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Dan R, Whitton AE, Treadway MT, Rutherford AV, Kumar P, Ironside ML, Kaiser RH, Ren B, Pizzagalli DA. Brain-based graph-theoretical predictive modeling to map the trajectory of anhedonia, impulsivity, and hypomania from the human functional connectome. Neuropsychopharmacology 2024; 49:1162-1170. [PMID: 38480910 PMCID: PMC11109096 DOI: 10.1038/s41386-024-01842-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 01/27/2024] [Accepted: 03/01/2024] [Indexed: 03/26/2024]
Abstract
Clinical assessments often fail to discriminate between unipolar and bipolar depression and identify individuals who will develop future (hypo)manic episodes. To address this challenge, we developed a brain-based graph-theoretical predictive model (GPM) to prospectively map symptoms of anhedonia, impulsivity, and (hypo)mania. Individuals seeking treatment for mood disorders (n = 80) underwent an fMRI scan, including (i) resting-state and (ii) a reinforcement-learning (RL) task. Symptoms were assessed at baseline as well as at 3- and 6-month follow-ups. A whole-brain functional connectome was computed for each fMRI task, and the GPM was applied for symptom prediction using cross-validation. Prediction performance was evaluated by comparing the GPM to a corresponding null model. In addition, the GPM was compared to the connectome-based predictive modeling (CPM). Cross-sectionally, the GPM predicted anhedonia from the global efficiency (a graph theory metric that quantifies information transfer across the connectome) during the RL task, and impulsivity from the centrality (a metric that captures the importance of a region) of the left anterior cingulate cortex during resting-state. At 6-month follow-up, the GPM predicted (hypo)manic symptoms from the local efficiency of the left nucleus accumbens during the RL task and anhedonia from the centrality of the left caudate during resting-state. Notably, the GPM outperformed the CPM, and GPM derived from individuals with unipolar disorders predicted anhedonia and impulsivity symptoms for individuals with bipolar disorders. Importantly, the generalizability of cross-sectional models was demonstrated in an external validation sample. Taken together, across DSM mood diagnoses, efficiency and centrality of the reward circuit predicted symptoms of anhedonia, impulsivity, and (hypo)mania, cross-sectionally and prospectively. The GPM is an innovative modeling approach that may ultimately inform clinical prediction at the individual level.
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Affiliation(s)
- Rotem Dan
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Alexis E Whitton
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Black Dog Institute, University of New South Wales, Sydney, Australia
| | - Michael T Treadway
- Department of Psychology, Emory University, Atlanta, GA, USA
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
| | - Ashleigh V Rutherford
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Poornima Kumar
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Manon L Ironside
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Roselinde H Kaiser
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Boyu Ren
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Laboratory for Psychiatric Biostatistics, McLean Hospital, Belmont, MA, USA
| | - Diego A Pizzagalli
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
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Pang X, Liang X, Chang W, Lv Z, Zhao J, Wu P, Li X, Wei W, Zheng J. The role of the thalamus in modular functional networks in temporal lobe epilepsy with cognitive impairment. CNS Neurosci Ther 2024; 30:e14345. [PMID: 37424152 PMCID: PMC10848054 DOI: 10.1111/cns.14345] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 06/04/2023] [Accepted: 06/27/2023] [Indexed: 07/11/2023] Open
Abstract
OBJECTIVE Cognitive deficit is common in patients with temporal lobe epilepsy (TLE). Here, we aimed to investigate the modular architecture of functional networks associated with distinct cognitive states in TLE patients together with the role of the thalamus in modular networks. METHODS Resting-state functional magnetic resonance imaging scans were acquired from 53 TLE patients and 37 matched healthy controls. All patients received the Montreal Cognitive Assessment test and accordingly were divided into TLE patients with normal cognition (TLE-CN, n = 35) and TLE patients with cognitive impairment (TLE-CI, n = 18) groups. The modular properties of functional networks were calculated and compared including global modularity Q, modular segregation index, intramodular connections, and intermodular connections. Thalamic subdivisions corresponding to the modular networks were generated by applying a 'winner-take-all' strategy before analyzing the modular properties (participation coefficient and within-module degree z-score) of each thalamic subdivision to assess the contribution of the thalamus to modular functional networks. Relationships between network properties and cognitive performance were then further explored. RESULTS Both TLE-CN and TLE-CI patients showed lower global modularity, as well as lower modular segregation index values for the ventral attention network and the default mode network. However, different patterns of intramodular and intermodular connections existed for different cognitive states. In addition, both TLE-CN and TLE-CI patients exhibited anomalous modular properties of functional thalamic subdivisions, with TLE-CI patients presenting a broader range of abnormalities. Cognitive performance in TLE-CI patients was not related to the modular properties of functional network but rather to the modular properties of functional thalamic subdivisions. CONCLUSIONS The thalamus plays a prominent role in modular networks and potentially represents a key neural mechanism underlying cognitive impairment in TLE.
