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Current Neuropharmacology logoLink to Current Neuropharmacology
. 2015 Jul;13(4):458–465. doi: 10.2174/1570159X1304150831121909

Brain Structural Effects of Antidepressant Treatment in Major Depression

Nicola Dusi 1,*, Stefano Barlati 2, Antonio Vita 2,3, Paolo Brambilla 4,5
PMCID: PMC4790407  PMID: 26412065

Abstract

Depressive disorder is a very frequent and heterogeneous syndrome. Structural imaging techniques offer a useful tool in the comprehension of neurobiological alterations that concern depressive disorder. Altered brain structures in depressive disorder have been particularly located in the prefrontal cortex (medial prefrontal cortex and orbitofrontal cortex, OFC) and medial temporal cortex areas (hippocampus). These brain areas belong to a structural and functional network related to cognitive and emotional processes putatively implicated in depressive symptoms. These volumetric alterations may also represent biological predictors of response to pharmacological treatment. In this context, major findings of magnetic resonance (MR) imaging, in relation to treatment response in depressive disorder, will here be presented and discussed.

Keywords: amitriptyline, amygdala, cingulate, citalopram, doxepine, fluoxetine, fluxovamine, hippocampus, mirtazapine, paroxetine, prefrontal cortex, reboxetine, sertraline, trimipramine, venlafaxine.

INTRODUCTION

Depression is a very common disease, being an important cause of burden worldwide [1]. Patients with depressive disease have different clinical outcome with some of them facing a benign course of illness and others presenting severe, recurrent and remitting episodes [2]. To date, the neuropathological alterations that sustain this wide syndromic entity and the mechanisms behind drug response are still not completely understood [3, 4]. Many hypothesis have been proposed regarding the alterations involved in the neurobiology of depressive disorder: most of them have been focused on brain areas that are implicated in the circuits of serotonin and norepinephrine [5], which are also the main target neurotransmitters of antidepressants [6-9]. Impaired neural circuits that involve these neurotransmitters and encode cognitive and emotional functions have been observed in depressive disorder [10]. Brain areas that are implicated in these networks have been studied with neuroimaging techniques that have revealed specific structural [11-13] and functional alterations [14] features.

Magnetic resonance imaging (MRI) studies on depressive disorder have shown volume reductions in frontal regions, hippocampus, putamen and caudate nucleus [15-18], anterior cingulate [19], amygdala [20], as well as white matter hyperintense lesions [21]. Alterations in limbic and prefrontal areas are suggested to be involved in affective symptoms, such as exaggerated response to negative emotions, guilt, hopelessness and despair, whereas alterations in hypothalamus, locus coeruleus and periacqueductal grey matter may be involved in neurovegetative and neuroendocrine alterations, such as sleep and appetite disturbances, loss of weight, psychomotor retardation or agitation [22].

Imaging methods are required to overcome classical nosological definitions based on syndromic clinical descriptions, by offering reliable models of neuro-morphological alterations that can explain those phenotypes commonly considered as part of the disease [23]. In addition, imaging methods have also been applied to evaluate treatment response to antidepressants among responder and non-responder patients, in order to establish trait markers of depression biological features of refractory illness and predictors of clinical outcome [24, 25]. While phar-macotherapy is often prescribed as an effective intervention for depressive disorder, not all patients who undergo antidepressant treatment get significant amelioration, with almost one third of them failing to achieve remission even after several pharmacological trials [26]. Despite prescriptions of pharmacological therapy for depressive disorder are incresing world wide, treatment response is still uncertain and there is a lack of indicators of those group of patients who can actually benefit from antidepressant therapy or not. In general, neurobiological features are relevant key factors in understanding the course of illness in psychiatric disorders, therefore their identification would help both clinical and research progress. Characterizing homogeneous diagnostic groups based on neural features will facilitate genetic investigations on the etiology of depression and will ameliorate the effectiveness of interventions [27, 28]. In this perspective, evidence from imaging research has shed light on the importance of early diagnosis and intervention on major depression [29-31]. In particular, MRI offers, in vivo, the possibility to explore the structural basis of the response mechanisms to antidepressants, allowing to improve the understanding of how these compounds work on the brain, and ultimately lead to clinical improvement.

We here first review the most robust findings on brain areas involved in depressive disorder and then debate them in relationship to antidepressant treatment response.

MAJOR STRUCTURAL BRAIN ALTERATIONS IN DEPRESSIVE DISORDER

Whole Brain

Total brain volume and whole gray matter volume have not consistently been reported to be altered in adult and geriatric patients with depressive disorder [32-37], as recently confirmed by a meta-analysis [38]. White matter hyperintensities have also been reported, particularly in older patients [38-41].

FRONTAL LOBES AND CINGULATE

Patients with depressive disorder have been shown lower volume in prefrontal/orbitofrontal cortex (OFC) [32, 42-44] and anterior cingulate [33, 37, 38, 42, 45, 46]. These findings were not always replicated in other research studies [38, 47]. Interestingly, shrinkage of medial prefrontal cortex in drug naïve patients [48], along with anterior cingulate volume reduction, seem to progress over time at a faster rate than healthy controls [49]. In regards of cortical folding, lower gyrification index has been reported in orbitofrontal and cingulate cortices as well as in the insula and temporal operculum [12].

TEMPORAL LOBES

Evidence of reduced temporal gray matter has been found by some studies [42, 50], though not confirmed by others [33, 51, 52]. Furthermore, an inverse relationship between superior temporal gyrus volume and length of illness has been shown in unmedicated patients [53]. On the other hand, greater cortical thickness was reported on some paralimbic areas located in the temporal lobes, such as temporal poles in first episode [54] and child-adolescence depression [55].

BASAL GANGLIA AND THALAMUS

Volume reduction in putamen and caudate nucleus have been reported in depression [36-38, 42, 56, 57]. Hyperintensities in putamen and globus pallidus have also been shown, mostly in elderly patients [58, 59], being possible predictors of lack of response in geriatric population [60-63].

Reduced thalamus have been observed in patients with depression by some reports [34, 42, 48], whereas others found no difference [64, 65].

HIPPOCAMPUS AND AMYGDALA

Smaller hippocampal volumes have consistently been observed in chronic, acute and non remitting patients with depression [18, 49, 66-69], as confirmed by a comprehensive meta-analysis [15], with progressive reduction over time [70]. Amygdala has also been reported as reduced by some studies [71-75], particularly in unmedicated [53, 76, 77] and recurrent patients [51, 53, 78]. However, preserved [74, 79-84] or even enlarged amygdala volumes [49, 84-88] have been observed. Inconsistency across findings has been attributed to differences in illness stage, age and gender composition of samples and effect of treatment [15, 89, 90].

CEREBELLUM AND BRAINSTEM

Depressed patients have been reported to have smaller cerebellar [42, 91, 92] and brain stem [92] volumes compared to healthy controls. However, the literature is limited by the paucity of the studies.

VENTRICLES AND CEREBROSPINAL FLUID (CSF)

A vast majority of studies has shown larger volume of third [93-96], lateral ventricles [95, 97-101] and CSF in patients with depressive disorder, whereas some others found preserved size [33, 92, 102-106]. A recent meta-analysis reported a trend of enlargement of CSF among patients with depression, but remarked the heterogeneity across studies [38].

CORPUS CALLOSUM

Enlarged corpus callosum has been observed by one study [107], though not confirmed by others [36, 57, 108].

PITUITARY

A reduced volume in pituitary gland has been reported by one study [109], whereas others did not find any difference [110], even longitudinally after remission [111]. Morover, in a recent meta-analysis that included psychotic depression [112], pituitary gland was larger in depressed patients, relative to healthy controls [38].

EFFECTS OF ANTIDEPRESSANT TREATMENT ON BRAIN MORPHOLOGY IN DEPRESSION

Several imaging studies have assessed the effects of antidepressant treatment - in terms of duration, efficacy and compounds - on brain volumes in patients with depressive disorder. The purpose of this kind of investigation is twofold: on one hand to investigate how treatment affects brain anatomy; on the other hand, to understand the mechanism of action of antidepressants. Furthermore, clinical outcome of patients with depressive disorder can be fairly variable and prediction of treatment response is a challenge for development of reliable therapies [113].

