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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 2024:sbae110. [PMID: 38982882 DOI: 10.1093/schbul/sbae110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [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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Zhou C, Tang X, Yu M, Zhang H, Zhang X, Gao J, Zhang X, Chen J. Convergent and divergent genes expression profiles associated with brain-wide functional connectome dysfunction in deficit and non-deficit schizophrenia. Transl Psychiatry 2024; 14:124. [PMID: 38413564 PMCID: PMC10899251 DOI: 10.1038/s41398-024-02827-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 02/07/2024] [Accepted: 02/13/2024] [Indexed: 02/29/2024] Open
Abstract
Deficit schizophrenia (DS) is a subtype of schizophrenia characterized by the primary and persistent negative symptoms. Previous studies have identified differences in brain functions between DS and non-deficit schizophrenia (NDS) patients. However, the genetic regulation features underlying these abnormal changes are still unknown. This study aimed to detect the altered patterns of functional connectivity (FC) in DS and NDS and investigate the gene expression profiles underlying these abnormal FC. The study recruited 82 DS patients, 96 NDS patients, and 124 healthy controls (CN). Voxel-based unbiased brain-wide association study was performed to reveal altered patterns of FC in DS and NDS patients. Machine learning techniques were used to access the utility of altered FC for diseases diagnosis. Weighted gene co-expression network analysis (WGCNA) was employed to explore the associations between altered FC and gene expression of 6 donated brains. Enrichment analysis was conducted to identify the genetic profiles, and the spatio-temporal expression patterns of the key genes were further explored. Comparing to CN, 23 and 20 brain regions with altered FC were identified in DS and NDS patients. The altered FC among these regions showed significant correlations with the SDS scores and exhibited high efficiency in disease classification. WGCNA revealed associations between DS/NDS-related gene expression and altered FC. Additionally, 22 overlapped genes, including 12 positive regulation genes and 10 negative regulation genes, were found between NDS and DS. Enrichment analyses demonstrated relationships between identified genes and significant pathways related to cellular response, neuro regulation, receptor binding, and channel activity. Spatial and temporal gene expression profiles of SCN1B showed the lowest expression at the initiation of embryonic development, while DPYSL3 exhibited rapid increased in the fetal. The present study revealed different altered patterns of FC in DS and NDS patients and highlighted the potential value of FC in disease classification. The associations between gene expression and neuroimaging provided insights into specific and common genetic regulation underlying these brain functional changes in DS and NDS, suggesting a potential genetic-imaging pathogenesis of schizophrenia.
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Affiliation(s)
- Chao Zhou
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiaowei Tang
- Department of Psychiatry, Affiliated WuTaiShan Hospital of Medical College of Yangzhou University, Yangzhou, Jiangsu, China
| | - Miao Yu
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongying Zhang
- Department of Radiology, Subei People's Hospital of Jiangsu Province, Yangzhou University, Yangzhou, Jiangsu, China
| | - Xiaobin Zhang
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Ju Gao
- Institute of Mental Health, Suzhou Psychiatric Hospital, The Affiliated Guangji Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Jiu Chen
- Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, Jiangsu, China.
- Medical Imaging Center, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.
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Sun Y, Hou Y, Wang X, Wang H, Yan R, Xue L, Yao Z, Lu Q. Links among genetic variants and hierarchical brain structural and functional networks for antidepressant treatment: A multivariate study. Brain Res 2024; 1822:148661. [PMID: 37918703 DOI: 10.1016/j.brainres.2023.148661] [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: 06/03/2023] [Revised: 10/10/2023] [Accepted: 10/30/2023] [Indexed: 11/04/2023]
Abstract
BACKGROUND Antidepressant treatment effects are strongly heritable and have substantial effects on brain function and structure, but the underlying mechanisms are still poorly understood. In this research, we aimed to evaluate the factors of single nucleotide polymorphisms (SNPs) and hierarchical brain structural and functional networks that were associated with antidepressant treatment. Moreover, we further explored the correlations and mediation pattern among "brain structure-brain function-gene" in major depressive disorder (MDD). METHODS We analysed 405 SNPs and rich club/feeder/local connections of hierarchical structural and functional networks with three-way parallel independent component analysis in 179 MDD patients. The group-discriminative independent components of the three modalities between responders and non-responders of antidepressant treatment were identified. Pearson correlations and mediation analysis were further utilized to investigate the associations among SNPs and connections of the structural and functional networks. RESULTS Notably, correlations with antidepressant treatment outcomes were found in structural, functional and SNP modalities simultaneously. The features of group-discriminative independent components included the shared feeder connections of hub regions with the inferior frontal orbital gyrus and amygdala in structural and functional modalities and genes enriched in circadian rhythmic processes and dopaminergic synapse pathways. The structural feeder network displayed close correlations with SNPs and the functional feeder network. Furthermore, the structural feeder network could mediate the association between SNPs and the functional feeder network, implying that genetic variants might influence brain function by affecting brain structure in MDD. CONCLUSIONS These findings provide potential biomarkers for antidepressant therapy and provide a better grasp of the associations among SNPs and hierarchical structural and functional networks in MDD.
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Affiliation(s)
- Yurong Sun
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Yingling Hou
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Xinyi Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Huan Wang
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Rui Yan
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Li Xue
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China
| | - Zhijian Yao
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, China.
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Feng Y, Zhi D, Zhu Y, Guo X, Luo X, Dang C, Liu L, Sui J, Sun L. Symptom-guided multimodal neuroimage fusion patterns in children with attention-deficit/hyperactivity disorder and its potential "brain structure-function-cognition-behavior" pathological pathways. Eur Child Adolesc Psychiatry 2023:10.1007/s00787-023-02303-8. [PMID: 37777608 DOI: 10.1007/s00787-023-02303-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 09/14/2023] [Indexed: 10/02/2023]
Abstract
The "brain-cognition-behavior" process is an important pathological pathway in children with attention-deficit/hyperactivity disorder (ADHD). Symptom guided multimodal neuroimaging fusion can capture behaviorally relevant and intrinsically linked structural and functional features, which can help to construct a systematic model of the pathology. Analyzing the multimodal neuroimage fusion pattern and exploring how these brain features affect executive function (EF) and leads to behavioral impairment is the focus of this study. Based on gray matter volume (GMV) and fractional amplitude of low frequency fluctuation (fALFF) for 152 ADHD and 102 healthy controls (HC), the total symptom score (TO) was set as a reference to identify co-varying components. Based on the correlation between the identified co-varying components and EF, further mediation analysis was used to explore the relationship between brain image features, EF and clinical symptoms. This study found that the abnormalities of GMV and fALFF in ADHD are mainly located in the default mode network (DMN) and prefrontal-striatal-cerebellar circuits, respectively. GMV in ADHD influences the TO through Metacognition Index, while fALFF in HC mediates the TO through behavior regulation index (BRI). Further analysis revealed that GMV in HC influences fALFF, which further modulates BRI and subsequently affects hyperactivity-impulsivity score. To conclude, structural brain abnormalities in the DMN in ADHD may affect local brain function in the prefrontal-striatal-cerebellar circuit, making it difficult to regulate EF in terms of inhibit, shift, and emotional control, and ultimately leading to hyperactive-impulsive behavior.
