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Long H, Chen Z, Xu X, Zhou Q, Fang Z, Lv M, Yang XH, Xiao J, Sun H, Fan M. Elucidating genetic and molecular basis of altered higher-order brain structure-function coupling in major depressive disorder. Neuroimage 2024; 297:120722. [PMID: 38971483 DOI: 10.1016/j.neuroimage.2024.120722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 06/24/2024] [Accepted: 07/03/2024] [Indexed: 07/08/2024] Open
Abstract
Previous studies have shown that major depressive disorder (MDD) patients exhibit structural and functional impairments, but few studies have investigated changes in higher-order coupling between structure and function. Here, we systematically investigated the effect of MDD on higher-order coupling between structural connectivity (SC) and functional connectivity (FC). Each brain region was mapped into embedding vector by the node2vec algorithm. We used support vector machine (SVM) with the brain region embedding vector to distinguish MDD patients from health controls (HCs) and identify the most discriminative brain regions. Our study revealed that MDD patients had decreased higher-order coupling in connections between the most discriminative brain regions and local connections in rich-club organization and increased higher-order coupling in connections between the ventral attentional network and limbic network compared with HCs. Interestingly, transcriptome-neuroimaging association analysis demonstrated the correlations between regional rSC-FC coupling variations between MDD patients and HCs and α/β-hydrolase domain-containing 6 (ABHD6), β 1,3-N-acetylglucosaminyltransferase-9(β3GNT9), transmembrane protein 45B (TMEM45B), the correlation between regional dSC-FC coupling variations and retinoic acid early transcript 1E antisense RNA 1(RAET1E-AS1), and the correlations between regional iSC-FC coupling variations and ABHD6, β3GNT9, katanin-like 2 protein (KATNAL2). In addition, correlation analysis with neurotransmitter receptor/transporter maps found that the rSC-FC and iSC-FC coupling variations were both correlated with neuroendocrine transporter (NET) expression, and the dSC-FC coupling variations were correlated with metabotropic glutamate receptor 5 (mGluR5). Further mediation analysis explored the relationship between genes, neurotransmitter receptor/transporter and MDD related higher-order coupling variations. These findings indicate that specific genetic and molecular factors underpin the observed disparities in higher-order SC-FC coupling between MDD patients and HCs. Our study confirmed that higher-order coupling between SC and FC plays an important role in diagnosing MDD. The identification of new biological evidence for MDD etiology holds promise for the development of innovative antidepressant therapies.
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Affiliation(s)
- Haixia Long
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
| | - Zihao Chen
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
| | - Xinli Xu
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
| | - Qianwei Zhou
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
| | - Zhaolin Fang
- Network Information Center, Zhejiang University of Technology, Hangzhou 310023, China
| | - Mingqi Lv
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
| | - Xu-Hua Yang
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
| | - Jie Xiao
- College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
| | - Hui Sun
- College of Electrical Engineering, Sichuan University, Chengdu 610065, China.
| | - Ming Fan
- Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou 310018, China.
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Mai N, Wu Y, Zhong X, Chen B, Zhang M, Peng Q, Ning Y. Increasing variance of rich-club nodes distribution in early onset depression according to dynamic network. Brain Imaging Behav 2024; 18:662-674. [PMID: 38349505 DOI: 10.1007/s11682-023-00848-5] [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] [Accepted: 12/23/2023] [Indexed: 07/04/2024]
Abstract
Early onset depression (EOD) and late onset depression (LOD) are thought to have different pathogeneses, but lack of pathological evidence. In the current study we describe the dynamic rich-club properties of patients with EOD and LOD to address this question indirectly. We recruited 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. Memory, executive function and processing speed were measured, and resting-stage functional MRI was performed with all participants. We constructed a dynamic functional connectivity network and carried out rich-club and modularity analyses. Normalized mutual information (NMI) was applied to describe the variance in rich-club nodes distribution and partitioning. The NMI coefficient of rich club nodes distribution among the three groups was the lowest in the EOD patients (F = 4.298; P = 0.0151, FDR = 0.0231), which was positively correlated with rich-club connectivity (R = 0.886, P < 0.001) and negatively correlated with memory (R = -0.347, P = 0.038) in the EOD group. In the LOD patients, non-rich-club connectivity was positively correlated with memory (R = 0.353, P = 0.030 and R = 0.420, P = 0.009). Furthermore, local connectivity was positively correlated with processing speed in the LOD patients (R = 0.374, P = 0.021). The modular partition was different between the EOD patients and the HCs (P = 0.0013 < 0.05/3). The temporal instability of rich-club nodes was found in the EOD patients, but not the LOD patients, supporting the hypothesis that EOD and LOD result from different pathogenesis, and showing that the instability of the rich-club nodes across time might disrupt rich-club connectivity.
