1
|
Yu T, Pei WZ, Xu CY, Deng CC, Zhang XL. Identification of male schizophrenia patients using brain morphology based on machine learning algorithms. World J Psychiatry 2024; 14:804-811. [DOI: 10.5498/wjp.v14.i6.804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 05/01/2024] [Accepted: 05/21/2024] [Indexed: 06/19/2024] Open
Abstract
BACKGROUND Schizophrenia is a severe psychiatric disease, and its prevalence is higher. However, diagnosis of early-stage schizophrenia is still considered a challenging task.
AIM To employ brain morphological features and machine learning method to differentiate male individuals with schizophrenia from healthy controls.
METHODS The least absolute shrinkage and selection operator and t tests were applied to select important features from structural magnetic resonance images as input features for classification. Four commonly used machine learning algorithms, the general linear model, random forest (RF), k-nearest neighbors, and support vector machine algorithms, were used to develop the classification models. The performance of the classification models was evaluated according to the area under the receiver operating characteristic curve (AUC).
RESULTS A total of 8 important features with significant differences between groups were considered as input features for the establishment of classification models based on the four machine learning algorithms. Compared to other machine learning algorithms, RF yielded better performance in the discrimination of male schizophrenic individuals from healthy controls, with an AUC of 0.886.
CONCLUSION Our research suggests that brain morphological features can be used to improve the early diagnosis of schizophrenia in male patients.
Collapse
Affiliation(s)
- Tao Yu
- Department of Clinical Nutrition, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
| | - Wen-Zhi Pei
- Department of Psychiatry, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
| | - Chun-Yuan Xu
- Department of Clinical Nutrition, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
| | - Chen-Chen Deng
- Department of Gynaecology, Anhui Maternal and Child Health Hospital, Hefei 230032, Anhui Province, China
| | - Xu-Lai Zhang
- Department of Psychiatry, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
| |
Collapse
|
2
|
Tandon R, Nasrallah H, Akbarian S, Carpenter WT, DeLisi LE, Gaebel W, Green MF, Gur RE, Heckers S, Kane JM, Malaspina D, Meyer-Lindenberg A, Murray R, Owen M, Smoller JW, Yassin W, Keshavan M. The schizophrenia syndrome, circa 2024: What we know and how that informs its nature. Schizophr Res 2024; 264:1-28. [PMID: 38086109 DOI: 10.1016/j.schres.2023.11.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 11/23/2023] [Accepted: 11/29/2023] [Indexed: 03/01/2024]
Abstract
With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.
Collapse
Affiliation(s)
- Rajiv Tandon
- Department of Psychiatry, WMU Homer Stryker School of Medicine, Kalamazoo, MI 49008, United States of America.
| | - Henry Nasrallah
- Department of Psychiatry, University of Cincinnati College of Medicine Cincinnati, OH 45267, United States of America
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, United States of America
| | - William T Carpenter
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21201, United States of America
| | - Lynn E DeLisi
- Department of Psychiatry, Cambridge Health Alliance and Harvard Medical School, Cambridge, MA 02139, United States of America
| | - Wolfgang Gaebel
- Department of Psychiatry and Psychotherapy, LVR-Klinikum Dusseldorf, Heinrich-Heine University, Dusseldorf, Germany
| | - Michael F Green
- Department of Psychiatry and Biobehavioral Sciences, Jane and Terry Semel Institute of Neuroscience and Human Behavior, UCLA, Los Angeles, CA 90024, United States of America; Greater Los Angeles Veterans' Administration Healthcare System, United States of America
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, United States of America
| | - Stephan Heckers
- Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN 37232, United States of America
| | - John M Kane
- Department of Psychiatry, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Glen Oaks, NY 11004, United States of America
| | - Dolores Malaspina
- Department of Psychiatry, Neuroscience, Genetics, and Genomics, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, United States of America
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannhein/Heidelberg University, Mannheim, Germany
| | - Robin Murray
- Institute of Psychiatry, Psychology, and Neuroscience, Kings College, London, UK
| | - Michael Owen
- Centre for Neuropsychiatric Genetics and Genomics, and Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Jordan W Smoller
- Center for Precision Psychiatry, Department of Psychiatry, Psychiatric and Neurodevelopmental Unit, Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States of America
| | - Walid Yassin
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States of America
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02115, United States of America
| |
Collapse
|
3
|
Yang W, Niu H, Jin Y, Cui J, Li M, Qiu Y, Lu D, Li G, Li J. Altered dynamic functional connectivity of the thalamus subregions in patients with schizophrenia. J Psychiatr Res 2023; 167:86-92. [PMID: 37862908 DOI: 10.1016/j.jpsychires.2023.09.021] [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: 03/12/2023] [Revised: 06/05/2023] [Accepted: 09/27/2023] [Indexed: 10/22/2023]
Abstract
BACKGROUND Previous neuroimaging studies indicated that patients with schizophrenia showed impaired thalamus and thalamo-cortical circuits. However, the dynamic functional connectivity (dFC) patterns of the thalamus remain unclear. In this study, we explored the dFC of the thalamus in SZ patients and whether clinical features are correlated with altered dFC. METHODS Forty-three patients with schizophrenia and 31 healthy controls underwent 3.0 T rs-fMRI. Based on the human Brainnetome atlas, the thalamus is divided into 8 subregions. Subsequently, we performed flexible least squares method to calculate the dFC of each thalamus subregions. RESULTS Compared with healthy controls, patients with schizophrenia exhibited increased dFC between the thalamus and cerebellar, visual-related cortex, sensorimotor-related cortex, and frontal lobe. In addition, we found that the dFC of the thalamus and the right fusiform gyrus was negatively associated with age of onset. CONCLUSIONS Our findings demonstrated that the dFC of specific thalamus sub-regions is altered in patients with schizophrenia. Our results further suggested the dysconnectivity of thalamus plays an important role in the pathophysiology of schizophrenia.
Collapse
Affiliation(s)
- Weiliang Yang
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China
| | - Huiming Niu
- The Third People's Hospital of Tianshui, Tianshui, 741000, China
| | - Yiqiong Jin
- The Third People's Hospital of Tianshui, Tianshui, 741000, China
| | - Jie Cui
- The Third People's Hospital of Tianshui, Tianshui, 741000, China
| | - Meijuan Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China
| | - Yuying Qiu
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China
| | - Duihong Lu
- The Third People's Hospital of Tianshui, Tianshui, 741000, China
| | - Gang Li
- The Third People's Hospital of Tianshui, Tianshui, 741000, China
| | - Jie Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China.
| |
Collapse
|
4
|
Palau P, Solanes A, Madre M, Saez-Francas N, Sarró S, Moro N, Verdolini N, Sanchez M, Alonso-Lana S, Amann BL, Romaguera A, Martin-Subero M, Fortea L, Fuentes-Claramonte P, García-León MA, Munuera J, Canales-Rodríguez EJ, Fernández-Corcuera P, Brambilla P, Vieta E, Pomarol-Clotet E, Radua J. Improved estimation of the risk of manic relapse by combining clinical and brain scan data. SPANISH JOURNAL OF PSYCHIATRY AND MENTAL HEALTH 2023; 16:235-243. [PMID: 37839962 DOI: 10.1016/j.rpsm.2023.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 12/22/2022] [Accepted: 01/04/2023] [Indexed: 01/11/2023]
Abstract
INTRODUCTION Estimating the risk of manic relapse could help the psychiatrist individually adjust the treatment to the risk. Some authors have attempted to estimate this risk from baseline clinical data. Still, no studies have assessed whether the estimation could improve by adding structural magnetic resonance imaging (MRI) data. We aimed to evaluate it. MATERIAL AND METHODS We followed a cohort of 78 patients with a manic episode without mixed symptoms (bipolar type I or schizoaffective disorder) at 2-4-6-9-12-15-18 months and up to 10 years. Within a cross-validation scheme, we created and evaluated a Cox lasso model to estimate the risk of manic relapse using both clinical and MRI data. RESULTS The model successfully estimated the risk of manic relapse (Cox regression of the time to relapse as a function of the estimated risk: hazard ratio (HR)=2.35, p=0.027; area under the curve (AUC)=0.65, expected calibration error (ECE)<0.2). The most relevant variables included in the model were the diagnosis of schizoaffective disorder, poor impulse control, unusual thought content, and cerebellum volume decrease. The estimations were poorer when we used clinical or MRI data separately. CONCLUSION Combining clinical and MRI data may improve the risk of manic relapse estimation after a manic episode. We provide a website that estimates the risk according to the model to facilitate replication by independent groups before translation to clinical settings.
Collapse
Affiliation(s)
- Pol Palau
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Benito Menni CASM - Hospital General de Granollers, Germanes Hospitalàries, Barcelona, Spain; Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Aleix Solanes
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona, Barcelona, Spain
| | - Merce Madre
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Hospital de la Santa Creu i Sant Pau, IIB SANT PAU, Barcelona, Spain
| | - Naia Saez-Francas
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Hospital Sant Rafael, Germanes Hospitalàries. Barcelona, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Noemí Moro
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Benito Menni CASM - Hospital General de Granollers, Germanes Hospitalàries, Barcelona, Spain
| | - Norma Verdolini
- Institute of Neurosciences, University of Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Barcelona Bipolar Disorders and Depressive Unit, Institute of Neurosciences, Hospital Clinic, Barcelona, Spain
| | - Manel Sanchez
- Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona, Barcelona, Spain; Department of Geriatric Psychiatry, Sagrat Cor Hospital, Martorell, Barcelona, Spain; Sociedad Española de Psicogeriatría (SEPG), Barcelona, Spain
| | - Sílvia Alonso-Lana
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
| | - Benedikt L Amann
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Centre Fòrum Research Unit, Institute of Neuropsychiatry and Addiction, Parc de Salut Mar, Barcelona, Spain; Mental Health Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain; Pompeu Fabra University, Barcelona, Spain; Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstrasse 7, 80336 Munich, Germany
| | - Anna Romaguera
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Hospital Mare de Déu de la Mercè, Germanes Hospitalàries, Barcelona, Spain
| | - Marta Martin-Subero
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Centre Fòrum Research Unit, Institute of Neuropsychiatry and Addiction, Parc de Salut Mar, Barcelona, Spain; Mental Health Research Group, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Lydia Fortea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Paola Fuentes-Claramonte
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Maria A García-León
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Josep Munuera
- Imatge Diagnòstica i Terapèutica, Institut de Recerca Sant Joan de Déu, Santa Rosa 39-57, 08950 Esplugues de Llobregat, Spain; Servei de Diagnòstic per la Imatge, Hospital Sant Joan de Déu, Passeig Sant Joan de Déu 2, 08950 Esplugues de Llobregat, Spain
| | - Erick Jorge Canales-Rodríguez
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), EPFL-STI-IEL-LTS5, Station 11, CH-1015 Lausanne, Switzerland
| | - Paloma Fernández-Corcuera
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Psychiatry Department, Hospital de Mataró, Consorci Sanitari del Maresme, Mataró, Spain
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Eduard Vieta
- Institute of Neurosciences, University of Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Barcelona Bipolar Disorders and Depressive Unit, Institute of Neurosciences, Hospital Clinic, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.
| | - Joaquim Radua
- Institute of Neurosciences, University of Barcelona, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, United Kingdom; Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
| |
Collapse
|
5
|
Su W, Yuan A, Tang Y, Xu L, Wei Y, Wang Y, Li Z, Cui H, Qian Z, Tang X, Hu Y, Zhang T, Feng J, Li Z, Zhang J, Wang J. Effects of polygenic risk of schizophrenia on interhemispheric callosal white matter integrity and frontotemporal functional connectivity in first-episode schizophrenia. Psychol Med 2023; 53:2868-2877. [PMID: 34991756 DOI: 10.1017/s0033291721004840] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
BACKGROUND Schizophrenia is a severely debilitating psychiatric disorder with high heritability and polygenic architecture. A higher polygenic risk score for schizophrenia (SzPRS) has been associated with smaller gray matter volume, lower activation, and decreased functional connectivity (FC). However, the effect of polygenic inheritance on the brain white matter microstructure has only been sparsely reported. METHODS Eighty-four patients with first-episode schizophrenia (FES) patients and ninety-three healthy controls (HC) with genetics, diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (rs-fMRI) data were included in our study. We investigated impaired white matter integrity as measured by fractional anisotropy (FA) in the FES group, further examined the effect of SzPRS on white matter FA and FC in the regions connected by SzPRS-related white matter tracts. RESULTS Decreased FA was observed in FES in many commonly identified regions. Among these regions, we observed that in the FES group, but not the HC group, SzPRS was negatively associated with the mean FA in the genu and body of corpus callosum, right anterior corona radiata, and right superior corona radiata. Higher SzPRS was also associated with lower FCs between the left inferior frontal gyrus (IFG)-left inferior temporal gyrus (ITG), right IFG-left ITG, right IFG-left middle frontal gyrus (MFG), and right IFG-right MFG in the FES group. CONCLUSION Higher polygenic risks are linked with disrupted white matter integrity and FC in patients with schizophrenia. These correlations are strongly driven by the interhemispheric callosal fibers and the connections between frontotemporal regions.
