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Zhang R, Ren J, Lei X, Wang Y, Chen X, Fu L, Li Q, Guo C, Teng X, Wu Z, Yu L, Wang D, Chen Y, Zhang C. Aberrant patterns of spontaneous brain activity in schizophrenia: A resting-state fMRI study and classification analysis. Prog Neuropsychopharmacol Biol Psychiatry 2024; 134:111066. [PMID: 38901758 DOI: 10.1016/j.pnpbp.2024.111066] [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: 01/17/2024] [Accepted: 06/17/2024] [Indexed: 06/22/2024]
Abstract
BACKGROUND Schizophrenia is a prevalent mental disorder, leading to severe disability. Currently, the absence of objective biomarkers hinders effective diagnosis. This study was conducted to explore the aberrant spontaneous brain activity and investigate the potential of abnormal brain indices as diagnostic biomarkers employing machine learning methods. METHODS A total of sixty-one schizophrenia patients and seventy demographically matched healthy controls were enrolled in this study. The static indices of resting-state functional magnetic resonance imaging (rs-fMRI) including amplitude of low frequency fluctuations (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and degree centrality (DC) were calculated to evaluate spontaneous brain activity. Subsequently, a sliding-window method was then used to conduct temporal dynamic analysis. The comparison of static and dynamic rs-fMRI indices between the patient and control groups was conducted using a two-sample t-test. Finally, the machine learning analysis was applied to estimate the diagnostic value of abnormal indices of brain activity. RESULTS Schizophrenia patients exhibited a significant increase ALFF value in inferior frontal gyrus, alongside significant decreases in fALFF values observed in left postcentral gyrus and right cerebellum posterior lobe. Pervasive aberrations in ReHo indices were observed among schizophrenia patients, particularly in frontal lobe and cerebellum. A noteworthy reduction in voxel-wise concordance of dynamic indices was observed across gray matter regions encompassing the bilateral frontal, parietal, occipital, temporal, and insular cortices. The classification analysis achieved the highest values for area under curve at 0.87 and accuracy at 81.28% when applying linear support vector machine and leveraging a combination of abnormal static and dynamic indices in the specified brain regions as features. CONCLUSIONS The static and dynamic indices of brain activity exhibited as potential neuroimaging biomarkers for the diagnosis of schizophrenia.
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Affiliation(s)
- Rong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Juanjuan Ren
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaoxia Lei
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yewei Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaochang Chen
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lirong Fu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qingyi Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chaoyue Guo
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinyue Teng
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zenan Wu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lingfang Yu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dandan Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yan Chen
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Chen Zhang
- Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Yu T, Pei WZ, Xu CY, Deng CC, Zhang XL. Identification of male schizophrenia patients using brain morphology based on machine learning algorithms. World J Psychiatry 2024; 14:804-811. [PMID: 38984327 PMCID: PMC11230103 DOI: 10.5498/wjp.v14.i6.804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 05/01/2024] [Accepted: 05/21/2024] [Indexed: 06/19/2024] Open
Abstract
BACKGROUND Schizophrenia is a severe psychiatric disease, and its prevalence is higher. However, diagnosis of early-stage schizophrenia is still considered a challenging task. AIM To employ brain morphological features and machine learning method to differentiate male individuals with schizophrenia from healthy controls. METHODS The least absolute shrinkage and selection operator and t tests were applied to select important features from structural magnetic resonance images as input features for classification. Four commonly used machine learning algorithms, the general linear model, random forest (RF), k-nearest neighbors, and support vector machine algorithms, were used to develop the classification models. The performance of the classification models was evaluated according to the area under the receiver operating characteristic curve (AUC). RESULTS A total of 8 important features with significant differences between groups were considered as input features for the establishment of classification models based on the four machine learning algorithms. Compared to other machine learning algorithms, RF yielded better performance in the discrimination of male schizophrenic individuals from healthy controls, with an AUC of 0.886. CONCLUSION Our research suggests that brain morphological features can be used to improve the early diagnosis of schizophrenia in male patients.
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Affiliation(s)
- Tao Yu
- Department of Clinical Nutrition, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
| | - Wen-Zhi Pei
- Department of Psychiatry, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
| | - Chun-Yuan Xu
- Department of Clinical Nutrition, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
| | - Chen-Chen Deng
- Department of Gynaecology, Anhui Maternal and Child Health Hospital, Hefei 230032, Anhui Province, China
| | - Xu-Lai Zhang
- Department of Psychiatry, Hefei Fourth People’s Hospital, Hefei 230032, Anhui Province, China
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Li H, Zhang W, Song H, Zhuo L, Yao H, Sun H, Liu R, Feng R, Tang C, Lui S. Altered temporal lobe connectivity is associated with psychotic symptoms in drug-naïve adolescent patients with first-episode schizophrenia. Eur Child Adolesc Psychiatry 2024:10.1007/s00787-024-02485-9. [PMID: 38832962 DOI: 10.1007/s00787-024-02485-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Accepted: 05/23/2024] [Indexed: 06/06/2024]
Abstract
Research on individuals with a younger onset age of schizophrenia is important for identifying neurobiological processes derived from the interaction of genes and the environment that lead to the manifestation of schizophrenia. Schizophrenia has long been recognized as a disorder of dysconnectivity, but it is largely unknown how brain connectivity changes are associated with psychotic symptoms. Twenty-one adolescent-onset schizophrenia (AOS) patients and 21 matched healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging. Regional homogeneity (ReHo) was used to investigate local brain connectivity alterations in AOS. Regions with significant ReHo changes in patients were selected as "seeds" for further functional connectivity (FC) analysis and Granger causality analysis (GCA), and associations of the obtained functional brain measures with psychotic symptoms in patients with AOS were examined. Compared with HCs, AOS patients showed significantly increased ReHo in the right middle temporal gyrus (MTG), which was positively correlated with PANSS-positive scores, PSYRATS-delusion scores and auditory hallucination scores. With the MTG as the seed, lower connectivity with the bilateral postcentral gyrus (PCG) and higher connectivity with the right precuneus were observed in patients. The reduced FC between the right MTG and bilateral PCG was significantly and positively correlated with hallucination scores. GCA indicated decreased Granger causality from the right MTG to the left middle frontal gyrus (MFG) and from the right MFG to the right MTG in AOS patients, but such effects did not significantly associate with psychotic symptoms. Abnormalities in the connectivity within the MTG and its connectivity with other networks were identified and were significantly correlated with hallucination and delusion ratings. This region may be a key neural substrate of psychotic symptoms in AOS.
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Affiliation(s)
- Hongwei Li
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Radiology, The Third Hospital of Mianyang/Sichuan Mental Health Center, Mianyang, China
| | - Wenjing Zhang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Hui Song
- Department of Psychiatry, The Third Hospital of Mianyang/Sichuan Mental Health Center, Mianyang, China
| | - Lihua Zhuo
- Department of Radiology, The Third Hospital of Mianyang/Sichuan Mental Health Center, Mianyang, China
| | - Hongchao Yao
- Department of Radiology, The Third Hospital of Mianyang/Sichuan Mental Health Center, Mianyang, China
| | - Hui Sun
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Ruishan Liu
- Department of Radiology, The Third Hospital of Mianyang/Sichuan Mental Health Center, Mianyang, China
| | - Ruohan Feng
- Department of Radiology, The Third Hospital of Mianyang/Sichuan Mental Health Center, Mianyang, China
| | - Chungen Tang
- Department of Radiology, The Third Hospital of Mianyang/Sichuan Mental Health Center, Mianyang, China
| | - Su Lui
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, China.
- Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
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Wang LN, Lin S, Tian L, Wu H, Jin WQ, Wang W, Pan WG, Yang CL, Ren YP, Ma X, Tang YL. Subregional thalamic functional connectivity abnormalities and cognitive impairments in first-episode schizophrenia. Asian J Psychiatr 2024; 96:104042. [PMID: 38615577 DOI: 10.1016/j.ajp.2024.104042] [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: 01/01/2024] [Revised: 03/15/2024] [Accepted: 03/31/2024] [Indexed: 04/16/2024]
Abstract
BACKGROUND Previous studies have documented thalamic functional connectivity (FC) abnormalities in schizophrenia, typically examining the thalamus as a whole. The specific link between subregional thalamic FC and cognitive deficits in first-episode schizophrenia (FES) remains unexplored. METHODS Using data from resting-state functional magnetic resonance imaging, we compared whole-brain FC with thalamic subregions between patients and HCs, and analyzed FC changes in drug-naïve patients separately. We then examined correlations between FC abnormalities with both cognitive impairment and clinical symptoms. RESULTS A total of 33 FES patients (20 drug-naïve) and 32 age- and sex-matched healthy controls (HCs) were included. Compared to HCs, FES patients exhibited increased FC between specific thalamic subregions and cortical regions, particularly bilateral middle temporal lobe and cuneus gyrus, left medial superior frontal gyrus, and right inferior/superior occipital gyrus. Decreased FC was observed between certain thalamic subregions and the left inferior frontal triangle. These findings were largely consistent in drug-naïve patients. Notably, deficits in social cognition and visual learning in FES patients correlated with increased FC between certain thalamic subregions and cortical regions involving the right superior occipital gyrus and cuneus gyrus. The severity of negative symptoms was associated with increased FC between a thalamic subregion and the left middle temporal gyrus. CONCLUSION Our findings suggest FC abnormalities between thalamic subregions and cortical areas in FES patients. Increased FC correlated with cognitive deficits and negative symptoms, highlighting the importance of thalamo-cortical connectivity in the pathophysiology of schizophrenia.
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Affiliation(s)
- Li-Na Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Shuo Lin
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Lu Tian
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Han Wu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Wen-Qing Jin
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Wen Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Wei-Gang Pan
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Chun-Lin Yang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
| | - Yan-Ping Ren
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
| | - Xin Ma
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
| | - Yi-Lang Tang
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA 30329, USA; Mental Health Service Line, Atlanta VA Medical Center, Decatur, GA 30033, USA
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Shen L, Lin X, Wang C, Chen X, Li J, Wang W, Tang J, Shan X, Yan Z, Lu Y. Longitudinal unraveling: The impact of recombinant human growth hormone on spontaneous brain activity in children with short stature-A resting-state fMRI study. J Neuroradiol 2024; 51:101159. [PMID: 37827488 DOI: 10.1016/j.neurad.2023.10.004] [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: 08/12/2023] [Revised: 10/06/2023] [Accepted: 10/09/2023] [Indexed: 10/14/2023]
Abstract
Recombinant human growth hormone (rhGH) is an approved method to improve the growth and ameliorate behavioral issues in children with short stature. However, the data concerning the effects of rhGH treatment on spontaneous brain activity remains unclear. This study included 35 children with short stature, categorized into two groups: the treated group (n = 14) and the untreated group (n = 21). All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological assessments at baseline and at the end of a one-year follow-up. The rs-fMRI based amplitude of low frequency fluctuation (ALFF) analysis method was employed to assess spontaneous brain activity. Interaction effects between rhGH and time on ALFF were detected using a mixed-effects analysis. Additionally, Stepwise regression analysis was conducted to investigate the associations between ALFF values and significant clinical indicators. The treated group exhibited significant improvements in height, weight, insulin-like growth factor-1 (IGF-1) levels, insulin-like growth factor binding protein 3 (IGFBP-3) levels, and processing speed index (PSI) when reevaluated from baseline. The interaction effect of rhGH × time was evident in the right putamen (RPUT), where the ALFF value showed a significant increase following rhGH treatment, while also demonstrating a notable positive correlation with height. Moreover, The main effect of time was manifested as a significant decrease in the ALFF value of the left dorsolateral superior frontal gyrus (LSFG) within the untreated group during the follow-up period, concurrently displaying a positive correlation with age. In conclusion, rhGH treatment not only has a positive effect on the growth, cognition, and behavior of children with short stature, but also improves and normalizes spontaneous brain activity.
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Affiliation(s)
- Liting Shen
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Xingtong Lin
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Chenyan Wang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Xian Chen
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Jie Li
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Weiyi Wang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Jing Tang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Xiaoou Shan
- Department of Pediatric Endocrinology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China
| | - Zhihan Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China.
| | - Yi Lu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, China.
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Faris P, Pischedda D, Palesi F, D’Angelo E. New clues for the role of cerebellum in schizophrenia and the associated cognitive impairment. Front Cell Neurosci 2024; 18:1386583. [PMID: 38799988 PMCID: PMC11116653 DOI: 10.3389/fncel.2024.1386583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 04/26/2024] [Indexed: 05/29/2024] Open
Abstract
Schizophrenia (SZ) is a complex neuropsychiatric disorder associated with severe cognitive dysfunction. Although research has mainly focused on forebrain abnormalities, emerging results support the involvement of the cerebellum in SZ physiopathology, particularly in Cognitive Impairment Associated with SZ (CIAS). Besides its role in motor learning and control, the cerebellum is implicated in cognition and emotion. Recent research suggests that structural and functional changes in the cerebellum are linked to deficits in various cognitive domains including attention, working memory, and decision-making. Moreover, cerebellar dysfunction is related to altered cerebellar circuit activities and connectivity with brain regions associated with cognitive processing. This review delves into the role of the cerebellum in CIAS. We initially consider the major forebrain alterations in CIAS, addressing impairments in neurotransmitter systems, synaptic plasticity, and connectivity. We then focus on recent findings showing that several mechanisms are also altered in the cerebellum and that cerebellar communication with the forebrain is impaired. This evidence implicates the cerebellum as a key component of circuits underpinning CIAS physiopathology. Further studies addressing cerebellar involvement in SZ and CIAS are warranted and might open new perspectives toward understanding the physiopathology and effective treatment of these disorders.
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Affiliation(s)
- Pawan Faris
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Doris Pischedda
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Fulvia Palesi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Egidio D’Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Digital Neuroscience Center, IRCCS Mondino Foundation, Pavia, Italy
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Feng S, Huang Y, Lu H, Li H, Zhou S, Lu H, Feng Y, Ning Y, Han W, Chang Q, Zhang Z, Liu C, Li J, Wu K, Wu F. Association between degree centrality and neurocognitive impairments in patients with Schizophrenia: A Longitudinal rs-fMRI Study. J Psychiatr Res 2024; 173:115-123. [PMID: 38520845 DOI: 10.1016/j.jpsychires.2024.03.007] [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: 09/11/2023] [Revised: 02/27/2024] [Accepted: 03/04/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Evidence indicates that patients with schizophrenia (SZ) experience significant changes in their functional connectivity during antipsychotic treatment. Despite previous reports of changes in brain network degree centrality (DC) in patients with schizophrenia, the relationship between brain DC changes and neurocognitive improvement in patients with SZ after antipsychotic treatment remains elusive. METHODS A total of 74 patients with acute episodes of chronic SZ and 53 age- and sex-matched healthy controls were recruited. The Positive and Negative Syndrome Scale (PANSS), Symbol Digit Modalities Test, digital span test (DST), and verbal fluency test were used to evaluate the clinical symptoms and cognitive performance of the patients with SZ. Patients with SZ were treated with antipsychotics for six weeks starting at baseline and underwent MRI and clinical interviews at baseline and after six weeks, respectively. We then divided the patients with SZ into responding (RS) and non-responding (NRS) groups based on the PANSS scores (reduction rate of PANSS ≥50%). DC was calculated and analyzed to determine its correlation with clinical symptoms and cognitive performance. RESULTS After antipsychotic treatment, the patients with SZ showed significant improvements in clinical symptoms, semantic fluency performance. Correlation analysis revealed that the degree of DC increase in the left anterior inferior parietal lobe (aIPL) after treatment was negatively correlated with changes in the excitement score (r = -0.256, p = 0.048, adjusted p = 0.080), but this correlation failed the multiple test correction. Patients with SZ showed a significant negative correlation between DC values in the left aIPL and DST scores after treatment, which was not observed at the baseline (r = -0.359, p = 0.005, adjusted p = 0.047). In addition, we did not find a significant difference in DC between the RS and NRS groups, neither at baseline nor after treatment. CONCLUSIONS The results suggested that DC changes in patients with SZ after antipsychotic treatment are correlated with neurocognitive performance. Our findings provide new insights into the neuropathological mechanisms underlying antipsychotic treatment of SZ.
