Hostname: page-component-84b7d79bbc-rnpqb Total loading time: 0 Render date: 2024-07-25T16:33:48.898Z Has data issue: false hasContentIssue false

Local dynamic spontaneous brain activity changes in first-episode, treatment-naïve patients with major depressive disorder and their associated gene expression profiles

Published online by Cambridge University Press:  30 October 2020

Kaizhong Xue
Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
Sixiang Liang
Tianjin Anding Hospital, Tianjin 300222, China The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University & the Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100088, China
Bingbing Yang
Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
Dan Zhu
Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
Yingying Xie
Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
Wen Qin
Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
Feng Liu*
Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
Yong Zhang*
Tianjin Anding Hospital, Tianjin 300222, China
Chunshui Yu*
Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
Author for correspondence: Feng Liu, E-mail:; Yong Zhang, E-mail:; Chunshui Yu, E-mail:
Author for correspondence: Feng Liu, E-mail:; Yong Zhang, E-mail:; Chunshui Yu, E-mail:
Author for correspondence: Feng Liu, E-mail:; Yong Zhang, E-mail:; Chunshui Yu, E-mail:



Major depressive disorder (MDD) is a common debilitating disorder characterized by impaired spontaneous brain activity, yet little is known about its alterations in dynamic properties and the molecular mechanisms associated with these changes.


Based on the resting-state functional MRI data of 65 first-episode, treatment-naïve patients with MDD and 66 healthy controls, we compared dynamic regional homogeneity (dReHo) of spontaneous brain activity between the two groups, and we investigated gene expression profiles associated with dReHo alterations in MDD by leveraging transcriptional data from the Allen Human Brain Atlas and weighted gene co-expression network analysis.


Compared with healthy controls, patients with MDD consistently showed reduced dReHo in both fusiform gyri and in the right temporal pole and hippocampus. The expression profiles of 16 gene modules were correlated with dReHo alterations in MDD. These gene modules were enriched for various biological process terms, including immune, synaptic signalling, ion channels, mitochondrial function and protein metabolism, and were preferentially expressed in different cell types.


Patients with MDD have reduced dReHo in brain areas associated with emotional and cognitive regulation, and these changes may be related to complex polygenetic and polypathway mechanisms.

Original Article
Copyright © The Author(s) 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)



These authors contributed equally to this work.


