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Drug and Alcohol Dependence 232 (2022) 109284
Available online 11 January 2022
0376-8716/© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Different brain oxidative and neuroinammation status in rats during
prolonged abstinence depending on their ethanol relapse-like drinking
behavior: Effects of ethanol reintroduction
S. Fern´
andez-Rodríguez
a
,
1
, M.J. Cano-Cebri´
an
a
,
1
, S. Rius-P´
erez
b
, S. P´
erez
b
, C. Guerri
c
,
L. Granero
a
, T. Zornoza
a
,
*
, A. Polache
a
a
Departament de Farm`
acia i Tecnologia Farmac`
eutica i Parasitologia, Universitat de Val`
encia, Avda Vicente Andr´
es Estell´
es, s/n 46100 Burjassot, Spain
b
Departament de Fisiologia, Universitat de Val`
encia, Avda Vicente Andr´
es Estell´
es, s/n 46100 Burjassot, Spain
c
Department of Molecular and Cellular Pathology of Alcohol, Príncipe Felipe Research Center, Carrer d′Eduardo Primo Yúfera, 3, 46012 Valencia, Spain
ARTICLE INFO
Keywords:
Alcohol relapse
Alcohol deprivation effect
Oxidative stress
Neuroinammation
Craving
ABSTRACT
Rationale: Accumulating evidence suggests that chronic alcohol consumption is associated with excessive
oxidative damage and neuroinammatory processes and these events have been associated to early alcohol
withdrawal. In the present research we wonder if brain oxidative stress and neuroinammation remains altered
during prolonged withdrawal situations and whether these alterations can be correlated with relapse behavior in
alcohol consumption. The effects of alcohol reintroduction were also evaluated
Methods: We have used a model based on the alcohol deprivation effect (ADE) within a cohort of wild-type male
Wistar rats. Two subpopulations were identied according to the alcohol relapse-like drinking behavior dis-
played (ADE and NO-ADE subpopulations). Oxidized and reduced glutathione content was determined within the
hippocampus and the amygdala using a mass spectrometry method. The levels of mRNA of seven different in-
ammatory mediators in the prefrontal cortex of rats were quantied. All the analyses were performed in two
different conditions: after 21-day alcohol deprivation (prolonged abstinence) and after 24 h of ethanol rein-
troduction in both subpopulations.
Results: ADE and NO-ADE rats showed different endophenotypes. ADE rats always displayed a signicant lower
alcohol intake rate and ethanol preference than NO-ADE rats. The results also demonstrated the existence of
altered brain redox and neuroinammation status after prolonged abstinence exclusively in ADE rats. Moreover,
when ethanol was reintroduced in the ADE subpopulation, altered oxidative stress and neuroinammatory
markers were restored.
Conclusions: Present ndings provide new mechanisms underlying the neurobiology of relapse behavior and
suggest the development of new pharmacological approaches to treat alcohol-induced relapse.
1. Introduction
Alcohol Use Disorders (AUDs), formerly called alcohol dependence
or alcohol abuse, are complex, chronic disorders with a high relapse rate
(Koob and Volkow, 2016; Rehm, 2011). Thus, even after successful
detoxication and abstinence treatment, an alcohol-dependent patient
remains at risk of relapse. Drug craving may even incubate over time,
leading to a relapse risk several months after detoxication (Pickens
et al., 2011). Literature shows that 60–80% of abstinent alcoholics will
relapse during their lifetime (Barrick and Connors, 2002; Weiss et al.,
2001). All in all, drug seeking and relapse are the main clinical problems
related to AUDs. Thus, deepen the understanding of the underlying
neurobiology of relapse behavior could be essential for improving
available treatments to reduce the relapse rate or, to a lesser extent,
reduce alcohol intake (Cannella et al., 2019; Reilly et al., 2014; Spanagel
and Vengeliene, 2013).
Accumulating evidence from preclinical and clinical studies suggests
that chronic alcohol consumption is associated with excessive oxidative
* Corresponding author.
E-mail address: teodoro.zornoza@uv.es (T. Zornoza).
1
These authors have contributed equally to this work
Contents lists available at ScienceDirect
Drug and Alcohol Dependence
journal homepage: www.elsevier.com/locate/drugalcdep
https://doi.org/10.1016/j.drugalcdep.2022.109284
Received 19 October 2021; Received in revised form 17 December 2021; Accepted 3 January 2022
Drug and Alcohol Dependence 232 (2022) 109284
2
damage and reduced levels of endogenous antioxidants, leading to
excessive reactive oxygen species (ROS) production (Das et al., 2007;
Jung and Metzger, 2016; Peng et al., 2005). These alterations in the
oxidative stress status are not only restricted to the period of con-
sumption itself but also have been linked to the early withdrawal phase.
Thus, Huang et al. (2009) demonstrated the existence of alterations in
the oxidative stress status only during early, but not prolonged, alcohol
withdrawal symptoms in alcoholic patients. In experimental animals,
Jung et al. (2008) clearly showed that oxidative stress is even more
intense during early withdrawal than during previous ethanol exposure.
At present, it is not known if these changes in oxidative brain status are
also evident in prolonged withdrawal.
On the other hand, it has been suggested that inammatory factors
also play a key role in the development of alcohol-related behavioral and
mood disorders (Kelley and Dantzer, 2011; Leclercq et al., 2014). In the
case of AUDs, a number of animal and human studies have demonstrated
the role of neuroinammation in the pathophysiology of the disease
(Robinson et al., 2014). The neuroinammatory response has been
observed at the mRNA and/or protein level when different cells or tis-
sues are directly exposed to ethanol (Alfonso-Loeches et al., 2010, 2009,
2014). Systemic administration of ethanol to experimental animals also
induces neuroinammation. Thus, binge intoxication induces an in-
ammatory response in the brain of rats (Crews et al., 2006; Pascual
et al., 2007) or mice (Crews et al., 2013; Kane et al., 2014; Montesinos
et al., 2016), as does chronic exposure to ethanol in mice (Alfonso--
Loeches et al., 2010; Whitman et al., 2013; Lippai et al., 2013). The
inammatory response has also been described after 24-hour ethanol
withdrawal and a 15-day period of alcohol exposure. Curiously, this
response was dependent on the cytokine and the brain region considered
(Knapp et al., 2016).
A very important aspect that, according to our available information,
has not been explored so far is whether the phenomena of alteration of
the oxidative stress state of the brain and neuroinammation, appear in
late withdrawal situations and whether these alterations can be corre-
lated with relapse behavior in alcohol consumption.
