/jcpp.14154] [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] [Accepted: 02/02/2025] [Indexed: 03/19/2025]
Abstract
BACKGROUND Previous research studies have demonstrated cognitive deficits in adolescents with depression; however, the neuroelectrophysiological mechanisms underlying these deficits remain poorly understood. Utilizing electroencephalography (EEG) data collected during cognitive tasks, this study applies time-frequency analysis and functional connectivity (FC) techniques to explore the neuroelectrophysiological alterations associated with cognitive deficits in adolescents with depression. METHODS A total of 173 adolescents with depression and 126 healthy controls (HC) participated in the study, undergoing EEG while performing a visual oddball task. Delta, theta, and alpha power spectra, along with FC, were calculated and analyzed. RESULTS Adolescents with depression exhibited significantly reduced delta, theta, and alpha power at the Fz, Cz, C5, C6, Pz, P5, and P6 electrodes compared to the HC group. Notably, theta power at the F5 electrode and alpha power at the F5 and F6 electrodes were significantly lower in the depression group than in the HC group. Additionally, cortical FC in the frontal and central regions was markedly decreased in adolescents with depression compared to HC. CONCLUSIONS During cognitive tasks, adolescents with depression display distinct abnormalities in both high- and low-frequency brain oscillations, as well as reduced functional connectivity in the frontal, central, and parietal regions compared to HC. These findings offer valuable neuroelectrophysiological insights into the cognitive deficits associated with adolescent depression.
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Affiliation(s)
- Yaru Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Tingyu Yang
- Department of Child Health Care, The Affiliated Children's Hospital of Xiangya School of Medicine, Central South University (Hunan children's hospital), Changsha, China
| | - Xingyue Jin
- Department of Child and Adolescent Psychiatry, The Affiliated Kangning Hospital of Ningbo University, Ningbo, China
| | - Jinqiao Huang
- Department of psychology, The first affiliated hospital of Fujian Medical University, Fuzhou, China
| | - Zexuan Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Chunxiang Huang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xuerong Luo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yuqiong He
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xilong Cui
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
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32
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Manning KY, Llera A, Lebel C. Reliable Multimodal Brain Signatures Predict Mental Health Outcomes in Children. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2025:S2451-9022(25)00092-8. [PMID: 40107499 DOI: 10.1016/j.bpsc.2025.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2024] [Revised: 03/04/2025] [Accepted: 03/04/2025] [Indexed: 03/22/2025]
Abstract
BACKGROUND Interindividual brain differences likely precede the emergence of mood and anxiety disorders; however, the specific brain alterations remain unclear. While many studies focus on a single imaging modality in isolation, recent advances in multimodal image analysis allow for a more comprehensive understanding of the complex neurobiology that underlies mental health. METHODS In a large population-based cohort of children from the ABCD (Adolescent Brain Cognitive Development) Study (N > 10,000), we applied data-driven linked independent component analysis to identify linked variations in cortical structure and white matter microstructure that together predict longitudinal behavioral and mental health symptoms. Brain differences were examined in a subsample of twins depending on the presence of at-risk behaviors. RESULTS Two multimodal brain signatures at ages 9 to 10 years predicted longitudinal mental health symptoms from 9 to 12 years, with small effect sizes. Cortical variations in association, limbic, and default mode regions linked with peripheral white matter microstructure together predicted higher depression and anxiety symptoms across 2 independent split-halves. The brain signature differed between depression and anxiety symptom trajectories and related to emotion regulation network functional connectivity. Linked variations of subcortical structures and projection tract microstructure variably predicted behavioral inhibition, sensation seeking, and psychosis symptom severity over time in male participants. These brain patterns were significantly different between pairs of twins discordant for self-injurious behavior. CONCLUSIONS Our results demonstrate reliable, multimodal brain patterns in childhood, before mood and anxiety disorders tend to emerge, that lay the foundation for long-term mental health outcomes and offer targets for early identification of children at risk.
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Affiliation(s)
- Kathryn Y Manning
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Developmental Neuroimaging Lab, Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
| | - Alberto Llera
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, the Netherlands; LIS Data Solutions, Santander, Spain
| | - Catherine Lebel
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Developmental Neuroimaging Lab, Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
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Chi D, Zhang K, Zhang J, He Z, Zhou H, Huang W, Liu Y, Huang J, Zeng W, Bai X, Ou C, Ouyang H. Astrocytic pleiotrophin deficiency in the prefrontal cortex contributes to stress-induced depressive-like responses in male mice. Nat Commun 2025; 16:2528. [PMID: 40087317 PMCID: PMC11909280 DOI: 10.1038/s41467-025-57924-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2024] [Accepted: 03/03/2025] [Indexed: 03/17/2025] Open
Abstract
Astrocytes are closely linked to depression, and the prefrontal cortex (PFC) is an important brain region involved in major depressive disorder (MDD). However, the underlying mechanism by which astrocytes within PFC contribute to MDD remains unclear. Using single-nucleus RNA sequencing analyses, we show a significant reduction in astrocytes and attenuated pleiotrophin-protein tyrosine phosphatase receptor type Z1 (PTN-PTPRZ1) signaling in astrocyte-to-excitatory neuron communication in the PFC of male MDD patients. We find reduced astrocytes and PTN in the dorsomedial PFC of male mice with depression induced by chronic restraint and social defeat stress. Knockdown of astrocytic PTN induces depression-related responses, which is reversed by exogenous PTN supplementation or overexpression of astrocytic PTN. The antidepressant effects exerted by astrocytic PTN require interaction with PTPRZ1 in excitatory neurons, and PTN-PTPRZ1 activates the AKT signaling pathway to regulate depression-related responses. Our findings indicate the PTN-PTPRZ1-AKT pathway may be a potential therapeutic target for MDD.
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Affiliation(s)
- Dongmei Chi
- Department of Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Kun Zhang
- Department of Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Jianxing Zhang
- Department of Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Zhaoli He
- Department of Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Hongxia Zhou
- Department of Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Wan Huang
- Department of Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Yang Liu
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Jingxiu Huang
- Department of Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Weian Zeng
- Department of Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Xiaohui Bai
- Department of Anesthesiology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation; Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
| | - Chaopeng Ou
- Department of Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China.
| | - Handong Ouyang
- Department of Anesthesiology, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China.
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Li J, Long Z, Ji GJ, Han S, Chen Y, Yao G, Xu Y, Zhang K, Zhang Y, Cheng J, Wang K, Chen H, Liao W. Major depressive disorder on a neuromorphic continuum. Nat Commun 2025; 16:2405. [PMID: 40069198 PMCID: PMC11897166 DOI: 10.1038/s41467-025-57682-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Accepted: 02/25/2025] [Indexed: 03/15/2025] Open
Abstract
The heterogeneity of major depressive disorder (MDD) has hindered clinical translation and neuromarker identification. Biotyping facilitates solving the problems of heterogeneity, by dissecting MDD patients into discrete subgroups. However, interindividual variations suggest that depression may be conceptualized as a "continuum," rather than as a "category." We use a Bayesian model to decompose structural MRI features of MDD patients from a multisite cross-sectional cohort into three latent disease factors (spatial pattern) and continuum factor compositions (individual expression). The disease factors are associated with distinct neurotransmitter receptors/transporters obtained from open PET sources. Increases cortical thickness in sensory and decreases in orbitofrontal cortices (Factor 1) associate with norepinephrine and 5-HT2A density, decreases in the cingulo-opercular network and subcortex (Factor 2) associate with norepinephrine and 5-HTT density, and increases in social and affective brain systems (Factor 3) relate to 5-HTT density. Disease factor patterns can also be used to predict depressive symptom improvement in patients from the longitudinal cohort. Moreover, individual factor expressions in MDD are stable over time in a longitudinal cohort, with differentially expressed disease controls from a transdiagnostic cohort. Collectively, our data-driven disease factors reveal that patients with MDD organize along continuous dimensions that affect distinct sets of regions.
