Neuroscience 262 (2014) 107–117

DOSE-DEPENDENT INFLUENCE OF SHORT-TERM INTERMITTENTETHANOL INTOXICATION ON CEREBRAL NEUROCHEMICAL CHANGESIN RATS DETECTED BY EX VIVO PROTON NUCLEAR MAGNETICRESONANCE SPECTROSCOPY

DO-WAN LEE, a,b YOON-KI NAM, c TAI-KYUNG KIM, d

JAE-HWA KIM, e SANG-YOUNG KIM, a,b JUNG-WHAN MIN, f

JUNG-HOON LEE, a,b,g HWI-YOOL KIM, d

DAI-JIN KIM e,h AND BO-YOUNG CHOE a,b*

aDepartment of Biomedical Engineering, The Catholic University of

Korea, College of Medicine, #505 Banpo-dong, Seocho-gu, Seoul

137-701, Republic of Korea

bResearch Institute of Biomedical Engineering, The Catholic Univer-

sity of Korea, #505 Banpo-dong, Seocho-gu, Seoul 137-701,

Republic of Korea

cNMR Research Team & Life Science Group, Agilent Technologies

Korea Ltd., #966-5 Daechi-dong, Gangnam-gu, Seoul 135-848,

Republic of Korea

dDepartment of Veterinary Surgery, Konkuk University, #120 Neu-

ngdong-ro, Gwangjin-gu, Seoul 143-701, Republic of Korea

eDepartment of Biomedical Science, The Catholic University of

Korea, College of Medicine, #505 Banpo-dong, Seocho-gu, Seoul

137-701, Republic of Korea

fDepartment of Radiological Science, The Shingu University College

of Korea, Geumgwang 2-dong, Jungwon-gu, Seongnam-si,

Gyeonggi-do 462-743, Republic of Korea

gDepartment of Radiology, Kyunghee Medical Center, #23 Kyun-

gheedae-ro, Dongdaemun-gu, Seoul 130-872, Republic of KoreahDepartment of Psychiatry, Seoul St. Mary’s Hospital, The Catholic

University of Korea, College of Medicine, #505 Banpo-dong, Seocho-

gu, Seoul 137-701, Republic of Korea

Abstract—The aim of this study was to quantitatively assess

the effects of short-term intermittent ethanol intoxication on

cerebral metabolite changes among sham controls (CNTL),

low-dose ethanol (LDE)-exposed, and high-dose ethanol

(HDE)-exposed rats, which were determined with ex vivo

high-resolution spectra. Eight-week-old male Wistar rats

0306-4522/13 $36.00 � 2014 IBRO. Published by Elsevier Ltd. All rights reservehttp://dx.doi.org/10.1016/j.neuroscience.2013.12.061

*Correspondence to: B.-Y. Choe, Department of Biomedical Engi-neering, Research Institute of Biomedical Engineering, College ofMedicine, The Catholic University of Korea, #505 Banpo-Dong,Seocho-Gu, Seoul 137-701, Republic of Korea. Tel: +82-2-2258-7233; fax: +82-2-2258-7760.

E-mail address: bychoe@catholic.ac.kr (B.-Y. Choe).Abbreviations: Ala, alanine; ANOVA, analysis of variance; Asp,aspartate; BALs, blood-alcohol levels; CNTL, controls; Cr, creatine;D2O, deuterium oxide; Eth, ethanol; GAD, glutamic acid decarboxylase;Gln, glutamine; Glu, glutamate; Glx, glutamine complex; GPC,glycerophosphocholine; GSH, glutathione; HDE, high-dose-ethanol;HR-MAS, high-resolution magic angle spinning; HSD, honestlysignificant difference; Lac, lactate; LDE, low-dose ethanol; mIns,myo-Inositol; MRS, magnetic resonance spectroscopy; NAA,N-acetylaspartate; NAAG, N-acetyl-aspartyl-glutamate; NMR,nuclear magnetic resonance; PCh, phosphocholine; PCr,phosphocreatine; SD, standard deviation; Tau, taurine; tNAA, totalN-acetylaspartate; TSP, trimethylsilyl propionate.

107

were divided into three groups. Twenty rats in the LDE

(n= 10) and the HDE (n= 10) groups received ethanol

doses of 1.5 and 2.5 g/kg, respectively, through oral gavage

every 8 h for 4 days. At the end of the 4-day intermittent eth-

anol exposure, one-dimensional ex vivo 500-MHz 1H nuclear

magnetic resonance spectra were acquired from 30 samples

of the frontal cortex region (from the three groups). Normal-

ized total N-acetylaspartate (tNAA: NAA+ NAAG [N-acetyl-

aspartyl-glutamate]), GABA, and glutathione (GSH) levels

were significantly lower in the frontal cortex of the HDE-

exposed rats than that of the LDE-exposed rats. Moreover,

compared to the CNTL group, the LDE rats exhibited signif-

icantly higher normalized GABA levels. The six pairs of nor-

malized metabolite levels were positively (+) or negatively

(�) correlated in the rat frontal cortex as follows: tNAA and

GABA (+), tNAA and aspartate (Asp) (+), myo-Inositol

(mIns) and Asp (�), mIns and alanine (+), mIns and taurine

(+), and mIns and tNAA (�). Our results suggested that

short-term intermittent ethanol intoxication might result in

neuronal degeneration and dysfunction, changes in the rate

of GABA synthesis, and oxidative stress in the rat frontal

cortex. Our ex vivo 1H high-resolution magic angle spinning

nuclear magnetic resonance spectroscopy results sug-

gested some novel metabolic markers for the dose-depen-

dent influence of short-term intermittent ethanol

intoxication in the frontal cortex. � 2014 IBRO. Published

by Elsevier Ltd. All rights reserved.

