Connectome gradient dysfunction in major depression and its association with gene expression profiles and treatment outcomes.

Brain Connectome Depression Depressive Disorder, Major / drug therapy Humans Magnetic Resonance Imaging / methods Nerve Net Transcriptome / genetics Treatment Outcome

Journal

Molecular psychiatry
ISSN: 1476-5578
Titre abrégé: Mol Psychiatry
Pays: England
ID NLM: 9607835

Informations de publication

Date de publication:
03 2022
Historique:
received: 19 01 2022
accepted: 03 03 2022
revised: 23 02 2022
pubmed: 27 3 2022
medline: 18 5 2022
entrez: 26 3 2022
Statut: ppublish

Résumé

Patients with major depressive disorder (MDD) exhibit concurrent deficits in both sensory and higher-order cognitive processing. Connectome studies have suggested a principal primary-to-transmodal gradient in functional brain networks, supporting the spectrum from sensation to cognition. However, whether this gradient structure is disrupted in patients with MDD and how this disruption associates with gene expression profiles and treatment outcome remain unknown. Using a large cohort of resting-state fMRI data from 2227 participants (1148 MDD patients and 1079 healthy controls) recruited at nine sites, we investigated MDD-related alterations in the principal connectome gradient. We further used Neurosynth, postmortem gene expression, and an 8-week antidepressant treatment (20 MDD patients) data to assess the meta-analytic cognitive functions, transcriptional profiles, and treatment outcomes related to MDD gradient alterations, respectively. Relative to the controls, MDD patients exhibited global topographic alterations in the principal primary-to-transmodal gradient, including reduced explanation ratio, gradient range, and gradient variation (Cohen's d = 0.16-0.21), and focal alterations mainly in the primary and transmodal systems (d = 0.18-0.25). These gradient alterations were significantly correlated with meta-analytic terms involving sensory processing and higher-order cognition. The transcriptional profiles explained 53.9% variance of the altered gradient pattern, with the most correlated genes enriched in transsynaptic signaling and calcium ion binding. The baseline gradient maps of patients significantly predicted symptomatic improvement after treatment. These results highlight the connectome gradient dysfunction in MDD and its linkage with gene expression profiles and clinical management, providing insight into the neurobiological underpinnings and potential biomarkers for treatment evaluation in this disorder.

Identifiants

DOI: 10.1038/s41380-022-01519-5 PMID: 35338312
pubmed: 35338312
doi: 10.1038/s41380-022-01519-5
pii: 10.1038/s41380-022-01519-5
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1384-1393

Informations de copyright

© 2022. The Author(s), under exclusive licence to Springer Nature Limited.