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Affiliation(s)
- Jiao Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, P.R. China
| | - Zhiliang Long
- School of Psychology, Southwest University, Chongqing, P.R. China
| | - Gong-Jun Ji
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, P.R. China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Guanqun Yao
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, P.R. China
| | - Yong Xu
- Department of Clinical Psychology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, P.R. China
| | - Kerang Zhang
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan, P.R. China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, P.R. China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, P.R. China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, P.R. China
| | - Wei Liao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China.
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, P.R. China.
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Bian Z, Shang B, Luo C, Lv F, Sun W, Gong Y, Liu J. Exploring symptom clusters and core symptoms during the vulnerable phase in patients with chronic heart failure: a network-based analysis. Eur J Cardiovasc Nurs 2025; 24:279-287. [PMID: 39743303 DOI: 10.1093/eurjcn/zvae152] [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: 05/07/2024] [Revised: 07/25/2024] [Accepted: 10/25/2025] [Indexed: 01/04/2025]
Abstract
AIMS To construct a symptom network of chronic heart failure patients in the vulnerable period and identify core symptoms and bridge symptoms between different symptom clusters. METHODS AND RESULTS A convenience sampling method was used to select 402 patients with chronic heart failure within 3 months after discharge from the cardiology departments of two tertiary-level A hospitals in Zhenjiang City, and symptom-related entries of the Minnesota living with heart failure questionnaire (MLHFQ) were used to conduct the survey. Symptom networks were constructed using the R language. The constructed symptom network was structurally stable, and the correlation stability coefficient was 0.595. In the network, 'depression' (MLHFQ9), 'dyspnoea on exertion' (MLHFQ3), and 'worry' (MLHFQ7) are the core symptoms. 'Cognitive problems' (MLHFQ8), 'sleep difficulties' (MLHFQ4), and 'fatigue' (MLHFQ6) are bridge symptoms connecting the emotional-cognitive and somatic symptom clusters. In the network comparison test, there were no significant differences in symptom networks between patients of different genders and places of residence. CONCLUSION 'Depression' and 'increased need to rest' are the core and most severe symptoms, respectively, in the vulnerable phase of chronic heart failure, and 'cognitive problems' is the most important bridge symptom. Clinical caregivers can build a precise intervention programme based on the core and bridge symptoms and focus on the emotional and cognitive symptom clusters, in order to improve the efficacy of symptom management during the vulnerable period in patients with chronic heart failure.
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Affiliation(s)
- Zekun Bian
- School of Medicine, Jiangsu University, No. 301 Xuefu Road, Jingkou District, Zhenjiang 212000, China
| | - Bin Shang
- School of Medicine, Jiangsu University, No. 301 Xuefu Road, Jingkou District, Zhenjiang 212000, China
| | - Caifeng Luo
- School of Medicine, Jiangsu University, No. 301 Xuefu Road, Jingkou District, Zhenjiang 212000, China
| | - Fei Lv
- Department of Nursing, Jingjiang College, Jiangsu University, No. 537 Chang Xiang Xi Avenue, Dantu District, Zhenjiang 212000, China
| | - Weiyi Sun
- School of Medicine, Jiangsu University, No. 301 Xuefu Road, Jingkou District, Zhenjiang 212000, China
| | - Yijing Gong
- School of Medicine, Jiangsu University, No. 301 Xuefu Road, Jingkou District, Zhenjiang 212000, China
| | - Jun Liu
- Cardiology Department, Affiliated Hospital of Jiangsu University, No. 438 Jiefang Road, Jingkou District, Zhenjiang 212000, China
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Mucci F, Arone A, Gurrieri R, Weiss F, Russomanno G, Marazziti D. Third-Generation Antipsychotics: The Quest for the Key to Neurotrophism. Life (Basel) 2025; 15:391. [PMID: 40141736 PMCID: PMC11944073 DOI: 10.3390/life15030391] [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: 12/27/2024] [Revised: 02/24/2025] [Accepted: 02/26/2025] [Indexed: 03/28/2025] Open
Abstract
Antipsychotic drugs (APs) have profoundly changed the treatment landscape for psychiatric disorders, yet their impact on neuroplasticity and neurotrophism remains only partially understood. While second-generation antipsychotics (SGAs) are associated with a better side effect profile than their predecessors, the emergence of third-generation antipsychotics (TGAs)-such as brexpiprazole, cariprazine, lurasidone, iloperidone, lumateperone, pimavanserin, and roluperidone-has prompted renewed interest in their potential neuroprotective and pro-cognitive effects. This review attempts to carefully examine the evidence on the neurotrophic properties of TGAs and their role in modulating brain plasticity by analyzing studies published between 2010 and 2024. Although data remain limited and focused primarily on earlier SGAs, emerging findings suggest that some TGAs may exert positive effects on neuroplastic processes, including the modulation of brain-derived neurotrophic factors (BDNFs) and synaptic architecture. However, robust clinical data on their long-term effects and comparative efficacy are lacking; therefore, further research is necessary to validate their role in preventing neurodegenerative changes and improving cognitive outcomes in patients with psychiatric conditions.
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Affiliation(s)
- Federico Mucci
- Department of Psychiatry, Lucca Zone, Azienda USL Toscana Nord Ovest, 55100 Lucca, Italy;
| | - Alessandro Arone
- Department of Clinical and Experimental Medicine, Section of Psychiatry, University of Pisa, 56100 Pisa, Italy; (A.A.); (R.G.); (F.W.); (G.R.)
| | - Riccardo Gurrieri
- Department of Clinical and Experimental Medicine, Section of Psychiatry, University of Pisa, 56100 Pisa, Italy; (A.A.); (R.G.); (F.W.); (G.R.)
| | - Francesco Weiss
- Department of Clinical and Experimental Medicine, Section of Psychiatry, University of Pisa, 56100 Pisa, Italy; (A.A.); (R.G.); (F.W.); (G.R.)
| | - Gerardo Russomanno
- Department of Clinical and Experimental Medicine, Section of Psychiatry, University of Pisa, 56100 Pisa, Italy; (A.A.); (R.G.); (F.W.); (G.R.)
| | - Donatella Marazziti
- Department of Clinical and Experimental Medicine, Section of Psychiatry, University of Pisa, 56100 Pisa, Italy; (A.A.); (R.G.); (F.W.); (G.R.)
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Dong Y, Zhang P, Zhong J, Wang J, Xu Y, Huang H, Liu X, Sun W. Modifiable lifestyle factors influencing neurological and psychiatric disorders mediated by structural brain reserve: An observational and Mendelian randomization study. J Affect Disord 2025; 372:440-450. [PMID: 39672473 DOI: 10.1016/j.jad.2024.12.038] [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: 06/18/2024] [Revised: 09/27/2024] [Accepted: 12/08/2024] [Indexed: 12/15/2024]
Abstract
BACKGROUND Modifiable lifestyle factors are implicated as risk factors for neurological and psychiatric disorders, but whether these associations are causal remains uncertain. We aimed to evaluate associations and ascertain causal relationships between modifiable lifestyle factors, neurological and psychiatric disorder risk, and brain structural magnetic resonance imaging (MRI) markers. METHODS We analyzed data from over 50,000 UK Biobank participants with self-reported lifestyle factors, including alcohol consumption, smoking, physical activity, diet, sleep, electronic device use, and sexual factors. Primary outcomes were stroke, all-cause dementia, Parkinson's disease (PD), Major depression disorder (MDD), Anxiety Disorders (ANX), and Bipolar Disorder (BIP), alongside MRI markers. Summary statistics were obtained from genome-wide association studies and Mendelian randomization (MR) analyses investigated bidirectional associations between lifestyle factors, neurological/psychiatric disorders, and MRI markers, with mediation assessed using multivariable Mendelian randomization (MVMR). RESULTS Cross-sectional analyses identified lifestyle factors were associated with neurological and psychiatric disorders and brain morphology. MR confirmed causal relationships, including lifetime smoking index on Stroke, PD, MDD, ANX and BIP; play computer games on BIP; leisure screen time on Stroke and MDD; automobile speeding propensity on MDD; sexual factors on MDD and BIP; sleep characteristics on BIP and MDD. Brain structure mediated several lifestyle-disorder associations, such as daytime dozing and dementia, lifetime smoking and PD and age first had sexual intercourse and PD. CONCLUSION Our results provide support for a causal effect of multiple lifestyle measures on the risk of neurological and psychiatric disorders, with brain structural morphology serving as a potential biological mediator in their associations.
