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Yu J, Xu Q, Ma L, Huang Y, Zhu W, Liang Y, Wang Y, Tang W, Zhu C, Jiang X. Convergent functional change of frontoparietal network in obsessive-compulsive disorder: a voxel-based meta-analysis. Front Psychiatry 2024; 15:1401623. [PMID: 39041046 PMCID: PMC11260709 DOI: 10.3389/fpsyt.2024.1401623] [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: 03/15/2024] [Accepted: 06/11/2024] [Indexed: 07/24/2024] Open
Abstract
Background Obsessive-compulsive disorder (OCD) is a chronic psychiatric illness with complex clinical manifestations. Cognitive dysfunction may underlie OC symptoms. The frontoparietal network (FPN) is a key region involved in cognitive control. However, the findings of impaired FPN regions have been inconsistent. We employed meta-analysis to identify the fMRI-specific abnormalities of the FPN in OCD. Methods PubMed, Web of Science, Scopus, and EBSCOhost were searched to screen resting-state functional magnetic resonance imaging (rs-fMRI) studies exploring dysfunction in the FPN of OCD patients using three indicators: the amplitude of low-frequency fluctuation/fractional amplitude of low-frequency fluctuation (ALFF/fALFF), regional homogeneity (ReHo) and functional connectivity (FC). We compared all patients with OCD and control group in a primary analysis, and divided the studies by medication in secondary meta-analyses with the activation likelihood estimation (ALE) algorithm. Results A total of 31 eligible studies with 1359 OCD patients (756 men) and 1360 healthy controls (733 men) were included in the primary meta-analysis. We concluded specific changes in brain regions of FPN, mainly in the left dorsolateral prefrontal cortex (DLPFC, BA9), left inferior frontal gyrus (IFG, BA47), left superior temporal gyrus (STG, BA38), right posterior cingulate cortex (PCC, BA29), right inferior parietal lobule (IPL, BA40) and bilateral caudate. Additionally, altered connectivity within- and between-FPN were observed in the bilateral DLPFC, right cingulate gyrus and right thalamus. The secondary analyses showed improved convergence relative to the primary analysis. Conclusion OCD patients showed dysfunction FPN, including impaired local important nodal brain regions and hypoconnectivity within the FPN (mainly in the bilateral DLPFC), during the resting state. Moreover, FPN appears to interact with the salience network (SN) and default mode network (DMN) through pivotal brain regions. Consistent with the hypothesis of fronto-striatal circuit dysfunction, especially in the dorsal cognitive circuit, these findings provide strong evidence for integrating two pathophysiological models of OCD.
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Affiliation(s)
- Jianping Yu
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Qianwen Xu
- School of Psychology, Nanjing Normal University, Nanjing, China
| | - Lisha Ma
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yueqi Huang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wenjing Zhu
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yan Liang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yunzhan Wang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wenxin Tang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Cheng Zhu
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiaoying Jiang
- Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
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Wang Y, Yang J, Zhang H, Dong D, Yu D, Yuan K, Lei X. Altered morphometric similarity networks in insomnia disorder. Brain Struct Funct 2024; 229:1433-1445. [PMID: 38801538 DOI: 10.1007/s00429-024-02809-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 05/17/2024] [Indexed: 05/29/2024]
Abstract
Previous studies on structural covariance network (SCN) suggested that patients with insomnia disorder (ID) show abnormal structural connectivity, primarily affecting the somatomotor network (SMN) and default mode network (DMN). However, evaluating a single structural index in SCN can only reveal direct covariance relationship between two brain regions, failing to uncover synergistic changes in multiple structural features. To cover this research gap, the present study utilized novel morphometric similarity networks (MSN) to examine the morphometric similarity between cortical areas in terms of multiple sMRI parameters measured at each area. With seven T1-weighted imaging morphometric features from the Desikan-Killiany atlas, individual MSN was constructed for patients with ID (N = 87) and healthy control groups (HCs, N = 84). Two-sample t-test revealed differences in MSN between patients with ID and HCs. Correlation analyses examined associations between MSNs and sleep quality, insomnia symptom severity, and depressive symptoms severity in patients with ID. The right paracentral lobule (PCL) exhibited decreased morphometric similarity in patients with ID compared to HCs, mainly manifested by its de-differentiation (meaning loss of distinctiveness) with the SMN, DMN, and ventral attention network (VAN), as well as its decoupling with the visual network (VN). Greater PCL-based de-differentiation correlated with less severe insomnia and fewer depressive symptoms in the patients group. Additionally, patients with less depressive symptoms showed greater PCL de-differentiation from the SMN. As an important pilot step in revealing the underlying morphometric similarity alterations in insomnia disorder, the present study identified the right PCL as a hub region that is de-differentiated with other high-order networks. Our study also revealed that MSN has an important potential to capture clinical significance related to insomnia disorder.
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Affiliation(s)
- Yulin Wang
- Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, 400715, China.
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, 400715, China.
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
| | - Jingqi Yang
- Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, 400715, China
| | - Haobo Zhang
- Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, 400715, China
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, 400715, China
| | - Debo Dong
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, 400715, China
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Dahua Yu
- Information Processing Laboratory, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, Inner Mongolia, 014010, China
| | - Kai Yuan
- School of Life Science and Technology, Xidian University, Xi'an, Shanxi, 710126, China
| | - Xu Lei
- Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, 400715, China.
- Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, 400715, China.
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Cao HL, Meng YJ, Wei W, Li T, Li ML, Guo WJ. Altered individual gray matter structural covariance networks in early abstinence patients with alcohol dependence. Brain Imaging Behav 2024:10.1007/s11682-024-00888-5. [PMID: 38713331 DOI: 10.1007/s11682-024-00888-5] [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] [Accepted: 04/27/2024] [Indexed: 05/08/2024]
Abstract
While alterations in cortical thickness have been widely observed in individuals with alcohol dependence, knowledge about cortical thickness-based structural covariance networks is limited. This study aimed to explore the topological disorganization of structural covariance networks based on cortical thickness at the single-subject level among patients with alcohol dependence. Structural imaging data were obtained from 61 patients with alcohol dependence during early abstinence and 59 healthy controls. The single-subject structural covariance networks were constructed based on cortical thickness data from 68 brain regions and were analyzed using graph theory. The relationships between network architecture and clinical characteristics were further investigated using partial correlation analysis. In the structural covariance networks, both patients with alcohol dependence and healthy controls displayed small-world topology. However, compared to controls, alcohol-dependent individuals exhibited significantly altered global network properties characterized by greater normalized shortest path length, greater shortest path length, and lower global efficiency. Patients exhibited lower degree centrality and nodal efficiency, primarily in the right precuneus. Additionally, scores on the Alcohol Use Disorder Identification Test were negatively correlated with the degree centrality and nodal efficiency of the left middle temporal gyrus. The results of this correlation analysis did not survive after multiple comparisons in the exploratory analysis. Our findings may reveal alterations in the topological organization of gray matter networks in alcoholism patients, which may contribute to understanding the mechanisms of alcohol addiction from a network perspective.
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Affiliation(s)
- Hai-Ling Cao
- Mental Health Center, West China Hospital, Sichuan University, No. 28 Dianxin South Street, Chengdu, Sichuan, 610041, China
| | - Ya-Jing Meng
- Mental Health Center, West China Hospital, Sichuan University, No. 28 Dianxin South Street, Chengdu, Sichuan, 610041, China
| | - Wei Wei
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310063, China
| | - Tao Li
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310063, China
| | - Ming-Li Li
- Mental Health Center, West China Hospital, Sichuan University, No. 28 Dianxin South Street, Chengdu, Sichuan, 610041, China.
| | - Wan-Jun Guo
- Mental Health Center, West China Hospital, Sichuan University, No. 28 Dianxin South Street, Chengdu, Sichuan, 610041, China.
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310063, China.
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, 1369 West Wenyi Road, Hangzhou, 311121, China.
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Zhang Y, Huang J, Huang L, Peng L, Wang X, Zhang Q, Zeng Y, Yang J, Li Z, Sun X, Liang S. Atypical characteristic changes of surface morphology and structural covariance network in developmental dyslexia. Neurol Sci 2024; 45:2261-2270. [PMID: 37996775 DOI: 10.1007/s10072-023-07193-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 11/03/2023] [Indexed: 11/25/2023]
Abstract
BACKGROUND Developmental dyslexia (DD) is a neurodevelopmental disorder that is characterized by difficulties with all aspects of information acquisition in the written word, including slow and inaccurate word recognition. The neural basis behind DD has not been fully elucidated. METHOD The study included 22 typically developing (TD) children, 16 children with isolated spelling disorder (SpD), and 20 children with DD. The cortical thickness, folding index, and mean curvature of Broca's area, including the triangular part of the left inferior frontal gyrus (IFGtriang) and the opercular part of the left inferior frontal gyrus, were assessed to explore the differences of surface morphology among the TD, SpD, and DD groups. Furthermore, the structural covariance network (SCN) of the triangular part of the left inferior frontal gyrus was analyzed to explore the changes of structural connectivity in the SpD and DD groups. RESULTS The DD group showed higher curvature and cortical folding of the left IFGtriang than the TD group and SpD group. In addition, compared with the TD group and the SpD group, the structural connectivity between the left IFGtriang and the left middle-frontal gyrus and the right mid-orbital frontal gyrus was increased in the DD group, and the structural connectivity between the left IFGtriang and the right precuneus and anterior cingulate was decreased in the DD group. CONCLUSION DD had atypical structural connectivity in brain regions related to visual attention, memory and which might impact the information input and integration needed for reading and spelling.
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Affiliation(s)
- Yusi Zhang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- Fujian Key Laboratory of Cognitive Rehabilitation, Affiliated Rehabilitation Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, 350001, Fujian, China
| | - Jiayang Huang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Li Huang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Lixin Peng
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Xiuxiu Wang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Qingqing Zhang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Yi Zeng
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Junchao Yang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Zuanfang Li
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China
| | - Xi Sun
- College of Information Engineering, Nanyang Institute of Technology, Nanyang, 473004, China
| | - Shengxiang Liang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China.
- Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China.
- Fujian Key Laboratory of Cognitive Rehabilitation, Affiliated Rehabilitation Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, 350001, Fujian, China.
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Collantoni E, Alberti F, Dahmen B, von Polier G, Konrad K, Herpertz-Dahlmann B, Favaro A, Seitz J. Intra-individual cortical networks in Anorexia Nervosa: Evidence from a longitudinal dataset. EUROPEAN EATING DISORDERS REVIEW 2024; 32:298-309. [PMID: 37876109 DOI: 10.1002/erv.3043] [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: 03/20/2023] [Revised: 10/14/2023] [Accepted: 10/16/2023] [Indexed: 10/26/2023]
Abstract
OBJECTIVE This work investigates cortical thickness (CT) and gyrification patterns in Anorexia Nervosa (AN) before and after short-term weight restoration using graph theory tools. METHODS 38 female adolescents with AN underwent structural magnetic resonance imaging scans at baseline and after - on average - 3.5 months following short-term weight restoration while 53 age-matched healthy controls (HCs) were scanned once. Graph measures were compared between groups and longitudinally within the AN group. Associations with clinical measures such as age of onset, duration of illness, BMI standard deviation score (BMI-SDS), and longitudinal weight changes were tested via stepwise regression. RESULTS Cortical thickness graphs of patients with acute AN displayed lower modularity and small-world index (SWI) than HCs. Modularity recovered after weight gain. Reduced global efficiency and SWI were observed in patients at baseline compared to HCs based on gyrification networks. Significant associations between local clustering of CT at admission and BMI-SDS, and clustering/global efficiency of gyrification and duration of illness emerged. CONCLUSIONS Our results indicate a shift towards less organised CT networks in patients with acute AN. After weight recovery, the disarrangement seems to be partially reduced. However, longer-term follow-ups are needed to determine whether cortical organizational patterns fully return to normal.
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Affiliation(s)
- Enrico Collantoni
- Department of Neurosciences, University of Padua, Padova, Italy
- Padua Neuroscience Center, University of Padua, Padova, Italy
| | | | - Brigitte Dahmen
- Child and Adolescent Psychiatry, University Hospital, RWTH Aachen, Aachen, Germany
| | - Georg von Polier
- Child and Adolescent Psychiatry, University Hospital, RWTH Aachen, Aachen, Germany
- Child and Adolescent Psychiatry, University Hospital, Frankfurt, Germany
| | - Kerstin Konrad
- Child and Adolescent Psychiatry, University Hospital, RWTH Aachen, Aachen, Germany
- Section Neuropsychology, Child and Adolescent Psychiatry, University Hospital, RWTH Aachen, Aachen, Germany
| | | | - Angela Favaro
- Department of Neurosciences, University of Padua, Padova, Italy
- Padua Neuroscience Center, University of Padua, Padova, Italy
| | - Jochen Seitz
- Child and Adolescent Psychiatry, University Hospital, RWTH Aachen, Aachen, Germany
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Kang N, Chung S, Lee SH, Bang M. Cerebro-cerebellar gray matter abnormalities associated with cognitive impairment in patients with recent-onset and chronic schizophrenia. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:11. [PMID: 38280893 PMCID: PMC10851702 DOI: 10.1038/s41537-024-00434-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 01/12/2024] [Indexed: 01/29/2024]
Abstract
Although the role of the cerebellum in schizophrenia has gained attention, its contribution to cognitive impairment remains unclear. We aimed to investigate volumetric alterations in the cerebro-cerebellar gray matter (GM) in patients with recent-onset schizophrenia (ROS) and chronic schizophrenia (CS) compared with healthy controls (HCs). Seventy-two ROS, 43 CS, and 127 HC participants were recruited, and high-resolution T1-weighted structural magnetic resonance images of the brain were acquired. We compared cerebellar GM volumes among the groups using voxel-based morphometry and examined the cerebro-cerebellar GM volumetric correlations in participants with schizophrenia. Exploratory correlation analysis investigated the functional relevance of cerebro-cerebellar GM volume alterations to cognitive function in the schizophrenia group. The ROS and CS participants demonstrated smaller cerebellar GM volumes, particularly in Crus I and II, than HCs. Extracted cerebellar GM volumes demonstrated significant positive correlations with the cerebral GM volume in the fronto-temporo-parietal association areas engaged in higher-order association. The exploratory analysis showed that smaller cerebellar GM in the posterior lobe regions was associated with poorer cognitive performance in participants with schizophrenia. Our study suggests that cerebellar pathogenesis is present in the early stages of schizophrenia and interconnected with structural abnormalities in the cerebral cortex. Integrating the cerebellum into the pathogenesis of schizophrenia will help advance our understanding of the disease and identify novel treatment targets concerning dysfunctional cerebro-cerebellar interactions.
