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Gao S, Sun Y, Wu F, Jiang J, Peng T, Zhang R, Ling C, Han Y, Xu Q, Zou L, Liao Y, Liang C, Zhang D, Qi S, Tang J, Xu X. Effects on Multimodal Connectivity Patterns in Female Schizophrenia During 8 Weeks of Antipsychotic Treatment. Schizophr Bull 2025; 51:829-840. [PMID: 39729483 PMCID: PMC12061653 DOI: 10.1093/schbul/sbae176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2024]
Abstract
BACKGROUND AND HYPOTHESIS Respective abnormal structural connectivity (SC) and functional connectivity (FC) have been reported in individuals with schizophrenia. However, transmodal associations between SC and FC following antipsychotic treatment, especially in female schizophrenia, remain unclear. We hypothesized that increased SC-FC coupling may be found in female schizophrenia, and could be normalized after antipsychotic treatment. STUDY DESIGN Sixty-four female drug-naïve patients with first-diagnosed schizophrenia treated with antipsychotic drugs for 8 weeks, and 55 female healthy controls (HCs) were enrolled. Magnetic resonance imaging (MRI) data were collected from HCs at baseline and from patients at baseline and after treatment. SC and FC were analyzed by network-based statistics, calculating nonzero SC-FC coupling of the whole brain and altered connectivity following treatment. Finally, an Elastic-net logistic regression analysis was employed to establish a predictive model for evaluating the clinical efficacy treatment. STUDY RESULTS At baseline, female schizophrenia patients exhibited abnormal SC in cortico-cortical, frontal-limbic, frontal-striatal, limbic-striatal, and limbic-cerebellar connectivity compared to HCs, while FC showed no abnormalities. Following treatment, cortico-cortical, frontal-limbic, frontal-striatal, limbic-striatal, temporal-cerebellar, and limbic-cerebellar connectivity were altered in both SC and FC. Additionally, SC-FC coupling of altered connectivity was higher in patients at baseline than in HC, trending toward normalization after treatment. Furthermore, identified FC or/and SC predicted changes in psychopathological symptoms and cognitive impairment among female schizophrenia following treatment. CONCLUSIONS SC-FC coupling may be a potential predictive biomarker of treatment response. Cortico-cortical, frontal-limbic, frontal-striatal, limbic-striatal, temporal-cerebellar, and limbic-cerebellar could represent major targets for antipsychotic drugs in female schizophrenia.
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Affiliation(s)
- Shuzhan Gao
- Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
- Department of Psychiatry, Nanjing Brain Hospital, Medical School, Nanjing University, Nanjing, 210029, China
| | - Yunkai Sun
- Department of Psychiatry, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
| | - Fan Wu
- Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Jing Jiang
- Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Ting Peng
- Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Rongrong Zhang
- Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Chenxi Ling
- Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Yanlin Han
- Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Qing Xu
- Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Lulu Zou
- Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Yanhui Liao
- Department of Psychiatry, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
| | - Chuang Liang
- College of Computer Science and Technology and the Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China
| | - Daoqiang Zhang
- College of Computer Science and Technology and the Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China
| | - Shile Qi
- College of Computer Science and Technology and the Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China
| | - Jinsong Tang
- Department of Psychiatry, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China
| | - Xijia Xu
- Department of Psychiatry, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
- Department of Psychiatry, Nanjing Brain Hospital, Medical School, Nanjing University, Nanjing, 210029, China
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Du Y, Niu J, Xing Y, Li B, Calhoun VD. Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade. Schizophr Bull 2025; 51:325-342. [PMID: 38982882 PMCID: PMC11908864 DOI: 10.1093/schbul/sbae110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/11/2024]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, distinguish SZ from healthy conditions or other mental disorders, and explore biotypes within SZ or across SZ and other mental disorders, which aim to promote the accurate diagnosis of SZ. In China, research on SZ using MRI has grown considerably in recent years. STUDY DESIGN The article reviews advanced neuroimaging and artificial intelligence (AI) methods using single-modal or multimodal MRI to reveal the mechanism of SZ and promote accurate diagnosis of SZ, with a particular emphasis on the achievements made by Chinese scholars around the past decade. STUDY RESULTS Our article focuses on the methods for capturing subtle brain functional and structural properties from the high-dimensional MRI data, the multimodal fusion and feature selection methods for obtaining important and sparse neuroimaging features, the supervised statistical analysis and classification for distinguishing disorders, and the unsupervised clustering and semi-supervised learning methods for identifying neuroimage-based biotypes. Crucially, our article highlights the characteristics of each method and underscores the interconnections among various approaches regarding biomarker extraction and neuroimage-based diagnosis, which is beneficial not only for comprehending SZ but also for exploring other mental disorders. CONCLUSIONS We offer a valuable review of advanced neuroimage analysis and AI methods primarily focused on SZ research by Chinese scholars, aiming to promote the diagnosis, treatment, and prevention of SZ, as well as other mental disorders, both within China and internationally.
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Affiliation(s)
- Yuhui Du
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Ju Niu
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Ying Xing
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Bang Li
- School of Computer and Information Technology, Shanxi University, Taiyuan, 030006, China
| | - Vince D Calhoun
- The Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, 30303, GA, USA
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Cimmino DB, Zabriskie B, Luke S, Gutman B, Isaev D, Alpert K, Glahn D, Rodrigue A, Kelly S, Pearlson G, Calhoun V, Ehrlich S, Andreassen O, Tordesillas-Gutierrez D, Crespo-Facorro B, Satterthwaite T, Gur R, Gur R, Spalletta G, Piras F, Donohoe G, McDonald C, Pomarol-Clotet E, Salvador R, Karuk A, Voineskos A, Kochunov P, Borgwardt S, Agartz I, Jonsson E, Kircher T, Stein F, Brosch K, Nenadic I, Iasevoli F, Pontillo G, de Bartolomeis A, Barone A, Ciccarelli M, Di Giorgio A, Brunetti A, Cocozza S, Tranfa M, James A, Zarei M, Hough M, Flyckt L, Busatto GF, Rosa PGP, Serpa MH, Zanetti MV, van Erp T, Preda A, Nguyen D, Thompson P, Turner J, Wang L, Cobia D. Sex differences in deep brain shape and asymmetry persist across schizophrenia and healthy individuals: A meta-analysis from the ENIGMA-Schizophrenia Working Group. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.24.619733. [PMID: 39484539 PMCID: PMC11526939 DOI: 10.1101/2024.10.24.619733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2024]
Abstract
Background Schizophrenia (SCZ) is characterized by a disconnect from reality that manifests as various clinical and cognitive symptoms, and persistent neurobiological abnormalities. Sex-related differences in clinical presentation imply separate brain substrates. The present study characterized deep brain morphology using shape features to understand the independent effects of diagnosis and sex on the brain, and to determine whether the neurobiology of schizophrenia varies as a function of sex. Methods This study analyzed multi-site archival data from 1,871 male (M) and 955 female (F) participants with SCZ, and 2,158 male and 1,877 female healthy controls (CON) from twenty-three cross-sectional samples from the ENIGMA Schizophrenia Workgroup. Harmonized shape analysis protocols were applied to each site's data for seven deep brain regions obtained from T1-weighted structural MRI scans. Effect sizes were calculated for the following main contrasts: 1) Sex effects;2) Diagnosis-by-Sex interaction; 3) within sex tests of diagnosis; 4) within diagnosis tests of sex differences. Meta-regression models between brain structure and clinical variables were also computed separately in men and women with schizophrenia. Results Mass univariate meta-analyses revealed more concave-than-convex shape differences in all regions for women relative to men, across diagnostic groups ( d = -0.35 to 0.20, SE = 0.02 to 0.07); there were no significant diagnosis-by-sex interaction effects. Within men and women separately, we identified more-concave-than-convex shape differences for the hippocampus, amygdala, accumbens, and thalamus, with more-convex-than-concave differences in the putamen and pallidum in SCZ ( d = -0.30 to 0.30, SE = 0.03 to 0.10). Within CON and SZ separately, we found more-concave-than-convex shape differences in the thalamus, pallidum, putamen, and amygdala among females compared to males, with mixed findings in the hippocampus and caudate ( d = -0.30 to 0.20, SE = 0.03 to 0.09). Meta-regression models revealed similarly small, but significant relationships, with medication and positive symptoms in both SCZ-M and SCZ-F. Conclusions Sex-specific variation is an overriding feature of deep brain shape regardless of disease status, underscoring persistent patterns of sex differences observed both within and across diagnostic categories, and highlighting the importance of including it as a critical variable in studies of neurobiology. Future work should continue to explore these dimensions independently to determine whether these patterns of brain morphology extend to other aspects of neurobiology in schizophrenia, potentially uncovering broader implications for diagnosis and treatment. Key Points Statistical analyses revealed significant main effects for diagnosis and sex in deep brain shape morphology. Among patients with schizophrenia, there was a pattern of thinning and surface contraction in the bilateral hippocampus, amygdala, accumbens, and thalamus, and a pattern of significant thickening and surface expansion in the bilateral putamen and pallidum compared to healthy control participants. Between males and females, there was a pattern of significant thinning and surface contraction in the bilateral thalamus, pallidum, putamen, and amygdala in females compared to males.There was no significant interaction between diagnosis and biological sex, suggesting that sex differences in deep brain shape and asymmetry among patients with schizophrenia reflect those observed in healthy individuals.Small but statistically significant relationships exist between brain structure and clinical correlates of schizophrenia were similar for both men and women with the disease, such that higher CPZ was associated with shape-derived thinning and surface contraction in the caudate, accumbens, hippocampus, amygdala, and thalamus, and elevated positive symptoms were associated with shape-derived thinning and surface contraction in the bilateral caudate, right hippocampus, and right amygdala.