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Affiliation(s)
- Shixuan Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuanyuan Huang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hongxin Lu
- Department of Psychiatry, Longyan Third Hospital of Fujian Province, Longyan, China
| | - Hehua Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Sumiao Zhou
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hanna Lu
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yangdong Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuping Ning
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China
| | - Wei Han
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qing Chang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ziyun Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chenyu Liu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Junhao Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kai Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China; Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China; National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China; Key Laboratory of Biomedical Engineering of Guangdong Province, South China University of Technology, Guangzhou, China; Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital, Guangzhou, China; Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
| | - Fengchun Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China.
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8
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Li H, Huang Y, Liang L, Li H, Li S, Feng Y, Feng S, Wu K, Wu F. The relationship between the gut microbiota and oxidative stress in the cognitive function of schizophrenia: A pilot study in China. Schizophr Res 2024; 267:444-450. [PMID: 38643725 DOI: 10.1016/j.schres.2024.03.053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 03/22/2024] [Accepted: 03/31/2024] [Indexed: 04/23/2024]
Abstract
Cognitive impairment is a core symptom of schizophrenia. The gut microbiota (GM) and oxidative stress may play important roles in the pathophysiological mechanisms of cognitive impairment. This study aimed to explore the relationship between GM and oxidative stress in the cognitive function of schizophrenia. GM obtained by 16S RNA sequencing and serum superoxide dismutase (SOD) levels from schizophrenia patients (N = 68) and healthy controls (HCs, N = 72) were analyzed. All psychiatric symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). Cognitive function was assessed using the MATRICS Consensus Cognitive Battery (MCCB). Correlation analysis was used to explore the relationship between GM, SOD, and cognitive function. Machine learning models were used to identify potential biomarkers. Compared to HCs, the relative abundances of Collinsella, undefined Ruminococcus, Lactobacillus, Eubacterium, Mogibacterium, Desulfovibrio, Bulleidia, Succinivibrio, Corynebacterium, and Atopobium were higher in patients with schizophrenia, but Faecalibacterium, Anaerostipes, Turicibacter, and Ruminococcus were lower. In patients with schizophrenia, the positive factor, general factor, and total score of MCCB positively correlated with Lactobacillus, Collinsella, and Lactobacillus, respectively; SOD negatively correlated with Eubacterium, Collinsella, Lactobacillus, Corynebacterium, Bulleidia, Mogibacterium, and Succinivibrio, but positively correlated with Faecalibacterium, Ruminococcus, and MCCB verbal learning index scores; Faecalibacterium and Turicibacter were positively correlated with MCCB visual learning index scores and speed of processing index scores, respectively. Our findings revealed a correlation between SOD and GM and confirmed that cognitive dysfunction in patients with schizophrenia involves abnormal SOD levels and GM changes.
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Affiliation(s)
- Hehua Li
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuanyuan Huang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Liqin Liang
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China
| | - Hanqiu Li
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Shijia Li
- Swammerdam Institute for Life Sciences (SILS)-University of Amsterdam, Amsterdam, the Netherlands
| | - Yangdong Feng
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Shixuan Feng
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kai Wu
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China.
| | - Fengchun Wu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China.
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9
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Gan L, Wang L, Liu H, Wang G. Based on neural network cascade abnormal texture information dissemination of classification of patients with schizophrenia and depression. Brain Res 2024; 1830:148819. [PMID: 38403037 DOI: 10.1016/j.brainres.2024.148819] [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: 08/22/2023] [Revised: 02/11/2024] [Accepted: 02/20/2024] [Indexed: 02/27/2024]
Abstract
This study used MRI brain image segmentation to identify novel magnetic resonance imaging (MRI) biomarkers to distinguish patients with schizophrenia (SCZ), major depressive disorder (MD), and healthy control (HC). Brain texture measurements, including entropy and contrast, were calculated to capture variability in adjacent MRI voxel intensity. These measures are then applied to group classification in deep learning techniques and combined with hierarchical correlations to locate results. Texture feature maps were extracted from segmented brain MRI scans of 141 patients with schizophrenia (SCZ), 103 patients with major depressive disorder (MD) and 238 healthy controls (HC). Gray scale coassociation matrix (GLCM) is a monomer matrix calculated in a voxel cube. Deep learning methods were evaluated to determine the application capability of texture feature mapping in binary classification (SCZ vs. HC, MD vs. HC, SCZ vs. MD). The method is implemented by repeated nesting and cross-validation for feature selection. Regions that show the highest correlation (positive or negative). In this study, the authors successfully classified SCZ, MD and HC. This suggests that texture analysis can be used as an effective feature extraction method to distinguish different disease states. Compared with other methods, texture analysis can capture richer image information and improve classification accuracy in some cases. The classification accuracy of SCZ and HC, MD and HC, SCZ and MD reached 84.6%, 86.4% and 76.21%, respectively. Among them, SCZ and HC are the most significant features with high sensitivity and specificity.
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Affiliation(s)
- Linfeng Gan
- School of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, China
| | - Linfeng Wang
- School of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, China
| | - Hu Liu
- Peking University Health Science Center, Institute of Medical Technology, Beijing 100069, China.
| | - Gang Wang
- School of Railway Transportation, Shanghai Institute of Technology, Shanghai 201418, China
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10
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Wang Y, Yang Y, Xu W, Yao X, Xie X, Zhang L, Sun J, Wang L, Hua Q, He K, Tian Y, Wang K, Ji GJ. Heterogeneous Brain Abnormalities in Schizophrenia Converge on a Common Network Associated With Symptom Remission. Schizophr Bull 2024; 50:545-556. [PMID: 38253437 PMCID: PMC11059819 DOI: 10.1093/schbul/sbae003] [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: 01/24/2024]
Abstract
BACKGROUND AND HYPOTHESIS There is a huge heterogeneity of magnetic resonance imaging findings in schizophrenia studies. Here, we hypothesized that brain regions identified by structural and functional imaging studies of schizophrenia could be reconciled in a common network. STUDY DESIGN We systematically reviewed the case-control studies that estimated the brain morphology or resting-state local function for schizophrenia patients in the literature. Using the healthy human connectome (n = 652) and a validated technique "coordinate network mapping" to identify a common brain network affected in schizophrenia. Then, the specificity of this schizophrenia network was examined by independent data collected from 13 meta-analyses. The clinical relevance of this schizophrenia network was tested on independent data of medication, neuromodulation, and brain lesions. STUDY RESULTS We identified 83 morphological and 60 functional studies comprising 7389 patients with schizophrenia and 7408 control subjects. The "coordinate network mapping" showed that the atrophy and dysfunction coordinates were functionally connected to a common network although they were spatially distant from each other. Taking all 143 studies together, we identified the schizophrenia network with hub regions in the bilateral anterior cingulate cortex, insula, temporal lobe, and subcortical structures. Based on independent data from 13 meta-analyses, we showed that these hub regions were specifically connected with regions of cortical thickness changes in schizophrenia. More importantly, this schizophrenia network was remarkably aligned with regions involving psychotic symptom remission. CONCLUSIONS Neuroimaging abnormalities in cross-sectional schizophrenia studies converged into a common brain network that provided testable targets for developing precise therapies.
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Affiliation(s)
- Yingru Wang
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
| | - Yinian Yang
- Department of Clinical Psychiatry, School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Wenqiang Xu
- Department of Clinical Psychiatry, School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Xiaoqing Yao
- Department of Clinical Psychiatry, School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
| | - Xiaohui Xie
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
| | - Long Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
| | - Jinmei Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
| | - Lu Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
| | - Qiang Hua
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
| | - Kongliang He
- Department of Psychiatry, Fourth People’s Hospital of Hefei, Anhui Mental Health Center, Hefei, China
| | - Yanghua Tian
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders,Hefei, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
- Anhui Institute of Translational Medicine, Hefei, China
| | - Gong-Jun Ji
- Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, China
- Department of Clinical Psychiatry, School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders,Hefei, China
- Collaborative Innovation Centre of Neuropsychiatric Disorder and Mental Health, Hefei, China
- Anhui Institute of Translational Medicine, Hefei, China
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11
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Geffen T, Hardikar S, Smallwood J, Kaliuzhna M, Carruzzo F, Böge K, Zierhut MM, Gutwinski S, Katthagen T, Kaiser S, Schlagenhauf F. Striatal Functional Hypoconnectivity in Patients With Schizophrenia Suffering From Negative Symptoms, Longitudinal Findings. Schizophr Bull 2024:sbae052. [PMID: 38687874 DOI: 10.1093/schbul/sbae052] [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: 05/02/2024]
Abstract
BACKGROUND Negative symptoms in schizophrenia (SZ), such as apathy and diminished expression, have limited treatments and significantly impact daily life. Our study focuses on the functional division of the striatum: limbic-motivation and reward, associative-cognition, and sensorimotor-sensory and motor processing, aiming to identify potential biomarkers for negative symptoms. STUDY DESIGN This longitudinal, 2-center resting-state-fMRI (rsfMRI) study examines striatal seeds-to-whole-brain functional connectivity. We examined connectivity aberrations in patients with schizophrenia (PwSZ), focusing on stable group differences across 2-time points using intra-class-correlation and associated these with negative symptoms and measures of cognition. Additionally, in PwSZ, we used negative symptoms to predict striatal connectivity aberrations at the baseline and used the striatal aberration to predict symptoms 9 months later. STUDY RESULTS A total of 143 participants (77 PwSZ, 66 controls) from 2 centers (Berlin/Geneva) participated. We found sensorimotor-striatum and associative-striatum hypoconnectivity. We identified 4 stable hypoconnectivity findings over 3 months, revealing striatal-fronto-parietal-cerebellar hypoconnectivity in PwSZ. From those findings, we found hypoconnectivity in the bilateral associative striatum with the bilateral paracingulate-gyrus and the anterior cingulate cortex in PwSZ. Additionally, hypoconnectivity between the associative striatum and the superior frontal gyrus was associated with lower cognition scores in PwSZ, and weaker sensorimotor striatum connectivity with the superior parietal lobule correlated negatively with diminished expression and could predict symptom severity 9 months later. CONCLUSIONS Importantly, patterns of weaker sensorimotor striatum and superior parietal lobule connectivity fulfilled the biomarker criteria: clinical significance, reflecting underlying pathophysiology, and stability across time and centers.
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Affiliation(s)
- Tal Geffen
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, NeuroCure Clinical Research Center (NCRC), Campus Mitte, Berlin, Germany
| | - Samyogita Hardikar
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | - Mariia Kaliuzhna
- Clinical and Experimental Psychopathology Laboratory, University of Geneva, Faculty of Medicine, Geneva, Switzerland
| | - Fabien Carruzzo
- Clinical and Experimental Psychopathology Laboratory, University of Geneva, Faculty of Medicine, Geneva, Switzerland
| | - Kerem Böge
- Department of Psychiatry and Neuroscience, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
- German Center for Mental Health (DZPG), Partner Site, Berlin, Germany
| | - Marco Matthäus Zierhut
- Department of Psychiatry and Neuroscience, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
- German Center for Mental Health (DZPG), Partner Site, Berlin, Germany
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Clinician Scientist Program, Berlin, Germany
| | - Stefan Gutwinski
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, NeuroCure Clinical Research Center (NCRC), Campus Mitte, Berlin, Germany
| | - Teresa Katthagen
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, NeuroCure Clinical Research Center (NCRC), Campus Mitte, Berlin, Germany
| | - Stephan Kaiser
- Adult Psychiatry Division, Department of Psychiatry, Geneva University Hospital, Geneva, Switzerland
| | - Florian Schlagenhauf
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, NeuroCure Clinical Research Center (NCRC), Campus Mitte, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
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12
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Chang Z, Liu L, Lin L, Wang G, Zhang C, Tian H, Liu W, Wang L, Zhang B, Ren J, Zhang Y, Xie Y, Du X, Wei X, Wei L, Luo Y, Dong H, Li X, Zhao Z, Liang M, Zhang C, Wang X, Yu C, Qin W, Liu H. Selective disrupted gray matter volume covariance of amygdala subregions in schizophrenia. Front Psychiatry 2024; 15:1349989. [PMID: 38742128 PMCID: PMC11090100 DOI: 10.3389/fpsyt.2024.1349989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 04/11/2024] [Indexed: 05/16/2024] Open
Abstract
Objective Although extensive structural and functional abnormalities have been reported in schizophrenia, the gray matter volume (GMV) covariance of the amygdala remain unknown. The amygdala contains several subregions with different connection patterns and functions, but it is unclear whether the GMV covariance of these subregions are selectively affected in schizophrenia. Methods To address this issue, we compared the GMV covariance of each amygdala subregion between 807 schizophrenia patients and 845 healthy controls from 11 centers. The amygdala was segmented into nine subregions using FreeSurfer (v7.1.1), including the lateral (La), basal (Ba), accessory-basal (AB), anterior-amygdaloid-area (AAA), central (Ce), medial (Me), cortical (Co), corticoamygdaloid-transition (CAT), and paralaminar (PL) nucleus. We developed an operational combat harmonization model for 11 centers, subsequently employing a voxel-wise general linear model to investigate the differences in GMV covariance between schizophrenia patients and healthy controls across these subregions and the entire brain, while adjusting for age, sex and TIV. Results Our findings revealed that five amygdala subregions of schizophrenia patients, including bilateral AAA, CAT, and right Ba, demonstrated significantly increased GMV covariance with the hippocampus, striatum, orbitofrontal cortex, and so on (permutation test, P< 0.05, corrected). These findings could be replicated in most centers. Rigorous correlation analysis failed to identify relationships between the altered GMV covariance with positive and negative symptom scale, duration of illness, and antipsychotic medication measure. Conclusion Our research is the first to discover selectively impaired GMV covariance patterns of amygdala subregion in a large multicenter sample size of patients with schizophrenia.