Arnatkevic Iūtė, A., Fulcher, B. D., & Fornito, A. (2019). A practical guide to linking brain-wide gene expression and neuroimaging data. Neuroimage, 189, 353367. doi: 10.1016/j.neuroimage.2019.01.011.CrossRefGoogle Scholar
Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. Neuroimage, 38(1), 95113. doi: 10.1016/j.neuroimage.2007.07.007.CrossRefGoogle ScholarPubMed
Chao-Gan, Y., & Yu-Feng, Z. (2010). DPARSF: A MATLAB toolbox for “pipeline” data analysis of resting-state fMRI. Frontiers in Systems Neuroscience, 4, 13. doi: 10.3389/fnsys.2010.00013.Google ScholarPubMed
Chen, J. D., Liu, F., Xun, G. L., Chen, H. F., Hu, M. R., Guo, X. F., … Zhao, J. P. (2012). Early and late onset, first-episode, treatment-naive depression: Same clinical symptoms, different regional neural activities. Journal of Affective Disorders, 143(1–3), 5663. doi: 10.1016/j.jad.2012.05.025.CrossRefGoogle ScholarPubMed
Chumbley, J., Worsley, K., Flandin, G., & Friston, K. (2010). Topological FDR for neuroimaging. Neuroimage, 49(4), 30573064. doi: 10.1016/j.neuroimage.2009.10.090.CrossRefGoogle ScholarPubMed
Cuijpers, P., Beekman, A. T. F., & Reynolds, C. F., 3rd. (2012). Preventing depression: A global priority. JAMA, 307(10), 10331034. doi: 10.1001/jama.2012.271.CrossRefGoogle ScholarPubMed
Demirtaş, M., Tornador, C., Falcón, C., López-Solà, M., Hernández-Ribas, R., Pujol, J., … Deco, G. (2016). Dynamic functional connectivity reveals altered variability in functional connectivity among patients with major depressive disorder. Human Brain Mapping, 37(8), 29182930. doi: 10.1002/hbm.23215.CrossRefGoogle ScholarPubMed
de Vos, F., Koini, M., Schouten, T. M., Seiler, S., van der Grond, J., Lechner, A., … Rombouts, S. (2018). A comprehensive analysis of resting state fMRI measures to classify individual patients with Alzheimer's disease. Neuroimage, 167, 6272. doi: 10.1016/j.neuroimage.2017.11.025.CrossRefGoogle ScholarPubMed
Dougherty, J. D., Schmidt, E. F., Nakajima, M., & Heintz, N. (2010). Analytical approaches to RNA profiling data for the identification of genes enriched in specific cells. Nucleic Acids Research, 38(13), 42184230. doi: 10.1093/nar/gkq130.CrossRefGoogle ScholarPubMed
Felger, J. C., & Lotrich, F. E. (2013). Inflammatory cytokines in depression: Neurobiological mechanisms and therapeutic implications. Neuroscience, 246, 199229. doi: 10.1016/j.neuroscience.2013.04.060.CrossRefGoogle ScholarPubMed
Fitzgerald, P. B., Laird, A. R., Maller, J., & Daskalakis, Z. J. (2008). A meta-analytic study of changes in brain activation in depression. Human Brain Mapping, 29(6), 683695. doi: 10.1002/hbm.20426.CrossRefGoogle ScholarPubMed
Friston, K. J. (2011). Functional and effective connectivity: A review. Brain Connectivity, 1(1), 1336. doi: 10.1089/brain.2011.0008.CrossRefGoogle ScholarPubMed
Friston, K. J., Williams, S., Howard, R., Frackowiak, R. S., & Turner, R. (1996). Movement-related effects in fMRI time-series. Magnetic Resonance in Medicine, 35(3), 346355. doi: 10.1002/mrm.1910350312.CrossRefGoogle ScholarPubMed
Frith, U., & Frith, C. (2010). The social brain: Allowing humans to boldly go where no other species has been. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 365(1537), 165176. doi: 10.1098/rstb.2009.0160.CrossRefGoogle ScholarPubMed
Geng, J., Yan, R., Shi, J., Chen, Y., Mo, Z., Shao, J., … Lu, Q. (2019). Altered regional homogeneity in patients with somatic depression: A resting-state fMRI study. Journal of Affective Disorders, 246, 498505. doi: 10.1016/j.jad.2018.12.066.CrossRefGoogle ScholarPubMed
Gold, P. W. (2015). The organization of the stress system and its dysregulation in depressive illness. Molecular Psychiatry, 20(1), 3247. doi: 10.1038/mp.2014.163.CrossRefGoogle ScholarPubMed
Gottesman, I. I., & Gould, T. D. (2003). The endophenotype concept in psychiatry: Etymology and strategic intentions. The American Journal of Psychiatry, 160(4), 636645. ScholarPubMed
