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Wu J, Yang J, Yuan Z, Zhang J, Zhang Z, Qin T, Li X, Deng H, Gong L. Functional connectome gradient predicts clinical symptoms of chronic insomnia disorder. Prog Neuropsychopharmacol Biol Psychiatry 2024; 135:111120. [PMID: 39154930 DOI: 10.1016/j.pnpbp.2024.111120] [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: 05/29/2024] [Revised: 07/30/2024] [Accepted: 08/15/2024] [Indexed: 08/20/2024]
Abstract
Insomnia is the second most prevalent psychiatric disorder worldwide, but the understanding of the pathophysiology of insomnia remains fragmented. In this study, we calculated the connectome gradient in 50 chronic insomnia disorder (CID) patients and 38 healthy controls (HC) to assess changes due to insomnia and utilized these gradients in a connectome-based predictive modeling (CPM) to predict clinical symptoms associated with insomnia. The results suggested that insomnia led to significant alterations in the functional gradients of some brain areas. Specifically, the gradient scores in the middle frontal gyrus, superior anterior cingulate gyrus, and right nucleus accumbens were significantly higher in the CID patients than in the HC group, whereas the scores in the middle occipital gyrus, right fusiform gyrus, and right postcentral gyrus were significantly lower than in the HC group. Further correlation analysis revealed that the right middle frontal gyrus is positively correlated with the self-rating anxiety scale (r=0.3702). Additionally, the prediction model built with functional gradients could well predict the sleep quality (r=0.5858), anxiety (r=0.6150), and depression (r=0.4022) levels of insomnia patients. This offers an objective depiction of the clinical diagnosis of insomnia, yielding a beneficial impact on the identification of effective biomarkers and the comprehension of insomnia.
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Affiliation(s)
- Jiahui Wu
- College of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu, China
| | - Jianbo Yang
- Sichuan University of Science and Engineering, Zigong, China
| | - Zhen Yuan
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Macau, SAR China
| | - Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China.
| | - Zhiwei Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Tianwei Qin
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Xiaoxuan Li
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Hanbin Deng
- Sichuan Institute of Computer Sciences, Chengdu, China.
| | - Liang Gong
- Department of Neurology, Chengdu Second People's Hospital, Chengdu, China.
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Chen M, Shao H, Wang L, Ma J, Chen J, Li J, Zhong J, Zhu B, Bi B, Chen K, Wang J, Gong L. Aberrant individual large-scale functional network connectivity and topology in chronic insomnia disorder with and without depression. Prog Neuropsychopharmacol Biol Psychiatry 2024; 136:111158. [PMID: 39368537 DOI: 10.1016/j.pnpbp.2024.111158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2024] [Revised: 09/28/2024] [Accepted: 10/01/2024] [Indexed: 10/07/2024]
Abstract
Insomnia is increasingly prevalent with significant associations with depression. Delineating specific neural circuits for chronic insomnia disorder (CID) with and without depressive symptoms is fundamental to develop precision diagnosis and treatment. In this study, we examine static, dynamic and network topology changes of individual large-scale functional network for CID with (CID-D) and without depression to reveal their specific neural underpinnings. Seventeen individual-specific functional brain networks are obtained using a regularized nonnegative matrix factorization technique. Disorders-shared and -specific differences in static and dynamic large-scale functional network connectivities within or between the cognitive control network, dorsal attention network, visual network, limbic network, and default mode network are found for CID and CID-D. Additionally, CID and CID-D groups showed compromised network topological architecture including reduced small-world properties, clustering coefficients and modularity indicating decreased network efficiency and impaired functional segregation. Moreover, the altered neuroimaging indices show significant associations with clinical manifestations and could serve as effective neuromarkers to distinguish among healthy controls, CID and CID-D. Taken together, these findings provide novel insights into the neural basis of CID and CID-D, which may facilitate developing new diagnostic and therapeutic approaches.
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Affiliation(s)
- Meiling Chen
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China; Department of Clinical Psychology, the First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Heng Shao
- Department of Geriatrics, the First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Libo Wang
- The Second People's Hospital of Yuxi, the Affiliated Hospital of Kunming University of Science and Technology, Yuxi, China
| | - Jianing Ma
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, China
| | - Jin Chen
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, China
| | - Junying Li
- Department of Neurology, Chengdu Second People's Hospital, Chengdu, China
| | - Jingmei Zhong
- Department of Clinical Psychology, the First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Baosheng Zhu
- Department of Medical Genetics, the First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, China
| | - Bin Bi
- Department of Clinical Psychology, the Second People's Hospital of Guizhou Province, Guiyang, China..
| | - Kexuan Chen
- Medical School, Kunming University of Science and Technology, Kunming, China.
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, China.
| | - Liang Gong
- Department of Neurology, Chengdu Second People's Hospital, Chengdu, China.
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Hu X, Cheng B, Tang Y, Long T, Huang Y, Li P, Song Y, Song X, Li K, Yin Y, Chen X. Gray matter volume and corresponding covariance connectivity are biomarkers for major depressive disorder. Brain Res 2024; 1837:148986. [PMID: 38714227 DOI: 10.1016/j.brainres.2024.148986] [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: 10/13/2023] [Revised: 04/06/2024] [Accepted: 05/04/2024] [Indexed: 05/09/2024]
Abstract
The major depressive disorder (MDD) is a common and severe mental disorder. To identify a reliable biomarker for MDD is important for early diagnosis and prevention. Given easy access and high reproducibility, the structural magnetic resonance imaging (sMRI) is an ideal method to identify the biomarker for depression. In this study, sMRI data of first episode, treatment-naïve 66 MDD patients and 54 sex-, age-, and education-matched healthy controls (HC) were used to identify the differences in gray matter volume (GMV), group-level, individual-level covariance connections. Finally, the abnormal GMV and individual covariance connections were applied to classify MDD from HC. MDD patients showed higher GMV in middle occipital gyrus (MOG) and precuneus (PCun), and higher structural covariance connections between MOG and PCun. In addition, the Allen Human Brain Atlas (AHBA) was applied and revealed the genetic basis for the changes of gray matter volume. Importantly, we reported that GMV in MOG, PCun and structural covariance connectivity between MOG and PCun are able to discriminate MDD from HC. Our results revealed structural underpinnings for MDD, which may contribute towards early discriminating for depression.
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Affiliation(s)
- Xiao Hu
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu 610041, China
| | - Bochao Cheng
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China; Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yuying Tang
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Tong Long
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Yan Huang
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Pei Li
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Yu Song
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Xiyang Song
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Kun Li
- Mental Health Center and Psychiatric Laboratory, the State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yijie Yin
- School of Sociality and Psychology, Southwest Minzu University, Chengdu 610041, China
| | - Xijian Chen
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu 610041, China.
