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 »  Abstract
 » Introduction
 »  Materials and Me...
 » Results
 » Discussion
 » Conclusion
 »  References
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 Table of Contents    
RESEARCH ARTICLE
Year : 2017  |  Volume : 49  |  Issue : 3  |  Page : 236-242
 

The impact of antidepressant treatment on brain-derived neurotrophic factor level: An evidence-based approach through systematic review and meta-analysis


1 Department of Pharmacy Practice, Drug and Poison Information Center, KMCH College of Pharmacy, Coimbatore, Tamil Nadu, India
2 Department of Pharmaceutical Technology, Division of Pharmacology, Jadavpur University, Kolkata, West Bengal, India

Date of Submission27-Oct-2016
Date of Acceptance20-Jul-2017
Date of Web Publication27-Sep-2017

Correspondence Address:
Vijayakumar Arumugam
Manager-Pharmacy Services, Kovai Medical Center and Hospital, Coimbatore - 641 014, Tamil Nadu
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijp.IJP_700_16

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 » Abstract 

Objectives: Antidepressant treatment alters brain-derived neurotrophic factor (BDNF) levels, but it is not well established whether BDNF can be used as a marker to prove the efficacy of antidepressant treatment. The present systematic review and meta-analysis aim at assessing the influence of antidepressant treatment on BDNF level and the Hamilton Depression Rating Scale (HDRS) score, thereby to establish the rationale of utilizing BDNF as a predictive biomarker and HDRS score as an indicator for antidepressant treatment efficacy.
Materials and Methods: Search was conducted in PubMed, Science Direct, and Cochrane databases using the key words “BDNF” and “Depression” and “Antidepressants.” On the basis of the inclusion and exclusion criteria, studies were filtered and finally 6 randomized controlled trials were shortlisted.
Results: Comparison of serum BDNF level before and after antidepressant treatment was performed and the result showed that antidepressant treatment does not significantly affect the BDNF levels (confidence interval [CI]: −0.483 to 0.959; standard mean difference [SMD]: 0.238, P = 0.518). Egger's regression test (P = 0.455) and heterogeneity test (I2 = 88.909%) were done. Similarly, comparison of HDRS scores before and after antidepressant treatment indicated improvement in HDRS score suggesting positive outcome (CI: 1.719 to 3.707; SMD: 2.713, P < 0.001). Egger's regression test (P = 0.1417) and heterogeneity test (I2 = 89.843%) were performed. Publication bias was observed by funnel plot.
Conclusion: Changes in BDNF levels do not occur uniformly for all the antidepressants. Hence, to use BDNF as a biomarker, it needs to be seen whether the same is true for all antidepressants.


Keywords: Antidepressants, brain-derived neurotrophic factor, depression, Hamilton rating scale for depression, meta-analysis


How to cite this article:
Arumugam V, John VS, Augustine N, Jacob T, Joy SM, Sen S, Sen T. The impact of antidepressant treatment on brain-derived neurotrophic factor level: An evidence-based approach through systematic review and meta-analysis. Indian J Pharmacol 2017;49:236-42

How to cite this URL:
Arumugam V, John VS, Augustine N, Jacob T, Joy SM, Sen S, Sen T. The impact of antidepressant treatment on brain-derived neurotrophic factor level: An evidence-based approach through systematic review and meta-analysis. Indian J Pharmacol [serial online] 2017 [cited 2020 Sep 30];49:236-42. Available from: http://www.ijp-online.com/text.asp?2017/49/3/236/215729



 » Introduction Top


Affective disorders have been on the rise worldwide. Current estimates state that around one in ten individuals suffer from depression at least once in a life time, which would require medical treatment.[1] Major depressive disorder (MDD) is a mental disorder characterized by a pervasive and persistent low mood that is accompanied by low self-esteem coupled with a loss of interest or pleasure in normally enjoyable activities.[2] MDD has a significant socioeconomic impact and is associated with a deterioration in the quality of life which raises the susceptibility to several other complex disorders. Depression has a familial disposition and may be aggravated on exposure to severe stressors.[3]