Guo, W. B., Liu, F., Xue, Z. M., Yu, Y., Ma, C. Q., Tan, C. L., … Zhao, J. P. (2011a). Abnormal neural activities in first-episode, treatment-naïve, short-illness-duration, and treatment-response patients with major depressive disorder: A resting-state fMRI study. Journal of Affective Disorders, 135(1–3), 326331. doi: 10.1016/j.jad.2011.06.048.CrossRefGoogle Scholar
Guo, W. B., Sun, X. L., Liu, L., Xu, Q., Wu, R. R., Liu, Z. N., … Zhao, J. P. (2011b). Disrupted regional homogeneity in treatment-resistant depression: A resting-state fMRI study. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 35(5), 12971302. doi: 10.1016/j.pnpbp.2011.02.006.CrossRefGoogle Scholar
Han, S., Wang, X., He, Z., Sheng, W., Zou, Q., Li, L., … Chen, H. (2019). Decreased static and increased dynamic global signal topography in major depressive disorder. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 94, 109665. doi: 10.1016/j.pnpbp.2019.109665.CrossRefGoogle ScholarPubMed
Hawrylycz, M. J., Lein, E. S., Guillozet-Bongaarts, A. L., Shen, E. H., Ng, L., Miller, J. A., … Jones, A. R. (2012). An anatomically comprehensive atlas of the adult human brain transcriptome. Nature, 489(7416), 391399. doi: 10.1038/nature11405.CrossRefGoogle ScholarPubMed
Hawrylycz, M., Miller, J. A., Menon, V., Feng, D., Dolbeare, T., Guillozet-Bongaarts, A. L., … Lein, E. (2015). Canonical genetic signatures of the adult human brain. Nature Neuroscience, 18(12), 18321844. doi: 10.1038/nn.4171.CrossRefGoogle ScholarPubMed
Hickok, G., & Poeppel, D. (2007). The cortical organization of speech processing. Nature Reviews. Neuroscience, 8(5), 393402. doi: 10.1038/nrn2113.CrossRefGoogle ScholarPubMed
Hodes, G. E., Kana, V., Menard, C., Merad, M., & Russo, S. J. (2015). Neuroimmune mechanisms of depression. Nature Neuroscience, 18(10), 13861393. doi: 10.1038/nn.4113.CrossRefGoogle ScholarPubMed
Howard, D. M., Adams, M. J., Clarke, T.-K., Hafferty, J. D., Gibson, J., Shirali, M., … McIntosh, A. M. (2019). Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nature Neuroscience, 22(3), 343352. doi: 10.1038/s41593-018-0326-7.CrossRefGoogle ScholarPubMed
Howard, D. M., Adams, M. J., Shirali, M., Clarke, T. K., Marioni, R. E., Davies, G., … McIntosh, A. M. (2018). Genome-wide association study of depression phenotypes in UK biobank identifies variants in excitatory synaptic pathways. Nature Communications, 9(1), 1470. doi: 10.1038/s41467-018-03819-3.CrossRefGoogle ScholarPubMed
Hutchison, R. M., & Morton, J. B. (2015). Tracking the brain's functional coupling dynamics over development. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 35(17), 68496859. doi: 10.1523/jneurosci.4638-14.2015.CrossRefGoogle ScholarPubMed
Hutchison, R. M., Womelsdorf, T., Allen, E. A., Bandettini, P. A., Calhoun, V. D., Corbetta, M., … Chang, C. (2013). Dynamic functional connectivity: Promise, issues, and interpretations. Neuroimage, 80, 360378. doi: 10.1016/j.neuroimage.2013.05.079.CrossRefGoogle ScholarPubMed
Iadecola, C. (2017). The neurovascular unit coming of age: A journey through neurovascular coupling in health and disease. Neuron, 96(1), 1742. doi: 10.1016/j.neuron.2017.07.030.CrossRefGoogle ScholarPubMed
Kaiser, R. H., Whitfield-Gabrieli, S., Dillon, D. G., Goer, F., Beltzer, M., Minkel, J., … Pizzagalli, D. A. (2016). Dynamic resting-state functional connectivity in major depression. Neuropsychopharmacology, 41(7), 18221830. doi: 10.1038/npp.2015.352.CrossRefGoogle ScholarPubMed
Kanwisher, N., McDermott, J., & Chun, M. M. (1997). The fusiform face area: A module in human extrastriate cortex specialized for face perception. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 17(11), 43024311. doi: 10.1523/JNEUROSCI.17-11-04302.1997.CrossRefGoogle ScholarPubMed
Kessler, R. C. (1997). The effects of stressful life events on depression. Annual Review of Psychology, 48, 191214. doi: 10.1146/annurev.psych.48.1.191.CrossRefGoogle ScholarPubMed