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Affiliation(s)
- Yuan Feng
- Peking University Sixth Hospital/Institute of Mental Health, No.51, North Huayuan Road, Haidian District, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders and Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, 100191, China
| | - Dongmei Zhi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No.19, Xinjiekouwai Street, Haidian District, Beijing, 100088, China
| | - Yu Zhu
- Peking University Sixth Hospital/Institute of Mental Health, No.51, North Huayuan Road, Haidian District, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders and Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, 100191, China
| | - Xiaojie Guo
- Peking University Sixth Hospital/Institute of Mental Health, No.51, North Huayuan Road, Haidian District, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders and Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, 100191, China
| | - Xiangsheng Luo
- Peking University Sixth Hospital/Institute of Mental Health, No.51, North Huayuan Road, Haidian District, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders and Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, 100191, China
| | - Chen Dang
- Peking University Sixth Hospital/Institute of Mental Health, No.51, North Huayuan Road, Haidian District, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders and Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, 100191, China
| | - Lu Liu
- Peking University Sixth Hospital/Institute of Mental Health, No.51, North Huayuan Road, Haidian District, Beijing, 100191, China
- National Clinical Research Center for Mental Disorders and Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, 100191, China
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No.19, Xinjiekouwai Street, Haidian District, Beijing, 100088, China.
| | - Li Sun
- Peking University Sixth Hospital/Institute of Mental Health, No.51, North Huayuan Road, Haidian District, Beijing, 100191, China.
- National Clinical Research Center for Mental Disorders and Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, 100191, China.
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Jiang S, Huang H, Zhou J, Li H, Duan M, Yao D, Luo C. Progressive trajectories of schizophrenia across symptoms, genes, and the brain. BMC Med 2023; 21:237. [PMID: 37400838 DOI: 10.1186/s12916-023-02935-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 06/12/2023] [Indexed: 07/05/2023] Open
Abstract
BACKGROUND Schizophrenia is characterized by complex psychiatric symptoms and unclear pathological mechanisms. Most previous studies have focused on the morphological changes that occur over the development of the disease; however, the corresponding functional trajectories remain unclear. In the present study, we aimed to explore the progressive trajectories of patterns of dysfunction after diagnosis. METHODS Eighty-six patients with schizophrenia and 120 healthy controls were recruited as the discovery dataset. Based on multiple functional indicators of resting-state brain functional magnetic resonance imaging, we conducted a duration-sliding dynamic analysis framework to investigate trajectories in association with disease progression. Neuroimaging findings were associated with clinical symptoms and gene expression data from the Allen Human Brain Atlas database. A replication cohort of patients with schizophrenia from the University of California, Los Angeles, was used as the replication dataset for the validation analysis. RESULTS Five stage-specific phenotypes were identified. A symptom trajectory was characterized by positive-dominated, negative ascendant, negative-dominated, positive ascendant, and negative surpassed stages. Dysfunctional trajectories from primary and subcortical regions to higher-order cortices were recognized; these are associated with abnormal external sensory gating and a disrupted internal excitation-inhibition equilibrium. From stage 1 to stage 5, the importance of neuroimaging features associated with behaviors gradually shifted from primary to higher-order cortices and subcortical regions. Genetic enrichment analysis identified that neurodevelopmental and neurodegenerative factors may be relevant as schizophrenia progresses and highlighted multiple synaptic systems. CONCLUSIONS Our convergent results indicate that progressive symptoms and functional neuroimaging phenotypes are associated with genetic factors in schizophrenia. Furthermore, the identification of functional trajectories complements previous findings of structural abnormalities and provides potential targets for drug and non-drug interventions in different stages of schizophrenia.
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Affiliation(s)
- Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Jingyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
| | - Mingjun Duan
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, 611731, Chengdu, Sichuan, People's Republic of China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, 611731, Chengdu, Sichuan, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, People's Republic of China.
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, People's Republic of China.
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave., West Hi-Tech Zone, 611731, Chengdu, Sichuan, People's Republic of China.
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Zhang T, Fang Y, Wang L, Gu L, Tang J. Exosome and exosomal contents in schizophrenia. J Psychiatr Res 2023; 163:365-371. [PMID: 37267733 DOI: 10.1016/j.jpsychires.2023.05.072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 03/06/2023] [Accepted: 05/25/2023] [Indexed: 06/04/2023]
Abstract
Schizophrenia (SCZ) is a severe mental disorder that affects approximately 1% general population worldwide and poses a considerable burden to society. Despite decades of research, its etiology remains unclear, and diagnosis remains challenging due to its heterogeneous symptoms. Exosomes play a crucial role in intercellular communication, and their contents, including nucleotides, proteins and metabolites, have been linked to various diseases. Recent studies have implicated exosome abnormalities in the pathogenesis of schizophrenia. In this review, we discuss the current understanding of the relationship between exosomes and schizophrenia, focusing on the role of exosomal contents in this disease. We summarize recent findings and provide insights into the potential use of exosomes as biomarkers for the diagnosis and treatment of schizophrenia.
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Affiliation(s)
- Tingkai Zhang
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yehong Fang
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Liangliang Wang
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lin Gu
- RIKEN AIP, Tokyo, Japan; Research Center for Advanced Science and Technology (RCAST), The University of Tokyo, Tokyo, Japan
| | - Jinsong Tang
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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Association between fractional amplitude of low-frequency fluctuation (fALFF) and facial emotion recognition ability in first-episode schizophrenia patients: a fMRI study. Sci Rep 2022; 12:19561. [PMID: 36380188 PMCID: PMC9666540 DOI: 10.1038/s41598-022-24258-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 11/14/2022] [Indexed: 11/16/2022] Open
Abstract
It was still unclear that the correlation between the resting-state intrinsic activity in brain regions and facial emotion recognition (FER) ability in patients with first-episode schizophrenia (FSZ). Our aim was to analyse the correlation between the fractional amplitude of low-frequency fluctuation (fALFF) and FER ability in FSZ patients. A total of 28 patients with FSZ and 33 healthy controls (HCs) completed visual search tasks for FER ability. Regions of interest (ROIs) related to facial emotion were obtained from a previous meta-analysis. Pearson correlation analysis was performed to understand the correlation between fALFF and FER ability. Our results indicated that the patients performed worse than the HCs in the accuracy performances of happy FER and fearful FER. The previous meta-analysis results showed that the brain regions related to FER included the bilateral amygdala (AMY)/hippocampus (HIP), right fusiform gyrus (FFG), and right supplementary motor area (SMA). Partial correlation analysis showed that the fALFF of the right FFG was associated with high-load fearful FER accuracy (r = - 0.60, p = 0.004). Our study indicated that FER ability is correlated with resting-state intrinsic activity in brain regions related to facial emotion, which may provide a reference for the study of FER deficiency in schizophrenia.