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Affiliation(s)
- Naikeng Mai
- Department of Neurology, the Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangdong, Guangzhou, China
| | - Yujie Wu
- School of Education Science, Guangdong Polytechnic Normal University, Guangdong, Guangzhou, China
| | - Xiaomei Zhong
- Geriatric Neuroscience center, the Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangdong, Guangzhou, China
| | - Ben Chen
- Geriatric Neuroscience center, the Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangdong, Guangzhou, China
| | - Min Zhang
- Geriatric Neuroscience center, the Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangdong, Guangzhou, China
| | - Qi Peng
- Geriatric Neuroscience center, the Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangdong, Guangzhou, China
| | - Yuping Ning
- Geriatric Neuroscience center, the Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangdong, Guangzhou, China.
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Liao QM, Zhang ZJ, Yang X, Wei JX, Wang M, Dou YK, Du Y, Ma XH. Changes of structural functional connectivity coupling and its correlations with cognitive function in patients with major depressive disorder. J Affect Disord 2024; 351:259-267. [PMID: 38266932 DOI: 10.1016/j.jad.2024.01.173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 01/05/2024] [Accepted: 01/17/2024] [Indexed: 01/26/2024]
Abstract
BACKGROUND Previous neuroimaging studies have reported structural and functional brain abnormalities in major depressive disorder (MDD). This study aimed to explore whether the coherence of structural-functional networks was affected by disease and investigate its correlation with clinical manifestations. METHODS The severity of symptoms and cognitive function of 121 MDD patients and 139 healthy controls (HC) were assessed, and imaging data, including diffusion tensor imaging, T1 structural magnetic resonance imaging (MRI) and resting-state functional MRI, were collected. Spearman correlation coefficients of Kullback-Leibler similarity (KLS), fiber number (FN), fractional anisotropy (FA) and functional connectivity (FC) were calculated as coupling coefficients. Double-weight median correlation analysis was conducted to investigate the correlations between differences in brain networks and clinical assessments. RESULTS The percentage of total correct response of delayed matching to sample and the percentage of delayed correct response of pattern recognition memory was lower in MDD. Compared with the HC, KLS-FC coupling between the parietal lobe and subcortical area, FA-FC coupling between the temporal and parietal lobe, and FN-FC coupling in the frontal lobe was lower in MDD. Several correlations between structural-functional connectivity and clinical manifestations were identified. LIMITATIONS First, our study lacks longitudinal follow-up data. Second, the sample size was relatively small. Moreover, we only used the Anatomical Automatic Labeling template to construct the brain network. Finally, the validation of the causal relationship of neuroimaging-behavior factors was still insufficient. CONCLUSIONS The alternation in structural-functional coupling were related to clinical characterization and might be involved in the neuropathology of depression.
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Affiliation(s)
- Qi-Meng Liao
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Zi-Jian Zhang
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xiao Yang
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Jin-Xue Wei
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Min Wang
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Yi-Kai Dou
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Yue Du
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xiao-Hong Ma
- Mental Health Center and Psychiatric Laboratory, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China.
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Dai YR, Wu YK, Chen X, Zeng YW, Li K, Li JT, Su YA, Zhu LL, Yan CG, Si TM. Eight-week antidepressant treatment changes intrinsic functional brain topology in first-episode drug-naïve patients with major depressive disorder. J Affect Disord 2023; 329:225-234. [PMID: 36858265 DOI: 10.1016/j.jad.2023.02.126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/20/2023] [Accepted: 02/22/2023] [Indexed: 03/03/2023]
Abstract
BACKGROUND A recent study revealed disrupted topological organization of whole-brain networks in patients with major depressive disorder (MDD); however, these results were mostly driven by recurrent MDD patients, rather than first-episode drug-naïve (FEDN) patients. Furthermore, few longitudinal studies have explored the effects of antidepressant therapy on the topological organization of whole-brain networks. METHODS We collected clinical and neuroimaging data from 159 FEDN MDD patients and 152 normal controls (NCs). A total of 115 MDD patients completed an eight-week antidepressant treatment procedure. Topological features of brain networks were calculated using graph theory-based methods and compared between FEDN MDD patients and NCs, as well as before and after treatment. RESULTS Decreased global efficiency, local efficiency, small-worldness, and modularity were found in pretreatment FEDN MDD patients compared with NCs. Nodal degrees, betweenness, and efficiency decreased in several networks compared with NCs. After antidepressant treatment, the global efficiency increased, while the local efficiency, the clustering coefficient of the network, the path length, and the normalized characteristic path length decreased. Moreover, the reduction rate of the normalized characteristic path length was positively correlated with the reduction rate of retardation factor scores. LIMITATIONS The interaction effects of groups and time on the topological features were not explored because of absence of the eighth-week data of NC group. CONCLUSIONS The topological architecture of functional brain networks is disrupted in FEDN MDD patients. After antidepressant therapy, the global efficiency shifted toward recovery, but the local efficiency deteriorated, suggesting a correlation between recovery of retardation symptoms and global efficiency.
