Brain-derived neurotrophic factor in substance use disorders: A systematic review and meta-analysis

Accepted Manuscript Title: Brain-derived neurotrophic factor in substance use disorders: A systematic review and meta-analysis Authors: Felipe Ornell, Fernanda Hansen, Felipe Barreto Schuch, Fernando Pezzini Rebelatto, Ana Laura Tavares, Juliana Nichterwitz Scherer, Andrei Garziera Valerio, Flavio Pechansky, Felix Henrique Paim Kessler, Lisia von Diemen PII: DOI: Reference:

S0376-8716(18)30725-7 https://doi.org/10.1016/j.drugalcdep.2018.08.036 DAD 7161

To appear in:

Drug and Alcohol Dependence

Received date: Revised date: Accepted date:

15-6-2018 23-8-2018 29-8-2018

Please cite this article as: Ornell F, Hansen F, Schuch FB, Pezzini Rebelatto F, Tavares AL, Scherer JN, Valerio AG, Pechansky F, Paim Kessler FH, von Diemen L, Brain-derived neurotrophic factor in substance use disorders: A systematic review and meta-analysis, Drug and Alcohol Dependence (2018), https://doi.org/10.1016/j.drugalcdep.2018.08.036 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Brain-derived neurotrophic factor in substance use disorders: A systematic review and meta-analysis*

Felipe Ornell a, b, f, Fernanda Hansen a, c, Felipe Barreto Schuch d, e, Fernando Pezzini Rebelatto a

, Ana Laura Tavares a, Juliana Nichterwitz Scherer

a, b

, Andrei Garziera Valerio a, Flavio

Pechansky a, b, Felix Henrique Paim Kessler a, b, Lisia von Diemen a, b a

IP T

Center for Drug and Alcohol Research and Collaborating Center on Alcohol and Drugs,

Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Rua Professor b

SC R

Álvaro Alvim, 400, 90420-020, Porto Alegre, RS, Brazil

Postgraduate Program in Psychiatry and Behavioral Science, Federal University of Rio

Grande do Sul, Porto Alegre, RS, Brazil c

Department of Nutrition, Health Sciences Center, Federal University of Santa Catarina,

U

Florianópolis, SC, Brazil

Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil

e

Universidade La Salle, Porto Alegre, RS, Brazil

M

A

N

d

Correspondence

ED

Felipe Ornell

Center for Drug and Alcohol Research and Collaborating Center on Alcohol and Drugs

PT

Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul

CC E

Rua Professor Álvaro Alvim, 400, 90420-020, Porto Alegre, RS, Brazil Phone: +55 51 33596488

A

[email protected]; [email protected]

Highlights  Patients with active drug use show lower serum brain-derived neurotropic factor (BDNF) than controls.  There is no difference between BDNF levels of abstinence users and controls.

 Alcohol and crack/cocaine users showed lower levels of serum BDNF than controls.  Sex, age, and age of the first use influence BDNF levels in subjects with substance use disorders (SUDs).

Abstract

IP T

Background: Brain-derived neurotrophic factor (BDNF) is associated with several neurodegenerative and psychiatric disorders. It is not clear, however, whether BDNF levels are

SC R

modified in substance use disorders (SUDs).

Methods: We conducted a systematic search of electronic databases to identify studies comparing peripheral plasma or serum BDNF levels in adults with SUDs vs. non-user controls.

U

Forty studies were included in the meta-analysis involving a total of 2238 participants with

N

SUDs and 2574 controls.

A

Results: After trim and fill adjustment, current drug users presented lower serum BDNF levels

M

(SMD= -0.99, 95%CI -1.40 to -0.58, I2=95.9) than non-user controls. However, this difference

ED

disappears during withdrawal. Studies using serum or plasma BDNF samples have shown different results. Subgroup analysis revealed lower levels of serum BDNF in alcohol users

PT

(SMD= -0.70, 95%CI -1.15 to -0.25, I2=89.81) and crack/cocaine users (SMD= -1.78, 95%CI -2.92 to -0.65, I2=97.59) than controls. Meta-regression analysis revealed that gender, age, and

CC E

age of first use moderate the effects of drug use in peripheral BDNF levels. Conclusions: Peripheral BDNF levels are decreased in the serum, but not the plasma, of active

A

drug users. Altogether, these findings suggest that BDNF levels may be related to acute use and addiction severity and also point to BDNF’s potential utility as a biomarker in this population.

Keywords: Biomarker; Substance Use Disorder; Brain-Derived Neurotrophic Factor; Meta-

Analysis; Alcohol; Crack-Cocaine

1. Introduction Drug addiction is a chronic disorder characterized by a set of cognitive, behavioral, and physiological symptoms that include continued use despite negative consequences as well as

IP T

high rates of relapse (American Psychiatric Association, 2013; Wikler, 1973). Although it has been postulated that the chronic use of psychoactive-substances (PAS) entails changes in brain

SC R

function and structure which lead to dysfunctional neuroadaptations (whether transitory or

permanent), the period of use and quantities necessary to provoke such alterations are unknown

U

(George and Koob, 2010; Seger, 2010; Volkow et al., 2011). A better understanding of these

N

neuroadaptations may lead to analytical tools that characterize interindividual variability in

A

drug abuse and treatment response (Büttner, 2011; Mendelson et al., 2011; Seger, 2010; Sinha,

M

2011).

In recent decades, significant advances have been made in the psychobiology of

ED

addictive disorders, which have reinforced the idea that addiction is a chronic disease characterized by structural and functional alterations in different brain systems (George and

PT

Koob, 2010; George et al., 2012; Goldstein and Volkow, 2002; Koob, 1992, 2000; Koob et al., 2004; Leshner, 1997; Sinha, 2011; Volkow et al., 2010). Brain-derived neurotrophic factor

CC E

(BDNF) has been studied as a potential biomarker in several psychiatric disorders, including substance use disorder (SUD) (Autry and Monteggia, 2012; Nagahara and Tuszynski, 2011).

A

BDNF is the most abundant neurotrophin in the brain and is related to cell growth and differentiation, synaptic connectivity and neuroplasticity, modulation of neurotransmission and neuronal repair, neurogenic and neurodegenerative processes (Binder and Scharfman, 2004; Huang and Reichardt, 2001), and learning and memory (Bekinschtein et al., 2008). Pre-clinical and clinical evidence indicates that neurotrophins are involved in neuroadaptation to PAS as

well as different processes related to the mediation of behavioral effects including drug sensitization, craving, and relapse (Castrén, 2004; Grimm et al., 2003; Miguel-Hidalgo, 2009; Schmidt and Duman, 2010; Volkow et al., 2015). Since it freely crosses the blood-brain barrier, and its peripheral concentration is strongly correlated with concentrations found in the central nervous system, peripheral BDNF has been widely assessed in clinical studies (Karege et al.,

IP T

2002; Pan et al., 1998).

Previous studies evaluating BDNF levels in individuals with SUDs have found different

SC R

and even controversial results, which indicates that the variations could be related to drug type, usage patterns at the moment of testing, and stage of dependence (Angelucci et al., 2010a;

U

Cavus et al., 2012; Corominas-Roso et al., 2015; D'Sa et al., 2011; Huang et al., 2011; Ke et

N

al., 2014; Pedraz et al., 2015; Roncero et al., 2016; Sordi et al., 2014). In healthy social drinkers

A

submitted to an acute stress protocol, family history of alcohol use disorder and age at first

M

alcohol use were also related to a decrease in serum BDNF (Sharma et al., 2017). However, these studies have mostly involved small heterogeneous samples and

ED

evaluated only one type of drug, preventing comparison of BDNF levels between different substance users. To the authors’ knowledge, no systematic review has meta-analyzed the

PT

difference between BDNF levels in individuals with SUDs and controls. Therefore, the present study aims to: 1) compare peripheral serum and plasma levels of BDNF between individuals

CC E

with SUDs and non-user controls, 2) determine whether this difference occurs in different drug types and subtypes, during withdrawal, and in blood fractions through subgroup analysis, and

A

3) explore, using meta-regressions, potential moderating factors. 2. Methods and materials The protocol developed for this meta-analytic review followed the recommendations of the PRISMA statement (Moher et al., 2009). Each element of the search, the selection of eligible studies (FO and AGV), and data extraction (FPR and ALT) were performed by two

authors. Disagreements were resolved through consensus and the opinion of a third author (LVD). 2.1 Search strategy We conducted a systematic search of all potentially eligible references, without language restrictions, in the PubMed/MEDLINE, EMBASE and PsycINFO databases. The

IP T

search was performed on November 21, 2017. This search strategy was augmented by manually tracking the reference list of all retrieved publications to identify additional eligible studies.

SC R

The search strategy is described in the supplementary material1. 2.2 Study selection

U

The included studies (1) evaluated individuals diagnosed with an SUD for alcohol or

N

an illicit drug according the DSM-5 or the ICD-10 (American Psychiatric Association, 2013;

A

WHO, 2013), (2) compared BDNF levels between individuals with SUDs and non-user

M

controls or were clinical trials using baseline data before drug treatment, and (3) measured peripheral BDNF levels. Excluded studies (1) involved participants with clinical or

ED

comorbidities (e.g., depression, HIV, Parkinson's disease, alzheimer or dementia) and (2) did not present original data (e.g., letters, posters, reviews, case reports, opinion pieces, or

PT

commentary). Studies with prescribed drugs (e.g., benzodiazepines) were not included in the search due to the difficulty of differentiating prescribed use vs. dependence and the high

CC E

prevalence of primary psychiatric disorders. The authors came to a consensus on the final inclusion of references.

A

2.3 Data extraction Two reviewers (FPR and ALT) independently extracted data on the control and SUD

groups (sample size, mean and standard deviation) from all included articles to prevent

1

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:

potential errors. Data entry discrepancies were double-checked by the reviewers against the original published data, and a consensus was reached. We extracted information regarding the primary drug, psychiatric comorbidities, scales and/or questionnaires used to evaluate psychiatric symptoms or disorders, BDNF levels, biological sample used to measure peripheral BDNF levels (plasma vs. serum), and time of withdrawal when the BDNF levels were

IP T

measured. Information about sex, mean age, age of first use, years of use, tobacco use, body mass index (BMI), and clinical diseases were also extracted. When necessary data were

SC R

unavailable in an included study, requests were emailed to the corresponding author on two different occasions. In cases where multiple reports pertained to the same participants, we

U

included only the largest data set. When the data were available only in graphs, they were

A

2.4 Assessment of methodological quality

N

extracted using Plot Digitizer software, version 2.6.8 (http://plotdigitizer.sourceforge.net/).

M

The quality of the studies included in the systematic review was evaluated using the nine-item Newcastle-Ottawa Scale (NOS) for case-control studies (Wells et al., 2014).