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Wang Z, Su L, Wu T, Sun L, Sun Z, Wang Y, Li P, Cui G. Inhibition of MicroRNA-182/183 Cluster Ameliorates Schizophrenia by Activating the Axon Guidance Pathway and Upregulating DCC. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:9411276. [PMID: 36406766 PMCID: PMC9671740 DOI: 10.1155/2022/9411276] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 06/14/2022] [Indexed: 09/21/2023]
Abstract
Schizophrenia (SZ) is a complex disorder caused by a variety of genetic and environmental factors. Mounting evidence suggests the involvement of microRNAs (miRNAs) in the pathology of SZ. Accordingly, the current study set out to investigate the possible implication of the miR-182/183 cluster, as well as its associated mechanism in the progression of SZ. Firstly, rat models of SZ were established by intraperitoneal injection of MK-801. Moreover, rat primary hippocampal neurons were exposed to MK-801 to simulate injury of hippocampal neurons. The expression of miR-182/183 or its putative target gene DCC was manipulated to examine their effects on SZ in vitro and in vivo. It was found that miR-182 and miR-183 were both highly expressed in peripheral blood of SZ patients and hippocampal tissues of SZ rats. In addition, the miR-182/183 cluster could target DDC and downregulate the expression of DDC. On the other hand, inhibition of the miR-182/183 cluster ameliorated SZ, as evidenced by elevated serum levels of NGF and BDNF, along with reductions in spontaneous activity, serum GFAP levels, and hippocampal neuronal apoptosis. Additionally, DCC was found to activate the axon guiding pathway and influence synaptic activity in hippocampal neurons. Collectively, our findings highlighted that inhibition of the miR-182/183 cluster could potentially attenuate SZ through DCC-dependent activation of the axon guidance pathway. Furthermore, inhibition of the miR-182/183 cluster may represent a potential target for the SZ treatment.
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Affiliation(s)
- Zhichao Wang
- Department of Academic Research, Qiqihar Medical University, Qiqihar 161000, China
| | - Lin Su
- Jiangxi Provincial Key Laboratory of Preventive Medicine School of Public Health, Nanchang University, Nanchang 330006, China
| | - Tong Wu
- Department of Psychology, Qiqihar Medical University, Qiqihar 161000, China
| | - Lei Sun
- Department of Psychology, Qiqihar Medical University, Qiqihar 161000, China
| | - Zhenghai Sun
- Department of Psychology, Qiqihar Medical University, Qiqihar 161000, China
| | - Yuchen Wang
- Department of Psychology, Qiqihar Medical University, Qiqihar 161000, China
| | - Ping Li
- Department of Psychology, Qiqihar Medical University, Qiqihar 161000, China
| | - Guangcheng Cui
- Department of Psychology, Qiqihar Medical University, Qiqihar 161000, China
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9
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Fabbri C, Leggio GM, Drago F, Serretti A. Imputed expression of schizophrenia-associated genes and cognitive measures in patients with schizophrenia. Mol Genet Genomic Med 2022; 10:e1942. [PMID: 35488718 PMCID: PMC9184669 DOI: 10.1002/mgg3.1942] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 10/07/2021] [Accepted: 03/24/2022] [Indexed: 11/23/2022] Open
Abstract
Background Cognitive dysfunction is a core manifestation of schizophrenia and one of the best predictors of long‐term disability. Genes increasing risk for schizophrenia may partly act through the modulation of cognition. Methods We imputed the expression of 130 genes recently prioritized for association with schizophrenia, using PsychENCODE variant weights and genotypes of patients with schizophrenia in CATIE. Processing speed, reasoning, verbal memory, working memory, vigilance, and a composite cognitive score were used as phenotypes. We performed linear regression models for each cognitive measure and gene expression score, adjusting for age, years of education, antipsychotic treatment, years since the first antipsychotic treatment and population principal components. Results We included 425 patients and expression scores of 91 genes (others had no heritable expression; Bonferroni corrected alpha = 5.49e‐4). No gene expression score was associated with cognitive measures, though ENOX1 expression was very close to the threshold for verbal memory (p = 6e‐4) and processing speed (p = 7e‐4). Other genes were nominally associated with multiple phenotypes (MAN2A1 and PCGF3). Conclusion A better understanding of the mechanisms mediating cognitive dysfunction in schizophrenia may help in the definition of disease prognosis and in the identification of new treatments, as the treatment of cognitive impairment remains an unmet therapeutic need.
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Affiliation(s)
- Chiara Fabbri
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy.,Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Gian Marco Leggio
- Department of Biomedical and Biotechnological Sciences, Section of Pharmacology, University of Catania, Catania, Italy
| | - Filippo Drago
- Department of Biomedical and Biotechnological Sciences, Section of Pharmacology, University of Catania, Catania, Italy
| | - Alessandro Serretti
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
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10
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Wang X, Chen X, Liu Y, Huang S, Ding J, Wang B, Dong P, Sun Z, Chen L. CSMD1 suppresses cancer progression by inhibiting proliferation, epithelial-mesenchymal transition, chemotherapy-resistance and inducing immunosuppression in esophageal squamous cell carcinoma. Exp Cell Res 2022; 417:113220. [PMID: 35623420 DOI: 10.1016/j.yexcr.2022.113220] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 05/15/2022] [Accepted: 05/19/2022] [Indexed: 11/17/2022]
Abstract
Human CUB and Sushi multiple domains (CSMD1) is considered a crucial role in cancer progression, but the specific function in esophageal squamous cell carcinoma (ESCC) is not clear. Understanding the role of CSMD1 in ESCC progression may lead to a novel strategy for ESCC treatment. Here, we found that both CSMD1 mRNA and protein levels were downregulated in ESCC tissues. Reduced CSMD1 expression was correlated with a poor prognosis in ESCC patients. CSMD1 expression inhibited proliferation, migration and invasion in ESCC cell lines in vitro. CSMD1 deficiency in established xenografted tumors increases tumor size and weight. We further found that CSMD1-overexpression cells are more sensitive to chemotherapy. Moreover, we addressed the role of CSMD1 in the CD8+ T cell immune response. An in vitro killing assay showed that the cytotoxicity of CD8+ T cells was inhibited in CSMD1-overexpression tumor cells. In vivo, in CSMD1 deficiency tumor-bearing mice activation and expansion of CD8+ T cells were increased. Further investigation showed that CSMD1 expression on tumor cells was positively correlated with CD8+ T cells infiltration and cytokines secretion. These findings highlight that CSMD1 is a tumor suppressor gene in ESCC patients and a positive regulator of CD8+ T cells expansion and activation, and could increase cytokines secretion, indicating that tumor cell-associated CSMD1 might be a target for ESCC.
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Affiliation(s)
- Xing Wang
- Translational Medicine Center, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, 201620, Shanghai, China
| | - Xinwei Chen
- Department of Otolaryngology: Head and Neck Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Yuanyuan Liu
- Department of Otolaryngology: Head and Neck Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Shan Huang
- National Engineering Research Center for Nanomedicine, Key Laboratory of Molecular Biophysics of Ministry of Education, College of Life Science and Technology, Tongji Hospital, Huazhong University of Science and Technology, 430074, Wuhan, China
| | - Jian Ding
- Department of Otolaryngology: Head and Neck Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Baoxin Wang
- Department of Otolaryngology: Head and Neck Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Pin Dong
- Department of Otolaryngology: Head and Neck Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Zhenfeng Sun
- Department of Otolaryngology: Head and Neck Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Lixiao Chen
- Department of Otolaryngology: Head and Neck Surgery, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China.
