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Qin K, Pan N, Lei D, Zhang F, Yu Y, Sweeney JA, DelBello MP, Gong Q. Common and distinct neural correlates of emotional processing in individuals at familial risk for major depressive disorder and bipolar disorder: A comparative meta-analysis. J Affect Disord 2024; 348:97-106. [PMID: 38113944 PMCID: PMC10846904 DOI: 10.1016/j.jad.2023.12.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 12/04/2023] [Accepted: 12/13/2023] [Indexed: 12/21/2023]
Abstract
Individuals at familial risk for mood disorders exhibit deficits in emotional processing and associated brain dysfunction prior to illness onset. However, such brain-behavior abnormalities related to familial predisposition remain poorly understood. To investigate robust abnormal functional activation patterns during emotional processing in unaffected at-risk relatives of patients with major depressive disorder (UAR-MDD) and bipolar disorder (UAR-BD), we performed a meta-analysis of task-based functional magnetic resonance imaging studies using Seed-based d Mapping (SDM) toolbox. Common and distinct patterns of abnormal functional activation between UAR-MDD and UAR-BD were detected via conjunction and differential analyses. A total of 17 studies comparing 481 UAR and 670 healthy controls (HC) were included. Compared with HC, UAR-MDD exhibited hyperactivation in the parahippocampal gyrus, amygdala and cerebellum, while UAR-BD exhibited parahippocampal hyperactivation and hypoactivation in the striatum and middle occipital gyrus (MOG). Conjunction analysis revealed shared hyperactivated PHG in both groups. Differential analysis indicated that the activation patterns of amygdala and MOG significantly differed between UAR-MDD and UAR-BD. These findings provide novel insights into common and distinct neural phenotypes for familial risk and associated risk mechanisms in MDD and BD, which may have implications in guiding precise prevention strategies tailored to the family context.
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Affiliation(s)
- Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States of America
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States of America; College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China
| | - Feifei Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yifan Yu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States of America
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States of America
| | - Qiyong Gong
- 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 361021, China.
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Huang Y, Zhang J, He K, Mo X, Yu R, Min J, Zhu T, Ma Y, He X, Lv F, Lei D, Liu M. Innovative Neuroimaging Biomarker Distinction of Major Depressive Disorder and Bipolar Disorder through Structural Connectome Analysis and Machine Learning Models. Diagnostics (Basel) 2024; 14:389. [PMID: 38396428 PMCID: PMC10888009 DOI: 10.3390/diagnostics14040389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 02/03/2024] [Accepted: 02/08/2024] [Indexed: 02/25/2024] Open
Abstract
Major depressive disorder (MDD) and bipolar disorder (BD) share clinical features, which complicates their differentiation in clinical settings. This study proposes an innovative approach that integrates structural connectome analysis with machine learning models to discern individuals with MDD from individuals with BD. High-resolution MRI images were obtained from individuals diagnosed with MDD or BD and from HCs. Structural connectomes were constructed to represent the complex interplay of brain regions using advanced graph theory techniques. Machine learning models were employed to discern unique connectivity patterns associated with MDD and BD. At the global level, both BD and MDD patients exhibited increased small-worldness compared to the HC group. At the nodal level, patients with BD and MDD showed common differences in nodal parameters primarily in the right amygdala and the right parahippocampal gyrus when compared with HCs. Distinctive differences were found mainly in prefrontal regions for BD, whereas MDD was characterized by abnormalities in the left thalamus and default mode network. Additionally, the BD group demonstrated altered nodal parameters predominantly in the fronto-limbic network when compared with the MDD group. Moreover, the application of machine learning models utilizing structural brain parameters demonstrated an impressive 90.3% accuracy in distinguishing individuals with BD from individuals with MDD. These findings demonstrate that combined structural connectome and machine learning enhance diagnostic accuracy and may contribute valuable insights to the understanding of the distinctive neurobiological signatures of these psychiatric disorders.
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Affiliation(s)
- Yang Huang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Jingbo Zhang
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China (J.M.)
| | - Kewei He
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China (J.M.)
| | - Xue Mo
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Renqiang Yu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Jing Min
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China (J.M.)
| | - Tong Zhu
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China (J.M.)
| | - Yunfeng Ma
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China (J.M.)
| | - Xiangqian He
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China (J.M.)
| | - Fajin Lv
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
| | - Du Lei
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China (J.M.)
| | - Mengqi Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China
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Ai Y, Li F, Hou Y, Li X, Li W, Qin K, Suo X, Lei D, Shang H, Gong Q. Differential cortical gray matter changes in early- and late-onset patients with amyotrophic lateral sclerosis. Cereb Cortex 2024; 34:bhad426. [PMID: 38061694 DOI: 10.1093/cercor/bhad426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 10/11/2023] [Accepted: 10/14/2023] [Indexed: 01/19/2024] Open
Abstract
Age at onset may be an important feature associated with distinct subtypes of amyotrophic lateral sclerosis (ALS). Little is known about the neuropathological mechanism of early-onset ALS (EO-ALS) and late-onset ALS (LO-ALS). Ninety ALS patients were divided into EO-ALS and LO-ALS group, and 128 healthy controls were matched into young controls(YCs) and old controls (OCs). A voxel-based morphometry approach was employed to investigate differences in gray matter volume (GMV). Significant age at onset-by-diagnosis interactions were found in the left parietal operculum, left precentral gyrus, bilateral postcentral gyrus, right occipital gyrus, and right orbitofrontal cortex. Post hoc analysis revealed a significant decrease in GMV in all affected regions of EO-ALS patients compared with YCs, with increased GMV in 5 of the 6 brain regions, except for the right orbitofrontal cortex, in LO-ALS patients compared with OCs. LO-ALS patients had a significantly increased GMV than EO-ALS patients after removing the aging effect. Correspondingly, GMV of the left postcentral gyrus correlated with disease severity in the 2 ALS groups. Our findings suggested that the pathological mechanisms in ALS patients with different ages at onset might differ. These findings provide unique insight into the clinical and biological heterogeneity of the 2 ALS subtypes.
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Affiliation(s)
- Yuan Ai
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
| | - Fei Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
| | - Yanbing Hou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
| | - Xiuli Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
| | - Wenbin Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
| | - Kun Qin
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
| | - Xueling Suo
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
| | - Du Lei
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
| | - Huifang Shang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, No. 37 Guoxue Alley, Wuhou District, Chengdu, Sichuan 610041, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, 699 Jinyuan Xi Road, Jimei District, Xiamen, Fujian 361021, China
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Pan N, Qin K, Patino LR, Tallman MJ, Lei D, Lu L, Li W, Blom TJ, Bruns KM, Welge JA, Strawn JR, Gong Q, Sweeney JA, Singh MK, DelBello MP. Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task-based fMRI connectome study. J Child Psychol Psychiatry 2024. [PMID: 38220469 DOI: 10.1111/jcpp.13946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/26/2023] [Indexed: 01/16/2024]
Abstract
BACKGROUND Youth with a family history of bipolar disorder (BD) may be at increased risk for mood disorders and for developing side effects after antidepressant exposure. The neurobiological basis of these risks remains poorly understood. We aimed to identify biomarkers underlying risk by characterizing abnormalities in the brain connectome of symptomatic youth at familial risk for BD. METHODS Depressed and/or anxious youth (n = 119, age = 14.9 ± 1.6 years) with a family history of BD but no prior antidepressant exposure and typically developing controls (n = 57, age = 14.8 ± 1.7 years) received functional magnetic resonance imaging (fMRI) during an emotional continuous performance task. A generalized psychophysiological interaction (gPPI) analysis was performed to compare their brain connectome patterns, followed by machine learning of topological metrics. RESULTS High-risk youth showed weaker connectivity patterns that were mainly located in the default mode network (DMN) (network weight = 50.1%) relative to controls, and connectivity patterns derived from the visual network (VN) constituted the largest proportion of aberrant stronger pairs (network weight = 54.9%). Global local efficiency (Elocal , p = .022) and clustering coefficient (Cp , p = .029) and nodal metrics of the right superior frontal gyrus (SFG) (Elocal : p < .001; Cp : p = .001) in the high-risk group were significantly higher than those in healthy subjects, and similar patterns were also found in the left insula (degree: p = .004; betweenness: p = .005; age-by-group interaction, p = .038) and right hippocampus (degree: p = .003; betweenness: p = .003). The case-control classifier achieved a cross-validation accuracy of 78.4%. CONCLUSIONS Our findings of abnormal connectome organization in the DMN and VN may advance mechanistic understanding of risk for BD. Neuroimaging biomarkers of increased network segregation in the SFG and altered topological centrality in the insula and hippocampus in broader limbic systems may be used to target interventions tailored to mitigate the underlying risk of brain abnormalities in these at-risk youth.
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Affiliation(s)
- Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, USA
| | - Kun Qin
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, USA
| | - Luis R Patino
- Department of Psychiatry, University of Cincinnati, Cincinnati, USA
| | | | - Du Lei
- College of Medical Informatics, Chongqing Medical University, Chongqing, China
| | - Lu Lu
- Huaxi MR Research Center (HMRRC), Department of Radiology, Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, USA
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Thomas J Blom
- Department of Psychiatry, University of Cincinnati, Cincinnati, USA
| | - Kaitlyn M Bruns
- Department of Psychiatry, University of Cincinnati, Cincinnati, USA
| | - Jeffrey A Welge
- Department of Psychiatry, University of Cincinnati, Cincinnati, USA
| | - Jeffrey R Strawn
- Department of Psychiatry, University of Cincinnati, Cincinnati, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, OH, China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, USA
| | - Manpreet K Singh
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, California, USA
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Li X, Lei D, Qin K, Li L, Zhang Y, Zhou D, Kemp GJ, Gong Q. Effects of PRRT2 mutation on brain gray matter networks in paroxysmal kinesigenic dyskinesia. Cereb Cortex 2024; 34:bhad418. [PMID: 37955636 DOI: 10.1093/cercor/bhad418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 10/16/2023] [Accepted: 10/17/2023] [Indexed: 11/14/2023] Open
Abstract
Although proline-rich transmembrane protein 2 is the primary causative gene of paroxysmal kinesigenic dyskinesia, its effects on the brain structure of paroxysmal kinesigenic dyskinesia patients are not yet clear. Here, we explored the influence of proline-rich transmembrane protein 2 mutations on similarity-based gray matter morphological networks in individuals with paroxysmal kinesigenic dyskinesia. A total of 51 paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations, 55 paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation, and 80 healthy controls participated in the study. We analyzed the structural connectome characteristics across groups by graph theory approaches. Relative to paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation and healthy controls, paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations exhibited a notable increase in characteristic path length and a reduction in both global and local efficiency. Relative to healthy controls, both patient groups showed reduced nodal metrics in right postcentral gyrus, right angular, and bilateral thalamus; Relative to healthy controls and paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation, paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations showed almost all reduced nodal centralities and structural connections in cortico-basal ganglia-thalamo-cortical circuit including bilateral supplementary motor area, bilateral pallidum, and right caudate nucleus. Finally, we used support vector machine by gray matter network matrices to classify paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations and paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation, achieving an accuracy of 73%. These results show that proline-rich transmembrane protein 2 related gray matter network deficits may contribute to paroxysmal kinesigenic dyskinesia, offering new insights into its pathophysiological mechanisms.
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Affiliation(s)
- Xiuli Li
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu, 610041, China
| | - Du Lei
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu, 610041, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, 260 Stetson St., Suite 3326, Cincinnati, Ohio, 45219, United States
| | - Kun Qin
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu, 610041, China
| | - Lei Li
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu, 610041, China
| | - Yingying Zhang
- Department of Neurology, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu, 610041, China
| | - Dong Zhou
- Department of Neurology, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu, 610041, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, L69 3BX, Liverpool, L3 5TR, United Kingdom
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu, 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, No. 37 Guoxue Lane, Wuhou District, Chengdu, 610041, China
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Zhang T, Zhang Y, Ren J, Zhou H, Yang M, Li L, Lei D, Gong Q, Zhou D, Yang T. Dynamic alterations of striatal-related functional networks in juvenile absence epilepsy. Epilepsy Behav 2023; 149:109506. [PMID: 37925871 DOI: 10.1016/j.yebeh.2023.109506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 10/18/2023] [Accepted: 10/20/2023] [Indexed: 11/07/2023]
Abstract
PURPOSE To explore the features of dynamic functional connectivity (dFC) variability of striatal-cortical/subcortical networks in juvenile absence epilepsy (JAE). METHODS We collected resting-state functional magnetic imaging data from 18 JAE patients and 28 healthy controls. The striatum was divided into six pairs of regions: the inferior-ventral striatum (VSi), superior-ventral striatum (VSs), dorsal-caudal putamen, dorsal-rostral putamen, dorsal-caudate (DC) and ventral-rostral putamen. We assessed the dFC variability of each subdivision in the whole brain using the sliding-window method, and correlated altered circuit with clinical variables in JAE patients. RESULTS We found altered dFC variability of striatal-cortical/subcortical networks in patients with JAE. The VSs exhibited decreased dFC variability with subcortical regions, and dFC variability between VSs and thalamus was negatively correlated with epilepsy duration. For the striatal-cortical networks, the dFC variability was decreased in VSi-affective network but increased in DC-executive network. The altered dynamics of striatal-cortical networks involved crucial nodes of the default mode network (DMN). CONCLUSION JAE patients exhibit excessive stability in the striatal-subcortical networks. For striatal-cortical networks in JAE, the striatal-affective circuit was more stable, while the striatal-executive circuit was more variable. Furthermore, crucial nodes of DMN were changed in striatal-cortical networks in JAE.
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Affiliation(s)
- Tianyu Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yingying Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jiechuan Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Huanyu Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Menghan Yang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lei Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Du Lei
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Tianhua Yang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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Zhu Z, Lei D, Qin K, Tallman MJ, Patino LR, Fleck DE, Gong Q, Sweeney JA, DelBello MP, McNamara RK. Cortical and subcortical structural differences in psychostimulant-free ADHD youth with and without a family history of bipolar I disorder: a cross-sectional morphometric comparison. Transl Psychiatry 2023; 13:368. [PMID: 38036505 PMCID: PMC10689449 DOI: 10.1038/s41398-023-02667-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 10/31/2023] [Accepted: 11/13/2023] [Indexed: 12/02/2023] Open
Abstract
Although attention-deficit/hyperactivity disorder (ADHD) and a family history of bipolar I disorder (BD) are associated with increased risk for developing BD, their neuroanatomical substrates remain poorly understood. This study compared cortical and subcortical gray matter morphology in psychostimulant-free ADHD youth with and without a first-degree relative with BD and typically developing healthy controls. ADHD youth (ages 10-18 years) with ('high-risk', HR) or without ('low-risk', LR) a first-degree relative with BD and healthy comparison youth (HC) were enrolled. High-resolution 3D T1-weighted images were acquired using a Philips 3.0 T MR scanner. The FreeSurfer image analysis suite was used to measure cortical thickness, surface area, and subcortical volumes. A general linear model evaluated group differences in MRI features with age and sex as covariates, and exploratory correlational analyses evaluated associations with symptom ratings. A total of n = 142 youth (mean age: 14.16 ± 2.54 years, 35.9% female) were included in the analysis (HC, n = 48; LR, n = 49; HR, n = 45). The HR group exhibited a more severe symptom profile, including higher mania and dysregulation scores, compared to the LR group. For subcortical volumes, the HR group exhibited smaller bilateral thalamic, hippocampal, and left caudate nucleus volumes compared to both LR and HC, and smaller right caudate nucleus compared with LR. No differences were found between LR and HC groups. For cortical surface area, the HR group exhibited lower parietal and temporal surface area compared with HC and LR, and lower orbitofrontal and superior frontal surface area compared to LR. The HR group exhibited lower left anterior cingulate surface area compared with HC. LR participants exhibited greater right pars opercularis surface area compared with the HC. Some cortical alterations correlated with symptom severity ratings. These findings suggest that ADHD in youth with a BD family history is associated with a more a severe symptom profile and a neuroanatomical phenotype that distinguishes it from ADHD without a BD family history.