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Affiliation(s)
- Naok Kang
- Department of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea
| | - Subin Chung
- CHA University School of Medicine, Pocheon, Republic of Korea
| | - Sang-Hyuk Lee
- Department of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea
| | - Minji Bang
- Department of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea.
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Symons GF, Gregg MC, Hicks AJ, Rowe CC, Shultz SR, Ponsford JL, Spitz G. Altered grey matter structural covariance in chronic moderate-severe traumatic brain injury. Sci Rep 2024; 14:1728. [PMID: 38242923 PMCID: PMC10799053 DOI: 10.1038/s41598-023-50396-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 12/19/2023] [Indexed: 01/21/2024] Open
Abstract
Traumatic brain injury (TBI) alters brain network connectivity. Structural covariance networks (SCNs) reflect morphological covariation between brain regions. SCNs may elucidate how altered brain network topology in TBI influences long-term outcomes. Here, we assessed whether SCN organisation is altered in individuals with chronic moderate-severe TBI (≥ 10 years post-injury) and associations with cognitive performance. This case-control study included fifty individuals with chronic moderate-severe TBI compared to 75 healthy controls recruited from an ongoing longitudinal head injury outcome study. SCNs were constructed using grey matter volume measurements from T1-weighted MRI images. Global and regional SCN organisation in relation to group membership and cognitive ability was examined using regression analyses. Globally, TBI participants had reduced small-worldness, longer characteristic path length, higher clustering, and higher modularity globally (p < 0.05). Regionally, TBI participants had greater betweenness centrality (p < 0.05) in frontal and central areas of the cortex. No significant associations were observed between global network measures and cognitive ability in participants with TBI (p > 0.05). Chronic moderate-severe TBI was associated with a shift towards a more segregated global network topology and altered organisation in frontal and central brain regions. There was no evidence that SCNs are associated with cognition.
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Affiliation(s)
- Georgia F Symons
- Department of Neuroscience, Monash University, 6th Floor, The Alfred Centre, 99 Commercial Road, Melbourne, VIC, 3004, Australia.
| | - Matthew C Gregg
- Monash-Epworth Rehabilitation Research Centre, Ground Floor, 185-187 Hoddle St, Richmond, 3121, Australia
| | - Amelia J Hicks
- Monash-Epworth Rehabilitation Research Centre, Ground Floor, 185-187 Hoddle St, Richmond, 3121, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy, Austin Health, 145 Studley Rd, Heidelberg, VIC, 3084, Australia
| | - Sandy R Shultz
- Department of Neuroscience, Monash University, 6th Floor, The Alfred Centre, 99 Commercial Road, Melbourne, VIC, 3004, Australia
- Health Sciences, Vancouver Island University, 900 Fifth Street, Nanaimo, BC, V9R 5S5, Canada
| | - Jennie L Ponsford
- Monash-Epworth Rehabilitation Research Centre, Ground Floor, 185-187 Hoddle St, Richmond, 3121, Australia
| | - Gershon Spitz
- Department of Neuroscience, Monash University, 6th Floor, The Alfred Centre, 99 Commercial Road, Melbourne, VIC, 3004, Australia
- Monash-Epworth Rehabilitation Research Centre, Ground Floor, 185-187 Hoddle St, Richmond, 3121, Australia
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Yun JY, Choi SH, Park S, Jang JH. Association of executive function with suicidality based on resting-state functional connectivity in young adults with subthreshold depression. Sci Rep 2023; 13:20690. [PMID: 38001278 PMCID: PMC10673918 DOI: 10.1038/s41598-023-48160-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 11/22/2023] [Indexed: 11/26/2023] Open
Abstract
Subthreshold depression (StD) is associated an increased risk of developing major depressive disorder (MDD) and suicidality. Suicidality could be linked to distress intolerance and use of context-dependent strategies. We identified neural correlates of executive functioning among the hubs in the resting-state functional connectome (rs-FCN) and examined associations with recent suicidality in StD and MDD. In total, 79 young adults [27 StD, 30 MDD, and 23 healthy controls (HC)] were scanned using magnetic resonance imaging. Neurocognitive measures of the mean latency to correct five moves in the One Touch Stockings of Cambridge (OTSMLC5), spatial working memory between errors (SWMBE), rapid visual information processing A' (RVPA'), and the stop signal reaction time in the stop signal test (SSTSSRT) were obtained. Global graph metrics were calculated to measure the network integration, segregation, and their balance in the rs-FCN. Regional graph metrics reflecting the number of neighbors (degree centrality; DC), participation in the shortcuts (betweenness centrality; BC), and accessibility to intersections (eigenvector centrality; EC) in the rs-FCN defined group-level hubs for StD, HC, and MDD, separately. Global network metrics were comparable among the groups (all P > 0.05). Among the group-level hubs, regional graph metrics of left dorsal anterior insula (dAI), right dorsomedial prefrontal cortex (dmPFC), right rostral temporal thalamus, right precuneus, and left postcentral/middle temporal/anterior subgenual cingulate cortices were different among the groups. Further, significant associations with neurocognitive measures were found in the right dmPFC with SWMBE, and left dAI with SSTSSRT and RVPA'. Shorter OTSMLC5 was related to the lower centralities of right thalamus and suffer of recent 1-year suicidal ideation (all Ps < 0.05 in ≥ 2 centralities out of DC, BC, and EC). Collectively, salience and thalamic networks underlie spatial strategy and planning, response inhibition, and suicidality in StD and MDD. Anti-suicidal therapies targeting executive function and modulation of salience-thalamic network in StD and MDD are required.
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Affiliation(s)
- Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea
- Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Soo-Hee Choi
- Department of Psychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Susan Park
- Department of Psychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Joon Hwan Jang
- Department of Psychiatry, Seoul National University Health Service Center, 1 Gwanak-Ro, Gwanak-Gu, 08826, Seoul, Republic of Korea.
- Department of Human Systems Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
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Li Q, Zhang X, Yang X, Pan N, Li X, Kemp GJ, Wang S, Gong Q. Pre-COVID brain network topology prospectively predicts social anxiety alterations during the COVID-19 pandemic. Neurobiol Stress 2023; 27:100578. [PMID: 37842018 PMCID: PMC10570707 DOI: 10.1016/j.ynstr.2023.100578] [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: 07/24/2023] [Revised: 09/12/2023] [Accepted: 09/30/2023] [Indexed: 10/17/2023] Open
Abstract
Background Social anxiety (SA) is a negative emotional response that can lead to mental health issues, which some have experienced during the coronavirus disease 2019 (COVID-19) pandemic. Little attention has been given to the neurobiological mechanisms underlying inter-individual differences in SA alterations related to COVID-19. This study aims to identify neurofunctional markers of COVID-specific SA development. Methods 110 healthy participants underwent resting-state magnetic resonance imaging and behavioral tests before the pandemic (T1, October 2019 to January 2020) and completed follow-up behavioral measurements during the pandemic (T2, February to May 2020). We constructed individual functional networks and used graph theoretical analysis to estimate their global and nodal topological properties, then used Pearson correlation and partial least squares correlations examine their associations with COVID-specific SA alterations. Results In terms of global network parameters, SA alterations (T2-T1) were negatively related to pre-pandemic brain small-worldness and normalized clustering coefficient. In terms of nodal network parameters, SA alterations were positively linked to a pronounced degree centrality pattern, encompassing both the high-level cognitive networks (dorsal attention network, cingulo-opercular task control network, default mode network, memory retrieval network, fronto-parietal task control network, and subcortical network) and low-level perceptual networks (sensory/somatomotor network, auditory network, and visual network). These findings were robust after controlling for pre-pandemic general anxiety, other stressful life events, and family socioeconomic status, as well as by treating SA alterations as categorical variables. Conclusions The individual functional network associated with SA alterations showed a disrupted topological organization with a more random state, which may shed light on the neurobiological basis of COVID-related SA changes at the network level.
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Affiliation(s)
- Qingyuan Li
- Department of Interventional Therapy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Xun Zhang
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Xun Yang
- School of Public Affairs, Chongqing University, Chongqing, 400044, China
| | - Nanfang Pan
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Xiao Li
- Department of Interventional Therapy, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Graham J. Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L69 3BX, UK
| | - Song Wang
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Qiyong Gong
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, 361000, China
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Jung WH, Kim E. Different topological patterns in structural covariance networks between high and low delay discounters. Front Psychol 2023; 14:1210652. [PMID: 37711326 PMCID: PMC10498536 DOI: 10.3389/fpsyg.2023.1210652] [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: 04/23/2023] [Accepted: 08/18/2023] [Indexed: 09/16/2023] Open
Abstract
Introduction People prefer immediate over future rewards because they discount the latter's value (a phenomenon termed "delay discounting," used as an index of impulsivity). However, little is known about how the preferences are implemented in brain in terms of the coordinated pattern of large-scale structural brain networks. Methods To examine this question, we classified high discounting group (HDG) and low discounting group (LDG) in young adults by assessing their propensity for intertemporal choice. We compared global and regional topological properties in gray matter volume-based structural covariance networks between two groups using graph theoretical analysis. Results HDG had less clustering coefficient and characteristic path length over the wide sparsity range than LDG, indicating low network segregation and high integration. In addition, the degree of small-worldness was more significant in HDG. Locally, HDG showed less betweenness centrality (BC) in the parahippocampal gyrus and amygdala than LDG. Discussion These findings suggest the involvement of structural covariance network topology on impulsive choice, measured by delay discounting, and extend our understanding of how impulsive choice is associated with brain morphological features.
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Affiliation(s)
- Wi Hoon Jung
- Department of Psychology, Gachon University, Seongnam, Republic of Korea
| | - Euitae Kim
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
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11
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Robinson B, Bhamidi S, Dayan E. The spatial distribution of coupling between tau and neurodegeneration in amyloid-β positive mild cognitive impairment. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.13.23288533. [PMID: 37131677 PMCID: PMC10153340 DOI: 10.1101/2023.04.13.23288533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Synergies between amyloid-β (Aβ), tau, and neurodegeneration persist along the Alzheimer's disease (AD) continuum. This study aimed to evaluate the extent of spatial coupling between tau and neurodegeneration (atrophy) and its relation to Aβ positivity in mild cognitive impairment (MCI). Data from 409 subjects were included (95 cognitively normal controls, 158 Aβ positive (Aβ+) MCI, and 156 Aβ negative (Aβ-) MCI) Florbetapir PET, Flortaucipir PET, and structural MRI were used as biomarkers for Aβ, tau and atrophy, respectively. Individual correlation matrices for tau load and atrophy were used to layer a multilayer network, with separate layers for tau and atrophy. A measure of coupling between corresponding regions of interest/nodes in the tau and atrophy layers was computed, as a function of Aβ positivity. The extent to which tau-atrophy coupling mediated associations between Aβ burden and cognitive decline was also evaluated. Heightened coupling between tau and atrophy in Aβ+ MCI was found primarily in the entorhinal and hippocampal regions (i.e., in regions corresponding to Braak stages I/II), and to a lesser extent in limbic and neocortical regions (i.e., corresponding to later Braak stages). Coupling strengths in the right middle temporal and inferior temporal gyri mediated the association between Aβ burden and cognition in this sample. Higher coupling between tau and atrophy in Aβ+ MCI is primarily evident in regions corresponding to early Braak stages and relates to overall cognitive decline. Coupling in neocortical regions is more restricted in MCI.
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Zhang L, Hu X, Hu Y, Tang M, Qiu H, Zhu Z, Gao Y, Li H, Kuang W, Ji W. Structural covariance network of the hippocampus-amygdala complex in medication-naïve patients with first-episode major depressive disorder. PSYCHORADIOLOGY 2022; 2:190-198. [PMID: 38665275 PMCID: PMC10917195 DOI: 10.1093/psyrad/kkac023] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/05/2022] [Accepted: 12/14/2022] [Indexed: 04/28/2024]
Abstract
Background The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder (MDD). Each of these structures consists of several heterogeneous subfields. We aim to explore the topologic properties of the volume-based intrinsic network within the hippocampus-amygdala complex in medication-naïve patients with first-episode MDD. Methods High-resolution T1-weighted magnetic resonance imaging scans were acquired from 123 first-episode, medication-naïve, and noncomorbid MDD patients and 81 age-, sex-, and education level-matched healthy control participants (HCs). The structural covariance network (SCN) was constructed for each group using the volumes of the hippocampal subfields and amygdala subregions; the weights of the edges were defined by the partial correlation coefficients between each pair of subfields/subregions, controlled for age, sex, education level, and intracranial volume. The global and nodal graph metrics were calculated and compared between groups. Results Compared with HCs, the SCN within the hippocampus-amygdala complex in patients with MDD showed a shortened mean characteristic path length, reduced modularity, and reduced small-worldness index. At the nodal level, the left hippocampal tail showed increased measures of centrality, segregation, and integration, while nodes in the left amygdala showed decreased measures of centrality, segregation, and integration in patients with MDD compared with HCs. Conclusion Our results provide the first evidence of atypical topologic characteristics within the hippocampus-amygdala complex in patients with MDD using structure network analysis. It provides more delineate mechanism of those two structures that underlying neuropathologic process in MDD.