Key words: intermittent ethanol intoxication, brain, metabo-

lites, frontal cortex, high-resolution spectra.

INTRODUCTION

Alcohol is the most commonly used intoxicating

substance worldwide and in developing countries, and it

ranks high as a cause of disability (Saraceno, 2002;

Little et al., 2008). Binge alcohol consumption (heavy

consumption of alcohol over a short period) can cause

various adverse consequences, including an increased

risk of developing alcohol dependence and diverse

systemic effects on various organs (Kim and Shukla,

2006; Lowery-Gionta et al., 2012). A number of studies

have suggested that excessive alcohol abuse can cause

various brain disorders such as changes in brain

structure/volume, neurological dysfunction, functional

abnormalities, and neurochemical alterations (Obernier

et al., 2002b; Kelso et al., 2011; Welch et al., 2013).

Numerous studies have shown that binge ethanol-

exposed rats exhibit significant metabolic abnormalities,

d.

108 D.-W. Lee et al. / Neuroscience 262 (2014) 107–117

functional impairments, and neuronal changes such as

cerebral metabolite changes (Zahr et al., 2010),

cognitive deficits (Cippitelli et al., 2010), and neuronal

dysfunction and degeneration/recovery (Crews et al.,

2000; Crews and Nixon, 2009) in the hippocampus

(Zahr et al., 2010; Kelso et al., 2011), temporal

(entorhinal/perirhinal) cortex (Crews et al., 2000; Crews

and Braun, 2003; Crews and Nixon, 2009), and olfactory

bulb (Cippitelli et al., 2010). To date, to the best of our

knowledge, studies on the neurochemical effects of

binge alcohol intoxication in the rat frontal cortex are

scarce. Moreover, information and studies on the dose-

dependent effects of binge alcohol intoxication are also

lacking. Here, we have created a model of binge-like

alcohol intoxication with a 4-day binge protocol

(Majchrowicz, 1975; Zahr et al., 2010). The binge protocol

described by Majchrowicz is extensively used as a model

of alcoholism because of the continuously sustained

blood-alcohol levels (BALs) due to intragastric ethanol

exposure (Zahr et al., 2010). Therefore, the Majchrowicz

binge protocol is appropriate for the assessment of dose-

dependent effects on the neurochemical changes induced

in intermittent ethanol-intoxicated rats.

In vivo magnetic resonance spectroscopy (MRS)

provides a noninvasive approach for the biochemical

identification and quantification of specific organs

(Batouli et al., 2012). However, quantification of the

in vivo MRS technique has been severely limited by

overlapping peaks in the narrow chemical shift range

(Lee et al., 2013). The potential of high-field nuclear

magnetic resonance (NMR) spectroscopy in providing

biologically detailed neurochemical profiles on the basis

of increased spectral resolution and improved signal-to-

noise ratios has been demonstrated in previous reports

(Gruetter et al., 1998; Tkac et al., 2009). Ex vivo proton

(1H) high-resolution magic angle spinning (HR-MAS)

NMR spectroscopy is widely used in biological

applications (Sitter et al., 2010). The HR-MAS is a

powerful tool for observing cerebral neurochemical

changes and allows high-resolution spectra to be

harvested directly from biopsy tissues (Opstad et al.,

2010; Llorente et al., 2012). Moreover, the HR-MAS

technique can provide narrow line-widths of metabolite

peaks by reducing the line-broadening effects in semi-

solid tissues through rapid sample spinning at a magic

angle (54.7�) against the magnetic field (Beckonert

et al., 2010).

To date, the influence of dose effects of binge alcohol

intoxication on cerebral metabolite changes of the frontal

cortex region of the rats has not been experimentally

investigated using 1H in vivo MRS or ex vivo NMRS.

Therefore, the first goal of this study was to determine

the influence of the dose-dependent effects of

intermittent ethanol intoxication on cerebral metabolite

changes among sham controls and low- and high-dose

ethanol-exposed rats with ex vivo high-resolution

spectra. The second goal of this study was to determine

the correlations between the metabolite-metabolite

levels (pairs of metabolite levels) from all of the

individual data from the frontal cortex of the intermittent

ethanol-intoxicated rats. We hypothesized that the high-

dose ethanol-exposed rats would exhibit significantly lower

levels of total acetylaspartate (tNAA; N-acetylaspartate[NAA] + N-acetylaspartyl-glutamate [NAAG]), GABA, and

glutathione (GSH) in the region of the frontal cortex

because of the greater neurochemical damages from the

ethanol toxicity compared to those of the sham controls

and the low-dose ethanol-exposed rats. In addition, we

hypothesized that the pairs of cerebral metabolites would

significantly correlate with the pairs of metabolite levels

among the sham-control rats and the intermittent low-

and high-dose ethanol-exposed rats. In order to test these

hypotheses, we compared the cerebral neurochemical

levels and the pairs of metabolite levels in a dose-

dependent manner in the intermittent ethanol-exposed rats.

EXPERIMENTAL PROCEDURES

Ethics statement

The animal experiments were approved by the

Institutional Animal Care and Use Committee at The

Catholic University of Korea, College of Medicine

(IACUC Number: 2012-0084-02). The animals were

maintained according to the ‘Guide for the Care and

Use of Laboratory Animals’ (NIH Publications No. 80-

23) issued by ILAR, USA.

Animals

Eight-week-old male Wistar rats (mean body weight,

314.7 g; range, 295.0–329.0 g; n= 30; Central Lab.