The diagnosis of MDD differs from other complex disorders in that it depends on the verbal communication and other subjective measures.[4] Hence, a biological marker would be greatly desired to confirm the diagnosis of MDD. A biomarker can be used as an indicator that can be measured and assessed to predict normal biological, pathogenic processes, or a pharmacological response to a therapeutic intervention.[4] Biomarkers can be used for predicting treatment course. They may also assist discovery of new antidepressant drugs. MDD treatment is long and very often fails to meet up to the remission criteria. Assessment of cure with the help of a biomarker could reduce ambiguity and give therapy a definite direction and lead to personalized treatment.[5] The biomarkers which could be used for denoting antidepressant treatment response are shown in [Figure 1].[6]
Figure 1: Overview: Biomarkers of antidepressant treatment response. CRH, corticotropin-releasing hormone; CYP = Cytochrome P450, Dex = Dexamethasone, FKBP5 = FK506-binding protein 5, IGF-1 = Insulin-like growth factor 1, QEEG = Quantitative electroencephalographic, rACC = Rostral anterior cingulate cortex, REM = Rapid eye movement, VEGF = Vascular endothelial growth factor

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Brain-derived neurotrophic factor (BDNF) has been extensively studied with regard to antidepressant response prediction. BDNF is a key regulator of synaptic plasticity and plays an important role in cognitive functions.[7] It is a secretory protein and a member of the neurotrophin family of growth factors, which acts in both central and peripheral nervous system. It helps in the survival of existing neurons, and in the growth and differentiation of new neurons and synapses.[8] The neurotrophin hypothesis of depression is associated with reduced brain BDNF levels in depressive states which are alleviated with antidepressant therapy and increase in the BDNF levels.[9] Several studies have reported an association between BDNF and antidepressant response[10],[11],[12],[13] whereas certain others have obtained conflicting results.[14],[15],[16],[17]

Brunoni et al.[18] performed a systematic review and meta-analysis which dealt with the association of major depression and BDNF levels. The meta-analysis was performed to study the correlation between BDNF and depression (prognosis of antidepressant therapy). The results showed that BDNF levels were associated with clinical changes in depression. The study suggested that BDNF could be used together with the depression rating scales to address the efficacy of antidepressant therapy.

The Hamilton Depression Rating Scale (HDRS) is a clinician administered depression assessment scale. It has proven useful for many years as a way of determining a patient's level of depression before, during, and after treatment.[19] In clinical studies of antidepressants, HDRS total score is used for establishing and comparing the treatment efficacy.[20]

Our study is an attempt to identify the association of antidepressants with BDNF levels so as to analyze the use of BDNF as a predictive biomarker for assessing the efficacy of antidepressant therapy. The HDRS was taken as an indicator for antidepressant treatment outcome.


 » Materials and Methods Top


The aim of the study was to analyze the use of BDNF as a predictive biomarker which would be indicative of antidepressant treatment outcome in MDD patients. Hence, we fixed the hypothesis that there is no significant variation in BDNF before and after antidepressant treatment.

Selection criteria

Randomized controlled trials (RCTs) analyzing the pre and post treatment BDNF levels and HDRS score in MDD patients, regardless of age, gender, sample size, and ethnic background were selected. We included only the studies published in English. Plasma or serum BDNF concentration was expressed in picogram/ml. Studies published during 2000–2014 were selected. Review articles and studies assessing BDNF polymorphism, BDNF m-RNA levels, and postmortem studies were excluded from the study.