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Salehi MA, Zafari R, Mohammadi S, Shahrabi Farahani M, Dolatshahi M, Harandi H, Poopak A, Dager SR. Brain-based sex differences in schizophrenia: A systematic review of fMRI studies. Hum Brain Mapp 2024; 45:e26664. [PMID: 38520370 PMCID: PMC10960555 DOI: 10.1002/hbm.26664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 02/29/2024] [Accepted: 03/08/2024] [Indexed: 03/25/2024] Open
Abstract
Schizophrenia is a chronic psychiatric disorder with characteristic symptoms of delusions, hallucinations, lack of motivation, and paucity of thought. Recent evidence suggests that the symptoms of schizophrenia, negative symptoms in particular, vary widely between the sexes and that symptom onset is earlier in males. A better understanding of sex-based differences in functional magnetic resonance imaging (fMRI) studies of schizophrenia may provide a key to understanding sex-based symptom differences. This study aimed to summarize sex-based functional magnetic resonance imaging (fMRI) differences in brain activity of patients with schizophrenia. We searched PubMed and Scopus to find fMRI studies that assessed sex-based differences in the brain activity of patients with schizophrenia. We excluded studies that did not evaluate brain activity using fMRI, did not evaluate sex differences, and were nonhuman or in vitro studies. We found 12 studies that met the inclusion criteria for the current systematic review. Compared to females with schizophrenia, males with schizophrenia showed more blood oxygen level-dependent (BOLD) activation in the cerebellum, the temporal gyrus, and the right precuneus cortex. Male patients also had greater occurrence of low-frequency fluctuations in cerebral blood flow in frontal and parietal lobes and the insular cortex, while female patients had greater occurrence of low-frequency fluctuations in the hippocampus, parahippocampus, and lentiform nucleus. The current study summarizes fMRI studies that evaluated sex-based fMRI brain differences in schizophrenia that may help to shed light on the underlying pathophysiology and further understanding of sex-based differences in the clinical presentation and course of the disorder.
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Affiliation(s)
| | - Rasa Zafari
- School of MedicineTehran University of Medical SciencesTehranIran
| | - Soheil Mohammadi
- School of MedicineTehran University of Medical SciencesTehranIran
| | | | - Mahsa Dolatshahi
- Mallinckrodt Institute of Radiology, Division of NeuroradiologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Hamid Harandi
- School of MedicineTehran University of Medical SciencesTehranIran
| | | | - Stephen R. Dager
- Department of RadiologyUniversity of WashingtonSeattleWashingtonUSA
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5
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Chen X, Tan W, Cheng Y, Huang D, Liu D, Zhang J, Li J, Liu Z, Pan Y, Palaniyappan L. Polygenic risk for schizophrenia and the language network: Putative compensatory reorganization in unaffected siblings. Psychiatry Res 2023; 326:115319. [PMID: 37352748 DOI: 10.1016/j.psychres.2023.115319] [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: 04/28/2023] [Revised: 06/11/2023] [Accepted: 06/18/2023] [Indexed: 06/25/2023]
Abstract
Language-related symptoms, such as disorganized, impoverished speech and communicative behaviors, are one of the core features of schizophrenia. These features most strongly correlate with cognitive deficits and polygenic risk among various symptom dimensions of schizophrenia. Nevertheless, unaffected siblings with genetic high-risk fail to show consistent deficits in language network (LN), indicating that either (1) polygenic risk has no notable effect on LN and/or (2) siblings show compensatory changes in opposing direction to patients. To answer this question, we related polygenic risk scores (PRS) to the region-level, tract-level, and systems-level structure (cortical thickness and fiber connectivity) of LN in 182 patients, 48 unaffected siblings and 135 healthy controls. We also studied the relationships between symptoms, language-related cognition, social functioning and LN structure. We observed a significantly lower thickness in LN (especially the Broca's, Wernicke's area and their right homologues) in patients. Siblings had a distinctly higher thickness in parts of the LN and a more pronounced small-world-like structural integration within the LN. Patients with reduced LN thickness had higher PRS, more disorganization and impoverished speech with lower language-related cognition and social functioning. We conclude that the genetic susceptibility and putative compensatory changes for schizophrenia operate, in part, via key regions in the Language Network.
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Affiliation(s)
- Xudong Chen
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Wenjian Tan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Yixin Cheng
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Danqing Huang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Dayi Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jiamei Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jinyue Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zhening Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Yunzhi Pan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
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6
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Chang X, Zhao W, Kang J, Xiang S, Xie C, Corona-Hernández H, Palaniyappan L, Feng J. Language abnormalities in schizophrenia: binding core symptoms through contemporary empirical evidence. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:95. [PMID: 36371445 PMCID: PMC9653408 DOI: 10.1038/s41537-022-00308-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 10/26/2022] [Indexed: 06/16/2023]
Abstract
Both the ability to speak and to infer complex linguistic messages from sounds have been claimed as uniquely human phenomena. In schizophrenia, formal thought disorder (FTD) and auditory verbal hallucinations (AVHs) are manifestations respectively relating to concrete disruptions of those abilities. From an evolutionary perspective, Crow (1997) proposed that "schizophrenia is the price that Homo sapiens pays for the faculty of language". Epidemiological and experimental evidence points to an overlap between FTD and AVHs, yet a thorough investigation examining their shared neural mechanism in schizophrenia is lacking. In this review, we synthesize observations from three key domains. First, neuroanatomical evidence indicates substantial shared abnormalities in language-processing regions between FTD and AVHs, even in the early phases of schizophrenia. Second, neurochemical studies point to a glutamate-related dysfunction in these language-processing brain regions, contributing to verbal production deficits. Third, genetic findings further show how genes that overlap between schizophrenia and language disorders influence neurodevelopment and neurotransmission. We argue that these observations converge into the possibility that a glutamatergic dysfunction in language-processing brain regions might be a shared neural basis of both FTD and AVHs. Investigations of language pathology in schizophrenia could facilitate the development of diagnostic tools and treatments, so we call for multilevel confirmatory analyses focused on modulations of the language network as a therapeutic goal in schizophrenia.