Animal, Inc., Seoul, Republic of Korea) were divided into

three groups (control rats [CNTL]: n= 10; low-dose

[1.5 g/kg] ethanol [LDE] group: n= 10; and high-dose

[2.5 g/kg] ethanol [HDE] group: n= 10). All animals

were individually housed in standard plastic cages and

maintained on a 12-h light–dark cycle at ambient

temperature (24–25 �C). Before the start of the

experiments, the rats were allowed free access to food

and water for a week.

Intermittent ethanol intoxication

The design of the intermittent ethanol intoxication model

has been previously described (Majchrowicz, 1975; Zahr

et al., 2010). For the initial exposure on the first day

(day 1; at 18:00 h), the 20 rats in the LDE and HDE

groups received an initial dose of 5.0 g/kg (30% w/v

solution) through oral gavage, and the rats then

received additional doses of 1.5 g/kg and 2.5 g/kg (25%

w/v solution), respectively, every 8 h (at 02:00 10:00,

and 18:00 h) for 4 days. The 10 rats in the sham CNTL

group received an equivalent volume (about 2.66 mL) of

distilled water at comparable times (at 03:00, 11:00, and

19:00 h). Oral gavage ethanol was administered

according to body weight as mentioned in the

Majchrowicz binge alcohol protocol (Majchrowicz, 1975).

The LDE- and the HDE-exposed rats showed signs of

intoxication, including sedation and ataxia, after

intermittent ethanol injections. The body weights of the

rats in the CNTL, LDE, and HDE groups were recorded

daily for 5 days; the initial body weights before ethanol

D.-W. Lee et al. / Neuroscience 262 (2014) 107–117 109

exposure were also recorded. After 4 days of oral gavage,

all animals were sacrificed, and their brain tissues were

carefully harvested from the frontal cortical region.

BALs

Sixty minutes after (at 11:00 h) the morning gavage

session (at 10:00 h) on each day, blood samples

(1.20 mL) were collected from the LDE- and HDE-

exposed rats once a day during the 4 days. The blood

samples (n= 20) were collected in a regular sequence

after each individual gavage in the LDE- and HDE-

exposed rats (n= 20). In each sequence, blood samples

were collected simultaneously from three rats, and this

sequence was repeated seven times to obtain the 20

blood samples from 20 rats (i.e., three samples each in

the first six sequences, and two samples in the last

sequence). We tried to match the time of the blood

sampling procedure in the LDE- and HDE-exposed rats

(blood collection time per sequence was <4 min).

Therefore, all of the blood samples of the LDE- and the

HDE-exposed rats were collected within 60–64 min after

the morning ethanol gavage on each day. Twenty blood

samples were collected daily from the retro-orbital plexus

using plain capillary tubes (Nonheparinized Color-Coded

Capillary Tubes, Blue band, 70 lL, 1.2 � 75.0 mm,

Kimble Chase Life Science and Research Products LLC,

Vineland, NJ, USA). Immediately after the retro-orbital

plexus blood collection, all blood samples were put into

ethylenediaminetetraacetic acid tubes to assess the

alcohol content in the plasma, which was assayed with

an enzymatic method using alcohol dehydrogenase

(Cobas 6000 analyzer with a cobas c 501 module, Roche

Diagnostics GmbH, Mannheim, Germany). During the

4 days of intermittent ethanol exposure, the LDE- and the

HDE-exposed groups were treated daily with a mean

dose of 5.38 ± 1.75 and 8.13 ± 1.25 g/kg/day,

respectively (including the initial dose of 5.0 g/kg). The

LDE- and the HDE-exposed group received a mean total

cumulative dose of 21.53 ± 0.87 g/kg/animal and

32.51 ± 0.42 g/kg/animal, respectively. At the end of the

4 days of intermittent ethanol intoxication, the LDE- and

the HDE-intoxicated rats had daily mean BALs of

193.03 ± 84.98 and 234.33 ± 87.97 mg/dL, respectively.

Tissue harvesting and sample preparation

Sixty minutes after (at 11:00 h) the end of the last gavage

(day 4; at 10:00 h), all animals were euthanized with

carbon dioxide inhalation and immediately decapitated.

The BALs have been reported to exhibit markedly higher

peaks 60 min after the last binge ethanol exposure as

previously described (Livy et al., 2003). We considered

the killing time to minimize the early withdrawal

symptoms because early withdrawal symptoms might

affect cerebral metabolite changes due to specific

metabolite recovery, short-term abstinence effects, or

seizure activity. All protocols followed the Guide for the

Care and Use of Laboratory Animals (NIH Publications

No. 80-23) issued by ILAR (USA) and were approved by

the Institutional Animal Care and Use Committee at The

Catholic University of Korea, College of Medicine (IACUC

Number: 2012-0084-02). The scalp and muscles were

removed quickly. Each brain was carefully placed into the

brain slicer matrix (Stainless-steel Zivic rat brain slicer

matrix with 1.0-mm coronal section interval; Zivic

Instruments, Pittsburgh, PA, USA) according to the brain

shape. Thirty frontal cortical tissue sections were quickly

and carefully harvested with the brain slicer matrix. The

regional dissection of the rat brain has been previously

described (Heffner et al., 1980). The olfactory bulbs were

separated from the frontal poles. Relative to the bregma,

a brain slice was taken for the frontal cortex within the

3 mm+ bregma to the frontal poles (frontal

poles + 2 mm slices). We carefully chose the dissected

tissues to minimize the inclusion of the nucleus

accumbens, the caudate putamen, and other regions.

