1
|
Wang J, Cheng Y. Mediating role of right superior corona microstructural changes in linking attentional control and trait anxiety among youth with childhood maltreatment. Neuroreport 2024; 35:744-752. [PMID: 38829957 DOI: 10.1097/wnr.0000000000002053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
This study explores the neural correlates between attentional control and trait anxiety among youth with a history of childhood maltreatment. Using diffusion tensor imaging, we investigated the microstructural integrity of brain white matter, particularly focusing on the right superior corona radiata (SCA-R). A total of 173 university students with experiences of childhood maltreatment underwent behavioral assessments using the Attentional Control Scale and trait anxiety measurements via the Spielberger State-Trait Anxiety Inventory. Our analysis found significant correlations between fractional anisotropy values in the SCA-R and trait anxiety levels, controlled for age and sex. Notably, SCA-R fractional anisotropy values partially mediated the relationship between attentional control and trait anxiety, suggesting a potential pathway through which attentional control could mitigate trait anxiety. These insights highlight attentional control as a potential mitigating factor against trait anxiety, particularly noting the partial mediation role of the SCA-R. Importantly, this study is descriptive and correlative, highlighting associations rather than causal relationships among the variables studied. These findings enhance our understanding of the neural mechanisms underlying anxiety in individuals with a history of childhood maltreatment.
Collapse
Affiliation(s)
- Junyi Wang
- School of Teacher Education, Nanjing University of Information Science & Technology, Nanjing
| | | |
Collapse
|
2
|
Rootes-Murdy K, Panta S, Kelly R, Romero J, Quidé Y, Cairns MJ, Loughland C, Carr VJ, Catts SV, Jablensky A, Green MJ, Henskens F, Kiltschewskij D, Michie PT, Mowry B, Pantelis C, Rasser PE, Reay WR, Schall U, Scott RJ, Watkeys OJ, Roberts G, Mitchell PB, Fullerton JM, Overs BJ, Kikuchi M, Hashimoto R, Matsumoto J, Fukunaga M, Sachdev PS, Brodaty H, Wen W, Jiang J, Fani N, Ely TD, Lorio A, Stevens JS, Ressler K, Jovanovic T, van Rooij SJ, Federmann LM, Jockwitz C, Teumer A, Forstner AJ, Caspers S, Cichon S, Plis SM, Sarwate AD, Calhoun VD. Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC. PATTERNS (NEW YORK, N.Y.) 2024; 5:100987. [PMID: 39081570 PMCID: PMC11284501 DOI: 10.1016/j.patter.2024.100987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/02/2024] [Accepted: 04/10/2024] [Indexed: 08/02/2024]
Abstract
Structural neuroimaging studies have identified a combination of shared and disorder-specific patterns of gray matter (GM) deficits across psychiatric disorders. Pooling large data allows for examination of a possible common neuroanatomical basis that may identify a certain vulnerability for mental illness. Large-scale collaborative research is already facilitated by data repositories, institutionally supported databases, and data archives. However, these data-sharing methodologies can suffer from significant barriers. Federated approaches augment these approaches by enabling access or more sophisticated, shareable and scaled-up analyses of large-scale data. We examined GM alterations using Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation, an open-source, decentralized analysis application. Through federated analysis of eight sites, we identified significant overlap in the GM patterns (n = 4,102) of individuals with schizophrenia, major depressive disorder, and autism spectrum disorder. These results show cortical and subcortical regions that may indicate a shared vulnerability to psychiatric disorders.
Collapse
Affiliation(s)
- Kelly Rootes-Murdy
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Sandeep Panta
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Ross Kelly
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Javier Romero
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Yann Quidé
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Murray J. Cairns
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia
- Centre for Brain and Mental Health Research, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Carmel Loughland
- Centre for Brain and Mental Health Research, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Vaughan J. Carr
- Neuroscience Research Australia, Sydney, NSW, Australia
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
- Department of Psychiatry, Monash University, Clayton, VIC, Australia
| | - Stanley V. Catts
- School of Medicine, University of Queensland, Brisbane, QLD, Australia
| | | | - Melissa J. Green
- Neuroscience Research Australia, Sydney, NSW, Australia
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Frans Henskens
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- School of Medicine & Public Health, University of Newcastle, Newcastle, NSW, Australia
- Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle, NSW, Australia
| | - Dylan Kiltschewskij
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia
- Centre for Brain and Mental Health Research, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Patricia T. Michie
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- School of Psychological Sciences, University of Newcastle, Callaghan, NSW, Australia
| | - Bryan Mowry
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
- Queensland Centre for Mental Health Research, University of Queensland, Brisbane, QLD, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne & Melbourne Health, Carlton South, VIC, Australia
- Florey Institute of Neuroscience & Mental Health, Parkville, VIC, Australia
| | - Paul E. Rasser
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
- Priority Research Centre for Health Behaviour, University of Newcastle, Newcastle, NSW, Australia
| | - William R. Reay
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia
- Centre for Brain and Mental Health Research, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Ulrich Schall
- Centre for Brain and Mental Health Research, University of Newcastle, Callaghan, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW, Australia
| | - Rodney J. Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia
| | - Oliver J. Watkeys
- Neuroscience Research Australia, Sydney, NSW, Australia
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Gloria Roberts
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Philip B. Mitchell
- Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Janice M. Fullerton
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, NSW, Australia
| | | | - Masataka Kikuchi
- Department of Computational Biology and Medical Sciences, University of Tokyo, Chiba, Japan
| | - Ryota Hashimoto
- 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
| | - Masaki Fukunaga
- Section of Brain Function Information, National Institute for Physiological Sciences, Aichi, Japan
| | - Perminder S. Sachdev
- Centre for Healthy Brain Aging, Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Henry Brodaty
- Centre for Healthy Brain Aging, Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Wei Wen
- Centre for Healthy Brain Aging, Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Aging, Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, Australia
| | - Negar Fani
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
| | - Timothy D. Ely
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
| | | | - Jennifer S. Stevens
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
- Atlanta VA Medical Center, Decatur, GA, USA
| | - Kerry Ressler
- McLean Hospital, Harvard Medical School, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Tanja Jovanovic
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA
| | - Sanne J.H. van Rooij
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
| | - Lydia M. Federmann
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Christiane Jockwitz
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Alexander Teumer
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Andreas J. Forstner
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Sven Cichon
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Department of Biomedicine, University of Basel, Basel, Switzerland
- Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
| | - Sergey M. Plis
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Anand D. Sarwate
- Department of Electrical and Computer Engineering, Rutgers University-New Brunswick, Piscataway, NJ, USA
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| |
Collapse
|
3
|
Antenucci N, D'Errico G, Fazio F, Nicoletti F, Bruno V, Battaglia G. Changes in kynurenine metabolites in the gray and white matter of the dorsolateral prefrontal cortex of individuals affected by schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:27. [PMID: 38413629 PMCID: PMC10899223 DOI: 10.1038/s41537-024-00447-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 02/02/2024] [Indexed: 02/29/2024]
Abstract
Alterations in the kynurenine pathway of tryptophan metabolism have been implicated in the pathophysiology of schizophrenia. Here, we performed an in-depth analysis of all metabolites of the kynurenine pathway, i.e., tryptophan (TRY), kynurenic acid (KYNA), L-kynurenine (KYN), 3-hydroxykynurenine (3-HK), anthranylic acid (ANA), 3-hydroxyanthranylic acid (3-HANA), xanthurenic acid (XA) and quinolinic acid (QUINA), in postmortem samples of the dorsolateral prefrontal cortex (DLPFC, Brodmann area 46, 9) of individuals affected by schizophrenia and non-schizophrenic controls. The analysis was carried out in the gray and white matter. Levels of KYN, 3-HK, ANA, and 3-HANA were significantly increased in both the gray and white matter of the DLPFC of individuals affected by schizophrenia, whereas levels of TRY, KYNA, and QUINA were increased exclusively in the white matter and remained unchanged in the gray matter. These increases in kynurenine metabolites did not correlate with age, sex, duration of the disease, and duration and type of antipsychotic medication. These findings suggest that the two major branches of the kynurenine pathway, i.e., the transamination of KYN into KYNA, and hydroxylation of KYN into 3-HK are activated in the white matter of individuals affected by schizophrenia, perhaps as a result of neuroinflammation, and support the evidence that abnormalities of the white matter are consistenly associated with schizophrenia.
