Skip to main content

Advertisement

SpringerLink
Log in

Molecular, Functional, and Structural Imaging of Major Depressive Disorder

  • Review
  • Published:
Neuroscience Bulletin Aims and scope Submit manuscript

Abstract

Major depressive disorder (MDD) is a significant cause of morbidity and mortality worldwide, correlating with genetic susceptibility and environmental risk factors. Molecular, functional, and structural imaging approaches have been increasingly used to detect neurobiological changes, analyze neurochemical correlates, and parse pathophysiological mechanisms underlying MDD. We reviewed recent neuroimaging publications on MDD in terms of molecular, functional, and structural alterations as detected mainly by magnetic resonance imaging (MRI) and positron emission tomography. Altered structure and function of brain regions involved in the cognitive control of affective state have been demonstrated. An abnormal default mode network, as revealed by resting-state functional MRI, is likely associated with aberrant metabolic and serotonergic function revealed by radionuclide imaging. Further multi-modal investigations are essential to clarify the characteristics of the cortical network and serotonergic system associated with behavioral and genetic variations in MDD.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

(reprint permission was obtained from both the publisher and the corresponding author)

Fig. 3

(reprint permission was obtained from both the publisher and the corresponding author)

Fig. 4

(reprint permission was obtained from both the publisher and the corresponding author)

Fig. 5

(reprint permission was obtained from both the publisher and the corresponding author)

Fig. 6

(reprint permission was obtained from both the publisher and the corresponding author)

Similar content being viewed by others

References

  1. Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-of-onset distributions of dsm-iv disorders in the national comorbidity survey replication. Archives of General Psychiatry 2005, 62: 593–602.

    Article  PubMed  Google Scholar 

  2. Greenberg PE, Fournier AA, Sisitsky T, Pike CT, Kessler RC. The economic burden of adults with major depressive disorder in the United States (2005 and 2010). J Clin Psychiatry 2015, 76: 155–162.

    Article  PubMed  Google Scholar 

  3. Global Burden of Disease Study C. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015, 386: 743–800.

    Article  Google Scholar 

  4. Thompson SM, Kallarackal AJ, Kvarta MD, Van Dyke AM, LeGates TA, Cai X. An excitatory synapse hypothesis of depression. Trends Neurosci 2015, 38: 279–294.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Gartlehner G, Hansen RA, Morgan LC, Thaler K, Lux L, Van Noord M, et al. Comparative benefits and harms of second-generation antidepressants for treating major depressive disorder: an updated meta-analysis. Ann Intern Med 2011, 155: 772–785.

    Article  PubMed  Google Scholar 

  6. Gaynes BN, Warden D, Trivedi MH, Wisniewski SR, Fava M, Rush AJ. What did STAR*D teach us? Results from a large-scale, practical, clinical trial for patients with depression. Psychiatr Serv 2009, 60: 1439–1445.

    Article  PubMed  Google Scholar 

  7. Fowler AM. A molecular approach to breast imaging. J Nucl Med 2014, 55: 177–180.

    Article  PubMed  Google Scholar 

  8. Weissleder R, Mahmood U. Molecular imaging. Radiology 2001, 219: 316–333.

    Article  CAS  PubMed  Google Scholar 

  9. James ML, Gambhir SS. A molecular imaging primer: modalities, imaging agents, and applications. Physiol Rev 2012, 92: 897–965.

    Article  CAS  PubMed  Google Scholar 

  10. Blamire AM. The technology of MRI–the next 10 years? Br J Radiol 2008, 81: 601–617.

    Article  CAS  PubMed  Google Scholar 

  11. Logothetis NK. The neural basis of the blood-oxygen-level-dependent functional magnetic resonance imaging signal. Philos Trans R Soc Lond B Biol Sci 2002, 357: 1003–1037.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Tu PC, Chen LF, Hsieh JC, Bai YM, Li CT, Su TP. Regional cortical thinning in patients with major depressive disorder: a surface-based morphometry study. Psychiatry Res 2012, 202: 206–213.

    Article  PubMed  Google Scholar 

  13. Han KM, Choi S, Jung J, Na KS, Yoon HK, Lee MS, et al. Cortical thickness, cortical and subcortical volume, and white matter integrity in patients with their first episode of major depression. J Affect Disord 2014, 155: 42–48.