It is well-known that the alcoholic population is heterogeneous in
nature (Epstein et al., 1995; Lesch and Walter, 1996; Windle and
Scheidt, 2004). In fact, AUDs can be considered the result of a complex
interplay between polygenic, environmental, and neurobiological
components leading to very heterogeneous patient populations (Can-
nella et al., 2019). Identifying specic behavioral and genetic traits that
could predispose individuals to develop drug abuse is a major goal in the
eld of Neurobiology of Addiction (Reilly et al., 2014; Spanagel and
Vengeliene, 2013). The phenomenon of relapse in alcoholics is another
behavioral trait of AUDs that clearly shows a great heterogeneity in
patient populations. The neurobiology of alcohol relapse has tried to be
studied with some success using different animal models. Among the
repertoire of animal models of relapse presently available, the model
based on the alcohol deprivation effect (ADE) is probably one of the
most commonly used preclinical approach to study the ethanol
relapse-like drinking behavior. This model is considered an excellent
model in its face, predictive and ecological validity (Bell et al., 2012;
Spanagel, 2017). The use of the ADE model reveals the existence of an
enormous heterogeneity in the relapse behaviour in non-selected rat
lines that has been linked by many authors to greater variability in the
expression of several genes that may have a great importance in the
functioning of critical brain areas (Vengeliene et al., 2014). To date, it is
not known whether this heterogeneity in relapse behavior is related to a
different neuroinammatory response, with a differentiated alteration
in the oxidative stress control mechanisms, or with both phenomena at
the same time.
Therefore, the main aim of the current study was to investigate the
existence of brain oxidative stress and to evaluate the neuro-
inammation status in the late ethanol withdrawal in two sub-
populations of male Wistar rats with a long experience in voluntary
alcohol consumption. These subpopulations were selected according to
the alcohol relapse-like drinking behavior displayed after experiencing
several deprivation and reintroduction episodes. This research focuses
particularly on the exploration of a crucial stage of the disease: the
abstinence period which leads to the relapse phenomenon, and more
specically to the long-lasting abstinence period (21 days). We also
examined the effect of the alcohol reintroduction in brain oxidative
stress as well as in the expression of different neuroinammation factors.
We have focused our present research on the hippocampus, amygdala
and prefrontal cortex (PFC) as these brain areas are highly affected by
ethanol consumption and abstinence-induced damage (Chefer et al.,
2011; Elibol-Can et al., 2011; Roberto et al., 2004).
2. Materials and methods
2.1. Animals
In this study, 58 male Wistar rats purchased from ENVIGO (Barce-
lona, Spain) were used. All animals, weighing 356 ±3.2 g at the
beginning of the experiment, were housed in individual cages in a
temperature- and humidity-controlled room with a 12-hour inverted
light/dark cycle (on 22:00, off 10:00). All the procedures were per-
formed in accordance with Directive 2010/63/EU, Spanish laws (RD
53/2013) and animal protection policies. The Animal Care Committee of
University of Valencia and the regional government (Conselleria de
Agricultura, Medio Ambiente y Cambio Clim´
atico) approved and
authorized all experiments.
2.2. Experimental design: long-term voluntary alcohol drinking procedure
As can be seen in Fig. 1, the 58 animals were divided into two
experimental groups. Animals from the rst experimental group
(Experimental group 1; n =43) were subjected to a long-term voluntary
alcohol drinking procedure (total duration: 32 weeks) with repeated
deprivation phases. This procedure has previously been used and vali-
dated under our experimental conditions (Orrico et al., 2013, 2014;
Cano-Cebri´
an, 2021). During the procedure, animals were given
continuous free access to tap water and 5%, 10% and 20% (v/v) ethanol
solutions in their home cages. Alcohol drinking solutions were prepared
from 96% v/v (Scharlau S.A., Spain) and then diluted with tap water to
the different concentrations. Animals were subjected to three random
deprivation periods (DPs). The duration of the drinking and DPs was
irregular in order to prevent behavioural adaptations (Vengeliene et al.,
2005). Moreover, when bottles were removed to quantify alcohol con-
sumption, the position of the four bottles was always changed to avoid
location preferences.
Animals from the second group of rats (Experimental group 2;
n=15) were distributed into two experimental subgroups, which were
given continuous ad libitum access to tap water (“Water” subgroup;
n=9) or tap water and 5%, 10% and 20% alcohol dilutions (“Ethanol”
subgroup; n =6) during 32 weeks without any deprivation phase. After
this period, these rats were euthanized to remove their brains.
2.3. Experiments
Three experiments were designed to achieve the planned aims.
2.3.1. Experiment 1: identication of two subpopulations of rats according
to their alcohol relapse-like drinking behavior
In this experiment, we studied the manifestation of the ADE in the
cohort of 43 rats of Experimental Group 1. Ethanol intake (expressed as
g/kg/day), total uid intake (expressed in mL), total ethanol preference
(expressed in percentage as the quotient of mL of ethanol consumption
and total uid intake) and ethanol preference from every alcohol dilu-
tion (mL of 5, 10 or 20% ethanol consumption and total alcohol intake,
expressed in percentage) were calculated individually. Basal values in
each animal were determined by averaging the obtained values during
S. Fern´
andez-Rodríguez et al.
Drug and Alcohol Dependence 232 (2022) 109284
3
the last three pre-abstinence days. The measurements for the three days
following the reintroduction of the ethanol bottles (post-abstinence
days) were also calculated in order to determine the manifestation of the
ADE phenomenon. N.B. the ADE is a marked and transient increase in
the alcohol intake over basal values following a period of deprivation
which is correlated with the loss of control associated with the alcohol
relapse-like drinking behavior (Spanagel, 2017). All animals were sub-
jected to three random abstinence periods. A positive ADE was consid-
ered when alcohol consumption increased by more than 50% with
respect to the basal consumption determined before the deprivation
period (Sinclair et al., 1973). Animals that, during the experiment,
displayed two or three positive ADEs were assigned to the so-called
“ADE” subgroup, while rats that expressed only one or no ADE epi-
sodes were assigned to the “NO-ADE” subgroup. After this rst
adscription, we proceeded in experiment 1 to characterize the drinking
phenotype of both subgroups by analysing several variables such as:
total ethanol intake (g/kg/day), total uid intake (mL/day), weight
(kg), total ethanol preference (%), and particular ethanol dilution
preferences (%). For this characterization, data from the entire cohort of
rats (n =43) was used.
To perform Experiments 2 and 3 (see below), twenty-three of the
forty-three rats in Experimental Group 1 above were forced to undergo a
fourth period of abstinence. Of these twenty-three rats, eleven rats from
the ADE (n =5) and NO-ADE (n =6) subgroups were sacriced after
21-day of abstinence (hereinafter referred to as “ADE Abs” and “NO-ADE
Abs” subgroups) and their brains were extracted. The twelve remaining
rats were not only subjected to the fourth abstinence period but also, at
the end of this period, they were allowed free access to alcohol for 24 h,
after which they were euthanized and their brains processed as well.
Hereinafter, we will refer to these 12 animals as "ADE Reintr" (n =5)
and "NO-ADE Reintr" (n =7) subgroups. The remaining twenty of the
forty-three rats in Experimental Group 1 were extracted from the present
research and were used for other pharmacological experiments (see
Fig. 1). Animals of the “Water” (n =9) and “Ethanol” (n =6) subgroups,
belonging to Experimental Group 2, were used as control groups for
experiments 2 and 3.