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Affiliation(s)
- Zhongyu Chang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Liping Liu
- Department of Psychiatry, The First Psychiatric Hospital of Harbin, Harbin, Heilongjiang, China
| | - Liyuan Lin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Gang Wang
- Wuhan Mental Health Center, The Ninth Clinical School, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chen Zhang
- Department of Biochemistry and Psychopharmacology, Shanghai Mental Health Center, Shanghai, China
| | - Hongjun Tian
- Department of Psychiatry, Tianjin Fourth Center Hospital, The Fourth Central Clinical College, Tianjin Medical University, Tianjin, China
| | - Wei Liu
- Department of Psychiatry, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Lina Wang
- Department of Psychiatry, Tianjin Fourth Center Hospital, The Fourth Central Clinical College, Tianjin Medical University, Tianjin, China
| | - Bin Zhang
- Department of Psychiatry, Tianjin Fourth Center Hospital, The Fourth Central Clinical College, Tianjin Medical University, Tianjin, China
| | - Juanjuan Ren
- Department of Biochemistry and Psychopharmacology, Shanghai Mental Health Center, Shanghai, China
| | - Yu Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yingying Xie
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiaotong Du
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xiaotong Wei
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Luli Wei
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yun Luo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Haoyang Dong
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Xin Li
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhen Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Meng Liang
- School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Congpei Zhang
- Department of Psychiatry, The First Psychiatric Hospital of Harbin, Harbin, Heilongjiang, China
| | - Xijin Wang
- Department of Psychiatry, The First Psychiatric Hospital of Harbin, Harbin, Heilongjiang, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- School of Medical Imaging, Tianjin Medical University, Tianjin, China
- State Key Laboratory of Experimental Hematology, Tianjin Medical University General Hospital, Tianjin, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Huaigui Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
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13
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Yang Y, Jin X, Xue Y, Li X, Chen Y, Kang N, Yan W, Li P, Guo X, Luo B, Zhang Y, Liu Q, Shi H, Zhang L, Su X, Liu B, Lu L, Lv L, Li W. Right superior frontal gyrus: A potential neuroimaging biomarker for predicting short-term efficacy in schizophrenia. Neuroimage Clin 2024; 42:103603. [PMID: 38588618 PMCID: PMC11015154 DOI: 10.1016/j.nicl.2024.103603] [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: 01/11/2024] [Revised: 03/24/2024] [Accepted: 04/02/2024] [Indexed: 04/10/2024]
Abstract
Antipsychotic drug treatment for schizophrenia (SZ) can alter brain structure and function, but it is unclear if specific regional changes are associated with treatment outcome. Therefore, we examined the effects of antipsychotic drug treatment on regional grey matter (GM) density, white matter (WM) density, and functional connectivity (FC) as well as associations between regional changes and treatment efficacy. SZ patients (n = 163) and health controls (HCs) (n = 131) were examined by structural magnetic resonance imaging (sMRI) at baseline, and a subset of SZ patients (n = 77) were re-examined after 8 weeks of second-generation antipsychotic treatment to assess changes in regional GM and WM density. In addition, 88 SZ patients and 81 HCs were examined by resting-state functional MRI (rs-fMRI) at baseline and the patients were re-examined post-treatment to examine FC changes. The Positive and Negative Syndrome Scale (PANSS) and MATRICS Consensus Cognitive Battery (MCCB) were applied to measure psychiatric symptoms and cognitive impairments in SZ. SZ patients were then stratified into response and non-response groups according to PANSS score change (≥50 % decrease or <50 % decrease, respectively). The GM density of the right cingulate gyrus, WM density of the right superior frontal gyrus (SFG) plus 5 other WM tracts were reduced in the response group compared to the non-response group. The FC values between the right anterior cingulate and paracingulate gyrus and left thalamus were reduced in the entire SZ group (n = 88) after treatment, while FC between the right inferior temporal gyrus (ITG) and right medial superior frontal gyrus (SFGmed) was increased in the response group. There were no significant changes in regional FC among the non-response group after treatment and no correlations with symptom or cognition test scores. These findings suggest that the right SFG is a critical target of antipsychotic drugs and that WM density and FC alterations within this region could be used as potential indicators in predicting the treatment outcome of antipsychotics of SZ.
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Affiliation(s)
- Yongfeng Yang
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Xueyan Jin
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Yongjiang Xue
- The Second Clinical College of Xinxiang Medical University, Xinxiang 453002, China
| | - Xue Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Yi Chen
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Ning Kang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Wei Yan
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China
| | - Peng Li
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China
| | - Xiaoge Guo
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Binbin Luo
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Yan Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Qing Liu
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Han Shi
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Luwen Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Xi Su
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Chinese Institute for Brain Research, Beijing 102206, China
| | - Lin Lu
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing 100191, China; National Institute on Drug Dependence, Beijing Key Laboratory of Drug Dependence, Peking University, Beijing 100191, China; Peking-Tsinghua Centre for Life Sciences and PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China.
| | - Wenqiang Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China; Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China; Henan Collaborative Innovation Center of Prevention and Treatment of Mental Disorder, Xinxiang 453002, China.
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14
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Li F, Zhao Q, Tang T, Liu Y, Wang Z, Wang Z, Han X, Xu Z, Chang Y, Li Y. Brain imaging derived phenotypes: a biomarker for the onset of inflammatory bowel disease and a potential mediator of mental complications. Front Immunol 2024; 15:1359540. [PMID: 38469291 PMCID: PMC10925669 DOI: 10.3389/fimmu.2024.1359540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/14/2024] [Indexed: 03/13/2024] Open
Abstract
Background and aims Inflammatory bowel disease (IBD), mainly categorized into Crohn's disease (CD) and ulcerative colitis (UC), is a chronic relapsing gastrointestinal disorder that significantly impairs patients' quality of life. IBD patients often experience comorbidities such as anxiety and depression, and the underlying mechanisms and treatment strategies remain areas of investigation. Methods We conducted a Mendelian randomization(MR) analysis utilizing brain image derived phenotypes (IDP) from the UK Biobank database to investigate the causal relationships between IBD and alterations in brain structural morphology and connectivity of neural tracts. This study aimed to identify biological evidence linking IBD to psychiatric disorders such as anxiety and depression. Results Specifically, the volume of grey matter in the Left Frontal Orbital Cortex exhibited a negative association with the onset of Crohn's disease (odds ratio (OR) [95% confidence interval (CI)]: 0.315[0.180~0.551], adjusted P=0.001), while the volume of the superior frontal cortex in the right hemisphere showed a positive correlation with the development of Ulcerative colitis (OR [95% CI]: 2.285[1.793~2.911], adjusted P<0.001), and the volume of lateral occipital cortex in the left hemisphere demonstrated a positive relationship with Crohn's disease onset (OR [95% CI]: 1.709[1.671~1.747], adjusted P<0.001). In the context of reverse causality, the onset of UC or CD has led to alterations in imaging derived phenotypes associated with five disorders (anxiety, depression, schizophrenia, bipolar disorder, pain) and three functions (memory, emotion, language). Conclusion Our study has demonstrated a causal relationship between IBD and IDPs. IDPs may serve as potential biomarkers for the progression of IBD and as predictive intermediaries for the development of neurological diseases in IBD patients.
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Affiliation(s)
- Fan Li
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Qi Zhao
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Tongyu Tang
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
| | - Yuyuan Liu
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Zhaodi Wang
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Zhi Wang
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Xiaoping Han
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Zifeng Xu
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Yu Chang
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
- Norman Bethune Health Science Center, Jilin University, Changchun, China
| | - Yuqin Li
- Department of Gastroenterology, The First Hospital of Jilin University, Changchun, China
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Xiong J, Ding Y, Wu X, Zhan J, Wan Q, Wan H, Wei B, Chen H, Yang Y. Association between serum insulin-like growth factor 1 levels and the improvements of cognitive impairments in a subgroup of schizophrenia: Preliminary findings. Schizophr Res 2024; 264:282-289. [PMID: 38198881 DOI: 10.1016/j.schres.2024.01.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 12/18/2023] [Accepted: 01/01/2024] [Indexed: 01/12/2024]
Abstract
BACKGROUND Numerous studies have implicated abnormal insulin-like growth factor 1 (IGF-1) in the pathophysiology of schizophrenia, but findings have been inconsistent. METHODS We conducted a meta-analysis to compare IGF-1 levels in schizophrenia patients with healthy controls and explored factors contributing to variability between estimates. In an independent sample (58 chronic schizophrenia patients and 30 healthy controls), we investigated differences in IGF-1 levels among schizophrenia subgroups with distinct cognitive profiles, identified using k-means clustering based on five cognitive domains from The Repeatable Battery for the Assessment of Neuropsychological Status. Associations between serum IGF-1 levels and clinical and neurocognitive improvements were also examined. RESULTS The meta-analysis revealed significantly lower serum IGF-1 levels in schizophrenia patients compared to healthy controls, albeit with high heterogeneity. Medication status, BMI, and severity of negative symptoms were identified as potential contributors to this heterogeneity. In our independent study, antipsychotic treatment led to a significant increase in IGF-1 levels, and lower pre-treatment serum IGF-1 levels correlated with greater improvement in cognitive deficits, particularly in a subgroup with more severe cognitive symptoms. CONCLUSIONS Our findings support the "IGF-1 deficiency hypothesis" in the pathogenesis of schizophrenia. Further research is crucial to elucidate the role of IGF-1 in the cognitive impairments associated with schizophrenia.
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Affiliation(s)
- Jianwen Xiong
- Department of Psychiatry, Jiangxi Mental Hospital & Affiliated Mental Hospital of Nanchang University, Nanchang 330029, Jiangxi, China; Nanchang City Key Laboratory of Biological Psychiatry, Jiangxi Mental Hospital, Nanchang 330029, Jiangxi, China
| | - Yudan Ding
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Xiaopeng Wu
- Department of Psychiatry, Jiangxi Mental Hospital & Affiliated Mental Hospital of Nanchang University, Nanchang 330029, Jiangxi, China
| | - Jinqiong Zhan
- Department of Psychiatry, Jiangxi Mental Hospital & Affiliated Mental Hospital of Nanchang University, Nanchang 330029, Jiangxi, China; Nanchang City Key Laboratory of Biological Psychiatry, Jiangxi Mental Hospital, Nanchang 330029, Jiangxi, China
| | - Qigen Wan
- Department of Psychiatry, Jiangxi Mental Hospital & Affiliated Mental Hospital of Nanchang University, Nanchang 330029, Jiangxi, China
| | - Hongying Wan
- Department of Psychiatry, Jiangxi Mental Hospital & Affiliated Mental Hospital of Nanchang University, Nanchang 330029, Jiangxi, China
| | - Bo Wei
- Department of Psychiatry, Jiangxi Mental Hospital & Affiliated Mental Hospital of Nanchang University, Nanchang 330029, Jiangxi, China; Nanchang City Key Laboratory of Biological Psychiatry, Jiangxi Mental Hospital, Nanchang 330029, Jiangxi, China.
| | - Haibo Chen
- Department of Psychiatry, Jiangxi Mental Hospital & Affiliated Mental Hospital of Nanchang University, Nanchang 330029, Jiangxi, China.
| | - Yuanjian Yang
- Department of Psychiatry, Jiangxi Mental Hospital & Affiliated Mental Hospital of Nanchang University, Nanchang 330029, Jiangxi, China; Nanchang City Key Laboratory of Biological Psychiatry, Jiangxi Mental Hospital, Nanchang 330029, Jiangxi, China.
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16
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Cattarinussi G, Grimaldi DA, Sambataro F. Spontaneous Brain Activity Alterations in First-Episode Psychosis: A Meta-analysis of Functional Magnetic Resonance Imaging Studies. Schizophr Bull 2023; 49:1494-1507. [PMID: 38029279 PMCID: PMC10686347 DOI: 10.1093/schbul/sbad044] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
BACKGROUND AND HYPOTHESIS Several studies have shown that spontaneous brain activity, including the total and fractional amplitude of low-frequency fluctuations (LFF) and regional homogeneity (ReHo), is altered in psychosis. Nonetheless, neuroimaging results show a high heterogeneity. For this reason, we gathered the extant literature on spontaneous brain activity in first-episode psychosis (FEP), where the effects of long-term treatment and chronic disease are minimal. STUDY DESIGN A systematic research was conducted on PubMed, Scopus, and Web of Science to identify studies exploring spontaneous brain activity and local connectivity in FEP estimated using functional magnetic resonance imaging. 20 LFF and 15 ReHo studies were included. Coordinate-Based Activation Likelihood Estimation Meta-Analyses stratified by brain measures, age (adolescent vs adult), and drug-naïve status were performed to identify spatially-convergent alterations in spontaneous brain activity in FEP. STUDY RESULTS We found a significant increase in LFF in FEP compared to healthy controls (HC) in the right striatum and in ReHo in the left striatum. When pooling together all studies on LFF and ReHo, spontaneous brain activity was increased in the bilateral striatum and superior and middle frontal gyri and decreased in the right precentral gyrus and the right inferior frontal gyrus compared to HC. These results were also replicated in the adult and drug-naïve samples. CONCLUSIONS Abnormalities in the frontostriatal circuit are present in early psychosis independently of treatment status. Our findings support the view that altered frontostriatal can represent a core neural alteration of the disorder and could be a target of treatment.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, Padua, Italy
| | | | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Padua, Italy
- Department of Neuroscience (DNS), Padova Neuroscience Center, University of Padova, Padua, Italy
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17
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Zorzo C, Solares L, Mendez M, Mendez-Lopez M. Hippocampal alterations after SARS-CoV-2 infection: A systematic review. Behav Brain Res 2023; 455:114662. [PMID: 37703951 DOI: 10.1016/j.bbr.2023.114662] [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: 06/23/2023] [Revised: 08/30/2023] [Accepted: 09/08/2023] [Indexed: 09/15/2023]
Abstract
SARS-CoV-2 infection produces a wide range of symptoms. Some of the structural changes caused by the virus in the nervous system are found in the medial temporal lobe, and several neuropsychological sequelae of COVID-19 are related to the function of the hippocampus. The main objective of the systematic review is to update and further analyze the existing evidence of hippocampal and related cortices' structural and functional alterations due to SARS-CoV-2 infection. Both clinical and preclinical studies that used different methodologies to explore the effects of this disease at different stages and grades of severity were considered, besides exploring related cognitive and emotional symptomatology. A total of 24 studies were identified by searching in SCOPUS, Web Of Science (WOS), PubMed, and PsycInfo databases up to October 3rd, 2022. Thirteen studies were performed in clinical human samples, 9 included preclinical animal models, 3 were performed post-mortem, and 1 included both post-mortem and preclinical samples. Alterations in the hippocampus were detected in the acute stage and after several months of infection. Clinical studies revealed alterations in hippocampal connectivity and metabolism. Memory alterations correlated with altered metabolic profiles or changes in grey matter volumes. Hippocampal human postmortem and animal studies observed alterations in neurogenesis, dendrites, and immune response, besides high apoptosis and neuroinflammation. Preclinical studies reported the viral load in the hippocampus. Olfactory dysfunction was associated with alterations in brain functionality. Several clinical studies revealed cognitive complaints, neuropsychological alterations, and depressive and anxious symptomatology.
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Affiliation(s)
- Candela Zorzo
- Neuroscience Institute of Principado de Asturias (INEUROPA), Faculty of Psychology, Plaza Feijoo s/n, 33003 Oviedo, Asturias, Spain; Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Av. del Hospital Universitario, s/n, 33011 Oviedo, Asturias, Spain; Department of Psychology, University of Oviedo, Faculty of Psychology, Plaza Feijoo s/n, 33003 Oviedo, Asturias, Spain.
| | - Lucía Solares
- Department of Psychology, University of Oviedo, Faculty of Psychology, Plaza Feijoo s/n, 33003 Oviedo, Asturias, Spain.
| | - Marta Mendez
- Neuroscience Institute of Principado de Asturias (INEUROPA), Faculty of Psychology, Plaza Feijoo s/n, 33003 Oviedo, Asturias, Spain; Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Av. del Hospital Universitario, s/n, 33011 Oviedo, Asturias, Spain; Department of Psychology, University of Oviedo, Faculty of Psychology, Plaza Feijoo s/n, 33003 Oviedo, Asturias, Spain.
| | - Magdalena Mendez-Lopez
- Department of Psychology and Sociology, University of Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza, Aragón, Spain; IIS Aragón, San Juan Bosco, 13, 50009 Zaragoza, Aragón, Spain.
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18
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Zhang Y, Yang T, He Y, Meng F, Zhang K, Jin X, Cui X, Luo X. Value of P300 amplitude in the diagnosis of untreated first-episode schizophrenia and psychosis risk syndrome in children and adolescents. BMC Psychiatry 2023; 23:743. [PMID: 37828471 PMCID: PMC10571359 DOI: 10.1186/s12888-023-05218-5] [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: 04/01/2023] [Accepted: 09/23/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND Identifying the characteristic neurobiological changes of early psychosis is helpful for early clinical diagnosis. However, previous studies on the brain electrophysiology of children and adolescents with psychosis are rare. METHODS This study compared P300 amplitude at multiple electrodes between children and adolescents with first-episode schizophrenia (FES, n = 48), children and adolescents with psychosis risk syndrome (PRS, n = 24), and healthy controls (HC, n = 30). Receiver operating characteristic (ROC) analysis was used to test the ability of P300 amplitude to distinguish FES, PRS and HC individuals. RESULTS The P300 amplitude in the FES group were significantly lower than those in the HC at the Cz, Pz, and Oz electrodes. The P300 amplitude was also significantly lower in the prodromal group than in the HC at the Pz and Oz electrodes. ROC curve analysis showed that at the Pz electrode, the P300 amplitude evoked by the target and standard stimulus showed high sensitivity, specificity, accuracy, and area under the curve value for distinguishing FES from HC individuals. CONCLUSIONS This study found early visual P300 deficits in children and adolescents with FES and PRS, with the exclusion of possible influence of medication and chronic medical conditions, suggesting the value of P300 amplitude for the identification of early psychosis.
