1
|
Cao P, Li Y, Dong Y, Tang Y, Xu G, Si Q, Chen C, Yao Y, Li R, Sui Y. Different structural connectivity patterns in the subregions of the thalamus, hippocampus, and cingulate cortex between schizophrenia and psychotic bipolar disorder. J Affect Disord 2024; 363:269-281. [PMID: 39053628 DOI: 10.1016/j.jad.2024.07.077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 06/25/2024] [Accepted: 07/14/2024] [Indexed: 07/27/2024]
Abstract
OBJECTIVE Schizophrenia (SCZ) and psychotic bipolar disorder (PBD) are two major psychotic disorders with similar symptoms and tight associations on the psychopathological level, posing a clinical challenge for their differentiation. This study aimed to investigate and compare the structural connectivity patterns of the limbic system between SCZ and PBD, and to identify specific regional disruptions associated with psychiatric symptoms. METHODS Using sMRI data from 146 SCZ, 160 PBD, and 145 healthy control (HC) participants, we employed a data-driven approach to segment the hippocampus, thalamus, hypothalamus, amygdala, and cingulate cortex into subregions. We then investigated the structural connectivity patterns between these subregions at the global and nodal levels. Additionally, we assessed psychotic symptoms by utilizing the subscales of the Brief Psychiatric Rating Scale (BPRS) to examine correlations between symptom severity and network metrics between groups. RESULTS Patients with SCZ and PBD had decreased global efficiency (Eglob) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.003), local efficiency (Eloc) (SCZ and PBD: adjusted P<0.001), and clustering coefficient (Cp) (SCZ and PBD: adjusted P<0.001), and increased path length (Lp) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.004) compared to HC. Patients with SCZ showed more pronounced decreases in Eglob (adjusted P<0.001), Eloc (adjusted P<0.001), and Cp (adjusted P = 0.029), and increased Lp (adjusted P = 0.024) compared to patients with PBD. The most notable structural disruptions were observed in the hippocampus and thalamus, which correlated with different psychotic symptoms, respectively. CONCLUSION This study provides evidence of distinct structural connectivity disruptions in the limbic system of patients with SCZ and PBD. These findings might contribute to our understanding of the neuropathological basis for distinguishing SCZ and PBD.
Collapse
Affiliation(s)
- Peiyu Cao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Yuting Li
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China; Huzhou Third People's Hospital, Huzhou 313000, Zhejiang, China
| | - Yingbo Dong
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Yilin Tang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Guoxin Xu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Qi Si
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China; Huai'an No. 3 People's Hospital, Huai'an 223001, Jiangsu, China
| | - Congxin Chen
- Women's Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing 210000, Jiangsu, China
| | - Ye Yao
- Nanjing Medical University, Nanjing 210000, Jiangsu, China
| | - Runda Li
- Vanderbilt University, Nashville 37240, TN, USA
| | - Yuxiu Sui
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China.
| |
Collapse
|
2
|
Jing Y, Liu Y, Zhou Y, Li M, Gao Y, Zhang B, Li J. Inflammation-related abnormal dynamic brain activity correlates with cognitive impairment in first-episode, drug-naïve major depressive disorder. J Affect Disord 2024; 366:217-225. [PMID: 39197551 DOI: 10.1016/j.jad.2024.08.165] [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: 04/28/2024] [Revised: 07/22/2024] [Accepted: 08/23/2024] [Indexed: 09/01/2024]
Abstract
BACKGROUND Cognitive impairment is common in major depressive disorder (MDD) and potentially linked to inflammation-induced alterations in brain function. However, the relationship between inflammation, dynamic brain activity, and cognitive impairment in MDD remains unclear. METHODS Fifty-seven first-episode, drug-naïve MDD patients and sixty healthy controls underwent fMRI scanning. Dynamic amplitude of low-frequency fluctuations (dALFF) and dynamic functional connectivity (dFC) were measured using the sliding window method. Plasma IL - 6 levels and cognitive function were assessed using enzyme-linked immunosorbent assay (ELISA) and the Repeated Battery for Assessment of Neuropsychological Status (RBANS), respectively. RESULTS MDD patients exhibited decreased dALFF in the bilateral inferior temporal gyrus (ITG), right inferior frontal gyrus, opercular part (IFGoperc), and bilateral middle occipital gyrus (MOG). Regions of dALFF associated with IL-6 included right ITG (r = -0.400/p = 0.003), left ITG (r = -0.381/p = 0.004), right IFGoperc (r = -0.342/p = 0.011), and right MOG (r = -0.327/p = 0.016). Furthermore, IL-6-related abnormal dALFF (including right ITG: r = 0.309/p = 0.023, left ITG: r = 0.276/p = 0.044) was associated with attention impairment. These associations were absent entirely in MDD patients without suicidal ideation. Additionally, IL-6 levels were correlated with dFC of specific brain regions. LIMITATIONS Small sample size and cross-sectional study design. CONCLUSIONS Inflammation-related dALFF was associated with attention impairment in MDD patients, with variations observed among MDD subgroups. These findings contribute to the understanding of the intricate relationship between inflammation, dynamic brain activity and cognitive impairments in MDD.
Collapse
Affiliation(s)
- Yifan Jing
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Yuan Liu
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Yuwen Zhou
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Meijuan Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Ying Gao
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Bin Zhang
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Jie Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China.
| |
Collapse
|
3
|
Gencheva TM, Valkov BV, Kandilarova SS, Maes MHJ, Stoyanov DS. Diagnostic value of structural, functional and effective connectivity in bipolar disorder. Acta Psychiatr Scand 2024. [PMID: 39137928 DOI: 10.1111/acps.13742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 07/25/2024] [Accepted: 07/26/2024] [Indexed: 08/15/2024]
Abstract
INTRODUCTION The aim of this systematic review is to assess the functional magnetic resonance imaging (fMRI) studies of bipolar disorder (BD) patients that characterize differences in terms of structural, functional, and effective connectivity between the patients with BD, patients with other psychiatric disorders and healthy controls as possible biomarkers for diagnosing the disorder using neuroimaging. METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), guidelines a systematic search for recent (since 2015) original studies on connectivity in bipolar disorder was conducted in PUBMED and SCOPUS. RESULTS A total of 60 studies were included in this systematic review: 20 of the structural connectivity, 33 of the functional connectivity, and only 7 of the studies focused on effective connectivity complied with the inclusion and exclusion criteria. DISCUSSION Despite the great heterogeneity in the findings, there are several trends that emerge. In structural connectivity studies, the main abnormalities in bipolar disorder patients were in the frontal gyrus, anterior, as well as posterior cingulate cortex and differences in emotion and reward-related networks. Cerebellum (vermis) to cerebrum functional connectivity was found to be the most common finding in BD. Moreover, prefrontal cortex and amygdala connectivity as part of the rich-club hubs were often reported to be disrupted. The most common findings based on effective connectivity were alterations in salience network, default mode network and executive control network. Although more studies with larger sample sizes are needed to ascertain altered brain connectivity as diagnostic biomarker, there is a perspective that the method could be used as a single marker of diagnosis in the future, and the process of adoption could be accelerated by using approaches such as semiunsupervised machine learning.
Collapse
Affiliation(s)
| | - Bozhidar V Valkov
- Faculty of Medicine, Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Sevdalina S Kandilarova
- Department of Psychiatry and Medical Psychology, and Research Institute, Medical University of Plovdiv, Plovdiv, Bulgaria
- Research and Innovation Program for the Development of MU - PLOVDIV - (SRIPD-MUP), Creation of a Network of Research Higher Schools, National Plan For Recovery and Sustainability, European Union - NextGenerationEU, Plovdiv, Bulgaria
| | - Michael H J Maes
- Department of Psychiatry and Medical Psychology, and Research Institute, Medical University of Plovdiv, Plovdiv, Bulgaria
- Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
- Research and Innovation Program for the Development of MU - PLOVDIV - (SRIPD-MUP), Creation of a Network of Research Higher Schools, National Plan For Recovery and Sustainability, European Union - NextGenerationEU, Plovdiv, Bulgaria
| | - Drozdstoy S Stoyanov
- Department of Psychiatry and Medical Psychology, and Research Institute, Medical University of Plovdiv, Plovdiv, Bulgaria
- Research and Innovation Program for the Development of MU - PLOVDIV - (SRIPD-MUP), Creation of a Network of Research Higher Schools, National Plan For Recovery and Sustainability, European Union - NextGenerationEU, Plovdiv, Bulgaria
| |
Collapse
|
4
|
Shang T, Chen Y, Ding Z, Qin W, Li S, Wei S, Ding Z, Yang X, Qi J, Qin X, Lv D, Li T, Pan Z, Zhan C, Xiao J, Sun Z, Wang N, Yu Z, Li C, Li P. Altered dynamic neural activities in individuals with obsessive-compulsive disorder and comorbid depressive symptoms. Front Psychiatry 2024; 15:1403933. [PMID: 39176228 PMCID: PMC11339690 DOI: 10.3389/fpsyt.2024.1403933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Accepted: 06/19/2024] [Indexed: 08/24/2024] Open
Abstract
Objectives Depressive symptoms are the most prevalent comorbidity in individuals with obsessive-compulsive disorder (OCD). The objective of this study was to investigate the dynamic characteristics of resting-state neural activities in OCD patients with depressive symptoms. Methods We recruited 29 OCD patients with depressive symptoms, 21 OCD patients without depressive symptoms, and 27 healthy controls, and collected data via structural and functional magnetic resonance imaging (fMRI). We analyzed the fMRI results using the dynamic amplitude of low-frequency fluctuation (dALFF) and support vector machine (SVM) techniques. Results Compared with OCD patients without depressive symptoms, OCD patients with depressive symptoms exhibited an increased dALFF in the left precuneus and decreased dALFF in the right medial frontal gyrus. The SVM indicated that the integration of aberrant dALFF values in the left precuneus and right medial frontal gyrus led to an overall accuracy of 80%, a sensitivity of 79%, and a specificity of 100% in detecting depressive symptoms among OCD patients. Conclusion Therefore, our study reveals that OCD patients with depressive symptoms display neural activities with unique dynamic characteristics in the resting state. Accordingly, abnormal dALFF values in the left precuneus and right medial frontal gyrus could be used to identify depressive symptoms in OCD patients.