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Zhou Z, Gao Y, Bao W, Liang K, Cao L, Tang M, Li H, Hu X, Zhang L, Sun H, Roberts N, Gong Q, Huang X. Distinctive intrinsic functional connectivity alterations of anterior cingulate cortex subdivisions in major depressive disorder: A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 159:105583. [PMID: 38365137 DOI: 10.1016/j.neubiorev.2024.105583] [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: 09/30/2023] [Revised: 01/22/2024] [Accepted: 02/11/2024] [Indexed: 02/18/2024]
Abstract
Evidence of whether the intrinsic functional connectivity of anterior cingulate cortex (ACC) and its subregions is altered in major depressive disorder (MDD) remains inconclusive. A systematic review and meta-analysis were therefore performed on the whole-brain resting-state functional connectivity (rsFC) studies using the ACC and its subregions as seed regions in MDD, in order to draw more reliable conclusions. Forty-four ACC-based rsFC studies were included, comprising 25 subgenual ACC-based studies, 11 pregenual ACC-based studies, and 17 dorsal ACC-based studies. Specific alterations of rsFC were identified for each ACC subregion in patients with MDD, with altered rsFC of subgenual ACC in emotion-related brain regions, of pregenual ACC in sensorimotor-related regions, and of dorsal ACC in cognition-related regions. Furthermore, meta-regression analysis revealed a significant negative correlation between the pgACC-caudate hypoconnectivity and percentage of female patients in the study cohort. This meta-analysis provides robust evidence of altered intrinsic functional connectivity of the ACC subregions in MDD, which may hold relevance to understanding the origin of, and treating, the emotional, sensorimotor and cognitive dysfunctions that are often observed in these patients.
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Affiliation(s)
- Zilin Zhou
- 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
| | - Yingxue Gao
- 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
| | - Weijie Bao
- 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
| | - Kaili Liang
- 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
| | - Lingxiao Cao
- 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
| | - Mengyue Tang
- 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
| | - Hailong Li
- 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
| | - Xinyue Hu
- 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
| | - Lianqing Zhang
- 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
| | - Huaiqiang Sun
- 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 Science, Chengdu, China
| | - Neil Roberts
- 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; Centre for Reproductive Health (CRH), 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 Science, Chengdu, China; The Xiaman Key Lab of psychoradiology and neuromodulation, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
| | - Xiaoqi Huang
- 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 Science, Chengdu, China; The Xiaman Key Lab of psychoradiology and neuromodulation, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China.
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5
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Deng D, Sun H, Wang Y, Guo X, Yuan Y, Wang J, Qiu L. Structural and functional abnormalities in first-episode drug-naïve pediatric idiopathic generalized epilepsy. Cereb Cortex 2024; 34:bhae021. [PMID: 38314605 DOI: 10.1093/cercor/bhae021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 01/09/2024] [Accepted: 01/10/2024] [Indexed: 02/06/2024] Open
Abstract
The aim of this study was to investigate brain structure and corresponding static and dynamic functional connectivity (sFC & dFC) abnormalities in untreated, first-episode pediatric idiopathic generalized epilepsy (IGE), with the goal of better understanding the underlying pathological mechanisms of IGE. Thirty-one children with IGE and 31 age-matched healthy controls (HC) were recruited. Structural magnetic resonance imaging (sMRI) data were acquired, and voxel-based morphometry (VBM) analysis were performed to reveal abnormal gray matter volume (GMV). Moreover, sFC and dFC analyses were conducted using the brain areas exhibiting abnormal GMV as seed regions to explore abnormal functional couplings. Compared to HC, the IGE group exhibited increased GMV in left middle cingulate cortex (MCC) and right parahippocampus (ParaHipp). In addition, the analyses of dFC and sFC with MCC and ParaHipp as seeds revealed more extensive functional connectivity (FC) changes in dFC. Notably, the structurally and functionally abnormal brain areas were primarily localized in the default mode network (DMN). However, our study did not find any significant associations between these altered neuroimaging measurements and clinical outcomes. This study uncovered microstructural changes as well as corresponding sFC and dFC changes in patients with new-onset, untreated pediatric IGE. The affected brain regions were primarily located within the DMN, highlighting the DMN's crucial role in the development of pediatric IGE.
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Affiliation(s)
- Dingmei Deng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No. 18, South Section 3, First Ring Road, Wuhou District, Chengdu 610041, China
- Medical Imaging Center, The Second People's Hospital of Yibin, 96# Beida Street, Cuiping District, Yibin 644000, China
- Clinical Research and Translational Center, Second People's Hospital of Yibin City-West China Yibin Hospital, Sichuan University, 96# Beida Street, Cuiping District, Yibin 644000, China
| | - Hui Sun
- College of Electrical Engineering, Sichuan University, No. 24, South Section 1, First Ring Road, Wuhou District, Chengdu 610065, China
| | - Yuting Wang
- Medical Imaging Center, The Second People's Hospital of Yibin, 96# Beida Street, Cuiping District, Yibin 644000, China
- Clinical Research and Translational Center, Second People's Hospital of Yibin City-West China Yibin Hospital, Sichuan University, 96# Beida Street, Cuiping District, Yibin 644000, China
| | - Xin Guo
- Medical Imaging Center, The Second People's Hospital of Yibin, 96# Beida Street, Cuiping District, Yibin 644000, China
- Clinical Research and Translational Center, Second People's Hospital of Yibin City-West China Yibin Hospital, Sichuan University, 96# Beida Street, Cuiping District, Yibin 644000, China
| | - Yizhi Yuan
- Medical Imaging Center, The Second People's Hospital of Yibin, 96# Beida Street, Cuiping District, Yibin 644000, China
- Clinical Research and Translational Center, Second People's Hospital of Yibin City-West China Yibin Hospital, Sichuan University, 96# Beida Street, Cuiping District, Yibin 644000, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, No.7, Zhiyuan Road, Chenggong District, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, No.7, Zhiyuan Road, Chenggong District, Kunming 650500, China
| | - Lihua Qiu
- Medical Imaging Center, The Second People's Hospital of Yibin, 96# Beida Street, Cuiping District, Yibin 644000, China
- Clinical Research and Translational Center, Second People's Hospital of Yibin City-West China Yibin Hospital, Sichuan University, 96# Beida Street, Cuiping District, Yibin 644000, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, No. 24, South Section 1, First Ring Road, Wuhou District, Chengdu City, Sichuan Province, Chengdu 610065, China
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Zhang J, Zhang J, Sun H, Yang J, Ma Y, Chen K, Su J, Yu X, Yang F, Zhang Z, Zhao T, Hu X, Zhai Y, Liu Q, Wang J, Liu C, Wang Z. Cerebellum drives functional dysfunctions in restless leg syndrome. Sleep Med 2023; 110:172-178. [PMID: 37595434 DOI: 10.1016/j.sleep.2023.08.014] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 07/04/2023] [Accepted: 08/14/2023] [Indexed: 08/20/2023]
Abstract
OBJECTIVE Restless legs syndrome (RLS) has serious effects on patients' sleep quality, physical and mental health. However, the pathophysiological mechanisms of RLS remain unclear. This study utilized both static and dynamic functional activity and connectivity analyses approaches as well as effective connectivity analysis to reveal the neurophysiological basis of RLS. METHODS The resting-state functional MRI (rs-fMRI) data from 32 patients with RLS and 33 age-, and gender-matched healthy control (HC) were collected. Dynamic and static amplitude of low frequency fluctuation (ALFF), functional connectivity (FC), and Granger causality analysis (GCA) were employed to reveal the abnormal functional activities and couplings in patients with RLS. RESULTS RLS patients showed over-activities in left parahippocampus and right cerebellum, hyper-connectivities of right cerebellum with left basal ganglia, left postcentral gyrus and right precentral gyrus, and enhanced effective connectivity from right cerebellum to left postcentral gyrus compared to HC. CONCLUSIONS Abnormal cerebellum-basal ganglia-sensorimotor cortex circuit may be the underlying neuropathological basis of RLS. Our findings highlight the important role of right cerebellum in the onset of RLS and suggest right cerebellum may be a potential target for precision therapy.