Search strategy for identification of studies

The study has been done in accordance to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The authors independently conducted the literature search in PubMed, Science Direct, and Cochrane using the key words “BDNF” and “Depression” and “Antidepressants.” Data were extracted independently by six authors (S.S, A.V, V.S.J, N.A, T.J, and S.M.J) and the discrepancies were resolved by consultation with the seventh author (T.S). From the initial search, a total of 566 results were obtained. These results were further screened and segregated on the basis of human studies, year of publication (2000/01/01-2014/12/31), abstracts available, and clinical trials. With these criteria we obtained a total of 285, 281, 258, and 41 studies, respectively. The reference lists of the articles were cross-checked to identify other significant studies. Titles and abstracts of the relevant articles identified were screened for eligibility, and any abstract which was potentially relevant was reviewed in full text. Finally, 6 RCTs that met the criteria were included based on (FAST and PICO) methods. PICO model is a tool which helps organizing and focusing the foreground research question. PICO denotes patient/population, intervention/exposure, comparison and outcome, respectively [Table 1]. Four simple questions can be used to identify if the study is worth reading and using and is called the FAST method. FAST method signifies finding, appraisal, synthesis, and transferability of results. The literature search and trial selection process has been shown in [Figure 2]. All the 6 RCT's[21],[22],[23],[24],[25],[26] addressed the pre and post treatment BDNF levels in MDD patients treated with antidepressants. All the RCT's included in the study were assessed using the Jadad score, which independently assesses the methodological quality of a clinical trial [Table 2].
Table 1: PICO statement

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Figure 2: Diagram of literature search and trial selection process

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Table 2: Design and characteristics of studies included in meta-analysis

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Data extraction and analysis

Details extracted from each trial revealed information about the year of publication, sample size, treatment given, duration of treatment, age, gender, mean and standard deviation (SD) of BDNF level, and HDRS score in pre- and post-treatment patient. The summary of the six RCT's shortlisted for the study has been included in [Table 2].

All the analyses were performed using the software “Comprehensive Meta-Analysis”. In all of the selected studies, BDNF levels and HDRS scores were reported (mean ± SD). From these values, standard mean difference (SMD) with 95% confidence intervals (CI) for individual studies was computed using random effect analyses model. Further, funnel plot was computed and heterogeneity test was also carried out. Tests were considered statistically significant when the P value was found to be <0.05.


 » Results Top


Search results

A total of 566 studies were identified, among which 5 studies were selected based on the criteria mentioned earlier. Among the six articles that were chosen from cross references, only one article met our conditions for inclusion criteria while the remaining five were excluded from the study. Finally, six randomized control trials that met the criteria were included in the systematic review and meta-analysis. A total of 154 subjects with MDD were considered in all the studies. Among the studies, two trials were conducted in Turkey, and remaining studies were conducted in Italy, Japan, Korea, and Germany. Duration of intervention for all the studies was between 5 and 12 weeks. All the selected articles followed the DSM-IV criteria for the diagnosis of MDD. Immunoassay was used to assess the levels of BDNF in all the studies. There were no particular age limits for the patients. Both females and males participated in the studies. Different classes of antidepressants in different doses were used in the selected studies. In all the studies, the changes in BDNF levels and HDRS score (before and after antidepressant treatment) were measured. Among the 6 articles selected for the meta-analysis, 3 of them[22],[23],[24] clearly classified the patients as responders and nonresponders based on the HDRS score and one[26] of them classified the patient group into responders and nonresponders based on both HDRS score as well as BDNF levels. The remaining article[21],[22] did not divide the group based on the response, but they evaluated the change in BDNF levels as well as HDRS scores. Two of the Asian studies by Lee and Kim[24] and Yoshimura et al.[26] and another study by Aydemir et al.[21] suggested a correlation between antidepressant treatment and BDNF concentration where the same was found to be increased. An Italian study conducted by Matrisciano et al.[25] reported that different antidepressant drugs have variable effects on serum BDNF levels. A study on Turkish population conducted by Başterzi et al.[22] did not reveal any significant change, whereas a similar study in Germany by Hellweg et al.[23] indicated a decline of BDNF by 12% in paroxetine-treated patients.