As previously mentioned, there is a convergent research line focusing on hippocampus as a possible biomarker of depressive disorder, even in relation to clinical outcome and treatment effect. Indeed, a smaller hippocampal volume has been associated with severity of depression [114, 115], early onset [116-118], refractory illness [70, 114, 119, 120], longer duration of untreated depression [121], comorbidity with childhood abuse [122] and high levels of disease burden [72, 123-125] or anxiety [126, 127].

In this context, increased right hippocampal volumes have been found in female responders compared to non-responders after eight weeks of fluoxetine treatment [114]; female responders also had larger caudate nucleus compared to male responders and to female non responders [128, 129]. This may indicate a modulatory response effect influenced by gender [67, 130]. In another (one-year) longitudinal study non remitting patients to various antidepressants (including fluxovamine, paroxetine, sertraline, citalopram, venlafaxine, mirtazapine, amitriptyline, doxepine, trimipramine and reboxetine) had lower bilateral hippocampal volumes both at baseline and at follow-up, compared to remitted patients [70], whereas patients who remitted at 3 years follow-up had lower shrinkage of hippocampus [49]. In agreement with these observations, larger hippocampal volumes at baseline predicted remission after antidepressant treatment [131, 132], whereas lower volumes predicted relapse or lack of remission [119, 131]. However, it has to be noted that no effects on hippocampal size after remission mostly with SSRIs have been found in patients with major depression by one study [68].

Morover, imaging studies have produced interesting findings on the structural effects of antidepressant treatment in prefrontal areas. Larger frontal cortical thickness [131] and medial frontal gyrus, dorsolateral prefrontal cortex (DLPFC) and cingulate cortex volumes [24, 133, 134] predicted remission after antidepressant treatment [84, 128]. Furthermore, effective treatment with fluoxetine and sertraline determined enlargement in middle frontal gyrus, DLPFC and OFC [48, 135]. Accordingly, it has been shown that remission correlates to more preserved volumes of anterior cingulate, dorsomedial prefrontal cortex and DLPFC over time [49, 136]. Finally, geriatric patients previously exposed to antidepressant treatment had larger OFC volumes compared to drug-naïve patients [32].

However, even though there is convergent evidence from MRI studies of antidepressant effect on an altered prefrontal-limbic network, some controversial results deserve consideration. Drug-naïve, first-episode patients with depression and comorbid panic disorder treated with duloxetine for 6 weeks had only subtle enlargement of infero-frontal areas, although they underwent clinical amelioration [137]. Furthermore, in two other longitudinal studies, no volumetric changes were observed to SSRIs or nortriptiline, though in presence of clinical response [68, 138], and no predictive property of hippocampal volume was observed [66].

DISCUSSION

Based on the above reviewed literature, it looks that depressive disorder is characterized by an altered structural network that encompasses reduced volumes of OFC, anterior cingulate, hippocampus, and striatum with enlarged ventricles. Also, in regards to the structural effects of antidepressants, taken together the literature’s results underlie the implication of hippocampus, DLPFC and cingulate cortex in their neurobiological mechanisms. In this regards, other imaging techniques that specifically assess white matter, such as diffusion tensor imaging (DTI), corroborated these data showing an impaired fiber integrity connecting cingulate, DLPFC, and hippocampus in non remitter patients [136, 139]. Therefore, such brain areas may represent the biological markers of treatment response and outcome in depressive disorder.

Effective antidepressant treatment might have a neurobiological impact on depressive disorder by reducing structural shrinkage processes in hippocampus and prefrontal cortex, based on a putative neuroprotective or neuro-modulatory effect [140, 141]. In this perspective, antidepressants SSRIs have caused an increase of volume in cingulate subdivisions and precuneus in healthy controls under short administration, confirming a structural remodeling, independent of depressive illness, by serotonergic neurotransmission [142]. Serotonin and norepinephrine have indeed been observed in some reports to enhance neuro-trophic factors, such as BDNF, that increases neurogenesis on grey matter [143]. Furthermore, according to fMRI studies, antidepressants affect this network by reversing hyperactivation of limbic areas to emotional stimuli and by enhancing frontal cortex and cingulate top-down modulatory influence on subcortical structures [144-146].

However, larger studies, focused on specific compounds administered longitudinally to drug-naive patients are needed to finally clarify the impact of antidepressants on brain morphology in major depression. Indeed, a major limitation of the studies presented here is the low sample size, with most studies below 50 subjects and only one over 100 [62, 131]. Moreover, it is impossible to draw conclusions on the effect of single specific compounds because many studies include multiple antidepressants [49, 67, 68, 84, 119, 132, 133, 147] and very few studies focused on the effect of “non SSRIs” antidepressants [138, 148, 149]. Although these designs are closer to real world interventions which apply multiple drugs [150] they limit the possibility to investigate the contribute of different compounds to the brain altered circuits, in order to plan more effective and targeted interventions.

ACKNOWLEDGEMENTS

P.B. was partially supported by grants from the Italian Ministry of Health (GR-2010- 2316745; GR-2010-2319022, 2011-2014; GR-2010-2317873, 2011-2014).

CONFLICT OF INTEREST

The authors confirm that this article content has no conflict of interest.