Collapse
Affiliation(s)
- Tinghuizi Shang
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Yunhui Chen
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Zhenning Ding
- Medical Imaging Department, Qingdao Mental Health Center, Qingdao, Shandong, China
| | - Weiqi Qin
- The Second Affiliated Hospital, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Shancong Li
- The Second Affiliated Hospital, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Siyi Wei
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Zhipeng Ding
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Xu Yang
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Jiale Qi
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Xiaoqing Qin
- Medical Technology Department, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Dan Lv
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Tong Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Zan Pan
- Infection Control Department, Harbin Puning Hospital, Harbin, Heilongjiang, China
| | - Chuang Zhan
- Department of Psychiatry, Baiyupao Psychiatric Hospital of Harbin, Harbin, Heilongjiang, China
| | - Jian Xiao
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Zhenghai Sun
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Na Wang
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Zengyan Yu
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Chengchong Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| | - Ping Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, China
| |
Collapse
|
5
|
Pan N, Qin K, Patino LR, Tallman MJ, Lei D, Lu L, Li W, Blom TJ, Bruns KM, Welge JA, Strawn JR, Gong Q, Sweeney JA, Singh MK, DelBello MP. Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task-based fMRI connectome study. J Child Psychol Psychiatry 2024; 65:1072-1086. [PMID: 38220469 PMCID: PMC11246494 DOI: 10.1111/jcpp.13946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/26/2023] [Indexed: 01/16/2024]
Abstract
BACKGROUND Youth with a family history of bipolar disorder (BD) may be at increased risk for mood disorders and for developing side effects after antidepressant exposure. The neurobiological basis of these risks remains poorly understood. We aimed to identify biomarkers underlying risk by characterizing abnormalities in the brain connectome of symptomatic youth at familial risk for BD. METHODS Depressed and/or anxious youth (n = 119, age = 14.9 ± 1.6 years) with a family history of BD but no prior antidepressant exposure and typically developing controls (n = 57, age = 14.8 ± 1.7 years) received functional magnetic resonance imaging (fMRI) during an emotional continuous performance task. A generalized psychophysiological interaction (gPPI) analysis was performed to compare their brain connectome patterns, followed by machine learning of topological metrics. RESULTS High-risk youth showed weaker connectivity patterns that were mainly located in the default mode network (DMN) (network weight = 50.1%) relative to controls, and connectivity patterns derived from the visual network (VN) constituted the largest proportion of aberrant stronger pairs (network weight = 54.9%). Global local efficiency (Elocal, p = .022) and clustering coefficient (Cp, p = .029) and nodal metrics of the right superior frontal gyrus (SFG) (Elocal: p < .001; Cp: p = .001) in the high-risk group were significantly higher than those in healthy subjects, and similar patterns were also found in the left insula (degree: p = .004; betweenness: p = .005; age-by-group interaction, p = .038) and right hippocampus (degree: p = .003; betweenness: p = .003). The case-control classifier achieved a cross-validation accuracy of 78.4%. CONCLUSIONS Our findings of abnormal connectome organization in the DMN and VN may advance mechanistic understanding of risk for BD. Neuroimaging biomarkers of increased network segregation in the SFG and altered topological centrality in the insula and hippocampus in broader limbic systems may be used to target interventions tailored to mitigate the underlying risk of brain abnormalities in these at-risk youth.
Collapse
Affiliation(s)
- Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Kun Qin
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Luis R. Patino
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Maxwell J. Tallman
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Du Lei
- College of Medical Informatics, Chongqing Medical University, Chongqing, China
| | - Lu Lu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Thomas J. Blom
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Kaitlyn M. Bruns
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Jeffrey A. Welge
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Jeffrey R. Strawn
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
| | - John A. Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences; Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Department of Psychiatry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Manpreet K. Singh
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, California, USA
| | | |
Collapse
|
6
|
Zhu QQ, Tian S, Zhang L, Ding HY, Gao YX, Tang Y, Yang X, Zhu Y, Qi M. Altered dynamic amplitude of low-frequency fluctuation in individuals at high risk for Alzheimer's disease. Eur J Neurosci 2024; 59:2391-2402. [PMID: 38314647 DOI: 10.1111/ejn.16267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 01/12/2024] [Accepted: 01/14/2024] [Indexed: 02/06/2024]
Abstract
The brain's dynamic spontaneous neural activity is significant in supporting cognition; however, how brain dynamics go awry in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains unclear. Thus, the current study aimed to investigate the dynamic amplitude of low-frequency fluctuation (dALFF) alterations in patients at high risk for Alzheimer's disease and to explore its correlation with clinical cognitive assessment scales, to identify an early imaging sign for these special populations. A total of 152 participants, including 72 SCD patients, 44 MCI patients and 36 healthy controls (HCs), underwent a resting-state functional magnetic resonance imaging and were assessed with various neuropsychological tests. The dALFF was measured using sliding-window analysis. We employed canonical correlation analysis (CCA) to examine the bi-multivariate correlations between neuropsychological scales and altered dALFF among multiple regions in SCD and MCI patients. Compared to those in the HC group, both the MCI and SCD groups showed higher dALFF values in the right opercular inferior frontal gyrus (voxel P < .001, cluster P < .05, correction). Moreover, the CCA models revealed that behavioural tests relevant to inattention correlated with the dALFF of the right middle frontal gyrus and right opercular inferior frontal gyrus, which are involved in frontoparietal networks (R = .43, P = .024). In conclusion, the brain dynamics of neural activity in frontal areas provide insights into the shared neural basis underlying SCD and MCI.
Collapse
Affiliation(s)
- Qin-Qin Zhu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shui Tian
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ling Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hong-Yuan Ding
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ya-Xin Gao
- Rehabilitation Center, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Yin Tang
- Department of Medical imaging, Jingjiang People's Hospital, Jingjiang, China
| | - Xi Yang
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
| | - Yi Zhu
- Rehabilitation Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ming Qi
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| |
Collapse
|
7
|
Sun H, Yan R, Hua L, Xia Y, Chen Z, Huang Y, Wang X, Xia Q, Yao Z, Lu Q. Abnormal stability of spontaneous neuronal activity as a predictor of diagnosis conversion from major depressive disorder to bipolar disorder. J Psychiatr Res 2024; 171:60-68. [PMID: 38244334 DOI: 10.1016/j.jpsychires.2024.01.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 01/10/2024] [Accepted: 01/15/2024] [Indexed: 01/22/2024]
Abstract
OBJECTIVE Bipolar disorder (BD) is often misdiagnosed as major depressive disorder (MDD) in the early stage, which may lead to inappropriate treatment. This study aimed to characterize the alterations of spontaneous neuronal activity in patients with depressive episodes whose diagnosis transferred from MDD to BD. METHODS 532 patients with MDD and 132 healthy controls (HCs) were recruited over 10 years. During the follow-up period, 75 participants with MDD transferred to BD (tBD), and 157 participants remained with the diagnosis of unipolar depression (UD). After excluding participants with poor image quality and excessive head movement, 68 participants with the diagnosis of tBD, 150 participants with the diagnosis of UD, and 130 HCs were finally included in the analysis. The dynamic amplitude of low-frequency fluctuations (dALFF) of spontaneous neuronal activity was evaluated in tBD, UD and HC using functional magnetic resonance imaging at study inclusion. Receiver operating characteristic (ROC) analysis was performed to evaluate sensitivity and specificity of the conversion prediction from MDD to BD based on dALFF. RESULTS Compared to HC, tBD exhibited elevated dALFF at left premotor cortex (PMC_L), right lateral temporal cortex (LTC_R) and right early auditory cortex (EAC_R), and UD showed reduced dALFF at PMC_L, left paracentral lobule (PCL_L), bilateral medial prefrontal cortex (mPFC), right orbital frontal cortex (OFC_R), right dorsolateral prefrontal cortex (DLPFC_R), right posterior cingulate cortex (PCC_R) and elevated dALFF at LTC_R. Furthermore, tBD exhibited elevated dALFF at PMC_L, PCL_L, bilateral mPFC, bilateral OFC, DLPFC_R, PCC_R and LTC_R than UD. In addition, ROC analysis based on dALFF in differential areas obtained an area under the curve (AUC) of 72.7%. CONCLUSIONS The study demonstrated the temporal dynamic abnormalities of tBD and UD in the critical regions of the somatomotor network (SMN), default mode network (DMN), and central executive network (CEN). The differential abnormal patterns of temporal dynamics between the two diseases have the potential to predict the diagnosis transition from MDD to BD.