2.3.2. Experiment 2: determination of brain oxidation levels
Drug seeking and relapse are under the control of specic brain
nuclei including the hippocampus, amygdala, PFC, insula and dorsal
striatum (Koob and Volkow, 2016), so that experiment 2 and 3 focused
on some of them. Probably, it would have been interesting to determine
both oxidative and neuroinammatory response in the same nuclei,
however, the amount of biological material available led us to perform
our study in different brain regions. For the measurement of reduced
Glutathione (GSH) and oxidized Glutathione (GSSG) levels, the hippo-
campus and amygdala were dissected. Tissues were homogenized in
phosphate buffered saline (PBS) and 10 mmol/L N-ethylmaleimide
Fig. 1. Experimental protocol used in Experiment 1, 2 and 3. Animals from Experimental group 1 (n =43) were categorised in two different subpopulations, ADE
and NO-ADE, based on the manifestation of the Alcohol Deprivation Effect (ADE) (Experiment 1). For the development of experiments 2 and 3, 23 rats were selected.
In a random-manner, 10 rats from the ADE and 13 rats from the NO-ADE subgroup were assigned to the ADE Abstinence (represented in framed blue; n =5), ADE
Reintroduction (solid blue; n =5), NO-ADE Abstinence (framed green; n =6) and NO-ADE Reintroduction (solid green; n =7) subgroups. “Abstinence” animals were
sacriced after 21-day ethanol abstinence, while “Reintroduction” animals were sacriced after 24-hours ethanol reintroduction. Animals from the second group of
rats (Experimental group 2; n =15) were distributed into two experimental subgroups, which were given continuous ad libitum access to tap water (“Water”
subgroup; n =9) or tap water and 5%, 10% and 20% alcohol dilutions (“Ethanol” subgroup; n =6) during 32 weeks without any deprivation phase. After this period,
all animals were sacriced in order to obtain their brains. The same color legend has been applied in the other Figures. (For interpretation of the references to colour
in this gure, the reader is referred to the web version of this article.)
S. Fern´
andez-Rodríguez et al.
Drug and Alcohol Dependence 232 (2022) 109284
4
(NEM) (Sigma-Aldrich, St. Louis, MO, USA) (pH 7.0), with a
tissue-buffer ratio of 1:4. Then, perchloric acid solution was added to
obtain a nal concentration of 4% and samples were centrifuged at
11.000 rpm for 15 min at 4 ◦C. Supernatants were injected in the
chromatographic system (UPLC-MS/MS).
The chromatographic system consisted of a Micromass QuatroTM
triple-quadrupole mass spectrometer (Micromass, Manchester, UK)
equipped with a Zspray electrospray ionization source operating in the
positive ion mode with a LC-10A Shimadzu (Shimadzu, Kyoto, Japan)
coupled to the MassLynx 4.1 software for data acquisition and pro-
cessing. Samples were analyzed by reversed-phase UPLC with a C18
Mediterranea SEA column (Teknokroma, Barcelona, Spain)
(5.060.21 cm) with 3 mm particle size. In all cases, 20
μ
l of the super-
natant were injected onto the analytical column. The mobile phase
consisted of the following gradient system (min/%A/%B) (A, 0.5%
formic acid; B, isopropanol/acetonitrile 50/50; 0,5% formic acid): 5/
100/0, 10/0/100, 15/0/100, 15.10/100/0, and 60/100/0. The ow
rate was set at 0.2 mL/min. Positive ion electrospray tandem mass
spectra were recorded with the electrospray capillary set at 3 kV and a
source block temperature of 120 ◦C. Nitrogen was used as drying and
nebulizing gas at ow rates of 500 and 30 L/h, respectively. Argon at
1.5610–3 mbar was used as collision gas for collision-induced dissoci-
ation. An assay based on UPLC-MS/MS with multiple reaction moni-
toring was developed using the transitions m/z, cone energy (V),
collision energy (eV) and retention time (min) for each compound that
represents favorable fragmentation pathways for these protonated
molecules (Table 1). This procedure was previously validated under our
experimental conditions (Rius-P´
erez et al., 2020). Calibration curves
were obtained using twelve-point (0.01–100 mmol/l) standards (pur-
chased from Sigma-Aldrich, St Louis, USA) for each compound. The
concentrations of metabolites were expressed as nmol/mg of protein.
2.3.3. Experiment 3: determination of neuroinammation
The gene expression levels of different inammatory mediators, such
as TNF-
α
, IL-6, IL-1β, iNOS, Nfκβ, HMGB1 and NLRP3, were determined in
brain prefrontal cortex (PFC). RNA was extracted using Trizol according to
the manufacturer’s instructions (Sigma). RNA was measured in a Nano-
Drop ND-1000 Spectrophotometer (260/280 nm ratio). First-strand cDNA
synthesis was performed with the NZY First-Strand cDNA Synthesis Flex-
ible PAck (NZYtech) using 1000 ng of total RNA according to the manu-
facturer’s instructions. The RT-PCR reactions contained LightCycler 480
SYBR Green I Master (2 ×; Roche Applied Science), 5
μ
M forward and
reverse primers, and 1
μ
l of cDNA. RT-PCR was performed in a Light-
Cycler® 480 System (Roche). The relative expression ratio of a target/
reference gene was calculated according to the Pfaf equation (Pfaf,
2001). Housekeeping cyclophilin A (PPIA) was used as an internal control.
The sequences of primers used in this study are: PPIA-F 5′
TGTGCCAGGGTGGTGACTTT 3′, PPIA-R 5′CGTTTGTGTTTGGTCCAGCAT
3′; IL1β-F 5′CAGCAGCATCTCGACAAGAG 3′, IL1β-R 5′CATCATCCCAC-
GAGTCACAG 3′; IL6-F 5′TGTGCAATGGCAATTCTGAT 3′, IL6-R 5′
CGGAACTCCAGAAGACCAGAG 3′; TNF
α
-F 5′GGTGGGCTGGGTAA-
CAAGTA 3′, TNF
α
-R 5′AGGGACAAACCACAATATAGGAAAA 3′;
HMGB1-F 5′ATCTAAATACGGATTGCTCAGGAA 3′, HMGB1-R 5′AGG-
GACAAACCACAATATAGGAAAA 3′; iNOS-F 5′ACCAGCACCTACCAGCT-
CAA 3′, iNOS-R 5′CCCTTTGTTGGTGGCATACT 3′; Nfκβ-F 5′
CAAGAGTGACGACAGGGAGAT 3′, Nfκβ-R 5′GCCAGCAGCATCTTCACAT
3′. Fluorescence was recorded in the annealing/elongation step in each
cycle. To check the specicity of the primers, a melting curve analysis was
performed at the end of each PCR. All these procedures were previously
validated in our laboratory (Alfonso-Loeches et al., 2014; Ure˜
na-Peralta
et al., 2020; Vall´
es et al., 2004).
