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Wei J, Li L, Zhang J, Shi E, Yang J, Liu X. Computational Modeling of the Prefrontal-Cingulate Cortex to Investigate the Role of Coupling Relationships for Balancing Emotion and Cognition. Neurosci Bull 2024:10.1007/s12264-024-01246-7. [PMID: 38869704 DOI: 10.1007/s12264-024-01246-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/11/2024] [Indexed: 06/14/2024] Open
Abstract
Within the prefrontal-cingulate cortex, abnormalities in coupling between neuronal networks can disturb the emotion-cognition interactions, contributing to the development of mental disorders such as depression. Despite this understanding, the neural circuit mechanisms underlying this phenomenon remain elusive. In this study, we present a biophysical computational model encompassing three crucial regions, including the dorsolateral prefrontal cortex, subgenual anterior cingulate cortex, and ventromedial prefrontal cortex. The objective is to investigate the role of coupling relationships within the prefrontal-cingulate cortex networks in balancing emotions and cognitive processes. The numerical results confirm that coupled weights play a crucial role in the balance of emotional cognitive networks. Furthermore, our model predicts the pathogenic mechanism of depression resulting from abnormalities in the subgenual cortex, and network functionality was restored through intervention in the dorsolateral prefrontal cortex. This study utilizes computational modeling techniques to provide an insight explanation for the diagnosis and treatment of depression.
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Affiliation(s)
- Jinzhao Wei
- Key Laboratory of Digital Medical Engineering of Hebei Province, Hebei University, Baoding, 071000, China
- College of Electronic Information Engineering, Hebei University, Baoding, 071000, China
| | - Licong Li
- Key Laboratory of Digital Medical Engineering of Hebei Province, Hebei University, Baoding, 071000, China.
- College of Electronic Information Engineering, Hebei University, Baoding, 071000, China.
| | - Jiayi Zhang
- Key Laboratory of Digital Medical Engineering of Hebei Province, Hebei University, Baoding, 071000, China
- College of Electronic Information Engineering, Hebei University, Baoding, 071000, China
| | - Erdong Shi
- Key Laboratory of Digital Medical Engineering of Hebei Province, Hebei University, Baoding, 071000, China
- College of Electronic Information Engineering, Hebei University, Baoding, 071000, China
| | - Jianli Yang
- Key Laboratory of Digital Medical Engineering of Hebei Province, Hebei University, Baoding, 071000, China
- College of Electronic Information Engineering, Hebei University, Baoding, 071000, China
| | - Xiuling Liu
- Key Laboratory of Digital Medical Engineering of Hebei Province, Hebei University, Baoding, 071000, China.
- College of Electronic Information Engineering, Hebei University, Baoding, 071000, China.
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Ysbæk-Nielsen AT. Exploring volumetric abnormalities in subcortical L-HPA axis structures in pediatric generalized anxiety disorder. Nord J Psychiatry 2024:1-9. [PMID: 38573199 DOI: 10.1080/08039488.2024.2335980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 03/22/2024] [Indexed: 04/05/2024]
Abstract
BACKGROUND Pediatric generalized anxiety disorder (GAD) is debilitating and increasingly prevalent, yet its etiology remains unclear. Some believe the disorder to be propagated by chronic dysregulation of the limbic-hypothalamic-pituitary-adrenal (L-HPA) axis, but morphometric studies of implicated subcortical areas have been largely inconclusive. Recognizing that certain subcortical subdivisions are more directly involved in L-HPA axis functioning, this study aims to detect specific abnormalities in these critical areas. METHODS Thirty-eight MRI scans of preschool children with (n = 15) and without (n = 23) GAD underwent segmentation and between-group volumetric comparisons of the basolateral amygdala (BLA), ventral hippocampal subiculum (vSC), and mediodorsal medial magnocellular (MDm) area of the thalamus. RESULTS Children with GAD displayed significantly larger vSC compared to healthy peers, F(1, 31) = 6.50, pFDR = .048. On average, children with GAD presented with larger BLA and MDm, Fs(1, 31) ≥ 4.86, psFDR ≤ .054. Exploratory analyses revealed right-hemispheric lateralization of all measures, most notably the MDm, F(1, 31) = 8.13, pFDR = .024, the size of which scaled with symptom severity, r = .83, pFDR = .033. CONCLUSION The BLA, vSC, and MDm are believed to be involved in the regulation of anxiety and stress, both individually and collectively through the excitation and inhibition of the L-HPA axis. All were found to be enlarged in children with GAD, perhaps reflecting hypertrophy related to hyperexcitability, or early neuronal overgrowth. Longitudinal studies should investigate the relationship between these early morphological differences and the long-term subcortical atrophy previously observed.
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Cardoner N, Andero R, Cano M, Marin-Blasco I, Porta-Casteràs D, Serra-Blasco M, Via E, Vicent-Gil M, Portella MJ. Impact of Stress on Brain Morphology: Insights into Structural Biomarkers of Stress-related Disorders. Curr Neuropharmacol 2024; 22:935-962. [PMID: 37403395 PMCID: PMC10845094 DOI: 10.2174/1570159x21666230703091435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/04/2023] [Accepted: 01/23/2023] [Indexed: 07/06/2023] Open
Abstract
Exposure to acute and chronic stress has a broad range of structural effects on the brain. The brain areas commonly targeted in the stress response models include the hippocampus, the amygdala, and the prefrontal cortex. Studies in patients suffering from the so-called stress-related disorders -embracing post-traumatic stress, major depressive and anxiety disorders- have fairly replicated animal models of stress response -particularly the neuroendocrine and the inflammatory models- by finding alterations in different brain areas, even in the early neurodevelopment. Therefore, this narrative review aims to provide an overview of structural neuroimaging findings and to discuss how these studies have contributed to our knowledge of variability in response to stress and the ulterior development of stress-related disorders. There are a gross number of studies available but neuroimaging research of stress-related disorders as a single category is still in its infancy. Although the available studies point at particular brain circuitries involved in stress and emotion regulation, the pathophysiology of these abnormalities -involving genetics, epigenetics and molecular pathways-, their relation to intraindividual stress responses -including personality characteristics, self-perception of stress conditions…-, and their potential involvement as biomarkers in diagnosis, treatment prescription and prognosis are discussed.