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11
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González-Calvo I, Cizeron M, Bessereau JL, Selimi F. Synapse Formation and Function Across Species: Ancient Roles for CCP, CUB, and TSP-1 Structural Domains. Front Neurosci 2022; 16:866444. [PMID: 35546877 PMCID: PMC9083331 DOI: 10.3389/fnins.2022.866444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 03/28/2022] [Indexed: 11/17/2022] Open
Abstract
The appearance of synapses was a crucial step in the creation of the variety of nervous systems that are found in the animal kingdom. With increased complexity of the organisms came a greater number of synaptic proteins. In this review we describe synaptic proteins that contain the structural domains CUB, CCP, or TSP-1. These domains are found in invertebrates and vertebrates, and CUB and CCP domains were initially described in proteins belonging to the complement system of innate immunity. Interestingly, they are found in synapses of the nematode C. elegans, which does not have a complement system, suggesting an ancient function. Comparison of the roles of CUB-, CCP-, and TSP-1 containing synaptic proteins in various species shows that in more complex nervous systems, these structural domains are combined with other domains and that there is partial conservation of their function. These three domains are thus basic building blocks of the synaptic architecture. Further studies of structural domains characteristic of synaptic proteins in invertebrates such as C. elegans and comparison of their role in mammals will help identify other conserved synaptic molecular building blocks. Furthermore, this type of functional comparison across species will also identify structural domains added during evolution in correlation with increased complexity, shedding light on mechanisms underlying cognition and brain diseases.
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Affiliation(s)
- Inés González-Calvo
- Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France
| | - Mélissa Cizeron
- Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR-5284, INSERM U-1314, MeLiS, Institut NeuroMyoGène, Lyon, France
| | - Jean-Louis Bessereau
- Univ Lyon, Université Claude Bernard Lyon 1, CNRS UMR-5284, INSERM U-1314, MeLiS, Institut NeuroMyoGène, Lyon, France
| | - Fekrije Selimi
- Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France
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12
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Association of reduced local activities in the default mode and sensorimotor networks with clinical characteristics in first-diagnosed of schizophrenia. Neuroscience 2022; 495:47-57. [DOI: 10.1016/j.neuroscience.2022.05.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 05/15/2022] [Accepted: 05/16/2022] [Indexed: 01/10/2023]
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13
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Zhao M, Yan W, Luo N, Zhi D, Fu Z, Du Y, Yu S, Jiang T, Calhoun VD, Sui J. An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data. Med Image Anal 2022; 78:102413. [PMID: 35305447 PMCID: PMC9035078 DOI: 10.1016/j.media.2022.102413] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 10/27/2021] [Accepted: 03/01/2022] [Indexed: 12/30/2022]
Abstract
Functional magnetic resonance imaging (fMRI) as a promising tool to investigate psychotic disorders can be decomposed into useful imaging features such as time courses (TCs) of independent components (ICs) and functional network connectivity (FNC) calculated by TC cross-correlation. TCs reflect the temporal dynamics of brain activity and the FNC characterizes temporal coherence across intrinsic brain networks. Both features have been used as input to deep learning approaches with decent results. However, few studies have tried to leverage their complementary information to learn optimal representations at multiple facets. Motivated by this, we proposed a Hybrid Deep Learning Framework integrating brain Connectivity and Activity (HDLFCA) together by combining convolutional recurrent neural network (C-RNN) and deep neural network (DNN), aiming to improve classification accuracy and interpretability simultaneously. Specifically, C-RNNAM was proposed to extract temporal dynamic dependencies with an attention module (AM) to automatically learn discriminative knowledge from TC nodes, while DNN was applied to identify the most group-discriminative FNC patterns with layer-wise relevance propagation (LRP). Then, both prediction outputs were concatenated to build a new feature matrix, generating the final decision by logistic regression. The effectiveness of HDLFCA was validated on both multi-site schizophrenia (SZ, n ∼ 1100) and public autism datasets (ABIDE, n ∼ 1522) by outperforming 12 alternative models at 2.8-8.9% accuracy, including 8 models using either static FNC or TCs and 4 models using dynamic FNC. Appreciable classification accuracy was achieved for HC vs. SZ (85.3%) and HC vs. Autism (72.4%) respectively. More importantly, the most group-discriminative brain regions can be easily attributed and visualized, providing meaningful biological interpretability and highlighting the great potential of the proposed HDLFCA model in the identification of valid neuroimaging biomarkers.
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Affiliation(s)
- Min Zhao
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Weizheng Yan
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Na Luo
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Dongmei Zhi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Yuhui Du
- School of Computer and Information Technology, Shanxi University, Taiyuan, China
| | - Shan Yu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Jing Sui
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
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14
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Chen T, Mandal A, Zhu H, Liu R. Imaging Genetic Based Mediation Analysis for Human Cognition. Front Neurosci 2022; 16:824069. [PMID: 35573299 PMCID: PMC9097855 DOI: 10.3389/fnins.2022.824069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 03/23/2022] [Indexed: 11/30/2022] Open
Abstract
The brain connectome maps the structural and functional connectivity that forms an important neurobiological basis for the analysis of human cognitive traits while the genetic predisposition and our cognition ability are frequently found in close association. The issue of how genetic architecture and brain connectome causally affect human behaviors remains unknown. To seek for the potential causal relationship, in this paper, we carried out the causal pathway analysis from single nucleotide polymorphism (SNP) data to four common human cognitive traits, mediated by the brain connectome. Specifically, we selected 942 SNPs that are significantly associated with the brain connectome, and then estimated the direct and indirect effect on the human traits for each SNP. We found out that a majority of the selected SNPs have significant direct effects on human traits and discussed the trait-related brain regions and their implications.
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Affiliation(s)
- Tingan Chen
- Department of Statistics, Florida State University, Tallahassee, FL, United States
| | - Abhishek Mandal
- Department of Statistics, Florida State University, Tallahassee, FL, United States
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Rongjie Liu
- Department of Statistics, Florida State University, Tallahassee, FL, United States
- *Correspondence: Rongjie Liu
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15
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Feng A, Luo N, Zhao W, Calhoun VD, Jiang R, Zhi D, Shi W, Jiang T, Yu S, Xu Y, Liu S, Sui J. Multimodal brain deficits shared in early-onset and adult-onset schizophrenia predict positive symptoms regardless of illness stage. Hum Brain Mapp 2022; 43:3486-3497. [PMID: 35388581 PMCID: PMC9248316 DOI: 10.1002/hbm.25862] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 03/10/2022] [Accepted: 03/23/2022] [Indexed: 11/25/2022] Open
Abstract
Incidence of schizophrenia (SZ) has two predominant peaks, in adolescent and young adult. Early‐onset schizophrenia provides an opportunity to explore the neuropathology of SZ early in the disorder and without the confound of antipsychotic mediation. However, it remains unexplored what deficits are shared or differ between adolescent early‐onset (EOS) and adult‐onset schizophrenia (AOS) patients. Here, based on 529 participants recruited from three independent cohorts, we explored AOS and EOS common and unique co‐varying patterns by jointly analyzing three MRI features: fractional amplitude of low‐frequency fluctuations (fALFF), gray matter (GM), and functional network connectivity (FNC). Furthermore, a prediction model was built to evaluate whether the common deficits in drug‐naive SZ could be replicated in chronic patients. Results demonstrated that (1) both EOS and AOS patients showed decreased fALFF and GM in default mode network, increased fALFF and GM in the sub‐cortical network, and aberrant FNC primarily related to middle temporal gyrus; (2) the commonly identified regions in drug‐naive SZ correlate with PANSS positive significantly, which can also predict PANSS positive in chronic SZ with longer duration of illness. Collectively, results suggest that multimodal imaging signatures shared by two types of drug‐naive SZ are also associated with positive symptom severity in chronic SZ and may be vital for understanding the progressive schizophrenic brain structural and functional deficits.