References

  • 1.Aakhus E., Flottorp S.A., Oxman A.D. Implementing evidence-based guidelines for managing depression in elderly patients: a Norwegian perspective. Epidemiol. Psychiatr. Sci. 2012;21(3):237–240. doi: 10.1017/S204579601200025X. [DOI] [PubMed] [Google Scholar]
  • 2.Li C.T., Bai Y.M., Huang Y.L., Chen Y.S., Chen T.J., Cheng J.Y., Su T.P. Association between antidepressant resistance in unipolar depression and subsequent bipolar disorder: cohort study. Br. J. Psychiatry. 2012;200(1):45–51. doi: 10.1192/bjp.bp.110.086983. [DOI] [PubMed] [Google Scholar]
  • 3.Brambilla P., Perez J., Barale F., Schettini G., Soares J. C. GABAergic dysfunction in mood disorders. Mol. Psychiatry. 2003;8(8):721-37–715. doi: 10.1038/sj.mp.4001362. [DOI] [PubMed] [Google Scholar]
  • 4.Brambilla P., Cipriani A., Hotopf M., Barbui C. Side-effect profile of fluoxetine in comparison with other SSRIs, tricyclic and newer antidepressants: a meta-analysis of clinical trial data. Pharmacopsychiatry. 2005;38(2):69–77. doi: 10.1055/s-2005-837806. [DOI] [PubMed] [Google Scholar]
  • 5.Mann J.J., Malone K.M., Diehl D.J., Perel J., Cooper T.B., Mintun M.A. Demonstration in vivo of reduced serotonin responsivity in the brain of untreated depressed patients. Am. J. Psychiatry. 1996;153(2):174–182. doi: 10.1176/ajp.153.2.174. [DOI] [PubMed] [Google Scholar]
  • 6.Manji H.K., Quiroz J.A., Sporn J., Payne J.L., Denicoff K., A Gray N., Zarate C.A., Jr, Charney D.S. Enhancing neuronal plasticity and cellular resilience to develop novel, improved therapeutics for difficult-to-treat depression. Biol. Psychiatry. 2003;53(8):707–742. doi: 10.1016/S0006-3223(03)00117-3. [DOI] [PubMed] [Google Scholar]
  • 7.Sala M., Coppa F., Cappucciati C., Brambilla P., d’Allio G., Caverzasi E., Barale F., De Ferrari G.M. Antidepressants: their effects on cardiac channels, QT prolongation and Torsade de Pointes. Curr. Opin. Investig. Drugs. 2006;7(3):256–263. [PubMed] [Google Scholar]
  • 8.Sala M., Caverzasi E., Marraffini E., De Vidovich G., Lazzaretti M., d’Allio G., Isola M., Balestrieri M., D’Angelo E., Thyrion F.Z., Scagnelli P., Barale F., Brambilla P. Cognitive memory control in borderline personality disorder patients. Psychol. Med. 2009;39(5):845–853. doi: 10.1017/S0033291708004145. [DOI] [PubMed] [Google Scholar]
  • 9.Verdoux H., Tournier M., Bégaud B. Pharmacoepidemiology of psychotropic drugs: examples of current research challenges on major public health issues. Epidemiol. Psichiatr. Soc. 2009;18(2):107–113. [PubMed] [Google Scholar]
  • 10.Murrough J.W., Iacoviello B., Neumeister A., Charney D.S., Iosifescu D.V. Cognitive dysfunction in depression: neurocircuitry and new therapeutic strategies. Neurobiol. Learn. Mem. 2011;96(4):553–563. doi: 10.1016/j.nlm.2011.06.006. [DOI] [PubMed] [Google Scholar]
  • 11.Malykhin N.V., Carter R., Hegadoren K.M., Seres P., Coupland N.J. Fronto-limbic volumetric changes in major depressive disorder. J. Affect. Disord. 2012;136(3):1104–1113. doi: 10.1016/j.jad.2011.10.038. [DOI] [PubMed] [Google Scholar]
  • 12.Zhang Y., Yu C., Zhou Y., Li K., Li C., Jiang T. Decreased gyrification in major depressive disorder. Neuroreport. 2009;20(4):378–380. doi: 10.1097/WNR.0b013e3283249b34. [DOI] [PubMed] [Google Scholar]
  • 13.Tu P. C., Chen L. F., Hsieh J. C., Bai Y. M., Li C. T., Su T. P. Regional cortical thinning in patients with major depressive disorder: a surface-based morphometry study. Psychiatry Res. 2012;202(3):206–13. doi: 10.1016/j.pscychresns.2011.07.011. [DOI] [PubMed] [Google Scholar]
  • 14.Graham J., Salimi-Khorshidi G., Hagan C., Walsh N., Goodyer I., Lennox B., Suckling J. Meta-analytic evidence for neuroimaging models of depression: state or trait? J. Affect. Disord. 2013;151(2):423–431. doi: 10.1016/j.jad.2013.07.002. [DOI] [PubMed] [Google Scholar]
  • 15.Campbell S., Marriott M., Nahmias C., MacQueen G.M. Lower hippocampal volume in patients suffering from depression: a meta-analysis. Am. J. Psychiatry. 2004;161(4):598–607. doi: 10.1176/appi.ajp.161.4.598. [DOI] [PubMed] [Google Scholar]
  • 16.Koolschijn P.C., van Haren N.E., Lensvelt-Mulders G.J., Hulshoff Pol H.E., Kahn R.S. Brain volume abnormalities in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. Hum. Brain Mapp. 2009;30(11):3719–3735. doi: 10.1002/hbm.20801. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Videbech P., Ravnkilde B. Hippocampal volume and depression: a meta-analysis of MRI studies. Am. J. Psychiatry. 2004;161(11):1957–1966. doi: 10.1176/appi.ajp.161.11.1957. [DOI] [PubMed] [Google Scholar]
  • 18.McKinnon M.C., Yucel K., Nazarov A., MacQueen G.M. A meta-analysis examining clinical predictors of hippocampal volume in patients with major depressive disorder. J. Psychiatry Neurosci. 2009;34(1):41–54. [PMC free article] [PubMed] [Google Scholar]
  • 19.Hajek T., Kozeny J., Kopecek M., Alda M., Höschl C. Reduced subgenual cingulate volumes in mood disorders: a meta-analysis. J. Psychiatry Neurosci. 2008;33(2):91–99. [PMC free article] [PubMed] [Google Scholar]
  • 20.Hamilton J.P., Siemer M., Gotlib I.H. Amygdala volume in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. Mol. Psychiatry. 2008;13(11):993–1000. doi: 10.1038/mp.2008.57. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Videbech P. MRI findings in patients with affective disorder: a meta-analysis. Acta Psychiatr. Scand. 1997;96(3):157–168. doi: 10.1111/j.1600-0447.1997.tb10146.x. [DOI] [PubMed] [Google Scholar]
  • 22.Agarwal N., Port J.D., Bazzocchi M., Renshaw P.F. Update on the use of MR for assessment and diagnosis of psychiatric diseases. Radiology. 2010;255(1):23–41. doi: 10.1148/radiol.09090339. [DOI] [PubMed] [Google Scholar]
  • 23.Andreone N., Tansella M., Cerini R., Rambaldelli G., Versace A., Marrella G., Perlini C., Dusi N., Pelizza L., Balestrieri M., Barbui C., Nosè M., Gasparini A., Brambilla P. Cerebral atrophy and white matter disruption in chronic schizophrenia. Eur. Arch. Psychiatry Clin. Neurosci. 2007;257(1):3–11. doi: 10.1007/s00406-006-0675-1. [DOI] [PubMed] [Google Scholar]
  • 24.Chen C. H., Ridler K., Suckling J., Williams S., Fu C. H., Merlo-Pich E., Bullmore E. Brain imaging correlates of depressive symptom severity and predictors of symptom improvement after antidepressant treatment. Biol. Psychiatry. 2007;62(5):407–14. doi: 10.1016/j.biopsych.2006.09.018. [DOI] [PubMed] [Google Scholar]
  • 25.Phillips J.L., Batten L.A., Aldosary F., Tremblay P., Blier P. Brain-volume increase with sustained remission in patients with treatment-resistant unipolar depression. J. Clin. Psychiatry. 2012;73(5):625–631. doi: 10.4088/JCP.11m06865. [DOI] [PubMed] [Google Scholar]
  • 26.Gaynes B.N., Warden D., Trivedi M.H., Wisniewski S.R., Fava M., Rush A.J. What did STAR*D teach us? Results from a large-scale, practical, clinical trial for patients with depression. Psychiatr. Serv. 2009;60(11):1439–1445. doi: 10.1176/ps.2009.60.11.1439. [DOI] [PubMed] [Google Scholar]
  • 27.Bellani M., Dusi N., Brambilla P. 2013. Can brain imaging address psychosocial functioning and outcome in schizophrenia? [DOI] [Google Scholar]