ED

However, item three (“Equivalent non-response rate between groups”) was not used in quality assessment due to the purposes of this review. For comparability questions, age was set a priori

PT

as the most important matching or adjustment factor. The articles were evaluated with the Cochrane Collaboration tool, which assesses the risk of bias of randomized clinical trials in six

CC E

domains (Cochrane Handbook) (Higgins et al., 2011). 2.5 Meta-analysis

A

We conducted random effect meta-analyses due to the anticipated heterogeneity across

studies. The analyses were performed using Comprehensive Meta-Analysis software version 3. The meta-analyses were conducted in three steps. First, a comparative meta-analysis was used to investigate differences in the BDNF levels of drug users vs. non-user controls. The standardized mean deviation (SMD) and the 95% confidence intervals (CI) of the effect size of

the difference were compared separately between serum and plasma BDNF levels. Second, we calculated the differences according to 1) withdrawal time (we considered withdrawal groups to be those with a minimum of 6 days of abstinence) and 2) drug subtype (cocaine or crack/cocaine, methamphetamine, alcohol, heroin, opiates, ketamine, cannabis, amphetamine derivative (±)-3, 4 methylenedioxymethamphetamine (MDMA/escstasy)) in users vs. non-user

IP T

controls in subgroup analyses. Third, we investigated potential moderators of BDNF levels

with meta-regression analyses. The potential moderators of interest were mean age, percentage

SC R

of males, withdrawal length, and years of drug use. We assessed heterogeneity using the I²

statistic for each analysis. Publication bias was verified with the Begg-Mazumdar and Egger

U

tests and adjusted using the Trim and Fill technique. The trim and fill method is a rank-based

N

data augmentation technique that can be used to estimate the number of studies missing from

A

a meta-analysis, adjust the effect removing the most extreme results on one side of the funnel

Duval and Tweedie, 2000).

ED

3. Results

M

plot, and augment the observed data until the funnel plot is more symmetric (Duval et al., 2000;

A total of 4175 studies were identified as potentially relevant, of which 91 were selected

PT

for review. After reading these papers in full and checking their reference lists for further relevant publications, a total of 50 articles were considered to meet the eligibility criteria and

CC E

were included in this systematic review, of which 40 were included in the meta-analysis. Three papers were identified in hand-searches and were added to the analysis (Figure 1).

A

3.1 Study and participants’ characteristics Forty unique studies with 58 arms were included (44 serum samples and 14 plasma

samples), totaling 2575 participants with SUDs and 2425 controls. The sample size of drug users ranged from 9 to 378. Thirteen studies evaluated BDNF levels in alcohol users (n=672), nine in crack/cocaine users (n=515), nine in opiate users (n=685), two in cannabis users (n=35),

five in methamphetamine users (n=3535), two in ketamine users (n=110), and one in MDMA/ecstasy users (n=23). Fourteen arms used data from plasma samples to measure BDNF levels (n=994, 399 in active use and 595 in withdrawal), while 44 used serum samples (n=2171, 1255 in active use and 559 in withdrawal). Out of the 40 studies included in the meta-analysis, 20 excluded subjects with psychiatric comorbidities, 13 reported the existence of

IP T

comorbidities, and 7 did not present this information. Of the 40 studies that integrated this meta-analysis, 11 included only men, 27 included men and women, and 2 studies evaluated

SC R

only women. The time of consumption among the users was: Alcohol = 15.32 (7.22), Heroin = 11.28 (7.60), Crack / cocaine = 7.76 (8.55), Methamphetamine = 9 (7.62), and MDMA =

U

3.08. Further details of the included studies are summarized in Table 1.

N

3.2 Study quality

A

3.2.1 Quality assessment with the NOS. Two authors (FH and AS) conducted the quality

M

assessment of the studies using The Newcastle-Ottawa Scale (NOS). This instrument is broadly used to assess the quality of non-randomized studies in meta-analyses (Wells et al., 2000,

ED

2011). The scores range from 0 to 9, with lower scores indicating lower study quality. In our paper, we classified the studies included from 0 to 8 stars because we believed the question

PT

regarding "non-response rate" did not apply to any of the studies, since there was no comparison between groups in this matter. Studies with quality scores lower than 3 were

CC E

considered of low quality (Wu et al., 2015). According to NOS, the studies included presented a good quality evaluation (mean = 6.45, SD = 1.01). The quality assessment details can be

A

found in the supplementary materials 2. 3.2.2 Quality assessment with the Cochrane Collaboration’s Risk of Bias Tool. Although none of the eligible studies presented a high risk of bias, one had an uncertain

2, 3

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:

risk of bias for allocation concealment and selective reporting (D'Souza et al., 2009), while another had an uncertain risk of bias for random sequence generation (Geisel et al., 2016). The quality assessment details can be found in the supplementary materials 3. 3.3 Meta-analyses We investigated BDNF levels in plasma or serum separately as different subgroups

IP T

(Table 2 and Table 3). For each matrix, we investigated the specific role of current substance

use status (current use/withdrawal) and the drug subtype: alcohol, heroin, crack/cocaine,

SC R

cannabis, ketamine, MDMA/ecstasy, or Methamphetamine. Powder cocaine and crack cocaine originate from the same active principle. Although the route of administration (inhaled and

U

smoked) changes the pharmacokinetics of the drug in the body, the pharmacodynamics are very

N

similar (Cone, 1995). Thus, we chose to analyze these substances together according to the

A

class of substance independent of the route of administration. We also investigated the role of

M

drug action and drug subtype for current users and those in withdrawal separately and did the same for both serum and plasma BDNF levels. The subgroup analyses are detailed below

ED

(Table 2 and Table 3). 3.4 Serum BDNF levels

PT

The 45 subgroups included a pooled total of 2171 blood samples from participants with SUDs and 2484 from controls, and significant differences in BDNF levels were found between

CC E

them (SMD=-0.30, 95%CI -0.62 to 0.02, p=0.02, I2=95.9). No significant publication bias was identified in the Begg-Mazumdar (tau=-0.13, p=0.20) or Egger tests (intercept=-5.10, p=0.01).

A

However, the Duval and Tweedie trim and fill method was used to adjust the effect size to 0.99 (95%CI -1.40 to -0.58) by trimming eight studies. Detailed analysis of BDNF levels can be seen in Table 2; they will be briefly summarized below. 3.4.1 Subgroup analysis considering drug use status. Active users generally presented higher BDNF levels than controls (SMD= -0.62 95CI -1.18 to -0.06, p=0.02). After adjusting

for publication bias, decreased levels were found for serum BDNF levels in current users (SMD=-1.54, 95%CI -2.20 to -0.73) with eight studies trimmed. There were no differences in BDNF between drug users in withdrawal and controls (Table 2). 3.4.2 Subgroup analysis according to drug subtype. Compared to controls, lower BDNF levels were found in alcohol (SMD=-0.44, 95%CI -0.84 to -0.03, p=0.03, I2=89.81) and

IP T

crack/cocaine users (SMD= -1.03, 95%CI -2.00 to -0.06 p=0.03, I2=97.59), although higher

levels were found in MDMA/Ecstasy users (SMD=5.72, 95%CI 4.35 to 7.09, p<0.001, I2=0).

SC R

The adjusted differences between alcohol users and controls and between crack/cocaine users and controls were reduced to -0.70 (95%CI -1.15 to -0.25) and -1.78 (95%CI -2.92 to -0.65),

U

respectively, after trimming 3 studies (Table 2).

N

3.4.3 Subgroup analysis according to drug subtype among users in withdrawal. No

A

significant differences were found among the BDNF serum levels of users in withdrawal, even

M

when analyzed according to drug subtype (Table 2).

3.4.4 Subgroup analysis according to drug subtype among active users. Lower BDNF

ED

levels were found in alcohol (SMD=-0.59, 95%CI -1.03to -0.16, p=0.007, I2=84.38) and crack/cocaine users (SMD=-3,10, 95%CI -6.25 to 003, p=0.05, I2=99.01), while higher BDNF

PT

levels were found in ketamine users (SMD=1.13, 95%CI 0.53 to 2.22, p=0.001, I2=0). For active alcohol users, the effect size, adjusted for publication bias, was -0.83 (95%CI -1.31 to -

CC E

0.35) after trimming two studies (Table 2). 3.5 Plasma BDNF levels

A

Fourteen arms, including 994 blood samples from drug users and 679 from controls,

were compared; no significant differences were found between them (SMD=0.12, 95%CI -0.33 to 0.59, p=0.59, I2=94.49). Significant publication bias was identified in the Begg-Mazumdar (tau=0.38, p=0.04) and Egger tests (intercept=7.38, p=0.01). However, adjustments with the Duval and Tweedie trim and fill method were not made. A detailed analysis of plasma BDNF

levels can be seen in Table 3, and they are briefly summarized below. 3.5.1 Subgroup analysis according to drug use status. No significant differences were found in BDNF plasma level between active users and controls or between users in withdrawal and controls (Table 3). 3.5.2 Subgroup analysis according to drug subtype. Methamphetamine users had

IP T

higher BDNF levels than controls (SMD=0.59, 95%CI 0.25 to 0.92, p=0.002, I2=0), and

crack/cocaine users also tended to have higher BDNF levels than controls (SMD=0.58, CI -

SC R

0.06 to 1.23, p=0.07, l2=85.83), while heroin users had lower BDNF levels than controls (SMD= -0.86, 95%CI -1.14 to -0.58, p<0.001, I2=61.44) (Table 3).

U

3.5.3 Subgroup analysis according to drug subtype among users in withdrawal. Lower

N

BDNF levels were found among alcohol users (SMD=-0.87, 95%CI -1.29 to -0.44, p=0.001 l2=58.24), while higher BDNF levels were found among methamphetamine users (SMD=0.59,

M

A

95%CI 0.25 to 0.92, p=0.001, I2=0). No analysis of this subgroup was adjusted for publication bias (Table 3).

ED

3.5.4 Subgroup analysis according to drug subtype among active users. In the crack/cocaine group, plasma BDNF was higher than controls (SMD=0.97, 95%CI, 0.48 to 1.47,

PT

p<0.001, I2=0), while in the heroin group it was lower (SMD=-1.01, 95%CI, -1.27 to -0.75

CC E

p<0.001, I2=0); however, only one study was involved in the heroin analysis (Table 3). 3.6 Meta-regressions of potential moderators Among active users, sex (k=26, β=-0.009, 95%CI -0.01 to -0.00, p<0.001, R2=0.35),

A

age (k=26, β=0.06 95%CI 0.00 to -0.12, p=0.02, R2=0.05) and age of the first use (k=10, β=0.49, 95%CI 0.20 to 0.79, p<0.001, R2=0.004) moderated the difference in BDNF levels between drug users and healthy controls. For users in withdrawal, the percent of males (k=23, β=-0.013, 95%CI -0.02 to -0.79, p=0.03, R2=0.08) was the only moderating variable for differences in BDNF levels among drug users and controls. The full details of the tested models

can be found in Table 4. 4. Discussion To the best of our knowledge, this is the first meta-analysis to compare peripheral BDNF levels in individuals with SUDs and non-user controls, and its main finding was that BDNF levels were lower in individuals with SUDs. Subanalysis showed that this reduction was

IP T

related to active drug use, to alcohol and crack/cocaine use, and to serum samples (regardless

of drug type and active use or withdrawal). Age of first drug use, years of use, and male gender

SC R

were found to be moderators in meta-regression analysis, supporting the hypothesis that BDNF levels are modified in individuals with SUDs.