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Affiliation(s)
- Aichen Feng
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,The School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Na Luo
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Wentao Zhao
- Department of Psychiatry, First Clinical Medical College/ First Hospital of Shanxi Medical University, Taiyuan, China
| | - Vince D Calhoun
- Tri-Institutional Centre for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA
| | - Rongtao Jiang
- Department of Radiology and Biomedical imaging, Yale University, New Haven, Connecticut, USA
| | - Dongmei Zhi
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Weiyang Shi
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,The School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,The School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Shan Yu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,The School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Yong Xu
- Department of Psychiatry, First Clinical Medical College/ First Hospital of Shanxi Medical University, Taiyuan, China
| | - Sha Liu
- Department of Psychiatry, First Clinical Medical College/ First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jing Sui
- Tri-Institutional Centre for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA.,State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
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16
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Li P, Zhao SW, Wu XS, Zhang YJ, Song L, Wu L, Liu XF, Fu YF, Wu D, Wu WJ, Zhang YH, Yin H, Cui LB, Guo F. The Association Between Lentiform Nucleus Function and Cognitive Impairments in Schizophrenia. Front Hum Neurosci 2021; 15:777043. [PMID: 34744673 PMCID: PMC8566813 DOI: 10.3389/fnhum.2021.777043] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 09/29/2021] [Indexed: 01/10/2023] Open
Abstract
Introduction: Cognitive decline is the core schizophrenia symptom, which is now well accepted. Holding a role in various aspects of cognition, lentiform nucleus (putamen and globus pallidus) dysfunction contributes to the psychopathology of this disease. However, the effects of lentiform nucleus function on cognitive impairments in schizophrenia are yet to be investigated. Objectives: We aim to detect the fractional amplitude of low-frequency fluctuation (fALFF) alterations in patients with schizophrenia, and examine how their behavior correlates in relation to the cognitive impairments of the patients. Methods: All participants underwent magnetic resonance imaging (MRI) and cognitive assessment (digit span and digit symbol coding tests). Screening of brain regions with significant changes in fALFF values was based on analysis of the whole brain. The data were analyzed between Jun 2020 and Mar 2021. There were no interventions beyond the routine therapy determined by their clinicians on the basis of standard clinical practice. Results: There were 136 patients (75 men and 61 women, 24.1 ± 7.4 years old) and 146 healthy controls (82 men and 64 women, 24.2 ± 5.2 years old) involved in the experiments seriatim. Patients with schizophrenia exhibited decreased raw scores in cognitive tests (p < 0.001) and increased fALFF in the bilateral lentiform nuclei (left: 67 voxels; x = −24, y = −6, z = 3; peak t-value = 6.90; right: 16 voxels; x = 18, y = 0, z = 3; peak t-value = 6.36). The fALFF values in the bilateral lentiform nuclei were positively correlated with digit span-backward test scores (left: r = 0.193, p = 0.027; right: r = 0.190, p = 0.030), and the right lentiform nucleus was positively correlated with digit symbol coding scores (r = 0.209, p = 0.016). Conclusion: This study demonstrates that cognitive impairments in schizophrenia are associated with lentiform nucleus function as revealed by MRI, involving working memory and processing speed.
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Affiliation(s)
- Ping Li
- Medical Imaging Department 1, Xi'an Mental Health Center, Xi'an, China
| | - Shu-Wan Zhao
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Xu-Sha Wu
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Ya-Juan Zhang
- Department of Clinical Psychology, School of Medical Psychology, The Fourth Military Medical University, Xi'an, China
| | - Lei Song
- Department of Clinical Psychology, School of Medical Psychology, The Fourth Military Medical University, Xi'an, China
| | - Lin Wu
- Department of Clinical Psychology, School of Medical Psychology, The Fourth Military Medical University, Xi'an, China
| | - Xiao-Fan Liu
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Di Wu
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Wen-Jun Wu
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Ya-Hong Zhang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, The Fourth Military Medical University, Xi'an, China.,Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
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17
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Cheng W, Luo N, Zhang Y, Zhang X, Tan H, Zhang D, Sui J, Yue W, Yan H. DNA Methylation and Resting Brain Function Mediate the Association between Childhood Urbanicity and Better Speed of Processing. Cereb Cortex 2021; 31:4709-4718. [PMID: 33987663 PMCID: PMC8408435 DOI: 10.1093/cercor/bhab117] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 04/07/2021] [Accepted: 04/09/2021] [Indexed: 01/10/2023] Open
Abstract
Urbanicity has been suggested to affect cognition, but the underlying mechanism remains unknown. We examined whether epigenetic modification (DNA methylation, DNAm), and brain white matter fiber integrity (fractional anisotropy, FA) or local spontaneous brain function activity (regional homogeneity, ReHo) play roles in the association between childhood urbanicity and cognition based on 497 healthy Chinese adults. We found significant correlation between childhood urbanicity and better cognitive performance. Multiset canonical correlation analysis (mCCA) identified an intercorrelated DNAm-FA-ReHo triplet, which showed significant pairwise correlations (DNAm-FA: Bonferroni-adjusted P, Pbon = 4.99E−03, rho = 0.216; DNAm-ReHo: Pbon = 4.08E−03, rho = 0.239; ReHo-FA: Pbon = 1.68E−06, rho = 0.328). Causal mediation analysis revealed that 1) ReHo mediated 10.86% childhood urbanicity effects on the speed of processing and 2) childhood urbanicity alters ReHo through DNA methylation in the cadherin and Wnt signaling pathways (mediated effect: 48.55%). The mediation effect of increased ReHo in the superior temporal gyrus underlying urbanicity impact on a better speed of processing was further validated in an independent cohort. Our work suggests a mediation role for ReHo, particularly increased brain activity in the superior temporal gyrus, in the urbanicity-associated speed of processing.