All tissues were immediately stored in liquid nitrogen (at

�196 �C) to prevent tissue decomposition and biochemical

changes. The harvested tissue sample was placed in a

Petri dish, and a small globular piece of tissue was

dissected quickly for the metabolite analysis. The masses

of the brain tissues were 14–20 mg. All dissected tissues

were then rinsed with deuterium oxide (D2O) to provide a

locking signal. The ampoules (1.0 mL) of D2O containing

0.05% weight trimethylsilyl propionate (TSP) were

used for referencing and scaling. These tissue samples

were inserted in a 4-mm nanotube (#190595803,

Narrow-mouth Nano-probe Sample Tube Kit, Agilent

Technologies Korea Ltd., Seoul, Republic of Korea), and

the remaining space in the nanotube was filled with D2O.

A zirconium plug was gently pushed in and tightly closed

to suppress air bubbles. The masses of the D2O solvent

in the nanotubes were 9–14 mg. The nanoglueless drive

ring (top screw) was then slowly inserted and tightened,

and the rotor was placed in the HR-MAS nanoprobe for

signal acquisition.

Ex vivo 1H HR-MAS NMR spectroscopy

Ex vivo 1H HR-MAS NMR spectroscopy was performed

on a VNMRS-500 spectrometer (500.13 MHz [11.7 T],

Agilent Technologies Korea Ltd., Seoul, Republic of

Korea) with a quadruple nuclei (1H, 2H, 13C, 31P)

HR-MAS NMR nano-probe. The samples were placed in

4-mm-diameter rotors, placed on top of the nano-probe,

and spun at 4–5 kHz and at 54.7�. The designs of the1H HR-MAS NMR spectroscopic studies have been

previously described (Lee et al., 2012; 2013; Swanson

et al., 2006; Woo et al., 2010). All one-dimensional

(1-D) HR-MAS NMR spectra were acquired with a

Carr-Purcell-Meiboom-Gill pulse sequence at 277.2 K

[complex data number, 16,384; spectral width, 8012.8 Hz;

acquisition time, 2.05 s; relaxation delay time, 5.0 s;

presaturation time, 2.0 s; interpulse delay (s), 0.4 ms; big-

tau (80 refocusing pulses at 180�), 0.064 s; number of

acquisitions, 128; and total scan time, 15 min, 24 s].

Spectral quantification

The acquired raw data were analyzed and quantified with

MestReNova software (Mestrelab Research S.L.,

Ver.8.1.1-11591, Santiago de Compostela, Spain). The

1-D free induction decay (FID) data were zero-filled to

110 D.-W. Lee et al. / Neuroscience 262 (2014) 107–117

65,536 complex points, apodized with a 2.0-Hz Gaussian

filter, and then Fourier transformed. The resulting spectra

were manually phased, frequency referenced to TSP at

0.00 ppm, and baseline corrected. The postprocessed

spectra were fitted with a global spectral deconvolution

algorithm for an improved multiplet analysis. The fitting

was performed using a Generalized-Lorentzian shape.

All metabolite intensities were fitted in the chemical shift

range from 4.20 to 1.00 ppm. The ex vivo data were

processed by the total signal intensity normalization

method as described previously (Lentz et al., 2008; Lee

et al., 2013). The relative signal intensity levels of each

metabolite were calculated by dividing the peak area by

the total area of all of the metabolites of interest. The

metabolites were quantified with fitted spectra, and each

deconvolution peak was as follows: Alanine (Ala),

aspartate (Asp), free-choline (fCho), creatine (Cr),

phosphocreatine (PCr), GABA, glutamine (Gln),

glutamate (Glu), glycerophosphocholine (GPC), GSH,

myo-inositol (mIns), lactate (Lac), NAA, NAAG,

phosphocholine (PCh), ethanol (Eth), taurine (Tau),

glutamine complex (Glx: Glu + Gln), total NAA (tNAA:

NAA+ NAAG), and total Cr (tCr: Cr + PCr).

Statistical analyses

All statistical analyses were performed using the PASW

Statistics 18 software (SPSS Inc., IBM Corporation,

Armonk, NY, USA). The ex vivo spectroscopy data were

compared among the ethanol dose groups of intermittent

intoxication (CNTL, LDE, and HDE), and the normalized

cerebral metabolite levels were compared with an analysis

of variance (ANOVA) test for multiple comparisons. The

group differences in the animal body weights were also

analyzed using an ANOVA test for multiple comparisons.

The post hoc comparisons were analyzed with a Tukey’s

honestly significant difference (HSD) procedure

(a =0.05). The examination of each variable in the overall

analysis was performed using the Levene’s Fhomogeneity-of-variance test. Normalized Tau and Lac

levels and Day-1, Day-2, and Day-3 were excluded from

the evaluation of the ANOVA results because these values

showed a significant difference (p< 0.05) in the results of

the Levene’s F homogeneity-of-variance test. The results

are expressed as mean values± standard deviation (SD)

of the normalized metabolite levels and 95% confidence

intervals. Differences in metabolite levels among the three

groups were considered statistically significant when pvalues were less than 0.05 (⁄p<0.05; ⁄⁄p<0.01;⁄⁄⁄p<0.005). The relationships between the individual

rat data of the three groups and the cerebral metabolite

levels were tested by Pearson correlations (metabolite–

metabolite levels). P values less than 0.05 were

considered statistically significant (⁄p< 0.05; ⁄⁄p< 0.01;⁄⁄⁄p< 0.005). The statistically analyzed data are

presented as mean ± SD, unless otherwise indicated.