U

These results corroborate prior evidence that BDNF is a reliable biomarker for other

N

psychiatric and neurodegenerative disorders (Angelucci et al., 2010b; Ciammola et al., 2007;

A

Connor et al., 1997; Fernandes et al., 2014; Fernandes et al., 2011; Fernandes et al., 2015a;

M

Fernandes et al., 2015b; Kishi et al., 2017; Krabbe et al., 2007; Lee et al., 2009; Munkholm et al., 2016; Murer et al., 2001; Polyakova et al., 2015; Qin et al., 2017; Salas-Magaña et al.,

ED

2017; Ventriglia et al., 2013; Yasutake et al., 2006; Zuccato and Cattaneo, 2009). For example, in bipolar disorder, depressive disorder, suicide, and schizophrenia, lower BDNF levels were

PT

observed in symptomatic phases than in euthymic subjects and healthy controls (Fernandes et al., 2014; Fernandes et al., 2011; Fernandes et al., 2015a; Fernandes et al., 2015b; Kishi et al.,

CC E

2017; Munkholm et al., 2016; Polyakova et al., 2015; Salas-Magaña et al., 2017). The lack of significant difference in BDNF levels between cases in withdrawal and controls also agrees

A

with previous evidence from other psychiatric disorders, where BDNF increased in asymptomatic periods to levels similar to those of controls (Fernandes et al., 2015a; Polyakova et al., 2015). Benzodiazepine-dependent patients with major depression diagnoses also showed similar BDNF levels compared to controls after completion of benzodiazepine withdrawal (Heberlein et al., 2010). However, in this same study, the BDNF levels of the patients were

increased in relation to the controls at baseline, diverging from our findings. This may be due to treatment with antidepressants, which may increase levels of BDNF (Shimizu et al., 2003). Nevertheless, while acute administration of benzodiazepine-like drugs generates a significant reduction in expression and level of BDNF in the hippocampus, repeated administration failed to influence BDNF expression in this brain area involved in drug-related plasticity (Licata et

IP T

al., 2013).

The apparent contradiction in peripheral BDNF levels (plasma vs. serum) could be

SC R

explained by different analytical mechanisms (Fernandes et al., 2015a; Fernandes et al., 2015b;

Fujimura et al., 2002) and phases of the disease, e.g., chronic exposure and withdrawal (Barker

U

et al., 2015). These results were more consistent in crack/cocaine and alcohol users. In

N

ketamine and MDMA/ecstasy users, the observed differences are not generalizable, since the

A

analysis only included one study. These findings agree with previous pre-clinical and clinical

M

studies (Barker et al., 2015). Studies with voluntary administration protocols have found that acute use of alcohol and cocaine transiently increases brain BDNF levels, although prolonged

ED

and excessive use lead to a robust reduction in BDNF expression. Nevertheless, after discontinuing use, animal studies indicate that BDNF levels return to baseline (Geoffroy and

PT

Noble, 2017; Graham et al., 2007; Li and Wolf, 2015; Logrip et al., 2015). Corroborating the hypothesis of transient drug-induced changes in BDNF, a study with rats submitted to a

CC E

protocol of acute benzodiazepine administration verified that BDNF returned to near baseline levels after 40 hours (Huopaniemi et al., 2004). Pre-clinical and clinical studies suggest that

A

BDNF could vary in different stages of drug use (e.g. acute, chronic, recovery) and could be associated with cumulative neurological damage (Gama et al., 2013; Grande et al., 2012; Kapczinski et al., 2014; Kapczinski et al., 2008). We also verified that peripheral BDNF levels varied according to the drug used, possibly due to factors such as the substance’s mechanism of action, the pattern and duration

of drug use, the user’s clinical and psychiatric comorbidities, and polysubstance use. In crack/cocaine users, for example, polysubstance use is very common: 77% and 85% report alcohol and tobacco consumption, respectively, in the last year (Bastos and Bertoni, 2014). Hilburn et al. found differences in serum BDNF levels among alcohol, cocaine, and methamphetamine users in relation to craving and duration of withdrawal (Hilburn et al., 2011).

IP T

In young ecstasy users, who had fewer years of use and less frequent use, BDNF was higher at

baseline, which could indicate that they were in the initial phase of the disease (Zhang et al.,

SC R

2014). Another study involving controlled administration of THC found higher serum BDNF in healthy controls than in subjects who had previously used cannabis (D'Souza et al., 2009),

U

which indicates that recreational and chronic drug use have different effects on BDNF levels.

N

Our meta-regressions showed that serum BDNF levels are moderated by sex, years of

A

use, and age of first use, which corroborates previous findings that age and sex affect stored

M

and circulating levels of BDNF in peripheral blood (Lommatzsch et al., 2005b). In psychiatric disorders, such as bipolar disorder and schizophrenia, meta-analyses have already shown that

Fernandes et al., 2015b).

ED

age and disease duration are associated with lower BDNF levels (Fernandes et al., 2011;

PT

It has been demonstrated that homeostatic functioning is disturbed during the course of mental disorders, and the central nervous system reorganizes itself. Although in the short term

CC E

such reorganization can indicate a functional response mechanism, in the long term it can cause dysfunctional and pathological alterations (allostatic load), resulting in inappropriate response

A

(Kapczinski et al., 2008; McEwen, 1998a, 1998b, 2000, 2002, 2003; McEwen and Wingfield, 2003). Moreover, in advanced stages, inappropriate responses can persist even during remission (Berk et al., 2011). In SUDs, the chronic use of PAS generates repeated overactivation of the dopaminergic pathway, leading to neuroadaptive mechanisms that may cause dysregulation in the brain reward system and in BDNF regulation.

The impact of age and sex in our results is in line with previous investigations of stored and circulating BDNF levels in peripheral blood (Lommatzsch et al., 2005b). Elderly women, for example, seem to have higher BDNF levels than men (Bus et al., 2011), which may result from sex-related hormonal differences. Estrogen, for instance, interferes in BDNF expression and causes variations in the menstrual cycle (Erickson et al., 2010; Lewis, 2006; Lommatzsch

IP T

et al., 2005b). It is noteworthy that the only study with an all-female sample found higher

BDNF levels in crack/cocaine users during early withdrawal than in controls, and more than

SC R

half of the women had some additional psychiatric comorbidity (Viola et al., 2014).

According to previous studies, the severity of drug dependence can also affect BDNF

U

levels (Costa et al., 2011; D'Sa et al., 2011; Huang et al., 2011; Sordi et al., 2014). Even among

N

individuals using the same substance, there are differences in BDNF levels according to the

A

severity of drug use and prognosis (Corominas-Roso et al., 2015; Corominas-Roso et al., 2013;

M

D'Sa et al., 2011; Scherer et al., 2015). In alcohol users, for example, significantly lower BDNF levels were found in individuals with delirium tremens than users without this condition and

ED

controls, and these levels persisted even after detoxification (Huang et al., 2011). In another study that followed patients for 180 days after detoxification, the serum BDNF levels of

PT

patients who maintained abstinence were higher than both baseline values and patients who relapsed during this period (Costa et al., 2011). Similarly, Scherer et al. found an association

CC E

between higher BDNF levels and better clinical outcomes in crack users during detoxification (2015). Thus, during treatment, BDNF levels approaching those of controls may be associated

A

with better clinical outcomes (Duman and Monteggia, 2006; Zuccato and Cattaneo, 2009). Moreover, studies with other psychiatric populations have also reported similar results: in bipolar patients, for example, different serum BDNF levels in the early and late stages have been reported. Our results also revealed differences in peripheral BDNF levels between serum and

plasma. Only two of the forty studies included in this investigation evaluated serum and plasma samples simultaneously, and they found intra-individual and intra-group variations (D'Sa et al., 2012; Zanardini et al., 2011). This difference has also been demonstrated in studies with other psychiatric disorders (Bocchio-Chiavetto et al., 2010; Piccinni et al., 2008; Polyakova et al., 2015; Salas-Magaña et al., 2017). A previous meta-analysis of subjects with major depression

IP T

found lower serum BDNF levels and no significant differences in plasma levels, indicating that

the BDNF levels in these biological samples are not correlated (Bocchio-Chiavetto et al.,

SC R

2010). Several hypotheses could help clarify this discrepancy in peripheral BDNF level

between biological samples. First, the origin of BDNF in the blood is not completely known.

U

Although the brain is believed to be the main source of circulating peripheral BDNF, it is also

N

produced in other regions (Azoulay et al., 2005; Donovan et al., 1995; Kerschensteiner et al.,

A

1999; Nakahashi et al., 2000; Rasmussen et al., 2009; Sohrabji and Lewis, 2006; Yamamoto

M

and Gurney, 1990). While plasma BDNF derives mainly from lymphocytes, endothelial cells, monocytes, and non-neural peripheral cells, including vascular smooth muscle cells (Donovan

ED

et al., 1995; Nakahashi et al., 2000), serum BDNF is probably related to the total amount of BDNF stored and released by platelets during the blood clotting process (Fujimura et al., 2002;

PT

Lommatzsch et al., 2005a), which generates a serum BDNF concentration up to 50 times higher than that in plasma (Fujimura et al., 2002; Lommatzsch et al., 2005a). Furthermore, while

CC E

plasma BDNF has a half-life of less than an hour, platelets circulate for up to 11 days (Kishino et al., 2001; Poduslo and Curran, 1996). Considering that platelets contain the majority of the

A

circulating BDNF in the blood, some investigations point out that serum levels seem to better reflect the amount of BDNF in whole blood and are thus a more reliable marker (Fujimura et al., 2002; Lommatzsch et al., 2005a; Serra-Millàs, 2016; Trajkovska et al., 2007). BDNF measurement is subject to variability in both plasma and serum due to biological, methodological, and analytical factors. The methodology used for collection and storage may

affect the stability of the sample (Bocchio-Chiavetto et al., 2010; Bus et al., 2011; Trajkovska et al., 2007; Zuccato et al., 2011). In plasma, the time between sample collection and processing, centrifugation conditions (Fujimura et al., 2002; Zuccato et al., 2011), and choice of anticoagulant can also interfere with the results. While ethylenediaminetetraacetic acid could increase BDNF detection due to platelet release (Lommatzsch et al., 2005a; Lommatzsch and

IP T

Virchow, 2006), the use of heparin could result in up to a 60% decrease in plasma detection

(Begliuomini et al., 2007). Thus, plasma is considered to represent short-term BDNF content,

SC R

while serum represents long-term BDNF content (Polyakova et al., 2015).

It should be pointed out that we found important limitations in the studies included in

U

this review. Tobacco, for example, which is associated with increased peripheral BDNF, was

N

not controlled in 39% of the studies (Hashimoto et al., 2006; Jamal et al., 2015). Moreover,

A

several studies showed no information about the possible confounding effects of psychiatric

M

comorbidities. Many studies did not exclude or did not report the existence of psychiatric comorbidities.

ED

The high prevalence of comorbid psychiatric disorders among subjects with SUDs is well-described in previous studies (Alcorn et al., 2013; Compton et al., 2005; Falck et al., 2004;

PT

Kessler et al., 1994; Narvaez et al., 2014; Pavarin, 2006; Sartor et al., 2014; Toftdahl et al., 2015). Thus, the exclusion of psychiatric comorbidities would not represent a real sample.

CC E

Moreover, we excluded studies whose samples were based on other psychiatric disorders as main diagnosis; however, we did not exclude studies in which comorbidities were secondary

A

or stabilized at the time of evaluation. It is emphasized that a minimum period of abstinence is necessary for an accurate diagnosis and to differentiate effects resulting from drug use. Studies with methamphetamine-dependent patients and depression symptoms showed significantly lower BDNF levels compared to those with no depression symptoms (Ren et al., 2017), and depressive patients with or without alcohol dependence have significantly lower

serum BDNF levels than healthy subjects. Nonetheless, no significant difference was found in the

serum

BDNF

levels

of

depressive

patients

comparing

subjects

with

and

without alcohol dependence (Umene-Nakano et al., 2009). In studies of our group, we found no relationship between psychiatric comorbidities and BDNF in subjects with SUDS (von Diemen et al., 2014).

IP T

Data about psychotic symptoms indicate that BDNF levels did not differ significantly

between 'ecstasy dependent' and 'ecstasy addicted with signs of psychosis', although both were

SC R

increased compared to controls (Angelucci et al., 2010a). Otherwise, a case report found a reduction in the BDNF level of patients in a psychotic episode induced by cocaine (Roncero et

U

al., 2016). Therefore, it is not possible to rule out that psychotic and depressive symptoms may

N

interfere in the BDNF levels because the data available to-date are inconclusive.