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Affiliation(s)
- Weiqiu Cheng
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China.,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Na Luo
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuyanan Zhang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China.,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Xiao Zhang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China.,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Haoyang Tan
- Lieber Institute for Brain Development, Baltimore, MD 21205, USA.,Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Dai Zhang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China.,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.,Tsinghua University-Peking University Joint Center for Life Sciences, Beijing 100871, China.,PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Jing Sui
- University of Chinese Academy of Sciences, Beijing 100049, China.,State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Weihua Yue
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China.,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.,PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Hao Yan
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China.,NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
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18
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Na + leak-current channel (NALCN) at the junction of motor and neuropsychiatric symptoms in Parkinson's disease. J Neural Transm (Vienna) 2021; 128:749-762. [PMID: 33961117 DOI: 10.1007/s00702-021-02348-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 04/30/2021] [Indexed: 12/27/2022]
Abstract
Parkinson's disease (PD) is a debilitating movement disorder often accompanied by neuropsychiatric symptoms that stem from the loss of dopaminergic function in the basal ganglia and altered neurotransmission more generally. Akinesia, postural instability, tremors and frozen gait constitute the major motor disturbances, whereas neuropsychiatric symptoms include altered circadian rhythms, disordered sleep, depression, psychosis and cognitive impairment. Evidence is emerging that the motor and neuropsychiatric symptoms may share etiologic factors. Calcium/ion channels (CACNA1C, NALCN), synaptic proteins (SYNJ1) and neuronal RNA-binding proteins (RBFOX1) are among the risk genes that are common to PD and various psychiatric disorders. The Na+ leak-current channel (NALCN) is the focus of this review because it has been implicated in dystonia, regulation of movement, cognitive impairment, sleep and circadian rhythms. It regulates the resting membrane potential in neurons, mediates pace-making activity, participates in synaptic vesicle recycling and is functionally co-localized to the endoplasmic reticulum (ER)-several of the major processes adversely affected in PD. Here, we summarize the literature on mechanisms and pathways that connect the motor and neuropsychiatric symptoms of PD with a focus on recurring relationships to the NALCN. It is hoped that the various connections outlined here will stimulate further discussion, suggest additional areas for exploration and ultimately inspire novel treatment strategies.
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19
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Todeva-Radneva A, Paunova R, Kandilarova S, St Stoyanov D. The Value of Neuroimaging Techniques in the Translation and Transdiagnostic Validation of Psychiatric Diagnoses - Selective Review. Curr Top Med Chem 2021; 20:540-553. [PMID: 32003690 DOI: 10.2174/1568026620666200131095328] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 12/09/2019] [Accepted: 12/12/2019] [Indexed: 01/05/2023]
Abstract
Psychiatric diagnosis has long been perceived as more of an art than a science since its foundations lie within the observation, and the self-report of the patients themselves and objective diagnostic biomarkers are lacking. Furthermore, the diagnostic tools in use not only stray away from the conventional medical framework but also remain invalidated with evidence-based concepts. However, neuroscience, as a source of valid objective knowledge has initiated the process of a paradigm shift underlined by the main concept of psychiatric disorders being "brain disorders". It is also a bridge closing the explanatory gap among the different fields of medicine via the translation of the knowledge within a multidisciplinary framework. The contemporary neuroimaging methods, such as fMRI provide researchers with an entirely new set of tools to reform the current status quo by creating an opportunity to define and validate objective biomarkers that can be translated into clinical practice. Combining multiple neuroimaging techniques with the knowledge of the role of genetic factors, neurochemical imbalance and neuroinflammatory processes in the etiopathophysiology of psychiatric disorders is a step towards a comprehensive biological explanation of psychiatric disorders and a final differentiation of psychiatry as a well-founded medical science. In addition, the neuroscientific knowledge gained thus far suggests a necessity for directional change to exploring multidisciplinary concepts, such as multiple causality and dimensionality of psychiatric symptoms and disorders. A concomitant viewpoint transition of the notion of validity in psychiatry with a focus on an integrative validatory approach may facilitate the building of a collaborative bridge above the wall existing between the scientific fields analyzing the mind and those studying the brain.
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Affiliation(s)
- Anna Todeva-Radneva
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Rositsa Paunova
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Sevdalina Kandilarova
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Drozdstoy St Stoyanov
- Department of Psychiatry and Medical Psychology and Scientific Research Institute, The Medical University of Plovdiv, Plovdiv, Bulgaria
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20
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Li Y, Xue YZ, Zhao WT, Li SS, Li J, Xu Y. Correlates of intelligence via resting-state functional connectivity of the amygdala in healthy adults. Brain Res 2020; 1751:147176. [PMID: 33121922 DOI: 10.1016/j.brainres.2020.147176] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 10/19/2020] [Accepted: 10/21/2020] [Indexed: 11/24/2022]
Abstract
Intelligence is a form of advanced cognition that includes reasoning, problem solving, pattern recognition, and establishing relationships among items. The amygdala plays an important role in cognitive processing, but the relationship between amygdalar function and intelligence has rarely been explored directly. Here, we investigated the relationship between resting-state functional connectivity (RSFC) of the amygdala and intelligence test performance in a large sample of healthy adults (N = 197). We found that two pairs of RSFCs were significantly increased in the high IQ group compared with that of the general IQ group. One of these RSFCs consisted of the right amygdala and the right superior parietal lobule, whereas the other RSFC consisted of the right amygdala and the left middle cingulum. In addition, we found that the brain regions in which the strength of RSFC significantly correlated with full IQ (FIQ) were mainly distributed in the parietal and limbic lobes. What's more, a further mediation analysis indicated that the functional connectivity of the right amygdala and the right superior parietal lobule significantly mediated the correlation between comprehension and object assembly, whereas the functional connectivity of the right amygdala and the left middle cingulum mediated the association between similarities and digit symbol. These findings suggest that amygdalar RSFC may reflect individual differences in intelligence and mediate specific relationships among different intellectual abilities.
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Affiliation(s)
- Yue Li
- Department of Psychiatry, First Hospital /First Clinical Medical College of Shanxi Medical University, Taiyuan, China; Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yun-Zhen Xue
- Department of Humanities and Social Science, Shanxi Medical University, Taiyuan, China
| | - Wen-Tao Zhao
- Department of Psychiatry, First Hospital /First Clinical Medical College of Shanxi Medical University, Taiyuan, China; Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Sha-Sha Li
- Department of Humanities and Social Science, Shanxi Medical University, Taiyuan, China
| | - Jing Li
- Department of Psychiatry, First Hospital /First Clinical Medical College of Shanxi Medical University, Taiyuan, China; Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yong Xu
- Department of Psychiatry, First Hospital /First Clinical Medical College of Shanxi Medical University, Taiyuan, China; Department of Humanities and Social Science, Shanxi Medical University, Taiyuan, China; MDT Center for Cognitive Impairment and Sleep Disorders, First Hospital of Shanxi Medical University, Taiyuan, China; Shanxi Key Laboratory of Artificial Intelligence Assisted Diagnosis and Treatment for Mental Disorder, First Hospital of Shanxi Medical University, Taiyuan, China.