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Affiliation(s)
- Xiaomin Pang
- Department of NeurologyGuangxi Medical University First Affiliated HospitalNanningChina
| | - Xiulin Liang
- Department of NeurologyGuangxi Medical University First Affiliated HospitalNanningChina
| | - Weiwei Chang
- Department of NeurologyGuangxi Medical University First Affiliated HospitalNanningChina
| | - Zongxia Lv
- Department of NeurologyGuangxi Medical University First Affiliated HospitalNanningChina
| | - Jingyuan Zhao
- Department of NeurologyGuangxi Medical University First Affiliated HospitalNanningChina
| | - Peirong Wu
- Department of NeurologyGuangxi Medical University First Affiliated HospitalNanningChina
| | - Xinrong Li
- Department of NeurologyGuangxi Medical University First Affiliated HospitalNanningChina
| | - Wutong Wei
- Department of NeurologyGuangxi Medical University First Affiliated HospitalNanningChina
| | - Jinou Zheng
- Department of NeurologyGuangxi Medical University First Affiliated HospitalNanningChina
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van Kleef RS, Müller A, van Velzen LS, Marie Bas-Hoogendam J, van der Wee NJA, Schmaal L, Veltman DJ, Rive MM, Ruhé HG, Marsman JBC, van Tol MJ. Functional MRI correlates of emotion regulation in major depressive disorder related to depressive disease load measured over nine years. Neuroimage Clin 2023; 40:103535. [PMID: 37984226 PMCID: PMC10696117 DOI: 10.1016/j.nicl.2023.103535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 10/26/2023] [Accepted: 10/30/2023] [Indexed: 11/22/2023]
Abstract
Major Depressive Disorder (MDD) often is a recurrent and chronic disorder. We investigated the neurocognitive underpinnings of the incremental risk for poor disease course by exploring relations between enduring depression and brain functioning during regulation of negative and positive emotions using cognitive reappraisal. We used fMRI-data from the longitudinal Netherlands Study of Depression and Anxiety acquired during an emotion regulation task in 77 individuals with MDD. Task-related brain activity was related to disease load, calculated from presence and severity of depression in the preceding nine years. Additionally, we explored task related brain-connectivity. Brain functioning in individuals with MDD was further compared to 35 controls to explore overlap between load-effects and general effects related to MDD history/presence. Disease load was not associated with changes in affect or with brain activity, but with connectivity between areas essential for processing, integrating and regulating emotional information during downregulation of negative emotions. Results did not overlap with general MDD-effects. Instead, MDD was generally associated with lower parietal activity during downregulation of negative emotions. During upregulation of positive emotions, disease load was related to connectivity between limbic regions (although driven by symptomatic state), and connectivity between frontal, insular and thalamic regions was lower in MDD (vs controls). Results suggest that previous depressive load relates to brain connectivity in relevant networks during downregulation of negative emotions. These abnormalities do not overlap with disease-general abnormalities and could foster an incremental vulnerability to recurrence or chronicity of MDD. Therefore, optimizing emotion regulation is a promising therapeutic target for improving long-term MDD course.
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Affiliation(s)
- Rozemarijn S van Kleef
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University Medical Center Groningen, Groningen, the Netherlands.
| | - Amke Müller
- Department of Psychology, Helmut Schmidt University / University of the Federal Armed Forces Hamburg, Hamburg, Germany
| | - Laura S van Velzen
- Orygen Parkville, VIC, Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Janna Marie Bas-Hoogendam
- Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, the Netherlands; Department of Psychiatry, Leiden University Medical Center, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University Medical Center, the Netherlands
| | - Nic J A van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University Medical Center, the Netherlands
| | - Lianne Schmaal
- Orygen Parkville, VIC, Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC location VUMC & Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Maria M Rive
- Department of Psychiatry, Amsterdam UMC location AMC, Amsterdam, the Netherlands; Triversum, Department of Child and Adolescent Psychiatry, GGZ Noord-Holland Noord, Hoorn, the Netherlands
| | - Henricus G Ruhé
- Department of Psychiatry, Radboudumc, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, the Netherlands
| | - Jan-Bernard C Marsman
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University Medical Center Groningen, Groningen, the Netherlands
| | - Marie-José van Tol
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University Medical Center Groningen, Groningen, the Netherlands
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Chibaatar E, Watanabe K, Quinn PM, Okamoto N, Shinkai T, Natsuyama T, Hayasaki G, Ikenouchi A, Kakeda S, Yoshimura R. Triple network connectivity changes in patients with major depressive disorder versus healthy controls via structural network imaging after electroconvulsive therapy treatment. J Affect Disord 2023; 340:923-929. [PMID: 37598718 DOI: 10.1016/j.jad.2023.08.020] [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: 04/13/2023] [Revised: 07/06/2023] [Accepted: 08/03/2023] [Indexed: 08/22/2023]
Abstract
OBJECTIVE To investigate the effect of electroconvulsive treatment (ECT) on dynamic structural network connectivity in major depressive disorder (MDD), based on the triple-network model. METHODS Twenty-one first-episode, drug-naïve patients with MDD and 21 age- and sex-matched healthy subjects were recruited. Bilateral electrical stimulation was performed thrice a week for a total of 4-5 weeks in the MDD group. MRI data were obtained, and triple-network structural connectivity was evaluated using source-based morphometry (SBM) analysis. A paired t-test was used to analyze structural connectivity differences between pre- and post-ECT MDD groups, one-way analysis was used to calculate three intrinsic network differences between HCs, pre- and post-ECT groups, and partial least squares structural equation modelling was used to investigate dynamic structural network connectivity (dSNC) across groups. RESULTS Pre-ECT patients with MDD exhibited significantly lower salience network (SN) structural connectivity (p = 0.010) than the healthy control (HC) group and after ECT therapy SN structural connectivity was significantly elevated (p = 0.002) in post-ECT group compared with pre-ECT. PLS-SEM analysis conducted on inter-network connectivity in the triple-network model indicated a significant difference between SN and central executive network (CEN) in all three groups. The HC and post-ECT MDD groups showed notable direct connectivity between the SN and default mode network (DMN), while the pre-ECT MDD group showed consequential pathological connectivity between the CEN and DMN. A mediation analysis revealed a significant indirect effect of the SN on the DMN through the CEN (β = 0.363, p = 0.008) only in the pre-ECT MDD group. CONCLUSIONS ECT may be an effective and minimally invasive treatment for addressing structural changes in the SN and direct communication abnormalities between the three core brain networks in patients with MDD, with possible beneficial correction of indirect connections.
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Affiliation(s)
- Enkmurun Chibaatar
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Keita Watanabe
- Department of Radiology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Patrick M Quinn
- Wakamatsu Hospital, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Naomichi Okamoto
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Takahiro Shinkai
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Tomoya Natsuyama
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Gaku Hayasaki
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Atsuko Ikenouchi
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Shingo Kakeda
- Department of Radiology, Graduate School of Medicine, Hirosaki University, Hirosaki, Japan
| | - Reiji Yoshimura
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan.
