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Fang K, Hou Y, Niu L, Han S, Zhang W. Individualized gray matter morphological abnormalities uncover two robust transdiagnostic biotypes. J Affect Disord 2024; 365:193-204. [PMID: 39173920 DOI: 10.1016/j.jad.2024.08.102] [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: 06/12/2024] [Revised: 07/22/2024] [Accepted: 08/19/2024] [Indexed: 08/24/2024]
Abstract
Psychiatric disorders exhibit a shared neuropathology, yet the diverse presentations among patients necessitate the identification of transdiagnostic subtypes to enhance diagnostic and treatment strategies. This study aims to unveil potential transdiagnostic subtypes based on personalized gray matter morphological abnormalities. A total of 496 patients with psychiatric disorders and 255 healthy controls (HCs) from three distinct datasets (one for discovery and two for validation) were enrolled. Individualized gray matter morphological abnormalities were determined using normative modeling to identify transdiagnostic subtypes. In the discovery dataset, two transdiagnostic subtypes with contrasting patterns of structural abnormalities compared to HCs were identified. Reproducibility and generalizability analyses demonstrated that these subtypes could be generalized to new patients and even to new disorders in the validation datasets. These subtypes were characterized by distinct disease epicenters. The gray matter abnormal pattern in subtype 1 was mainly linked to excitatory receptors, whereas subtype 2 showed a predominant association with inhibitory receptors. Furthermore, we observed that the gray matter abnormal pattern in subtype 2 was correlated with transcriptional profiles of inflammation-related genes, while subtype 1 did not show this association. Our findings reveal two robust transdiagnostic biotypes, offering novel insights into psychiatric nosology.
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Affiliation(s)
- Keke Fang
- Department of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, China; Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Cancer Hospital, China; Henan Provincial Key Laboratory of Anticancer Drug Research, Henan Cancer Hospital, China
| | - Ying Hou
- Department of ultrasound, the affiliated cancer hospital of Zhengzhou University & Henan Cancer Hospital, China
| | - Lianjie Niu
- Department of Breast Disease, Henan Breast Cancer Center, the affiliated Cancer Hidospital of Zhengzhou University & Henan Cancer Hospital, China.
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Henan Province, China.
| | - Wenzhou Zhang
- Department of Pharmacy, Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, China; Henan Engineering Research Center for Tumor Precision Medicine and Comprehensive Evaluation, Henan Cancer Hospital, China; Henan Provincial Key Laboratory of Anticancer Drug Research, Henan Cancer Hospital, China.
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2
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Xiao Y, Kandala S, Huang J, Liu J, McGonigle T, Barch D, Tang Y, Fan G, Wang F, Womer FY. The involvement of the cerebellar vermis across the psychotic-affective spectrum in enriched samples of recent-onset schizophrenia, bipolar disorder, and major depressive disorder. J Psychiatr Res 2024; 181:14-22. [PMID: 39577028 DOI: 10.1016/j.jpsychires.2024.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 10/25/2024] [Accepted: 11/08/2024] [Indexed: 11/24/2024]
Abstract
BACKGROUND The cerebellar vermis is implicated in cognition and emotion, two key components of the psychotic-affective spectrum that includes schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). METHODS Volumes [N = 391; 97 SCZ, 78 BD, 103 MDD, and 113 healthy controls (HC)] and seed-to-whole brain functional connectivity (FC) [N = 136; 33 SCZ, 23 BD, 51 MDD, and 29 HC] of total vermis and its subregions, V1 (anterior), V2 (posterior superior), and V3 (posterior inferior), were examined across SCZ, BD, MDD, and HC in samples enriched for first episode individuals. The relationship between vermis volumes and FC and cognitive measures were explored. RESULTS Significant diagnosis (p = 0.05) and diagnosis by subregion (p = 0.02) effects on vermis volumes were observed across the four groups, particularly in V2 (p = 0.01) with decreased V2 volumes in SCZ compared to BD (pFDR = 0.01). SCZ, BD, and MDD had significant effects on vermis FC, with SCZ having the greatest effects. SCZ had effects on FC of V1, V2, and V3 with broadly distributed cortical and subcortical regions, while BD and MDD effects were observed in FC of V2 and V3 with frontotemporal regions. Exploratory analyses found significant canonical correlation between V3 FC and WM and visual learning for SCZ and MDD. No significant associations were shown between vermis volumes and cognitive measures. CONCLUSIONS Structural and functional alterations of the vermis appear to vary across the psychotic-affective spectrum of SCZ, BD, and MDD. Posterior vermis may be a key neural intersection between affective and psychotic psychopathology.
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Affiliation(s)
- Yao Xiao
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Rd, Nanjing, Jiangsu, 210029, China.
| | - Sri Kandala
- Department of Psychiatry, Washington University, 660 South Euclid Ave, St. Louis, MO, 63108, USA.
| | - Jenny Huang
- Department of Psychiatry, Washington University, 660 South Euclid Ave, St. Louis, MO, 63108, USA.
| | - Jinyuan Liu
- Department of Biostatistics, Vanderbilt University Medical Center, 2525 West End Ave, Nashville, TN, 37203, USA; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, 1601 23rd Ave South, Nashville, TN, 37212, USA.
| | - Trey McGonigle
- Department of Biostatistics, Vanderbilt University Medical Center, 2525 West End Ave, Nashville, TN, 37203, USA.
| | - Deanna Barch
- Department of Psychiatry, Washington University, 660 South Euclid Ave, St. Louis, MO, 63108, USA; Department of Psychological Sciences, Washington University, 1 Brookings Dr, St. Louis, MO, 63130, USA; Department of Radiology, Washington University, 510 South Kingshighway Blvd, St. Louis, MO, 63108, USA.
| | - Yangqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, 155 Nanjing St, Shenyang, Liaoning, Shenyang, 110001, China.
| | - Guoguang Fan
- Department of Radiology, The First Affiliated Hospital of China Medical University, 155 Nanjing St, Shenyang, Liaoning, Shenyang, 110001, China.
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, 264 Guangzhou Rd, Nanjing, Jiangsu, 210029, China.
| | - Fay Y Womer
- Department of Psychiatry, Washington University, 660 South Euclid Ave, St. Louis, MO, 63108, USA; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, 1601 23rd Ave South, Nashville, TN, 37212, USA.
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Chen C, Zhang B, Qin X, Huang H, Rong B, Wang H, Zhang L, Yuan W. Altered resting-state brain activity of the superior parietal cortex and striatum in major depressive disorder and schizophrenia. Asian J Psychiatr 2024; 102:104303. [PMID: 39531911 DOI: 10.1016/j.ajp.2024.104303] [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: 08/20/2024] [Revised: 11/02/2024] [Accepted: 11/03/2024] [Indexed: 11/16/2024]
Abstract
BACKGROUND Resting-state functional magnetic resonance imaging (fMRI) studies have shown altered brain activity in major depressive disorder (MDD) and schizophrenia (SZ). Despite differing diagnoses, SZ and MDD share similar features. However, functional brain activity similarities and differences between SZ and MDD remain unclear. METHODS Participants with MDD, SZ, and normal controls (n=36 each) underwent resting-state fMRI scans. Amplitude of low-frequency fluctuations (ALFF) was used to analyze the preprocessed rs-fMRI data. One-way ANOVAs and post hoc analyses compared ALFF values in different brain regions. Pearson correlation analysis examined associations with clinical symptoms. RESULTS Comparison among the three groups revealed significant differences in ALFF values within the left superior parietal cortex (L-SPC) and bilateral striatum. Through pairwise comparisons, patients with SZ but not patients with MDD were found to exhibit increased striatum ALFF values relative to NC individuals, but decreased in MDD. Meanwhile, L-SPC ALFF values were significantly increased in patients with SZ relative to both normal control individuals and patients with MDD, while no differences in these values were observed between the normal control and MDD groups. The Pearson correlation analyses showed significant positive correlations between ALFF in the striatum and PANSS positive score, but no significant correlation with other symptom severity in SZ and MDD. CONCLUSION These findings support the hypothesis of alterations in brain functional activity as a fundamental component of the pathogenesis of MDD and SZ. The observed differences in functional brain activity in the superior parietal cortex and striatum between MDD and SZ provide a neuroimaging basis that can contribute to the differential diagnosis of these debilitating conditions.
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Affiliation(s)
- Cheng Chen
- Department of Psychiatry,Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Baoli Zhang
- Department of Psychiatry,Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Xucong Qin
- Department of Psychiatry,Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Huan Huang
- Department of Psychiatry,Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Bei Rong
- Department of Psychiatry,Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Huiling Wang
- Department of Psychiatry,Renmin Hospital of Wuhan University, Wuhan 430060, China; Hubei Provincial Key Laboratory of Developmentally Originated Disease, Wuhan 430071, China.
| | - Liang Zhang
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China
| | - Wei Yuan
- Department of Psychiatry,Yidu People' s Hospital, Yidu 443300, China.
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Guo Y, Liu Y, Zhang T, Ruan J, Liu S, Ren Z. Intrinsic disruption of white matter microarchitecture in major depressive disorder: A voxel-based meta analysis of diffusion tensor imaging. J Affect Disord 2024; 363:161-173. [PMID: 39032713 DOI: 10.1016/j.jad.2024.07.050] [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: 12/12/2023] [Revised: 06/17/2024] [Accepted: 07/12/2024] [Indexed: 07/23/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) is a prevalent and disabling mood disorder, thought to be linked with brain white matter (WM) alterations. Prior diffusion tensor imaging (DTI) studies have reported inconsistent changes in fractional anisotropy (FA) across different brain regions in MDD patients. However, none of these studies utilized raw t-map data for WM meta-analysis in MDD. Our study aims to address this gap by conducting a whole-brain-based meta-analysis of FA in MDD using Seed-based d mapping via permutation of subject images (SDM-PSI), combining reported peak coordinates and raw statistical parametric maps. OBJECTIVES Following PRISMA guidelines, we performed a systematic search and meta-analysis to compare FA in MDD patients with healthy controls (HC). Our goal was to identify WM abnormalities in MDD, using SDM, which could shed light on the disorder's pathogenesis. RESULTS The meta-analysis included 39 studies with 3696 participants (2094 with MDD, 1602HC). It revealed that MDD patients, in comparison to HC, have lower FA in the corpus callosum (CC) and anterior thalamic projections (ATP). Subgroup analyses indicated that the CC is a more stable pathogenic factor in MDD. Meta-regression analyses showed no linear correlation between the mean age, percentage of female patients, duration of depression, and FA abnormalities. This suggests that WM impairments in interhemispheric connections and anterior thalamocortical circuits are significant in the pathogenesis of MDD.
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Affiliation(s)
- Yunxiao Guo
- Key Laboratory of Adolescent Cyberpsychology and Behavior (Ministry of Education), School of Psychology, Central China Normal University, Wuhan, China; Key Laboratory of Human Development and Mental Health of Hubei Province, National Intelligent Society Governance Experiment Base (Education), School of Psychology, Central China Normal University, Wuhan, China
| | - Yinong Liu
- Key Laboratory of Adolescent Cyberpsychology and Behavior (Ministry of Education), School of Psychology, Central China Normal University, Wuhan, China; Key Laboratory of Human Development and Mental Health of Hubei Province, National Intelligent Society Governance Experiment Base (Education), School of Psychology, Central China Normal University, Wuhan, China
| | - Tao Zhang
- Key Laboratory of Adolescent Cyberpsychology and Behavior (Ministry of Education), School of Psychology, Central China Normal University, Wuhan, China; Key Laboratory of Human Development and Mental Health of Hubei Province, National Intelligent Society Governance Experiment Base (Education), School of Psychology, Central China Normal University, Wuhan, China
| | - Jun Ruan
- Key Laboratory of Adolescent Cyberpsychology and Behavior (Ministry of Education), School of Psychology, Central China Normal University, Wuhan, China; Key Laboratory of Human Development and Mental Health of Hubei Province, National Intelligent Society Governance Experiment Base (Education), School of Psychology, Central China Normal University, Wuhan, China
| | - Sijun Liu
- Key Laboratory of Adolescent Cyberpsychology and Behavior (Ministry of Education), School of Psychology, Central China Normal University, Wuhan, China; Key Laboratory of Human Development and Mental Health of Hubei Province, National Intelligent Society Governance Experiment Base (Education), School of Psychology, Central China Normal University, Wuhan, China
| | - Zhihong Ren
- Key Laboratory of Adolescent Cyberpsychology and Behavior (Ministry of Education), School of Psychology, Central China Normal University, Wuhan, China; Key Laboratory of Human Development and Mental Health of Hubei Province, National Intelligent Society Governance Experiment Base (Education), School of Psychology, Central China Normal University, Wuhan, China.
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Tang L, Zhao P, Pan C, Song Y, Zheng J, Zhu R, Wang F, Tang Y. Epigenetic molecular underpinnings of brain structural-functional connectivity decoupling in patients with major depressive disorder. J Affect Disord 2024; 363:249-257. [PMID: 39029702 DOI: 10.1016/j.jad.2024.07.110] [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: 10/04/2023] [Revised: 06/24/2024] [Accepted: 07/16/2024] [Indexed: 07/21/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) is progressively recognized as a stress-related disorder characterized by aberrant brain network dynamics, encompassing both structural and functional domains. Yet, the intricate interplay between these dynamic networks and their molecular underpinnings remains predominantly unexplored. METHODS Both structural and functional networks were constructed using multimodal neuroimaging data from 183 MDD patients and 300 age- and gender-matched healthy controls (HC). structural-functional connectivity (SC-FC) coupling was evaluated at both the connectome- and nodal-levels. Methylation data of five HPA axis key genes, including NR3C1, FKBP5, CRHBP, CRHR1, and CRHR2, were analyzed using Illumina Infinium Methylation EPIC BeadChip. RESULTS We observed a significant reduction in SC-FC coupling at the connectome-level in patients with MDD compared to HC. At the nodal level, we found an imbalance in SC-FC coupling, with reduced coupling in cortical regions and increased coupling in subcortical regions. Furthermore, we identified 23 differentially methylated CpG sites on the HPA axis, following adjustment for multiple comparisons and control of age, gender, and medication status. Notably, three CpG sites on NR3C1 (cg01294526, cg19457823, and cg23430507), one CpG site on FKBP5 (cg25563198), one CpG site on CRHR1 (cg26656751), and one CpG site on CRHR2 (cg18351440) exhibited significant associations with SC-FC coupling in MDD patients. CONCLUSIONS These findings provide valuable insights into the connection between micro-scale epigenetic changes in the HPA axis and SC-FC coupling at macro-scale connectomes. They unveil the mechanisms underlying increased susceptibility to MDD resulting from chronic stress and may suggest potential pharmacological targets within the HPA-axis for MDD treatment.
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Affiliation(s)
- Lili Tang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China; Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, PR China
| | - Pengfei Zhao
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China
| | - Chunyu Pan
- School of Computer Science and Engineering, Northeastern University, Shenyang, PR China
| | - Yanzhuo Song
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, PR China
| | - Junjie Zheng
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China
| | - Rongxin Zhu
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China.
| | - Yanqing Tang
- Department of Psychiatry, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR China.