RESULTS

Intermittent ethanol exposure affected body weight

Table 1 shows the mean body weights for each group for

each day among the CNTL, LDE-, and HDE-exposed

groups. Four days of intermittent ethanol intoxication

resulted in altered animal body weights on Day 4

[F(2,27) = 23.01, p< 0.005] among the three groups

(CNTL vs. LDE vs. HDE). The initial body weights were

not significantly different among the three groups. The

body weights of the LDE- (⁄⁄⁄p< 0.005) and the HDE-

(⁄⁄⁄p< 0.005) exposed groups were significantly lighter

than that in the CNTL group. Between the LDE- and the

HDE-exposed groups, the body weights were not

significantly different. From the Day-1 intermittent

ethanol exposure, the LDE- and the HDE-exposed

groups exhibited body weights that were markedly

reduced as compared to that of the CNTL group. The

CNTL group lost 7.3% body weight during the 4 days.

The LDE- and HDE-exposed groups lost 15.6% and

20.7% body weight, respectively, during the 4 days.

Ex vivo 1H HR-MAS NMR spectra

Fig. 1A–C shows the representative 500-MHz NMR

spectra acquired from the frontal cortex region of the 30

samples from the three groups (A [CNTL: n= 10], B

[LDE: n= 10], and C [HDE: n= 10]). The ex vivo NMR

spectra were assigned the following cerebral metabolite

signals: Lac, mIns, tCr, Glx, Eth, Tau, tCho, GSH,

GABA, Asp, NAA, Gln, Glu, tNAA, and Ala. Unlike the

CNTL (Fig. 1A) spectra, the LDE (Fig. 1B) and the HDE

(Fig. 1C) spectra showed Eth peaks (1.18 and

3.65 ppm) as a triplet in all of the intermittent ethanol-

exposed rats. Visual inspection of the NMR spectra did

not indicate any clear differentiation criteria among the

three groups. However, the Eth signal intensities

revealed that the HDE group had higher signal

intensities than that of the LDE group. This is because

the signal intensities were proportionally represented by

the cerebral metabolite concentrations.

Quantification of the ex vivo 1H HR-MAS NMR spectra

Fig. 2 illustrates the normalized cerebral metabolite levels

that were quantified from the 30 acquired ex vivo spectra

of the frontal cortex region. One-way ANOVA revealed an

interaction of metabolite levels among the three groups,

indicating a significant ethanol effect on the normalized

metabolite levels. Four days of intermittent ethanol

intoxication resulted in altered normalized metabolite

levels for tNAA [F(2,27) = 3.67, p= 0.039], GABA

[F(2,27) = 10.43, p< 0.001], and GSH [F(2,27) = 3.49,

p= 0.045] among the three groups (CNTL vs. LDE vs.

HDE). Additionally, the p-values from the post hoc

pairwise comparisons with Tukey’s HSD indicated which

normalized metabolite levels and ethanol doses were

responsible for the significant difference (Fig. 2). The

GSH levels (⁄p< 0.05) were significantly lower in the

HDE-exposed rats than in the LDE-exposed rats.

Between the CNTL and the LDE-exposed rats, the GSH

levels were not significantly different. The GABA levels

(p< 0.05) were significantly higher in the LDE-exposed

rats than in the CNTL rats. However, the GABA levels

(⁄⁄⁄p< 0.001) in the HDE-exposed rats were

significantly lower than that in the LDE-exposed rats.

The tNAA levels (⁄p< 0.05) were significantly lower in

Table 1. Schedule of intermittent ethanol exposure and rat body weights during the 5 days with plus and minus (±) standard deviations

Group N Initial body weight Day-1a Day-2a Day-3a Day-4***

CNTL 10 311.1 ± 11.7 302.5 ± 13.3 289.0 ± 11.9 289.5 ± 13.6 288.3 ± 13.9

LDE 10 315.8 ± 10.8 287.8 ± 14.6 278.0 ± 12.5 268.9 ± 10.6 266.4 ± 10.9

HDE 10 317.3 ± 8.6 291.4 ± 9.5 270.0 ± 8.4 257.6 ± 6.8 251.6 ± 8.8

The significance levels of the p values are as follows:*** p< 0.005.

a Body weight was excluded because the significance difference on the Levene’s F homogeneity-of-variance test was p< 0.05.

Fig. 1. Representative ex vivo spectra acquired at 500 MHz from the control (CNTL) rats (A, solid green), low-dose ethanol (LDE) rats (B, purple),

and the high-dose ethanol (HDE) rats (C, brown) in the frontal cortex (complex data number, 16,384; spectral width, 8012.8 Hz; acquisition time,

2.05 s; relaxation delay time, 5.0 s; presaturation time, 2.0 s; interpulse delay (s), 0.4 ms; and number of acquisitions, 128). The chemical shift range

was from 4.20 to 1.00 ppm. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 2. Mean normalized metabolite levels quantified from the CNTL, LDE, and HDE-exposed rats in the frontal cortex. The normalized metabolite

levels were analyzed by the total signal intensity ratios of the one-dimensional ex vivo nuclear magnetic resonance (NMR) spectra. The vertical lines

on each of the bars indicate the (+) standard deviation of the mean values. Significance levels (one-way ANOVA): ⁄p< 0.05; ⁄⁄⁄p< 0.005.

D.-W. Lee et al. / Neuroscience 262 (2014) 107–117 111

the HDE-exposed rats than in the LDE-exposed rats. The

mean values of the ex vivo normalized metabolite levels

are shown with the probability values (p-values) and

SDs in Table 2. From the visual verification of the

112 D.-W. Lee et al. / Neuroscience 262 (2014) 107–117

statistical findings, the mIns and Asp levels were not

significantly different among the three groups, but these

two metabolite levels were slightly lowered with

increasing ethanol doses of intermittent intoxication.