Références

DALYs GBD, Collaborators H. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392:1859–922.
doi: 10.1016/S0140-6736(18)32335-3
Bubl E, Kern E, Ebert D, Bach M, Tebartz van Elst L. Seeing gray when feeling blue? Depression can be measured in the eye of the diseased. Biol Psychiatry. 2010;68:205–8.
pubmed: 20359698 doi: 10.1016/j.biopsych.2010.02.009
Adler G, Gattaz WF. Pain perception threshold in major depression. Biol Psychiatry. 1993;34:687–9.
pubmed: 8292672 doi: 10.1016/0006-3223(93)90041-B
Fitzgerald PJ. Gray colored glasses: is major depression partially a sensory perceptual disorder? J Affect Disord. 2013;151:418–22.
pubmed: 23906865 doi: 10.1016/j.jad.2013.06.045
Millan MJ, Agid Y, Brune M, Bullmore ET, Carter CS, Clayton NS, et al. Cognitive dysfunction in psychiatric disorders: characteristics, causes and the quest for improved therapy. Nat Rev Drug Discov. 2012;11:141–68.
pubmed: 22293568 doi: 10.1038/nrd3628
Dillon DG, Pizzagalli DA. Mechanisms of Memory Disruption in Depression. Trends Neurosci. 2018;41:137–49.
pubmed: 29331265 pmcid: 5835184 doi: 10.1016/j.tins.2017.12.006
Kupferberg A, Bicks L, Hasler G. Social functioning in major depressive disorder. Neurosci Biobehav Rev. 2016;69:313–32.
pubmed: 27395342 doi: 10.1016/j.neubiorev.2016.07.002
Huys QJ, Daw ND, Dayan P. Depression: a decision-theoretic analysis. Annu Rev Neurosci. 2015;38:1–23.
pubmed: 25705929 doi: 10.1146/annurev-neuro-071714-033928
Xia M, Si T, Sun X, Ma Q, Liu B, Wang L, et al. Reproducibility of functional brain alterations in major depressive disorder: Evidence from a multisite resting-state functional MRI study with 1,434 individuals. Neuroimage. 2019;189:700–14.
pubmed: 30716456 doi: 10.1016/j.neuroimage.2019.01.074
Cheng W, Rolls ET, Qiu J, Liu W, Tang Y, Huang CC, et al. Medial reward and lateral non-reward orbitofrontal cortex circuits change in opposite directions in depression. Brain. 2016;139:3296–309.
pubmed: 27742666 doi: 10.1093/brain/aww255
Schmaal L, Hibar DP, Samann PG, Hall GB, Baune BT, Jahanshad N, et al. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group. Mol Psychiatry. 2017;22:900–9.
pubmed: 27137745 doi: 10.1038/mp.2016.60
Singh MK, Kesler SR, Hadi Hosseini SM, Kelley RG, Amatya D, Hamilton JP, et al. Anomalous gray matter structural networks in major depressive disorder. Biol Psychiatry. 2013;74:777–85.
pubmed: 23601854 pmcid: 3805751 doi: 10.1016/j.biopsych.2013.03.005
Wang L, Xia M, Li K, Zeng Y, Su Y, Dai W, et al. The effects of antidepressant treatment on resting-state functional brain networks in patients with major depressive disorder. Hum Brain Mapp. 2015;36:768–78.
pubmed: 25332057 doi: 10.1002/hbm.22663
Perrin JS, Merz S, Bennett DM, Currie J, Steele DJ, Reid IC, et al. Electroconvulsive therapy reduces frontal cortical connectivity in severe depressive disorder. Proc Natl Acad Sci USA. 2012;109:5464–8.
pubmed: 22431642 pmcid: 3325678 doi: 10.1073/pnas.1117206109
Mesulam MM. From sensation to cognition. Brain. 1998;121:1013–52.
pubmed: 9648540 doi: 10.1093/brain/121.6.1013
Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med. 1995;34:537–41.
pubmed: 8524021 doi: 10.1002/mrm.1910340409
Margulies DS, Ghosh SS, Goulas A, Falkiewicz M, Huntenburg JM, Langs G, et al. Situating the default-mode network along a principal gradient of macroscale cortical organization. Proc Natl Acad Sci USA. 2016;113:12574–9.
pubmed: 27791099 pmcid: 5098630 doi: 10.1073/pnas.1608282113
Huntenburg JM, Bazin PL, Margulies DS. Large-Scale Gradients in Human Cortical Organization. Trends Cogn Sci. 2018;22:21–31.
pubmed: 29203085 doi: 10.1016/j.tics.2017.11.002