    Article  PubMed  Google Scholar 

  14. Reynolds S, Carrey N, Jaworska N, Langevin LM, Yang XR, Macmaster FP. Cortical thickness in youth with major depressive disorder. BMC Psychiatry 2014, 14: 83.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Grieve SM, Korgaonkar MS, Koslow SH, Gordon E, Williams LM. Widespread reductions in gray matter volume in depression. Neuroimage Clin 2013, 3: 332–339.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Nakano M, Matsuo K, Nakashima M, Matsubara T, Harada K, Egashira K, et al. Gray matter volume and rapid decision-making in major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2014, 48: 51–56.

    Article  PubMed  Google Scholar 

  17. Qi H, Ning Y, Li J, Guo S, Chi M, Gao M, et al. Gray matter volume abnormalities in depressive patients with and without anxiety disorders. Medicine (Baltimore) 2014, 93: e345.

    Article  Google Scholar 

  18. Ashburner J, Friston KJ. Voxel-based morphometry–the methods. Neuroimage 2000, 11: 805–821.

    Article  CAS  PubMed  Google Scholar 

  19. Machino A, Kunisato Y, Matsumoto T, Yoshimura S, Ueda K, Yamawaki Y, et al. Possible involvement of rumination in gray matter abnormalities in persistent symptoms of major depression: an exploratory magnetic resonance imaging voxel-based morphometry study. J Affect Disord 2014, 168: 229–235.

    Article  PubMed  Google Scholar 

  20. Depping MS, Wolf ND, Vasic N, Sambataro F, Thomann PA, Christian Wolf R. Specificity of abnormal brain volume in major depressive disorder: a comparison with borderline personality disorder. J Affect Disord 2015, 174: 650–657.

    Article  PubMed  Google Scholar 

  21. Bora E, Fornito A, Pantelis C, Yucel M. Gray matter abnormalities in Major Depressive Disorder: a meta-analysis of voxel based morphometry studies. J Affect Disord 2012, 138: 9–18.

    Article  PubMed  Google Scholar 

  22. Lai CH. Gray matter volume in major depressive disorder: a meta-analysis of voxel-based morphometry studies. Psychiatry Res 2013, 211: 37–46.

    Article  PubMed  Google Scholar 

  23. Du MY, Wu QZ, Yue Q, Li J, Liao Y, Kuang WH, et al. Voxelwise meta-analysis of gray matter reduction in major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2012, 36: 11–16.

    Article  PubMed  Google Scholar 

  24. Botvinick MM. Conflict monitoring and decision making: reconciling two perspectives on anterior cingulate function. Cogn Affect Behav Neurosci 2007, 7: 356–366.

    Article  PubMed  Google Scholar 

  25. Decety J, Moriguchi Y. The empathic brain and its dysfunction in psychiatric populations: implications for intervention across different clinical conditions. Biopsychosoc Med 2007, 1: 22.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Smoski MJ, Felder J, Bizzell J, Green SR, Ernst M, Lynch TR, et al. fMRI of alterations in reward selection, anticipation, and feedback in major depressive disorder. J Affect Disord 2009, 118: 69–78.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Carter CS, Braver TS, Barch DM, Botvinick MM, Noll D, Cohen JD. Anterior cingulate cortex, error detection, and the online monitoring of performance. Science 1998, 280: 747–749.

    Article  CAS  PubMed  Google Scholar 

  28. Lai CH, Wu YT. Frontal-insula gray matter deficits in first-episode medication-naive patients with major depressive disorder. J Affect Disord 2014, 160: 74–79.

    Article  PubMed  Google Scholar 

  29. Lai CH, Wu YT. The gray matter alterations in major depressive disorder and panic disorder: Putative differences in the pathogenesis. J Affect Disord 2015, 186: 1–6.

    Article  PubMed  Google Scholar 

  30. Zhao YJ, Du MY, Huang XQ, Lui S, Chen ZQ, Liu J, et al. Brain grey matter abnormalities in medication-free patients with major depressive disorder: a meta-analysis. Psychol Med 2014, 44: 2927–2937.

    Article  PubMed  Google Scholar 

  31. Qiu L, Lui S, Kuang W, Huang X, Li J, Li J, et al. Regional increases of cortical thickness in untreated, first-episode major depressive disorder. Transl Psychiatry 2014, 4: e378.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Phillips JL, Batten LA, Tremblay P, Aldosary F, Blier P. A prospective, longitudinal study of the effect of remission on cortical thickness and hippocampal volume in patients with treatment-resistant depression. Int J Neuropsychopharmacol 2015, 18: pyv037.

  33. Jarnum H, Eskildsen SF, Steffensen EG, Lundbye-Christensen S, Simonsen CW, Thomsen IS, et al. Longitudinal MRI study of cortical thickness, perfusion, and metabolite levels in major depressive disorder. Acta Psychiatr Scand 2011, 124: 435–446.