  • 28.Buchsbaum M.S., Haznedar M., Newmark R.E., Chu K.W., Dusi N., Entis J.J., Goldstein K.E., Goodman C.R., Gupta A., Hazlett E., Iannuzzi J., Torosjan Y., Zhang J., Wolkin A. FDG-PET and MRI imaging of the effects of sertindole and haloperidol in the prefrontal lobe in schizophrenia. Schizophr. Res. 2009;114(1-3):161–171. doi: 10.1016/j.schres.2009.07.015. [DOI] [PubMed] [Google Scholar]
  • 29.Horga G., Bernacer J., Dusi N., Entis J., Chu K., Hazlett E.A., Haznedar M.M., Kemether E., Byne W., Buchsbaum M.S. Correlations between ventricular enlargement and gray and white matter volumes of cortex, thalamus, striatum, and internal capsule in schizophrenia. Eur. Arch. Psychiatry Clin. Neurosci. 2011;261(7):467–476. doi: 10.1007/s00406-011-0202-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Bellani M., Dusi N., Brambilla P. Longitudinal imaging studies in schizophrenia: the relationship between brain morphology and outcome measures. Epidemiol. Psichiatr. Soc. 2010;19(3):207–210. [PubMed] [Google Scholar]
  • 31.Bellani M., Dusi N., Yeh P.H., Soares J.C., Brambilla P. The effects of antidepressants on human brain as detected by imaging studies. Focus on major depression. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2011;35(7):1544–1552. doi: 10.1016/j.pnpbp.2010.11.040. [DOI] [PubMed] [Google Scholar]
  • 32.Lavretsky H., Roybal D. J., Ballmaier M., Toga A. W., Kumar A. Antidepressant exposure may protect against decrement in frontal gray matter volumes in geriatric depression. J. Clin. Psychiatry. 2005;66(8):964–7. doi: 10.4088/JCP.v66n0801. [DOI] [PubMed] [Google Scholar]
  • 33.Coffey C.E., Wilkinson W.E., Weiner R.D., Parashos I.A., Djang W.T., Webb M.C., Figiel G.S., Spritzer C.E. Quantitative cerebral anatomy in depression. A controlled magnetic resonance imaging study. Arch. Gen. Psychiatry. 1993;50(1):7–16. doi: 10.1001/archpsyc.1993.01820130009002. [DOI] [PubMed] [Google Scholar]
  • 34.Dupont R.M., Jernigan T.L., Heindel W., Butters N., Shafer K., Wilson T., Hesselink J., Gillin J.C. Magnetic resonance imaging and mood disorders. Localization of white matter and other subcortical abnormalities. Arch. Gen. Psychiatry. 1995;52(9):747–755. doi: 10.1001/archpsyc.1995.03950210041009. [DOI] [PubMed] [Google Scholar]
  • 35.Axelson D.A., Doraiswamy P.M., McDonald W.M., Boyko O.B., Tupler L.A., Patterson L.J., Nemeroff C.B., Ellinwood E.H., Jr, Krishnan K.R. Hypercortisolemia and hippocampal changes in depression. Psychiatry Res. 1993;47(2):163–173. doi: 10.1016/0165-1781(93)90046-J. [DOI] [PubMed] [Google Scholar]
  • 36.Husain M.M., McDonald W.M., Doraiswamy P.M., Figiel G.S., Na C., Escalona P.R., Boyko O.B., Nemeroff C.B., Krishnan K.R. A magnetic resonance imaging study of putamen nuclei in major depression. Psychiatry Res. 1991;40(2):95–99. doi: 10.1016/0925-4927(91)90001-7. [DOI] [PubMed] [Google Scholar]
  • 37.Krishnan K.R., McDonald W.M., Escalona P.R., Doraiswamy P.M., Na C., Husain M.M., Figiel G.S., Boyko O.B., Ellinwood E.H., Nemeroff C.B. Magnetic resonance imaging of the caudate nuclei in depression. Preliminary observations. Arch. Gen. Psychiatry. 1992;49(7):553–557. doi: 10.1001/archpsyc.1992.01820070047007. [DOI] [PubMed] [Google Scholar]
  • 38.Arnone D., McIntosh A.M., Ebmeier K.P., Munafò M.R., Anderson I.M. Magnetic resonance imaging studies in unipolar depression: systematic review and meta-regression analyses. Eur. Neuropsychopharmacol. 2012;22(1):1–16. doi: 10.1016/j.euroneuro.2011.05.003. [DOI] [PubMed] [Google Scholar]
  • 39.Guze B.H., Szuba M.P. Leukoencephalopathy and major depression: a preliminary report. Psychiatry Res. 1992;45(3):169–175. doi: 10.1016/0925-4927(92)90024-X. [DOI] [PubMed] [Google Scholar]
  • 40.Sassi R.B., Brambilla P., Nicoletti M., Mallinger A.G., Frank E., Kupfer D.J., Keshavan M.S., Soares J.C. White matter hyperintensities in bipolar and unipolar patients with relatively mild-to-moderate illness severity. J. Affect. Disord. 2003;77(3):237–245. doi: 10.1016/S0165-0327(02)00170-2. [DOI] [PubMed] [Google Scholar]
  • 41.Salloway S., Correia S., Boyle P., Malloy P., Schneider L., Lavretsky H., Sackheim H., Roose S., Krishnan K. R. R. MRI subcortical hyperintensities in old and very old depressed outpatients: The important role of age in late-life depression. J.Neurol. Sci. 2002;203–204:227–233. doi: 10.1016/s0022-510x(02)00296-4. [DOI] [PubMed] [Google Scholar]
  • 42.Grieve S.M., Korgaonkar M.S., Koslow S.H., Gordon E., Williams L.M. Widespread reductions in gray matter volume in depression. Neuroimage Clin. 2013;3:332–339. doi: 10.1016/j.nicl.2013.08.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Salvadore G., Nugent A.C., Lemaitre H., Luckenbaugh D.A., Tinsley R., Cannon D.M., Neumeister A., Zarate C.A., Jr, Drevets W.C. Prefrontal cortical abnormalities in currently depressed versus currently remitted patients with major depressive disorder. Neuroimage. 2011;54(4):2643–2651. doi: 10.1016/j.neuroimage.2010.11.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Lai T., Payne M.E., Byrum C.E., Steffens D.C., Krishnan K.R. Reduction of orbital frontal cortex volume in geriatric depression. Biol. Psychiatry. 2000;48(10):971–975. doi: 10.1016/S0006-3223(00)01042-8. [DOI] [PubMed] [Google Scholar]
  • 45.Drevets W. C., Frank E., Price J. C., Kupfer D. J., Holt D., Greer P. J., Huang Y., Gautier C., Mathis C. PET imaging of serotonin 1A receptor binding in depression. Biol. Psychiatry. 1999;46(10):1375–87. doi: 10.1016/s0006-3223(99)00189-4. [DOI] [PubMed] [Google Scholar]
  • 46.Hirayasu Y., Shenton M.E., Salisbury D.F., Kwon J.S., Wible C.G., Fischer I.A., Yurgelun-Todd D., Zarate C., Kikinis R., Jolesz F.A., McCarley R.W. Subgenual cingulate cortex volume in first-episode psychosis. Am. J. Psychiatry. 1999;156(7):1091–1093. doi: 10.1176/ajp.156.7.1091. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Brambilla P., Nicoletti M.A., Harenski K., Sassi R.B., Mallinger A.G., Frank E., Kupfer D.J., Keshavan M.S., Soares J.C. Anatomical MRI study of subgenual prefrontal cortex in bipolar and unipolar subjects. Neuropsychopharmacology. 2002;27(5):792–799. doi: 10.1016/S0893-133X(02)00352-4. [DOI] [PubMed] [Google Scholar]
  • 48.Kong L., Wu F., Tang Y., Ren L., Kong D., Liu Y., Xu K., Wang F. Frontal-subcortical volumetric deficits in single episode, medication-naïve depressed patients and the effects of 8 weeks fluoxetine treatment: a VBM-DARTEL study. PLoS One. 2014;9(1):e79055. doi: 10.1371/journal.pone.0079055. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Frodl T.S., Koutsouleris N., Bottlender R., Born C., Jäger M., Scupin I., Reiser M., Möller H.J., Meisenzahl E.M. Depression-related variation in brain morphology over 3 years: effects of stress? Arch. Gen. Psychiatry. 2008;65(10):1156–1165. doi: 10.1001/archpsyc.65.10.1156. [DOI] [PubMed] [Google Scholar]
  • 50.Shah P.J., Ebmeier K.P., Glabus M.F., Goodwin G.M. Cortical grey matter reductions associated with treatment-resistant chronic unipolar depression. Controlled magnetic resonance imaging study. Br. J. Psychiatry. 1998;172:527–532. doi: 10.1192/bjp.172.6.527. [DOI] [PubMed] [Google Scholar]