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Affiliation(s)
- Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China; Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Jingyue Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Hui Sun
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Jia Yang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China
| | - Yingzi Ma
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China
| | - Kexuan Chen
- Medical School, Kunming University of Science and Technology, Kunming, China
| | - Jing Su
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China
| | - Xiaohui Yu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China
| | - Futing Yang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China
| | - Zhiwei Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Tianyu Zhao
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Xiuying Hu
- Med-X Center for Informatics, Sichuan University, Chengdu, China; Innovation Center of Nursing Research, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Yiran Zhai
- College of Electrical Engineering, Sichuan University, Chengdu, China; Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Qihong Liu
- College of Biomedical Engineering, Sichuan University, Chengdu, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China.
| | - Chunyan Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neuromodulation, Beijing, China.
| | - Zhengbo Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan, China.
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7
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Xu J, Yu H, Lv H, Zhou Y, Huang X, Xu Y, Fan X, Luo W, Liu Y, Li X, Yang Z, Zhao H. Consistent functional abnormalities in patients with postpartum depression. Behav Brain Res 2023; 450:114467. [PMID: 37146719 DOI: 10.1016/j.bbr.2023.114467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 04/26/2023] [Accepted: 05/02/2023] [Indexed: 05/07/2023]
Abstract
Postpartum depression (PPD) is a common public health concern. A wide range of functional abnormalities in various brain regions have been reported in fMRI studies on PPD, however, a consistent functional changing pattern is still lacking. Herein, we obtained functional Magnetic Resonance Imaging (fMRI) data from 52 patients with PPD and 24 healthy postpartum women (HPW). Functional indexes (low-frequency fluctuation, degree centrality, and regional homogeneity) were calculated and compared among these groups to explore the functional changing patterns of PPD. Then, correlation analyses were performed to investigate the relationship between changed functional indexes and clinical measurements in the PPD. Finally, support vector machine (SVM) was performed to test whether these abnormal features can be used to distinguish PPD from HPW. As a result, we identified significantly and consistently functional changing pattern characterizing by increased functional activity in the left inferior occipital gyrus and decreased functional activity right anterior cingulate cortex in the PPD as compared to HPW. These functional values in the right anterior cingulate cortex were significantly correlated with depression symptoms in the PPD, and can be used as features to distinguish PPD from HPW. In conclusion, our results suggested that the right anterior cingulate cortex could be served as a functional neuro-imaging biomarker for PPD, which might be used as a potential target for neuro-modulation.
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Affiliation(s)
- Jinping Xu
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Haibo Yu
- Acupuncture and Moxibustion Department, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China
| | - Hanqing Lv
- Department of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China
| | - Yumei Zhou
- Acupuncture and Moxibustion Department, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China
| | - Xingxian Huang
- Acupuncture and Moxibustion Department, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China
| | - Yuqin Xu
- Acupuncture and Moxibustion Department, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China
| | - Xinxin Fan
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Wenshu Luo
- Department of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China
| | - Yongfeng Liu
- Department of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China
| | - Xinbei Li
- Department of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China
| | - Zhuoxin Yang
- Department of Radiology, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China.
| | - Hong Zhao
- Acupuncture and moxibustion Department, Luohu District Hospital of Traditional Chinese Medicine, Shenzhen, China.
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Xie X, Hu P, Tian Y, Qiu B, Wang K, Bai T. Abnormal resting-state function within language network and its improvement among post-stroke aphasia. Behav Brain Res 2023; 443:114344. [PMID: 36781021 DOI: 10.1016/j.bbr.2023.114344] [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: 10/26/2022] [Revised: 01/30/2023] [Accepted: 02/10/2023] [Indexed: 02/13/2023]
Abstract
Several studies with resting-state magnetic resonance imaging (rs-fMRI) have examined functional impairments and plasticity within language network in patients with post-stroke aphasia (PSA). However, there is still ubiquitous inconsistency across these studies, partly due to restricted to very small sample size and the absence of validation with follow-up data. In the current study, we aimed at providing relatively strong evidence to support functional impairments and its reorganization in PSA. Here, the amplitude of low frequency fluctuations (ALFF) and functional connectivity were used to assess functional alterations of PSA with moderate sample size at baseline (thirty-five PSA patients and thirty-five healthy controls). Functional abnormalities at baseline were observed whether improved among sixteen follow-up patients. Compared with controls, PSA at baseline presented decreased ALFF in the left inferior frontal gyrus (IFG) and decreased functional connectivity of the left IFG with the bilateral supplementary motor area (SMA) and right superior temporal gyrus (STG). The decreased ALFF in IFG, decreased IFG-SMA and IFG-STG connectivity were enhanced among follow-up patients and was synchronized with language-performance improvement. Our results revealed reduced intrinsic neural activity and inter-connections within language network in PSA, which would be normalized synchronously as the improvement of language performance.
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Affiliation(s)
- Xiaohui Xie
- Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Panpan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yanghua Tian
- Department of Neurology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China; Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
| | - Bensheng Qiu
- Center for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China; The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.
| | - Tongjian Bai
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
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9
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Hu Y, Dong F, Xue T, Zhou M, Huang R, Sui F, Guo Q, Hou W, Cai W, Yuan K, Wang H, Yu D. Glutamate levels in the ventromedial prefrontal cortex and resting‐state functional connectivity within reward circuits in alcohol‐dependent patients. Addict Biol 2023; 28:e13272. [PMID: 37016753 DOI: 10.1111/adb.13272] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 01/17/2023] [Accepted: 02/13/2023] [Indexed: 03/06/2023]
Abstract
Great progress has been made in understanding the neural mechanisms associated with alcohol-dependent (AD) patients. However, the interactions within the reward circuits of the patients need further exploration. Glutamatergic projections from the prefrontal cortex to some brain regions are present in the reward circuit. However, little is known about the potential implications of glutamate levels in the prefrontal cortex on abnormal interactions within reward circuits in AD patients. To determine the potential roles of reward circuits in drinking, we investigated differences in resting-state functional connectivity (RSFC) and multivariate Granger causality analysis between 20 AD patients and 20 healthy controls (HC). The neuroimaging findings were then correlated with clinical variables (alcohol use disorder identification test). The ventromedial prefrontal cortex (VmPFC) is believed to play a critical role in addiction disorders, and glutamatergic projections from the prefrontal cortex to several regions of the brain are present in reward circuits. Proton magnetic resonance spectroscopy was also performed to assess the difference in glutamate levels in VmPFC between AD patients and HC. The results showed that the strength of functional connectivity in the reward circuit was generally attenuated in AD patients, and the reciprocal enhancement of activity between the right insula, left thalamus and VmPFC was found to be significantly greater in AD patients. It is worth noting that although glutamate levels in the VmPFC did not show significant differences between the two groups, the level of glutamate in the VmPFC was significantly correlated with RSFC. We hope that the current findings will help us to develop new intervention models based on the important role of the VmPFC in AD.