    Article  PubMed  Google Scholar 

  34. Leistedt SJ, Linkowski P. Brain, networks, depression, and more. Eur Neuropsychopharmacol 2013, 23: 55–62.

    Article  CAS  PubMed  Google Scholar 

  35. Malykhin NV, Coupland NJ. Hippocampal neuroplasticity in major depressive disorder. Neuroscience 2015, 309: 200–213.

    Article  CAS  PubMed  Google Scholar 

  36. MacQueen GM, Campbell S, McEwen BS, Macdonald K, Amano S, Joffe RT, et al. Course of illness, hippocampal function, and hippocampal volume in major depression. Proc Natl Acad Sci U S A 2003, 100: 1387–1392.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Warner-Schmidt JL, Duman RS. Hippocampal neurogenesis: opposing effects of stress and antidepressant treatment. Hippocampus 2006, 16: 239–249.

    Article  CAS  PubMed  Google Scholar 

  38. Price JL, Drevets WC. Neurocircuitry of mood disorders. Neuropsychopharmacology 2010, 35: 192–216.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Jung J, Kang J, Won E, Nam K, Lee MS, Tae WS, et al. Impact of lingual gyrus volume on antidepressant response and neurocognitive functions in Major Depressive Disorder: a voxel-based morphometry study. J Affect Disord 2014, 169: 179–187.

    Article  PubMed  Google Scholar 

  40. Liu CH, Jing B, Ma X, Xu PF, Zhang Y, Li F, et al. Voxel-based morphometry study of the insular cortex in female patients with current and remitted depression. Neuroscience 2014, 262: 190–199.

    Article  CAS  PubMed  Google Scholar 

  41. Opel N, Redlich R, Zwanzger P, Grotegerd D, Arolt V, Heindel W, et al. Hippocampal atrophy in major depression: a function of childhood maltreatment rather than diagnosis? Neuropsychopharmacology 2014, 39: 2723–2731.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Stratmann M, Konrad C, Kugel H, Krug A, Schoning S, Ohrmann P, et al. Insular and hippocampal gray matter volume reductions in patients with major depressive disorder. PLoS One 2014, 9: e102692.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Hagan CC, Graham JM, Tait R, Widmer B, van Nieuwenhuizen AO, Ooi C, et al. Adolescents with current major depressive disorder show dissimilar patterns of age-related differences in ACC and thalamus. Neuroimage Clin 2015, 7: 391–399.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Cauda F, D’Agata F, Sacco K, Duca S, Geminiani G, Vercelli A. Functional connectivity of the insula in the resting brain. Neuroimage 2011, 55: 8–23.

    Article  PubMed  Google Scholar 

  45. Stephani C, Fernandez-Baca Vaca G, Maciunas R, Koubeissi M, Luders HO. Functional neuroanatomy of the insular lobe. Brain Struct Funct 2011, 216: 137–149.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Turner AD, Furey ML, Drevets WC, Zarate C, Jr., Nugent AC. Association between subcortical volumes and verbal memory in unmedicated depressed patients and healthy controls. Neuropsychologia 2012, 50: 2348–2355.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Kaymak SU, Demir B, Senturk S, Tatar I, Aldur MM, Ulug B. Hippocampus, glucocorticoids and neurocognitive functions in patients with first-episode major depressive disorders. Eur Arch Psychiatry Clin Neurosci 2010, 260: 217–223.

    Article  PubMed  Google Scholar 

  48. Sexton CE, Mackay CE, Ebmeier KP. A systematic review of diffusion tensor imaging studies in affective disorders. Biol Psychiatry 2009, 66: 814–823.

    Article  PubMed  Google Scholar 

  49. Li L, Ma N, Li Z, Tan L, Liu J, Gong G, et al. Prefrontal white matter abnormalities in young adult with major depressive disorder: a diffusion tensor imaging study. Brain Res 2007, 1168: 124–128.

    Article  CAS  PubMed  Google Scholar 

  50. Song YJ, Korgaonkar MS, Armstrong LV, Eagles S, Williams LM, Grieve SM. Tractography of the brainstem in major depressive disorder using diffusion tensor imaging. PLoS One 2014, 9: e84825.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Ota M, Noda T, Sato N, Hattori K, Hori H, Sasayama D, et al. White matter abnormalities in major depressive disorder with melancholic and atypical features: A diffusion tensor imaging study. Psychiatry Clin Neurosci 2015, 69: 360–368.