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Li M, Hou X, Yan W, Wang D, Yu R, Li X, Li F, Chen J, Wei L, Liu J, Wang H, Zeng Q. Identification of Bipolar Disorder and Schizophrenia Based on Brain CT and Deep Learning Methods. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024:10.1007/s10278-024-01279-4. [PMID: 39327378 DOI: 10.1007/s10278-024-01279-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 09/03/2024] [Accepted: 09/18/2024] [Indexed: 09/28/2024]
Abstract
With the increasing prevalence of mental illness, accurate clinical diagnosis of mental illness is crucial. Compared with MRI, CT has the advantages of wide application, low price, short scanning time, and high patient cooperation. This study aims to construct a deep learning (DL) model based on CT images to make identification of bipolar disorder (BD) and schizophrenia (SZ). A total of 506 patients (BD = 227, SZ = 279) and 179 healthy controls (HC) was collected from January 2022 to May 2023 at two hospitals, and divided into an internal training set and an internal validation set according to a ratio of 4:1. An additional 65 patients (BD = 35, SZ = 30) and 40 HC were recruited from different hospitals, and served as an external test set. All subjects accepted the conventional brain CT examination. The DenseMD model for identify BD and SZ using multiple instance learning was developed and compared with other classical DL models. The results showed that DenseMD performed excellently with an accuracy of 0.745 in the internal validation set, whereas the accuracy of the ResNet-18, ResNeXt-50, and DenseNet-121model was 0.672, 0.664, and 0.679, respectively. For the external test set, DenseMD again outperformed other models with an accuracy of 0.724; however, the accuracy of the ResNet-18, ResNeXt-50, and DenseNet-121model was 0.657, 0.638, and 0.676, respectively. Therefore, the potential of DL models for identification of BD and SZ based on brain CT images was established, and identification ability of the DenseMD model was better than other classical DL models.
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Affiliation(s)
- Meilin Li
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, 250000, China
- Shandong First Medical University, Jinan, 250000, China
| | - Xingyu Hou
- Department of Psychiatry, Shandong Mental Health Center, Shandong University, Jinan, 250000, China
| | - Wanying Yan
- Infervision Medical Technology Co., Ltd, Beijing, 100000, China
| | - Dawei Wang
- Infervision Medical Technology Co., Ltd, Beijing, 100000, China
| | - Ruize Yu
- Infervision Medical Technology Co., Ltd, Beijing, 100000, China
| | - Xixiang Li
- Department of Radiology, Zaozhuang Mental Health Center (Zaozhuang Municipal No. 2 Hospital), Zaozhuang, 277000, China
| | - Fuyan Li
- Department of Radiology, Shandong Provincial Hospital Afliated to Shandong First Medical University, Jinan, 250000, China
| | - Jinming Chen
- Department of Radiology, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan, 250000, China
| | - Lingzhen Wei
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, 250000, China
- School of Clinical Medicine, Jining Medical University, Jining, 272000, China
| | - Jiahao Liu
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, 250000, China
- Shandong First Medical University, Jinan, 250000, China
| | - Huaizhen Wang
- The First Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, 250000, China
| | - Qingshi Zeng
- Department of Radiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, 250000, China.
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Xu Y, Cheng X, Li Y, Shen H, Wan Y, Ping L, Yu H, Cheng Y, Xu X, Cui J, Zhou C. Shared and Distinct White Matter Alterations in Major Depression and Bipolar Disorder: A Systematic Review and Meta-Analysis. J Integr Neurosci 2024; 23:170. [PMID: 39344242 DOI: 10.31083/j.jin2309170] [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: 04/21/2024] [Revised: 07/22/2024] [Accepted: 07/31/2024] [Indexed: 10/01/2024] Open
Abstract
BACKGROUND Identifying white matter (WM) microstructural similarities and differences between major depressive disorder (MDD) and bipolar disorder (BD) is an important way to understand the potential neuropathological mechanism in emotional disorders. Numerous diffusion tensor imaging (DTI) studies over recent decades have confirmed the presence of WM anomalies in these two affective disorders, but the results were inconsistent. This study aimed to determine the statistical consistency of DTI findings for BD and MDD by using the coordinate-based meta-analysis (CBMA) approach. METHODS We performed a systematic search of tract-based spatial statistics (TBSS) studies comparing MDD or BD with healthy controls (HC) as of June 30, 2024. The seed-based d-mapping (SDM) was applied to investigate fractional anisotropy (FA) changes. Meta-regression was then used to analyze the potential correlations between demographics and neuroimaging alterations. RESULTS Regional FA reductions in the body of the corpus callosum (CC) were identified in both of these two diseases. Besides, MDD patients also exhibited decreased FA in the genu and splenium of the CC, as well as the left anterior thalamic projections (ATP), while BD patients showed FA reduction in the left median network, and cingulum in addition to the CC. CONCLUSIONS The results highlighted that altered integrity in the body of CC served as the shared basis of MDD and BD, and distinct microstructural WM abnormalities also existed, which might induce the various clinical manifestations of these two affective disorders. The study was registered on PROSPERO (http://www.crd.york.ac.uk/PROSPERO), registration number: CRD42022301929.
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Affiliation(s)
- Yinghong Xu
- Department of Psychiatry, Shandong Daizhuang Hospital, 272075 Jining, Shandong, China
- School of Mental Health, Jining Medical University, 272002 Jining, Shandong, China
| | - Xiaodong Cheng
- Department of Psychiatry, Shandong Daizhuang Hospital, 272075 Jining, Shandong, China
| | - Ying Li
- School of Mental Health, Jining Medical University, 272002 Jining, Shandong, China
| | - Hailong Shen
- School of Mental Health, Jining Medical University, 272002 Jining, Shandong, China
| | - Yu Wan
- School of Mental Health, Jining Medical University, 272002 Jining, Shandong, China
| | - Liangliang Ping
- Department of Psychiatry, Xiamen Xianyue Hospital, 361012 Xiamen, Fujian, China
| | - Hao Yu
- School of Mental Health, Jining Medical University, 272002 Jining, Shandong, China
| | - Yuqi Cheng
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, 650032 Kunming, Yunnan, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, 650032 Kunming, Yunnan, China
| | - Jian Cui
- Department of Psychiatry, Shandong Daizhuang Hospital, 272075 Jining, Shandong, China
| | - Cong Zhou
- School of Mental Health, Jining Medical University, 272002 Jining, Shandong, China
- Department of Psychology, Affiliated Hospital of Jining Medical University, 272067 Jining, Shandong, China
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Shu YP, Zhang Q, Hou YZ, Liang S, Zheng ZL, Li JL, Wu G. Multimodal abnormalities of brain structures in adolescents and young adults with major depressive disorder: An activation likelihood estimation meta-analysis. World J Psychiatry 2024; 14:1106-1117. [PMID: 39050198 PMCID: PMC11262923 DOI: 10.5498/wjp.v14.i7.1106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 05/10/2024] [Accepted: 05/27/2024] [Indexed: 07/12/2024] Open
Abstract
BACKGROUND Major depressive disorder (MDD) in adolescents and young adults contributes significantly to global morbidity, with inconsistent findings on brain structural changes from structural magnetic resonance imaging studies. Activation likelihood estimation (ALE) offers a method to synthesize these diverse findings and identify consistent brain anomalies. AIM To identify consistent brain structural changes in adolescents and young adults with MDD using ALE meta-analysis. METHODS We performed a comprehensive literature search in PubMed, Web of Science, Embase, and Chinese National Knowledge Infrastructure databases for neuroimaging studies on MDD among adolescents and young adults published up to November 19, 2023. Two independent researchers performed the study selection, quality assessment, and data extraction. The ALE technique was employed to synthesize findings on localized brain function anomalies in MDD patients, which was supplemented by sensitivity analyses. RESULTS Twenty-two studies comprising fourteen diffusion tensor imaging (DTI) studies and eight voxel-based morphometry (VBM) studies, and involving 451 MDD patients and 465 healthy controls (HCs) for DTI and 664 MDD patients and 946 HCs for VBM, were included. DTI-based ALE demonstrated significant reductions in fractional anisotropy (FA) values in the right caudate head, right insula, and right lentiform nucleus putamen in adolescents and young adults with MDD compared to HCs, with no regions exhibiting increased FA values. VBM-based ALE did not demonstrate significant alterations in gray matter volume. Sensitivity analyses highlighted consistent findings in the right caudate head (11 of 14 analyses), right insula (10 of 14 analyses), and right lentiform nucleus putamen (11 of 14 analyses). CONCLUSION Structural alterations in the right caudate head, right insula, and right lentiform nucleus putamen in young MDD patients may contribute to its recurrent nature, offering insights for targeted therapies.
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Affiliation(s)
- Yan-Ping Shu
- Department of Psychiatry of Women and Children, The Second People’s Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
| | - Qin Zhang
- Department of Radiology, The Second People’s Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
- Department of Radiology, Guizhou Provincial People’s Hospital, Guiyang 550000, Guizhou Province, China
| | - Yong-Zhe Hou
- Department of Psychiatry of Women and Children, The Second People’s Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
| | - Shuang Liang
- Department of Radiology, The Second People’s Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
| | - Zu-Li Zheng
- Department of Psychiatry of Women and Children, The Second People’s Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
| | - Jia-Lin Li
- Medical Humanities College, Guizhou Medical University, Guiyang 550000, Guizhou Province, China
| | - Gang Wu
- Department of Psychiatry of Women and Children, The Second People’s Hospital of Guizhou Province, Guiyang 550000, Guizhou Province, China
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Krug A, Stein F, David FS, Schmitt S, Brosch K, Pfarr JK, Ringwald KG, Meller T, Thomas-Odenthal F, Meinert S, Thiel K, Winter A, Waltemate L, Lemke H, Grotegerd D, Opel N, Repple J, Hahn T, Streit F, Witt SH, Rietschel M, Andlauer TFM, Nöthen MM, Philipsen A, Nenadić I, Dannlowski U, Kircher T, Forstner AJ. Factor analysis of lifetime psychopathology and its brain morphometric and genetic correlates in a transdiagnostic sample. Transl Psychiatry 2024; 14:235. [PMID: 38830892 PMCID: PMC11148082 DOI: 10.1038/s41398-024-02936-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 05/16/2024] [Accepted: 05/16/2024] [Indexed: 06/05/2024] Open
Abstract
There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.
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Affiliation(s)
- Axel Krug
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany.
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany.
| | - Friederike S David
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Simon Schmitt
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Kai G Ringwald
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lena Waltemate
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- German Centre for Mental Health (DZPG), Site Jena-Magdeburg-Halle, Jena, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Goethe University Frankfurt, University Hospital, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Frankfurt, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Hector Institute for Artificial Intelligence in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159, Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159, Mannheim, Germany
| | - Till F M Andlauer
- Department of Neurology, Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Alexandra Philipsen
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior, University of Marburg, Marburg, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Centre for Human Genetics, University of Marburg, Marburg, Germany
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10
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Ota M, Noda T, Sato N, Okabe K, Nakazawa K, Oshio Y, Nakagome K. Common Relationship Between Causality Orientation and the Prefrontal Region in Psychiatric Disorders as Revealed by Diffusional Kurtosis Imaging. Cureus 2024; 16:e61138. [PMID: 38933632 PMCID: PMC11199088 DOI: 10.7759/cureus.61138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/26/2024] [Indexed: 06/28/2024] Open
Abstract
Background Motivation dysregulation is common in several psychiatric disorders. However, little is known about the relationships between motivation and the regional brain areas involved. We evaluated the relationships between brain microstructural features and causality orientation in patients with schizophrenia, major depressive disorder (MDD), and bipolar disorder (BD) using diffusional kurtosis imaging (DKI) techniques. Methods Forty patients with MDD, 36 with BD, and 30 with schizophrenia underwent DKI and assessment using the General Causality Orientation Scale (GCOS). We analyzed the DKI index and the GCOS subscales. Results The psychiatric patients showed significant positive correlations between the GCOS-autonomy orientation score and the mean kurtosis (MK) values in the prefrontal regions, orbitofrontal regions, and posterior cingulate cortex. When the analyses were performed separately by disease and gender, a positive correlation was found between the GCOS-autonomy orientation score and the MK values in the left prefrontal regions transdiagnostically, especially among female patients with MDD, BD, and schizophrenia. Conclusions A similar association between intrinsic motivation and MK value in the left prefrontal cortex was suggested in patients with schizophrenia, MDD, and BD. The commonality of this association among these disorders might lead to the discovery of a new biomarker for psychiatric clinical research.
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Affiliation(s)
- Miho Ota
- Department of Neuropsychiatry, University of Tsukuba, Tsukuba, JPN
- Department of Radiology, National Center of Neurology and Psychiatry, Kodaira, JPN
| | - Takamasa Noda
- Department of Psychiatry, National Center of Neurology and Psychiatry, Kodaira, JPN
| | - Noriko Sato
- Department of Radiology, National Center of Neurology and Psychiatry, Kodaira, JPN
| | - Kaori Okabe
- Department of Psychiatry, National Center of Neurology and Psychiatry, Kodaira, JPN
| | - Kanako Nakazawa
- Faculty of Human Sciences, University of Tsukuba, Tsukuba, JPN
| | - Yoshiko Oshio
- Department of Psychiatry, National Center of Neurology and Psychiatry, Kodaira, JPN
| | - Kazuyuki Nakagome
- Department of Psychiatry, National Center of Neurology and Psychiatry, Kodaira, JPN
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11
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Lisoni J, Nibbio G, Baldacci G, Zucchetti A, Cicale A, Zardini D, Miotto P, Deste G, Barlati S, Vita A. Improving depressive symptoms in patients with schizophrenia using bilateral bipolar-nonbalanced prefrontal tDCS: Results from a double-blind sham-controlled trial. J Affect Disord 2024; 349:165-175. [PMID: 38199388 DOI: 10.1016/j.jad.2024.01.050] [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: 07/21/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
BACKGROUND Treating depressive symptoms in patients with schizophrenia is challenging. While transcranical Dicrect Current Stimulation (tDCS) improved other core symptoms of schizophrenia, conflicting results have been obtained on depressive symptoms. Thus, we aimed to expand current evidence on tDCS efficacy to improve depressive symptoms in patients with schizophrenia. METHODS A double-blind RCT was performed with patients randomized to 2 mA active-tDCS or sham-tDCS (15 daily sessions) with a bilateral bipolar-nonbalanced prefrontal placement (anode: left Dorsolateral prefrontal cortex; cathode: right orbitofrontal region). Clinical outcomes included variations of Calgary Depression Scale for Schizophrenia total score (CDSS) and of Depression-hopelessness and Guilty idea of reference-pathological guilt factors. Analysis of covariance was performed evaluating between-group changes over time. The presence/absence of probable clinically significant depression was determined when CDSS > 6. RESULTS As 50 outpatients were included (both groups, n = 25), significant improvements following active-tDCS were observed for CDSS total score (p = 0.001), Depression-hopelessness (p = 0.001) and Guilty idea of reference-pathological guilt (p = 0.03). Considering patients with CDSS>6 (n = 23), compared to sham, active-tDCS significantly improved CDSS total score (p < 0.001), Depression-hopelessness (p = 0.001) but Guilty idea of reference-pathological guilt only marginally improved (p = 0.051). Considering response rates of clinically significant depression, important reductions of CDSS score were observed (78 % of the sample scored ≤6; active-tDCS, n = 23; sham-tDCS, n = 16; p = 0.017). Early wakening item did not significantly change in any group. LIMITATIONS The study lacks a follow-up period and evaluation of tDCS effects on psychosocial functioning. CONCLUSIONS Bilateral bipolar-nonbalanced prefrontal tDCS is a successful protocol for the treatment of depressive symptoms in patients with schizophrenia.