Correlations of normalized metabolite levels (pair ofmetabolite levels)

To visualize the normalized metabolite levels quantified

from the individual rat data and to assess the

relationship among them, the pairs of normalized

metabolite levels that changed the most were selected

for linear scatter plots (Fig. 3A–F). The clusters of

individual data from 30 rats were significantly correlated

(negatively or positively) in six scatter plots. The

selected correlated scatter plots exhibited highly

significant levels and reliable correlation coefficients

(Table 3). For all six scatter plots from the individual

quantified data, two pair-groups revealed strong

correlations in the two pairs of metabolite groups: mIns

vs. Tau levels (Fig. 3E) and tNAA vs. Asp levels

(Fig. 3F). Fig. 3 shows the characteristic patterns of the

normalized neurochemical level changes among the

three groups.

DISCUSSION

To the best of our knowledge, this study is the first to use

ex vivo 1H HR-MAS NMR spectroscopy in a rat model to

quantitatively assess the dose-dependent influences of

short-term intermittent ethanol intoxication on cerebral

neurochemical changes in the rat frontal cortex. The

present study provided several new findings. (1)

Normalized tNAA, GABA, and GSH levels were

significantly different among the HDE, LDE, and CNTL

groups. (2) We found correlations between pairs of

metabolites levels, such as tNAA and GABA, tNAA and

Asp, mIns and Asp, mIns and Ala, mIns and Tau, and

mIns and tNAA. Our results possibly indicate that tNAA,

GABA, and GSH levels were most sensitive to the

dose-dependent effects of short-term intermittent

Table 2. The mean values of the ex vivo normalized metabolite levels in the f

standard deviation

Metabolite CNTL LDE HDE

Glx 0.228 ± 0.016 0.240 ± 0.012 0.229 ± 0.01

Laca 0.109 ± 0.005 0.095 ± 0.007 0.130 ± 0.02

mIns 0.132 ± 0.011 0.130 ± 0.018 0.128 ± 0.00

tCr 0.106 ± 0.007 0.103 ± 0.010 0.103 ± 0.00

Taua 0.083 ± 0.008 0.078 ± 0.009 0.079 ± 0.00

tCho 0.055 ± 0.007 0.055 ± 0.005 0.056 ± 0.00

tNAA 0.095 ± 0.006 0.092 ± 0.005 0.088 ± 0.00

GABA 0.074 ± 0.006 0.081 ± 0.006 0.069 ± 0.00

GSH 0.015 ± 0.002 0.016 ± 0.003 0.012 ± 0.00

Asp 0.023 ± 0.002 0.022 ± 0.004 0.020 ± 0.00

Ala 0.006 ± 0.001 0.005 ± 0.001 0.006 ± 0.00

The significance levels of the p values are as follows:* p< 0.05.*** p< 0.005.

a Excluded metabolite levels because the significance difference of the Levene’s F hom

ethanol intoxication. Furthermore, these results require

additional study involving pathological and

neurophysiological investigations of intermittent ethanol

exposure to provide conclusive evidence and to interpret

the correlation among the various metabolites. From our

ex vivo 1H HR-MAS NMRS results, the present study

suggested some novel metabolic markers of short-term

intermittent ethanol-intoxicated rats in the frontal cortex.

To the best of our knowledge, investigations of the

short-term intermittent ethanol intoxication (including

heavy alcohol consumption) effects on cerebral

metabolite changes are scarce, and the literature is

lacking. The influence of the short-term dose effects of

intermittent ethanol intoxication on cerebral metabolite

changes has not been experimentally investigated with1H in vivo MRS and ex vivo NMRS. Previous studies

that have utilized MRS have identified alterations in the

neurochemical profiles of Tau, NAA, choline-containing

compounds (GPC+ PCh), Cr, mIns, Glu, and Gln in

binge alcohol-abusing patients (Meyerhoff et al., 2004;

Gomez et al., 2012) and in an binge ethanol-exposed

rat model (Zahr et al., 2010). Zahr et al. have

demonstrated in an in vivo 1H MRS study that the

cerebral metabolite concentrations are significantly

altered in binge ethanol-intoxicated rats than in control

rats (Zahr et al., 2010).

In the present study, compared to the LDE-exposed

rats, the HDE-exposed rats exhibited significantly lower

levels of tNAA in the frontal cortex. Until recently, the

findings of previous studies have indicated that the

significant reduction in NAA levels and concentrations

may reflect the loss of neuronal densities and

dysfunction due to the long-term alcohol consumption

and binge-like heavy drinking (Meyerhoff et al., 2004;

Biller et al., 2009). NAA is localized in neurons,

neuroglial precursors, and immature oligodendrocytes

(Biller et al., 2009; Paul and Medina, 2012). Miller and

colleagues have demonstrated that NAA concentrations

are positively correlated with neuronal densities and

viability (Miller, 1991; Guimaraes et al., 1995; Biller

et al., 2009). Furthermore, NAA is regarded as a key

rontal cortex of the rat brain with the p values and plus and minus (±)

p-value

CNTL vs. LDE LDE vs. HDE CNTL vs. HDE

0 0.113 0.179 0.967

2 0.081 <0.001 0.006

6 0.949 0.945 0.805

5 0.672 0.997 0.713

2 0.245 0.379 0.955

5 0.999 0.841 0.86

7 0.525 0.263 0.031*

6 0.037* <0.001*** 0.148

4 0.67 0.039* 0.211

3 0.75 0.549 0.195

1 0.624 0.482 0.97

ogeneity-of-variance test was p< 0.05.