Collapse
Affiliation(s)
- Nico Antenucci
- Department of Physiology and Pharmacology, Sapienza University, Rome, Italy
- Department of Pharmacology and Neuroscience, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | | | - Francesco Fazio
- IRCCS Neuromed, Pozzilli, Italy
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Ferdinando Nicoletti
- Department of Physiology and Pharmacology, Sapienza University, Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Valeria Bruno
- Department of Physiology and Pharmacology, Sapienza University, Rome, Italy.
- IRCCS Neuromed, Pozzilli, Italy.
| | - Giuseppe Battaglia
- Department of Physiology and Pharmacology, Sapienza University, Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| |
Collapse
|
4
|
Stogsdill JA, Harwell CC, Goldman SA. Astrocytes as master modulators of neural networks: Synaptic functions and disease-associated dysfunction of astrocytes. Ann N Y Acad Sci 2023; 1525:41-60. [PMID: 37219367 DOI: 10.1111/nyas.15004] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Astrocytes are the most abundant glial cell type in the central nervous system and are essential to the development, plasticity, and maintenance of neural circuits. Astrocytes are heterogeneous, with their diversity rooted in developmental programs modulated by the local brain environment. Astrocytes play integral roles in regulating and coordinating neural activity extending far beyond their metabolic support of neurons and other brain cell phenotypes. Both gray and white matter astrocytes occupy critical functional niches capable of modulating brain physiology on time scales slower than synaptic activity but faster than those adaptive responses requiring a structural change or adaptive myelination. Given their many associations and functional roles, it is not surprising that astrocytic dysfunction has been causally implicated in a broad set of neurodegenerative and neuropsychiatric disorders. In this review, we focus on recent discoveries concerning the contributions of astrocytes to the function of neural networks, with a dual focus on the contribution of astrocytes to synaptic development and maturation, and on their role in supporting myelin integrity, and hence conduction and its regulation. We then address the emerging roles of astrocytic dysfunction in disease pathogenesis and on potential strategies for targeting these cells for therapeutic purposes.
Collapse
Affiliation(s)
| | - Corey C Harwell
- Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Steven A Goldman
- Sana Biotechnology Inc., Cambridge, Massachusetts, USA
- Center for Translational Neuromedicine, University of Rochester, Rochester, New York, USA
- University of Copenhagen Faculty of Health and Medical Sciences, Copenhagen, Denmark
| |
Collapse
|
5
|
Gengeç Benli Ş, Andaç M. Constructing the Schizophrenia Recognition Method Employing GLCM Features from Multiple Brain Regions and Machine Learning Techniques. Diagnostics (Basel) 2023; 13:2140. [PMID: 37443534 DOI: 10.3390/diagnostics13132140] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 06/15/2023] [Accepted: 06/16/2023] [Indexed: 07/15/2023] Open
Abstract
Accurately diagnosing schizophrenia, a complex psychiatric disorder, is crucial for effectively managing the treatment process and methods. Various types of magnetic resonance (MR) images have the potential to serve as biomarkers for schizophrenia. The aim of this study is to numerically analyze differences in the textural characteristics that may occur in the bilateral amygdala, caudate, pallidum, putamen, and thalamus regions of the brain between individuals with schizophrenia and healthy controls via structural MR images. Towards this aim, Gray Level Co-occurence Matrix (GLCM) features obtained from five regions of the right, left, and bilateral brain were classified using machine learning methods. In addition, it was analyzed in which hemisphere these features were more distinctive and which method among Adaboost, Gradient Boost, eXtreme Gradient Boosting, Random Forest, k-Nearest Neighbors, Linear Discriminant Analysis (LDA), and Naive Bayes had higher classification success. When the results were examined, it was demonstrated that the GLCM features of these five regions in the left hemisphere could be classified as having higher performance in schizophrenia compared to healthy individuals. Using the LDA algorithm, classification success was achieved with a 100% AUC, 94.4% accuracy, 92.31% sensitivity, 100% specificity, and an F1 score of 91.9% in healthy and schizophrenic individuals. Thus, it has been revealed that the textural characteristics of the five predetermined regions, instead of the whole brain, are an important indicator in identifying schizophrenia.
Collapse
Affiliation(s)
- Şerife Gengeç Benli
- Department of Biomedical Engineering, Faculty of Engineering, Erciyes University, Kayseri 38280, Turkey
| | - Merve Andaç
- Department of Biomedical Engineering, Faculty of Engineering, Erciyes University, Kayseri 38280, Turkey
| |
Collapse
|
6
|
Adamu MJ, Qiang L, Nyatega CO, Younis A, Kawuwa HB, Jabire AH, Saminu S. Unraveling the pathophysiology of schizophrenia: insights from structural magnetic resonance imaging studies. Front Psychiatry 2023; 14:1188603. [PMID: 37275974 PMCID: PMC10236951 DOI: 10.3389/fpsyt.2023.1188603] [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: 03/17/2023] [Accepted: 04/20/2023] [Indexed: 06/07/2023] Open
Abstract
Background Schizophrenia affects about 1% of the global population. In addition to the complex etiology, linking this illness to genetic, environmental, and neurobiological factors, the dynamic experiences associated with this disease, such as experiences of delusions, hallucinations, disorganized thinking, and abnormal behaviors, limit neurological consensuses regarding mechanisms underlying this disease. Methods In this study, we recruited 72 patients with schizophrenia and 74 healthy individuals matched by age and sex to investigate the structural brain changes that may serve as prognostic biomarkers, indicating evidence of neural dysfunction underlying schizophrenia and subsequent cognitive and behavioral deficits. We used voxel-based morphometry (VBM) to determine these changes in the three tissue structures: the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). For both image processing and statistical analysis, we used statistical parametric mapping (SPM). Results Our results show that patients with schizophrenia exhibited a significant volume reduction in both GM and WM. In particular, GM volume reductions were more evident in the frontal, temporal, limbic, and parietal lobe, similarly the WM volume reductions were predominantly in the frontal, temporal, and limbic lobe. In addition, patients with schizophrenia demonstrated a significant increase in the CSF volume in the left third and lateral ventricle regions. Conclusion This VBM study supports existing research showing that schizophrenia is associated with alterations in brain structure, including gray and white matter, and cerebrospinal fluid volume. These findings provide insights into the neurobiology of schizophrenia and may inform the development of more effective diagnostic and therapeutic approaches.