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Affiliation(s)
- Lianqing Zhang
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Xinyue Hu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Yongbo Hu
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Mengyue Tang
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Hui Qiu
- Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Ziyu Zhu
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Yingxue Gao
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Hailong Li
- Functional and molecular imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, PR China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Weidong Ji
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science and Affiliated Mental Health Center, East China Normal University, Shanghai 200335, China
- Child Psychiatry, Shanghai Changning Mental Health Center, Shanghai 200335, China
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13
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Bharti K, Conte G, Tommasin S, Giannì C, Suppa A, Mirabella G, Cardona F, Pantano P. White matter alterations in drug-naïve children with Tourette syndrome and obsessive-compulsive disorder. Front Neurol 2022; 13:960979. [PMID: 36262836 PMCID: PMC9575657 DOI: 10.3389/fneur.2022.960979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 08/29/2022] [Indexed: 11/13/2022] Open
Abstract
Tourette syndrome (TS) and early-onset obsessive-compulsive disorder (OCD) are frequently associated and conceptualized as distinct phenotypes of a common disease spectrum. However, the nature of their relationship is still largely unknown on a pathophysiological level. In this study, early structural white matter (WM) changes investigated through diffusion tensor imaging (DTI) were compared across four groups of drug-naïve children: TS-pure (n = 16), TS+OCD (n = 14), OCD (n = 10), and 11 age-matched controls. We analyzed five WM tracts of interest, i.e., cortico-spinal tract (CST), anterior thalamic radiations (ATR), inferior longitudinal fasciculus (ILF), corpus callosum (CC), and cingulum and evaluated correlations of DTI changes to symptom severity. Compared to controls, TS-pure and TS+OCD showed a comparable pattern of increased fractional anisotropy (FA) in CST, ATR, ILF and CC, with FA changes displaying negative correlation to tic severity. Conversely, in OCD, FA decreased in all WM tracts (except for the cingulum) compared to controls and negatively correlated to symptoms. We demonstrate different early WM microstructural alterations in children with TS-pure/TS+OCD as opposed to OCD. Our findings support the conceptualization of TS+OCD as a subtype of TS while suggesting that OCD is characterized by independent pathophysiological mechanisms affecting WM development.
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Affiliation(s)
- Komal Bharti
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Giulia Conte
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
- *Correspondence: Giulia Conte
| | - Silvia Tommasin
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Costanza Giannì
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Neuromed, Isernia, Italy
| | - Antonio Suppa
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Neuromed, Isernia, Italy
| | - Giovanni Mirabella
- Department of Clinical and Experimental Sciences Section, Brescia University, Brescia, Italy
| | - Francesco Cardona
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Patrizia Pantano
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Neuromed, Isernia, Italy
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Sehmbi M, Suh JS, Rowley CD, Minuzzi L, Kapczinski F, Bock NA, Frey BN. Network properties of intracortical myelin associated with psychosocial functioning in bipolar I disorder. Bipolar Disord 2022; 24:539-548. [PMID: 35114029 DOI: 10.1111/bdi.13181] [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: 11/27/2022]
Abstract
OBJECTIVE Psychosocial functioning in bipolar disorder (BD) persists even during euthymia and has repeatedly been associated with illness progression and cognitive function. Its neurobiological correlates remain largely unexplored. Using a structural covariance approach, we explored whole cortex intracortical myelin (ICM) and psychosocial functioning in 39 BD type I and 58 matched controls. METHOD T1 -weighted images (3T) optimized for ICM measurement were analyzed using a surface-based approach. The ICM signal was sampled at cortical mid-depth using the MarsAtlas parcellation, and psychosocial functioning was measured via the Functioning Assessment Short Test (FAST). Following construction of structural covariance matrices, graph theoretical measures were calculated for each subject. Within BD and HC groups separately, correlations between network measures and FAST were explored. After accounting for multiple comparisons, significant correlations were tested formally using rank-based regressions accounting for sex differences. RESULTS In BD only, psychosocial functioning was associated with global efficiency (β = -0.312, pcorr = 0.03), local efficiency in the right rostral dorsolateral prefrontal cortex (β = 0.545, pcorr = 0.001) and clustering coefficient in this region (β = 0.497, pcorr = 0.0002) as well as in the right ventromedial prefrontal cortex (β = 0.428, pcorr = 0.002). All results excepting global efficiency remained significant after accounting for severity of depressive symptoms. In contrast, no significant associations between functioning and network measures were observed in the HC group. CONCLUSION These results uncovered a novel brain-behaviour relationship between intracortical myelin signal changes and psychosocial functioning in BD.
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Affiliation(s)
- Manpreet Sehmbi
- Mood Disorders Program, Department of Psychiatry & Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
| | - Jee Su Suh
- Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada
| | | | - Luciano Minuzzi
- Mood Disorders Program, Department of Psychiatry & Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
| | - Flavio Kapczinski
- Mood Disorders Program, Department of Psychiatry & Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada
| | - Nicholas A Bock
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, Ontario, Canada
| | - Benicio N Frey
- Mood Disorders Program, Department of Psychiatry & Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada.,Women's Health Concerns Clinic, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
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Zhang J, Liu Y, Guo X, Guo J, Du Z, He M, Liu Q, Xu D, Liu T, Zhang J, Yuan H, Wang M, Li S. Causal Structural Covariance Network Suggesting Structural Alterations Progression in Type 2 Diabetes Patients. Front Hum Neurosci 2022; 16:936943. [PMID: 35911591 PMCID: PMC9336220 DOI: 10.3389/fnhum.2022.936943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 06/16/2022] [Indexed: 12/02/2022] Open
Abstract
Background and Purpose According to reports, type 2 diabetes (T2D) is a progressive disease. However, no known research has examined the progressive brain structural changes associated with T2D. The purpose of this study was to determine whether T2D patients exhibit progressive brain structural alterations and, if so, how the alterations progress. Materials and Methods Structural magnetic resonance imaging scans were collected for 81 T2D patients and 48 sex-and age-matched healthy controls (HCs). Voxel-based morphometry (VBM) and causal structural covariance network (CaSCN) analyses were applied to investigate gray matter volume (GMV) alterations and the likely chronological processes underlying them in T2D. Two sample t-tests were performed to compare group differences, and the differences were corrected using Gaussian random field (GRF) correction (voxel-level p < 0.001, cluster-level p < 0.01). Results Our findings demonstrated that GMV alterations progressed in T2D patients as disease duration increased. In the early stages of the disease, the right temporal pole of T2D patients had GMV atrophy. As the diseases duration prolonged, the limbic system, cerebellum, subcortical structures, parietal cortex, frontal cortex, and occipital cortex progressively exhibited GMV alterations. The patients also exhibited a GMV alterations sequence exerting from the right temporal pole to the limbic-cerebellum-striatal-cortical network areas. Conclusion Our results indicate that the progressive GMV alterations of T2D patients manifested a limbic-cerebellum-striatal-cortical sequence. These findings may contribute to a better understanding of the progression and an improvement of current diagnosis and intervention strategies for T2D.
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Affiliation(s)
- Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yuyan Liu
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Xiaonan Guo
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
- Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao, China
| | - Jing Guo
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhengcong Du
- School of Information Science and Technology, Xichang University, Xichang, China
| | - Muyuan He
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Qihong Liu
- College of Biomedical Engineering, Sichuan University, Chengdu, China
| | - Dundi Xu
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Taiyuan Liu
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
| | - Junran Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
- *Correspondence: Junran Zhang
| | - Huijuan Yuan
- Department of Endocrinology, Henan Provincial People's Hospital, Zhengzhou, China
- Huijuan Yuan
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
- Meiyun Wang
| | - Shasha Li
- The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
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16
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Nigro S, Filardi M, Tafuri B, De Blasi R, Cedola A, Gigli G, Logroscino G. The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia. Front Neurol 2022; 13:910054. [PMID: 35837233 PMCID: PMC9275562 DOI: 10.3389/fneur.2022.910054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/02/2022] [Indexed: 11/21/2022] Open
Abstract
Frontotemporal dementia (FTD) is a spectrum of clinical syndromes that affects personality, behavior, language, and cognition. The current diagnostic criteria recognize three main clinical subtypes: the behavioral variant of FTD (bvFTD), the semantic variant of primary progressive aphasia (svPPA), and the non-fluent/agrammatic variant of PPA (nfvPPA). Patients with FTD display heterogeneous clinical and neuropsychological features that highly overlap with those presented by psychiatric syndromes and other types of dementia. Moreover, up to now there are no reliable disease biomarkers, which makes the diagnosis of FTD particularly challenging. To overcome this issue, different studies have adopted metrics derived from magnetic resonance imaging (MRI) to characterize structural and functional brain abnormalities. Within this field, a growing body of scientific literature has shown that graph theory analysis applied to MRI data displays unique potentialities in unveiling brain network abnormalities of FTD subtypes. Here, we provide a critical overview of studies that adopted graph theory to examine the topological changes of large-scale brain networks in FTD. Moreover, we also discuss the possible role of information arising from brain network organization in the diagnostic algorithm of FTD-spectrum disorders and in investigating the neural correlates of clinical symptoms and cognitive deficits experienced by patients.
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Affiliation(s)
- Salvatore Nigro
- Institute of Nanotechnology (NANOTEC), National Research Council, Lecce, Italy
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, “Pia Fondazione Cardinale G. Panico”, Tricase, Italy
- Salvatore Nigro
| | - Marco Filardi
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, “Pia Fondazione Cardinale G. Panico”, Tricase, Italy
- Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Benedetta Tafuri
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, “Pia Fondazione Cardinale G. Panico”, Tricase, Italy
- Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Roberto De Blasi
- Department of Radiology, “Pia Fondazione Cardinale G. Panico”, Tricase, Lecce, Italy
| | - Alessia Cedola
- Institute of Nanotechnology (NANOTEC), National Research Council, Lecce, Italy
| | - Giuseppe Gigli
- Institute of Nanotechnology (NANOTEC), National Research Council, Lecce, Italy
- Department of Mathematics and Physics “Ennio De Giorgi”, University of Salento, Lecce, Italy
| | - Giancarlo Logroscino
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, “Pia Fondazione Cardinale G. Panico”, Tricase, Italy
- Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- *Correspondence: Giancarlo Logroscino
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Lammertink F, van den Heuvel MP, Hermans EJ, Dudink J, Tataranno ML, Benders MJNL, Vinkers CH. Early-life stress exposure and large-scale covariance brain networks in extremely preterm-born infants. Transl Psychiatry 2022; 12:256. [PMID: 35717524 PMCID: PMC9206645 DOI: 10.1038/s41398-022-02019-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 05/25/2022] [Accepted: 06/07/2022] [Indexed: 12/03/2022] Open
Abstract
The stressful extrauterine environment following premature birth likely has far-reaching and persistent adverse consequences. The effects of early "third-trimester" ex utero stress on large-scale brain networks' covariance patterns may provide a potential avenue to understand how early-life stress following premature birth increases risk or resilience. We evaluated the impact of early-life stress exposure (e.g., quantification of invasive procedures) on maturational covariance networks (MCNs) between 30 and 40 weeks of gestational age in 180 extremely preterm-born infants (<28 weeks of gestation; 43.3% female). We constructed MCNs using covariance of gray matter volumes between key nodes of three large-scale brain networks: the default mode network (DMN), executive control network (ECN), and salience network (SN). Maturational coupling was quantified by summating the number of within- and between-network connections. Infants exposed to high stress showed significantly higher SN but lower DMN maturational coupling, accompanied by DMN-SN decoupling. Within the SN, the insula, amygdala, and subthalamic nucleus all showed higher maturational covariance at the nodal level. In contrast, within the DMN, the hippocampus, parahippocampal gyrus, and fusiform showed lower coupling following stress. The decoupling between DMN-SN was observed between the insula/anterior cingulate cortex and posterior parahippocampal gyrus. Early-life stress showed longitudinal network-specific maturational covariance patterns, leading to a reprioritization of developmental trajectories of the SN at the cost of the DMN. These alterations may enhance the ability to cope with adverse stimuli in the short term but simultaneously render preterm-born individuals at a higher risk for stress-related psychopathology later in life.
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Affiliation(s)
- Femke Lammertink
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije University Amsterdam, Amsterdam, The Netherlands
- Department of Child Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, The Netherlands
| | - Erno J Hermans
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jeroen Dudink
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Maria L Tataranno
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Manon J N L Benders
- Department of Neonatology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Christiaan H Vinkers
- Department of Anatomy & Neurosciences, Amsterdam UMC (location Vrije University Amsterdam), Amsterdam, The Netherlands
- Department of Psychiatry, Amsterdam UMC (location Vrije University Amsterdam), Amsterdam, The Netherlands
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18
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Fang S, Li L, Weng S, Guo Y, Zhong Z, Fan X, Jiang T, Wang Y. Contralesional Sensorimotor Network Participates in Motor Functional Compensation in Glioma Patients. Front Oncol 2022; 12:882313. [PMID: 35530325 PMCID: PMC9072743 DOI: 10.3389/fonc.2022.882313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 03/11/2022] [Indexed: 11/18/2022] Open
Abstract
Background Some gliomas in sensorimotor areas induce motor deficits, while some do not. Cortical destruction and reorganization contribute to this phenomenon, but detailed reasons remain unclear. This study investigated the differences of the functional connectivity and topological properties in the contralesional sensorimotor network (cSMN) between patients with motor deficit and those with normal motor function. Methods We retrospectively reviewed 65 patients (32 men) between 2017 and 2020. The patients were divided into four groups based on tumor laterality and preoperative motor status (deficit or non-deficit). Thirty-three healthy controls (18 men) were enrolled after matching for sex, age, and educational status. Graph theoretical measurement was applied to reveal alterations of the topological properties of the cSMN by analyzing resting-state functional MRI. Results The results for patients with different hemispheric gliomas were similar. The clustering coefficient, local efficiency, transitivity, and vulnerability of the cSMN significantly increased in the non-deficit group and decreased in the deficit group compared to the healthy group (p < 0.05). Moreover, the nodes of the motor-related thalamus showed a significantly increased nodal efficiency and nodal local efficiency in the non-deficit group and decreased in the deficit group compared with the healthy group (p < 0.05). Conclusions We posited the existence of two stages of alterations of the preoperative motor status. In the compensatory stage, the cSMN sacrificed stability to acquire high efficiency and to compensate for impaired motor function. With the glioma growing and the motor function being totally damaged, the cSMN returned to a stable state and maintained healthy hemispheric motor function, but with low efficiency.