Collapse
Affiliation(s)
- Wenjun Su
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Aihua Yuan
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yingying Tang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Lihua Xu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yanyan Wei
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yingchan Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Zhixing Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Huiru Cui
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Zhenying Qian
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Xiaochen Tang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yegang Hu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Tianhong Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Zhiqiang Li
- Affiliated Hospital of Qingdao University & Biomedical Sciences Institute of Qingdao University, Qingdao University, Qingdao 266000, China
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Centre for Brain Science, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Jijun Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Science, Shanghai 200031, China
- Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai 200240, China
| |
Collapse
|
6
|
Xu X, Li Q, Qian Y, Cai H, Zhang C, Zhao W, Zhu J, Yu Y. Genetic mechanisms underlying gray matter volume changes in patients with drug-naive first-episode schizophrenia. Cereb Cortex 2023; 33:2328-2341. [PMID: 35640648 DOI: 10.1093/cercor/bhac211] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
Brain structural damage is a typical feature of schizophrenia. Investigating such disease phenotype in patients with drug-naive first-episode schizophrenia (DFSZ) may exclude the confounds of antipsychotics and illness chronicity. However, small sample sizes and marked clinical heterogeneity have precluded definitive identification of gray matter volume (GMV) changes in DFSZ as well as their underlying genetic mechanisms. Here, GMV changes in DFSZ were assessed using a neuroimaging meta-analysis of 19 original studies, including 605 patients and 637 controls. Gene expression data were derived from the Allen Human Brain Atlas and processed with a newly proposed standardized pipeline. Then, we used transcriptome-neuroimaging spatial correlations to identify genes associated with GMV changes in DFSZ, followed by a set of gene functional feature analyses. Meta-analysis revealed consistent GMV reduction in the right superior temporal gyrus, right insula and left inferior temporal gyrus in DFSZ. Moreover, we found that these GMV changes were spatially correlated with expression levels of 1,201 genes, which exhibited a wide range of functional features. Our findings may provide important insights into the genetic mechanisms underlying brain morphological abnormality in schizophrenia.
Collapse
Affiliation(s)
- Xiaotao Xu
- Department of Radiology, The Fourth Affiliated Hospital of Anhui Medical University, Hefei 230012, China.,Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Qian Li
- Department of Radiology, Chaohu Hospital of Anhui Medical University, Hefei 238000, China.,Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yinfeng Qian
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Huanhuan Cai
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Cun Zhang
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Wenming Zhao
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Jiajia Zhu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China.,Research Center of Clinical Medical Imaging, Anhui Province, Hefei, 230032, China.,Anhui Provincial Institute of Translational Medicine, Hefei 230032, China.,Department of Radiology, Chaohu Hospital of Anhui Medical University, Hefei 238000, China.,Department of Radiology, The Fourth Affiliated Hospital of Anhui Medical University, Hefei 230012, China
| |
Collapse
|
7
|
Wu H, Dai G, Aizezi M, Tang J, Zou K, Wu Y, Wu X. Gray matter reduction in bilateral insula mediating adverse psychiatric effects of body mass index in schizophrenia. BMC Psychiatry 2022; 22:639. [PMID: 36221050 PMCID: PMC9552355 DOI: 10.1186/s12888-022-04285-4] [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: 07/02/2022] [Accepted: 09/26/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Both schizophrenia (SZ) and overweight/obesity (OWB) have shown some structural alterations in similar brain regions. As higher body mass index (BMI) often contributes to worse psychiatric outcomes in SZ, this study was designed to examine the effects of OWB on gray matter volume (GMV) in patients with SZ. METHODS Two hundred fifty subjects were included and stratified into four groups (n = 69, SZ patients with OWB, SZ-OWB; n = 74, SZ patients with normal weight, SZ-NW; n = 54, healthy controls with OWB, HC-OWB; and n = 53, HC with NW, HC-NW). All participants were scanned using high-resolution T1-weighted sequence. The whole-brain voxel-based morphometry was applied to examine the GMV alterations, and a 2 × 2 full factorial analysis of variance was performed to identify the main effects of diagnosis (SZ vs HC), BMI (NW vs OWB) factors, and their interactions. Further, the post hoc analysis was conducted to compare the pairwise differences in GMV alterations. RESULTS The main effects of diagnosis were located in right hippocampus, bilateral insula, rectus, median cingulate/paracingulate gyri and thalamus (SZ < HC); while the main effects of BMI were displayed in right amygdala, left hippocampus, bilateral insula, left lingual gyrus, and right superior temporal gyrus (OWB < NW). There were no significant diagnosis-by-BMI interaction effects in the present study, but the results showed that both SZ and OWB were additively associated with lower GMV in bilateral insula. Moreover, mediation analyses revealed the indirect effect of BMI on negative symptom via GMV reduction in bilateral insula. CONCLUSION This study further supports that higher BMI is associated with lower GMV, which may increase the risk of unfavourable disease courses in SZ.
Collapse
Affiliation(s)
- Hui Wu
- grid.412558.f0000 0004 1762 1794Psychiatry Department, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Tianhe District, Guangzhou, Guangdong China ,The Affiliated Kashi Hospital of Sun Yat-Sen University, Kashi, China
| | - Guochao Dai
- The Affiliated Kashi Hospital of Sun Yat-Sen University, Kashi, China ,Radiology Department, The First People’s Hospital of Kashi Prefecture, Kashi, China
| | - Muyeseer Aizezi
- The Affiliated Kashi Hospital of Sun Yat-Sen University, Kashi, China ,Psychiatry Department, The First People’s Hospital of Kashi Prefecture, 120 Yingbin Avenue, Kashi, Xinjiang China
| | - Juan Tang
- The Affiliated Kashi Hospital of Sun Yat-Sen University, Kashi, China ,Psychiatry Department, The First People’s Hospital of Kashi Prefecture, 120 Yingbin Avenue, Kashi, Xinjiang China
| | - Ke Zou
- The Affiliated Kashi Hospital of Sun Yat-Sen University, Kashi, China ,Radiology Department, The First People’s Hospital of Kashi Prefecture, Kashi, China
| | - Yuhua Wu
- The Affiliated Kashi Hospital of Sun Yat-Sen University, Kashi, China. .,Psychiatry Department, The First People's Hospital of Kashi Prefecture, 120 Yingbin Avenue, Kashi, Xinjiang, China.
| | - Xiaoli Wu
- Psychiatry Department, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Road, Tianhe District, Guangzhou, Guangdong, China. .,The Affiliated Kashi Hospital of Sun Yat-Sen University, Kashi, China.
| |
Collapse
|
8
|
Gray Matter Abnormalities in Patients with Complex Regional Pain Syndrome: A Systematic Review and Meta-Analysis of Voxel-Based Morphometry Studies. Brain Sci 2022; 12:brainsci12081115. [PMID: 36009176 PMCID: PMC9405829 DOI: 10.3390/brainsci12081115] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 08/10/2022] [Accepted: 08/17/2022] [Indexed: 11/17/2022] Open
Abstract
Current findings on brain structural alterations in complex regional pain syndrome (CRPS) are heterogenous and controversial. This study aimed to perform a systematic review and meta-analysis to explore the significant gray matter volume (GMV) abnormalities between patients with CRPS and healthy controls (HCs). A systematic search of the PubMed, Web of Science, and MEDLINE databases was performed, updated through 27 January 2022. A total of five studies (93 CRPS patients and 106 HCs) were included. Peak coordinates and effect sizes were extracted and meta-analyzed by anisotropic effect size-signed differential mapping (AES-SDM). Heterogeneity, sensitivity, and publication bias of the main results were checked by the Q test, jackknife analysis, and the Egger test, respectively. Meta-regression analysis was performed to explore the potential impact of risk factors on GMV alterations in patients with CRPS. The main analysis exhibited that patients with CRPS had increased GMV in the left medial superior frontal gyrus (SFGmedial.L), left striatum, and an undefined area (2, 0, -8) that may be in hypothalamus, as well as decreased GMV in the corpus callosum (CC) (extending to right supplementary motor area (SMA.R), right median cingulate/paracingulate gyri (MCC.R)), and an undefined area (extending to the right caudate nucleus (CAU.R), and right thalamus (THA.R)). Meta-regression analysis showed a negative relationship between increased GMV in the SFGmedial.L and disease duration, and the percentage of female patients with CRPS. Brain structure abnormalities in the sensorimotor regions (e.g., SFGmedial.L, SMA.R, CAU.R, MCC.R, and THA.R) may be susceptible in patients with CRPS. Additionally, sex differences and disease duration may have a negative effect on the increased GMV in SFGmedial.L.
Collapse
|
9
|
Zeng J, Zhang W, Wu G, Wang X, Shah C, Li S, Xiao Y, Yao L, Cao H, Li Z, Sweeney JA, Lui S, Gong Q. Effects of Antipsychotic Medications and Illness Duration on Brain Features That Distinguish Schizophrenia Patients. Schizophr Bull 2022; 48:1354-1362. [PMID: 35925035 PMCID: PMC9673268 DOI: 10.1093/schbul/sbac094] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND AND HYPOTHESIS Previous studies have reported effects of antipsychotic treatment and illness duration on brain features. This study used a machine learning approach to examine whether these factors in aggregate impacted the utility of MRI features for differentiating individual schizophrenia patients from healthy controls. STUDY DESIGN This case-control study used patients with never-treated first-episode schizophrenia (FES, n = 179) and long-term ill schizophrenia (LTSZ, n = 30), with follow-up of the FES group after treatment (n = 71), a group of patients who had received long-term antipsychotic treatment (n = 93) and age and sex-matched healthy controls (n = 373) for each patient group. A multiple kernel learning classifier combining both structural and functional brain features was used to discriminate individual patients from controls. STUDY RESULTS MRI features differentiated untreated FES (0.73) and LTSZ (0.83) patients from healthy controls with moderate accuracy, but accuracy was significantly higher in antipsychotic-treated FES (0.94) and LTSZ (0.98) patients. Treatment was associated with significantly increased accuracy of case identification in both early course and long-term ill patients (both p < .001). Effects of illness duration, examined separately in treated and untreated patients, were less robust. CONCLUSIONS Our results demonstrate that initiation of antipsychotic treatment alters brain features in ways that further distinguish individual schizophrenia patients from healthy individuals, and have a modest effect of illness duration. Intrinsic illness-related brain alterations in untreated patients, regardless of illness duration, are not sufficiently robust for accurate identification of schizophrenia patients.
Collapse
Affiliation(s)
| | | | - Guorong Wu
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing, China
| | - Xiaowan Wang
- Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing, China
| | - Chandan Shah
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Siyi Li
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Yuan Xiao
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Li Yao
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Hengyi Cao
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China,Center for Psychiatry Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, USA,Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, USA
| | - Zhenlin Li
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - John A Sweeney
- Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Su Lui
- To whom correspondence should be addressed; Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China, tel/fax: +86-28-85423960; e-mail:
| | - Qiyong Gong
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China,Department of Radiology, Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| |
Collapse
|
10
|
Iftimovici A, Chaumette B, Duchesnay E, Krebs MO. Brain anomalies in early psychosis: From secondary to primary psychosis. Neurosci Biobehav Rev 2022; 138:104716. [PMID: 35661683 DOI: 10.1016/j.neubiorev.2022.104716] [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: 09/28/2021] [Revised: 03/12/2022] [Accepted: 05/25/2022] [Indexed: 10/18/2022]
Abstract
Brain anomalies are frequently found in early psychoses. Although they may remain undetected for many years, their interpretation is critical for differential diagnosis. In secondary psychoses, their identification may allow specific management. They may also shed light on various pathophysiological aspects of primary psychoses. Here we reviewed cases of secondary psychoses associated with brain anomalies, reported over a 20-year period in adolescents and young adults aged 13-30 years old. We considered age at first psychotic symptoms, relevant medical history, the nature of psychiatric symptoms, clinical red flags, the nature of the brain anomaly reported, and the underlying disease. We discuss the relevance of each brain area in light of normal brain function, recent case-control studies, and postulated pathophysiology. We show that anomalies in all regions, whether diffuse, multifocal, or highly localized, may lead to psychosis, without necessarily being associated with non-psychiatric symptoms. This underlines the interest of neuroimaging in the initial workup, and supports the hypothesis of psychosis as a global network dysfunction that involves many different regions.