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Applying dimensional psychopathology: transdiagnostic associations among regional homogeneity, leptin and depressive symptoms. Transl Psychiatry 2020; 10:248. [PMID: 32699219 PMCID: PMC7376105 DOI: 10.1038/s41398-020-00932-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 07/03/2020] [Accepted: 07/14/2020] [Indexed: 12/29/2022] Open
Abstract
Dimensional psychopathology and its neurobiological underpinnings could provide important insights into major psychiatric disorders, including major depressive disorder, bipolar disorder and schizophrenia. In a dimensional transdiagnostic approach, we examined depressive symptoms and their relationships with regional homogeneity and leptin across major psychiatric disorders. A total of 728 participants (including 403 patients with major psychiatric disorders and 325 age-gender-matched healthy controls) underwent resting-state functional magnetic resonance imaging at a single site. We obtained plasma leptin levels and depressive symptom measures (Hamilton Depression Rating Scale (HAMD)) within 24 h of scanning and compared the regional homogeneity (ReHo), plasma leptin levels and HAMD total score and factor scores between patients and healthy controls. To reveal the potential relationships, we performed correlational and mediational analyses. Patients with major psychiatric disorders had significant lower ReHo in primary sensory and visual association cortices and higher ReHo in the frontal cortex and angular gyrus; plasma leptin levels were also elevated. Furthermore, ReHo alterations, leptin and HAMD factor scores had significant correlations. We also found that leptin mediated the transdiagnostic relationships among ReHo alterations in primary somatosensory and visual association cortices, core depressive symptoms and body mass index. The transdiagnostic associations we demonstrated support the common neuroanatomical substrates and neurobiological mechanisms. Moreover, leptin could be an important association among ReHo, core depressive symptoms and body mass index, suggesting a potential therapeutic target for dimensional depressive symptoms across major psychiatric disorders.
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22
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Zhang Y, Peng P, Ju Y, Li G, Calhoun VD, Wang YP. Canonical Correlation Analysis of Imaging Genetics Data Based on Statistical Independence and Structural Sparsity. IEEE J Biomed Health Inform 2020; 24:2621-2629. [PMID: 32071012 DOI: 10.1109/jbhi.2020.2972581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Current developments of neuroimaging and genetics promote an integrative and compressive study of schizophrenia. However, it is still difficult to explore how gene mutations are related to brain abnormalities due to the high dimension but low sample size of these data. Conventional approaches reduce the dimension of dataset separately and then calculate the correlation, but ignore the effects of the response variables and the structure of data. To improve the identification of risk genes and abnormal brain regions on schizophrenia, in this paper, we propose a novel method called Independence and Structural sparsity Canonical Correlation Analysis (ISCCA). ISCCA combines independent component analysis (ICA) and Canonical Correlation Analysis (CCA) to reduce the collinear effects, which also incorporate graph structure of the data into the model to improve the accuracy of feature selection. The results from simulation studies demonstrate its higher accuracy in discovering correlations compared with other competing methods. Moreover, applying ISCCA to a real imaging genetics dataset collected by Mind Clinical Imaging Consortium (MCIC), a set of distinct gene-ROI interactions are identified, which are verified to be both statistically and biologically significant.
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23
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Vosberg DE, Leyton M, Flores C. The Netrin-1/DCC guidance system: dopamine pathway maturation and psychiatric disorders emerging in adolescence. Mol Psychiatry 2020; 25:297-307. [PMID: 31659271 PMCID: PMC6974431 DOI: 10.1038/s41380-019-0561-7] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Revised: 08/01/2019] [Accepted: 08/19/2019] [Indexed: 02/02/2023]
Abstract
Axon guidance molecules direct growing axons toward their targets, assembling the intricate wiring of the nervous system. One of these molecules, Netrin-1, and its receptor, DCC (deleted in colorectal cancer), has profound effects, in laboratory animals, on the adolescent expansion of mesocorticolimbic pathways, particularly dopamine. Now, a rapidly growing literature suggests that (1) these same alterations could occur in humans, and (2) genetic variants in Netrin-1 and DCC are associated with depression, schizophrenia, and substance use. Together, these findings provide compelling evidence that Netrin-1 and DCC influence mesocorticolimbic-related psychopathological states that emerge during adolescence.
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Affiliation(s)
- Daniel E Vosberg
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Integrated Program in Neuroscience (IPN), McGill University, Montreal, QC, Canada
- Population Neuroscience and Developmental Neuroimaging, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada
| | - Marco Leyton
- Department of Psychiatry, McGill University, Montreal, QC, Canada.
- Integrated Program in Neuroscience (IPN), McGill University, Montreal, QC, Canada.
- Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
| | - Cecilia Flores
- Department of Psychiatry, McGill University, Montreal, QC, Canada.
- Integrated Program in Neuroscience (IPN), McGill University, Montreal, QC, Canada.
- Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
- Douglas Mental Health University Institute, Montreal, QC, Canada.
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24
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Mallet J, Le Strat Y, Dubertret C, Gorwood P. Polygenic Risk Scores Shed Light on the Relationship between Schizophrenia and Cognitive Functioning: Review and Meta-Analysis. J Clin Med 2020; 9:E341. [PMID: 31991840 PMCID: PMC7074036 DOI: 10.3390/jcm9020341] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Revised: 01/14/2020] [Accepted: 01/23/2020] [Indexed: 12/26/2022] Open
Abstract
Schizophrenia is a multifactorial disease associated with widespread cognitive impairment. Although cognitive deficits are one of the factors most strongly associated with functional impairment in schizophrenia (SZ), current treatment strategies hardly tackle these impairments. To develop more efficient treatment strategies in patients, a better understanding of their pathogenesis is needed. Recent progress in genetics, driven by large genome-wide association studies (GWAS) and the use of polygenic risk scores (PRS), has provided new insights about the genetic architecture of complex human traits, including cognition and SZ. Here, we review the recent findings examining the genetic links between SZ and cognitive functions in population-based samples as well as in participants with SZ. The performed meta-analysis showed a negative correlation between the polygenetic risk score of schizophrenia and global cognition (p < 0.001) when the samples rely on general and healthy participants, while no significant correlation was detected when the three studies devoted to schizophrenia patients were meta-analysed (p > 0.05). Our review and meta-analysis therefore argues against universal pleiotropy for schizophrenia alleles and cognition, since cognition in SZ patients would be underpinned by the same genetic factors than in the general population, and substantially independent of common variant liability to the disorder.
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Affiliation(s)
- Jasmina Mallet
- APHP; Department of Psychiatry, Universitary Hospital Louis Mourier, 92700 Colombes, France; (Y.L.S.); (C.D.)
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
| | - Yann Le Strat
- APHP; Department of Psychiatry, Universitary Hospital Louis Mourier, 92700 Colombes, France; (Y.L.S.); (C.D.)
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
| | - Caroline Dubertret
- APHP; Department of Psychiatry, Universitary Hospital Louis Mourier, 92700 Colombes, France; (Y.L.S.); (C.D.)
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
| | - Philip Gorwood
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
- GHU Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France
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25
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Hasbi A, Madras BK, Bergman J, Kohut S, Lin Z, Withey SL, George SR. Δ-Tetrahydrocannabinol Increases Dopamine D1-D2 Receptor Heteromer and Elicits Phenotypic Reprogramming in Adult Primate Striatal Neurons. iScience 2020; 23:100794. [PMID: 31972514 PMCID: PMC6971351 DOI: 10.1016/j.isci.2019.100794] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 11/01/2019] [Accepted: 12/18/2019] [Indexed: 01/09/2023] Open
Abstract
Long-term cannabis users manifest deficits in dopaminergic functions, reflecting Δ9-tetrahydrocannabinol (THC)-induced neuroadaptive dysfunctional dopamine signaling, similar to those observed upon dopamine D1-D2 heteromer activation. The molecular mechanisms remain largely unknown. We show evolutionary and regional differences in D1-D2 heteromer abundance in mammalian striatum. Importantly, chronic THC increased the number of D1-D2 heteromer-expressing neurons, and the number of heteromers within individual neurons in adult monkey striatum. The majority of these neurons displayed a phenotype co-expressing the characteristic markers of both striatonigral and striatopallidal neurons. Furthermore, THC increased D1-D2-linked calcium signaling markers (pCaMKIIα, pThr75-DARPP-32, BDNF/pTrkB) and inhibited cyclic AMP signaling (pThr34-DARPP-32, pERK1/2, pS845-GluA1, pGSK3). Cannabidiol attenuated most but not all of these THC-induced neuroadaptations. Targeted pathway analyses linked these changes to neurological and psychological disorders. These data underline the importance of the D1-D2 receptor heteromer in cannabis use-related disorders, with THC-induced changes likely responsible for the reported adverse effects observed in heavy long-term users.