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Long Z, Chen D, Lei X. Enhanced rich club connectivity in mild or moderate depression after nonpharmacological treatment: A preliminary study. Brain Behav 2023; 13:e3198. [PMID: 37680015 PMCID: PMC10570500 DOI: 10.1002/brb3.3198] [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: 04/27/2023] [Revised: 07/14/2023] [Accepted: 07/21/2023] [Indexed: 09/09/2023] Open
Abstract
INTRODUCTION It has been suggested that the rich club organization in major depressive disorder (MDD) was altered. However, it remained unclear whether the rich club organization could be served as a biomarker that predicted the improvement of clinical symptoms in MDD. METHODS The current study included 29 mild or moderate patients with MDD, who were grouped into a treatment group (receiving cognitive behavioral therapy or real-time fMRI feedback treatment) and a no-treatment group. Resting-state MRI scans were obtained for all participants. Graph theory was employed to investigate the treatment-related changes in network properties and rich club organization. RESULTS We found that patients in the treatment group had decreased depressive symptom scores and enhanced rich club connectivity following the nonpharmacological treatment. Moreover, the changes in rich club connectivity were significantly correlated with the changes in depressive symptom scores. In addition, the nonpharmacological treatment on patients with MDD increased functional connectivity mainly among the salience network, default mode network, frontoparietal network, and subcortical network. Patients in the no-treatment group did not show significant changes in depressive symptom scores and rich club organization. CONCLUSIONS Those results suggested that the remission of depressive symptoms after nonpharmacological treatment in MDD patients was associated with the increased efficiency of global information processing.
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Affiliation(s)
- Zhiliang Long
- Sleep and NeuroImaging CenterFaculty of PsychologySouthwest UniversityChongqingP. R. China
- Key Laboratory of Cognition and Personality (Southwest University), Ministry of EducationChongqingP. R. China
| | - Danni Chen
- Sleep and NeuroImaging CenterFaculty of PsychologySouthwest UniversityChongqingP. R. China
- Key Laboratory of Cognition and Personality (Southwest University), Ministry of EducationChongqingP. R. China
| | - Xu Lei
- Sleep and NeuroImaging CenterFaculty of PsychologySouthwest UniversityChongqingP. R. China
- Key Laboratory of Cognition and Personality (Southwest University), Ministry of EducationChongqingP. R. China
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Pizzagalli D, Whitton A, Treadway M, Rutherford A, Kumar P, Ironside M, Kaiser R, Ren B, Dan R. Brain-based graph-theoretical predictive modeling to map the trajectory of transdiagnostic symptoms of anhedonia, impulsivity, and hypomania from the human functional connectome. RESEARCH SQUARE 2023:rs.3.rs-3168186. [PMID: 37841877 PMCID: PMC10571608 DOI: 10.21203/rs.3.rs-3168186/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
Clinical assessments often fail to discriminate between unipolar and bipolar depression and identify individuals who will develop future (hypo)manic episodes. To address this challenge, we developed a brain-based graph-theoretical predictive model (GPM) to prospectively map symptoms of anhedonia, impulsivity, and (hypo)mania. Individuals seeking treatment for mood disorders (n = 80) underwent an fMRI scan, including (i) resting-state and (ii) a reinforcement-learning (RL) task. Symptoms were assessed at baseline as well as at 3- and 6-month follow-ups. A whole-brain functional connectome was computed for each fMRI task, and the GPM was applied for symptom prediction using cross-validation. Prediction performance was evaluated by comparing the GPM's mean square error (MSE) to that of a corresponding null model. In addition, the GPM was compared to the connectome-based predictive modeling (CPM). Cross-sectionally, the GPM predicted anhedonia from the global efficiency (a graph theory metric that quantifies information transfer across the connectome) during the RL task, and impulsivity from the centrality (a metric that captures the importance of a region for information spread) of the left anterior cingulate cortex during resting-state. At 6-month follow-up, the GPM predicted (hypo)manic symptoms from the local efficiency of the left nucleus accumbens during the RL task and anhedonia from the centrality of the left caudate during resting-state. Notably, the GPM outperformed the CPM, and GPM derived from individuals with unipolar disorders predicted anhedonia and impulsivity symptoms for individuals with bipolar disorders, highlighting transdiagnostic generalization. Taken together, across DSM mood diagnoses, efficiency and centrality of the reward circuit predicted symptoms of anhedonia, impulsivity, and (hypo)mania, cross-sectionally and prospectively. The GPM is an innovative modeling approach that may ultimately inform clinical prediction at the individual level. ClinicalTrials.gov identifier: NCT01976975.
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Affiliation(s)
| | - Alexis Whitton
- Black Dog Institute, University of New South Wales, Sydney
| | | | | | | | | | | | - Boyu Ren
- McLean Hospital / Harvard Medical School
| | - Rotem Dan
- McLean Hospital / Harvard Medical School
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Liu C, Belleau EL, Dong D, Sun X, Xiong G, Pizzagalli DA, Auerbach RP, Wang X, Yao S. Trait- and state-like co-activation pattern dynamics in current and remitted major depressive disorder. J Affect Disord 2023; 337:159-168. [PMID: 37245549 PMCID: PMC10897955 DOI: 10.1016/j.jad.2023.05.074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 05/02/2023] [Accepted: 05/21/2023] [Indexed: 05/30/2023]
Abstract
BACKGROUND Distinguishing between trait- and state-like neural alternations in major depressive disorder (MDD) may advance our understanding of this recurring disorder. We aimed to investigate dynamic functional connectivity alternations in unmedicated individuals with current or past MDD using co-activation pattern analyses. METHODS Resting-state functional magnetic resonance imaging data were acquired from individuals with first-episode current MDD (cMDD, n = 50), remitted MDD (rMDD, n = 44), and healthy controls (HCs, n = 64). Using a data-driven consensus clustering technique, four whole-brain states of spatial co-activation were identified and associated metrics (dominance, entries, transition frequency) were analyzed with respect to clinical characteristics. RESULTS Relative to rMDD and HC, cMDD showed increased dominance and entries of state 1 (primarily involving default mode network (DMN)), and decreased dominance of state 4 (mostly involving frontal-parietal network (FPN)). Among cMDD, state 1 entries correlated positively with trait rumination. Conversely, relative to cMDD and HC, individuals with rMDD were characterized by increased state 4 entries. Relative to HC, both MDD groups showed increased state 4-to-1 (FPN to DMN) transition frequency but reduction in state 3 (spanning visual attention, somatosensory, limbic networks), with the former metric specifically related to trait rumination. LIMITATIONS Further confirmation with longitudinal studies are required. CONCLUSIONS Regardless of symptoms, MDD was characterized by increased FPN-to-DMN transitions and reduced dominance of a hybrid network. State-related effect emerged in regions critically implicated in repetitive introspection and cognitive control. Asymptomatic individuals with past MDD were uniquely linked to increased FPN entries. Our findings identify trait-like brain network dynamics that might increase vulnerability to future MDD.