  52. Korgaonkar MS, Williams LM, Song YJ, Usherwood T, Grieve SM. Diffusion tensor imaging predictors of treatment outcomes in major depressive disorder. Br J Psychiatry 2014, 205: 321–328.

    Article  PubMed  Google Scholar 

  53. Raichle ME. The restless brain: how intrinsic activity organizes brain function. Philos Trans R Soc Lond B Biol Sci 2015, 370.

  54. Smith SM, Vidaurre D, Beckmann CF, Glasser MF, Jenkinson M, Miller KL, et al. Functional connectomics from resting-state fMRI. Trends Cogn Sci 2013, 17: 666–682.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Liu CH, Ma X, Song LP, Tang LR, Jing B, Zhang Y, et al. Alteration of spontaneous neuronal activity within the salience network in partially remitted depression. Brain Res 2015, 1599: 93–102.

    Article  CAS  PubMed  Google Scholar 

  56. Manoliu A, Meng C, Brandl F, Doll A, Tahmasian M, Scherr M, et al. Insular dysfunction within the salience network is associated with severity of symptoms and aberrant inter-network connectivity in major depressive disorder. Front Hum Neurosci 2013, 7: 930.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Sambataro F, Wolf ND, Pennuto M, Vasic N, Wolf RC. Revisiting default mode network function in major depression: evidence for disrupted subsystem connectivity. Psychol Med 2014, 44: 2041–2051.

    Article  CAS  PubMed  Google Scholar 

  58. Chen Y, Wang C, Zhu X, Tan Y, Zhong Y. Aberrant connectivity within the default mode network in first-episode, treatment-naive major depressive disorder. J Affect Disord 2015, 183: 49–56.

    Article  PubMed  Google Scholar 

  59. Alexopoulos GS, Hoptman MJ, Kanellopoulos D, Murphy CF, Lim KO, Gunning FM. Functional connectivity in the cognitive control network and the default mode network in late-life depression. J Affect Disord 2012, 139: 56–65.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Zeng LL, Shen H, Liu L, Wang L, Li B, Fang P, et al. Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis. Brain 2012, 135: 1498–1507.

    Article  PubMed  Google Scholar 

  61. Shen T, Li C, Wang B, Yang WM, Zhang C, Wu Z, et al. Increased cognition connectivity network in major depression disorder: a FMRI study. Psychiatry Investig 2015, 12: 227–234.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Zhang X, Zhu X, Wang X, Zhu X, Zhong M, Yi J, et al. First-episode medication-naive major depressive disorder is associated with altered resting brain function in the affective network. PLoS One 2014, 9: e85241.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. Seeley WW, Menon V, Schatzberg AF, Keller J, Glover GH, Kenna H, et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci 2007, 27: 2349–2356.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Hamilton JP, Etkin A, Furman DJ, Lemus MG, Johnson RF, Gotlib IH. Functional neuroimaging of major depressive disorder: a meta-analysis and new integration of base line activation and neural response data. The American journal of psychiatry 2012, 169: 693–703.

    Article  PubMed  Google Scholar 

  65. Campbell KL, Grigg O, Saverino C, Churchill N, Grady CL. Age differences in the intrinsic functional connectivity of default network subsystems. Front Aging Neurosci 2013, 5: 73.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A 2005, 102: 9673–9678.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Posner J, Hellerstein DJ, Gat I, Mechling A, Klahr K, Wang Z, et al. Antidepressants normalize the default mode network in patients with dysthymia. JAMA Psychiatry 2013, 70: 373–382.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Siegle GJ, Thompson W, Carter CS, Steinhauer SR, Thase ME. Increased amygdala and decreased dorsolateral prefrontal BOLD responses in unipolar depression: related and independent features. Biol Psychiatry 2007, 61: 198–209.

    Article  PubMed  Google Scholar 

  69. Fitzgerald PB, Oxley TJ, Laird AR, Kulkarni J, Egan GF, Daskalakis ZJ. An analysis of functional neuroimaging studies of dorsolateral prefrontal cortical activity in depression. Psychiatry Res 2006, 148: 33–45.

    Article  PubMed  Google Scholar 

  70. Nejad AB, Fossati P, Lemogne C. Self-referential processing, rumination, and cortical midline structures in major depression. Front Hum Neurosci 2013, 7: 666.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Sheline YI, Price JL, Yan Z, Mintun MA. Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proc Natl Acad Sci U S A 2010, 107: 11020–11025.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Broyd SJ, Demanuele C, Debener S, Helps SK, James CJ, Sonuga-Barke EJ. Default-mode brain dysfunction in mental disorders: a systematic review. Neurosci Biobehav Rev 2009, 33: 279–296.