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Affiliation(s)
- Jacopo Lisoni
- Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy.
| | - Gabriele Nibbio
- Department of Clinical and Experimental Sciences, University of Brescia, Viale Europa 11, 25123 Brescia, Italy
| | - Giulia Baldacci
- Department of Clinical and Experimental Sciences, University of Brescia, Viale Europa 11, 25123 Brescia, Italy
| | - Andrea Zucchetti
- Department of Clinical and Experimental Sciences, University of Brescia, Viale Europa 11, 25123 Brescia, Italy
| | - Andrea Cicale
- Department of Clinical and Experimental Sciences, University of Brescia, Viale Europa 11, 25123 Brescia, Italy
| | - Daniela Zardini
- Department of Clinical and Experimental Sciences, University of Brescia, Viale Europa 11, 25123 Brescia, Italy
| | - Paola Miotto
- Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy
| | - Giacomo Deste
- Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy; Department of Clinical and Experimental Sciences, University of Brescia, Viale Europa 11, 25123 Brescia, Italy
| | - Stefano Barlati
- Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy; Department of Clinical and Experimental Sciences, University of Brescia, Viale Europa 11, 25123 Brescia, Italy
| | - Antonio Vita
- Department of Mental Health and Addiction Services, ASST Spedali Civili of Brescia, Piazzale Spedali Civili 1, 25123 Brescia, Italy; Department of Clinical and Experimental Sciences, University of Brescia, Viale Europa 11, 25123 Brescia, Italy
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12
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Lin X, Huo Y, Wang Q, Liu G, Shi J, Fan Y, Lu L, Jing R, Li P. Using normative modeling to assess pharmacological treatment effect on brain state in patients with schizophrenia. Cereb Cortex 2024; 34:bhae003. [PMID: 38252996 DOI: 10.1093/cercor/bhae003] [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: 10/30/2023] [Revised: 12/28/2023] [Accepted: 12/30/2023] [Indexed: 01/24/2024] Open
Abstract
Quantifying individual differences in neuroimaging metrics is attracting interest in clinical studies with mental disorders. Schizophrenia is diagnosed exclusively based on symptoms, and the biological heterogeneity makes it difficult to accurately assess pharmacological treatment effects on the brain state. Using the Cambridge Centre for Ageing and Neuroscience data set, we built normative models of brain states and mapped the deviations of the brain characteristics of each patient, to test whether deviations were related to symptoms, and further investigated the pharmacological treatment effect on deviation distributions. Specifically, we found that the patients can be divided into 2 groups: the normalized group had a normalization trend and milder symptoms at baseline, and the other group showed a more severe deviation trend. The baseline severity of the depression as well as the overall symptoms could predict the deviation of the static characteristics for the dorsal and ventral attention networks after treatment. In contrast, the positive symptoms could predict the deviations of the dynamic fluctuations for the default mode and dorsal attention networks after treatment. This work evaluates the effect of pharmacological treatment on static and dynamic brain states using an individualized approach, which may assist in understanding the heterogeneity of the illness pathology as well as the treatment response.
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Affiliation(s)
- Xiao Lin
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China
| | - Yanxi Huo
- School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing 100192, China
| | - Qiandong Wang
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Faculty of Psychology, Beijing Normal University, Beijing 100875, China
| | - Guozhong Liu
- School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing 100192, China
| | - Jie Shi
- National Institute on Drug Dependence and Beijing Key Laboratory on Drug Dependence Research, Peking University, Beijing 100191, China
| | - Yong Fan
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia 19104, United States
| | - Lin Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China
| | - Rixing Jing
- School of Instrument Science and Opto-Electronics Engineering, Beijing Information Science and Technology University, Beijing 100192, China
| | - Peng Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Chinese Academy of Medical Sciences Research Unit (No. 2018RU006), Peking University, Beijing 100191, China
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13
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Xiao Y, Womer FY, Dong S, Zhu R, Zhang R, Yang J, Zhang L, Liu J, Zhang W, Liu Z, Zhang X, Wang F. A neuroimaging-based precision medicine framework for depression. Asian J Psychiatr 2024; 91:103803. [PMID: 37992593 DOI: 10.1016/j.ajp.2023.103803] [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: 08/07/2023] [Revised: 09/20/2023] [Accepted: 10/16/2023] [Indexed: 11/24/2023]
Abstract
BACKGROUND Symptom-based diagnostic criteria of depression leads to notorious heterogeneity and subjectivity. METHODS The study was conducted in two stages at two sites: development of a neuroimaging-based subtyping and precise repetitive transcranial magnetic stimulation (rTMS) strategy for depression at Center 1 and its clinical application at Center 2. Center 1 identified depression subtypes and subtype-specific rTMS targets based on amplitude of low frequency fluctuation (ALFF) in a cohort of 238 major depressive disorder patients and 66 healthy controls (HC). Subtypes were identified using a Gaussian Mixture Model, and subtype-specific rTMS targets were selected based on dominant brain regions prominently differentiating depression subtypes from HC. Subsequently, one classifier was employed and 72 hospitalized, depressed youths at Center 2 received two-week precise rTMS. MRI and clinical assessments were obtained at baseline, midpoint, and treatment completion for evaluation. RESULTS Two neuroimaging subtypes of depression, archetypal and atypical depression, were identified based on distinct frontal-posterior functional imbalance patterns as measured by ALFF. The dorsomedial prefrontal cortex was identified as the rTMS target for archetypal depression, and the occipital cortex for atypical depression. Following precise rTMS, ALFF alterations were normalized in both archetypal and atypical depressed youths, corresponding with symptom response of 90.00% in archetypal depression and 70.73% in atypical depression. CONCLUSIONS A precision medicine framework for depression was developed based on objective neurobiomarkers and implemented with promising results, actualizing a subtyping-treatment-evaluation closed loop in depression. Future randomized controlled trials are warranted.
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Affiliation(s)
- Yao Xiao
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Fay Y Womer
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shuai Dong
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Rongxin Zhu
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Ran Zhang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Jingyu Yang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Luheng Zhang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Juan Liu
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China
| | - Weixiong Zhang
- Department of Health Technology and Informatics, Department of Computing, The Hong Kong Polytechnic University, Hong Kong
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China; Taikang center for life and medical sciences, Wuhan University, Wuhan, China.
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China.
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China.
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14
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Liang S, Zhao L, Ni P, Wang Q, Guo W, Xu Y, Cai J, Tao S, Li X, Deng W, Palaniyappan L, Li T. Frontostriatal circuitry and the tryptophan kynurenine pathway in major psychiatric disorders. Psychopharmacology (Berl) 2024; 241:97-107. [PMID: 37735237 DOI: 10.1007/s00213-023-06466-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 09/09/2023] [Indexed: 09/23/2023]
Abstract
RATIONALE An imbalance of the tryptophan kynurenine pathway (KP) commonly occurs in psychiatric disorders, though the neurocognitive and network-level effects of this aberration are unclear. OBJECTIVES In this study, we examined the connection between dysfunction in the frontostriatal brain circuits, imbalances in the tryptophan kynurenine pathway (KP), and neurocognition in major psychiatric disorders. METHODS Forty first-episode medication-naive patients with schizophrenia (SCZ), fifty patients with bipolar disorder (BD), fifty patients with major depressive disorder (MDD), and forty-two healthy controls underwent resting-state functional magnetic resonance imaging. Plasma levels of KP metabolites were measured, and neurocognitive function was evaluated. Frontostriatal connectivity and KP metabolites were compared between groups while controlling for demographic and clinical characteristics. Canonical correlation analyses were conducted to explore multidimensional relationships between frontostriatal circuits-KP and KP-cognitive features. RESULTS Patient groups shared hypoconnectivity between bilateral ventrolateral prefrontal cortex (vlPFC) and left insula, with disorder-specific dysconnectivity in SCZ related to PFC, left dorsal striatum hypoconnectivity. The BD group had higher anthranilic acid and lower xanthurenic acid levels than the other groups. KP metabolites and ratios related to disrupted frontostriatal dysconnectivity in a transdiagnostic manner. The SCZ group and MDD group separately had high-dimensional associations between KP metabolites and cognitive measures. CONCLUSIONS The findings suggest that KP may influence cognitive performance across psychiatric conditions via frontostriatal dysfunction.
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Affiliation(s)
- Sugai Liang
- Department of Neurobiology, Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310013, Zhejiang, China
| | - Liansheng Zhao
- Mental Health Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Peiyan Ni
- Mental Health Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Qiang Wang
- Mental Health Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Wanjun Guo
- Department of Neurobiology, Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310013, Zhejiang, China
| | - Yan Xu
- Department of Neurobiology, Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310013, Zhejiang, China
| | - Jia Cai
- Mental Health Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Shiwan Tao
- Mental Health Centre & Psychiatric Laboratory, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Xiaojing Li
- Department of Neurobiology, Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310013, Zhejiang, China
| | - Wei Deng
- Department of Neurobiology, Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310013, Zhejiang, China
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, H4H1R3, Canada.
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, N6A5K8, Canada.
| | - Tao Li
- Department of Neurobiology, Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, 310013, Zhejiang, China.
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Zhejiang, 310000, Hangzhou, China.
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Zhejiang, 310063, Hangzhou, China.
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15
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Sun Y, Bo Q, Mao Z, Tian Q, Dong F, Li L, Wang C. Different levels of prepulse inhibition among patients with first-episode schizophrenia, bipolar disorder and major depressive disorder. J Psychiatry Neurosci 2024; 49:E1-E10. [PMID: 38238035 PMCID: PMC10803101 DOI: 10.1503/jpn.230083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/10/2023] [Accepted: 09/27/2023] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND Deficits in prepulse inhibition may be a common feature in first-episode schizophrenia, bipolar disorder (BD) and major depressive disorder (MDD). We sought to explore the levels and viability of prepulse inhibition to differentiate first-episode schizophrenia, BD and MDD in patient populations. METHODS We tested patients with first-episode schizophrenia, BD or MDD and healthy controls using prepulse inhibition paradigms, namely perceived spatial co-location (PSC-PPI) and perceived spatial separation (PSS-PPI). RESULTS We included 53 patients with first-episode schizophrenia, 30 with BD and 25 with MDD, as well as 82 healthy controls. The PSS-PPI indicated that the levels of prepulse inhibition were smallest to largest, respectively, in the first-episode schizophrenia, BD, MDD and control groups. Relative to the healthy controls, the prepulse inhibition deficits in the first-episode schizophrenia group were significant (p < 0.001), but the prepulse inhibitions were similar between patients with BD and healthy controls, and between patients with MDD and healthy controls. The receiver operating characteristic curve analysis showed that PSS-PPI (area under the curve [AUC] 0.73, p < 0.001) and latency (AUC 0.72, p < 0.001) were significant for differentiating patients with first-episode schizophrenia or BD from healthy controls. LIMITATIONS The demographics of the 4 groups were not ideally matched. We did not perform cognitive assessments. The possible confounding effect of medications on prepulse inhibition could not be eliminated. CONCLUSION The level of prepulse inhibition among patients with first-episode schizophrenia was the lowest, with levels among patients with BD, patients with MDD and healthy controls increasingly higher. The PSS-PPI paradigm was more effective than PSC-PPI to recognize deficits in prepulse inhibition. These results provide a basis for further research on biological indicators that can assist differential diagnoses in psychosis.
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Affiliation(s)
- Yue Sun
- From the National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, and Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the Advanced Innovation Center for Human Brain Protection, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China (Li)
| | - Qijing Bo
- From the National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, and Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the Advanced Innovation Center for Human Brain Protection, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China (Li)
| | - Zhen Mao
- From the National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, and Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the Advanced Innovation Center for Human Brain Protection, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China (Li)
| | - Qing Tian
- From the National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, and Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the Advanced Innovation Center for Human Brain Protection, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China (Li)
| | - Fang Dong
- From the National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, and Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the Advanced Innovation Center for Human Brain Protection, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China (Li)
| | - Liang Li
- From the National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, and Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the Advanced Innovation Center for Human Brain Protection, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China (Li)
| | - Chuanyue Wang
- From the National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, and Beijing Institute for Brain Disorders Center of Schizophrenia, Beijing Anding Hospital, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the Advanced Innovation Center for Human Brain Protection, Capital Medical University (Sun, Bo, Mao, Tian, Dong, Wang); the School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China (Li)
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16
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Radoeva PD, Milev VT, Hunt JI, Legere CH, Deoni SCL, Sheinkopf SJ, Mazefsky CA, Philip NS, Dickstein DP. Systematic Review: White Matter Microstructural Organization in Adolescents With Depression. JAACAP OPEN 2023; 1:233-245. [PMID: 38576601 PMCID: PMC10994197 DOI: 10.1016/j.jaacop.2023.08.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
Objective A growing body of literature has focused on the neural mechanisms of depression. Our goal was to conduct a systematic review on the white matter microstructural differences in adolescents with depressive disorders vs adolescents without depressive disorders. Method We searched PubMed and PsycINFO for publications on August 3, 2022 (original search conducted in July 2021). The review was registered on PROSPERO (registration number: CRD42021268200), and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Eligible studies were original research papers comparing diffusion tensor/spectrum imaging findings in adolescents with vs without depression (originally ages 12-19 years, later expanded to 11-21 years). Studies were excluded if they focused on depression exclusively in the context of another condition, used only dimensional depressive symptom assessment(s), or used the same dataset as another included publication. Results The search yielded 575 unique records, of which 14 full-text papers were included (824 adolescents with depression and 686 without depression). The following white matter regions showed significant differences in fractional anisotropy in at least 3 studies: uncinate fasciculus, cingulum, anterior corona radiata, inferior fronto-occipital fasciculus, and corpus callosum (genu and body). Most studies reported decreased, rather than increased, fractional anisotropy in adolescents with depression. Limitations include the possibility for selective reporting bias and risk of imprecision, given the small sample sizes in some studies. Conclusion Our systematic review suggests aberrant white matter microstructure in limbic-cortical-striatal-thalamic circuits, and the corpus callosum, in adolescents with depression. Future research should focus on developmental trajectories in depression, identifying sources of heterogeneity and integrating findings across imaging modalities.
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Affiliation(s)
- Petya D Radoeva
- Warren Alpert Medical School of Brown University, Providence, Rhode Island
- Emma Pendleton Bradley Hospital, East Providence, Rhode Island
| | | | - Jeffrey I Hunt
- Warren Alpert Medical School of Brown University, Providence, Rhode Island
- Emma Pendleton Bradley Hospital, East Providence, Rhode Island
| | - Christopher H Legere
- Warren Alpert Medical School of Brown University, Providence, Rhode Island
- Emma Pendleton Bradley Hospital, East Providence, Rhode Island
| | - Sean C L Deoni
- Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Stephen J Sheinkopf
- Thompson Center for Autism & Neurodevelopment, University of Missouri, Columbia, Missouri
| | - Carla A Mazefsky
- University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Noah S Philip
- VA Providence Healthcare System, Providence, Rhode Island
| | - Daniel P Dickstein
- Pediatric Mood, Imaging, and NeuroDevelopment (Ped-iMIND) Program, McLean Hospital, Belmont, Massachusetts and Harvard Medical School, Boston, Massachusetts
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17
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Hao M, Qin Y, Li Y, Tang Y, Ma Z, Tan J, Jin L, Wang F, Gong X. Metabolome subtyping reveals multi-omics characteristics and biological heterogeneity in major psychiatric disorders. Psychiatry Res 2023; 330:115605. [PMID: 38006718 DOI: 10.1016/j.psychres.2023.115605] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 11/02/2023] [Accepted: 11/10/2023] [Indexed: 11/27/2023]
Abstract
Growing evidence suggests that major psychiatric disorders (MPDs) share common etiologies and pathological processes. However, the diagnosis is currently based on descriptive symptoms, which ignores the underlying pathogenesis and hinders the development of clinical treatments. This highlights the urgency of characterizing molecular biomarkers and establishing objective diagnoses of MPDs. Here, we collected untargeted metabolomics, proteomics and DNA methylation data of 327 patients with MPDs, 131 individuals with genetic high risk and 146 healthy controls to explore the multi-omics characteristics of MPDs. First, differential metabolites (DMs) were identified and we classified MPD patients into 3 subtypes based on DMs. The subtypes showed distinct metabolomics, proteomics and DNA methylation signatures. Specifically, one subtype showed dysregulation of complement and coagulation proteins, while the DNA methylation showed abnormalities in chemical synapses and autophagy. Integrative analysis in metabolic pathways identified the important roles of the citrate cycle, sphingolipid metabolism and amino acid metabolism. Finally, we constructed prediction models based on the metabolites and proteomics that successfully captured the risks of MPD patients. Our study established molecular subtypes of MPDs and elucidated their biological heterogeneity through a multi-omics investigation. These results facilitate the understanding of pathological mechanisms and promote the diagnosis and prevention of MPDs.