Collapse
Affiliation(s)
- Mohammed Jajere Adamu
- Department of Electronic Science and Technology, School of Microelectronics, Tianjin University, Tianjin, China
- Department of Computer Science, Yobe State University, Damaturu, Nigeria
| | - Li Qiang
- Department of Electronic Science and Technology, School of Microelectronics, Tianjin University, Tianjin, China
| | - Charles Okanda Nyatega
- Department of Information and Communication Engineering, School of Electrical and Information Engineering, Tianjin University, Tianjin, China
- Department of Electronics and Telecommunication Engineering, Mbeya University of Science and Technology, Mbeya, Tanzania
| | - Ayesha Younis
- Department of Electronic Science and Technology, School of Microelectronics, Tianjin University, Tianjin, China
| | - Halima Bello Kawuwa
- Department of Biomedical Engineering and Scientific Instruments, School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Adamu Halilu Jabire
- Department of Electrical and Electronics Engineering, Taraba State University, Jalingo, Nigeria
| | - Sani Saminu
- Department of Biomedical Engineering, University of Ilorin, Ilorin, Nigeria
| |
Collapse
|
7
|
Pinto D, Martins R, Macedo A, Castelo Branco M, Valente Duarte J, Madeira N. Brain Hemispheric Asymmetry in Schizophrenia and Bipolar Disorder. J Clin Med 2023; 12:jcm12103421. [PMID: 37240527 DOI: 10.3390/jcm12103421] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/01/2023] [Accepted: 05/10/2023] [Indexed: 05/28/2023] Open
Abstract
BACKGROUND This study aimed to compare brain asymmetry in patients with schizophrenia (SCZ), bipolar disorder (BPD), and healthy controls to test whether asymmetry patterns could discriminate and set boundaries between two partially overlapping severe mental disorders. METHODS We applied a fully automated voxel-based morphometry (VBM) approach to assess structural brain hemispheric asymmetry in magnetic resonance imaging (MRI) anatomical scans in 60 participants (SCZ = 20; BP = 20; healthy controls = 20), all right-handed and matched for gender, age, and education. RESULTS Significant differences in gray matter asymmetry were found between patients with SCZ and BPD, between SCZ patients and healthy controls (HC), and between BPD patients and HC. We found a higher asymmetry index (AI) in BPD patients when compared to SCZ in Brodmann areas 6, 11, and 37 and anterior cingulate cortex and an AI higher in SCZ patients when compared to BPD in the cerebellum. CONCLUSION Our study found significant differences in brain asymmetry between patients with SCZ and BPD. These promising results could be translated to clinical practice, given that structural brain changes detected by MRI are good candidates for exploration as biological markers for differential diagnosis, besides helping to understand disease-specific abnormalities.
Collapse
Affiliation(s)
- Diogo Pinto
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
| | - Ricardo Martins
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal
| | - António Macedo
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal
- Department of Psychiatry, Centro Hospitalar e Universitário de Coimbra (CHUC), 3000-075 Coimbra, Portugal
| | - Miguel Castelo Branco
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal
| | - João Valente Duarte
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal
| | - Nuno Madeira
- Faculty of Medicine, University of Coimbra (UC), 3004-504 Coimbra, Portugal
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, 3000-548 Coimbra, Portugal
- Department of Psychiatry, Centro Hospitalar e Universitário de Coimbra (CHUC), 3000-075 Coimbra, Portugal
| |
Collapse
|
8
|
Goel T, Varaprasad SA, Tanveer M, Pilli R. Investigating White Matter Abnormalities Associated with Schizophrenia Using Deep Learning Model and Voxel-Based Morphometry. Brain Sci 2023; 13:brainsci13020267. [PMID: 36831810 PMCID: PMC9954172 DOI: 10.3390/brainsci13020267] [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: 12/30/2022] [Revised: 01/19/2023] [Accepted: 01/27/2023] [Indexed: 02/09/2023] Open
Abstract
Schizophrenia (SCZ) is a devastating mental condition with significant negative consequences for patients, making correct and prompt diagnosis crucial. The purpose of this study is to use structural magnetic resonance image (MRI) to better classify individuals with SCZ from control normals (CN) and to locate a region of the brain that represents abnormalities associated with SCZ. Deep learning (DL), which is based on the nervous system, could be a very useful tool for doctors to accurately predict, diagnose, and treat SCZ. Gray Matter (GM), Cerebrospinal Fluid (CSF), and White Matter (WM) brain regions are extracted from 99 MRI images obtained from the open-source OpenNeuro database to demonstrate SCZ's regional relationship. In this paper, we use a pretrained ResNet-50 deep network to extract features from MRI images and an ensemble deep random vector functional link (edRVFL) network to classify those features. By examining the results obtained, the edRVFL deep model provides the highest classification accuracy of 96.5% with WM and is identified as the best-performing algorithm compared to the traditional algorithms. Furthermore, we examined the GM, WM, and CSF tissue volumes in CN subjects and SCZ patients using voxel-based morphometry (VBM), and the results show 1363 significant voxels, 6.90 T-value, and 6.21 Z-value in the WM region of SCZ patients. In SCZ patients, WM is most closely linked to structural alterations, as evidenced by VBM analysis and the DL model.
Collapse
Affiliation(s)
- Tripti Goel
- Biomedical Imaging Lab, Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar 788010, Assam, India
- Correspondence: (T.G.); (M.T.)
| | - Sirigineedi A. Varaprasad
- Biomedical Imaging Lab, Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar 788010, Assam, India
| | - M. Tanveer
- Department of Mathematics, Indian Institute of Technology Indore, Simrol 453552, Madhya Pradesh, India
- Correspondence: (T.G.); (M.T.)
| | - Raveendra Pilli
- Biomedical Imaging Lab, Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Silchar 788010, Assam, India
| |
Collapse
|
9
|
Du H, Yang B, Wang H, Zeng Y, Xin J, Li X. The non-linear correlation between the volume of cerebral white matter lesions and incidence of bipolar disorder: A secondary analysis of data from a cross-sectional study. Front Psychiatry 2023; 14:1149663. [PMID: 37009125 PMCID: PMC10061585 DOI: 10.3389/fpsyt.2023.1149663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Accepted: 02/21/2023] [Indexed: 04/04/2023] Open
Abstract
Cerebral white matter lesions (WML) are major risk factors for bipolar disorder (BD). However, studies on the association between cerebral WML volume and BD risk are limited. This study aimed to investigate the relationship between cerebral WML volume and BD incidence. This is a secondary retrospective analysis of patients (N = 146, 72 males, 74 females, mean age = 41.77 years) who have previously undergone magnetic resonance imaging examinations. Information was obtained from the Dryad database. Univariate analysis, piecewise linear regression model, and multivariable logistic regression model were used for statistical analysis. A non-linear relationship was recognized between the cerebral WML volume and BD incidence, in which the inflection point of the WML volume was 6,200 mm3. The effect sizes and confidence intervals on the left and right sides of the emphasis point were 1.0009 (1.0003, 1.0015) and 0.9988 (0.9974, 1.0003), respectively. Subgroup analysis (WML volume < 6,200 mm3) showed that the cerebral WML volume (for 0.1 mm3 increase) was positively related to the BD incidence (OR = 1.11, 95% confidence interval [CI] (1.03, 1.21)). Here we show that the cerebral WML volume is positively and non-linearly correlated to the BD risk. Volumetric analysis of WML provide a better understanding of the association between WML and the BD risk, and thereby the pathophysiological mechanisms of BD. Graphical abstract A non-linear relationship between the volume of cerebral white matter lesions (WML) and bipolar disorder (BD) incidence is shown. The cerebral WML volume is positively and non-linearly correlated to the BD risk. The correlation is stronger when the cerebral WML volume was <6,200 mm3.Graphical AbstractA non-linear relationship between the volume of cerebral white matter lesions and bipolar disorder incidence is shown after adjusting for age; sex; lithium, atypical antipsychotic, antiepileptic, and antidepressant drug use; BMI; migraine; smoking; hypertension; diabetes mellitus; substance and alcohol dependency; and anxiety disorder.