Fig. 3. Scatter plots of the metabolite-metabolite level correlations quantified from individual rats that were distinguished by symbols among the

CNTL (rhombus, gray), LDE (square, black), and HDE (triangle, white) rats. All individual data are represented by the three types of symbols and the

Pearson correlation coefficients [positive correlation (+): blue, negative correlation (�): red]. The illustrations in A–F show the relationships

between the pairs of normalized metabolite levels as follows: total N-acetyl aspartate (tNAA: NAA + NAAG) vs. gamma-aminobutyric acid (GABA)

levels (A), myo-Inositol (mIns) vs. tNAA levels (B), mIns vs. Aspartate (Asp) levels (C), mIns vs. Alanine (Ala) levels (D), mIns vs. Taurine (Tau) (E)

levels, and tNAA vs. Asp levels (F). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this

article.)

D.-W. Lee et al. / Neuroscience 262 (2014) 107–117 113

neuronal marker in neurodegenerative disorders (Miller,

1991). Previous studies have demonstrated neuronal

degeneration and dysfunctions in the regions of the

hippocampus, the temporal (entorhinal/perirhinal) cortex,

and the olfactory bulb of binge alcohol-induced rats, and

these changes were detected by the Fluoro-Jade B and

amino-cupric silver-staining methods (Crews et al.,

2000, 2004; Obernier et al., 2002a; Cippitelli et al.,

2010; Kelso et al., 2011). Thus, from our results and

those of previous studies, significantly lower tNAA levels

Table 3. Pearson correlation coefficients and p values of the pairs of normalized metabolite levels evaluated from the individual data of the intermittent

ethanol-intoxicated rats in the frontal cortex

Pair of normalized metabolites levels

tNAA vs. GABA mIns vs. tNAA mIns vs. Asp mIns vs. Ala mIns vs. Tau tNAA vs. Asp

p-value 0.001*** 0.008*** 0.001*** <0.001*** <0.001*** <0.001***

r-value 0.5262 0.4392 0.5544 0.576 0.7776 0.7468

The significance levels of the p values are as follows:*** p< 0.005.

114 D.-W. Lee et al. / Neuroscience 262 (2014) 107–117

might reflect that HDE short-term intermittent ethanol

intoxication resulted in neuronal degeneration and

dysfunction in the frontal cortex of HDE-exposed rats

than in the CNTL group and the LDE-exposed rats.

Therefore, future studies with immunological and

histochemical methodologies in the short-term

intermittent ethanol-exposed rats with a regional

quantification of the brain are required to strengthen our

findings. Interestingly, there were no significant

differences between the CNTL and the LDE-exposed

rats. Although the normalized tNAA levels did not differ

significantly between the CNTL and the LDE-exposed

rats, the normalized tNAA levels were higher in the

LDE-exposed rats than in the CNTL rats. Hirakawa and

coworkers have identified that NAA levels in response to

the binge effects of ethanol were significantly higher in

the binge ethanol-exposed rats than in the control rats

(Hirakawa et al., 1994). The authors have interpreted

that the altered NAA levels might reflect neuronal

dysfunction in the neuronal cells because of the binge

ethanol exposure, as has been demonstrated in an

electron microscopic study (Hirakawa et al., 1994).

Thus, from our results and those of a previous study

(Hirakawa et al., 1994), one possible explanation of

such a slight increase in tNAA levels might be that

intermittent ethanol exposures of LDE possibly result in

neuronal dysfunction in the neuronal cells.

Several studies have investigated the levels of GABA

following binge ethanol exposure in humans and animals

(Buck, 1996; Grobin et al., 1998; Gomez et al., 2012).

GABA is a well-known major inhibitory neurotransmitter

in the central nervous system (Buck, 1996), and it plays

an essential role in regulating neuronal excitability and

energy metabolism in the brain (Choi et al., 2006).

Mason and coworkers have emphasized that GABA

receptors are the main targets for ethanol action in the

brain (Buck, 1996; Grobin et al., 1998; Mason et al.,

2005). Moreover, Grobin and coworkers have suggested

that in the brain, GABAA receptors are sensitive to

ethanol and are clearly involved in the actions of ethanol

(Grobin et al., 1998). Thus, significantly altered brain

GABA levels that are induced by ethanol consumption

are associated with GABAA receptor function (Krystal

et al., 2006; Gomez et al., 2012). Ethanol actions can

modulate GABA function as well as the synthesis and

density of GABAA receptors in specific brain regions

(Ward et al., 2009). Ward and coworkers have

suggested that ethanol can lead to increased GABA

release because it may inhibit the cerebral degradation

of GABA (Ward et al., 2009). Therefore, significantly

higher GABA levels in the LDE-exposed rats, compared

to the CNTL rats, may reflect increased GABA synthesis

and an increased density of GABAA receptors because

of inhibitions of cerebral GABA degradation caused by

intermittent LDE intoxication in the rat frontal cortex.