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Affiliation(s)
- Meng Hao
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Fudan Zhangjiang Institute, Obstetrics and Gynecology Hospital, Human Phenome Institute, Fudan University, China
| | - Yue Qin
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Fudan Zhangjiang Institute, Obstetrics and Gynecology Hospital, Human Phenome Institute, Fudan University, China
| | - Yi Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Fudan Zhangjiang Institute, Obstetrics and Gynecology Hospital, Human Phenome Institute, Fudan University, China; International Human Phenome Institutes, Shanghai, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Zehan Ma
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Jingze Tan
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China; Zhangjiang Fudan International Innovation Center, Fudan Zhangjiang Institute, Obstetrics and Gynecology Hospital, Human Phenome Institute, Fudan University, China; International Human Phenome Institutes, Shanghai, China
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China.
| | - Xiaohong Gong
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China.
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18
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Zhang E, Hauson AO, Pollard AA, Meis B, Lackey NS, Carson B, Khayat S, Fortea L, Radua J. Lateralized grey matter volume changes in adolescents versus adults with major depression: SDM-PSI meta-analysis. Psychiatry Res Neuroimaging 2023; 335:111691. [PMID: 37837793 DOI: 10.1016/j.pscychresns.2023.111691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 05/22/2023] [Accepted: 07/19/2023] [Indexed: 10/16/2023]
Abstract
The current study is the first meta-analysis to examine grey matter volume (GMV) changes in adolescents and across the lifespan in major depressive disorder (MDD). Seed-based d mapping-with permutation of subject images (SDM-PSI) has advantages over previous coordinate-based meta-analytical methods (CBMA), such as reducing bias (via the MetaNSUE algorithm) and including non-statistically significant unreported effects. SDM-PSI was used to analyze 105 whole-brain GMV voxel-based morphometry (VBM) studies comparing 6,530 individuals with MDD versus 6,821 age-matched healthy controls (HC). A laterality effect was observed in which adults with MDD showed lower GMV than adult HC in left fronto-temporo-parietal structures (superior temporal gyrus, insula, Rolandic operculum, and inferior frontal gyrus). However, these abnormalities were not statistically significant for adolescent MDD versus adolescent HC. Instead, adolescent MDD showed lower GMV than adult MDD in right temporo-parietal structures (angular gyrus and middle temporal gyrus). These regional differences may be used as potential biomarkers to predict and monitor treatment outcomes as well as to choose the most effective treatments in adolescents versus adults. Finally, due to the paucity of youth, older adult, and longitudinal studies, future studies should attempt to replicate these GMV findings and examine whether they correlate with treatment response and illness severity.
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Affiliation(s)
- Emily Zhang
- California School of Professional Psychology, Clinical Psychology Ph.D. Program, San Diego, CA, United States of America; Institute of Brain Research and Integrated Neuropsychological Services (iBRAINs.org), San Diego, CA, United States of America
| | - Alexander O Hauson
- California School of Professional Psychology, Clinical Psychology Ph.D. Program, San Diego, CA, United States of America; Institute of Brain Research and Integrated Neuropsychological Services (iBRAINs.org), San Diego, CA, United States of America; Department of Psychiatry, University of California San Diego, La Jolla, CA, United States of America.
| | - Anna A Pollard
- California School of Professional Psychology, Clinical Psychology Ph.D. Program, San Diego, CA, United States of America; Institute of Brain Research and Integrated Neuropsychological Services (iBRAINs.org), San Diego, CA, United States of America
| | - Benjamin Meis
- California School of Professional Psychology, Clinical Psychology Ph.D. Program, San Diego, CA, United States of America; Institute of Brain Research and Integrated Neuropsychological Services (iBRAINs.org), San Diego, CA, United States of America
| | - Nicholas S Lackey
- California School of Professional Psychology, Clinical Psychology Ph.D. Program, San Diego, CA, United States of America; Institute of Brain Research and Integrated Neuropsychological Services (iBRAINs.org), San Diego, CA, United States of America
| | - Bryce Carson
- California School of Professional Psychology, Clinical Psychology Ph.D. Program, San Diego, CA, United States of America; Institute of Brain Research and Integrated Neuropsychological Services (iBRAINs.org), San Diego, CA, United States of America
| | - Sarah Khayat
- Institute of Brain Research and Integrated Neuropsychological Services (iBRAINs.org), San Diego, CA, United States of America
| | - Lydia Fortea
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Joaquim Radua
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, University of Barcelona, Barcelona, Spain; Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden; Department of Psychosis Studies, Institute of Psychology, Psychiatry, and Neuroscience, King's College London, London, United Kingdom
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19
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Zhao G, Zhang H, Ma L, Wang Y, Chen R, Liu N, Men W, Tan S, Gao JH, Qin S, He Y, Dong Q, Tao S. Reduced volume of the left cerebellar lobule VIIb and its increased connectivity within the cerebellum predict more general psychopathology one year later via worse cognitive flexibility in children. Dev Cogn Neurosci 2023; 63:101296. [PMID: 37690374 PMCID: PMC10507200 DOI: 10.1016/j.dcn.2023.101296] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/30/2023] [Accepted: 09/05/2023] [Indexed: 09/12/2023] Open
Abstract
Predicting the risk for general psychopathology (the p factor) requires the examination of multiple factors ranging from brain to cognitive skills. While an increasing number of findings have reported the roles of the cerebral cortex and executive functions, it is much less clear whether and how the cerebellum and cognitive flexibility (a core component of executive function) may be associated with the risk for general psychopathology. Based on the data from more than 400 children aged 6-12 in the Children School Functions and Brain Development (CBD) Project, this study examined whether the left cerebellar lobule VIIb and its connectivity within the cerebellum may prospectively predict the risk for general psychopathology one year later and whether cognitive flexibility may mediate such predictions in school-age children. The reduced gray matter volume in the left cerebellar lobule VIIb and the increased connectivity of this region to the left cerebellar lobule VI prospectively predicted the risk for general psychopathology and was partially mediated by worse cognitive flexibility. Deficits in cognitive flexibility may play an important role in linking cerebellar structure and function to the risk for general psychopathology.
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Affiliation(s)
- Gai Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Haibo Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Leilei Ma
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Rui Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Ningyu Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Weiwei Men
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Shuping Tan
- Psychiatry Research Center, Beijing Huilongguan Hospital, Peking University, Beijing 100096, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Sha Tao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
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20
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State of illness-dependent associations of neuro-cognition and psychopathological syndromes in a large transdiagnostic cohort. J Affect Disord 2023; 324:589-599. [PMID: 36586619 DOI: 10.1016/j.jad.2022.12.129] [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: 12/14/2021] [Revised: 05/19/2022] [Accepted: 12/23/2022] [Indexed: 12/29/2022]
Abstract
BACKGROUND There is a lack of knowledge regarding the relationship between dimensional psychopathological syndromes and neurocognitive functions, particularly across the major psychiatric disorders (i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), and Schizophrenia (SZ)). METHOD SANS, SAPS, HAMA, HAM-D, and YMRS were assessed in 1064 patients meeting DSM-IV-TR criteria for MDD, BD, SZ or schizoaffective disorder (SZA). In addition, a comprehensive neuropsychological test battery was administered. Psychopathological syndromes derived from factor analysis and present state of illness were used to explore psychopathology-cognition relationships. Correlational analyses were corrected for age, sex, verbal IQ, years of education, and DSM-IV-TR diagnosis. Age of onset and total duration of hospitalizations as proxies for illness severity were tested as moderators on the cognition - psychopathology relationship. RESULTS The negative syndrome, positive formal thought disorder as well as the paranoid-hallucinatory syndrome exhibited associations with neuro-cognition in an illness state-dependent manner, while the psychopathological factors depression and increased appetite only showed weak associations. Illness severity showed moderating effects on the neurocognitive-psychopathology relationship only for the negative syndrome and positive formal thought disorder. LIMITATIONS No healthy control subjects were entered into the analyses because of lack of variance in psychopathological symptoms, which prevents from drawing conclusions regarding the relative level of potential cognitive impairments. CONCLUSIONS This study suggests the relationship of neuro-cognition and psychopathology to be highly state of illness-dependent across affective and psychotic disorders. Results hint at the moderating effects of illness severity on psychopathological factors that might be more treatment resistant.
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21
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Sun Y, Hu N, Wang M, Lu L, Luo C, Tang B, Yao C, Sweeney JA, Gong Q, Qiu C, Lui S. Hippocampal subfield alterations in schizophrenia and major depressive disorder: a systematic review and network meta-analysis of anatomic MRI studies. J Psychiatry Neurosci 2023; 48:E34-E49. [PMID: 36750240 PMCID: PMC9911126 DOI: 10.1503/jpn.220086] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 07/28/2022] [Accepted: 10/30/2022] [Indexed: 02/09/2023] Open
Abstract
BACKGROUND Hippocampal disturbances are important in the pathophysiology of both schizophrenia and major depressive disorder (MDD). Imaging studies have shown selective volume deficits across hippocampal subfields in both disorders. We aimed to investigate whether these volumetric alterations in hippocampal subfields are shared or divergent across disorders. METHODS We searched PubMed and Embase from database inception to May 8, 2021. We identified MRI studies in patients with schizophrenia, MDD or both, in which hippocampal subfield volumes were measured. We excluded nonoriginal, animal or postmortem studies, and studies that used other imaging modalities or overlapping data. We conducted a network meta-analysis to estimate and contrast alterations in subfield volumes in the 2 disorders. RESULTS We identified 45 studies that met the initial criteria for systematic review, of which 15 were eligible for network metaanalysis. Compared to healthy controls, patients with schizophrenia had reduced volumes in the bilateral cornu ammonis (CA) 1, granule cell layer of the dentate gyrus, subiculum, parasubiculum, molecular layer, hippocampal tail and hippocampus-amygdala transition area (HATA); in the left CA4 and presubiculum; and in the right fimbria. Patients with MDD had decreased volumes in the left CA3 and CA4 and increased volumes in the right HATA compared to healthy controls. The bilateral parasubiculum and right HATA were smaller in patients with schizophrenia than in patients with MDD. LIMITATIONS We did not investigate medication effects because of limited information. Study heterogeneity was noteworthy in direct comparisons between patients with MDD and healthy controls. CONCLUSION The volumes of multiple hippocampal subfields are selectively altered in patients with schizophrenia and MDD, with overlap and differentiation in subfield alterations across disorders. Rigorous head-to-head studies are needed to validate our findings.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Changjian Qiu
- From the Huaxi MR Research Center, Department of Radiology and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Sun, Lu, Tang, Yao, Sweeney, Gong, Lui); the Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Hu, Luo); the Chinese Evidence-Based Medicine Center and Cochrane China Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Wang); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio, United States (Sweeney); the Mental Health Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Qiu); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (Lui); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Lui)
| | - Su Lui
- From the Huaxi MR Research Center, Department of Radiology and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Sun, Lu, Tang, Yao, Sweeney, Gong, Lui); the Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Hu, Luo); the Chinese Evidence-Based Medicine Center and Cochrane China Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Wang); the Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio, United States (Sweeney); the Mental Health Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Qiu); the Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China (Lui); the Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China (Lui)
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22
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Wei Y, de Lange SC, Savage JE, Tissink E, Qi T, Repple J, Gruber M, Kircher T, Dannlowski U, Posthuma D, van den Heuvel MP. Associated Genetics and Connectomic Circuitry in Schizophrenia and Bipolar Disorder. Biol Psychiatry 2022:S0006-3223(22)01719-X. [PMID: 36803976 DOI: 10.1016/j.biopsych.2022.11.006] [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: 07/04/2022] [Revised: 10/15/2022] [Accepted: 11/02/2022] [Indexed: 11/11/2022]
Abstract
BACKGROUND Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions that can involve symptoms of psychosis and cognitive dysfunction. The 2 conditions share symptomatology and genetic etiology and are regularly hypothesized to share underlying neuropathology. Here, we examined how genetic liability to SCZ and BD shapes normative variations in brain connectivity. METHODS We examined the effect of the combined genetic liability for SCZ and BD on brain connectivity from two perspectives. First, we examined the association between polygenic scores for SCZ and BD for 19,778 healthy subjects from the UK Biobank and individual variation in brain structural connectivity reconstructed by means of diffusion weighted imaging data. Second, we conducted genome-wide association studies using genotypic and imaging data from the UK Biobank, taking SCZ-/BD-involved brain circuits as phenotypes of interest. RESULTS Our findings showed brain circuits of superior parietal and posterior cingulate regions to be associated with polygenic liability for SCZ and BD, circuitry that overlaps with brain networks involved in disease conditions (r = 0.239, p < .001). Genome-wide association study analysis showed 9 significant genomic loci associated with SCZ-involved circuits and 14 loci associated with BD-involved circuits. Genes related to SCZ-/BD-involved circuits were significantly enriched in gene sets previously reported in genome-wide association studies for SCZ and BD. CONCLUSIONS Our findings suggest that polygenic liability of SCZ and BD is associated with normative individual variation in brain circuitry.
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Affiliation(s)
- Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China; Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
| | - Siemon C de Lange
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Jeanne E Savage
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Elleke Tissink
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Ting Qi
- Department of Neurology, School of Medicine, University of California San Francisco, San Francisco, California
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Marius Gruber
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Department of Child and Adolescent Psychiatry and Psychology, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam UMC, Amsterdam, the Netherlands
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Department of Child and Adolescent Psychiatry and Psychology, Section Complex Trait Genetics, Amsterdam Neuroscience, Vrije Universiteit Medical Center, Amsterdam UMC, Amsterdam, the Netherlands.
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23
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Neacsiu AD, Szymkiewicz V, Galla JT, Li B, Kulkarni Y, Spector CW. The neurobiology of misophonia and implications for novel, neuroscience-driven interventions. Front Neurosci 2022; 16:893903. [PMID: 35958984 PMCID: PMC9359080 DOI: 10.3389/fnins.2022.893903] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 06/28/2022] [Indexed: 11/25/2022] Open
Abstract
Decreased tolerance in response to specific every-day sounds (misophonia) is a serious, debilitating disorder that is gaining rapid recognition within the mental health community. Emerging research findings suggest that misophonia may have a unique neural signature. Specifically, when examining responses to misophonic trigger sounds, differences emerge at a physiological and neural level from potentially overlapping psychopathologies. While these findings are preliminary and in need of replication, they support the hypothesis that misophonia is a unique disorder. In this theoretical paper, we begin by reviewing the candidate networks that may be at play in this complex disorder (e.g., regulatory, sensory, and auditory). We then summarize current neuroimaging findings in misophonia and present areas of overlap and divergence from other mental health disorders that are hypothesized to co-occur with misophonia (e.g., obsessive compulsive disorder). Future studies needed to further our understanding of the neuroscience of misophonia will also be discussed. Next, we introduce the potential of neurostimulation as a tool to treat neural dysfunction in misophonia. We describe how neurostimulation research has led to novel interventions in psychiatric disorders, targeting regions that may also be relevant to misophonia. The paper is concluded by presenting several options for how neurostimulation interventions for misophonia could be crafted.
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Affiliation(s)
- Andrada D. Neacsiu
- Duke Center for Misophonia and Emotion Regulation, Duke Brain Stimulation Research Center, Department of Psychiatry and Behavioral Neuroscience, School of Medicine, Duke University, Durham, NC, United States
| | - Victoria Szymkiewicz
- Department of Psychology and Neuroscience, Duke University, Durham, NC, United States
| | - Jeffrey T. Galla
- Department of Psychology and Neuroscience, Duke University, Durham, NC, United States
| | - Brenden Li
- Department of Psychology and Neuroscience, Duke University, Durham, NC, United States
| | - Yashaswini Kulkarni
- Department of Psychology and Neuroscience, Duke University, Durham, NC, United States
| | - Cade W. Spector
- Department of Philosophy, Duke University, Durham, NC, United States
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Zhou L, Wang L, Wang M, Dai G, Xiao Y, Feng Z, Wang S, Chen G. Alterations in white matter microarchitecture in adolescents and young adults with major depressive disorder: A voxel-based meta-analysis of diffusion tensor imaging. Psychiatry Res Neuroimaging 2022; 323:111482. [PMID: 35477111 DOI: 10.1016/j.pscychresns.2022.111482] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 03/18/2022] [Accepted: 04/14/2022] [Indexed: 02/08/2023]
Abstract
Adolescents and young adults are at a critical stage of life development, and depression can have serious consequences. In recent decades, an increasing number of diffusion tensor imaging (DTI) studies of major depressive disorder (MDD) have reported inconsistent alterations in white matter (WM) microarchitecture. To rule out the confounding effects of age, we conducted a meta-analysis of fractional anisotropy (FA) in adolescents and young adults with MDD to identify abnormalities in WM involved in the pathogenesis of MDD using anisotropic effect-size signed differential mapping (AES-SDM). The pooled meta-analysis revealed significantly lower FA mainly in the corpus callosum (CC) extending to the left anterior thalamic projections (ATP) and left cortico-spinal projection (CSP) in depressed adolescents and young adults than that in healthy controls. A reduction in FA was also identified in the right frontal orbito-polar tract (FOPT) extending to the right inferior fronto-occipital fasciculus (IFOF). In the meta-regression analysis, the mean age of patients, percentage of female patients and duration of depression were not linearly associated with abnormalities in FA. These results constitute robust evidence that abnormalities in WM microarchitecture in the interhemispheric connections and frontal-subcortical neuronal circuits may contribute to the pathogenesis of MDD during adolescence and young adulthood.