Collapse
Affiliation(s)
- Hui Du
- Department of Blood Transfusion, Affiliated Xiaolan Hospital, Southern Medical University, Zhongshan, Guangdong, China
| | - Bing Yang
- Neurological Department and Stroke Center, the First Affiliated Hospital of Jinan University and Clinical Neuroscience Institute, Jinan University, Guangzhou, Guangdong, China
| | - Hui Wang
- Department of Neurology, Affiliated Xiaolan Hospital, Southern Medical University, Zhongshan, Guangdong, China
| | - Yaqing Zeng
- Department of Neurology, Affiliated Xiaolan Hospital, Southern Medical University, Zhongshan, Guangdong, China
| | - Jianpin Xin
- Department of Radiology, Affiliated Xiaolan Hospital, Southern Medical University, Zhongshan, Guangdong, China
| | - Xiaoqiang Li
- Department of Neurology, Affiliated Xiaolan Hospital, Southern Medical University, Zhongshan, Guangdong, China
- *Correspondence: Xiaoqiang Li,
| |
Collapse
|
10
|
de Sousa TR, Dt C, Novais F. Exploring the Hypothesis of a Schizophrenia and Bipolar Disorder Continuum: Biological, Genetic and Pharmacologic Data. CNS & NEUROLOGICAL DISORDERS DRUG TARGETS 2023; 22:161-171. [PMID: 34477537 DOI: 10.2174/1871527320666210902164235] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 07/19/2021] [Accepted: 08/08/2021] [Indexed: 12/16/2022]
Abstract
Present time nosology has its roots in Kraepelin's demarcation of schizophrenia and bipolar disorder. However, accumulating evidence has shed light on several commonalities between the two disorders, and some authors have advocated for the consideration of a disease continuum. Here, we review previous genetic, biological and pharmacological findings that provide the basis for this conceptualization. There is a cross-disease heritability, and they share single-nucleotide polymorphisms in some common genes. EEG and imaging patterns have a number of similarities, namely reduced white matter integrity and abnormal connectivity. Dopamine, serotonin, GABA and glutamate systems have dysfunctional features, some of which are identical among the disorders. Finally, cellular calcium regulation and mitochondrial function are, also, impaired in the two.
Collapse
Affiliation(s)
- Teresa Reynolds de Sousa
- Department of Neurosciences and Mental Health, Centro Hospitalar Universitário Lisboa Norte (CHULN), Hospital de Santa Maria, Lisbon, Portugal
| | - Correia Dt
- Department of Neurosciences and Mental Health, Centro Hospitalar Universitário Lisboa Norte (CHULN), Hospital de Santa Maria, Lisbon, Portugal
- Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal
- ISAMB - Instituto de Saúde Ambiental, Lisboa, Portugal
| | - Filipa Novais
- Department of Neurosciences and Mental Health, Centro Hospitalar Universitário Lisboa Norte (CHULN), Hospital de Santa Maria, Lisbon, Portugal
- Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal
- ISAMB - Instituto de Saúde Ambiental, Lisboa, Portugal
| |
Collapse
|
11
|
Rootes-Murdy K, Edmond JT, Jiang W, Rahaman MA, Chen J, Perrone-Bizzozero NI, Calhoun VD, van Erp TGM, Ehrlich S, Agartz I, Jönsson EG, Andreassen OA, Westlye LT, Wang L, Pearlson GD, Glahn DC, Hong E, Buchanan RW, Kochunov P, Voineskos A, Malhotra A, Tamminga CA, Liu J, Turner JA. Clinical and cortical similarities identified between bipolar disorder I and schizophrenia: A multivariate approach. Front Hum Neurosci 2022; 16:1001692. [PMID: 36438633 PMCID: PMC9684186 DOI: 10.3389/fnhum.2022.1001692] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 10/17/2022] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND Structural neuroimaging studies have identified similarities in the brains of individuals diagnosed with schizophrenia (SZ) and bipolar I disorder (BP), with overlap in regions of gray matter (GM) deficits between the two disorders. Recent studies have also shown that the symptom phenotypes associated with SZ and BP may allow for a more precise categorization than the current diagnostic criteria. In this study, we sought to identify GM alterations that were unique to each disorder and whether those alterations were also related to unique symptom profiles. MATERIALS AND METHODS We analyzed the GM patterns and clinical symptom presentations using independent component analysis (ICA), hierarchical clustering, and n-way biclustering in a large (N ∼ 3,000), merged dataset of neuroimaging data from healthy volunteers (HV), and individuals with either SZ or BP. RESULTS Component A showed a SZ and BP < HV GM pattern in the bilateral insula and cingulate gyrus. Component B showed a SZ and BP < HV GM pattern in the cerebellum and vermis. There were no significant differences between diagnostic groups in these components. Component C showed a SZ < HV and BP GM pattern bilaterally in the temporal poles. Hierarchical clustering of the PANSS scores and the ICA components did not yield new subgroups. N-way biclustering identified three unique subgroups of individuals within the sample that mapped onto different combinations of ICA components and symptom profiles categorized by the PANSS but no distinct diagnostic group differences. CONCLUSION These multivariate results show that diagnostic boundaries are not clearly related to structural differences or distinct symptom profiles. Our findings add support that (1) BP tend to have less severe symptom profiles when compared to SZ on the PANSS without a clear distinction, and (2) all the gray matter alterations follow the pattern of SZ < BP < HV without a clear distinction between SZ and BP.
Collapse
Affiliation(s)
- Kelly Rootes-Murdy
- Department of Psychology, Georgia State University, Atlanta, GA, United States
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Jesse T. Edmond
- Department of Psychology, Georgia State University, Atlanta, GA, United States
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Wenhao Jiang
- Department of Psychosomatics and Psychiatry, Medical School, Zhongda Hospital, Institute of Psychosomatics, Southeast University, Nanjing, China
| | - Md A. Rahaman
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Jiayu Chen
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | | | - Vince D. Calhoun
- Department of Psychology, Georgia State University, Atlanta, GA, United States
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, United States
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Ingrid Agartz
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute and Stockholm Health Care Services, Stockholm, Sweden
- K. G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Erik G. Jönsson
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institute and Stockholm Health Care Services, Stockholm, Sweden
| | - Ole A. Andreassen
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- K. G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Lars T. Westlye
- Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, Oslo University Hospital, University of Oslo, Oslo, Norway
- K. G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Lei Wang
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, United States
| | - Godfrey D. Pearlson
- Department of Psychiatry, Yale University, New Haven, CT, United States
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT, United States
| | - David C. Glahn
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT, United States
- Boston Children’s Hospital and Harvard Medical School, Boston, MA, United States
| | - Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Robert W. Buchanan
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Aristotle Voineskos
- Department of Psychiatry, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada
| | - Anil Malhotra
- Division of Psychiatry Research, Zucker Hillside Hospital, Queens, NY, United States
| | - Carol A. Tamminga
- Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, United States
| | - Jingyu Liu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, Emory University, Atlanta, GA, United States
| | - Jessica A. Turner
- Psychiatry and Behavioral Health, Ohio State Wexner Medical Center, Columbus, OH, United States
| |
Collapse
|
12
|
Chen G, Wang J, Gong J, Qi Z, Fu S, Tang G, Chen P, Huang L, Wang Y. Functional and structural brain differences in bipolar disorder: a multimodal meta-analysis of neuroimaging studies. Psychol Med 2022; 52:2861-2873. [PMID: 36093787 DOI: 10.1017/s0033291722002392] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
BACKGROUND Numerous studies of resting-state functional imaging and voxel-based morphometry (VBM) have revealed differences in specific brain regions of patients with bipolar disorder (BD), but the results have been inconsistent. METHODS A whole-brain voxel-wise meta-analysis was conducted on resting-state functional imaging and VBM studies that compared differences between patients with BD and healthy controls using Seed-based d Mapping with Permutation of Subject Images software. RESULTS A systematic literature search identified 51 functional imaging studies (1842 BD and 2190 controls) and 83 VBM studies (2790 BD and 3690 controls). Overall, patients with BD displayed increased resting-state functional activity in the left middle frontal gyrus, right inferior frontal gyrus (IFG) extending to the right insula, right superior frontal gyrus and bilateral striatum, as well as decreased resting-state functional activity in the left middle temporal gyrus extending to the left superior temporal gyrus and post-central gyrus, left cerebellum, and bilateral precuneus. The meta-analysis of VBM showed that patients with BD displayed decreased VBM in the right IFG extending to the right insula, temporal pole and superior temporal gyrus, left superior temporal gyrus extending to the left insula, temporal pole, and IFG, anterior cingulate cortex, left superior frontal gyrus (medial prefrontal cortex), left thalamus, and right fusiform gyrus. CONCLUSIONS The multimodal meta-analyses suggested that BD showed similar patterns of aberrant brain activity and structure in the insula extending to the temporal cortex, fronto-striatal-thalamic, and default-mode network regions, which provide useful insights for understanding the underlying pathophysiology of BD.