Huntenburg JM, Bazin PL, Goulas A, Tardif CL, Villringer A, Margulies DS. A Systematic Relationship Between Functional Connectivity and Intracortical Myelin in the Human Cerebral Cortex. Cereb Cortex. 2017;27:981–97.
pubmed: 28184415 pmcid: 5390400 doi: 10.1093/cercor/bhx030
Gong Q, He Y. Depression, neuroimaging and connectomics: a selective overview. Biol Psychiatry. 2015;77:223–35.
pubmed: 25444171 doi: 10.1016/j.biopsych.2014.08.009
Ma Q, Tang Y, Wang F, Liao X, Jiang X, Wei S, et al. Transdiagnostic Dysfunctions in Brain Modules Across Patients with Schizophrenia, Bipolar Disorder, and Major Depressive Disorder: A Connectome-Based Study. Schizophr Bull. 2020;46:699–712.
pubmed: 31755957 doi: 10.1093/schbul/sbz111
Xia M, Womer FY, Chang M, Zhu Y, Zhou Q, Edmiston EK, et al. Shared and Distinct Functional Architectures of Brain Networks Across Psychiatric Disorders. Schizophr Bull. 2019;45:450–63.
pubmed: 29897593 doi: 10.1093/schbul/sby046
Yan CG, Chen X, Li L, Castellanos FX, Bai TJ, Bo QJ, et al. Reduced default mode network functional connectivity in patients with recurrent major depressive disorder. Proc Natl Acad Sci USA. 2019;116:9078–83.
pubmed: 30979801 pmcid: 6500168 doi: 10.1073/pnas.1900390116
Yu M, Linn KA, Shinohara RT, Oathes DJ, Cook PA, Duprat R, et al. Childhood trauma history is linked to abnormal brain connectivity in major depression. Proc Natl Acad Sci USA. 2019;116:8582–90.
pubmed: 30962366 pmcid: 6486762 doi: 10.1073/pnas.1900801116
Kaiser RH, Andrews-Hanna JR, Wager TD, Pizzagalli DA. Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity. JAMA Psychiatry. 2015;72:603–11.
pubmed: 25785575 pmcid: 4456260 doi: 10.1001/jamapsychiatry.2015.0071
Flint J, Kendler KS. The Genetics of Major Depression. Neuron. 2014;81:1214.
pubmed: 28898628 pmcid: 5629020 doi: 10.1016/j.neuron.2014.02.033
Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 2018;50:668–81.
pubmed: 29700475 pmcid: 5934326 doi: 10.1038/s41588-018-0090-3
Hawrylycz MJ, Lein ES, Guillozet-Bongaarts AL, Shen EH, Ng L, Miller JA, et al. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature. 2012;489:391–9.
pubmed: 22996553 pmcid: 4243026 doi: 10.1038/nature11405
Richiardi J, Altmann A, Milazzo AC, Chang C, Chakravarty MM, Banaschewski T, et al. BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks. Science. 2015;348:1241–4.
pubmed: 26068849 pmcid: 4829082 doi: 10.1126/science.1255905
Fornito A, Arnatkeviciute A, Fulcher BD. Bridging the Gap between Connectome and Transcriptome. Trends Cogn Sci. 2019;23:34–50.
pubmed: 30455082 doi: 10.1016/j.tics.2018.10.005
Liu J, Xia M, Wang X, Liao X, He Y. The spatial organization of the chronnectome associates with cortical hierarchy and transcriptional profiles in the human brain. Neuroimage. 2020;222:117296.
pubmed: 32828922 doi: 10.1016/j.neuroimage.2020.117296
Vertes PE, Rittman T, Whitaker KJ, Romero-Garcia R, Vasa F, Kitzbichler MG, et al. Gene transcription profiles associated with inter-modular hubs and connection distance in human functional magnetic resonance imaging networks. Philos Trans R Soc Lond B Biol Sci. 2016;371:20150362.
pubmed: 27574314 pmcid: 5003862 doi: 10.1098/rstb.2015.0362
First M, Spitzer R, Gibbon M, Williams J. Structured Clinical Interview for DSM-IV Axis I Disorders. Washington, DC: American Psychiatric Publishing; 1997.
Williams JB. A structured interview guide for the Hamilton Depression Rating Scale. Arch Gen Psychiatry. 1988;45:742–7.
pubmed: 3395203 doi: 10.1001/archpsyc.1988.01800320058007
Hawrylycz M, Miller JA, Menon V, Feng D, Dolbeare T, Guillozet-Bongaarts AL, et al. Canonical genetic signatures of the adult human brain. Nat Neurosci. 2015;18:1832–44.
pubmed: 26571460 pmcid: 4700510 doi: 10.1038/nn.4171