  • 51.Bremner J.D., Narayan M., Anderson E.R., Staib L.H., Miller H.L., Charney D.S. Hippocampal volume reduction in major depression. Am. J. Psychiatry. 2000;157(1):115–118. doi: 10.1176/ajp.157.1.115. [DOI] [PubMed] [Google Scholar]
  • 52.Pantel J., Schröder J., Essig M., Popp D., Dech H., Knopp M.V., Schad L.R., Eysenbach K., Backenstrass M., Friedlinger M. Quantitative magnetic resonance imaging in geriatric depression and primary degenerative dementia. J. Affect. Disord. 1997;42(1):69–83. doi: 10.1016/S0165-0327(96)00105-X. [DOI] [PubMed] [Google Scholar]
  • 53.Caetano S.C., Hatch J.P., Brambilla P., Sassi R.B., Nicoletti M., Mallinger A.G., Frank E., Kupfer D.J., Keshavan M.S., Soares J.C. Anatomical MRI study of hippocampus and amygdala in patients with current and remitted major depression. Psychiatry Res. 2004;132(2):141–147. doi: 10.1016/j.pscychresns.2004.08.002. [DOI] [PubMed] [Google Scholar]
  • 54.van Eijndhoven P., van Wingen G., Katzenbauer M., Groen W., Tepest R., Fernández G., Buitelaar J., Tendolkar I. Paralimbic cortical thickness in first-episode depression: evidence for trait-related differences in mood regulation. Am. J. Psychiatry. 2013;170(12):1477–1486. doi: 10.1176/appi.ajp.2013.12121504. [DOI] [PubMed] [Google Scholar]
  • 55.Fallucca E., MacMaster F.P., Haddad J., Easter P., Dick R., May G., Stanley J.A., Rix C., Rosenberg D.R. Distinguishing between major depressive disorder and obsessive-compulsive disorder in children by measuring regional cortical thickness. Arch. Gen. Psychiatry. 2011;68(5):527–533. doi: 10.1001/archgenpsychiatry.2011.36. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Krishnan K.R., McDonald W.M., Tupler L.A. Neuropathology in affective illness. Am. J. Psychiatry. 1993;150(10):1568–1569. doi: 10.1176/ajp.150.10.1568b. [DOI] [PubMed] [Google Scholar]
  • 57.Parashos I.A., Tupler L.A., Blitchington T., Krishnan K.R. Magnetic-resonance morphometry in patients with major depression. Psychiatry Res. 1998;84(1):7–15. doi: 10.1016/S0925-4927(98)00042-0. [DOI] [PubMed] [Google Scholar]
  • 58.Greenwald B.S., Kramer-Ginsberg E., Krishnan R.R., Ashtari M., Aupperle P.M., Patel M. MRI signal hyperintensities in geriatric depression. Am. J. Psychiatry. 1996;153(9):1212–1215. doi: 10.1176/ajp.153.9.1212. [DOI] [PubMed] [Google Scholar]
  • 59.Iidaka T., Nakajima T., Kawamoto K., Fukuda H., Suzuki Y., Maehara T., Shiraishi H. Signal hyperintensities on brain magnetic resonance imaging in elderly depressed patients. Eur. Neurol. 1996;36(5):293–299. doi: 10.1159/000117275. [DOI] [PubMed] [Google Scholar]
  • 60.Papakostas G.I., Iosifescu D.V., Renshaw P.F., Lyoo I.K., Lee H.K., Alpert J.E., Nierenberg A.A., Fava M. Brain MRI white matter hyperintensities and one-carbon cycle metabolism in non-geriatric outpatients with major depressive disorder (Part II). Psychiatry Res. 2005;140(3):301–307. doi: 10.1016/j.pscychresns.2005.09.001. [DOI] [PubMed] [Google Scholar]
  • 61.Sneed J.R., Culang-Reinlieb M.E., Brickman A.M., Gunning-Dixon F.M., Johnert L., Garcon E., Roose S.P. MRI signal hyperintensities and failure to remit following antidepressant treatment. J. Affect. Disord. 2011;135(1-3):315–320. doi: 10.1016/j.jad.2011.06.052. [DOI] [PubMed] [Google Scholar]
  • 62.Sheline Y.I., Pieper C.F., Barch D.M., Welsh-Bohmer K., McKinstry R.C., MacFall J.R., D’Angelo G., Garcia K.S., Gersing K., Wilkins C., Taylor W., Steffens D.C., Krishnan R.R., Doraiswamy P.M. Support for the vascular depression hypothesis in late-life depression: results of a 2-site, prospective, antidepressant treatment trial. Arch. Gen. Psychiatry. 2010;67(3):277–285. doi: 10.1001/archgenpsychiatry.2009.204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Gunning-Dixon F.M., Walton M., Cheng J., Acuna J., Klimstra S., Zimmerman M.E., Brickman A.M., Hoptman M.J., Young R.C., Alexopoulos G.S. MRI signal hyperintensities and treatment remission of geriatric depression. J. Affect. Disord. 2010;126(3):395–401. doi: 10.1016/j.jad.2010.04.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Krishnan K.R., McDonald W.M., Doraiswamy P.M., Tupler L.A., Husain M., Boyko O.B., Figiel G.S., Ellinwood E.H., Jr Neuroanatomical substrates of depression in the elderly. 1993. [DOI] [PubMed]
  • 65.Caetano S.C., Sassi R., Brambilla P., Harenski K., Nicoletti M., Mallinger A.G., Frank E., Kupfer D.J., Keshavan M.S., Soares J.C. MRI study of thalamic volumes in bipolar and unipolar patients and healthy individuals. Psychiatry Res. 2001;108(3):161–168. doi: 10.1016/S0925-4927(01)00123-8. [DOI] [PubMed] [Google Scholar]
  • 66.Colla M., Kronenberg G., Deuschle M., Meichel K., Hagen T., Bohrer M., Heuser I. Hippocampal volume reduction and HPA-system activity in major depression. J. Psychiatr. Res. 2007;41(7):553–560. doi: 10.1016/j.jpsychires.2006.06.011. [DOI] [PubMed] [Google Scholar]
  • 67.Kronmüller K.T., Pantel J., Götz B., Köhler S., Victor D., Mundt C., Magnotta V.A., Giesel F., Essig M., Schröder J. Life events and hippocampal volume in first-episode major depression. J. Affect. Disord. 2008;110(3):241–247. doi: 10.1016/j.jad.2008.01.022. [DOI] [PubMed] [Google Scholar]
  • 68.Vythilingam M., Vermetten E., Anderson G. M., Luckenbaugh D., Anderson E. R., Snow J., Staib L. H., Charney D. S., Bremner J. D. Hippocampal volume, memory, and cortisol status in major depressive disorder: effects of treatment. 2004. [DOI] [PubMed]
  • 69.Bearden C.E., Thompson P.M., Avedissian C., Klunder A.D., Nicoletti M., Dierschke N., Brambilla P., Soares J.C. Altered hippocampal morphology in unmedicated patients with major depressive illness. ASN Neuro. 2009;1(4):e00020. doi: 10.1042/AN20090026. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Frodl T., Meisenzahl E.M., Zetzsche T., Höhne T., Banac S., Schorr C., Jäger M., Leinsinger G., Bottlender R., Reiser M., Möller H.J. Hippocampal and amygdala changes in patients with major depressive disorder and healthy controls during a 1-year follow-up. J. Clin. Psychiatry. 2004;65(4):492–499. doi: 10.4088/JCP.v65n0407. [DOI] [PubMed] [Google Scholar]
  • 71.Sheline Y.I., Gado M.H., Price J.L. Amygdala core nuclei volumes are decreased in recurrent major depression. Neuroreport. 1998;9(9):2023–2028. doi: 10.1097/00001756-199806220-00021. [DOI] [PubMed] [Google Scholar]
  • 72.Sheline Y.I., Sanghavi M., Mintun M.A., Gado M.H. Depression duration but not age predicts hippocampal volume loss in medically healthy women with recurrent major depression. J. Neurosci. 1999;19(12):5034–5043. doi: 10.1523/JNEUROSCI.19-12-05034.1999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73.Hickie I.B., Naismith S.L., Ward P.B., Scott E.M., Mitchell P.B., Schofield P.R., Scimone A., Wilhelm K., Parker G. Serotonin transporter gene status predicts caudate nucleus but not amygdala or hippocampal volumes in older persons with major depression. J. Affect. Disord. 2007;98(1-2):137–142. doi: 10.1016/j.jad.2006.07.010. [DOI] [PubMed] [Google Scholar]