A

Probably due to the large methodological differences in the included studies (ex:

M

sampling, data collection protocol, etc.), there was high heterogeneity (80% or higher) for all analyses in our review. We therefore used subgroup and moderator analysis which found that

ED

certain potential sources (age, gender, duration of drug use, and the drug type and subtype) explained some of the heterogeneity. Moreover, we found only a limited number of studies

PT

evaluating certain PAS, such as heroin and ecstasy, which restricted our analysis of them. Considering the neurotrophic hypothesis, based on the assumption that the SUDs may be due

CC E

to neuronal inability to develop an appropriate adaptive neuroplastic response (Altar, 1999; Bolaños and Nestler, 2004; Castrén, 2014; Russo et al., 2009; Sharma and Ceballos, 2016),

A

strategies that restore drug-induced changes in BDNF levels can aid in reestablishing brain neuroplasticity and enhance treatment responses such as longer hospitalizations for detoxification, specific medications, cognitive rehabilitation, and therapeutic community (Clark and Beck, 2010; Erickson et al., 2011; Hoefer et al., 2014; Srinivasan et al., 2013). 5. Conclusion

In conclusion, the evidence of this review suggests that serum BDNF levels are lower among chronic drug users, and this could be related to the years and severity of drug dependence. Serum seems to be a more stable fluid for measuring BDNF than plasma. When interpreting BDNF levels in drug users, factors such as the biological sample (plasma or serum), drug type, pattern of drug use, psychiatric comorbidities, and polysubstance abuse

IP T

should be considered. Although it appears that different drug classes affect BDNF levels in

different ways, their mechanisms of action on BDNF concentration are not yet fully

SC R

understood. Nevertheless, the present study provides a better understanding of

neurophysiological factors and biomarkers in SUDs, which could lead to better treatment

U

strategies such as adoption of more individualized therapeutic procedures. In addition,

N

behavioral or pharmacological interventions aimed at improving neuroplasticity may be a

M

A

promising pathway.

Author Disclosures

ED

Role of Funding Source

Funding for this study was provided by Research and Events Support Fund at Hospital de Clínicas de

PT

Porto Alegre (FIPE-HCPA). FIPE-HCPA had no further role in study design, in the collection, analysis and interpretation of data, in the writing of the report, and in the decision to submit the paper for

CC E

publication.

Additional Financial support was provided by the Coordination for the Improvement of Higher Education Personnel (CAPES). As cited above, this institution had no further role in study design, in

A

the collection, analysis and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication as well. Contributors Felipe Ornell was involved with protocol development, hypothesis elaboration, search strategy

elaboration, search and selection of eligible studies, interpretation and discussion of data and results, writing and review of the manuscript. Fernanda Hansen was involved with protocol development, hypothesis elaboration, search strategy elaboration, assessment of methodological quality, interpretation and discussion of data and results, writing and review of the manuscript. Felipe Barreto Schuch was involved with construction of the data basis, conduction of the random

IP T

effect meta-analyses, interpretation and discussion of data and results, writing and review of the manuscript. Fernando Pezzini Rebelatto was involved with data extraction, interpretation and

SC R

discussion of data and results, writing and review of the manuscript. Ana Laura Tavares was involved with data extraction, assessment of methodological quality, interpretation and discussion of data and results, writing and review of the manuscript.

U

Juliana Scherer was involved with the writing of the discussion of data and results, writing and review

N

of the manuscript. Andrei Garziera Valerio assisted with search and selection of eligible studies,

A

interpretation and discussion of data and results, writing and review of the manuscript. Flavio

M

Pechansky was involved with discussion of data and results, writing and review of the manuscript.

ED

Felix Henrique Paim Kessler was involved with protocol development, hypothesis elaboration, search strategy elaboration, interpretation and discussion of data and results, writing and review of the

PT

manuscript. Lisia von Diemen contributed to protocol development, hypothesis elaboration, search strategy elaboration interpretation and discussion of data and results, writing and review of the

CC E

manuscript. All authors contributed to and approved the final version of the manuscript.

Conflict of Interest

A

The authors declare that they have no conflicts of interest.

Acknowledgements

We acknowledge all participants who took part in the present study, the FIPE-HCPA, CAPES and

A

CC E

PT

ED

M

A

N

U

SC R

IP T

Postgraduate Program in Psychiatry and Behavioral Science, for providing funding to this research.

References Alcorn, J.L., Gowin, J.L., Green, C.E., Swann, A.C., Moeller, F.G., Lane, S.D., 2013. Aggression, impulsivity, and psychopathic traits in combined antisocial personality disorder and substance use disorder. J. Neuropsychiatry Clin. Neurosci. 25, 229-232. Altar, C.A., 1999. Neurotrophins and depression. Trends Pharmacol. Sci. 20, 59-61.

disorders (5th ed.). American Psychiatric Publishing, Arlington, VA.

IP T

American Psychiatric Association (APA), 2013. Diagnostic and statistical manual of mental

SC R

Angelucci, F., Ricci, V., Martinotti, G., Palladino, I., Spalletta, G., Caltagirone, C., Bria, P.,

2010a. Ecstasy (MDMA)-addicted subjects show increased serum levels of brain-

U

derived neurotrophic factor, independently from a rise of drug-induced psychotic

N

symptoms. Addict. Biol. 15, 365-367.

A

Angelucci, F., Spalletta, G., di Iulio, F., Ciaramella, A., Salani, F., Colantoni, L., Varsi, A.E.,

M

Gianni, W., Sancesario, G., Caltagirone, C., Bossù, P., 2010b. Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) patients are characterized by increased

ED

BDNF serum levels. Curr. Alzheimer Res. 7, 15-20. Autry, A.E., Monteggia, L.M., 2012. Brain-derived neurotrophic factor and neuropsychiatric

PT

disorders. Pharmacol. Rev. 64, 238-258. Azoulay, D., Vachapova, V., Shihman, B., Miler, A., Karni, A., 2005. Lower brain-derived

CC E

neurotrophic factor in serum of relapsing remitting MS: Reversal by glatiramer acetate. J. Neuroimmunol. 167, 215-218.

A

Barker, J.M., Taylor, J.R., De Vries, T.J., Peters, J., 2015. Brain-derived neurotrophic factor and addiction: Pathological versus therapeutic effects on drug seeking. Brain Res. 1628, 68-81.

Bastos, F.I., Bertoni, N., 2014. Pesquisa nacional sobre o uso de crack: Quem são os usuários de crack e/ou similares do Brasil? Quantos são nas capitais brasileiras? Editora Fiocruz, Rio de Janeiro. p. 224. Begliuomini, S., Casarosa, E., Pluchino, N., Lenzi, E., Centofanti, M., Freschi, L., Pieri, M., Genazzani, A.D., Luisi, S., Genazzani, A.R., 2007. Influence of endogenous and

IP T

exogenous sex hormones on plasma brain-derived neurotrophic factor. Hum. Reprod. 22, 995-1002.

formation and storage. Neuroscientist 14, 147-156.

SC R

Bekinschtein, P., Cammarota, M., Izquierdo, I., Medina, J.H., 2008. BDNF and memory

U

Berk, M., Kapczinski, F., Andreazza, A.C., Dean, O.M., Giorlando, F., Maes, M., Yücel, M.,

N

Gama, C.S., Dodd, S., Dean, B., Magalhães, P.V., Amminger, P., McGorry, P., Malhi,

A

G.S., 2011. Pathways underlying neuroprogression in bipolar disorder: Focus on

M

inflammation, oxidative stress and neurotrophic factors. Neurosci. Biobehav. Rev. 35, 804-817.

123-131.

ED

Binder, D.K., Scharfman, H.E., 2004. Brain-derived neurotrophic factor. Growth Factors 22,

PT

Bocchio-Chiavetto, L., Bagnardi, V., Zanardini, R., Molteni, R., Nielsen, M.G., Placentino, A., Giovannini, C., Rillosi, L., Ventriglia, M., Riva, M.A., Gennarelli, M., 2010. Serum

CC E

and plasma BDNF levels in major depression: A replication study and meta-analyses. World J. Biol. Psychiatry 11, 763-773.

A

Bolaños, C.A., Nestler, E.J., 2004. Neurotrophic mechanisms in drug addiction. Neuromolecular Med. 5, 69-83.

Bus, B.A., Molendijk, M.L., Penninx, B.J., Buitelaar, J.K., Kenis, G., Prickaerts, J., Elzinga, B.M., Voshaar, R.C., 2011. Determinants of serum brain-derived neurotrophic factor. Psychoneuroendocrinology 36, 228-239.

Büttner, A., 2011. Review: The neuropathology of drug abuse. Neuropathol. Appl. Neurobiol. 37, 118-134. Castrén, E., 2004. Neurotrophins as mediators of drug effects on mood, addiction, and neuroprotection. Mol. Neurobiol. 29, 289-302. Castrén, E., 2014. Neurotrophins and psychiatric disorders. Handb. Exp. Pharmacol. 220, 461-

IP T

479.

Cavus, S.Y., Dilbaz, N., Darcin, A.E., Eren, F., Kaya, H., Kaya, O., 2012. Alterations in serum

SC R

BDNF levels in early alcohol withdrawal and comparison with healthy controls. Bull. Clin. Psychopharmacol. 22, 210-215.

U

Ciammola, A., Sassone, J., Cannella, M., Calza, S., Poletti, B., Frati, L., Squitieri, F., Silani,

N

V., 2007. Low brain-derived neurotrophic factor (BDNF) levels in serum of

A

Huntington's disease patients. Am. J. Med. Genet. B. Neuropsychiatr. Genet. 144B,

M

574-577.

Clark, D.A., Beck, A.T., 2010. Cognitive theory and therapy of anxiety and depression:

ED

Convergence with neurobiological findings. Trends Cogn. Sci. 14, 418-424. Compton, W.M., Thomas, Y.F., Conway, K.P., Colliver, J.D., 2005. Developments in the

PT

epidemiology of drug use and drug use disorders. Am. J. Psychiatry 162, 1494-1502. Cone, E.J., 1995. Pharmacokinetics and pharmacodynamics of cocaine. J. Anal. Toxicol. 19,

CC E

459-478.

Connor, B., Young, D., Yan, Q., Faull, R.L., Synek, B., Dragunow, M., 1997. Brain-derived

A

neurotrophic factor is reduced in Alzheimer's disease. Brain Res. Mol. Brain Res. 49, 71-81.

Corominas-Roso, M., Roncero, C., Daigre, C., Grau-Lopez, L., Ros-Cucurull, E., RodríguezCintas, L., Sanchez-Mora, C., Lopez, M.V., Ribases, M., Casas, M., 2015. Changes in

brain-derived neurotrophic factor (BDNF) during abstinence could be associated with relapse in cocaine-dependent patients. Psychiatry Res. 225, 309-314. Corominas-Roso, M., Roncero, C., Eiroa-Orosa, F.J., Gonzalvo, B., Grau-Lopez, L., Ribases, M., Rodriguez-Cintas, L., Sánchez-Mora, C., Ramos-Quiroga, J.A., Casas, M., 2013.

early abstinence. Eur. Neuropsychopharmacol. 23, 1078-1084.

IP T

Brain-derived neurotrophic factor serum levels in cocaine-dependent patients during

Costa, M.A., Girard, M., Dalmay, F., Malauzat, D., 2011. Brain-derived neurotrophic factor

SC R

serum levels in alcohol-dependent subjects 6 months after alcohol withdrawal. Alcohol. Clin. Exp. Res. 35, 1966-1973.