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Affiliation(s)
- Yaru Zhang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Tingyu Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Yuqiong He
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Fanchao Meng
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Kun Zhang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Xingyue Jin
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Xilong Cui
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China.
| | - Xuerong Luo
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China.
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19
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Wu Y, Wang H, Li C, Zhang C, Li Q, Shao Y, Yang Z, Li C, Fan Q. Deficits in Key Brain Network for Social Interaction in Individuals with Schizophrenia. Brain Sci 2023; 13:1403. [PMID: 37891773 PMCID: PMC10605178 DOI: 10.3390/brainsci13101403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/24/2023] [Accepted: 09/29/2023] [Indexed: 10/29/2023] Open
Abstract
Individuals with schizophrenia (SZ) show impairment in social functioning. The reward network and the emotional salience network are considered to play important roles in social interaction. The current study investigated alterations in the resting-state (rs-) amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo) and functional connectivity (fc) in the reward network and the emotional salience network in SZ patients. MRI scans were collected from 60 subjects, including 30 SZ patients and 30 matched healthy controls. SZ symptoms were measured using the Positive and Negative Syndrome Scale (PANSS). We analyzed the ALFF, fALFF and ReHo in key brain regions in the reward network and emotional salience network as well as rs-fc among the bilateral amygdala, lateral orbitofrontal cortex (OFC), medial OFC and insula between groups. The SZ patients demonstrated increased ALFF in the right caudate and right putamen, increased fALFF and ReHo in the bilateral caudate, putamen and pallidum, along with decreased fALFF in the bilateral insula. Additionally, reduced rs-fc was found between the right lateral OFC and the left amygdala, which simultaneously belong to the reward network and the emotional salience network. These findings highlight the association between impaired social functioning in SZ patients and aberrant resting-state ALFF, fALFF, ReHo and fc. Future studies are needed to conduct network-based statistical analysis and task-state fMRI, reflecting live social interaction to advance our understanding of the mechanism of social interaction deficits in SZ.
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Affiliation(s)
- Yiwen Wu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Hongyan Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Chuoran Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Chen Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Qingfeng Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yang Shao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Zhi Yang
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100069, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
- Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Qing Fan
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
- Mental Health Branch, China Hospital Development Institute, Shanghai Jiao Tong University, Shanghai 200030, China
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20
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Yildiz Taskiran S, Taskiran M, Unal G, Bozkurt NM, Golgeli A. The long-lasting effects of aceclofenac, a COX-2 inhibitor, in a Poly I:C-Induced maternal immune activation model of schizophrenia in rats. Behav Brain Res 2023; 452:114565. [PMID: 37414224 DOI: 10.1016/j.bbr.2023.114565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 07/01/2023] [Accepted: 07/02/2023] [Indexed: 07/08/2023]
Abstract
It is well established that rats exposed to inflammation during pregnancy or the perinatal period have an increased chance of developing schizophrenia-like symptoms and behaviors, and people with schizophrenia also have raised levels of inflammatory markers. Therefore, there is evidence supporting the idea that anti-inflammatory drugs may have therapeutic benefits. Aceclofenac is a nonsteroidal anti-inflammatory drug that has anti-inflammatory properties and is used clinically to treat inflammatory and painful processes such as osteoarthritis and rheumatoid arthritis, making it a potential candidate for preventive or adjunctive therapy in schizophrenia. This study therefore examined the effect of aceclofenac in a maternal immune activation model of schizophrenia, in which polyinosinic-polycytidylic acid (Poly I:C) (8 mg/kg, i.p.) was administered to pregnant rat dams. Young female rat pups received daily aceclofenac (5, 10, and 20 mg/kg, i.p., n = 10) between postnatal day 56 and 76. The effects of aceclofenac were compared with assessment of behavioral tests and ELISA results. During the postnatal days (PNDs) 73-76, behavioral tests were conducted in rats, and on PND 76, ELISA tests were performed to examine the changes in Tumor necrosis factor alpha (TNF-α), Interleukin-1β (IL-1β), Brain-derived neurotrophic factor (BDNF), and nestin levels. Aceclofenac treatment reversed deficits in prepulse inhibition, novel object recognition, social interaction, and locomotor activity tests. In addition, aceclofenac administration decreased TNF-α and IL-1β expression in the prefrontal cortex and hippocampus. In contrast, BDNF and nestin levels did not change significantly during treatment with aceclofenac. Taken together, these results suggest that aceclofenac may be an alternative therapeutic adjunctive strategy to improve the clinical expression of schizophrenia in the further studies.
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Affiliation(s)
| | - Mehmet Taskiran
- Department of Biology, Faculty of Science, Erciyes University, Kayseri, Türkiye
| | - Gokhan Unal
- Department of Pharmacology, Faculty of Pharmacy, Erciyes University, Kayseri, Türkiye
| | - Nuh Mehmet Bozkurt
- Department of Pharmacology, Faculty of Pharmacy, Erciyes University, Kayseri, Türkiye
| | - Asuman Golgeli
- Department of Physiology, Faculty of Medicine, Erciyes University, Kayseri, Türkiye
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21
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Qian H, Liu X, Guo Z, Wang G, Chen X, Liu J. Alterations in Resting-State Interhemispheric Coordination With Refractory Auditory Verbal Hallucinations in Schizophrenia. J Neuropsychiatry Clin Neurosci 2023; 35:385-392. [PMID: 37259546 DOI: 10.1176/appi.neuropsych.20220054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
OBJECTIVE The purpose of this study was to investigate resting-state interhemispheric functional connectivity in patients with schizophrenia and refractory auditory verbal hallucinations (RAVHs) by using voxel-mirrored homotopic connectivity (VMHC). METHODS Thirty-four patients with schizophrenia and RAVHs (RAVH group), 23 patients with schizophrenia but no auditory verbal hallucinations (non-AVH group), and 28 matched healthy volunteers (healthy control group) were recruited in China. VMHC analyses were used to identify brain areas with significant differences in functional connectivity among the three groups, and correlations between symptom scores and neurological measures were examined. RESULTS VMHC analyses showed aberrant bilateral connectivity between several homotopic brain regions: the RAVH and non-AVH groups showed differences in bilateral connectivity of the superior and middle temporal gyri, and the RAVH and healthy control groups showed differences in bilateral connectivity of the gyrus rectus, inferior frontal gyrus, and putamen. In addition, interhemispheric connectivity of the superior and middle temporal gyri correlated with patients' positive symptom scores. CONCLUSIONS These findings may help to elucidate the pathophysiological mechanisms underlying auditory verbal hallucinations. The results revealed interhemispheric functional dysconnectivity among patients with schizophrenia and suggest that the dysconnectivity of homotopic brain regions may play an important role in the development of auditory verbal hallucinations.
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Affiliation(s)
- Huichang Qian
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (Qian, J. Liu); Department of Radiology, Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, China (X. Liu); Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, China (Guo); and Departments of Radiology (Wang), Psychogeriatrics (Chen), and Science and Education (J. Liu), Hangzhou Seventh People's Hospital, Hangzhou, China
| | - Xiaozheng Liu
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (Qian, J. Liu); Department of Radiology, Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, China (X. Liu); Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, China (Guo); and Departments of Radiology (Wang), Psychogeriatrics (Chen), and Science and Education (J. Liu), Hangzhou Seventh People's Hospital, Hangzhou, China
| | - Zhongwei Guo
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (Qian, J. Liu); Department of Radiology, Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, China (X. Liu); Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, China (Guo); and Departments of Radiology (Wang), Psychogeriatrics (Chen), and Science and Education (J. Liu), Hangzhou Seventh People's Hospital, Hangzhou, China
| | - Guanjun Wang
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (Qian, J. Liu); Department of Radiology, Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, China (X. Liu); Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, China (Guo); and Departments of Radiology (Wang), Psychogeriatrics (Chen), and Science and Education (J. Liu), Hangzhou Seventh People's Hospital, Hangzhou, China
| | - Xiuhong Chen
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (Qian, J. Liu); Department of Radiology, Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, China (X. Liu); Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, China (Guo); and Departments of Radiology (Wang), Psychogeriatrics (Chen), and Science and Education (J. Liu), Hangzhou Seventh People's Hospital, Hangzhou, China
| | - Jian Liu
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China (Qian, J. Liu); Department of Radiology, Second Affiliated Hospital and Yuying Children's Hospital, Wenzhou Medical University, Wenzhou, China (X. Liu); Department of Psychiatry, Tongde Hospital of Zhejiang Province, Hangzhou, China (Guo); and Departments of Radiology (Wang), Psychogeriatrics (Chen), and Science and Education (J. Liu), Hangzhou Seventh People's Hospital, Hangzhou, China
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22
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Mısır E, Akay GG. Synaptic dysfunction in schizophrenia. Synapse 2023:e22276. [PMID: 37210696 DOI: 10.1002/syn.22276] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 04/25/2023] [Accepted: 05/07/2023] [Indexed: 05/22/2023]
Abstract
Schizophrenia is a chronic disease presented with psychotic symptoms, negative symptoms, impairment in the reward system, and widespread neurocognitive deterioration. Disruption of synaptic connections in neural circuits is responsible for the disease's development and progression. Because deterioration in synaptic connections results in the impaired effective processing of information. Although structural impairments of the synapse, such as a decrease in dendritic spine density, have been shown in previous studies, functional impairments have also been revealed with the development of genetic and molecular analysis methods. In addition to abnormalities in protein complexes regulating exocytosis in the presynaptic region and impaired vesicle release, especially, changes in proteins related to postsynaptic signaling have been reported. In particular, impairments in postsynaptic density elements, glutamate receptors, and ion channels have been shown. At the same time, effects on cellular adhesion molecular structures such as neurexin, neuroligin, and cadherin family proteins were detected. Of course, the confusing effect of antipsychotic use in schizophrenia research should also be considered. Although antipsychotics have positive and negative effects on synapses, studies indicate synaptic deterioration in schizophrenia independent of drug use. In this review, the deterioration in synapse structure and function and the effects of antipsychotics on the synapse in schizophrenia will be discussed.
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Affiliation(s)
- Emre Mısır
- Department of Psychiatry, Baskent University Faculty of Medicine, Ankara, Turkey
- Department of Interdisciplinary Neuroscience, Ankara University, Ankara, Turkey
| | - Güvem Gümüş Akay
- Department of Interdisciplinary Neuroscience, Ankara University, Ankara, Turkey
- Faculty of Medicine, Department of Physiology, Ankara University, Ankara, Turkey
- Brain Research Center (AÜBAUM), Ankara University, Ankara, Turkey
- Department of Cellular Neuroscience and Advanced Microscopic Neuroimaging, Neuroscience and Neurotechnology Center of Excellence (NÖROM), Ankara, Turkey
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23
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Adamu MJ, Qiang L, Nyatega CO, Younis A, Kawuwa HB, Jabire AH, Saminu S. Unraveling the pathophysiology of schizophrenia: insights from structural magnetic resonance imaging studies. Front Psychiatry 2023; 14:1188603. [PMID: 37275974 PMCID: PMC10236951 DOI: 10.3389/fpsyt.2023.1188603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 04/20/2023] [Indexed: 06/07/2023] Open
Abstract
Background Schizophrenia affects about 1% of the global population. In addition to the complex etiology, linking this illness to genetic, environmental, and neurobiological factors, the dynamic experiences associated with this disease, such as experiences of delusions, hallucinations, disorganized thinking, and abnormal behaviors, limit neurological consensuses regarding mechanisms underlying this disease. Methods In this study, we recruited 72 patients with schizophrenia and 74 healthy individuals matched by age and sex to investigate the structural brain changes that may serve as prognostic biomarkers, indicating evidence of neural dysfunction underlying schizophrenia and subsequent cognitive and behavioral deficits. We used voxel-based morphometry (VBM) to determine these changes in the three tissue structures: the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). For both image processing and statistical analysis, we used statistical parametric mapping (SPM). Results Our results show that patients with schizophrenia exhibited a significant volume reduction in both GM and WM. In particular, GM volume reductions were more evident in the frontal, temporal, limbic, and parietal lobe, similarly the WM volume reductions were predominantly in the frontal, temporal, and limbic lobe. In addition, patients with schizophrenia demonstrated a significant increase in the CSF volume in the left third and lateral ventricle regions. Conclusion This VBM study supports existing research showing that schizophrenia is associated with alterations in brain structure, including gray and white matter, and cerebrospinal fluid volume. These findings provide insights into the neurobiology of schizophrenia and may inform the development of more effective diagnostic and therapeutic approaches.
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Affiliation(s)
- Mohammed Jajere Adamu
- Department of Electronic Science and Technology, School of Microelectronics, Tianjin University, Tianjin, China
- Department of Computer Science, Yobe State University, Damaturu, Nigeria
| | - Li Qiang
- Department of Electronic Science and Technology, School of Microelectronics, Tianjin University, Tianjin, China
| | - Charles Okanda Nyatega
- Department of Information and Communication Engineering, School of Electrical and Information Engineering, Tianjin University, Tianjin, China
- Department of Electronics and Telecommunication Engineering, Mbeya University of Science and Technology, Mbeya, Tanzania
| | - Ayesha Younis
- Department of Electronic Science and Technology, School of Microelectronics, Tianjin University, Tianjin, China
| | - Halima Bello Kawuwa
- Department of Biomedical Engineering and Scientific Instruments, School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Adamu Halilu Jabire
- Department of Electrical and Electronics Engineering, Taraba State University, Jalingo, Nigeria
| | - Sani Saminu
- Department of Biomedical Engineering, University of Ilorin, Ilorin, Nigeria
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24
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Iasevoli F, D’Ambrosio L, Ciccarelli M, Barone A, Gaudieri V, Cocozza S, Pontillo G, Brunetti A, Cuocolo A, de Bartolomeis A, Pappatà S. Altered Patterns of Brain Glucose Metabolism Involve More Extensive and Discrete Cortical Areas in Treatment-resistant Schizophrenia Patients Compared to Responder Patients and Controls: Results From a Head-to-Head 2-[18F]-FDG-PET Study. Schizophr Bull 2023; 49:474-485. [PMID: 36268829 PMCID: PMC10016407 DOI: 10.1093/schbul/sbac147] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND AND HYPOTHESIS Treatment resistant schizophrenia (TRS) affects almost 30% of patients with schizophrenia and has been considered a different phenotype of the disease. In vivo characterization of brain metabolic patterns associated with treatment response could contribute to elucidate the neurobiological underpinnings of TRS. Here, we used 2-[18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) to provide the first head-to-head comparative analysis of cerebral glucose metabolism in TRS patients compared to schizophrenia responder patients (nTRS), and controls. Additionally, we investigated, for the first time, the differences between clozapine responders (Clz-R) and non-responders (Clz-nR). STUDY DESIGN 53 participants underwent FDG-PET studies (41 patients and 12 controls). Response to conventional antipsychotics and to clozapine was evaluated using a standardized prospective procedure based on PANSS score changes. Maps of relative brain glucose metabolism were processed for voxel-based analysis using Statistical Parametric Mapping software. STUDY RESULTS Restricted areas of significant bilateral relative hypometabolism in the superior frontal gyrus characterized TRS compared to nTRS. Moreover, reduced parietal and frontal metabolism was associated with high PANSS disorganization factor scores in TRS (P < .001 voxel level uncorrected, P < .05 cluster level FWE-corrected). Only TRS compared to controls showed significant bilateral prefrontal relative hypometabolism, more extensive in CLZ-nR than in CLZ-R (P < .05 voxel level FWE-corrected). Relative significant hypermetabolism was observed in the temporo-occipital regions in TRS compared to nTRS and controls. CONCLUSIONS These data indicate that, in TRS patients, altered metabolism involved discrete brain regions not found affected in nTRS, possibly indicating a more severe disrupted functional brain network associated with disorganization symptoms.