    Article  PubMed  Google Scholar 

  73. Rogers MA, Kasai K, Koji M, Fukuda R, Iwanami A, Nakagome K, et al. Executive and prefrontal dysfunction in unipolar depression: a review of neuropsychological and imaging evidence. Neurosci Res 2004, 50: 1–11.

    Article  PubMed  Google Scholar 

  74. MacDonald AW, 3rd, Cohen JD, Stenger VA, Carter CS. Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science 2000, 288: 1835–1838.

    Article  CAS  PubMed  Google Scholar 

  75. Corbetta M, Shulman GL. Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci 2002, 3: 201–215.

    Article  CAS  PubMed  Google Scholar 

  76. Phillips ML, Drevets WC, Rauch SL, Lane R. Neurobiology of emotion perception I: The neural basis of normal emotion perception. Biol Psychiatry 2003, 54: 504–514.

    Article  PubMed  Google Scholar 

  77. Lai CH, Wu YT. Decreased inter-hemispheric connectivity in anterior sub-network of default mode network and cerebellum: significant findings in major depressive disorder. Int J Neuropsychopharmacol 2014, 17: 1935–1942.

    Article  PubMed  Google Scholar 

  78. Guo W, Liu F, Liu J, Yu M, Zhang Z, Liu G, et al. Increased cerebellar-default-mode-network connectivity in drug-naive major depressive disorder at rest. Medicine (Baltimore) 2015, 94: e560.

    Article  Google Scholar 

  79. Fava M, Kendler KS. Major depressive disorder. Neuron 2000, 28: 335–341.

    Article  CAS  PubMed  Google Scholar 

  80. Dichter GS, Gibbs D, Smoski MJ. A systematic review of relations between resting-state functional-MRI and treatment response in major depressive disorder. J Affect Disord 2014, 172c: 8–17.

  81. Shen Y, Yao J, Jiang X, Zhang L, Xu L, Feng R, et al. Sub-hubs of baseline functional brain networks are related to early improvement following two-week pharmacological therapy for major depressive disorder. Hum Brain Mapp 2015, 36: 2915–2927.

  82. Oltedal L, Kessler U, Ersland L, Gruner R, Andreassen OA, Haavik J, et al. Effects of ECT in treatment of depression: study protocol for a prospective neuroradiological study of acute and longitudinal effects on brain structure and function. BMC Psychiatry 2015, 15: 94.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Wang LJ, Kuang WH, Xu JJ, Lei D, Yang YC. Resting-state brain activation correlates with short-time antidepressant treatment outcome in drug-naive patients with major depressive disorder. J Int Med Res 2014, 42: 966–975.

    Article  PubMed  CAS  Google Scholar 

  84. Salomons TV, Dunlop K, Kennedy SH, Flint A, Geraci J, Giacobbe P, et al. Resting-state cortico-thalamic-striatal connectivity predicts response to dorsomedial prefrontal rTMS in major depressive disorder. Neuropsychopharmacology 2014, 39: 488–498.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Crowther A, Smoski MJ, Minkel J, Moore T, Gibbs D, Petty C, et al. Resting-state connectivity predictors of response to psychotherapy in major depressive disorder. Neuropsychopharmacology 2015, 40: 1659–1673.

    Article  PubMed  Google Scholar 

  86. Weiduschat N, Dubin MJ. Prefrontal cortical blood flow predicts response of depression to rTMS. J Affect Disord 2013, 150: 699–702.

    Article  PubMed  Google Scholar 

  87. 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: 768–778.

    Article  PubMed  Google Scholar 

  88. Lisiecka D, Meisenzahl E, Scheuerecker J, Schoepf V, Whitty P, Chaney A, et al. Neural correlates of treatment outcome in major depression. Int J Neuropsychopharmacol 2011, 14: 521–534.

    Article  CAS  PubMed  Google Scholar 

  89. Frodl T, Scheuerecker J, Schoepf V, Linn J, Koutsouleris N, Bokde AL, et al. Different effects of mirtazapine and venlafaxine on brain activation: an open randomized controlled fMRI study. J Clin Psychiatry 2011, 72: 448–457.

    Article  CAS  PubMed  Google Scholar 

  90. Outhred T, Hawkshead BE, Wager TD, Das P, Malhi GS, Kemp AH. Acute neural effects of selective serotonin reuptake inhibitors versus noradrenaline reuptake inhibitors on emotion processing: Implications for differential treatment efficacy. Neurosci Biobehav Rev 2013, 37: 1786–1800.