Collapse
Affiliation(s)
- Anton Iftimovici
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Paris, France; NeuroSpin, Atomic Energy Commission, Gif-sur Yvette, France; GHU Paris Psychiatrie et Neurosciences, Paris, France.
| | - Boris Chaumette
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Paris, France; GHU Paris Psychiatrie et Neurosciences, Paris, France
| | | | - Marie-Odile Krebs
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, GDR 3557-Institut de Psychiatrie, Paris, France; GHU Paris Psychiatrie et Neurosciences, Paris, France
| |
Collapse
|
11
|
Zhao X, Yao J, Lv Y, Zhang X, Han C, Chen L, Ren F, Zhou Q, Jin Z, Li Y, Du Y, Sui Y. Facial emotion perception abilities are related to grey matter volume in the culmen of cerebellum anterior lobe in drug-naïve patients with first-episode schizophrenia. Brain Imaging Behav 2022; 16:2072-2085. [PMID: 35751735 DOI: 10.1007/s11682-022-00677-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/13/2022] [Indexed: 11/02/2022]
Abstract
Impaired capability for understanding and interpreting the expressions on other people's faces manifests itself as a core feature of schizophrenia, contributing to social dysfunction. With the purpose of better understanding of the neurobiological basis of facial emotion perception deficits in schizophrenia, we investigated facial emotion perception abilities and regional structural brain abnormalities in drug-naïve patients with first-episode schizophrenia, and then examined the correlation between them. Fifty-two drug-naive patients with first-episode schizophrenia and 29 group-matched healthy controls were examined for facial emotion perception abilities assessed with the Facial Emotion Categorization and performed magnetic resonance imaging. The Facial Emotion Categorization data were inserted into a logistic function model so as to calculate shift point and slope as outcome measurements. Voxel-based morphometry was applied to investigate regional grey matter volume (GMV) alterations. The relationship between facial emotion perception and GMV was explored in patients using voxel-wise correlation analysis within brain regions that showed a significant GMV alterations in patients compared with controls. The schizophrenic patients performed differently on Facial Emotion Categorization tasks from the controls and presented a higher shift point and a steeper slope. Relative to the controls, patients showed GMV reductions in the superior temporal gyrus, middle occipital gyrus, parahippocampa gyrus, posterior cingulate, the culmen of cerebellum anterior lobe, cerebellar tonsil, and the declive of cerebellum posterior lobe. Importantly, abnormal performance on Facial Emotion Categorization was found correlated with GMV alterations in the culmen of cerebellum anterior lobe in schizophrenia. This study suggests that reduced GMV in the culmen of cerebellum anterior lobe occurs in first-episode schizophrenia, constituting a potential neuropathological basis for the impaired facial emotion perception in schizophrenia.
Collapse
Affiliation(s)
- Xiaoxin Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
| | | | - Yiding Lv
- Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China
| | | | - Chongyang Han
- Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China
| | - Lijun Chen
- Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China
| | - Fangfang Ren
- Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China
| | - Qun Zhou
- Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China
| | - Zhuma Jin
- Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China
| | - Yuan Li
- Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China
| | - Yasong Du
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
| | - Yuxiu Sui
- Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, China.
| |
Collapse
|
12
|
Schaub N, Ammann N, Conring F, Müller T, Federspiel A, Wiest R, Hoepner R, Stegmayer K, Walther S. Effect of Season of Birth on Hippocampus Volume in a Transdiagnostic Sample of Patients With Depression and Schizophrenia. Front Hum Neurosci 2022; 16:877461. [PMID: 35769255 PMCID: PMC9234120 DOI: 10.3389/fnhum.2022.877461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/17/2022] [Indexed: 11/13/2022] Open
Abstract
Psychiatric disorders share an excess of seasonal birth in winter and spring, suggesting an increase of neurodevelopmental risks. Evidence suggests season of birth can serve as a proxy of harmful environmental factors. Given that prenatal exposure of these factors may trigger pathologic processes in the neurodevelopment, they may consequently lead to brain volume alterations. Here we tested the effects of season of birth on gray matter volume in a transdiagnostic sample of patients with schizophrenia and depression compared to healthy controls (n = 192). We found a significant effect of season of birth on gray matter volume with reduced right hippocampal volume in summer-born compared to winter-born patients with depression. In addition, the volume of the right hippocampus was reduced independent from season of birth in schizophrenia. Our results support the potential impact of season of birth on hippocampal volume in depression.
Collapse
Affiliation(s)
- Nora Schaub
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Nina Ammann
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Frauke Conring
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Thomas Müller
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Andrea Federspiel
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| | - Roland Wiest
- Support Center of Advanced Neuroimaging (SCAN), Inselspital, University Institute of Diagnostic and Interventional Neuroradiology, Bern, Switzerland
| | - Robert Hoepner
- Department of Neurology, Inselspital, University Hospital and University of Bern, Bern, Switzerland
| | - Katharina Stegmayer
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
- *Correspondence: Katharina Stegmayer,
| | - Sebastian Walther
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, Bern, Switzerland
| |
Collapse
|
13
|
Zhang M, Hong X, Yang F, Fan H, Fan F, Song J, Wang Z, Tan Y, Tan S, Elliot Hong L. Structural brain imaging abnormalities correlate with positive symptom in schizophrenia. Neurosci Lett 2022; 782:136683. [PMID: 35595192 DOI: 10.1016/j.neulet.2022.136683] [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: 11/13/2020] [Revised: 03/04/2022] [Accepted: 05/13/2022] [Indexed: 10/18/2022]
Abstract
Accumulating evidence indicates neuroanatomical mechanisms underlying positive symptoms in schizophrenia; however, the exact structural determinants of positive symptoms remain unclear. This study aimed to investigate associations between positive symptoms and structural brain changes, including alterations in grey matter (GM) volume and cortical thickness, in patients with first-episode schizophrenia (FES). This study included 44 patients with FES and 48 healthy controls (HCs). Clinical symptoms of patients were evaluated and individual-level GM volume and cortical thickness were assessed. Patients with FES showed reduced GM volume in the right superior temporal gyrus (STG) and increased cortical thickness in the left inferior segment of the circular sulcus of the insula (S_circular_insula_inf) compared with HCs. Increased thickness of the left S_circular_insula_inf correlated positively with positive symptoms in patients with FES. Exploratory correlation analysis found that increased thickness of the left S_circular_insula_inf correlated positively with conceptual disorganization and excitement symptoms, and the right STG GM volume correlated negatively with hallucinations. This study suggests that GM abnormalities in the STG and altered cortical thickness of the S_circular_insula_inf, which were detected at the early stage of schizophrenia, may underlie positive symptoms in patients with FES.
Collapse
Affiliation(s)
- Meng Zhang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Xiang Hong
- Chongqing Three Gorges Central Hospital, Chongqing 404000, China
| | - Fude Yang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Hongzhen Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Fengmei Fan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Jiaqi Song
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Zhiren Wang
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Yunlong Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China
| | - Shuping Tan
- Peking University HuiLongGuan Clinical Medical School, Beijing HuiLongGuan Hospital, Beijing 100096, China.
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD 21288, USA
| |
Collapse
|
14
|
Qi Z, Wang J, Gong J, Su T, Fu S, Huang L, Wang Y. Common and specific patterns of functional and structural brain alterations in schizophrenia and bipolar disorder: a multimodal voxel-based meta-analysis. J Psychiatry Neurosci 2022; 47:E32-E47. [PMID: 35105667 PMCID: PMC8812718 DOI: 10.1503/jpn.210111] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 10/12/2021] [Accepted: 11/16/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Schizophrenia and bipolar disorder have been linked to alterations in the functional activity and grey matter volume of some brain areas, reflected in impaired regional homogeneity and aberrant voxel-based morphometry. However, because of variable findings and methods used across studies, identifying patterns of brain alteration in schizophrenia and bipolar disorder has been difficult. METHODS We conducted a meta-analysis of differences in regional homogeneity and voxel-based morphometry between patients and healthy controls for schizophrenia and bipolar disorder separately, using seed-based d mapping. RESULTS We included 45 publications on regional homogeneity (26 in schizophrenia and 19 in bipolar disorder) and 190 publications on voxel-based morphometry (120 in schizophrenia and 70 in bipolar disorder). Patients with schizophrenia showed increased regional homogeneity in the frontal cortex and striatum and the supplementary motor area; they showed decreased regional homogeneity in the insula, primary sensory cortex (visual and auditory cortices) and sensorimotor cortex. Patients with bipolar disorder showed increased regional homogeneity in the frontal cortex and striatum; they showed decreased regional homogeneity in the insula. Patients with schizophrenia showed decreased grey matter volume in the superior temporal gyrus, inferior frontal gyrus, cingulate cortex and cerebellum. Patients with bipolar disorder showed decreased grey matter volume in the insula, cingulate cortex, frontal cortex and thalamus. Overlap analysis showed that patients with schizophrenia displayed decreased regional homogeneity and grey matter volume in the left insula and left superior temporal gyrus; patients with bipolar disorder displayed decreased regional homogeneity and grey matter volume in the left insula. LIMITATIONS The small sample size for our subgroup analysis (unmedicated versus medicated patients and substantial heterogeneity in the results for some regions could limit the interpretability and generalizability of the results. CONCLUSION Patients with schizophrenia and bipolar disorder shared a common pattern of regional functional and structural alterations in the insula and frontal cortex. Patients with schizophrenia showed more widespread functional and structural impairment, most prominently in the primary sensory motor areas.
Collapse
Affiliation(s)
| | - Junjing Wang
- From the Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou 510630, China (Qi, Su, Fu, Huang, Y. Wang); the Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, China (Qi, Su, Fu, Huang, Y. Wang); the Department of Applied Psychology, Guangdong University of Foreign Studies, Guangzhou, China (J. Wang); and the Department of Radiology, Six Affiliated Hospital of Sun Yat-sen University, Guangzhou, China (Gong)
| | | | | | | | | | | |
Collapse
|
15
|
Zhu T, Wang Z, Zhou C, Fang X, Huang C, Xie C, Ge H, Yan Z, Zhang X, Chen J. Meta-analysis of structural and functional brain abnormalities in schizophrenia with persistent negative symptoms using activation likelihood estimation. Front Psychiatry 2022; 13:957685. [PMID: 36238945 PMCID: PMC9552970 DOI: 10.3389/fpsyt.2022.957685] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 09/05/2022] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Persistent negative symptoms (PNS) include both primary and secondary negative symptoms that persist after adequate treatment, and represent an unmet therapeutic need. Published magnetic resonance imaging (MRI) evidence of structural and resting-state functional brain abnormalities in schizophrenia with PNS has been inconsistent. Thus, the purpose of this meta-analysis is to identify abnormalities in structural and functional brain regions in patients with PNS compared to healthy controls. METHODS We systematically searched PubMed, Web of Science, and Embase for structural and functional imaging studies based on five research methods, including voxel-based morphometry (VBM), diffusion tensor imaging (DTI), functional connectivity (FC), the amplitude of low-frequency fluctuation or fractional amplitude of low-frequency fluctuation (ALFF/fALFF), and regional homogeneity (ReHo). Afterward, we conducted a coordinate-based meta-analysis by using the activation likelihood estimation algorithm. RESULTS Twenty-five structural MRI studies and thirty-two functional MRI studies were included in the meta-analyses. Our analysis revealed the presence of structural alterations in patients with PNS in some brain regions including the bilateral insula, medial frontal gyrus, anterior cingulate gyrus, left amygdala, superior temporal gyrus, inferior frontal gyrus, cingulate gyrus and middle temporal gyrus, as well as functional differences in some brain regions including the bilateral precuneus, thalamus, left lentiform nucleus, posterior cingulate gyrus, medial frontal gyrus, and superior frontal gyrus. CONCLUSION Our study suggests that structural brain abnormalities are consistently located in the prefrontal, temporal, limbic and subcortical regions, and functional alterations are concentrated in the thalamo-cortical circuits and the default mode network (DMN). This study provides new insights for targeted treatment and intervention to delay further progression of negative symptoms. SYSTEMATIC REVIEW REGISTRATION [https://www.crd.york.ac.uk/prospero/], identifier [CRD42022338669].