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Affiliation(s)
- Ziyu Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, PR China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Du Lei
- College of Medical Informatics, Chongqing Medical University, Chongqing, 400016, PR China.
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, PR China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, PR China
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, 442012, PR China
| | - Maxwell J Tallman
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - L Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - David E Fleck
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, PR China.
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, 361021, Fujian, PR China.
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, PR China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Robert K McNamara
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
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Li W, Lei D, Tallman MJ, Welge JA, Blom TJ, Fleck DE, Klein CC, Adler CM, Patino LR, Strawn JR, Gong Q, Sweeney JA, DelBello MP. Morphological abnormalities in youth with bipolar disorder and their relationship to clinical characteristics. J Affect Disord 2023; 338:312-320. [PMID: 37301295 PMCID: PMC10527418 DOI: 10.1016/j.jad.2023.05.070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 03/24/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023]
Abstract
OBJECTIVES To characterize the neuroanatomy of BD in youth and its correlation to clinical characteristics. METHODS The current study includes a sample of 105 unmedicated youth with first-episode BD, aged between 10.1 and 17.9 years, and 61 healthy comparison adolescents, aged between 10.1 and 17.7 years, who were matched for age, race, sex, socioeconomic status, intelligence quotient (IQ), and education level. T1-weighted magnetic resonance imaging (MRI) images were obtained using a 4 T MRI scanner. Freesurfer (V6.0) was used to preprocess and parcellate the structural data, and 68 cortical and 12 subcortical regions were considered for statistical comparisons. The relationship between morphological deficits and clinical and demographic characteristics were evaluated using linear models. RESULTS Compared with healthy youth, youth with BD had decreased cortical thickness in frontal, parietal, and anterior cingulate regions. These youth also showed decreased gray matter volumes in 6 of the 12 subcortical regions examined including thalamus, putamen, amygdala and caudate. In further subgroup analyses, we found that youth with BD with comorbid attention-deficit hyperactivity disorder (ADHD) or with psychotic symptoms had more significant deficits in subcortical gray matter volume. LIMITATIONS We cannot provide information about the course of structural changes and impact of treatment and illness progression. CONCLUSIONS Our findings indicate that youth with BD have significant neurostructural deficits in both cortical and subcortical regions mainly located in the regions related to emotion processing and regulation. Variability in clinical characteristics and comorbidities may contribute to the severity of anatomic alterations in this disorder.
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Affiliation(s)
- Wenbin Li
- Departments of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu 610000, Sichuan, PR China; Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA; Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan, PR China
| | - Du Lei
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, PR China.
| | - Maxwell J Tallman
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Jeffrey A Welge
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Thomas J Blom
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - David E Fleck
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Christina C Klein
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Caleb M Adler
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - L Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Jeffrey R Strawn
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Qiyong Gong
- Departments of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu 610000, Sichuan, PR China.
| | - John A Sweeney
- Departments of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu 610000, Sichuan, PR China; Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
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Li W, Jiang Y, Li X, Huang H, Lei D, Li J, Zhang H, Yao D, Luo C, Gong Q, Zhou D, An D. More extensive structural damage in temporal lobe epilepsy with hippocampal sclerosis type 1. Seizure 2023; 111:130-137. [PMID: 37633152 DOI: 10.1016/j.seizure.2023.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 08/04/2023] [Accepted: 08/06/2023] [Indexed: 08/28/2023] Open
Abstract
OBJECTIVE To explore clinical and structural differences between mesial temporal lobe epilepsy (mTLE) patients with different hippocampal sclerosis (HS) subtypes. METHODS High-resolution T1-weighted MRI and diffusion tensor imaging data were obtained in 41 refractory mTLE patients and 52 age- and sex-matched healthy controls. Postoperative histopathological examination confirmed HS type 1 in 30 patients and HS type 2 in eleven patients. Clinical features, postoperative seizure outcomes, hippocampal subfields volumes, fractional anisotropy (FA) values of white matter regions and graph theory parameters were explored and compared between the HS type 1 and HS type 2 groups. RESULTS No significant differences in clinical features and postsurgical seizure outcomes were found between the HS type 1 and type 2 groups. However, the HS type 1 group showed extra atrophy in ipsilateral parasubiculum than healthy controls and more severe atrophy in contralateral hippocampal fissure than the HS type 2 group. More extensive FA decrease were also observed in the HS type 1 group, involving ipsilateral optic radiation, superior fronto-occipital fasciculus, contralateral uncinate fasciculus, tapetum, bilateral hippocampal cingulum, corona radiata, etc. Furthermore, in spite of similar impairments in characteristic path length, global efficiency and local efficiency in two HS groups, the HS type 1 group showed additional decrease of clustering coefficient than healthy controls. CONCLUSIONS HS type 1 and 2 groups had similar clinical characteristics and postoperative seizure outcomes. More widespread neuronal cell loss in the HS type 1 group contributed to more extensive structural damage and connectivity abnormality. These results shed new light on the imaging correlates of different HS pathology.
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Affiliation(s)
- Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China; National Clinical Research Center for Geriatrics, Department of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Xiuli Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Huan Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Du Lei
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jinmei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Heng Zhang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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Lei D, Qin K, Li W, Pinaya WHL, Tallman MJ, Patino LR, Strawn JR, Fleck D, Klein CC, Lui S, Gong Q, Adler CM, Mechelli A, Sweeney JA, DelBello MP. Brain morphometric features predict medication response in youth with bipolar disorder: a prospective randomized clinical trial. Psychol Med 2023; 53:4083-4093. [PMID: 35392995 PMCID: PMC10317810 DOI: 10.1017/s0033291722000757] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 01/17/2022] [Accepted: 02/27/2022] [Indexed: 02/05/2023]
Abstract
BACKGROUND Identification of treatment-specific predictors of drug therapies for bipolar disorder (BD) is important because only about half of individuals respond to any specific medication. However, medication response in pediatric BD is variable and not well predicted by clinical characteristics. METHODS A total of 121 youth with early course BD (acute manic/mixed episode) were prospectively recruited and randomized to 6 weeks of double-blind treatment with quetiapine (n = 71) or lithium (n = 50). Participants completed structural magnetic resonance imaging (MRI) at baseline before treatment and 1 week after treatment initiation, and brain morphometric features were extracted for each individual based on MRI scans. Positive antimanic treatment response at week 6 was defined as an over 50% reduction of Young Mania Rating Scale scores from baseline. Two-stage deep learning prediction model was established to distinguish responders and non-responders based on different feature sets. RESULTS Pre-treatment morphometry and morphometric changes occurring during the first week can both independently predict treatment outcome of quetiapine and lithium with balanced accuracy over 75% (all p < 0.05). Combining brain morphometry at baseline and week 1 allows prediction with the highest balanced accuracy (quetiapine: 83.2% and lithium: 83.5%). Predictions in the quetiapine and lithium group were found to be driven by different morphometric patterns. CONCLUSIONS These findings demonstrate that pre-treatment morphometric measures and acute brain morphometric changes can serve as medication response predictors in pediatric BD. Brain morphometric features may provide promising biomarkers for developing biologically-informed treatment outcome prediction and patient stratification tools for BD treatment development.
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Affiliation(s)
- Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Kun Qin
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Wenbin Li
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Walter H. L. Pinaya
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, Westminster Bridge Road, London, UK
| | - Maxwell J. Tallman
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - L. Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Jeffrey R. Strawn
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - David Fleck
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Christina C. Klein
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Caleb M. Adler
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - John A. Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, PR China
| | - Melissa P. DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
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11
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Zhu Z, Lei D, Qin K, Li X, Li W, Tallman MJ, Patino LR, Fleck DE, Aghera V, Gong Q, Sweeney JA, McNamara RK, DelBello MP. Brain network structural connectome abnormalities among youth with attention-deficit/hyperactivity disorder at varying risk for bipolar I disorder: a cross-sectional graph-based magnetic resonance imaging study. J Psychiatry Neurosci 2023; 48:E315-E324. [PMID: 37643802 PMCID: PMC10473038 DOI: 10.1503/jpn.220209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 04/10/2023] [Accepted: 05/30/2023] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is highly prevalent among youth with or at familial risk for bipolar-I disorder (BD-I), and ADHD symptoms commonly precede and may increase the risk for BD-I; however, associated neuropathophysiological mechanisms are not known. In this cross-sectional study, we sought to investigate brain structural network topology among youth with ADHD, with and without familial risk of BD-I. METHODS We recruited 3 groups of psychostimulant-free youth (aged 10-18 yr), namely youth with ADHD and at least 1 biological parent or sibling with BD-I (high-risk group), youth with ADHD who did not have a first- or second-degree relative with a mood or psychotic disorder (low-risk group) and healthy controls. We used graph-based network analysis of structural magnetic resonance imaging data to investigate topological properties of brain networks. We also evaluated relationships between topological metrics and mood and ADHD symptom ratings. RESULTS A total of 149 youth were included in the analysis (49 healthy controls, 50 low-risk youth, 50 high-risk youth). Low-risk and high-risk ADHD groups exhibited similar differences from healthy controls, mainly in the default mode network and central executive network. We found topological alterations in the salience network of the high-risk group, relative to both low-risk and control groups. We found significant abnormalities in global network properties in the high-risk group only, compared with healthy controls. Among both low-risk and high-risk ADHD groups, nodal metrics in the right triangular inferior frontal gyrus correlated positively with ADHD total and hyperactivity/impulsivity subscale scores. LIMITATIONS The cross-sectional design of this study could not determine the relevance of these findings to BD-I risk progression. CONCLUSION Youth with ADHD, with and without familial risk for BD-I, exhibit common regional abnormalities in the brain connectome compared with healthy youth, whereas alterations in the salience network distinguish these groups and may represent a prodromal feature relevant to BD-I risk.
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Affiliation(s)
- Ziyu Zhu
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - Du Lei
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - Kun Qin
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - Xiuli Li
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - Wenbin Li
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - Maxwell J Tallman
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - L Rodrigo Patino
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - David E Fleck
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - Veronica Aghera
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - Qiyong Gong
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - John A Sweeney
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - Robert K McNamara
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
| | - Melissa P DelBello
- From the Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, China (Zhu, Qin, X. Li, Gong); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH (Zhu, Qin, Tallman, Patino, Fleck, Aghera, Sweeney, McNamara, DelBello); the College of Medical Informatics, Chongqing Medical University, Chongqing, China (Lei); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (X. Li); the Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China (W. Li); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Gong); the Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China (Gong)
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Qin K, Lei D, Zhu Z, Li W, Tallman MJ, Rodrigo Patino L, Fleck DE, Aghera V, Gong Q, Sweeney JA, McNamara RK, DelBello MP. Different brain functional network abnormalities between attention-deficit/hyperactivity disorder youth with and without familial risk for bipolar disorder. Eur Child Adolesc Psychiatry 2023:10.1007/s00787-023-02245-1. [PMID: 37336861 DOI: 10.1007/s00787-023-02245-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 06/07/2023] [Indexed: 06/21/2023]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) commonly precedes the initial onset of mania in youth with familial risk for bipolar disorder (BD). Although ADHD youth with and without BD familial risk exhibit different clinical features, associated neuropathophysiological mechanisms remain poorly understood. This study aimed to identify brain functional network abnormalities associated with ADHD in youth with and without familial risk for BD. Resting-state functional magnetic resonance imaging scans were acquired from 37 ADHD youth with a family history of BD (high-risk), 45 ADHD youth without a family history of BD (low-risk), and 32 healthy controls (HC). Individual whole-brain functional networks were constructed, and graph theory analysis was applied to estimate network topological metrics. Topological metrics, including network efficiency, small-worldness and nodal centrality, were compared across groups, and associations between topological metrics and clinical ratings were evaluated. Compared to HC, low-risk ADHD youth exhibited weaker global integration (i.e., decreased global efficiency and increased characteristic path length), while high-risk ADHD youth showed a disruption of localized network components with decreased frontoparietal and frontolimbic connectivity. Common topological deficits were observed in the medial superior frontal gyrus between low- and high-risk ADHD. Distinct network deficits were found in the inferior parietal lobule and corticostriatal circuitry. Associations between global topological metrics and externalizing symptoms differed significantly between the two ADHD groups. Different patterns of functional network topological abnormalities were found in high- as compared to low-risk ADHD, suggesting that ADHD in youth with BD familial risk may represent a phenotype that is different from ADHD alone.
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Affiliation(s)
- Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, China
| | - Du Lei
- College of Medical Informatics, Chongqing Medical University, Chongqing, 400016, China.
| | - Ziyu Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - Wenbin Li
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, Henan, China
| | - Maxwell J Tallman
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - L Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - David E Fleck
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - Veronica Aghera
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China.
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - Robert K McNamara
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, 45219, USA
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13
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Lei D, Qin K, Li W, Zhu Z, Tallman MJ, Patino LR, Fleck DE, Aghera V, Gong Q, Sweeney JA, DelBello MP, McNamara RK. Regional microstructural differences in ADHD youth with and without a family history of bipolar I disorder. J Affect Disord 2023; 334:238-245. [PMID: 37149051 DOI: 10.1016/j.jad.2023.04.125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 03/21/2023] [Accepted: 04/29/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND Having a first-degree relative with bipolar I disorder (BD) in conjunction with prodromal attention deficit/hyperactivity disorder (ADHD) may represent a unique phenotype that confers greater risk for developing BD than ADHD alone. However, underlying neuropathoetiological mechanisms remain poorly understood. This cross-sectional study compared regional microstructure in psychostimulant-free ADHD youth with ('high-risk', HR) and without ('low-risk', LR) a first-degree relative with BD, and healthy controls (HC). METHODS A total of 140 (high-risk, n = 44; low-risk, n = 49; and HC, n = 47) youth (mean age: 14.1 ± 2.5 years, 65 % male) were included in the analysis. Diffusion tensor images were collected and fractional anisotropy (FA) and mean diffusivity (MD) maps calculated. Both tract-based and voxel-based analyses were performed. Correlations between clinical ratings and microstructural metrics that differed among groups were examined. RESULTS No significant group differences in major long-distance fiber tracts were observed. The high-risk ADHD group exhibited predominantly higher FA and lower MD in frontal, limbic, and striatal subregions compared with the low-risk ADHD group. Both low-risk and high-risk ADHD groups exhibited higher FA in unique and overlapping regions compared with HC subjects. Significant correlations between regional microstructural metrics and clinical ratings were observed in ADHD groups. LIMITATIONS Prospective longitudinal studies will be required to determine the relevance of these findings to BD risk progression. CONCLUSIONS Psychostimulant-free ADHD youth with a BD family history exhibit different microstructure alterations in frontal, limbic, and striatal regions compared with ADHD youth without a BD family history, and may therefore represent unique phenotypes relevant to BD risk progression.