Collapse
Affiliation(s)
- Guanmao Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Junjing Wang
- Department of Applied Psychology, Guangdong University of Foreign Studies, Guangzhou, 510006, China
| | - Jiaying Gong
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
- Department of Radiology, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, China
| | - Zhangzhang Qi
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Siying Fu
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Guixian Tang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Pan Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Li Huang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, 510630, China
- Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, 510630, China
| |
Collapse
|
13
|
Rajashekar N, Blumberg HP, Villa LM. Neuroimaging Studies of Brain Structure in Older Adults with Bipolar Disorder: A Review. JOURNAL OF PSYCHIATRY AND BRAIN SCIENCE 2022; 7:e220006. [PMID: 36092855 PMCID: PMC9453888 DOI: 10.20900/jpbs.20220006] [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: 11/20/2022]
Abstract
Bipolar disorder (BD) is a common mood disorder that can have severe consequences during later life, including suffering and impairment due to mood and cognitive symptoms, elevated risk for dementia and an especially high risk for suicide. Greater understanding of the brain circuitry differences involved in older adults with BD (OABD) in later life and their relationship to aging processes is required to improve outcomes of OABD. The current literature on gray and white matter findings, from high resolution structural and diffusion-weighted magnetic resonance imaging (MRI) studies, has shown that BD in younger age groups is associated with gray matter reductions within cortical and subcortical brain regions that subserve emotion processing and regulation, as well as reduced structural integrity of white matter tracts connecting these brain regions. While fewer neuroimaging studies have focused on OABD, it does appear that many of the structural brain differences found in younger samples are present in OABD. There is also initial suggestion that there are additional brain differences, for at least a subset of OABD, that may result from more pronounced gray and white matter declines with age that may contribute to adverse outcomes. Preclinical and clinical data supporting neuro-plastic and -protective effects of mood-stabilizing medications, suggest that treatments may reverse and/or prevent the progression of brain changes thereby reducing symptoms. Future neuroimaging research implementing longitudinal designs, and large-scale, multi-site initiatives with detailed clinical and treatment data, holds promise for reducing suffering, cognitive dysfunction and suicide in OABD.
Collapse
Affiliation(s)
- Niroop Rajashekar
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Hilary P. Blumberg
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT 06520, USA
- Child Study Center, Yale School of Medicine, New Haven, CT 06519, USA
| | - Luca M. Villa
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
- Department of Psychiatry, University of Oxford, Oxford, OX37JX, UK
| |
Collapse
|
14
|
Long Q, Lv Z, Zhao J, Shi K, Li C, Fan B, Zheng J. Cerebral gray matter volume changes in patients with anti-N-methyl-D-aspartate receptor encephalitis: A voxel-based morphometry study. Front Neurol 2022; 13:892242. [PMID: 35959389 PMCID: PMC9358280 DOI: 10.3389/fneur.2022.892242] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 07/04/2022] [Indexed: 01/19/2023] Open
Abstract
Background Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is an autoimmune disease with typical clinical features. Whether and how cerebral gray matter structural damage inherent to the disorder affects cognitive function in patients is still unclear. Therefore, this study aimed to explore the changes in cerebral gray matter volume and whether these alterations contribute to cognitive impairment and mood disorders. Methods Forty patients with anti-NMDAR encephalitis and forty healthy controls (HCs) matched for gender, age, and education were recruited. All participants underwent attention network tests (ANT), neuropsychological tests and magnetic resonance imaging (MRI). Voxel-based morphological analysis (VBM) and correlation analysis was performed on all participants. Finally, according to the course of disease, patients were divided into two groups: NMDARE_SD (short duration; course ≤ 2 years since diagnosis) and NMDARE_LD (long duration; course >2 years since diagnosis), to evaluate gray matter volume changes that differ as a function of disease course. Results Compared to HCs, patients with anti-NMDAR encephalitis showed decreased executive control ability and lower MoCA score, while increased anxiety and depression as reflected by HAMA and HAMD24 scores (all P < 0.05). In VBM analysis, patients showed decreased gray matter volume in bilateral thalamus, left medial prefrontal cortex (mPFC_L), left superior temporal gyrus (STG_L), and left rectus gyrus. In the analysis stratified by disease course, the NMDARE_LD group exhibited decreased gray matter volume in the left precuneus and right posterior cerebellar lobe compared to the NMDARE_SD group. Conclusions Patients with anti-NMDAR encephalitis have cognitive, executive, and emotional dysfunction, and the sites of gray matter atrophy are concentrated in the thalamus, frontal lobe, and temporal lobe. These abnormalities may be involved in the process of cognitive and affective dysfunction.Patients with different courses of anti-NMDAR encephalitis have different brain atrophy sites. These results may help to clarify the contradiction between clinical and imaging manifestations of anti NMDAR encephalitis, which is worthy of further longitudinal studies.
Collapse
Affiliation(s)
| | | | | | | | | | | | - Jinou Zheng
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| |
Collapse
|
15
|
Structural MRI-Based Schizophrenia Classification Using Autoencoders and 3D Convolutional Neural Networks in Combination with Various Pre-Processing Techniques. Brain Sci 2022; 12:brainsci12050615. [PMID: 35625002 PMCID: PMC9139344 DOI: 10.3390/brainsci12050615] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 01/10/2023] Open
Abstract
Schizophrenia is a severe neuropsychiatric disease whose diagnosis, unfortunately, lacks an objective diagnostic tool supporting a thorough psychiatric examination of the patient. We took advantage of today’s computational abilities, structural magnetic resonance imaging, and modern machine learning methods, such as stacked autoencoders (SAE) and 3D convolutional neural networks (3D CNN), to teach them to classify 52 patients with schizophrenia and 52 healthy controls. The main aim of this study was to explore whether complex feature extraction methods can help improve the accuracy of deep learning-based classifiers compared to minimally preprocessed data. Our experiments employed three commonly used preprocessing steps to extract three different feature types. They included voxel-based morphometry, deformation-based morphometry, and simple spatial normalization of brain tissue. In addition to classifier models, features and their combination, other model parameters such as network depth, number of neurons, number of convolutional filters, and input data size were also investigated. Autoencoders were trained on feature pools of 1000 and 5000 voxels selected by Mann-Whitney tests, and 3D CNNs were trained on whole images. The most successful model architecture (autoencoders) achieved the highest average accuracy of 69.62% (sensitivity 68.85%, specificity 70.38%). The results of all experiments were statistically compared (the Mann-Whitney test). In conclusion, SAE outperformed 3D CNN, while preprocessing using VBM helped SAE improve the results.