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Affiliation(s)
- Xiao Chang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Zhao
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, PR China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Shanghai Center for Mathematical Sciences, Shanghai, China
| | - Shitong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Hugo Corona-Hernández
- Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada.
- Robarts Research Institute, University of Western Ontario, London, Ontario, Canada.
- Lawson Health Research Institute, London, Ontario, Canada.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- Shanghai Center for Mathematical Sciences, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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Lu W, Cheng Z, Xie X, Li K, Duan Y, Li M, Ma C, Liu S, Qiu J. An atlas of glucose uptake across the entire human body as measured by the total-body PET/CT scanner: a pilot study. LIFE METABOLISM 2022; 1:190-199. [PMID: 39872349 PMCID: PMC11749875 DOI: 10.1093/lifemeta/loac030] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 09/24/2022] [Accepted: 10/24/2022] [Indexed: 01/30/2025]
Abstract
Glucose uptake differs in organs and tissues across the human body. To date, however, there has been no single atlas providing detailed glucose uptake profiles across the entire human body. Therefore, we aimed to generate a detailed profile of glucose uptake across the entire human body using the uEXPLORER positron emission tomography/computed tomography scanner, which offers the opportunity to collect glucose metabolic imaging quickly and simultaneously in all sites of the body. The standardized uptake value normalized by lean body mass (SUL) of 18F-fluorodeoxyglucose was used as a measure of glucose uptake. We developed a fingerprint of glucose uptake reflecting the mean SULs of major organs and parts across the entire human body in 15 healthy-weight and 18 overweight subjects. Using the segmentation of organs and body parts from the atlas, we uncovered the significant impacts of age, sex, and obesity on glucose uptake in organs and parts across the entire body. A difference was recognized between the right and left side of the body. Overall, we generated a total-body glucose uptake atlas that could be used as the reference for the diagnosis and evaluation of disordered states involving dysregulated glucose metabolism.
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Affiliation(s)
- Weizhao Lu
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong 271016, China
| | - Zhaoping Cheng
- Department of PET/CT, the First Affiliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital Affiliated to Shandong University, Jinan, Shandong 250014, China
| | - Xue Xie
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong 271016, China
| | - Kun Li
- Department of PET/CT, the First Affiliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital Affiliated to Shandong University, Jinan, Shandong 250014, China
| | - Yanhua Duan
- Department of PET/CT, the First Affiliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital Affiliated to Shandong University, Jinan, Shandong 250014, China
| | - Min Li
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong 271016, China
| | - Chao Ma
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong 271016, China
| | - Sijin Liu
- Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong 250100, China
- State Key Laboratory of Environment Chemistry and Ecotoxicology, Research Center for Eco-Environment Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Jianfeng Qiu
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong 271016, China
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8
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Mallet J, Godin O, Le Strat Y, Mazer N, Berna F, Boyer L, Capdevielle D, Clauss J, Chéreau I, D'Amato T, Dubreucq J, Leigner S, Llorca PM, Misdrahi D, Passerieux C, Rey R, Pignon B, Urbach M, Schürhoff F, Fond G, Dubertret C. Handedness as a neurodevelopmental marker in schizophrenia: Results from the FACE-SZ cohort. World J Biol Psychiatry 2022; 23:525-536. [PMID: 34918618 DOI: 10.1080/15622975.2021.2013094] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
OBJECTIVES High rates of non-right-handedness (NRH) including mixed-handedness have been reported in neurodevelopmental disorders. In schizophrenia (SZ), atypical handedness has been inconsistently related to impaired features. We aimed to determine whether SZ subjects with NRH and mixed-handedness had poorer clinical and cognitive outcomes compared to their counterparts. METHODS 667 participants were tested with a battery of neuropsychological tests, and assessed for laterality using the Edinburg Handedness Inventory. Clinical symptomatology was assessed. Learning disorders and obstetrical complications were recorded. Biological parameters were explored. RESULTS The prevalence of NRH and mixed-handedness was high (respectively, 42.4% and 34.1%). In the multivariable analyses, NRH was associated with cannabis use disorder (p = 0.045). Mixed-handedness was associated with positive symptoms (p = 0.041), current depressive disorder (p = 0.005)), current cannabis use (p = 0.024) and less akathisia (p = 0.019). A history of learning disorder was associated with NRH. No association was found with cognition, trauma history, obstetrical complications, psychotic symptoms, peripheral inflammation. CONCLUSIONS Non-right and mixed-handedness are very high in patients with SZ, possibly reflecting a neurodevelopmental origin. NRH is associated with learning disorders and cannabis use. Mixed-handedness is associated with positive symptoms, current depressive disorder, cannabis use and less akathisia. However, this study did not confirm greater cognitive impairment in these patients.
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Affiliation(s)
- Jasmina Mallet
- Institute of Psychiatry and Neuroscience of Paris, Université de Paris INSERM UMR1266, Paris, France.,AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, Service de Psychiatrie et Addictologie, Hôpital Louis Mourier, Colombes, France.,Fondation Fondamental F94010, Créteil, France
| | - Ophélia Godin
- Fondation Fondamental F94010, Créteil, France.,UPEC, Créteil, France Inserm, U955, Equipe 15 Psychiatrie Génétique, Créteil, France AP-HP, Hôpital H. Mondor-A. Chenevier, Pôle de Psychiatrie, Créteil, France Fondation FondaMental, Fondation de Cooperation Scientifique, Université Paris-Est, UMR_S955, Créteil, France
| | - Yann Le Strat
- Institute of Psychiatry and Neuroscience of Paris, Université de Paris INSERM UMR1266, Paris, France.,AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, Service de Psychiatrie et Addictologie, Hôpital Louis Mourier, Colombes, France.,Fondation Fondamental F94010, Créteil, France
| | - Nicolas Mazer
- Institute of Psychiatry and Neuroscience of Paris, Université de Paris INSERM UMR1266, Paris, France.,AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, Service de Psychiatrie et Addictologie, Hôpital Louis Mourier, Colombes, France.,Fondation Fondamental F94010, Créteil, France
| | - Fabrice Berna
- Fondation Fondamental F94010, Créteil, France.,Fédération de Médecine Translationnelle de Strasbourg, Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, INSERM U1114, Strasbourg, France
| | - Laurent Boyer
- School of medicine - La Timone Medical Campus, EA 3279: CEReSS - Health Service Research and Quality of Life Center, AP-HM, Aix-Marseille University, Marseille, France
| | - Delphine Capdevielle
- Fondation Fondamental F94010, Créteil, France.,Service Universitaire de Psychiatrie Adulte, Hôpital la Colombière, CHRU Montpellier, Université Montpellier 1, Montpellier, France
| | - Julie Clauss
- Fondation Fondamental F94010, Créteil, France.,Fédération de Médecine Translationnelle de Strasbourg, Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, INSERM U1114, Strasbourg, France
| | - Isabelle Chéreau
- Fondation Fondamental F94010, Créteil, France.,CHU Clermont-Ferrand, Department of Psychiatry, University of Clermont Auvergne, Clermont-Ferrand, France
| | - Thierry D'Amato
- Fondation Fondamental F94010, Créteil, France.,INSERM U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Université Claude Bernard Lyon 1, Equipe PSYR2, Centre Hospitalier Le Vinatier, Lyon, France
| | - Julien Dubreucq
- Fondation Fondamental F94010, Créteil, France.,Centre Référent de Réhabilitation Psychosociale et de Remédiation Cognitive (C3R), CH Alpes Isère, Saint-Egrève, France