Collapse
Affiliation(s)
- Hao Sun
- Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Rui Yan
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Lingling Hua
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Yi Xia
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Zhilu Chen
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Yinghong Huang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Xiaoqin Wang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Qiudong Xia
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Zhijian Yao
- Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China; School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, 210096, China.
| | - Qing Lu
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, 210096, China.
| |
Collapse
|
8
|
Cui L, Li S, Wang S, Wu X, Liu Y, Yu W, Wang Y, Tang Y, Xia M, Li B. Major depressive disorder: hypothesis, mechanism, prevention and treatment. Signal Transduct Target Ther 2024; 9:30. [PMID: 38331979 PMCID: PMC10853571 DOI: 10.1038/s41392-024-01738-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 12/24/2023] [Accepted: 12/28/2023] [Indexed: 02/10/2024] Open
Abstract
Worldwide, the incidence of major depressive disorder (MDD) is increasing annually, resulting in greater economic and social burdens. Moreover, the pathological mechanisms of MDD and the mechanisms underlying the effects of pharmacological treatments for MDD are complex and unclear, and additional diagnostic and therapeutic strategies for MDD still are needed. The currently widely accepted theories of MDD pathogenesis include the neurotransmitter and receptor hypothesis, hypothalamic-pituitary-adrenal (HPA) axis hypothesis, cytokine hypothesis, neuroplasticity hypothesis and systemic influence hypothesis, but these hypothesis cannot completely explain the pathological mechanism of MDD. Even it is still hard to adopt only one hypothesis to completely reveal the pathogenesis of MDD, thus in recent years, great progress has been made in elucidating the roles of multiple organ interactions in the pathogenesis MDD and identifying novel therapeutic approaches and multitarget modulatory strategies, further revealing the disease features of MDD. Furthermore, some newly discovered potential pharmacological targets and newly studied antidepressants have attracted widespread attention, some reagents have even been approved for clinical treatment and some novel therapeutic methods such as phototherapy and acupuncture have been discovered to have effective improvement for the depressive symptoms. In this work, we comprehensively summarize the latest research on the pathogenesis and diagnosis of MDD, preventive approaches and therapeutic medicines, as well as the related clinical trials.
Collapse
Affiliation(s)
- Lulu Cui
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Shu Li
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Siman Wang
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Xiafang Wu
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Yingyu Liu
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Weiyang Yu
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Yijun Wang
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China
- China Medical University Centre of Forensic Investigation, Shenyang, China
| | - Yong Tang
- International Joint Research Centre on Purinergic Signalling/Key Laboratory of Acupuncture for Senile Disease (Chengdu University of TCM), Ministry of Education/School of Health and Rehabilitation, Chengdu University of Traditional Chinese Medicine/Acupuncture and Chronobiology Key Laboratory of Sichuan Province, Chengdu, China
| | - Maosheng Xia
- Department of Orthopaedics, The First Hospital, China Medical University, Shenyang, China.
| | - Baoman Li
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China.
- Liaoning Province Key Laboratory of Forensic Bio-evidence Sciences, Shenyang, China.
- China Medical University Centre of Forensic Investigation, Shenyang, China.
| |
Collapse
|
9
|
Cattarinussi G, Di Giorgio A, Moretti F, Bondi E, Sambataro F. Dynamic functional connectivity in schizophrenia and bipolar disorder: A review of the evidence and associations with psychopathological features. Prog Neuropsychopharmacol Biol Psychiatry 2023; 127:110827. [PMID: 37473954 DOI: 10.1016/j.pnpbp.2023.110827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 06/05/2023] [Accepted: 07/10/2023] [Indexed: 07/22/2023]
Abstract
Alterations of functional network connectivity have been implicated in the pathophysiology of schizophrenia (SCZ) and bipolar disorder (BD). Recent studies also suggest that the temporal dynamics of functional connectivity (dFC) can be altered in these disorders. Here, we summarized the existing literature on dFC in SCZ and BD, and their association with psychopathological and cognitive features. We systematically searched PubMed, Web of Science, and Scopus for studies investigating dFC in SCZ and BD and identified 77 studies. Our findings support a general model of dysconnectivity of dFC in SCZ, whereas a heterogeneous picture arose in BD. Although dFC alterations are more severe and widespread in SCZ compared to BD, dysfunctions of a triple network system underlying goal-directed behavior and sensory-motor networks were present in both disorders. Furthermore, in SCZ, positive and negative symptoms were associated with abnormal dFC. Implications for understanding the pathophysiology of disorders, the role of neurotransmitters, and treatments on dFC are discussed. The lack of standards for dFC metrics, replication studies, and the use of small samples represent major limitations for the field.
Collapse
Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Italy; Padova Neuroscience Center, University of Padova, Italy
| | - Annabella Di Giorgio
- Department of Mental Health and Addictions, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Federica Moretti
- Department of Medicine and Surgery, University of Milan Bicocca, Milan, Italy
| | - Emi Bondi
- Department of Mental Health and Addictions, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Italy; Padova Neuroscience Center, University of Padova, Italy.
| |
Collapse
|
10
|
Wu J, Qi S, Yu W, Gao Y, Ma J. Regional Homogeneity of the Left Posterior Cingulate Gyrus May Be a Potential Imaging Biomarker of Manic Episodes in First-Episode, Drug-Naive Bipolar Disorder. Neuropsychiatr Dis Treat 2023; 19:2775-2785. [PMID: 38106358 PMCID: PMC10725752 DOI: 10.2147/ndt.s441021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 12/07/2023] [Indexed: 12/19/2023] Open
Abstract
Introduction Abnormal brain networks with emotional response in bipolar disorder (BD). However, there have been few studies on the local consistency between manic episodes in drug-naive first-episode BD patients and healthy controls (HCs). The purpose of this study is to evaluate the utility of neural activity values analyzed by Regional Homogeneity (ReHo). Methods Thirty-seven manic episodes in first-episode, drug-naive BD patients and 37 HCs participated in resting-state functional magnetic resonance rescanning and scale estimation. Reho and receiver operating characteristic (ROC) curve methods were used to analyze the imaging data. Support vector machine (SVM) method was used to analyze ReHo in different brain regions. Results Compared to HCs, ReHo increased in the left middle temporal gyrus (MTG.L), posterior cingulate gyrus (PCG), inferior parietal gyrus, and bilateral angular gyrus, and decreased in the left dorsolateral superior frontal gyrus in target group. The ROC results showed that the ReHo value of the left PCG could discriminate the target group from the HCs, and the AUC was 0.8766. In addition, the results of the support vector machine show that the increase in ReHo value in the left PCG can effectively discriminate the patients from the controls, with accuracy, sensitivity, and specificity of 86.02%, 86.49%, and 81.08%, respectively. Conclusion The increased activity of the left PCG may contribute new evidence of participation in the pathophysiology of manic episodes in first-episode, drug-naive BD patients. The Reho value of the left posterior cingulate gyrus may be a potential neuroimaging biomarker to discriminate target group from HCs.
Collapse
Affiliation(s)
- Jiajia Wu
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan, People’s Republic of China
- Wuhan Hospital for Psychotherapy, Wuhan, People’s Republic of China
| | - Shuangyu Qi
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan, People’s Republic of China
- Wuhan Hospital for Psychotherapy, Wuhan, People’s Republic of China
| | - Wei Yu
- Department of Psychiatry, Xianning Bode Mental Hospital, Xianning, People’s Republic of China
| | - Yujun Gao
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China
| | - Jun Ma
- Department of Psychiatry, Wuhan Mental Health Center, Wuhan, People’s Republic of China
- Wuhan Hospital for Psychotherapy, Wuhan, People’s Republic of China
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China
| |
Collapse
|
11
|
Jiang W, Liu J, Zhou J, Wu Q, Pu X, Chen H, Xu X, Wu F, Hu H. Altered dynamic brain activity and functional connectivity in thyroid-associated ophthalmopathy. Hum Brain Mapp 2023; 44:5346-5356. [PMID: 37515416 PMCID: PMC10543102 DOI: 10.1002/hbm.26437] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/18/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
Although previous neuroimaging evidence has confirmed the brain functional disturbances in thyroid-associated ophthalmopathy (TAO), the dynamic characteristics of brain activity and functional connectivity (FC) in TAO were rarely concerned. The present study aims to investigate the alterations of temporal variability of brain activity and FC in TAO using resting-state functional magnetic resonance imaging (rs-fMRI). Forty-seven TAO patients and 30 age-, gender-, education-, and handedness-matched healthy controls (HCs) were enrolled and underwent rs-fMRI scanning. The dynamic amplitude of low-frequency fluctuation (dALFF) was first calculated using a sliding window approach to characterize the temporal variability of brain activity. Based on the dALFF results, seed-based dynamic functional connectivity (dFC) analysis was performed to identify the temporal variability of efficient communication between brain regions in TAO. Additionally, correlations between dALFF and dFC and the clinical indicators were analyzed. Compared with HCs, TAO patients displayed decreased dALFF in the left superior occipital gyrus (SOG) and cuneus (CUN), while showing increased dALFF in the left triangular part of inferior frontal gyrus (IFGtriang), insula (INS), orbital part of inferior frontal gyrus (ORBinf), superior temporal gyrus (STG) and temporal pole of superior temporal gyrus (TPOsup). Furthermore, TAO patients exhibited decreased dFC between the left STG and the right middle occipital gyrus (MOG), as well as decreased dFC between the left TPOsup and the right calcarine fissure and surrounding cortex (CAL) and MOG. Correlation analyses showed that the altered dALFF in the left SOG/CUN was positively related to visual acuity (r = .409, p = .004), as well as the score of QoL for visual functioning (r = .375, p = .009). TAO patients developed abnormal temporal variability of brain activity in areas related to vision, emotion, and cognition, as well as reduced temporal variability of FC associated with vision deficits. These findings provided additional insights into the neurobiological mechanisms of TAO.