2.4. Statistical analysis
To analyze, after each deprivation period (DP), the relapse-like
drinking behavior in experiment 1, two statistical analyses were per-
formed: rst, a two-way repeated measures ANOVA with time being the
within-groups factor and subpopulation the between-groups factor.
Alcohol intake or preference along 6 days (three days before and after
each DP were used. Secondly, the ethanol consumption or preference of
the 3 days before and after the considered DP were collapsed and
compared by using a paired Student’s t-test. Moreover, ethanol intake
and ethanol preference between the ADE and NO-ADE groups along the
four consumption periods experienced were analyzed using a mixed
two-way ANOVA, with consumption period being the within-groups fac-
tor and subpopulation the between-groups factor. For this comparison,
data from individual rats were collapsed at each consumption period
considered (Figs. 2D and 3D). In experiment 1, particular ethanol-
dilution preferences between the ADE and NO-ADE groups along
months were analyzed through a 3-way ANOVA with months being the
within-groups factor and ethanol dilution and subpopulation the
between-groups factors (Fig. 4A). Moreover, after collapsing data along
time, a 2-way ANOVA was performed with ethanol dilution and subpop-
ulation being the studied factors (Fig. 5B). Whenever signicant differ-
ences were found, post-hoc adjusted Bonferroni tests were performed.
In experiments 2 and 3, a power analysis was performed that
revealed a sample size of N =5/group was determined necessary to
detect the key variables at an
α
level of p <0.05% and 80% power. In
both experiments, levels of GSH, GSSG, GSH/GSSG and mRNA expres-
sion were analyzed using one-way analysis of variance (ANOVA).
Additionally, a two-way ANOVA was also performed with subpopulation
and alcohol reintroduction being the factors analyzed. Whenever signi-
cant differences were found, a post-hoc Tukey test was performed. All
data are presented as mean ±standard error (SE). Analyses were carried
out using GraphPad Prism v.8.0.1. and IBM SPSS Statistics v.26.
3. Results
3.1. Experiment 1: identication of two subpopulations of rats depending
on their alcohol relapse-like drinking behavior
Based on the manifestation or not of the ADE phenomenon, experi-
ment 1 allowed us to categorize our rats according to their relapse-like
drinking behavior. According to the obtained results, 30 animals tted
the ADE group conditions, while the other 13 rats were assigned to the
NO-ADE group. Fig. 2A shows the average alcohol intake, expressed as
grams per kilogram per day, and the time course in both experimental
groups. Data included in each framed-line rectangle (see Fig. 2A), were
used to perform a two-way ANOVA for repeated measures at each DP.
The signicant effects on alcohol intake detected were: time [F (5,
205) =8.930; p <0.001], subpopulation [F(1, 41) =7.150; p =0.011]
and subpopulation x time interaction [F(5, 205)=6.108; p <0.001] in
DP-1; time [F(5, 205)=10.628; p <0.001] and subpopulation x time
interaction [F(5, 205)=2.839; p =0.017] in DP-2; subpopulation [F(1,
41) =5.855; p =0.020] and subpopulation x time interaction [F(5,
205)=2.542; p =0.029] in DP-3. Data extracted and collapsed from
Fig. 2A have been used to perform additional statistical analysis depic-
ted in Fig. 2B, C and D.
As can be observed in Fig. 2B (ADE group) and according to paired t-
tests, average ethanol intake increased signicantly, with respect to the
basal value, along the three consecutive deprivation periods assayed: [T
(29) = − 7.521; p <0.0001], [T(29) = − 5.046; p <0.0001], and [T
(29) = − 2.605; p =0.014], respectively, thus conrming the depriva-
tion effect in this group of animals. On the other hand, animals assigned
Table 1.-
Transitions and retention times for analytes determined by LC–MS/MS.
Analyte Cone (V) Collision (eV) Transition (m/Z) Retention time (min)
GS-
NEM
30 15 433 >304 4.32
GSSG 30 25 613 >355 1.46
S. Fern´
andez-Rodríguez et al.
Drug and Alcohol Dependence 232 (2022) 109284
5
to the NO-ADE subgroup (see Fig. 2C) clearly showed a different relapse-
like drinking behavior pattern. Specically, neither in the rst [T
(12) = − 0.592; p =0.564] nor in the third [T(12) =1.391; p =0.189]
deprivation period did animals display a signicant increase in average
ethanol intake. Moreover, differences detected in the second deprivation
period were not very intense [T(12) = − 2.254; p =0.044], conrming
that these animals tend not to show relapse behavior. Another differ-
ential behavioral trait between these two subpopulations of rats is the
voluntary alcohol intake displayed along time. As can be observed in
Fig. 2A, from the huge amount of data collected, on most days, ADE rats
displayed a lower alcohol consumption than NO-ADE animals. The two-
way ANOVA for repeated measures conrmed these observations.
ANOVA revealed a signicant subpopulation effect [F(1, 41)=5.485;
p=0.024] and consumption period effect [F(1, 41)=5.485; p =0.024]
on alcohol intake (Fig. 2D).
When alcohol preference was analyzed between the ADE and NO-
ADE groups, the results obtained were even clearer. Fig. 3A shows the
time course of average alcohol preference in both experimental groups
(ADE and no ADE). Data included in each framed-line rectangle (see
Fig. 3A), were used to perform a two-way ANOVA for repeated measures
at each DP. The signicant effects detected on alcohol preference were:
time [F(5, 205)=8.976; p <0.001], subpopulation [F(1, 41)=10.621;
p=0.002] and subpopulation x time interaction [F(5205) =3.383;
p=0.006] on alcohol preference in DP-1; time [F(5, 205) =3.148;
p=0.009], subpopulation [F(1, 41) =6.185; p =0.017] and subpopu-
lation x time interaction [F(5, 205) =3.515; p =0.005] in DP-2; time [F
(5, 205)=2.664; p =0.023] and subpopulation [F(1, 41)=13.489;
p=0.001] in DP-3. As can be observed in Fig. 3B, average ethanol
preference signicantly increased from approximately 40% to nearly
60%, with respect to the basal value, along the three consecutive
deprivation periods assayed: [T(29) = − 7.596; p <0.0001], [T
(29) = − 5.407; p <0.0001], and [T(29) = − 3.084; p =0.004] in the
ADE subgroup, thus re-conrming the expression of the ADE phenom-
enon in this subpopulation of rats. Conversely, animals assigned to the
NO-ADE subgroup (Fig. 3C) did not show signicant changes in their
alcohol preference after experiencing a DP. In Fig. 3C, statistical analysis
results were: T(12) = − 1.259; p =0.231], [T(29) = − 0.054; p =0.957]
and [T(12) =1.064; p =0.308] for the 1st, 2nd and 3rd DP, respec-
tively. Curiously, as can be observed in Fig. 3D, ADE rats displayed a
lower ethanol preference than NO-ADE rats throughout the experiment.