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Affiliation(s)
- Chengwen Liu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Emily L Belleau
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Daifeng Dong
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Xiaoqiang Sun
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Ge Xiong
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Diego A Pizzagalli
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Randy P Auerbach
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China.
| | - Shuqiao Yao
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China; China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China.
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van Kleef RS, Kaushik P, Besten M, Marsman JBC, Bockting CLH, van Vugt M, Aleman A, van Tol MJ. Understanding and predicting future relapse in depression from resting state functional connectivity and self-referential processing. J Psychiatr Res 2023; 165:305-314. [PMID: 37556963 DOI: 10.1016/j.jpsychires.2023.07.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 07/21/2023] [Accepted: 07/24/2023] [Indexed: 08/11/2023]
Abstract
BACKGROUND The recurrent nature of Major Depressive Disorder (MDD) asks for a better understanding of mechanisms underlying relapse. Previously, self-referential processing abnormalities have been linked to vulnerability for relapse. We investigated whether abnormalities in self-referential cognitions and functioning of associated brain-networks persist upon remission and predict relapse. METHODS Remitted recurrent MDD patients (n = 48) and never-depressed controls (n = 23) underwent resting-state fMRI scanning at baseline and were additionally assessed for their implicit depressed self-associations and ruminative behaviour. A template-based dual regression approach was used to investigate between-group differences in default mode, cingulo-opercular and frontoparietal network resting-state functional connectivity (RSFC). Additional prediction of relapse status at 18-month follow-up was investigated within patients using both regression analyses and machine learning classifiers. RESULTS Remitted patients showed higher rumination, but no implicit depressed self-associations or RSFC abnormalities were observed between patients and controls. Nevertheless, relapse was related to i) baseline RSFC between the ventral default mode network and the precuneus, dorsomedial frontal gyrus, and inferior occipital lobe, ii) implicit self-associations, and iii) uncontrollability of ruminative thinking, when controlled for depressive symptomatology. Moreover, preliminary machine learning classifiers demonstrated that RSFC within the investigated networks predicted relapse on an individual basis. CONCLUSIONS Remitted MDD patients seem to be commonly characterized by abnormal rumination, but not by implicit self-associations or abnormalities in relevant brain networks. Nevertheless, relapse was predicted by self-related cognitions and default mode RSFC during remission, suggesting that variations in self-relevant processing play a role in the complex dynamics associated with the vulnerability to developing recurrent depressive episodes. CLINICAL TRIAL REGISTRATION Netherlands Trial Register, August 18, 2015, trial number NL53205.042.15.
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Affiliation(s)
- Rozemarijn S van Kleef
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands.
| | - Pallavi Kaushik
- Bernoulli Institute of Mathematics, Computer Science and Artificial Intelligence, University of Groningen, the Netherlands; Department of Computer Science and Engineering, Indian Institute of Technology, Roorkee, India
| | - Marlijn Besten
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands; Department of Clinical and Developmental Neuropsychology, Faculty of Behavioural and Social Sciences, University of Groningen, Groningen, the Netherlands
| | - Jan-Bernard C Marsman
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands
| | - Claudi L H Bockting
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Marieke van Vugt
- Bernoulli Institute of Mathematics, Computer Science and Artificial Intelligence, University of Groningen, the Netherlands
| | - André Aleman
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands; Department of Clinical and Developmental Neuropsychology, Faculty of Behavioural and Social Sciences, University of Groningen, Groningen, the Netherlands
| | - Marie-José van Tol
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, the Netherlands
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Teng C, Liu T, Zhang N, Zhong Y, Wang C. Cognitive behavioral therapy may rehabilitate abnormally functional communication pattern among the triple-network in major depressive disorder: A follow-up study. J Affect Disord 2022; 304:28-39. [PMID: 35192866 DOI: 10.1016/j.jad.2022.02.050] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Revised: 02/12/2022] [Accepted: 02/15/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Cognitive behavioral therapy (CBT) is an established treatment for Major Depressive Disorder (MDD). MDD is characterized by imbalanced communication patterns among three networks: the central executive network (CEN), the default mode network (DMN) and the salience network (SN). The effect of CBT in restoring communications among these networks in MDD is unknown. METHODS Thirty-three patients with MDD and 27 healthy controls (HC) participated in the study. Patients were treated with CBT. Resting-state functional magnetic resonance imaging (rs-fMRI) data were obtained in patients at three stages (T0: before treatment; T1: after 6 weeks CBT; T2: after 28 weeks CBT) and in HC (only T0). Both independent component analysis (ICA) and granger causality analysis (GCA) were used to explore dynamic causal communication patterns among the three networks (CEN, DMN, SN) over a course of CBT treatment. RESULTS In the HC group, the SN had an inhibitory causal effect on CEN; the CEN and DMN had an excitatory causal effect on the SN. The SN had an inhibitory causal effect on the CEN and the DMN; only the DMN had an excitatory causal effect on the SN in the MDD patients at the T0 stage. As the CBT treatment went on for MDD patients, the CEN restored excitatory causal effect on the SN, and the SN lost inhibitory effect on the DMN. This result mimicked the one found in the HC group. Four regions, left ventromedial prefrontal cortex (lvmPFC), posterior cingulate gyrus (PCC), right inferior parietal lobule (rIPL) and right insula, were implicated in mediating network communications. LIMITATIONS The findings should be considered preliminary given the small sample sizes, and assessed only one stage in HC subjects. CONCLUSION CBT may enhance the regulatory function of the SN, and rehabilitate the imbalanced brain network communication mode in the MDD. PCC, lvmPFC and rIPL may all be potential targets of CBT.
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Affiliation(s)
- Changjun Teng
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Tianchen Liu
- School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, China
| | - Ning Zhang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China; School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, China
| | - Yuan Zhong
- School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, China.
| | - Chun Wang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China; School of Psychology, Nanjing Normal University, Nanjing, Jiangsu, China.