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Affiliation(s)
- Shengyu Fang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Lianwang Li
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Shimeng Weng
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Yuhao Guo
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Zhang Zhong
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xing Fan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- *Correspondence: Xing Fan, ; Tao Jiang, ; Yinyan Wang,
| | - Tao Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Research Unit of Accurate Diagnosis, Treatment and Translational Medicine of Brain Tumors, Chinese Academy of Medical Sciences, Beijing, China
- *Correspondence: Xing Fan, ; Tao Jiang, ; Yinyan Wang,
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- *Correspondence: Xing Fan, ; Tao Jiang, ; Yinyan Wang,
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Han S, Xu Y, Guo H, Fang K, Wei Y, Liu L, Cheng J, Zhang Y, Cheng J. Two distinct subtypes of obsessive compulsive disorder revealed by heterogeneity through discriminative analysis. Hum Brain Mapp 2022; 43:3037-3046. [PMID: 35384125 PMCID: PMC9188970 DOI: 10.1002/hbm.25833] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 02/18/2022] [Accepted: 02/21/2022] [Indexed: 01/31/2023] Open
Abstract
Neurobiological heterogeneity in obsessive compulsive disorder (OCD) is understudied leading to conflicting neuroimaging findings. Therefore, we investigated objective neuroanatomical subtypes of OCD by adopting a newly proposed method based on gray matter volumes (GMVs). GMVs were derived from T1‐weighted anatomical images of patients with OCD (n = 100) and matched healthy controls (HCs; n = 106). We first inquired whether patients with OCD presented higher interindividual variability HCs in terms of GMVs. Then, we identified distinct subtypes of OCD by adopting heterogeneity through discriminative analysis (HYDRA), where regional GMVs were treated as features. Patients with OCD presented higher interindividual variability than HCs, suggesting a high structural heterogeneity of OCD. HYDRA identified two distinct robust subtypes of OCD presenting opposite neuroanatomical aberrances compared with HCs, while sharing indistinguishable clinical and demographic features. Specifically, Subtype 1 exhibited widespread increased GMVs in cortical and subcortical regions, including the orbitofrontal gyrus, right anterior insula, bilateral hippocampus, and bilateral parahippocampus and cerebellum. Subtype 2 demonstrated overall decreased GMVs in regions such as the orbitofrontal gyrus, right anterior insula, and precuneus. When mixed together, none of patients presented significant differences compared with HCs. In addition, the total intracranial volume of Subtype 2 was significantly correlated with the total score of the Yale–Brown Obsessive Compulsive Scale while that of Subtype 1 was not. These results identified two distinct neuroanatomical subtypes, providing a possible explanation for conflicting neuroimaging findings, and proposed a potential objective taxonomy contributing to precise clinical diagnosis and treatment in OCD.
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20
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Sha Z, van Rooij D, Anagnostou E, Arango C, Auzias G, Behrmann M, Bernhardt B, Bolte S, Busatto GF, Calderoni S, Calvo R, Daly E, Deruelle C, Duan M, Duran FLS, Durston S, Ecker C, Ehrlich S, Fair D, Fedor J, Fitzgerald J, Floris DL, Franke B, Freitag CM, Gallagher L, Glahn DC, Haar S, Hoekstra L, Jahanshad N, Jalbrzikowski M, Janssen J, King JA, Lazaro L, Luna B, McGrath J, Medland SE, Muratori F, Murphy DGM, Neufeld J, O'Hearn K, Oranje B, Parellada M, Pariente JC, Postema MC, Remnelius KL, Retico A, Rosa PGP, Rubia K, Shook D, Tammimies K, Taylor MJ, Tosetti M, Wallace GL, Zhou F, Thompson PM, Fisher SE, Buitelaar JK, Francks C. Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium. Mol Psychiatry 2022; 27:2114-2125. [PMID: 35136228 PMCID: PMC9126820 DOI: 10.1038/s41380-022-01452-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 12/23/2021] [Accepted: 01/14/2022] [Indexed: 12/30/2022]
Abstract
Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium's ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.
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Affiliation(s)
- Zhiqiang Sha
- Department of Language & Genetics, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
| | - Daan van Rooij
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Evdokia Anagnostou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital and Department of Pediatrics, University of Toronto, Toronto, ON, Canada
| | - Celso Arango
- Child and Adolescent Psychiatry Department, Institute of Psychiatry and Mental Health, Gregorio Maran General University Hospital, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, Madrid, Spain
| | - Guillaume Auzias
- Institut de Neurosciences de la Timone, UMR 7289, Aix Marseille Universit, CNRS, Marseille, France
| | - Marlene Behrmann
- Department of Psychology and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Boris Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Sven Bolte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
- Curtin Autism Research Group, Curtin School of Allied Health, Curtin University, Perth, WA, Australia
| | - Geraldo F Busatto
- Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Sara Calderoni
- IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Rosa Calvo
- Department of Child and Adolescent Psychiatry and Psychology Hospital Clinic, Psychiatry Unit, Department of Medicine, 2017SGR881, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Spain
| | - Eileen Daly
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience King's College London, London, UK
| | - Christine Deruelle
- Institut de Neurosciences de la Timone, UMR 7289, Aix Marseille Universit, CNRS, Marseille, France
| | - Meiyu Duan
- BioKnow Health Informatics Lab, College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Fabio Luis Souza Duran
- Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Sarah Durston
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Christine Ecker
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Frankfurt, Germany
- The Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Stefan Ehrlich
- Department of Child and Adolescent Psychiatry & Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Damien Fair
- Institute of Child Development, Department of Pediatrics, Masonic Institute of the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Jennifer Fedor
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jacqueline Fitzgerald
- Department of Psychiatry, School of Medicine, Trinity College, Dublin, Ireland
- The Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Dorothea L Floris
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christine M Freitag
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital, Goethe University Frankfurt am Main, Frankfurt, Germany
| | - Louise Gallagher
- Department of Psychiatry, School of Medicine, Trinity College, Dublin, Ireland
- The Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, 02115-5724, USA
- Olin Neuropsychiatric Research Center, Hartford, CT, USA
| | - Shlomi Haar
- Department of Brain Sciences, Imperial College London, London, UK
| | - Liesbeth Hoekstra
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA
| | - Maria Jalbrzikowski
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Joost Janssen
- Child and Adolescent Psychiatry Department, Institute of Psychiatry and Mental Health, Gregorio Maran General University Hospital, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, Madrid, Spain
| | - Joseph A King
- Department of Child and Adolescent Psychiatry & Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Luisa Lazaro
- Department of Child and Adolescent Psychiatry and Psychology Hospital Clinic, Psychiatry Unit, Department of Medicine, 2017SGR881, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Spain
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jane McGrath
- Department of Psychiatry, School of Medicine, Trinity College, Dublin, Ireland
- The Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Filippo Muratori
- IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Declan G M Murphy
- The Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Behavioural Genetics Clinic, Adult Autism Service, Behavioural and Developmental Psychiatry Clinical Academic Group, South London and Maudsley Foundation NHS Trust, London, UK
| | - Janina Neufeld
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Kirsten O'Hearn
- Department of Physiology and Pharmacology, Wake Forest Baptist Medical Center, Winston-Salem, NC, USA
| | - Bob Oranje
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mara Parellada
- Child and Adolescent Psychiatry Department, Institute of Psychiatry and Mental Health, Gregorio Maran General University Hospital, School of Medicine, Universidad Complutense, IiSGM, CIBERSAM, Madrid, Spain
| | - Jose C Pariente
- Magnetic Resonance Image Core Facility, IDIBAPS (Institut d'Investigacions Biomdiques August Pi i Sunyer), Barcelona, Spain
| | - Merel C Postema
- Department of Language & Genetics, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Karl Lundin Remnelius
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Women's and Children's Health, Karolinska Institutet & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden
| | - Alessandra Retico
- National Institute for Nuclear Physics, Pisa Division, Largo B. Pontecorvo 3, Pisa, Italy
| | - Pedro Gomes Penteado Rosa
- Laboratory of Psychiatric Neuroimaging (LIM-21), Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Katya Rubia
- Institute of Psychiatry, King's College London, London, UK
| | - Devon Shook
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Kristiina Tammimies
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region, Stockholm, Sweden
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research; Department of Womens and Childrens Health, Karolinska Institutet and Child and Adolescent Psychiatry, Stockholm Health Care Services, Stockholm County Council, Stockholm, Sweden
| | - Margot J Taylor
- Diagnostic Imaging, The Hospital for Sick Children, and Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | | | - Gregory L Wallace
- Department of Speech, Language, and Hearing Sciences, The George Washington University, Washington, DC, USA
| | - Fengfeng Zhou
- BioKnow Health Informatics Lab, College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, Jilin, 130012, China
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA
| | - Simon E Fisher
- Department of Language & Genetics, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Clyde Francks
- Department of Language & Genetics, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
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21
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Li S, Bai R, Yang Y, Zhao R, Upreti B, Wang X, Liu S, Cheng Y, Xu J. Abnormal cortical thickness and structural covariance networks in systemic lupus erythematosus patients without major neuropsychiatric manifestations. Arthritis Res Ther 2022; 24:259. [PMID: 36443835 PMCID: PMC9703716 DOI: 10.1186/s13075-022-02954-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 11/11/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Non-neuropsychiatric systemic lupus erythematosus (non-NPSLE) has been confirmed to have subtle changes in brain structure before the appearance of obvious neuropsychiatric symptoms. Previous literature mainly focuses on brain structure loss in non-NPSLE; however, the results are heterogeneous, and the impact of structural changes on the topological structure of patients' brain networks remains to be determined. In this study, we combined neuroimaging and network analysis methods to evaluate the changes in cortical thickness and its structural covariance networks (SCNs) in patients with non-NPSLE. METHODS We compare the cortical thickness of non-NPSLE patients (N=108) and healthy controls (HCs, N=88) using both surface-based morphometry (SBM) and regions of interest (ROI) methods, respectively. After that, we analyzed the correlation between the abnormal cortical thickness results found in the ROI method and a series of clinical features. Finally, we constructed the SCNs of two groups using the regional cortical thickness and analyzed the abnormal SCNs of non-NPSLE. RESULTS By SBM method, we found that cortical thickness of 34 clusters in the non-NPSLE group was thinner than that in the HC group. ROI method based on Destrieux atlas showed that cortical thickness of 57 regions in the non-NPSLE group was thinner than that in the HC group and related to the course of disease, autoantibodies, the cumulative amount of immunosuppressive agents, and cognitive psychological scale. In the SCN analysis, the cortical thickness SCNs of the non-NPSLE group did not follow the small-world attribute at a few densities, and the global clustering coefficient appeared to increase. The area under the curve analysis showed that there were significant differences between the two groups in clustering coefficient, degree, betweenness, and local efficiency. There are a total of seven hubs for non-NPSLE, and five hubs in HCs, the two groups do not share a common hub distribution. CONCLUSION Extensive and obvious reduction in cortical thickness and abnormal topological organization of SCNs are observed in non-NPSLE patients. The observed abnormalities may not only be the realization of brain damage caused by the disease, but also the contribution of the compensatory changes within the nervous system.
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Affiliation(s)
- Shu Li
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Ru Bai
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yifan Yang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Ruotong Zhao
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Bibhuti Upreti
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiangyu Wang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shuang Liu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China.
| | - Jian Xu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
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22
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Fu X, Quan W, Liu L, Li T, Dong W, Wang J, Tian J, Yan J, Liao J. Similarities and Differences in Brain Activation Between Patients With Schizophrenia and Obsessive-Compulsive Disorder: A Near-Infrared Spectroscopy Study. Front Psychiatry 2022; 13:853428. [PMID: 35558422 PMCID: PMC9086627 DOI: 10.3389/fpsyt.2022.853428] [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: 03/14/2022] [Indexed: 11/13/2022] Open
Abstract
Schizophrenia (SZ) and obsessive-compulsive disorder (OCD) share several epidemiological and clinical features, but the neurobiological substrates shared by these two diseases remain unclear. This study aimed to explore the similarities and differences in brain function between them using near-infrared spectroscopy (NIRS). Eventually, 130 SZ patients, 70 OCD and 75 normal controls (NCs) were enrolled. A 52-channel NIRS instrument was used to detect the concentration changes in oxygenated hemoglobin ([oxy-Hb]) during the verbal fluency task. Ten regions of interests (ROIs) were defined: the bilateral dorsolateral prefrontal cortex (DLPFC), frontopolar cortex (FPC), orbitofrontal cortex (OFC), inferior prefrontal gyrus (IFG) and temporal gyrus (TG). Through two different analysis strategies based on channels or ROIs, we compared the [oxy-Hb] changes in three groups by one-way analysis of variance (ANOVA) and post-hoc tests. Across 52 channels, compared to the NC group, both SZ and OCD groups exhibited reduced activity in 17 channels, including left FPC, left DLPFC, bilateral OFC, IFG, middle TG, supplementary motor cortex and Broca's area, while SZ showed lower activity in channel 35 (right OFC) than OCD patients. Across all ROIs, compared to the NC group, both SZ and OCD groups showed reduced activity in 7 ROIs, including left FPC, bilateral OFC, IFG and TG, while SZ showed lower activity in the right OFC than OCD group, which were almost consistent with the results based on channels. This study suggests SZ and OCD present with some similar neuropathological changes, while SZ shows more severe impairment in the right OFC than OCD.
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Affiliation(s)
- Xiaoyu Fu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.,Zhongshan Hospital, Fudan University, Xiamen, China
| | - Wenxiang Quan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Lijun Liu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Tian Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Wentian Dong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jiuju Wang
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Ju Tian
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jun Yan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jinmin Liao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
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23
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Coenen VA, Schlaepfer TE, Meyer D, Kilian H, Spanier S, Sajonz BEA, Reinacher PC, Reisert M. Resolving dyskinesias at sustained anti-OCD efficacy by steering of DBS away from the anteromedial STN to the mesencephalic ventral tegmentum - case report. Acta Neurochir (Wien) 2022; 164:2303-2307. [PMID: 35499574 PMCID: PMC9427876 DOI: 10.1007/s00701-022-05206-w] [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: 02/24/2022] [Accepted: 04/03/2022] [Indexed: 02/05/2023]
Abstract
Here we describe therapeutic results in a female patient who underwent bilateral slMFB DBS for OCD. During a 35-month long course of stimulation, she suffered from stimulation-induced dyskinesia of her right leg which we interpreted as co-stimulation of the adjacent anteromedial subthalamic nucleus (amSTN). After reprogramming to steer the stimulation away from the amSTN medial into the direction of the mesencephalic ventral tegmentum (MVT which contains the ventral tegmental area, VTA), the dyskinesias disappeared. Remarkably, anti-OCD efficacy in the presented patient was preserved and achieved with a bilateral stimulation which by our imaging study fully avoided the amSTN.