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Affiliation(s)
- Yiran Dong
- Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Pan Zhang
- Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Jinghui Zhong
- Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Jinjing Wang
- Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Yingjie Xu
- Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Hongmei Huang
- Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China
| | - Xinfeng Liu
- Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China.
| | - Wen Sun
- Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, China.
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Zheng H, Fang Y, Wang X, Feng S, Tang T, Chen M. Causal Association Between Major Depressive Disorder and Cortical Structure: A Bidirectional Mendelian Randomization Study and Mediation Analysis. CNS Neurosci Ther 2025; 31:e70319. [PMID: 40059068 PMCID: PMC11890974 DOI: 10.1111/cns.70319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 02/07/2025] [Accepted: 02/20/2025] [Indexed: 05/13/2025] Open
Abstract
BACKGROUND Previous observational studies have reported a possible association between major depressive disorder (MDD) and abnormal cortical structure. However, it is unclear whether MDD causes reductions in global cortical thickness (CT) and global area (SA). OBJECTIVE We aimed to test the bidirectional causal relationship between MDD and CT and SA using a Mendelian randomization (MR) design and performed exploratory analyses of MDD on CT and SA in different brain regions. METHODS Summary-level data were obtained from two GWAS meta-analysis studies: one screening for single nucleotide polymorphisms (SNPs) predicting the development of MDD (n = 135,458) and the other identifying SNPs predicting the magnitude of cortical thickness (CT) and surface area (SA) (n = 51,665). RESULTS The results showed that MDD caused a decrease in CT in the medial orbitofrontal region, a decrease in SA in the paracentral region, and an increase in SA in the lateral occipital region. C-reactive protein, tumor necrosis factor alpha (TNF-α), interleukin-1β, and interleukin-6 did not mediate the reduction. We also found that a reduction in CT in the precentral region and a reduction in SA in the orbitofrontal regions might be associated with a higher risk of MDD. CONCLUSION Our study did not suggest an association between MDD and cortical CT and SA.
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Affiliation(s)
- Hui Zheng
- The Acupuncture and Tuina SchoolChengdu University of Traditional Chinese MedicineChengdu CityChina
| | - Yong‐Jiang Fang
- Department of AcupunctureKunming Municipal Hospital of Traditional Chinese MedicineKunming CityChina
| | - Xiao‐Ying Wang
- The Acupuncture and Tuina SchoolChengdu University of Traditional Chinese MedicineChengdu CityChina
| | - Si‐Jia Feng
- The Acupuncture and Tuina SchoolChengdu University of Traditional Chinese MedicineChengdu CityChina
| | - Tai‐Chun Tang
- Department of Colorectal DiseasesHospital of Chengdu University of Traditional Chinese MedicineChengduChina
| | - Min Chen
- Department of Colorectal DiseasesHospital of Chengdu University of Traditional Chinese MedicineChengduChina
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Li C, Ren H, Liu H, Li T, Liu Y, Wu B, Han K, Zang S, Zhao G, Wang X. Middle frontal gyrus volume mediates the relationship between interleukin-1β and antidepressant response in major depressive disorder. J Affect Disord 2025; 372:56-65. [PMID: 39592061 DOI: 10.1016/j.jad.2024.11.070] [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: 08/14/2024] [Revised: 11/21/2024] [Accepted: 11/22/2024] [Indexed: 11/28/2024]
Abstract
Inflammation is a leading biological risk factor contributing to unfavorable outcomes of major depressive disorder (MDD). Both inflammation and depression are associated with similar alterations in brain structure, indicating that brain structural alterations could serve as a mediating factor in the adverse influence of inflammation on clinical outcomes in MDD. Nonetheless, longitudinal research has yet to confirm this hypothesis. Therefore, this study aimed at elucidating the relationships between peripheral inflammatory cytokines, gray matter volume (GMV) alterations, and antidepressant response in MDD. We studied 104 MDD patients treated with selective serotonin reuptake inhibitors and 85 healthy controls (HCs). Antidepressant response was assessed after 8-week antidepressant treatment by changes in 17-item Hamilton Depression Rating Scale (HAMD-17) scores. The GMV alterations were investigated using a voxel-based morphometry analysis. Inflammatory cytokines were measured using flow cytometry. Partial correlations were used to explore the relationships between inflammatory cytokines, GMV alterations, and antidepressant response. Compared to HCs, MDD patients showed reduced GMVs primarily in the frontal-limbic area, right insula, and right superior temporal gyrus. Furthermore, the alterations in GMVs, particularly in the right middle frontal gyrus and the left anterior cingulate gyrus, were associated with ΔHAMD-17 and inflammatory cytokines. Additionally, GMV alterations in the right middle frontal gyrus mediated the negative relationship between interleukin -1β and ΔHAMD-17. This study contributes to understanding the effect of inflammation on the brain and their relationships with antidepressant response, offering a potential explanation for the connection between inflammatory status and treatment efficacy.
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Affiliation(s)
- Cuicui Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Honghong Ren
- Department of Psychology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Hongzhu Liu
- School of Medical Imaging, Binzhou Medical University, Yantai, Shandong, China
| | - Tong Li
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Yigang Liu
- Department of Clinical Laboratory Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Baolin Wu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ke Han
- Department of Rehabilitation, Shandong Provincial Hospital Affiliated to Shandong First Medical University Jinan, Shandong, China
| | - Shuqi Zang
- Department of Rehabilitation, Shandong Provincial Hospital Affiliated to Shandong First Medical University Jinan, Shandong, China
| | - Guoqing Zhao
- Department of Psychology, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, China.
