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Huang XL, Gao J, Wang YM, Zhu F, Qin J, Yao QN, Zhang XB, Sun HY. Neuropathological characteristics of abnormal white matter functional signaling in adolescents with major depression. World J Psychiatry 2024; 14:276-286. [PMID: 38464765 PMCID: PMC10921285 DOI: 10.5498/wjp.v14.i2.276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 12/13/2023] [Accepted: 01/08/2024] [Indexed: 02/06/2024] Open
Abstract
BACKGROUND Major depression disorder (MDD) constitutes a significant mental health concern. Epidemiological surveys indicate that the lifetime prevalence of depression in adolescents is much higher than that in adults, with a corresponding increased risk of suicide. In studying brain dysfunction associated with MDD in adole-scents, research on brain white matter (WM) is sparse. Some researchers even mistakenly regard the signals generated by the WM as noise points. In fact, studies have shown that WM exhibits similar blood oxygen level-dependent signal fluctuations. The alterations in WM signals and their relationship with disease severity in adolescents with MDD remain unclear. AIM To explore potential abnormalities in WM functional signals in adolescents with MDD. METHODS This study involved 48 adolescent patients with MDD and 31 healthy controls (HC). All participants were assessed using the Patient Health Questionnaire-9 Scale and the mini international neuropsychiatric interview (MINI) suicide inventory. In addition, a Siemens Skyra 3.0T magnetic resonance scanner was used to obtain the subjects' image data. The DPABI software was utilized to calculate the WM signal of the fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity, followed by a two-sample t-test between the MDD and HC groups. Independent component analysis (ICA) was also used to evaluate the WM functional signal. Pearson's correlation was performed to assess the relationship between statistical test results and clinical scales. RESULTS Compared to HC, individuals with MDD demonstrated a decrease in the fALFF of WM in the corpus callosum body, left posterior limb of the internal capsule, right superior corona radiata, and bilateral posterior corona radiata [P < 0.001, family-wise error (FWE) voxel correction]. The regional homogeneity of WM increased in the right posterior limb of internal capsule and left superior corona radiata, and decreased in the left superior longitudinal fasciculus (P < 0.001, FWE voxel correction). The ICA results of WM overlapped with those of regional homo-geneity. The fALFF of WM signal in the left posterior limb of the internal capsule was negatively correlated with the MINI suicide scale (P = 0.026, r = -0.32), and the right posterior corona radiata was also negatively correlated with the MINI suicide scale (P = 0.047, r = -0.288). CONCLUSION Adolescents with MDD involves changes in WM functional signals, and these differences in brain regions may increase the risk of suicide.
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Affiliation(s)
- Xin-Lin Huang
- Imaging and Nuclear Medicine, Jiamusi University, Jiamusi 154000, Heilongjiang Province, China
| | - Ju Gao
- Department of Psychiatry, The Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu Province, China
| | - Yong-Ming Wang
- School of Biology & Basic Medical Sciences, Medical College of Soochow University, Suzhou 215137, Jiangsu Province, China
| | - Feng Zhu
- Department of Psychiatry, The Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu Province, China
| | - Jing Qin
- Department of Radiology, Shanghai Anting Hospital, Shanghai 20000, China
| | - Qian-Nan Yao
- Imaging and Nuclear Medicine, Jiamusi University, Jiamusi 154000, Heilongjiang Province, China
| | - Xiao-Bin Zhang
- Department of Psychiatry, The Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu Province, China
| | - Hong-Yan Sun
- Department of Radiology, The Affiliated Guangji Hospital of Soochow University, Suzhou 215137, Jiangsu Province, China
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Wu B, Long X, Cao Y, Xie H, Wang X, Roberts N, Gong Q, Jia Z. Abnormal intrinsic brain functional network dynamics in first-episode drug-naïve adolescent major depressive disorder. Psychol Med 2024:1-10. [PMID: 38173122 DOI: 10.1017/s0033291723003719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
BACKGROUND Alterations in brain functional connectivity (FC) have been frequently reported in adolescent major depressive disorder (MDD). However, there are few studies of dynamic FC analysis, which can provide information about fluctuations in neural activity related to cognition and behavior. The goal of the present study was therefore to investigate the dynamic aspects of FC in adolescent MDD patients. METHODS Resting-state functional magnetic resonance imaging data were acquired from 94 adolescents with MDD and 78 healthy controls. Independent component analysis, a sliding-window approach, and graph-theory methods were used to investigate the potential differences in dynamic FC properties between the adolescent MDD patients and controls. RESULTS Three main FC states were identified, State 1 which was predominant, and State 2 and State 3 which occurred less frequently. Adolescent MDD patients spent significantly more time in the weakly-connected and relatively highly-modularized State 1, spent significantly less time in the strongly-connected and low-modularized State 2, and had significantly higher variability of both global and local efficiency, compared to the controls. Classification of patients with adolescent MDD was most readily performed based on State 1 which exhibited disrupted intra- and inter-network FC involving multiple functional networks. CONCLUSIONS Our study suggests local segregation and global integration impairments and segregation-integration imbalance of functional networks in adolescent MDD patients from the perspectives of dynamic FC. These findings may provide new insights into the neurobiology of adolescent MDD.