Collapse
Affiliation(s)
- Wen‐Hao Jiang
- Department of RadiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Jun Liu
- Department of RadiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Jiang Zhou
- Department of RadiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Qian Wu
- Department of RadiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Xiong‐Ying Pu
- Department of RadiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Huan‐Huan Chen
- Department of EndocrinologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Xiao‐Quan Xu
- Department of RadiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Fei‐Yun Wu
- Department of RadiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| | - Hao Hu
- Department of RadiologyThe First Affiliated Hospital of Nanjing Medical UniversityNanjingChina
| |
Collapse
|
12
|
Gai Q, Chu T, Che K, Li Y, Dong F, Zhang H, Li Q, Ma H, Shi Y, Zhao F, Liu J, Mao N, Xie H. Classification of Major Depressive Disorder Based on Integrated Temporal and Spatial Functional MRI Variability Features of Dynamic Brain Network. J Magn Reson Imaging 2023; 58:827-837. [PMID: 36579618 DOI: 10.1002/jmri.28578] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 12/13/2022] [Accepted: 12/13/2022] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Characterization of the dynamics of functional brain network has gained increased attention in the study of depression. However, most studies have focused on single temporal dimension, while ignoring spatial dimensional information, hampering the discovery of validated biomarkers for depression. PURPOSE To integrate temporal and spatial functional MRI variability features of dynamic brain network in machine-learning techniques to distinguish patients with major depressive disorder (MDD) from healthy controls (HCs). STUDY TYPE Prospective. POPULATION A discovery cohort including 119 patients and 106 HCs and an external validation cohort including 126 patients and 124 HCs from Rest-meta-MDD consortium. FIELD STRENGTH/SEQUENCE A 3.0 T/resting-state functional MRI using the gradient echo sequence. ASSESSMENT A random forest (RF) model integrating temporal and spatial variability features of dynamic brain networks with separate feature selection method (MSFS ) was implemented for MDD classification. Its performance was compared with three RF models that used: temporal variability features (MTVF ), spatial variability features (MSVF ), and integrated temporal and spatial variability features with hybrid feature selection method (MHFS ). A linear regression model based on MSFS was further established to assess MDD symptom severity, with prediction performance evaluated by the correlations between true and predicted scores. STATISTICAL TESTS Receiver operating characteristic analyses with the area under the curve (AUC) were used to evaluate models' performance. Pearson's correlation was used to assess relationship of predicted scores and true scores. P < 0.05 was considered statistically significant. RESULTS The model with MSFS achieved the best performance, with AUCs of 0.946 and 0.834 in the discovery and validation cohort, respectively. Additionally, altered temporal and spatial variability could significantly predict the severity of depression (r = 0.640) and anxiety (r = 0.616) in MDD. DATA CONCLUSION Integration of temporal and spatial variability features provides potential assistance for clinical diagnosis and symptom prediction of MDD. EVIDENCE LEVEL 2. TECHNICAL EFFICACY Stage 2.
Collapse
Affiliation(s)
- Qun Gai
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
| | - Tongpeng Chu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
- Big Data & Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
| | - Kaili Che
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
| | - Yuna Li
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
| | - Fanghui Dong
- School of Medical Imaging, Binzhou Medical University, Yantai, Shandong, People's Republic of China
| | - Haicheng Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
- Big Data & Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
| | - Qinghe Li
- School of Medical Imaging, Binzhou Medical University, Yantai, Shandong, People's Republic of China
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
| | - Yinghong Shi
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
| | - Feng Zhao
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, Shandong, People's Republic of China
| | - Jing Liu
- Department of Pediatrics, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
- Big Data & Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
| | - Haizhu Xie
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, People's Republic of China
| |
Collapse
|
13
|
Zhang G, Xiao Q, Wang C, Gao W, Su L, Lu G, Zhong Y. The Different Impact of Depressive or Manic First-episode on Pediatric Bipolar Disorder Patients: Evidence From Resting-state fMRI. Neuroscience 2023; 526:185-195. [PMID: 37385333 DOI: 10.1016/j.neuroscience.2023.06.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 06/14/2023] [Accepted: 06/16/2023] [Indexed: 07/01/2023]
Abstract
Bipolar disorder may begin as depression or mania, which can affect the treatment and prognosis of bipolar disorder. However, the physiological and pathological differences of pediatric bipolar disorder (PBD) patients with different onset symptoms are not clear. The purpose of this study was to investigate the differences of clinical, cognitive function and intrinsic brain networks in PBD patients with first-episode depression and first-episode mania. A total of 63 participants, including 43 patients and 20 healthy controls, underwent resting-state fMRI scans. PBD patients were classified as first-episode depressive and first-episode manic based on their first-episode symptoms. Cognitive tests were used to measure attention and memory of all participants. Independent component analysis (ICA) was used to extract the salience network (SN), default-mode network (DMN), central executive network (ECN) and limbic network (LN) for each participant. Spearman rank correlation analysis was performed between abnormal activation and clinical and cognitive measures. The results showed that there were differences in cognitive functions such as attention and visual memory between first-episode depression and mania, as well as differences activation in anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), precuneus, inferior parietal cortex and parahippocampus. And significant associations of brain activity with clinical assessments or cognition were found in different patients. In conclusion, we found differential impairments in cognitive and brain network activation in first-episode depressive and first-episode manic PBD patients, and correlations were found between these impairments. These evidences may shed light on the different developmental paths of bipolar disorder.
Collapse
Affiliation(s)
- Gui Zhang
- School of Psychology, Nanjing Normal University, Nanjing 210097, China
| | - Qian Xiao
- Mental Health Centre of Xiangya Hospital, Central South University, Changsha 410008, Hunan, China
| | - Chun Wang
- Department of Psychiatry, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Weijia Gao
- Children's Hospital affiliated to the Medical College of Zhejiang University, Hangzhou 310003, Zhejiang, China
| | - Linyan Su
- Second Xiangya Hospital of Central South University, Changsha 410011, Hunan, China
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, 210093 Nanjing, Jiangsu, China
| | - Yuan Zhong
- School of Psychology, Nanjing Normal University, Nanjing 210097, China.
| |
Collapse
|
14
|
Long Y, Liu X, Liu Z. Temporal Stability of the Dynamic Resting-State Functional Brain Network: Current Measures, Clinical Research Progress, and Future Perspectives. Brain Sci 2023; 13:brainsci13030429. [PMID: 36979239 PMCID: PMC10046056 DOI: 10.3390/brainsci13030429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 02/20/2023] [Accepted: 02/28/2023] [Indexed: 03/06/2023] Open
Abstract
Based on functional magnetic resonance imaging and multilayer dynamic network model, the brain network’s quantified temporal stability has shown potential in predicting altered brain functions. This manuscript aims to summarize current knowledge, clinical research progress, and future perspectives on brain network’s temporal stability. There are a variety of widely used measures of temporal stability such as the variance/standard deviation of dynamic functional connectivity strengths, the temporal variability, the flexibility (switching rate), and the temporal clustering coefficient, while there is no consensus to date which measure is the best. The temporal stability of brain networks may be associated with several factors such as sex, age, cognitive functions, head motion, circadian rhythm, and data preprocessing/analyzing strategies, which should be considered in clinical studies. Multiple common psychiatric disorders such as schizophrenia, major depressive disorder, and bipolar disorder have been found to be related to altered temporal stability, especially during the resting state; generally, both excessively decreased and increased temporal stabilities were thought to reflect disorder-related brain dysfunctions. However, the measures of temporal stability are still far from applications in clinical diagnoses for neuropsychiatric disorders partly because of the divergent results. Further studies with larger samples and in transdiagnostic (including schizoaffective disorder) subjects are warranted.
Collapse
|
15
|
Chen B, Yang M, Zhong X, Wang Q, Zhou H, Liu M, Zhang M, Hou L, Wu Z, Zhang S, Lin G, Ning Y. Disrupted dynamic functional connectivity of hippocampal subregions mediated the slowed information processing speed in late-life depression. Psychol Med 2023; 53:1-11. [PMID: 36803969 PMCID: PMC10600940 DOI: 10.1017/s0033291722003786] [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: 02/27/2022] [Revised: 10/11/2022] [Accepted: 11/29/2022] [Indexed: 02/22/2023]
Abstract
BACKGROUND Slowed information processing speed (IPS) is the core contributor to cognitive impairment in patients with late-life depression (LLD). The hippocampus is an important link between depression and dementia, and it may be involved in IPS slowing in LLD. However, the relationship between a slowed IPS and the dynamic activity and connectivity of hippocampal subregions in patients with LLD remains unclear. METHODS One hundred thirty-four patients with LLD and 89 healthy controls were recruited. Sliding-window analysis was used to assess whole-brain dynamic functional connectivity (dFC), dynamic fractional amplitude of low-frequency fluctuations (dfALFF) and dynamic regional homogeneity (dReHo) for each hippocampal subregion seed. RESULTS Cognitive impairment (global cognition, verbal memory, language, visual-spatial skill, executive function and working memory) in patients with LLD was mediated by their slowed IPS. Compared with the controls, patients with LLD exhibited decreased dFC between various hippocampal subregions and the frontal cortex and decreased dReho in the left rostral hippocampus. Additionally, most of the dFCs were negatively associated with the severity of depressive symptoms and were positively associated with various domains of cognitive function. Moreover, the dFC between the left rostral hippocampus and middle frontal gyrus exhibited a partial mediation effect on the relationships between the scores of depressive symptoms and IPS. CONCLUSIONS Patients with LLD exhibited decreased dFC between the hippocampus and frontal cortex, and the decreased dFC between the left rostral hippocampus and right middle frontal gyrus was involved in the underlying neural substrate of the slowed IPS.
Collapse
Affiliation(s)
- Ben Chen
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Mingfeng Yang
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Xiaomei Zhong
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Qiang Wang
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Huarong Zhou
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Meiling Liu
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Min Zhang
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Le Hou
- Department of Neurology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Zhangying Wu
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Si Zhang
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Gaohong Lin
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
| | - Yuping Ning
- Center for Geriatric Neuroscience, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, Guangdong Province, China
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong Province, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| |
Collapse
|
16
|
Keller AS, Sydnor VJ, Pines A, Fair DA, Bassett DS, Satterthwaite TD. Hierarchical functional system development supports executive function. Trends Cogn Sci 2023; 27:160-174. [PMID: 36437189 PMCID: PMC9851999 DOI: 10.1016/j.tics.2022.11.005] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/01/2022] [Accepted: 11/03/2022] [Indexed: 11/26/2022]
Abstract
In this perspective, we describe how developmental improvements in youth executive function (EF) are supported by hierarchically organized maturational changes in functional brain systems. We first highlight evidence that functional brain systems are embedded within a hierarchical sensorimotor-association axis of cortical organization. We then review data showing that functional system developmental profiles vary along this axis: systems near the associative end become more functionally segregated, while those in the middle become more integrative. Developmental changes that strengthen the hierarchical organization of the cortex may support EF by facilitating top-down information flow and balancing within- and between-system communication. We propose a central role for attention and frontoparietal control systems in the maturation of healthy EF and suggest that reduced functional system differentiation across the sensorimotor-association axis contributes to transdiagnostic EF deficits.