| | - Ximing Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
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Yasuda Y, Ito S, Matsumoto J, Okada N, Onitsuka T, Ikeda M, Kushima I, Sumiyoshi C, Fukunaga M, Nemoto K, Miura K, Hashimoto N, Ohi K, Takahashi T, Sasabayashi D, Koeda M, Yamamori H, Fujimoto M, Takano H, Hasegawa N, Narita H, Yamamoto M, Tha KK, Kikuchi M, Kamishikiryo T, Itai E, Okubo Y, Tateno A, Nakamura M, Kubota M, Igarashi H, Hirano Y, Okada G, Miyata J, Numata S, Abe O, Yoshimura R, Nakagawa S, Yamasue H, Ozaki N, Kasai K, Hashimoto R. Proposal for a Novel Classification of Patients With Enlarged Ventricles and Cognitive Impairment Based on Data-Driven Analysis of Neuroimaging Results in Patients With Psychiatric Disorders. Neuropsychopharmacol Rep 2025; 45:e70010. [PMID: 40011069 PMCID: PMC11864853 DOI: 10.1002/npr2.70010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2024] [Revised: 01/29/2025] [Accepted: 02/07/2025] [Indexed: 02/28/2025] Open
Abstract
One of the challenges in diagnosing psychiatric disorders is that the results of biological and neuroscience research are not reflected in the diagnostic criteria. Thus, data-driven analyses incorporating biological and cross-disease perspectives, regardless of the diagnostic category, have recently been proposed. A data-driven clustering study based on subcortical volumes in 5604 subjects classified into four brain biotypes associated with cognitive/social functioning. Among the four brain biotypes identified in controls and patients with schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, and other psychiatric disorders, we further analyzed the brain biotype 1 subjects, those with an extremely small limbic region, for clinical utility. We found that the representative feature of brain biotype 1 is enlarged lateral ventricles. An enlarged ventricle, defined by an average z-score of left and right lateral ventricle volumes > 3, had a sensitivity of 99.1% and a specificity of 98.1% for discriminating brain biotype 1. However, the presence of an enlarged ventricle was not sufficient to classify patient subgroups, as 1% of the controls also had enlarged ventricles. Reclassification of patients with enlarged ventricles according to cognitive impairment resulted in a stratified subgroup that included patients with a high proportion of schizophrenia diagnoses, electroencephalography abnormalities, and rare pathological genetic copy number variations. Data-driven clustering analysis of neuroimaging data revealed subgroups with enlarged ventricles and cognitive impairment. This subgroup could be a new diagnostic candidate for psychiatric disorders. This concept and strategy may be useful for identifying biologically defined psychiatric disorders in the future.
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Grants
- 18-IMS-C162 The computation was performed using Research Center for Computational Science, Okazaki, Japan (Project: NIPS)
- 19-IMS-C181 The computation was performed using Research Center for Computational Science, Okazaki, Japan (Project: NIPS)
- 20-IMS-C162 The computation was performed using Research Center for Computational Science, Okazaki, Japan (Project: NIPS)
- 21-IMS-C179 The computation was performed using Research Center for Computational Science, Okazaki, Japan (Project: NIPS)
- 22-IMS-C195 The computation was performed using Research Center for Computational Science, Okazaki, Japan (Project: NIPS)
- UTokyo Institute for Diversity and Adaptation of Human Mind (UTIDAHM, KK)
- JP18K07550 Japan Society for the Promotion of Science
- JP19H05467 Japan Society for the Promotion of Science
- JP20H03611 Japan Society for the Promotion of Science
- JP20K06920 Japan Society for the Promotion of Science
- JP20KK0193 Japan Society for the Promotion of Science
- JP21H00194 Japan Society for the Promotion of Science
- JP21H02851 Japan Society for the Promotion of Science
- JP21H05171 Japan Society for the Promotion of Science
- JP21H05174 Japan Society for the Promotion of Science
- JP21K07543 Japan Society for the Promotion of Science
- JP22H04926 Japan Society for the Promotion of Science
- JP23H00395 Japan Society for the Promotion of Science
- JP23H02834 Japan Society for the Promotion of Science
- JP23K07001 Japan Society for the Promotion of Science
- National Institute for Physiological Sciences
- JPMJMS2021 Moonshot Research and Development Program
- 2019 SIRS Research Fund Award
- the International Research Center for Neurointelligence (WPI-IRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS, KK)
- Intramural Research Grant (3-1, 4-6) for Neurological and Psychiatric Disorders of NCNP
- JP18dm0307002 Japan Agency for Medical Research and Development
- JP19dm0207069 Japan Agency for Medical Research and Development
- JP21dk0307103 Japan Agency for Medical Research and Development
- JP21km0405216 Japan Agency for Medical Research and Development
- JP21uk1024002 Japan Agency for Medical Research and Development
- JP21wm0425007 Japan Agency for Medical Research and Development
- JP21wm0425012 Japan Agency for Medical Research and Development
- JP22tm0424222 Japan Agency for Medical Research and Development
- 01412303 NINS program of Promoting Research by Networking among Institutions
- Japan Society for the Promotion of Science
- National Institute for Physiological Sciences
- Moonshot Research and Development Program
- Japan Agency for Medical Research and Development
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Affiliation(s)
- Yuka Yasuda
- Life Grow Brilliant Mental ClinicMedical Corporation FosterOsakaOsakaJapan
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Satsuki Ito
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Junya Matsumoto
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Naohiro Okada
- Department of Neuropsychiatry, Graduate School of MedicineThe University of TokyoBunkyo‐kuTokyoJapan
- International Research Center for Neurointelligence (WPI‐IRCN)The University of Tokyo Institutes for Advanced Study (UTIAS), The University of TokyoBunkyo‐kuTokyoJapan
| | | | - Masashi Ikeda
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaAichiJapan
| | - Itaru Kushima
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaAichiJapan
- Medical Genomics CenterNagoya University HospitalNagoyaAichiJapan
| | - Chika Sumiyoshi
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaTokyoJapan
- Faculty of Human Development and CultureFukushima UniversityFukushimaFukushimaJapan
- Department of Preventive Intervention for Psychiatric DisordersNational Institute of Mental Health National Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Masaki Fukunaga
- Section of Brain Function InformationNational Institute for Physiological SciencesOkazakiAichiJapan
- Physiological Sciences ProgramThe Graduate University for Advanced StudiesOkazakiAichiJapan
| | - Kiyotaka Nemoto
- Department of PsychiatryInstitute of Medicine, University of TsukubaTsukubaIbarakiJapan
| | - Kenichiro Miura
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Naoki Hashimoto
- Department of PsychiatryHokkaido University Graduate School of MedicineSapporoHokkaidoJapan
| | - Kazutaka Ohi
- Department of PsychiatryGifu University Graduate School of MedicineGifuGifuJapan
- Department of General Internal MedicineKanazawa Medical UniversityUchinadaIshikawaJapan
| | - Tsutomu Takahashi
- Department of NeuropsychiatryUniversity of Toyama Graduate School of Medicine and Pharmaceutical SciencesToyamaToyamaJapan
- Research Center for Idling Brain ScienceUniversity of ToyamaToyamaToyamaJapan
| | - Daiki Sasabayashi
- Department of NeuropsychiatryUniversity of Toyama Graduate School of Medicine and Pharmaceutical SciencesToyamaToyamaJapan
- Research Center for Idling Brain ScienceUniversity of ToyamaToyamaToyamaJapan
| | - Michihiko Koeda
- Department of NeuropsychiatryNippon Medical School Tama Nagayama HospitalTamaTokyoJapan
- Department of Neuropsychiatry, Graduate School of MedicineNippon Medical SchoolBunkyo‐KuTokyoJapan
| | - Hidenaga Yamamori
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaTokyoJapan
- Department of PsychiatryOsaka University Graduate School of MedicineSuitaOsakaJapan
- Japan Community Health Care Organization Osaka HospitalOsakaOsakaJapan
| | - Michiko Fujimoto
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaTokyoJapan
- Department of PsychiatryOsaka University Graduate School of MedicineSuitaOsakaJapan
| | - Harumasa Takano
- Department of Clinical NeuroimagingIntegrative Brain Imaging Center, National Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Naomi Hasegawa
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Hisashi Narita
- Department of Psychiatry and NeurologyHokkaido University HospitalSapporoHokkaidoJapan
| | - Maeri Yamamoto
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaAichiJapan
| | - Khin Khin Tha