U

D'Sa, C., Dileone, R.J., Anderson, G.M., Sinha, R., 2012. Serum and plasma brain-derived

N

neurotrophic factor (BDNF) in abstinent alcoholics and social drinkers. Alcohol 46,

A

253-259.

M

D'Sa, C., Fox, H.C., Hong, A.K., Dileone, R.J., Sinha, R., 2011. Increased serum brain-derived neurotrophic factor is predictive of cocaine relapse outcomes: A prospective study.

ED

Biol. Psychiatry 70, 706-711.

D'Souza, D.C., Pittman, B., Perry, E., Simen, A., 2009. Preliminary evidence of cannabinoid on

brain-derived

neurotrophic

factor

(BDNF)

levels

in

humans.

PT

effects

Psychopharmacology 202, 569-578.

CC E

Donovan, M.J., Miranda, R.C., Kraemer, R., McCaffrey, T.A., Tessarollo, L., Mahadeo, D., Sharif, S., Kaplan, D.R., Tsoulfas, P., Parada, L., 1995. Neurotrophin and neurotrophin

A

receptors in vascular smooth muscle cells. Regulation of expression in response to injury. Am. J. Pathol. 147, 309-324.

Duman, R.S., Monteggia, L.M., 2006. A neurotrophic model for stress-related mood disorders. Biol. Psychiatry 59, 1116-1127.

Duval, S., Tweedie, R., 2000. A nonparametric “trim and fill” method of accounting for publication bias in meta-analysis. J. Am. Stat. Assoc. 95, 89-98. Duval, S., Tweedie, R., 2000. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 56, 455-463. Erickson, K.I., Prakash, R.S., Voss, M.W., Chaddock, L., Heo, S., McLaren, M., Pence, B.D.,

IP T

Martin, S.A., Vieira, V.J., Woods, J.A., McAuley, E., Kramer, A.F., 2010. Brainderived neurotrophic factor is associated with age-related decline in hippocampal

SC R

volume. J. Neurosci. 30, 5368-5375.

Erickson, K.I., Voss, M.W., Prakash, R.S., Basak, C., Szabo, A., Chaddock, L., Kim, J.S., Heo,

U

S., Alves, H., White, S.M., Wojcicki, T.R., Mailey, E., Vieira, V.J., Martin, S.A., Pence,

N

B.D., Woods, J.A., McAuley, E., Kramer, A.F., 2011. Exercise training increases size

A

of hippocampus and improves memory. Proc. Natl. Acad. Sci. U.S.A. 108, 3017-3022.

M

Falck, R.S., Wang, J., Siegal, H.A., Carlson, R.G., 2004. The prevalence of psychiatric disorder among a community sample of crack cocaine users: An exploratory study with practical

ED

implications. J. Nerv. Ment. Dis. 192, 503-507. Fernandes, B.S., Berk, M., Turck, C.W., Steiner, J., Gonçalves, C.A., 2014. Decreased

PT

peripheral brain-derived neurotrophic factor levels are a biomarker of disease activity in major psychiatric disorders: A comparative meta-analysis. Mol. Psychiatry 19, 750-

CC E

751.

Fernandes, B.S., Gama, C.S., Ceresér, K.M., Yatham, L.N., Fries, G.R., Colpo, G., de Lucena,

A

D., Kunz, M., Gomes, F.A., Kapczinski, F., 2011. Brain-derived neurotrophic factor as a state-marker of mood episodes in bipolar disorders: A systematic review and metaregression analysis. J. Psychiatr. Res. 45, 995-1004.

Fernandes, B.S., Molendijk, M.L., Köhler, C.A., Soares, J.C., Leite, C.M., Machado-Vieira, R., Ribeiro, T.L., Silva, J.C., Sales, P.M., Quevedo, J., Oertel-Knöchel, V., Vieta, E.,

González-Pinto, A., Berk, M., Carvalho, A.F., 2015a. Peripheral brain-derived neurotrophic factor (BDNF) as a biomarker in bipolar disorder: A meta-analysis of 52 studies. BMC Med. 13, 289. Fernandes, B.S., Steiner, J., Berk, M., Molendijk, M.L., Gonzalez-Pinto, A., Turck, C.W., Nardin, P., Gonçalves, C.A., 2015b. Peripheral brain-derived neurotrophic factor in

IP T

schizophrenia and the role of antipsychotics: Meta-analysis and implications. Mol. Psychiatry 20, 1108-1119.

SC R

Fujimura, H., Altar, C.A., Chen, R., Nakamura, T., Nakahashi, T., Kambayashi, J., Sun, B.,

Tandon, N.N., 2002. Brain-derived neurotrophic factor is stored in human platelets and

U

released by agonist stimulation. Thromb. Haemost. 87, 728-734.

N

Gama, C.S., Kunz, M., Magalhães, P.V., Kapczinski, F., 2013. Staging and neuroprogression

A

in bipolar disorder: A systematic review of the literature. Rev. Bras. Psiquiatr. 35, 70-

M

74.

Geisel, O., Hellweg, R., Müller, C.A., 2016. Serum levels of brain-derived neurotrophic factor

ED

in alcohol-dependent patients receiving high-dose baclofen. Psychiatry Res. 240, 177180.

PT

Geoffroy, H., Noble, F., 2017. BDNF during withdrawal. Vitam. Horm. 104, 475-496. George, O., Koob, G.F., 2010. Individual differences in prefrontal cortex function and the

CC E

transition from drug use to drug dependence. Neurosci. Biobehav. Rev. 35, 232-247.

George, O., Le Moal, M., Koob, G.F., 2012. Allostasis and addiction: Role of the dopamine

A

and corticotropin-releasing factor systems. Physiol. Behav. 106, 58-64.

Goldstein, R.Z., Volkow, N.D., 2002. Drug addiction and its underlying neurobiological basis: Neuroimaging evidence for the involvement of the frontal cortex. Am. J. Psychiatry 159, 1642-1652.

Graham, D.L., Edwards, S., Bachtell, R.K., DiLeone, R.J., Rios, M., Self, D.W., 2007. Dynamic BDNF activity in nucleus accumbens with cocaine use increases selfadministration and relapse. Nat. Neurosci. 10, 1029-1037. Grande, I., Magalhães, P.V., Kunz, M., Vieta, E., Kapczinski, F., 2012. Mediators of allostasis and systemic toxicity in bipolar disorder. Physiol. Behav. 106, 46-50.

IP T

Grimm, J.W., Lu, L., Hayashi, T., Hope, B.T., Su, T.P., Shaham, Y., 2003. Time-dependent increases in brain-derived neurotrophic factor protein levels within the mesolimbic

SC R

dopamine system after withdrawal from cocaine: Implications for incubation of cocaine craving. J. Neurosci. 23, 742-747.

U

Hashimoto, K., Iwata, Y., Nakamura, K., Tsujii, M., Tsuchiya, K.J., Sekine, Y., Suzuki, K.,

N

Minabe, Y., Takei, N., Iyo, M., Mori, N., 2006. Reduced serum levels of brain-derived

M

Biol. Psychiatry 30, 1529-1531.

A

neurotrophic factor in adult male patients with autism. Prog. Neuropsychopharmacol.

Heberlein, A., Lenz, B., Muschler, M., Frieling, H., Buechl, R., Gröschl, M., Kornhuber, J.,

ED

Bleich, S., Hillemacher, T., 2010. BDNF plasma levels decrease during benzodiazepine withdrawal in patients suffering from comorbidity of depressive disorder and

PT

benzodiazepine dependence. Psychopharmacology 209, 213-215. Higgins, J., Green, S. (Eds.)., 2011. Cochrane handbook for systematic reviews of interventions

CC E

version 5.1.0. The Cochrane Collaboration, London.

Hilburn, C., Nejtek, V.A., Underwood, W.A., Singh, M., Patel, G., Gangwani, P., Forster, M.J.,

A

2011. Is serum brain-derived neurotrophic factor related to craving for or use of alcohol, cocaine, or methamphetamine? Neuropsychiatr. Dis. Treat. 7, 357-364.

Hoefer, M.E., Pennington, D.L., Durazzo, T.C., Mon, A., Abé, C., Truran, D., Hutchison, K.E., Meyerhoff, D.J., 2014. Genetic and behavioral determinants of hippocampal volume recovery during abstinence from alcohol. Alcohol 48, 631-638.

Huang, E.J., Reichardt, L.F., 2001. Neurotrophins: Roles in neuronal development and function. Annu. Rev. Neurosci. 24, 677-736. Huang, M.C., Chen, C.H., Liu, H.C., Chen, C.C., Ho, C.C., Leu, S.J., 2011. Differential patterns of serum brain-derived neurotrophic factor levels in alcoholic patients with and without delirium tremens during acute withdrawal. Alcohol. Clin. Exp. Res. 35, 126-

IP T

131.

Huopaniemi, L., Keist, R., Randolph, A., Certa, U., Rudolph, U., 2004. Diazepam-induced

SC R

adaptive plasticity revealed by alpha1 GABAA receptor-specific expression profiling. J. Neurochem. 88, 1059-1067.

U

Jamal, M., Van der Does, W., Elzinga, B.M., Molendijk, M.L., Penninx, B.W., 2015.

N

Association between smoking, nicotine dependence, and BDNF Val66Met

A

polymorphism with BDNF concentrations in serum. Nicotine Tob. Res. 17, 323-329.

M

Kapczinski, F., Magalhães, P.V., Balanzá-Martinez, V., Dias, V.V., Frangou, S., Gama, C.S., Gonzalez-Pinto, A., Grande, I., Ha, K., Kauer-Sant'Anna, M., Kunz, M., Kupka, R.,

ED

Leboyer, M., Lopez-Jaramillo, C., Post, R.M., Rybakowski, J.K., Scott, J., Strejilevitch, S., Tohen, M., Vazquez, G., Yatham, L., Vieta, E., Berk, M., 2014. Staging systems in

PT

bipolar disorder: An International Society for Bipolar Disorders Task Force report. Acta. Psychiatr. Scand. 130, 354-363.

CC E

Kapczinski, F., Vieta, E., Andreazza, A.C., Frey, B.N., Gomes, F.A., Tramontina, J., KauerSant'anna, M., Grassi-Oliveira, R., Post, R.M., 2008. Allostatic load in bipolar disorder:

A

Implications for pathophysiology and treatment. Neurosci. Biobehav. Rev. 32, 675692.

Karege, F., Schwald, M., Cisse, M., 2002. Postnatal developmental profile of brain-derived neurotrophic factor in rat brain and platelets. Neurosci. Lett. 328, 261-264.

Ke, X., Ding, Y., Xu, K., He, H., Zhang, M., Wang, D., Deng, X., Zhang, X., Zhou, C., Liu, Y., Ning, Y., Fan, N., 2014. Serum brain-derived neurotrophic factor and nerve growth factor decreased in chronic ketamine abusers. Drug Alcohol Depend. 142, 290-294. Kerschensteiner, M., Gallmeier, E., Behrens, L., Leal, V.V., Misgeld, T., Klinkert, W.E., Kolbeck, R., Hoppe, E., Oropeza-Wekerle, R.L., Bartke, I., Stadelmann, C., Lassmann,

IP T

H., Wekerle, H., Hohlfeld, R., 1999. Activated human T cells, B cells, and monocytes

produce brain-derived neurotrophic factor in vitro and in inflammatory brain lesions:

SC R

A neuroprotective role of inflammation? J. Exp. Med. 189, 865-870.