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Affiliation(s)
- Li Zhou
- Department of Radiology, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Li Wang
- Department of Radiology, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Maohua Wang
- Department of Anesthesiology, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Guidong Dai
- Department of Radiology, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Yan Xiao
- Department of Radiology, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Zhi Feng
- Department of Radiology, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
| | - Guangxiang Chen
- Department of Radiology, Affiliated Hospital of Southwest Medical University, Luzhou 646000, Sichuan, China.
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25
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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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Shared Transdiagnostic Neuroanatomical Signatures Across First-episode Patients with Major Psychiatric Diseases and Individuals at Familial Risk. Neuroimage Clin 2022; 35:103074. [PMID: 35691252 PMCID: PMC9194955 DOI: 10.1016/j.nicl.2022.103074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 05/31/2022] [Accepted: 06/01/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND Nowadays, increasing evidence has found transdiagnostic neuroimaging biomarkers across major psychiatric disorders (MPDs). However, it remains to be known whether this transdiagnostic pattern of abnormalities could also be seen in individuals at familial high-risk for MPDs (FHR). We aimed to examine shared neuroanatomical endophenotypes and protective biomarkers for MPDs. METHODS This study examined brain grey matter volume (GMV) of individuals by voxel-based morphometry method. A total of 287 individuals were included, involving 100 first-episode medication-naive MPDs, 87 FHR, and 110 healthy controls (HC). They all underwent high-resolution structural magnetic resonance imaging (MRI). RESULTS At the group level, we found MPDs were characterized by decreased GMV in the right fusiform gyrus, the right inferior occipital gyrus, and the left anterior and middle cingulate gyri compared to HC and FHR. Of note, the GMV of the left superior temporal gyrus was increased in FHR relative to MPDs and HC. At the subgroup level, the comparisons within the FHR group did not return any significant difference, and we found GMV difference among subgroups within the MPDs group only in the opercular part of the right inferior frontal gyrus. CONCLUSION Together, our findings uncover common structural disturbances across MPDs and substantial changes in grey matter that may relate to high hereditary risk across FHR, potentially underscoring the importance of a transdiagnostic way to explore the neurobiological mechanisms of major psychiatric disorders.
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27
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DeRamus TP, Wu L, Qi S, Iraji A, Silva R, Du Y, Pearlson G, Mayer A, Bustillo JR, Stromberg SF, Calhoun VD. Multimodal data fusion of cortical-subcortical morphology and functional network connectivity in psychotic spectrum disorder. Neuroimage Clin 2022; 35:103056. [PMID: 35709557 PMCID: PMC9207350 DOI: 10.1016/j.nicl.2022.103056] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 04/18/2022] [Accepted: 05/21/2022] [Indexed: 11/20/2022]
Abstract
Overlap has been noted disorders which fall on the psychotic spectrum. Univariate studies may miss joint brain features across diagnostic categories. mCCA with jICA is paired with features across the psychotic spectrum to produce joint components. One joint component displayed a significant relationship with cognitive scores. The replicate trends of cortical-subcortical irregularity in psychotic spectrum disorders.
Multiple authors have noted overlapping symptoms and alterations across clinical, anatomical, and functional brain features in schizophrenia (SZ), schizoaffective disorder (SZA), and bipolar disorder (BPI). However, regarding brain features, few studies have approached this line of inquiry using analytical techniques optimally designed to extract the shared features across anatomical and functional information in a simultaneous manner. Univariate studies of anatomical or functional alterations across these disorders can be limited and run the risk of omitting small but potentially crucial overlapping or joint neuroanatomical (e.g., structural images) and functional features (e.g., fMRI-based features) which may serve as informative clinical indicators of across multiple diagnostic categories. To address this limitation, we paired an unsupervised multimodal canonical correlation analysis (mCCA) together with joint independent component analysis (jICA) to identify linked spatial gray matter (GM), resting-state functional network connectivity (FNC), and white matter fractional anisotropy (FA) features across these diagnostic categories. We then calculated associations between the identified linked features and trans-diagnostic behavioral measures (MATRICs Consensus Cognitive Battery, MCCB). Component number 4 of the 13 identified displayed a statistically significant relationship with overall MCCB scores across GM, resting-state FNC, and FA. These linked modalities of component 4 consisted primarily of positive correlations within subcortical structures including the caudate and putamen in the GM maps with overall MCCB, sparse negative correlations within subcortical and cortical connection tracts (e.g., corticospinal tract, superior longitudinal fasciculus) in the FA maps with overall MCCB, and negative relationships with MCCB values and loading parameters with FNC matrices displaying increased FNC in subcortical-cortical regions with auditory, somatomotor, and visual regions.
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Affiliation(s)
- T P DeRamus
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA.
| | - L Wu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - S Qi
- College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China
| | - A Iraji
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - R Silva
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - Y Du
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA; School of Computer and Information Technology, Shanxi University, Taiyuan, China
| | - G Pearlson
- Olin Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, Hartford, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - A Mayer
- The Mind Research Network, Lovelace Biomedical and Environmental Research Institute, Albuquerque, USA
| | - J R Bustillo
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM, USA
| | - S F Stromberg
- Psychiatry and Behavioral Health Clinical Program, Presbyterian Healthcare System, Albuquerque, NM, USA
| | - V D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) - Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA; The Mind Research Network, Lovelace Biomedical and Environmental Research Institute, Albuquerque, USA; Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA; Department of Computer Science, Georgia State University, Atlanta, USA; Department of Psychology, Georgia State University, Atlanta, USA
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28
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Huang Q, Qiao C, Jing K, Zhu X, Ren K. Biomarkers identification for Schizophrenia via VAE and GSDAE-based data augmentation. Comput Biol Med 2022; 146:105603. [PMID: 35588680 DOI: 10.1016/j.compbiomed.2022.105603] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 04/13/2022] [Accepted: 05/07/2022] [Indexed: 11/24/2022]
Abstract
Deep learning has made great progress in analyzing MRI data, while the MRI data with high dimensional but small sample size (HDSSS) brings many limitations to biomarkers identification. Few-shot learning has been proposed to solve such problems and data augmentation is a typical method of it. The variational auto-encoder (VAE) is a generative method based on variational Bayesian inference that is used for data augmentation. Graph regularized sparse deep autoencoder (GSDAE) can reconstruct sparse samples and keep the manifold structure of data which will facilitate biomarkers selection greatly. To generate better HDSSS data for biomarkers identification, a data augmentation method based on VAE and GSDAE is proposed in this paper, termed GS-VDAE. Instead of utilizing the final products of GSDAE, our proposed model embeds the generation procedure into GSDAE for augmentation. In this way, the augmented samples will be rooted in the significant features extracted from the original samples, which can ensure the newly formed samples contain the most significant characteristics of the original samples. The classification accuracy of the samples generated directly from VAE is 0.74, while the classification accuracy of the samples generated from GS-VDAE is 0.84, which proves the validity of our model. Additionally, a regression feature selection method with truncated nuclear norm regularization is chosen for biomarkers selection. The biomarkers selection results of schizophrenia data reveal that the augmented samples obtained by our proposed method can get higher classification accuracy with less ranked features compared with original samples, which proves the validation of our model.
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Affiliation(s)
- Qi Huang
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China.
| | - Chen Qiao
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China.
| | - Kaili Jing
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China; Department of Mathematics and Statistics, University of Ottawa, Ottawa, K7L 3P7, Canada.
| | - Xu Zhu
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China.
| | - Kai Ren
- Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
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29
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He E, Liu M, Gong S, Fu X, Han Y, Deng F. White Matter Alterations in Depressive Disorder. Front Immunol 2022; 13:826812. [PMID: 35634314 PMCID: PMC9133348 DOI: 10.3389/fimmu.2022.826812] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 03/22/2022] [Indexed: 11/13/2022] Open
Abstract
Depressive disorder is the most prevalent affective disorder today. Depressive disorder has been linked to changes in the white matter. White matter changes in depressive disorder could be a result of impaired cerebral blood flow (CBF) and CBF self-regulation, impaired blood-brain barrier function, inflammatory factors, genes and environmental factors. Additionally, white matter changes in patients with depression are associated with clinical variables such as differential diagnosis, severity, treatment effect, and efficacy assessment. This review discusses the characteristics, possible mechanisms, clinical relevance, and potential treatment of white matter alterations caused by depressive disorders.
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Luttenbacher I, Phillips A, Kazemi R, Hadipour AL, Sanghvi I, Martinez J, Adamson MM. Transdiagnostic role of glutamate and white matter damage in neuropsychiatric disorders: A Systematic Review. J Psychiatr Res 2022; 147:324-348. [PMID: 35151030 DOI: 10.1016/j.jpsychires.2021.12.042] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/08/2021] [Accepted: 12/19/2021] [Indexed: 12/09/2022]
Abstract
Neuropsychiatric disorders including generalized anxiety disorder (GAD), obsessive-compulsive disorder (OCD), major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ) have been considered distinct categories of diseases despite their overlapping characteristics and symptomatology. We aimed to provide an in-depth review elucidating the role of glutamate/Glx and white matter (WM) abnormalities in these disorders from a transdiagnostic perspective. The PubMed online database was searched for studies published between 2010 and 2021. After careful screening, 401 studies were included. The findings point to decreased levels of glutamate in the Anterior Cingulate Cortex in both SZ and BD, whereas Glx is elevated in the Hippocampus in SZ and MDD. With regard to WM abnormalities, the Corpus Callosum and superior Longitudinal Fascicle were the most consistently identified brain regions showing decreased fractional anisotropy (FA) across all the reviewed disorders, except GAD. Additionally, the Uncinate Fasciculus displayed decreased FA in all disorders, except OCD. Decreased FA was also found in the inferior Longitudinal Fasciculus, inferior Fronto-Occipital Fasciculus, Thalamic Radiation, and Corona Radiata in SZ, BD, and MDD. Decreased FA in the Fornix and Corticospinal Tract were found in BD and SZ patients. The Cingulum and Anterior Limb of Internal Capsule exhibited decreased FA in MDD and SZ patients. The results suggest a gradual increase in severity from GAD to SZ defined by the number of brain regions with WM abnormality which may be partially caused by abnormal glutamate levels. WM damage could thus be considered a potential marker of some of the main neuropsychiatric disorders.
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Affiliation(s)
- Ines Luttenbacher
- Department of Social & Behavioral Sciences, University of Amsterdam, Amsterdam, Netherlands; Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Angela Phillips
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Reza Kazemi
- Department of Cognitive Psychology, Institute for Cognitive Science Studies, Tehran, Iran
| | - Abed L Hadipour
- Department of Cognitive Sciences, University of Messina, Messina, Italy
| | - Isha Sanghvi
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Neuroscience, University of Southern California, Los Angeles, CA, USA
| | - Julian Martinez
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Palo Alto University, Palo Alto, CA, USA
| | - Maheen M Adamson
- Rehabilitation Service, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA.
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31
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Kang J, Jiao Z, Qin Y, Wang Y, Wang J, Jin L, Feng J, Wang F, Tang Y, Gong X. Associations between polygenic risk scores and amplitude of low-frequency fluctuation of inferior frontal gyrus in schizophrenia. J Psychiatr Res 2022; 147:4-12. [PMID: 34999338 DOI: 10.1016/j.jpsychires.2021.12.043] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 12/14/2021] [Accepted: 12/20/2021] [Indexed: 10/19/2022]
Abstract
Schizophrenia (SCZ) is a serious and complex mental disorder with high heritability. Polygenic risk score (PRS) is a useful tool calculating the accumulating effects of multiple common genetic variants of schizophrenia. The amplitude of low-frequency fluctuation (ALFF) is an efficient index to reflect spontaneous, intrinsic neuronal activity. Aberrant ALFF of brain regions were reported in schizophrenia frequently, but the relationship between PRS and ALFF has not been studied. In the present study, we compared PRS and ALFF in 101 schizophrenia patients and 106 age-matched healthy controls to test their associations with schizophrenia. Then, the correlation of PRS with ALFF was measured to reveal the effect of polygenic risk on brain activity in schizophrenia. We found that schizophrenia patients showed significant differences in PRS and ALFF compared with controls. Twenty-six brain regions showed significant difference of ALFF between schizophrenia cases and controls, of which left inferior frontal gyrus, triangular part (IFGtriang.L) showed increased activity in schizophrenia. PRS-SCZ was positively correlated with ALFF in IFGtriang.L in 57 non-chronic patients. Genes involved in synaptic organization and transmission, especially in glutamatergic synapse, were highly enriched in PRS-SCZ genes, suggesting the dysfunction of synapses in schizophrenia. These results help to understand the molecular mechanism underlying schizophrenia and related brain dysfunction.
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Affiliation(s)
- Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Zeyu Jiao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China
| | - Yue Qin
- School of Life Sciences, Fudan University, Shanghai, China
| | - Yi Wang
- School of Life Sciences, Fudan University, Shanghai, China
| | - Jiucun Wang
- School of Life Sciences, Fudan University, Shanghai, China; Human Phoneme Institute, Fudan University, Shanghai, China
| | - Li Jin
- School of Life Sciences, Fudan University, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Shanghai Center for Mathematical Science, Fudan University, Shanghai, China; Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK
| | - Fei Wang
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, China.
| | - Xiaohong Gong
- School of Life Sciences, Fudan University, Shanghai, China.
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Liu Y, Chen K, Luo Y, Wu J, Xiang Q, Peng L, Zhang J, Zhao W, Li M, Zhou X. Distinguish bipolar and major depressive disorder in adolescents based on multimodal neuroimaging: Results from the Adolescent Brain Cognitive Development study ®. Digit Health 2022; 8:20552076221123705. [PMID: 36090673 PMCID: PMC9452797 DOI: 10.1177/20552076221123705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 08/16/2022] [Indexed: 01/10/2023] Open
Abstract
Background Major depressive disorder and bipolar disorder in adolescents are prevalent and are associated with cognitive impairment, executive dysfunction, and increased mortality. Early intervention in the initial stages of major depressive disorder and bipolar disorder can significantly improve personal health. Methods We collected 309 samples from the Adolescent Brain Cognitive Development study, including 116 adolescents with bipolar disorder, 64 adolescents with major depressive disorder, and 129 healthy adolescents, and employed a support vector machine to develop classification models for identification. We developed a multimodal model, which combined functional connectivity of resting-state functional magnetic resonance imaging and four anatomical measures of structural magnetic resonance imaging (cortical thickness, area, volume, and sulcal depth). We measured the performances of both multimodal and single modality classifiers. Results The multimodal classifiers showed outstanding performance compared with all five single modalities, and they are 100% for major depressive disorder versus healthy controls, 100% for bipolar disorder versus healthy control, 98.5% (95% CI: 95.4–100%) for major depressive disorder versus bipolar disorder, 100% for major depressive disorder versus depressed bipolar disorder and the leave-one-site-out analysis results are 77.4%, 63.3%, 79.4%, and 81.7%, separately. Conclusions The study shows that multimodal classifiers show high classification performances. Moreover, cuneus may be a potential biomarker to differentiate major depressive disorder, bipolar disorder, and healthy adolescents. Overall, this study can form multimodal diagnostic prediction workflows for clinically feasible to make more precise diagnose at the early stage and potentially reduce loss of personal pain and public society.