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Affiliation(s)
- Narcís Cardoner
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Raül Andero
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
- Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
- Departament de Psicobiologia i de Metodologia de les Ciències de la Salut, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Marta Cano
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Ignacio Marin-Blasco
- Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
| | - Daniel Porta-Casteràs
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Maria Serra-Blasco
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Programa eHealth ICOnnecta't, Institut Català d'Oncologia, Barcelona, Spain
| | - Esther Via
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
| | - Muriel Vicent-Gil
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Maria J. Portella
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
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Choi KS, Hwang I, Moon JH, Kim M. Progressive reduction in basal ganglia explains and predicts cerebral structural alteration in type 2 diabetes. J Cereb Blood Flow Metab 2023; 43:2096-2104. [PMID: 37632261 PMCID: PMC10925861 DOI: 10.1177/0271678x231197273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 06/21/2023] [Accepted: 07/03/2023] [Indexed: 08/27/2023]
Abstract
Type 2 diabetes is consistently reported to be associated with reduced gray matter, mainly in the cortical-striatal-limbic networks. However, little is known about how the progression of diabetes affects cerebral gray matter. To investigate, we collected 543 age- and sex-matched participants of nondiabetes, prediabetes, and diabetes. Voxel-based morphometry using a linear trend model was performed to reveal brain regions associated with disease progression. The Granger causal network of structural covariance was used to assess the causal relationships of brain structural alterations according to disease progression. Multivariate pattern analysis was applied for the stage-specific predictions of hyperglycemia. We detected a linear trend of gray matter volume reduction in the basal ganglia with disease progression (P < 0.05, FWER corrected), which caused a reduction in bilateral temporal gyri, frontal pole, parahippocampus, and bilateral posterior cingulate/precuneus volumes. In addition, the gray matter pattern of the basal ganglia could predict patients with diabetes (accuracy 60.12%, p = 0.002). In conclusion, the basal ganglia is the brain area with progressive gray matter reduction as diabetes progress. The reduced volume in the basal ganglia causes widespread gray matter reductions throughout diabetes progression. These findings indicate that the basal ganglia play a key role in diabetes by affecting the cortical-striatal-limbic network.
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Affiliation(s)
- Kyu Sung Choi
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, Seoul, Korea
| | - Joon Ho Moon
- Divison of Endocrinology & Metabolism, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Minchul Kim
- Department of Radiology, Kangnam Sacred Heart Hospital, Hallym University School of Medicine, Seoul, Korea
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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5
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Hamed A, Mohamed MF. A feature selection framework for anxiety disorder analysis using a novel multiview harris hawk optimization algorithm. Artif Intell Med 2023; 143:102605. [PMID: 37673574 DOI: 10.1016/j.artmed.2023.102605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 05/30/2023] [Accepted: 06/05/2023] [Indexed: 09/08/2023]
Abstract
Machine learning (ML) has demonstrated its ability to exploit important relationships within data collection, which can be used in the diagnosis, treatment, and prediction of outcomes in a variety of clinical contexts. Anxiety mental disorder analysis is one of the pending difficulties that ML can help with. A thorough study is demanded to gain a better understanding of this illness. Since the anxiety data is generally multidimensional, which complicates processing and as a result of technology improvements, medical data from several perspectives, known as multiview data (MVD), is being collected. Each view has its own data type and feature values, so there is a lot of diversity. This work introduces a novel preprocessing feature selection (FS) approach, multiview harris hawk optimization (MHHO), which has the potential to reduce the dimensionality of anxiety data, hence reducing analytical effort. The uniqueness of MHHO originates from combining a multiview linking methodology with the power of the harris hawk optimization (HHO) method. The HHO is used to identify the lowest optimal MVD feature subset, while multiview linking is utilized to find a promising fitness function to direct the HHO FS while accounting for all data views' heterogeneity. The complexity of MHHO is O(THL2), where T is the number of iterations, H is the number of involved harris hawks, and L is the number of objects. Using two publicly available anxiety MVDs, MHHO is validated against ten recent rivals in its category. The experimental findings show that MHHO has a considerable advantage in terms of convergence speed (converging in less than ten iterations), subset size (removing 75% of the views; reducing feature size by 66%), and classification accuracy (approaching 100%). Furthermore, statistical analyses reveal that MHHO is statistically different from its competitors, bolstering its applicability. Finally, feature importance is evaluated, shedding light on the most anxiety-inducing characteristics. The likelihood of developing additional disorders (such as depression or stress) is also investigated.
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Affiliation(s)
- Ahmed Hamed
- Department of Computer Science, Faculty of Computers and Information, Damanhour University, 22511, Damanhour, Egypt.
| | - Marwa F Mohamed
- Department of Computer Science, Faculty of Computers and Informatics, Suez Canal University, 41522, Ismailia, Egypt
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Zheng A, Chen X, Li Q, Ling Y, Liu X, Li W, Liu Y, Chen H. Neural correlates of Type A personality: Type A personality mediates the association of resting-state brain activity and connectivity with eating disorder symptoms. J Affect Disord 2023; 333:331-341. [PMID: 37086800 DOI: 10.1016/j.jad.2023.04.063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 04/05/2023] [Accepted: 04/16/2023] [Indexed: 04/24/2023]
Abstract
BACKGROUND Type A personality (TAP) was characterized by impatience, competitiveness, aggressiveness, and hostility. Higher TAP was proved to be associated with more eating disorder symptoms (EDS). While little is known about the underlying neural substrates of TAP and how TAP is linked to EDS at the neural level. METHODS To investigate the neural basis of TAP, we adopted fractional amplitude of low-frequency fluctuations (fALFF) and resting-state functional connectivity (RSFC) via resting-state functional magnetic resonance imaging (rs-fMRI) (N = 1620). Mediation models were examined to explore the relationship between TAP, EDS, and brain activity. RESULTS TAP was associated with decreased fALFF in the left middle frontal gyrus (MFG) and increased fALFF in the left precentral gyrus (PreCG). Furthermore, TAP was positively correlated to RSFC between the left MFG and left inferior temporal gyrus (ITG) and between the left PreCG and right middle temporal gyrus (MTG). Mediation analysis showed TAP fully mediated the association of the left MFG activity, MFG-ITG connectivity, and PreCG-MTG connectivity with EDS. LIMITATIONS The cross-sectional design of this study precludes us from specifying the causal relationship in the associations we observed. CONCLUSIONS Our results suggested spontaneous activity in the left MFG and PreCG is associated with TAP, and even in general sample, people with higher TAP showed more EDS. The present study is the first to investigate the neurobiological underpinnings of TAP in a large sample and further offered new insights into the relation between TAP and EDS from a neural basis perspective.
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Affiliation(s)
- Anqi Zheng
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Ximei Chen
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Qingqing Li
- School of Psychology, Central China Normal University, China
| | - Ying Ling
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Xinyuan Liu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Wei Li
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Yong Liu
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China
| | - Hong Chen
- Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing 400715, China; Faculty of Psychology, Southwest University, Chongqing 400715, China; Research Center of Psychology and Social Development, Chongqing 400715, China.
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Han S, Zheng R, Li S, Liu L, Wang C, Jiang Y, Wen M, Zhou B, Wei Y, Pang J, Li H, Zhang Y, Chen Y, Cheng J. Progressive brain structural abnormality in depression assessed with MR imaging by using causal network analysis. Psychol Med 2023; 53:2146-2155. [PMID: 34583785 DOI: 10.1017/s0033291721003986] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
BACKGROUND As a neuroprogressive illness, depression is accompanied by brain structural abnormality that extends to many brain regions. However, the progressive structural alteration pattern remains unknown. METHODS To elaborate the progressive structural alteration of depression according to illness duration, we recruited 195 never-treated first-episode patients with depression and 130 healthy controls (HCs) undergoing T1-weighted MRI scans. Voxel-based morphometry method was adopted to measure gray matter volume (GMV) for each participant. Patients were first divided into three stages according to the length of illness duration, then we explored stage-specific GMV alterations and the causal effect relationship between them using causal structural covariance network (CaSCN) analysis. RESULTS Overall, patients with depression presented stage-specific GMV alterations compared with HCs. Regions including the hippocampus, the thalamus and the ventral medial prefrontal cortex (vmPFC) presented GMV alteration at onset of illness. Then as the illness advanced, others regions began to present GMV alterations. These results suggested that GMV alteration originated from the hippocampus, the thalamus and vmPFC then expanded to other brain regions. The results of CaSCN analysis revealed that the hippocampus and the vmPFC corporately exerted causal effect on regions such as nucleus accumbens, the precuneus and the cerebellum. In addition, GMV alteration in the hippocampus was also potentially causally related to that in the dorsolateral frontal gyrus. CONCLUSIONS Consistent with the neuroprogressive hypothesis, our results reveal progressive morphological alteration originating from the vmPFC and the hippocampus and further elucidate possible details about disease progression of depression.