Kessler, R.C., McGonagle, K.A., Zhao, S., Nelson, C.B., Hughes, M., Eshleman, S., Wittchen,

U

H.U., Kendler, K.S., 1994. Lifetime and 12-month prevalence of DSM-III-R

A

Survey. Arch. Gen. Psychiatry 51, 8-19.

N

psychiatric disorders in the United States. Results from the National Comorbidity

M

Kishi, T., Yoshimura, R., Ikuta, T., Iwata, N., 2017. Brain-derived neurotrophic factor and major depressive disorder: Evidence from meta-analyses. Front. Psychiatry 8, 308.

ED

Kishino, A., Katayama, N., Ishige, Y., Yamamoto, Y., Ogo, H., Tatsuno, T., Mine, T., Noguchi, H., Nakayama, C., 2001. Analysis of effects and pharmacokinetics of subcutaneously

PT

administered BDNF. Neuroreport 12, 1067-1072. Koob, G.F., 1992. Drugs of abuse: Anatomy, pharmacology and function of reward pathways.

CC E

Trends Pharmacol. Sci. 13, 177-184.

Koob, G.F., 2000. Neurobiology of addiction. Toward the development of new therapies. Ann.

A

N. Y. Acad. Sci. 909, 170-185.

Koob, G.F., Ahmed, S.H., Boutrel, B., Chen, S.A., Kenny, P.J., Markou, A., O'Dell, L.E., Parsons, L.H., Sanna, P.P., 2004. Neurobiological mechanisms in the transition from drug use to drug dependence. Neurosci. Biobehav. Rev. 27, 739-749.

Krabbe, K.S., Nielsen, A.R., Krogh-Madsen, R., Plomgaard, P., Rasmussen, P., Erikstrup, C., Fischer, C.P., Lindegaard, B., Petersen, A.M., Taudorf, S., Secher, N.H., Pilegaard, H., Bruunsgaard, H., Pedersen, B.K., 2007. Brain-derived neurotrophic factor (BDNF) and type 2 diabetes. Diabetologia 50, 431-438. Lee, J.G., Shin, B.S., You, Y.S., Kim, J.E., Yoon, S.W., Jeon, D.W., Baek, J.H., Park, S.W.,

IP T

Kim, Y.H., 2009. Decreased serum brain-derived neurotrophic factor levels in elderly korean with dementia. Psychiatry Investig. 6, 299-305.

SC R

Leshner, A.I., 1997. Addiction is a brain disease, and it matters. Science 278, 45-47.

Lewis, C., 2006. Treating incarcerated women: Gender matters. Psychiatr. Clin. North Am. 29,

U

773-789.

N

Li, X., Wolf, M.E., 2015. Multiple faces of BDNF in cocaine addiction. Behav. Brain Res. 279,

A

240-254.

M

Licata, S.C., Shinday, N.M., Huizenga, M.N., Darnell, S.B., Sangrey, G.R., Rudolph, U., Rowlett, J.K., Sadri-Vakili, G., 2013. Alterations in brain-derived neurotrophic factor

ED

in the mouse hippocampus following acute but not repeated benzodiazepine treatment. PLoS One 8, e84806.

PT

Logrip, M.L., Barak, S., Warnault, V., Ron, D., 2015. Corticostriatal BDNF and alcohol addiction. Brain Res. 1628, 60-67.

CC E

Lommatzsch, M., Schloetcke, K., Klotz, J., Schuhbaeck, K., Zingler, D., Zingler, C., SchulteHerbrüggen, O., Gill, H., Schuff-Werner, P., Virchow, J.C., 2005a. Brain-derived

A

neurotrophic factor in platelets and airflow limitation in asthma. Am. J. Respir. Crit. Care Med. 171, 115-120.

Lommatzsch, M., Virchow, J.C., 2006. Letter regarding article by Ejiri et al., "possible role of brain-derived neurotrophic factor in the pathogenesis of coronary artery disease". Circulation 113, e724; author reply e724-e725.

Lommatzsch, M., Zingler, D., Schuhbaeck, K., Schloetcke, K., Zingler, C., Schuff-Werner, P., Virchow, J.C., 2005b. The impact of age, weight and gender on BDNF levels in human platelets and plasma. Neurobiol. Aging 26, 115-123. McEwen, B.S., 1998a. Protective and damaging effects of stress mediators. N. Engl. J. Med. 338, 171-179.

Y. Acad. Sci. 840, 33-44. B.S.,

2000.

Allostasis

and

allostatic

load:

Implications

SC R

McEwen,

IP T

McEwen, B.S., 1998b. Stress, adaptation, and disease. Allostasis and allostatic load. Ann. N.

for

neuropsychopharmacology. Neuropsychopharmacology 22, 108-124.

U

McEwen, B.S., 2002. Sex, stress and the hippocampus: Allostasis, allostatic load and the aging

N

process. Neurobiol. Aging 23, 921-939.

A

McEwen, B.S., 2003. Mood disorders and allostatic load. Biol. Psychiatry 54, 200-207.

Horm. Behav. 43, 2-15.

M

McEwen, B.S., Wingfield, J.C., 2003. The concept of allostasis in biology and biomedicine.

ED

Mendelson, J., Baggott, M.J., Flower, K., Galloway, G., 2011. Developing biomarkers for methamphetamine addiction. Curr. Neuropharmacol. 9, 100-103.

82.

PT

Miguel-Hidalgo, J.J., 2009. The role of glial cells in drug abuse. Curr. Drug Abuse Rev. 2, 72-

CC E

Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G., Group, P., 2009. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. BMJ 339, b2535.

A

Munkholm, K., Vinberg, M., Kessing, L.V., 2016. Peripheral blood brain-derived neurotrophic factor in bipolar disorder: A comprehensive systematic review and meta-analysis. Mol. Psychiatry 21, 216-228.

Murer, M.G., Yan, Q., Raisman-Vozari, R., 2001. Brain-derived neurotrophic factor in the control human brain, and in Alzheimer's disease and Parkinson's disease. Prog. Neurobiol. 63, 71-124. Nagahara, A.H., Tuszynski, M.H., 2011. Potential therapeutic uses of BDNF in neurological and psychiatric disorders. Nat. Rev. Drug Discov. 10, 209-219.

IP T

Nakahashi, T., Fujimura, H., Altar, C.A., Li, J., Kambayashi, J., Tandon, N.N., Sun, B., 2000.

Vascular endothelial cells synthesize and secrete brain-derived neurotrophic factor.

SC R

FEBS Lett. 470, 113-117.

Narvaez, J.C.M., Jansen, K., Pinheiro, R.T., Kapczinski, F., Silva, R.A., Pechansky, F.,

U

Magalhães, P.V., 2014. Psychiatric and substance-use comorbidities associated with

N

lifetime crack cocaine use in young adults in the general population. Compr. Psychiatry

A

55, 1369-1376.

M

Pan, W., Banks, W.A., Kastin, A.J., 1998. Permeability of the blood-brain barrier to neurotrophins. Brain Res. 788, 87-94.

ED

Pavarin, R.M., 2006. Substance use and related problems: A study on the abuse of recreational and not recreational drugs in Northern Italy. Ann. Ist Super Sanita. 42, 477-484.

PT

Pedraz, M., Martín-Velasco, A.I., García-Marchena, N., Araos, P., Serrano, A., RomeroSanchiz, P., Suárez, J., Castilla-Ortega, E., Barrios, V., Campos-Cloute, R., Ruiz, J.J.,

CC E

Torrens, M., Chowen, J.A., Argente, J., de la Torre, R., Santín, L.J., Villanúa, M., Rodríguez de Fonseca, F., Pavón, F.J., 2015. Plasma concentrations of BDNF and IGF-

A

1 in abstinent cocaine users with high prevalence of substance use disorders: Relationship to psychiatric comorbidity. PLoS One 10, e0118610.

Piccinni, A., Marazziti, D., Catena, M., Domenici, L., Del Debbio, A., Bianchi, C., Mannari, C., Martini, C., Da Pozzo, E., Schiavi, E., Mariotti, A., Roncaglia, I., Palla, A., Consoli, G., Giovannini, L., Massimetti, G., Dell'Osso, L., 2008. Plasma and serum brain-

derived neurotrophic factor (BDNF) in depressed patients during 1 year of antidepressant treatments. J. Affect. Disord. 105, 279-283. Poduslo, J.F., Curran, G.L., 1996. Permeability at the blood-brain and blood-nerve barriers of the neurotrophic factors: NGF, CNTF, NT-3, BDNF. Brain Res. Mol. Brain Res. 36, 280-286.

IP T

Polyakova, M., Stuke, K., Schuemberg, K., Mueller, K., Schoenknecht, P., Schroeter, M.L.,

2015. BDNF as a biomarker for successful treatment of mood disorders: A systematic

SC R

and quantitative meta-analysis. J. Affect. Disord. 174, 432-440.

Qin, X.Y., Cao, C., Cawley, N.X., Liu, T.T., Yuan, J., Loh, Y.P., Cheng, Y., 2017. Decreased

U

peripheral brain-derived neurotrophic factor levels in Alzheimer's disease: A meta-

N

analysis study (N=7277). Mol. Psychiatry 22, 312-320.

A

Rasmussen, P., Brassard, P., Adser, H., Pedersen, M.V., Leick, L., Hart, E., Secher, N.H.,

M

Pedersen, B.K., Pilegaard, H., 2009. Evidence for a release of brain-derived neurotrophic factor from the brain during exercise. Exp. Physiol. 94, 1062-1069.

ED

Ren, W., Luan, X., Zhang, J., Gutteea, P., Cai, Y., Zhao, J., Gu, Y., Wu, C., Su, H., Tao, J., Xie, Y., Lv, D., Feng, L., He, J., 2017. Brain-derived neurotrophic factor levels and

PT

depression during methamphetamine withdrawal. J. Affect. Disord. 221, 165-171. Roncero, C., Palma-Álvarez, R.F., Ros-Cucurull, E., Barral, C., Gonzalvo, B., Corominas-

CC E

Roso, M., Casas, M., Grau-López, L., 2016. Cocaine-induced psychosis and brainderived neurothrophic factor in patients with cocaine dependence: Report of two cases.

A

Clin. Psychopharmacol. Neurosci. 14, 109-113.

Russo, S.J., Mazei-Robison, M.S., Ables, J.L., Nestler, E.J., 2009. Neurotrophic factors and structural plasticity in addiction. Neuropharmacology 56 Suppl. 1, 73-82. Salas-Magaña, M., Tovilla-Zárate, C.A., González-Castro, T.B., Juárez-Rojop, I.E., LópezNarváez, M.L., Rodríguez-Pérez, J.M., Ramírez Bello, J., 2017. Decrease in brain-

derived neurotrophic factor at plasma level but not in serum concentrations in suicide behavior: A systematic review and meta-analysis. Brain Behav. 7, e00706. Sartor, C.E., Kranzler, H.R., Gelernter, J., 2014. Rate of progression from first use to dependence on cocaine or opioids: A cross-substance examination of associated demographic, psychiatric, and childhood risk factors. Addict. Behav. 39, 473-479.

IP T

Scherer, J.N., Schuch, S., Ornell, F., Sordi, A.O., Kessler, F.H.P., von, Lisia, D., Pechansky,

F., 2015. Higher levels of BDNF are associated with inpatient treatment adherence of

SC R

crack-cocaine users. Drug Alcohol Depend. 156, e183-245.

Schmidt, H.D., Duman, R.S., 2010. Peripheral BDNF produces antidepressant-like effects in

U

cellular and behavioral models. Neuropsychopharmacology 35, 2378-2391.