Collapse
Affiliation(s)
- Tingting Zhu
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zixu Wang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chao Zhou
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xinyu Fang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chengbing Huang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Department of Psychiatry, The Third People's Hospital of Huai'an, Huaian, China
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine Southeast University, Nanjing, China
| | - Honglin Ge
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zheng Yan
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,The Affiliated Xuzhou Oriental Hospital of Xuzhou Medical University, Xuzhou, China
| | - Jiu Chen
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| |
Collapse
|
16
|
Wen K, Zhao Y, Gong Q, Zhu Z, Li Q, Pan N, Fu S, Radua J, Vieta E, Kumar P, Kemp GJ, Biswal BB. Cortical thickness abnormalities in patients with first episode psychosis: a meta-analysis of psychoradiologic studies and replication in an independent sample. PSYCHORADIOLOGY 2021; 1:185-198. [PMID: 35156043 PMCID: PMC8826222 DOI: 10.1093/psyrad/kkab015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 11/14/2021] [Accepted: 11/17/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND Abnormalities of cortical thickness (CTh) in patients with their first episode psychosis (FEP) have been frequently reported, but findings are inconsistent. OBJECTIVE To define the most consistent CTh changes in patients with FEP by meta-analysis of published whole-brain studies. METHODS The meta-analysis used seed-based d mapping (SDM) software to obtain the most prominent regional CTh changes in FEP, and meta-regression analyses to explore the effects of demographics and clinical characteristics. The meta-analysis results were verified in an independent sample of 142 FEP patients and 142 age- and sex-matched healthy controls (HCs), using both a vertex-wise and a region of interest analysis, with multiple comparisons correction. RESULTS The meta-analysis identified lower CTh in the right middle temporal cortex (MTC) extending to superior temporal cortex (STC), insula, and anterior cingulate cortex (ACC) in FEP compared with HCs. No significant correlations were identified between CTh alterations and demographic or clinical variables. These results were replicated in the independent dataset analysis. CONCLUSION This study identifies a robust pattern of cortical abnormalities in FEP and extends understanding of gray matter abnormalities and pathological mechanisms in FEP.
Collapse
Affiliation(s)
- Keren Wen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Youjin Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Sichuan, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, Chengdu 610041, Sichuan, China
| | - Ziyu Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Qian Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Shiqin Fu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, Sichuan, China
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Mental Health Research Networking Center (CIBERSAM), Barcelona 08036, Catalonia, Spain
- Centre for Psychiatric Research and Education, Department of Clinical Neuroscience, Karolinska Institutet, Solna 171-77, Stockholm, Sweden
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London WC2R 2LS, UK
| | - Eduard Vieta
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Mental Health Research Networking Center (CIBERSAM), Barcelona 08036, Catalonia, Spain
- Barcelona Bipolar Disorders and Depressive Unit, Hospital Clinic, Institute of Neurosciences, University of Barcelona, Barcelona 08036, Catalonia, Spain
| | - Poornima Kumar
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont 02478, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston 02115, MA, USA
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 3GE, UK
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark 07102, NJ, USA
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, Sichuan, China
| |
Collapse
|
17
|
Subtypes of schizophrenia identified by multi-omic measures associated with dysregulated immune function. Mol Psychiatry 2021; 26:6926-6936. [PMID: 34588622 DOI: 10.1038/s41380-021-01308-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 08/08/2021] [Accepted: 09/14/2021] [Indexed: 02/05/2023]
Abstract
Epigenetic modifications are plausible molecular sources of phenotypic heterogeneity across schizophrenia patients. The current study investigated biological heterogeneity in schizophrenia using peripheral epigenetic profiles to delineate illness subtypes independent of their phenomenological manifestations. We applied epigenome-wide profiling with a DNA methylation array from blood samples of 63 schizophrenia patients and 59 healthy controls. Non-negative matrix factorization (NMF) and k-means clustering were performed to identify DNA methylation-related patient subtypes. The validity of the partition was tested by assessing the profile of the T cell receptor (TCR) repertoires. The uniqueness of the identified subtypes in relation to brain structural and clinical measures were evaluated. Two distinct patterns of DNA methylation profiles were identified in patients. One subtype (60.3% of patients) showed relatively limited changes in methylation levels and cell composition compared to controls, while a second subtype (39.7% of patients) exhibited widespread methylation level alterations among genes enriched in immune cell activity, as well as a higher proportion of neutrophils and lower proportion of lymphocytes. Differentiation of the two patient subtypes was validated by TCR repertoires, which paralleled the partition based on DNA methylation profiles. The subtype with widespread methylation modifications had higher symptom severity, performed worse on cognitive measures, and displayed greater reductions in fractional anisotropy of white matter tracts and evidence of gray matter thickening compared to the other subtype. Identification of a distinct subtype of schizophrenia with unique molecular, cerebral, and clinical features provide a novel parcellation of the schizophrenia syndrome with potential to guide development of individualized therapeutics.
Collapse
|
18
|
De Peri L, Deste G, Vita A. Strucutural brain imaging at the onset of schizophrenia:What have we learned and what have we missed. Psychiatry Res 2021; 301:113962. [PMID: 33945963 DOI: 10.1016/j.psychres.2021.113962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 04/19/2021] [Indexed: 11/28/2022]
Abstract
Over the past 50 years, the application of structural neuroimaging techniques to schizophrenia research has added relevant information about the pathophysiology of the disorder. Several lines of investigation gave strong evidence that schizophrenia is associated with multiple subtle brain abnormalities that involve both cerebral grey and white matter volumes and structure. The time of onset and longitudinal course of brain morphological abnormalities support the notion that brain pathology of schizophrenia has a neurodevelopmental component and a progressive course, although several confounders of brain changes should be carefully taken into account. Brain anomalies detected before and close to the onset of schizophrenia are likely to be unrelated to confounders of brain changes such as antipsychotic drug treatment, duration of illness or illicit substance abuse, i.e. they related to the pathological process of the disorder per se. Nonetheless, clinically useful diagnostic or prognostic biomarkers have not derived from neuroimaging studies and this is likely related to the neurobiological heterogeneity of the disorder. Thus, there is the compelling need to set new methodological standards for developing innovative hypothesis-driven studies to overcome what we have missed to date in neuroimaging research in schizophrenia.
Collapse
Affiliation(s)
- Luca De Peri
- Cantonal Psychiatric Clinic, Cantonal Socio-Psychiatric Association, Mendrisio, Switzerland
| | - Giacomo Deste
- Department of Mental Health, Spedali Civili Hospital, Brescia, Italy
| | - Antonio Vita
- Department of Mental Health, Spedali Civili Hospital, Brescia, Italy; Department of Clinical and Experimentale Sciences, University of Brescia, Italy.
| |
Collapse
|
19
|
Pigoni A, Dwyer D, Squarcina L, Borgwardt S, Crespo-Facorro B, Dazzan P, Smesny S, Spaniel F, Spalletta G, Sanfelici R, Antonucci LA, Reuf A, Oeztuerk OF, Schmidt A, Ciufolini S, Schönborn-Harrisberger F, Langbein K, Gussew A, Reichenbach JR, Zaytseva Y, Piras F, Delvecchio G, Bellani M, Ruggeri M, Lasalvia A, Tordesillas-Gutiérrez D, Ortiz V, Murray RM, Reis-Marques T, Di Forti M, Koutsouleris N, Brambilla P. Classification of first-episode psychosis using cortical thickness: A large multicenter MRI study. Eur Neuropsychopharmacol 2021; 47:34-47. [PMID: 33957410 DOI: 10.1016/j.euroneuro.2021.04.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 03/21/2021] [Accepted: 04/06/2021] [Indexed: 12/19/2022]
Abstract
Machine learning classifications of first-episode psychosis (FEP) using neuroimaging have predominantly analyzed brain volumes. Some studies examined cortical thickness, but most of them have used parcellation approaches with data from single sites, which limits claims of generalizability. To address these limitations, we conducted a large-scale, multi-site analysis of cortical thickness comparing parcellations and vertex-wise approaches. By leveraging the multi-site nature of the study, we further investigated how different demographical and site-dependent variables affected predictions. Finally, we assessed relationships between predictions and clinical variables. 428 subjects (147 females, mean age 27.14) with FEP and 448 (230 females, mean age 27.06) healthy controls were enrolled in 8 centers by the ClassiFEP group. All subjects underwent a structural MRI and were clinically assessed. Cortical thickness parcellation (68 areas) and full cortical maps (20,484 vertices) were extracted. Linear Support Vector Machine was used for classification within a repeated nested cross-validation framework. Vertex-wise thickness maps outperformed parcellation-based methods with a balanced accuracy of 66.2% and an Area Under the Curve of 72%. By stratifying our sample for MRI scanner, we increased generalizability across sites. Temporal brain areas resulted as the most influential in the classification. The predictive decision scores significantly correlated with age at onset, duration of treatment, and positive symptoms. In conclusion, although far from the threshold of clinical relevance, temporal cortical thickness proved to classify between FEP subjects and healthy individuals. The assessment of site-dependent variables permitted an increase in the across-site generalizability, thus attempting to address an important machine learning limitation.
Collapse
Affiliation(s)
- A Pigoni
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, via F. Sforza 35, 20122 Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - D Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - L Squarcina
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, via F. Sforza 35, 20122 Milan, Italy
| | - S Borgwardt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland; Department of Psychiatry and Psychotherapy, University of Lübeck, Germany
| | - B Crespo-Facorro
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain; University Hospital Virgen del Rocio, Department of Psychiatry, School of Medicine, University of Sevilla-IBiS, CIBERSAM, Sevilla, Spain
| | - P Dazzan
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - S Smesny
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - F Spaniel
- Department of Applied Neurosciences and Brain Imaging, National Institute of Mental Health, Klecany Czechia
| | - G Spalletta
- Department of Clinical and Behavioural Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - R Sanfelici
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany; Max Planck School of Cognition, Stephanstrasse 1a, Leipzig, Germany
| | - L A Antonucci
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany; Department of Education, Psychology, Communication, University of Bari Aldo Moro, Bari, Italy
| | - A Reuf
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - Oe F Oeztuerk
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany
| | - A Schmidt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - S Ciufolini
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | | | - K Langbein
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - A Gussew
- Department of Radiology, University Hospital Halle (Saale), Germany
| | - J R Reichenbach
- Medical Physics Group, Department of Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany
| | - Y Zaytseva
- Department of Applied Neurosciences and Brain Imaging, National Institute of Mental Health, Klecany Czechia
| | - F Piras
- Department of Clinical and Behavioural Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - G Delvecchio
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - M Bellani
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Italy; UOC of Psychiatry, Azienda Ospedaliera Universitaria Integrata (AOUI) of Verona, Italy
| | - M Ruggeri
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Italy; UOC of Psychiatry, Azienda Ospedaliera Universitaria Integrata (AOUI) of Verona, Italy
| | - A Lasalvia
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Italy; UOC of Psychiatry, Azienda Ospedaliera Universitaria Integrata (AOUI) of Verona, Italy
| | - D Tordesillas-Gutiérrez
- Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Spain
| | - V Ortiz
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain
| | - R M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - T Reis-Marques
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - M Di Forti
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - N Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - P Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, via F. Sforza 35, 20122 Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
| |
Collapse
|
20
|
Wolf RC, Hildebrandt V, Schmitgen MM, Pycha R, Kirchler E, Macina C, Karner M, Hirjak D, Kubera KM, Romanov D, Freudenmann RW, Huber M. Aberrant Gray Matter Volume and Cortical Surface in Paranoid-Type Delusional Disorder. Neuropsychobiology 2021; 79:335-344. [PMID: 32160619 DOI: 10.1159/000505601] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 12/24/2019] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Delusions are core symptoms of schizophrenia-spectrum and related disorders. Despite their clinical relevance, the neural correlates underlying such phenomena are unclear. Recent research suggests that specific delusional content may be associated with distinct neural substrates. OBJECTIVE Here, we used structural magnetic resonance imaging to investigate multiple parameters of brain morphology in patients presenting with paranoid type delusional disorder (pt-DD, n = 14) compared to those of healthy controls (HC, n = 25). METHODS Voxel- and surface-based morphometry for structural data was used to investigate gray matter volume (GMV), cortical thickness (CT) and gyrification. RESULTS Compared to HC, patients with pt-DD showed reduced GMV in bilateral amygdala and right inferior frontal gyrus. Higher GMV in patients was found in bilateral orbitofrontal and in left superior frontal cortices. Patients also had lower CT in frontal and temporal regions. Abnormal gyrification in patients was evident in frontal and temporal areas, as well as in bilateral insula. CONCLUSIONS The data suggest the presence of aberrant GMV in a right prefrontal region associated with belief evaluation, as well as distinct structural abnormalities in areas that essentially subserve processing of fear, anxiety and threat in patients with pt-DD. It is possible that cortical features of distinct evolutionary and genetic origin, i.e. CT and gyrification, contribute differently to the pathogenesis of pt-DD.