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Affiliation(s)
- Yiting Hu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Fang Dong
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Ting Xue
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
- School of Science Inner Mongolia University of Science and Technology Baotou China
| | - Mi Zhou
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Ruoyan Huang
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
| | - Feng Sui
- Xilinguole Meng Mongolian General Hospital Xilinhaote China
| | - Qiang Guo
- Xilinguole Meng Mongolian General Hospital Xilinhaote China
| | - Wenbao Hou
- Xilinguole Meng Mongolian General Hospital Xilinhaote China
| | - Wenlong Cai
- Xilinguole Meng Mongolian General Hospital Xilinhaote China
| | - Kai Yuan
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
- Center for Brain Imaging, School of Life Science and Technology Xidian University Xi'an China
- Engineering Research Center of Molecular and Neuro Imaging Ministry of Education Xi'an China
- International Joint Research Center for Advanced Medical Imaging and Intelligent Diagnosis and Treatment & Xi'an Key Laboratory of Intelligent Sensing and Regulation of trans‐Scale Life Information, School of Life Science and Technology Xidian University Xi'an China
| | - Hongde Wang
- Xilinguole Meng Mongolian General Hospital Xilinhaote China
| | - Dahua Yu
- Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering Inner Mongolia University of Science and Technology Baotou China
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10
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Long X, Zhou Y, Zhang F, Li F, Wang X, Meng Y, Roberts N, Cheng B, Jia Z. Altered MRI Diffusion Properties of the White Matter Tracts Connecting Frontal and Thalamic Brain Regions in First-Episode, Drug-Naïve Patients With Postpartum Depression. J Magn Reson Imaging 2023; 57:899-906. [PMID: 35796680 DOI: 10.1002/jmri.28346] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 06/22/2022] [Accepted: 06/22/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Although progress has been made in exploring postpartum depression (PPD), the involvement of cerebral structure connectivity in PPD patients keeps unclear. PURPOSE To explore structural connectivity alternations in mothers with PPD, diffusion tensor imaging (DTI) and automated fiber quantification (AFQ) were used to calculate brain white matter microstructure properties. STUDY TYPE Cross-sectional. POPULATION A total of 51 women with first-episode, treatment-näive PPD, and 49 matched healthy postpartum women (HPW) controls. FIELD STRENGTH A 3.0 T; single-shot echo-planar imaging sequence. ASSESSMENT DTI measurements of fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) were obtained for 18 specific white matter tracts. The relationship between PDD symptoms, hormone levels, and postpartum days was also investigated. STATISTICAL TESTS Two sample t test and Pearson's correlation analysis. The analysis was performed by using a permutation-based multiple-comparison correction approach, with the threshold of P < 0.05 (family wise error corrected [FWE-corrected]) separately across the four different outcome measures. RESULTS Women with PPD showed significantly increased FA and AD in right anterior thalamic radiation (ATR) tract and significantly increased FA and significantly reduced RD in the cingulum tract, compared to women without PPD. The RD values of right cingulum were significantly positively correlated with postpartum days in HPW (r = 0.39). There were no significant relationships between brain measures and hormone levels in either patients or controls. DATA CONCLUSIONS DTI measures have revealed altered integrity in the white matter of the cortical-thalamic circuits in women with PPD compared to HPW. Damage to these circuits may be a structural basis for the impaired emotional regulation and blunted mother-infant bonding in mothers with PPD and a potential target for the development of new treatments. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Xipeng Long
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China.,Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Yushan Zhou
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Feifei Zhang
- Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Fei Li
- Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Xiuli Wang
- Department of Clinical Psychology, the Fourth People's Hospital of Chengdu, Chengdu, China
| | - Yajing Meng
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China
| | - Neil Roberts
- School of Clinical Sciences, the Queens Medical Research Institute (QMRI), University of Edinburgh, Edinburgh, UK
| | - Bochao Cheng
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, China
| | - Zhiyun Jia
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China.,Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
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11
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Yang W, Jiang Y, Ma L, Xiao M, Liu M, Ren Z, Hu L, Zhang Y. Cortical and subcortical morphological alterations in postpartum depression. Behav Brain Res 2023; 447:114414. [PMID: 37001820 DOI: 10.1016/j.bbr.2023.114414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/16/2023] [Accepted: 03/27/2023] [Indexed: 03/31/2023]
Abstract
Postpartum depression (PPD) is the most common postpartum psychiatric disorder, which can negatively affect both mothers and their offspring. Although the functional changes of PPD have been extensively studied, little is known about its structural abnormalities. This study aimed to examine the cortical and subcortical morphological abnormalities in PPD. High resolution T1 structural MRI data of 29 PPD women and 23 matched healthy postpartum women (HPW) were included in this study. Using surface-based morphometry, we examined the differences between the PPD and HPW group in the cortical thickness, local gyrification index and shape changes of deep gray matter nuclei. Compared with the HPW group, women with PPD showed significantly increased cortical thickness in the left superior frontal gyrus, cuneus and right lingual gyrus and fusiform gyrus, which correlated marginally with the EPDS scores of these subjects. In addition, women with PPD showed significant regional inflation in the right pallidum compared with the HPW group. These findings provided further evidence for the structural brain abnormalities in PPD.
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12
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Zeng J, Yan J, Cao H, Su Y, Song Y, Luo Y, Yang X. Neural substrates of reward anticipation and outcome in schizophrenia: a meta-analysis of fMRI findings in the monetary incentive delay task. Transl Psychiatry 2022; 12:448. [PMID: 36244990 PMCID: PMC9573872 DOI: 10.1038/s41398-022-02201-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 01/10/2023] Open
Abstract
Dysfunction of the mesocorticolimbic dopaminergic reward system is a core feature of schizophrenia (SZ), yet its precise contributions to different stages of reward processing and their relevance to disease symptomology are not fully understood. We performed a coordinate-based meta-analysis, using the monetary incentive delay task, to identify which brain regions are implicated in different reward phases in functional magnetic resonance imaging in SZ. A total of 17 studies (368 SZ and 428 controls) were included in the reward anticipation, and 10 studies (229 SZ and 281 controls) were included in the reward outcome. Our meta-analysis revealed that during anticipation, patients showed hypoactivation in the striatum, anterior cingulate cortex, median cingulate cortex (MCC), amygdala, precentral gyrus, and superior temporal gyrus compared with controls. Striatum hypoactivation was negatively associated with negative symptoms and positively associated with the proportion of second-generation antipsychotic users (percentage of SGA users). During outcome, patients displayed hyperactivation in the striatum, insula, amygdala, hippocampus, parahippocampal gyrus, cerebellum, postcentral gyrus, and MCC, and hypoactivation in the dorsolateral prefrontal cortex (DLPFC) and medial prefrontal cortex (mPFC). Hypoactivity of mPFC during outcome was negatively associated with positive symptoms. Moderator analysis showed that the percentage of SGA users was a significant moderator of the association between symptom severity and brain activity in both the anticipation and outcome stages. Our findings identified the neural substrates for different reward phases in SZ and may help explain the neuropathological mechanisms underlying reward processing deficits in the disorder.