Impact of antidepressant treatment on brain-derived neurotrophic factor level

The data extracted from the articles with regard to BDNF before and after antidepressant treatment is summarized in [Table 3]. Using the random effects model, comparison of serum BDNF levels (before and after antidepressant therapy) was performed, and from these results, it could be suggested that antidepressant therapy is associated with a change in BDNF level, but did not produce any significant impact on it [Figure 3]. (CI: −0.483–0.959; SMD: 0.238, P = 0.518). The effect size was similar in most of these studies. To identify bias, the funnel plot was utilized and possibilities of bias were observed. Further, Egger's regression analysis was performed which indicated the absence of publication bias (P = 0.455). The imputed funnel plot was then computed to identify heterogeneity. This was further confirmed using the heterogeneity test when I2, Q, and P values were found to be 88.909%, 45.081, and 0.001 respectively, thus indicating considerable heterogeneity [Table 4].
Table 3: Data extracted from articles with regard to brain-derived neurotrophic factor before and after antidepressant treatment

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Figure 3: Forest plot that shows the association of derived neurotrophic factor level in major depressive disorder patients before and after antidepressant treatment using random effect model. The pooled standard mean difference is represented by a diamond plot of standard height, with the width indicating 95% confidence interval

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Table 4: Results of heterogeneity study

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Impact of antidepressant treatment on Hamilton Depression Rating Scale score

Data extracted from articles with regard to HDRS score before and after antidepressant treatment is given in [Table 5]. HDRS score before and after antidepressant treatment was also compared using random effect model and the results indicate that the score improves after antidepressant therapy; hence, the HDRS score signifies a positive antidepressant treatment outcome [Figure 4]. (CI: −1.719–3.707; SMD: 2.713, P < 0.001). The effect size was similar in most of these studies. The funnel plot was computed to identify probabilities of any kind of bias. This was further evaluated by Egger's regression analysis which confirmed the absence of publication bias (P = 0.1417) and the asymmetry in the funnel plot may be due to other bias. The imputed funnel plot was obtained to detect heterogeneity. It was further confirmed using the heterogeneity test which gave an I2 value of 89.843%, Q value of 49.228, and (P < 0.001) indicating considerable heterogeneity [Table 4].
Table 5: Data extracted from articles with regard to Hamilton Depression Rating Scale score before and after antidepressant treatment

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Figure 4: Forest plot that shows the association of Hamilton Depression Rating Scale scores in major depressive disorder patients before and after antidepressant treatment using random effect model. The pooled standard mean difference is represented by a diamond plot of standard height, with the width indicating 95% confidence interval

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 » Discussion Top


Several articles have been published which deal with the association of BDNF levels in MDD patients. Studies have suggested that BDNF can be used as a diagnostic marker in depressive patients as the level of BDNF is low in depressive patients and antidepressants increase the BDNF level in accordance to the neurotrophin hypothesis. Inspite of such suggestions from several studies, it is still not applied to clinical practice, as many contradictions exist on this topic. Moreover, none of the studies have proven the usefulness of BDNF as a biomarker to predict the antidepressant treatment efficacy. A previous meta-analysis[18] has reported an association of antidepressant treatment and BDNF levels, which aimed to evaluate whether BDNF levels were correlated with improvement of depression. The study concluded that the BDNF level increased significantly after antidepressant treatment. A significant correlation also existed between changes in BDNF levels and depression scores.

The present meta-analysis was an initiative to identify whether antidepressant therapy is associated with changes in BDNF and if the same can be used as a predictive biomarker with regard to antidepressant treatment efficacy. The change in HDRS score in regard to antidepressant therapy was taken as an indicator for antidepressant treatment outcome. While studying the association between antidepressants and BDNF level, the pooled “P” value (P > 0.05) with 95% CI suggested that the antidepressant treatment does not have a significant impact on BDNF level. The HDRS data analysis indicates a decrease in the severity of depression (P < 0.001). Hence, BDNF levels may not reflect antidepressant therapy outcome, and therefore, this restricts its use as a biomarker.

Certain limitations must be considered while interpreting the results of our studies. The sample size included in the meta-analysis is considerably small. Antidepressant classes, dosage regimen, duration of treatment, and ethnicity of the patient population are varied among the studies. The outcome definitions are also different among the studies.