Khan, A., Bhat, A., Kolts, R., Thase, M. E., & Brown, W. (2010). Why has the antidepressant-placebo difference in antidepressant clinical trials diminished over the past three decades? CNS Neuroscience & Therapeutics, 16(4), 217226. doi: 10.1111/j.1755-5949.2010.00151.x.CrossRefGoogle ScholarPubMed
Krishnan, V., & Nestler, E. J. (2008). The molecular neurobiology of depression. Nature, 455(7215), 894902. doi: 10.1038/nature07455.CrossRefGoogle ScholarPubMed
Lai, C.-H. (2018). The regional homogeneity of cingulate-precuneus regions: The putative biomarker for depression and anxiety. Journal of Affective Disorders, 229, 171176. doi: 10.1016/j.jad.2017.12.086.CrossRefGoogle ScholarPubMed
Leonardi, N., & Van De Ville, D. (2015). On spurious and real fluctuations of dynamic functional connectivity during rest. Neuroimage, 104, 430436. doi: 10.1016/j.neuroimage.2014.09.007.CrossRefGoogle ScholarPubMed
Li, J., Duan, X., Cui, Q., Chen, H., & Liao, W. (2019). More than just statics: Temporal dynamics of intrinsic brain activity predicts the suicidal ideation in depressed patients. Psychological Medicine, 49(5), 852860. doi: 10.1017/s0033291718001502.CrossRefGoogle ScholarPubMed
Li, L., Lu, B., & Yan, C. G. (2020). Stability of dynamic functional architecture differs between brain networks and states. Neuroimage, 216, 116230. doi: 10.1016/j.neuroimage.2019.116230.CrossRefGoogle ScholarPubMed
Liao, W., Zhang, Z., Mantini, D., Xu, Q., Ji, G. J., Zhang, H., … Lu, G. (2014). Dynamical intrinsic functional architecture of the brain during absence seizures. Brain Structure & Function, 219(6), 20012015. doi: 10.1007/s00429-013-0619-2.CrossRefGoogle ScholarPubMed
Liu, F., Guo, W., Liu, L., Long, Z., Ma, C., Xue, Z., … Chen, H. (2013). Abnormal amplitude low-frequency oscillations in medication-naive, first-episode patients with major depressive disorder: A resting-state fMRI study. Journal of Affective Disorders, 146(3), 401406. doi: 10.1016/j.jad.2012.10.001.CrossRefGoogle ScholarPubMed
Liu, F., Tian, H., Li, J., Li, S., & Zhuo, C. (2019). Altered voxel-wise gray matter structural brain networks in schizophrenia: Association with brain genetic expression pattern. Brain Imaging and Behavior, 13(2), 493502. doi: 10.1007/s11682-018-9880-6.CrossRefGoogle ScholarPubMed
Liu, F., Wang, Y., Li, M., Wang, W., Li, R., Zhang, Z., … Chen, H. (2017). Dynamic functional network connectivity in idiopathic generalized epilepsy with generalized tonic-clonic seizure. Human Brain Mapping, 38(2), 957973. doi: 10.1002/hbm.23430.CrossRefGoogle ScholarPubMed
Liu, Z., Xu, C., Xu, Y., Wang, Y., Zhao, B., Lv, Y., … Du, C. (2010). Decreased regional homogeneity in insula and cerebellum: A resting-state fMRI study in patients with major depression and subjects at high risk for major depression. Psychiatry Research, 182(3), 211215. doi: 10.1016/j.pscychresns.2010.03.004.CrossRefGoogle ScholarPubMed
Ma, C., Ding, J., Li, J., Guo, W., Long, Z., Liu, F., … Chen, H. (2012). Resting-state functional connectivity bias of middle temporal gyrus and caudate with altered gray matter volume in major depression. PLoS ONE, 7(9), e45263. doi: 10.1371/journal.pone.0045263.CrossRefGoogle ScholarPubMed
McEwen, B. S. (2008). Understanding the potency of stressful early life experiences on brain and body function. Metabolism: Clinical and Experimental, 57(Suppl 2), S1115. doi: 10.1016/j.metabol.2008.07.006.CrossRefGoogle ScholarPubMed
Mogil, L. S., Andaleon, A., Badalamenti, A., Dickinson, S. P., Guo, X., Rotter, J. I., … Wheeler, H. E. (2018). Genetic architecture of gene expression traits across diverse populations. PLoS Genetics, 14(8), e1007586. doi: 10.1371/journal.pgen.1007586.CrossRefGoogle ScholarPubMed
Morgan, S. E., Seidlitz, J., Whitaker, K. J., Romero-Garcia, R., Clifton, N. E., Scarpazza, C., … Bullmore, E. T. (2019). Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes. Proceedings of the National Academy of Sciences of the United States of America, 116(19), 96049609. doi: 10.1073/pnas.1820754116CrossRefGoogle ScholarPubMed