The two-way ANOVA for repeated measures conrmed these observa-
tions. ANOVA revealed a signicant subpopulation effect [F(1, 41) =
10.841; p =0.002] and consumption period effect [F(1, 41) =5.485;
p=0.024] on alcohol preference (Fig. 3D).
Particular preferences for each ethanol dilution were also explored in
both subpopulation of rats along time. As can be observed in Fig. 4, ADE
and NO-ADE rats displayed, once again, differential behaviors. The
three-way ANOVA for repeated measures conrmed these observations.
ANOVA revealed a signicant ethanol dilution effect [F(2, 123)=
185.771; p <0.001] and ethanol dilution x subpopulation interaction
effect [F(2, 123) =3.944; p =0.022] on particular alcohol preference
(Fig. 4A). As the factor months revealed no statistical differences, an
Fig. 2. Average voluntary ethanol intake, expressed in g/kg/day, displayed by rats categorized in the ADE (blue triangle, n =30) or NO-ADE (green circle, n =13)
subgroups. (A) time course in both experimental groups along the entire experiment. As depicted, animals experienced 4 consumption (CP) and 3 deprivation periods
(DP). (B and C) Manifestation of the ADE phenomenon in two different subpopulations. Bars represent the collapsed values of alcohol intake determined during the 3
days before and after each deprivation period in the ADE (B) and NO-ADE (C) subgroup. (D) Compared average voluntary ethanol intake between ADE and NO-ADE
rats along the four ethanol-consumption periods assayed, excluding the 3 days post-abstinence in each period. Asterisks denote signicant differences relative to the
pre- and post-abstinence period (panel B and C) or between ADE and NO-ADE groups (panel D). [* p <0.05; * * p <0.01; * ** * p <0.0001]. (For interpretation of
the references to colour in this gure, the reader is referred to the web version of this article.)
S. Fern´
andez-Rodríguez et al.
Drug and Alcohol Dependence 232 (2022) 109284
6
additional 2-way ANOVA, collapsing data, was performed. As depicted
in Fig. 4B, animals depending on the subpopulation considered dis-
played a different alcohol consumption pattern, as the interaction be-
tween subpopulation x ethanol dilution (F
2,30
=27,75; p <0.001) was
statistically signicant. As can be observed in this Figure, ADE animals
showed a signicant lower preference for 5% ethanol dilution in com-
parison with NO-ADE animals (p <0.001), however a signicant higher
preference for 20% ethanol dilution was detected in ADE rats with
respect to NO-ADE rats (p <0.001).
The total uid intake, i.e. the consumed volume of water and ethanol
per day was also analysed. No statistical differences between the two
experimental groups were found. ADE and NO-ADE rats consumed an
average volume of 38.62 ±0.71 and 35.56 ±0.55 mL/day, respec-
tively. Finally, the body weight of the animals was checked throughout
the experiment. Their growth-curves did not differ from previous ones
obtained in our laboratory (data not shown) (Orrico et al., 2013; Can-
o-Cebri´
an et al., 2021). At the end of the experiment, ADE and NO-ADE
rats weighed 612.4 ±9.4 and 581.7 ±11.6 g, respectively. No signi-
cant differences between the two experimental groups were detected.
3.2. Experiment 2: determination of brain oxidation levels
To assess the possible oxidative stress by ethanol intake, the levels of
GSSG and GSH were determined in two different brain regions: hippo-
campus (Fig. 5A, B) and amygdala (Fig. 6A, B). As the GSSG/GSH ratio is
one of most common index of oxidative stress, it was also calculated
(Figs. 5C, and 6C). As can be observed in Figs. 5C and 6C, under our
experimental conditions, animals with long-term exposure to voluntary
ethanol consumption did not show statistical differences with respect to
control animals when the GSSG/GSH ratio in either the hippocampus or
amygdala was analyzed. However, the most remarkable results were
obtained within the hippocampus, where a rather large difference be-
tween the ADE and NO-ADE groups in the GSSG/GSH ratio was detected
when animals were subjected to a 21-day deprivation period. In
particular, as can be observed in Fig. 5C, rats of the ADE group suffered a
great increase in oxidative stress levels during abstinence
(4.147 ±0.557) with respect to the water (1.378 ±0.227; p <0.0001)
or ethanol exposed rats (2.005 ±0.468; p =0.005). However, the
GSSG/GSH ratio in NO-ADE rats (0.917 ±0.382) remained invariable
with respect to water and ethanol groups during the abstinence period.
Additionally, Tuckey’s post-hoc test also detected statistical differences
between the ADE Abs and NO-ADE Abs groups (p <0.0001). Another
interesting aspect that emerges from the results obtained is the role of
alcohol when it is reintroduced. In particular, whereas high oxidative
stress levels, as revealed by GSSG/GSH levels, were detected in ADE rats
during abstinence, these levels were normalized after 24 h of ethanol
reintroduction, decreasing from 4.147 ±0.557–0.649 ±0.272. These
statistical results were conrmed through an additional analysis.
Concretely, 2-way ANOVA revealed a signicant subpopulation [F(1,
14)=28.730; p <0.001], alcohol reintroduction [F(1, 14)=38.670;
p<0.001] and alcohol reintroduction x subpopulation interaction ef-
fect [F(1, 14)=25.210; p <0.001] on hippocampal GSSG/GSH ratio. It
Fig. 3. Average ethanol preference, expressed in % of total uid intake, displayed by ADE (blue triangle, n =30) and NO-ADE (green circle, n =13) rats. (A) time
course in both experimental groups along the entire experiment. As depicted, animals experienced 4 consumption (CP) and 3 deprivation periods (DP). (B and C)
Manifestation of the relapse-like drinking behavior in ADE and NO-ADE rats. Bars represent the collapsed values of alcohol preference determined during the 3 days
before and after each deprivation period in the ADE (B) and NO-ADE (C) subgroup. (D) Compared average ethanol preference between ADE and NO-ADE rats along
the four ethanol-consumption periods assayed, excluding the 3 days post-abstinence in each period. Asterisks denote signicant differences relative to the pre- and
post-abstinence period in ADE (panel B) and NO-ADE (panel C) subgroups. (For interpretation of the references to colour in this gure, the reader is referred to the
web version of this article.)
S. Fern´
andez-Rodríguez et al.