Glasser MF, Coalson TS, Robinson EC, Hacker CD, Harwell J, Yacoub E, et al. A multi-modal parcellation of human cerebral cortex. Nature. 2016;536:171–8.
pubmed: 27437579 pmcid: 4990127 doi: 10.1038/nature18933
Arnatkeviciute A, Fulcher BD, Fornito A. A practical guide to linking brain-wide gene expression and neuroimaging data. Neuroimage. 2019;189:353–67.
pubmed: 30648605 doi: 10.1016/j.neuroimage.2019.01.011
Hong SJ, Vos de Wael R, Bethlehem RAI, Lariviere S, Paquola C, Valk SL, et al. Atypical functional connectome hierarchy in autism. Nat Commun. 2019;10:1022.
pubmed: 30833582 pmcid: 6399265 doi: 10.1038/s41467-019-08944-1
Lariviere S, Vos de Wael R, Hong SJ, Paquola C, Tavakol S, Lowe AJ, et al. Multiscale Structure-Function Gradients in the Neonatal Connectome. Cereb Cortex. 2020;30:47–58.
pubmed: 31220215 doi: 10.1093/cercor/bhz069
Paquola C, Vos De Wael R, Wagstyl K, Bethlehem RAI, Hong SJ, Seidlitz J, et al. Microstructural and functional gradients are increasingly dissociated in transmodal cortices. PLoS Biol. 2019;17:e3000284.
pubmed: 31107870 pmcid: 6544318 doi: 10.1371/journal.pbio.3000284
Yu M, Linn KA, Cook PA, Phillips ML, McInnis M, Fava M, et al. Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data. Hum Brain Mapp. 2018;39:4213–27.
pubmed: 29962049 pmcid: 6179920 doi: 10.1002/hbm.24241
Eklund A, Nichols TE, Knutsson H. Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates. Proc Natl Acad Sci USA. 2016;113:7900–5.
pubmed: 27357684 pmcid: 4948312 doi: 10.1073/pnas.1602413113
Watts DJ, Strogatz SH. Collective dynamics of ‘small-world’ networks. Nature. 1998;393:440–2.
pubmed: 9623998 doi: 10.1038/30918
Liao X, Vasilakos AV, He Y. Small-world human brain networks: Perspectives and challenges. Neurosci Biobehav Rev. 2017;77:286–300.
pubmed: 28389343 doi: 10.1016/j.neubiorev.2017.03.018
Yarkoni T, Poldrack RA, Nichols TE, Van Essen DC, Wager TD. Large-scale automated synthesis of human functional neuroimaging data. Nat Methods. 2011;8:665–70.
pubmed: 21706013 pmcid: 3146590 doi: 10.1038/nmeth.1635
Burt JB, Helmer M, Shinn M, Anticevic A, Murray JD. Generative modeling of brain maps with spatial autocorrelation. Neuroimage. 2020;220:117038.
pubmed: 32585343 doi: 10.1016/j.neuroimage.2020.117038
Abdi H. Partial least squares regression and projection on latent structure regression (PLS Regression). Wiley Interdiscip Rev: Computational Stat. 2010;2:97–106.
doi: 10.1002/wics.51
Whitaker KJ, Vertes PE, Romero-Garcia R, Vasa F, Moutoussis M, Prabhu G, et al. Adolescence is associated with genomically patterned consolidation of the hubs of the human brain connectome. Proc Natl Acad Sci USA. 2016;113:9105–10.
pubmed: 27457931 pmcid: 4987797 doi: 10.1073/pnas.1601745113
Eden E, Navon R, Steinfeld I, Lipson D, Yakhini Z. GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinforma. 2009;10:48.
doi: 10.1186/1471-2105-10-48
Romero-Garcia R, Warrier V, Bullmore ET, Baron-Cohen S, Bethlehem RAI. Synaptic and transcriptionally downregulated genes are associated with cortical thickness differences in autism. Mol psychiatry. 2019;24:1053–64.
pubmed: 29483624 doi: 10.1038/s41380-018-0023-7
Benazzi F. Classifying mood disorders by age-at-onset instead of polarity. Prog Neuro-Psychopharmacol Biol Psychiatry. 2009;33:86–93.
doi: 10.1016/j.pnpbp.2008.10.007
Smallwood J, Bernhardt BC, Leech R, Bzdok D, Jefferies E, Margulies DS. The default mode network in cognition: a topographical perspective. Nat Rev Neurosci. 2021;22:503–13.
pubmed: 34226715 doi: 10.1038/s41583-021-00474-4
Buckner RL, Krienen FM. The evolution of distributed association networks in the human brain. Trends Cogn Sci. 2013;17:648–65.
pubmed: 24210963 doi: 10.1016/j.tics.2013.09.017