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Affiliation(s)
- Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Shuying Li
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Liang Liu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yu Jiang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Mengmeng Wen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jianyue Pang
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hengfen Li
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
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Yan H, Han Y, Shan X, Li H, Liu F, Xie G, Li P, Guo W. Common and exclusive spontaneous neural activity patterns underlying pure generalized anxiety disorder and comorbid generalized anxiety disorder and depression. J Affect Disord 2023; 331:82-91. [PMID: 36958484 DOI: 10.1016/j.jad.2023.03.047] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 03/05/2023] [Accepted: 03/16/2023] [Indexed: 03/25/2023]
Abstract
BACKGROUND This study aimed to identify common and exclusive neural substrates underlying pure generalized anxiety disorder (GAD, G0) and comorbid GAD and depression (G1), assess whether they could assist in diagnosis and prediction of treatment response, and determine whether comorbid depression in GAD patients would change their neural plasticity. METHODS A longitudinal study was conducted, involving 98 patients (40 in the G0 group and 58 in the G1 group) and 54 healthy controls (HCs). The fractional amplitude of low-frequency fluctuations (fALFF), support vector machine, and support vector regression were employed. RESULTS The shared neural underpinnings across the two subtypes of GAD were hyperactivity in the right cerebellar Crus II and inferior temporal gyrus and hypoactivity in the right postcentral gyrus. The G1 group showed hypoactivity in the frontal gyrus, compared with HCs, and hyperactivity in the middle temporal gyrus, compared with the G0 group or HCs. These alterations could aid in diagnosis and the prediction of treatment response with high accuracy. After treatment, both the G1 and G0 groups showed higher fALFF than those before treatment but were located in different brain regions. LIMITATIONS The study was performed in a single center and subjects showed a fairly homogeneous ethnicity. CONCLUSIONS Common and exclusive neural substrates underlying the two subtypes of GAD were identified, which could assist in diagnosis and the prediction of treatment response. Pharmacotherapy for the two subtypes of GAD recruited different pathways, suggesting that comorbid depression in GAD patients would change their neural plasticity.
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Affiliation(s)
- Haohao Yan
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Yiding Han
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Xiaoxiao Shan
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Huabing Li
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Guojun Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan 528000, Guangdong, China
| | - Ping Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang 161006, China
| | - Wenbin Guo
- Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China.
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9
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Fan YS, Xu Y, Li Q, Chen Y, Guo X, Yang S, Guo J, Sheng W, Wang C, Gao Q, Chen H. Systematically mapping gray matter abnormal patterns in drug-naïve first-episode schizophrenia from childhood to adolescence. Cereb Cortex 2023; 33:1452-1461. [PMID: 35396845 DOI: 10.1093/cercor/bhac148] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Schizophrenia originates early in neurodevelopment, underscoring the need to elaborate on anomalies in the still maturing brain of early-onset schizophrenia (EOS). METHODS Gray matter (GM) volumes were evaluated in 94 antipsychotic-naïve first-episode EOS patients and 100 typically developing (TD) controls. The anatomical profiles of changing GM deficits in EOS were detected using 2-way analyses of variance with diagnosis and age as factors, and its timing was further charted using stage-specific group comparisons. Interregional relationships of GM alterations were established using structural covariance network analyses. RESULTS Antagonistic interaction results suggested dynamic GM abnormalities of the left fusiform gyrus, inferior occipital gyrus, and lingual gyrus in EOS. These regions comprise a dominating part of the ventral stream, a ventral occipitotemporal (vOT) network engaged in early social information processing. GM abnormalities were mainly located in the vOT regions in childhood-onset patients, whereas in the rostral prefrontal cortex (rPFC) in adolescent-onset patients. Moreover, compared with TD controls, patients' GM synchronization with the ventral stream was disrupted in widespread high-order social perception regions including the rPFC and salience network. CONCLUSIONS The current findings reveal age-related anatomical abnormalities of the social perception system in pediatric patients with schizophrenia.
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Affiliation(s)
- Yun-Shuang Fan
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yong Xu
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan 030000, China
| | - Qiang Li
- Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University, Taiyuan 030000, China
| | - Yuyan Chen
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Xiaonan Guo
- School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China
| | - Siqi Yang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Jing Guo
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Wei Sheng
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Chong Wang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Qing Gao
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Huafu Chen
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China
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10
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Lu F, Cui Q, Chen Y, He Z, Sheng W, Tang Q, Yang Y, Luo W, Yu Y, Chen J, Li D, Deng J, Zeng Y, Chen H. Insular-associated causal network of structural covariance evaluating progressive gray matter changes in major depressive disorder. Cereb Cortex 2023; 33:831-843. [PMID: 35357431 DOI: 10.1093/cercor/bhac105] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 01/17/2022] [Accepted: 02/15/2022] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Morphometric studies demonstrated wide-ranging distribution of brain structural abnormalities in major depressive disorder (MDD). OBJECTIVE This study explored the progressive gray matter volume (GMV) changes pattern of structural network in 108 MDD patients throughout the illness duration by using voxel-based morphometric analysis. METHODS The causal structural covariance network method was applied to map the causal effects of GMV alterations between the original source of structural changes and other brain regions as the illness duration prolonged in MDD. This was carried out by utilizing the Granger causality analysis to T1-weighted data ranked based on the disease progression information. RESULTS With greater illness duration, the GMV reduction was originated from the right insula and progressed to the frontal lobe, and then expanded to the occipital lobe, temporal lobe, dorsal striatum (putamen and caudate) and the cerebellum. Importantly, results revealed that the right insula was the prominent node projecting positive causal influences (i.e., GMV decrease) to frontal lobe, temporal lobe, postcentral gyrus, putamen, and precuneus. While opposite causal effects were detected from the right insula to the angular, parahippocampus, supramarginal gyrus and cerebellum. CONCLUSIONS This work may provide further information and vital evidence showing that MDD is associated with progressive brain structural alterations.