- Global Center for Biomedical Science and EngineeringHokkaido University Faculty of MedicineSapporoHokkaidoJapan
| | - Masataka Kikuchi
- Department of Computational Biology and Medical SciencesGraduate School of Frontier Science, the University of TokyoKashiwaChibaJapan
| | - Toshiharu Kamishikiryo
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health SciencesHiroshima UniversityHiroshimaHiroshimaJapan
| | - Eri Itai
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health SciencesHiroshima UniversityHiroshimaHiroshimaJapan
| | - Yoshiro Okubo
- Department of Neuropsychiatry, Graduate School of MedicineNippon Medical SchoolBunkyo‐KuTokyoJapan
| | - Amane Tateno
- Department of Neuropsychiatry, Graduate School of MedicineNippon Medical SchoolBunkyo‐KuTokyoJapan
| | - Motoaki Nakamura
- Medical Institute of Developmental Disabilities ResearchShowa UniversitySetagayaTokyoJapan
| | - Manabu Kubota
- Department of Psychiatry, Graduate School of MedicineKyoto UniversitySakyo‐kuKyotoJapan
| | - Hiroyuki Igarashi
- Department of Psychiatry, Graduate School of MedicineKyoto UniversitySakyo‐kuKyotoJapan
| | - Yoji Hirano
- Division of Clinical Neuroscience, Department of Psychiatry, Faculty of MedicineUniversity of MiyazakiKiyotakeMiyazakiJapan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health SciencesHiroshima UniversityHiroshimaHiroshimaJapan
| | - Jun Miyata
- Department of Psychiatry, Graduate School of MedicineKyoto UniversitySakyo‐kuKyotoJapan
- Department of PsychiatryAichi Medical UniversityNagakuteAichiJapan
| | - Shusuke Numata
- Department of Psychiatry, Graduate School of Biomedical ScienceTokushima UniversityTokushimaTokushimaJapan
| | - Osamu Abe
- Department of Radiology, Graduate School of MedicineThe University of TokyoBunkyo‐kuTokyoJapan
| | - Reiji Yoshimura
- Department of PsychiatryUniversity of Occupational and Environmental Health, JapanKitakyushuFukuokaJapan
| | - Shin Nakagawa
- Division of Neuropsychiatry, Department of NeuroscienceYamaguchi University Graduate School of MedicineUbeYamaguchiJapan
| | - Hidenori Yamasue
- Department of PsychiatryHamamatsu University School of MedicineHamamatsuShizuokaJapan
| | - Norio Ozaki
- Pathophysiology of Nagoya University Graduate School of MedicineNagoyaAichiJapan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of MedicineThe University of TokyoBunkyo‐kuTokyoJapan
- International Research Center for Neurointelligence (WPI‐IRCN)The University of Tokyo Institutes for Advanced Study (UTIAS), The University of TokyoBunkyo‐kuTokyoJapan
- International Research Center for Neurointelligence (IRCN)Bunkyo‐kuTokyoJapan
| | - Ryota Hashimoto
- Department of Pathology of Mental DiseasesNational Institute of Mental Health, National Center of Neurology and PsychiatryKodairaTokyoJapan
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41
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Moreau AL, Hansen I, Bogdan R. A systematic review of structural neuroimaging markers of psychotherapeutic and pharmacological treatment for obsessive-compulsive disorder. Front Psychiatry 2025; 15:1432253. [PMID: 40018086 PMCID: PMC11865061 DOI: 10.3389/fpsyt.2024.1432253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 12/19/2024] [Indexed: 03/01/2025] Open
Abstract
Identifying individual difference factors associated with treatment response and putative mechanisms of therapeutic change may improve treatment for Obsessive Compulsive Disorder (OCD). Our systematic review of structural neuroimaging markers (i.e., morphometry, structural connectivity) of psychotherapy and medication treatment response for OCD identified 26 eligible publications from 20 studies (average study total n=54 ± 41.6 [range: 11-175]; OCD group n=29 ± 19) in child, adolescent, and adult samples evaluating baseline brain structure correlates of treatment response as well as treatment-related changes in brain structure. Findings were inconsistent across studies; significant associations within the anterior cingulate cortex (3/5 regional, 2/8 whole brain studies) and orbitofrontal cortex (5/10 regional, 2/7 whole brain studies) were most common, but laterality and directionality were not always consistent. Structural neuroimaging markers of treatment response do not currently hold clinical utility. Given increasing evidence that associations between complex behavior and brain structure are characterized by small, but potentially meaningful, effects, much larger samples are likely needed. Multivariate approaches (e.g., machine learning) may also improve the clinical predictive utility of neuroimaging data.
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Affiliation(s)
- Allison L. Moreau
- Department of Psychological and Brain Sciences, Washington University in St. Louis, Saint Louis, MO, United States
| | | | - Ryan Bogdan
- Department of Psychological and Brain Sciences, Washington University in St. Louis, Saint Louis, MO, United States
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42
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Manns M, Juckel G, Freund N. The Balance in the Head: How Developmental Factors Explain Relationships Between Brain Asymmetries and Mental Diseases. Brain Sci 2025; 15:169. [PMID: 40002502 PMCID: PMC11852682 DOI: 10.3390/brainsci15020169] [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: 11/18/2024] [Revised: 01/29/2025] [Accepted: 02/07/2025] [Indexed: 02/27/2025] Open
Abstract
Cerebral lateralisation is a core organising principle of the brain that is characterised by a complex pattern of hemispheric specialisations and interhemispheric interactions. In various mental disorders, functional and/or structural hemispheric asymmetries are changed compared to healthy controls, and these alterations may contribute to the primary symptoms and cognitive impairments of a specific disorder. Since multiple genetic and epigenetic factors influence both the pathogenesis of mental illness and the development of brain asymmetries, it is likely that the neural developmental pathways overlap or are even causally intertwined, although the timing, magnitude, and direction of interactions may vary depending on the specific disorder. However, the underlying developmental steps and neuronal mechanisms are still unclear. In this review article, we briefly summarise what we know about structural, functional, and developmental relationships and outline hypothetical connections, which could be investigated in appropriate animal models. Altered cerebral asymmetries may causally contribute to the development of the structural and/or functional features of a disorder, as neural mechanisms that trigger neuropathogenesis are embedded in the asymmetrical organisation of the developing brain. Therefore, the occurrence and severity of impairments in neural processing and cognition probably cannot be understood independently of the development of the lateralised organisation of intra- and interhemispheric neuronal networks. Conversely, impaired cellular processes can also hinder favourable asymmetry development and lead to cognitive deficits in particular.
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Affiliation(s)
- Martina Manns
- Research Division Experimental and Molecular Psychiatry, Department of Psychiatry, Psychotherapy and Preventive Medicine, LWL University Hospital, Ruhr-University, 44809 Bochum, Germany;
| | - Georg Juckel
- Department of Psychiatry, Psychotherapy and Preventive Medicine, LWL University Hospital, Ruhr-University, 44791 Bochum, Germany;
| | - Nadja Freund
- Research Division Experimental and Molecular Psychiatry, Department of Psychiatry, Psychotherapy and Preventive Medicine, LWL University Hospital, Ruhr-University, 44809 Bochum, Germany;
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43
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Huang Z, Liu Q, Guo Q, Gao J, Zhang L, Li L. Effects and mechanisms of Apelin in treating central nervous system diseases. Neuroscience 2025; 566:177-189. [PMID: 39681256 DOI: 10.1016/j.neuroscience.2024.12.025] [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: 03/11/2024] [Revised: 12/11/2024] [Accepted: 12/12/2024] [Indexed: 12/18/2024]
Abstract
Apelin, an endogenous ligand of G protein-coupled receptor APJ, is widely distributed in the central nervous system (CNS). It can be divided into such subtypes as Apelin-13, Apelin-17, and Apelin-36 as they have different amino acid structures. All Apelin is widely studied as an adipokine, showing a significant protective effect through regulating apoptosis, autophagy, oxidative stress, angiogenesis, inflammation, and other pathophysiological processes. As an adipokine, Apelin has been found to play a crucial role in cardiovascular disease development. In this paper, we reviewed the effects and mechanisms of Apelin in treating CNS diseases, such as neurotrauma, stroke, spinal cord injury, primary tumors, neurodegenerative diseases, psychiatric diseases, epilepsy, and pain.