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Affiliation(s)
- Du Lei
- College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA.
| | - Kun Qin
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA; Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Wenbin Li
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA; Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Ziyu Zhu
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA; Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Maxwell J Tallman
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - L Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - David E Fleck
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Veronica Aghera
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu 610041, China.
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA; Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
| | - Robert K McNamara
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati 45219, OH, USA
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14
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Lei D, Li W, Qin K, Ai Y, Tallman MJ, Patino LR, Welge JA, Blom TJ, Klein CC, Fleck DE, Gong Q, Adler CM, Strawn JR, Sweeney JA, DelBello MP. Effects of short-term quetiapine and lithium therapy for acute manic or mixed episodes on the limbic system and emotion regulation circuitry in youth with bipolar disorder. Neuropsychopharmacology 2023; 48:615-622. [PMID: 36229596 PMCID: PMC9938175 DOI: 10.1038/s41386-022-01463-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 09/11/2022] [Accepted: 09/14/2022] [Indexed: 01/07/2023]
Abstract
Disruptions in the limbic system, and in emotion regulation circuitry that supports affect modulation, have been reported during acute manic episodes of bipolar disorder (BD). The impact of pharmacological treatment on these deficits, especially in youth, remains poorly characterized. 107 youths with acute manic or mixed episodes of bipolar I disorder and 60 group-matched healthy controls were recruited. Youth with bipolar disorder were randomized to double-blind treatment with quetiapine or lithium and assessed weekly. Task-based fMRI studies were performed using an identical pairs continuous performance task (CPT-IP) at pre-treatment baseline and post-treatment weeks one and six. Region of interest analyses focused on the limbic system and ventral PFC - basal ganglia - thalamocortical loop structures known to be involved in emotion regulation. Changes in regional activation were compared between the two treatment groups, and pretreatment regional activation was used to predict treatment outcome. Mania treatment scores improved more rapidly in the quetiapine than lithium treated group, as did significant normalization of neural activation toward that of healthy individuals in left amygdala (p = 0.007), right putamen (p < 0.001), and right globus pallidus (p = 0.003). Activation changes in the right putamen were correlated with reduction of mania symptoms. The limbic and emotion regulation system activation at baseline and week one predicted treatment outcome in youth with bipolar disorder with significant accuracy (up to 87.5%). Our findings document more rapid functional brain changes associated with quetiapine than lithium treatment in youth with bipolar disorder, with most notable changes in the limbic system and emotion regulation circuitry. Pretreatment alterations in these regions predicted treatment response. These findings advance understanding of regional brain alterations in youth with bipolar disorder, and show that fMRI data can predict treatment outcome before it can be determined clinically, highlighting the potential utility of fMRI biomarkers for early prediction of treatment outcomes in bipolar disorder.Clinical Trials Registration: Name: Multimodal Neuroimaging of Treatment Effects in Adolescent Mania. URL: https://clinicaltrials.gov/ . Registration number: NCT00893581.
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Affiliation(s)
- Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA.
| | - Wenbin Li
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, 610041, PR China
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, PR China
| | - Kun Qin
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, 610041, PR China
| | - Yuan Ai
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, 610041, PR China
| | - Maxwell J Tallman
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - L Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Jeffrey A Welge
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Thomas J Blom
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Christina C Klein
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - David E Fleck
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, 610041, PR China
| | - Caleb M Adler
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Jeffrey R Strawn
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, 610041, PR China
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
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15
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Suo X, Lei D, Li N, Peng J, Chen C, Li W, Qin K, Kemp GJ, Peng R, Gong Q. Brain functional network abnormalities in parkinson's disease with mild cognitive impairment. Cereb Cortex 2022; 32:4857-4868. [PMID: 35078209 PMCID: PMC9923713 DOI: 10.1093/cercor/bhab520] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 12/18/2021] [Accepted: 12/19/2021] [Indexed: 11/13/2022] Open
Abstract
Mild cognitive impairment in Parkinson's disease (PD-M) is related to a high risk of dementia. This study explored the whole-brain functional networks in early-stage PD-M. Forty-one patients with PD classified as cognitively normal (PD-N, n = 17) and PD-M (n = 24) and 24 demographically matched healthy controls (HC) underwent clinical and neuropsychological evaluations and resting-state functional magnetic resonance imaging. The global, regional, and modular topological characteristics were assessed in the brain functional networks, and their relationships to cognitive scores were tested. At the global level, PD-M and PD-N exhibited higher characteristic path length and lower clustering coefficient, local and global efficiency relative to HC. At the regional level, PD-M and PD-N showed lower nodal centrality in sensorimotor regions relative to HC. At the modular level, PD-M showed lower intramodular connectivity in default mode and cerebellum modules, and lower intermodular connectivity between default mode and frontoparietal modules than PD-N, correlated with Montreal Cognitive Assessment scores. Early-stage PD patients showed weaker small-worldization of brain networks. Modular connectivity alterations were mainly observed in patients with PD-M. These findings highlight the shared and distinct brain functional network dysfunctions in PD-M and PD-N, and yield insight into the neurobiology of cognitive decline in PD.
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Affiliation(s)
- Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH 45227, USA
| | - Nannan Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Jiaxin Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Chaolan Chen
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 3GE, UK
| | - Rong Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China.,Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian 361022, China
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16
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Caplette JN, Gfeller L, Lei D, Liao J, Xia J, Zhang H, Feng X, Mestrot A. Antimony release and volatilization from rice paddy soils: Field and microcosm study. Sci Total Environ 2022; 842:156631. [PMID: 35691353 DOI: 10.1016/j.scitotenv.2022.156631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/01/2022] [Accepted: 06/07/2022] [Indexed: 06/15/2023]
Abstract
The fate of antimony (Sb) in submerged soils and the impact of common agricultural practices (e.g., manuring) on Sb release and volatilization is understudied. We investigated porewater Sb release and volatilization in the field and laboratory for three rice paddy soils. In the field study, the porewater Sb concentration (up to 107.1 μg L-1) was associated with iron (Fe) at two sites, and with pH, Fe, manganese (Mn), and sulfate (SO42-) at one site. The surface water Sb concentrations (up to 495.3 ± 113.7 μg L-1) were up to 99 times higher than the regulatory values indicating a potential risk to aquaculture and rice agriculture. For the first time, volatile Sb was detected in rice paddy fields using a validated quantitative method (18.1 ± 5.2 to 217.9 ± 160.7 mg ha-1 y-1). We also investigated the influence of two common rice agriculture practices (flooding and manuring) on Sb release and volatilization in a 56-day microcosm experiment using the same soils from the field campaign. Flooding induced an immediate, but temporary, Sb release into the porewater that declined with SO42-, indicating that SO42- reduction may reduce porewater Sb concentrations. A secondary Sb release, corresponding to Fe reduction in the porewater, was observed in some of the microcosms. Our results suggest flooding-induced Sb release into rice paddy porewaters is temporary but relevant. Manuring the soils did not impact the porewater Sb concentration but did enhance Sb volatilization. Volatile Sb (159.6 ± 108.4 to 2237.5 ± 679.7 ng kg-1 y-1) was detected in most of the treatments and was correlated with the surface water Sb concentration. Our study indicates that Sb volatilization could be occurring at the soil-water interface or directly in the surface water and highlights that future works should investigate this potentially relevant mechanism.
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Affiliation(s)
| | - L Gfeller
- Institute of Geography, University of Bern, Switzerland
| | - D Lei
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, PR China
| | - J Liao
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, PR China
| | - J Xia
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, PR China
| | - H Zhang
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, PR China
| | - X Feng
- State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, PR China.
| | - A Mestrot
- Institute of Geography, University of Bern, Switzerland.
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17
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Lei D, Li W, Tallman MJ, Strakowski SM, DelBello MP, Rodrigo Patino L, Fleck DE, Lui S, Gong Q, Sweeney JA, Strawn JR, Nery FG, Welge JA, Rummelhoff E, Adler CM. Changes in the structural brain connectome over the course of a nonrandomized clinical trial for acute mania. Neuropsychopharmacology 2022; 47:1961-1968. [PMID: 35585125 PMCID: PMC9485114 DOI: 10.1038/s41386-022-01328-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 03/17/2022] [Accepted: 04/11/2022] [Indexed: 02/05/2023]
Abstract
Disrupted topological organization of brain functional networks has been widely reported in bipolar disorder. However, the potential clinical implications of structural connectome abnormalities have not been systematically investigated. The present study included 109 unmedicated subjects with acute mania who were assigned to 8 weeks of treatment with quetiapine or lithium and 60 healthy controls. High resolution 3D-T1 weighted magnetic resonance images (MRI) were collected from both groups at baseline, week 1 and week 8. Brain networks were constructed based on the similarity of morphological features across brain regions and analyzed using graph theory approaches. At baseline, individuals with bipolar disorder illness showed significantly lower clustering coefficient (Cp) (p = 0.012) and normalized characteristic path length (λ) (p = 0.004) compared to healthy individuals, as well as differences in nodal centralities across multiple brain regions. No baseline or post-treatment differences were identified between drug treatment conditions, so change after treatment were considered in the combined treatment groups. Relative to healthy individuals, differences in Cp, λ and cingulate gyrus nodal centrality were significantly reduced with treatment; changes in these parameters correlated with changes in Young Mania Rating Scale scores. Baseline structural connectome matrices significantly differentiated responder and non-responder groups at 8 weeks with 74% accuracy. Global and nodal network alterations evident at baseline were normalized with treatment and these changes associated with symptomatic improvement. Further, baseline structural connectome matrices predicted treatment response. These findings suggest that structural connectome abnormalities are clinically significant and may be useful for predicting clinical outcome of treatment and tracking drug effects on brain anatomy in bipolar disorder. CLINICAL TRIALS REGISTRATION Name: Functional and Neurochemical Brain Changes in First-episode Bipolar Mania Following Successful Treatment with Lithium or Quetiapine. URL: https://clinicaltrials.gov/ . REGISTRATION NUMBER NCT00609193. Name: Neurofunctional and Neurochemical Markers of Treatment Response in Bipolar Disorder. URL: https://clinicaltrials.gov/ . REGISTRATION NUMBER NCT00608075.
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Affiliation(s)
- Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA.
| | - Wenbin Li
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, P.R. China
- Department of the Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, P.R. China
| | - Maxwell J Tallman
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Stephen M Strakowski
- Department of Psychiatry & Behavioral Sciences, Dell Medical School of The University of Texas at Austin, Austin, 78712, TX, USA
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - L Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - David E Fleck
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, P.R. China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, P.R. China
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, P.R. China
| | - Jeffrey R Strawn
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Fabiano G Nery
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Jeffrey A Welge
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Emily Rummelhoff
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
| | - Caleb M Adler
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, 45219, OH, USA
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18
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Yang J, Lei D, Suo X, Tallman MJ, Qin K, Li W, Bruns KM, Blom TJ, Duran LRP, Cotton S, Sweeney JA, Gong Q, DelBello MP. A preliminary study of the effects of mindfulness-based cognitive therapy on structural brain networks in mood-dysregulated youth with a familial risk for bipolar disorder. Early Interv Psychiatry 2022; 16:1011-1019. [PMID: 34808702 DOI: 10.1111/eip.13245] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 10/17/2021] [Accepted: 11/07/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND Mindfulness-based cognitive therapy for children (MBCT-C), as a psychotherapeutic intervention, has been shown to be effective for treating mood dysregulation (MD). While previous neuroimaging studies of MD have reported both pre-treatment structural and functional alterations, the effects of MBCT-C on brain morphological network organisation has not been investigated. METHODS We investigated brain morphological network organisation in 10 mood-dysregulated youth with familial risk for bipolar disorder and 15 matched healthy comparison youth (HC). Effects of 12 weeks of MBCT-C were examined in the mood-dysregulated youth. Topological properties of brain networks used for analyses were constructed based on morphological similarities in regional grey matter using a graph-theory approach using MRI data. RESULTS At baseline, compared with the HC group, the mood-dysregulated group exhibited increased global efficiency (Eglob ), decreased path length (Lp ), and abnormal nodal properties, mainly in the limbic system. Right temporal pole alterations at baseline predicted change in Child and Adolescent Mindfulness Measure scores after treatment. The mood-dysregulated group showed significant decreases in both the Eglob and Lp metrics after MBCT-C, suggesting an improved capacity for optimal information processing. Changes in Lp were correlated with changes in Emotion Regulation Checklist scores. Our results show significant topological alterations in the mood-dysregulated group as compared to controls at baseline. After MBCT-C, disrupted topological properties in the mood-dysregulated group were significantly reduced. CONCLUSION MBCT-C may facilitate clinically meaningful changes in the brain structural network in mood-dysregulated individuals.
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Affiliation(s)
- Jing Yang
- Huaxi MR Research Center (HMRRC), Departments of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Xueling Suo
- Huaxi MR Research Center (HMRRC), Departments of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Maxwell J Tallman
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Departments of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Departments of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Kaitlyn M Bruns
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Thomas J Blom
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Luis Rodrigo Patino Duran
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Sian Cotton
- Department of Family and Community Medicine, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Departments of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Departments of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi Xiamen Hospital of Sichuan University, Xiamen, China
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
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19
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Yin T, He Z, Chen Y, Sun R, Yin S, Lu J, Yang Y, Liu X, Ma P, Qu Y, Zhang T, Suo X, Lei D, Gong Q, Tang Y, Liang F, Zeng F. Predicting acupuncture efficacy for functional dyspepsia based on functional brain network features: a machine learning study. Cereb Cortex 2022; 33:3511-3522. [PMID: 35965072 DOI: 10.1093/cercor/bhac288] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2022] [Revised: 06/28/2022] [Accepted: 06/29/2022] [Indexed: 12/19/2022] Open
Abstract
Acupuncture is effective in treating functional dyspepsia (FD), while its efficacy varies significantly from different patients. Predicting the responsiveness of different patients to acupuncture treatment based on the objective biomarkers would assist physicians to identify the candidates for acupuncture therapy. One hundred FD patients were enrolled, and their clinical characteristics and functional brain MRI data were collected before and after treatment. Taking the pre-treatment functional brain network as features, we constructed the support vector machine models to predict the responsiveness of FD patients to acupuncture treatment. These features contributing critically to the accurate prediction were identified, and the longitudinal analyses of these features were performed on acupuncture responders and non-responders. Results demonstrated that prediction models achieved an accuracy of 0.76 ± 0.03 in predicting acupuncture responders and non-responders, and a R2 of 0.24 ± 0.02 in predicting dyspeptic symptoms relief. Thirty-eight functional brain network features associated with the orbitofrontal cortex, caudate, hippocampus, and anterior insula were identified as the critical predictive features. Changes in these predictive features were more pronounced in responders than in non-responders. In conclusion, this study provided a promising approach to predicting acupuncture efficacy for FD patients and is expected to facilitate the optimization of personalized acupuncture treatment plans for FD.