Collapse
Affiliation(s)
- Arielle S Keller
- Penn Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA
| | - Dani S Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA; Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute, Children's Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
| |
Collapse
|
17
|
Zhong X, Chen B, Hou L, Wang Q, Liu M, Yang M, Zhang M, Zhou H, Wu Z, Zhang S, Lin G, Ning Y. Shared and specific dynamics of brain activity and connectivity in amnestic and nonamnestic mild cognitive impairment. CNS Neurosci Ther 2022; 28:2053-2065. [PMID: 35975454 PMCID: PMC9627396 DOI: 10.1111/cns.13937] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 07/25/2022] [Accepted: 07/26/2022] [Indexed: 02/06/2023] Open
Abstract
AIMS The present study aimed to compare temporal variability in the spontaneous fluctuations of activity and connectivity between amnestic MCI (aMCI) and nonamnestic MCI (naMCI), which enhances the understanding of their different pathophysiologies and provides targets for individualized intervention. METHODS Sixty-five naMCI and 48 aMCI subjects and 75 healthy controls were recruited. A sliding window analysis was used to evaluate the dynamic amplitude of low-frequency fluctuations (dALFF), dynamic regional homogeneity (dReHo), and dynamic functional connectivity (dFC). The caudal/rostral hippocampus was selected as the seeds for calculating dFC. RESULTS Both aMCI and naMCI exhibited abnormal dALFF, dReHo, and hippocampal dFC compared with healthy controls. Compared with individuals with naMCI, those with aMCI exhibited (1) higher dALFF variability in the right putamen, left Rolandic operculum, and right middle cingulum, (2) lower dReHo variability in the right superior parietal lobule, and (3) lower dFC variability between the hippocampus and other regions (left superior occipital gyrus, middle frontal gyrus, inferior cerebellum, precuneus, and right superior frontal gyrus). Additionally, variability in dALFF, dReHo, and hippocampal dFC exhibited different associations with cognitive scores in aMCI and naMCI patients, respectively. Finally, dReHo variability in the right superior parietal lobule and dFC variability between the right caudal hippocampus and left inferior cerebellum exhibited partially mediated effects on the different memory scores between people with aMCI and naMCI. CONCLUSION The aMCI and naMCI patients exhibited shared and specific patterns of dynamic brain activity and connectivity. The dReHo of the superior parietal lobule and dFC of the hippocampus-cerebellum contributed to the memory heterogeneity of MCI subtypes. Analyzing the temporal variability in the spontaneous fluctuations of brain activity and connectivity provided a new perspective for exploring the different pathophysiological mechanisms in MCI subtypes.
Collapse
Affiliation(s)
- Xiaomei Zhong
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
| | - Ben Chen
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
| | - Le Hou
- Department of NeurologyThe Affiliated Brain Hospital of Guangzhou Medical UniversityGuangzhouGuangdong ProvinceChina
| | - Qiang Wang
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
- Department of Geriatric PsychiatryThe Second People's Hospital of Dali Bai Autonomous PrefectureDaliYunnan ProvinceChina
| | - Meiling Liu
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
| | - Mingfeng Yang
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
| | - Min Zhang
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
| | - Huarong Zhou
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
| | - Zhangying Wu
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
| | - Si Zhang
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
| | - Gaohong Lin
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
| | - Yuping Ning
- Center for Geriatric NeuroscienceThe Affiliated Brain Hospital of Guangzhou Medical University, Memory ClinicGuangzhouGuangdong ProvinceChina
- The First School of Clinical Medicine, Southern Medical UniversityGuangzhouGuangdong ProvinceChina
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental DisordersGuangzhouChina
| |
Collapse
|
18
|
Liu D, Liu X, Long Y, Xiang Z, Wu Z, Liu Z, Bian D, Tang S. Problematic smartphone use is associated with differences in static and dynamic brain functional connectivity in young adults. Front Neurosci 2022; 16:1010488. [PMID: 36340758 PMCID: PMC9635624 DOI: 10.3389/fnins.2022.1010488] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 10/07/2022] [Indexed: 11/17/2022] Open
Abstract
Introduction This study aimed to investigate the possible associations between problematic smartphone use and brain functions in terms of both static and dynamic functional connectivity patterns. Materials and methods Resting-state functional magnetic resonance imaging data were scanned from 53 young healthy adults, all of whom completed the Short Version of the Smartphone Addiction Scale (SAS-SV) to assess their problematic smartphone use severity. Both static and dynamic functional brain network measures were evaluated for each participant. The brain network measures were correlated the SAS-SV scores, and compared between participants with and without a problematic smartphone use after adjusting for sex, age, education, and head motion. Results Two participants were excluded because of excessive head motion, and 56.9% (29/51) of the final analyzed participants were found to have a problematic smartphone use (SAS-SV scores ≥ 31 for males and ≥ 33 for females, as proposed in prior research). At the global network level, the SAS-SV score was found to be significantly positively correlated with the global efficiency and local efficiency of static brain networks, and negatively correlated with the temporal variability using the dynamic brain network model. Large-scale subnetwork analyses indicated that a higher SAS-SV score was significantly associated with higher strengths of static functional connectivity within the frontoparietal and cinguloopercular subnetworks, as well as a lower temporal variability of dynamic functional connectivity patterns within the attention subnetwork. However, no significant differences were found when directly comparing between the groups of participants with and without a problematic smartphone use. Conclusion Our results suggested that problematic smartphone use is associated with differences in both the static and dynamic brain network organizations in young adults. These findings may help to identify at-risk population for smartphone addiction and guide targeted interventions for further research. Nevertheless, it might be necessary to confirm our findings in a larger sample, and to investigate if a more applicable SAS-SV cutoff point is required for defining problematic smartphone use in young Chinese adults nowadays.
Collapse
Affiliation(s)
- Dayi Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xiaoxuan Liu
- Department of Neurology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yicheng Long
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zhibiao Xiang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zhipeng Wu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zhening Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Dujun Bian
- Department of Radiology, Clinical Research Center for Medical Imaging in Hunan Province, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Shixiong Tang
- Department of Radiology, Clinical Research Center for Medical Imaging in Hunan Province, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| |
Collapse
|
19
|
Brenner AM, Claudino FCDA, Burin LM, Scheibe VM, Padilha BL, de Souza GR, Duarte JA, da Rocha NS. Structural magnetic resonance imaging findings in severe mental disorders adult inpatients: A systematic review. Psychiatry Res Neuroimaging 2022; 326:111529. [PMID: 36058133 DOI: 10.1016/j.pscychresns.2022.111529] [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: 03/14/2022] [Revised: 07/13/2022] [Accepted: 08/04/2022] [Indexed: 11/21/2022]
Abstract
In severe presentations, major depressive disorder (MDD), schizophrenia (SZ), and bipolar disorder (BD) can be categorized as severe mental disorders (SMD). Our aim is to evaluate structural magnetic resonance imaging and computed tomography findings in adult inpatients diagnosed with SMD and hospitalized at psychiatric wards. PubMed, Embase, PsycInfo, Cochrane Library, and Web of Science were searched up to May 27th, 2021. Articles were screened and extracted by two independent groups, with third-party raters for discrepancies. Quality of evidence was evaluated with the Newcastle-Ottawa Scale. Synthesis was made by qualitative analysis. This study was registered on PROSPERO (CRD42020171718) and followed the PRISMA protocol. 35 studies were included, of which none was considered to likely introduce bias in our analyses. Overlapping areas in MDD, SZ, and Affective Psychosis (AP) patients, that include BD and MDD with psychotic features, are presented in the inferior temporal and cingulate gyri. MDD and SZ had commonly affected areas in the inferior and middle frontal gyri, transverse temporal gyrus, insula, and hippocampus. SZ and AP had commonly affected areas in the temporal pole. Overlapping affected areas among SMD patients are reported, but the heterogeneity of studies' designs and findings are still a limitation for clinically relevant guidelines.
Collapse
Affiliation(s)
- Augusto Mädke Brenner
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; School of Medicine, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
| | - Felipe Cesar de Almeida Claudino
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Luísa Monteiro Burin
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Victória Machado Scheibe
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; School of Medicine, Universidade Luterana do Brasil, Canoas, Rio Grande do Sul, Brazil
| | - Barbara Larissa Padilha
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; School of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Gianfranco Rizzotto de Souza
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; School of Medicine, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Juliana Avila Duarte
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Medical Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Neusa Sica da Rocha
- Center for Clinical Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Post-graduation Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; Department of Psychiatry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| |
Collapse
|
20
|
Zhang ZF, Bo QJ, Li F, Zhao L, Gao P, Wang Y, Liu R, Chen XY, Wang CY, Zhou Y. Altered frequency-specific/universal amplitude characteristics of spontaneous brain oscillations in patients with bipolar disorder. Neuroimage Clin 2022; 36:103207. [PMID: 36162237 PMCID: PMC9668601 DOI: 10.1016/j.nicl.2022.103207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 09/12/2022] [Accepted: 09/19/2022] [Indexed: 12/14/2022]
Abstract
The human brain is a dynamic system with intrinsic oscillations in spontaneous neural activity. Whether the dynamic characteristics of these spontaneous oscillations are differentially altered across different frequency bands in patients with bipolar disorder (BD) remains unclear. This study recruited 65 patients with BD and 85 healthy controls (HCs). The entire frequency range of resting-state fMRI data was decomposed into four frequency intervals. Two-way repeated-measures ANCOVA was employed to detect frequency-specific/universal alterations in the dynamic oscillation amplitude in BD. The patients were then divided into two subgroups according to their mood states to explore whether these alterations were independent of their mood states. Finally, other window sizes, step sizes, and window types were tested to replicate all analyses. Frequency-specific abnormality of the dynamic oscillation amplitude was detected within the posterior medial parietal cortex (centered at the precuneus extending to the posterior cingulate cortex). This specific profile indicates decreased amplitudes in the lower frequency bands (slow-5/4) and no amplitude changes in the higher frequency bands (slow-3/2) compared with HCs. Frequency-universal abnormalities of the dynamic oscillation amplitude were also detectable, indicating increased amplitudes in the thalamus and left cerebellum anterior lobe but decreased amplitudes in the medial superior frontal gyrus. These alterations were independent of the patients' mood states and replicable across multiple analytic and parametric settings. In short, frequency-specific/universal amplitude characteristics of spontaneous oscillations were observed in patients with BD. These abnormal characteristics have important implications for specific functional changes in BD from multiple frequency and dynamic perspectives.