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Affiliation(s)
- Ahmed Hasbi
- Department of Pharmacology, University of Toronto, Toronto, ON, Canada
| | - Bertha K Madras
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA; McLean Hospital, Belmont, USA
| | - Jack Bergman
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA; McLean Hospital, Belmont, USA
| | - Stephen Kohut
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA; McLean Hospital, Belmont, USA
| | - Zhicheng Lin
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA; McLean Hospital, Belmont, USA
| | - Sarah L Withey
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA; McLean Hospital, Belmont, USA
| | - Susan R George
- Department of Pharmacology, University of Toronto, Toronto, ON, Canada; Department of Medicine, University of Toronto, Toronto, ON, Canada.
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Li H, Guo W, Liu F, Chen J, Su Q, Zhang Z, Fan X, Zhao J. Enhanced baseline activity in the left ventromedial putamen predicts individual treatment response in drug-naive, first-episode schizophrenia: Results from two independent study samples. EBioMedicine 2019; 46:248-255. [PMID: 31307956 PMCID: PMC6712417 DOI: 10.1016/j.ebiom.2019.07.022] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 06/20/2019] [Accepted: 07/08/2019] [Indexed: 11/28/2022] Open
Abstract
Background Antipsychotic medications are the common treatment for schizophrenia. However, reliable biomarkers that can predict individual treatment response are still lacking. The present study aimed to examine whether baseline putamen activity can predict individual treatment response in schizophrenia. Methods Two independent samples of patients with drug-naive, first-episode schizophrenia (32 patients in sample 1 and 44 in sample 2) and matched healthy controls underwent resting-state functional magnetic resonance imaging (fMRI) at baseline. Patients were treated with olanzapine for 8 weeks; symptom severity was assessed using the Positive and Negative Syndrome Scale (PANSS) at baseline and week 8. Fractional amplitude of low frequency fluctuation (fALFF) and pattern classification techniques were used to analyze the data. Findings Univariate analysis shows an elevated pre-treatment fALFF in the left ventromedial putamen in both patient samples compared to healthy controls (p's < 0.001). The support vector regression (SVR) analysis suggests a positive relationship between baseline pre-treatment fALFF in the left ventromedial putamen and improvement in positive symptom at week 8 in each patient group using a cross-validated method (r = 0.452, p = .002; r = 0.511, p = .003, respectively). Interpretation Our study suggests that elevated pre-treatment mean fALFF in the left ventromedial putamen may predict individual therapeutic response to olanzapine treatment in drug-naive, first-episode patients with schizophrenia. Future studies are needed to confirm whether this finding is generalizable to patients with schizophrenia treated with other antipsychotic medications. Fund The National Key R&D Program of China and the National Natural Science Foundation of China.
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Affiliation(s)
- Huabing Li
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Wenbin Guo
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China.
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300000, China
| | - Jindong Chen
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
| | - Qinji Su
- Mental Health Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530007, China
| | - Zhikun Zhang
- Mental Health Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530007, China
| | - Xiaoduo Fan
- University of Massachusetts Medical School, UMass Memorial Medical Center, One Biotech, Suite 100, 365 Plantation Street, Worcester, MA 01605, United States.
| | - Jingping Zhao
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China; National Clinical Research Center on Mental Disorders, Changsha, Hunan 410011, China
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27
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Luo N, Tian L, Calhoun VD, Chen J, Lin D, Vergara VM, Rao S, Yang J, Zhuo C, Xu Y, Turner JA, Zhang F, Sui J. Brain function, structure and genomic data are linked but show different sensitivity to duration of illness and disease stage in schizophrenia. NEUROIMAGE-CLINICAL 2019; 23:101887. [PMID: 31176952 PMCID: PMC6558215 DOI: 10.1016/j.nicl.2019.101887] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 05/28/2019] [Accepted: 05/29/2019] [Indexed: 01/05/2023]
Abstract
The progress of schizophrenia at various stages is an intriguing question, which has been explored to some degree using single-modality brain imaging data, e.g. gray matter (GM) or functional connectivity (FC). However it remains unclear how those changes from different modalities are correlated with each other and if the sensitivity to duration of illness and disease stages across modalities is different. In this work, we jointly analyzed FC, GM volume and single nucleotide polymorphisms (SNPs) data of 159 individuals including healthy controls (HC), drug-naïve first-episode schizophrenia (FESZ) and chronic schizophrenia patients (CSZ), aiming to evaluate the links among SNP, FC and GM patterns, and their sensitivity to duration of illness and disease stages in schizophrenia. Our results suggested: 1) both GM and FC highlighted impairments in hippocampal, temporal gyrus and cerebellum in schizophrenia, which were significantly correlated with genes like SATB2, GABBR2, PDE4B, CACNA1C etc. 2) GM and FC presented gradually decrease trend (HC > FESZ>CSZ), while SNP indicated a non-gradual variation trend with un-significant group difference observed between FESZ and CSZ; 3) Group difference between HC and FESZ of FC was more remarkable than GM, and FC presented a stronger negative correlation with duration of illness than GM (p = 0.0006). Collectively, these results highlight the benefit of leveraging multimodal data and provide additional clues regarding the impact of mental illness at various disease stages.
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Affiliation(s)
- Na Luo
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lin Tian
- Wuxi Mental Health Center, Wuxi 214000, China
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): {Georgia State University, Georgia Institute of Technology, and Emory University}, Atlanta, GA 30303, USA; The Mind Research Network, Albuquerque, NM 87106, USA
| | - Jiayu Chen
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): {Georgia State University, Georgia Institute of Technology, and Emory University}, Atlanta, GA 30303, USA
| | - Dongdong Lin
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): {Georgia State University, Georgia Institute of Technology, and Emory University}, Atlanta, GA 30303, USA
| | - Victor M Vergara
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): {Georgia State University, Georgia Institute of Technology, and Emory University}, Atlanta, GA 30303, USA
| | - Shuquan Rao
- School of Life Science and Engineering, Southwest Jiaotong University, Chengdu 610031, China
| | - Jian Yang
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, China
| | - Chuanjun Zhuo
- Department of Psychiatric-Neuroimaging-Genetics and Morbidity Laboratory (PNGC-Lab), Tianjin Mental Health Center, Nankai University Affiliated Anding Hospital, Tianjin 300222, China
| | - Yong Xu
- Department of Psychiatry, First Clinical Medical College, First Hospital of Shanxi Medical University, Taiyuan 030000, China
| | - Jessica A Turner
- Department of Psychology, Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | | | - Jing Sui
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
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