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Affiliation(s)
- Tao Yin
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Zhaoxuan He
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China.,Key Laboratory of Sichuan Province for Acupuncture and Chronobiology, Chengdu, Sichuan 610075, China
| | - Yuan Chen
- International Education College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Ruirui Sun
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Shuai Yin
- First Affiliated Hospital, Henan University of Traditional Chinese Medicine, Zhengzhou, Henan 450002, China
| | - Jin Lu
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Yue Yang
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Xiaoyan Liu
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Peihong Ma
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China.,School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Yuzhu Qu
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Tingting Zhang
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Xueling Suo
- Departments of Radiology, Huaxi Magnetic Resonance Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Du Lei
- Departments of Radiology, Huaxi Magnetic Resonance Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Qiyong Gong
- Departments of Radiology, Huaxi Magnetic Resonance Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Yong Tang
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China.,Key Laboratory of Sichuan Province for Acupuncture and Chronobiology, Chengdu, Sichuan 610075, China
| | - Fanrong Liang
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Fang Zeng
- Acupuncture and Tuina School, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China.,Key Laboratory of Sichuan Province for Acupuncture and Chronobiology, Chengdu, Sichuan 610075, China
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20
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Qin L, Zhang Y, Ren J, Lei D, Li X, Yang T, Gong Q, Zhou D. Altered brain activity in juvenile myoclonic epilepsy with a monotherapy: a resting-state fMRI study. Acta Epileptologica 2022. [DOI: 10.1186/s42494-022-00101-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Juvenile myoclonic epilepsy (JME) is the most common syndrome of idiopathic generalized epilepsy. Although resting-state functional magnetic resonance imaging (rs-fMRI) studies have found thalamocortical circuit dysfunction in patients with JME, the pathophysiological mechanism of JME remains unclear. In this study, we used three complementary parameters of rs-fMRI to investigate aberrant brain activity in JME patients in comparison to that of healthy controls.
Methods
Rs-fMRI and clinical data were acquired from 49 patients with JME undergoing monotherapy and 44 age- and sex-matched healthy controls. After fMRI data preprocessing, the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC) were calculated and compared between the two groups. Correlation analysis was conducted to explore the relationship between local brain abnormalities and clinical features in JME patients.
Results
Compared with the controls, the JME patients exhibited significantly decreased fALFF, ReHo and DC in the cerebellum, inferior parietal lobe, and visual cortex (including the fusiform and the lingual and middle occipital gyri), and increased DC in the right orbitofrontal cortex. In the JME patients, there were no regions with reduced ReHo compared to the controls. No significant correlation was observed between regional abnormalities of fALFF, ReHo or DC, and clinical features.
Conclusions
We demonstrated a wide range of abnormal functional activity in the brains of patients with JME, including the prefrontal cortex, visual cortex, default mode network, and cerebellum. The results suggest dysfunctions of the cerebello-cerebral circuits, which provide a clue on the potential pathogenesis of JME.
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21
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Li W, Lei D, Tallman MJ, Ai Y, Welge JA, Blom TJ, Fleck DE, Klein CC, Patino LR, Strawn JR, Gong Q, Strakowski SM, Sweeney JA, Adler CM, DelBello MP. Pretreatment Alterations and Acute Medication Treatment Effects on Brain Task-Related Functional Connectivity in Youth With Bipolar Disorder: A Neuroimaging Randomized Clinical Trial. J Am Acad Child Adolesc Psychiatry 2022; 61:1023-1033. [PMID: 35091050 PMCID: PMC9479201 DOI: 10.1016/j.jaac.2021.12.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 12/02/2021] [Accepted: 01/18/2022] [Indexed: 02/05/2023]
Abstract
OBJECTIVE Disruptions in cognition are a clinically significant feature of bipolar disorder (BD). The effects of different treatments on these deficits and the brain systems that support them remain to be established. METHOD A continuous performance test was administered to 55 healthy controls and 71 acutely ill youths with mixed/manic BD to assess vigilance and working memory during task-based functional magnetic resonance imaging studies. Patients, who were untreated for at least 7 days at baseline, and controls were scanned at pretreatment baseline and at weeks 1 and 6. After baseline testing, patients (n = 71) were randomly assigned to 6-week double-blind treatment with lithium (n = 26; 1.0-1.2 mEq/L) or quetiapine (n = 45; 400-600 mg). Weighted seed-based connectivity (wSBC) was used to assess regional brain interactions during the attention task compared with the control condition. RESULTS At baseline, youths with BD showed reduced connectivity between bilateral anterior cingulate cortex and both left ventral lateral prefrontal cortex and left insula and increased connectivity between left ventral lateral prefrontal cortex and left temporal pole, left orbital frontal cortex and right postcentral gyrus, and right amygdala and right occipital pole compared with controls. At 1-week follow-up, quetiapine, but not lithium, treatment led to a significant shift of connectivity patterns toward those of the controls. At week 6, compared with baseline, there was no difference between treatment conditions, at which time both patient groups showed significant normalization of brain connectivity toward that of controls. CONCLUSION Functional alterations in several brain regions associated with cognitive processing and the integration of cognitive and affective processing were demonstrated in untreated youths with BD before treatment. Treatment reduced several of these alterations, with significant effects at week 1 only in the quetiapine treatment group. Normalization of functional connectivity might represent a promising biomarker for early target engagement in youth with BD. CLINICAL TRIAL REGISTRATION INFORMATION Multimodal Neuroimaging of Treatment Effects in Adolescent Mania; https://clinicaltrials.gov/; NCT00893581.
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Affiliation(s)
- Wenbin Li
- West China Hospital of Sichuan University, Sichuan, China.,Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio.,The First Affiliated Hospital of Zhengzhou, University, Zhengzhou, Henan, China
| | - Du Lei
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - Maxwell J. Tallman
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - Yuan Ai
- West China Hospital of Sichuan University, Sichuan, China.,Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - Jeffrey A. Welge
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - Thomas J. Blom
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - David E. Fleck
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - Christina C. Klein
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - Luis R. Patino
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - Jeffrey R. Strawn
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China; Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian Province, China.
| | - Stephen M. Strakowski
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio.,Dell Medical School, University of Texas at Austin, Texas
| | - John A. Sweeney
- West China Hospital of Sichuan University, Sichuan, China.,Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - Caleb M. Adler
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
| | - Melissa P. DelBello
- Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Ohio
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22
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Ji-Xu A, Lei D, Worswick S, Maloney N, Kim M, Cutler L. 229 Pityriaris rubra pilaris has a significant psychiatric burden and impact on quality of life. J Invest Dermatol 2022. [DOI: 10.1016/j.jid.2022.05.236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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23
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Zhao W, Chen W, Li G, Lei D, Yang J, Chen Y, Jiang Y, Wu J, Ni B, Sun Y, Wang S, Sun Y, Li M, Liu J. GMILT: A Novel Transformer Network That Can Noninvasively Predict EGFR Mutation Status. IEEE Trans Neural Netw Learn Syst 2022; PP:1-15. [PMID: 35862326 DOI: 10.1109/tnnls.2022.3190671] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Noninvasively and accurately predicting the epidermal growth factor receptor (EGFR) mutation status is a clinically vital problem. Moreover, further identifying the most suspicious area related to the EGFR mutation status can guide the biopsy to avoid false negatives. Deep learning methods based on computed tomography (CT) images may improve the noninvasive prediction of EGFR mutation status and potentially help clinicians guide biopsies by visual methods. Inspired by the potential inherent links between EGFR mutation status and invasiveness information, we hypothesized that the predictive performance of a deep learning network can be improved through extra utilization of the invasiveness information. Here, we created a novel explainable transformer network for EGFR classification named gated multiple instance learning transformer (GMILT) by integrating multi-instance learning and discriminative weakly supervised feature learning. Pathological invasiveness information was first introduced into the multitask model as embeddings. GMILT was trained and validated on a total of 512 patients with adenocarcinoma and tested on three datasets (the internal test dataset, the external test dataset, and The Cancer Imaging Archive (TCIA) public dataset). The performance (area under the curve (AUC) = 0.772 on the internal test dataset) of GMILT exceeded that of previously published methods and radiomics-based methods (i.e., random forest and support vector machine) and attained a preferable generalization ability (AUC = 0.856 in the TCIA test dataset and AUC = 0.756 in the external dataset). A diameter-based subgroup analysis further verified the efficiency of our model (most of the AUCs exceeded 0.772) to noninvasively predict EGFR mutation status from computed tomography (CT) images. In addition, because our method also identified the "core area" of the most suspicious area related to the EGFR mutation status, it has the potential ability to guide biopsies.
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24
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Yang T, Zhang Y, Zhang T, Zhou H, Yang M, Ren J, Li L, Lei D, Gong Q, Zhou D. Altered dynamic functional connectivity of striatal-cortical circuits in Juvenile Myoclonic Epilepsy. Seizure 2022; 101:103-108. [DOI: 10.1016/j.seizure.2022.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 06/29/2022] [Accepted: 07/01/2022] [Indexed: 11/30/2022] Open
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25
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Lei D, Qin K, Pinaya WHL, Young J, Van Amelsvoort T, Marcelis M, Donohoe G, Mothersill DO, Corvin A, Vieira S, Lui S, Scarpazza C, Arango C, Bullmore E, Gong Q, McGuire P, Mechelli A. Graph Convolutional Networks Reveal Network-Level Functional Dysconnectivity in Schizophrenia. Schizophr Bull 2022; 48:881-892. [PMID: 35569019 PMCID: PMC9212102 DOI: 10.1093/schbul/sbac047] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia is increasingly understood as a disorder of brain dysconnectivity. Recently, graph-based approaches such as graph convolutional network (GCN) have been leveraged to explore complex pairwise similarities in imaging features among brain regions, which can reveal abstract and complex relationships within brain networks. STUDY DESIGN We used GCN to investigate topological abnormalities of functional brain networks in schizophrenia. Resting-state functional magnetic resonance imaging data were acquired from 505 individuals with schizophrenia and 907 controls across 6 sites. Whole-brain functional connectivity matrix was extracted for each individual. We examined the performance of GCN relative to support vector machine (SVM), extracted the most salient regions contributing to both classification models, investigated the topological profiles of identified salient regions, and explored correlation between nodal topological properties of each salient region and severity of symptom. STUDY RESULTS GCN enabled nominally higher classification accuracy (85.8%) compared with SVM (80.9%). Based on the saliency map, the most discriminative brain regions were located in a distributed network including striatal areas (ie, putamen, pallidum, and caudate) and the amygdala. Significant differences in the nodal efficiency of bilateral putamen and pallidum between patients and controls and its correlations with negative symptoms were detected in post hoc analysis. CONCLUSIONS The present study demonstrates that GCN allows classification of schizophrenia at the individual level with high accuracy, indicating a promising direction for detection of individual patients with schizophrenia. Functional topological deficits of striatal areas may represent a focal neural deficit of negative symptomatology in schizophrenia.
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Affiliation(s)
| | | | - Walter H L Pinaya
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Jonathan Young
- Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
| | - Therese Van Amelsvoort
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Machteld Marcelis
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
- Mental Health Care Institute Eindhoven (GGzE), Eindhoven, The Netherlands
| | - Gary Donohoe
- School of Psychology & Center for Neuroimaging and Cognitive Genomics, NUI Galway University, Galway, Ireland
| | - David O Mothersill
- Psychology Department, School of Business, National College of Ireland, Dublin, Ireland
| | - Aiden Corvin
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Sandra Vieira
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Cristina Scarpazza
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Department of General Psychology, University of Padova, Padova, Italy
- Padova Neuroscience Centre, University of Padova, Padova, Italy
| | - Celso Arango
- Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañon, School of Medicine, Universidad Complutense Madrid, IiSGM, CIBERSAM, Madrid, Spain
| | - Ed Bullmore
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Qiyong Gong
- To whom correspondence should be addressed; Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, No 37 Guo Xue Xiang, Chengdu, 610041, China; tel: 86-18980601593, fax: 028-85423503,
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
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Peng J, Yang J, Li N, Lei D, Li J, Duan L, Chen C, Zeng Y, Xi J, Jiang Y, Gong Q, Peng R. Topologically Disrupted Gray Matter Networks in Drug-Naïve Essential Tremor Patients With Poor Sleep Quality. Front Neurol 2022; 13:834277. [PMID: 35557617 PMCID: PMC9086904 DOI: 10.3389/fneur.2022.834277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 03/14/2022] [Indexed: 11/16/2022] Open
Abstract
Background Sleep disturbances are widespread among patients with essential tremor (ET) and may have adverse effects on patients' quality of life. However, the pathophysiology underlying poor quality of sleep (QoS) in patients with ET remains unclear. Our study aimed to identify gray matter (GM) network alterations in the topological properties of structural MRI related to QoS in patients with ET. Method We enrolled 45 ET patients with poor QoS (SleET), 59 ET patients with normal QoS (NorET), and 66 healthy controls (HC), and they all underwent a three-dimensional T1-weighted MRI scan. We used a graph-theoretical approach to investigate the topological organization of GM morphological networks, and individual morphological brain networks were constructed according to the interregional similarity of GM volume distributions. Furthermore, we performed network-based statistics, and partial correlation analyses between topographic features and clinical characteristics were conducted. Results Global network organization was disrupted in patients with ET. Compared with the NorET group, the SleET group exhibited disrupted topological GM network organization with a shift toward randomization. Moreover, they showed altered nodal centralities in mainly the frontal, temporal, parietal, and cerebellar lobes. Morphological connection alterations within the default mode network (DMN), salience, and basal ganglia networks were observed in the SleET group and were generally more extensive than those in the NorET and HC groups. Alterations within the cerebello-thalamo-(cortical) network were only detected in the SleET group. The nodal degree of the left thalamus was negatively correlated with the Fahn-Tolosa-Marin Tremor Rating Scale score (r = −0.354, p =0.027). Conclusion Our findings suggest that potential complex interactions underlie tremor and sleep disruptions in patients with ET. Disruptions within the DMN and the cerebello-thalamo-(cortical) network may have a broader impact on sleep quality in patients with ET. Our results offer valuable insight into the neural mechanisms underlying poor QoS in patients with ET.