Collapse
Affiliation(s)
- Zhi-Fang Zhang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Qi-Jing Bo
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China,Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Feng Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China,Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Lei Zhao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China,Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Peng Gao
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Yun Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Rui Liu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Xiong-Ying Chen
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Chuan-Yue Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China,Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University, Beijing, China,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China,Corresponding authors at: The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University, No. 5 Ankang Lane, Dewai Avenue, Xicheng District, Beijing, China (C.-Y. Wang). CAS Key Laboratory of Behavioral Science, Institute of Psychology, No. 16 Lincui Road, Chaoyang District, Beijing, PR China (Y. Zhou).
| | - Yuan Zhou
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China,CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China,Corresponding authors at: The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University, No. 5 Ankang Lane, Dewai Avenue, Xicheng District, Beijing, China (C.-Y. Wang). CAS Key Laboratory of Behavioral Science, Institute of Psychology, No. 16 Lincui Road, Chaoyang District, Beijing, PR China (Y. Zhou).
| |
Collapse
|
21
|
Siegel-Ramsay JE, Bertocci MA, Wu B, Phillips ML, Strakowski SM, Almeida JRC. Distinguishing between depression in bipolar disorder and unipolar depression using magnetic resonance imaging: a systematic review. Bipolar Disord 2022; 24:474-498. [PMID: 35060259 DOI: 10.1111/bdi.13176] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
OBJECTIVES Magnetic resonance imaging (MRI) studies comparing bipolar and unipolar depression characterize pathophysiological differences between these conditions. However, it is difficult to interpret the current literature due to differences in MRI modalities, analysis methods, and study designs. METHODS We conducted a systematic review of publications using MRI to compare individuals with bipolar and unipolar depression. We grouped studies according to MRI modality and task design. Within the discussion, we critically evaluated and summarized the functional MRI research and then further complemented these findings by reviewing the structural MRI literature. RESULTS We identified 88 MRI publications comparing participants with bipolar depression and unipolar depressive disorder. Compared to individuals with unipolar depression, participants with bipolar disorder exhibited heightened function, increased within network connectivity, and reduced grey matter volume in salience and central executive network brain regions. Group differences in default mode network function were less consistent but more closely associated with depressive symptoms in participants with unipolar depression but distractibility in bipolar depression. CONCLUSIONS When comparing mood disorder groups, the neuroimaging evidence suggests that individuals with bipolar disorder are more influenced by emotional and sensory processing when responding to their environment. In contrast, depressive symptoms and neurofunctional response to emotional stimuli were more closely associated with reduced central executive function and less adaptive cognitive control of emotionally oriented brain regions in unipolar depression. Researchers now need to replicate and refine network-level trends in these heterogeneous mood disorders and further characterize MRI markers associated with early disease onset, progression, and recovery.
Collapse
Affiliation(s)
- Jennifer E Siegel-Ramsay
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, Texas, USA
| | - Michele A Bertocci
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Bryan Wu
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, Texas, USA
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Stephen M Strakowski
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, Texas, USA
| | - Jorge R C Almeida
- Department of Psychiatry and Behavioral Sciences, Dell Medical School, University of Texas, Austin, Texas, USA
| |
Collapse
|
22
|
Tang J, Xia Y, Liu N, Li L, Zou P, Zhu P, Shan X, Lui S, Lu Y, Yan Z. Growth hormone deficiency interferes with dynamic brain networks in short children. Psychoneuroendocrinology 2022; 142:105786. [PMID: 35552090 DOI: 10.1016/j.psyneuen.2022.105786] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 03/10/2022] [Accepted: 04/26/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE This study aimed to explore the disparities in dynamic brain networks between children with growth hormone deficiency (GHD) and idiopathic short stature (ISS, non-growth hormone deficiency). METHODS This study enrolled 65 children with GHD and 60 sex- and age-matched children with ISS. Resting-state functional magnetic resonance imaging (rs-fMRI) was performed for all participants to obtain information on dynamic regional homogeneity (dReHo) and functional connectivity (FC) in dynamic (dFC) or static (sFC) state. The rs-fMRI metrics were subsequently compared between the GHD and ISS groups. RESULTS Compared to the ISS group, the GHD group showed significant dynamic abnormalities in intra-networks of the central executive and cerebellar networks and in inter-networks of the central executive network to attentional, sensorimotor, and visual networks, as well as cerebellar network to default mode, sensorimotor, and visual networks. In addition, FC changes in the dynamic state were different from those in the static state. CONCLUSIONS The abnormal dynamics in intra- and inter-networks involved in cognitive, emotional, and motor functions in children with GHD extend the knowledge on brain functional alterations in children with GHD as reflected by dynamic changes in macroscopic neural activity patterns. These findings may help explain how GHD leads to various behavioral and cognitive deficits in children with short stature.
Collapse
Affiliation(s)
- Jing Tang
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Yikai Xia
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Naici Liu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, 610041, Chengdu, China
| | - Lan Li
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Pinfa Zou
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Pingyi Zhu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Xiaoou Shan
- Children's Department of Endocrinology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, 610041, Chengdu, China
| | - Yi Lu
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China.
| | - Zhihan Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, 325027, Wenzhou, Zhejiang, China.
| |
Collapse
|
23
|
Li W, Wang C, Lan X, Fu L, Zhang F, Ye Y, Liu H, Wu K, Lao G, Chen J, Li G, Zhou Y, Ning Y. Aberrant Dynamic Functional Connectivity of Posterior Cingulate Cortex Subregions in Major Depressive Disorder With Suicidal Ideation. Front Neurosci 2022; 16:937145. [PMID: 35928017 PMCID: PMC9344055 DOI: 10.3389/fnins.2022.937145] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 06/17/2022] [Indexed: 01/08/2023] Open
Abstract
Accumulating evidence indicates the presence of structural and functional abnormalities of the posterior cingulate cortex (PCC) in patients with major depressive disorder (MDD) with suicidal ideation (SI). Nevertheless, the subregional-level dynamic functional connectivity (dFC) of the PCC has not been investigated in MDD with SI. We therefore sought to investigate the presence of aberrant dFC variability in PCC subregions in MDD patients with SI. We analyzed resting-state functional magnetic resonance imaging (fMRI) data from 31 unmedicated MDD patients with SI (SI group), 56 unmedicated MDD patients without SI (NSI group), and 48 matched healthy control (HC) subjects. The sliding-window method was applied to characterize the whole-brain dFC of each PCC subregion [the ventral PCC (vPCC) and dorsal PCC (dPCC)]. In addition, we evaluated associations between clinical variables and the aberrant dFC variability of those brain regions showing significant between-group differences. Compared with HCS, the SI and the NSI groups exhibited higher dFC variability between the left dPCC and left fusiform gyrus and between the right vPCC and left inferior frontal gyrus (IFG). The SI group showed higher dFC variability between the left vPCC and left IFG than the NSI group. Furthermore, the dFC variability between the left vPCC and left IFG was positively correlated with Scale for Suicidal Ideation (SSI) score in patients with MDD (i.e., the SI and NSI groups). Our results indicate that aberrant dFC variability between the vPCC and IFG might provide a neural-network explanation for SI and may provide a potential target for future therapeutic interventions in MDD patients with SI.
Collapse
Affiliation(s)
- Weicheng Li
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Chengyu Wang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Xiaofeng Lan
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Ling Fu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Fan Zhang
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Yanxiang Ye
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Haiyan Liu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Kai Wu
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
- School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou, China
| | - Guohui Lao
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Jun Chen
- Guangdong Institute of Medical Instruments, Guangzhou, China
| | - Guixiang Li
- Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou, China
| | - Yanling Zhou
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| | - Yuping Ning
- The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China
| |
Collapse
|
24
|
Dong F, Zhang Z, Chu T, Che K, Li Y, Gai Q, Shi Y, Ma H, Zhao F, Mao N, Xie H. Altered dynamic amplitude of low-frequency fluctuations in patients with postpartum depression. Behav Brain Res 2022; 433:113980. [PMID: 35809693 DOI: 10.1016/j.bbr.2022.113980] [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: 01/19/2022] [Revised: 06/21/2022] [Accepted: 06/22/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Postpartum depression (PPD) is a common mood disorder with increasing incidence year by year. However, the dynamic changes in local neural activity of patients with PPD remain unclear. In this study, we utilized the dynamic amplitude of low-frequency fluctuation (dALFF) method to investigate the abnormal temporal variability of local neural activity and its potential correlation with clinical severity in PPD. METHODS Twenty-four patients with PPD and nineteen healthy primiparous mothers controls (HCs) matched for age, education level and body mass index were examined by resting-state functional magnetic resonance imaging (rs-fMRI). A sliding-window method was used to assess the dALFF, and a k-means clustering method was used to identify dALFF states. Two-sample t-test was used to compare the differences of dALFF variability and state metrics between PPD and HCs. Pearson correlation analysis was used to analyze the relationship between dALFF variability, states metrics and clinical severity. RESULTS (1) Patients with PPD had lower variance of dALFF than HCs in the cognitive control network, cerebellar network and sensorimotor network. (2) Four dALFF states were identified, and patients with PPD spent more time on state 2 than the other three states. The number of transitions between the four dALFF states increased in the patients compared with that in HCs. (3) Multiple dALFF states were found to be correlated with the severity of depression. The variance of dALFF in the right middle frontal gyrus was negatively correlated with the Edinburgh postnatal depression scale score. CONCLUSION This study provides new insights into the brain dysfunction of PPD from the perspective of dynamic local brain activity, highlighting the important role of dALFF variability in understanding the neurophysiological mechanisms of PPD.