Collapse
Affiliation(s)
- Robert Christian Wolf
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany,
| | - Viviane Hildebrandt
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Mike M Schmitgen
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Roger Pycha
- Department of Psychiatry, General Hospital Bruneck, Bruneck, Italy
| | - Erwin Kirchler
- Department of Psychiatry, General Hospital Bruneck, Bruneck, Italy
| | - Christian Macina
- Department of Psychiatry, General Hospital Bruneck, Bruneck, Italy
| | - Martin Karner
- Department of Radiology, General Hospital Bruneck, Bruneck, Italy
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Katharina M Kubera
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany
| | - Dmitry Romanov
- Department of Psychiatry and Psychosomatics, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russian Federation
| | | | - Markus Huber
- Department of Psychiatry, General Hospital Bruneck, Bruneck, Italy
| |
Collapse
|
21
|
Li H, Zhang H, Yin L, Zhang F, Chen Z, Chen T, Jia Z, Gong Q. Altered cortical morphology in major depression disorder patients with suicidality. PSYCHORADIOLOGY 2021; 1:13-22. [PMID: 38665310 PMCID: PMC10917214 DOI: 10.1093/psyrad/kkaa002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 02/05/2023]
Abstract
Background Major depressive disorder (MDD) is associated with high risk of suicide, but the biological underpinnings of suicidality in MDD patients are far from conclusive. Previous neuroimaging studies using voxel-based morphometry (VBM) demonstrated that depressed individuals with suicidal thoughts or behaviors exhibit specific cortical structure alterations. To complement VBM findings, surface-based morphometry (SBM) can provide more details into gray matter structure, including the cortical complexity, cortical thickness and sulcal depth for brain images. Objective This study aims to use SBM to investigate cortical morphology alterations to obtain evidence for neuroanatomical alterations in depressed patients with suicidality. Methods Here, 3D T1-weighted MR images of brain from 39 healthy controls, 40 depressed patients without suicidality (patient controls), and 39 with suicidality (suicidal groups) were analyzed based on SBM to estimate the fractal dimension, gyrification index, sulcal depth, and cortical thickness using the Computational Anatomy Toolbox. Correlation analyses were performed between clinical data and cortical surface measurements from patients. Results Surface-based morphometry showed decreased sulcal depth in the parietal, frontal, limbic, occipital and temporal regions and decreased fractal dimension in the frontal regions in depressed patients with suicidality compared to both healthy and patient controls. Additionally, in patients with depression, the sulcal depth of the left caudal anterior cingulate cortex was negatively correlated with Hamilton Depression Rating Scale scores. Conclusions Depressed patients with suicidality had abnormal cortical morphology in some brain regions within the default mode network, frontolimbic circuitry and temporal regions. These structural deficits may be associated with the dysfunction of emotional processing and impulsivity control. This study provides insights into the underlying neurobiology of the suicidal brain.
Collapse
Affiliation(s)
- Huiru Li
- Huaxi MR Research Center (HMRRC), Functional and molecular imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 610041
| | - Huawei Zhang
- Huaxi MR Research Center (HMRRC), Functional and molecular imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 610041
| | - Li Yin
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China, 610041
| | - Feifei Zhang
- Huaxi MR Research Center (HMRRC), Functional and molecular imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 610041
| | - Ziqi Chen
- Huaxi MR Research Center (HMRRC), Functional and molecular imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 610041
| | - Taolin Chen
- Huaxi MR Research Center (HMRRC), Functional and molecular imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 610041
| | - Zhiyun Jia
- Huaxi MR Research Center (HMRRC), Functional and molecular imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 610041
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China, 610041
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Functional and molecular imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 610041
- Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Chengdu, China, 610041
| |
Collapse
|
22
|
Korda AI, Andreou C, Borgwardt S. Pattern classification as decision support tool in antipsychotic treatment algorithms. Exp Neurol 2021; 339:113635. [PMID: 33548218 DOI: 10.1016/j.expneurol.2021.113635] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 01/20/2021] [Accepted: 02/01/2021] [Indexed: 10/22/2022]
Abstract
Pattern classification aims to establish a new approach in personalized treatment. The scope is to tailor treatment on individual characteristics during all phases of care including prevention, diagnosis, treatment, and clinical outcome. In psychotic disorders, this need results from the fact that a third of patients with psychotic symptoms do not respond to antipsychotic treatment and are described as having treatment-resistant disorders. This, in addition to the high variability of treatment responses among patients, enhances the need of applying advanced classification algorithms to identify antipsychotic treatment patterns. This review comprehensively summarizes advancements and challenges of pattern classification in antipsychotic treatment response to date and aims to introduce clinicians and researchers to the challenges of including pattern classification into antipsychotic treatment decision algorithms.
Collapse
Affiliation(s)
- Alexandra I Korda
- Department of Psychiatry and Psychotherapy, University Hospital Lübeck (UKSH), Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Christina Andreou
- Department of Psychiatry and Psychotherapy, University Hospital Lübeck (UKSH), Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Stefan Borgwardt
- Department of Psychiatry and Psychotherapy, University Hospital Lübeck (UKSH), Ratzeburger Allee 160, 23538 Lübeck, Germany.
| |
Collapse
|
23
|
Adolescent Neurodevelopment and Vulnerability to Psychosis. Biol Psychiatry 2021; 89:184-193. [PMID: 32896384 PMCID: PMC9397132 DOI: 10.1016/j.biopsych.2020.06.028] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 06/23/2020] [Accepted: 06/25/2020] [Indexed: 12/28/2022]
Abstract
Adolescence is characterized by significant changes in several domains, including brain structure and function, puberty, and social and environmental factors. Some of these changes serve to increase the likelihood of psychosis onset during this period, while others may buffer this risk. This review characterizes our current knowledge regarding the unique aspects of adolescence that may serve as risk factors for schizophrenia spectrum disorders. In addition, we provide potential future directions for research into adolescent-specific developmental mechanisms that impart vulnerability to psychosis and the possibility of interventions that capitalize on adolescents' unique characteristics. Specifically, we explore the ways in which gray and white matter develop throughout adolescence in typically developing youth as well as in those with psychosis spectrum disorders. We also discuss current views on the function that social support and demands, as well as role expectations, play in risk for psychosis. We further highlight the importance of considering biological factors such as puberty and hormonal changes as areas of unique vulnerability for adolescents. Finally, we discuss cannabis use as a factor that may have a unique impact during adolescent neurodevelopment, and subsequently potentially impact psychosis onset. Throughout, we include discussion of resilience factors that may provide unique opportunities for intervention during this dynamic life stage.
Collapse
|
24
|
Vieira S, Gong Q, Scarpazza C, Lui S, Huang X, Crespo-Facorro B, Tordesillas-Gutierrez D, de la Foz VOG, Setien-Suero E, Scheepers F, van Haren NE, Kahn R, Reis Marques T, Ciufolini S, Di Forti M, Murray RM, David A, Dazzan P, McGuire P, Mechelli A. Neuroanatomical abnormalities in first-episode psychosis across independent samples: a multi-centre mega-analysis. Psychol Med 2021; 51:340-350. [PMID: 31858920 PMCID: PMC7893510 DOI: 10.1017/s0033291719003568] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 10/10/2019] [Accepted: 11/21/2019] [Indexed: 02/05/2023]
Abstract
BACKGROUND Neuroanatomical abnormalities in first-episode psychosis (FEP) tend to be subtle and widespread. The vast majority of previous studies have used small samples, and therefore may have been underpowered. In addition, most studies have examined participants at a single research site, and therefore the results may be specific to the local sample investigated. Consequently, the findings reported in the existing literature are highly heterogeneous. This study aimed to overcome these issues by testing for neuroanatomical abnormalities in individuals with FEP that are expressed consistently across several independent samples. METHODS Structural Magnetic Resonance Imaging data were acquired from a total of 572 FEP and 502 age and gender comparable healthy controls at five sites. Voxel-based morphometry was used to investigate differences in grey matter volume (GMV) between the two groups. Statistical inferences were made at p < 0.05 after family-wise error correction for multiple comparisons. RESULTS FEP showed a widespread pattern of decreased GMV in fronto-temporal, insular and occipital regions bilaterally; these decreases were not dependent on anti-psychotic medication. The region with the most pronounced decrease - gyrus rectus - was negatively correlated with the severity of positive and negative symptoms. CONCLUSIONS This study identified a consistent pattern of fronto-temporal, insular and occipital abnormalities in five independent FEP samples; furthermore, the extent of these alterations is dependent on the severity of symptoms and duration of illness. This provides evidence for reliable neuroanatomical alternations in FEP, expressed above and beyond site-related differences in anti-psychotic medication, scanning parameters and recruitment criteria.
Collapse
Affiliation(s)
- Sandra Vieira
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Psychoradiology Research Unit of Chinese Academy of Medical Sciences, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Cristina Scarpazza
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of General Psychology, University of Padova, Padova, Italy
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Psychoradiology Research Unit of Chinese Academy of Medical Sciences, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Psychoradiology Research Unit of Chinese Academy of Medical Sciences, West China Hospital of Sichuan University, Chengdu, Sichuan, China
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Benedicto Crespo-Facorro
- CIBERSAM, Centro Investigación Biomédica en Red de Salud Mental, Madrid, Spain
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain
| | - Diana Tordesillas-Gutierrez
- CIBERSAM, Centro Investigación Biomédica en Red de Salud Mental, Madrid, Spain
- Neuroimaging Unit, Technological Facilities, Valdecilla Biomedical Research Institute IDIVAL, Santander, Cantabria, Spain
| | - Víctor Ortiz-García de la Foz
- CIBERSAM, Centro Investigación Biomédica en Red de Salud Mental, Madrid, Spain
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain
| | - Esther Setien-Suero
- CIBERSAM, Centro Investigación Biomédica en Red de Salud Mental, Madrid, Spain
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain
| | - Floor Scheepers
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands
| | | | - René Kahn
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Tiago Reis Marques
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Simone Ciufolini
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Marta Di Forti
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Anthony David
- UCL Institute of Mental Health, University College London, UK
| | - Paola Dazzan
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| |
Collapse
|
25
|
Hu N, Luo C, Zhang W, Yang X, Xiao Y, Sweeney JA, Lui S, Gong Q. Hippocampal subfield alterations in schizophrenia: A selective review of structural MRI studies. Biomark Neuropsychiatry 2020. [DOI: 10.1016/j.bionps.2020.100026] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
|
26
|
Zhang X, Liu W, Guo F, Li C, Wang X, Wang H, Yin H, Zhu Y. Disrupted structural covariance network in first episode schizophrenia patients: Evidence from a large sample MRI-based morphometric study. Schizophr Res 2020; 224:24-32. [PMID: 33203611 DOI: 10.1016/j.schres.2020.11.004] [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] [Received: 03/23/2020] [Revised: 09/30/2020] [Accepted: 11/02/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Recent progress in neuroscience research has provided evidence that schizophrenia is a disease that involves dysconnectivity of brain networks. Widespread gray matter loss was commonly observed but how these gray matter abnormalities are characterized at the large-scale network-level in schizophrenia, especially patients with first-episode (FE-SCZ) remains unclear. METHODS In this study, gray matter structural network aberrations were investigated by applying structural covariance network analysis to 193 first episode schizophrenia patients and 178 age and gender-matched healthy controls (HCs). The mean gray matter volume in seed regions relating to eight specific networks (visual, auditory, sensorimotor, speech, semantic, default-mode, executive control, and salience) were extracted, and voxel-wise analyses of covariance were conducted to compare the association between whole-brain gray matter volume and each seed region for FE-SCZ and HCs. RESULTS The auditory network was less extended in FE-SCZ compared with HCs, with a significant decrease in the structural association between the Hesch's gyrus and the middle frontal gyrus and the superior frontal gyrus. Hyperconnectivity was observed in executive control network with a significant increase in the structural association between the dorsal lateral prefrontal cortex and the superior frontal gyrus and supplementary motor area. CONCLUSION Our research shows that seed based structural covariance analysis can well characterize multiple large-scale networks, the observed changes might underly the hallucinations and cognitive impairments observed in FE-SCZ. Given that these patients were experiencing their first episode of schizophrenia, our findings suggest that such structural network deficits are present at an early stage in this disorder.
Collapse
Affiliation(s)
- Xiao Zhang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Wenming Liu
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Chen Li
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Xingrui Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
| | - Yuanqiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
| |
Collapse
|
27
|
Wang YM, Zhang YJ, Cai XL, Yang HX, Shan HD, Cheung EFC, Chan RCK. Altered grey matter volume and white matter integrity in individuals with high schizo-obsessive traits, high schizotypal traits and obsessive-compulsive symptoms. Asian J Psychiatr 2020; 52:102096. [PMID: 32315977 DOI: 10.1016/j.ajp.2020.102096] [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] [Received: 11/05/2019] [Revised: 04/02/2020] [Accepted: 04/07/2020] [Indexed: 12/22/2022]
Abstract
Altered brain structures have been found in patients with schizo-obsessive disorder, schizophrenia and obsessive-compulsive disorder in previous studies. However, it is unclear whether similar brain changes are also found in individuals with high schizo-obsessive traits (SOT), high schizotypal traits (SCT) and obsessive-compulsive symptoms (OCS). We examined grey matter volume (GMV) and white matter integrity (WMI, including fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity) in 26 individuals with high SOT, 30 individuals with high SCT, 25 individuals with OCS and 30 individuals with low trait scores (LT) in this study. Correlation analysis between GMV, WMI, Schizotypal Personality Questionnaire (SPQ) scores and Obsessive-Compulsive Inventory-Revised (OCI-R) scores in the subclinical groups was also carried out. We found that the SOT group exhibited increased GMV at the right superior occipital gyrus and the left postcentral gyrus compared with the LT group. The SCT group exhibited increased GMV at the right precentral gyrus and the bilateral cuneus compared with the LT group, and decreased fractional anisotropy at the anterior corona radiata compared with the other three groups. The OCS group exhibited increased GMV at the left superior temporal gyrus and decreased GMV at the left pre-supplementary motor area compared with the LT group. These findings highlight specific brain changes in individuals with high SOT, high SCT and OCS, and may thus provide new insights into the neurobiological changes that occur in sub-clinical populations of these disorders.