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Affiliation(s)
- Jiaxin Peng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Jing Yang
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Nannan Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Du Lei
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Junying Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Liren Duan
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Chaolan Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Yan Zeng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Jing Xi
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Jiang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Rong Peng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
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27
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Lei D, Suo X, Qin K, Pinaya WHL, Ai Y, Li W, Kuang W, Lui S, Kemp GJ, Sweeney JA, Gong Q. Magnetization transfer imaging alterations and its diagnostic value in antipsychotic-naïve first-episode schizophrenia. Transl Psychiatry 2022; 12:189. [PMID: 35523792 PMCID: PMC9076920 DOI: 10.1038/s41398-022-01939-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 04/15/2022] [Accepted: 04/20/2022] [Indexed: 02/08/2023] Open
Abstract
Magnetization transfer imaging (MTI) may provide more sensitivity and mechanistic understanding of neuropathological changes associated with schizophrenia than volumetric MRI. This study aims to identify brain magnetization transfer ratio (MTR) changes in antipsychotic-naïve first-episode schizophrenia (FES), and to correlate MTR findings with clinical symptom severity. A total of 143 individuals with antipsychotic-naïve FES and 147 healthy controls (HCs) were included and underwent 3.0 T brain MTI between August 2005 and July 2014. Voxelwise analysis was performed to test for MTR differences with family-wise error corrections. Relationships of these differences to symptom severity were assessed using partial correlations. Exploratory analyses using a support vector machine (SVM) classifier were conducted to discriminate FES from HCs using MTR maps. Model performance was examined using a 10-fold stratified cross-validation. Compared with HCs, individuals with FES exhibited higher MTR values in left thalamus, precuneus, cuneus, and paracentral lobule, that were positively correlated with schizophrenia symptom severity [precuneus (r = 0.34, P = 0.0004), cuneus (r = 0.33, P = 0.0006) and paracentral lobule (r = 0.37, P = 0.001)]. Whole-brain MTR maps identified individuals with FES with overall accuracy 75.5% (219 of 290 individuals) based on SVM approach. In antipsychotic-naïve FES, clinically relevant biophysical abnormalities detected by MTI mainly in the left parieto-occipital regions are informative about local brain pathology, and have potential as diagnostic markers.
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Affiliation(s)
- Du Lei
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, 45227, USA
| | - Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
| | - Walter H L Pinaya
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, WC2R 2LS, UK
| | - Yuan Ai
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, 610041, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, 610041, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L69 3GE, UK
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, 45227, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, Sichuan, China.
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, 361022, China.
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Li W, Jiang Y, Qin Y, Li X, Lei D, Zhang H, Luo C, Gong Q, Zhou D, An D. Cortical remodeling before and after successful temporal lobe epilepsy surgery. Acta Neurol Scand 2022; 146:144-151. [PMID: 35506500 DOI: 10.1111/ane.13631] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 04/11/2022] [Accepted: 04/24/2022] [Indexed: 02/05/2023]
Abstract
OBJECTIVES To explore dynamic alterations of cortical thickness before and after successful anterior temporal lobectomy (ATL) in patients with unilateral mesial temporal lobe epilepsy (mTLE). MATERIALS AND METHODS High-resolution T1-weighted MRI was obtained in 28 mTLE patients who achieved seizure freedom for at least 24 months after ATL and 29 healthy controls. Patients were scanned at five timepoints, including before surgery, 3, 6, 12 and 24 months after surgery. Preoperative cortical thickness of mTLE patients were compared with healthy controls. Dynamic alterations of cortical thickness before and after surgery were compared among five scans using linear mixed models. RESULTS Patients with mTLE showed cortical thinning pre-surgically in ipsilateral entorhinal cortex, parahippocampal gyrus, inferior parietal cortex, lateral occipital cortex; contralateral pericalcarine cortex (PCC); and bilateral caudal middle frontal gyrus (cMFG), paracentral lobule, precentral gyrus (PCG), superior parietal cortex. Cortical thickening was observed in contralateral rostral anterior cingulate cortex (rACC). Patients showed postsurgical cortical thinning in ipsilateral temporal lobe, fusiform gyrus, caudal anterior cingulate cortex, lingual gyrus, and insula. Ipsilateral cMFG, PCC, and contralateral PCG showed significant cortical thickening after surgery. In addition, contralateral rACC showed cortical thickening at 3 months follow-up, however, with obvious cortical thinning at 24 months follow-up. CONCLUSIONS Mesial temporal lobe epilepsy patients showed widespread cortical thinning before and after anterior temporal lobectomy. Progressive cortical thinning mainly existed in neighboring regions of resection. Postoperative cortical thickening may indicate cortical remodeling after successful surgery.
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Affiliation(s)
- Wei Li
- Department of Neurology, West China Hospital Sichuan University Chengdu China
| | - Yuchao Jiang
- MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, The Clinical Hospital of Chengdu Brain Science Institute University of Electronic Science and Technology of China Chengdu China
| | - Yingjie Qin
- Department of Neurology, West China Hospital Sichuan University Chengdu China
| | - Xiuli Li
- Department of Radiology, Huaxi MR Research Center, West China Hospital Sichuan University Chengdu China
| | - Du Lei
- Department of Radiology, Huaxi MR Research Center, West China Hospital Sichuan University Chengdu China
| | - Heng Zhang
- Department of Neurosurgery, West China Hospital Sichuan University Chengdu China
| | - Cheng Luo
- MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, The Clinical Hospital of Chengdu Brain Science Institute University of Electronic Science and Technology of China Chengdu China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center, West China Hospital Sichuan University Chengdu China
| | - Dong Zhou
- Department of Neurology, West China Hospital Sichuan University Chengdu China
| | - Dongmei An
- Department of Neurology, West China Hospital Sichuan University Chengdu China
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Qin K, Lei D, Pinaya WHL, Pan N, Li W, Zhu Z, Sweeney JA, Mechelli A, Gong Q. Using graph convolutional network to characterize individuals with major depressive disorder across multiple imaging sites. EBioMedicine 2022; 78:103977. [PMID: 35367775 PMCID: PMC8983334 DOI: 10.1016/j.ebiom.2022.103977] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/01/2022] [Accepted: 03/16/2022] [Indexed: 11/19/2022] Open
Abstract
Background Establishing objective and quantitative neuroimaging biomarkers at individual level can assist in early and accurate diagnosis of major depressive disorder (MDD). However, most previous studies using machine learning to identify MDD were based on small sample size and did not account for the brain connectome that is associated with the pathophysiology of MDD. Here, we addressed these limitations by applying graph convolutional network (GCN) in a large multi-site MDD dataset. Methods Resting-state functional MRI scans of 1586 participants (821 MDD vs. 765 controls) across 16 sites of Rest-meta-MDD consortium were collected. GCN model was trained with individual whole-brain functional network to identify MDD patients from controls, characterize the most salient regions contributing to classification, and explore the relationship between topological characteristics of salient regions and clinical measures. Findings GCN achieved an accuracy of 81·5% (95%CI: 80·5–82·5%, AUC: 0·865), which was higher than other common machine learning classifiers. The most salient regions contributing to classification were primarily identified within the default mode, fronto-parietal, and cingulo-opercular networks. Nodal topologies of the left inferior parietal lobule and left dorsolateral prefrontal cortex were associated with depressive severity and illness duration, respectively. Interpretation These findings based on a large, multi-site dataset support the feasibility and effectiveness of GCN in characterizing MDD, and also illustrate the potential utility of GCN for enhancing understanding of the neurobiology of MDD by detecting clinically-relevant disruption in functional network topology. Funding This study was supported by the National Natural Science Foundation of China (Grant Nos. 81621003, 82027808, 81820108018).
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Affiliation(s)
- Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Walter H L Pinaya
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China; Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Ziyu Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China; Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China.
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Liu CY, Wei JJ, Huang XY, Dong LL, Li J, Wang J, Lei D, Mao CH, Hou B, Feng F, Cui LY, Gao J. [Relationship between white matter lesions and theresponse of cerebral spinal fluid tap test and clinical features in the patients with idiopathic normal pressure hydrocephalus]. Zhonghua Yi Xue Za Zhi 2022; 102:774-780. [PMID: 35325956 DOI: 10.3760/cma.j.cn112137-20210723-01649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Objective: To explore the relationship between white matter lesions and clinical features and response of cerebral spinal fluid (CSF) tap test in patients with idiopathic normal pressure hydrocephalus(iNPH). Methods: Possible iNPH patients were enrolled from outpatients and inpatients in Peking Union Medical College Hospital between 2014 and 2019. All patients underwent detailed neuropsychological and walking assessments, CSF tap test, as well as head magnetic resonance imaging. The Fazekas score of white matter lesions, the fractional anisotropy (FA)and mean diffusivity (MD) values of regions of interest by means ofdiffusion tensor imaging (DTI) were compared between CSF tap test positive and negative response groups. The correlation between DTI parameters and clinical characteristics was analyzed. Results: Forty-three patients (29 male and 14 female, age range: 52-79 years] wererecruited.Compared with the negative group, patients in the positive group tended to have higher Fazekas score of periventricular white matter(U=108.00, P=0.03), higher MD value of the region near anterior horn of left lateral ventricles[(1.14±0.27)×10-9mm2/s vs (0.85±0.08) ×10-9mm2/s, P=0.003], lower FA value of the region near anterior horn of the right lateral ventricles[(0.20±0.07)vs(0.27±0.09), P=0.058], and higher MD value near the posterior horn of right lateral ventricle [(1.17±0.34)×10-9mm2/s vs (0.95±0.01)×10-9mm2/s, P=0.003]. FA and MD were significantly correlated with motor function, cognitive and functional scores, and iNPH grading scale (iNPHGS) scores(all P<0.05). Conclusions: The white matter lesions might be one of the pathogeneses of lNPH and apathological changewhich can be reversed by CSF drainage. More white matter lesions should not be the contraindication of CSF drainage surgery.
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Affiliation(s)
- C Y Liu
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - J J Wei
- Department of Neurosurgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - X Y Huang
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - L L Dong
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - J Li
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - J Wang
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - D Lei
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - C H Mao
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - B Hou
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - F Feng
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - L Y Cui
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
| | - J Gao
- Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China
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Peng J, Yang J, Li J, Lei D, Li N, Suo X, Duan L, Chen C, Zeng Y, Xi J, Jiang Y, Gong Q, Peng R. Disrupted Brain Functional Network Topology in Essential Tremor Patients With Poor Sleep Quality. Front Neurosci 2022; 16:814745. [PMID: 35360181 PMCID: PMC8960629 DOI: 10.3389/fnins.2022.814745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Accepted: 01/14/2022] [Indexed: 11/30/2022] Open
Abstract
Sleep disturbances, especially poor quality of sleep (QoS), are common among essential tremor (ET) patients and may have adverse effects on their quality of life, but the etiology driving the poor QoS in these individuals remains inadequately understood. Few data are available on the neuroimaging alterations of ET with poor QoS. Thirty-eight ET patients with poor QoS (SleET), 48 ET patients with normal QoS (NorET), and 80 healthy controls (HCs) participated in this study. All subjects underwent a 3.0-T magnetic resonance imaging (MRI) scan for resting-state functional MRI data collection. Then, the whole-brain functional connectome was constructed by thresholding the partial correlation matrices of 116 brain regions. Graph theory and network-based statistical analyses were performed. We used a non-parametric permutation test for group comparisons of topological metrics. Partial correlation analyses between the topographical features and clinical characteristics were conducted. The SleET and NorET groups exhibited decreased clustering coefficients, global efficiency, and local efficiency and increased the characteristic path length. Both of these groups also showed reduced nodal degree and nodal efficiency in the left superior dorsolateral frontal gyrus, superior frontal medial gyrus (SFGmed), posterior cingulate gyrus (PCG), lingual gyrus, superior occipital gyrus, right middle occipital gyrus, and right fusiform gyrus. The SleET group additionally presented reduced nodal degrees and nodal efficiency in the right SFGmed relative to the NorET and HC groups, and nodal efficiency in the right SFGmed was negatively correlated with the Pittsburgh Sleep Quality Index score. The observed impaired topographical organizations of functional brain networks within the central executive network (CEN), default mode network (DMN), and visual network serve to further our knowledge of the complex interactions between tremor and sleep, adding to our understanding of the underlying neural mechanisms of ET with poor QoS.
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Affiliation(s)
- Jiaxin Peng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Jing Yang
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Junying Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Du Lei
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Nannan Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Xueling Suo
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Liren Duan
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Chaolan Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Yan Zeng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Jing Xi
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Jiang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Qiyong Gong,
| | - Rong Peng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
- Rong Peng,
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McNamara RK, Li W, Lei D, Tallman MJ, Welge JA, Strawn JR, Patino LR, DelBello MP. Fish oil supplementation alters emotion-generated corticolimbic functional connectivity in depressed adolescents at high-risk for bipolar I disorder: A 12-week placebo-controlled fMRI trial. Bipolar Disord 2022; 24:161-170. [PMID: 34214231 PMCID: PMC8720319 DOI: 10.1111/bdi.13110] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To evaluate the effects of fish oil (FO), a source of the omega-3 polyunsaturated fatty acids (n-3 PUFA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), on emotion-generated corticolimbic functional connectivity in depressed youth at high risk for developing bipolar I disorder. METHODS Thirty-nine antidepressant-free youth with a current depressive disorder diagnosis and a biological parent with bipolar I disorder were randomized to 12-week double-blind treatment with FO or placebo. At baseline and endpoint, fMRI (4 Tesla) scans were obtained while performing a continuous performance task with emotional and neutral distractors (CPT-END). Seed-to-voxel functional connectivity analyses were performed using bilateral orbitofrontal cortex (OFC) and amygdala (AMY) seeds. Measures of depression, mania, global symptom severity, and erythrocyte fatty acids were obtained. RESULTS Erythrocyte EPA+DHA composition increased significantly in the FO group (+47%, p ≤ 0.0001) but not in the placebo group (-10%, p = 0.11). Significant group by time interactions were found for functional connectivity between the left OFC and the left superior temporal gyrus (STG) and between the right AMY and right inferior temporal gyrus (ITG). OFC-STG connectivity increased in the FO group (p = 0.0001) and decreased in the placebo group (p = 0.0019), and AMY-ITG connectivity decreased in the FO group (p = 0.0014) and increased in the placebo group (p < 0.0001). In the FO group, but not placebo group, the decrease in AMY-ITG functional connectivity correlated with decreases in Childhood Depression Rating Scale-Revised and Clinical Global Impression-Severity Scale scores. CONCLUSIONS In depressed high-risk youth FO supplementation alters emotion-generated corticolimbic functional connectivity which correlates with changes in symptom severity ratings.
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Affiliation(s)
- Robert K. McNamara
- Corresponding author: Robert K. McNamara, Ph.D., Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, 260 Stetson Street, Cincinnati, OH 45219-0516, PH: 513-558-5601, FAX: 513-558-4805,
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Suo X, Lei D, Li W, Sun H, Qin K, Yang J, Li L, Kemp GJ, Gong Q. Psychoradiological abnormalities in treatment-naive noncomorbid patients with posttraumatic stress disorder. Depress Anxiety 2022; 39:83-91. [PMID: 34793618 PMCID: PMC9298779 DOI: 10.1002/da.23226] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 09/23/2021] [Accepted: 10/26/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Neuroimaging studies in posttraumatic stress disorder (PTSD) have identified various alterations in white matter (WM) microstructural organization. However, it remains unclear whether these are localized to specific regions of fiber tracts, and what diagnostic value they might have. This study set out to explore the spatial profile of WM abnormalities along defined fiber tracts in PTSD. METHODS Diffusion tensor images were obtained from 77 treatment-naive noncomorbid patients with PTSD and 76 demographically matched trauma-exposed non-PTSD (TENP) controls. Using automated fiber quantification, tract profiles of fractional anisotropy, axial diffusivity, mean diffusivity, and radial diffusivity were calculated to evaluate WM microstructural organization. Results were analyzed by pointwise comparisons, by correlation with symptom severity, and for diagnosis-by-sex interactions. Support vector machine analyses assessed the ability of tract profiles to discriminate PTSD from TENP. RESULTS Compared to TENP, PTSD showed lower fractional anisotropy accompanied by higher radial diffusivity and mean diffusivity in the left uncinate fasciculus, and lower fractional anisotropy accompanied by higher radial diffusivity in the right anterior thalamic radiation. Tract profile alterations were correlated with symptom severity, suggesting a pathophysiological relevance. There were no significant differences in diagnosis-by-sex interaction. Tract profiles allowed individual classification of PTSD versus TENP with significant accuracy, of potential diagnostic utility. CONCLUSIONS These findings add to the knowledge of the neuropathological basis of PTSD. WM alterations based on a tract-profile quantification approach are a potential biomarker for PTSD.