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Affiliation(s)
- Volker A. Coenen
- Department of Stereotactic and Functional Neurosurgery, Medical Center of Freiburg University, Freiburg, Germany ,Medical Faculty of Freiburg University, Freiburg, Germany ,Center for Deep Brain Stimulation, Medical Center of Freiburg University, Freiburg, Germany
| | - Thomas E. Schlaepfer
- Medical Faculty of Freiburg University, Freiburg, Germany ,Center for Deep Brain Stimulation, Medical Center of Freiburg University, Freiburg, Germany ,Department of Interventional Biological Psychiatry, University Hospital Freiburg, Freiburg, Germany
| | - Dora Meyer
- Medical Faculty of Freiburg University, Freiburg, Germany ,Department of Interventional Biological Psychiatry, University Hospital Freiburg, Freiburg, Germany
| | - Hannah Kilian
- Medical Faculty of Freiburg University, Freiburg, Germany ,Department of Interventional Biological Psychiatry, University Hospital Freiburg, Freiburg, Germany
| | - Susanne Spanier
- Medical Faculty of Freiburg University, Freiburg, Germany ,Department of Interventional Biological Psychiatry, University Hospital Freiburg, Freiburg, Germany
| | - Bastian E. A. Sajonz
- Department of Stereotactic and Functional Neurosurgery, Medical Center of Freiburg University, Freiburg, Germany ,Medical Faculty of Freiburg University, Freiburg, Germany
| | - Peter C. Reinacher
- Department of Stereotactic and Functional Neurosurgery, Medical Center of Freiburg University, Freiburg, Germany ,Medical Faculty of Freiburg University, Freiburg, Germany ,Fraunhofer Institute for Laser Technology (ILT), Aachen, Germany
| | - Marco Reisert
- Department of Stereotactic and Functional Neurosurgery, Medical Center of Freiburg University, Freiburg, Germany ,Medical Faculty of Freiburg University, Freiburg, Germany ,Department of Diagnostic and Interventional Radiology, Medical Physics, Medical Center – University of Freiburg, Freiburg, Germany
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24
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Weeland CJ, van den Heuvel OA, White T, Tiemeier H, Vriend C. Obsessive-compulsive symptoms and resting-state functional characteristics in pre-adolescent children from the general population. Brain Imaging Behav 2022; 16:2715-2724. [PMID: 36319909 PMCID: PMC9712396 DOI: 10.1007/s11682-022-00732-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 09/17/2022] [Accepted: 10/05/2022] [Indexed: 12/04/2022]
Abstract
While functional brain characteristics of obsessive-compulsive disorder have been extensively studied, literature on network topology and subnetwork connectivity related to obsessive-compulsive symptoms (OCS) is sparse. Here we investigated the functional brain characteristics of OCS in children from the general population using a multiscale approach. Since we previously observed OCS-related differences in thalamus morphology, we also focused on the network participation of thalamic subregions. The study included 1701 participants (9-12 years) from the population-based Generation R study. OCS were measured using the Short Obsessive-Compulsive Disorder Screener. We studied the brain network at multiple scales: global network topology, subnetwork connectivity and network participation of thalamic nodes (pre-registration: https://osf.io/azr9c ). Modularity, small-worldness and average participation coefficient were calculated on the global scale. We used a data-driven consensus community approach to extract a partition of five subnetworks involving thalamic subregions and calculate the within- and between-subnetwork functional connectivity and topology. Multiple linear regression models were fitted to model the relationship between OCS and functional brain measures. No significant associations were found when using our preregistered definition of probable OCS. However, post-hoc analyses showed that children endorsing at least one OCS (compared with controls) had higher modularity, lower connectivity between frontoparietal, limbic and visual networks as well as altered participation of the lateral prefrontal thalamus node. Our results suggest that network characteristics of OCS in children from the general population are partly symptom-specific and severity-dependent. Thorough assessment of symptom dimensions can deepen our understanding of OCS-related brain networks.
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Affiliation(s)
- Cees J Weeland
- Department of Anatomy and Neurosciences, Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, De Boelelaan 1117, 1081HV, Amsterdam, Netherlands.
- Dept. Child and Adolescent Psychiatry/Psychology, Erasmus Medical Center, Wytemaweg 8, 3015 GD, Rotterdam, the Netherlands.
- The Generation R Study Group, Erasmus Medical Center, Doctor Molewaterplein 40, 3015 GD, Rotterdam, the Netherlands.
| | - Odile A van den Heuvel
- Department of Anatomy and Neurosciences, Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, De Boelelaan 1117, 1081HV, Amsterdam, Netherlands
| | - T White
- Dept. Child and Adolescent Psychiatry/Psychology, Erasmus Medical Center, Wytemaweg 8, 3015 GD, Rotterdam, the Netherlands
| | - H Tiemeier
- Harvard TH Chan School of Public Health, 677 Huntington Ave, 02115, Boston, MA, USA
| | - C Vriend
- Department of Anatomy and Neurosciences, Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, PO Box 7057, 1007 MB, De Boelelaan 1117, 1081HV, Amsterdam, Netherlands
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25
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Liu J, Wen F, Yan J, Yu L, Wang F, Wang D, Zhang J, Yan C, Chu J, Li Y, Li Y, Cui Y. Gray Matter Alterations in Pediatric Schizophrenia and Obsessive-Compulsive Disorder: A Systematic Review and Meta-Analysis of Voxel-Based Morphometry Studies. Front Psychiatry 2022; 13:785547. [PMID: 35308883 PMCID: PMC8924120 DOI: 10.3389/fpsyt.2022.785547] [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: 09/29/2021] [Accepted: 02/02/2022] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVE The aim of this study is comparing gray matter alterations in SCZ pediatric patients with those suffering from obsessive-compulsive disorder (OCD) based on a systematic review and an activation likelihood estimation (ALE) meta-analysis. METHODS A systematic literature search was performed in PubMed, Elsevier, and China National Knowledge Infrastructure (CNKI). A systematic review and an ALE meta-analysis were performed to quantitatively examine brain gray matter alterations. RESULTS Children and adolescents with schizophrenia had decreased gray matter volume (GMV) mainly in the prefrontal cortex (PFC), temporal cortex (such as the middle temporal gyrus and transverse temporal gyrus), and insula, while children and adolescents with OCD mainly had increased GMV in the PFC and the striatum (including the lentiform nucleus and caudate nucleus), and decreased GMV in the parietal cortex. CONCLUSIONS Our results suggest that gray matter abnormalities in the PFC may indicate homogeneity between the two diseases. In children and adolescents, structural alterations in schizophrenia mainly involve the fronto-temporal and cortico-insula circuits, whereas those in OCD mainly involve the prefrontal-parietal and the prefrontal-striatal circuits.
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Affiliation(s)
- Jingran Liu
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Fang Wen
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Junjuan Yan
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Liping Yu
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Fang Wang
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Duo Wang
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Jishui Zhang
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Chunmei Yan
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Jiahui Chu
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Yanlin Li
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Ying Li
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Yonghua Cui
- Department of Psychiatry, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
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26
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Resolving heterogeneity in schizophrenia through a novel systems approach to brain structure: individualized structural covariance network analysis. Mol Psychiatry 2021; 26:7719-7731. [PMID: 34316005 DOI: 10.1038/s41380-021-01229-4] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 06/15/2021] [Accepted: 07/05/2021] [Indexed: 12/12/2022]
Abstract
Reliable mapping of system-level individual differences is a critical first step toward precision medicine for complex disorders such as schizophrenia. Disrupted structural covariance indicates a system-level brain maturational disruption in schizophrenia. However, most studies examine structural covariance at the group level. This prevents subject-level inferences. Here, we introduce a Network Template Perturbation approach to construct individual differential structural covariance network (IDSCN) using regional gray-matter volume. IDSCN quantifies how structural covariance between two nodes in a patient deviates from the normative covariance in healthy subjects. We analyzed T1 images from 1287 subjects, including 107 first-episode (drug-naive) patients and 71 controls in the discovery datasets and established robustness in 213 first-episode (drug-naive), 294 chronic, 99 clinical high-risk patients, and 494 controls from the replication datasets. Patients with schizophrenia were highly variable in their altered structural covariance edges; the number of altered edges was related to severity of hallucinations. Despite this variability, a subset of covariance edges, including the left hippocampus-bilateral putamen/globus pallidus edges, clustered patients into two distinct subgroups with opposing changes in covariance compared to controls, and significant differences in their anxiety and depression scores. These subgroup differences were stable across all seven datasets with meaningful genetic associations and functional annotation for the affected edges. We conclude that the underlying physiology of affective symptoms in schizophrenia involves the hippocampus and putamen/pallidum, predates disease onset, and is sufficiently consistent to resolve morphological heterogeneity throughout the illness course. The two schizophrenia subgroups identified thus have implications for the nosology and clinical treatment.
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27
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Nigro S, Tafuri B, Urso D, De Blasi R, Cedola A, Gigli G, Logroscino G. Altered structural brain networks in linguistic variants of frontotemporal dementia. Brain Imaging Behav 2021; 16:1113-1122. [PMID: 34755293 PMCID: PMC9107413 DOI: 10.1007/s11682-021-00560-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/13/2021] [Indexed: 12/31/2022]
Abstract
Semantic (svPPA) and nonfluent (nfvPPA) variants of primary progressive aphasia (PPA) have recently been associated with distinct patterns of white matter and functional network alterations in left frontoinsular and anterior temporal regions, respectively. Little information exists, however, about the topological characteristics of gray matter covariance networks in these two PPA variants. In the present study, we used a graph theory approach to describe the structural covariance network organization in 34 patients with svPPA, 34 patients with nfvPPA and 110 healthy controls. All participants underwent a 3 T structural MRI. Next, we used cortical thickness values and subcortical volumes to define subject-specific connectivity networks. Patients with svPPA and nfvPPA were characterized by higher values of normalized characteristic path length compared with controls. Moreover, svPPA patients had lower values of normalized clustering coefficient relative to healthy controls. At a regional level, patients with svPPA showed a reduced connectivity and impaired information processing in temporal and limbic brain areas relative to controls and nfvPPA patients. By contrast, local network changes in patients with nfvPPA were focused on frontal brain regions such as the pars opercularis and the middle frontal cortex. Of note, a predominance of local metric changes was observed in the left hemisphere in both nfvPPA and svPPA brain networks. Taken together, these findings provide new evidences of a suboptimal topological organization of the structural covariance networks in svPPA and nfvPPA patients. Moreover, we further confirm that distinct patterns of structural network alterations are related to neurodegenerative mechanisms underlying each PPA variant.
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Affiliation(s)
- Salvatore Nigro
- Institute of Nanotechnology (NANOTEC), National Research Council, Lecce, Italy.,Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, Pia Fondazione Cardinale G. Panico, Tricase, Lecce, Italy
| | - Benedetta Tafuri
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, Pia Fondazione Cardinale G. Panico, Tricase, Lecce, Italy.,Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Daniele Urso
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, Pia Fondazione Cardinale G. Panico, Tricase, Lecce, Italy.,Department of Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, SE5 8AF, UK
| | - Roberto De Blasi
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, Pia Fondazione Cardinale G. Panico, Tricase, Lecce, Italy.,Department of Radiology, Pia Fondazione Cardinale G. Panico, Tricase, Lecce, Italy
| | - Alessia Cedola
- Institute of Nanotechnology (NANOTEC), National Research Council, Lecce, Italy
| | - Giuseppe Gigli
- Institute of Nanotechnology (NANOTEC), National Research Council, Lecce, Italy.,Department of Mathematics and Physics Ennio De Giorgi, University of Salento, Campus Ecotekne, Lecce, Italy
| | - Giancarlo Logroscino
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari Aldo Moro, Pia Fondazione Cardinale G. Panico, Tricase, Lecce, Italy. .,Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari Aldo Moro, Bari, Italy.
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Szejko N, Dunalska A, Lombroso A, McGuire JF, Piacentini J. Genomics of Obsessive-Compulsive Disorder-Toward Personalized Medicine in the Era of Big Data. Front Pediatr 2021; 9:685660. [PMID: 34746045 PMCID: PMC8564378 DOI: 10.3389/fped.2021.685660] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 09/20/2021] [Indexed: 01/11/2023] Open
Abstract
Pathogenesis of obsessive-compulsive disorder (OCD) mainly involves dysregulation of serotonergic neurotransmission, but a number of other factors are involved. Genetic underprints of OCD fall under the category of "common disease common variant hypothesis," that suggests that if a disease that is heritable is common in the population (a prevalence >1-5%), then the genetic contributors-specific variations in the genetic code-will also be common in the population. Therefore, the genetic contribution in OCD is believed to come from multiple genes simultaneously and it is considered a polygenic disorder. Genomics offers a number of advanced tools to determine causal relationship between the exposure and the outcome of interest. Particularly, methods such as polygenic risk score (PRS) or Mendelian Randomization (MR) enable investigation of new pathways involved in OCD pathogenesis. This premise is also facilitated by the existence of publicly available databases that include vast study samples. Examples include population-based studies such as UK Biobank, China Kadoorie Biobank, Qatar Biobank, All of US Program sponsored by National Institute of Health or Generations launched by Yale University, as well as disease-specific databases, that include patients with OCD and co-existing pathologies, with the following examples: Psychiatric Genomics Consortium (PGC), ENIGMA OCD, The International OCD Foundation Genetics Collaborative (IOCDF-GC) or OCD Collaborative Genetic Association Study. The aim of this review is to present a comprehensive overview of the available Big Data resources for the study of OCD pathogenesis in the context of genomics and demonstrate that OCD should be considered a disorder which requires the approaches offered by personalized medicine.