    Article  CAS  PubMed  Google Scholar 

  91. Wagner G, Koch K, Schachtzabel C, Sobanski T, Reichenbach JR, Sauer H, et al. Differential effects of serotonergic and noradrenergic antidepressants on brain activity during a cognitive control task and neurofunctional prediction of treatment outcome in patients with depression. J Psychiatry Neurosci 2010, 35: 247–257.

    Article  PubMed  PubMed Central  Google Scholar 

  92. Fu CH, Costafreda SG, Sankar A, Adams TM, Rasenick MM, Liu P, et al. Multimodal functional and structural neuroimaging investigation of major depressive disorder following treatment with duloxetine. BMC Psychiatry 2015, 15: 82.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  93. Phelps ME. PET: the merging of biology and imaging into molecular imaging. J Nucl Med 2000, 41: 661–681.

    CAS  PubMed  Google Scholar 

  94. Jones T, Rabiner EA, Company PETRA. The development, past achievements, and future directions of brain PET. J Cereb Blood Flow Metab 2012, 32: 1426–1454.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Phelps ME. Positron emission tomography provides molecular imaging of biological processes. Proc Natl Acad Sci U S A 2000, 97: 9226–9233.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Laruelle M. Imaging synaptic neurotransmission with in vivo binding competition techniques: a critical review. J Cereb Blood Flow Metab 2000, 20: 423–451.

    Article  CAS  PubMed  Google Scholar 

  97. Su L, Cai Y, Xu Y, Dutt A, Shi S, Bramon E. Cerebral metabolism in major depressive disorder: a voxel-based meta-analysis of positron emission tomography studies. BMC Psychiatry 2014, 14: 321.

    Article  PubMed  PubMed Central  Google Scholar 

  98. Sacher J, Neumann J, Funfstuck T, Soliman A, Villringer A, Schroeter ML. Mapping the depressed brain: a meta-analysis of structural and functional alterations in major depressive disorder. J Affect Disord 2012, 140: 142–148.

    Article  PubMed  Google Scholar 

  99. Baldacara L, Borgio JG, Lacerda AL, Jackowski AP. Cerebellum and psychiatric disorders. Rev Bras Psiquiatr 2008, 30: 281–289.

    Article  PubMed  Google Scholar 

  100. Luna B, Minshew NJ, Garver KE, Lazar NA, Thulborn KR, Eddy WF, et al. Neocortical system abnormalities in autism: an fMRI study of spatial working memory. Neurology 2002, 59: 834–840.

    Article  CAS  PubMed  Google Scholar 

  101. Chen CH, Suckling J, Lennox BR, Ooi C, Bullmore ET. A quantitative meta-analysis of fMRI studies in bipolar disorder. Bipolar Disord 2011, 13: 1–15.

    Article  CAS  PubMed  Google Scholar 

  102. Roffman JL, Witte JM, Tanner AS, Ghaznavi S, Abernethy RS, Crain LD, et al. Neural predictors of successful brief psychodynamic psychotherapy for persistent depression. Psychother Psychosom 2014, 83: 364–370.

    PubMed  Google Scholar 

  103. Conway CR, Chibnall JT, Gangwani S, Mintun MA, Price JL, Hershey T, et al. Pretreatment cerebral metabolic activity correlates with antidepressant efficacy of vagus nerve stimulation in treatment-resistant major depression: a potential marker for response? J Affect Disord 2012, 139: 283–290.

    Article  PubMed  PubMed Central  Google Scholar 

  104. Elhwuegi AS. Central monoamines and their role in major depression. Prog Neuropsychopharmacol Biol Psychiatry 2004, 28: 435–451.

    Article  CAS  PubMed  Google Scholar 

  105. Maes M, Leonard BE, Myint AM, Kubera M, Verkerk R. The new ‘5-HT’ hypothesis of depression: cell-mediated immune activation induces indoleamine 2,3-dioxygenase, which leads to lower plasma tryptophan and an increased synthesis of detrimental tryptophan catabolites (TRYCATs), both of which contribute to the onset of depression. Prog Neuropsychopharmacol Biol Psychiatry 2011, 35: 702–721.

    Article  CAS  PubMed  Google Scholar 

  106. Neumeister A, Nugent AC, Waldeck T, Geraci M, Schwarz M, Bonne O, et al. Neural and behavioral responses to tryptophan depletion in unmedicated patients with remitted major depressive disorder and controls. Arch Gen Psychiatry 2004, 61: 765–773.