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Affiliation(s)
- Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduSichuanChina
| | - Du Lei
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduSichuanChina,Department of Psychiatry and Behavioral NeuroscienceUniversity of CincinnatiCincinnatiOhioUnited States
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduSichuanChina
| | - Huaiqiang Sun
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduSichuanChina
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduSichuanChina
| | - Jing Yang
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduSichuanChina
| | - Lingjiang Li
- Mental Health InstituteThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Graham J. Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical SciencesUniversity of LiverpoolLiverpoolUK
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of RadiologyWest China Hospital of Sichuan UniversityChengduSichuanChina,Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduSichuanChina,Functional and Molecular Imaging Key Laboratory of Sichuan ProvinceHuaxi Xiamen Hospital of Sichuan UniversityXiamenFujianChina
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Yin T, Sun R, He Z, Chen Y, Yin S, Liu X, Lu J, Ma P, Zhang T, Huang L, Qu Y, Suo X, Lei D, Gong Q, Liang F, Li S, Zeng F. Subcortical-Cortical Functional Connectivity as a Potential Biomarker for Identifying Patients with Functional Dyspepsia. Cereb Cortex 2021; 32:3347-3358. [PMID: 34891153 DOI: 10.1093/cercor/bhab419] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 10/21/2021] [Accepted: 10/22/2021] [Indexed: 02/05/2023] Open
Abstract
The diagnosis of functional dyspepsia (FD) presently relies on the self-reported symptoms. This study aimed to determine the potential of functional brain network features as biomarkers for the identification of FD patients. Firstly, the functional brain Magnetic Resonance Imaging data were collected from 100 FD patients and 100 healthy subjects, and the functional brain network features were extracted by the independent component analysis. Then, a support vector machine classifier was established based on these functional brain network features to discriminate FD patients from healthy subjects. Features that contributed substantially to the classification were finally identified as the classifying features. The results demonstrated that the classifier performed pretty well in discriminating FD patients. Namely, the accuracy of classification was 0.84 ± 0.03 in cross-validation set and 0.80 ± 0.07 in independent test set, respectively. A total of 15 connections between the subcortical nucleus (the thalamus and caudate) and sensorimotor cortex, parahippocampus, orbitofrontal cortex were finally determined as the classifying features. Furthermore, the results of cross-brain atlas validation showed that these classifying features were quite robust in the identification of FD patients. In summary, the current findings suggested the potential of using machine learning method and functional brain network biomarkers to identify FD patients.
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Affiliation(s)
- Tao Yin
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Ruirui Sun
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Zhaoxuan He
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China.,Key Laboratory of Sichuan Province for Acupuncture and Chronobiology, Chengdu, Sichuan 610075, China
| | - Yuan Chen
- International Education College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Shuai Yin
- First Affiliated Hospital, Henan University of Traditional Chinese Medicine, Zhengzhou, Henan 450002, China
| | - Xiaoyan Liu
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Jin Lu
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Peihong Ma
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China.,School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Tingting Zhang
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Liuyang Huang
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Yuzhu Qu
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Xueling Suo
- Departments of Radiology, Huaxi Magnetic Resonance Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Du Lei
- Departments of Radiology, Huaxi Magnetic Resonance Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Qiyong Gong
- Departments of Radiology, Huaxi Magnetic Resonance Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
| | - Fanrong Liang
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
| | - Shenghong Li
- State Key Laboratory of Southwestern Chinese Medicine Resources, Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China
| | - Fang Zeng
- Acupuncture and Tuina School, The 3rd Teaching Hospital, Acupuncture and Brain Science Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China.,Key Laboratory of Sichuan Province for Acupuncture and Chronobiology, Chengdu, Sichuan 610075, China
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Chen Y, Lei D, Cao H, Niu R, Chen F, Chen L, Zhou J, Hu X, Huang X, Guo L, Sweeney JA, Gong Q. Altered single-subject gray matter structural networks in drug-naïve attention deficit hyperactivity disorder children. Hum Brain Mapp 2021; 43:1256-1264. [PMID: 34797010 PMCID: PMC8837581 DOI: 10.1002/hbm.25718] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 10/09/2021] [Accepted: 11/04/2021] [Indexed: 02/05/2023] Open
Abstract
Altered topological organization of brain structural covariance networks has been observed in attention deficit hyperactivity disorder (ADHD). However, results have been inconsistent, potentially related to confounding medication effects. In addition, since structural networks are traditionally constructed at the group level, variabilities in individual structural features remain to be well characterized. Structural brain imaging with MRI was performed on 84 drug‐naïve children with ADHD and 83 age‐matched healthy controls. Single‐subject gray matter (GM) networks were obtained based on areal similarities of GM, and network topological properties were analyzed using graph theory. Group differences in each topological metric were compared using nonparametric permutation testing. Compared with healthy subjects, GM networks in ADHD patients demonstrated significantly altered topological characteristics, including higher global and local efficiency and clustering coefficient, and shorter path length. In addition, ADHD patients exhibited abnormal centrality in corticostriatal circuitry including the superior frontal gyrus, orbitofrontal gyrus, medial superior frontal gyrus, precentral gyrus, middle temporal gyrus, and pallidum (all p < .05, false discovery rate [FDR] corrected). Altered global and nodal topological efficiencies were associated with the severity of hyperactivity symptoms and the performance on the Stroop and Wisconsin Card Sorting Test tests (all p < .05, FDR corrected). ADHD combined and inattention subtypes were differentiated by nodal attributes of amygdala (p < .05, FDR corrected). Alterations in GM network topologies were observed in drug‐naïve ADHD patients, in particular in frontostriatal loops and amygdala. These alterations may contribute to impaired cognitive functioning and impulsive behavior in ADHD.
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Affiliation(s)
- Ying Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio, USA
| | - Hengyi Cao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York, USA.,Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, New York, USA.,Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Running Niu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Fuqin Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Lizhou Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Jinbo Zhou
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China
| | - Xinyu Hu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Lanting Guo
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, Huaxi Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
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Yang J, Lei D, Qin K, Pinaya WHL, Suo X, Li W, Li L, Kemp GJ, Gong Q. Using deep learning to classify pediatric posttraumatic stress disorder at the individual level. BMC Psychiatry 2021; 21:535. [PMID: 34711200 PMCID: PMC8555083 DOI: 10.1186/s12888-021-03503-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 09/28/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Children exposed to natural disasters are vulnerable to developing posttraumatic stress disorder (PTSD). Previous studies using resting-state functional neuroimaging have revealed alterations in graph-based brain topological network metrics in pediatric PTSD patients relative to healthy controls (HC). Here we aimed to apply deep learning (DL) models to neuroimaging markers of classification which may be of assistance in diagnosis of pediatric PTSD. METHODS We studied 33 pediatric PTSD and 53 matched HC. Functional connectivity between 90 brain regions from the automated anatomical labeling atlas was established using partial correlation coefficients, and the whole-brain functional connectome was constructed by applying a threshold to the resultant 90 * 90 partial correlation matrix. Graph theory analysis was used to examine the topological properties of the functional connectome. A DL algorithm then used this measure to classify pediatric PTSD vs HC. RESULTS Graphic topological measures using DL provide a potentially clinically useful classifier for differentiating pediatric PTSD and HC (overall accuracy 71.2%). Frontoparietal areas (central executive network), cingulate cortex, and amygdala contributed the most to the DL model's performance. CONCLUSIONS Graphic topological measures based on fMRI data could contribute to imaging models of clinical utility in distinguishing pediatric PTSD from HC. DL model may be a useful tool in the identification of brain mechanisms PTSD participants.
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Affiliation(s)
- Jing Yang
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, 45219, USA
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Walter H L Pinaya
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, SE5 8AF, UK
| | - Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Lingjiang Li
- Mental Health Institute, the Second Xiangya Hospital of Central South University, Changsha, 410008, Hunan, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, L9 7AL, UK
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China.
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Schwartzman G, Lei D, Ahmed A, Chavda R, Gabriel S, Silverberg JI. Longitudinal course and phenotypes of health-related quality of life in adults with atopic dermatitis. Clin Exp Dermatol 2021; 47:359-372. [PMID: 34623642 DOI: 10.1111/ced.14948] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 08/27/2021] [Accepted: 09/23/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND The real-world course of health-related quality of life (HRQoL) in atopic dermatitis (AD) is not well established. AIM To examine predictors, longitudinal course and phenotypes of HRQoL in adult patients with AD. METHODS This was a prospective dermatology-practice based study of 955 patients with AD (age 18-97 years). Patients were assessed at baseline and approximately 6, 12, 18 and 24 months. HRQoL was assessed using the 10-item short-form Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health (PGH). AD severity and impact was assessed by patient-reported global AD severity, Patient-Oriented Eczema Measure (POEM), Eczema Area and Severity Index (EASI), Objective SCORing Atopic Dermatitis (O-SCORAD), Investigator's Global Assessment (IGA), Numerical Rating Scale (NRS) average and worst itch, PROMIS sleep-related impairment (SRI), and nine-item Patient Health Questionnaire (PHQ)-9. Repeated-measures regression models were constructed to examine itch over time. RESULTS In multivariable linear regression models controlling for age, race/ethnicity, history of asthma, hay fever and food allergy, baseline PGH-physical (PGH-P4) T scores were inversely associated with patient-reported global AD severity, POEM, EASI, objective SCORAD, IGA, NRS average and worst itch, PROMIS SRI and PHQ-9, with stepwise decreases of physical health with worsening severity. PGH-mental health (PGH-M4) T scores were associated with all aforementioned severity measures aside from POEM. In multivariable repeated measures linear regression models, decreased PGH-P4 and PGH-M4 T scores and mapped five-dimension EuroQoL over time were associated with self-reported global AD severity, NRS worst and mean itch, POEM, PROMIS sleep disturbance and SRI, EASI, objective SCORAD, IGA and PHQ-9. Latent class analysis identified six classes of HRQoL, which were associated with measures of AD severity, nonwhite race, Hispanic ethnicity and having only public health insurance, but not age or sex. CONCLUSION Patients with AD have a heterogeneous longitudinal course and distinct patterns of HRQoL. Many patients had fluctuating HRQoL over time. Most patients with moderate to severe disease at baseline had persistent HRQoL impairment over time.
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Affiliation(s)
- G Schwartzman
- Department of Dermatology, The George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - D Lei
- Department of Dermatology, Feinberg School of Medicine at Northwestern University, Chicago, IL, USA
| | - A Ahmed
- Department of Dermatology, Feinberg School of Medicine at Northwestern University, Chicago, IL, USA
| | - R Chavda
- Galderma SA Rx Strategy and Innovation Group, La Tour-de-Peliz, Switzerland
| | - S Gabriel
- Department of Dermatology, The George Washington University School of Medicine and Health Sciences, Washington, DC, USA
| | - J I Silverberg
- Department of Dermatology, The George Washington University School of Medicine and Health Sciences, Washington, DC, USA.,Department of Dermatology, Feinberg School of Medicine at Northwestern University, Chicago, IL, USA
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Li N, Lei D, Peng J, Suo X, Li J, Duan L, Chen C, Gong Q, Peng R. Brain network topology and future development of freezing of gait in Parkinson's disease: a longitudinal study. J Neurol 2021; 269:2503-2512. [PMID: 34618223 DOI: 10.1007/s00415-021-10817-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 09/08/2021] [Accepted: 09/21/2021] [Indexed: 02/06/2023]
Abstract
BACKGROUND Freezing of gait (FOG) is a common disabling gait disturbance in Parkinson's disease (PD). The objectives of this study were to explore alterations in the topological organization of whole-brain functional networks in patients with PD who will develop FOG. METHODS We recruited 20 patients with PD who developed FOG (PD-FOGt) during a 5-year follow-up period, 20 patients with PD who did not developed FOG (PD-FOGn) within the follow-up period, and 20 healthy control subjects. Using graph theory approaches, we performed a comparative analysis of the topological organization of whole-brain functional networks among the groups, and further explored their potential relationships with latency to develop FOG. RESULTS At baseline, the global topological properties of functional brain networks in PD-FOGt and PD-FOGn showed no abnormalities. Additionally, regarding regional topological properties, compared with PD-FOGn patients, PD-FOGt patients exhibited decreased nodal centrality in the left middle frontal gyrus (MFG). Although there were no significant differences compared with PD-FOGn patients, the PD-FOGt group exhibited the lowest nodal centrality values in the frontal cortex (left gyrus rectus), and visual cortex (bilateral inferior occipital gyrus and left fusiform gyrus), and the highest nodal centrality values in the cerebellum (vermis_6) among the three groups. However, no relationship was found between the nodal centrality in above brain regions and latency to develop FOG. CONCLUSION This study demonstrates the disrupted regional topological organization might contribute to the future development of FOG in PD patients, especially associated with damage to the left MFG.
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Affiliation(s)
- Nannan Li
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Du Lei
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Jiaxin Peng
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Xueling Suo
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Junying Li
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Liren Duan
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Chaolan Chen
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Rong Peng
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China.
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Li W, Wei Q, Hou Y, Lei D, Ai Y, Qin K, Yang J, Kemp GJ, Shang H, Gong Q. Disruption of the white matter structural network and its correlation with baseline progression rate in patients with sporadic amyotrophic lateral sclerosis. Transl Neurodegener 2021; 10:35. [PMID: 34511130 PMCID: PMC8436442 DOI: 10.1186/s40035-021-00255-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 08/01/2021] [Indexed: 02/08/2023] Open
Abstract
OBJECTIVE There is increasing evidence that amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease impacting large-scale brain networks. However, it is still unclear which structural networks are associated with the disease and whether the network connectomics are associated with disease progression. This study was aimed to characterize the network abnormalities in ALS and to identify the network-based biomarkers that predict the ALS baseline progression rate. METHODS Magnetic resonance imaging was performed on 73 patients with sporadic ALS and 100 healthy participants to acquire diffusion-weighted magnetic resonance images and construct white matter (WM) networks using tractography methods. The global and regional network properties were compared between ALS and healthy subjects. The single-subject WM network matrices of patients were used to predict the ALS baseline progression rate using machine learning algorithms. RESULTS Compared with the healthy participants, the patients with ALS showed significantly decreased clustering coefficient Cp (P = 0.0034, t = 2.98), normalized clustering coefficient γ (P = 0.039, t = 2.08), and small-worldness σ (P = 0.038, t = 2.10) at the global network level. The patients also showed decreased regional centralities in motor and non-motor systems including the frontal, temporal and subcortical regions. Using the single-subject structural connection matrix, our classification model could distinguish patients with fast versus slow progression rate with an average accuracy of 85%. CONCLUSION Disruption of the WM structural networks in ALS is indicated by weaker small-worldness and disturbances in regions outside of the motor systems, extending the classical pathophysiological understanding of ALS as a motor disorder. The individual WM structural network matrices of ALS patients are potential neuroimaging biomarkers for the baseline disease progression in clinical practice.