Collapse
Affiliation(s)
- Yong-Ming Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, 100101, PR China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100190, PR China; Sino-Danish Center for Education and Research, Beijing, 100190, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Yi-Jing Zhang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, 100101, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Xin-Lu Cai
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, 100101, PR China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100190, PR China; Sino-Danish Center for Education and Research, Beijing, 100190, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Han-Xue Yang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, 100101, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Hai-di Shan
- Translational Neuropsychology and Applied Cognitive Neuroscience Laboratory, Shanghai Mental Health Centre, Shanghai Jiao Tong University School of Medicine, Shanghai, PR China
| | - Eric F C Cheung
- Castle Peak Hospital, Hong Kong Special Administrative Region, PR China
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, 100101, PR China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100190, PR China; Sino-Danish Center for Education and Research, Beijing, 100190, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China.
| |
Collapse
|
28
|
Brain structural correlates of familial risk for mental illness: a meta-analysis of voxel-based morphometry studies in relatives of patients with psychotic or mood disorders. Neuropsychopharmacology 2020; 45:1369-1379. [PMID: 32353861 PMCID: PMC7297956 DOI: 10.1038/s41386-020-0687-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 04/19/2020] [Accepted: 04/22/2020] [Indexed: 02/05/2023]
Abstract
Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are heritable psychiatric disorders with partially overlapping genetic liability. Shared and disorder-specific neurobiological abnormalities associated with familial risk for developing mental illnesses are largely unknown. We performed a meta-analysis of structural brain imaging studies in relatives of patients with SCZ, BD, and MDD to identify overlapping and discrete brain structural correlates of familial risk for mental disorders. Search for voxel-based morphometry studies in relatives of patients with SCZ, BD, and MDD in PubMed and Embase identified 33 studies with 2292 relatives and 2052 healthy controls (HC). Seed-based d Mapping software was used to investigate global differences in gray matter volumes between relatives as a group versus HC, and between those of each psychiatric disorder and HC. As a group, relatives exhibited gray matter abnormalities in left supramarginal gyrus, right striatum, right inferior frontal gyrus, left thalamus, bilateral insula, right cerebellum, and right superior frontal gyrus, compared with HC. Decreased right cerebellar gray matter was the only abnormality common to relatives of all three conditions. Subgroup analyses showed disorder-specific gray matter abnormalities in left thalamus and bilateral insula associated with risk for SCZ, in left supramarginal gyrus and right frontal regions with risk for BD, and in right striatum with risk for MDD. While decreased gray matter in right cerebellum might be a common brain structural abnormality associated with shared risk for SCZ, BD, and MDD, regional gray matter abnormalities in neocortex, thalamus, and striatum appear to be disorder-specific.
Collapse
|
29
|
Characteristics of gray matter alterations in never-treated and treated chronic schizophrenia patients. Transl Psychiatry 2020; 10:136. [PMID: 32398765 PMCID: PMC7217843 DOI: 10.1038/s41398-020-0828-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 04/15/2020] [Accepted: 04/22/2020] [Indexed: 02/05/2023] Open
Abstract
Though gray matter deficits have been consistently revealed in chronic treated schizophrenia, it is still not clear whether there are different brain alterations between chronic never treated and treated patients. To explore the different patterns of gray matter alterations among chronic never treated patients and those treated with monotherapy, we recruited 35 never-treated chronic schizophrenia patients with illness durations ranging from 5 to 48 years, 20 illness duration-matched risperidone monotherapy and 20 clozapine monotherapy patients, and 55 healthy controls. GM (surface area, cortical thickness, and cortical volume) measures were extracted and compared using ANCOVA across the four groups followed by post hoc tests. Relative to controls, both treated and never-treated chronic schizophrenia patients showed reduced GM mainly involving the bilateral medial and rostral middle frontal, left banks superior temporal sulcus, left fusiform, and left pericalcarine cortex and increased in the left cuneus. Compared with the untreated patient group, the two treated groups showed reductions mainly in the bilateral prefrontal, temporal, and left inferior parietal lobules. The clozapine monotherapy patients demonstrated more severe decreases in the bilateral prefrontal cortex and left cuneus and less severe decreases in the left ventral temporal lobe than risperidone monotherapy patients. These findings provide new insights into the long-term effects of antipsychotic treatment on gray matter alterations in schizophrenia patients. Furthermore, the characteristic findings of reductions in the inferior parietal lobule might be specific for long-term antipsychotic treatment, which could be a possible target for medication development in the future.
Collapse
|
30
|
Yu T, Jia T, Zhu L, Desrivières S, Macare C, Bi Y, Bokde ALW, Quinlan EB, Heinz A, Ittermann B, Liu C, Ji L, Banaschewski T, Ren D, Du L, Hou B, Flor H, Frouin V, Garavan H, Gowland P, Martinot JL, Paillère Martinot ML, Nees F, Orfanos DP, Luo Q, Chu C, Paus T, Poustka L, Hohmann S, Millenet S, Smolka MN, Vetter NC, Mennigen E, Lei C, Walter H, Fröhner JH, Whelan R, He G, He L, Schumann G, Robert G, Artiges E, Schneider S, Bach C, Paus T, Barbot A, Barker G, Bokde A, Vetter N, Büchel C, Cattrell A, Constant P, Gowland P, Crombag H, Czech K, Dalley J, Decideur B, Spranger T, Ripley T, Heym N, Flor H, Sommer W, Fuchs B, Gallinat J, Garavan H, Spanagel R, Kaviani M, Heinrichs B, Heinz A, Subramaniam N, Jia T, Ihlenfeld A, Delosis JI, Ittermann B, Conrod P, Banaschewski T, Jones J, Klaassen A, Lalanne C, Lanzerath D, Lawrence C, Lemaitre H, Desrivieres S, Mallik C, Mann K, Mar A, Martinez-Medina L, Martinot JL, Mennigen E, de Carvahlo FM, Schwartz Y, Bruehl R, Müller K, Nees F, Nymberg C, Lathrop M, Robbins T, Pausova Z, Pentilla J, Biondo F, Poline JB, Hohmann S, Poustka L, Millenet S, Smolka M, Fröhner J, Struve M, Williams S, Hübner T, Bromberg U, Aydin S, Rogers J, Romanowski A, Schmäl C, Schmidt D, Ripke S, Arroyo M, Schubert F, Pena-Oliver Y, Fauth-Bühler M, Mignon X, Whelan R, Speiser C, Fadai T, Stephens D, Ströhle A, Paillere ML, Strache N, Theobald D, Jurk S, Vulser H, Miranda R, Yacubilin J, Frouin V, Genauck A, Parchetka C, Gemmeke I, Kruschwitz J, WeiB K, Walter H, Feng J, Papadopoulos D, Filippi I, Ing A, Ruggeri B, Xu B, Macare C, Chu C, Hanratty E, Quinlan EB, Robert G, Schumann G, Yu T, Ziesch V, Stedman A. Cannabis-Associated Psychotic-like Experiences Are Mediated by Developmental Changes in the Parahippocampal Gyrus. J Am Acad Child Adolesc Psychiatry 2020; 59:642-649. [PMID: 31326579 DOI: 10.1016/j.jaac.2019.05.034] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 05/15/2019] [Accepted: 07/15/2019] [Indexed: 01/06/2023]
Abstract
OBJECTIVE Cannabis consumption during adolescence has been reported as a risk factor for psychotic-like experiences (PLEs) and schizophrenia. However, brain developmental processes associated with cannabis-related PLEs are still poorly described. METHOD A total of 706 adolescents from the general population who were recruited by the IMAGEN consortium had structural magnetic resonance imaging scans at both 14 and 19 years of age. We used deformation-based morphometry to map voxelwise brain changes between the two time points, using the pairwise algorithm in SPM12b. We used an a priori region-of-interest approach focusing on the hippocampus/parahippocampus to perform voxelwise linear regressions. Lifetime cannabis consumption was assessed using the European School Survey Project on Alcohol and other Drugs (ESPAD), and PLEs were assessed with the Comprehensive Assessment Psychotic-like experiences (CAPE) tool. We first tested whether hippocampus/parahippocampus development was associated with PLEs. Then we formulated and tested an a priori simple mediation model in which uncus development mediates the association between lifetime cannabis consumption and PLEs. RESULTS We found that PLEs were associated with reduced expansion within a specific region of the right hippocampus/parahippocampus formation, the uncus (p = .002 at the cluster level, p = .018 at the peak level). The partial simple mediation model revealed a significant total effect from lifetime cannabis consumption to PLEs (b = 0.069, 95% CI = 0.04-0.1, p =2 × 10-16), as well as a small yet significant, indirect effect of right uncus development (0.004; 95% CI = 0.0004-0.01, p = .026). CONCLUSION We show here that the uncus development is involved in the cerebral basis of PLEs in a population-based sample of healthy adolescents.
Collapse
Affiliation(s)
- Tao Yu
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; Shanghai Center for Women and Children's Health, China; Jining Medical University, Shandong, China
| | - Tianye Jia
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; Institute of Science and Technology for Brain-Inspired Intelligence, MoE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Liping Zhu
- Shanghai Center for Women and Children's Health, China
| | - Sylvane Desrivières
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Christine Macare
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Yan Bi
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, College Green, Dublin, Ireland
| | - Erin Burke Quinlan
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Andreas Heinz
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Charité Mitte, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany
| | | | - Lei Ji
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Tobias Banaschewski
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Decheng Ren
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Li Du
- Shanghai Center for Women and Children's Health, China
| | - Binyin Hou
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Herta Flor
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; School of Social Sciences, University of Mannheim, Germany
| | - Vincent Frouin
- NeuroSpin, Commissariat à l'Energie Atomique, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | | | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale (INSERM), University Paris Sud, Orsay, France
| | | | - Frauke Nees
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | - Qiang Luo
- Institute of Science and Technology for Brain-Inspired Intelligence, MoE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Congying Chu
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Tomas Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital and the University of Toronto, Ontario, Canada
| | - Luise Poustka
- University Medical Centre Göttingen, Göttingen, Germany
| | - Sarah Hohmann
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sabina Millenet
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | | | | | | | - Cai Lei
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Henrik Walter
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Charité Mitte, Berlin, Germany
| | | | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Guang He
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Lin He
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; Shanghai Center for Women and Children's Health, China; Baoan Maternal and Child Health Hospital, Jinan University, Shenzhen, China. IMAGEN consortium authors, affiliations, and acknowledgement are listed in the supplementary materials
| | - Gunter Schumann
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Gabriel Robert
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; Behavior and Basal Ganglia Unit, Medical University of Rennes, France.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
31
|
Treatment response prediction and individualized identification of first-episode drug-naïve schizophrenia using brain functional connectivity. Mol Psychiatry 2020; 25:906-913. [PMID: 29921920 DOI: 10.1038/s41380-018-0106-5] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 04/11/2018] [Accepted: 05/01/2018] [Indexed: 12/28/2022]
Abstract
Identifying biomarkers in schizophrenia during the first episode without the confounding effects of treatment has been challenging. Leveraging these biomarkers to establish diagnosis and make individualized predictions of future treatment responses to antipsychotics would be of great value, but there has been limited progress. In this study, by using machine learning algorithms and the functional connections of the superior temporal cortex, we successfully identified the first-episode drug-naive (FEDN) schizophrenia patients (accuracy 78.6%) and predict their responses to antipsychotic treatment (accuracy 82.5%) at an individual level. The functional connections (FC) were derived using the mutual information and the correlations, between the blood-oxygen-level dependent signals of the superior temporal cortex and other cortical regions acquired with the resting-state functional magnetic resonance imaging. We also found that the mutual information and correlation FC was informative in identifying individual FEDN schizophrenia and prediction of treatment response, respectively. The methods and findings in this paper could provide a critical step toward individualized identification and treatment response prediction in first-episode drug-naive schizophrenia, which could complement other biomarkers in the development of precision medicine approaches for this severe mental disorder.