Collapse
|
16
|
Zhang L, Zhang R, Han S, Womer FY, Wei Y, Duan J, Chang M, Li C, Feng R, Liu J, Zhao P, Jiang X, Wei S, Yin Z, Zhang Y, Zhang Y, Zhang X, Tang Y, Wang F. Three major psychiatric disorders share specific dynamic alterations of intrinsic brain activity. Schizophr Res 2022; 243:322-329. [PMID: 34244046 DOI: 10.1016/j.schres.2021.06.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2020] [Revised: 05/21/2021] [Accepted: 06/18/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Increasing evidence suggests that major psychiatric disorders, including major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SZ) share biological, neuropsychological and clinical features, despite the criteria for their respective diagnoses being different. Neuroimaging studies have shown disrupted 'static' neural connectivity in these disorders. However, the changes in brain dynamics across the three psychiatric disorders remain unknown. METHODS We aim to examine the connections and divergencies of the dynamic amplitude of low-frequency fluctuation (dALFF) in MDD, BD and SZ. In total, 901 participants [MDD, 229; BD, 146; SZ, 142; and healthy controls (HCs), 384] received resting-state functional magnetic resonance imaging. The dALFF was calculated using sliding-window analysis and compared across three psychiatric disorders. RESULTS We found significant increases of dALFF in the right fusiform, right hippocampus, right parahippocampal in participants with MDD, BD and SZ compared to HC. We also found specific increased dALFF changes in caudate and left thalamus for SZ and BD and decreased dALFF changes in calcarine and lingual for SZ and MDD. CONCLUSION Our study found significant intrinsic brain activity changes in the limbic system and primary visual area in MDD, BD, and SZ, which indicates these areas disruptions are core neurobiological features shared among three psychiatric disorders. Meanwhile, our findings also indicate that specific alterations in MDD, BD, and SZ provide neuroimaging evidence for the differential diagnosis of the three mental disorders.
Collapse
Affiliation(s)
- Luheng Zhang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Ran Zhang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, PR China
| | - Shaoqiang Han
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, PR China
| | - Fay Y Womer
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Yange Wei
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, PR China
| | - Jia Duan
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Miao Chang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Chao Li
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Ruiqi Feng
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Juan Liu
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Pengfei Zhao
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Xiaowei Jiang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Shengnan Wei
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Zhiyang Yin
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Yifan Zhang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China
| | - Yanbo Zhang
- Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Canada
| | - Xizhe Zhang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, PR China; School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China.
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China.
| | - Fei Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China; Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, PR China.
| |
Collapse
|
17
|
Zhao Z, Zhu L, Wu X, Chen Q, Xu B, Yang J, Guo X, Su L. Genome-wide association studies-supported rs12966547 variant of the long noncoding RNA LOC105372125 is significantly associated with susceptibility to schizophrenia and bipolar disorder in Han Chinese women. Psychiatr Genet 2022; 32:74-79. [PMID: 35191423 DOI: 10.1097/ypg.0000000000000312] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Genome-wide association studies have found that rs12966547 polymorphism was associated with susceptibility to schizophrenia in European populations. Recent studies showed that a genetic overlap may exist in schizophrenia and bipolar disorder. Here, we analyzed the associations between LOC105372125 rs12966547 polymorphism and schizophrenia and bipolar disorder in the Han Chinese population. METHODS Our study recruited 548 schizophrenia patients, 512 bipolar disorder patients, and 598 healthy controls. Genotyping of rs12966547 were performed using the Sequenom MassARRAY platform. RESULTS A significant association between rs12966547 polymorphism and susceptibility to bipolar disorder was observed after adjusting for sex and age (additive model: Padj = 0.040, recessive model: Padj = 0.044). However, no significant association was found between rs12966547 polymorphism and schizophrenia risk (all P > 0.05). In the analysis of gender, rs12966547 polymorphism was significantly associated with bipolar disorder (additive model: Padj = 0.027) and schizophrenia (dominant model: Padj = 0.039) in women. However, no significant association was found between rs12966547 polymorphism and the risk of bipolar disorder or schizophrenia in men (all Padj > 0.05). CONCLUSIONS Polymorphism of rs12966547 on the long noncoding RNA LOC10537215 are a shared genetic variant of schizophrenia and bipolar disorder in Han Chinese women.
Collapse
Affiliation(s)
- Zhi Zhao
- School of Public Health of Guangxi Medical University, Nanning
| | - Lulu Zhu
- School of Public Health of Guangxi Medical University, Nanning
| | - Xulong Wu
- School of Public Health of Guangxi Medical University, Nanning
| | - Qiang Chen
- Guangxi Brain Hospital, Liuzhou, Guangxi, China
| | - Bingyi Xu
- School of Public Health of Guangxi Medical University, Nanning
| | - Jialei Yang
- School of Public Health of Guangxi Medical University, Nanning
| | | | - Li Su
- School of Public Health of Guangxi Medical University, Nanning
| |
Collapse
|
18
|
Hsu TW, Bai YM, Tsai SJ, Chen TJ, Liang CS, Chen MH. Risk of retinal disease in patients with bipolar disorder: A nationwide cohort study. Psychiatry Clin Neurosci 2022; 76:106-113. [PMID: 34994991 DOI: 10.1111/pcn.13326] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 12/06/2021] [Accepted: 12/21/2021] [Indexed: 12/13/2022]
Abstract
AIMS Patients with brain diseases have been associated with several retinal abnormalities. This study aimed to assess the risk of retinal diseases in patients with bipolar disorder (BD). METHODS This nationwide cohort of 73,271 patients with BD was enrolled between 2001 and 2009. To identify newly diagnosed retinal diseases, the patients were followed to the end of 2011. The control group included 293,084 patients, matched for demographic characteristics and medical and ophthalmological comorbidities. The Kaplan-Meier method was used to estimate incidence rates of retinal diseases. Cox regression was applied to calculate the hazard ratios (HRs) with 95% confidence intervals (CIs) after adjusting for confounders. RESULTS Patients with BD had higher incidence rates of any retinal disease than the controls (1.27% vs 0.48%, P < 0.001), and retinal diseases were diagnosed at a young age (54.23 years [±12.68 years] vs 57.01 years [±13.12 years], P < 0.001). After adjusting for demographic characteristics, physical and ophthalmological comorbidities, and medications, the HR was 3.24 (95% CI, 2.18-4.82) for retinal detachment, 2.35 (95% CI, 1.83-3.03) for primary retinopathy, 2.26 (95% CI, 1.91-2.68) for diabetes retinopathy, 2.39 (95% CI, 1.49-3.82) for hypertensive retinopathy, and 3.46 (95% CI, 2.45-4.89) for retinal vascular complications in patients with BD vs controls. The cumulative daily dose of bipolar medications was not associated with the incidence of any retinal disease. CONCLUSION Patients with BD were associated with a higher risk of retinal detachment, primary retinopathy, diabetes retinopathy, hypertensive retinopathy, and retinal vascular complications than the controls. Further studies are needed to examine the mechanisms mediating these retinal diseases in patients with BD.
Collapse
Affiliation(s)
- Tien-Wei Hsu
- Department of Psychiatry, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - Ya-Mei Bai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Tzeng-Ji Chen
- Department of Psychiatry, Beitou Branch, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.,Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan
| | - Chih-Sung Liang
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Hospital and Health Care Administration, National Yang-Ming University, Taipei, Taiwan
| | - Mu-Hong Chen
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| |
Collapse
|
19
|
The Limits between Schizophrenia and Bipolar Disorder: What Do Magnetic Resonance Findings Tell Us? Behav Sci (Basel) 2022; 12:bs12030078. [PMID: 35323397 PMCID: PMC8944966 DOI: 10.3390/bs12030078] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 01/10/2022] [Accepted: 03/10/2022] [Indexed: 02/01/2023] Open
Abstract
Schizophrenia and bipolar disorder, two of the most severe psychiatric illnesses, have historically been regarded as dichotomous entities but share many features of the premorbid course, clinical profile, genetic factors and treatment approaches. Studies focusing on neuroimaging findings have received considerable attention, as they plead for an improved understanding of the brain regions involved in the pathophysiology of schizophrenia and bipolar disorder. In this review, we summarize the main magnetic resonance imaging findings in both disorders, aiming at exploring the neuroanatomical and functional similarities and differences between the two. The findings show that gray and white matter structural changes and functional dysconnectivity predominate in the frontal and limbic areas and the frontotemporal circuitry of the brain areas involved in the integration of executive, cognitive and affective functions, commonly affected in both disorders. Available evidence points to a considerable overlap in the affected regions between the two conditions, therefore possibly placing them at opposite ends of a psychosis continuum.