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10
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Yun JY, Kim YK. Graph theory approach for the structural-functional brain connectome of depression. Prog Neuropsychopharmacol Biol Psychiatry 2021; 111:110401. [PMID: 34265367 DOI: 10.1016/j.pnpbp.2021.110401] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 06/30/2021] [Accepted: 07/07/2021] [Indexed: 01/22/2023]
Abstract
To decipher the organizational styles of neural underpinning in major depressive disorder (MDD), the current article reviewed recent neuroimaging studies (published during 2015-2020) that applied graph theory approach to the diffusion tensor imaging data or functional brain activation data acquired during task-free resting state. The global network organization of resting-state functional connectivity network in MDD were diverse according to the onset age and medication status. Intra-modular functional connections were weaker in MDD compared to healthy controls (HC) for default mode and limbic networks. Weaker local graph metrics of default mode, frontoparietal, and salience network components in MDD compared to HC were also found. On the contrary, brain regions comprising the limbic, sensorimotor, and subcortical networks showed higher local graph metrics in MDD compared to HC. For the brain white matter-based structural connectivity network, the global network organization was comparable to HC in adult MDD but was attenuated in late-life depression. Local graph metrics of limbic, salience, default-mode, subcortical, insular, and frontoparietal network components in structural connectome were affected from the severity of depressive symptoms, burden of perceived stress, and treatment effects. Collectively, the current review illustrated changed global network organization of structural and functional brain connectomes in MDD compared to HC and were varied according to the onset age and medication status. Intra-modular functional connectivity within the default mode and limbic networks were weaker in MDD compared to HC. Local graph metrics of structural connectome for MDD reflected severity of depressive symptom and perceived stress, and were also changed after treatments. Further studies that explore the graph metrics-based neural correlates of clinical features, cognitive styles, treatment response and prognosis in MDD are required.
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Affiliation(s)
- Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea; Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea.
| | - Yong-Ku Kim
- Department of Psychiatry, College of Medicine, Korea University, Seoul, South Korea
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11
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Xu SX, Deng WF, Qu YY, Lai WT, Huang TY, Rong H, Xie XH. The integrated understanding of structural and functional connectomes in depression: A multimodal meta-analysis of graph metrics. J Affect Disord 2021; 295:759-770. [PMID: 34517250 DOI: 10.1016/j.jad.2021.08.120] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 07/26/2021] [Accepted: 08/28/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND From the perspective of information processing, an integrated understanding of the structural and functional connectomes in depression patients is important, a multimodal meta-analysis is required to detect the robust alterations in graph metrics across studies. METHODS Following a systematic search, 952 depression patients and 1447 controls in nine diffusion magnetic resonance imaging (dMRI) and twelve rest state functional MRI (rs-fMRI) studies with high methodological quality met the inclusion criteria and were included in the meta-analysis. RESULTS Regarding the dMRI results, no significant differences of meta-analytic metrics were found; regarding the rs-fMRI results, the modularity and local efficiency were found to be significantly lower in the depression group than in the controls (Hedge's g = -0.330 and -0.349, respectively). CONCLUSION Our findings suggested a lower modularity and network efficiency in the rs-fMRI network in depression patients, indicating that the pathological imbalances in brain connectomes needs further exploration. LIMITATIONS Included number of trials was low and heterogeneity should be noted.
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Affiliation(s)
- Shu-Xian Xu
- Brain Function and Psychosomatic Medicine Institute, Second People's Hospital of Huizhou, Huizhou, Guangdong, China; Department of Psychiatry, Shenzhen Kangning Hospital and Shenzhen Mental Health Center, Shenzhen, Guangdong, China; Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China
| | - Wen-Feng Deng
- Huizhou Center for Disease Control and Prevention, Huizhou, Guangdong, China
| | - Ying-Ying Qu
- Center of Acute Psychiatry Service, Second People's Hospital of Huizhou, Huizhou, Guangdong, China
| | - Wen-Tao Lai
- Department of Radiology, Shenzhen Kangning Hospital and Shenzhen Mental Health Center, Shenzhen, Guangdong, China
| | - Tan-Yu Huang
- Department of Radiology, Second People's Hospital of Huizhou, Huizhou, Guangdong, China
| | - Han Rong
- Department of Psychiatry, Shenzhen Kangning Hospital and Shenzhen Mental Health Center, Shenzhen, Guangdong, China; Affiliated Shenzhen Clinical College of Psychiatry, Jining Medical University, Jining, Shandong, China
| | - Xin-Hui Xie
- Brain Function and Psychosomatic Medicine Institute, Second People's Hospital of Huizhou, Huizhou, Guangdong, China; Department of Psychiatry, Shenzhen Kangning Hospital and Shenzhen Mental Health Center, Shenzhen, Guangdong, China; Center of Acute Psychiatry Service, Second People's Hospital of Huizhou, Huizhou, Guangdong, China.
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12
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Xiong G, Dong D, Cheng C, Jiang Y, Sun X, He J, Li C, Gao Y, Zhong X, Zhao H, Wang X, Yao S. Potential structural trait markers of depression in the form of alterations in the structures of subcortical nuclei and structural covariance network properties. NEUROIMAGE-CLINICAL 2021; 32:102871. [PMID: 34749291 PMCID: PMC8578037 DOI: 10.1016/j.nicl.2021.102871] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 10/20/2021] [Accepted: 10/29/2021] [Indexed: 11/18/2022]
Abstract
It has been proposed recently that major depressive disorder (MDD) could represent an adaptation to conserve energy after the perceived loss of an investment in a vital source, such as group identity, personal assets, or relationships. Energy conserving behaviors associated with MDD may form a persistent marker in brain regions and networks involved in cognition and emotion regulation. In this study, we examined whether subcortical regions and volume-based structural covariance networks (SCNs) have state-independent alterations (trait markers). First-episode drug-naïve currently depressed (cMDD) patients (N = 131), remitted MDD (RD) patients (N = 67), and healthy controls (HCs, N = 235) underwent structural magnetic resonance imaging (MRI). Subcortical gray matter volumes (GMVs) were calculated in FreeSurfer software, and group differences in GMVs and SCN were analyzed. Compared to HCs, major findings were decreased GMVs of left pallidum and pulvinar anterior of thalamus in the cMDD and RD groups, indicative of a trait marker. Relative to HCs, subcortical SCNs of both cMDD and RD patients were found to have reduced small-world-ness and path length, which together may represent a trait-like topological feature of depression. In sum, the left pallidum, left pulvinar anterior of thalamus volumetric alterations may represent trait marker and reduced small-world-ness, path length may represent trait-like topological feature of MDD.