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Affiliation(s)
- Felice Iasevoli
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Luigi D’Ambrosio
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Mariateresa Ciccarelli
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Annarita Barone
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
| | - Valeria Gaudieri
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Alberto Cuocolo
- Department of Advanced Biomedical Sciences, University of Naples Federico II, Via S. Pansini 5, 80131, Naples, Italy
| | - Andrea de Bartolomeis
- Section of Psychiatry, Unit of Treatment Resistant Psychosis, Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Naples, Italy
- UNESCO Chair on Health Education and Sustainable Development - University of Naples Federico II, Naples, Italy
| | - Sabina Pappatà
- Institute of Biostructure and Bioimaging, National Research Council, Via T. De Amicis 95, 80145, Naples, Italy
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Santarriaga S, Gerlovin K, Layadi Y, Karmacharya R. Human stem cell-based models to study synaptic dysfunction and cognition in schizophrenia: A narrative review. Schizophr Res 2023:S0920-9964(23)00084-1. [PMID: 36925354 PMCID: PMC10500041 DOI: 10.1016/j.schres.2023.02.029] [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: 10/21/2022] [Revised: 02/27/2023] [Accepted: 02/28/2023] [Indexed: 03/18/2023]
Abstract
Cognitive impairment is the strongest predictor of functional outcomes in schizophrenia and is hypothesized to result from synaptic dysfunction. However, targeting synaptic plasticity and cognitive deficits in patients remains a significant clinical challenge. A comprehensive understanding of synaptic plasticity and the molecular basis of learning and memory in a disease context can provide specific targets for the development of novel therapeutics targeting cognitive impairments in schizophrenia. Here, we describe the role of synaptic plasticity in cognition, summarize evidence for synaptic dysfunction in schizophrenia and demonstrate the use of patient derived induced-pluripotent stem cells for studying synaptic plasticity in vitro. Lastly, we discuss current advances and future technologies for bridging basic science research of synaptic dysfunction with clinical and translational research that can be used to predict treatment response and develop novel therapeutics.
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Affiliation(s)
- Stephanie Santarriaga
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Chemical Biology and Therapeutic Science Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Kaia Gerlovin
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Chemical Biology and Therapeutic Science Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yasmine Layadi
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Chimie ParisTech, Université Paris Sciences et Lettres, Paris, France
| | - Rakesh Karmacharya
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Chemical Biology and Therapeutic Science Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, USA; Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA, USA.
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26
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Percie du Sert O, Unrau J, Gauthier CJ, Chakravarty M, Malla A, Lepage M, Raucher-Chéné D. Cerebral blood flow in schizophrenia: A systematic review and meta-analysis of MRI-based studies. Prog Neuropsychopharmacol Biol Psychiatry 2023; 121:110669. [PMID: 36341843 DOI: 10.1016/j.pnpbp.2022.110669] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 10/19/2022] [Accepted: 10/23/2022] [Indexed: 11/06/2022]
Abstract
INTRODUCTION Schizophrenia-spectrum disorders (SSD) represent one of the leading causes of disability worldwide and are usually underpinned by neurodevelopmental brain abnormalities observed on a structural and functional level. Nuclear medicine imaging studies of cerebral blood flow (CBF) have already provided insights into the pathophysiology of these disorders. Recent developments in non-invasive MRI techniques such as arterial spin labeling (ASL) have allowed broader examination of CBF across SSD prompting us to conduct an updated literature review of MRI-based perfusion studies. In addition, we conducted a focused meta-analysis of whole brain studies to provide a complete picture of the literature on the topic. METHODS A systematic OVID search was performed in Embase, MEDLINEOvid, and PsycINFO. Studies eligible for inclusion in the review involved: 1) individuals with SSD, first-episode psychosis or clinical-high risk for psychosis, or; 2) had healthy controls for comparison; 3) involved MRI-based perfusion imaging methods; and 4) reported CBF findings. No time span was specified for the database queries (last search: 08/2022). Information related to participants, MRI techniques, CBF analyses, and results were systematically extracted. Whole-brain studies were then selected for the meta-analysis procedure. The methodological quality of each included studies was assessed. RESULTS For the systematic review, the initial Ovid search yielded 648 publications of which 42 articles were included, representing 3480 SSD patients and controls. The most consistent finding was that negative symptoms were linked to cortical fronto-limbic hypoperfusion while positive symptoms seemed to be associated with hyperperfusion, notably in subcortical structures. The meta-analysis integrated results from 13 whole-brain studies, across 426 patients and 401 controls, and confirmed the robustness of the hypoperfusion in the left superior and middle frontal gyri and right middle occipital gyrus while hyperperfusion was found in the left putamen. CONCLUSION This updated review of the literature supports the implication of hemodynamic correlates in the pathophysiology of psychosis symptoms and disorders. A more systematic exploration of brain perfusion could complete the search of a multimodal biomarker of SSD.
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Affiliation(s)
- Olivier Percie du Sert
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Joshua Unrau
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Claudine J Gauthier
- Concordia University, Montreal, QC, Canada; Montreal Heart Institute, Montreal, QC, Canada
| | - Mallar Chakravarty
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Ashok Malla
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada
| | - Martin Lepage
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada.
| | - Delphine Raucher-Chéné
- McGill University, Montreal, QC, Canada; Douglas Mental Health University Institute, Montreal, QC, Canada; University of Reims Champagne-Ardenne, Cognition, Health, and Society Laboratory (EA 6291), Reims, France; Academic Department of Psychiatry, University Hospital of Reims, EPSM Marne, Reims, France
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27
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Li H, Li H, Zhu Z, Xiong X, Huang Y, Feng Y, Li Z, Wu K, Wu F. Association of serum homocysteine levels with intestinal flora and cognitive function in schizophrenia. J Psychiatr Res 2023; 159:258-265. [PMID: 36773527 DOI: 10.1016/j.jpsychires.2023.01.045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 12/28/2022] [Accepted: 01/26/2023] [Indexed: 02/04/2023]
Abstract
Some studies have indicated that elevated homocysteine (Hcy) levels and intestinal flora may be involved in schizophrenia (SZ) cognition pathophysiology. This study was the first to investigate the association among Hcy, intestinal flora and schizophrenia cognition. Here, 140 individuals were divided into two groups: SZ patients (N = 68) and healthy controls (HCs, N = 72). Participant data on serum Hcy levels, intestinal flora and cognitive function evaluation using the MATRICS Consensus Cognitive Battery (MCCB) were collected. Clinical symptoms of patients were evaluated using the Positive and Negative Syndrome Scale. Serum Hcy levels and the incidence of hyperhomocysteinaemia were considerably increased in SZ patients compared with HCs. Hcy levels were significantly negatively associated with verbal learning index scores (r = -0.425, p < 0.001) but positively associated with Eubacterium (r = 0.32, p = 0.007), Lactobacillus (r = 0.32, p = 0.008), Corynebacterium (r = 0.26, p = 0.035), Mogibacterium (r = 0.31, p = 0.01), and Bulleidia (r = 0.31, p = 0.01) in SZ patients. Our findings suggest that serum Hcy levels are associated with cognitive function and intestinal flora in SZ patients. However, the mechanism of the interaction between Hcy and intestinal flora and its effects on cognitive function in SZ patients requires further investigation.
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Affiliation(s)
- Hehua Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hanqiu Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zhimin Zhu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiang Xiong
- The Second People's Hospital of Guizhou Province, Guiyang City, Guizhou Province, China
| | - Yuanyuan Huang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yangdong Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zezhi Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kai Wu
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China.
| | - Fengchun Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China.
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28
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Vucurovic K, Raucher-Chéné D, Obert A, Gobin P, Henry A, Barrière S, Traykova M, Gierski F, Portefaix C, Caillies S, Kaladjian A. Activation of the left medial temporal gyrus and adjacent brain areas during affective theory of mind processing correlates with trait schizotypy in a nonclinical population. Soc Cogn Affect Neurosci 2023; 18:6701589. [PMID: 36107738 PMCID: PMC9949503 DOI: 10.1093/scan/nsac051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 07/31/2022] [Accepted: 09/13/2022] [Indexed: 11/12/2022] Open
Abstract
Schizophrenia, a severe psychiatric disorder, is associated with abnormal brain activation during theory of mind (ToM) processing. Researchers recently suggested that there is a continuum running from subclinical schizotypal personality traits to fully expressed schizophrenia symptoms. Nevertheless, it remains unclear whether schizotypal personality traits in a nonclinical population are associated with atypical brain activation during ToM tasks. Our aim was to investigate correlations between fMRI brain activation during affective ToM (ToMA) and cognitive ToM (ToMC) tasks and scores on the Schizotypal Personality Questionnaire (SPQ) and the Basic Empathy Scale in 39 healthy individuals. The total SPQ score positively correlated with brain activation during ToMA processing in clusters extending from the left medial temporal gyrus (MTG), lingual gyrus and fusiform gyrus to the parahippocampal gyrus (Brodmann area: 19). During ToMA processing, the right inferior occipital gyrus, right MTG, precuneus and posterior cingulate cortex negatively correlated with the emotional disconnection subscore and the total score of self-reported empathy. These posterior brain regions are known to be involved in memory and language, as well as in creative reasoning, in nonclinical individuals. Our findings highlight changes in brain processing associated with trait schizotypy in nonclinical individuals during ToMA but not ToMC processing.
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Affiliation(s)
- Ksenija Vucurovic
- Université de Reims Champagne Ardenne, Laboratoire Cognition, Santé, Société, EA 6291, 51100 Reims, France.,Centre Rémois de Psychothérapie et Neuromodulation, 51100 Reims, France
| | - Delphine Raucher-Chéné
- Université de Reims Champagne Ardenne, Laboratoire Cognition, Santé, Société, EA 6291, 51100 Reims, France.,Pôle Universitaire de Psychiatrie, EPSM et CHU de Reims, 51100 Reims, France.,McGill University, Douglas Mental Health University Institute, 11290 Montreal, Canada
| | - Alexandre Obert
- Champollion National University Institute, Cognition Sciences, Technology & Ergonomics Laboratory, University of Toulouse, 81000 Albi, France
| | - Pamela Gobin
- Université de Reims Champagne Ardenne, Laboratoire Cognition, Santé, Société, EA 6291, 51100 Reims, France.,Pôle Universitaire de Psychiatrie, EPSM et CHU de Reims, 51100 Reims, France
| | - Audrey Henry
- Université de Reims Champagne Ardenne, Laboratoire Cognition, Santé, Société, EA 6291, 51100 Reims, France.,Pôle Universitaire de Psychiatrie, EPSM et CHU de Reims, 51100 Reims, France
| | - Sarah Barrière
- Pôle Universitaire de Psychiatrie, EPSM et CHU de Reims, 51100 Reims, France
| | - Martina Traykova
- Pôle Universitaire de Psychiatrie, EPSM et CHU de Reims, 51100 Reims, France
| | - Fabien Gierski
- Université de Reims Champagne Ardenne, Laboratoire Cognition, Santé, Société, EA 6291, 51100 Reims, France.,Pôle Universitaire de Psychiatrie, EPSM et CHU de Reims, 51100 Reims, France.,INSERM U1247 GRAP, Research Group on Alcohol and Drugs, Université de Picardie Jules Verne, 80000 Amiens, France
| | - Christophe Portefaix
- Radiology Department, Reims University Hospital, 51100 Reims, France.,University of Reims Champagne-Ardenne, CReSTIC Laboratory, 51100 Reims, France
| | - Stéphanie Caillies
- Université de Reims Champagne Ardenne, Laboratoire Cognition, Santé, Société, EA 6291, 51100 Reims, France
| | - Arthur Kaladjian
- Université de Reims Champagne Ardenne, Laboratoire Cognition, Santé, Société, EA 6291, 51100 Reims, France.,Pôle Universitaire de Psychiatrie, EPSM et CHU de Reims, 51100 Reims, France.,University of Reims Champagne-Ardenne Faculty of Medicine, 51100 Reims, France
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Lang X, Wang D, Zhou H, Wang L, Kosten TR, Zhang XY. P50 inhibition defects, psychopathology and gray matter volume in patients with first-episode drug-naive schizophrenia. Asian J Psychiatr 2023; 80:103421. [PMID: 36563611 DOI: 10.1016/j.ajp.2022.103421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 12/08/2022] [Accepted: 12/16/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Sensory gating deficits and gray matter volume (GMV) abnormalities have been found to be associated with the pathogenesis and psychopathology of patients with schizophrenia (SCZ). However, no studies have investigated their interrelationship in first-episode treatment-naive (FETN) SCZ patients. METHODS We recruited 52 FETN SCZ patients and 57 healthy controls. The Positive and Negative Syndrome Scale (PANSS) was used to measure the psychopathology of the patients. We collected magnetic resonance imaging and P50 inhibition data from all participants. RESULTS Compared to healthy controls, patients had shorter S1 and S2 latencies but larger S2 amplitudes and P50 ratio (Bonferroni adjusted all p < 0.01). In patients, S2 latency was independently associated with PANSS total score, negative symptoms and general psychopathology (t = 2.26-2.58, both P < 0.05), whereas S1 (t = 2.44, P < 0.05) and S2 latencies (t = 2.13, P < 0.05) were associated with PANSS cognitive factor. Moreover, GMV in the left inferior temporal gyrus, left lingual gyrus and right superior occipital gyrus, and bilateral dorsolateral superior frontal gyrus were each associated with the P50 components (all p < 0.05). In addition, GMV associated with S2 latency was negatively correlated with PANSS general psychopathology (t = -2.46, p < 0.05) and total score (t = -2.34, p < 0.05). CONCLUSIONS Our findings indicate that FETN SCZ patients exhibit deficits in P50 inhibition and GMV of brain regions associated with these deficits may be associated with their psychopathological symptoms, suggesting that brain structures associated with P50 components may be important biomarkers of SCZ psychopathology. Future studies could use a prospective longitudinal design to investigate the potential causal relationship of brain structures associated with P50 components in the psychopathological symptoms of SCZ patients.
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Affiliation(s)
- XiaoE Lang
- Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan, China.
| | - Dongmei Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Huixia Zhou
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Li Wang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Thomas R Kosten
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
| | - Xiang-Yang Zhang
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
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Progressive brain abnormalities in schizophrenia across different illness periods: a structural and functional MRI study. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:2. [PMID: 36604437 PMCID: PMC9816110 DOI: 10.1038/s41537-022-00328-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 11/16/2022] [Indexed: 01/07/2023]
Abstract
Schizophrenia is a chronic brain disorder, and neuroimaging abnormalities have been reported in different stages of the illness for decades. However, when and how these brain abnormalities occur and evolve remains undetermined. We hypothesized structural and functional brain abnormalities progress throughout the illness course at different rates in schizophrenia. A total of 115 patients with schizophrenia were recruited and stratified into three groups of different illness periods: 5-year group (illness duration: ≤5 years), 15-year group (illness duration: 12-18 years), and 25-year group (illness duration: ≥25 years); 230 healthy controls were matched by age and sex to the three groups, respectively. All participants underwent resting-state MRI scanning. Each group of patients with schizophrenia was compared with the corresponding controls in terms of voxel-based morphometry (VBM), fractional anisotropy (FA), global functional connectivity density (gFCD), and sample entropy (SampEn) abnormalities. In the 5-year group we observed only SampEn abnormalities in the putamen. In the 15-year group, we observed VBM abnormalities in the insula and cingulate gyrus and gFCD abnormalities in the temporal cortex. In the 25-year group, we observed FA abnormalities in nearly all white matter tracts, and additional VBM and gFCD abnormalities in the frontal cortex and cerebellum. By using two structural and two functional MRI analysis methods, we demonstrated that individual functional abnormalities occur in limited brain areas initially, functional connectivity and gray matter density abnormalities ensue later in wider brain areas, and structural connectivity abnormalities involving almost all white matter tracts emerge in the third decade of the course in schizophrenia.