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Affiliation(s)
- Jianguang Zeng
- grid.190737.b0000 0001 0154 0904School of Economics and Business Administration, Chongqing University, Chongqing, 400044 China
| | - Jiangnan Yan
- grid.190737.b0000 0001 0154 0904School of Economics and Business Administration, Chongqing University, Chongqing, 400044 China
| | - Hengyi Cao
- grid.250903.d0000 0000 9566 0634Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Hempstead, NY USA ,grid.440243.50000 0004 0453 5950Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY USA
| | - Yueyue Su
- grid.190737.b0000 0001 0154 0904School of Public Affairs, Chongqing University, Chongqing, 400044 China
| | - Yuan Song
- grid.190737.b0000 0001 0154 0904School of Public Affairs, Chongqing University, Chongqing, 400044 China
| | - Ya Luo
- grid.412901.f0000 0004 1770 1022Department of Psychiatry, State Key Lab of Biotherapy, West China Hospital of Sichuan University, Chengdu, 610041 China
| | - Xun Yang
- School of Public Affairs, Chongqing University, Chongqing, 400044, China.
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13
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Zhang J, Zhao T, Zhang J, Zhang Z, Li H, Cheng B, Pang Y, Wu H, Wang J. Prediction of childhood maltreatment and subtypes with personalized functional connectome of large-scale brain networks. Hum Brain Mapp 2022; 43:4710-4721. [PMID: 35735128 PMCID: PMC9491288 DOI: 10.1002/hbm.25985] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 05/12/2022] [Accepted: 05/24/2022] [Indexed: 12/20/2022] Open
Abstract
Childhood maltreatment (CM) has a long impact on physical and mental health of children. However, the neural underpinnings of CM are still unclear. In this study, we aimed to establish the associations between functional connectome of large-scale brain networks and influences of CM evaluated through Childhood Trauma Questionnaire (CTQ) at the individual level based on resting-state functional magnetic resonance imaging data of 215 adults. A novel individual functional mapping approach was employed to identify subject-specific functional networks and functional network connectivities (FNCs). A connectome-based predictive modeling (CPM) was used to estimate CM total and subscale scores using individual FNCs. The CPM established with FNCs can well predict CM total scores and subscale scores including emotion abuse, emotion neglect, physical abuse, physical neglect, and sexual abuse. These FNCs primarily involve default mode network, fronto-parietal network, visual network, limbic network, motor network, dorsal and ventral attention networks, and different networks have distinct contributions to predicting CM and subtypes. Moreover, we found that CM showed age and sex effects on individual functional connections. Taken together, the present findings revealed that different types of CM are associated with different atypical neural networks which provide new clues to understand the neurobiological consequences of childhood adversity.
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Affiliation(s)
- Jiang Zhang
- College of Electrical EngineeringSichuan UniversityChengduChina
- Med‐X Center for InformaticsSichuan UniversityChengduChina
| | - Tianyu Zhao
- College of Electrical EngineeringSichuan UniversityChengduChina
| | - Jingyue Zhang
- College of Electrical EngineeringSichuan UniversityChengduChina
| | - Zhiwei Zhang
- College of Electrical EngineeringSichuan UniversityChengduChina
| | - Hongming Li
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Bochao Cheng
- Department of RadiologyWest China Second University Hospital of Sichuan UniversityChengduChina
| | - Yajing Pang
- School of Electrical EngineeringZhengzhou UniversityZhengzhouChina
| | - Huawang Wu
- The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital)GuangzhouChina
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingChina
- Yunnan Key Laboratory of Primate Biomedical ResearchKunmingYunnanChina
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14
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Zhao C, Chen M, Ding Z, Liu C, Wu X. Altered functional association and couplings: Effective diagnostic neuromarkers for Alzheimer’s disease. Front Aging Neurosci 2022; 14:1009632. [PMID: 36313014 PMCID: PMC9606803 DOI: 10.3389/fnagi.2022.1009632] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 09/05/2022] [Indexed: 11/29/2022] Open
Abstract
Alzheimer’s disease (AD) is a common neurodegenerative disorder causing dementia in the elderly population. Functional disconnection of brain is considered to be the main cause of AD. In this study, we applied a newly developed association (Asso) mapping approach to directly quantify the functional disconnections and to explore the diagnostic effects for AD with resting-state functional magnetic resonance imaging data from 36 AD patients and 42 age-, gender-, and education-matched healthy controls (HC). We found that AD patients showed decreased Asso in left dorsoanterior insula (INS) while increased functional connections of INS with right medial prefrontal cortex (MPFC) and left posterior cingulate cortex (PCC). The changed Asso and functional connections were closely associated with cognitive performances. In addition, the reduced Asso and increased functional connections could serve as effective neuromarkers to distinguish AD patients from HC. Our research provided new evidence for functional disconnections in AD and demonstrated that functional disconnections between cognition-memory networks may be potential early biomarkers for AD.
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Affiliation(s)
- Chongyi Zhao
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China
- Department of Gynecology, The First People’s Hospital of Yunnan Province, Kunming University of Science and Technology, Kunming, China
| | - Meiling Chen
- Department of Clinical Psychology, The First People’s Hospital of Yunnan Province, Kunming University of Science and Technology, Kunming, China
| | - Zhiyong Ding
- Department of Medical Imaging, Qujing Maternal and Child Health Care Hospital, Kunming University of Science and Technology, Qujing, China
- *Correspondence: Zhiyong Ding,
| | - Chunyan Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neuromodulation, Beijing, China
- Chunyan Liu,
| | - Xiaomei Wu
- Department of Gynecology, The First People’s Hospital of Yunnan Province, Kunming University of Science and Technology, Kunming, China
- Xiaomei Wu,
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15
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Li Y, Yu X, Ma Y, Su J, Li Y, Zhu S, Bai T, Wei Q, Becker B, Ding Z, Wang K, Tian Y, Wang J. Neural signatures of default mode network in major depression disorder after electroconvulsive therapy. Cereb Cortex 2022; 33:3840-3852. [PMID: 36089839 DOI: 10.1093/cercor/bhac311] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 06/17/2022] [Accepted: 07/08/2022] [Indexed: 11/12/2022] Open
Abstract
Functional abnormalities of default mode network (DMN) have been well documented in major depressive disorder (MDD). However, the association of DMN functional reorganization with antidepressant treatment and gene expression is unclear. Moreover, whether the functional interactions of DMN could predict treatment efficacy is also unknown. Here, we investigated the link of treatment response with functional alterations of DMN and gene expression with a comparably large sample including 46 individuals with MDD before and after electroconvulsive therapy (ECT) and 46 age- and sex-matched healthy controls. Static and dynamic functional connectivity (dFC) analyses showed increased intrinsic/static but decreased dynamic functional couplings of inter- and intra-subsystems and between nodes of DMN. The changes of static functional connections of DMN were spatially correlated with brain gene expression profiles. Moreover, static and dFC of the DMN before treatment as features could predict depressive symptom improvement following ECT. Taken together, these results shed light on the underlying neural and genetic basis of antidepressant effect of ECT and the intrinsic functional connectivity of DMN have the potential to serve as prognostic biomarkers to guide accurate personalized treatment.