N

Seger, D., 2010. Cocaine, metamfetamine, and MDMA abuse: The role and clinical importance

A

of neuroadaptation. Clin. Toxicol. 48, 695-708.

M

Serra-Millàs, M., 2016. Are the changes in the peripheral brain-derived neurotrophic factor levels due to platelet activation? World J. Psychiatry 6, 84-101.

ED

Sharma, S., Ceballos, N., 2016. Risk and resilience: The role of brain-derived neurotrophic factor in alcohol use disorder. AIMS Neurosci. 3, 398-432.

PT

Sharma, S., Graham, R., Rohde, R., Ceballos, N.A., 2017. Stress-induced change in serum BDNF is related to quantitative family history of alcohol use disorder and age at first

CC E

alcohol use. Pharmacol. Biochem. Behav. 153, 12-17.

Shimizu, E., Hashimoto, K., Okamura, N., Koike, K., Komatsu, N., Kumakiri, C., Nakazato,

A

M., Watanabe, H., Shinoda, N., Okada, S., Iyo, M., 2003. Alterations of serum levels of brain-derived neurotrophic factor (BDNF) in depressed patients with or without antidepressants. Biol. Psychiatry 54, 70-75.

Sinha, R., 2011. New findings on biological factors predicting addiction relapse vulnerability. Curr. Psychiatry Rep. 13, 398-405.

Sohrabji,

F.,

Lewis,

D.K.,

2006.

Estrogen-BDNF

interactions:

Implications

for

neurodegenerative diseases. Front. Neuroendocrinol. 27, 404-414. Sordi, A.O., Pechansky, F., Kessler, F.H., Kapczinski, F., Pfaffenseller, B., Gubert, C., de Aguiar, B.W., de Magalhães Narvaez, J.C., Ornell, F., von Diemen, L., 2014. Oxidative

withdrawal. Psychopharmacology 231, 4031-4039.

IP T

stress and BDNF as possible markers for the severity of crack cocaine use in early

Srinivasan, S., Shariff, M., Bartlett, S.E., 2013. The role of the glucocorticoids in developing

SC R

resilience to stress and addiction. Front. Psychiatry 4, 68.

Toftdahl, N.G., Nordentoft, M., Hjorthøj, C., 2015. Prevalence of substance use disorders in

U

psychiatric patients: A nationwide Danish population-based study. Soc. Psychiatry

N

Psychiatr. Epidemiol. 51, 129-140.

A

Trajkovska, V., Marcussen, A.B., Vinberg, M., Hartvig, P., Aznar, S., Knudsen, G.M., 2007.

M

Measurements of brain-derived neurotrophic factor: Methodological aspects and demographical data. Brain Res. Bull. 73, 143-149.

ED

Umene-Nakano, W., Yoshimura, R., Ikenouchi-Sugita, A., Hori, H., Hayashi, K., Ueda, N., Nakamura, J., 2009. Serum levels of brain-derived neurotrophic factor in comorbidity

PT

of depression and alcohol dependence. Hum. Psychopharmacol. 24, 409-413. Ventriglia, M., Zanardini, R., Bonomini, C., Zanetti, O., Volpe, D., Pasqualetti, P., Gennarelli,

CC E

M., Bocchio-Chiavetto, L., 2013. Serum brain-derived neurotrophic factor levels in different neurological diseases. Biomed. Res. Int. 2013, 901082.

A

Viola, T.W., Tractenberg, S.G., Levandowski, M.L., Pezzi, J.C., Bauer, M.E., Teixeira, A.L., Grassi-Oliveira, R., 2014. Neurotrophic factors in women with crack cocaine dependence during early abstinence: The role of early life stress. J. Psychiatry Neurosci. 39, 206-214.

Volkow, N.D., Fowler, J.S., Wang, G.J., Telang, F., Logan, J., Jayne, M., Ma, Y., Pradhan, K., Wong, C., Swanson, J.M., 2010. Cognitive control of drug craving inhibits brain reward regions in cocaine abusers. Neuroimage 49, 2536-2543. Volkow, N.D., Koob, G., Baler, R., 2015. Biomarkers in substance use disorders. ACS Chem. Neurosci. 6, 522-525.

IP T

Volkow, N.D., Wang, G.J., Fowler, J.S., Tomasi, D., Telang, F., 2011. Addiction: Beyond dopamine reward circuitry. Proc. Natl. Acad. Sci. U. S. A. 108, 15037-15042.

SC R

von Diemen, L., Kapczinski, F., Sordi, A.O., de Magalhães Narvaez, J.C., Guimarães, L.S.,

Kessler, F.H., Pfaffenseller, B., de Aguiar, B.W., de Moura Gubert, C., Pechansky, F.,

U

2014. Increase in brain-derived neurotrophic factor expression in early crack cocaine

N

withdrawal. Int. J. Neuropsychopharmacol. 17, 33-40.

A

Wells, G., Shea, B., O'Connell, D., Peterson, J., Welch, V., Losos, M., Tugwell, P., 2014. The

M

Newcastle–Ottawa Scale (NOS) for assessing the quality of non-randomized studies in meta-analysis. The Ottawa Hospital, Ottawa.

ED

World Health Organization, 2013. World Health Organization (WHO). International Classification of Diseases (ICD-10). World Health Organization, Geneva.

PT

Wikler, A., 1973. Dynamics of drug dependence. Implications of a conditioning theory for research and treatment. Arch. Gen. Psychiatry 28, 611-616.

CC E

Wu, W., Tong, Y., Zhao, Q., Yu, G., Wei, X., Lu, Q., 2015. Coffee consumption and bladder cancer: A meta-analysis of observational studies. Sci. Rep. 5, 9051.

A

Yamamoto, H., Gurney, M.E., 1990. Human platelets contain brain-derived neurotrophic factor. J. Neurosci. 10, 3469-3478.

Yasutake, C., Kuroda, K., Yanagawa, T., Okamura, T., Yoneda, H., 2006. Serum BDNF, TNFalpha and IL-1beta levels in dementia patients: Comparison between Alzheimer's disease and vascular dementia. Eur. Arch. Psychiatry Clin. Neurosci. 256, 402-406.

Zanardini, R., Fontana, A., Pagano, R., Mazzaro, E., Bergamasco, F., Romagnosi, G., Gennarelli, M., Bocchio-Chiavetto, L., 2011. Alterations of brain-derived neurotrophic factor serum levels in patients with alcohol dependence. Alcohol. Clin. Exp. Res. 35, 1529-1533. Zhang, J., Zhang, X., Su, H., Tao, J., Xie, Y., Han, B., Lu, Y., Wei, Y., Sun, H., Wang, Y., Wu,

IP T

W., Zou, S., Liang, H., Zoghbi, A.W., Tang, W., He, J., 2014. Increased serum brain-

derived neurotrophic factor levels during opiate withdrawal. Neurosci. Lett. 571, 61-

SC R

65.

Zuccato, C., Cattaneo, E., 2009. Brain-derived neurotrophic factor in neurodegenerative

U

diseases. Nat. Rev. Neurol. 5, 311-322.

N

Zuccato, C., Marullo, M., Vitali, B., Tarditi, A., Mariotti, C., Valenza, M., Lahiri, N., Wild,

A

E.J., Sassone, J., Ciammola, A., Bachoud-Lèvi, A.C., Tabrizi, S.J., Di Donato, S.,

A

CC E

PT

ED

disease. PLoS One 6, e22966.

M

Cattaneo, E., 2011. Brain-derived neurotrophic factor in patients with Huntington's

Figure Legends Figure 1. Flow diagram of the meta-analysis of brain-derived neurotrophic factor (BDNF) in

ED

M

A

N

U

SC R

IP T

individuals with substance use disorders.

A

CC E

PT

Figure 2. BDNF serum levels.

A ED

PT

CC E

IP T

SC R

U

N

A

M

A

N

U

SC R

IP T

Figure 3. BDNF serum levels in alcohol users.

A

CC E

PT

ED

M

Figure 4. BDNF serum levels in crack/cocaine users

I N U SC R

Study

Year

Drug

Withdrawal

Biological material

Cavus, S.Y.

2012

Alcohol

No

Serum

Yes 2011

Alcohol

No Yes

2012

Alcohol

Garcia-Marchena, N

2017

Alcohol

Geisel, O.

2016

Alcohol

PT Alcohol

CC E

2015

2011

Alcohol

29

Men

Baseline: 22.98 ± 7.95

24.2 ± 5.1

pg/mL

101

39

Mixed

ng/mL

16

16

Mixed

6 months (withdrawal): 31.9 ± 10.1 6 months (no withdrawal): 27.5 ± 10.4 Plasma: 1.27 ± 1.12

Plasma 1.52 ± 0.68

Yes

Serum

Serum: 35.3 ± 11.1

Serum: 26.9 ± 9.5

Yes

Plasma

127.35 ± 236.00

483.05 ± 451.87

pg/mL

91

55

Mixed

Yes

Serum

Placebo drug group (baseline): 3446.2 ± 3716.8 ± 1403.7 1285.8 Placebo drug group (T1): 3511.9 ± 1493.5 Placebo drug group (T2): 3796.7 ± 2047.4 Day 1: 647.67 ± 510.13 623.29 ± 303.03

pg/mL

28

10

Mixed

pg/mL

99

33

Men

ng/mL

65

39

Mixed

pg/mL

64

75

Men

Yes No

Serum

Yes

Day 7: 554.74 ± 398.25

Yes

Day 14: 653.81 ± 518.95

Joe, K-H.

2007

Alcohol

Yes

Plasma

Baseline (Without Delirium Tremens): 14.8 ± 4.7 12.3 ± 3.3 Baseline (With Delirium Tremens): 6.2 ± 2.6 Day 7 (Without Delirium TreMens): 13.4 ± 3.5 Day 7 (With Delirium TreMens): 8.9 ± 4.4 389.5 ± 501.7 822.5 ± 420.7

Lee, B.C.

2009

Alcohol

No

Plasma

3502.2 ± 1726.9

861.75 ± 478.9

pg/mL

41

41

Men

Meng, D.

2011

Alcohol

Yes

Serum

Baseline: 12.69 ± 4.79

Baseline: 11.76 ± 5.05

ng/mL

14

10

Men

Sönmez, MB

2016

Alcohol

No

Serum

Baseline: 39.56 ± 17.09

44.72 ± 17.52

ng/mL

34

32

Men

A

Huang, M-C.

31

Plasma /

Yes

Heberlein, A.

Controls Gender (n)

Yes

ED

D'Sa, C. (1)

Serum

M

No

Cases (n)

Day 7: 33.5 ± 8.8

A

Costa, M.A.

Mean BDNF ± Mean BDNF ± Standard Deviation Standard Deviation Unit (cases) (controls) Baseline: 52.9 ± 19 65.3 ± 15.9 ng/mL

No

Serum

No Yes Yes

Yes

Day 7: 47.02 ± 17.25

I N U SC R Day 14: 51.47 ± 15.46

Yes

2011

Alcohol

Alcohol

2008

Cannabis

D'Souza, D.C.

2009

Cannabis

Ke, X.

2014

Ketamine

Ricci, V.

2011

Ketamine

Angelucci, F. (2)

2007

Cocaine

Corominas-Roso, M.