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31
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Matrisciano F, Pinna G. The Strategy of Targeting Peroxisome Proliferator-Activated Receptor (PPAR) in the Treatment of Neuropsychiatric Disorders. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1411:513-535. [PMID: 36949324 DOI: 10.1007/978-981-19-7376-5_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
Peroxisome proliferator-activated receptors (PPARs) are nonsteroid nuclear receptors and transcription factors that regulate several neuroinflammatory and metabolic processes, recently involved in several neuropsychiatric conditions, including Alzheimer's disease, Parkinson's disease, major depressive disorder, post-traumatic stress disorder (PTSD), schizophrenia spectrum disorders, and autism spectrum disorders. PPARs are ligand-activated receptors that, following stimulation, induce neuroprotective effects by decreasing neuroinflammatory processes through inhibition of the nuclear factor kappa-light-chain-enhancer of activated B cell (NF-κB) expression and consequent suppression of pro-inflammatory cytokine production. PPARs heterodimerize with the retinoid X-receptor (RXR) and bind to PPAR-responsive regulatory elements (PPRE) in the promoter region of target genes involved in lipid metabolism, synthesis of cholesterol, catabolism of amino acids, and inflammation. Interestingly, PPARs are considered functionally part of the extended endocannabinoid (eCB) system that includes the classic eCB, anandamide, which act at cannabinoid receptor types 1 (CB1) and 2 (CB2) and are implicated in the pathophysiology of stress-related neuropsychiatric disorders. In preclinical studies, PPAR stimulation improves anxiety and depression-like behaviors by enhancing neurosteroid biosynthesis. The peculiar functional role of PPARs by exerting anti-inflammatory and neuroprotective effects and their expression localization in neurons and glial cells of corticolimbic circuits make them particularly interesting as novel therapeutic targets for several neuropsychiatric disorders characterized by underlying neuroinflammatory/neurodegenerative mechanisms. Herein, we discuss the pathological hallmarks of neuropsychiatric conditions associated with neuroinflammation, as well as the pivotal role of PPARs with a special emphasis on the subtype alpha (PPAR-α) as a suitable molecular target for therapeutic interventions.
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Affiliation(s)
- Francesco Matrisciano
- Department of Psychiatry, College of Medicine, The Psychiatric Institute, University of Illinois at Chicago, Chicago, IL, USA
| | - Graziano Pinna
- Department of Psychiatry, College of Medicine, The Psychiatric Institute, University of Illinois at Chicago, Chicago, IL, USA.
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Neuroimaging biomarkers for detecting schizophrenia: A resting-state functional MRI-based radiomics analysis. Heliyon 2022; 8:e12276. [PMID: 36582679 PMCID: PMC9793282 DOI: 10.1016/j.heliyon.2022.e12276] [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: 02/18/2022] [Revised: 05/19/2022] [Accepted: 12/02/2022] [Indexed: 12/14/2022] Open
Abstract
Schizophrenia (SZ) is a common psychiatric disorder that is difficult to accurately diagnose in clinical practice. Quantifiable biomarkers are urgently required to explore the potential physiological mechanism of SZ and improve its diagnostic accuracy. Thus, this study aimed to identify biomarkers that classify SZ patients and healthy control subjects and investigate the potential neural mechanisms of SZ using degree centrality (DC)- and voxel-mirrored homotopic connectivity (VMHC)-based radiomics. Radiomics features were extracted from DC and VMHC metrics generated via resting-state functional magnetic resonance imaging, and significant features were selected and dimensionality was reduced using t-tests and least absolute shrinkage and selection operator. Subsequently, we built our model using a support vector machine classifier. We observed that our method obtained great classification performance (area under the curve, 0.808; accuracy, 74.02%), and it could be generalized to different brain atlases. The regions that we identified as discriminative features mainly included bilateral dorsal caudate and front-parietal, somatomotor, limbic, and default mode networks. Our findings showed that the radiomics-based machine learning method could facilitate us to understand the potential pathological mechanism of SZ more comprehensively and contribute to the accurate diagnosis of patients with SZ.
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Cui Y, Li C, Liu B, Sui J, Song M, Chen J, Chen Y, Guo H, Li P, Lu L, Lv L, Ning Y, Wan P, Wang H, Wang H, Wu H, Yan H, Yan J, Yang Y, Zhang H, Zhang D, Jiang T. Consistent brain structural abnormalities and multisite individualised classification of schizophrenia using deep neural networks. Br J Psychiatry 2022; 221:732-739. [PMID: 35144702 DOI: 10.1192/bjp.2022.22] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia. AIMS To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers. METHOD We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites. RESULTS We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19-85.74%; sensitivity, 75.31-89.29% and area under the receiver operating characteristic curve, 0.797-0.909. CONCLUSIONS These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.
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Affiliation(s)
- Yue Cui
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, China, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China
| | - Chao Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, China, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, China and Chinese Institute for Brain Research, China
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, China
| | - Ming Song
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, China, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China
| | - Jun Chen
- Department of Radiology, Renmin Hospital of Wuhan University, China
| | - Yunchun Chen
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, China
| | - Hua Guo
- Zhumadian Psychiatric Hospital, China
| | - Peng Li
- Peking University Sixth Hospital/Institute of Mental Health, China and Key Laboratory of Mental Health, Ministry of Health (Peking University), China
| | - Lin Lu
- Peking University Sixth Hospital/Institute of Mental Health, China, Key Laboratory of Mental Health, Ministry of Health (Peking University), China and Center for Life Sciences/PKU-IDG/McGovern Institute for Brain Research, Peking University, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, China and Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, China
| | - Yuping Ning
- Guangzhou Brain Hospital, Guangzhou Hui-Ai Hospital, The Affiliated Brain Hospital of Guangzhou Medical University, China
| | - Ping Wan
- Zhumadian Psychiatric Hospital, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, China
| | - Huawang Wu
- Guangzhou Brain Hospital, Guangzhou Hui-Ai Hospital, The Affiliated Brain Hospital of Guangzhou Medical University, China
| | - Hao Yan
- Peking University Sixth Hospital/Institute of Mental Health, China and Key Laboratory of Mental Health, Ministry of Health (Peking University), China
| | - Jun Yan
- Peking University Sixth Hospital/Institute of Mental Health, China and Key Laboratory of Mental Health, Ministry of Health (Peking University), China
| | - Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, China, Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, China and CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, China
| | - Hongxing Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, China, Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, China and Department of Psychology, Xinxiang Medical University, China
| | - Dai Zhang
- Peking University Sixth Hospital/Institute of Mental Health, China, Key Laboratory of Mental Health, Ministry of Health (Peking University), China and Center for Life Sciences/PKU-IDG/McGovern Institute for Brain Research, Peking University, China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, China, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China and University of Chinese Academy of Sciences, China, CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, China; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, China and Queensland Brain Institute, University of Queensland, Australia
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34
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Lin B, Li XB, Ruan S, Wu YX, Zhang CY, Wang CY, Wang LB. Convergent and divergent gray matter volume abnormalities in unaffected first-degree relatives and ultra-high risk individuals of schizophrenia. SCHIZOPHRENIA 2022; 8:55. [PMID: 35853913 PMCID: PMC9261104 DOI: 10.1038/s41537-022-00261-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 05/24/2022] [Indexed: 01/10/2023]
Abstract
High-risk populations of schizophrenia can be mainly identified as genetic high-risk based on putative endophenotypes or ultra-high-risk (UHR) based on clinically manifested symptoms. Previous studies have consistently shown brain structural abnormalities in both genetic high-risk and UHR individuals. In this study, we aimed to disentangle the convergent and divergent pattern of gray matter alterations between UHR and unaffected first-degree relatives from genetic high-risk individuals. We used structural MRI scans and voxel-based morphometry method to examine gray matter volume (GMV) differences among 23 UHR subjects meeting the Structured Interview for Prodromal Syndromes (SIPS) criteria, 18 unaffected first-degree relatives (UFDR), 26 first-episode schizophrenia patients (FES) and 54 healthy controls (CN). We found that a number of brain regions exhibited a monotonically decreasing trend of GMV from CN to UFDR to UHR to FES. Compared with CN, the UHR subjects showed significant decreases of GMV similar to the patients in the inferior temporal gyrus, fusiform gyrus, middle occipital gyrus, insula, and limbic regions. Moreover, the UHR transformed subgroup had significantly lower GMV than UHR non-transformed subgroup in the right inferior temporal/fusiform gyrus. On the other hand, the UFDR subjects only showed significant GMV decreases in the inferior temporal gyrus and fusiform. Moreover, we found GMV in the occipital lobe was negatively correlated with the UHR subjects’ composite positive symptom of SIPS, and GMV in the cerebellum was positively correlated with FES subjects’ symptom severity. Our results suggest that GMV deficits and regional dysfunction are evident prior to the onset of psychosis and are more prominent in the UHR than the UFDR individuals.
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Sun J, Du Z, Ma Y, Guo C, Gao S, Luo Y, Chen Q, Hong Y, Xiao X, Yu X, Fang J. Characterization of Resting-State Striatal Differences in First-Episode Depression and Recurrent Depression. Brain Sci 2022; 12:brainsci12121603. [PMID: 36552063 PMCID: PMC9776048 DOI: 10.3390/brainsci12121603] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/19/2022] [Accepted: 11/19/2022] [Indexed: 11/24/2022] Open
Abstract
The presence of reward deficits in major depressive disorder is associated with abnormal striatal function. However, differences in striatal whole-brain functional between recurrent depressive episode (RDE) and first-episode depression (FDE) have not been elucidated. Thirty-three patients with RDE, 27 with FDE, and 35 healthy controls (HCs) were recruited for this study. A seed-based functional connectivity (FC) method was used to analyze abnormalities in six predefined striatal subregion circuits among the three groups of subjects and to further explore the correlation between abnormal FC and clinical symptoms. The results revealed that compared with the FDE group, the RDE group showed higher FC of the striatal subregion with the left middle occipital gyrus, left orbital area of the middle frontal gyrus, and bilateral posterior cerebellar gyrus, while showing lower FC of the striatal subregion with the right thalamus, left inferior parietal lobule, left middle cingulate gyrus, right angular gyrus, right cerebellum anterior lobe, and right caudate nucleus. In the RDE group, the HAMD-17 scores were positively correlated with the FC between the left dorsal rostral putamen and the left cerebellum posterior lobe. This study provides new insights into understanding the specificity of striatal circuits in the RDE group.
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Affiliation(s)
- Jifei Sun
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Zhongming Du
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China
| | - Yue Ma
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Chunlei Guo
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Shanshan Gao
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Yi Luo
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Qingyan Chen
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Yang Hong
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
| | - Xue Xiao
- Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing 100026, China
| | - Xue Yu
- Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing 100026, China
| | - Jiliang Fang
- Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China
- Correspondence: ; Tel.: +86-010-88001493
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36
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Identification of texture MRI brain abnormalities on first-episode psychosis and clinical high-risk subjects using explainable artificial intelligence. Transl Psychiatry 2022; 12:481. [PMID: 36385133 PMCID: PMC9668814 DOI: 10.1038/s41398-022-02242-z] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 10/21/2022] [Accepted: 10/27/2022] [Indexed: 11/17/2022] Open
Abstract
Structural MRI studies in first-episode psychosis and the clinical high-risk state have consistently shown volumetric abnormalities. Aim of the present study was to introduce radiomics texture features in identification of psychosis. Radiomics texture features describe the interrelationship between voxel intensities across multiple spatial scales capturing the hidden information of underlying disease dynamics in addition to volumetric changes. Structural MR images were acquired from 77 first-episode psychosis (FEP) patients, 58 clinical high-risk subjects with no later transition to psychosis (CHR_NT), 15 clinical high-risk subjects with later transition (CHR_T), and 44 healthy controls (HC). Radiomics texture features were extracted from non-segmented images, and two-classification schemas were performed for the identification of FEP vs. HC and FEP vs. CHR_NT. The group of CHR_T was used as external validation in both schemas. The classification of a subject's clinical status was predicted by importing separately (a) the difference of entropy feature map and (b) the contrast feature map, resulting in classification balanced accuracy above 72% in both analyses. The proposed framework enhances the classification decision for FEP, CHR_NT, and HC subjects, verifies diagnosis-relevant features and may potentially contribute to identification of structural biomarkers for psychosis, beyond and above volumetric brain changes.
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37
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Dabiri M, Dehghani Firouzabadi F, Yang K, Barker PB, Lee RR, Yousem DM. Neuroimaging in schizophrenia: A review article. Front Neurosci 2022; 16:1042814. [PMID: 36458043 PMCID: PMC9706110 DOI: 10.3389/fnins.2022.1042814] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 10/28/2022] [Indexed: 11/16/2022] Open
Abstract
In this review article we have consolidated the imaging literature of patients with schizophrenia across the full spectrum of modalities in radiology including computed tomography (CT), morphologic magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and magnetoencephalography (MEG). We look at the impact of various subtypes of schizophrenia on imaging findings and the changes that occur with medical and transcranial magnetic stimulation (TMS) therapy. Our goal was a comprehensive multimodality summary of the findings of state-of-the-art imaging in untreated and treated patients with schizophrenia. Clinical imaging in schizophrenia is used to exclude structural lesions which may produce symptoms that may mimic those of patients with schizophrenia. Nonetheless one finds global volume loss in the brains of patients with schizophrenia with associated increased cerebrospinal fluid (CSF) volume and decreased gray matter volume. These features may be influenced by the duration of disease and or medication use. For functional studies, be they fluorodeoxyglucose positron emission tomography (FDG PET), rs-fMRI, task-based fMRI, diffusion tensor imaging (DTI) or MEG there generally is hypoactivation and disconnection between brain regions. However, these findings may vary depending upon the negative or positive symptomatology manifested in the patients. MR spectroscopy generally shows low N-acetylaspartate from neuronal loss and low glutamine (a neuroexcitatory marker) but glutathione may be elevated, particularly in non-treatment responders. The literature in schizophrenia is difficult to evaluate because age, gender, symptomatology, comorbidities, therapy use, disease duration, substance abuse, and coexisting other psychiatric disorders have not been adequately controlled for, even in large studies and meta-analyses.
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Affiliation(s)
- Mona Dabiri
- Department of Radiology, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Kun Yang
- Department of Psychiatry, Molecular Psychiatry Program, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Peter B. Barker
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, Baltimore, MD, United States
| | - Roland R. Lee
- Department of Radiology, UCSD/VA Medical Center, San Diego, CA, United States
| | - David M. Yousem
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institution, Baltimore, MD, United States
- *Correspondence: David M. Yousem,
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38
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Nelson EA, Kraguljac NV, Maximo JO, Armstrong W, Lahti AC. Dorsal striatial hypoconnectivity predicts antipsychotic medication treatment response in first-episode psychosis and unmedicated patients with schizophrenia. Brain Behav 2022; 12:e2625. [PMID: 36237115 PMCID: PMC9660417 DOI: 10.1002/brb3.2625] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 03/28/2022] [Accepted: 04/24/2022] [Indexed: 01/10/2023] Open
Abstract
INTRODUCTION The dorsal striatum, comprised of the caudate and putamen, is implicated in the pathophysiology of psychosis spectrum disorders. Given the high concentration of dopamine receptors in the striatum, striatal dopamine imbalance is a likely cause in cortico-striatal dysconnectivity. There is great interest in understanding the relationship between striatal abnormalities in psychosis and antipsychotic treatment response, but few studies have considered differential involvement of the caudate and putamen. This study's goals were twofold. First, identify patterns of dorsal striatal dysconnectivity for the caudate and putamen separately in patients with a psychosis spectrum disorder; second, determine if these dysconnectivity patterns were predictive of treatment response. METHODS Using resting state functional connectivity, we evaluated dorsal striatal connectivity using separate bilateral caudate and putamen seed regions in two cohorts of subjects: a cohort of 71 medication-naïve first episode psychosis patients and a cohort of 42 unmedicated patients with schizophrenia (along with matched controls). Patient and control connectivity maps were contrasted for each cohort. After receiving 6 weeks of risperidone treatment, patients' clinical response was calculated. We used regression analyses to determine the relationship between baseline dysconnectivity and treatment response. RESULTS This dysconnectivity was also predictive of treatment response in both cohorts. DISCUSSION These findings suggest that the caudate may be more of a driving factor than the putamen in early cortico-striatal dysconnectivity.