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Affiliation(s)
- Ge Xiong
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Daifeng Dong
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Chang Cheng
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Yali Jiang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China; School of Psychology, South China Normal University, Guangzhou 510631, China
| | - Xiaoqiang Sun
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Jiayue He
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Chuting Li
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan 410011, China
| | - Yidian Gao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Xue Zhong
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Haofei Zhao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan 410011, China
| | - Shuqiao Yao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China; China National Clinical Research Center on Mental Disorders (Xiangya), Changsha, Hunan 410011, China.
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13
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Liu X, He C, Fan D, Zhu Y, Zang F, Wang Q, Zhang H, Zhang Z, Zhang H, Xie C. Disrupted rich-club network organization and individualized identification of patients with major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2021; 108:110074. [PMID: 32818534 DOI: 10.1016/j.pnpbp.2020.110074] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 07/14/2020] [Accepted: 08/10/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND Altered structural and functional brain networks have been extensively studied in major depressive disorder (MDD) patients. However, whether the differential connectivity patterns in the rich-club organization, assessed from structural brain network analyses, and the associated connections of these regions are particularly susceptible to depression remain unclear. METHODS We acquired resting-state functional magnetic resonance imaging (R-fMRI) and diffusion tensor imaging (DTI) from 31 unmedicated MDD patients and 32 cognitively normal (CN) subjects and completed a series of neuropsychological tests. Rich-club organization, network properties, and coupling between structural and functional connectivity (SC-FC) were explored. Furthermore, whether these indices could potentially deliver effective clinical predictive value for MDD patients were examined. RESULTS The MDD patients showed disrupted structural rich-club organization and modularity, as well as a distinct correlation pattern between global efficiency and rich-club organization. Importantly, reduced SC-FC coupling, reflecting a decreased agreement in the integrity of the networks, was significantly associated with the strength of structural rich-club connections in the MDD patients. Furthermore, the disrupted structural rich-club organization, which was primarily located in the default mode network (DMN) and executive control network (ECN), emerged as a valuable indicator to distinguish between MDD and CN. CONCLUSIONS Findings of this study identified that the disrupted rich-club structural organization significantly influenced brain structural network modularity and integrity and could serve as a promising biological marker for the identification of MDD patients.
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Affiliation(s)
- Xinyi Liu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Cancan He
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Dandan Fan
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Yao Zhu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Feifei Zang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Qing Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Haisan Zhang
- Psychology School of Xinxiang Medical University, Xinxiang, Henan 453003, China; Xinxiang Key Laboratory of Multimodal Brain Imaging, Henan Provincial Mental Hospital, Xinxiang Medical University, Xinxiang, Henan 45300, China; Department of Psychiatry, Henan Provincial Mental Hospital, Xinxiang Medical University, Xinxiang, Henan 45300, China
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China; Neuropsychiatric Institute, Affiliated ZhongDa Hospital, Southeast University, Nanjing, Jiangsu 210009, China
| | - Hongxing Zhang
- Psychology School of Xinxiang Medical University, Xinxiang, Henan 453003, China; Xinxiang Key Laboratory of Multimodal Brain Imaging, Henan Provincial Mental Hospital, Xinxiang Medical University, Xinxiang, Henan 45300, China; Department of Psychiatry, Henan Provincial Mental Hospital, Xinxiang Medical University, Xinxiang, Henan 45300, China.
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China; Neuropsychiatric Institute, Affiliated ZhongDa Hospital, Southeast University, Nanjing, Jiangsu 210009, China.
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14
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Impaired global efficiency in boys with conduct disorder and high callous unemotional traits. J Psychiatr Res 2021; 138:560-568. [PMID: 33991994 DOI: 10.1016/j.jpsychires.2021.04.041] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 04/06/2021] [Accepted: 04/25/2021] [Indexed: 11/22/2022]
Abstract
Callous unemotional (CU) traits differentiate subtypes of conduct disorder (CD). It has been suggested that CU traits may be related to topographical irregularities that hinder information integration. To date, there is limited evidence of whether CU traits may be associated with abnormal brain topology. In this study, 43 CD boys with high and low CU trait (CD-HCU, CD-LCU), and 46 healthy controls (HCs) were subjected to resting-state functional magnetic resonance imaging to investigate how CU trait level and conduct problems may be reflected in topological organization. Brain functional networks were constructed and network/nodal properties, including small-world properties and network/nodal efficiency, were calculated. Topological analysis revealed that, compared with HCs, CD-HCU group were characterized by decreased small-worldness (σ), decreased global efficiency, and increased path length (λ). These variables were similar between the CD-LCU and HC groups. Self-reported CU traits in CD patients correlated negatively with global efficiency and positively with λ. Regional analysis revealed diminished nodal efficiency in the right amygdala in the CD-HCU group compared with HCs. The present results suggest that disrupted global efficiency, together with a regional abnormality affecting the amygdala, may contribute to abnormal information processing and integration in adolescents with CD and high CU traits.
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15
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Uykur AB, Yıldız S, Velioglu HA, Ozsimsek A, Oktem EO, Bayraktaroglu Z, Ergun T, Lakadamyali H, Hanoglu L, Cankaya S, Saatçi Ö, Yulug B. Topological network mechanisms of clinical response to antidepressant treatment in drug-naive major depressive disorder. J Clin Neurosci 2020; 84:82-90. [PMID: 33358344 DOI: 10.1016/j.jocn.2020.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 10/25/2020] [Accepted: 12/06/2020] [Indexed: 12/28/2022]
Abstract
AIM There is rapidly increasing evidence that remission of MDD is associated with substantial changes in functional brain connectivity. These New data have provided a holistic view on the mechanism of antidepressants on multiple levels that goes beyond their conventional effects on neurotransmitters. METHOD The study was approved by the Local Ethics Committee of Istanbul Medipol University (10840098-604.01.01-E.65129) and followed the Helsinki Declaration principles. In our study, we have evaluated the effect of six weeks of treatment with antidepressants (escitalopram and duloxetine), and tested the underlying brain functional connectivity through a Graph analysis approach in a well-defined first-episode, drug-naive, and non-comorbid population with MDD. RESULTS Beyond indicating that there was a significant correlation between the antidepressant response and topological characteristics of the brain, our results suggested that global rather than regional network alterations may be implicated in the antidepressant effect. CONCLUSION Despite the small-sample size and non-controlled study design, our study provides important and relevant clinical data regarding the underlying mechanisms of the antidepressants on topological dynamics in the human brain.