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Affiliation(s)
- Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Qianqian Wei
- Laboratory of Neurodegenerative Disorders, Departments of Neurology, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Yanbing Hou
- Laboratory of Neurodegenerative Disorders, Departments of Neurology, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA
| | - Yuan Ai
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Jing Yang
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China
| | - Graham J Kemp
- Department of Musculoskeletal and Ageing Science and MRC - Versus Arthritis Centre for Integrated Research Into Musculoskeletal Ageing, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK
| | - Huifang Shang
- Laboratory of Neurodegenerative Disorders, Departments of Neurology, West China Hospital of Sichuan University, Chengdu, 610000, China.
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610000, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610000, China.
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Li W, Lei D, Tallman MJ, Patino LR, Gong Q, Strawn JR, DelBello MP, McNamara RK. Emotion-Related Network Reorganization Following Fish Oil Supplementation in Depressed Bipolar Offspring: An fMRI Graph-Based Connectome Analysis. J Affect Disord 2021; 292:319-327. [PMID: 34139404 PMCID: PMC8282765 DOI: 10.1016/j.jad.2021.05.086] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 05/03/2021] [Accepted: 05/31/2021] [Indexed: 02/04/2023]
Abstract
INTRODUCTION Mood disorders are associated with fronto-limbic structural and functional abnormalities and deficits in omega-3 polyunsaturated fatty acids including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Emerging evidence also suggests that n-3 PUFA, which are enriched in fish oil, promote cortical plasticity and connectivity. The present study performed a graph-based connectome analysis to investigate the role of n-3 PUFA in emotion-related network organization in medication-free depressed adolescent bipolar offspring. METHODS At baseline patients (n = 53) were compared with healthy controls (n = 53), and patients were then randomized to 12-week double-blind treatment with placebo or fish oil. At baseline and endpoint, erythrocyte EPA+DHA levels were measured and fMRI scans (4 Tesla) were obtained while performing a continuous performance task with emotional and neutral distractors (CPT-END). Graph-based analysis was used to characterize topological properties of large-scale brain network organization. RESULTS Compared with healthy controls, patients exhibited lower erythrocyte EPA+DHA levels (p = 0.0001), lower network clustering coefficients (p = 0.029), global efficiency (p = 0.042), and lower node centrality and connectivity strengths in frontal-limbic regions (p<0.05). Compared with placebo, 12-week fish oil supplementation increased erythrocyte EPA+DHA levels (p<0.001), network clustering coefficient (p = 0.005), global (p = 0.047) and local (p = 0.023) efficiency, and node centralities mainly in temporal regions (p<0.05). LIMITATIONS The duration of fish oil supplementation was relatively short and the sample size was relatively small. CONCLUSIONS These findings provide preliminary evidence that abnormalities in emotion-related network organization observed in depressed high-risk youth may be amenable to modification through fish oil supplementation.
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Affiliation(s)
- Wenbin Li
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267,Departments of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267
| | - Maxwell J. Tallman
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267
| | - L. Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267
| | - Qiyong Gong
- Departments of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan, China.
| | - Jeffrey R. Strawn
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267
| | - Melissa P. DelBello
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267
| | - Robert K. McNamara
- Department of Psychiatry and Behavioral Neuroscience, Division of Bipolar Disorders Research, University of Cincinnati College of Medicine, Cincinnati, OH 45267
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Yang J, Lei D, Peng J, Suo X, Pinaya WHL, Li W, Li J, Kemp GJ, Peng R, Gong Q. Disrupted brain gray matter networks in drug-naïve participants with essential tremor. Neuroradiology 2021; 63:1501-1510. [PMID: 33782719 DOI: 10.1007/s00234-021-02653-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 01/20/2021] [Indexed: 02/05/2023]
Abstract
PURPOSE To use structural magnetic resonance imaging and graph theory approaches to investigate the topological organization of the brain morphological network based on gray matter in essential tremor, and its potential relation to disease severity. METHODS In this prospective study conducted from November 2018 to November 2019, 36 participants with essential tremor and 37 matched healthy controls underwent magnetic resonance imaging. Brain networks based on the morphological similarity of gray matter across regions were analyzed using graph theory. Nonparametric permutation testing was used to assess group differences in topological metrics. Support vector machine was applied to the gray matter morphological matrices to classify participants with essential tremor vs. healthy controls. RESULTS Compared with healthy controls, participants with essential tremor showed increased global efficiency (p < 0.01) and decreased path length (p < 0.01); abnormal nodal properties in frontal, parietal, and cerebellar lobes; and disconnectivity in cerebello-thalamo-cortical network. The abnormal brain nodal centralities (left superior cerebellum gyrus; right caudate nucleus) correlated with clinical measures, both motor (Fahn-Tolosa-Marìn tremor rating, p = 0.017, r = - 0.41) and nonmotor (Hamilton depression scale, p = 0.040, r = - 0.36; Hamilton anxiety scale, p = 0.008, r = - 0.436). Gray matter morphological matrices classified individuals with high accuracy of 80.0%. CONCLUSION Participants with essential tremor showed randomization in global properties and dysconnectivity in the cerebello-thalamo-cortical network. Participants with essential tremor could be distinguished from healthy controls by gray matter morphological matrices.
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Affiliation(s)
- Jing Yang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Jiaxin Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Walter H L Pinaya
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Junying Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
| | - Rong Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, Sichuan, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
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Zhu Z, Lei D, Qin K, Suo X, Li W, Li L, DelBello MP, Sweeney JA, Gong Q. Combining Deep Learning and Graph-Theoretic Brain Features to Detect Posttraumatic Stress Disorder at the Individual Level. Diagnostics (Basel) 2021; 11:1416. [PMID: 34441350 PMCID: PMC8391111 DOI: 10.3390/diagnostics11081416] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/18/2021] [Accepted: 07/28/2021] [Indexed: 02/05/2023] Open
Abstract
Previous studies using resting-state functional MRI (rs-fMRI) have revealed alterations in graphical metrics in groups of individuals with posttraumatic stress disorder (PTSD). To explore the ability of graph measures to diagnose PTSD and capture its essential features in individual patients, we used a deep learning (DL) model based on a graph-theoretic approach to discriminate PTSD from trauma-exposed non-PTSD at the individual level and to identify its most discriminant features. Our study was performed on rs-fMRI data from 91 individuals with PTSD and 126 trauma-exposed non-PTSD patients. To evaluate our DL method, we used the traditional support vector machine (SVM) classifier as a reference. Our results showed that the proposed DL model allowed single-subject discrimination of PTSD and trauma-exposed non-PTSD individuals with higher accuracy (average: 80%) than the traditional SVM (average: 57.7%). The top 10 DL features were identified within the default mode, central executive, and salience networks; the first two of these networks were also identified in the SVM classification. We also found that nodal efficiency in the left fusiform gyrus was negatively correlated with the Clinician Administered PTSD Scale score. These findings demonstrate that DL based on graphical features is a promising method for assisting in the diagnosis of PTSD.
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Affiliation(s)
- Ziyu Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; (Z.Z.); (K.Q.); (X.S.); (W.L.); (J.A.S.)
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH 45219, USA; (D.L.); (M.P.D.)
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; (Z.Z.); (K.Q.); (X.S.); (W.L.); (J.A.S.)
| | - Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; (Z.Z.); (K.Q.); (X.S.); (W.L.); (J.A.S.)
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; (Z.Z.); (K.Q.); (X.S.); (W.L.); (J.A.S.)
| | - Lingjiang Li
- Mental Health Institute, The Second Xiangya Hospital of Central South University, Changsha 410008, China;
| | - Melissa P. DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH 45219, USA; (D.L.); (M.P.D.)
| | - John A. Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; (Z.Z.); (K.Q.); (X.S.); (W.L.); (J.A.S.)
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH 45219, USA; (D.L.); (M.P.D.)
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; (Z.Z.); (K.Q.); (X.S.); (W.L.); (J.A.S.)
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610000, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, Chengdu 610000, China
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Suo X, Lei D, Li N, Li J, Peng J, Li W, Yang J, Qin K, Kemp GJ, Peng R, Gong Q. Topologically convergent and divergent morphological gray matter networks in early-stage Parkinson's disease with and without mild cognitive impairment. Hum Brain Mapp 2021; 42:5101-5112. [PMID: 34322939 PMCID: PMC8449106 DOI: 10.1002/hbm.25606] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/07/2021] [Accepted: 06/26/2021] [Indexed: 02/05/2023] Open
Abstract
Patients with Parkinson's disease with mild cognitive impairment (PD‐M) progress to dementia more frequently than those with normal cognition (PD‐N), but the underlying neurobiology remains unclear. This study aimed to define the specific morphological brain network alterations in PD‐M, and explore their potential diagnostic value. Twenty‐four PD‐M patients, 17 PD‐N patients, and 29 healthy controls (HC) underwent a structural MRI scan. Similarity between interregional gray matter volume distributions was used to construct individual morphological brain networks. These were analyzed using graph theory and network‐based statistics (NBS), and their relationship to neuropsychological tests was assessed. Support vector machine (SVM) was used to perform individual classification. Globally, compared with HC, PD‐M showed increased local efficiency (p = .001) in their morphological networks, while PD‐N showed decreased normalized path length (p = .008). Locally, similar nodal deficits were found in the rectus and lingual gyrus, and cerebellum of both PD groups relative to HC; additionally in PD‐M nodal deficits involved several frontal and parietal regions, correlated with cognitive scores. NBS found that similar connections were involved in the default mode and cerebellar networks of both PD groups (to a greater extent in PD‐M), while PD‐M, but not PD‐N, showed altered connections involving the frontoparietal network. Using connections identified by NBS, SVM allowed discrimination with high accuracy between PD‐N and HC (90%), PD‐M and HC (85%), and between the two PD groups (65%). These results suggest that default mode and cerebellar disruption characterizes PD, more so in PD‐M, whereas frontoparietal disruption has diagnostic potential.
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Affiliation(s)
- Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Du Lei
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio, USA
| | - Nannan Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Junying Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Jiaxin Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Jing Yang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
| | - Rong Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.,Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
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44
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Li W, Jiang Y, Qin Y, Zhou B, Lei D, Zhang H, Lei D, Yao D, Luo C, Gong Q, Zhou D, An D. Structural and functional reorganization of contralateral hippocampus after temporal lobe epilepsy surgery. Neuroimage Clin 2021; 31:102714. [PMID: 34102537 PMCID: PMC8187253 DOI: 10.1016/j.nicl.2021.102714] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 05/27/2021] [Accepted: 05/28/2021] [Indexed: 02/08/2023]
Abstract
Postoperative changes of contralateral hippocampus in temporal lobe epilepsy. No obvious hippocampal volume change was observed after successful surgery. Surgical manipulation may lead to a transient functional connectivity reduction. Increased functional connectivity mostly involved bilateral frontal regions.
Objective To explore the structural and functional reorganization of contralateral hippocampus in patients with unilateral mesial temporal lobe epilepsy (mTLE) who achieved seizure-freedom after anterior temporal lobectomy (ATL). Methods We obtained high-resolution structural MRI and resting-state functional MRI data in 28 unilateral mTLE patients and 29 healthy controls. Patients were scanned before and three and 24 months after surgery while controls were scanned only once. Hippocampal gray matter volume (GMV) and functional connectivity (FC) were assessed. Results No obvious GMV changes were observed in contralateral hippocampus before and after successful surgery. Before surgery, ipsilateral hippocampus showed increased FC with ipsilateral insula (INS) and temporoparietal junction (TPJ), but decreased FC with widespread bilateral regions, as well as contralateral hippocampus. After successful ATL, contralateral hippocampus showed: (1) decreased FC with ipsilateral INS at three months follow-up, without further changes; (2) decreased FC with ipsilateral TPJ, postcentral gyrus and rolandic operculum at three months, with an obvious increase at 24 months follow-up; (3) increased FC with bilateral medial prefrontal cortex (MPFC) and superior frontal gyrus (SFG) at three months follow-up, without further changes. Conclusions Successful ATL may not lead to an obvious structural reorganization in contralateral hippocampus. Surgical manipulation may lead to a transient FC reduction of contralateral hippocampus. Increased FC between contralateral hippocampus and bilateral MPFC and SFG may be related to postoperative functional remodeling.
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Affiliation(s)
- Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Yingjie Qin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Baiwan Zhou
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Du Lei
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Heng Zhang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ding Lei
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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45
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Lei D, Li W, Tallman MJ, Patino LR, McNamara RK, Strawn JR, Klein CC, Nery FG, Fleck DE, Qin K, Ai Y, Yang J, Zhang W, Lui S, Gong Q, Adler CM, Sweeney JA, DelBello MP. Changes in the brain structural connectome after a prospective randomized clinical trial of lithium and quetiapine treatment in youth with bipolar disorder. Neuropsychopharmacology 2021; 46:1315-1323. [PMID: 33753882 PMCID: PMC8134458 DOI: 10.1038/s41386-021-00989-5] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 02/02/2021] [Accepted: 02/16/2021] [Indexed: 02/06/2023]
Abstract
The goals of the current study were to determine whether topological organization of brain structural networks is altered in youth with bipolar disorder, whether such alterations predict treatment outcomes, and whether they are normalized by treatment. Youth with bipolar disorder were randomized to double-blind treatment with quetiapine or lithium and assessed weekly. High-resolution MRI images were collected from children and adolescents with bipolar disorder who were experiencing a mixed or manic episode (n = 100) and healthy youth (n = 63). Brain networks were constructed based on the similarity of morphological features across regions and analyzed using graph theory approaches. We tested for pretreatment anatomical differences between bipolar and healthy youth and for changes in neuroanatomic network metrics following treatment in the youth with bipolar disorder. Youth with bipolar disorder showed significantly increased clustering coefficient (Cp) (p = 0.009) and characteristic path length (Lp) (p = 0.04) at baseline, and altered nodal centralities in insula, inferior frontal gyrus, and supplementary motor area. Cp, Lp, and nodal centrality of the insula exhibited normalization in patients following treatment. Changes in these neuroanatomic parameters were correlated with improvement in manic symptoms but did not differ between the two drug therapies. Baseline structural network matrices significantly differentiated medication responders and non-responders with 80% accuracy. These findings demonstrate that both global and nodal structural network features are altered in early course bipolar disorder, and that pretreatment alterations in neuroanatomic features predicted treatment outcome and were reduced by treatment. Similar connectome normalization with lithium and quetiapine suggests that the connectome changes are a downstream effect of both therapies that is related to their clinical efficacy.