Drug and Alcohol Dependence 232 (2022) 109284
7
is important to note that, in a general, GSSG levels displayed similar
tends than that observed in the GSSG/GSH ratio. Thus, during absti-
nence a marked and signicant increase in GSSG is noted only in ADE
rats (0.073 ±0.007 nmol/mg protein), when compared to either the
Water (0.037 ±0.005 nmol/mg protein; p =0.022) or Ethanol groups
(0.036 ±0.008 nmol/mg protein; p =0.043). Curiously, the
reintroduction of ethanol in abstinent ADE rats rapidly alleviated this
rise and restored GSSG levels (0.008 ±0.004 nmol/ mg protein;
p<0.0001). As previously, 2-way ANOVA also detected a signicant
subpopulation [F(1, 15)=9.821; p =0.007], alcohol reintroduction [F(1,
15)=36.240; p <0.001] and alcohol reintroduction x subpopulation
interaction [F(1, 15)=11.990; p =0.003] effects on hippocampal GSSG
Fig. 4. (A) 5%, 10% and 20% ethanol prefer-
ence, expressed in % of each solution with
respect of the total volume of alcohol
consumed, displayed by ADE (blue triangle,
n=30) and NO-ADE (green circle, n =13) rats
along time. As the three-way ANOVA for
repeated measures did not reveal a signicant
time effect, an additional 2-way ANOVA using
collapsed data was performed. These data are
depicted in panel (B). Asterisks indicate signif-
icant differences between ADE and NO-ADE
groups with respect to the preference dis-
played by rats depending on the different
ethanol dilutions available [* ** p <0.001].
(For interpretation of the references to colour in
this gure, the reader is referred to the web
version of this article.)
Fig. 5. (A) GSSG and (B) GSH levels, both
expressed as nmol/mg protein, and (C) GSSH/
GSH ratio determined in the rat Hippocampus
under the different experimental conditions
described in Fig. 1. The color legend is the same
as the one described in Fig. 1. One-way ANOVA
results were: (A) F(5,28)=8.523; p <0.001;
(B) F(5,27)=8.320; p <0.001; (C) F(5,24)=
13.770; p <0.001. Asterisk (*) indicates sig-
nicant differences among groups, and the hash
symbol (#) indicates signicant differences
with respect to “water” or “ethanol” groups.
S. Fern´
andez-Rodríguez et al.
Drug and Alcohol Dependence 232 (2022) 109284
8
values.
Concerning data obtained in the amygdala, one-way ANOVA detec-
ted statistical differences when GSSG, GSH or GSSG/GSH ratio were
analyzed. It is especially remarkable that during abstinence, GSSG levels
in NO-ADE rats (0.178 ±0.033 nmol/mg protein) were signicantly
higher (p =0.014) when compared with those obtained in EtOH rats
(0.037 ±0.009 nmol/mg protein). Strikingly, this effect was not
detected in ADE rats. Additionally, 2-way ANOVA revealed a signicant
subpopulation [F(1, 15)=7.033; p =0.018] effect on GSSG levels
determined in the amygdala. Similar results were obtained when GSH
levels were analyzed, suggesting the existence of biochemical differ-
ences between both subpopulations. On the other hand, GSSG/GSH
values showed that NO-ADE Reint subgroup showed clear differences
with respect to the other experimental conditions, an aspect that, from
our present knowledge we are not able to reasonably interpret. Again,
the existence of signicant differences in GSH/GSSG ratio between the
ADE Reint and NO-ADE Reint subgroups (p =0.036) could be indicative
of differences between the two subpopulations. The comparison
Fig. 6. (A) GSSG and (B) GSH levels, both
expressed as nmol/mg protein, and (C) GSSH/
GSH ratio determined in the rat Amygdala
under the different experimental conditions
described in Fig. 1. The color legend is the same
as the one described in Fig. 1. One-way ANOVA
results were: (A) F(5,26) =4.764; p =0.032
(B) F(5,26)=4.997; p =0.0024 (C) F(5,22) =
8.156; p =0.0002. Asterisk (*) indicates sig-
nicant differences among groups, and hash
symbol (#) indicates signicant differences
with respect to the “water” or “ethanol” groups.
Fig. 7. Levels of (A) IL-1B, (B) NFκB, (C) TNF
α
, (D) iNOS, (E) IL6, (F) HMGB1 and (G) NLRP-3 mRNA expressed in arbitrary units in the rat Prefrontal Cortex under
the experimental conditions described in Fig. 1. The color legend is the same as the one described in Fig. 1. One-way ANOVA results were: (A) F(5,27)=4.696;
p=0.003 (B) F(5,26)=1.751; p =0.158 (C) F(5,27)=7.176; p =0.0002 (D) F(5,25)=0.643; p =0.669 (E) F(5,28) =1.443; p =0.243 (F) F(5,27)=1.449;
p=0.239 (G) F(5,25)=3.027; p =0.028. Asterisk (*) indicates signicant differences among groups, and the hash symbol (#) indicates signicant differences with
respect to the “water” or “ethanol” groups.
S. Fern´
andez-Rodríguez et al.
Drug and Alcohol Dependence 232 (2022) 109284
9
between the NO-ADE Abs and NO-ADE Reint group was almost signi-
cant (p =0.059), suggesting the potential role of the reintroduction of
alcohol in the GSSG/GSH values only in one of the identied sub-
populations. Previous statistical results were conrmed through 2-way
ANOVA, given that a signicant subpopulation [F(1, 13)=7.117;
p=0.019] and alcohol reintroduction [F(1, 13)=4.872; p =0.045] ef-
fect on the GSSG/GSH ratio were determined in the amygdala.
3.3. Experiment 3: analysis of the gene expression levels of
neuroinammatory mediators
The neuroinammatory status was also analyzed in the ADE and NO-
ADE rats. For this objective, under the same experimental conditions as
in experiment 2, we evaluated the mRNA levels of different inamma-
tory modulators/mediators (IL-1B, IL6, TNF
α
, HMGB1, iNOS, NFκB and
NLRP-3) in the PFC of the different groups of rats. The results obtained
are depicted in Fig. 7. After three-week ethanol withdrawal, one-way
ANOVA only detected statistical differences in the IL-1B, TNF
α
and
NLRP3 mRNA expression. As can be observed in Fig. 7A, in the absti-
nence period, only ADE rats presented an increased IL-1B value of up to
200% with respect to the Water group. Tukey’s test conrmed the ex-
istence of statistical differences between both experimental groups
(p =0.014). Conversely, after prolonged abstinence, NO-ADE rats
showed no statistical differences with respect to rats from the Water
(p =0.991) or Ethanol group (p =0.987). On the other hand, elevated
IL-1B mRNA levels detected in ADE rats during abstinence rapidly
normalized after 24 h ethanol reintroduction (p =0.0039). This obser-
vation was conrmed by 2-way ANOVA given that a signicant alcohol
reintroduction [F(1, 17) =10.090; p =0.006] effect was determined. In
the case of TNF
α
mRNA expression (Fig. 7C), during abstinence, ADE
and NO-ADE showed statistical differences between them (p =0.0006).