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Affiliation(s)
- Yuanyuan Li
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China.,School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Xiaohui Yu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Yingzi Ma
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Jing Su
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
| | - Yue Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Shunli Zhu
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Tongjian Bai
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China
| | - Qiang Wei
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China
| | - Benjamin Becker
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Zhiyong Ding
- Medical Imaging Department, Maternal and Child Health-care Hospital of Qujing, Qujing 655000, China
| | - Kai Wang
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Anhui Medical University, School of Mental Health and Psychological Sciences, Hefei 230022, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230022, China.,Anhui Province Clinical Research Center for Neurological Disease, Hefei 230022, China
| | - Yanghua Tian
- Department of Neurology, The First Hospital of Anhui Medical University, Hefei 230022, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China.,Anhui Medical University, School of Mental Health and Psychological Sciences, Hefei 230022, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230022, China.,Anhui Province Clinical Research Center for Neurological Disease, Hefei 230022, China.,Department of Psychology and Sleep Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China.,Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
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16
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Cheng B, Guo Y, Chen X, Lv B, Liao Y, Qu H, Hu X, Yang H, Meng Y, Deng W, Wang J. Postpartum depression and major depressive disorder: the same or not? Evidence from resting-state functional MRI. PSYCHORADIOLOGY 2022; 2:121-128. [PMID: 38665602 PMCID: PMC10917173 DOI: 10.1093/psyrad/kkac015] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 10/18/2022] [Accepted: 10/27/2022] [Indexed: 04/28/2024]
Abstract
Background Although postpartum depression (PPD) and non-peripartum major depressive disorder (MDD) occurring within and outside the postpartum period share many clinical characteristics, whether PPD and MDD are the same or not remains controversial. Methods The current study was devoted to identify the shared and different neural circuits between PPD and MDD by resting-state functional magnetic resonance imaging data from 77 participants (22 first-episodic drug-naïve MDD, 26 drug-naïve PPD, and 29 healthy controls (HC)). Results Both the PPD and MDD groups exhibited higher fractional amplitude of low-frequency fluctuation (fALFF) in left temporal pole relative to the HC group; the MDD group showed specifically increased degree centrality in the right cerebellum while PPD showed specifically decreased fALFF in the left supplementary motor area and posterior middle temporal gyrus (pMTG_L), and specifically decreased functional connectivities between pMTG and precuneus and between left subgeneual anterior cingulate cortex (sgACC_L) and right sgACC. Moreover, sgACC and left thalamus showed abnormal regional homogeneity of functional activities between any pair of HC, MDD, and PPD. Conclusions These results provide initial evidence that PPD and MDD have common and distinct neural circuits, which may facilitate understanding the neurophysiological basis and precision treatment for PPD.
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Affiliation(s)
- Bochao Cheng
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu 610041, China
| | - Yi Guo
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China
| | - Xijian Chen
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China
| | - Bin Lv
- Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Yi Liao
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China
| | - Haibo Qu
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China
| | - Xiao Hu
- Department of Rehabilitation Medicine, West China Second University Hospital, Sichuan University, Chengdu 610041, China
| | - Haoxiang Yang
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China
| | - Yajing Meng
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Wei Deng
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
- Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310063, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
- Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
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17
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Li Y, Li Y, Wei Q, Bai T, Wang K, Wang J, Tian Y. Mapping intrinsic functional network topological architecture in major depression disorder after electroconvulsive therapy. J Affect Disord 2022; 311:103-109. [PMID: 35594966 DOI: 10.1016/j.jad.2022.05.067] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/07/2022] [Accepted: 05/12/2022] [Indexed: 12/22/2022]
Abstract
Disrupted topological organization of functional brain networks has been well documented in major depressive disorder (MDD). However, there is no report about how electroconvulsive therapy (ECT), a rapid way for depression remission, affects whole-brain functional network topological architecture to improve clinical symptoms in individuals with MDD. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) data were collected for twenty-four MDD patients before and after receiving ECT and 25 gender-, age- and education-matched healthy controls (HC). The functional brain network for each subject was mapped using Brainnetome Atlas and graph-theory was applied to measure topological properties for both binary and weighted network. The results showed that ECT can significantly increase shortest path length and decrease global efficiency in MDD patients. In addition, significant alterations in nodal degree, nodal efficiency as well as between nodal functional connectivity strength were found in MDD patients after ECT. The network nodes showing changed degree, efficiency and connectivity were primarily distributed in default mode network (DMN), fronto-parietal network (FPN), and limbic system. Our findings demonstrates that ECT improves depressive symptoms by reorganizing disrupted network topological architecture in MDD patients and highlights the important role of functional reorganization of DMN, FPN, and limbic network contributing to depression remission.
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Affiliation(s)
- Yuanyuan Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Yue Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Qiang Wei
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China
| | - Tongjian Bai
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China
| | - Kai Wang
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China; Anhui Medical University, School of Mental Health and Psychological Sciences, Hefei 230022, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230022, China; Anhui Province clinical research center for neurological disease, Hefei 230022, China
| | - Jiaojian Wang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China; Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing 400030, China.
| | - Yanghua Tian
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China; Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230022, China; Anhui Medical University, School of Mental Health and Psychological Sciences, Hefei 230022, China; Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230022, China; Anhui Province clinical research center for neurological disease, Hefei 230022, China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230022, China.