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Affiliation(s)
- Zimeng Huang
- Medicine School, Qingdao University, 308 Ningxia Road, Shinan District, Qingdao 266071, China
| | - Qing Liu
- Department of Anatomy, School of Basic Medicine, Shandong University, Jinan, Shandong, 250021, China; School of Health and Life Sciences, University of Health and Rehabilitation Sciences, Qingdao 266071, China
| | - Qixuan Guo
- Department of Human Anatomy, Binzhou Medical University, Yantai, Shandong, 264003, China
| | - Jianqing Gao
- College of Pharmaceutical Sciences and Dr. Li Dak Sum and Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Zhejiang University, Hangzhou 310058, China.
| | - Luping Zhang
- Department of Human Anatomy, Binzhou Medical University, Yantai, Shandong, 264003, China.
| | - Liming Li
- Rehabilitation Sciences and Engineering, University of Health and Rehabilitation Sciences, Qingdao 266071, China.
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44
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Ruge O, Hoppe JPM, Dalle Molle R, Silveira PP. Early environmental influences on the orbito-frontal cortex function and its effects on behavior. Neurosci Biobehav Rev 2025; 169:106013. [PMID: 39814119 DOI: 10.1016/j.neubiorev.2025.106013] [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: 10/17/2024] [Revised: 01/07/2025] [Accepted: 01/11/2025] [Indexed: 01/18/2025]
Abstract
Early-life adversity during pre- and early post-natal phases can impact brain development and lead to maladaptive changes in executive function related behaviors. This increases the risk for a range of psychopathologies and physical diseases. Importantly, exposure to adversities during these periods is also linked to alterations in the orbito-frontal cortex (OFC) which is a key player in these executive functions. The OFC thus appears to be a central node in this association between early life stress and disease risk. Gaining a clear, and detailed understanding of the association between early life stress, OFC function, and executive function, as well as the underlying mechanisms mediating this association is relevant to inform potential therapeutic interventions. In this paper, we begin by reviewing evidence linking early life adversities to 1) alterations in behaviors regulated by the OFC and 2) changes in OFC anatomy and function. We then present insights into the underlying mechanisms for these changes, stemming from early life adversity models, and highlight important future directions for this line of research.
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Affiliation(s)
- Olivia Ruge
- Douglas Research Centre, McGill University, Montreal, QC, Canada
| | - João Paulo Maires Hoppe
- Douglas Research Centre, McGill University, Montreal, QC, Canada; Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | | | - Patricia Pelufo Silveira
- Douglas Research Centre, McGill University, Montreal, QC, Canada; Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada; Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, QC, Canada.
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45
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Zhou HY, Zhou L, Zheng TX, Ma LP, Fan MX, Liu L, Zhao XD, Yan C. Unraveling the link between childhood maltreatment and depression: Insights from the role of ventral striatum and middle cingulate cortex in hedonic experience and emotion regulation. Dev Psychopathol 2025; 37:292-302. [PMID: 38179683 DOI: 10.1017/s0954579423001591] [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] [Indexed: 01/06/2024]
Abstract
Childhood maltreatment is an established risk factor for psychopathology. However, it remains unclear how childhood traumatic events relate to mental health problems and how the brain is involved. This study examined the serial mediation effect of brain morphological alterations and emotion-/reward-related functions on linking the relationship from maltreatment to depression. We recruited 156 healthy adolescents and young adults and an additional sample of 31 adolescents with major depressive disorder for assessment of childhood maltreatment, depressive symptoms, cognitive reappraisal and anticipatory/consummatory pleasure. Structural MRI data were acquired to identify maltreatment-related cortical and subcortical morphological differences. The mediation models suggested that emotional maltreatment of abuse and neglect, was respectively associated with increased gray matter volume in the ventral striatum and greater thickness in the middle cingulate cortex. These structural alterations were further related to reduced anticipatory pleasure and disrupted cognitive reappraisal, which contributed to more severe depressive symptoms among healthy individuals. The above mediating effects were not replicated in our clinical group partly due to the small sample size. Preventative interventions can target emotional and reward systems to foster resilience and reduce the likelihood of future psychiatric disorders among individuals with a history of maltreatment.
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Affiliation(s)
- Han-Yu Zhou
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
- Shanghai Changning Mental Health Centre, Shanghai, China
| | - Lan Zhou
- Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | | | - Li-Ping Ma
- Key Laboratory of Brain Functional Genomics (MOE&STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Ming-Xia Fan
- Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Materials Science, East China Normal University, Shanghai, China
| | - Liang Liu
- Clinical Research Center for Mental Disorders, Chinese-German Institute of Mental Health, Shanghai Pu-dong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai, China
| | - Xu-Dong Zhao
- Clinical Research Center for Mental Disorders, Chinese-German Institute of Mental Health, Shanghai Pu-dong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai, China
| | - Chao Yan
- Shanghai Changning Mental Health Centre, Shanghai, China
- Key Laboratory of Brain Functional Genomics (MOE&STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
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46
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Meng F, Wang J, Wang L, Zou W. Glucose metabolism impairment in major depressive disorder. Brain Res Bull 2025; 221:111191. [PMID: 39788458 DOI: 10.1016/j.brainresbull.2025.111191] [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: 10/14/2024] [Revised: 12/26/2024] [Accepted: 01/02/2025] [Indexed: 01/12/2025]
Abstract
Major depressive disorder (MDD) is a common mental disorder with chronic tendencies that seriously affect regular work, life, and study. However, its exact pathogenesis remains unclear. Patients with MDD experience systemic and localized impairments in glucose metabolism throughout the disease course, disrupting various processes such as glucose uptake, glycoprotein transport, glycolysis, the tricarboxylic acid cycle (TCA), and oxidative phosphorylation (OXPHOS). These impairments may result from mechanisms including insulin resistance, hyperglycemia-induced damage, oxidative stress, astrocyte abnormalities, and mitochondrial dysfunction, leading to insufficient energy supply, altered synaptic plasticity, neuronal cell death, and functional and structural damage to reward networks. These mechanical changes contribute to the pathogenesis of MDD and severely interfere with the prognosis. Herein, we summarized the impairment of glucose metabolism and its pathophysiological mechanisms in patients with MDD. In addition, we briefly discussed potential pharmacological interventions for glucose metabolism to alleviate MDD, including glucagon-like peptide-1 receptor agonists, metformin, topical insulin, liraglutide, and pioglitazone, to encourage the development of new therapeutics.
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Affiliation(s)
- Fanhao Meng
- The Graduate School, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang 150040, China
| | - Jing Wang
- The Graduate School, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang 150040, China
| | - Long Wang
- First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang 150040, China.
| | - Wei Zou
- First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, Heilongjiang 150040, China.
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47
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Liao C, Dua AN, Wojtasiewicz C, Liston C, Kwan AC. Structural neural plasticity evoked by rapid-acting antidepressant interventions. Nat Rev Neurosci 2025; 26:101-114. [PMID: 39558048 PMCID: PMC11892022 DOI: 10.1038/s41583-024-00876-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/17/2024] [Indexed: 11/20/2024]
Abstract
A feature in the pathophysiology of major depressive disorder (MDD), a mood disorder, is the impairment of excitatory synapses in the prefrontal cortex. Intriguingly, different types of treatment with fairly rapid antidepressant effects (within days or a few weeks), such as ketamine, electroconvulsive therapy and non-invasive neurostimulation, seem to converge on enhancement of neural plasticity. However, the forms and mechanisms of plasticity that link antidepressant interventions to the restoration of excitatory synaptic function are still unknown. In this Review, we highlight preclinical research from the past 15 years showing that ketamine and psychedelic drugs can trigger the growth of dendritic spines in cortical pyramidal neurons. We compare the longitudinal effects of various psychoactive drugs on neuronal rewiring, and we highlight rapid onset and sustained time course as notable characteristics for putative rapid-acting antidepressant drugs. Furthermore, we consider gaps in the current understanding of drug-evoked in vivo structural plasticity. We also discuss the prospects of using synaptic remodelling to understand other antidepressant interventions, such as repetitive transcranial magnetic stimulation. Finally, we conclude that structural neural plasticity can provide unique insights into the neurobiological actions of psychoactive drugs and antidepressant interventions.