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Affiliation(s)
- Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Yuyan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Wei Sheng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Qin Tang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Yang Yang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Wei Luo
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Yue Yu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Jiajia Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Di Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Jiaxin Deng
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Yuhong Zeng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, PR China.,MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, PR China
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11
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Cui Q, Chen Y, Tang Q, Sheng W, Li D, Zeng Y, Jiang K, He Z, Chen H. Neural mechanisms of aberrant self-referential processing in patients with generalized anxiety disorder. Prog Neuropsychopharmacol Biol Psychiatry 2022; 119:110595. [PMID: 35787397 DOI: 10.1016/j.pnpbp.2022.110595] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 06/07/2022] [Accepted: 06/27/2022] [Indexed: 10/17/2022]
Abstract
Massive theoretical studies in clinical psychology have implicated the self in understanding internalizing disorders (i.e., anxiety and mood disorders), in which self-related tasks were frequently used to investigate internalizing psychopathology. As one of the most frequently seen internalizing disorder in primary care, patients with generalized anxiety disorder (GAD) are characterized by inappropriate self-related processing such as negative self-referential thinking. However, relevant neural mechanisms remain unknown. In this study, participants underwent a self-related task which they were presented with several positive and negative trait words and were required to judge the extent to which these traits matched themselves when compared to their average peers. Aberrant brain activation and functional connectivity of GAD were detected during processing positive and negative traits. Compared to healthy controls (HCs), patients with GAD exhibited abnormal self-processing which manifested as lower biased self-rating scores particularly for negative traits and weaker brain activity in the left dorsomedial prefrontal cortex, inferior frontal gyrus, superior temporal sulcus (STS), and bilateral lingual gyrus when processing trait words. Abnormal functional connections between these hypoactive regions and regions associated with reward, emotion, and theory of mind were observed in subsequent psychophysiological interaction analysis. An attenuation of connectivity between the left insula and left STS was associated with greater severity of anxiety symptom in GAD patients. These findings provide insight into the abnormal neurocognitive mechanisms of biased self-related processing in GAD patients, which involves distorted self-schema accompanied by abnormal activation and functional connections of regions implicated in self-related and social cognition processing.
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Affiliation(s)
- Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuyan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Qin Tang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Wei Sheng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Di Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuhong Zeng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Kexing Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huafu Chen
- Department of Radiology, First Affiliated Hospital to Army Medical University, Chongqing, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.
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12
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Meng L, Zhang Y, Lin H, Mu J, Liao H, Wang R, Jiao S, Ma Z, Miao Z, Jiang W, Wang X. Abnormal hubs in global network as potential neuroimaging marker in generalized anxiety disorder at rest. Front Psychol 2022; 13:1075636. [PMID: 36591087 PMCID: PMC9801974 DOI: 10.3389/fpsyg.2022.1075636] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 11/29/2022] [Indexed: 12/23/2022] Open
Abstract
Background Mounting studies have reported altered neuroimaging features in generalized anxiety disorder (GAD). However, little is known about changes in degree centrality (DC) as an effective diagnostic method for GAD. Therefore, we aimed to explore the abnormality of DCs and whether these features can be used in the diagnosis of GAD. Methods Forty-one GAD patients and 45 healthy controls participated in the study. Imaging data were analyzed using DC and receiver operating characteristic (ROC) methods. Results Compared with the control group, increased DC values in bilateral cerebellum and left middle temporal gyrus (MTG), and decreased DC values in the left medial frontal orbital gyrus (MFOG), fusiform gyrus (FG), and bilateral posterior cingulate cortex (PCC). The ROC results showed that the DC value of the left MTG could serve as a potential neuroimaging marker with high sensitivity and specificity for distinguishing patients from healthy controls. Conclusion Our findings demonstrate that abnormal DCs in the left MTG can be observed in GAD, highlighting the importance of GAD pathophysiology.
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Affiliation(s)
- Lili Meng
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan, China,Department of Sleep, Wuhan Hospital for Psychotherapy, Wuhan, China
| | - Yuandong Zhang
- Clinical College, Wuhan University of Science and Technology, Wuhan, China
| | - Hang Lin
- Clinical College, Wuhan University of Science and Technology, Wuhan, China
| | - Jingping Mu
- Department of Mental Health, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Heng Liao
- Department of Mental Health, Taihe Hospital, Hubei University of Medicine, Shiyan, China
| | - Runlan Wang
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan, China,Department of Sleep, Wuhan Hospital for Psychotherapy, Wuhan, China
| | - Shufen Jiao
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan, China,Department of Sleep, Wuhan Hospital for Psychotherapy, Wuhan, China
| | - Zilong Ma
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan, China,Department of Sleep, Wuhan Hospital for Psychotherapy, Wuhan, China
| | - Zhuangzhuang Miao
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Jiang
- Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China,*Correspondence: Wei Jiang,
| | - Xi Wang
- Department of Mental Health, Taihe Hospital, Hubei University of Medicine, Shiyan, China,Xi Wang,
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13
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Liu X, Klugah-Brown B, Zhang R, Chen H, Zhang J, Becker B. Pathological fear, anxiety and negative affect exhibit distinct neurostructural signatures: evidence from psychiatric neuroimaging meta-analysis. Transl Psychiatry 2022; 12:405. [PMID: 36151073 PMCID: PMC9508096 DOI: 10.1038/s41398-022-02157-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 09/04/2022] [Accepted: 09/06/2022] [Indexed: 11/24/2022] Open
Abstract
Internalizing disorders encompass anxiety, fear and depressive disorders, which exhibit overlap at both conceptual and symptom levels. Given that a neurobiological evaluation is lacking, we conducted a Seed-based D-Mapping comparative meta-analysis including coordinates as well as original statistical maps to determine common and disorder-specific gray matter volume alterations in generalized anxiety disorder (GAD), fear-related anxiety disorders (FAD, i.e., social anxiety disorder, specific phobias, panic disorder) and major depressive disorder (MDD). Results showed that GAD exhibited disorder-specific altered volumes relative to FAD including decreased volumes in left insula and lateral/medial prefrontal cortex as well as increased right putamen volume. Both GAD and MDD showed decreased prefrontal volumes compared to controls and FAD. While FAD showed less robust alterations in lingual gyrus compared to controls, this group presented intact frontal integrity. No shared structural abnormalities were found. Our study is the first to provide meta-analytic evidence for distinct neuroanatomical abnormalities underlying the pathophysiology of anxiety-, fear-related and depressive disorders. These findings may have implications for determining promising target regions for disorder-specific neuromodulation interventions (e.g. transcranial magnetic stimulation or neurofeedback).
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Affiliation(s)
- Xiqin Liu
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Benjamin Klugah-Brown
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Ran Zhang
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Huafu Chen
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Jie Zhang
- grid.8547.e0000 0001 0125 2443Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, 200433 Shanghai, P. R. China ,grid.8547.e0000 0001 0125 2443Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, 200433 Shanghai, P. R. China
| | - Benjamin Becker
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731, Chengdu, P. R. China.
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14
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Effect of neurofeedback therapy on neurological post-COVID-19 complications (A pilot study). PLoS One 2022; 17:e0271350. [PMID: 35895740 PMCID: PMC9328527 DOI: 10.1371/journal.pone.0271350] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 06/28/2022] [Indexed: 11/19/2022] Open
Abstract
Objective
Anxiety, fatigue and depression are common neurological manifestations after COVID-19. So far, post-COVID complications were treated by rehabilitation, oxygen therapy and immunotherapy. Effects of neurofeedback on post-COVID complications and their potential interrelatedness have not been studied yet. In this pilot study, we investigated the effectiveness of neurofeedback (Othmer method) for treatment of fatigue, anxiety, and depression after COVID-19.
Methods
10 participants met inclusion criteria for having positive anamnesis of at least one of the following complications following COVID-19: fatigue, anxiety, and depression which were measured by questionnaires. ANOVA was used for calculating differences in questionnaire score before and after neurofeedback. Pearson’s correlation coefficient was used to calculate correlations between anxiety, depression and fatigue.