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18
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Luo Q, Chen J, Li Y, Wu Z, Lin X, Yao J, Yu H, Wu H, Peng H. Aberrant brain connectivity is associated with childhood maltreatment in individuals with major depressive disorder. Brain Imaging Behav 2022; 16:2021-2036. [PMID: 35906517 DOI: 10.1007/s11682-022-00672-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/28/2022] [Indexed: 11/02/2022]
Abstract
Although childhood maltreatment confers a high risk for the development of major depressive disorder, the neurobiological mechanisms underlying this connection remain unknown. The present study sought to identify the specific resting-state networks associated with childhood maltreatment. We recruited major depressive disorder patients with and without a history of childhood maltreatment (n = 31 and n = 30, respectively) and healthy subjects (n = 80). We used independent component analysis to compute inter- and intra- network connectivity. We found that individuals with major depressive disorder and childhood maltreatment could be characterized by the following network disconnectivity model relative to healthy subjects: (i) decreased intra-network connectivity in the left frontoparietal network and increased intra-network connectivity in the right frontoparietal network, (ii) decreased inter-network connectivity in the posterior default mode network-auditory network, posterior default mode network-limbic system, posterior default mode network-anterior default mode network, auditory network-medial visual network, lateral visual network - medial visual network, medial visual network-sensorimotor network, medial visual network - anterior default mode network, occipital pole visual network-dorsal attention network, and posterior default mode network-anterior default mode network, and (iii) increased inter-network connectivity in the sensorimotor network-ventral attention network, and dorsal attention network-ventral attention network. Moreover, we found significant correlations between the severity of childhood maltreatment and the intra-network connectivity of the frontoparietal network. Our study demonstrated that childhood maltreatment is integrally associated with aberrant network architecture in patients with major depressive disorder.
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Affiliation(s)
- Qianyi Luo
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Juran Chen
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Yuhong Li
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Zhiyao Wu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Xinyi Lin
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Jiazheng Yao
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Huiwen Yu
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China
| | - Huawang Wu
- Department of Radiology, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, 510370, China. .,Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China.
| | - Hongjun Peng
- Department of Clinical Psychology, The Affiliated Brain Hospital of Guangzhou Medical University, No.36, Mingxin Road, Liwan District, Guangzhou, 510370, China. .,Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, 510370, China.
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19
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Tan B, Yan J, Zhang J, Jin Z, Li L. Aberrant Whole-Brain Resting-State Functional Connectivity Architecture in Obsessive-Compulsive Disorder: An EEG Study. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1887-1897. [PMID: 35786557 DOI: 10.1109/tnsre.2022.3187966] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Obsessive-compulsive disorder (OCD) is a common neuropsychiatric disorder characterized by intrusive thoughts (obsessions) and repetitive behaviors (compulsions), and few studies have assessed the whole-brain functional connectivity architecture of OCD with electroencephalogram (EEG) during different resting states. Graph theory and network-based statistics (NBS) were employed to examine the neural synchronization and the whole-brain functional connectivity (FC) based on the phase-locking value (PLV) of OCD patients and healthy controls (HCs) during eyes-closed (EC) and eyes-open (EO) states. Compared with HCs, OCD patients exhibited not only decreased global synchronization in terms of phase synchrony but also aberrant global topological properties (decreased average shortest path lengths and normalized shortest path lengths together with increased global efficiencies and normalized clustering coefficients) together with inhibited intra-hemispheric and interhemispheric FCs during rest, which suggested an imbalance between functional integration and segregation of brain networks for OCD patients. Meanwhile, OCD patients had increased global efficiencies and normalized clustering coefficients, but decreased average clustering coefficients and normalized shortest path lengths together with significantly decreased FCs in the alpha band from EC to EO states, which suggested a dynamic switch between highly integrated (EC state) and highly specialized (EO state) modes of information processing. Moreover, the decreased FCs of OCD patients showed obvious hemispheric asymmetry within or between groups during EC and EO states, which might serve as a potential biomarker to classify OCD patients from HCs.
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20
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Dong F, Zhang Z, Chu T, Che K, Li Y, Gai Q, Shi Y, Ma H, Zhao F, Mao N, Xie H. Altered dynamic amplitude of low-frequency fluctuations in patients with postpartum depression. Behav Brain Res 2022; 433:113980. [PMID: 35809693 DOI: 10.1016/j.bbr.2022.113980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 06/21/2022] [Accepted: 06/22/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Postpartum depression (PPD) is a common mood disorder with increasing incidence year by year. However, the dynamic changes in local neural activity of patients with PPD remain unclear. In this study, we utilized the dynamic amplitude of low-frequency fluctuation (dALFF) method to investigate the abnormal temporal variability of local neural activity and its potential correlation with clinical severity in PPD. METHODS Twenty-four patients with PPD and nineteen healthy primiparous mothers controls (HCs) matched for age, education level and body mass index were examined by resting-state functional magnetic resonance imaging (rs-fMRI). A sliding-window method was used to assess the dALFF, and a k-means clustering method was used to identify dALFF states. Two-sample t-test was used to compare the differences of dALFF variability and state metrics between PPD and HCs. Pearson correlation analysis was used to analyze the relationship between dALFF variability, states metrics and clinical severity. RESULTS (1) Patients with PPD had lower variance of dALFF than HCs in the cognitive control network, cerebellar network and sensorimotor network. (2) Four dALFF states were identified, and patients with PPD spent more time on state 2 than the other three states. The number of transitions between the four dALFF states increased in the patients compared with that in HCs. (3) Multiple dALFF states were found to be correlated with the severity of depression. The variance of dALFF in the right middle frontal gyrus was negatively correlated with the Edinburgh postnatal depression scale score. CONCLUSION This study provides new insights into the brain dysfunction of PPD from the perspective of dynamic local brain activity, highlighting the important role of dALFF variability in understanding the neurophysiological mechanisms of PPD.
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Affiliation(s)
- Fanghui Dong
- School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Yantai, Shandong 264003, PR China; Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Zhongsheng Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Tongpeng Chu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Kaili Che
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Yuna Li
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Qun Gai
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Yinghong Shi
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Heng Ma
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China
| | - Feng Zhao
- School of Compute Science and Technology, Shandong Technology and Business University, Yantai, Shandong 264000, PR China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China.
| | - Haizhu Xie
- School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Yantai, Shandong 264003, PR China; Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong 264000, PR China.
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21
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Zhang S, Li B, Liu K, Hou X, Zhang P. Abnormal Voxel-Based Degree Centrality in Patients With Postpartum Depression: A Resting-State Functional Magnetic Resonance Imaging Study. Front Neurosci 2022; 16:914894. [PMID: 35844214 PMCID: PMC9280356 DOI: 10.3389/fnins.2022.914894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 06/03/2022] [Indexed: 11/15/2022] Open
Abstract
Postpartum depression (PPD) is a major public health concern with significant consequences for mothers, their children, and their families. However, less is known about its underlying neuropathological mechanisms. The voxel-based degree centrality (DC) analysis approach provides a new perspective for exploring the intrinsic dysconnectivity pattern of whole-brain functional networks of PPD. Twenty-nine patients with PPD and thirty healthy postpartum women were enrolled and received resting-state functional magnetic resonance imaging (fMRI) scans in the fourth week after delivery. DC image, clinical symptom correlation, and seed-based functional connectivity (FC) analyses were performed to reveal the abnormalities of the whole-brain functional network in PPD. Compared with healthy controls (HCs), patients with PPD exhibited significantly increased DC in the right hippocampus (HIP.R) and left inferior frontal orbital gyrus (ORBinf.L). The receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) of the above two brain regions is all over 0.7. In the seed-based FC analyses, the PPD showed significantly decreased FC between the HIP.R and right middle frontal gyrus (MFG.R), between the HIP.R and left median cingulate and paracingulate gyri (DCG.L), and between the ORBinf.L and the left fusiform (FFG.L) compared with HCs. The PPD showed significantly increased FC between the ORBinf.L and the right superior frontal gyrus, medial (SFGmed.R) compared with HCs. Mean FC between the HIP.R and DCG.L positively correlated with EDPS scores in the PPD group. This study provided evidence of aberrant DC and FC within brain regions in patients with PPD, which was associated with the default mode network (DMN) and limbic system (LIN). Identification of these above-altered brain areas may help physicians to better understand neural circuitry dysfunction in PPD.