Munoz-Lopez, M. M., Mohedano-Moriano, A., & Insausti, R. (2010). Anatomical pathways for auditory memory in primates. Frontiers in Neuroanatomy, 4, 129. doi: 10.3389/fnana.2010.00129.CrossRefGoogle ScholarPubMed
Muoio, V., Persson, P. B., & Sendeski, M. M. (2014). The neurovascular unit – concept review. Acta Physiologica (Oxford, England), 210(4), 790798. doi: 10.1111/apha.12250.CrossRefGoogle ScholarPubMed
Olsson, A., & Ochsner, K. N. (2008). The role of social cognition in emotion. Trends in Cognitive Scences, 12(2), 6571. doi: 10.1016/j.tics.2007.11.010.CrossRefGoogle ScholarPubMed
Pittenger, C., & Duman, R. S. (2008). Stress, depression, and neuroplasticity: A convergence of mechanisms. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 33(1), 88109. doi: 10.1038/sj.npp.1301574.CrossRefGoogle Scholar
Qiu, L., Xia, M., Cheng, B., Yuan, L., Kuang, W., Bi, F., … Gong, Q. (2018). Abnormal dynamic functional connectivity of amygdalar subregions in untreated patients with first-episode major depressive disorder. Journal of Psychiatry & Neuroscience: JPN, 43(4), 262272. doi: 10.1503/jpn.170112.CrossRefGoogle ScholarPubMed
Reimand, J., Arak, T., Adler, P., Kolberg, L., Reisberg, S., Peterson, H., & Vilo, J. (2016). g:Profiler – a web server for functional interpretation of gene lists (2016 update). Nucleic Acids Research, 44(W1), W83W89. doi: 10.1093/nar/gkw199.CrossRefGoogle Scholar
Romero-Garcia, R., Warrier, V., Bullmore, E. T., Baron-Cohen, S., & Bethlehem, R. A. I. (2019). Synaptic and transcriptionally downregulated genes are associated with cortical thickness differences in autism. Molecular Psychiatry, 24(7), 10531064. doi: 10.1038/s41380-018-0023-7.CrossRefGoogle ScholarPubMed
Romme, I. A., de Reus, M. A., Ophoff, R. A., Kahn, R. S., & van den Heuvel, M. P. (2017). Connectome disconnectivity and cortical gene expression in patients with schizophrenia. Biological Psychiatry, 81(6), 495502. doi: 10.1016/j.biopsych.2016.07.012.CrossRefGoogle ScholarPubMed
Sakoglu, U., Pearlson, G. D., Kiehl, K. A., Wang, Y. M., Michael, A. M., & Calhoun, V. D. (2010). A method for evaluating dynamic functional network connectivity and task-modulation: Application to schizophrenia. Magma (New York. N.Y.), 23(5–6), 351366. doi: 10.1007/s10334-010-0197-8.Google Scholar
Schmaal, L., Hibar, D. P., Samann, P. G., Hall, G. B., Baune, B. T., Jahanshad, N., … Veltman, D. J. (2017). 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. Molecular Psychiatry, 22(6), 900909. doi: 10.1038/mp.2016.60.CrossRefGoogle ScholarPubMed
Setiawan, E., Wilson, A. A., Mizrahi, R., Rusjan, P. M., Miler, L., Rajkowska, G., … Meyer, J. H. (2015). Role of translocator protein density, a marker of neuroinflammation, in the brain during major depressive episodes. JAMA Psychiatry, 72(3), 268275. doi: 10.1001/jamapsychiatry.2014.2427.CrossRefGoogle ScholarPubMed
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., … Ideker, T. (2003). Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 13(11), 24982504. doi: 10.1101/gr.1239303.CrossRefGoogle ScholarPubMed
Somel, M., Guo, S., Fu, N., Yan, Z., Hu, H. Y., Xu, Y., … Khaitovich, P. (2010). MicroRNA, mRNA, and protein expression link development and aging in human and macaque brain. Genome Research, 20(9), 12071218. doi: 10.1101/gr.106849.110.CrossRefGoogle ScholarPubMed
Sullivan, P. F., de Geus, E. J., Willemsen, G., James, M. R., Smit, J. H., Zandbelt, T., … Penninx, B. W. (2009). Genome-wide association for major depressive disorder: A possible role for the presynaptic protein piccolo. Molecular Psychiatry, 14(4), 359375. doi: 10.1038/mp.2008.125.CrossRefGoogle ScholarPubMed
Sullivan, P. F., Neale, M. C., & Kendler, K. S. (2000). Genetic epidemiology of major depression: Review and meta-analysis. The American Journal of Psychiatry, 157(10), 15521562. doi: 10.1176/appi.ajp.157.10.1552.CrossRefGoogle ScholarPubMed
