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9.7 - Major Depressive Disorder

from 9 - Integrated Neurobiology of Specific Syndromes and Treatments

Published online by Cambridge University Press:  08 November 2023

Mary-Ellen Lynall
Affiliation:
University of Cambridge
Peter B. Jones
Affiliation:
University of Cambridge
Stephen M. Stahl
Affiliation:
University of California, San Diego
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Summary

Major depression is a debilitating mental health condition that affects many people and causes a great deal of suffering worldwide. Yet, our understanding of its etiology and pathophysiology is still poor. Neuroscientists have studied depressive disorders from different perspectives and have reported a range of abnormalities on different levels of neurobiological description. Based on these findings, various, mutually not necessarily exclusive theories have been put forward to explain the development and maintenance of depressive symptoms. The clinical relevance of these theories and how they relate to each other will have to be the subject of future neuroscientific research on depression.

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Publisher: Cambridge University Press
Print publication year: 2023

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References

American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, 5th ed. (DSM-5). American Psychiatric Association, 2013.Google Scholar
Harrison, P, Cowen, P, Burns, T, Fazel, M. Depression. In Shorter Oxford Textbook of Psychiatry, 7th ed. Oxford University Press, 2018, pp. 193232.Google Scholar
Cowen, P. Neuroendocrine and neurochemical processes in depression. In DeRubeis, RJ, Strunk, DR, eds., The Oxford Handbook of Mood Disorders. Oxford University Press, 2017, pp. 190200.Google Scholar
Ruhé, HG, Mason, NS, Schene, AH. Mood is indirectly related to serotonin, norepinephrine and dopamine levels in humans: a meta-analysis of monoamine depletion studies. Mol Psychiatry 2007; 12(4): 331359.CrossRefGoogle ScholarPubMed
Cowen, P. Serotonin and depression: pathophysiological mechanism or marketing myth? Trends Pharmacol Sci 2008; 29(9): 433436.CrossRefGoogle ScholarPubMed
Sanacora, G, Zarate, CA, Krystal, JH, Manji, HK. Targeting the glutamatergic system to develop novel, improved therapeutics for mood disorders. Nat Rev Drug Discov 2008; 7(5): 426437.CrossRefGoogle ScholarPubMed
Sanacora, G. Cortical inhibition, gamma-aminobutyric acid, and major depression: there is plenty of smoke but is there fire? Biol Psychiatry 2010; 67(5): 397398.CrossRefGoogle ScholarPubMed
Pariante, CM, Lightman, SL. The HPA axis in major depression: classical theories and new developments. Trends Neurosci 2008; 31(9): 464468.CrossRefGoogle ScholarPubMed
Pariante, CM. The glucocorticoid receptor: part of the solution or part of the problem? J Psychopharmacol 2006; 20: 7984.CrossRefGoogle ScholarPubMed
Dantzer, R, O’Connor, JC, Freund, GG, Johnson, RW, Kelley, KW. From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci 2008; 9(1): 4656.CrossRefGoogle ScholarPubMed
Krishnadas, R, Cavanagh, J. Depression: an inflammatory illness? J Neurol Neurosurg Psychiatry 2012; 83(5): 495502.CrossRefGoogle ScholarPubMed
Capuron, L, Miller, AH. Immune system to brain signaling: neuropsychopharmacological implications. Pharmacol Ther 2011; 130(2): 226238.CrossRefGoogle ScholarPubMed
Disabato, B, Bauer, IE, Soares, JC, Sheline, Y. Neural structure and organization of mood pathology. In DeRubeis, RJ, Strunk, DR eds., The Oxford Handbook of Mood Disorders. Oxford University Press, 2017, pp. 214224.Google Scholar
Arnone, D, McIntosh, AM, Ebmeier, KP, Munafò, MR, Anderson, IM. Magnetic resonance imaging studies in unipolar depression: Systematic review and meta-regression analyses. Eur Neuropsychopharmacol 2012; 22(1): 116.CrossRefGoogle ScholarPubMed
Herrmann, LL, Masurier, ML, Ebmeier, KP. White matter hyperintensities in late life depression: a systematic review. J Neurol Neurosurg Psychiatry 2008; 79(6): 619624.CrossRefGoogle ScholarPubMed
Price, JL, Drevets, WC. Neurocircuitry of mood disorders. Neuropsychopharmacology 2010; 35(1): 192216.CrossRefGoogle ScholarPubMed
Roiser, J, Sahakian, BJ. Information processing in mood disorders. In DeRubeis, RJ, Strunk, DR eds., The Oxford Handbook of Mood Disorders. Oxford University Press, 2017, pp. 179189.Google Scholar
Roiser, JP, Sahakian, BJ. Hot and cold cognition in depression. CNS Spectr 2013; 18(3): 139149.CrossRefGoogle ScholarPubMed
Harmer, C, Pringle, A. Neuropsychological mechanisms of depression and treatment. In DeRubeis, RJ, Strunk, DR eds., The Oxford Handbook of Mood Disorders. Oxford University Press, 2017, pp. 201213.Google Scholar
Harmer, CJ, Goodwin, GM, Cowen, PJ. Why do antidepressants take so long to work? A cognitive neuropsychological model of antidepressant drug action. Br J Psychiatry 2009; 195(2): 102108.CrossRefGoogle Scholar
Roiser, JP, Elliott, R, Sahakian, BJ. Cognitive mechanisms of treatment in depression. Neuropsychopharmacology 2012; 37: 117136.CrossRefGoogle ScholarPubMed
Eshel, N, Roiser, JP. Reward and punishment processing in depression. Biol Psychiatry 2010; 68(2): 118124.CrossRefGoogle ScholarPubMed
Harmer, CJ, Duman, RS, Cowen, PJ. How do antidepressants work? New perspectives for refining future treatment approaches. Lancet Psychiatry 2017; 4(5): 409418.CrossRefGoogle ScholarPubMed
MacKenzie, LE, Uher, R, Pavlova, B. Cognitive performance in first-degree relatives of individuals with vs without major depressive disorder: a meta-analysis. JAMA Psychiatry 2019; 76(3): 297.CrossRefGoogle ScholarPubMed
Stahl, SM. Mood disorders. In Stahl’s Essential Psychopharmacology: Neuroscientific Basis and Practical Applications. 4th ed. Cambridge University Press, 2013, pp. 237–283.Google Scholar
Guloksuz, S, Pries, L-K, van Os, J. Application of network methods for understanding mental disorders: pitfalls and promise. Psychol Med 2017; 47(16): 27432752.CrossRefGoogle ScholarPubMed

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