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Affiliation(s)
- Yujun Liu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Kai Chen
- School of Public Health, University of Texas Health Science Center at Houston, Houston, USA
| | - Yangyang Luo
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Jiqiu Wu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Qu Xiang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Li Peng
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Jian Zhang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Weiling Zhao
- Center for Computational Systems Medicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, USA
| | - Mingliang Li
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Med-X Center for Informatics, Sichuan University, Chengdu, China
| | - Xiaobo Zhou
- Center for Computational Systems Medicine, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, USA
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Zhang Y. Individual prediction of hemispheric similarity of functional connectivity during normal aging. Front Psychiatry 2022; 13:1016807. [PMID: 36226096 PMCID: PMC9548650 DOI: 10.3389/fpsyt.2022.1016807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 08/31/2022] [Indexed: 11/29/2022] Open
Abstract
In the aging process of normal people, the functional activity pattern of brain is in constant change, and the change of brain runs through the whole life cycle, which plays a crucial role in the track of individual development. In recent years, some studies had been carried out on the brain functional activity pattern during individual aging process from different perspectives, which provided an opportunity for the problem we want to study. In this study, we used the resting-state functional magnetic resonance imaging (rs-fMRI) data from Cambridge Center for Aging and Neuroscience (Cam-CAN) database with large sample and long lifespan, and computed the functional connectivity (FC) values for each individual. Based on these values, the hemispheric similarity of functional connectivity (HSFC) obtained by Pearson correlation was used as the starting point of this study. We evaluated the ability of individual recognition of HSFC in the process of aging, as well as the variation trend with aging process. The results showed that HSFC could be used to identify individuals effectively, and it could reflect the change rule in the process of aging. In addition, we observed a series of results at the sub-module level and find that the recognition rate in the sub-module was different from each other, as well as the trend with age. Finally, as a validation, we repeated the main results by human brainnetome atlas (BNA) template and without global signal regression, found that had a good robustness. This also provides a new clue to hemispherical change patterns during normal aging.
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Affiliation(s)
- Yingteng Zhang
- Department of Mathematics, Taizhou University, Taizhou, China
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34
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Song Y, Yang J, Chang M, Wei Y, Yin Z, Zhu Y, Zhou Y, Zhou Y, Jiang X, Wu F, Kong L, Xu K, Wang F, Tang Y. Shared and distinct functional connectivity of hippocampal subregions in schizophrenia, bipolar disorder, and major depressive disorder. Front Psychiatry 2022; 13:993356. [PMID: 36186868 PMCID: PMC9515660 DOI: 10.3389/fpsyt.2022.993356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 08/19/2022] [Indexed: 11/13/2022] Open
Abstract
Schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD) share etiological and pathophysiological characteristics. Although neuroimaging studies have reported hippocampal alterations in SZ, BD, and MDD, little is known about how different hippocampal subregions are affected in these conditions because such subregions, namely, the cornu ammonis (CA), dentate gyrus (DG), and subiculum (SUB), have different structural foundations and perform different functions. Here, we hypothesize that different hippocampal subregions may reflect some intrinsic features among the major psychiatric disorders, such as SZ, BD, and MDD. By investigating resting functional connectivity (FC) of each hippocampal subregion among 117 SZ, 103 BD, 96 MDD, and 159 healthy controls, we found similarly and distinctly changed FC of hippocampal subregions in the three disorders. The abnormal functions of middle frontal gyrus might be the core feature of the psychopathological mechanisms of SZ, BD, and MDD. Anterior cingulate cortex and inferior orbital frontal gyrus might be the shared abnormalities of SZ and BD, and inferior orbital frontal gyrus is also positively correlated with depression and anxiety symptoms in SZ and BD. Caudate might be the unique feature of SZ and showed a positive correlation with the cognitive function in SZ. Middle temporal gyrus and supplemental motor area are the differentiating features of BD. Our study provides evidence for the different functions of different hippocampal subregions in psychiatric pathology.
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Affiliation(s)
- Yanzhuo Song
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China
| | - Jingyu Yang
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China.,Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Miao Chang
- Department of Radiology, First Hospital of China Medical University, Shenyang, China
| | - Yange Wei
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China.,Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Zhiyang Yin
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China
| | - Yue Zhu
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China
| | - Yuning Zhou
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China
| | - Yifang Zhou
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China
| | - Xiaowei Jiang
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China.,Department of Radiology, First Hospital of China Medical University, Shenyang, China
| | - Feng Wu
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China
| | - Lingtao Kong
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China
| | - Ke Xu
- Department of Radiology, First Hospital of China Medical University, Shenyang, China
| | - Fei Wang
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China.,Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yanqing Tang
- Department of Psychiatry, First Hospital of China Medical University, Shenyang, China
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35
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Brosch K, Stein F, Schmitt S, Pfarr JK, Ringwald KG, Thomas-Odenthal F, Meller T, Steinsträter O, Waltemate L, Lemke H, Meinert S, Winter A, Breuer F, Thiel K, Grotegerd D, Hahn T, Jansen A, Dannlowski U, Krug A, Nenadić I, Kircher T. Reduced hippocampal gray matter volume is a common feature of patients with major depression, bipolar disorder, and schizophrenia spectrum disorders. Mol Psychiatry 2022; 27:4234-4243. [PMID: 35840798 PMCID: PMC9718668 DOI: 10.1038/s41380-022-01687-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 06/22/2022] [Accepted: 06/27/2022] [Indexed: 02/07/2023]
Abstract
Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorder (SSD, schizophrenia, and schizoaffective disorder) overlap in symptomatology, risk factors, genetics, and other biological measures. Based on previous findings, it remains unclear what transdiagnostic regional gray matter volume (GMV) alterations exist across these disorders, and with which factors they are associated. GMV (3-T magnetic resonance imaging) was compared between healthy controls (HC; n = 110), DSM-IV-TR diagnosed MDD (n = 110), BD (n = 110), and SSD patients (n = 110), matched for age and sex. We applied a conjunction analysis to identify shared GMV alterations across the disorders. To identify potential origins of identified GMV clusters, we associated them with early and current risk and protective factors, psychopathology, and neuropsychology, applying multiple regression models. Common to all diagnoses (vs. HC), we identified GMV reductions in the left hippocampus. This cluster was associated with the neuropsychology factor working memory/executive functioning, stressful life events, and with global assessment of functioning. Differential effects between groups were present in the left and right frontal operculae and left insula, with volume variances across groups highly overlapping. Our study is the first with a large, matched, transdiagnostic sample to yield shared GMV alterations in the left hippocampus across major mental disorders. The hippocampus is a major network hub, orchestrating a range of mental functions. Our findings underscore the need for a novel stratification of mental disorders, other than categorical diagnoses.
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Affiliation(s)
- Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany. .,Center for Mind, Brain and Behavior (CMBB), Marburg, Germany.
| | - Frederike Stein
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.513205.0Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Simon Schmitt
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.513205.0Center for Mind, Brain and Behavior (CMBB), Marburg, Germany ,grid.10423.340000 0000 9529 9877Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
| | - Julia-Katharina Pfarr
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.513205.0Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Kai G. Ringwald
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.513205.0Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Florian Thomas-Odenthal
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.513205.0Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Tina Meller
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.513205.0Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Olaf Steinsträter
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.10253.350000 0004 1936 9756Core-Facility BrainImaging, Faculty of Medicine, Philipps-University Marburg, Marburg, Germany
| | - Lena Waltemate
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany ,grid.5949.10000 0001 2172 9288Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Alexandra Winter
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Fabian Breuer
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Thiel
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Andreas Jansen
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.513205.0Center for Mind, Brain and Behavior (CMBB), Marburg, Germany ,grid.10253.350000 0004 1936 9756Core-Facility BrainImaging, Faculty of Medicine, Philipps-University Marburg, Marburg, Germany
| | - Udo Dannlowski
- grid.5949.10000 0001 2172 9288Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Axel Krug
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.10388.320000 0001 2240 3300Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Igor Nenadić
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.513205.0Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Tilo Kircher
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, Philipps-University Marburg, University Hospital Marburg, UKGM, Marburg, Germany ,grid.513205.0Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
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36
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Sun D, Guo H, Womer FY, Yang J, Tang J, Liu J, Zhu Y, Duan J, Peng Z, Wang H, Tan Q, Zhu Q, Wei Y, Xu K, Zhang Y, Tang Y, Zhang X, Xu F, Wang J, Wang F. Frontal-posterior functional imbalance and aberrant function developmental patterns in schizophrenia. Transl Psychiatry 2021; 11:495. [PMID: 34580274 PMCID: PMC8476507 DOI: 10.1038/s41398-021-01617-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 07/28/2021] [Accepted: 08/20/2021] [Indexed: 12/01/2022] Open
Abstract
Schizophrenia (SZ) is a neurodevelopmental disorder. There remain significant gaps in understanding the neural trajectory across development in SZ. A major research focus is to clarify the developmental functional changes of SZ and to identify the specific timing, the specific brain regions, and the underlying mechanisms of brain alterations during SZ development. Regional homogeneity (ReHo) characterizing brain function was collected and analyzed on humans with SZ (hSZ) and healthy controls (HC) cross-sectionally, and methylazoxymethanol acetate (MAM) rats, a neurodevelopmental model of SZ, and vehicle rats longitudinally from adolescence to adulthood. Metabolomic and proteomic profiling in adult MAM rats and vehicle rats was examined and bioanalyzed. Compared to HC or adult vehicle rats, similar ReHo alterations were observed in hSZ and adult MAM rats, characterized by increased frontal (medial prefrontal and orbitofrontal cortices) and decreased posterior (visual and associated cortices) ReHo. Longitudinal analysis of MAM rats showed aberrant ReHo patterns as decreased posterior ReHo in adolescence and increased frontal and decreased posterior ReHo in adulthood. Accordingly, it was suggested that the visual cortex was a critical locus and adolescence was a sensitive window in SZ development. In addition, metabolic and proteomic alterations in adult MAM rats suggested that central carbon metabolism disturbance and mitochondrial dysfunction were the potential mechanisms underlying the ReHo alterations. This study proposed frontal-posterior functional imbalance and aberrant function developmental patterns in SZ, suggesting that the adolescent visual cortex was a critical locus and a sensitive window in SZ development. These findings from linking data between hSZ and MAM rats may have a significant translational contribution to the development of effective therapies in SZ.
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Affiliation(s)
- Dandan Sun
- grid.452816.c0000 0004 1757 9522Department of Cardiovascular Ultrasound, The People’s Hospital of China Medical University & The People’s Hospital of Liaoning Province, Shenyang, China ,grid.412636.4Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Huiling Guo
- grid.412636.4Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China ,grid.89957.3a0000 0000 9255 8984Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Fay Y. Womer
- grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University School of Medicine, St Louis, MO USA
| | - Jingyu Yang
- grid.89957.3a0000 0000 9255 8984Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Jingwei Tang
- grid.412636.4Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Juan Liu
- grid.412636.4Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China ,grid.89957.3a0000 0000 9255 8984Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yue Zhu
- grid.412636.4Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Jia Duan
- grid.412636.4Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China ,grid.89957.3a0000 0000 9255 8984Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Zhengwu Peng
- grid.233520.50000 0004 1761 4404Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Huaning Wang
- grid.233520.50000 0004 1761 4404Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Qingrong Tan
- grid.233520.50000 0004 1761 4404Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Qiwen Zhu
- grid.415680.e0000 0000 9549 5392Liaoning Key Laboratory of Cognitive Neuroscience, Shenyang Medical College, Shenyang, China
| | - Yange Wei
- grid.89957.3a0000 0000 9255 8984Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Ke Xu
- grid.412636.4Department of Radiology, The First Hospital of China Medical University, Shenyang, China
| | - Yanbo Zhang
- grid.17089.37Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, Canada
| | - Yanqing Tang
- grid.412636.4Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China
| | - Xizhe Zhang
- grid.89957.3a0000 0000 9255 8984School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Fuqiang Xu
- grid.9227.e0000000119573309Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China ,grid.9227.e0000000119573309Shenzhen Key Lab of Neuropsychiatric Modulation, Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jie Wang
- grid.9227.e0000000119573309Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China
| | - Fei Wang
- Department of Psychiatry, The First Hospital of China Medical University, Shenyang, China. .,Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China. .,Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, China.
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37
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Duan J, Wei Y, Womer FY, Zhang X, Chang M, Zhu Y, Liu Z, Li C, Yin Z, Zhang R, Sun J, Wang P, Wang S, Jiang X, Wei S, Zhang Y, Tang Y, Wang F. Neurobiological substrates of major psychiatry disorders: transdiagnostic associations between white matter abnormalities, neuregulin 1 and clinical manifestation. J Psychiatry Neurosci 2021; 46:E506-E515. [PMID: 34467747 PMCID: PMC8526153 DOI: 10.1503/jpn.200166] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Abstract
BACKGROUND Schizophrenia, bipolar disorder and major depressive disorder are increasingly being conceptualized as a transdiagnostic continuum. Disruption of white matter is a common alteration in these psychiatric disorders, but the molecular mechanisms underlying the disruption remain unclear. Neuregulin 1 (NRG1) is genetically linked with susceptibility to schizophrenia, bipolar disorder and major depressive disorder, and it is also related to white matter. METHODS Using a transdiagnostic approach, we aimed to identify white matter differences associated with NRG1 and their relationship to transdiagnostic symptoms and cognitive function. We examined the white matter of 1051 participants (318 healthy controls and 733 patients with major psychiatric disorders: 254 with schizophrenia, 212 with bipolar disorder and 267 with major depressive disorder) who underwent diffusion tensor imaging. We measured the plasma NRG1-β1 levels of 331 participants. We also evaluated clinical symptoms and cognitive function. RESULTS In the patient group, abnormal white matter was negatively associated with NRG1-β1 levels in the genu of the corpus callosum, right uncinate fasciculus, bilateral inferior fronto-occipital fasciculus, right external capsule, fornix, right optic tract, left straight gyrus white matter and left olfactory radiation. These NRG1-associated white matter abnormalities were also associated with depression and anxiety symptoms and executive function in patients with a major psychiatric disorder. Furthermore, across the 3 disorders we observed analogous alterations in white matter, NRG1-β1 levels and clinical manifestations. LIMITATIONS Medication status, the wide age range and our cross-sectional findings were limitations of this study. CONCLUSION This study is the first to provide evidence for an association between NRG1, white matter abnormalities, clinical symptoms and cognition in a transdiagnostic psychiatric cohort. These findings provide further support for an understanding of the molecular mechanisms that underlie the neuroimaging substrates of major psychiatric disorders and their clinical implications.