MDD is a heterogeneous illness for which there is no effective method to assess the treatment response. BDNF regulates synaptic plasticity in neuronal networks involved in depressive behaviors.[27] Even though antidepressants play a vital role in the regulation of BDNF, further information is required regarding the role of specific classes of antidepressants on BDNF concentrations.


 » Conclusion Top


Changes in BDNF levels do not occur uniformly for all the antidepressants. Hence, to use BDNF as a biomarker, it needs to be seen whether the same is true for all antidepressants.

Acknowledgement

The authors are extremely thankful to Dr. Michael Borenstein, Director of Biostat, Inc, New Jersey, USA for providing trial version of Comprehensive Meta-analysis 2.0 software. We extent our sincere thanks to Dr. N. G. Palaniswami (Chairman and Managing Director) and Dr. Thavamani D. Palaniswami, (Trustee) of Kovai Medical Center Research and Educational Trust (Coimbatore) for providing the necessary infrastructural facilities and also for their continuous encouragement.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
 » References Top

1.
Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE, et al. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Arch Gen Psychiatry 2005;62:593-602.  Back to cited text no. 1
    
2.
Barlow D, Durand V. Abnormal Psychology. 1st ed. Belmont, CA: Wadsworth/Thomson Learning; 2007. p. 292-5.  Back to cited text no. 2
    
3.
Pyne JM, Patterson TL, Kaplan RM, Ho S, Gillin JC, Golshan S, et al. Preliminary longitudinal assessment of quality of life in patients with major depression. Psychopharmacol Bull 1997;33:23-9.  Back to cited text no. 3
    
4.
Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework. Clin Pharmacol Ther 2001;69:89-95.  Back to cited text no. 4
    
5.
Rush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: A STAR*D report. Am J Psychiatry 2006;163:1905-17.  Back to cited text no. 5
    
6.
Breitenstein B, Scheuer S, Holsboer F. Are there meaningful biomarkers of treatment response for depression? Drug Discov Today 2014;19:539-61.  Back to cited text no. 6
    
7.
Lu B, Martinowich K. Cell biology of BDNF and its relevance to schizophrenia. Novartis Found Symp 2008;289:119-29.  Back to cited text no. 7
    
8.
Acheson A, Conover JC, Fandl JP, DeChiara TM, Russell M, Thadani A, et al. A BDNF autocrine loop in adult sensory neurons prevents cell death. Nature 1995;374:450-3.  Back to cited text no. 8
    
9.
Tsai S, Hong C, Liou Y. Brain-derived neurotrophic factor and antidepressant action: Another piece of evidence from pharmacogenetics. Future Med 2008;9:1353-8.  Back to cited text no. 9
    
10.
Xu G, Lin K, Rao D, Dang Y, Ouyang H, Mai G, et al. Brain-derived neurotrophic factor gene polymorphism (Val66Met) and the early response to antidepressant in Chinese Han population. Psychiatr Genet 2012;22:214-5.  Back to cited text no. 10
    
11.
Taylor WD, McQuoid DR, Ashley-Koch A, MacFall JR, Bridgers J, Krishnan RR, et al. BDNF val66Met genotype and 6-month remission rates in late-life depression. Pharmacogenomics J 2011;11:146-54.  Back to cited text no. 11
    
12.
Chi MH, Chang HH, Lee SY, Lee IH, Gean PW, Yang YK, et al. Brain derived neurotrophic factor gene polymorphism (Val66Met) and short-term antidepressant response in major depressive disorder. J Affect Disord 2010;126:430-5.  Back to cited text no. 12
    
13.
Zou YF, Wang Y, Liu P, Feng XL, Wang BY, Zang TH, et al. Association of brain-derived neurotrophic factor genetic val66Met polymorphism with severity of depression, efficacy of fluoxetine and its side effects in Chinese major depressive patients. Neuropsychobiology 2010;61:71-8.  Back to cited text no. 13
    