Results
After five neurofeedback sessions, there came to significant reduction of severity of post-COVID anxiety and depression persisting for at least one month. Effect of neurofeedback on fatigue was insignificant. Severity of anxiety, fatigue and depression as well as reductions in depression and fatigue were positively correlated with each other.
Conclusion
These findings showed effectiveness neurofeedback for reducing anxiety and depression after COVID-19 and for studying correlations between neurological complications after COVID-19. However, since our pilot clinical trial was open-label, it is hard to differentiate between neurofeedback-specific and unspecific effects on our participants. Future randomized controlled trials with more robust sample are necessary to investigate feasibility of neurofeedback for post-COVID neurological complications. The study has identification number trial ID ISRCTN49037874 in ISRCTN register of clinical trials (Retrospectively registered).
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15
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Zhang J, Liu Y, Guo X, Guo J, Du Z, He M, Liu Q, Xu D, Liu T, Zhang J, Yuan H, Wang M, Li S. Causal Structural Covariance Network Suggesting Structural Alterations Progression in Type 2 Diabetes Patients. Front Hum Neurosci 2022; 16:936943. [PMID: 35911591 PMCID: PMC9336220 DOI: 10.3389/fnhum.2022.936943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 06/16/2022] [Indexed: 12/02/2022] Open
Abstract
Background and Purpose According to reports, type 2 diabetes (T2D) is a progressive disease. However, no known research has examined the progressive brain structural changes associated with T2D. The purpose of this study was to determine whether T2D patients exhibit progressive brain structural alterations and, if so, how the alterations progress. Materials and Methods Structural magnetic resonance imaging scans were collected for 81 T2D patients and 48 sex-and age-matched healthy controls (HCs). Voxel-based morphometry (VBM) and causal structural covariance network (CaSCN) analyses were applied to investigate gray matter volume (GMV) alterations and the likely chronological processes underlying them in T2D. Two sample t-tests were performed to compare group differences, and the differences were corrected using Gaussian random field (GRF) correction (voxel-level p < 0.001, cluster-level p < 0.01). Results Our findings demonstrated that GMV alterations progressed in T2D patients as disease duration increased. In the early stages of the disease, the right temporal pole of T2D patients had GMV atrophy. As the diseases duration prolonged, the limbic system, cerebellum, subcortical structures, parietal cortex, frontal cortex, and occipital cortex progressively exhibited GMV alterations. The patients also exhibited a GMV alterations sequence exerting from the right temporal pole to the limbic-cerebellum-striatal-cortical network areas. Conclusion Our results indicate that the progressive GMV alterations of T2D patients manifested a limbic-cerebellum-striatal-cortical sequence. These findings may contribute to a better understanding of the progression and an improvement of current diagnosis and intervention strategies for T2D.
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Affiliation(s)
- Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Yuyan Liu
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Xiaonan Guo
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
- Hebei Key Laboratory of Information Transmission and Signal Processing, Yanshan University, Qinhuangdao, China
| | - Jing Guo
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhengcong Du
- School of Information Science and Technology, Xichang University, Xichang, China
| | - Muyuan He
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Qihong Liu
- College of Biomedical Engineering, Sichuan University, Chengdu, China
| | - Dundi Xu
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Taiyuan Liu
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
| | - Junran Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
- *Correspondence: Junran Zhang
| | - Huijuan Yuan
- Department of Endocrinology, Henan Provincial People's Hospital, Zhengzhou, China
- Huijuan Yuan
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
- Meiyun Wang
| | - Shasha Li
- The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
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16
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Loss of superiority illusion in bipolar depressive disorder: A combined functional and structural MRI study. J Psychiatr Res 2022; 151:391-398. [PMID: 35580402 DOI: 10.1016/j.jpsychires.2022.04.034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 04/02/2022] [Accepted: 04/25/2022] [Indexed: 11/23/2022]
Abstract
Superiority illusion (SI) is a positive cognitive bias related to self, manifested as overestimated self-appraisal. Negative self-schema is a core feature of the cognitive model of depression, including bipolar depressive disorder (BDD). However, only little research has explored the impaired self-processing in BDD. The potential alteration of positive self-bias and the corresponding neural mechanism in BDD remains unclear. This study aimed to investigate the underlying neural mechanism of self-processing in BDD combining task-related functional magnetic resonance imaging and high-resolution T1 structural imaging. Forty-three BDD and forty-eight healthy controls were recruited and underwent a self-related task, where participants were required to evaluate how they compared with their average peers on a serial of positive and negative traits. We defined the ratio of neural activation and gray matter volume (GMV) in a region as the functional-structural coupling index to detect the changes of brain image in BDD. Furthermore, we used moderation analysis to explore the relationship among functional-structural coupling, behavioral scores and depression symptoms. BDD exhibited decreased task activation, GMV, and functional-structural coupling in bilateral anterior insula (AI) and inferior parietal lobule (IPL). The associations between functional-structural coupling in the right AI, IPL and negative trait self-rating scores were moderated by depressive symptom severity. The study revealed disturbed self-related processing and provided new evidences to neuropsychological dysfunction in BDD.
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Bashford‐Largo J, Zhang R, Mathur A, Elowsky J, Schwartz A, Dobbertin M, Blair RJR, Blair KS, Bajaj S. Reduced cortical volume of the default mode network in adolescents with generalized anxiety disorder. Depress Anxiety 2022; 39:485-495. [PMID: 35312127 PMCID: PMC9246827 DOI: 10.1002/da.23252] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 03/03/2022] [Accepted: 03/06/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Widespread structural alterations have been shown to be implicated in individuals with generalized anxiety disorder (GAD). However, there have been inconsistent findings in cortical volume (CV) differences. Most structural neuroimaging studies looking at GAD used region-based approach with relatively small sample sizes, let alone be specific to adolescents with GAD. We believe this is the first study to look at CV measures using a network-based approach in a larger sample of adolescents with GAD. The goal of the current study was to focus on three different brain networks (i.e., Limbic, Frontoparietal, and Default Mode Network [DMN]) in adolescents with GAD. METHOD The study involved 81 adolescents with GAD and 112 typically developing (TD) comparison individuals matched on age (15.98 and 15.63 respective means), sex (42F/39M and 45F/67M), and IQ (101.90 and 103.94 respective means). Participants underwent structural MRI. Freesurfer was used to estimate CV (both network-specific and region-specific within networks) and region-specific sub-cortical volume measures. Multivariate analysis of covariance (MANCOVA; with sex, age, IQ, and intracranial volume [ICV] as potential covariates) was used to estimate group differences. RESULTS We found significantly lower CV for the DMN in adolescents with GAD, compared with TD individuals. Adolescents with GAD also showed significantly lower hemispheric mean CV of the default-mode regions (particularly the prefrontal and temporal regions) and the hippocampus, compared with TD individuals. CONCLUSION The current findings suggest structural alterations in adolescents with GAD. These structural alterations will need to be addressed when implementing and developing treatments for patients with GAD.