| | - Sylvain Leigner
- Fondation Fondamental F94010, Créteil, France.,Centre Référent de Réhabilitation Psychosociale et de Remédiation Cognitive (C3R), CH Alpes Isère, Saint-Egrève, France
| | - Pierre-Michel Llorca
- Fondation Fondamental F94010, Créteil, France.,CHU Clermont-Ferrand, Department of Psychiatry, University of Clermont Auvergne, Clermont-Ferrand, France
| | - David Misdrahi
- Fondation Fondamental F94010, Créteil, France.,Department of Adult Psychiatry, Charles Perrens Hospital, Bordeaux, France, University of Bordeaux, Laboratory of Nutrition and Integrative Neurobiology (UMR INRA 1286), France
| | - Christine Passerieux
- Fondation Fondamental F94010, Créteil, France.,Service Universitaire de Psychiatrie d'Adultes, Centre Hospitalier de Versailles, Le Chesnay, France
| | - Romain Rey
- Fondation Fondamental F94010, Créteil, France.,INSERM U1028, CNRS UMR5292, Centre de Recherche en Neurosciences de Lyon, Université Claude Bernard Lyon 1, Equipe PSYR2, Centre Hospitalier Le Vinatier, Lyon, France
| | - Baptiste Pignon
- Fondation Fondamental F94010, Créteil, France.,UPEC, Créteil, France Inserm, U955, Equipe 15 Psychiatrie Génétique, Créteil, France AP-HP, Hôpital H. Mondor-A. Chenevier, Pôle de Psychiatrie, Créteil, France Fondation FondaMental, Fondation de Cooperation Scientifique, Université Paris-Est, UMR_S955, Créteil, France
| | - Mathieu Urbach
- Fondation Fondamental F94010, Créteil, France.,Service Universitaire de Psychiatrie d'Adultes, Centre Hospitalier de Versailles, Le Chesnay, France.,Laboratoire HandiRESP, EA4047, UFR des Sciences de la Santé Simone Veil, Université de Versailles Saint-Quentin-En-Yvelines, Montigny-le-Bretonneux, France
| | - Franck Schürhoff
- Fondation Fondamental F94010, Créteil, France.,UPEC, Créteil, France Inserm, U955, Equipe 15 Psychiatrie Génétique, Créteil, France AP-HP, Hôpital H. Mondor-A. Chenevier, Pôle de Psychiatrie, Créteil, France Fondation FondaMental, Fondation de Cooperation Scientifique, Université Paris-Est, UMR_S955, Créteil, France
| | - Guillaume Fond
- Fondation Fondamental F94010, Créteil, France.,School of medicine - La Timone Medical Campus, EA 3279: CEReSS - Health Service Research and Quality of Life Center, AP-HM, Aix-Marseille University, Marseille, France
| | - Caroline Dubertret
- Institute of Psychiatry and Neuroscience of Paris, Université de Paris INSERM UMR1266, Paris, France.,AP-HP, Groupe Hospitalo-Universitaire AP-HP Nord, Service de Psychiatrie et Addictologie, Hôpital Louis Mourier, Colombes, France.,Fondation Fondamental F94010, Créteil, France
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9
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Mallet J, Godin O, Mazer N, Le Strat Y, Bellivier F, Belzeaux R, Etain B, Fond G, Gard S, Henry C, Leboyer M, Llorca PM, Loftus J, Olié E, Passerieux C, Polosan M, Schwan R, Roux P, Dubertret C. Handedness in bipolar disorders is associated with specific neurodevelopmental features: results of the BD-FACE cohort. Eur Arch Psychiatry Clin Neurosci 2022; 272:827-838. [PMID: 34374842 DOI: 10.1007/s00406-021-01314-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 07/26/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVES High rates of non-right-handedness (NRH) and mixed-handedness exist in neurodevelopmental disorders. Dysfunctional neurodevelopmental pathways may be implicated in the underlying pathophysiology of bipolar disorders (BD), at least in some subgroups. Yet little is known about correlates of NRH and mixed-handedness in BD. The objectives of this national study are to determine (i) the prevalence of NRH and mixed-handedness in a well-stabilized sample of BD individuals; (ii) if NRH/mixed-handedness in BD is associated with a different clinical, biological and neurocognitive profile. METHODS We included 2174 stabilized individuals. Participants were tested with a comprehensive battery of neuropsychological tests. Handedness was assessed using a single oral question. Learning and/or language disorders and obstetrical complications were recorded using childhood records. Common environmental, clinical and biological parameters were assessed. RESULTS The prevalence of NRH and mixed-handedness were, respectively, 11.6 and 2.4%. Learning/language disorders were found in 9.7% out of the total sample and were associated with atypical handedness (only dyslexia for mixed-handedness (p < 0.01), and dyslexia and dysphasia for NRH (p = 0.01 and p = 0.04, respectively). In multivariate analyses, NRH was associated with a younger age of BD onset (aOR 0.98 (95% CI 0.96-0.99) and lifetime substance use disorder (aOR 1.40 (95% CI 1.03-1.82) but not with any of the cognitive subtasks. Mixed-handedness was associated in univariate analyses with lifetime substance use disorder, lifetime cannabis use disorder (all p < 0.01) and less mood stabilizer prescription (p = 0.028). No association was found between NRH or mixed-handedness and the following parameters: trauma history, obstetrical complications, prior psychotic symptoms, bipolar subtype, attention deficit/hyperactivity disorder, peripheral inflammation or body mass index. CONCLUSIONS Handedness may be associated with specific features in BD, possibly reflecting a specific subgroup with a neurodevelopmental load.
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Affiliation(s)
- Jasmina Mallet
- Fondation Fondamental, Créteil, France.
- Faculté de médecine, AP-HP, Department of Psychiatry, Université de Paris, Louis Mourier Hospital, CHU Louis Mourier, 178 rue des Renouillers, 92700, Colombes, France.
- INSERM UMR1266, Institute of Psychiatry and Neuroscience of Paris, University Paris Descartes, Paris, France.
| | - Ophélia Godin
- Fondation Fondamental, Créteil, France
- UMR_S955, UPEC, Créteil, France Inserm, Université Paris-Est, U955, Equipe 15 Psychiatrie génétique, Créteil, France
- AP-HP, Hôpital H. Mondor-A. Chenevier, Pôle de psychiatrie, Créteil, France
| | - Nicolas Mazer
- Fondation Fondamental, Créteil, France
- Faculté de médecine, AP-HP, Department of Psychiatry, Université de Paris, Louis Mourier Hospital, CHU Louis Mourier, 178 rue des Renouillers, 92700, Colombes, France
- INSERM UMR1266, Institute of Psychiatry and Neuroscience of Paris, University Paris Descartes, Paris, France
| | - Yann Le Strat
- Fondation Fondamental, Créteil, France
- Faculté de médecine, AP-HP, Department of Psychiatry, Université de Paris, Louis Mourier Hospital, CHU Louis Mourier, 178 rue des Renouillers, 92700, Colombes, France
- INSERM UMR1266, Institute of Psychiatry and Neuroscience of Paris, University Paris Descartes, Paris, France
| | - Frank Bellivier
- Fondation Fondamental, Créteil, France
- AP-HP, GH Saint-Louis-Lariboisière-Fernand Widal, Pôle Neurosciences Tête et Cou, INSERM UMRS 1144, University Paris Diderot, Paris, France
| | - Raoul Belzeaux
- Fondation Fondamental, Créteil, France
- AP-HM, Department of Psychiatry, Marseille, France
- INT-UMR7289, CNRS Aix Marseille University, Marseille, France
| | - Bruno Etain
- Fondation Fondamental, Créteil, France
- AP-HP, GH Saint-Louis-Lariboisière-Fernand Widal, Pôle Neurosciences Tête et Cou, INSERM UMRS 1144, University Paris Diderot, Paris, France
| | - Guillaume Fond
- Fondation Fondamental, Créteil, France
- AP-HM, Aix-Marseille University, School of Medicine-La Timone Medical Campus, EA 3279: CEReSS-Health Service Research and Quality of Life Center, 27 Boulevard Jean Moulin, 13005, Marseille, France
| | - Sébastien Gard
- Fondation Fondamental, Créteil, France
- Centre Expert Troubles Bipolaires, Service de Psychiatrie Adulte, Hôpital Charles-Perrens, Bordeaux, France
| | - Chantal Henry
- Fondation Fondamental, Créteil, France
- Department of Psychiatry, Service Hospitalo-Universitaire, GHU Paris Psychiatrie and Neurosciences, 75014, Paris, France
| | - Marion Leboyer
- Fondation Fondamental, Créteil, France
- UMR_S955, UPEC, Créteil, France Inserm, Université Paris-Est, U955, Equipe 15 Psychiatrie génétique, Créteil, France
- AP-HP, Hôpital H. Mondor-A. Chenevier, Pôle de psychiatrie, Créteil, France
- Fondation de Cooperation Scientifique, Fondation FondaMental, Créteil, France
| | - Pierre-Michel Llorca
- Fondation Fondamental, Créteil, France
- CHU Clermont-Ferrand, Department of Psychiatry, University of Clermont Auvergne, EA 7280, Clermont-Ferrand, France
| | - Joséphine Loftus
- Fondation Fondamental, Créteil, France
- Pôle de Psychiatrie, Centre Hospitalier Princesse Grace, Monaco, France