  • 74.Keller J., Shen L., Gomez R.G., Garrett A., Solvason H.B., Reiss A., Schatzberg A.F. Hippocampal and amygdalar volumes in psychotic and nonpsychotic unipolar depression. Am. J. Psychiatry. 2008;165(7):872–880. doi: 10.1176/appi.ajp.2008.07081257. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 75.Lorenzetti V., Allen N.B., Fornito A., Yücel M. Structural brain abnormalities in major depressive disorder: a selective review of recent MRI studies. J. Affect. Disord. 2009;117(1-2):1–17. doi: 10.1016/j.jad.2008.11.021. [DOI] [PubMed] [Google Scholar]
  • 76.Tang Y., Wang F., Xie G., Liu J., Li L., Su L., Liu Y., Hu X., He Z., Blumberg H.P. Reduced ventral anterior cingulate and amygdala volumes in medication-naïve females with major depressive disorder: A voxel-based morphometric magnetic resonance imaging study. Psychiatry Res. 2007;156(1):83–86. doi: 10.1016/j.pscychresns.2007.03.005. [DOI] [PubMed] [Google Scholar]
  • 77.Kronenberg G., Tebartz van Elst L., Regen F., Deuschle M., Heuser I., Colla M. Reduced amygdala volume in newly admitted psychiatric in-patients with unipolar major depression. J. Psychiatr. Res. 2009;43(13):1112–1117. doi: 10.1016/j.jpsychires.2009.03.007. [DOI] [PubMed] [Google Scholar]
  • 78.Hastings R.S., Parsey R.V., Oquendo M.A., Arango V., Mann J.J. Volumetric analysis of the prefrontal cortex, amygdala, and hippocampus in major depression. Neuropsychopharmacology. 2004;29(5):952–959. doi: 10.1038/sj.npp.1300371. [DOI] [PubMed] [Google Scholar]
  • 79.Mervaala E., Föhr J., Könönen M., Valkonen-Korhonen M., Vainio P., Partanen K., Partanen J., Tiihonen J., Viinamäki H., Karjalainen A.K., Lehtonen J. Quantitative MRI of the hippocampus and amygdala in severe depression. Psychol. Med. 2000;30(1):117–125. doi: 10.1017/S0033291799001567. [DOI] [PubMed] [Google Scholar]
  • 80.Munn M.A., Alexopoulos J., Nishino T., Babb C.M., Flake L.A., Singer T., Ratnanather J.T., Huang H., Todd R.D., Miller M.I., Botteron K.N. Amygdala volume analysis in female twins with major depression. Biol. Psychiatry. 2007;62(5):415–422. doi: 10.1016/j.biopsych.2006.11.031. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81.MacMaster F.P., Leslie R., Rosenberg D.R., Kusumakar V. Pituitary gland volume in adolescent and young adult bipolar and unipolar depression. Bipolar Disord. 2008;10(1):101–104. doi: 10.1111/j.1399-5618.2008.00476.x. [DOI] [PubMed] [Google Scholar]
  • 82.Monkul E.S., Hatch J.P., Nicoletti M.A., Spence S., Brambilla P., Lacerda A.L., Sassi R.B., Mallinger A.G., Keshavan M.S., Soares J.C. Fronto-limbic brain structures in suicidal and non-suicidal female patients with major depressive disorder. Mol. Psychiatry. 2007;12(4):360–366. doi: 10.1038/sj.mp.4001919. [DOI] [PubMed] [Google Scholar]
  • 83.van Eijndhoven P., van Wingen G., van Oijen K., Rijpkema M., Goraj B., Jan Verkes R., Oude Voshaar R., Fernández G., Buitelaar J., Tendolkar I. Amygdala volume marks the acute state in the early course of depression. Biol. Psychiatry. 2009;65(9):812–818. doi: 10.1016/j.biopsych.2008.10.027. [DOI] [PubMed] [Google Scholar]
  • 84.Lorenzetti V., Allen N.B., Whittle S., Yücel M. Amygdala volumes in a sample of current depressed and remitted depressed patients and healthy controls. J. Affect. Disord. 2010;120(1-3):112–119. doi: 10.1016/j.jad.2009.04.021. [DOI] [PubMed] [Google Scholar]
  • 85.Tebartz van Elst L., Woermann F., Lemieux L., Trimble M. R. 2000. [DOI] [PubMed]
  • 86.Frodl T., Meisenzahl E.M., Zetzsche T., Born C., Jäger M., Groll C., Bottlender R., Leinsinger G., Möller H.J. Larger amygdala volumes in first depressive episode as compared to recurrent major depression and healthy control subjects. Biol. Psychiatry. 2003;53(4):338–344. doi: 10.1016/S0006-3223(02)01474-9. [DOI] [PubMed] [Google Scholar]
  • 87.Weniger G., Lange C., Irle E. Abnormal size of the amygdala predicts impaired emotional memory in major depressive disorder. J. Affect. Disord. 2006;94(1-3):219–229. doi: 10.1016/j.jad.2006.04.017. [DOI] [PubMed] [Google Scholar]
  • 88.Lange C., Irle E. Enlarged amygdala volume and reduced hippocampal volume in young women with major depression. Psychol. Med. 2004;34(6):1059–1064. doi: 10.1017/S0033291703001806. [DOI] [PubMed] [Google Scholar]
  • 89.Bellani M., Baiano M., Brambilla P. Brain anatomy of major depression II. Focus on amygdala. Epidemiol. Psychiatr. Sci. 2011;20(1):33–36. doi: 10.1017/S2045796011000096. [DOI] [PubMed] [Google Scholar]
  • 90.Arnone D., McIntosh A.M., Tan G.M., Ebmeier K.P. Meta-analysis of magnetic resonance imaging studies of the corpus callosum in schizophrenia. Schizophr. Res. 2008;101(1-3):124–132. doi: 10.1016/j.schres.2008.01.005. [DOI] [PubMed] [Google Scholar]
  • 91.Machino A., Kunisato Y., Matsumoto T., Yoshimura S., Ueda K., Yamawaki Y., Okada G., Okamoto Y., Yamawaki S. 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. doi: 10.1016/j.jad.2014.06.030. [DOI] [PubMed] [Google Scholar]
  • 92.Shah S.A., Doraiswamy P.M., Husain M.M., Escalona P.R., Na C., Figiel G.S., Patterson L.J., Ellinwood E.H., Jr, McDonald W.M., Boyko O.B., et al. Posterior fossa abnormalities in major depression: a controlled magnetic resonance imaging study. Acta Psychiatr. Scand. 1992;85(6):474–479. doi: 10.1111/j.1600-0447.1992.tb03214.x. [DOI] [PubMed] [Google Scholar]
  • 93.Schlegel S., Kretzschmar K. Computed tomography in affective disorders. Part I. Ventricular and sulcal measurements. Biol. Psychiatry. 1987;22(1):4–14. doi: 10.1016/0006-3223(87)90124-7. [DOI] [PubMed] [Google Scholar]
  • 94.Beats B., Levy R., Förstl H. Ventricular enlargement and caudate hyperdensity in elderly depressives. Biol. Psychiatry. 1991;30(5):452–458. doi: 10.1016/0006-3223(91)90306-7. [DOI] [PubMed] [Google Scholar]
  • 95.Rabins P.V., Pearlson G.D., Aylward E., Kumar A.J., Dowell K. Cortical magnetic resonance imaging changes in elderly inpatients with major depression. Am. J. Psychiatry. 1991;148(5):617–620. doi: 10.1176/ajp.148.5.617. [DOI] [PubMed] [Google Scholar]
  • 96.Baumann B., Bornschlegl C., Krell D., Bogerts B. Changes in CSF spaces differ in endogenous and neurotic depression. A planimetric CT scan study. J. Affect. Disord. 1997;45(3):179–188. doi: 10.1016/S0165-0327(97)00073-6. [DOI] [PubMed] [Google Scholar]
  • 97.Scott M.L., Golden C.J., Ruedrich S.L., Bishop R.J. Ventricular enlargement in major depression. Psychiatry Res. 1983;8(2):91–93. doi: 10.1016/0165-1781(83)90095-1. [DOI] [PubMed] [Google Scholar]
  • 98.Shima S., Shikano T., Kitamura T., Masuda Y., Tsukumo T., Kanba S., Asai M. Depression and ventricular enlargement. Acta Psychiatr. Scand. 1984;70(3):275–277. doi: 10.1111/j.1600-0447.1984.tb01208.x. [DOI] [PubMed] [Google Scholar]
  • 99.Dolan R.J., Calloway S.P., Mann A.H. Cerebral ventricular size in depressed subjects. Psychol. Med. 1985;15(4):873–878. doi: 10.1017/S0033291700005110. [DOI] [PubMed] [Google Scholar]
  • 100.Andreasen N.C., Swayze V., II, Flaum M., Alliger R., Cohen G. Ventricular abnormalities in affective disorder: clinical and demographic correlates. Am. J. Psychiatry. 1990;147(7):893–900. doi: 10.1176/ajp.147.7.893. [DOI] [PubMed] [Google Scholar]