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Affiliation(s)
- Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
| | - Wenbin Li
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, P. R. China
| | - Maxwell J Tallman
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - L Rodrigo Patino
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Robert K McNamara
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Jeffrey R Strawn
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Christina C Klein
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Fabiano G Nery
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - David E Fleck
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, P. R. China
| | - Yuan Ai
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, P. R. China
| | - Jing Yang
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, P. R. China
| | - Wenjing Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, P. R. China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, P. R. China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, P. R. China.
| | - Caleb M Adler
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - John A Sweeney
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Huaxi MR Research Center (HMRRC), Department of Radiology, The Center for Medical Imaging, West China Hospital of Sichuan University, Chengdu, P. R. China
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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Li N, Suo X, Zhang J, Lei D, Wang L, Li J, Peng J, Duan L, Gong Q, Peng R. Disrupted functional brain network topology in Parkinson's disease patients with freezing of gait. Neurosci Lett 2021; 759:135970. [PMID: 34023405 DOI: 10.1016/j.neulet.2021.135970] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 05/16/2021] [Accepted: 05/17/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND Freezing of gait (FOG) is a common and debilitating gait disturbance in patients with Parkinson's disease (PD), but the potential mechanisms are still unclear. This study aimed to explore alterations in the topological organization of whole-brain functional networks in PD patients with FOG. METHODS We recruited 75 patients with PD, 37 patients with FOG and 38 patients without FOG, to undergo resting-state functional magnetic resonance imaging (fMRI). The whole-brain functional networks were constructed, and the topological properties at three (global, nodal, and connectional) levels were analyzed using graph theory approaches. RESULTS Compared with patients without FOG, patients with FOG exhibited altered global topological properties (a significant decrease in the normalized clustering coefficient and small-worldness), implying a shift toward randomization in their functional brain networks. At the node and connectional levels, patients with FOG showed increased nodal centralities and functional connectivity in the sensorimotor network, frontoparietal network, visual network, subcortical and limbic regions, and decreased nodal centralities in the frontoparietal network and the cerebellum. Furthermore, the altered nodal centralities in the right hippocampus (HIP) were positively correlated with FOG severity. CONCLUSIONS This study suggests that FOG in PD is associated with disrupted topological organization of whole-brain functional networks, involving dysfunction of the multiple networks.
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Affiliation(s)
- Nannan Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jinhong Zhang
- Department of Internal Medicine, Wangjiang Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Du Lei
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ling Wang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Junying Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jiaxin Peng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Liren Duan
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Rong Peng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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47
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Qin Y, Tong X, Li W, Zhang L, Zhang Y, Li X, Yang J, Qin K, Lei D, Gong Q, Zhou D, An D. Divergent Anatomical Correlates and Functional Network Connectivity Patterns in Temporal Lobe Epilepsy with and Without Depression. Brain Topogr 2021; 34:525-536. [PMID: 33973138 DOI: 10.1007/s10548-021-00848-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 05/05/2021] [Indexed: 02/05/2023]
Abstract
Epilepsy and depression were proposed to facilitate each other reciprocally through common neurobiological anomalies, especially the prefrontal-limbic-subcortical abnormalities. Yet neuroimaging patterns of higher-order cognitive networks and neuroanatomical correlates were rarely compared in temporal lobe epilepsy patients with (TLE-D) and without depression (TLE-N). We collected T1-weighted structural and resting-state functional MRI data from 20 TLE-D, 31 TLE-N and 20 healthy controls (HCs) and performed analyses including hippocampal volume (HCV), cortical thickness, gray matter volume (GMV) and whole-brain functional network connectivity (FNC) across three groups. Imaging differences were related to clinical and psychological measurements. TLE-D demonstrated disrupted functional role of subcortical (SUB) and higher-order cognitive networks compared to TLE-N and HCs. In TLE-D, GMV in the right supplementary motor area (SMA) and FNC between the dorsal attention (DAN) and SUB were attenuated compared to TLE-N and HCs, FNC between SUB and the visual network (VIS) decreased compared to HCs. GMV in the right SMA was negatively correlated with depression severity and some symptoms. Combined, explicit emotion regulation may be impaired in TLE-D. Meanwhile, compared to HCs, TLE-N showed smaller HCVs, TLE-D and TLE-N showed smaller GMV in the medial orbital frontal gyrus and right hippocampus and hippocampal gyrus, possibly implying predisposition of epileptic activities to co-morbid depression. Our findings suggest distinct anatomical and FNC patterns in TLE-D and TLE-N. More than prefrontal-limbic-subcortical anomalies, disrupted higher-order cognitive network may contribute to depression in TLE, providing new potential treatment targets for depression and calling attention to relation between cognitive dysfunction and co-morbid depression.
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Affiliation(s)
- Yingjie Qin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xin Tong
- Department of Neurology, West China Second Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Le Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yingying Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiuli Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jing Yang
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Kun Qin
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Du Lei
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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48
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Qin K, Lei D, Yang J, Li W, Tallman MJ, Duran LRP, Blom TJ, Bruns KM, Cotton S, Sweeney JA, Gong Q, DelBello MP. Network-level functional topological changes after mindfulness-based cognitive therapy in mood dysregulated adolescents at familial risk for bipolar disorder: a pilot study. BMC Psychiatry 2021; 21:213. [PMID: 33910549 PMCID: PMC8080341 DOI: 10.1186/s12888-021-03211-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 04/09/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Given that psychopharmacological approaches routinely used to treat mood-related problems may result in adverse outcomes in mood dysregulated adolescents at familial risk for bipolar disorder (BD), Mindfulness-Based Cognitive Therapy for Children (MBCT-C) provides an alternative effective and safe option. However, little is known about the brain mechanisms of beneficial outcomes from this intervention. Herein, we aimed to investigate the network-level neurofunctional effects of MBCT-C in mood dysregulated adolescents. METHODS Ten mood dysregulated adolescents at familial risk for BD underwent a 12-week MBCT-C intervention. Resting-state functional magnetic resonance imaging (fMRI) was performed prior to and following MBCT-C. Topological metrics of three intrinsic functional networks (default mode network (DMN), fronto-parietal network (FPN) and cingulo-opercular network (CON)) were investigated respectively using graph theory analysis. RESULTS Following MBCT-C, mood dysregulated adolescents showed increased global efficiency and decreased characteristic path length within both CON and FPN. Enhanced functional connectivity strength of frontal and limbic areas were identified within the DMN and CON. Moreover, change in characteristic path length within the CON was suggested to be significantly related to change in the Emotion Regulation Checklist score. CONCLUSIONS 12-week MBCT-C treatment in mood dysregulated adolescents at familial risk for BD yield network-level neurofunctional effects within the FPN and CON, suggesting enhanced functional integration of the dual-network. Decreased characteristic path length of the CON may be associated with the improvement of emotion regulation following mindfulness training. However, current findings derived from small sample size should be interpreted with caution. Future randomized controlled trials including larger samples are critical to validate our findings.
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Affiliation(s)
- Kun Qin
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Du Lei
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Jing Yang
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Wenbin Li
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China ,grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Maxwell J. Tallman
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Luis Rodrigo Patino Duran
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Thomas J. Blom
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Kaitlyn M. Bruns
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Sian Cotton
- grid.24827.3b0000 0001 2179 9593Department of Family and Community Medicine, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - John A. Sweeney
- grid.412901.f0000 0004 1770 1022Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China ,grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China. .,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China. .,Functional and Molecular Imaging Key Laboratory of Sichuan Province, Chengdu, China.
| | - Melissa P. DelBello
- grid.24827.3b0000 0001 2179 9593Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
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Sun R, He Z, Ma P, Yin S, Yin T, Liu X, Lu J, Qu Y, Zhang T, Huang L, Suo X, Lei D, Gong Q, Liang F, Zeng F. The participation of basolateral amygdala in the efficacy of acupuncture with deqi treating for functional dyspepsia. Brain Imaging Behav 2021; 15:216-230. [PMID: 32125619 DOI: 10.1007/s11682-019-00249-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Deqi is taken as an indispensable requirement to achieve acupuncture efficacy. This study aimed to explore the central influence of deqi on the efficacy of acupuncture for functional dyspepsia (FD). 70 FD patients were randomized to receive 20 sessions' acupuncture treatment with (n = 35) and without deqi (n = 35). In each group, 25 FD patients randomly selected underwent functional magnetic resonance imaging (fMRI) scans before and after treatment. After group re-division according to deqi response, changes of amygdala subregions-based resting-state functional connectivity (rsFC) were compared between the acupuncture with and without obvious deqi group. The clinical changes of the Nepean Dyspepsia Symptom Index (NDSI) measuring FD symptoms were also used to further assess the correlation with amygdala subregions rsFC in FD patients. The decrease in the NDSI scores (pre-pos) in the obvious deqi group was significantly greater than that in the acupuncture without obvious deqi group (p < 0.05). Compared to the without obvious deqi group, the obvious deqi group showed significantly decreased the left basolateral amygdala (BLA) rsFC with bilateral insular (INS), putamen and middle/posterior cingulate cortex (MCC/PCC), right pallidum and hippocampus (HIPP) after treatment. The changed NDSI scores(pre-post) of all 41 FD patients was significantly positively correlated with their Fisher's transformed z value of the left BLA rsFC with left INS (r = 0.376, FDR corrected p = 0.015), and rsFC with right HIPP (r = 0.394, FDR corrected p = 0.015). The changed NDSI scores(pre-post) of the obvious deqi group was significantly negatively correlated with their Fisher's transformed z value of the right centromedial amygdala (CMA) rsFC with left medial prefrontal cortex (mPFC) (r = -0.463, p = 0.035). The results tested the hypothesis that the advantage of deqi on efficacy is related to affecting the BLA and CMA rsFC. It suggested that deqi might influence the abnormal rsFC within the salience network (SN), and participate in the adaptive modulation of disrupted relationship between the SN and default mode network (DMN).
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Affiliation(s)
- Ruirui Sun
- Acupuncture and Tuina School, Acupuncture and Brain Research Center, The 3rd Teaching Hospital, Chengdu University of Traditional Chinese Medicine, 37# Shierqiao Road, Chengdu, 610075, Sichuan, China.,Acupuncture and Brain Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Zhaoxuan He
- Acupuncture and Tuina School, Acupuncture and Brain Research Center, The 3rd Teaching Hospital, Chengdu University of Traditional Chinese Medicine, 37# Shierqiao Road, Chengdu, 610075, Sichuan, China.,Acupuncture and Brain Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Peihong Ma
- Acupuncture and Tuina School, Acupuncture and Brain Research Center, The 3rd Teaching Hospital, Chengdu University of Traditional Chinese Medicine, 37# Shierqiao Road, Chengdu, 610075, Sichuan, China.,Acupuncture and Brain Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Shuai Yin
- First Affiliated Hospital of Henan University of Traditional Chinese Medicine, Zhengzhou, Henan Province, China
| | - Tao Yin
- Acupuncture and Tuina School, Acupuncture and Brain Research Center, The 3rd Teaching Hospital, Chengdu University of Traditional Chinese Medicine, 37# Shierqiao Road, Chengdu, 610075, Sichuan, China.,Acupuncture and Brain Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Xiaoyan Liu
- Acupuncture and Tuina School, Acupuncture and Brain Research Center, The 3rd Teaching Hospital, Chengdu University of Traditional Chinese Medicine, 37# Shierqiao Road, Chengdu, 610075, Sichuan, China.,Acupuncture and Brain Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Jin Lu
- Acupuncture and Tuina School, Acupuncture and Brain Research Center, The 3rd Teaching Hospital, Chengdu University of Traditional Chinese Medicine, 37# Shierqiao Road, Chengdu, 610075, Sichuan, China.,Acupuncture and Brain Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Yuzhu Qu
- First Affiliated Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Tingting Zhang
- Acupuncture and Tuina School, Acupuncture and Brain Research Center, The 3rd Teaching Hospital, Chengdu University of Traditional Chinese Medicine, 37# Shierqiao Road, Chengdu, 610075, Sichuan, China.,Acupuncture and Brain Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Liuyang Huang
- Acupuncture and Tuina School, Acupuncture and Brain Research Center, The 3rd Teaching Hospital, Chengdu University of Traditional Chinese Medicine, 37# Shierqiao Road, Chengdu, 610075, Sichuan, China.,Acupuncture and Brain Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Xueling Suo
- Departments of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Du Lei
- Departments of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Departments of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Fanrong Liang
- Acupuncture and Tuina School, Acupuncture and Brain Research Center, The 3rd Teaching Hospital, Chengdu University of Traditional Chinese Medicine, 37# Shierqiao Road, Chengdu, 610075, Sichuan, China. .,Acupuncture and Brain Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
| | - Fang Zeng
- Acupuncture and Tuina School, Acupuncture and Brain Research Center, The 3rd Teaching Hospital, Chengdu University of Traditional Chinese Medicine, 37# Shierqiao Road, Chengdu, 610075, Sichuan, China. .,Acupuncture and Brain Research Center, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
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50
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Suo X, Lei D, Li N, Li W, Kemp GJ, Sweeney JA, Peng R, Gong Q. Disrupted morphological grey matter networks in early-stage Parkinson's disease. Brain Struct Funct 2021; 226:1389-1403. [PMID: 33825053 PMCID: PMC8096749 DOI: 10.1007/s00429-020-02200-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 12/16/2020] [Indexed: 02/05/2023]
Abstract
While previous structural-covariance studies have an advanced understanding of brain alterations in Parkinson's disease (PD), brain–behavior relationships have not been examined at the individual level. This study investigated the topological organization of grey matter (GM) networks, their relation to disease severity, and their potential imaging diagnostic value in PD. Fifty-four early-stage PD patients and 54 healthy controls (HC) underwent structural T1-weighted magnetic resonance imaging. GM networks were constructed by estimating interregional similarity in the distributions of regional GM volume using the Kullback–Leibler divergence measure. Results were analyzed using graph theory and network-based statistics (NBS), and the relationship to disease severity was assessed. Exploratory support vector machine analyses were conducted to discriminate PD patients from HC and different motor subtypes. Compared with HC, GM networks in PD showed a higher clustering coefficient (P = 0.014) and local efficiency (P = 0.014). Locally, nodal centralities in PD were lower in postcentral gyrus and temporal-occipital regions, and higher in right superior frontal gyrus and left putamen. NBS analysis revealed decreased morphological connections in the sensorimotor and default mode networks and increased connections in the salience and frontoparietal networks in PD. Connection matrices and graph-based metrics allowed single-subject classification of PD and HC with significant accuracy of 73.1 and 72.7%, respectively, while graph-based metrics allowed single-subject classification of tremor-dominant and akinetic–rigid motor subtypes with significant accuracy of 67.0%. The topological organization of GM networks was disrupted in early-stage PD in a way that suggests greater segregation of information processing. There is potential for application to early imaging diagnosis.
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Affiliation(s)
- Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, PR China
| | - Du Lei
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, PR China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Nannan Li
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, PR China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, PR China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Rong Peng
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, No. 37 Guo Xue Xiang, Chengdu, 610041, PR China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China.
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
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