| | - Emilie Olié
- Fondation Fondamental, Créteil, France
- Department of Emergency Psychiatry and Acute Care, CHU Montpellier, INSERM U1061, Montpellier University, Montpellier, France
| | - Christine Passerieux
- Fondation Fondamental, Créteil, France
- Service Universitaire de Psychiatrie d'Adultes et d'Addictologie, Centre Hospitalier de Versailles, 177 rue de Versailles, 78157, Le Chesnay, France
- CESP, INSERM, Université Paris Saclay, Université de Versailles Saint-Quentin-En-Yvelines, 2 Avenue de la Source de la Bièvre, 78180, Montigny-le-Bretonneux, France
| | - Mircea Polosan
- Fondation Fondamental, Créteil, France
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut des Neurosciences, CHU Grenoble Alpes, 38000, Grenoble, France
| | - Raymund Schwan
- Faculté de médecine, AP-HP, Department of Psychiatry, Université de Paris, Louis Mourier Hospital, CHU Louis Mourier, 178 rue des Renouillers, 92700, Colombes, France
- CHRU de Nancy et Pôle de Psychiatrie et Psychologie Clinique, Université de Lorraine, Centre Psychothérapique de Nancy, Nancy, France
| | - Paul Roux
- Fondation Fondamental, Créteil, France
- Service Universitaire de Psychiatrie d'Adultes et d'Addictologie, Centre Hospitalier de Versailles, 177 rue de Versailles, 78157, Le Chesnay, France
- CESP, INSERM, Université Paris Saclay, Université de Versailles Saint-Quentin-En-Yvelines, 2 Avenue de la Source de la Bièvre, 78180, Montigny-le-Bretonneux, France
| | - Caroline Dubertret
- Fondation Fondamental, Créteil, France
- Faculté de médecine, AP-HP, Department of Psychiatry, Université de Paris, Louis Mourier Hospital, CHU Louis Mourier, 178 rue des Renouillers, 92700, Colombes, France
- INSERM UMR1266, Institute of Psychiatry and Neuroscience of Paris, University Paris Descartes, Paris, France
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10
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Zhao W, Voon V, Xue K, Xie C, Kang J, Lin CP, Wang J, Cheng J, Feng J. Common abnormal connectivity in first-episode and chronic schizophrenia in pre- and post-central regions: Implications for neuromodulation targeting. Prog Neuropsychopharmacol Biol Psychiatry 2022; 117:110556. [PMID: 35367293 DOI: 10.1016/j.pnpbp.2022.110556] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 03/23/2022] [Accepted: 03/27/2022] [Indexed: 11/30/2022]
Abstract
Schizophrenia is a neurodevelopmental disorder manifesting differing impairments at early onset and chronic disease stages. Brain imaging research suggests a core pathological region in patients with first-episode schizophrenia is Broca's area. With disease progression, alterations in thalamic connectivity becomes more prevalent. Understanding the common circuitry underlying pathology in these two groups might highlight a critical common network and novel targets for treatment. In this study, 937 subject samples were collected including patients with first-episode schizophrenia and those with chronic schizophrenia. We used hypothesis-based voxel-level functional connectivity analyses to calculate functional connectivity using the left Broca's area and thalamus as regions of interest in those with first-episode and chronic schizophrenia, respectively. We show for the first time that in both patients with first-episode and chronic schizophrenia the greatest functional connectivity disruption ended in the pre- and postcentral regions. At the early-onset stage, the core brain region is abnormally connected to pre- and postcentral areas responsible for mouth movement, while in the chronic stage, it expanded to a wider range of sensorimotor areas. Our findings suggest that expanding the focus on the low-order sensory-motor systems beyond high-order cognitive impairments in schizophrenia may show potential for neuromodulation treatment, given the relative accessibility of these cortical regions and their functional and structural connections to the core region at different stages of illness.
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Affiliation(s)
- Wei Zhao
- MOE-LCSM, School of Mathematics and Statistics, Hunan Normal University, Changsha, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Kangkang Xue
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Ching-Po Lin
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders (No. 13dz2260500), Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, China; Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China; Shanghai Center for Mathematical Sciences, Shanghai, China.
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11
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Jiang Y, Yao D, Zhou J, Tan Y, Huang H, Wang M, Chang X, Duan M, Luo C. Characteristics of disrupted topological organization in white matter functional connectome in schizophrenia. Psychol Med 2022; 52:1333-1343. [PMID: 32880241 DOI: 10.1017/s0033291720003141] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Neuroimaging characteristics have demonstrated disrupted functional organization in schizophrenia (SZ), involving large-scale networks within grey matter (GM). However, previous studies have ignored the role of white matter (WM) in supporting brain function. METHODS Using resting-state functional MRI and graph theoretical approaches, we investigated global topological disruptions of large-scale WM and GM networks in 93 SZ patients and 122 controls. Six global properties [clustering coefficient (Cp), shortest path length (Lp), local efficiency (Eloc), small-worldness (σ), hierarchy (β) and synchronization (S) and three nodal metrics [nodal degree (Knodal), nodal efficiency (Enodal) and nodal betweenness (Bnodal)] were utilized to quantify the topological organization in both WM and GM networks. RESULTS At the network level, both WM and GM networks exhibited reductions in Eloc, Cp and S in SZ. The SZ group showed reduced σ and β only for the WM network. Furthermore, the Cp, Eloc and S of the WM network were negatively correlated with negative symptoms in SZ. At the nodal level, the SZ showed nodal disturbances in the corpus callosum, optic radiation, posterior corona radiata and tempo-occipital WM tracts. For GM, the SZ manifested increased nodal centralities in frontoparietal regions and decreased nodal centralities in temporal regions. CONCLUSIONS These findings provide the first evidence for abnormal global topological properties in SZ from the perspective of a substantial whole brain, including GM and WM. Nodal centralities enhance GM areas, along with a reduction in adjacent WM, suggest that WM functional alterations may be compensated for adjacent GM impairments in SZ.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, P. R. China
| | - Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Yue Tan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - MeiLin Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Xin Chang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Department of Psychiatry, Chengdu Mental Health Center, Chengdu, P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, P. R. China
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12
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Gutman BA, van Erp TG, Alpert K, Ching CRK, Isaev D, Ragothaman A, Jahanshad N, Saremi A, Zavaliangos‐Petropulu A, Glahn DC, Shen L, Cong S, Alnæs D, Andreassen OA, Doan NT, Westlye LT, Kochunov P, Satterthwaite TD, Wolf DH, Huang AJ, Kessler C, Weideman A, Nguyen D, Mueller BA, Faziola L, Potkin SG, Preda A, Mathalon DH, Bustillo J, Calhoun V, Ford JM, Walton E, Ehrlich S, Ducci G, Banaj N, Piras F, Piras F, Spalletta G, Canales‐Rodríguez EJ, Fuentes‐Claramonte P, Pomarol‐Clotet E, Radua J, Salvador R, Sarró S, Dickie EW, Voineskos A, Tordesillas‐Gutiérrez D, Crespo‐Facorro B, Setién‐Suero E, van Son JM, Borgwardt S, Schönborn‐Harrisberger F, Morris D, Donohoe G, Holleran L, Cannon D, McDonald C, Corvin A, Gill M, Filho GB, Rosa PGP, Serpa MH, Zanetti MV, Lebedeva I, Kaleda V, Tomyshev A, Crow T, James A, Cervenka S, Sellgren CM, Fatouros‐Bergman H, Agartz I, Howells F, Stein DJ, Temmingh H, Uhlmann A, de Zubicaray GI, McMahon KL, Wright M, Cobia D, Csernansky JG, Thompson PM, Turner JA, Wang L. A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium. Hum Brain Mapp 2022; 43:352-372. [PMID: 34498337 PMCID: PMC8675416 DOI: 10.1002/hbm.25625] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/13/2021] [Accepted: 07/14/2021] [Indexed: 01/06/2023] Open
Abstract
Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.