2013

Cocaine

Women: 2.47 ± 0.64

Women 1.7 ± 0.9

Yes and No*

Men: 2.00 ± 0.71

Men 2.01 ± 0.72

ng/mL

51

31

Mixed

ng/mL

37

37

Mixed

No

Plasma /

Plasma: 4.77 ± 3.50

Plasma: 4.08 ± 4.00

No

Serum

Serum: 35.97 ± 10.49

Serum: 41.70 ± 11.49

Not described No

Serum

5984.23 ± 335.9

5683.62 ± 237.65

pg/mL

26

20

Mixed

Serum

2552 ± 4067

2552 ± 4932

pg/mL

9

14

Mixed

Not described No

Serum

9.5 ± 6.68

14.37 ± 6.07

ng/mL

93

39

Mixed

Serum

12.7 ± 5.48

6.159 ± 3.27

ng/mL

17

11

Mixed

Not described No

Serum

5182.46 ± 662.43

5433.32 ± 392.41

pg/mL

15

15

Mixed

Serum

Baseline: 51,676 ± 17.505

76,044 ± 32,661

ng/mL

23

46

Mixed

ED

Angelucci, F. (4)

Yes and No* Plasma

A

Zanardini, R.

2017

M

Wilhelm, CJ

Yes

Day 12: 60,643 ± 22.607

2011

Cocaine

Yes

Serum

36.0 ± 9.2

25.8 ± 8.9

ng/mL

35

34

Mixed

Mardini, V

2017

Crack/cocaine

Not described

Serum

4.03 ± 4.48

6.67 ± 5.17

ng/mL

57

99

Women

CC E

PT

D'Sa, C. (2)

2015

Cocaine

Yes

Plasma

274.9 ± 200.3

269.4 ± 242.7

pg/mL

89

85

Mixed

Pianca, TG

2017

Crack/cocaine

No

Serum

Baseline: 17.87 ± 0.8

24.66 ± 1.02

ng/mL

90

81

Mixed

Narvaez, J.C.M.

2013

Crack/cocaine

von Diemen, L.

2014

Crack/cocaine

Viola, T.W.

2014

Crack/cocaine

A

Pedraz, M.

Yes Not described No

Day 21: 21.98 ± 1.07 Serum

14.21 ± 3.24

12.67 ± 3.74

ng/mL

53

50

Mixed

Serum

Baseline: 28.6 ± 11.0

39.5 ± 10.6

ng/mL

49

97

Men

8344.90 ± 2662.48

pg/mL

104

20

Women

Yes

Angelucci, F. (3)

2007

Opiate (heroin)

Chen, S.L.

2015

Heberlein, A. (1)

2011

No

Discharge: 35.5 ± 12.3 Plasma

Day 4: 13726.88 ± 5908.50

Yes

Day 11: 13101.84 ± 6507.44

Yes

Day 18: 14137.92 ± 7613.95 Serum

5091.59 ± 422.91

5433.32 ± 392.41

pg/mL

15

15

Mixed

Opiate (heroin)

Not described No

Plasma

10.1 ± 7.7

18.6 ± 9.4

ng/mL

172

102

Mixed

Opiate (heroin)

No

Serum

865.14 ± 358.8

556.62 ± 174.04

pg/mL

27

21

Men

I Opiate (heroin)

Luan, X

2017

Schuster, R.

N U SC R

Plasma

10.4 ± 7.823

16.7 ± 9.5

ng/mL

170

141

Mixed

Opiate (heroin)

Not described No

Serum

1692.94 ± 707.71

1194.46 ± 230.98

pg/mL

86

238

Mixed

2016

Opiate

No

Serum

48.25 ± 12.95

71.25 ± 17.43

ng/mL

30

51

Mixed

Tsai, M

2017

Opiate (heroin)

Yes

Serum

2835.8 ± 1340.7

2671.3 ± 2210.5

pg/mL

60

30

Men

Zhang, K.

2016

Opiate (heroin)

No

Serum

Baseline: 987.25 ± 915.26

52

Men

Yes

Baseline 3989.07 ± pg/mL 2018.87 After 26 weeks 4003.05 ± 2011.83 1241 ± 335.52 pg/mL

53

A

2017

72

90

Mixed

8.53 ± 0.572

ng/mL

23

19

Mixed

16.26 ± 4.72

ng/mL

59

59

Mixed

1.91 ± 0.8

ng/mL

53

31

Mixed

Chen, P.H.

2014

2015

No

Serum

After 26 weeks: 2491.54 ± 1397.32 Baseline (n=72): 1680 ± 577.37

No

Baseline (n=37): 1565 ± 511.4

Yes

One month (n=37): 1454 ± 555.7

MDMA (ecstasy)

Not described Not described Methamphetamine No

Serum

Non-psychotic: 11.28 ± 0.39 Psychotic:11.36 ± 0.51

Serum

Baseline: 9.84 ± 4.85

No

Acute phase: 9.32 ± 4.33

Yes

Subacute phase: 10.45 ± 5.41

Methamphetamine No

CC E

Huckans, M

2010

Opiate (heroin)

ED

Angelucci, F. (1)

2014

PT

Zhang, J

M

Lu RB

Plasma

Yes

Active use: 2.36 ± 1.17 Withdrawal: 2.52 ± 1.30

2005

Methamphetamine Yes

Plasma

2536.25 ± 2310.49

1352.61 ± 1188.15

pg/mL

50

50

Men

Ren, W.

2016

Methamphetamine No

Serum

Baseline (n=179): 1460.28 ± 490.69

1241.27 ± 335.52

pg/mL

179

90

Mixed

1224.55 ± 365.27

pg/mL

194

378

Mixed

A

Kim, D.J.

Su, H

2015

No

Baseline (n=40): 1621.41 ± 591.07

Yes

One month (n=40): 1363.70 ± 580.59

Methamphetamine Yes

* 21 individuals were in active use and 30 in withdrawal at BDNF dosing.

Serum

1487.90 ± 507.18

I N U SC R

Analysis

n subgroups

n users

n controls

SMD 95%CI Lower and Upper limit

P value

Trim and fill adjusted ES

I²

Serum

44

2171

A

Table 2. Brain-derived neurotrophic factor (BDNF) levels from serum samples.

2484

-0.302

-0.62

0.02

0.02

-0.99 (95%CI -1.40 to -0.58) [15]

95.9

Withdrawn

15

559

683

-0.215

-0.64

0.21

0.35

-0.31 (95%CI -0.75 to 0.13) [1]

91.64

Active use

20

1255

1499

-0.627

-1.18

-0.06

0.02

-1.54 (95%CI -2.20 to -0.73) [8]

97.54

664

486

-0.442

-0.84

-0.03

0.03

-0.70 (95%CI -1.15 to -0.255) [3]

89.81

34

35

0.346

-1.01

1.70

0.61

N/A

85.27

Alcohol

15

Cannabis

2

Ketamine

2

ED

Drug subtype

M

User status

50

0.281

-1.80

2.36

0.79

N/A

95.08

394

565

-1.038

-2.00

-0.06

0.03

-1.78 (95%CI -2.92 to -0.65) [3]

97.59

8

446

654

-0.416

-1.24

0.41

0.32

Unchanged

95.88

1

23

19

5.723

4.35

7.09

<0.001

N/A

0

5

499

676

-0.95

0.61

0.67

Unchanged

96.96

Alcohol

8

297

215

-0.287

-1.01

0.43

0.43

-0.47 (95%CI -1.22 to 0.28) [1]

92.58

Crack/cocaine

3

107

177

0.076

-0.87

1.02

0.87

Unchanged

92.56

Heroin

2

88

142

-0.171

-1.52

1.17

0.80

N/A

95.69

Methamphetamine

2

67

149

-0.435

-1.86

0.99

0.55

N/A

95.40

Alcohol

7

367

271

-0.597

-1.03

-0.16

0.007

-0.83 (95%CI -1.31 to -0.35) [2]

84.38

Crack/cocaine

3

162

224

-3.107

-6.25

0.03

0.05

Unchanged

99.01

Cannabis

1

9

14

-0.381

-1.22

0.46

0.37

N/A

Heroin

5

268

452

-0.026

-1.28

1.23

0.98

Unchanged

Heroin

CC E

MDMA/Ecstasy

PT

110

9

Crack/cocaine

Methamphetamine

-0.170

A

Serum and withdrawn

Serum and active use Drug subtype

97.97

I 1

17

11

Methamphetamine

3

432

527

N U SC R

Ketamine

1.137

-0.001

0.53

2.22

0.001

N/A

-1.03

1.02

0.99

Unchanged

97.82

N subgroups

N participants

N controls

SMD 95%CI Lower and Upper limit

P value

Trim and fill adjusted ES

I²

Plasma

14

994

679

0.126

-0.33

0.59

0.59

Unchanged

94.49

595

448

-0.155

-0.65

0.34

0.86

Unchanged

92.51

399

231

0.521

-0.48

1.52

0.44

Unchanged

96.34

300

230

0.110

-0.73

0.95

0.69

0.33 (95%CI -0.56 to 1.23) [1]

94.82

285

125

0.583

-0.06

1.23

0.07

Unchanged

85.83

342

243

-0.866

-1.14

-0.58

<0.001

N/A

61.44

67

81

0.592

0.25

0.92

0.002

N/A

0

3

171

121

-0.870

-1.29

-0.44

0.001

Unchanged

58.24

2

187

105

0.398

-0.38

1.17

0.31

N/A

86.46

Heroin

1

170

141

-0.730

-0.96

-0.50

0.001

N/A

0

Methamphetamine

2

67

81

0.592

0.25

0.92

0.001

N/A

0

Alcohol

4

129

109

0.807

-0.20

1.81

0.18

Unchanged

92.04

Crack/cocaine

1

98

20

0.977

0.48

1.47

<0.001

N/A

0

Heroin

1

172

102

-1.015

-1.27

-0.75

<0.001

N/A

0

Withdrawn

8

Active use

6

ED

User status

Drug subtype 7

Crack/cocaine

3

Heroin

2

Methamphetamine

2

CC E

Alcohol

M

Analysis

PT

A

Table 3. Brain-derived neurotrophic factor (BDNF) levels from plasma samples.

Plasma and withdrawn Drug subtype Alcohol

A

Crack/cocaine

Plasma and active use Drug subtype

I N U SC R

Table 4. Meta-regression of potential moderators brain-derived neurotrophic factor (BDNF) in substance use disorders. β

N studies

95%CI

P value

R²

A

Moderator User status

26

-0.009

-0.01

-0.00

<0.001

0.35

Mean age

26

0.065

0.00

0.12

0.02

0.05

Years of use

9

-0.021

-0.13

0.08

0.63

0.15

10

0.498

0.20

0.79

<0.001

0.04

23

-0.013

-0.02

-0.00

0.03

0.08

22

-0.028

-0.08

0.02

0.33

0.03

15

-0.020

-0.08

0.04

0.53

0.10

Age of the first use

10

0.058

-0.12

0.23

0.52

0.21

Length of abstinence

21

-0.466

-1.14

0.21

0.17

0.02

% of males

43

-0.009

-0.01

-0.01

<0.001

0.33

Mean age

43

0.009

-0.03

0.05

0.66

0.03

Years of use

22

0.003

-0.08

0.09

0.94

0.08

Age of the first use

21

0.268

0.01

0.45

0.005

0.06

Length of abstinence

17

-0.715

-1.60

0.17

0.11

0.10

% of males

14

-0.007

-0.01

0.00

0.26

0.05

Mean age

13

-0.009

-0.08

0.06

0.79

0.07

Age of the first use Length of abstinence

Mean age

CC E

Years of use

N/A

PT

Withdraw % of males

ED

% of males

M

Active use

Sample

A

Serum

Plasma

I Age of the first use

6

Length of abstinence

8

N U SC R

8

0.039

-0.06

0.14

0.47

0

0.021

-0.23

0.27

0.86

0

0.619

-0.41

1.65

0.32

0.12

A

CC E

PT

ED

M

A

Years of use