  • 101.Wurthmann C., Bogerts B., Falkai P. Brain morphology assessed by computed tomography in patients with geriatric depression, patients with degenerative dementia, and normal control subjects. Psychiatry Res. 1995;61(2):103–111. doi: 10.1016/0925-4927(95)02592-L. [DOI] [PubMed] [Google Scholar]
  • 102.Weinberger D. R., DeLisi L. E., Perman G. P., Targum S., Wyatt R. J. Computed tomography in schizophreniform disorder and other acute psychiatric disorders. 1982. [DOI] [PubMed]
  • 103.Rossi A., Stratta P., di Michele V., Bolino F., Nistico R., de Leonardis R., Sabatini M.D., Casacchia M. A computerized tomographic study in patients with depressive disorder: a comparison with schizophrenic patients and controls. Acta Psychiatr. Belg. 1989;89(1-2):56–61. [PubMed] [Google Scholar]
  • 104.Abas M.A., Sahakian B.J., Levy R. Neuropsychological deficits and CT scan changes in elderly depressives. Psychol. Med. 1990;20(3):507–520. doi: 10.1017/S0033291700017025. [DOI] [PubMed] [Google Scholar]
  • 105.Lesser I.M., Miller B.L., Boone K.B., Hill-Gutierrez E., Mehringer C.M., Wong K., Mena I. Brain injury and cognitive function in late-onset psychotic depression. J. Neuropsychiatry Clin. Neurosci. 1991;3(1):33–40. doi: 10.1176/jnp.3.1.33. [DOI] [PubMed] [Google Scholar]
  • 106.Van den Bossche B., Maes M., Brussaard C., Schotte C., Cosyns P., De Moor J., De Schepper A. Computed tomography of the brain in unipolar depression. J. Affect. Disord. 1991;21(1):67–74. doi: 10.1016/0165-0327(91)90020-S. [DOI] [PubMed] [Google Scholar]
  • 107.Wu J.C., Buchsbaum M.S., Johnson J.C., Hershey T.G., Wagner E.A., Teng C., Lottenberg S. Magnetic resonance and positron emission tomography imaging of the corpus callosum: size, shape and metabolic rate in unipolar depression. J. Affect. Disord. 1993;28(1):15–25. doi: 10.1016/0165-0327(93)90073-S. [DOI] [PubMed] [Google Scholar]
  • 108.Lacerda A.L., Nicoletti M.A., Brambilla P., Sassi R.B., Mallinger A.G., Frank E., Kupfer D.J., Keshavan M.S., Soares J.C. Anatomical MRI study of basal ganglia in major depressive disorder. Psychiatry Res. 2003;124(3):129–140. doi: 10.1016/S0925-4927(03)00123-9. [DOI] [PubMed] [Google Scholar]
  • 109.Krishnan K.R., Doraiswamy P.M., Lurie S.N., Figiel G.S., Husain M.M., Boyko O.B., Ellinwood E.H., Jr, Nemeroff C.B. Pituitary size in depression. J. Clin. Endocrinol. Metab. 1991;72(2):256–259. doi: 10.1210/jcem-72-2-256. [DOI] [PubMed] [Google Scholar]
  • 110.Sassi R.B., Nicoletti M., Brambilla P., Harenski K., Mallinger A.G., Frank E., Kupfer D.J., Keshavan M.S., Soares J.C. Decreased pituitary volume in patients with bipolar disorder. Biol. Psychiatry. 2001;50(4):271–280. doi: 10.1016/S0006-3223(01)01086-1. [DOI] [PubMed] [Google Scholar]
  • 111.Schwartz P.J., Loe J.A., Bash C.N., Bove K., Turner E.H., Frank J.A., Wehr T.A., Rosenthal N.E. Seasonality and pituitary volume. Psychiatry Res. 1997;74(3):151–157. doi: 10.1016/S0925-4927(97)00015-2. [DOI] [PubMed] [Google Scholar]
  • 112.Pariante C.M., Dazzan P., Danese A., Morgan K.D., Brudaglio F., Morgan C., Fearon P., Orr K., Hutchinson G., Pantelis C., Velakoulis D., Jones P.B., Leff J., Murray R.M. Increased pituitary volume in antipsychotic-free and antipsychotic-treated patients of the AEsop first-onset psychosis study. Neuropsychopharmacology. 2005;30(10):1923–1931. doi: 10.1038/sj.npp.1300766. [DOI] [PubMed] [Google Scholar]
  • 113.Berton O., Nestler E.J. New approaches to antidepressant drug discovery: beyond monoamines. Nat. Rev. Neurosci. 2006;7(2):137–151. doi: 10.1038/nrn1846. [DOI] [PubMed] [Google Scholar]
  • 114.Vakili K., Pillay S.S., Lafer B., Fava M., Renshaw P.F., Bonello-Cintron C.M., Yurgelun-Todd D.A. Hippocampal volume in primary unipolar major depression: a magnetic resonance imaging study. Biol. Psychiatry. 2000;47(12):1087–1090. doi: 10.1016/S0006-3223(99)00296-6. [DOI] [PubMed] [Google Scholar]
  • 115.Saylam C., Uçerler H., Kitiş O., Ozand E., Gönül A.S. Reduced hippocampal volume in drug-free depressed patients. Surg. Radiol. Anat. 2006;28(1):82–87. doi: 10.1007/s00276-005-0050-3. [DOI] [PubMed] [Google Scholar]
  • 116.Hickie I., Naismith S., Ward P.B., Turner K., Scott E., Mitchell P., Wilhelm K., Parker G. Reduced hippocampal volumes and memory loss in patients with early- and late-onset depression. Br. J. Psychiatry. 2005;186:197–202. doi: 10.1192/bjp.186.3.197. [DOI] [PubMed] [Google Scholar]
  • 117.Lloyd A.J., Ferrier I.N., Barber R., Gholkar A., Young A.H., O’Brien J.T. Hippocampal volume change in depression: late- and early-onset illness compared. Br. J. Psychiatry. 2004;184:488–495. doi: 10.1192/bjp.184.6.488. [DOI] [PubMed] [Google Scholar]
  • 118.Taylor J.L., Blanton R.E., Levitt J.G., Caplan R., Nobel D., Toga A.W. Superior temporal gyrus differences in childhood-onset schizophrenia. Schizophr. Res. 2005;73(2-3):235–241. doi: 10.1016/j.schres.2004.07.023. [DOI] [PubMed] [Google Scholar]
  • 119.Hsieh M.H., McQuoid D.R., Levy R.M., Payne M.E., MacFall J.R., Steffens D.C. Hippocampal volume and antidepressant response in geriatric depression. Int. J. Geriatr. Psychiatry. 2002;17(6):519–525. doi: 10.1002/gps.611. [DOI] [PubMed] [Google Scholar]
  • 120.Neumeister A., Wood S., Bonne O., Nugent A. C., Luckenbaugh D. A., Young T., Bain E. E., Charney D. S., Drevets W. C. Reduced hippocampal volume in unmedicated, remitted patients with major depression versus control subjects. 2005. [DOI] [PubMed]
  • 121.Sheline Y.I. Neuroimaging studies of mood disorder effects on the brain. Biol. Psychiatry. 2003;54(3):338–352. doi: 10.1016/S0006-3223(03)00347-0. [DOI] [PubMed] [Google Scholar]
  • 122.Vythilingam M., Heim C., Newport J., Miller A.H., Anderson E., Bronen R., Brummer M., Staib L., Vermetten E., Charney D.S., Nemeroff C.B., Bremner J.D. Childhood trauma associated with smaller hippocampal volume in women with major depression. Am. J. Psychiatry. 2002;159(12):2072–2080. doi: 10.1176/appi.ajp.159.12.2072. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 123.Sheline Y.I. Hippocampal atrophy in major depression: a result of depression-induced neurotoxicity? Mol. Psychiatry. 1996;1(4):298–299. [PubMed] [Google Scholar]
  • 124.MacMaster F.P., Kusumakar V. Hippocampal volume in early onset depression. BMC Med. 2004;2:2. doi: 10.1186/1741-7015-2-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 125.MacQueen G.M., Campbell S., McEwen B.S., Macdonald K., Amano S., Joffe R.T., Nahmias C., Young L.T. Course of illness, hippocampal function, and hippocampal volume in major depression. Proc. Natl. Acad. Sci. USA. 2003;100(3):1387–1392. doi: 10.1073/pnas.0337481100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 126.Frodl T., Schaub A., Banac S., Charypar M., Jäger M., Kümmler P., Bottlender R., Zetzsche T., Born C., Leinsinger G., Reiser M., Möller H.J., Meisenzahl E.M. Reduced hippocampal volume correlates with executive dysfunctioning in major depression. J. Psychiatry Neurosci. 2006;31(5):316–323. [PMC free article] [PubMed] [Google Scholar]
  • 127.MacMillan S., Szeszko P.R., Moore G.J., Madden R., Lorch E., Ivey J., Banerjee S.P., Rosenberg D.R. Increased amygdala: hippocampal volume ratios associated with severity of anxiety in pediatric major depression. J. Child Adolesc. Psychopharmacol. 2003;13(1):65–73. doi: 10.1089/104454603321666207. [DOI] [PubMed] [Google Scholar]