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Affiliation(s)
- Boris A. Gutman
- Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoIllinoisUSA
- Institute for Information Transmission Problems (Kharkevich Institute)MoscowRussia
| | - Theo G.M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
- Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
| | - Kathryn Alpert
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Dmitry Isaev
- Department of Biomedical EngineeringDuke UniversityDurhamNorth CarolinaUSA
| | - Anjani Ragothaman
- Department of biomedical engineeringOregon Health and Science universityPortlandOregonUSA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Arvin Saremi
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Artemis Zavaliangos‐Petropulu
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - David C. Glahn
- Department of PsychiatryBoston Children's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Li Shen
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Shan Cong
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Dag Alnæs
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Ole Andreas Andreassen
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Nhat Trung Doan
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Lars T. Westlye
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
| | - Peter Kochunov
- Department of PsychiatryUniversity of Maryland School of MedicineBaltimoreMarylandUSA
| | - Theodore D. Satterthwaite
- Department of PsychiatryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Daniel H. Wolf
- Department of PsychiatryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvaniaUSA
| | - Alexander J. Huang
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Charles Kessler
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Andrea Weideman
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Dana Nguyen
- Department of PediatricsUniversity of California IrvineIrvineCaliforniaUSA
| | - Bryon A. Mueller
- Department of Psychiatry and Behavioral SciencesUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Lawrence Faziola
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Steven G. Potkin
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Adrian Preda
- Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
| | - Daniel H. Mathalon
- Department of Psychiatry and Weill Institute for NeurosciencesUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Judith Ford Mental HealthVA San Francisco Healthcare SystemSan FranciscoCaliforniaUSA
| | - Juan Bustillo
- Departments of Psychiatry & NeuroscienceUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Vince Calhoun
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology]Emory UniversityAtlantaGeorgiaUSA
- Department of Electrical and Computer EngineeringThe University of New MexicoAlbuquerqueNew MexicoUSA
| | - Judith M. Ford
- Judith Ford Mental HealthVA San Francisco Healthcare SystemSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | | | - Stefan Ehrlich
- Division of Psychological & Social Medicine and Developmental NeurosciencesFaculty of Medicine, TU‐DresdenDresdenGermany
| | | | - Nerisa Banaj
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Fabrizio Piras
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Federica Piras
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
| | - Gianfranco Spalletta
- Laboratory of NeuropsychiatryIRCCS Santa Lucia FoundationRomeItaly
- Menninger Department of Psychiatry and Behavioral SciencesBaylor College of MedicineHoustonTexasUSA
| | | | | | | | - Joaquim Radua
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
- Institut d'Investigacions Biomdiques August Pi i Sunyer (IDIBAPS)BarcelonaSpain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research FoundationCIBERSAMBarcelonaSpain
| | - Erin W. Dickie
- Centre for Addiction and Mental Health (CAMH)TorontoCanada
| | | | | | | | | | | | - Stefan Borgwardt
- Department of PsychiatryUniversity of BaselBaselSwitzerland
- Department of Psychiatry and PsychotherapyUniversity of LübeckLübeckGermany
| | | | - Derek Morris
- Centre for Neuroimaging and Cognitive Genomics, Discipline of BiochemistryNational University of Ireland GalwayGalwayIreland
| | - Gary Donohoe
- Centre for Neuroimaging and Cognitive Genomics, School of PsychologyNational University of Ireland GalwayGalwayIreland
| | - Laurena Holleran
- Centre for Neuroimaging and Cognitive Genomics, School of PsychologyNational University of Ireland GalwayGalwayIreland
| | - Dara Cannon
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive GenomicsNational University of Ireland GalwayGalwayIreland
| | - Colm McDonald
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive GenomicsNational University of Ireland GalwayGalwayIreland
| | - Aiden Corvin
- Neuropsychiatric Genetics Research Group, Department of PsychiatryTrinity College DublinDublinIreland
- Trinity College Institute of NeuroscienceTrinity College DublinDublinIreland
| | - Michael Gill
- Neuropsychiatric Genetics Research Group, Department of PsychiatryTrinity College DublinDublinIreland
- Trinity College Institute of NeuroscienceTrinity College DublinDublinIreland
| | - Geraldo Busatto Filho
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Pedro G. P. Rosa
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Mauricio H. Serpa
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
| | - Marcus V. Zanetti
- Laboratory of Psychiatric Neuroimaging (LIM‐21), Departamento e Instituto de PsiquiatriaHospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao PauloSao PauloSPBrazil
- Hospital Sirio‐LibanesSao PauloSPBrazil
| | - Irina Lebedeva
- Laboratory of Neuroimaging and Multimodal AnalysisMental Health Research CenterMoscowRussia
| | - Vasily Kaleda
- Department of Endogenous Mental DisordersMental Health Research CenterMoscowRussia
| | - Alexander Tomyshev
- Laboratory of Neuroimaging and Multimodal AnalysisMental Health Research CenterMoscowRussia
| | - Tim Crow
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Anthony James
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Simon Cervenka
- Centre for Psychiatry Reserach, Department of Clinical NeuroscienceKarolinska Institutet, & Stockholm Health Care Services, Region StockholmStockholmSweden
| | - Carl M Sellgren
- Department of Physiology and PharmacologyKarolinska InstitutetStockholmSweden
| | - Helena Fatouros‐Bergman
- Centre for Psychiatry Reserach, Department of Clinical NeuroscienceKarolinska Institutet, & Stockholm Health Care Services, Region StockholmStockholmSweden
| | - Ingrid Agartz
- NORMENT, Division of Mental Health and AddictionOslo University Hospital & Institute of Clinical Medicine, University of OsloOsloNorway
| | - Fleur Howells
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Neuroscience InstituteUniversity of Cape Town, Cape TownWCSouth Africa
| | - Dan J. Stein
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Neuroscience InstituteUniversity of Cape Town, Cape TownWCSouth Africa
- SA MRC Unit on Risk & Resilience in Mental DisordersUniversity of Cape TownCape TownWCSouth Africa
| | - Henk Temmingh
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
| | - Anne Uhlmann
- Department of Psychiatry and Mental Health, Faculty of Health SciencesUniversity of Cape TownCape TownWCSouth Africa
- Department of Child and Adolescent PsychiatryTU DresdenGermany
| | - Greig I. de Zubicaray
- School of Psychology, Faculty of HealthQueensland University of Technology (QUT)BrisbaneQLDAustralia
| | - Katie L. McMahon
- School of Clinical SciencesQueensland University of Technology (QUT)BrisbaneQLDAustralia
| | - Margie Wright
- Queensland Brain InstituteUniversity of QueenslandBrisbaneQLDAustralia
| | - Derin Cobia
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
- Department of Psychology and Neuroscience CenterBrigham Young UniversityProvoUtahUSA
| | - John G. Csernansky
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | | | - Lei Wang
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
- Department of Psychiatry and Behavioral HealthOhio State University Wexner Medical CenterColumbusOhioUSA
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13
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Palaniyappan L, Du J, Zhang J, Feng J. Reply to: "Historical pursuits of the language pathway hypothesis of schizophrenia". NPJ SCHIZOPHRENIA 2021; 7:54. [PMID: 34753936 PMCID: PMC8578441 DOI: 10.1038/s41537-021-00183-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Accepted: 09/13/2021] [Indexed: 12/12/2022]
Affiliation(s)
- Lena Palaniyappan
- Department of Psychiatry and Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
- Lawson Health Research Institute, London, Ontario, Canada
| | - Jingnan Du
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, 200030, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK.