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Affiliation(s)
- Natalia Szejko
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
- Department of Neurology, Medical University of Warsaw, Warsaw, Poland
- Department of Bioethics, Medical University of Warsaw, Warsaw, Poland
| | - Anna Dunalska
- Department of Neurology, Medical University of Warsaw, Warsaw, Poland
| | - Adam Lombroso
- Child Study Center, Yale School of Medicine, New Haven, CT, United States
| | - Joseph F. McGuire
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MS, United States
- Semel Institute of Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - John Piacentini
- Semel Institute of Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
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29
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Yang Y, Cheng Y, Wang X, Upreti B, Cui R, Liu S, Shan B, Yu H, Luo C, Xu J. Gout Is Not Just Arthritis: Abnormal Cortical Thickness and Structural Covariance Networks in Gout. Front Neurol 2021; 12:662497. [PMID: 34603178 PMCID: PMC8481804 DOI: 10.3389/fneur.2021.662497] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 08/12/2021] [Indexed: 12/27/2022] Open
Abstract
Background: Hyperuricemia is the cause of gout. The antioxidant and neuroprotective effects of uric acid seem to benefit some patients with central nervous system injury. However, changes in the brain structure have not been discovered in patients with gout. Object: Clarify the changes in cortical thickness in patients with gout and the alteration of the structural covariance networks (SCNs) based on cortical thickness. Methods: We collected structural MRIs of 23 male gout patients and 23 age-matched healthy controls. After calculating and comparing the difference in cortical thickness between the two groups, we constructed and analyzed the cortical thickness covariance networks of the two groups, and we investigated for any changes in SCNs of gout patients. Results: Gout patients have thicker cortices in the left postcentral, left supramarginal, right medial temporal, and right medial orbitofrontal regions; and thinner cortices were found in the left insula, left superior frontal, right pericalcarine, and right precentral regions. In SCN analysis, between-group differences in global network measures showed that gout patients have a higher global efficiency. In regional network measures, more nodes in gout patients have increased centrality. In network hub analysis, we found that the transfer of the core hub area, rather than the change in number, may be the characteristic of the gout's cortical thickness covariance network. Conclusion: This is the first study on changes in brain cortical thickness and SCN based on graph theory in patients with gout. The present study found that, compared with healthy controls, gout patients show regional cortical thinning or thickening, and variation in the properties of the cortical thickness covariance network also changed. These alterations may be the combined effect of disease damage and physiological compensation. More research is needed to fully understand the complex underlying mechanisms of gout brain variation.
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Affiliation(s)
- Yifan Yang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiangyu Wang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Bibhuti Upreti
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Ruomei Cui
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shuang Liu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Baoci Shan
- Nuclear Analysis Technology Key Laboratory, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| | - Hongjun Yu
- Magnetic Resonance Imaging Center, The First Hospital of Kunming, Kunming, China
| | - Chunrong Luo
- Magnetic Resonance Imaging Center, The First Hospital of Kunming, Kunming, China
| | - Jian Xu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
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30
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Qing X, Gu L, Li D. Abnormalities of Localized Connectivity in Obsessive-Compulsive Disorder: A Voxel-Wise Meta-Analysis. Front Hum Neurosci 2021; 15:739175. [PMID: 34602998 PMCID: PMC8481585 DOI: 10.3389/fnhum.2021.739175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 08/26/2021] [Indexed: 01/20/2023] Open
Abstract
Background: A large amount of resting-state functional magnetic resonance imaging (rs-fMRI) studies have revealed abnormalities of regional homogeneity (ReHo, an index of localized intraregional connectivity) in the obsessive-compulsive disorder (OCD) in the past few decades, However, the findings of these ReHo studies have remained inconsistent. Hence, we performed a meta-analysis to investigate the concurrence across ReHo studies for clarifying the most consistent localized connectivity underpinning this disorder. Methods: A systematic review of online databases was conducted for whole-brain rs-fMRI studies comparing ReHo between OCD patients and healthy control subjects (HCS). Anisotropic effect size version of the seed-based d mapping, a voxel-wise meta-analytic approach, was adopted to explore regions of abnormal ReHo alterations in OCD patients relative to HCS. Additionally, meta-regression analyses were conducted to explore the potential effects of clinical features on the reported ReHo abnormalities. Results: Ten datasets comprising 359 OCD patients and 361 HCS were included. Compared with HCS, patients with OCD showed higher ReHo in the bilateral inferior frontal gyri and orbitofrontal cortex (OFC). Meanwhile, lower ReHo was identified in the supplementary motor area (SMA) and bilateral cerebellum in OCD patients. Meta-regression analysis demonstrated that the ReHo in the OFC was negatively correlated with illness duration in OCD patients. Conclusions: Our meta-analysis gave a quantitative overview of ReHo findings in OCD and demonstrated that the most consistent localized connectivity abnormalities in individuals with OCD are in the prefrontal cortex. Meanwhile, our findings provided evidence that the hypo-activation of SMA and cerebellum might be associated with the pathophysiology of OCD.
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Affiliation(s)
- Xiuli Qing
- Department of Obstetrics, Key Laboratory of Birth Defects and Related Diseases of Women and Children in Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Li Gu
- Department of Obstetrics, Key Laboratory of Birth Defects and Related Diseases of Women and Children in Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Dehua Li
- Nursing Department, West China Second University Hospital, Sichuan University, Chengdu, China
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31
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He C, Cortes JM, Kang X, Cao J, Chen H, Guo X, Wang R, Kong L, Huang X, Xiao J, Shan X, Feng R, Chen H, Duan X. Individual-based morphological brain network organization and its association with autistic symptoms in young children with autism spectrum disorder. Hum Brain Mapp 2021; 42:3282-3294. [PMID: 33934442 PMCID: PMC8193534 DOI: 10.1002/hbm.25434] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 03/04/2021] [Accepted: 03/25/2021] [Indexed: 01/01/2023] Open
Abstract
Individual-based morphological brain networks built from T1-weighted magnetic resonance imaging (MRI) reflect synchronous maturation intensities between anatomical regions at the individual level. Autism spectrum disorder (ASD) is a socio-cognitive and neurodevelopmental disorder with high neuroanatomical heterogeneity, but the specific patterns of morphological networks in ASD remain largely unexplored at the individual level. In this study, individual-based morphological networks were constructed by using high-resolution structural MRI data from 40 young children with ASD (age range: 2-8 years) and 38 age-, gender-, and handedness-matched typically developing children (TDC). Measurements were recorded as threefold. Results showed that compared with TDC, young children with ASD exhibited lower values of small-worldness (i.e., σ) of individual-level morphological brain networks, increased morphological connectivity in cortico-striatum-thalamic-cortical (CSTC) circuitry, and decreased morphological connectivity in the cortico-cortical network. In addition, morphological connectivity abnormalities can predict the severity of social communication deficits in young children with ASD, thus confirming an associational impact at the behavioral level. These findings suggest that the morphological brain network in the autistic developmental brain is inefficient in segregating and distributing information. The results also highlight the crucial role of abnormal morphological connectivity patterns in the socio-cognitive deficits of ASD and support the possible use of the aberrant developmental patterns of morphological brain networks in revealing new clinically-relevant biomarkers for ASD.
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Affiliation(s)
- Changchun He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Jesus M. Cortes
- Computational Neuroimaging LaboratoryBiocruces‐Bizkaia Health Research InstituteBarakaldoSpain
- Ikerbasque: The Basque Foundation for ScienceBilbaoSpain
- Department of Cell Biology and HistologyUniversity of the Basque CountryLeioaSpain
| | - Xiaodong Kang
- Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCMSichuan Bayi Rehabilitation CenterChengduChina
| | - Jing Cao
- Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCMSichuan Bayi Rehabilitation CenterChengduChina
| | - Heng Chen
- School of MedicineMedical College of Guizhou UniversityGuiyangChina
| | - Xiaonan Guo
- School of Information Science and EngineeringYanshan UniversityQinhuangdaoChina
- Hebei Key Laboratory of information transmission and signal processingYanshan UniversityQinhuangdaoChina
| | - Ruishi Wang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Lingyin Kong
- Department of Biomedical Engineering, School of Material Science and EngineeringSouth China University of TechnologyGuangzhouChina
| | - Xinyue Huang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Jinming Xiao
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Xiaolong Shan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Rui Feng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
| | - Xujun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengduChina
- MOE Key Lab for NeuroinformationHigh‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of ChinaChengduChina
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Mosley PE, Windels F, Morris J, Coyne T, Marsh R, Giorni A, Mohan A, Sachdev P, O’Leary E, Boschen M, Sah P, Silburn PA. A randomised, double-blind, sham-controlled trial of deep brain stimulation of the bed nucleus of the stria terminalis for treatment-resistant obsessive-compulsive disorder. Transl Psychiatry 2021; 11:190. [PMID: 33782383 PMCID: PMC8007749 DOI: 10.1038/s41398-021-01307-9] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Revised: 02/19/2021] [Accepted: 03/05/2021] [Indexed: 12/13/2022] Open
Abstract
Deep brain stimulation (DBS) is a promising treatment for severe, treatment-resistant obsessive-compulsive disorder (OCD). Here, nine participants (four females, mean age 47.9 ± 10.7 years) were implanted with DBS electrodes bilaterally in the bed nucleus of the stria terminalis (BNST). Following a one-month postoperative recovery phase, participants entered a three-month randomised, double-blind, sham-controlled phase before a twelve-month period of open-label stimulation incorporating a course of cognitive behavioural therapy (CBT). The primary outcome measure was OCD symptoms as rated with the Yale-Brown Obsessive-Compulsive Scale (YBOCS). In the blinded phase, there was a significant benefit of active stimulation over sham (p = 0.025, mean difference 4.9 points). After the open phase, the mean reduction in YBOCS was 16.6 ± 1.9 points (χ2 (11) = 39.8, p = 3.8 × 10-5), with seven participants classified as responders. CBT resulted in an additive YBOCS reduction of 4.8 ± 3.9 points (p = 0.011). There were two serious adverse events related to the DBS device, the most severe of which was an infection during the open phase necessitating device explantation. There were no serious psychiatric adverse events related to stimulation. An analysis of the structural connectivity of each participant's individualised stimulation field isolated right-hemispheric fibres associated with YBOCS reduction. These included subcortical tracts incorporating the amygdala, hippocampus and stria terminalis, in addition to cortical regions in the ventrolateral and ventromedial prefrontal cortex, parahippocampal, parietal and extrastriate visual cortex. In conclusion, this study provides further evidence supporting the efficacy and tolerability of DBS in the region of the BNST for individuals with otherwise treatment-refractory OCD and identifies a connectivity fingerprint associated with clinical benefit.
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Affiliation(s)
- Philip E. Mosley
- grid.1049.c0000 0001 2294 1395Systems Neuroscience Group, QIMR Berghofer Medical Research Institute, Herston, QLD Australia ,Neurosciences Queensland, St Andrew’s War Memorial Hospital, Spring Hill, QLD Australia ,grid.1003.20000 0000 9320 7537Queensland Brain Institute, University of Queensland, St Lucia, QLD Australia ,grid.1003.20000 0000 9320 7537Faculty of Medicine, University of Queensland, Herston, QLD Australia
| | - François Windels
- grid.1003.20000 0000 9320 7537Queensland Brain Institute, University of Queensland, St Lucia, QLD Australia
| | - John Morris
- grid.1003.20000 0000 9320 7537Queensland Brain Institute, University of Queensland, St Lucia, QLD Australia
| | - Terry Coyne
- grid.1003.20000 0000 9320 7537Queensland Brain Institute, University of Queensland, St Lucia, QLD Australia ,grid.417021.10000 0004 0627 7561Brizbrain and Spine, the Wesley Hospital, Auchenflower, QLD Australia
| | - Rodney Marsh
- Neurosciences Queensland, St Andrew’s War Memorial Hospital, Spring Hill, QLD Australia ,grid.1003.20000 0000 9320 7537Faculty of Medicine, University of Queensland, Herston, QLD Australia
| | - Andrea Giorni
- grid.1003.20000 0000 9320 7537Queensland Brain Institute, University of Queensland, St Lucia, QLD Australia
| | - Adith Mohan
- grid.1005.40000 0004 4902 0432Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, NSW Australia ,grid.415193.bNeuropsychiatric Institute, The Prince of Wales Hospital, Randwick, NSW Australia
| | - Perminder Sachdev
- grid.1005.40000 0004 4902 0432Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, NSW Australia ,grid.415193.bNeuropsychiatric Institute, The Prince of Wales Hospital, Randwick, NSW Australia
| | | | - Mark Boschen
- grid.1022.10000 0004 0437 5432School of Applied Psychology, Griffith University, Gold Coast, QLD Australia
| | - Pankaj Sah
- grid.1003.20000 0000 9320 7537Queensland Brain Institute, University of Queensland, St Lucia, QLD Australia ,grid.263817.9Joint Center for Neuroscience and Neural Engineering, and Department of Biology, Southern University of Science and Technology, Shenzhen, Guangdong Province P. R. China
| | - Peter A. Silburn
- Neurosciences Queensland, St Andrew’s War Memorial Hospital, Spring Hill, QLD Australia ,grid.1003.20000 0000 9320 7537Queensland Brain Institute, University of Queensland, St Lucia, QLD Australia
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Nigro S, Tafuri B, Urso D, De Blasi R, Frisullo ME, Barulli MR, Capozzo R, Cedola A, Gigli G, Logroscino G. Brain Structural Covariance Networks in Behavioral Variant of Frontotemporal Dementia. Brain Sci 2021; 11:brainsci11020192. [PMID: 33557411 PMCID: PMC7915789 DOI: 10.3390/brainsci11020192] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 01/29/2021] [Accepted: 02/01/2021] [Indexed: 11/17/2022] Open
Abstract
Recent research on behavioral variant frontotemporal dementia (bvFTD) has shown that personality changes and executive dysfunctions are accompanied by a disease-specific anatomical pattern of cortical and subcortical atrophy. We investigated the structural topological network changes in patients with bvFTD in comparison to healthy controls. In particular, 25 bvFTD patients and 20 healthy controls underwent structural 3T MRI. Next, bilaterally averaged values of 34 cortical surface areas, 34 cortical thickness values, and six subcortical volumes were used to capture single-subject anatomical connectivity and investigate network organization using a graph theory approach. Relative to controls, bvFTD patients showed altered small-world properties and decreased global efficiency, suggesting a reduced ability to combine specialized information from distributed brain regions. At a local level, patients with bvFTD displayed lower values of local efficiency in the cortical thickness of the caudal and rostral middle frontal gyrus, rostral anterior cingulate, and precuneus, cuneus, and transverse temporal gyrus. A significant correlation was also found between the efficiency of caudal anterior cingulate thickness and Mini-Mental State Examination (MMSE) scores in bvFTD patients. Taken together, these findings confirm the selective disruption in structural brain networks of bvFTD patients, providing new insights on the association between cognitive decline and graph properties.
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Affiliation(s)
- Salvatore Nigro
- Institute of Nanotechnology (NANOTEC), National Research Council, 73100 Lecce, Italy; (S.N.); (A.C.); (G.G.)