Collapse
Affiliation(s)
- Fanghui Dong
- School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Yantai, Shandong 264003, PR China; Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Zhongsheng Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Tongpeng Chu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Kaili Che
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Yuna Li
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Qun Gai
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Yinghong Shi
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Feng Zhao
- School of Compute Science and Technology, Shandong Technology and Business University, Yantai, Shandong 264000, PR China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China.
| | - Haizhu Xie
- School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Yantai, Shandong 264003, PR China; Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China.
| |
Collapse
|
25
|
Chen Q, Bi Y, Zhao X, Lai Y, Yan W, Xie L, Gao T, Xie S, Zeng T, Li J, Kuang S, Gao L, Lv Z. Regional amplitude abnormities in the major depressive disorder: A resting-state fMRI study and support vector machine analysis. J Affect Disord 2022; 308:1-9. [PMID: 35398104 DOI: 10.1016/j.jad.2022.03.079] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 03/28/2022] [Accepted: 03/31/2022] [Indexed: 12/11/2022]
Abstract
PURPOSE Major depressive disorder (MDD) is a common mood disorder. However, it still remains challenging to select sensitive biomarkers and establish reliable diagnosis methods currently. This study aimed to investigate the abnormalities of the spontaneous brain activity in the MDD and explore the clinical diagnostic value of three amplitude metrics in altered regions by applying the support vector machine (SVM) method. METHODS A total of fifty-two HCs and forty-eight MDD patients were recruited in the study. The amplitude of low-frequency fluctuation (ALFF), fractional amplitude of low-frequency fluctuation (fALFF) and percent amplitude of fluctuation (PerAF) metrics were calculated to assess local spontaneous brain activity. Then we performed correlation analysis to examine the association between cerebral abnormalities and clinical characteristics. Finally, SVM analysis was applied to conduct the classification model for evaluating the diagnostic value. RESULTS Two-sample t-test exhibited that MDD patients had increased ALFF value in the right caudate and corpus callosum, increased fALFF value in the same regions and increased PerAF value in the inferior parietal lobule and right caudate compared to HCs. Moreover, PerAF value in the inferior parietal lobule was negatively correlated with the slow factor scores. The SVM results showed that a combination of mean ALFF and fALFF in the right caudate and corpus callosum selected as features achieved a highest area under curve (AUC) value (0.89), accuracy (79.79%), sensitivity (65.12%) and specificity (92.16%). CONCLUSION Collectively, we found increased mean ALFF and fALFF may serve as a potential neuroimaging marker to discriminate MDD and HCs.
Collapse
Affiliation(s)
- Qing Chen
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Yanmeng Bi
- College of Integrated Traditional Chinese and Western Medicine, Jining Medical University, Jining, China
| | - Xiaohua Zhao
- School of Beauty, Yichun University, Yichun, China
| | - Yuqi Lai
- Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Weixin Yan
- The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lingpeng Xie
- Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Tingting Gao
- Department of General medicine, The first affiliated hospital of Guangdong Pharmaceutical University, Guangzhou, China
| | - Shuwen Xie
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Ting Zeng
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Jun Li
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Shanshan Kuang
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Lei Gao
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
| | - Zhiping Lv
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China.
| |
Collapse
|
26
|
Jiang Y, Chen Y, Zheng R, Zhou B, Wei Y, Gao A, Wei Y, Li S, Guo J, Han S, Zhang Y, Cheng J. More Than Just Statics: Temporal Dynamic Changes in Inter- and Intrahemispheric Functional Connectivity in First-Episode, Drug-Naive Patients With Major Depressive Disorder. Front Hum Neurosci 2022; 16:868135. [PMID: 35463932 PMCID: PMC9024080 DOI: 10.3389/fnhum.2022.868135] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 03/14/2022] [Indexed: 11/13/2022] Open
Abstract
Several functional magnetic resonance imaging (fMRI) studies have demonstrated abnormalities in static intra- and interhemispheric functional connectivity among diverse brain regions in patients with major depressive disorder (MDD). However, the dynamic changes in intra- and interhemispheric functional connectivity patterns in patients with MDD remain unclear. Fifty-eight first-episode, drug-naive patients with MDD and 48 age-, sex-, and education level-matched healthy controls (HCs) underwent resting-state fMRI. Whole-brain functional connectivity, analyzed using the functional connectivity density (FCD) approach, was decomposed into ipsilateral and contralateral functional connectivity. We computed the intra- and interhemispheric dynamic FCD (dFCD) using a sliding window analysis to capture the dynamic patterns of functional connectivity. The temporal variability in functional connectivity was quantified as the variance of the dFCD over time. In addition, intra- and interhemispheric static FCD (sFCD) patterns were calculated. Associations between the dFCD variance and sFCD in abnormal brain regions and the severity of depressive symptoms were analyzed. Compared to HCs, patients with MDD showed lower interhemispheric dFCD variability in the inferior/middle frontal gyrus and decreased sFCD in the medial prefrontal cortex/anterior cingulate cortex and posterior cingulate cortex/precuneus in both intra- and interhemispheric comparisons. No significant correlations were found between any abnormal dFCD variance or sFCD at the intra- and interhemispheric levels and the severity of depressive symptoms. Our results suggest intra- and interhemispheric functional connectivity alterations in the dorsolateral prefrontal cortex (DLPFC) and default mode network regions involved in cognition, execution and emotion. Furthermore, our study emphasizes the essential role of altered interhemispheric communication dynamics in the DLPFC in patients with MDD. These findings contribute to our understanding of the pathophysiology of MDD.
Collapse
Affiliation(s)
- 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
| | - 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
| | - 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
| | - 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
| | - Ying 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
| | - Ankang Gao
- 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
| | - Shuying Li
- Department of Psychiatry, 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
- 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,
| | - 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
- Yong Zhang,
| | - 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,
| |
Collapse
|
27
|
Claeys EHI, Mantingh T, Morrens M, Yalin N, Stokes PRA. Resting-state fMRI in depressive and (hypo)manic mood states in bipolar disorders: A systematic review. Prog Neuropsychopharmacol Biol Psychiatry 2022; 113:110465. [PMID: 34736998 DOI: 10.1016/j.pnpbp.2021.110465] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 10/01/2021] [Accepted: 10/27/2021] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Abnormalities in spontaneous brain activity, measured with resting-state functional magnetic resonance imaging (rs-fMRI), may be key biomarkers for bipolar disorders. This systematic review compares rs-fMRI findings in people experiencing a bipolar depressive or (hypo)manic episode to bipolar euthymia and/or healthy participants. METHODS Medline, Web of Science and Embase were searched up until April 2021. Studies without control group, or including minors, neurological co-morbidities or mixed episodes, were excluded. Qualitative synthesis was used to report results and risk of bias was assessed using the National Heart, Lung and Blood Institute tool for case-control studies. RESULTS Seventy-one studies were included (3167 bipolar depressed/706 (hypo)manic). In bipolar depression, studies demonstrated default-mode (DMN) and frontoparietal network (FPN) dysfunction, altered baseline activity in the precuneus, insula, striatum, cingulate, frontal and temporal cortex, and disturbed regional homogeneity in parietal, temporal and pericentral areas. Functional connectivity was altered in thalamocortical circuits and between the cingulate cortex and precuneus. In (hypo)mania, studies reported altered functional connectivity in the amygdala, frontal and cingulate cortex. Finally, rs-fMRI disturbances in the insula and putamen correlate with depressive symptoms, cerebellar resting-state alterations could evolve with disease progression and altered amygdala connectivity might mediate lithium effects. CONCLUSIONS Our results suggest DMN and FPN dysfunction in bipolar depression, whereas local rs-fMRI alterations might differentiate mood states. Future studies should consider controlling rs-fMRI findings for potential clinical confounding factors such as medication. Considerable heterogeneity of methodology between studies limits conclusions. Standardised clinical reporting and consistent analysis approaches would increase coherence in this promising field.
Collapse
Affiliation(s)
- Eva H I Claeys
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Campus Drie Eiken, S.033, Universiteitsplein 1, 2610 Antwerpen, Belgium; Department of Psychiatry, University Psychiatric Centre Duffel, Stationsstraat 22, 2570 Duffel, Belgium
| | - Tim Mantingh
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Manuel Morrens
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Campus Drie Eiken, S.033, Universiteitsplein 1, 2610 Antwerpen, Belgium; Department of Psychiatry, University Psychiatric Centre Duffel, Stationsstraat 22, 2570 Duffel, Belgium
| | - Nefize Yalin
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
| | - Paul R A Stokes
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| |
Collapse
|
28
|
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.