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14
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Jiang Y, Duan M, Li X, Huang H, Zhao G, Li X, Li S, Song X, He H, Yao D, Luo C. Function-structure coupling: White matter functional magnetic resonance imaging hyper-activation associates with structural integrity reductions in schizophrenia. Hum Brain Mapp 2021; 42:4022-4034. [PMID: 34110075 PMCID: PMC8288085 DOI: 10.1002/hbm.25536] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 05/04/2021] [Accepted: 05/08/2021] [Indexed: 01/12/2023] Open
Abstract
White matter (WM) microstructure deficit may be an underlying factor in the brain dysconnectivity hypothesis of schizophrenia using diffusion tensor imaging (DTI). However, WM dysfunction is unclear in schizophrenia. This study aimed to investigate the association between structural deficits and functional disturbances in major WM tracts in schizophrenia. Using functional magnetic resonance imaging (fMRI) and DTI, we developed the skeleton-based WM functional analysis, which could achieve voxel-wise function-structure coupling by projecting the fMRI signals onto a skeleton in WM. We measured the fractional anisotropy (FA) and WM low-frequency oscillation (LFO) and their couplings in 93 schizophrenia patients and 122 healthy controls (HCs). An independent open database (62 schizophrenia patients and 71 HCs) was used to test the reproducibility. Finally, associations between WM LFO and five behaviour assessment categories (cognition, emotion, motor, personality and sensory) were examined. This study revealed a reversed pattern of structure and function in frontotemporal tracts, as follows. (a) WM hyper-LFO was associated with reduced FA in schizophrenia. (b) The function-structure association was positive in HCs but negative in schizophrenia patients. Furthermore, function-structure dissociation was exacerbated by long illness duration and severe negative symptoms. (c) WM activations were significantly related to cognition and emotion. This study indicated function-structure dys-coupling, with higher LFO and reduced structural integration in frontotemporal WM, which may reflect a potential mechanism in WM neuropathologic processing of schizophrenia.
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Affiliation(s)
- Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Mingjun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Department of Psychiatry, Chengdu Mental Health CenterInstitute of Chengdu Brain Science in University of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xiangkui Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Guocheng Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Department of Radiology, Chengdu Mental Health CenterInstitute of Chengdu Brain Science in University of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xuan Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Shicai Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Department of Psychiatry, Chengdu Mental Health CenterInstitute of Chengdu Brain Science in University of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Xufeng Song
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Department of Psychiatry, Chengdu Mental Health CenterInstitute of Chengdu Brain Science in University of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical SciencesChengduPeople's Republic of China
- Department of NeurologyThe First Affiliated Hospital of Hainan Medical UniversityHaikouPeople's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduPeople's Republic of China
- Research Unit of NeuroInformation (2019RU035), Chinese Academy of Medical SciencesChengduPeople's Republic of China
- Department of NeurologyThe First Affiliated Hospital of Hainan Medical UniversityHaikouPeople's Republic of China
- Radiation Oncology Key Laboratory of Sichuan ProvinceSichuan Cancer HospitalChengduPeople's Republic of China
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15
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Abstract
China accounts for 17% of the global disease burden attributable to mental, neurological and substance use disorders. As a country undergoing profound societal change, China faces growing challenges to reduce the disease burden caused by psychiatric disorders. In this review, we aim to present an overview of progress in neuroscience research and clinical services for psychiatric disorders in China during the past three decades, analysing contributing factors and potential challenges to the field development. We first review studies in the epidemiological, genetic and neuroimaging fields as examples to illustrate a growing contribution of studies from China to the neuroscience research. Next, we introduce large-scale, open-access imaging genetic cohorts and recently initiated brain banks in China as platforms to study healthy brain functions and brain disorders. Then, we show progress in clinical services, including an integration of hospital and community-based healthcare systems and early intervention schemes. We finally discuss opportunities and existing challenges: achievements in research and clinical services are indispensable to the growing funding investment and continued engagement in international collaborations. The unique aspect of traditional Chinese medicine may provide insights to develop a novel treatment for psychiatric disorders. Yet obstacles still remain to promote research quality and to provide ubiquitous clinical services to vulnerable populations. Taken together, we expect to see a sustained advancement in psychiatric research and healthcare system in China. These achievements will contribute to the global efforts to realize good physical, mental and social well-being for all individuals.
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16
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Choe HN, Jarvis ED. The role of sex chromosomes and sex hormones in vocal learning systems. Horm Behav 2021; 132:104978. [PMID: 33895570 DOI: 10.1016/j.yhbeh.2021.104978] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 12/12/2022]
Abstract
Vocal learning is the ability to imitate and modify sounds through auditory experience, a rare trait found in only a few lineages of mammals and birds. It is a critical component of human spoken language, allowing us to verbally transmit speech repertoires and knowledge across generations. In many vocal learning species, the vocal learning trait is sexually dimorphic, where it is either limited to males or present in both sexes to different degrees. In humans, recent findings have revealed subtle sexual dimorphism in vocal learning/spoken language brain regions and some associated disorders. For songbirds, where the neural mechanisms of vocal learning have been well studied, vocal learning appears to have been present in both sexes at the origin of the lineage and was then independently lost in females of some subsequent lineages. This loss is associated with an interplay between sex chromosomes and sex steroid hormones. Even in species with little dimorphism, like humans, sex chromosomes and hormones still have some influence on learned vocalizations. Here we present a brief synthesis of these studies, in the context of sex determination broadly, and identify areas of needed investigation to further understand how sex chromosomes and sex steroid hormones help establish sexually dimorphic neural structures for vocal learning.
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Affiliation(s)
- Ha Na Choe
- Duke University Medical Center, The Rockefeller University, Howard Hughes Medical Institute, United States of America.
| | - Erich D Jarvis
- Duke University Medical Center, The Rockefeller University, Howard Hughes Medical Institute, United States of America.
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17
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Du J, Palaniyappan L, Liu Z, Cheng W, Gong W, Zhu M, Wang J, Zhang J, Feng J. The genetic determinants of language network dysconnectivity in drug-naïve early stage schizophrenia. NPJ SCHIZOPHRENIA 2021; 7:18. [PMID: 33658499 PMCID: PMC7930279 DOI: 10.1038/s41537-021-00141-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Accepted: 01/12/2021] [Indexed: 01/31/2023]
Abstract
Schizophrenia is a neurocognitive illness of synaptic and brain network-level dysconnectivity that often reaches a persistent chronic stage in many patients. Subtle language deficits are a core feature even in the early stages of schizophrenia. However, the primacy of language network dysconnectivity and language-related genetic variants in the observed phenotype in early stages of illness remains unclear. This study used two independent schizophrenia dataset consisting of 138 and 53 drug-naïve first-episode schizophrenia (FES) patients, and 112 and 56 healthy controls, respectively. A brain-wide voxel-level functional connectivity analysis was conducted to investigate functional dysconnectivity and its relationship with illness duration. We also explored the association between critical language-related genetic (such as FOXP2) mutations and the altered functional connectivity in patients. We found elevated functional connectivity involving Broca's area, thalamus and temporal cortex that were replicated in two FES datasets. In particular, Broca's area - anterior cingulate cortex dysconnectivity was more pronounced for patients with shorter illness duration, while thalamic dysconnectivity was predominant in those with longer illness duration. Polygenic risk scores obtained from FOXP2-related genes were strongly associated with functional dysconnectivity identified in patients with shorter illness duration. Our results highlight the criticality of language network dysconnectivity, involving the Broca's area in early stages of schizophrenia, and the role of language-related genes in this aberration, providing both imaging and genetic evidence for the association between schizophrenia and the determinants of language.