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
| | - Benedetta Tafuri
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
| | - Daniele Urso
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
- Department of Neurosciences, King’s College London, Institute of Psychiatry, Psychology and Neuroscience, De Crespigny Park, London SE5 8AF, UK
| | - Roberto De Blasi
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
- Department of Radiology, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy
| | - Maria Elisa Frisullo
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
| | - Maria Rosaria Barulli
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
| | - Rosa Capozzo
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
| | - Alessia Cedola
- Institute of Nanotechnology (NANOTEC), National Research Council, 73100 Lecce, Italy; (S.N.); (A.C.); (G.G.)
| | - Giuseppe Gigli
- Institute of Nanotechnology (NANOTEC), National Research Council, 73100 Lecce, Italy; (S.N.); (A.C.); (G.G.)
- Department of Mathematics and Physics “Ennio De Giorgi”, University of Salento, Campus Ecotekne, 73100 Lecce, Italy
| | - Giancarlo Logroscino
- Center for Neurodegenerative Diseases and the Aging Brain, Department of Clinical Research in Neurology, University of Bari ‘Aldo Moro, “Pia Fondazione Cardinale G. Panico”, 73039 Tricase, Italy; (B.T.); (D.U.); (R.D.B.); (M.E.F.); (M.R.B.); (R.C.)
- Department of Basic Medicine, Neuroscience, and Sense Organs, University of Bari ‘Aldo Moro’, 70124 Bari, Italy
- Correspondence: or giancarlo.; Tel.: +39-0833/773904
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Altered Topological Properties of Grey Matter Structural Covariance Networks in Complete Thoracic Spinal Cord Injury Patients: A Graph Theoretical Network Analysis. Neural Plast 2021; 2021:8815144. [PMID: 33603780 PMCID: PMC7872768 DOI: 10.1155/2021/8815144] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 01/12/2021] [Accepted: 01/16/2021] [Indexed: 01/04/2023] Open
Abstract
Purpose This study is aimed at investigating brain structural changes and structural network properties in complete spinal cord injury (SCI) patients, as well as their relationship with clinical variables. Materials and Methods Structural MRI of brain was acquired in 24 complete thoracic SCI patients (38.50 ± 11.19 years, 22 males) within the first postinjury year, while 26 age- and gender-matched healthy participants (38.38 ± 10.63 years, 24 males) were enrolled as control. The voxel-based morphometry (VBM) approach and graph theoretical network analysis based on cross-subject grey matter volume- (GMV-) based structural covariance networks (SCNs) were conducted to investigate the impact of SCI on brain structure. Partial correlation analysis was performed to explore the relationship between the GMV of structurally changed brain regions and SCI patients' clinical variables, including injury duration, injury level, Visual Analog Scale (VAS), American Spinal Injury Association Impairment Scale (AIS), International Classification of Functioning, Disability and Health (ICF) scale, Self-rating Depression Scale (SDS), and Self-rating Anxiety Scale (SAS), after removing the effects of age and gender. Results Compared with healthy controls, SCI patients showed higher SDS score (t = 4.392 and p < 0.001). In the VBM analysis, significant GMV reduction was found in the left middle frontal cortex, right superior orbital frontal cortex (OFC), and left inferior OFC. No significant difference was found in global network properties between SCI patients and healthy controls. In the regional network properties, significantly higher betweenness centrality (BC) was noted in the right anterior cingulum cortex (ACC) and left inferior OFC and higher nodal degree and efficiency in bilateral middle OFCs, while decreased BC was noted in the right putamen in SCI patients. Only negative correlation was found between GMV of right middle OFC and SDS score in SCI patients (r = −0.503 and p = 0.017), while no significant correlation between other abnormal brain regions and any of the clinical variables (all p > 0.05). Conclusions SCI patients would experience depressive and/or anxious feelings at the early stage. Their GMV reduction mainly involved psychology-cognition related rather than sensorimotor brain regions. The efficiency of regional information transmission in psychology-cognition regions increased. Greater GMV reduction in psychology region was related with more severe depressive feelings. Therefore, early neuropsychological intervention is suggested to prevent psychological and cognitive dysfunction as well as irreversible brain structure damage.
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Yun JY, Kim YK. Phenotype Network and Brain Structural Covariance Network of Major Depression. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1305:3-18. [PMID: 33834391 DOI: 10.1007/978-981-33-6044-0_1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Phenotype networks enable clinicians to elucidate the patterns of coexistence and interactions among the clinical symptoms, negative cognitive styles , neurocognitive performance, and environmental factors in major depressive disorder (MDD). Results of phenotype network approach could be used in finding the target symptoms as these are tightly connected or associated with many other phenomena within the phenotype network of MDD specifically when comorbid psychiatric disorder(s) is/are present. Further, by comparing the differential patterns of phenotype networks before and after the treatment, changing or enduring patterns of associations among the clinical phenomena in MDD have been deciphered.Brain structural covariance networks describe the inter-regional co-varying patterns of brain morphologies, and overlapping findings have been reported between the brain structural covariance network and coordinated trajectories of brain development and maturation. Intra-individual brain structural covariance illustrates the degrees of similarities among the different brain regions for how much the values of brain morphological features are deviated from those of healthy controls. Inter-individual brain structural covariance reflects the degrees of concordance among the different brain regions for the inter-individual distribution of brain morphologic values. Estimation of the graph metrics for these brain structural covariance networks uncovers the organizational profile of brain morphological variations in the whole brain and the regional distribution of brain hubs.
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Affiliation(s)
- Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea. .,Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Yong-Ku Kim
- Department of Psychiatry, Korea University Ansan Hospital, College of Medicine, Ansan, Republic of Korea
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Abstract
Anatomical imaging in OCD using magnetic resonance imaging (MRI) has been performed since the late 1980s. MRI research was further stimulated with the advent of automated image processing techniques such as voxel-based morphometry (VBM) and surface-based methods (e.g., FreeSurfer) which allow for detailed whole-brain data analyses. Early studies suggesting involvement of corticostriatal circuitry (particularly orbitofrontal cortex and ventral striatum) have been complemented by meta-analyses and pooled analyses indicating additional involvement of posterior brain regions, in particular parietal cortex. Recent large-scale meta-analyses from the ENIGMA consortium have revealed greater pallidum and smaller hippocampus volume in adult OCD, coupled with parietal cortical thinning. Frontal cortical thinning was only observed in medicated patients. Previous reports of symptom dimension-specific alterations were not confirmed. In paediatric OCD, thalamus enlargement has been a consistent finding. Studies investigating white matter volume (VBM) or integrity (using diffusion tensor imaging (DTI)) have shown mixed results, with recent DTI meta-analyses mainly showing involvement of posterior cortical-subcortical tracts in addition to subcortical-prefrontal connections. To which extent these abnormalities are unique to OCD or common to other psychiatric disorders is unclear, as few comparative studies have been performed. Overall, neuroanatomical alterations in OCD appear to be subtle and may vary with time, stressing the need for adequately powered longitudinal studies. Although multivariate approaches using machine learning methodologies have so far been disappointing in distinguishing individual OCD patients from healthy controls, including multimodal data in such analyses may aid in further establishing a neurobiological profile of OCD.
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Affiliation(s)
- D J Veltman
- Department of Psychiatry, Amsterdam UMC, Amsterdam, The Netherlands.
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Abstract
OCD has lagged behind other psychiatric illnesses in the identification of molecular treatment targets, due in part to a lack of significant findings in genome-wide association studies. However, while progress in this area is being made, OCD's symptoms of obsessions, compulsions, and anxiety can be deconstructed into distinct neural functions that can be dissected in animal models. Studies in rodents and non-human primates have highlighted the importance of cortico-basal ganglia-thalamic circuits in OCD pathophysiology, and emerging studies in human post-mortem brain tissue point to glutamatergic synapse abnormalities as a potential cellular substrate for observed dysfunctional behaviors. In addition, accumulated evidence points to a potential role for neuromodulators including serotonin and dopamine in both OCD pathology and treatment. Here, we review current efforts to use animal models for the identification of molecules, cell types, and circuits relevant to OCD pathophysiology. We start by describing features of OCD that can be modeled in animals, including circuit abnormalities and genetic findings. We then review different strategies that have been used to study OCD using animal model systems, including transgenic models, circuit manipulations, and dissection of OCD-relevant neural constructs. Finally, we discuss how these findings may ultimately help to develop new treatment strategies for OCD and other related disorders.
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Affiliation(s)
- Brittany L Chamberlain
- Department of Psychiatry, Translational Neuroscience Program, University of Pittsburgh, Pittsburgh, PA, USA.,Center for Neuroscience Program and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
| | - Susanne E Ahmari
- Department of Psychiatry, Translational Neuroscience Program, University of Pittsburgh, Pittsburgh, PA, USA. .,Center for Neuroscience Program and Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA.
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Gender-Related and Hemispheric Effects in Cortical Thickness-Based Hemispheric Brain Morphological Network. BIOMED RESEARCH INTERNATIONAL 2020; 2020:3560259. [PMID: 32851064 PMCID: PMC7439209 DOI: 10.1155/2020/3560259] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 06/19/2020] [Accepted: 07/06/2020] [Indexed: 12/18/2022]
Abstract
Objective The current study examined gender-related differences in hemispheric asymmetries of graph metrics, calculated from a cortical thickness-based brain structural covariance network named hemispheric morphological network. Methods Using the T1-weighted magnetic resonance imaging scans of 285 participants (150 females, 135 males) retrieved from the Human Connectome Project (HCP), hemispheric morphological networks were constructed per participant. In these hemispheric morphologic networks, the degree of similarity between two different brain regions in terms of the distributed patterns of cortical thickness values (the Jensen–Shannon divergence) was defined as weight of network edge that connects two different brain regions. After the calculation and summation of global and local graph metrics (across the network sparsity levels K = 0.10‐0.36), asymmetry indexes of these graph metrics were derived. Results Hemispheric morphological networks satisfied small-worldness and global efficiency for the network sparsity ranges of K = 0.10–0.36. Between-group comparisons (female versus male) of asymmetry indexes revealed opposite directionality of asymmetries (leftward versus rightward) for global metrics of normalized clustering coefficient, normalized characteristic path length, and global efficiency (all p < 0.05). For the local graph metrics, larger rightward asymmetries of cingulate-superior parietal gyri for nodal efficiency in male compared to female, larger leftward asymmetry of temporal pole for degree centrality in female compared to male, and opposite directionality of interhemispheric asymmetry of rectal gyrus for degree centrality between female (rightward) and male (leftward) were shown (all p < 0.05). Conclusion Patterns of interhemispheric asymmetries for cingulate, superior parietal gyrus, temporal pole, and rectal gyrus are different between male and female for the similarities of the cortical thickness distribution with other brain regions. Accordingly, possible effect of gender-by-hemispheric interaction has to be considered in future studies of brain morphology and brain structural covariance networks.
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Lin X, Chen Y, Wang M, Song C, Lin B, Yuan X, Liu Q, Yang H, Jiang N. Altered Topological Patterns of Gray Matter Networks in Tinnitus: A Graph-Theoretical-Based Study. Front Neurosci 2020; 14:541. [PMID: 32536854 PMCID: PMC7267018 DOI: 10.3389/fnins.2020.00541] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 05/01/2020] [Indexed: 11/13/2022] Open
Abstract
Objective Tinnitus is a prevalent hearing disorder, which could have a devastating impact on a patient’s life. Functional studies have revealed connectivity pattern changes in the tinnitus brains that suggested a change of network dynamics as well as topological organization. However, no studies have yet provided evidence for the topological network changes in the gray matter. In this research, we aim to use the graph-theoretical approach to investigate the changes of topology in the tinnitus brain using structural MRI data, which could provide insights into the underlying anatomical basis for the neural mechanism in generating phantom sounds. Methods We collected 3D MRI images on 46 bilateral tinnitus patients and 46 age and gender-matched healthy controls. Brain networks were constructed with correlation matrices of the cortical thickness and subcortical volumes of 80 cortical/subcortical regions of interests. Global network properties were analyzed using local and global efficiency, clustering coefficient, and small-world coefficient, and regional network properties were evaluated using the betweenness coefficient for hub connectivity, and interregional correlations for edge properties. Between-group differences in cortical thickness and subcortical volumes were assessed using independent sample t-tests, and local efficiency, global efficiency, clustering coefficient, sigma, and interregional correlation were compared using non-parametric permutation tests. Results Tinnitus was found to have increased global efficiency, local efficiency, and cluster coefficient, indicating generally heightened connectivity of the network. The small-world coefficient remained normal for tinnitus, indicating intact small-worldness. Betweenness centrality analysis showed that hubs in the amygdala and parahippocampus were only found for tinnitus but not controls. In contrast, hubs in the auditory cortex, insula, and thalamus were only found for controls but not tinnitus. Interregional correlation analysis further found in tinnitus enhanced connectivity between the auditory cortex and prefrontal lobe, and decreased connectivity of the insula with anterior cingulate gyrus and parahippocampus. Conclusion These findings provided the first morphological evidence of altered topological organization of the brain networks in tinnitus. These alterations suggest that heightened efficiency of the brain network and altered auditory-limbic connection for tinnitus, which could be developed in compensation for the auditory deafferentation, leading to overcompensation and, ultimately, an emotional and cognitive burden.