The effects of alcohol reintroduction were analyzed as well. Again, it can
be observed that the presence of ethanol, rapidly and signicantly
decreased TNF
α
mRNA expression in ADE rats (p =0.0024). Similarly,
in the case of TNF
α
mRNA expression, 2-way ANOVA conrmed a sig-
nicant subpopulation [F(1, 18) =9.118; p =0.007], alcohol reintro-
duction [F(1, 18) =5.147; p =0.036] and alcohol reintroduction x
subpopulation interaction [F(1, 18) =12.080; p =0.003] effects. Statis-
tical analysis also detected differences in NLRP3 mRNA expression
(Fig. 7E), but only between Ethanol and ADE Reintr conditions, a
difcult comparison to interpret, given that in this case two aspects are
involved: the abstinence experience and the alcohol reintroduction. A
nal observation should be noted: although statistical analysis could not
conrm it, the rest of inammatory modulators/mediators explored,
always tended to decrease when alcohol was reintroduced in ADE sub-
population, i.e. when compared ADE Abs vs ADE Reintr.
4. Discussion
To the best of our knowledge, the present study provides the rst
evidence of both altered brain redox and neuroinammation status after
three-week ethanol abstinence in Wistar rats exposed to a long-term
ethanol experience. In the current study, we demonstrate that oxida-
tive and neuroinammation status remain altered after long-term
ethanol withdrawal. However, in our opinion, one of the most signi-
cant ndings of the present study, is the fact that this effect was observed
exclusively in rats that repeatedly displayed ethanol relapse-like
drinking behavior. Moreover, according to our results, the reintro-
duction to alcohol consumption rapidly blunted these effects in this
subpopulation of animals.
The understanding of the underlying neurobiology of relapse
behavior could be crucial in the improvement of available treatments to
reduce relapse, which is one of the main clinical problems related to
AUDs. As the neurobiology of relapse behavior is difcult to study in
patients, we have designed the present research applying the ADE
model, which is, probably, one of the most commonly used preclinical
approach to ethanol relapse-drinking behavior (Bell et al., 2012; Spa-
nagel, 2017). This animal model encompassed the entire range of the
addiction cycle, including acquisition and maintenance of drug taking,
withdrawal and craving during periods of drug abstinence and ulti-
mately relapse; processes that were repeated several times in this
experimental model. All these facts support the model’s high face and
predictive validity (Leong et al., 2018; Bell et al., 2017). One of the few
limitations of this animal model could be that the abstinence is not freely
chosen by the rat. Thus, recently new rat models of relapse after
voluntary abstinence (achieved either by introducing adverse conse-
quences to drug taking or seeking or by providing mutually exclusive
choices between the self-administered drug and nondrug rewards) are
being developed. However, at present it is not known whether the use of
these novel models will improve the predictive validity of classical
relapse models because, to date, there are no published reports showing
its postdictive validity using approved medications (Fredriksson et al.,
2021).
Using a heterogeneous and non-selected cohort of rats as well as the
aforementioned ADE model, we have been able to identify and catego-
rize two different subpopulations of rats that showed specic behavioral
endophenotypes related to their relapse-like drinking behavior. The
obtained results also demonstrate that this behavioral trait correlates
with their pattern of voluntary alcohol-drinking behavior. Specically,
animals with a high probability of displaying alcohol-relapse (called
“ADE group”) always showed lower alcohol intake rates than that
observed in NO-ADE animals, as can be appreciated in Fig. 2D. Similar
results were obtained when total ethanol preference was analyzed.
Moreover, a great difference between both groups was detected when
the particular pattern of ethanol consumption was analyzed (see Fig. 4).
The present results also indicate that the applied criterion to categorize
ADE/NO-ADE rats clearly allowed us to distinguish two subpopulations,
of which ADE rats always displayed lower ethanol intake and lower
ethanol preference, but a signicantly higher preference for 20%
ethanol dilution than NO-ADE rats. These results are consistent with
previous observations extracted from the study of the ADE manifestation
in various alcohol-preferring rat lines, which are widely used in alcohol
research (Bell et al., 2017) since they were selected for their high
ethanol preference or excessive alcohol drinking. After a single depri-
vation period, neither sP, nor HAD, nor AA lines show an ADE phe-
nomenon (Agabio et al., 2000; Sinclair and Tiihonen, 1988; Vengeliene
et al., 2003) and only alcohol-preferring P rats exhibit a robust ADE
(McKinzie et al., 1998). In other words, these selective breeding rat lines
emerged for the selection of animals characterized by their high ethanol
preference or excessive alcohol drinking, and not because of their
relapse-drinking behavior. Hence, according to the present results, it is
plausible that the occurrence of the ADE is unlikely in these selected
lines. It has been proposed that the high basal intake may explain the
lack of ADE due to a ceiling effect (Vengeliene et al., 2014). In general,
data obtained in the present paper demonstrate that male Wistar rats
show specic behavioral endophenotypes related with their voluntary
alcohol-drinking behavior (such as basal ethanol intake, total alcohol
preference or particular preference for an alcohol dilution) that corre-
lates with their relapse-like drinking behavior.
A great deal of evidence has been gathered demonstrating that
alcohol triggers inammatory responses and oxidative stress, especially
after excessive consumption (Das and Vasudevan, 2007; Barcia et al.,
2015; Quintanilla et al., 2018, 2007). The central nervous system is
highly sensitive to oxidative stress, because of its high oxygen con-
sumption and lipid content as well as its low antioxidant defense activity
(Halliwell, 2006). Ethanol-induced hippocampal oxidative damage has
also been well documented in rats (Almansa et al., 2013;
Johnsen-Soriano et al., 2007; Quintanilla et al., 2018; Scolaro et al.,
2012). However, under our experimental conditions GSH and GSSG
levels were not modied by prolonged chronic ethanol consumption in
the hippocampus nor amygdala. In previous papers in which signicant
effects were reported, rats were exposed to the Lieber-deCarli alcohol
S. Fern´
andez-Rodríguez et al.
Drug and Alcohol Dependence 232 (2022) 109284
10
liquid diet, that enhances the rate of alcohol consumed by the animal
(Almansa et al., 2013; Johnsen-Soriano et al., 2007), or elevated ethanol
doses (3 g/kg) were intraperitoneally administered (Scolaro et al.,
2012). Nonetheless, when a lower ethanol dose was administered, for
example by oral gavage (1.5 g/kg), no changes in GSH levels were
observed in the frontal cortex, hippocampus or striatum of male Spra-
gue–Dawley rats (Sommavilla et al., 2012). Similar conclusions can be
reached when inammatory responses are explored. Under our experi-
mental conditions, prolonged chronic ethanol consumption did not alter
any cytokine or inammatory mediator. However, several studies have
demonstrated that after chronic ethanol exposure, rats show signi-
cantly elevated cytokine expression in the hippocampus and cortex. Yet,
in those experiments, once again, high ethanol doses were administered
following a forced schedule (10 g/kg by oral gavage for 10 weeks), or
animals were fed the Lieber-deCarli diet (5 months), respectively
(Tiwari et al., 2009; Vall´
es et al., 2004). However, under the free-choice
four-bottle paradigm used in our research, our male Wistar rats dis-
played a voluntary average ethanol intake of 2.21 ±0.12 g/kg during
24 h, which is a low ethanol dosing rate compared to previous data
reported. Our research is supported by the use of a high face, predictive
and ecological validity model in the preclinical setting, the ADE model,
in which alcohol consumption is voluntarily controlled by the animal
and leads to a lower average alcohol dosage rate. According to obtained
outcomes, this limited alcohol consumption was not enough to trigger
signicant oxidative/neuroinammatory damage. However, and very
interestingly, in ADE rats (animals that have displayed similar levels of
ethanol intake but have experienced several abstinence periods) a robust
brain redox disbalance after three-weeks abstinence was observed,
suggesting the critical role that oxidative stress might play in triggering
alcohol craving and relapse, as discussed in the next paragraph.