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Affiliation(s)
- Jingnan Du
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Lena Palaniyappan
- Department of Psychiatry and Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Lawson Health Research Institute, London, ON, Canada
| | - Zhaowen Liu
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Weikang Gong
- Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Mengmeng Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, UK.
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18
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Liloia D, Brasso C, Cauda F, Mancuso L, Nani A, Manuello J, Costa T, Duca S, Rocca P. Updating and characterizing neuroanatomical markers in high-risk subjects, recently diagnosed and chronic patients with schizophrenia: A revised coordinate-based meta-analysis. Neurosci Biobehav Rev 2021; 123:83-103. [PMID: 33497790 DOI: 10.1016/j.neubiorev.2021.01.010] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 01/07/2021] [Accepted: 01/15/2021] [Indexed: 01/10/2023]
Abstract
Characterizing neuroanatomical markers of different stages of schizophrenia (SZ) to assess pathophysiological models of how the disorder develops is an important target for the clinical practice. We performed a meta-analysis of voxel-based morphometry studies of genetic and clinical high-risk subjects (g-/c-HR), recently diagnosed (RDSZ) and chronic SZ patients (ChSZ). We quantified gray matter (GM) changes associated with these four conditions and compared them with contrast and conjunctional data. We performed the behavioral analysis and networks decomposition of alterations to obtain their functional characterization. Results reveal a cortical-subcortical, left-to-right homotopic progression of GM loss. The right anterior cingulate is the only altered region found altered among c-HR, RDSZ and ChSZ. Contrast analyses show left-lateralized insular, amygdalar and parahippocampal GM reduction in RDSZ, which appears bilateral in ChSZ. Functional decomposition shows involvement of the salience network, with an enlargement of the sensorimotor network in RDSZ and the thalamus-basal nuclei network in ChSZ. These findings support the current neuroprogressive models of SZ and integrate this deterioration with the clinical evolution of the disease.
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Affiliation(s)
- Donato Liloia
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Claudio Brasso
- Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy.
| | - Franco Cauda
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy.
| | - Lorenzo Mancuso
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Andrea Nani
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Jordi Manuello
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Tommaso Costa
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy.
| | - Sergio Duca
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
| | - Paola Rocca
- Department of Neuroscience "Rita Levi Montalcini", University of Turin, Turin, Italy; Neuroscience Institute of Turin (NIT), University of Turin, Turin, Italy.
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19
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Li H, Zhang C, Cai X, Wang L, Luo F, Ma Y, Li M, Xiao X. Genome-wide Association Study of Creativity Reveals Genetic Overlap With Psychiatric Disorders, Risk Tolerance, and Risky Behaviors. Schizophr Bull 2020; 46:1317-1326. [PMID: 32133506 PMCID: PMC7505179 DOI: 10.1093/schbul/sbaa025] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Creativity represents one of the most important and partially heritable human characteristics, yet little is known about its genetic basis. Epidemiological studies reveal associations between creativity and psychiatric disorders as well as multiple personality and behavioral traits. To test whether creativity and these disorders or traits share genetic basis, we performed genome-wide association studies (GWAS) followed by polygenic risk score (PRS) analyses. Two cohorts of Han Chinese subjects (4,834 individuals in total) aged 18-45 were recruited for creativity measurement using typical performance test. After exclusion of the outliers with significantly deviated creativity scores and low-quality genotyping results, 4,664 participants were proceeded for GWAS. We conducted PRS analyses using both the classical pruning and thresholding (P+T) method and the LDpred method. The extent of polygenic risk was estimated through linear regression adjusting for the top 3 genotyping principal components. R2 was used as a measurement of the explained variance. PRS analyses demonstrated significantly positive genetic overlap, respectively, between creativity with schizophrenia ((P+T) method: R2(max) ~ .196%, P = .00245; LDpred method: R2(max) ~ .226%, P = .00114), depression ((P+T) method: R2(max) ~ .178%, P = .00389; LDpred method: R2(max) ~ .093%, P = .03675), general risk tolerance ((P+T) method: R2(max) ~ .177%, P = .00399; LDpred method: R2(max) ~ .305%, P = .00016), and risky behaviors ((P+T) method: R2(max) ~ .187%, P = .00307; LDpred method: R2(max) ~ .155%, P = .00715). Our results suggest that human creativity is probably a polygenic trait affected by numerous variations with tiny effects. Genetic variations that predispose to psychiatric disorders and risky behaviors may underlie part of the genetic basis of creativity, confirming the epidemiological associations between creativity and these traits.
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Affiliation(s)
- Huijuan Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Chuyi Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xin Cai
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Lu Wang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Fang Luo
- Faculty of Psychology, Beijing Normal University, Beijing, China
| | - Yina Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
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20
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Antipsychotic effects of sex hormones and atypical hemispheric asymmetries. Cortex 2020; 127:313-332. [DOI: 10.1016/j.cortex.2020.02.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 02/27/2020] [Accepted: 02/29/2020] [Indexed: 12/16/2022]
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Lin Y, Li M, Zhou Y, Deng W, Ma X, Wang Q, Guo W, Li Y, Jiang L, Hu X, Zhang N, Li T. Age-Related Reduction in Cortical Thickness in First-Episode Treatment-Naïve Patients with Schizophrenia. Neurosci Bull 2019; 35:688-696. [PMID: 30790217 DOI: 10.1007/s12264-019-00348-x] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2018] [Accepted: 10/25/2018] [Indexed: 02/05/2023] Open
Abstract
Substantial evidence supports the neurodevelopmental hypothesis of schizophrenia. Meanwhile, progressive neurodegenerative processes have also been reported, leading to the hypothesis that neurodegeneration is a characteristic component in the neuropathology of schizophrenia. However, a major challenge for the neurodegenerative hypothesis is that antipsychotic drugs used by patients have profound impact on brain structures. To clarify this potential confounding factor, we measured the cortical thickness across the whole brain using high-resolution T1-weighted magnetic resonance imaging in 145 first-episode and treatment-naïve patients with schizophrenia and 147 healthy controls. The results showed that, in the patient group, the frontal, temporal, parietal, and cingulate gyri displayed a significant age-related reduction of cortical thickness. In the control group, age-related cortical thickness reduction was mostly located in the frontal, temporal, and cingulate gyri, albeit to a lesser extent. Importantly, relative to healthy controls, patients exhibited a significantly smaller age-related cortical thickness in the anterior cingulate, inferior temporal, and insular gyri in the right hemisphere. These results provide evidence supporting the existence of neurodegenerative processes in schizophrenia and suggest that these processes already occur in the early stage of the illness.
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Affiliation(s)
- Yin Lin
- Mental Health Centre and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China.,West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu, 610041, China.,Department of Psychology, Shenzhen Children's Hospital, Shenzhen, 518038, China
| | - Mingli Li
- Mental Health Centre and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China.,West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Yi Zhou
- Department of Radiology, Hospital for Chengdu Office of Tibetan Autonomous Region, Branch Hospital of West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Wei Deng
- Mental Health Centre and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China.,West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Xiaohong Ma
- Mental Health Centre and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China.,West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Qiang Wang
- Mental Health Centre and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China.,West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Wanjun Guo
- Mental Health Centre and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China.,West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Yinfei Li
- Mental Health Centre and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China.,West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Lijun Jiang
- Mental Health Centre and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China.,West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Xun Hu
- Huaxi Biobank, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Nanyin Zhang
- Department of Biomedical Engineering, Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA.
| | - Tao Li
- Mental Health Centre and Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, China. .,West China Brain Research Centre, West China Hospital, Sichuan University, Chengdu, 610041, China.
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