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Affiliation(s)
- Eric A Nelson
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Nina V Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Jose O Maximo
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - William Armstrong
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
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39
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Ni MH, Li ZY, Sun Q, Yu Y, Yang Y, Hu B, Ma T, Xie H, Li SN, Tao LQ, Yuan DX, Zhu JL, Yan LF, Cui GB. Neurovascular decoupling measured with quantitative susceptibility mapping is associated with cognitive decline in patients with type 2 diabetes. Cereb Cortex 2022; 33:5336-5346. [PMID: 36310091 DOI: 10.1093/cercor/bhac422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 09/26/2022] [Accepted: 09/28/2022] [Indexed: 01/10/2023] Open
Abstract
Abstract
Disturbance of neurovascular coupling (NVC) is suggested to be one potential mechanism in type 2 diabetes mellitus (T2DM) associated mild cognitive impairment (MCI). However, NVC evidence derived from functional magnetic resonance imaging ignores the relationship of neuronal activity with vascular injury. Twenty-seven T2DM patients without MCI and thirty healthy controls were prospectively enrolled. Brain regions with changed susceptibility detected by quantitative susceptibility mapping (QSM) were used as seeds for functional connectivity (FC) analysis. NVC coefficients were estimated using combined degree centrality (DC) with susceptibility or cerebral blood flow (CBF). Partial correlations between neuroimaging indicators and cognitive decline were investigated. In T2DM group, higher susceptibility values in right hippocampal gyrus (R.PHG) were found and were negatively correlated with Naming Ability of Montreal Cognitive Assessment. FC increased remarkably between R.PHG and right middle temporal gyrus (R.MTG), right calcarine gyrus (R.CAL). Both NVC coefficients (DC-QSM and DC-CBF) reduced in R.PHG and increased in R.MTG and R.CAL. Both NVC coefficients in R.PHG and R.MTG increased with the improvement of cognitive ability, especially for executive function. These demonstrated that QSM and DC-QSM coefficients can be promising biomarkers for early evaluation of cognitive decline in T2DM patients and help to better understand the mechanism of NVC.
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Affiliation(s)
- Min-Hua Ni
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
- Faculty of Medical Technology, Shaanxi University of Chinese Medicine , 1 Middle Section of Shiji Road, Xian yang, Shaanxi 712046 , China
| | - Ze-Yang Li
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Qian Sun
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Ying Yu
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Yang Yang
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Bo Hu
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Teng Ma
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Hao Xie
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Si-Ning Li
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
- Faculty of Medical Technology, Xi’an Medical University , 1 Xinwang Road, Xi'an, Shaanxi 710016 , China
| | - Lan-Qiu Tao
- Student Brigade, Fourth Military Medical University , 169 Changle Road, Xi'an, Shaanxi 710032 , China
| | - Ding-Xin Yuan
- Student Brigade, Fourth Military Medical University , 169 Changle Road, Xi'an, Shaanxi 710032 , China
| | - Jun-Ling Zhu
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Lin-Feng Yan
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
| | - Guang-Bin Cui
- Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University , 569 Xinsi Road, Xi'an 710038, Shaanxi , China
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40
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Zeng J, Yan J, Cao H, Su Y, Song Y, Luo Y, Yang X. Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI findings in the monetary incentive delay task. Transl Psychiatry 2022; 12:448. [PMID: 36244990 PMCID: PMC9573872 DOI: 10.1038/s41398-022-02201-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 01/10/2023] Open
Abstract
Dysfunction of the mesocorticolimbic dopaminergic reward system is a core feature of schizophrenia (SZ), yet its precise contributions to different stages of reward processing and their relevance to disease symptomology are not fully understood. We performed a coordinate-based meta-analysis, using the monetary incentive delay task, to identify which brain regions are implicated in different reward phases in functional magnetic resonance imaging in SZ. A total of 17 studies (368 SZ and 428 controls) were included in the reward anticipation, and 10 studies (229 SZ and 281 controls) were included in the reward outcome. Our meta-analysis revealed that during anticipation, patients showed hypoactivation in the striatum, anterior cingulate cortex, median cingulate cortex (MCC), amygdala, precentral gyrus, and superior temporal gyrus compared with controls. Striatum hypoactivation was negatively associated with negative symptoms and positively associated with the proportion of second-generation antipsychotic users (percentage of SGA users). During outcome, patients displayed hyperactivation in the striatum, insula, amygdala, hippocampus, parahippocampal gyrus, cerebellum, postcentral gyrus, and MCC, and hypoactivation in the dorsolateral prefrontal cortex (DLPFC) and medial prefrontal cortex (mPFC). Hypoactivity of mPFC during outcome was negatively associated with positive symptoms. Moderator analysis showed that the percentage of SGA users was a significant moderator of the association between symptom severity and brain activity in both the anticipation and outcome stages. Our findings identified the neural substrates for different reward phases in SZ and may help explain the neuropathological mechanisms underlying reward processing deficits in the disorder.
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Affiliation(s)
- Jianguang Zeng
- grid.190737.b0000 0001 0154 0904School of Economics and Business Administration, Chongqing University, Chongqing, 400044 China
| | - Jiangnan Yan
- grid.190737.b0000 0001 0154 0904School of Economics and Business Administration, Chongqing University, Chongqing, 400044 China
| | - Hengyi Cao
- grid.250903.d0000 0000 9566 0634Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Hempstead, NY USA ,grid.440243.50000 0004 0453 5950Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY USA
| | - Yueyue Su
- grid.190737.b0000 0001 0154 0904School of Public Affairs, Chongqing University, Chongqing, 400044 China
| | - Yuan Song
- grid.190737.b0000 0001 0154 0904School of Public Affairs, Chongqing University, Chongqing, 400044 China
| | - Ya Luo
- grid.412901.f0000 0004 1770 1022Department of Psychiatry, State Key Lab of Biotherapy, West China Hospital of Sichuan University, Chengdu, 610041 China
| | - Xun Yang
- School of Public Affairs, Chongqing University, Chongqing, 400044, China.
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41
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Yang Y, Sun Y, Zhang Y, Jin X, Li Z, Ding M, Shi H, Liu Q, Zhang L, Su X, Shao M, Song M, Zhang Y, Li W, Yue W, Liu B, Lv L. Abnormal patterns of regional homogeneity and functional connectivity across the adolescent first-episode, adult first-episode and adult chronic schizophrenia. Neuroimage Clin 2022; 36:103198. [PMID: 36116163 PMCID: PMC9486119 DOI: 10.1016/j.nicl.2022.103198] [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: 05/18/2022] [Revised: 09/03/2022] [Accepted: 09/13/2022] [Indexed: 01/10/2023]
Abstract
Functional deficits in schizophrenia (SZ) are observed prior to the onset of psychosis and differ at different stages of SZ. However, there is a paucity of studies focused on adolescent first-episode SZ (AOS), adult first-episode SZ (AFES), and adult chronic SZ (CHSZ). In this study, we investigated regional activity and corresponding functional connectivity alterations that have aimed to compare the three disease stages simultaneously. The subjects comprised 49 patients with AOS, 57 patients with AFES, 51 patients with CHSZ, 41 adolescent healthy controls, and 138 adult healthy controls. We compared regional homogeneity (ReHo) between patients at each disease stage with matched healthy controls. We focused on the shared brain regions that showed significant differences between SZ patients at the three different disease stages and healthy controls. Further analysis was conducted to explore whether the patterns of the whole brain functional connectivity alterations were similar. The putamen and medial frontal gyrus (MFG) showed consistently abnormal patterns in AOS, AFES, and CHSZ. Commonly decreased ReHo values in the MFG and increased ReHo values in the bilateral putamen were found in AOS, AFES, and CHSZ. Functional connectivity of MFG remained common abnormality in different SZ stage. In conclusion, ReHo abnormalities in the MFG and the putamen may be common abnormal patterns of brain function in the three different stages of SZ. The vmPFC-dlPFC FC abnormality common occurs in adolescence and adulthood.. This study may provide a more comprehensive understanding of the neurodevelopmental abnormality across the AOS, AFES, and CHSZ.
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Affiliation(s)
- Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Yuqing Sun
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China,Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Yuliang Zhang
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China,Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Xueyan Jin
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Zheng Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Minli Ding
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China
| | - Han Shi
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China
| | - Qing Liu
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Luwen Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Xi Su
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Minglong Shao
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Meng Song
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Yan Zhang
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Wenqiang Li
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China
| | - Weihua Yue
- Institute of Mental Health, Peking University, Beijing 100191, China,Key Laboratory for Mental Health, Ministry of Health, Beijing 100191, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China,Chinese Institute for Brain Research, Beijing 102206, China,Corresponding authors at: The Second Affiliated Hospital of Xinxiang Medical University, No.388, Jianshe Middle Road, Xinxiang 453002, China.
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang 453002, China,Corresponding authors at: The Second Affiliated Hospital of Xinxiang Medical University, No.388, Jianshe Middle Road, Xinxiang 453002, China.
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Buizza C, Strozza C, Sbravati G, de Girolamo G, Ferrari C, Iozzino L, Macis A, Kennedy HG, Candini V. Positive and negative syndrome scale in forensic patients with schizophrenia spectrum disorders: a systematic review and meta-analysis. Ann Gen Psychiatry 2022; 21:36. [PMID: 36088451 PMCID: PMC9463849 DOI: 10.1186/s12991-022-00413-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 06/19/2022] [Indexed: 01/10/2023] Open
Abstract
Among forensic patients with schizophrenia spectrum disorders, the association between symptomatology and violence is still not entirely clear in literature, especially because symptoms shift both during the acute phase of the illness and after. The aims were to investigate the level of symptomatology in forensic patients and to evaluate if there are differences in the level of symptoms between forensic and non-forensic patients. According to PRISMA guidelines, a systematic search was performed in PubMed, Web of Science, and ProQuest, using the following key words: "forensic" AND "Positive and Negative Syndrome Scale" OR "PANSS". A total of 27 studies were included in the systematic review, while only 23 studies in the meta-analysis. The overall sample included a total of 1702 participants, most commonly male and inpatients in forensic settings. We found that studies with an entirely male sample had significantly lower Positive PANSS ratings than studies with mixed samples. Although both forensic and non-forensic patients were affected by mild psychopathological symptoms, forensic patients presented higher ratings in all four PANSS scales. This meta-analysis shows that forensic patients reported a mild level of symptomatology, as assessed with the PANSS, and therefore might be considered as patients in partial remission. Among patients with schizophrenia, the association between symptoms and violence is very complex: many factors might be considered as key mediators and thus should be taken into account to explain this association. Further studies are needed.Trial registration all materials and data can be found on the OSF framework: https://osf.io/5ceja (date of registration: 8 September 2021).
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Affiliation(s)
- Chiara Buizza
- Psychiatric Epidemiology and Evaluation Unit, IRCCS Istituto Centro San Giovanni Di Dio Fatebenefratelli, Via Pilastroni 4, 25125, Brescia, Italy.,Department of Clinical and Experimental Sciences, University of Brescia, Viale Europa 11, 25123, Brescia, Italy
| | - Cosmo Strozza
- Interdisciplinary Centre On Population Dynamics, University of Southern Denmark, 5000, Odense, Denmark
| | - Giulio Sbravati
- Psychiatric Epidemiology and Evaluation Unit, IRCCS Istituto Centro San Giovanni Di Dio Fatebenefratelli, Via Pilastroni 4, 25125, Brescia, Italy
| | - Giovanni de Girolamo
- Psychiatric Epidemiology and Evaluation Unit, IRCCS Istituto Centro San Giovanni Di Dio Fatebenefratelli, Via Pilastroni 4, 25125, Brescia, Italy
| | - Clarissa Ferrari
- Service of Statistics, IRCCS Istituto Centro San Giovanni Di Dio Fatebenefratelli, Via Pilastroni 4, Brescia, Italy
| | - Laura Iozzino
- Psychiatric Epidemiology and Evaluation Unit, IRCCS Istituto Centro San Giovanni Di Dio Fatebenefratelli, Via Pilastroni 4, 25125, Brescia, Italy
| | - Ambra Macis
- Service of Statistics, IRCCS Istituto Centro San Giovanni Di Dio Fatebenefratelli, Via Pilastroni 4, Brescia, Italy
| | - Harry G Kennedy
- The National Forensic Mental Health Service, Central Mental Hospital, Dundrum, Dublin 14, Ireland.,Academic Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Valentina Candini
- Psychiatric Epidemiology and Evaluation Unit, IRCCS Istituto Centro San Giovanni Di Dio Fatebenefratelli, Via Pilastroni 4, 25125, Brescia, Italy.
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43
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Detecting abnormal connectivity in schizophrenia via a joint directed acyclic graph estimation model. Neuroimage 2022; 260:119451. [PMID: 35842099 DOI: 10.1016/j.neuroimage.2022.119451] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 06/14/2022] [Accepted: 07/03/2022] [Indexed: 01/10/2023] Open
Abstract
Functional connectivity (FC) between brain region has been widely studied and linked with cognition and behavior of an individual. FC is usually defined as the correlation or partial correlation of fMRI blood oxygen level-dependent (BOLD) signals between two brain regions. Although FC has been effective to understand brain organization, it cannot reveal the direction of interactions. Many directed acyclic graph (DAG) based methods have been applied to study the directed interactions but their performance was limited by the small sample size while high dimensionality of the available data. By enforcing group regularization and utilizing samples from both case and control groups, we propose a joint DAG model to estimate the directed FC. We first demonstrate that the proposed model is efficient and accurate through a series of simulation studies. We then apply it to the case-control study of schizophrenia (SZ) with data collected from the MIND Clinical Imaging Consortium (MCIC). We have successfully identified decreased functional integration, disrupted hub structures and characteristic edges (CtEs) in SZ patients. Those findings have been confirmed by previous studies with some identified to be potential markers for SZ patients. A comparison of the results between the directed FC and undirected FC showed substantial differences in the selected features. In addition, we used the identified features based on directed FC for the classification of SZ patients and achieved better accuracy than using undirected FC or raw features, demonstrating the advantage of using directed FC for brain network analysis.
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44
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Shailaja B, Javadekar A, Chaudhury S, Saldanha D. Clinical correlates of regional gray matter volumes in schizophrenia: A structural magnetic resonance imaging study. Ind Psychiatry J 2022; 31:282-292. [PMID: 36419700 PMCID: PMC9678149 DOI: 10.4103/ipj.ipj_104_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 06/21/2021] [Accepted: 10/12/2021] [Indexed: 03/14/2023] Open
Abstract
OBJECTIVES The objective of this study is to investigate the correlation between the regional gray matter volumes and length of Para Cingulate Sulcus (PCS) with the clinical profile of patients with schizophrenia. MATERIALS AND METHODS In this hospital-based, cross-sectional study, thirty consecutive in-patients diagnosed with schizophrenia and equal number of healthy volunteers matched for age- and sex- were recruited as controls. Detailed clinical assessment and magnetic resonance imaging (MRI) of the brain were carried out within 2 days for controls and within 2 weeks of hospitalization for patients. The Positive and Negative Syndrome Scale and Montreal Cognitive Assessment were applied to schizophrenia patients to assess symptoms and cognitive function, respectively. RESULTS Schizophrenia patients had significant volume deficit in bilateral amygdalae, bilateral superior temporal gyri, anterior cingulate cortex and bilateral hippocampi, along with a highly significant reduction in the length of right PCS. Schizophrenia patients with the duration of untreated psychosis (DUP) of 6-12 months showed a significantly greater volume of the right superior temporal gyrus (STG). First-episode schizophrenia patients had a significant reduction in the length of the left PCS. The volume of bilateral superior temporal gyri in schizophrenia patients showed a significant direct correlation with positive symptoms and an inverse correlation with negative symptoms. CONCLUSION Schizophrenia patients have significant volume deficit in some brain regions. DUP of 6-12 months is associated with significantly greater volume of the right STG. First-episode schizophrenia patients have a significant reduction in the length of the left PCS. In schizophrenia patients, the volume of bilateral superior temporal gyri showed a significant direct correlation with the positive symptoms and an inverse correlation with the negative symptoms.