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Affiliation(s)
- Baolin Wu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Xipeng Long
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Yuan Cao
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Hongsheng Xie
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Xiuli Wang
- Department of Clinical Psychology, The Fourth People's Hospital of Chengdu, Chengdu, China
| | - Neil Roberts
- The Queens Medical Research Institute (QMRI), School of Clinical Sciences, University of Edinburgh, Edinburgh, UK
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, China
| | - Zhiyun Jia
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
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Cîrstian R, Pilmeyer J, Bernas A, Jansen JFA, Breeuwer M, Aldenkamp AP, Zinger S. Objective biomarkers of depression: A study of Granger causality and wavelet coherence in resting-state fMRI. J Neuroimaging 2023; 33:404-414. [PMID: 36710075 DOI: 10.1111/jon.13085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 01/09/2023] [Accepted: 01/10/2023] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND AND PURPOSE The lack of a robust diagnostic biomarker makes understanding depression from a neurobiological standpoint an important goal, especially in the context of brain imaging. METHODS In this study, we aim to create novel image-based features for objective diagnosis of depression. Resting-state network time series are used to investigate neurodynamics with the help of wavelet coherence and Granger causality (G-causality). Three new features are introduced: total wavelet coherence, wavelet lead coherence, and wavelet coherence blob analysis. The fourth feature, pair-wise conditional G-causality, is used to establish the causality between resting-state networks. We use the proposed features to classify depression in adult subjects. RESULTS We obtained an accuracy of 86% in the wavelet lead coherence, 80% in Granger causality, and 86% in wavelet coherence blob analysis. Subjects with depression showed hyperconnectivity between the dorsal attention network and the auditory network as well as between the posterior default mode network and the dorsal attention network. Hypoconnectivity was found between the anterior default mode network and the auditory network as well as the right frontoparietal network and the lateral visual network. An abnormal co-activation pattern was found between cerebellum and the lateral motor network according to the wavelet coherence blob analysis. CONCLUSION Based on abnormal functional dynamics between brain networks, we were able to identify subjects with depression with high accuracy. The findings of this study contribute to the understanding of the impaired emotional and attention processing associated with depression, as well as decreased motor activity.