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Affiliation(s)
- Johannah Bashford‐Largo
- Multimodal Clinical Neuroimaging Laboratory (MCNL), Center for Neurobehavioral ResearchBoys Town National Research HospitalBoys TownNebraskaUSA,Center for Brain, Biology, and BehaviorUniversity of Nebraska‐LincolnLincolnNebraskaUSA
| | - Ru Zhang
- Multimodal Clinical Neuroimaging Laboratory (MCNL), Center for Neurobehavioral ResearchBoys Town National Research HospitalBoys TownNebraskaUSA
| | - Avantika Mathur
- Multimodal Clinical Neuroimaging Laboratory (MCNL), Center for Neurobehavioral ResearchBoys Town National Research HospitalBoys TownNebraskaUSA
| | - Jaimie Elowsky
- Multimodal Clinical Neuroimaging Laboratory (MCNL), Center for Neurobehavioral ResearchBoys Town National Research HospitalBoys TownNebraskaUSA
| | - Amanda Schwartz
- Department of PsychologyUniversity of North DakotaGrand ForksNorth DakotaUSA
| | - Matthew Dobbertin
- Inpatient Psychiatric Care UnitBoys Town National Research HospitalBoys TownNebraskaUSA
| | - Robert James R. Blair
- Child and Adolescent Mental Health Centre, Mental Health ServicesCapital Region of DenmarkCopenhagenDenmark
| | - Karina S. Blair
- Multimodal Clinical Neuroimaging Laboratory (MCNL), Center for Neurobehavioral ResearchBoys Town National Research HospitalBoys TownNebraskaUSA
| | - Sahil Bajaj
- Multimodal Clinical Neuroimaging Laboratory (MCNL), Center for Neurobehavioral ResearchBoys Town National Research HospitalBoys TownNebraskaUSA
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18
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Lin S, Guo Z, Chen S, Lin X, Ye M, Qiu Y. Progressive Brain Structural Impairment Assessed via Network and Causal Analysis in Patients With Hepatitis B Virus-Related Cirrhosis. Front Neurol 2022; 13:849571. [PMID: 35599731 PMCID: PMC9120530 DOI: 10.3389/fneur.2022.849571] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 04/12/2022] [Indexed: 12/03/2022] Open
Abstract
Objectives This research amid to elucidate the disease stage-specific spatial patterns and the probable sequences of gray matter (GM) deterioration as well as the causal relationship among structural network components in hepatitis B virus-related cirrhosis (HBV-RC) patients. Methods Totally 30 HBV-RC patients and 38 healthy controls (HC) were recruited for this study. High-resolution T1-weighted magnetic resonance imaging and psychometric hepatic encephalopathy score (PHES) were evaluated in all participants. Voxel-based morphometry (VBM), structural covariance network (SCN), and causal SCN (CaSCN) were applied to identify the disease stage-specific GM abnormalities in morphology and network, as well as their causal relationship. Results Compared to HC (0.443 ± 0.073 cm3), the thalamus swelled significantly in the no minimal hepatic encephalopathy (NMHE) stage (0.607 ± 0.154 cm3, p <0.05, corrected) and further progressed and expanded to the bilateral basal ganglia, the cortices, and the cerebellum in the MHE stage (p < 0.05, corrected). Furthermore, the thalamus swelling had a causal effect on other parts of cortex-basal ganglia-thalamus circuits (p < 0.05, corrected), which was negatively correlated with cognitive performance (r = −0.422, p < 0.05). Moreover, the thalamus-related SCN also displayed progressive deterioration as the disease advanced in HBV-RC patients (p < 0.05, corrected). Conclusion Progressive deterioration of GM morphology and SCN exists in HBV-RC patients during advanced disease, displaying thalamus-related causal effects. These findings indicate that bilateral thalamus morphology as well as the thalamus-related network may serve as an in vivo biomarker for monitoring the progression of the disease in HBV-RC patients.
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Affiliation(s)
- Shiwei Lin
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
- Department of Radiology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Zheng Guo
- Department of Radiology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Shengli Chen
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
- Department of Radiology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
| | - Xiaoshan Lin
- Department of Hematology and Oncology, International Cancer Center, Shenzhen Key Laboratory of Precision Medicine for Hematological Malignancies, Shenzhen University General Hospital, Shenzhen University Clinical Medical Academy, Shenzhen University Health Science Center, Shenzhen, China
| | - Min Ye
- Department of Geriatrics, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
- Department of Geriatrics, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, China
- *Correspondence: Min Ye
| | - Yingwei Qiu
- Department of Radiology, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China
- Yingwei Qiu
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19
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Mitrea L, Nemeş SA, Szabo K, Teleky BE, Vodnar DC. Guts Imbalance Imbalances the Brain: A Review of Gut Microbiota Association With Neurological and Psychiatric Disorders. Front Med (Lausanne) 2022; 9:813204. [PMID: 35433746 PMCID: PMC9009523 DOI: 10.3389/fmed.2022.813204] [Citation(s) in RCA: 72] [Impact Index Per Article: 36.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 02/23/2022] [Indexed: 12/12/2022] Open
Abstract
Over the last 10 years, there has been a growing interest in the relationship between gut microbiota, the brain, and neurologic-associated affections. As multiple preclinical and clinical research studies highlight gut microbiota’s potential to modulate the general state of health state, it goes without saying that gut microbiota plays a significant role in neurogenesis, mental and cognitive development, emotions, and behaviors, and in the progression of neuropsychiatric illnesses. Gut microbiota produces important biologic products that, through the gut-brain axis, are directly connected with the appearance and evolution of neurological and psychiatric disorders such as depression, anxiety, bipolar disorder, autism, schizophrenia, Parkinson’s disease, Alzheimer’s disease, dementia, multiple sclerosis, and epilepsy. This study reviews recent research on the link between gut microbiota and the brain, and microbiome’s role in shaping the development of the most common neurological and psychiatric illnesses. Moreover, special attention is paid to the use of probiotic formulations as a potential non-invasive therapeutic opportunity for prevention and management of neuropsychiatric-associated affections.
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Affiliation(s)
- Laura Mitrea
- Institute of Life Sciences, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Cluj-Napoca, Romania.,Faculty of Food Science and Technology, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Cluj-Napoca, Romania
| | - Silvia-Amalia Nemeş
- Institute of Life Sciences, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Cluj-Napoca, Romania.,Faculty of Food Science and Technology, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Cluj-Napoca, Romania
| | - Katalin Szabo
- Institute of Life Sciences, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Cluj-Napoca, Romania
| | - Bernadette-Emőke Teleky
- Institute of Life Sciences, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Cluj-Napoca, Romania
| | - Dan-Cristian Vodnar
- Institute of Life Sciences, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Cluj-Napoca, Romania.,Faculty of Food Science and Technology, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Cluj-Napoca, Romania
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20
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Han S, Zheng R, Li S, Zhou B, Jiang Y, Wang C, Wei Y, Pang J, Li H, Zhang Y, Chen Y, Cheng J. Integrative Functional, Molecular, and Transcriptomic Analyses of Altered Intrinsic Timescale Gradient in Depression. Front Neurosci 2022; 16:826609. [PMID: 35250462 PMCID: PMC8891525 DOI: 10.3389/fnins.2022.826609] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 01/10/2022] [Indexed: 12/13/2022] Open
Abstract
The pathophysiology and pharmacology of depression are hypothesized to be related to the imbalance of excitation–inhibition that gives rise to hierarchical dynamics (or intrinsic timescale gradient), further supporting a hierarchy of cortical functions. On this assumption, intrinsic timescale gradient is theoretically altered in depression. However, it remains unknown. We investigated altered intrinsic timescale gradient recently developed to measure hierarchical brain dynamics gradient and its underlying molecular architecture and brain-wide gene expression in depression. We first presented replicable intrinsic timescale gradient in two independent Chinese Han datasets and then investigated altered intrinsic timescale gradient and its possible underlying molecular and transcriptional bases in patients with depression. As a result, patients with depression showed stage-specifically shorter timescales compared with healthy controls according to illness duration. The shorter timescales were spatially correlated with monoamine receptor/transporter densities, suggesting the underlying molecular basis of timescale aberrance and providing clues to treatment. In addition, we identified that timescale aberrance-related genes ontologically enriched for synapse-related and neurotransmitter (receptor) terms, elaborating the underlying transcriptional basis of timescale aberrance. These findings revealed atypical timescale gradient in depression and built a link between neuroimaging, transcriptome, and neurotransmitter information, facilitating an integrative understanding of depression.