Collapse
|
20
|
Luttenbacher I, Phillips A, Kazemi R, Hadipour AL, Sanghvi I, Martinez J, Adamson MM. Transdiagnostic role of glutamate and white matter damage in neuropsychiatric disorders: A Systematic Review. J Psychiatr Res 2022; 147:324-348. [PMID: 35151030 DOI: 10.1016/j.jpsychires.2021.12.042] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/08/2021] [Accepted: 12/19/2021] [Indexed: 12/09/2022]
Abstract
Neuropsychiatric disorders including generalized anxiety disorder (GAD), obsessive-compulsive disorder (OCD), major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ) have been considered distinct categories of diseases despite their overlapping characteristics and symptomatology. We aimed to provide an in-depth review elucidating the role of glutamate/Glx and white matter (WM) abnormalities in these disorders from a transdiagnostic perspective. The PubMed online database was searched for studies published between 2010 and 2021. After careful screening, 401 studies were included. The findings point to decreased levels of glutamate in the Anterior Cingulate Cortex in both SZ and BD, whereas Glx is elevated in the Hippocampus in SZ and MDD. With regard to WM abnormalities, the Corpus Callosum and superior Longitudinal Fascicle were the most consistently identified brain regions showing decreased fractional anisotropy (FA) across all the reviewed disorders, except GAD. Additionally, the Uncinate Fasciculus displayed decreased FA in all disorders, except OCD. Decreased FA was also found in the inferior Longitudinal Fasciculus, inferior Fronto-Occipital Fasciculus, Thalamic Radiation, and Corona Radiata in SZ, BD, and MDD. Decreased FA in the Fornix and Corticospinal Tract were found in BD and SZ patients. The Cingulum and Anterior Limb of Internal Capsule exhibited decreased FA in MDD and SZ patients. The results suggest a gradual increase in severity from GAD to SZ defined by the number of brain regions with WM abnormality which may be partially caused by abnormal glutamate levels. WM damage could thus be considered a potential marker of some of the main neuropsychiatric disorders.
Collapse
Affiliation(s)
- Ines Luttenbacher
- Department of Social & Behavioral Sciences, University of Amsterdam, Amsterdam, Netherlands; Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Angela Phillips
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Reza Kazemi
- Department of Cognitive Psychology, Institute for Cognitive Science Studies, Tehran, Iran
| | - Abed L Hadipour
- Department of Cognitive Sciences, University of Messina, Messina, Italy
| | - Isha Sanghvi
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Neuroscience, University of Southern California, Los Angeles, CA, USA
| | - Julian Martinez
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Palo Alto University, Palo Alto, CA, USA
| | - Maheen M Adamson
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA.
| |
Collapse
|
21
|
Valdés-Tovar M, Rodríguez-Ramírez AM, Rodríguez-Cárdenas L, Sotelo-Ramírez CE, Camarena B, Sanabrais-Jiménez MA, Solís-Chagoyán H, Argueta J, López-Riquelme GO. Insights into myelin dysfunction in schizophrenia and bipolar disorder. World J Psychiatry 2022; 12:264-285. [PMID: 35317338 PMCID: PMC8900585 DOI: 10.5498/wjp.v12.i2.264] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/10/2021] [Accepted: 01/17/2022] [Indexed: 02/06/2023] Open
Abstract
Schizophrenia and bipolar disorder are disabling psychiatric disorders with a worldwide prevalence of approximately 1%. Both disorders present chronic and deteriorating prognoses that impose a large burden, not only on patients but also on society and health systems. These mental illnesses share several clinical and neurobiological traits; of these traits, oligodendroglial dysfunction and alterations to white matter (WM) tracts could underlie the disconnection between brain regions related to their symptomatic domains. WM is mainly composed of heavily myelinated axons and glial cells. Myelin internodes are discrete axon-wrapping membrane sheaths formed by oligodendrocyte processes. Myelin ensheathment allows fast and efficient conduction of nerve impulses through the nodes of Ranvier, improving the overall function of neuronal circuits. Rapid and precisely synchronized nerve impulse conduction through fibers that connect distant brain structures is crucial for higher-level functions, such as cognition, memory, mood, and language. Several cellular and subcellular anomalies related to myelin and oligodendrocytes have been found in postmortem samples from patients with schizophrenia or bipolar disorder, and neuroimaging techniques have revealed consistent alterations at the macroscale connectomic level in both disorders. In this work, evidence regarding these multilevel alterations in oligodendrocytes and myelinated tracts is discussed, and the involvement of proteins in key functions of the oligodendroglial lineage, such as oligodendrogenesis and myelination, is highlighted. The molecular components of the axo-myelin unit could be important targets for novel therapeutic approaches to schizophrenia and bipolar disorder.
Collapse
Affiliation(s)
- Marcela Valdés-Tovar
- Departamento de Farmacogenética, Subdirección de Investigaciones Clínicas, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City 14370, Mexico
| | | | - Leslye Rodríguez-Cárdenas
- Departamento de Farmacogenética, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City 14370, Mexico
| | - Carlo E Sotelo-Ramírez
- Departamento de Farmacogenética, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City 14370, Mexico
- Doctorado en Biología Experimental, Universidad Autónoma Metropolitana-Iztapalapa, Mexico City 09340, Mexico
| | - Beatriz Camarena
- Departamento de Farmacogenética, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City 14370, Mexico
| | | | - Héctor Solís-Chagoyán
- Laboratorio de Neurofarmacología, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City 14370, Mexico
| | - Jesús Argueta
- Doctorado en Biología Experimental, Universidad Autónoma Metropolitana-Iztapalapa, Mexico City 09340, Mexico
- Laboratorio de Neurofarmacología, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City 14370, Mexico
| | - Germán Octavio López-Riquelme
- Laboratorio de Socioneurobiología, Centro de Investigación en Ciencias Cognitivas, Universidad del Estado de Morelos, Cuernavaca 62209, Morelos, Mexico
| |
Collapse
|
22
|
Abstract
Bipolar disorder (BD) is a complex group of neuropsychiatric disorders, typically comprising both manic and depressive episodes. The underlying neuropathology of BD is not established, but a consistent feature is progressive thinning of cortical grey matter (GM) and white matter (WM) in specific pathways, due to loss of subpopulations of neurons and astrocytes, with accompanying disturbance of connectivity. Dysregulation of astrocyte homeostatic functions are implicated in BD, notably regulation of glutamate, calcium signalling, circadian rhythms and metabolism. Furthermore, the beneficial therapeutic effects of the frontline treatments for BD are due at least in part to their positive actions on astrocytes, notably lithium, valproic acid (VPA) and carbamazepine (CBZ), as well as antidepressants and antipsychotics that are used in the management of this disorder. Treatments for BD are ineffective in a large proportion of cases, and astrocytes represent new therapeutic targets that can also serve as biomarkers of illness progression and treatment responsiveness in BD.