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Affiliation(s)
- Jia Duan
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Yange Wei
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Fay Y Womer
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Xizhe Zhang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Miao Chang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Yue Zhu
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Zhuang Liu
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Chao Li
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Zhiyang Yin
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Ran Zhang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Jiaze Sun
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Pengshuo Wang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Shuai Wang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Xiaowei Jiang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Shengnan Wei
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Yanbo Zhang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Yanqing Tang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
| | - Fei Wang
- From the Department of Psychiatry, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Duan, Zhu, Yin, R. Zhang, Sun, P. Wang, S. Wang, Tang, F. Wang); the Early Intervention Unit, Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, PR China (Duan, Y. Wei, R. Zhang, F. Wang); the Department of Psychiatry and Behavioral Neuroscience, Saint Louis University, St. Louis, MO (Womer); the School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, PR China (X. Zhang); the Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, Liaoning, PR China (Chang, Li, Jiang, S.Wei); the School of Public Health, China Medical University, Shenyang, Liaoning, PR China (Liu); the Department of Psychiatry, College of Medicine, University of Saskatchewan, SK (Y. Zhang)
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Huang K, Kang Y, Wu Z, Wang Y, Cai S, Huang L. Asymmetrical alterations of grey matter among psychiatric disorders: A systematic analysis by voxel-based activation likelihood estimation. Prog Neuropsychopharmacol Biol Psychiatry 2021; 110:110322. [PMID: 33838150 DOI: 10.1016/j.pnpbp.2021.110322] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 04/02/2021] [Accepted: 04/04/2021] [Indexed: 10/21/2022]
Abstract
Schizophrenia (SZ), bipolar disorder (BD) and major depression disorder (MDD) have been regarded as highly diverged independent entities in current psychiatric diagnosis. However, ample new evidence suggests that they may have common biological traits. Neuroimaging studies showed that psychiatric disorders might associated with altered grey matter (GM) asymmetry compared to controls; however, the degree to which SZ, BD and MDD have common and/or distinct asymmetrical alterations in GM is still ambiguous. In this study, we analysed 169 voxel-based studies (including 3517 SZ patients, 1575 BD patients, 3280 MDD patients and 9733 controls) using activation likelihood estimation (ALE) meta-analysis to systematically review the existence of similar GM atrophy and asymmetrical alteration patterns among these psychiatric disorders, and the functional association between behaviour domains and topological alterations. We found that the right parahippocampal gyrus and left superior frontal gyrus showed commonly altered GM volume across all three illnesses, but did not identify common asymmetrical alteration. The asymmetrical alteration with leftward bias appeared in SZ and bipolar disorder at different locations, but more asymmetrical alteration with rightward bias appeared in MDD. Moreover, these changes have been confirmed to be associate with several symptoms and may have roles in functional networks. Our findings support the existence of common neurobiological damnification in these psychiatric disorders and provides valuable insights for the neural commonalties among different psychiatric disorders based on a large sample size.
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Affiliation(s)
- Kexin Huang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Yafei Kang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Zhongcheng Wu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Yubo Wang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Suping Cai
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Liyu Huang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China.
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Pigoni A, Dwyer D, Squarcina L, Borgwardt S, Crespo-Facorro B, Dazzan P, Smesny S, Spaniel F, Spalletta G, Sanfelici R, Antonucci LA, Reuf A, Oeztuerk OF, Schmidt A, Ciufolini S, Schönborn-Harrisberger F, Langbein K, Gussew A, Reichenbach JR, Zaytseva Y, Piras F, Delvecchio G, Bellani M, Ruggeri M, Lasalvia A, Tordesillas-Gutiérrez D, Ortiz V, Murray RM, Reis-Marques T, Di Forti M, Koutsouleris N, Brambilla P. Classification of first-episode psychosis using cortical thickness: A large multicenter MRI study. Eur Neuropsychopharmacol 2021; 47:34-47. [PMID: 33957410 DOI: 10.1016/j.euroneuro.2021.04.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 03/21/2021] [Accepted: 04/06/2021] [Indexed: 12/19/2022]
Abstract
Machine learning classifications of first-episode psychosis (FEP) using neuroimaging have predominantly analyzed brain volumes. Some studies examined cortical thickness, but most of them have used parcellation approaches with data from single sites, which limits claims of generalizability. To address these limitations, we conducted a large-scale, multi-site analysis of cortical thickness comparing parcellations and vertex-wise approaches. By leveraging the multi-site nature of the study, we further investigated how different demographical and site-dependent variables affected predictions. Finally, we assessed relationships between predictions and clinical variables. 428 subjects (147 females, mean age 27.14) with FEP and 448 (230 females, mean age 27.06) healthy controls were enrolled in 8 centers by the ClassiFEP group. All subjects underwent a structural MRI and were clinically assessed. Cortical thickness parcellation (68 areas) and full cortical maps (20,484 vertices) were extracted. Linear Support Vector Machine was used for classification within a repeated nested cross-validation framework. Vertex-wise thickness maps outperformed parcellation-based methods with a balanced accuracy of 66.2% and an Area Under the Curve of 72%. By stratifying our sample for MRI scanner, we increased generalizability across sites. Temporal brain areas resulted as the most influential in the classification. The predictive decision scores significantly correlated with age at onset, duration of treatment, and positive symptoms. In conclusion, although far from the threshold of clinical relevance, temporal cortical thickness proved to classify between FEP subjects and healthy individuals. The assessment of site-dependent variables permitted an increase in the across-site generalizability, thus attempting to address an important machine learning limitation.
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Affiliation(s)
- A Pigoni
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, via F. Sforza 35, 20122 Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - D Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - L Squarcina
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, via F. Sforza 35, 20122 Milan, Italy
| | - S Borgwardt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland; Department of Psychiatry and Psychotherapy, University of Lübeck, Germany
| | - B Crespo-Facorro
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain; University Hospital Virgen del Rocio, Department of Psychiatry, School of Medicine, University of Sevilla-IBiS, CIBERSAM, Sevilla, Spain
| | - P Dazzan
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - S Smesny
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - F Spaniel
- Department of Applied Neurosciences and Brain Imaging, National Institute of Mental Health, Klecany Czechia
| | - G Spalletta
- Department of Clinical and Behavioural Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - R Sanfelici
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany; Max Planck School of Cognition, Stephanstrasse 1a, Leipzig, Germany
| | - L A Antonucci
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany; Department of Education, Psychology, Communication, University of Bari Aldo Moro, Bari, Italy
| | - A Reuf
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - Oe F Oeztuerk
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany
| | - A Schmidt
- Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - S Ciufolini
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | | | - K Langbein
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - A Gussew
- Department of Radiology, University Hospital Halle (Saale), Germany
| | - J R Reichenbach
- Medical Physics Group, Department of Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany
| | - Y Zaytseva
- Department of Applied Neurosciences and Brain Imaging, National Institute of Mental Health, Klecany Czechia
| | - F Piras
- Department of Clinical and Behavioural Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - G Delvecchio
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - M Bellani
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Italy; UOC of Psychiatry, Azienda Ospedaliera Universitaria Integrata (AOUI) of Verona, Italy
| | - M Ruggeri
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Italy; UOC of Psychiatry, Azienda Ospedaliera Universitaria Integrata (AOUI) of Verona, Italy
| | - A Lasalvia
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Psychiatry, University of Verona, Italy; UOC of Psychiatry, Azienda Ospedaliera Universitaria Integrata (AOUI) of Verona, Italy
| | - D Tordesillas-Gutiérrez
- Department of Radiology, Marqués de Valdecilla University Hospital, Valdecilla Biomedical Research Institute IDIVAL, Spain
| | - V Ortiz
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain
| | - R M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - T Reis-Marques
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - M Di Forti
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - N Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany
| | - P Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, via F. Sforza 35, 20122 Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
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Stein F, Meller T, Brosch K, Schmitt S, Ringwald K, Pfarr JK, Meinert S, Thiel K, Lemke H, Waltemate L, Grotegerd D, Opel N, Jansen A, Nenadić I, Dannlowski U, Krug A, Kircher T. Psychopathological Syndromes Across Affective and Psychotic Disorders Correlate With Gray Matter Volumes. Schizophr Bull 2021; 47:1740-1750. [PMID: 33860786 PMCID: PMC8530386 DOI: 10.1093/schbul/sbab037] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
INTRODUCTION More than a century of research on the neurobiological underpinnings of major psychiatric disorders (major depressive disorder [MDD], bipolar disorder [BD], schizophrenia [SZ], and schizoaffective disorder [SZA]) has been unable to identify diagnostic markers. An alternative approach is to study dimensional psychopathological syndromes that cut across categorical diagnoses. The aim of the current study was to identify gray matter volume (GMV) correlates of transdiagnostic symptom dimensions. METHODS We tested the association of 5 psychopathological factors with GMV using multiple regression models in a sample of N = 1069 patients meeting Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for MDD (n = 818), BD (n = 132), and SZ/SZA (n = 119). T1-weighted brain images were acquired with 3-Tesla magnetic resonance imaging and preprocessed with CAT12. Interactions analyses (diagnosis × psychopathological factor) were performed to test whether local GMV associations were driven by DSM-IV diagnosis. We further tested syndrome specific regions of interest (ROIs). RESULTS Whole brain analysis showed a significant negative association of the positive formal thought disorder factor with GMV in the right middle frontal gyrus, the paranoid-hallucinatory syndrome in the right fusiform, and the left middle frontal gyri. ROI analyses further showed additional negative associations, including the negative syndrome with bilateral frontal opercula, positive formal thought disorder with the left amygdala-hippocampus complex, and the paranoid-hallucinatory syndrome with the left angular gyrus. None of the GMV associations interacted with DSM-IV diagnosis. CONCLUSIONS We found associations between psychopathological syndromes and regional GMV independent of diagnosis. Our findings open a new avenue for neurobiological research across disorders, using syndrome-based approaches rather than categorical diagnoses.
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Affiliation(s)
- Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind Brain and Behavior, University of Marburg, Marburg, Germany,To whom correspondence should be addressed; Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; tel: +49-6421-58-63831, fax: +49-6421-58-68939, e-mail:
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind Brain and Behavior, University of Marburg, Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind Brain and Behavior, University of Marburg, Marburg, Germany
| | - Simon Schmitt
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind Brain and Behavior, University of Marburg, Marburg, Germany
| | - Kai Ringwald
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind Brain and Behavior, University of Marburg, Marburg, Germany
| | - Julia Katharina Pfarr
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind Brain and Behavior, University of Marburg, Marburg, Germany
| | - Susanne Meinert
- Department of Psychiatry University of Münster, Münster, Germany
| | - Katharina Thiel
- Department of Psychiatry University of Münster, Münster, Germany
| | - Hannah Lemke
- Department of Psychiatry University of Münster, Münster, Germany
| | - Lena Waltemate
- Department of Psychiatry University of Münster, Münster, Germany
| | | | - Nils Opel
- Department of Psychiatry University of Münster, Münster, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind Brain and Behavior, University of Marburg, Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind Brain and Behavior, University of Marburg, Marburg, Germany
| | - Udo Dannlowski
- Department of Psychiatry University of Münster, Münster, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind Brain and Behavior, University of Marburg, Marburg, Germany,Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany,Center for Mind Brain and Behavior, University of Marburg, Marburg, Germany
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41
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Vanes LD, Dolan RJ. Transdiagnostic neuroimaging markers of psychiatric risk: A narrative review. NEUROIMAGE-CLINICAL 2021; 30:102634. [PMID: 33780864 PMCID: PMC8022867 DOI: 10.1016/j.nicl.2021.102634] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 03/03/2021] [Accepted: 03/12/2021] [Indexed: 02/07/2023]
Abstract
We review the literature on neural correlates of a general psychopathology factor General psychopathology relates to structural and functional neurodevelopment Disrupted network connectivity maturation may underlie psychiatric vulnerability
Several decades of neuroimaging research in psychiatry have shed light on structural and functional neural abnormalities associated with individual psychiatric disorders. However, there is increasing evidence for substantial overlap in the patterns of neural dysfunction seen across disorders, suggesting that risk for psychiatric illness may be shared across diagnostic boundaries. Gaining insights on the existence of shared neural mechanisms which may transdiagnostically underlie psychopathology is important for psychiatric research in order to tease apart the unique and common aspects of different disorders, but also clinically, so as to help identify individuals early on who may be biologically vulnerable to psychiatric disorder in general. In this narrative review, we first evaluate recent studies investigating the functional and structural neural correlates of a general psychopathology factor, which is thought to reflect the shared variance across common mental health symptoms and therefore index psychiatric vulnerability. We then link insights from this research to existing meta-analytic evidence for shared patterns of neural dysfunction across categorical psychiatric disorders. We conclude by providing an integrative account of vulnerability to mental illness, whereby delayed or disrupted maturation of large-scale networks (particularly default-mode, executive, and sensorimotor networks), and more generally between-network connectivity, results in a compromised ability to integrate and switch between internally and externally focused tasks.
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Affiliation(s)
- Lucy D Vanes
- Centre for the Developing Brain, Department of Perinatal Imaging and Health, King's College London, United Kingdom.
| | - Raymond J Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom
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42
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Hanlon FM, Dodd AB, Ling JM, Shaff NA, Stephenson DD, Bustillo JR, Stromberg SF, Lin DS, Ryman SG, Mayer AR. The clinical relevance of gray matter atrophy and microstructural brain changes across the psychosis continuum. Schizophr Res 2021; 229:12-21. [PMID: 33607607 PMCID: PMC8137524 DOI: 10.1016/j.schres.2021.01.016] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 12/30/2020] [Accepted: 01/23/2021] [Indexed: 12/21/2022]
Abstract
Patients with psychotic spectrum disorders (PSD) exhibit similar patterns of atrophy and microstructural changes that may be associated with common symptomatology (e.g., symptom burden and/or cognitive impairment). Gray matter concentration values (proxy for atrophy), fractional anisotropy (FA), mean diffusivity (MD), intracellular neurite density (Vic) and isotropic diffusion volume (Viso) measures were therefore compared in 150 PSD (schizophrenia, schizoaffective disorder, and bipolar disorder Type I) and 63 healthy controls (HC). Additional analyses evaluated whether regions showing atrophy and/or microstructure abnormalities were better explained by DSM diagnoses, symptom burden or cognitive dysfunction. PSD exhibited increased atrophy within bilateral medial temporal lobes and subcortical structures. Gray matter along the left lateral sulcus showed evidence of increased atrophy and MD. Increased MD was also observed in homotopic fronto-temporal regions, suggesting it may serve as a precursor to atrophic changes. Global cognitive dysfunction, rather than DSM diagnoses or psychotic symptom burden, was the best predictor of increased gray matter MD. Regions of decreased FA (i.e., left frontal gray and white matter) and Vic (i.e., frontal and temporal regions and along central sulcus) were also observed for PSD, but were neither spatially concurrent with atrophic regions nor associated with clinical symptoms. Evidence of expanding microstructural spaces in gray matter demonstrated the greatest spatial overlap with current and potentially future regions of atrophy, and was associated with cognitive deficits. These results suggest that this particular structural abnormality could potentially underlie global cognitive impairment that spans traditional diagnostic categories.
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Affiliation(s)
- Faith M Hanlon
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87106, USA
| | - Andrew B Dodd
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87106, USA
| | - Josef M Ling
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87106, USA
| | - Nicholas A Shaff
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87106, USA
| | - David D Stephenson
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87106, USA
| | - Juan R Bustillo
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM 87131, USA
| | - Shannon F Stromberg
- Psychiatry and Behavioral Health Clinical Program, Presbyterian Healthcare System, Albuquerque, NM 87112, USA
| | - Denise S Lin
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM 87131, USA
| | - Sephira G Ryman
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87106, USA
| | - Andrew R Mayer
- The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87106, USA; Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM 87131, USA; Department of Psychology, University of New Mexico, Albuquerque, NM 87131, USA; Department of Neurology, University of New Mexico School of Medicine, Albuquerque, NM 87131, USA.
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Temporal trajectory of brain tissue property changes induced by electroconvulsive therapy. Neuroimage 2021; 232:117895. [PMID: 33617994 DOI: 10.1016/j.neuroimage.2021.117895] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 12/31/2020] [Accepted: 02/16/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND After more than eight decades of electroconvulsive therapy (ECT) for pharmaco-resistant depression, the mechanisms governing its anti-depressant effects remain poorly understood. Computational anatomy studies using longitudinal T1-weighted magnetic resonance imaging (MRI) data have demonstrated ECT effects on hippocampus volume and cortical thickness, but they lack the interpretational specificity about underlying neurobiological processes. METHODS We sought to fill in the gap of knowledge by acquiring quantitative MRI indicative for brain's myelin, iron and tissue water content at multiple time-points before, during and after ECT treatment. We adapted established tools for longitudinal spatial registration of MRI data to the relaxometry-based multi-parameter maps aiming to preserve the initial total signal amount and introduced a dedicated multivariate analytical framework. RESULTS The whole-brain voxel-based analysis based on a multivariate general linear model showed that there is no brain tissue oedema contributing to the predicted ECT-induced hippocampus volume increase neither in the short, nor in the long-term observations. Improvements in depression symptom severity over time were associated with changes in both volume estimates and brain tissue properties expanding beyond mesial temporal lobe structures to anterior cingulate cortex, precuneus and striatum. CONCLUSION The obtained results stemming from multi-contrast MRI quantitative data provided a fingerprint of ECT-induced brain tissue changes over time that are contrasted against the background of established morphometry findings. The introduced data processing and statistical testing algorithms provided a reliable analytical framework for longitudinal multi-parameter brain maps. The results, particularly the evidence of lack of ECT impact on brain tissue water, should be considered preliminary considering the small sample size of the study.