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Affiliation(s)
- Abdullah Burak Uykur
- Alanya Alaaddin Keykubat University, Department of Psychiatry, Antalya/Alanya, Turkey.
| | - Sultan Yıldız
- Istanbul Medipol University, Restorative and Regenerative Medicine Center, Istanbul, Turkey
| | - Halil Aziz Velioglu
- Istanbul Medipol University, Restorative and Regenerative Medicine Center, Istanbul, Turkey
| | - Ahmet Ozsimsek
- Alanya Alaaddin Keykubat University, Department of Neurology, Antalya/Alanya, Turkey
| | - Ece Ozdemir Oktem
- Alanya Alaaddin Keykubat University, Department of Neurology, Antalya/Alanya, Turkey
| | - Zübeyir Bayraktaroglu
- Istanbul Medipol University, Restorative and Regenerative Medicine Center, Istanbul, Turkey
| | - Tarkan Ergun
- Alanya Alaaddin Keykubat University, Department of Radiology, Antalya/Alanya, Turkey
| | - Hatice Lakadamyali
- Alanya Alaaddin Keykubat University, Department of Radiology, Antalya/Alanya, Turkey
| | - Lütfü Hanoglu
- Istanbul Medipol University, Restorative and Regenerative Medicine Center, Istanbul, Turkey; Istanbul Medipol University, Department of Neurology, Istanbul, Turkey
| | - Seyda Cankaya
- Alanya Alaaddin Keykubat University, Department of Neurology, Antalya/Alanya, Turkey
| | - Özlem Saatçi
- Istanbul Sancaktepe Research Hospital, Department of Rhinology, Istanbul, Turkey
| | - Burak Yulug
- Alanya Alaaddin Keykubat University, Department of Neurology, Antalya/Alanya, Turkey; Istanbul Medipol University, Restorative and Regenerative Medicine Center, Istanbul, Turkey
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16
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Zhao Y, Niu R, Lei D, Shah C, Xiao Y, Zhang W, Chen Z, Lui S, Gong Q. Aberrant Gray Matter Networks in Non-comorbid Medication-Naive Patients With Major Depressive Disorder and Those With Social Anxiety Disorder. Front Hum Neurosci 2020; 14:172. [PMID: 32587507 PMCID: PMC7298146 DOI: 10.3389/fnhum.2020.00172] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 04/20/2020] [Indexed: 02/05/2023] Open
Abstract
Major depressive disorder (MDD) and social anxiety disorder (SAD) are among the most prevalent and frequently co-occurring psychiatric disorders in adults and may have, at least in part, a common etiology. However, the unique and the shared neuroanatomical characteristics of the two disorders have not been fully identified. The aim of this study was to compare the topological organization of gray matter networks between non-comorbid medication-naive MDD patients and SAD patients. High-resolution T1-weighted images were acquired from 37 non-comorbid medication-naive MDD patients, 24 non-comorbid medication-naive SAD patients, and 41 healthy controls. Single-subject gray matter graphs were extracted from structural MRI scans, and whole-brain neuroanatomic organization was compared across the three groups. The relationships between brain network measures and clinical characteristics were analyzed. Relative to healthy controls, both the MDD and the SAD patients showed global decreases in clustering coefficient, normalized clustering coefficient, and small-worldness and locally decreased nodal centralities and morphological connections in the left insular, lingual, and calcarine cortices. Compared with healthy controls, the SAD patients exhibited increased nodal centralities and morphological connections mainly involving the prefrontal cortex and the sensorimotor network. Furthermore, compared to the SAD patients, the MDD patients showed increased characteristic path length, reduced global efficiency, and decreased nodal centralities and morphological connections in the right middle occipital gyrus and the right postcentral gyrus. Our findings provide new evidence for shared and specific similarity-based gray matter network alterations in MDD and SAD and emphasize that the psychopathological changes in the right middle occipital gyrus and the right postcentral gyrus might be different between the two disorders.
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Affiliation(s)
- Youjin Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Running Niu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China.,Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Du Lei
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Chandan Shah
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Yuan Xiao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Ziqi Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
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17
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Jiao K, Xu H, Teng C, Song X, Xiao C, Fox PT, Zhang N, Wang C, Zhong Y. Connectivity patterns of cognitive control network in first episode medication-naive depression and remitted depression. Behav Brain Res 2019; 379:112381. [PMID: 31770543 DOI: 10.1016/j.bbr.2019.112381] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Revised: 11/19/2019] [Accepted: 11/22/2019] [Indexed: 01/19/2023]
Abstract
BACKGROUND Cognitive dysfunctions, such as impaired cognitive control, are frequently observed in patients with major depressive disorder (MDD). Although the cognitive control network (CCN) is widely considered a core feature of major depressive disorder (MDD), the relationship between cognitive dysfunction and symptom dimensions remains unclear. This study investigated differences in resting-state functional connectivity of the cognitive control network (CCN) between first-episode medication-naive MDD patients and remitted MDD. METHODS We collected resting-state functional MRI (rs-fMRI) data from 22 first-episode medication-naive major depressive disorder (fMDD) patients, 20 patients previously diagnosed with MDD in the remitted phase of depression (rMDD), and 20 healthy controls (HC). The CCN was derived from fMRI images using independent component analysis (ICA), a data-driven image analysis method. RESULTS Changes in functional connectivity (FC) within the CCN was mainly attenuated in the right dorsolateral prefrontal cortex and the left inferior parietal lobule, while strengthened in the right dorsal anterior cingulate cortex and the right insula in both fMDD and rMDD groups. Compared with the fMDD group, the rMDD group had decreased FC in the bilateral insula and the right dorsolateral prefrontal cortex. Further analysis explored that the FC in the bilateral insula, the right dorsal anterior cingulate cortex and the right inferior parietal lobule were correlated positively cognitive disturbance factor scores in both patients groups. CONCLUSIONS These findings are in agreement with the previous findings that the cognitive control network are impaired in MDD. Furthermore, our results suggest that the alteration of CCN might underpin the cognitive disturbance and the distinct patterns of the CCN between fMDD and rMDD patients may be an important target for effective cognitive remediation in MDD.