Zhang J, Wang J, Wu Q, Kuang W, Huang X, He Y, et al. Disrupted brain connectivity networks in drug-naive, first-episode major depressive disorder. Biol Psychiatry. 2011;70:334–42.
pubmed: 21791259 doi: 10.1016/j.biopsych.2011.05.018
Borchardt V, Lord AR, Li M, van der Meer J, Heinze HJ, Bogerts B, et al. Preprocessing strategy influences graph-based exploration of altered functional networks in major depression. Hum Brain Mapp. 2016;37:1422–42.
pubmed: 26888761 pmcid: 6867554 doi: 10.1002/hbm.23111
Korgaonkar MS, Goldstein-Piekarski AN, Fornito A, Williams LM. Intrinsic connectomes are a predictive biomarker of remission in major depressive disorder. Mol Psychiatry. 2020;25:1537–49.
pubmed: 31695168 doi: 10.1038/s41380-019-0574-2
Chin Fatt CR, Jha MK, Cooper CM, Fonzo G, South C, Grannemann B, et al. Effect of Intrinsic Patterns of Functional Brain Connectivity in Moderating Antidepressant Treatment Response in Major Depression. Am J Psychiatry. 2020;177:143–54.
pubmed: 31537090 doi: 10.1176/appi.ajp.2019.18070870
Bethlehem RAI, Paquola C, Seidlitz J, Ronan L, Bernhardt B, Consortium CC, et al. Dispersion of functional gradients across the adult lifespan. Neuroimage. 2020;222:117299.
pubmed: 32828920 doi: 10.1016/j.neuroimage.2020.117299
Fossati M, Assendorp N, Gemin O, Colasse S, Dingli F, Arras G, et al. Trans-Synaptic Signaling through the Glutamate Receptor Delta-1 Mediates Inhibitory Synapse Formation in Cortical Pyramidal. Neurons Neuron. 2019;104:1081–94 e1087.
pubmed: 31704028 doi: 10.1016/j.neuron.2019.09.027
de Wit J, Ghosh A. Specification of synaptic connectivity by cell surface interactions. Nat Rev Neurosci. 2016;17:22–35.
pubmed: 26656254
Duman RS, Aghajanian GK. Synaptic dysfunction in depression: potential therapeutic targets. Science. 2012;338:68–72.
pubmed: 23042884 pmcid: 4424898 doi: 10.1126/science.1222939
Duman RS, Voleti B. Signaling pathways underlying the pathophysiology and treatment of depression: novel mechanisms for rapid-acting agents. Trends Neurosci. 2012;35:47–56.
pubmed: 22217452 pmcid: 3278537 doi: 10.1016/j.tins.2011.11.004
Duric V, Banasr M, Licznerski P, Schmidt HD, Stockmeier CA, Simen AA, et al. A negative regulator of MAP kinase causes depressive behavior. Nat Med. 2010;16:1328–32.
pubmed: 20953200 pmcid: 3066515 doi: 10.1038/nm.2219
Krishnan V, Nestler EJ. The molecular neurobiology of depression. Nature. 2008;455:894–902.
pubmed: 18923511 pmcid: 2721780 doi: 10.1038/nature07455
Rajkowska G, O’Dwyer G, Teleki Z, Stockmeier CA, Miguel-Hidalgo JJ. GABAergic neurons immunoreactive for calcium binding proteins are reduced in the prefrontal cortex in major depression. Neuropsychopharmacol: Off Publ Am Coll Neuropsychopharmacol. 2007;32:471–82.
doi: 10.1038/sj.npp.1301234
Schmaal L, Veltman DJ, van Erp TG, Samann PG, Frodl T, Jahanshad N, et al. Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group. Mol Psychiatry. 2016;21:806–12.
pubmed: 26122586 doi: 10.1038/mp.2015.69
Anderson KM, Collins MA, Kong R, Fang K, Li J, He T, et al. Convergent molecular, cellular, and cortical neuroimaging signatures of major depressive disorder. Proc Natl Acad Sci USA. 2020;117:25138–49.
pubmed: 32958675 pmcid: 7547155 doi: 10.1073/pnas.2008004117
Xia M, Wang J, He Y. BrainNet Viewer: a network visualization tool for human brain connectomics. PLoS One. 2013;8:e68910.
pubmed: 23861951 pmcid: 3701683 doi: 10.1371/journal.pone.0068910
Yeo BT, Krienen FM, Sepulcre J, Sabuncu MR, Lashkari D, Hollinshead M, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol. 2011;106:1125–65.
pubmed: 21653723 doi: 10.1152/jn.00338.2011
Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage. 2002;15:273–89.
pubmed: 11771995 doi: 10.1006/nimg.2001.0978