    Article  CAS  PubMed  Google Scholar 

  107. Gray NA, Milak MS, DeLorenzo C, Ogden RT, Huang YY, Mann JJ, et al. Antidepressant treatment reduces serotonin-1A autoreceptor binding in major depressive disorder. Biol Psychiatry 2013, 74: 26–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Miller JM, Hesselgrave N, Ogden RT, Zanderigo F, Oquendo MA, Mann JJ, et al. Brain serotonin 1A receptor binding as a predictor of treatment outcome in major depressive disorder. Biol Psychiatry 2013, 74: 760–767.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Miller JM, Brennan KG, Ogden TR, Oquendo MA, Sullivan GM, Mann JJ, et al. Elevated serotonin 1A binding in remitted major depressive disorder: evidence for a trait biological abnormality. Neuropsychopharmacology 2009, 34: 2275–2284.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Parsey RV, Oquendo MA, Ogden RT, Olvet DM, Simpson N, Huang YY, et al. Altered serotonin 1A binding in major depression: a [carbonyl-C-11]WAY100635 positron emission tomography study. Biol Psychiatry 2006, 59: 106–113.

    Article  CAS  PubMed  Google Scholar 

  111. Naudon L, El Yacoubi M, Vaugeois JM, Leroux-Nicollet I, Costentin J. A chronic treatment with fluoxetine decreases 5-HT(1A) receptors labeling in mice selected as a genetic model of helplessness. Brain Res 2002, 936: 68–75.

    Article  CAS  PubMed  Google Scholar 

  112. Shishkina GT, Kalinina TS, Dygalo NN. Serotonergic changes produced by repeated exposure to forced swimming: correlation with behavior. Ann N Y Acad Sci 2008, 1148: 148–153.

    Article  PubMed  Google Scholar 

  113. Lemonde S, Turecki G, Bakish D, Du L, Hrdina PD, Bown CD, et al. Impaired repression at a 5-hydroxytryptamine 1A receptor gene polymorphism associated with major depression and suicide. J Neurosci 2003, 23: 8788–8799.

    CAS  PubMed  Google Scholar 

  114. Neff CD, Abkevich V, Packer JC, Chen Y, Potter J, Riley R, et al. Evidence for HTR1A and LHPP as interacting genetic risk factors in major depression. Mol Psychiatry 2009, 14: 621–630.

    Article  CAS  PubMed  Google Scholar 

  115. Purselle DC, Nemeroff CB. Serotonin transporter: a potential substrate in the biology of suicide. Neuropsychopharmacology 2003, 28: 613–619.

    Article  CAS  PubMed  Google Scholar 

  116. Ho PS, Ho KK, Huang WS, Yen CH, Shih MC, Shen LH, et al. Association study of serotonin transporter availability and SLC6A4 gene polymorphisms in patients with major depression. Psychiatry Res 2013, 212: 216–222.

    Article  CAS  PubMed  Google Scholar 

  117. Miller JM, Hesselgrave N, Ogden RT, Sullivan GM, Oquendo MA, Mann JJ, et al. Positron emission tomography quantification of serotonin transporter in suicide attempters with major depressive disorder. Biol Psychiatry 2013, 74: 287–295.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Selvaraj S, Murthy NV, Bhagwagar Z, Bose SK, Hinz R, Grasby PM, et al. Diminished brain 5-HT transporter binding in major depression: a positron emission tomography study with [11C]DASB. Psychopharmacology (Berl) 2011, 213: 555–562.

    Article  CAS  Google Scholar 

  119. Owens MJ, Nemeroff CB. Role of serotonin in the pathophysiology of depression: focus on the serotonin transporter. Clin Chem 1994, 40: 288–295.

    CAS  PubMed  Google Scholar 

  120. Yeh YW, Ho PS, Chen CY, Kuo SC, Liang CS, Ma KH, et al. Incongruent reduction of serotonin transporter associated with suicide attempts in patients with major depressive disorder: a positron emission tomography study with 4-[18F]-ADAM. Int J Neuropsychopharmacol 2014, 18: pyu065.

  121. Huang WS, Huang SY, Ho PS, Ma KH, Huang YY, Yeh CB, et al. PET imaging of the brain serotonin transporters (SERT) with N,N-dimethyl-2-(2-amino-4-[18F]fluorophenylthio)benzylamine (4-[18F]-ADAM) in humans: a preliminary study. Eur J Nucl Med Mol Imaging 2013, 40: 115–124.