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Affiliation(s)
- Clara Liao
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
| | - Alisha N Dua
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | | | - Conor Liston
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Alex C Kwan
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.
- Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA.
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48
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Wu C, Mu Q, Xu Y, Chen Y, Zhang P, Cui D, Lu S. Altered local spontaneous activity and functional connectivity density in major depressive disorder patients with anhedonia. Asian J Psychiatr 2025; 104:104380. [PMID: 39889674 DOI: 10.1016/j.ajp.2025.104380] [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: 10/20/2024] [Revised: 01/20/2025] [Accepted: 01/22/2025] [Indexed: 02/03/2025]
Abstract
OBJECTIVE The purpose of this study was to investigate the alterations of intrinsic brain function in major depressive disorder (MDD) patients with and without anhedonia based on whole-brain level by using two novel measures, four-dimensional spatial-temporal consistency of local neural activity (FOCA) and local functional connectivity density (lFCD). METHODS A total of 26 MDD patients with anhedonia (MDD-WA), 29 MDD patients without anhedonia (MDD-WoA), and 30 healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning and intrinsic brain function was explored by FOCA and lFCD. A two-sample t-test was conducted to explore FOCA and lFCD differences between MDD patients and HCs, then analysis of covariance (ANCOVA) and post hoc tests were performed to obtain brain regions with significant differences among three groups. Finally, the diagnostic performance of FOCA and lFCD values with significant inter-group difference was evaluated using receiver operating characteristic (ROC) curves. RESULTS Compared to HCs, MDD patients showed decreased FOCA in the right cuneus (CUN) and left postcentral gyrus (PoCG), as well as diminished lFCD in the right CUN and left calcarine fissure and surrounding cortex (CAL). Interestingly, the MDD-WA group was more likely to exhibit decreased FOCA in the left PoCG and reduced lFCD in the left CAL after consideration for the effect of anhedonia in MDD patients. The MDD-WA group further showed increased FOCA in the bilateral caudate (CAU) and right ventral anterior nucleus (VA) when comparing to HCs. Additionally, as compared with MDD-WoA group, the MDD-WA group presented decreased FOCA in the right middle occipital gyrus (MOG), which was also negatively associated with the severity of anhedonia in MDD patients. Finally, FOCA values of the right MOG exhibited excellent discriminant validity in differentiating MDD-WA from MDD-WoA, and the other individual or combined indices of FOCA or lFCD values in the aforementioned distinct brain regions presented significant utility in distinguishing between MDD or MDD-WA and HCs. CONCLUSIONS The present findings suggest that aberrant intrinsic brain function in the left CAL, left PoCG, bilateral CAU, right VA, and, especially the right MOG may be associated with anhedonia in patients with MDD. Altered FOCA in the right MOG may have the potential to be a diagnostic neuroimaging biomarker for MDD patients with anhedonia.
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Affiliation(s)
- Congchong Wu
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision psychiatry, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang, China; Department of Child Psychology, The Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou, Zhejiang, China
| | - Qingli Mu
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision psychiatry, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang, China; Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yuwei Xu
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision psychiatry, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang, China; Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yue Chen
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision psychiatry, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang, China; Faculty of Clinical Medicine, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Peng Zhang
- Department of Psychiatry, Affiliated Xiaoshan Hospital, Hangzhou Normal University, Hangzhou, Zhejiang, China.
| | - Dong Cui
- School of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, Shandong, China.
| | - Shaojia Lu
- Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision psychiatry, Zhejiang Engineering Center for Mathematical Mental Health, Hangzhou, Zhejiang, China.
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Yang H, Wu G, Li Y, Xu X, Cong J, Xu H, Ma Y, Li Y, Chen R, Pines A, Xu T, Sydnor VJ, Satterthwaite TD, Cui Z. Connectional axis of individual functional variability: Patterns, structural correlates, and relevance for development and cognition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2023.03.08.531800. [PMID: 36945479 PMCID: PMC10028904 DOI: 10.1101/2023.03.08.531800] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
The human cerebral cortex exhibits intricate interareal functional synchronization at the macroscale, with substantial individual variability in these functional connections. However, the spatial organization of functional connectivity (FC) variability across the human connectome edges and its significance in cognitive development remain unclear. Here, we identified a connectional axis in the edge-level FC variability. The variability declined continuously along this axis from within-network to between-network connections, and from the edges linking association networks to those linking the sensorimotor and association networks. This connectional axis of functional variability is associated with spatial pattern of structural connectivity variability. Moreover, the connectional variability axis evolves in youth with an increasing flatter axis slope. We also observed that the slope of connectional variability axis was positively related to the performance in the higher-order cognition. Together, our results reveal a connectional axis in functional variability that is linked with structural connectome variability, refines during development, and is relevant to cognition.
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Affiliation(s)
- Hang Yang
- Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 102206, China
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Guowei Wu
- Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 102206, China
- 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
- Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 102206, China
- Chinese Institute for Brain Research, Beijing, 102206, China
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Xiaoyu Xu
- Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 102206, China
- Chinese Institute for Brain Research, Beijing, 102206, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Jing Cong
- Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 102206, China
- Chinese Institute for Brain Research, Beijing, 102206, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
| | - Haoshu Xu
- Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 102206, China
- Chinese Institute for Brain Research, Beijing, 102206, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Yiyao Ma
- Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 102206, China
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Yang Li
- Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 102206, China
- 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
- Department of Psychiatry, University of Pittsburgh Medical Center; Pittsburgh, PA, USA
- 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
- Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 102206, China
- Chinese Institute for Brain Research, Beijing, 102206, China
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50
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Goya-Maldonado R, Erwin-Grabner T, Zeng LL, Ching CRK, Aleman A, Amod AR, Basgoze Z, Benedetti F, Besteher B, Brosch K, Bülow R, Colle R, Connolly CG, Corruble E, Couvy-Duchesne B, Cullen K, Dannlowski U, Davey CG, Dols A, Ernsting J, Evans JW, Fisch L, Fuentes-Claramonte P, Gonul AS, Gotlib IH, Grabe HJ, Groenewold NA, Grotegerd D, Hahn T, Hamilton JP, Han LKM, Harrison BJ, Ho TC, Jahanshad N, Jamieson AJ, Karuk A, Kircher T, Klimes-Dougan B, Koopowitz SM, Lancaster T, Leenings R, Li M, Linden DEJ, MacMaster FP, Mehler DMA, Meinert S, Melloni E, Mueller BA, Mwangi B, Nenadić I, Ojha A, Okamoto Y, Oudega ML, Penninx BWJH, Poletti S, Pomarol-Clotet E, Portella MJ, Pozzi E, Radua J, Rodríguez-Cano E, Sacchet MD, Salvador R, Schrantee A, Sim K, Soares JC, Solanes A, Stein DJ, Stein F, Stolicyn A, Thomopoulos SI, Toenders YJ, Uyar-Demir A, Vieta E, Vives-Gilabert Y, Völzke H, Walter M, Whalley HC, Whittle S, Winter N, Wittfeld K, Wright MJ, Wu MJ, Yang TT, Zarate C, Veltman DJ, Schmaal L, Thompson PM, for the ENIGMA Major Depressive Disorder working group. Classification of Major Depressive Disorder Using Vertex-Wise Brain Sulcal Depth, Curvature, and Thickness with a Deep and a Shallow Learning Model. ARXIV 2025:arXiv:2311.11046v2. [PMID: 39975425 PMCID: PMC11838705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing 7,012 participants from 30 sites (N=2,772 MDD and N=4,240 HC), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible. Future studies are needed to determine whether more sophisticated integration of information from other MRI modalities such as fMRI and DWI will lead to a higher performance in this diagnostic task.