Auteurs

Mingrui Xia (M)

State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
ORCID: 0000-0003-4615-9132

Jin Liu (J)

State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.

Andrea Mechelli (A)

Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK.

Xiaoyi Sun (X)

State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
School of Systems Science, Beijing Normal University, Beijing, China.

Qing Ma (Q)

State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.

Xiaoqin Wang (X)

Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China.
Department of Psychology, Southwest University, Chongqing, China.

Dongtao Wei (D)

Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China.
Department of Psychology, Southwest University, Chongqing, China.

Yuan Chen (Y)

Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Bangshan Liu (B)

Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China.

Chu-Chung Huang (CC)

Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China.

Yanting Zheng (Y)

Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.

Yankun Wu (Y)

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), Peking University, Beijing, China.

Taolin Chen (T)

Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.

Yuqi Cheng (Y)

Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China.

Xiufeng Xu (X)

Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China.

Qiyong Gong (Q)

Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China.

Tianmei Si (T)

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), Peking University, Beijing, China.

Shijun Qiu (S)

Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.

Ching-Po Lin (CP)

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Institute of Neuroscience, National Yang-Ming Chiao-Tung University, Taipei, Taiwan.
ORCID: 0000-0001-6848-8776

Jingliang Cheng (J)

Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Yanqing Tang (Y)

Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.
ORCID: 0000-0003-4212-3212

Fei Wang (F)

Department of Psychiatry, The First Affiliated Hospital of China Medical University, Shenyang, China.
ORCID: 0000-0002-7650-6345

Jiang Qiu (J)

Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China.
Department of Psychology, Southwest University, Chongqing, China.

Peng Xie (P)

Chongqing Key Laboratory of Neurobiology, Chongqing, China.
Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
ORCID: 0000-0002-0081-6048

Lingjiang Li (L)

Department of Psychiatry, and National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Key Laboratory of Psychiatry and Mental Health, Hunan Medical Center for Mental Health, Changsha, Hunan, China.

Yong He (Y)

State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China. yong.he@bnu.edu.cn.
Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China. yong.he@bnu.edu.cn.
IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China. yong.he@bnu.edu.cn.
Chinese Institute for Brain Research, Beijing, China. yong.he@bnu.edu.cn.
ORCID: 0000-0002-7039-2850

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female

Evaluation of Low-Value Services Across Major Medicare Advantage Insurers and Traditional Medicare.

Ciara Duggan, Adam L Beckman, Ishani Ganguli et al.
1.00
Humans United States Aged Cross-Sectional Studies Medicare Part C

Effectiveness of Virtual Yoga for Chronic Low Back Pain: A Randomized Clinical Trial.

Hallie Tankha, Devyn Gaskins, Amanda Shallcross et al.
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH

questionsmedicales.fr › Système nerveux › Système nerveux central › Encéphale › Connectome gradient dysfunction in major...
questionsmedicales.fr › Techniques d'investigation › Neuroimagerie › Neuroimagerie fonctionnelle › Cartographie cérébrale › Connectome › Connectome gradient dysfunction in major...
questionsmedicales.fr › Comportement et mécanismes comportementaux › Émotions › Dépression › Connectome gradient dysfunction in major...
questionsmedicales.fr › Troubles mentaux › Troubles de l'humeur › Trouble dépressif › Trouble dépressif majeur › Connectome gradient dysfunction in major...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Connectome gradient dysfunction in major...
questionsmedicales.fr › Diagnostic › Techniques et procédures diagnostiques › Imagerie diagnostique › Tomographie › Imagerie par résonance magnétique › Connectome gradient dysfunction in major...
questionsmedicales.fr › Système nerveux › Réseau nerveux › Connectome gradient dysfunction in major...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Transcriptome › Connectome gradient dysfunction in major...
questionsmedicales.fr › Qualité, accès, évaluation des soins de santé › Qualité des soins de santé › Mécanismes d'évaluation des soins de santé › Évaluation des résultats et des processus en soins de santé › Évaluation de résultat (soins) › Résultat thérapeutique › Connectome gradient dysfunction in major...