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Affiliation(s)
- Xiaofeng Lin
- Department of Nuclear Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Nuclear Medicine, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Yueyao Chen
- Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Mingxia Wang
- Department of Hearing and Speech Sciences, Xinhua College of Sun Yat-sen University, Guangzhou, China
| | - Chao Song
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Bingling Lin
- Department of Radiology, Peking University Shen Zhen Hospital, Shenzhen, China
| | - Xiaoping Yuan
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qingyu Liu
- Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Haidi Yang
- Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ningyi Jiang
- Department of Nuclear Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Nuclear Medicine, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
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40
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Thompson PM, Jahanshad N, Ching CRK, Salminen LE, Thomopoulos SI, Bright J, Baune BT, Bertolín S, Bralten J, Bruin WB, Bülow R, Chen J, Chye Y, Dannlowski U, de Kovel CGF, Donohoe G, Eyler LT, Faraone SV, Favre P, Filippi CA, Frodl T, Garijo D, Gil Y, Grabe HJ, Grasby KL, Hajek T, Han LKM, Hatton SN, Hilbert K, Ho TC, Holleran L, Homuth G, Hosten N, Houenou J, Ivanov I, Jia T, Kelly S, Klein M, Kwon JS, Laansma MA, Leerssen J, Lueken U, Nunes A, Neill JO, Opel N, Piras F, Piras F, Postema MC, Pozzi E, Shatokhina N, Soriano-Mas C, Spalletta G, Sun D, Teumer A, Tilot AK, Tozzi L, van der Merwe C, Van Someren EJW, van Wingen GA, Völzke H, Walton E, Wang L, Winkler AM, Wittfeld K, Wright MJ, Yun JY, Zhang G, Zhang-James Y, Adhikari BM, Agartz I, Aghajani M, Aleman A, Althoff RR, Altmann A, Andreassen OA, Baron DA, Bartnik-Olson BL, Marie Bas-Hoogendam J, Baskin-Sommers AR, Bearden CE, Berner LA, Boedhoe PSW, Brouwer RM, Buitelaar JK, Caeyenberghs K, Cecil CAM, Cohen RA, Cole JH, Conrod PJ, De Brito SA, de Zwarte SMC, Dennis EL, Desrivieres S, Dima D, Ehrlich S, Esopenko C, Fairchild G, Fisher SE, Fouche JP, Francks C, Frangou S, Franke B, Garavan HP, Glahn DC, Groenewold NA, Gurholt TP, Gutman BA, Hahn T, Harding IH, Hernaus D, Hibar DP, Hillary FG, Hoogman M, Hulshoff Pol HE, Jalbrzikowski M, Karkashadze GA, Klapwijk ET, Knickmeyer RC, Kochunov P, Koerte IK, Kong XZ, Liew SL, Lin AP, Logue MW, Luders E, Macciardi F, Mackey S, Mayer AR, McDonald CR, McMahon AB, Medland SE, Modinos G, Morey RA, Mueller SC, Mukherjee P, Namazova-Baranova L, Nir TM, Olsen A, Paschou P, Pine DS, Pizzagalli F, Rentería ME, Rohrer JD, Sämann PG, Schmaal L, Schumann G, Shiroishi MS, Sisodiya SM, Smit DJA, Sønderby IE, Stein DJ, Stein JL, Tahmasian M, Tate DF, Turner JA, van den Heuvel OA, van der Wee NJA, van der Werf YD, van Erp TGM, van Haren NEM, van Rooij D, van Velzen LS, Veer IM, Veltman DJ, Villalon-Reina JE, Walter H, Whelan CD, Wilde EA, Zarei M, Zelman V. ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries. Transl Psychiatry 2020; 10:100. [PMID: 32198361 PMCID: PMC7083923 DOI: 10.1038/s41398-020-0705-1] [Citation(s) in RCA: 296] [Impact Index Per Article: 74.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 12/11/2019] [Accepted: 12/20/2019] [Indexed: 02/07/2023] Open
Abstract
This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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Affiliation(s)
- Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Lauren E Salminen
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Joanna Bright
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Sara Bertolín
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, Barcelona, Spain
| | - Janita Bralten
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Willem B Bruin
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Robin Bülow
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Jian Chen
- Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA
| | - Yann Chye
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Carolien G F de Kovel
- Biometris Wageningen University and Research, Wageningen, The Netherlands
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Gary Donohoe
- The Center for Neuroimaging and Cognitive Genomics, School of Psychology, National University of Ireland, Galway, Ireland
| | - Lisa T Eyler
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
- Desert-Pacific Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Stephen V Faraone
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Pauline Favre
- INSERM Unit 955 Team 15 'Translational Psychiatry', Créteil, France
- NeuroSpin, UNIACT Lab, Psychiatry Team, CEA Saclay, Gif-Sur-Yvette, France
| | - Courtney A Filippi
- National Institute of Mental Health, National of Health, Bethesda, MD, USA
| | - Thomas Frodl
- Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Daniel Garijo
- Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA
| | - Yolanda Gil
- Information Sciences Institute, University of Southern California, Marina del Rey, CA, USA
- Department of Computer Science, University of Southern California, Los Angeles, CA, USA
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Katrina L Grasby
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- National Institute of Mental Health, Klecany, Czech Republic
| | - Laura K M Han
- Department of Psychiatry, Amsterdam University Medical Centers, VU University Medical Center, GGZ inGeest, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Sean N Hatton
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
- Brain and Mind Centre, University of Sydney, Sydney, Australia
| | - Kevin Hilbert
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Tiffany C Ho
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
- Department of Psychiatry & Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Laurena Holleran
- The Center for Neuroimaging and Cognitive Genomics, School of Psychology, National University of Ireland, Galway, Ireland
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Norbert Hosten
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Josselin Houenou
- INSERM Unit 955 Team 15 'Translational Psychiatry', Créteil, France
- NeuroSpin, UNIACT Lab, Psychiatry Team, CEA Saclay, Gif-Sur-Yvette, France
- APHP, Mondor University Hospitals, School of Medicine, DMU Impact, Psychiatry Department, Créteil, France
| | - Iliyan Ivanov
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sinead Kelly
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
| | - Marieke Klein
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Max A Laansma
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jeanne Leerssen
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Ulrike Lueken
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Abraham Nunes
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
- Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
| | - Joseph O' Neill
- Child & Adolescent Psychiatry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nils Opel
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Federica Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Merel C Postema
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Elena Pozzi
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia
| | - Natalia Shatokhina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Carles Soriano-Mas
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute-IDIBELL, Barcelona, Spain
- CIBERSAM-G17, Madrid, Spain
- Department of Psychobiology and Methodology in Health Sciences, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Daqiang Sun
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Mental Health, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Amanda K Tilot
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Leonardo Tozzi
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Celia van der Merwe
- Stanley Center for Psychiatric Research, The Broad Institute, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Eus J W Van Someren
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
- Psychiatry and Integrative Neurophysiology, VU University, Amsterdam UMC, Amsterdam, The Netherlands
| | - Guido A van Wingen
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research, Partner Site Greifswald, Greifswald, Germany
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK
| | - Lei Wang
- Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Anderson M Winkler
- National Institute of Mental Health, National of Health, Bethesda, MD, USA
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea
- Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Guohao Zhang
- Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, MD, USA
| | - Yanli Zhang-James
- Departments of Psychiatry and of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Bhim M Adhikari
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Research & Innovation, GGZ InGeest, Amsterdam, The Netherlands
| | - André Aleman
- University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Robert R Althoff
- Psychiatry, Pediatrics, and Psychological Sciences, University of Vermont, Burlington, VT, USA
| | - Andre Altmann
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - David A Baron
- Provost and Senior Vice President, Western University of Health Sciences, Pomona, CA, USA
| | | | - Janna Marie Bas-Hoogendam
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | | | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychology, University of California, Los Angeles, CA, USA
| | - Laura A Berner
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Premika S W Boedhoe
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Rachel M Brouwer
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC, Australia
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Ronald A Cohen
- Center for Cognitive Aging and Memory, University of Florida, Gainesville, FL, USA
- Clinical and Health Psychology, Gainesville, FL, USA
| | - James H Cole
- Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, London, UK
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Patricia J Conrod
- Universite de Montreal, Centre de Recherche CHU Ste-Justine, Montreal, QC, Canada
| | - Stephane A De Brito
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Sonja M C de Zwarte
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Emily L Dennis
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sylvane Desrivieres
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Danai Dima
- Department of Psychology, School of Arts and Social Sciences, City, University of London, London, UK
- Department of Neuroimaging, Institute of Psychology, Psychiatry and Neurosciences, King's College London, London, UK
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Carrie Esopenko
- Department of Rehabilitation and Movement Sciences, School of Health Professions, Rutgers Biomedical Health Sciences, Newark, NJ, USA
| | | | - Simon E Fisher
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Jean-Paul Fouche
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- SU/UCT MRC Unit on Risk & Resilience in Mental Disorders, University of Stellenbosch, Stellenbosch, South Africa
| | - Clyde Francks
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- University of British Columbia, Vancouver, Canada
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Hugh P Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Olin Neuropsychiatric Research Center, Institute of Living, Hartford, CT, USA
| | - Nynke A Groenewold
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Tiril P Gurholt
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Boris A Gutman
- Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
- Institute for Information Transmission Problems, Kharkevich Institute, Moscow, Russian Federation
| | - Tim Hahn
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Ian H Harding
- Turner Institute for Brain and Mental Health & School of Psychological Sciences, Monash University, Melbourne, VIC, Australia
| | - Dennis Hernaus
- Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | | - Frank G Hillary
- Department of Psychology, Penn State University, University Park, PA, USA
- Social Life and Engineering Sciences Imaging Center, University Park, PA, USA
| | - Martine Hoogman
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | | | - George A Karkashadze
- Research and Scientific Institute of Pediatrics and Child Health, CCH RAS, Ministry of Science and Higher Education, Moscow, Russian Federation
| | - Eduard T Klapwijk
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Rebecca C Knickmeyer
- Department of Pediatrics, Michigan State University, East Lansing, MI, USA
- Institute for Quantitative Health Science and Engineering, East Lansing, MI, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Peter Kochunov
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Inga K Koerte
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
- CBRAIN, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Xiang-Zhen Kong
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Sook-Lei Liew
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Chan Division of Occupational Science and Occupational Therapy, Los Angeles, CA, USA
| | - Alexander P Lin
- Center for Clinical Spectroscopy, Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Mark W Logue
- National Center for PTSD at Boston VA Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
- Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA
| | - Eileen Luders
- School of Psychology, University of Auckland, Auckland, New Zealand
- Laboratory of Neuro Imaging, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Fabio Macciardi
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, USA
| | - Scott Mackey
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | | | - Carrie R McDonald
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, USA
- Psychiatry, San Diego, CA, USA
| | - Agnes B McMahon
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- The Kavli Foundation, Los Angeles, CA, USA
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Gemma Modinos
- Department of Neuroimaging, Institute of Psychology, Psychiatry and Neurosciences, King's College London, London, UK
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Rajendra A Morey
- Department of Psychiatry, Duke University School of Medicine, Durham, NC, USA
- Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Sven C Mueller
- Experimental Clinical & Health Psychology, Ghent University, Ghent, Belgium
- Department of Personality, Psychological Assessment and Treatment, University of Deusto, Bilbao, Spain
| | | | - Leyla Namazova-Baranova
- Research and Scientific Institute of Pediatrics and Child Health, CCH RAS, Ministry of Science and Higher Education, Moscow, Russian Federation
- Department of Pediatrics, Russian National Research Medical University MoH RF, Moscow, Russian Federation
| | - Talia M Nir
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Alexander Olsen
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | | | - Daniel S Pine
- National Institute of Mental Health Intramural Research Program, Bethesda, MD, USA
| | - Fabrizio Pizzagalli
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jonathan D Rohrer
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | | | - Lianne Schmaal
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), MRC SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychiatry and Psychotherapy, Charite, Humboldt University, Berlin, Germany
| | - Mark S Shiroishi
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- Department of Radiology, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, University College London, London, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter, UK
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Ida E Sønderby
- Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health & Addiction, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Dan J Stein
- Department of Psychiatry & Neuroscience Institute, SA MRC Unit on Risk & Resilience in Mental Disorders, Cape Town, South Africa
| | - Jason L Stein
- Department of Genetics & UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Masoud Tahmasian
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, I. R., Iran
| | - David F Tate
- Department of Neurology, TBI and Concussion Center, Salt Lake City, UT, USA
- Missouri Institute of Mental Health, Berkeley, MO, USA
| | - Jessica A Turner
- Psychology Department & Neuroscience Institute, Georgia State University, Atlanta, GA, USA
| | - Odile A van den Heuvel
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Nic J A van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Ysbrand D van der Werf
- Department of Anatomy & Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, USA
| | - Neeltje E M van Haren
- Department of Psychiatry, UMC Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Daan van Rooij
- Donders Centre for Cognitive Neuroimaging, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Laura S van Velzen
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Ilya M Veer
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Location VUmc, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Julio E Villalon-Reina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Henrik Walter
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Christopher D Whelan
- Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin, Ireland
- Research and Early Development, Biogen Inc, Cambridge, MA, USA
| | - Elisabeth A Wilde
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- VA Salt Lake City Healthcare System, Salt Lake City, UT, USA
- Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, I. R., Iran
| | - Vladimir Zelman
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Skolkovo Institute of Science and Technology, Moscow, Russian Federation
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Szejko N, Fremer C, Müller-Vahl KR. Cannabis Improves Obsessive-Compulsive Disorder-Case Report and Review of the Literature. Front Psychiatry 2020; 11:681. [PMID: 32848902 PMCID: PMC7396551 DOI: 10.3389/fpsyt.2020.00681] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2020] [Accepted: 06/29/2020] [Indexed: 12/18/2022] Open
Abstract
Although several lines of evidence support the hypothesis of a dysregulation of serotoninergic neurotransmission in the pathophysiology of obsessive-compulsive disorder (OCD), there is also evidence for an involvement of other pathways such as the GABAergic, glutamatergic, and dopaminergic systems. Only recently, data obtained from a small number of animal studies alternatively suggested an involvement of the endocannabinoid system in the pathophysiology of OCD reporting beneficial effects in OCD-like behavior after use of substances that stimulate the endocannabinoid system. In humans, until today, only two case reports are available reporting successful treatment with dronabinol (tetrahydrocannabinol, THC), an agonist at central cannabinoid CB1 receptors, in patients with otherwise treatment refractory OCD. In addition, data obtained from a small open uncontrolled trial using the THC analogue nabilone suggest that the combination of nabilone plus exposure-based psychotherapy is more effective than each treatment alone. These reports are in line with data from a limited number of case studies and small controlled trials in patients with Tourette syndrome (TS), a chronic motor and vocal tic disorder often associated with comorbid obsessive compulsive behavior (OCB), reporting not only an improvement of tics, but also of comorbid OCB after use of different kinds of cannabis-based medicines including THC, cannabis extracts, and flowers. Here we present the case of a 22-year-old male patient, who suffered from severe OCD since childhood and significantly improved after treatment with medicinal cannabis with markedly reduced OCD and depression resulting in a considerable improvement of quality of life. In addition, we give a review of current literature on the effects of cannabinoids in animal models and patients with OCD and suggest a cannabinoid hypothesis of OCD.
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Affiliation(s)
- Natalia Szejko
- Clinic of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany.,Division of Neurocritical Care & Emergency Neurology, Department of Neurology, Yale School of Medicine, New Haven, CT, United States.,Department of Bioethics, Medical University of Warsaw, Warsaw, Poland.,Department of Neurology, Medical University of Warsaw, Warsaw, Poland
| | - Carolin Fremer
- Clinic of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
| | - Kirsten R Müller-Vahl
- Clinic of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
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