Once animals were separated in two clearly differentiated categories,
i.e., rats that show relapse-like drinking behavior (ADE) or not (NO-
ADE), the neurobiology of relapse behavior was explored after three-
week alcohol withdrawal. Experiment 2 evidenced that after this pro-
longed abstinence period, a remarkable difference between the ADE and
NO-ADE groups was detected in relation to brain oxidative status
determined in the hippocampus, with the GSSG/GSH ratio being
signicantly higher in ADE than in NO-ADE rats. Our results correlate
somewhat with clinical data according to which serum oxidative stress
markers remain elevated after 1–2 weeks of alcohol detoxication
(Huang et al., 2009). We additionally focused our studies on the
amygdala as it is considered one possible locus for alcohol
withdrawal-anxiety, a process related to craving and relapse behaviors
(Harper et al., 2019). However, according to the results obtained, the
quantication of the redox status during the abstinence period in the
hippocampus has revealed more interesting results than in the amyg-
dala. Similar conclusions were reached by Knapp et al. (2016) when
several neuroimmune mRNAs in cortex, hippocampus, and amygdala
were assessed in ethanol-withdrawn male rats. Strong increases in
TNF-
α
, IL-1β and CCL-2 were detected both in the hippocampus and
cortex. Nevertheless, no effect on any measure was detected in the
amygdala.
With regard to neuroinammation markers, although in the present
research we analysed seven different neuroinammation mediators in
PFC, after a three-week ethanol abstinence period only the IL-1β and
TNF-
α
mRNA expression remained altered and showed statistical dif-
ferences between ADE and NO-ADE rats. Our results are in accordance
with previous reports, using assimilable procedures to ours. Thus,
Schneider et al. (2017) exposed male Wistar rats to 2 g/kg alcohol twice
a day by oral gavage for 30 days. After a short alcohol cessation period
(5 days), animals showed increased values of TNF-
α
, IL-1β, IL-6 and
IL-18 in both, the hippocampus and frontal cortex. Knapp et al. (2016)
reported that, rats that received a continuous 7% (w/v) ethanol diet
followed by a 24-hour withdrawal period showed elevated cytokine
levels in the cortex and hippocampus. In the clinical setting, Yen et al.
(2017) reported that alcohol-dependent patients, during early
withdrawal, demonstrated higher plasma cytokine levels than healthy
controls (p <0.001 for all cytokines analyzed: IL-2, IFN-γ, TNF-
α
, IL-4,
IL-5 IL-6, IL-10, IL-1β, IL-8 and GM-GSF). However, after four weeks
of alcohol abstinence, the levels of cytokine expression were signi-
cantly lower (p <0.001; except for IL-1β and IL-5). In a study performed
with 29 patients, after an average of 6 days of ethanol abstinence,
increased serum levels of IL-6, IL-10 and IL-8 at the beginning of the
abstinence period declined (Gonz´
alez-Quintela et al., 2000). All in all,
data evidence that the time course of each neuroinammation mediator
is different and depends on the brain nuclei considered. As can be
observed, under our experimental conditions, only IL-1β and TNF-
α
remained altered after prolonged ethanol abstinence.
The effects of ethanol reintroduction in an ethanol-withdrawn pop-
ulation have also been explored in the present paper. Although alcohol is
considered a prooxidant substance, our results evidence that it has
different effects depending on the distinct endophenotypes displayed by
the rats. In fact, when ethanol was reintroduced in ADE rats, it restored
altered oxidative stress indicators as well as neuroinammation markers
such as IL-1β and TNF-
α
. This effect was not observed in NO-ADE rats. In
our opinion, this result should be considered in future pharmacological
research when an anti-relapse drug is being evaluated and the action
mechanism is being explored, as not only the drug but also the alcohol
could have an effect on the obtained results. For instance, when Quin-
tanilla and colleagues (2008), evaluated N-Acetylcysteine (NAC) as a
potential anti-relapse drug, it would have been very interesting to
determine hippocampal GSSG and GSH levels before ethanol was rein-
troduced, and not only after a 60-minutes alcohol re-access, since the
reduction in the GSSG/GSH ratio appreciated in the group treated with
NAC, could be due to, at least in part, by ethanol reintroduction.
4.1. Conclusions
The main nding of this study is the demonstration that after a
prolonged ethanol withdrawal, brain redox and neuroinammation
status remain altered, but only in animals that display ethanol-relapse
behavior, possibly being a plausible key in the induction of the
craving that will lead to the relapse process. According to the present
results, the next step in our research should be the elucidation of the
underlying mechanisms (precise causes), probably from the genetic
point of view, that lead to the different redox/neuroinammation status
identied in the different individuals. These aspects could be considered
a robust criterion for predicting the alcohol-addiction and non-addiction
vulnerability of individuals. Additionally, our results gather mechanistic
evidence concerning the use of antioxidant, antiinammatories or
combined therapies for preventing alcohol relapse, as currently being
evaluated by different groups (Berríos-C´
arcamo et al., 2020, Quintanilla
et al., 2020). However, in future research, the effects induced by the
ethanol reintroduction should be taken into consideration when the
pharmacological mechanism of anti-relapse drugs are evaluated.
CRediT authorship contribution statement
All authors contributed substantially to this research, revised and
approved the nal version of this manuscript. A. Polache: Conceptu-
alization, Writing – review & editing, Supervision. S. Rius-P´
erez:
Acquisition of data. T. Zornoza: Conceptualization, Methodology,
Formal analysis, Writing – original draft, Writing – review & editing,
Funding acquisition, Supervision. S. Fern´
andez-Rodríguez: Acquisi-
tion of data. M.J. Cano-Cebri´
an: Acquisition of data. C. Guerri:
Methodology, Formal analysis. S. P´
erez: Methodology, Formal analysis.
L. Granero: Conceptualization, Writing – review & editing.
Conict of interest
The Authors declare that there is no conict of interest.
S. Fern´
andez-Rodríguez et al.
Drug and Alcohol Dependence 232 (2022) 109284
11
Funding
This research was supported by a grant from Conselleria de Educa-
ci´
on, Investigaci´
on, Cultura y Deporte (Generalitat Valenciana
GVA2016-096). SF is recipient of a pre-doctoral Val i+D grant from
Conselleria de Educaci´
on, Investigaci´
on, Cultura y Deporte (Generalitat
Valenciana ACIF/2018/039).
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