14.
Katsuki A, Yoshimura R, Kishi T, Hori H, Umene-Nakano W, Ikenouchi-Sugita A, et al. Serum levels of brain-derived neurotrophic factor (BDNF), BDNF gene Val66Met polymorphism, or plasma catecholamine metabolites, and response to mirtazapine in Japanese patients with major depressive disorder (MDD). CNS Spectr 2012;17:155-63.  Back to cited text no. 14
    
15.
Yoshimura R, Kishi T, Suzuki A, Umene-Nakano W, Ikenouchi-Sugita A, Hori H, et al. The brain-derived neurotrophic factor (BDNF) polymorphism val66Met is associated with neither serum BDNF level nor response to selective serotonin reuptake inhibitors in depressed Japanese patients. Prog Neuropsychopharmacol Biol Psychiatry 2011;35:1022-5.  Back to cited text no. 15
    
16.
Illi A, Viikki M, Poutanen O, Setälä-Soikkeli E, Nuolivirta T, Kampman O, et al. No support for a role for BDNF gene polymorphisms rs11030101 and rs61888800 in major depressive disorder or antidepressant response in patients of Finnish origin. Psychiatr Genet 2013;23:33-5.  Back to cited text no. 16
    
17.
Lin E, Chen PS, Huang LC, Hsu SY. Association study of a brain-derived neurotrophic-factor polymorphism and short-term antidepressant response in major depressive disorders. Pharmgenomics Pers Med 2008;1:1-6.  Back to cited text no. 17
    
18.
Brunoni AR, Lopes M, Fregni F. A systematic review and meta-analysis of clinical studies on major depression and BDNF levels: Implications for the role of neuroplasticity in depression. Int J Neuropsychopharmacol 2008;11:1169-80.  Back to cited text no. 18
    
19.
Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56-62.  Back to cited text no. 19
    
20.
Faries D, Herrera J, Rayamajhi J, DeBrota D, Demitrack M, Potter WZ, et al. The responsiveness of the Hamilton Depression Rating Scale. J Psychiatr Res 2000;34:3-10.  Back to cited text no. 20
    
21.
Aydemir O, Deveci A, Taneli F. The effect of chronic antidepressant treatment on serum brain-derived neurotrophic factor levels in depressed patients: A preliminary study. Prog Neuropsychopharmacol Biol Psychiatry 2005;29:261-5.  Back to cited text no. 21
    
22.
Başterzi AD, Yazici K, Aslan E, Delialioğlu N, Taşdelen B, Tot Acar S, et al. Effects of fluoxetine and venlafaxine on serum brain derived neurotrophic factor levels in depressed patients. Prog Neuropsychopharmacol Biol Psychiatry 2009;33:281-5.  Back to cited text no. 22
    
23.
Hellweg R, Ziegenhorn A, Heuser I, Deuschle M. Serum concentrations of nerve growth factor and brain-derived neurotrophic factor in depressed patients before and after antidepressant treatment. Pharmacopsychiatry 2008;41:66-71.  Back to cited text no. 23
    
24.
Lee HY, Kim YK. Plasma brain-derived neurotrophic factor as a peripheral marker for the action mechanism of antidepressants. Neuropsychobiology 2008;57:194-9.  Back to cited text no. 24
    
25.
Matrisciano F, Bonaccorso S, Ricciardi A, Scaccianoce S, Panaccione I, Wang L, et al. Changes in BDNF serum levels in patients with major depression disorder (MDD) after 6 months treatment with sertraline, escitalopram, or venlafaxine. J Psychiatr Res 2009;43:247-54.  Back to cited text no. 25
    
26.
Yoshimura R, Mitoma M, Sugita A, Hori H, Okamoto T, Umene W, et al. Effects of paroxetine or milnacipran on serum brain-derived neurotrophic factor in depressed patients. Prog Neuropsychopharmacol Biol Psychiatry 2007;31:1034-7.  Back to cited text no. 26
    
27.
D'Sa C, Duman RS. Antidepressants and neuroplasticity. Bipolar Disord 2002;4:183-94.  Back to cited text no. 27
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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