    Article  PubMed  CAS  Google Scholar 

  122. Nye JA, Purselle D, Plisson C, Voll RJ, Stehouwer JS, Votaw JR, et al. Decreased brainstem and putamen SERT binding potential in depressed suicide attempters using [11C]-zient PET imaging. Depress Anxiety 2013, 30: 902–907.

    CAS  PubMed  Google Scholar 

  123. Marchand WR, Lee JN, Johnson S, Thatcher J, Gale P, Wood N, et al. Striatal and cortical midline circuits in major depression: implications for suicide and symptom expression. Prog Neuropsychopharmacol Biol Psychiatry 2012, 36: 290–299.

    Article  PubMed  Google Scholar 

  124. Hsieh PC, Chen KC, Yeh TL, Lee IH, Chen PS, Yao WJ, et al. Lower availability of midbrain serotonin transporter between healthy subjects with and without a family history of major depressive disorder—a preliminary two-ligand SPECT study. Eur Psychiatry 2014, 29: 414–418.

    Article  CAS  PubMed  Google Scholar 

  125. Selvaraj S, Arnone D, Cappai A, Howes O. Alterations in the serotonin system in schizophrenia: a systematic review and meta-analysis of postmortem and molecular imaging studies. Neurosci Biobehav Rev 2014, 45: 233–245.

    Article  CAS  PubMed  Google Scholar 

  126. Audet MC, Anisman H. Interplay between pro-inflammatory cytokines and growth factors in depressive illnesses. Front Cell Neurosci 2013, 7: 68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Catena-Dell’Osso M, Rotella F, Dell’Osso A, Fagiolini A, Marazziti D. Inflammation, serotonin and major depression. Curr Drug Targets 2013, 14: 571–577.

    Article  PubMed  Google Scholar 

  128. Brunswick DJ, Amsterdam JD, Mozley PD, Newberg A. Greater availability of brain dopamine transporters in major depression shown by [99m Tc]TRODAT-1 SPECT imaging. Am J Psychiatry 2003, 160: 1836–1841.

    Article  PubMed  Google Scholar 

  129. Neumeister A, Willeit M, Praschak-Rieder N, Asenbaum S, Stastny J, Hilger E, et al. Dopamine transporter availability in symptomatic depressed patients with seasonal affective disorder and healthy controls. Psychol Med 2001, 31: 1467–1473.

    Article  CAS  PubMed  Google Scholar 

  130. Yang YK, Yeh TL, Yao WJ, Lee IH, Chen PS, Chiu NT, et al. Greater availability of dopamine transporters in patients with major depression–a dual-isotope SPECT study. Psychiatry Res 2008, 162: 230–235.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

Research in the corresponding author’s laboratory was supported by the National Natural Science Foundation of China (81425015 and 81271601), the International S&T Cooperation Program of China (2015DFG32740), and the Zhejiang Provincial Natural Science Foundation of China (LR13H180001).

Author information

Authors and Affiliations

  1. Department of Nuclear Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China

    Kai Zhang, Yunqi Zhu, Yuankai Zhu, Shuang Wu, Hao Liu, Caiyun Xu, Hong Zhang & Mei Tian

  2. Zhejiang University Medical PET Center, Hangzhou, 310009, China

    Kai Zhang, Yunqi Zhu, Yuankai Zhu, Shuang Wu, Hao Liu, Caiyun Xu, Hong Zhang & Mei Tian

  3. Institute of Nuclear Medicine and Molecular Imaging, Zhejiang University, Hangzhou, 310009, China

    Kai Zhang, Yunqi Zhu, Yuankai Zhu, Shuang Wu, Hao Liu, Caiyun Xu, Hong Zhang & Mei Tian

  4. Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, 310009, China

    Kai Zhang, Yunqi Zhu, Yuankai Zhu, Shuang Wu, Hao Liu, Caiyun Xu, Hong Zhang & Mei Tian

  5. Department of Orthopedics, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China

    Wei Zhang

  6. Functional Architecture Imaging Unit, RIKEN Center for Life Science Technologies, Kobe, 650-0047, Japan

    Takuya Hayashi

Authors
  1. Kai Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yunqi Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yuankai Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shuang Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hao Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Wei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Caiyun Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Hong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Takuya Hayashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Mei Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Takuya Hayashi or Mei Tian.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, K., Zhu, Y., Zhu, Y. et al. Molecular, Functional, and Structural Imaging of Major Depressive Disorder. Neurosci. Bull. 32, 273–285 (2016). https://doi.org/10.1007/s12264-016-0030-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12264-016-0030-0

Keywords

Search

Navigation