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Brain morphology does not clearly map to cognition in individuals on the bipolar-schizophrenia-spectrum: a cross-diagnostic study of cognitive subgroups. J Affect Disord 2021; 281:776-785. [PMID: 33246649 DOI: 10.1016/j.jad.2020.11.064] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Accepted: 11/08/2020] [Indexed: 01/11/2023]
Abstract
BACKGROUND Characterisation of brain morphological features common to cognitively similar individuals with bipolar disorder (BD) and schizophrenia spectrum disorders (SSD) may be key to understanding their shared neurobiological deficits. In the current study we examined whether three previously characterised cross-diagnostic cognitive subgroups differed among themselves and in comparison to healthy controls across measures of brain morphology. METHOD T1-weighted structural magnetic resonance imaging scans were obtained for 143 individuals; 65 healthy controls and 78 patients (SSD, n = 40; BD I, n = 38) classified into three cross-diagnostic cognitive subgroups: Globally Impaired (n = 24), Selectively Impaired (n = 32), and Superior/Near-Normal (n = 22). Cognitive subgroups were compared to each other and healthy controls on three separate analyses investigating (1) global, (2) regional, and (3) vertex-wise comparisons of brain volume, thickness, and surface area. RESULTS No significant subgroup differences were evident in global measures of brain morphology. In region of interest analyses, the Selectively Impaired subgroup had greater right accumbens volume than those Superior/Near-Normal subgroup and healthy controls, and the Superior/Near-Normal subgroup had reduced volume of the left entorhinal region compared to all other groups. In vertex-wise comparisons, the Globally Impaired subgroup had greater right precentral volume than the Selectively Impaired subgroup, and thicker cortex in the postcentral region relative to the Superior/Near-Normal subgroup. LIMITATIONS Exploration of medication effects was limited in our data. CONCLUSIONS Although some differences were evident in this sample, generally cross-diagnostic cognitive subgroups of individuals with SSD and BD did not appear to be clearly distinguished by patterns in brain morphology.
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Mind the brain gap: The worldwide distribution of neuroimaging research on adolescent depression. Neuroimage 2021; 231:117865. [PMID: 33592242 PMCID: PMC8328473 DOI: 10.1016/j.neuroimage.2021.117865] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 11/25/2020] [Accepted: 02/09/2021] [Indexed: 12/26/2022] Open
Abstract
Adolescents comprise one fourth of the world’s population, with about 90% of them living in low- and middle-income countries (LMICs). The incidence of depression markedly increases during adolescence, making the disorder a leading cause of disease-related disability in this age group. However, most research on adolescent depression has been performed in high-income countries (HICs). To ascertain the extent to which this disparity operates in neuroimaging research, a systematic review of the literature was performed. A total of 148 studies were identified, with neuroimaging data available for 4,729 adolescents with depression. When stratified by income group, 122 (82%) studies originated from HICs, while 26 (18%) were conducted in LMICs, for a total of 3,705 and 1,024 adolescents with depression respectively. A positive Spearman rank correlation was observed between country per capita income and sample size (rs =0.673, p = 0.023). Our results support the previous reports showing a large disparity between the number of studies and the adolescent population per world region. Future research comparing neuroimaging findings across populations from HICs and LMICs may provide unique insights to enhance our understanding of the neurobiological processes underlying the development of depression.
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Zhuo C, Fang T, Chen C, Chen M, Sun Y, Ma X, Li R, Tian H, Ping J. Brain imaging features in schizophrenia with co-occurring auditory verbal hallucinations and depressive symptoms-Implication for novel therapeutic strategies to alleviate the reciprocal deterioration. Brain Behav 2021; 11:e01991. [PMID: 33305913 PMCID: PMC7882177 DOI: 10.1002/brb3.1991] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 11/20/2020] [Accepted: 11/23/2020] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Auditory verbal hallucinations (AVHs) and depressive symptoms are highly prevalent in schizophrenia, and recent progress has been made in understanding the reciprocal deterioration of both symptoms through structural and functional brain imaging studies. To date, there is limited literature on this topic. In this review, we synthesized the recent literature on the neuroimaging features of schizophrenia patients with concurrent AVHs and depressive symptoms. METHODS A literature search was conducted with the major databases using the keywords, mainly including schizophrenia, AVHs, depression, neuropsychiatric disorders, brain imaging, and magnetic resonance imaging. RESULTS The existing studies have shown that AVHs and depressive symptoms reciprocally deteriorate in patients with schizophrenia, which has challenged the conventional treatment of the disease. Interestingly, repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) therapies have emerged as two efficacious brain stimulation treatments that can normalize the brain regions associated with the symptoms, as shown through functional and structural brain imaging studies. In light of these important findings, there is an urgent need to conduct in-depth neuronal mechanistic studies to identify targets for stimulation therapy. CONCLUSIONS These new findings may elucidate the pathological mechanisms underlying schizophrenia with concurrent AVHs and depressive symptoms. Furthermore, this review has important clinical implications for developing novel therapeutic strategies to alleviate the reciprocal deterioration AVHs and depressive symptoms of schizophrenia patients.
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Affiliation(s)
- Chuanjun Zhuo
- Key Laboratory of Real Time Brain Circuits Tracing of Neurology and Psychiatry (RTBNB_Lab)Tianjin Fourth Center HospitalTianjin Medical Affiliated Tianjin Fourth Central HospitalNankai University Affiliated Tianjin Fourth Center HospitalTianjinChina
- Department of PsychiatryWenzhou Seventh People’s HospitalWenzhouChina
- Psychiatric‐Neuroimaging‐Genetics‐Comorbidity (PNGC) LaboratoryTianjin Mental Health CenterTianjin Anding HospitalNankai University Affiliated Anding HospitalTianjinChina
| | - Tao Fang
- Key Laboratory of Real Time Brain Circuits Tracing of Neurology and Psychiatry (RTBNB_Lab)Tianjin Fourth Center HospitalTianjin Medical Affiliated Tianjin Fourth Central HospitalNankai University Affiliated Tianjin Fourth Center HospitalTianjinChina
| | - Ce Chen
- Department of PsychiatryWenzhou Seventh People’s HospitalWenzhouChina
| | - Min Chen
- Department of PsychiatrySchool of Mental HealthyJining Medical UniversityJiningChina
| | - Yun Sun
- Psychiatric‐Neuroimaging‐Genetics‐Comorbidity (PNGC) LaboratoryTianjin Mental Health CenterTianjin Anding HospitalNankai University Affiliated Anding HospitalTianjinChina
| | - Xiaoyan Ma
- Psychiatric‐Neuroimaging‐Genetics‐Comorbidity (PNGC) LaboratoryTianjin Mental Health CenterTianjin Anding HospitalNankai University Affiliated Anding HospitalTianjinChina
| | - Ranli Li
- Psychiatric‐Neuroimaging‐Genetics‐Comorbidity (PNGC) LaboratoryTianjin Mental Health CenterTianjin Anding HospitalNankai University Affiliated Anding HospitalTianjinChina
| | - Hongjun Tian
- Key Laboratory of Real Time Brain Circuits Tracing of Neurology and Psychiatry (RTBNB_Lab)Tianjin Fourth Center HospitalTianjin Medical Affiliated Tianjin Fourth Central HospitalNankai University Affiliated Tianjin Fourth Center HospitalTianjinChina
| | - Jing Ping
- Department of PsychiatryWenzhou Seventh People’s HospitalWenzhouChina
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Jiang X, Wang X, Jia L, Sun T, Kang J, Zhou Y, Wei S, Wu F, Kong L, Wang F, Tang Y. Structural and functional alterations in untreated patients with major depressive disorder and bipolar disorder experiencing first depressive episode: A magnetic resonance imaging study combined with follow-up. J Affect Disord 2021; 279:324-333. [PMID: 33096331 DOI: 10.1016/j.jad.2020.09.133] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 09/16/2020] [Accepted: 09/28/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) could assist in identifying objective biomarkers and follow-up study could effectively improve subjective diagnostic accuracy. By combining MRI with follow-up, this study aims to determine the shared and distinct alterations between major depressive disorder (MDD) and bipolar disorder (BD). METHODS Untreated patients with MDD experiencing the first episode were subjected to MRI and subsequent follow-up. Fifteen patients with mania or hypomania were regrouped into BD group. Twenty patients were still grouped as MDD after an average of 37.95 months follow-up. Thirty healthy controls (HCs) were recruited to match the patients. Gray matter volume (GMV) and amygdala-seed functional connectivity (FC) in the whole brain were detected and compared among the three groups. RESULTS GMV analysis revealed that the MDD and BD groups presented reduced GMV predominantly in the parietal, occipital, and frontal regions in the bilateral cerebrum compared with the HCs. The BD group had reduced GMV predominantly in the parietal, temporal, insular regions and the Rolandic operculum in the right-side cerebrum compared with MDD and HC groups. FC analysis revealed that the MDD and BD patients displayed increased FC values mainly in the bilateral parietal, and left occipital regions. Only the BD group displayed increased FC values in the temporal, occipital, parietal and limbic regions in the right-side cerebrum relative to HCs. LIMITATIONS The main limitation is the relatively small sample size. CONCLUSIONS Alterations in the cortical regions and cortico-limbic neural system may provide the scientific basis for differential diagnosis in affective disorders.
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Affiliation(s)
- Xiaowei Jiang
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China; Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China; Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Xinrui Wang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Linna Jia
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Ting Sun
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Jiahui Kang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Yifang Zhou
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China; Department of Geriatric Medicine, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Shengnan Wei
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China; Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Feng Wu
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Lingtao Kong
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China
| | - Fei Wang
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China; Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China; Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China.
| | - Yanqing Tang
- Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China; Department of Geriatric Medicine, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning, 110001, PR China.
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Identifying and validating subtypes within major psychiatric disorders based on frontal-posterior functional imbalance via deep learning. Mol Psychiatry 2021; 26:2991-3002. [PMID: 33005028 PMCID: PMC8505253 DOI: 10.1038/s41380-020-00892-3] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 08/27/2020] [Accepted: 09/15/2020] [Indexed: 12/31/2022]
Abstract
Converging evidence increasingly implicates shared etiologic and pathophysiological characteristics among major psychiatric disorders (MPDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Examining the neurobiology of the psychotic-affective spectrum may greatly advance biological determination of psychiatric diagnosis, which is critical for the development of more effective treatments. In this study, ensemble clustering was developed to identify subtypes within a trans-diagnostic sample of MPDs. Whole brain amplitude of low-frequency fluctuations (ALFF) was used to extract the low-dimensional features for clustering in a total of 944 participants: 581 psychiatric patients (193 with SZ, 171 with BD, and 217 with MDD) and 363 healthy controls (HC). We identified two subtypes with differentiating patterns of functional imbalance between frontal and posterior brain regions, as compared to HC: (1) Archetypal MPDs (60% of MPDs) had increased frontal and decreased posterior ALFF, and decreased cortical thickness and white matter integrity in multiple brain regions that were associated with increased polygenic risk scores and enriched risk gene expression in brain tissues; (2) Atypical MPDs (40% of MPDs) had decreased frontal and increased posterior ALFF with no associated alterations in validity measures. Medicated Archetypal MPDs had lower symptom severity than their unmedicated counterparts; whereas medicated and unmedicated Atypical MPDs had no differences in symptom scores. Our findings suggest that frontal versus posterior functional imbalance as measured by ALFF is a novel putative trans-diagnostic biomarker differentiating subtypes of MPDs that could have implications for precision medicine.
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Cortical surface area alterations shaped by genetic load for neuroticism. Mol Psychiatry 2020; 25:3422-3431. [PMID: 30185937 DOI: 10.1038/s41380-018-0236-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 07/22/2018] [Accepted: 07/31/2018] [Indexed: 01/24/2023]
Abstract
Neuroticism has been shown to act as an important risk factor for major depressive disorder (MDD). Genetic and neuroimaging research has independently revealed biological correlates of neurotic personality including cortical alterations in brain regions of high relevance for affective disorders. Here we investigated the influence of a polygenic score for neuroticism (PGS) on cortical brain structure in a joint discovery sample of n = 746 healthy controls (HC) and n = 268 MDD patients. Findings were validated in an independent replication sample (n = 341 HC and n = 263 MDD). Subgroup analyses stratified for case-control status and analyses of associations between neurotic phenotype and cortical measures were carried out. PGS for neuroticism was significantly associated with a decreased cortical surface area of the inferior parietal cortex, the precuneus, the rostral cingulate cortex and the inferior frontal gyrus in the discovery sample. Similar associations between PGS and surface area of the inferior parietal cortex and the precuneus were demonstrated in the replication sample. Subgroup analyses revealed negative associations in the latter regions between PGS and surface area in both HC and MDD subjects. Neurotic phenotype was negatively correlated with surface area in similar cortical regions including the inferior parietal cortex and the precuneus. No significant associations between PGS and cortical thickness were detected. The morphometric overlap of associations between both PGS and neurotic phenotype in similar cortical regions closely related to internally focused cognition points to the potential relevance of genetically shaped cortical alterations in the development of neuroticism.
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Li C, Dong M, Womer FY, Han S, Yin Y, Jiang X, Wei Y, Duan J, Feng R, Zhang L, Zhang X, Wang F, Tang Y, Xu K. Transdiagnostic time-varying dysconnectivity across major psychiatric disorders. Hum Brain Mapp 2020; 42:1182-1196. [PMID: 33210798 PMCID: PMC7856647 DOI: 10.1002/hbm.25285] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 10/23/2020] [Accepted: 11/03/2020] [Indexed: 12/21/2022] Open
Abstract
Dynamic functional connectivity (DFC) analysis can capture time‐varying properties of connectivity. However, studies on large samples using DFC to investigate transdiagnostic dysconnectivity across schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD) are rare. In this study, we used resting‐state functional magnetic resonance imaging and a sliding‐window method to study DFC in a total of 610 individuals (150 with SZ, 100 with BD, 150 with MDD, and 210 healthy controls [HC]) at a single site. Using k‐means clustering, DFCs were clustered into three functional connectivity states: one was a more frequent state with moderate positive and negative connectivity (State 1), and the other two were less frequent states with stronger positive and negative connectivity (State 2 and State 3). Significant 4‐group differences (SZ, BD, MDD, and HC groups; q < .05, false‐discovery rate [FDR]‐corrected) in DFC were nearly only in State 1. Post hoc analyses (q < .05, FDR‐corrected) in State 1 showed that transdiagnostic dysconnectivity patterns among SZ, BD and MDD featured consistently decreased connectivity within most networks (the visual, somatomotor, salience and frontoparietal networks), which was most obvious in both range and extent for SZ. Our findings suggest that there is more common dysconnectivity across SZ, BD and MDD than we previously expected and that such dysconnectivity is state‐dependent, which provides new insights into the pathophysiological mechanism of major psychiatric disorders.
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Affiliation(s)
- Chao Li
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Mengshi Dong
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Fay Y Womer
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Shaoqiang Han
- Department of MRI, The First Affiliated Hospital of ZhengZhou University, ZhengZhou, China
| | - Yi Yin
- Guangdong Second Provincial General Hospital, The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Xiaowei Jiang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Yange Wei
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Jia Duan
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Ruiqi Feng
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Luheng Zhang
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China.,Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Fei Wang
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, USA
| | - Yanqing Tang
- Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China.,Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China
| | - Ke Xu
- Department of Radiology, The First Affiliated Hospital of China Medical University, Shenyang, China.,Brain Function Research Section, The First Affiliated Hospital of China Medical University, Shenyang, China
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