Collapse
|
29
|
Sun F, Liu Z, Fan Z, Zuo J, Xi C, Yang J. Dynamical regional activity in putamen distinguishes bipolar type I depression and unipolar depression. J Affect Disord 2022; 297:94-101. [PMID: 34678402 DOI: 10.1016/j.jad.2021.10.021] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Revised: 10/15/2021] [Accepted: 10/18/2021] [Indexed: 01/18/2023]
Abstract
OBJECTIVES Intrinsic human brain activity is time-varying and dynamic. However, there is still a lack of knowledge about the dynamic regional activity differences between unipolar depression (UD) and bipolar type I depression (BD-I), and whether their differential pattern can help to distinguish these two patient groups who are prone to misdiagnosis in clinical practice. METHOD In this study, we used the dynamical fractional amplitude of low-frequency fluctuations (dfALFF) to examine the resting-state dynamical regional activity in 40 BD-I, 42 UD, and 44 healthy controls (HCs). Analysis of covariance was applied to explore the shared and distinct dfALFF pattern among three groups, and machine-learning methods were conducted to classify BD-I from UD by using the detected distinct dfALFF pattern. RESULTS Compared with HCs, both BD-I and UD exhibited decreased dfALFF temporal variability in the left inferior temporal gyrus. The BD-I showed significantly decreased dfALFF temporal variability in the left putamen compared to UD. By using the dfALFF variability pattern of the left putamen as features, we achieved the 75.61% accuracy and 0.756 area under curve in classifying BD-I from UD. LIMITATIONS The small sample size of the current study may limit the generalizability of the findings. CONCLUSIONS The current study demonstrated that the dfALFF temporal variability pattern in the putamen may show a promise as future diagnostic aids for BD-I and UD.
Collapse
Affiliation(s)
- Fuping Sun
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Zhening Liu
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Zebin Fan
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Jing Zuo
- Clinical Medical Research Center of Hunan Provincial Mental Behavioral Disorder, Clinical Medical School of Hunan University of Chinese Medicine, Hunan Provincial Brain Hospital, Changsha, Hunan 410007, China
| | - Chang Xi
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Jie Yang
- National Clinical Research Center for Mental Disorders, and Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
| |
Collapse
|
30
|
Sun F, Liu Z, Yang J, Fan Z, Xi C, Cheng P, He Z, Yang J. Shared and distinct patterns of dynamical degree centrality in bipolar disorder across different mood states. Front Psychiatry 2022; 13:941073. [PMID: 35966464 PMCID: PMC9364672 DOI: 10.3389/fpsyt.2022.941073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 07/06/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Previous studies have probed the brain static activity pattern in bipolar disorder across different states. However, human intrinsic brain activity is time-varying and dynamic. There is a lack of knowledge about the brain dynamical pattern in bipolar disorder across different mood states. METHODS This study used the dynamical degree centrality (dDC) to investigate the resting-state whole-brain dynamical pattern voxel-wise in a total of 62 bipolar disorder [28 bipolar depression (BD), 13 bipolar mania (BM), 21 bipolar euthymia (BE)], and 30 healthy controls (HCs). One-way analysis of variance (ANOVA) was applied to explore the omnibus differences of the dDC pattern across all groups, and Pearson's correlation analysis was used to evaluate the relationship between the dDC variability in detected regions with clinical symptom severity. RESULTS One-way ANOVA analysis showed the omnibus differences in the left inferior parietal lobule/middle occipital gyrus (IPL/MOG) and right precuneus/posterior cingulate cortex (PCUN/PCC) across all groups. The post hoc analysis revealed that BD showed decreased dDC in the IPL/MOG compared with all other groups, and both BD and BM exhibited decreased dDC in the PCUN/PCC compared with BE and HCs. Furthermore, correlation analysis showed that the dDC variability of the IPL/MOG and PCUN/PCC negatively correlated with the depression symptom levels in all patients with bipolar disorder. CONCLUSION This study demonstrated the distinct and shared brain dynamical pattern of the depressive, manic, and euthymia states. Our findings provide new insights into the pathophysiology of bipolar disorder across different mood states from the dynamical brain network pattern perspective.
Collapse
Affiliation(s)
- Fuping Sun
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhening Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Jun Yang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zebin Fan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Chang Xi
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Peng Cheng
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhong He
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Jie Yang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| |
Collapse
|
31
|
Luo L, Lei X, Zhu C, Wu J, Ren H, Zhan J, Qin Y. Decreased Connectivity in Precuneus of the Ventral Attentional Network in First-Episode, Treatment-Naïve Patients With Major Depressive Disorder: A Network Homogeneity and Independent Component Analysis. Front Psychiatry 2022; 13:925253. [PMID: 35693966 PMCID: PMC9184427 DOI: 10.3389/fpsyt.2022.925253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 04/28/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND AND OBJECTIVE The ventral attentional network (VAN) can provide quantitative information on cognitive problems in patients with major depressive disorder (MDD). Nevertheless, little is known about network homogeneity (NH) changes in the VAN of these patients. The aim of this study was to examine the NH values in the VAN by independent component analysis (ICA) and compare the NH values between MDD patients and the normal controls (NCs). METHODS Attentional network test and resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 73 patients, and 70 NCs matched by gender, age, and education years. ICA and NH were employed to evaluate the data. Moreover, the NH values were compared, and Spearman's rank correlation analysis was used to assess the correlations with the executive control reaction time (ECRT). RESULTS Our results showed that the first-episode, treatment-naive MDD patients had decreased NH in the right precuneus (PCu) and abnormal ECRT compared with NCs. However, no significant correlation was found between the NH values and measured clinical variables. CONCLUSION Our results highlight the potential importance of VAN in the pathophysiology of cognitive problems in MDD, thus offering new directions for future research on MDD.
Collapse
Affiliation(s)
- Liqiong Luo
- Department of Oncology, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Xijun Lei
- Department of Oncology, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Canmin Zhu
- Department of Neurology, The First People's Hospital of Jiangxia District, Wuhan, China
| | - Jun Wu
- Department of Neurosurgery, Wuhan Central Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongwei Ren
- Department of Medical Imaging, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Jing Zhan
- Department of Oncology, Tianyou Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Yongzhang Qin
- Department of Endocrinology, First Affiliated Hospital of Gannan Medical University, Ganzhou, China
| |
Collapse
|
32
|
Chen F, Wang L, Ding Z. Alteration of whole-brain amplitude of low-frequency fluctuation and degree centrality in patients with mild to moderate depression: A resting-state functional magnetic resonance imaging study. Front Psychiatry 2022; 13:1061359. [PMID: 36569607 PMCID: PMC9768018 DOI: 10.3389/fpsyt.2022.1061359] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 11/22/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Mild to moderate depressive disorder has a high risk of progressing to major depressive disorder. METHODS Low-frequency amplitude and degree centrality were calculated to compare 49 patients with mild to moderate depression and 21 matched healthy controls. Correlation analysis was conducted to explore the correlation between the amplitude of low-frequency fluctuation (ALFF) and the degree centrality (DC) of altered brain region and the scores of clinical scale. Receiver operating characteristic (ROC) curves were further analyzed to evaluate the predictive value of above altered ALFF and DC areas as image markers for mild to moderate depression. RESULTS Compared with healthy controls, patients with mild to moderate depression had lower ALFF values in the left precuneus and posterior cingulate gyrus [voxel p < 0.005, cluster p < 0.05, Gaussian random field correction (GRF) corrected] and lower DC values in the left insula (voxel p < 0.005, cluster p < 0.05, GRF corrected). There was a significant negative correlation between DC in the left insula and scale scores of Zung's Depression Scale (ZungSDS), Beck Self-Rating Depression Scale (BDI), Toronto Alexithymia Scale (TAS26), and Ruminative Thinking Response Scale (RRS_SUM, RRS_REFLECTION, RRS_DEPR). Finally, ROC analysis showed that the ALFF of the left precuneus and posterior cingulate gyrus had a sensitivity of 61.9% and a specificity of 79.6%, and the DC of the left insula had a sensitivity of 81% and a specificity of 85.7% in differentiating mild to moderate depression from healthy controls. CONCLUSION Intrinsic abnormality of the brain was mainly located in the precuneus and insular in patients with mild to moderate depression, which provides insight into potential neurological mechanisms.
Collapse
Affiliation(s)
- Fenyang Chen
- The Fourth School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
| | - Luoyu Wang
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zhongxiang Ding
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| |
Collapse
|
33
|
Piguet C, Karahanoğlu FI, Saccaro LF, Van De Ville D, Vuilleumier P. Mood disorders disrupt the functional dynamics, not spatial organization of brain resting state networks. Neuroimage Clin 2021; 32:102833. [PMID: 34619652 PMCID: PMC8498469 DOI: 10.1016/j.nicl.2021.102833] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 09/10/2021] [Accepted: 09/19/2021] [Indexed: 12/24/2022]
Abstract
Spontaneous fluctuations in the blood oxygenation level dependent signal measured through resting-state functional magnetic resonance imaging have been corroborated to aggregate into multiple functional networks. Abnormal resting brain activity is observed in mood disorder patients, however with inconsistent results. How do such alterations relate to clinical symptoms; e.g., level of depression and rumination tendencies? Here we recovered spatially and temporally overlapping functional networks from 31 mood disorder patients and healthy controls during rest, by applying novel methods that identify transient changes in spontaneous brain activity. Our unique approach disentangles the dynamic engagement of resting-state networks unconstrained by the slow hemodynamic response. This time-varying characterization provides moment-to-moment information about functional networks in terms of their durations and dynamic coupling, and offers novel evidence for selective contributionsto particular clinical symptoms. Patients showed increased duration of default-mode network (DMN), increased duration and occurrence of posterior DMN as well as insula- and amygdala-centered networks, but decreased occurrence of visual and anterior salience networks. Coupling between limbic (insula and amygdala) networks was also reduced. Depression level modulated DMN duration, whereas intrusive thoughts correlated with occurrence of insula and posterior DMN. Anatomical network organization was similar to controls. In sum, altered brain dynamics in mood disorder patients appear to mediate distinct clinical dimensions including increased self-processing, and decreased attention to external world.
Collapse
Affiliation(s)
- Camille Piguet
- Department of Psychiatry, Faculty of Medicine, University of Geneva, Switzerland
| | - Fikret Işık Karahanoğlu
- MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Department of Radiology, Harvard Medical School, MA, USA
| | | | - Dimitri Van De Ville
- Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Switzerland
- Institute of Bioengineering, School of Engineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
| | - Patrik Vuilleumier
- Swiss Center for Affective Sciences, Campus Biotech, Geneva, Switzerland
| |
Collapse
|