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Affiliation(s)
- Roberto Goya-Maldonado
- Laboratory of Systems Neuroscience and Imaging in Psychiatry (SNIP-Lab), Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Georg-August University, Göttingen, Germany
| | - Tracy Erwin-Grabner
- Laboratory of Systems Neuroscience and Imaging in Psychiatry (SNIP-Lab), Department of Psychiatry and Psychotherapy, University Medical Center Göttingen (UMG), Georg-August University, Göttingen, Germany
| | - Ling-Li Zeng
- College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90274, USA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90274, USA
| | - Andre Aleman
- Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Alyssa R. Amod
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Zeynep Basgoze
- Department of Psychiatry and Behavioral Science, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Francesco Benedetti
- Division of Neuroscience, IRCCS Scientific Institute Ospedale San Raffaele, Milano, Italy
| | - Bianca Besteher
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Rudolf Bultmann Str. 8, 35039 Marburg, Germany
| | - Robin Bülow
- Institute for Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Romain Colle
- MOODS Team, CESP, INSERM U1018, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre 94275, France
- Service Hospitalo-Universitaire de Psychiatrie de Bicêtre, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux deParis, Hôpital de Bicêtre, Le Kremlin Bicêtre F-94275, France
| | - Colm G. Connolly
- Department of Biomedical Sciences, Florida State University, Tallahassee FL, USA
| | - Emmanuelle Corruble
- MOODS Team, CESP, INSERM U1018, Faculté de Médecine, Univ Paris-Saclay, Le Kremlin Bicêtre 94275, France
- Service Hospitalo-Universitaire de Psychiatrie de Bicêtre, Hôpitaux Universitaires Paris-Saclay, Assistance Publique-Hôpitaux deParis, Hôpital de Bicêtre, Le Kremlin Bicêtre F-94275, France
| | - Baptiste Couvy-Duchesne
- Sorbonne University, Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, F-75013, Paris, France
- Institute for Molecular Bioscience, the University of Queensland, St Lucia, QLD, Australia
| | - Kathryn Cullen
- Department of Psychiatry and Behavioral Science, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Christopher G. Davey
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, the University of Melbourne, Parkville, Victoria, Australia
| | - Annemiek Dols
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
- Department of Psychiatry, UMC Utrecht Brain Center, University Utrecht, Utrecht, the Netherlands
| | - Jan Ernsting
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jennifer W. Evans
- Experimental Therapeutics and Pathophysiology Branch, National Institute for Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Lukas Fisch
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Catalonia, Spain
| | - Ali Saffet Gonul
- SoCAT Lab, Department of Psychiatry, School of Medicine, Ege University, Izmir, Turkey
| | - Ian H. Gotlib
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Nynke A. Groenewold
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - J. Paul Hamilton
- Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Laura K. M. Han
- Centre for Youth Mental Health, the University of Melbourne, Parkville, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - Ben J. Harrison
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, the University of Melbourne, Parkville, Victoria, Australia
| | - Tiffany C. Ho
- Department of Psychiatry and Behavioral Sciences, Division of Child and Adolescent Psychiatry, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90274, USA
| | - Alec J. Jamieson
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, the University of Melbourne, Parkville, Victoria, Australia
| | - Andriana Karuk
- FIDMAG Germanes Hospitalàries Research Foundation, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Catalonia, Spain
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Rudolf Bultmann Str. 8, 35039 Marburg, Germany
| | | | - Sheri-Michelle Koopowitz
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Thomas Lancaster
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Ramona Leenings
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Meng Li
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - David E. J. Linden
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, 6229 ER, the Netherlands
| | - Frank P. MacMaster
- Departments of Psychiatry and Pediatrics, University of Calgary, Calgary, AB, Canada
| | - David M. A. Mehler
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Germany
| | - Elisa Melloni
- Division of Neuroscience, IRCCS Scientific Institute Ospedale San Raffaele, Milano, Italy
| | - Bryon A. Mueller
- Department of Psychiatry and Behavioral Science, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Benson Mwangi
- Center Of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences at McGovern Medical School, the University of Texas Health Science Center at Houston, USA
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Rudolf Bultmann Str. 8, 35039 Marburg, Germany
| | - Amar Ojha
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA; Center for Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Mardien L. Oudega
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
- GGZ inGeest Mental Health Care, Amsterdam, the Netherlands
| | - Brenda W. J. H. Penninx
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Sara Poletti
- Division of Neuroscience, IRCCS Scientific Institute Ospedale San Raffaele, Milano, Italy
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Catalonia, Spain
| | - Maria J. Portella
- Sant Pau Mental Health Research Group, Institut de Recerca de l’Hospital de la Santa Creu i Sant Pau, Barcelona, Catalonia, Spain. CIBERSAM, Madrid, Spain
| | - Elena Pozzi
- Centre for Youth Mental Health, the University of Melbourne, Parkville, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - Joaquim Radua
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Elena Rodríguez-Cano
- FIDMAG Germanes Hospitalàries Research Foundation, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Catalonia, Spain
| | - Matthew D. Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Catalonia, Spain
| | - Anouk Schrantee
- Amsterdam University Medical Centers, location AMC, Department of Radiology and Nuclear Medicine, Amsterdam, the Netherlands
| | - Kang Sim
- West Region, Institute of Mental Health, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Jair C. Soares
- Center Of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences at McGovern Medical School, the University of Texas Health Science Center at Houston, USA
| | - Aleix Solanes
- Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Dan J. Stein
- Department of Psychiatry & Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Rudolf Bultmann Str. 8, 35039 Marburg, Germany
| | - Aleks Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Scotland, UK
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90274, USA
| | - Yara J. Toenders
- Centre for Youth Mental Health, the University of Melbourne, Parkville, VIC, Australia
- Orygen, Parkville, VIC, Australia
- Developmental and Educational Psychology, Leiden University, the Netherlands
- Erasmus School of Social and Behavioral Sciences, Erasmus University Rotterdam, the Netherlands
| | - Aslihan Uyar-Demir
- SoCAT Lab, Department of Psychiatry, School of Medicine, Ege University, Izmir, Turkey
| | - Eduard Vieta
- Hospital Clinic, Institute of Neuroscience, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain
| | - Yolanda Vives-Gilabert
- Intelligent Data Analysis Laboratory (IDAL), Department of Electronic Engineering, Universitat de València, Valencia, Spain
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Clinical Affective Neuroimaging Laboratory, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Heather C. Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Scotland, UK
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, the University of Melbourne, Parkville, Victoria, Australia
| | - Nils Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/ Greifswald, Greifswald, Germany
| | - Margaret J. Wright
- Clinical Affective Neuroimaging Laboratory, Leibniz Institute for Neurobiology, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/ Greifswald, Greifswald, Germany
| | - Mon-Ju Wu
- Center Of Excellence on Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences at McGovern Medical School, the University of Texas Health Science Center at Houston, USA
| | - Tony T. Yang
- Department of Psychiatry and Behavioral Sciences, Division of Child and Adolescent Psychiatry, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Carlos Zarate
- Section on the Neurobiology and Treatment of Mood Disorders, National Institute of Mental Health, Bethesda, MD, USA
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Lianne Schmaal
- Centre for Youth Mental Health, the University of Melbourne, Parkville, VIC, Australia
- Orygen, Parkville, VIC, Australia
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90274, USA
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