Collapse
|
23
|
Differentiating white matter measures that protect against vs. predispose to bipolar disorder and other psychopathology in at-risk youth. Neuropsychopharmacology 2021; 46:2207-2216. [PMID: 34285367 PMCID: PMC8505429 DOI: 10.1038/s41386-021-01088-1] [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: 02/19/2021] [Revised: 06/17/2021] [Accepted: 06/24/2021] [Indexed: 12/02/2022]
Abstract
Bipolar disorder (BD) is highly heritable. Identifying objective biomarkers reflecting pathophysiological processes predisposing to, versus protecting against BD, can help identify BD risk in offspring of BD parents. We recruited 21 BD participants with a first-degree relative with BD, 25 offspring of BD parents, 27 offspring of comparison parents with non-BD psychiatric disorders, and 32 healthy offspring of healthy parents. In at-risk groups, 23 had non-BD diagnoses and 29, no Axis-I diagnoses(healthy). Five at-risk offspring who developed BD post scan(Converters) were included. Diffusion imaging(dMRI) analysis with tract segmentation identified between-group differences in the microstructure of prefrontal tracts supporting emotional regulation relevant to BD: forceps minor, anterior thalamic radiation(ATR), cingulum bundle(CB), and uncinate fasciculus(UF). BD participants showed lower fractional anisotropy (FA) in the right CB (anterior portion) than other groups (q < 0.05); and in bilateral ATR (posterior portion) versus at-risk groups (q < 0.001). Healthy, but not non-BD, at-risk participants showed significantly higher FA in bilateral ATR clusters than healthy controls (qs < 0.05). At-risk groups showed higher FA in these clusters than BD participants (qs < 0.05). Non-BD versus healthy at-risk participants, and Converters versus offspring of BD parents, showed lower FA in the right ATR cluster (qs < 0.05). Low anterior right CB FA in BD participants versus other groups might result from having BD. High bilateral ATR FA in at-risk groups, and in healthy at-risk participants, versus healthy controls might protect against BD/other psychiatric disorders. Absence of elevated right ATR FA in non-BD versus healthy at-risk participants, and in Converters versus non-converter offspring of BD parents, might lower protection against BD in at-risk groups.
Collapse
|
24
|
Kuang L, Gao W, Long Z, Cao W, Cui D, Guo Y, Jiao Q, Qiu J, Su L, Lu G. Common and Specific Characteristics of Adolescent Bipolar Disorder Types I and II: A Combined Cortical Thickness and Structural Covariance Analysis. Front Psychiatry 2021; 12:750798. [PMID: 35126192 PMCID: PMC8814452 DOI: 10.3389/fpsyt.2021.750798] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 12/08/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND By calculating cortical thickness (CT) and cortical structural covariance (SC), we aimed to investigate cortical morphology and cortical inter-regional correlation alterations in adolescent bipolar disorder type I (BD-I) and type II (BD-II) patients. METHODS T1-weighted images from 36 BD-I and 22 BD-II patients and 19 healthy controls (HCs) were processed to estimate CT. CT values of the whole brain were compared among three groups. Cortical regions showing CT differences in groups were regarded as seeds for analyzing cortical SC differences between groups. The relationship between CT and clinical indices was further assessed. RESULTS Both BD groups showed cortical thinning in several frontal and temporal areas vs. HCs, and CT showed no significant difference between two BD subtypes. Compared to HCs, both BD groups exhibited reduced SC connections between left superior frontal gyrus (SFG) and right postcentral gyrus (PCG), left superior temporal gyrus (STG) and right pars opercularis, and left STG and right PCG. Compared with HCs, decreased SC connections between left STG and right inferior parietal gyrus (IPG) and right pars opercularis and right STG were only observed in the BD-I group, and left PCG and left SFG only in the BD-II group. CT of right middle temporal gyrus was negatively correlated with number of episodes in BD-II patients. CONCLUSIONS Adolescent BD-I and BD-II showed commonly decreased CT while presenting commonly and distinctly declined SC connections. This study provides a better understanding of cortical morphology and cortical inter-regional correlation alterations in BD and crucial insights into neuroanatomical mechanisms and pathophysiology of different BD subtypes.
Collapse
Affiliation(s)
- Liangfeng Kuang
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Weijia Gao
- Department of Child Psychology, The Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhiliang Long
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Weifang Cao
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Dong Cui
- Institute of Biomedical Engineering, Chinese Academy of Medical Science and Peking Union Medical College, Tianjin, China
| | - Yongxin Guo
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Qing Jiao
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Jianfeng Qiu
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, China
| | - Linyan Su
- Mental Health Institute of The Second Xiangya Hospital, Central South University, Changsha, China
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing, China
| |
Collapse
|
25
|
Jones MT, Harvey PD. Major Neuropsychological Impairments in Schizophrenia Patients: Clinical Implications. Curr Psychiatry Rep 2020; 22:59. [PMID: 32886232 DOI: 10.1007/s11920-020-01181-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
PURPOSE OF REVIEW Schizophrenia is a complex severe mental illness with high morbidity and mortality. It is characterized by positive symptoms, negative symptoms, and cognitive impairment. Cognitive impairment is strongly associated with functional impairment and presents a major barrier to recovery. This article reviews some of the most recent research on cognition in schizophrenia and the clinical implications. RECENT FINDINGS There have been recent studies related to the genomics of cognition and neural structures involved in cognition. We review recent investigations into the assessment of social cognition and the implications of impaired introspective accuracy. A recent network analysis assessed the relationship of neurocognition and social cognition to functional capacity. We further discuss the role of specific symptoms in functioning, including negative symptoms and symptoms related to autism spectrum disorder. We conclude with a discussion of a novel computerized treatment for social cognition. Recent research has sought to better understand several dimensions of cognition including genomics, brain structure, social cognition, functional capacity, and symptomatology. This recent research brings us closer to understanding the complex clinical picture of schizophrenia and the best treatments to achieve recovery.
Collapse
Affiliation(s)
- Mackenzie T Jones
- Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, USA.
| | - Philip D Harvey
- Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, USA.,Research Service, Bruce W. Carter VA Medical Center, Miami, FL, USA
| |
Collapse
|
26
|
Benear SL, Ngo CT, Olson IR. Dissecting the Fornix in Basic Memory Processes and Neuropsychiatric Disease: A Review. Brain Connect 2020; 10:331-354. [PMID: 32567331 DOI: 10.1089/brain.2020.0749] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background: The fornix is the primary axonal tract of the hippocampus, connecting it to modulatory subcortical structures. This review reveals that fornix damage causes cognitive deficits that closely mirror those resulting from hippocampal lesions. Methods: We reviewed the literature on the fornix, spanning non-human animal lesion research, clinical case studies of human patients with fornix damage, as well as diffusion-weighted imaging (DWI) work that evaluates fornix microstructure in vivo. Results: The fornix is essential for memory formation because it serves as the conduit for theta rhythms and acetylcholine, as well as providing mnemonic representations to deep brain structures that guide motivated behavior, such as when and where to eat. In rodents and non-human primates, fornix lesions lead to deficits in conditioning, reversal learning, and navigation. In humans, damage to the fornix manifests as anterograde amnesia. DWI research reveals that the fornix plays a key role in mild cognitive impairment and Alzheimer's Disease, and can potentially predict conversion from the former to the latter. Emerging DWI findings link perturbations in this structure to schizophrenia, mood disorders, and eating disorders. Cutting-edge research has investigated how deep brain stimulation of the fornix can potentially attenuate memory loss, control epileptic seizures, and even improve mood. Conclusions: The fornix is essential to a fully functioning memory system and is implicated in nearly all neurological functions that rely on the hippocampus. Future research needs to use optimized DWI methods to study the fornix in vivo, which we discuss, given the difficult nature of fornix reconstruction. Impact Statement The fornix is a white matter tract that connects the hippocampus to several subcortical brain regions and is pivotal for episodic memory functioning. Functionally, the fornix transmits essential neurotransmitters, as well as theta rhythms, to the hippocampus. In addition, it is the conduit by which memories guide decisions. The fornix is biomedically important because lesions to this tract result in irreversible anterograde amnesia. Research using in vivo imaging methods has linked fornix pathology to cognitive aging, mild cognitive impairment, psychosis, epilepsy, and, importantly, Alzheimer's Disease.
Collapse
Affiliation(s)
- Susan L Benear
- Department of Psychology, Temple University, Philadelphia, Pennsylvania, USA
| | - Chi T Ngo
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Ingrid R Olson
- Department of Psychology, Temple University, Philadelphia, Pennsylvania, USA
| |
Collapse
|