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Affiliation(s)
- Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- *Correspondence: Shaoqiang Han,
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Shuying Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yu Jiang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jianyue Pang
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hengfen Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Yuan Chen,
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China
- Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China
- Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China
- Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China
- Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
- Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
- Jingliang Cheng,
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21
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Shared and distinct changes in local dynamic functional connectivity patterns in major depressive and bipolar depressive disorders. J Affect Disord 2022; 298:43-50. [PMID: 34715198 DOI: 10.1016/j.jad.2021.10.109] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 09/13/2021] [Accepted: 10/23/2021] [Indexed: 12/22/2022]
Abstract
BACKGROUND Distinguishing bipolar depressive disorder (BDD) from major depressive disorder (MDD) solely relying on clinical clues is a challenge. Evidence in neuroimaging have revealed potential neurological markers for the differential diagnosis. METHODS We aimed to characterize common and specific alterations in the dynamic local functional connectivity pattern in BDD and MDD by using the dynamic regional phase synchrony (DRePS), a newly developed method for assessing intrinsic dynamic local functional connectivity. A total of 98 patients with MDD and 56 patients with BDD patients, and 97 age-, gender-, and education-matched healthy controls (HC) were included and underwent the resting-state functional magnetic resonance imaging. RESULTS Compared with HC, patients with two disorders shared decreased DRePS value in the bilateral orbitofrontal cortex (OFC) extends to insula, the right insula extends to hippocampus, the left hippocampus, the right inferior frontal gyrus (IFG), the left thalamus extends to caudate, the right caudate, the bilateral superior frontal gyrus (SFG), and the right medial frontal gyrus (MFG). Furthermore, patients with MDD exhibited specific decreased DRePS value in the left caudate. Moreover, voxel signals in these regions during the support vector machine analysis contributed to the classification of the two diagnoses. CONCLUSIONS Our findings provided new insight into the neural mechanism of patients with MDD and BDD and could potentially inform the diagnosis and the treatment of this disease.
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22
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Liu L, Liu J, Yang L, Wen B, Zhang X, Cheng J, Han S, Zhang Y, Cheng J. Accelerated Brain Aging in Patients With Obsessive-Compulsive Disorder. Front Psychiatry 2022; 13:852479. [PMID: 35599767 PMCID: PMC9120421 DOI: 10.3389/fpsyt.2022.852479] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 03/28/2022] [Indexed: 12/14/2022] Open
Abstract
Obsessive-compulsive disorder (OCD) may be accompanied by an accelerated structural decline of the brain with age compared to healthy controls (HCs); however, this has yet to be proven. To answer this question, we built a brain age prediction model using mean gray matter volumes of each brain region as features, which were obtained by voxel-based morphometry derived from T1-weighted MRI scans. The prediction model was built using two Chinese Han datasets (dataset 1, N = 106 for HCs and N = 90 for patients with OCD; dataset 2, N = 270 for HCs) to evaluate its performance. Then, a new prediction model was trained using data for HCs in dataset 1 and applied to patients with OCD to investigate the brain aging trajectory. The brain-predicted age difference (brain-PAD) scores, defined as the difference between predicted brain age and chronological age, were calculated for all participants and compared between patients with matched HCs in dataset 1. It was demonstrated that the prediction model performs consistently across different datasets. Patients with OCD presented higher brain-PAD scores than matched HCs, suggesting that patients with OCD presented accelerated brain aging. In addition, brain-PAD scores were negatively correlated with the duration of illness, suggesting that brain-PAD scores might capture progressive structural brain changes. These results identified accelerated brain aging in patients with OCD for the first time and deepened our understanding of the pathogenesis of OCD.
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Affiliation(s)
- Liang Liu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Junhong Liu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Li Yang
- Department of Public Health, School of Medicine, Huanghuai University, Zhumadian, China
| | - Baohong Wen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaopan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Junying Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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23
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Chen Y, Cui Q, Sheng W, Tang Q, Lu F, Pang Y, Nan X, He Z, Li D, Lei T, Chen H. Anomalous neurovascular coupling in patients with generalized anxiety disorder evaluated by combining cerebral blood flow and functional connectivity strength. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110379. [PMID: 34111495 DOI: 10.1016/j.pnpbp.2021.110379] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Revised: 05/06/2021] [Accepted: 06/04/2021] [Indexed: 01/10/2023]
Abstract
Coupling between neuronal activity and blood perfusion is termed neurovascular coupling, and it provides a new mechanistic perspective into understanding numerous brain diseases. Although abnormal brain activity and blood supply have been separately reported in generalized anxiety disorder (GAD), whether anomalous neurovascular coupling would still be presented in such disease is hitherto unknown. In this study, the neuronal activity and blood supply were measured using the functional connectivity strength (FCS) and cerebral blood flow (CBF). The voxel-wise CBF-FCS correlations and CBF/FCS ratio were separately used to assess global and local neurovascular coupling in participants. Patients with GAD showed decreased voxel-wise CBF-FCS correlation, implicating global neurovascular decoupling. They also exhibited increased CBF/FCS ratio in the right superior parietal gyrus (SPG), and the enhanced CBF/FCS ratio in this region was negatively correlated with the self-esteem scores of GAD. The abnormal neurovascular coupling of GAD may indicate the disrupted balance between the intrinsic functional organization of the brain and corresponding blood perfusion of patients, and the abnormally increased local neurovascular coupling of the right SPG may be correlated with the abnormal self in GAD. These findings provide new information in understanding the brain dysfunction and abnormal cognition of GAD from the perspective of neurovascular coupling.
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Affiliation(s)
- Yuyan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qian Cui
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China.
| | - Wei Sheng
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qin Tang
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yajing Pang
- School of Electrical Engineering, Zhengzhou University, Zhengzhou, China
| | - Xiaoyu Nan
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Di Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ting Lei
- School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China; Department of Radiology, First Affiliated Hospital to Army Medical University, Chongqing, China.