Collapse
|
32
|
Madeira N, Duarte JV, Martins R, Costa GN, Macedo A, Castelo-Branco M. Morphometry and gyrification in bipolar disorder and schizophrenia: A comparative MRI study. NEUROIMAGE-CLINICAL 2020; 26:102220. [PMID: 32146321 PMCID: PMC7063231 DOI: 10.1016/j.nicl.2020.102220] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Revised: 01/20/2020] [Accepted: 02/17/2020] [Indexed: 12/31/2022]
Abstract
Increased right globus pallidus is a consistent marker in schizophrenia (SCZ). Left supramarginal gyrification increases in bipolar disorder (BPD) in contrast with SCZ. Gyrification analysis may help distinguish early phases of BPD and SCZ.
Schizophrenia is believed to be a neurodevelopmental disease with high heritability. Differential diagnosis is often challenging, especially in early phases, namely with other psychotic disorders or even mood disorders. such as bipolar disorder with psychotic symptoms. Key pathophysiological changes separating these two classical psychoses remain poorly understood, and current evidence favors a more dimensional than categorical differentiation between schizophrenia and bipolar disorder. While established biomarkers like cortical thickness and grey matter volume are heavily influenced by post-onset changes and thus provide limited possibility of accessing early pathologies, gyrification is assumed to be more specifically determined by genetic and early developmental factors. The aim of our study was to compare both classical and novel morphometric features in these two archetypal psychiatric disorders. We included 20 schizophrenia patients, 20 bipolar disorder patients and 20 age- and gender-matched healthy controls. Data analyses were performed with CAT12/SPM12 applying general linear models for four morphometric measures: gyrification and cortical thickness (surface-based morphometry), and whole-brain grey matter/grey matter volume (voxel-based morphometry - VBM). Group effects were tested using age and gender as covariates (and total intracranial volume for VBM). Voxel-based morphometry analysis revealed a schizophrenia vs. control group effect on regional grey matter volume (p < 0.05, familywise error correction) in the right globus pallidus. There was no group effect on white matter volume when correcting for multiple comparisons neither on cortical thickness. Gyrification changes in clinical samples were found in the left supramarginal gyrus (BA40) – increased and reduced gyrification, respectively, in BPD and SCZ patients - and in the right inferior frontal gyrus (BA47), with a reduction in gyrification of the SCZ group when compared with controls. The joint analysis of different morphometric features, namely measures such as gyrification, provides a promising strategy for the elucidation of distinct phenotypes in psychiatric disorders. Different morphological change patterns, highlighting specific disease trajectories, could potentially generate neuroimaging-derived biomarkers, helping to discriminate schizophrenia from bipolar disorder in early phases, such as first-episode psychosis patients.
Collapse
Affiliation(s)
- Nuno Madeira
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Portugal
| | - João Valente Duarte
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Portugal
| | - Ricardo Martins
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Portugal
| | - Gabriel Nascimento Costa
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Portugal
| | - António Macedo
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Psychological Medicine, Faculty of Medicine, University of Coimbra, Portugal; Department of Psychiatry, Centro Hospitalar e Universitário de Coimbra, Portugal
| | - Miguel Castelo-Branco
- Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), University of Coimbra, Portugal; Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Portugal.
| |
Collapse
|
33
|
Kolenič M, Španiel F, Hlinka J, Matějka M, Knytl P, Šebela A, Renka J, Hajek T. Higher Body-Mass Index and Lower Gray Matter Volumes in First Episode of Psychosis. Front Psychiatry 2020; 11:556759. [PMID: 33173508 PMCID: PMC7538831 DOI: 10.3389/fpsyt.2020.556759] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 09/02/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Neurostructural alterations are often reported in first episode of psychosis (FEP), but there is heterogeneity in the direction and location of findings between individual studies. The reasons for this heterogeneity remain unknown. Obesity is disproportionately frequent already early in the course of psychosis and is associated with smaller brain volumes. Thus, we hypothesized that obesity may contribute to brain changes in FEP. METHOD We analyzed MRI scans from 120 participants with FEP and 114 healthy participants. In primary analyses, we performed voxel-based morphometry (VBM) with small volume corrections to regions associated with FEP or obesity in previous meta-analyses. In secondary analyses, we performed whole-brain VBM analyses. RESULTS In primary analyses, we found that when controlling for BMI, FEP had lower GM volume than healthy participants in a) left fronto-temporal region (pTFCE = 0.008) and b) left postcentral gyrus (pTFCE = 0.043). When controlling for FEP, BMI was associated with lower GM volume in left cerebellum (pTFCE < 0.001). In secondary analyses, we found that when controlling for BMI, FEP had lower GM volume than healthy participants in the a) cerebellum (pTFCE = 0.004), b) left frontal (pTFCE = 0.024), and c) right temporal cortex (pTFCE = 0.031). When controlling for FEP, BMI was associated with lower GM volume in cerebellum (pTFCE = 0.004). Levels of C-reactive protein, HDL and LDL-cholesterol correlated with obesity related neurostructural alterations. CONCLUSIONS This study suggests that higher BMI, which is frequent in FEP, may contribute to cerebellar alterations in schizophrenia. As previous studies showed that obesity-related brain alterations may be reversible, our findings raise the possibility that improving the screening for and treatment of obesity and associated metabolic changes could preserve brain structure in FEP.
Collapse
Affiliation(s)
- Marián Kolenič
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia.,3rd Faculty of Medicine, Charles University, Prague, Czechia
| | - Filip Španiel
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia
| | - Jaroslav Hlinka
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia.,Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences, Prague, Czechia
| | - Martin Matějka
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia.,3rd Faculty of Medicine, Charles University, Prague, Czechia
| | - Pavel Knytl
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia.,3rd Faculty of Medicine, Charles University, Prague, Czechia
| | - Antonín Šebela
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia
| | - Jiří Renka
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia.,3rd Faculty of Medicine, Charles University, Prague, Czechia
| | - Tomas Hajek
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia.,Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| |
Collapse
|
34
|
Gao S, Ming Y, Wang J, Gu Y, Ni S, Lu S, Zhang R, Sun J, Zhang N, Xu X. Enhanced Prefrontal Regional Homogeneity and Its Correlations With Cognitive Dysfunction/Psychopathology in Patients With First-Diagnosed and Drug-Naive Schizophrenia. Front Psychiatry 2020; 11:580570. [PMID: 33192722 PMCID: PMC7649771 DOI: 10.3389/fpsyt.2020.580570] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 09/14/2020] [Indexed: 01/10/2023] Open
Abstract
Background: Schizophrenia, regarded as a neurodevelopmental disorder, is characterized by positive symptoms, negative symptoms, and cognitive dysfunction. Investigating the spontaneous brain activity in patients with schizophrenia can help us understand the underlying pathophysiologic mechanism of schizophrenia. However, results concerning abnormal neural activities and their correlations with cognitive dysfunction/psychopathology of patients with schizophrenia were inconsistent. Methods: We recruited 57 first-diagnosed and drug-naive patients with schizophrenia and 50 matched healthy controls underwent magnetic resonance imaging. The Positive and Negative Syndrome Scale (PANSS) and the MATRICS Consensus Cognitive Battery were used to assess the psychopathology/cognitive dysfunction. Regional homogeneity (ReHo) was used to explore neural activities. Correlation analyses were calculated between abnormal ReHo values and PANSS scores/standardized cognitive scores. Lastly, support vector machine analyses were conducted to evaluate the accuracy of abnormal ReHo values in distinguishing patients with schizophrenia from healthy controls. Results: Patients with schizophrenia showed cognitive dysfunction, and increased ReHo values in the right gyrus rectus, right inferior frontal gyrus/insula and left inferior frontal gyrus/insula compared with those of healthy controls. The ReHo values in the right inferior frontal gyrus/insula were positively correlated with negative symptom scores and negatively correlated with Hopkins verbal learning test-revised/verbal learning. Our results showed that the combination of increased ReHo values in the left inferior frontal gyrus/insula and right gyrus rectus had 78.5% (84/107) accuracy, 85.96% (49/57) sensitivity, and 70.00% specificity, which were higher than other combinations. Conclusions: Hyperactivities were primarily located in the prefrontal regions, and increased ReHo values in the right inferior frontal gyrus/insula might reflect the severity of negative symptoms and verbal learning abilities. The combined increases of ReHo values in these regions might be an underlying biomarker in differentiating patients with schizophrenia from healthy controls.
Collapse
Affiliation(s)
- Shuzhan Gao
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yidan Ming
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Jiayin Wang
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yuan Gu
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Sulin Ni
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Shuiping Lu
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Rongrong Zhang
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Jing Sun
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Ning Zhang
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.,Department of Psychiatry, Nanjing Brain Hospital, Medical School, Nanjing University, Nanjing, China
| | - Xijia Xu
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China.,Department of Psychiatry, Nanjing Brain Hospital, Medical School, Nanjing University, Nanjing, China
| |
Collapse
|
35
|
Liu F, Shao Y, Li X, Liu L, Zhao R, Xie B, Qiao Y. Volumetric Abnormalities in Violent Schizophrenia Patients on the General Psychiatric Ward. Front Psychiatry 2020; 11:788. [PMID: 33117201 PMCID: PMC7493665 DOI: 10.3389/fpsyt.2020.00788] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 07/23/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND In recent years, neuroimaging has been used increasingly to explore the biological underpinnings of violence carried out by schizophrenia patients (SPs). Studies have focused mostly on patients with a history of carrying out severe physical assaults, or comorbid with substance abuse/personality disorder (SA/PD). As a result, participants were unrepresentative and the interpretation of brain-structure changes was confusing. Here, we concentrated on SPs on a general psychiatric ward with a history of relatively lower violence, and individuals comorbid with SA or PD were excluded. We expected to identify the characteristics of brain morphometry in this population, and to explore whether the morphometric changes were universal. METHODS Forty-eight violent schizophrenia patients (VSPs), twenty-seven non-VSPs (nVSPs) and 28 nonviolent healthy controls (HCs) were investigated. Voxel-based morphometry was used to evaluate the gray matter volume (GMV) of all study participants. Whole-brain analyses were used to reveal group effects and differences between any two groups. Correlation analyses were undertaken between significant brain regions and behavioral measurements in the VSP group. RESULTS Patients showed a significantly smaller GMV in widespread frontal, temporal, and limbic regions compared with HCs. No region was found in which the two patient groups had significantly larger volumes compared with that in HCs. A significant decrease in the GMV of the right fusiform gyrus was found in the VSP group compared with that in the nVSP group (p = 0.004), where the GMV of this region had a negative correlation with the Physical Aggression [subscale of the Modified Overt Aggression Scale (MOAS)] or Hostility score. The VSP group showed a trend of GMV decrease in the left middle temporal cortex compared with that in the nVSP group (p = 0.077). Negative correlation was also found between the GMV of left inferior temporal gyrus/left Superior frontal gyrus, medial and the Hostility score. CONCLUSIONS Our results provide initial evidence demonstrating the generalizability of GMV abnormalities in SPs engaged in varying levels of violence, even when SA or PD have not been implicated. GMV reduction was correlated with only the Physical Aggression subscale score of the MOAS, suggesting that this change in brain morphology may be dependent upon different types of violent actions.
Collapse
Affiliation(s)
- FengJu Liu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yang Shao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xin Li
- Shanghai Pudong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai, China
| | - Li Liu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rong Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bin Xie
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yi Qiao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|
36
|
Li C, Liu W, Guo F, Wang X, Kang X, Xu Y, Xi Y, Wang H, Zhu Y, Yin H. Voxel-based morphometry results in first-episode schizophrenia: a comparison of publicly available software packages. Brain Imaging Behav 2019; 14:2224-2231. [PMID: 31377989 DOI: 10.1007/s11682-019-00172-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Investigations of brain structure in schizophrenia using magnetic resonance imaging (MRI) have identified variations in regional grey matter (GM) volume throughout the brain but the results are mixed. This study aims to investigate whether the inconsistent voxel-based morphometry (VBM) findings in schizophrenia are due to the use of different software packages. T1 MRI images were obtained from 86 first-episode schizophrenia (FESZ) patients and 86 age- and gender-matched Healthy controls (HCs). VBM analysis was carried out using FMRIB software library (FSL) 5.0 and statistical parametric mapping 8 (SPM8). All images were processed using the default parameter settings as provided by these software packages. FSL-VBM revealed widespread GM volume reductions in FESZ patients compared with HCs, however, for SPM-VBM, only increased and circumscribed GM volume changes were found, both software revealed increased GM volume within cerebellum. Significant correlations between Positive and Negative Syndrome Scale (PANSS) and GM volume were mainly found in frontal regions. Algorithms of GM tissue segmentation, image registration and statistical strategies might contribute to these disparate results.