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Affiliation(s)
- B Shailaja
- Department of Psychiatry, M. S. Ramaiah Medical College, Bengaluru, Karnataka, India
| | - Archana Javadekar
- Department of Psychiatry, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
| | - Suprakash Chaudhury
- Department of Psychiatry, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
| | - Daniel Saldanha
- Department of Psychiatry, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
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45
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Bellon A, Feuillet V, Cortez-Resendiz A, Mouaffak F, Kong L, Hong LE, De Godoy L, Jay TM, Hosmalin A, Krebs MO. Dopamine-induced pruning in monocyte-derived-neuronal-like cells (MDNCs) from patients with schizophrenia. Mol Psychiatry 2022; 27:2787-2802. [PMID: 35365810 PMCID: PMC9156413 DOI: 10.1038/s41380-022-01514-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Revised: 02/05/2022] [Accepted: 02/25/2022] [Indexed: 01/10/2023]
Abstract
The long lapse between the presumptive origin of schizophrenia (SCZ) during early development and its diagnosis in late adolescence has hindered the study of crucial neurodevelopmental processes directly in living patients. Dopamine, a neurotransmitter consistently associated with the pathophysiology of SCZ, participates in several aspects of brain development including pruning of neuronal extensions. Excessive pruning is considered the cause of the most consistent finding in SCZ, namely decreased brain volume. It is therefore possible that patients with SCZ carry an increased susceptibility to dopamine's pruning effects and that this susceptibility would be more obvious in the early stages of neuronal development when dopamine pruning effects appear to be more prominent. Obtaining developing neurons from living patients is not feasible. Instead, we used Monocyte-Derived-Neuronal-like Cells (MDNCs) as these cells can be generated in only 20 days and deliver reproducible results. In this study, we expanded the number of individuals in whom we tested the reproducibility of MDNCs. We also deepened the characterization of MDNCs by comparing its neurostructure to that of human developing neurons. Moreover, we studied MDNCs from 12 controls and 13 patients with SCZ. Patients' cells differentiate more efficiently, extend longer secondary neurites and grow more primary neurites. In addition, MDNCs from medicated patients expresses less D1R and prune more primary neurites when exposed to dopamine. Haloperidol did not influence our results but the role of other antipsychotics was not examined and thus, needs to be considered as a confounder.
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Affiliation(s)
- Alfredo Bellon
- Department of Psychiatry and Behavioral Health, Penn State Hershey Medical Center, Hershey, PA, USA.
- Department of Pharmacology, Penn State Hershey Medical Center, Hershey, PA, USA.
| | - Vincent Feuillet
- Aix-Marseille University, CNRS, INSERM, Centre d'Immunologie de Marseille-Luminy, Marseille, France
- Université de Paris, Institut Cochin, CNRS, INSERM, F-75014, Paris, France
| | - Alonso Cortez-Resendiz
- Department of Psychiatry and Behavioral Health, Penn State Hershey Medical Center, Hershey, PA, USA
| | - Faycal Mouaffak
- Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Pathophysiology of Psychiatric Disorders, Université de Paris, Paris, France
- Pôle de Psychiatrie d'Adultes 93G04, EPS Ville Evrard, Saint Denis, France
| | - Lan Kong
- Department of Public Health Sciences, Penn State Hershey Medical Center, Hershey, PA, USA
| | - L Elliot Hong
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Therese M Jay
- Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Pathophysiology of Psychiatric Disorders, Université de Paris, Paris, France
| | - Anne Hosmalin
- Université de Paris, Institut Cochin, CNRS, INSERM, F-75014, Paris, France
| | - Marie-Odile Krebs
- Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Pathophysiology of Psychiatric Disorders, Université de Paris, Paris, France
- Groupe-Hospitalo-Universitaire de Paris, Psychiatrie et Neuroscience, Pôle PEPIT, University of Paris, Paris, France
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Sun J, Chen L, He J, Du Z, Ma Y, Wang Z, Guo C, Luo Y, Gao D, Hong Y, Zhang L, Xu F, Cao J, Hou X, Xiao X, Tian J, Fang J, Yu X. Altered Brain Function in First-Episode and Recurrent Depression: A Resting-State Functional Magnetic Resonance Imaging Study. Front Neurosci 2022; 16:876121. [PMID: 35546875 PMCID: PMC9083329 DOI: 10.3389/fnins.2022.876121] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 03/30/2022] [Indexed: 01/10/2023] Open
Abstract
Background Studies on differences in brain function activity between the first depressive episode (FDE) and recurrent depressive episodes (RDE) are scarce. In this study, we used regional homogeneity (ReHo) and amplitude of low-frequency fluctuations (ALFF) as indices of abnormal brain function activity. We aimed to determine the differences in these indices between patients with FDE and those with RDE, and to investigate the correlation between areas of abnormal brain function and clinical symptoms. Methods A total of 29 patients with RDE, 28 patients with FDE, and 29 healthy controls (HCs) who underwent resting-state functional magnetic resonance imaging were included in this study. The ReHo and ALFF measurements were used for image analysis and further analysis of the correlation between different brain regions and clinical symptoms. Results Analysis of variance showed significant differences among the three groups in ReHo and ALFF in the frontal, parietal, temporal, and occipital lobes. ReHo was higher in the right inferior frontal triangular gyrus and lower in the left inferior temporal gyrus in the RDE group than in the FDE group. Meanwhile, ALFF was higher in the right inferior frontal triangular gyrus, left anterior cingulate gyrus, orbital part of the left middle frontal gyrus, orbital part of the left superior frontal gyrus, and right angular gyrus, but was lower in the right lingual gyrus in the RDE group than in the FDE group. ReHo and ALFF were lower in the left angular gyrus in the RDE and FDE groups than in the HC group. Pearson correlation analysis showed a positive correlation between the ReHo and ALFF values in these abnormal areas in the frontal lobe and the severity of depressive symptoms (P < 0.05). Abnormal areas in the temporal and occipital lobes were negatively correlated with the severity of depressive symptoms (P < 0.05). Conclusion The RDE and FDE groups had abnormal neural function activity in some of the same brain regions. ReHo and ALFF were more widely distributed in different brain regions and had more complex neuropathological mechanisms in the RDE group than in the FDE group, especially in the right inferior frontal triangular gyrus of the frontal lobe.
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Affiliation(s)
- Jifei Sun
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School, China Academy of Chinese Medical Sciences, Beijing, China
| | - Limei Chen
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jiakai He
- Graduate School, China Academy of Chinese Medical Sciences, Beijing, China.,Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhongming Du
- Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Yue Ma
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhi Wang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School, China Academy of Chinese Medical Sciences, Beijing, China
| | - Chunlei Guo
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yi Luo
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School, China Academy of Chinese Medical Sciences, Beijing, China
| | - Deqiang Gao
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yang Hong
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Lei Zhang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Fengquan Xu
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Jiudong Cao
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xiaobing Hou
- Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China
| | - Xue Xiao
- Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China
| | - Jing Tian
- Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China
| | - Jiliang Fang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Xue Yu
- Beijing First Hospital of Integrated Chinese and Western Medicine, Beijing, China
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47
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Structural MRI-Based Schizophrenia Classification Using Autoencoders and 3D Convolutional Neural Networks in Combination with Various Pre-Processing Techniques. Brain Sci 2022; 12:brainsci12050615. [PMID: 35625002 PMCID: PMC9139344 DOI: 10.3390/brainsci12050615] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 01/10/2023] Open
Abstract
Schizophrenia is a severe neuropsychiatric disease whose diagnosis, unfortunately, lacks an objective diagnostic tool supporting a thorough psychiatric examination of the patient. We took advantage of today’s computational abilities, structural magnetic resonance imaging, and modern machine learning methods, such as stacked autoencoders (SAE) and 3D convolutional neural networks (3D CNN), to teach them to classify 52 patients with schizophrenia and 52 healthy controls. The main aim of this study was to explore whether complex feature extraction methods can help improve the accuracy of deep learning-based classifiers compared to minimally preprocessed data. Our experiments employed three commonly used preprocessing steps to extract three different feature types. They included voxel-based morphometry, deformation-based morphometry, and simple spatial normalization of brain tissue. In addition to classifier models, features and their combination, other model parameters such as network depth, number of neurons, number of convolutional filters, and input data size were also investigated. Autoencoders were trained on feature pools of 1000 and 5000 voxels selected by Mann-Whitney tests, and 3D CNNs were trained on whole images. The most successful model architecture (autoencoders) achieved the highest average accuracy of 69.62% (sensitivity 68.85%, specificity 70.38%). The results of all experiments were statistically compared (the Mann-Whitney test). In conclusion, SAE outperformed 3D CNN, while preprocessing using VBM helped SAE improve the results.
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48
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Huang Y, Wang W, Hei G, Yang Y, Long Y, Wang X, Xiao J, Xu X, Song X, Gao S, Shao T, Huang J, Wang Y, Zhao J, Wu R. Altered regional homogeneity and cognitive impairments in first-episode schizophrenia: A resting-state fMRI study. Asian J Psychiatr 2022; 71:103055. [PMID: 35303593 DOI: 10.1016/j.ajp.2022.103055] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 01/11/2022] [Accepted: 02/27/2022] [Indexed: 01/18/2023]
Abstract
BACKGROUND Patients with schizophrenia consistently present pervasive cognitive deficits, but the neurobiological mechanism of cognitive impairments remains unclear. By analyzing regional homogeneity (ReHo) of resting-state functional Magnetic Resonance Imaging, this study aimed to explore the association between brain functional alterations and cognitive deficits in first-episode schizophrenia (FES) with a relatively large sample. METHODS A total of 187 patients with FES and 100 healthy controls from 3 independent cohorts underwent resting-state functional magnetic resonance scans. The MATRICS Consensus Cognitive Battery (MCCB) was used to assess cognitive function. Partial correlation analysis was performed between abnormal ReHo values and the severity of symptoms and cognitive deficits. RESULTS Compared with healthy controls, ReHo values increased in right superior frontal cortex and decreased in right anterior cingulate cortex (ACC), left middle occipital gyrus (MOG), left cuneus, right posterior cingulate cortex (PCC), and right superior occipital gyrus in schizophrenia patients. ReHo values in ACC, PCC and superior occipital gyrus were correlated with PANSS scores. In addition, ReHo values in ACC and MOG were negatively correlated with working memory; left cuneus was positively correlated with multiple cognitive domains (speed of processing, attention/vigilance and social cognition); PCC was positively correlated with verbal learning; right superior occipital gyrus was positively correlated with speed of processing and social cognition. CONCLUSION In conclusion, we found widespread ReHo alterations and cognitive dysfunction in FES. And the pathophysiology mechanism of a wide range of cognitive deficits may be related to abnormal spontaneous brain activity.
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Affiliation(s)
- Yuyan Huang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Weiyan Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Gangrui Hei
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, China
| | - Ye Yang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Yujun Long
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Xiaoyi Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Jingmei Xiao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Xijia Xu
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210000, Jiangsu, China
| | - Xueqin Song
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, China
| | - Shuzhan Gao
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210000, Jiangsu, China
| | - Tiannan Shao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Jing Huang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Ying Wang
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Jingping Zhao
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Renrong Wu
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China.
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49
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Bulbul O, Kurt E, Ulasoglu-Yildiz C, Demiralp T, Ucok A. Altered Resting State Functional Connectivity and Its Correlation with Cognitive Functions at Ultra High Risk for Psychosis. Psychiatry Res Neuroimaging 2022; 321:111444. [PMID: 35093807 DOI: 10.1016/j.pscychresns.2022.111444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 01/06/2022] [Accepted: 01/17/2022] [Indexed: 01/10/2023]
Abstract
The aim of this study is to identify robust resting state-functional connectivity (rs-FC) alterations and their correlations with the neuropsychological characteristics of Ultra-High Risk (UHR) for psychosis subjects compared to healthy controls (HCs). Twenty individuals with UHR and sixteen HCs underwent resting-state functional magnetic resonance imaging (rs-fMRI) and a cognitive battery evaluating attention, episodic memory and executive functions. Compared to HCs, UHR individuals showed working memory and set-shifting impairments. In functional connectivity (FC) analyses, the Default Mode Network (DMN) of the UHR subjects displayed increased FC with the visual areas and decreased FC with the Dorsal Attention Network (DAN). Additionally, the salience network (SN) of the UHR subjects displayed increased connectivity with wide posterior cortical areas in the temporal, parietal and occipital lobes, corresponding to posterior nodes of the SN itself, the Somato-Motor Network (SMN) and the DAN. The SN connectivity with the left SMN and DAN was positively correlated with the Trail Making Test - B scores of the UHR subjects. These findings show that the SN and DMN, which mostly show abnormal connectivity patterns in psychosis, are also affected in UHR subjects, while the SN plays a more central role with its hyperconnectivity to the DAN and SMN.
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Affiliation(s)
- Oznur Bulbul
- Department of Psychiatry, Erenkoy Training and Research Hospital for Psychiatric and Neurological Diseases, Istanbul, Turkey.
| | - Elif Kurt
- Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Çapa, Istanbul 34093, Turkey; Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Çapa, Istanbul 34093, Turkey
| | - Cigdem Ulasoglu-Yildiz
- Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Çapa, Istanbul 34093, Turkey; Department of Psychology, Faculty of Humanities and Social Sciences, Istinye University, Istanbul, Turkey
| | - Tamer Demiralp
- Hulusi Behçet Life Sciences Research Laboratory, Istanbul University, Çapa, Istanbul 34093, Turkey; Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, Çapa, Istanbul 34093, Turkey
| | - Alp Ucok
- Department of Psychiatry, Faculty of Medicine, Istanbul University, Istanbul, Turkey
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50
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Zhu D, Wang C, Guo L, Si D, Liu M, Cai M, Ma L, Fu D, Fu J, Wang J, Liu F. Total Brain Volumetric Measures and Schizophrenia Risk: A Two-Sample Mendelian Randomization Study. Front Genet 2022; 13:782476. [PMID: 35432453 PMCID: PMC9008758 DOI: 10.3389/fgene.2022.782476] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 03/02/2022] [Indexed: 01/10/2023] Open
Abstract
Schizophrenia (SCZ) is an idiopathic psychiatric disorder with a heritable component and a substantial public health impact. Although abnormalities in total brain volumetric measures (TBVMs) have been found in patients with SCZ, it is still unknown whether these abnormalities have a causal effect on the risk of SCZ. Here, we performed a Mendelian randomization (MR) study to investigate the possible causal associations between each TBVM and SCZ risk. Specifically, genome-wide association study (GWAS) summary statistics of total gray matter volume, total white matter volume, total cerebrospinal fluid volume, and total brain volume were obtained from the United Kingdom Biobank database (33,224 individuals), and SCZ GWAS summary statistics were provided by the Psychiatric Genomics Consortium (150,064 individuals). The main MR analysis was conducted using the inverse variance weighted method, and other MR methods, including MR-Egger, weighted median, simple mode, and weighted mode methods, were performed to assess the robustness of our findings. For pleiotropy analysis, we employed three approaches: MR-Egger intercept, MR-PRESSO, and heterogeneity tests. No TBVM was causally associated with SCZ risk according to the MR results, and no significant pleiotropy or heterogeneity was found for instrumental variables. Taken together, this study suggested that alterations in TBVMs were not causally associated with the risk of SCZ.
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Affiliation(s)
- Dan Zhu
- Department of Radiology, Tianjin Medical University General Hospital Airport Hospital, Tianjin, China
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Chunyang Wang
- Department of Scientific Research, Tianjin Medical University General Hospital, Tianjin, China
| | - Lining Guo
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Daojun Si
- National Supercomputer Center in Tianjin, Tianjin, China
| | - Mengge Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Mengjing Cai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Lin Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Dianxun Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Jilian Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- *Correspondence: Feng Liu, ; Junping Wang, ; Jilian Fu,
| | - Junping Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- *Correspondence: Feng Liu, ; Junping Wang, ; Jilian Fu,
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
- *Correspondence: Feng Liu, ; Junping Wang, ; Jilian Fu,
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