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Affiliation(s)
- You-Ran Dai
- 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), Beijing 100191, China
| | - Yan-Kun Wu
- 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), Beijing 100191, China
| | - Xiao Chen
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
| | - Ya-Wei Zeng
- PLA Strategic support Force Characteristic Medical Center, Beijing 100101, China
| | - Ke Li
- PLA Strategic support Force Characteristic Medical Center, Beijing 100101, China
| | - Ji-Tao 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), Beijing 100191, China
| | - Yun-Ai Su
- 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), Beijing 100191, China
| | - Lin-Lin Zhu
- 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), Beijing 100191, China.
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
| | - Tian-Mei Si
- 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), Beijing 100191, China.
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Hua JPY, Cummings J, Roach BJ, Fryer SL, Loewy RL, Stuart BK, Ford JM, Vinogradov S, Mathalon DH. Rich-club connectivity and structural connectome organization in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia. Schizophr Res 2023; 255:110-121. [PMID: 36989668 PMCID: PMC10705845 DOI: 10.1016/j.schres.2023.03.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 11/07/2022] [Accepted: 03/08/2023] [Indexed: 03/31/2023]
Abstract
Brain dysconnectivity has been posited as a biological marker of schizophrenia. Emerging schizophrenia connectome research has focused on rich-club organization, a tendency for brain hubs to be highly-interconnected but disproportionately vulnerable to dysconnectivity. However, less is known about rich-club organization in individuals at clinical high-risk for psychosis (CHR-P) and how it compares with abnormalities early in schizophrenia (ESZ). Combining diffusion tensor imaging (DTI) and magnetic resonance imaging (MRI), we examined rich-club and global network organization in CHR-P (n = 41) and ESZ (n = 70) relative to healthy controls (HC; n = 74) after accounting for normal aging. To characterize rich-club regions, we examined rich-club MRI morphometry (thickness, surface area). We also examined connectome metric associations with symptom severity, antipsychotic dosage, and in CHR-P specifically, transition to a full-blown psychotic disorder. ESZ had fewer connections among rich-club regions (ps < .024) relative to HC and CHR-P, with this reduction specific to the rich-club even after accounting for other connections in ESZ relative to HC (ps < .048). There was also cortical thinning of rich-club regions in ESZ (ps < .013). In contrast, there was no strong evidence of global network organization differences among the three groups. Although connectome abnormalities were not present in CHR-P overall, CHR-P converters to psychosis (n = 9) had fewer connections among rich-club regions (ps < .037) and greater modularity (ps < .037) compared to CHR-P non-converters (n = 19). Lastly, symptom severity and antipsychotic dosage were not significantly associated with connectome metrics (ps < .012). Findings suggest that rich-club and connectome organization abnormalities are present early in schizophrenia and in CHR-P individuals who subsequently transition to psychosis.
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Affiliation(s)
- Jessica P Y Hua
- Sierra Pacific Mental Illness Research Education and Clinical Centers, San Francisco VA Medical Center and the University of California, San Francisco, CA, USA; San Francisco VA Medical Center, San Francisco, CA 94121, USA; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA 94143, USA; Department of Psychological Sciences, University of Missouri, Columbia, MO 65211, USA
| | - Jennifer Cummings
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143, USA; Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94143, USA
| | - Brian J Roach
- San Francisco VA Medical Center, San Francisco, CA 94121, USA
| | - Susanna L Fryer
- San Francisco VA Medical Center, San Francisco, CA 94121, USA
| | - Rachel L Loewy
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA 94143, USA
| | - Barbara K Stuart
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA 94143, USA
| | - Judith M Ford
- San Francisco VA Medical Center, San Francisco, CA 94121, USA; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA 94143, USA
| | - Sophia Vinogradov
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN 55455, USA
| | - Daniel H Mathalon
- San Francisco VA Medical Center, San Francisco, CA 94121, USA; Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA 94143, USA.
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