Collapse
Affiliation(s)
- Chen Li
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi'an, 710032, China
| | - Wenming Liu
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi'an, 710032, China
| | - Xingrui Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi'an, 710032, China
| | - Xiaowei Kang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi'an, 710032, China
| | - Yongqiang Xu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi'an, 710032, China
| | - Yibin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi'an, 710032, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Yuanqiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi'an, 710032, China.
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi'an, 710032, China.
| |
Collapse
|
37
|
Identifying Brain Abnormalities with Schizophrenia Based on a Hybrid Feature Selection Technology. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9102148] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Many medical imaging data, especially the magnetic resonance imaging (MRI) data, usually have a small sample size, but a large number of features. How to reduce effectively the data dimension and locate accurately the biomarkers from such kinds of data are quite crucial for diagnosis and further precision medicine. In this paper, we propose a hybrid feature selection method based on machine learning and traditional statistical approaches and explore the brain abnormalities of schizophrenia by using the functional and structural MRI data. The results show that the abnormal brain regions are mainly distributed in the supramarginal gyrus, cingulate gyrus, frontal gyrus, precuneus and caudate, and the abnormal functional connections are related to the caudate nucleus, insula and rolandic operculum. In addition, some complex network analyses based on graph theory are utilized on the functional connection data, and the results demonstrate that the located abnormal functional connections in brain can distinguish schizophrenia patients from healthy controls. The identified abnormalities in brain with schizophrenia by the proposed hybrid feature selection method show that there do exist some abnormal brain regions and abnormal disruption of the network segregation and network integration for schizophrenia, and these changes may lead to inaccurate and inefficient information processing and synthesis in the brain, which provide further evidence for the cognitive dysmetria of schizophrenia.
Collapse
|
38
|
Wang X, Zhao N, Shi J, Wu Y, Liu J, Xiao Q, Hu J. Discussion on the Application of Multi-modal Magnetic Resonance Imaging Fusion in Schizophrenia. J Med Syst 2019; 43:131. [DOI: 10.1007/s10916-019-1215-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Accepted: 02/13/2019] [Indexed: 10/27/2022]
|
39
|
Jessen K, Mandl RCW, Fagerlund B, Bojesen KB, Raghava JM, Obaid HG, Jensen MB, Johansen LB, Nielsen MØ, Pantelis C, Rostrup E, Glenthøj BY, Ebdrup BH. Patterns of Cortical Structures and Cognition in Antipsychotic-Naïve Patients With First-Episode Schizophrenia: A Partial Least Squares Correlation Analysis. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 4:444-453. [PMID: 30420252 DOI: 10.1016/j.bpsc.2018.09.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 08/09/2018] [Accepted: 09/01/2018] [Indexed: 12/26/2022]
Abstract
BACKGROUND Schizophrenia is associated with alterations in cortical structures and cognitive impairments, but antipsychotic medication may affect these measures. We investigated patterns of relationships between cortical structures and cognitive domains in antipsychotic-naïve patients with first-episode schizophrenia. METHODS T1-weighted 3T magnetic resonance imaging was performed in 105 patients and 136 healthy control subjects. Using FreeSurfer, we obtained measurements of cortical thickness, surface area, and mean curvature. Using an extensive neurocognitive battery including the Danish Adult Reading Test and subtests from the Cambridge Neuropsychological Test Automated Battery, we obtained estimates of premorbid intelligence, spatial working memory, spatial planning, intra-extradimensional set shifting, and reaction and movement times. With univariate analyses, we tested group differences between cortical structures and cognition. With partial least squares correlation analyses, we investigated patterns of associations between cortical structures and cognition. RESULTS Patients had significantly higher mean curvature and were impaired on 7 of 11 cognitive parameters. The between-group partial least squares correlation analysis revealed two cortical thickness/cognition patterns that differentiated patients and healthy control subjects (omnibus test, p = .011). Most cortical regions contributed reliably to these patterns. In patients, spatial working memory, spatial planning, reaction and movement times, and premorbid intelligence contributed reliably to the pattern; in healthy control subjects, spatial planning and intra-extradimensional set shifting contributed reliably. CONCLUSIONS Antipsychotic-naïve patients with first-episode schizophrenia displayed a higher mean curvature, but no significant difference in other gray matter indices was found. Nevertheless, the pattern of associations between global cortical thickness and cognitive functions was markedly different between groups. These multivariate analyses reveal a novel linkage between regional cortical brain structure and cognitive deficits at the earliest, never-medicated illness stage.
Collapse
Affiliation(s)
- Kasper Jessen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Rene C W Mandl
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Kirsten B Bojesen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jayachandra M Raghava
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Functional Imaging Unit, Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet-Glostrup, Glostrup, Denmark
| | - Hayder G Obaid
- Department of Radiology, Copenhagen University Hospital Herlev Gentofte, Herlev, Denmark
| | - Marie B Jensen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Louise B Johansen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, Hvidovre, Denmark
| | - Mette Ø Nielsen
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Christos Pantelis
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia
| | - Egill Rostrup
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Birte Y Glenthøj
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Bjørn H Ebdrup
- Center for Neuropsychiatric Schizophrenia Research and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research, Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
40
|
Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia. Neuroimage 2018; 181:734-747. [PMID: 30055372 DOI: 10.1016/j.neuroimage.2018.07.047] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2017] [Revised: 07/16/2018] [Accepted: 07/18/2018] [Indexed: 01/01/2023] Open
Abstract
This work presents a novel approach to finding linkage/association between multimodal brain imaging data, such as structural MRI (sMRI) and functional MRI (fMRI). Motivated by the machine translation domain, we employ a deep learning model, and consider two different imaging views of the same brain like two different languages conveying some common facts. That analogy enables finding linkages between two modalities. The proposed translation-based fusion model contains a computing layer that learns "alignments" (or links) between dynamic connectivity features from fMRI data and static gray matter patterns from sMRI data. The approach is evaluated on a multi-site dataset consisting of eyes-closed resting state imaging data collected from 298 subjects (age- and gender matched 154 healthy controls and 144 patients with schizophrenia). Results are further confirmed on an independent dataset consisting of eyes-open resting state imaging data from 189 subjects (age- and gender matched 91 healthy controls and 98 patients with schizophrenia). We used dynamic functional connectivity (dFNC) states as the functional features and ICA-based sources from gray matter densities as the structural features. The dFNC states characterized by weakly correlated intrinsic connectivity networks (ICNs) were found to have stronger association with putamen and insular gray matter pattern, while the dFNC states of profuse strongly correlated ICNs exhibited stronger links with the gray matter pattern in precuneus, posterior cingulate cortex (PCC), and temporal cortex. Further investigation with the estimated link strength (or alignment score) showed significant group differences between healthy controls and patients with schizophrenia in several key regions including temporal lobe, and linked these to connectivity states showing less occupancy in healthy controls. Moreover, this novel approach revealed significant correlation between a cognitive score (attention/vigilance) and the function/structure alignment score that was not detected when data modalities were considered separately.
Collapse
|
41
|
Wang YM, Zou LQ, Xie WL, Yang ZY, Zhu XZ, Cheung EFC, Sørensen TA, Møller A, Chan RCK. Altered grey matter volume and cortical thickness in patients with schizo-obsessive comorbidity. Psychiatry Res Neuroimaging 2018; 276:65-72. [PMID: 29628272 DOI: 10.1016/j.pscychresns.2018.03.009] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 03/23/2018] [Accepted: 03/23/2018] [Indexed: 02/05/2023]
Abstract
Recent findings suggest that schizo-obsessive comorbidity (SOC) may be a unique diagnostic entity. We examined grey matter (GM) volume and cortical thickness in 22 patients with SOC, and compared them with 21 schizophrenia (SCZ) patients, 22 obsessive-compulsive disorder (OCD) patients and 22 healthy controls (HCs). We found that patients with SOC exhibited reduced GM volume in the left thalamus, the left inferior semi-lunar lobule of the cerebellum, the bilateral medial orbitofrontal cortex (medial oFC), the medial superior frontal gyrus (medial sFG), the rectus gyrus and the anterior cingulate cortex (aCC) compared with HCs. Patients with SOC also exhibited reduced cortical thickness in the right superior temporal gyrus (sTG), the right angular gyrus, the right supplementary motor area (SMA), the right middle cingulate cortex (mCC) and the right middle occipital gyrus (mOG) compared with HCs. Together with the differences in GM volume and cortical thickness between patients with SOC and patients with only SCZ or only OCD, these findings highlight the GM changes specific to patients with SOC.
Collapse
Affiliation(s)
- Yong-Ming Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, PR China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, PR China; Sino-Danish Center for Education and Research, Beijing 100190, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Lai-Quan Zou
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, PR China; Department of Psychology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou, Guangdong, PR China
| | - Wen-Lan Xie
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Zhuo-Ya Yang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China
| | - Xiong-Zhao Zhu
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, PR China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, PR China
| | - Eric F C Cheung
- Castle Peak Hospital, Hong Kong Special Administrative Region, PR China
| | - Thomas Alrik Sørensen
- Sino-Danish Center for Education and Research, Beijing 100190, PR China; Centre for Cognitive Neuroscience, Institute of Communication and Psychology, Aalborg University, Denmark
| | - Arne Møller
- Sino-Danish Center for Education and Research, Beijing 100190, PR China; Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Denmark; Centre of Functionally Integrative Neuroscience, Aarhus University, Denmark
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing 100101, PR China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, PR China; Sino-Danish Center for Education and Research, Beijing 100190, PR China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, PR China.
| |
Collapse
|
42
|
Cerebellar volume and cerebellocerebral structural covariance in schizophrenia: a multisite mega-analysis of 983 patients and 1349 healthy controls. Mol Psychiatry 2018; 23:1512-1520. [PMID: 28507318 DOI: 10.1038/mp.2017.106] [Citation(s) in RCA: 131] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/25/2016] [Revised: 02/20/2017] [Accepted: 04/04/2017] [Indexed: 12/24/2022]
Abstract
Although cerebellar involvement across a wide range of cognitive and neuropsychiatric phenotypes is increasingly being recognized, previous large-scale studies in schizophrenia (SZ) have primarily focused on supratentorial structures. Hence, the across-sample reproducibility, regional distribution, associations with cerebrocortical morphology and effect sizes of cerebellar relative to cerebral morphological differences in SZ are unknown. We addressed these questions in 983 patients with SZ spectrum disorders and 1349 healthy controls (HCs) from 14 international samples, using state-of-the-art image analysis pipelines optimized for both the cerebellum and the cerebrum. Results showed that total cerebellar grey matter volume was robustly reduced in SZ relative to HCs (Cohens's d=-0.35), with the strongest effects in cerebellar regions showing functional connectivity with frontoparietal cortices (d=-0.40). Effect sizes for cerebellar volumes were similar to the most consistently reported cerebral structural changes in SZ (e.g., hippocampus volume and frontotemporal cortical thickness), and were highly consistent across samples. Within groups, we further observed positive correlations between cerebellar volume and cerebral cortical thickness in frontotemporal regions (i.e., overlapping with areas that also showed reductions in SZ). This cerebellocerebral structural covariance was strongest in SZ, suggesting common underlying disease processes jointly affecting the cerebellum and the cerebrum. Finally, cerebellar volume reduction in SZ was highly consistent across the included age span (16-66 years) and present already in the youngest patients, a finding that is more consistent with neurodevelopmental than neurodegenerative etiology. Taken together, these novel findings establish the cerebellum as a key node in the distributed brain networks underlying SZ.
Collapse
|
43
|
Gao X, Zhang W, Yao L, Xiao Y, Liu L, Liu J, Li S, Tao B, Shah C, Gong Q, Sweeney JA, Lui S. Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis. J Psychiatry Neurosci 2017; 43:160219. [PMID: 29244020 PMCID: PMC5837885 DOI: 10.1503/jpn.160219] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Revised: 08/29/2017] [Accepted: 09/09/2017] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. METHODS We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. RESULTS We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus. LIMITATIONS The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. CONCLUSION The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia.
Collapse
Affiliation(s)
- Xin Gao
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - Wenjing Zhang
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - Li Yao
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - Yuan Xiao
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - Lu Liu
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - Jieke Liu
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - Siyi Li
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - Bo Tao
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - Chandan Shah
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - Qiyong Gong
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - John A Sweeney
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| | - Su Lui
- From the Department of Radiology, Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China (Gao, Lui); the Department of Radiology, the Centre for Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gao, Zhang, Yao, Xiao, Liu, Li, Tao, Shah, Gong, Lui); and the Department of Psychiatry, University of Texas Southwestern, Dallas, Tex, USA (Sweeney)
| |
Collapse
|