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24
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Gut microbiome diversity mediates the association between right dorsolateral prefrontal cortex and anxiety level. Brain Imaging Behav 2021; 16:397-405. [PMID: 34554317 DOI: 10.1007/s11682-021-00513-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/16/2021] [Indexed: 12/14/2022]
Abstract
Despite the fast growing interest in the impact of microbiome-gut-brain interaction on regulating emotional behavior in animals, the underlying mechanisms on how brain anatomy together with gut microbiotic condition jointly influence emotional state in healthy human volunteers remain largely unknown and hypothetic. Here, high-resolution structural magnetic resonance imaging data, stool samples, and psychological assessment results on anxiety level were collected from 61 healthy adults. Voxel-based morphometry was used to assess gray matter (GM) volumes, whereas 16s rRNA gene sequencing was used for bacterial classification. Correlation and mediation analysis were conducted to quantify the relationships among regional GM volume, gut microbiome diversity, and anxiety level. We observed that anxiety level was negatively correlated with GM volume in the right dorsolateral prefrontal cortex and alpha diversity index of gut microbiome. Additional mediation analysis revealed the indirect effect of dorsolateral prefrontal cortex GM volume on anxiety level via gut microbiome diversity. Our findings provide potential evidence of the microbiome-gut-brain interactions and their association with anxiety, highlighting gut microbiome diversity as a mediator that influences the relationship between brain morphometry and anxiety level.
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Xie S, Zhang X, Cheng W, Yang Z. Adolescent anxiety disorders and the developing brain: comparing neuroimaging findings in adolescents and adults. Gen Psychiatr 2021; 34:e100411. [PMID: 34423252 PMCID: PMC8340272 DOI: 10.1136/gpsych-2020-100411] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 06/21/2021] [Indexed: 02/07/2023] Open
Abstract
Adolescence is the peak period for the incidence of anxiety disorders. Recent findings have revealed the immaturity of neural networks underlying emotional regulation in this population. Brain vulnerability to anxiety in adolescence is related to the unsynchronised development of anxiety-relevant brain functional systems. However, our current knowledge on brain deficits in adolescent anxiety is mainly borrowed from studies on adults. Understanding adolescent-specific brain deficits is essential for developing biomarkers and brain-based therapies targeting adolescent anxiety. This article reviews and compares recent neuroimaging literature on anxiety-related brain structural and functional deficits between adolescent and adult populations, and proposes a model highlighting the differences between adolescence and adulthood in anxiety-related brain networks. This model emphasises that in adolescence the emotional control system tends to be hypoactivated, the fear conditioning system is immature, and the reward and stress response systems are hypersensitive. Furthermore, the striatum’s functional links to the amygdala and the prefrontal cortex are strengthened, while the link between the prefrontal cortex and the amygdala is weakened in adolescence. This model helps to explain why adolescents are vulnerable to anxiety disorders and provides insights into potential brain-based approaches to intervene in adolescent anxiety disorders.
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Affiliation(s)
- Shuqi Xie
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaochen Zhang
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wenhong Cheng
- Department of Child and Adolescent Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Psychological Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhi Yang
- Laboratory of Psychological Health and Imaging, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Institute of Psychological and Behavioral Sciences, Shanghai Jiao Tong University, Shanghai, China
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26
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Zhang F, Wang S, Feng Y, Qin K, Li H, Wu B, Jia Z, Gong Q. Regional gray matter volume associated with exercise dependence: A voxel-based morphometry study. Hum Brain Mapp 2021; 42:4857-4868. [PMID: 34236128 PMCID: PMC8449116 DOI: 10.1002/hbm.25585] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 06/07/2021] [Accepted: 06/26/2021] [Indexed: 02/05/2023] Open
Abstract
Although regular physical exercise has multiple positive benefits for the general population, excessive exercise may lead to exercise dependence (EXD), which is harmful to one's physical and mental health. Increasing evidence suggests that stress is a potential risk factor for the onset and development of EXD. However, little is known about the neural substrates of EXD and the underlying neuropsychological mechanism by which stress affects EXD. Herein, we investigate these issues in 86 individuals who exercise regularly by estimating their cortical gray matter volume (GMV) utilizing a voxel‐based morphometry method based on structural magnetic resonance imaging. Whole‐brain correlation analyses and prediction analyses showed negative relationships between EXD and GMV of the right orbitofrontal cortex (OFC), left subgenual cingulate gyrus (sgCG), and left inferior parietal lobe (IPL). Furthermore, mediation analyses found that the GMV of the right OFC was an important mediator between stress and EXD. Importantly, these results remained significant even when adjusting for sex, age, body mass index, family socioeconomic status, general intelligence and total intracranial volume, as well as depression and anxiety. Collectively, the results of the present study provide crucial evidence of the neuroanatomical basis of EXD and reveal a potential neuropsychological pathway in predicting EXD in which GMV mediates the relationship between stress and EXD.
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Affiliation(s)
- Feifei Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, China.,Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Yang Feng
- Huaxi MR Research Center (HMRRC), Department of Radiology, 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, China
| | - Huiru Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Baolin Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Zhiyun Jia
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, China.,Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
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27
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Guo X, Duan X, Suckling J, Wang J, Kang X, Chen H, Biswal BB, Cao J, He C, Xiao J, Huang X, Wang R, Han S, Fan YS, Guo J, Zhao J, Wu L, Chen H. Mapping Progressive Gray Matter Alterations in Early Childhood Autistic Brain. Cereb Cortex 2021; 31:1500-1510. [PMID: 33123725 DOI: 10.1093/cercor/bhaa304] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 09/09/2020] [Accepted: 09/14/2020] [Indexed: 12/16/2022] Open
Abstract
Autism spectrum disorder is an early-onset neurodevelopmental condition. This study aimed to investigate the progressive structural alterations in the autistic brain during early childhood. Structural magnetic resonance imaging scans were examined in a cross-sectional sample of 67 autistic children and 63 demographically matched typically developing (TD) children, aged 2-7 years. Voxel-based morphometry and a general linear model were used to ascertain the effects of diagnosis, age, and a diagnosis-by-age interaction on the gray matter volume. Causal structural covariance network analysis was performed to map the interregional influences of brain structural alterations with increasing age. The autism group showed spatially distributed increases in gray matter volume when controlling for age-related effects, compared with TD children. A significant diagnosis-by-age interaction effect was observed in the fusiform face area (FFA, Fpeak = 13.57) and cerebellum/vermis (Fpeak = 12.73). Compared with TD children, the gray matter development of the FFA in autism displayed altered influences on that of the social brain network regions (false discovery rate corrected, P < 0.05). Our findings indicate the atypical neurodevelopment of the FFA in the autistic brain during early childhood and highlight altered developmental effects of this region on the social brain network.
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Affiliation(s)
- Xiaonan Guo
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Xujun Duan
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - John Suckling
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge CB21 5EF, UK
| | - Jia Wang
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin 150086, China
| | - Xiaodong Kang
- Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCM, Sichuan Bayi Rehabilitation Center, Chengdu 611135, China
| | - Heng Chen
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.,School of Medicine, Guizhou University, Guiyang 550025, China
| | - Bharat B Biswal
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA
| | - Jing Cao
- Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCM, Sichuan Bayi Rehabilitation Center, Chengdu 611135, China
| | - Changchun He
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Jinming Xiao
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Xinyue Huang
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Runshi Wang
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Shaoqiang Han
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Yun-Shuang Fan
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Jing Guo
- MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
| | - Jingping Zhao
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha 410011, China
| | - Lijie Wu
- Department of Children's and Adolescent Health, Public Health College of Harbin Medical University, Harbin 150086, China
| | - Huafu Chen
- Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 611731, China.,MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
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