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Affiliation(s)
- Shufen Zhang
- Department of Obstetrics, Shandong Second Provincial General Hospital, Jinan, China
| | - Bo Li
- Department of Radiology, The 960th Hospital of the PLA Joint Logistics Support Force, Jinan, China
| | - Kai Liu
- Department of Radiology, The 960th Hospital of the PLA Joint Logistics Support Force, Jinan, China
| | - Xiaoming Hou
- Department of Pediatrics, Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
- *Correspondence: Xiaoming Hou,
| | - Ping Zhang
- Department of Neurosurgery, Qi Lu Hospital, Shandong University, Jinan, China
- Ping Zhang,
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22
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Yang Y, Li X, Cui Y, Liu K, Qu H, Lu Y, Li W, Zhang L, Zhang Y, Song J, Lv L. Reduced Gray Matter Volume in Orbitofrontal Cortex Across Schizophrenia, Major Depressive Disorder, and Bipolar Disorder: A Comparative Imaging Study. Front Neurosci 2022; 16:919272. [PMID: 35757556 PMCID: PMC9226907 DOI: 10.3389/fnins.2022.919272] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 05/02/2022] [Indexed: 11/29/2022] Open
Abstract
Schizophrenia (SZ), major depressive disorder (MDD), and bipolar disorder (BD) are severe psychiatric disorders and share common characteristics not only in clinical symptoms but also in neuroimaging. The purpose of this study was to examine common and specific neuroanatomical features in individuals with these three psychiatric conditions. In this study, 70 patients with SZ, 85 patients with MDD, 42 patients with BD, and 95 healthy controls (HCs) were recruited. Voxel-based morphometry (VBM) analysis was used to explore brain imaging characteristics. Psychopathology was assessed using the Beck Depression Inventory (BDI), the Beck Anxiety Inventory (BAI), the Young Mania Rating Scale (YMRS), and the Positive and Negative Syndrome Scale (PANSS). Cognition was assessed using the digit symbol substitution test (DSST), forward-digital span (DS), backward-DS, and semantic fluency. Common reduced gray matter volume (GMV) in the orbitofrontal cortex (OFC) region was found across the SZ, MDD, and BD. Specific reduced GMV of brain regions was also found. For patients with SZ, we found reduced GMV in the frontal lobe, temporal pole, occipital lobe, thalamus, hippocampus, and cerebellum. For patients with MDD, we found reduced GMV in the frontal and temporal lobes, insular cortex, and occipital regions. Patients with BD had reduced GMV in the medial OFC, inferior temporal and fusiform regions, insular cortex, hippocampus, and cerebellum. Furthermore, the OFC GMV was correlated with processing speed as assessed with the DSST across four groups (r = 0.17, p = 0.004) and correlated with the PANSS positive symptoms sub-score in patients with SZ (r = − 0.27, p = 0.026). In conclusion, common OFC alterations in SZ, MDD, and BD provided evidence that this region dysregulation may play a critical role in the pathophysiology of these three psychiatric disorders.
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Affiliation(s)
- Yongfeng Yang
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Xue Li
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Yue Cui
- Brainnetome Center and Institute of Automation, Chinese Academy of Sciences, Beijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Kang Liu
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Haoyang Qu
- Department of Psychiatry, The Second Clinic College of Xinxiang Medical University, Xinxiang, China
| | - Yanli Lu
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
| | - Wenqiang Li
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Luwen Zhang
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Yan Zhang
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Jinggui Song
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
| | - Luxian Lv
- Department of Psychiatry, Henan Mental Hospital, Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.,Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang, China.,International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang, China
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23
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Horáková A, Němcová H, Mohr P, Sebela A. Structural, functional, and metabolic signatures of postpartum depression: A systematic review. Front Psychiatry 2022; 13:1044995. [PMID: 36465313 PMCID: PMC9709336 DOI: 10.3389/fpsyt.2022.1044995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/31/2022] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVE Postpartum depression (PPD) is a serious condition with debilitating consequences for the mother, offspring, and the whole family. The scope of negative outcomes of PPD highlights the need to specify effective diagnostics and treatment which might differ from major depressive disorder (MDD). In order to improve our clinical care, we need to better understand the underlying neuropathological mechanisms of PPD. Therefore, we conducted a systematic review of published neuroimaging studies assessing functional, structural, and metabolic correlates of PPD. METHODS Relevant papers were identified using a search code for English-written studies in the PubMed, Scopus, and Web of Science databases published by March 2022. Included were studies with structural magnetic resonance imaging, functional magnetic resonance imaging, both resting-state and task-related, magnetic resonance spectroscopy, or positron emission tomography. The findings were analyzed to assess signatures in PPD-diagnosed women compared to healthy controls. The review protocol was registered in PROSPERO (CRD42022313794). RESULTS The total of 3,368 references were initially identified. After the removal of duplicates and non-applicable papers, the search yielded 74 full-text studies assessed for eligibility. Of them, 26 met the inclusion criteria and their findings were analyzed and synthesized. The results showed consistent functional, structural, and metabolic changes in the default mode network and the salient network in women with PPD. During emotion-related tasks, PPD was associated with changes in the corticolimbic system activity, especially the amygdala. DISCUSSION This review offers a comprehensive summary of neuroimaging signatures in PPD-diagnosed women. It indicates the brain regions and networks which show functional, structural, and metabolic changes. Our findings offer better understanding of the nature of PPD, which clearly copies some features of MDD, while differs in others.
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Affiliation(s)
- Anna Horáková
- Center of Perinatal Mental Health, National Institute of Mental Health, Klecany, Czechia.,Department of Psychology, Faculty of Arts, Charles University, Prague, Czechia
| | - Hana Němcová
- Center of Perinatal Mental Health, National Institute of Mental Health, Klecany, Czechia.,Department of Psychology, Faculty of Arts, Charles University, Prague, Czechia
| | - Pavel Mohr
- Department of Psychiatry and Medical Psychology, Third Faculty of Medicine, Charles University, Prague, Czechia.,Clinical Center, National Institute of Mental Health, Klecany, Czechia
| | - Antonin Sebela
- Center of Perinatal Mental Health, National Institute of Mental Health, Klecany, Czechia.,Department of Psychiatry and Medical Psychology, Third Faculty of Medicine, Charles University, Prague, Czechia
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