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Affiliation(s)
- Ramona Cîrstian
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Jesper Pilmeyer
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Research and Development, Epilepsy Center Kempenhaeghe, Heeze, The Netherlands
| | - Antoine Bernas
- Department of Biophysics, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Jacobus F A Jansen
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Radiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Marcel Breeuwer
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Albert P Aldenkamp
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Svitlana Zinger
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Research and Development, Epilepsy Center Kempenhaeghe, Heeze, The Netherlands
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Yin W, Zhou X, Li C, You M, Wan K, Zhang W, Zhu W, Li M, Zhu X, Qian Y, Sun Z. The Clustering Analysis of Time Properties in Patients With Cerebral Small Vessel Disease: A Dynamic Connectivity Study. Front Neurol 2022; 13:913241. [PMID: 35795790 PMCID: PMC9251301 DOI: 10.3389/fneur.2022.913241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 05/27/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeThis study aimed to investigate the dynamic functional connectivity (DFC) pattern in cerebral small vessel disease (CSVD) and explore the relationships between DFC temporal properties and cognitive impairment in CSVD.MethodsFunctional data were collected from 67 CSVD patients, including 35 patients with subcortical vascular cognitive impairment (SVCI) and 32 cognitively unimpaired (CU) patients, as well as 35 healthy controls (HCs). The DFC properties were estimated by k-means clustering analysis. DFC strength analysis was used to explore the regional functional alterations between CSVD patients and HCs. Correlation analysis was used for DFC properties with cognition and SVD scores, respectively.ResultsThe DFC analysis showed three distinct connectivity states (state I: sparsely connected, state II: strongly connected, state III: intermediate pattern). Compared to HCs, CSVD patients exhibited an increased proportion in state I and decreased proportion in state II. Besides, CSVD patients dwelled longer in state I while dwelled shorter in state II. CSVD subgroup analyses showed that state I frequently occurred and dwelled longer in SVCI compared with CSVD-CU. Also, the internetwork (frontal-parietal lobe, frontal-occipital lobe) and intranetwork (frontal lobe, occipital lobe) functional activities were obviously decreased in CSVD. Furthermore, the fractional windows and mean dwell time (MDT) in state I were negatively correlated with cognition in CSVD but opposite to cognition in state II.ConclusionPatients with CSVD accounted for a higher proportion and dwelled longer mean time in the sparsely connected state, while presented lower proportion and shorter mean dwell time in the strongly connected state, which was more prominent in SVCI. The changes in the DFC are associated with altered cognition in CSVD. This study provides a better explanation of the potential mechanism of CSVD patients with cognitive impairment from the perspective of DFC.
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Affiliation(s)
- Wenwen Yin
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xia Zhou
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Chenchen Li
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Mengzhe You
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Ke Wan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Wei Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Wenhao Zhu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Mingxu Li
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xiaoqun Zhu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yinfeng Qian
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zhongwu Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Zhongwu Sun
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Song Y, Huang C, Zhong Y, Wang X, Tao G. Abnormal Reginal Homogeneity in Left Anterior Cingulum Cortex and Precentral Gyrus as a Potential Neuroimaging Biomarker for First-Episode Major Depressive Disorder. Front Psychiatry 2022; 13:924431. [PMID: 35722559 PMCID: PMC9199967 DOI: 10.3389/fpsyt.2022.924431] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 05/06/2022] [Indexed: 01/19/2023] Open
Abstract
OBJECTIVE There is no objective method to diagnose major depressive disorder (MDD). This study explored the neuroimaging biomarkers using the support vector machine (SVM) method for the diagnosis of MDD. METHODS 52 MDD patients and 45 healthy controls (HCs) were involved in resting-state functional magnetic resonance imaging (rs-fMRI) scanning. Imaging data were analyzed with the regional homogeneity (ReHo) and SVM methods. RESULTS Compared with HCs, MDD patients showed increased ReHo in the left anterior cingulum cortex (ACC) and decreased ReHo in the left precentral gyrus (PG). No correlations were detected between the ReHo values and the Hamilton Rating Scale for Depression (HRSD) scores. The SVM results showed a diagnostic accuracy of 98.96% (96/97). Increased ReHo in the left ACC, and decreased ReHo in the left PG were illustrated, along with a sensitivity of 98.07%(51/52) and a specificity of100% (45/45). CONCLUSION Our results suggest that abnormal regional neural activity in the left ACC and PG may play a key role in the pathophysiological process of first-episode MDD. Moreover, the combination of ReHo values in the left ACC and precentral gyrusmay serve as a neuroimaging biomarker for first-episode MDD.
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Affiliation(s)
- Yan Song
- Nanning Fifth People's Hospital, Nanning, China
| | - Chunyan Huang
- Department of Cardiology, Tongren Hospital of Wuhan University (Wuhan Third Hospital), Wuhan, China
| | - Yi Zhong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), Beijing, China
| | - Xi Wang
- Department of Mental Health, Taihe Hospital, Hubei University of Medicine, Shiyan, China
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