  • 128.Pillay S.S., Yurgelun-Todd D.A., Bonello C.M., Lafer B., Fava M., Renshaw P.F. A quantitative magnetic resonance imaging study of cerebral and cerebellar gray matter volume in primary unipolar major depression: relationship to treatment response and clinical severity. Biol. Psychiatry. 1997;42(2):79–84. doi: 10.1016/S0006-3223(96)00335-6. [DOI] [PubMed] [Google Scholar]
  • 129.Pillay S.S., Renshaw P.F., Bonello C.M., Lafer B.C., Fava M., Yurgelun-Todd D. A quantitative magnetic resonance imaging study of caudate and lenticular nucleus gray matter volume in primary unipolar major depression: relationship to treatment response and clinical severity. Psychiatry Res. 1998;84(2-3):61–74. doi: 10.1016/S0925-4927(98)00048-1. [DOI] [PubMed] [Google Scholar]
  • 130.Hankin B.L., Abramson L.Y., Moffitt T.E., Silva P.A., McGee R., Angell K.E. Development of depression from preadolescence to young adulthood: emerging gender differences in a 10-year longitudinal study. J. Abnorm. Psychol. 1998;107(1):128–140. doi: 10.1037/0021-843X.107.1.128. [DOI] [PubMed] [Google Scholar]
  • 131.Sheline Y. I., Disabato B. M., Hranilovich J., Morris C., D'Angelo G., Pieper C., Toffanin T., Taylor W. D., MacFall J. R., Wilkins C., Barch D. M., Welsh-Bohmer K. A., Steffens D. C., Krishnan R. R., Doraiswamy P. M. Treatment course with antidepressant therapy in late-life depression. 2012. [DOI] [PMC free article] [PubMed]
  • 132.MacQueen G. M., Yucel K., Taylor V. H., Macdonald K., Joffe R. Posterior Hippocampal Volumes Are Associated with Remission Rates in Patients with Major Depressive Disorder. 2008. [DOI] [PubMed]
  • 133.Yucel K., McKinnon M., Chahal R., Taylor V., Macdonald K., Joffe R., MacQueen G. Increased subgenual prefrontal cortex size in remitted patients with major depressive disorder. 2009. [DOI] [PubMed]
  • 134.Costafreda S. G., Chu C., Ashburner J., Fu C. H. Prognostic and diagnostic potential of the structural neuroanatomy of depression. 2009. [DOI] [PMC free article] [PubMed]
  • 135.Smith R., Chen K., Baxter L., Fort C., Lane R.D. Antidepressant effects of sertraline associated with volume increases in dorsolateral prefrontal cortex. J. Affect. Disord. 2013;146(3):414–419. doi: 10.1016/j.jad.2012.07.029. [DOI] [PubMed] [Google Scholar]
  • 136.Gunning F.M., Cheng J., Murphy C.F., Kanellopoulos D., Acuna J., Hoptman M.J., Klimstra S., Morimoto S., Weinberg J., Alexopoulos G.S. Anterior cingulate cortical volumes and treatment remission of geriatric depression. Int. J. Geriatr. Psychiatry. 2009;24(8):829–836. doi: 10.1002/gps.2290. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 137.Lai C.H. Duloxetine-related growth of putamen and brainstem in first-onset drug-naive major depressive disorder with panic disorder: a case series. J. Neuropsychiatry Clin. Neurosci. 2011;23(2):E40–E41. doi: 10.1176/jnp.23.2.jnpe40. [DOI] [PubMed] [Google Scholar]
  • 138.Pizzagalli D.A., Oakes T.R., Fox A.S., Chung M.K., Larson C.L., Abercrombie H.C., Schaefer S.M., Benca R.M., Davidson R.J. Functional but not structural subgenual prefrontal cortex abnormalities in melancholia. Mol. Psychiatry. 2004;9(4):325–, 393-405. doi: 10.1038/sj.mp.4001501. [DOI] [PubMed] [Google Scholar]
  • 139.Alexopoulos G.S., Murphy C.F., Gunning-Dixon F.M., Latoussakis V., Kanellopoulos D., Klimstra S., Lim K.O., Hoptman M.J. Microstructural white matter abnormalities and remission of geriatric depression. Am. J. Psychiatry. 2008;165(2):238–244. doi: 10.1176/appi.ajp.2007.07050744. [DOI] [PubMed] [Google Scholar]
  • 140.Fossati P., Radtchenko A., Boyer P. Neuroplasticity: from MRI to depressive symptoms. Eur. Neuropsychopharmacol. 2004;14(Suppl. 5):S503–S510. doi: 10.1016/j.euroneuro.2004.09.001. [DOI] [PubMed] [Google Scholar]
  • 141.Ohira K., Takeuchi R., Shoji H., Miyakawa T. Fluoxetine-induced cortical adult neurogenesis. Neuropsychopharmacology. 2013;38(6):909–920. doi: 10.1038/npp.2013.2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 142.Kraus C., Ganger S., Losak J., Hahn A., Savli M., Kranz G. S., Baldinger P., Windischberger C., Kasper S., Lanzenberger R. Gray matter and intrinsic network changes in the posterior cingulate cortex after selective serotonin reuptake inhibitor intake. 2014. [DOI] [PubMed]
  • 143.Brody A.L., Saxena S., Mandelkern M.A., Fairbanks L.A., Ho M.L., Baxter L.R. Brain metabolic changes associated with symptom factor improvement in major depressive disorder. Biol. Psychiatry. 2001;50(3):171–178. doi: 10.1016/S0006-3223(01)01117-9. [DOI] [PubMed] [Google Scholar]
  • 144.Brody A.L., Saxena S., Silverman D.H., Alborzian S., Fairbanks L.A., Phelps M.E., Huang S.C., Wu H.M., Maidment K., Baxter L.R., Jr Brain metabolic changes in major depressive disorder from pre- to post-treatment with paroxetine. Psychiatry Res. 1999;91(3):127–139. doi: 10.1016/S0925-4927(99)00034-7. [DOI] [PubMed] [Google Scholar]
  • 145.Little J.T., Ketter T.A., Kimbrell T.A., Dunn R.T., Benson B.E., Willis M.W., Luckenbaugh D.A., Post R.M. Bupropion and venlafaxine responders differ in pretreatment regional cerebral metabolism in unipolar depression. Biol. Psychiatry. 2005;57(3):220–228. doi: 10.1016/j.biopsych.2004.10.033. [DOI] [PubMed] [Google Scholar]
  • 146.Konarski J.Z., Kennedy S.H., Segal Z.V., Lau M.A., Bieling P.J., McIntyre R.S., Mayberg H.S. Predictors of nonresponse to cognitive behavioural therapy or venlafaxine using glucose metabolism in major depressive disorder. J. Psychiatry Neurosci. 2009;34(3):175–180. [PMC free article] [PubMed] [Google Scholar]
  • 147.Frodl T., Jäger M., Smajstrlova I., Born C., Bottlender R., Palladino T., Reiser M., Möller H.J., Meisenzahl E.M. Effect of hippocampal and amygdala volumes on clinical outcomes in major depression: a 3-year prospective magnetic resonance imaging study. J. Psychiatry Neurosci. 2008;33(5):423–430. [PMC free article] [PubMed] [Google Scholar]
  • 148.Janssen J., Hulshoff Pol H.E., Schnack H.G., Kok R.M., Lampe I.K., de Leeuw F.E., Kahn R.S., Heeren T.J. Cerebral volume measurements and subcortical white matter lesions and short-term treatment response in late life depression. Int. J. Geriatr. Psychiatry. 2007;22(5):468–474. doi: 10.1002/gps.1790. [DOI] [PubMed] [Google Scholar]
  • 149.Lai C.H., Wu Y.T. Duloxetine’s modest short-term influences in subcortical structures of first episode drug-naïve patients with major depressive disorder and panic disorder. Psychiatry Res. 2011;194(2):157–162. doi: 10.1016/j.pscychresns.2011.03.011. [DOI] [PubMed] [Google Scholar]
  • 150.Ostuzzi G., Bighelli I., Carrara B.V., Dusi N., Imperadore G., Lintas C., Nifosì F., Nosè M., Piazza C., Purgato M., Rizzo R., Barbui C. Making the use of psychotropic drugs more rational through the development of GRADE recommendations in specialist mental healthcare. Int. J. Ment. Health Syst. 2013;7(1):14. doi: 10.1186/1752-4458-7-14. [DOI] [PMC free article] [PubMed] [Google Scholar]

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