Sun, H., Luo, L., Yuan, X., Zhang, L., He, Y., Yao, S., … Xiao, J. (2018). Regional homogeneity and functional connectivity patterns in major depressive disorder, cognitive vulnerability to depression and healthy subjects. Journal of Affective Disorders, 235, 229235. doi: 10.1016/j.jad.2018.04.061.CrossRefGoogle ScholarPubMed
Truong, W., Minuzzi, L., Soares, C. N., Frey, B. N., Evans, A. C., MacQueen, G. M., & Hall, G. B. (2013). Changes in cortical thickness across the lifespan in major depressive disorder. Psychiatry Research, 214(3), 204211. doi: 10.1016/j.pscychresns.2013.09.003.CrossRefGoogle ScholarPubMed
Van Dijk, K. R., Sabuncu, M. R., & Buckner, R. L. (2012). The influence of head motion on intrinsic functional connectivity MRI. Neuroimage, 59(1), 431438. doi: 10.1016/j.neuroimage.2011.07.044.CrossRefGoogle ScholarPubMed
Vasic, N., Walter, H., Hose, A., & Wolf, R. C. (2008). Gray matter reduction associated with psychopathology and cognitive dysfunction in unipolar depression: A voxel-based morphometry study. Journal of Affective Disorders, 109(1–2), 107116. doi: 10.1016/j.jad.2007.11.011.CrossRefGoogle ScholarPubMed
Weiner, K. S., & Grill-Spector, K. (2010). Sparsely-distributed organization of face and limb activations in human ventral temporal cortex. Neuroimage, 52(4), 15591573. doi: 10.1016/j.neuroimage.2010.04.262.CrossRefGoogle ScholarPubMed
Willner, P., Scheel-Kruger, J., & Belzung, C. (2013). The neurobiology of depression and antidepressant action. Neuroscience and Biobehavioral Reviews, 37(10 Pt 1), 23312371. doi: 10.1016/j.neubiorev.2012.12.007CrossRefGoogle ScholarPubMed
World Health Organization (2008). The Global Burden of Disease: 2004 Update. 2004 Update. Geneva, Switzerland: World Health Organization, p. 146.Google Scholar
Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., & Abdellaoui, A., … Major Depressive Disorder Working Group of the Psychiatric Genomics, C. (2018). Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nature Genetics, 50(5), 668681. doi: 10.1038/s41588-018-0090-3.CrossRefGoogle ScholarPubMed
Xia, M., Si, T., Sun, X., Ma, Q., Liu, B., Wang, L., … Group, D. I.-M. D. D. W. (2019). Reproducibility of functional brain alterations in major depressive disorder: Evidence from a multisite resting-state functional MRI study with 1434 individuals. Neuroimage, 189, 700714. doi: 10.1016/j.neuroimage.2019.01.074.CrossRefGoogle ScholarPubMed
Xu, J., Li, Q., Qin, W., Jun Li, M., Zhuo, C., Liu, H., … Yu, C. (2018). Neurobiological substrates underlying the effect of genomic risk for depression on the conversion of amnestic mild cognitive impairment. Brain: A Journal of Neurology, 141(12), 34573471. doi: 10.1093/brain/awy277.CrossRefGoogle ScholarPubMed
Yan, C. G., Wang, X. D., Zuo, X. N., & Zang, Y. F. (2016). DPABI: Data processing & analysis for (resting-state) brain imaging. Neuroinformatics, 14(3), 339351. doi: 10.1007/s12021-016-9299-4.CrossRefGoogle ScholarPubMed
Zang, Y., Jiang, T., Lu, Y., He, Y., & Tian, L. (2004). Regional homogeneity approach to fMRI data analysis. Neuroimage, 22(1), 394400. doi: 10.1016/j.neuroimage.2003.12.030.CrossRefGoogle ScholarPubMed
Zhang, B., & Horvath, S. (2005). A general framework for weighted gene co-expression network analysis. Statistical Applications in Genetics and Molecular Biology, 4, Article17. doi: 10.2202/1544-6115.1128CrossRefGoogle ScholarPubMed
Zhang, Y., Sloan, S. A., Clarke, L. E., Caneda, C., Plaza, C. A., Blumenthal, P. D., … Barres, B. A. (2016). Purification and characterization of progenitor and mature human astrocytes reveals transcriptional and functional differences with mouse. Neuron, 89(1), 3753. doi: 10.1016/j.neuron.2015.11.013.CrossRefGoogle ScholarPubMed
Supplementary material: File

Xue et al. Supplementary Materials

Xue et al. Supplementary Materials

Download Xue et al. Supplementary Materials(File)
File 41.6 MB