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Affiliation(s)
- Kaili Jiao
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Huazhen Xu
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Changjun Teng
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiu Song
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chaoyong Xiao
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
| | - Peter T Fox
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; South Texas Veterans Healthcare System, University of Texas Health Science Center at San Antonio, United States; Research Imaging Institute, University of Texas Health San Antonio, United States
| | - Ning Zhang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Chun Wang
- Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China; Cognitive Behavioral Therapy Institute of Nanjing Medical University, Nanjing, Jiangsu, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, Jiangsu, China; School of Psychology, Nanjing Normal University, Nanjing, China.
| | - Yuan Zhong
- School of Psychology, Nanjing Normal University, Nanjing, China; Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing Normal University, Nanjing, China.
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18
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Xiong G, Dong D, Cheng C, Jiang Y, Sun X, He J, Li C, Gao Y, Zhong X, Zhao H, Wang X, Yao S. State-independent and -dependent structural alterations in limbic-cortical regions in patients with current and remitted depression. J Affect Disord 2019; 258:1-10. [PMID: 31382099 DOI: 10.1016/j.jad.2019.07.065] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2019] [Revised: 07/24/2019] [Accepted: 07/29/2019] [Indexed: 12/21/2022]
Abstract
BACKGROUND The high recurrence of major depressive disorder (MDD) may derive from underlying state-independent structural alterations. METHODS First-episode drug-naïve currently depressed (cMDD) patients (N = 97), remitted depressed (RD) patients (N = 72), and healthy controls (HCs, N = 100) underwent structural magnetic resonance imaging (MRI). Group differences in cortical thickness (CT), surface area (SA), and local gyrification index (lGI) were analyzed in FreeSurfer. RESULTS Both groups of depressed patients had significantly decreased CT, relative to HCs, in the left precentral gyrus and significantly increased lGI values in the left superior frontal gyrus (SFG) indicative of state-independent alterations. Relative to HCs, the cMDD group had decreased CT of the SFG, caudal middle frontal gyrus (MFG), posterior cingulate cortex (PCC), and lateral occipital regions as well as increased SA or lGI of the superior temporal gyrus, precuneus, and pericalcarine, whereas the RD group had increased SA or lGI of the SFG, caudal MFG, and supramarginal gyrus; these alterations appeared to be state-dependent. SA or lGI values of the fusiform gyrus, inferior temporal gyrus, and superior parietal lobule differed between the cMDD and RD groups, consistent with state-dependent alterations. Beck depression inventory scores correlated with CT or lGI values of the caudal MFG, lateral occipital cortex in depressed patients. LIMITATIONS The structural features of several subcortical limbic regions were not analyzed. CONCLUSIONS Left precentral gyrus CT and left SFG gyrification alterations may represent state-independent alterations in MDD.
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Affiliation(s)
- Ge Xiong
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Daifeng Dong
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Chang Cheng
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Yali Jiang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Xiaoqiang Sun
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Jiayue He
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Chuting Li
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China; China National Clinical Research Center on Mental disorders (Xiangya), Changsha, Hunan 410011, China
| | - Yidian Gao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Xue Zhong
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Haofei Zhao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China; China National Clinical Research Center on Mental disorders (Xiangya), Changsha, Hunan 410011, China
| | - Shuqiao Yao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China; Medical Psychological Institute of Central South University, Changsha, Hunan 410011, China; China National Clinical Research Center on Mental disorders (Xiangya), Changsha, Hunan 410011, China.
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19
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Dinga R, Schmaal L, Penninx BWJH, van Tol MJ, Veltman DJ, van Velzen L, Mennes M, van der Wee NJA, Marquand AF. Evaluating the evidence for biotypes of depression: Methodological replication and extension of. NEUROIMAGE-CLINICAL 2019; 22:101796. [PMID: 30935858 PMCID: PMC6543446 DOI: 10.1016/j.nicl.2019.101796] [Citation(s) in RCA: 167] [Impact Index Per Article: 33.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 03/22/2019] [Accepted: 03/25/2019] [Indexed: 10/29/2022]
Abstract
BACKGROUND Psychiatric disorders are highly heterogeneous, defined based on symptoms with little connection to potential underlying biological mechanisms. A possible approach to dissect biological heterogeneity is to look for biologically meaningful subtypes. A recent study Drysdale et al. (2017) showed promising results along this line by simultaneously using resting state fMRI and clinical data and identified four distinct subtypes of depression with different clinical profiles and abnormal resting state fMRI connectivity. These subtypes were predictive of treatment response to transcranial magnetic stimulation therapy. OBJECTIVE Here, we attempted to replicate the procedure followed in the Drysdale et al. study and their findings in a different clinical population and a more heterogeneous sample of 187 participants with depression and anxiety. We aimed to answer the following questions: 1) Using the same procedure, can we find a statistically significant and reliable relationship between brain connectivity and clinical symptoms? 2) Is the observed relationship similar to the one found in the original study? 3) Can we identify distinct and reliable subtypes? 4) Do they have similar clinical profiles as the subtypes identified in the original study? METHODS We followed the original procedure as closely as possible, including a canonical correlation analysis to find a low dimensional representation of clinically relevant resting state fMRI features, followed by hierarchical clustering to identify subtypes. We extended the original procedure using additional statistical tests, to test the statistical significance of the relationship between resting state fMRI and clinical data, and the existence of distinct subtypes. Furthermore, we examined the stability of the whole procedure using resampling. RESULTS AND CONCLUSION As in the original study, we found extremely high canonical correlations between functional connectivity and clinical symptoms, and an optimal three-cluster solution. However, neither canonical correlations nor clusters were statistically significant. On the basis of our extensive evaluations of the analysis methodology used and within the limits of comparison of our sample relative to the sample used in Drysdale et al., we argue that the evidence for the existence of the distinct resting state connectivity-based subtypes of depression should be interpreted with caution.
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Affiliation(s)
- Richard Dinga
- Department of Psychiatry, Amsterdam UMC, Amsterdam, the Netherlands.
| | - Lianne Schmaal
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Australia; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | | | - Marie Jose van Tol
- Cognitive Neuroscience Center, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Amsterdam, the Netherlands
| | - Laura van Velzen
- Department of Psychiatry, Amsterdam UMC, Amsterdam, the Netherlands
| | - Maarten Mennes
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Nic J A van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
| | - Andre F Marquand
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
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