In contrast to the results of the CNTL vs. the LDE-

exposed rats, the HDE-exposed rats exhibited

significantly lower GABA levels than that of the LDE-

exposed rats. Smith and Gong have suggested that

GABA functions depend on the time course of the

ethanol exposure and ethanol concentrations doses

(Smith and Gong, 2007; Ward et al., 2009). Other

previous studies have suggested that reduced GABA

levels could reflect a reduction in GABA synthesis

generated from the decreased glutamatergic stimulation

of metabolic reactions and reduced concentrations of

the substrate for GABA synthesis (Sanacora et al.,

1999). The rate of GABA synthesis cannot be changed

without changing the glutamic acid decarboxylase

(GAD) reaction (Martin and Rimvall, 1993). Therefore,

significantly lower GABA levels in the HDE-exposed

rats compared to the LDE-exposed rats might reflect

a decreased rate of GABA synthesis and the

dysregulation of the glutamatergic stimulation because

of altered GAD reactions caused by the intermittent

HDE intoxication. Previous studies have suggested that

GABA levels could be affected by the brain region in

which it is present, the infusion time course of ethanol,

and its exposure periods (Smith and Gong, 2007; Ward

et al., 2009). For these reasons, further studies of short-

term and long-term intermittent ethanol exposure with a

regional quantification of the rat brain are required for

detailed quantitative assessments.

In the current study, the normalized GSH levels were

significantly lower in the HDE-exposed rats than in the

LDE-exposed rats. Findings of a previous study have

shown reduced GSH levels in a binge ethanol-

intoxicated rodent model (Uysal et al., 1989). Uysal and

coworkers have observed that cerebral GSH levels were

decreased after binge ethanol treatment (Uysal et al.,

1989). The authors interpreted that the significantly

decreased GSH levels may indicate that cerebral lipid

peroxidation is stimulated by binge ethanol exposure in

rats (Uysal et al., 1989). A number of studies have

demonstrated that ethanol action can stimulate lipid

peroxidation (Nordmann et al., 1990; Agar et al., 1999).

In turn, lipid peroxidation stimulation can lead to

oxidative stress in the brain through the formation of

D.-W. Lee et al. / Neuroscience 262 (2014) 107–117 115

free radicals and/or exhausting the antioxidant defense

system (Agar et al., 1999). Thus, from our results and

those from previous studies, significantly lower GSH

levels indicate that HDE intoxication (ethanol doses over

2.5 g/kg) may lead to oxidative stress, possibly due to

lipid peroxidation stimulation through the formation of

free radicals and/or abnormalities in the antioxidant

defense system in the frontal cortex of the HDE-

exposed rats.

In the present study, we identified that cerebral

metabolic fluctuations might cause linear associations

between pairs of normalized metabolite levels because of

the dose-dependent influence of short-term intermittent

ethanol intoxication. The results of the present study

revealed that the six pairs of normalized metabolite levels

that were significantly correlated in a positive (+) or

negative (�) manner in the frontal cortex were as follows:

tNAA and GABA (+), tNAA and Asp (+), mIns and Asp

(�), mIns and Ala (+), mIns and Tau (+), and mIns and

tNAA (�). Visually, the experimentally observed

significant correlations between the metabolite levels of

the individual rat data were not clearly distinguishable

among the three groups in each of the scatter plots.

Nevertheless, our results revealed significant correlations

between the pairs of metabolite levels that were dose-

dependent in the short-term intermittent ethanol-

intoxicated rats. Unfortunately, we cannot provide

conclusive evidence because we did not experimentally

evaluate the six metabolite-metabolite relationships, the

metabolic contributions, and the correlation among them

in the short-term intermittent ethanol-intoxicated rats.

To date, several studies have reported cerebral

neurochemical profile changes in binge alcohol-abusing

patients (Meyerhoff et al., 2004; Gomez et al., 2012)

and binge ethanol-exposed rat model (Zahr et al.,

2010). However, until recently, these studies have not

experimentally reported the correlations of the six pairs

of metabolites between the intermittently exposed states

of ethanol. In particular, the metabolite signals of GABA

(�1 mM), Asp (1–2 mM), and Ala (�0.5 mM) were

difficult to evaluate because of their lower metabolic

concentrations and/or severely overlapping peaks with

more intense resonances as compared to that of other

neurochemical compounds (De Graaf, 2007). Therefore,

further studies using pathological and neurophysiological

investigations of the intermittently exposed states of

ethanol are required to strengthen our findings and

interpret the correlation of the various metabolites.

There were some limitations in our methodology. First,

the present study assessed only the frontal cortical region

in the CNTL group and the short-term intermittent LDE-

and HDE-exposed rats. Numerous studies have

demonstrated that binge alcohol-exposed adult rat

models (Majchrowicz, 1975) reveal significant neuronal

degeneration in the regions of the temporal (entorhinal/

perirhinal) cortex and the hippocampus (Collins et al.,

1996; Nixon, 2006). Because we focused on quantifying

the alterations in the neurochemical profile induced by

short-term intermittent ethanol exposure in the region of

the rat frontal cortex, we did not assess neuronal

degeneration/recovery using previously described

methodologies (Crews et al., 2000; Obernier et al.,

2002a; Cippitelli et al., 2010). Hence, further studies on

binge ethanol exposure in the various regions of the rat

brain (particularly, the temporal [entorhinal/perirhinal]

cortex and the hippocampus) and neuronal

degeneration/recovery are necessary to obtain more

quantitative assessments to provide conclusive

evidence. Second, the intragastric administration

protocol in the animal model was a potentially stressful

model. Thus, all animals might have exhibited altered

cerebral metabolite alterations due to the handling

stress (e.g., insertion of the intragastric tube [gavage

method] and immobilization with the hand) during

ethanol administration. However, several studies have

used the 4-day model of the binge protocol because of

its several advantages (Majchrowicz, 1975). The

intragastric administration protocol causes sustained

BALs and rapidly induces physical dependence in binge

ethanol-exposed rats (Zahr et al., 2010). Therefore,

the influences of immobility and handling stress are

necessary considerations for the quantitative

assessment of the cerebral metabolite changes in the

intermittent ethanol intoxication rat model. Finally, the

number of experimental animals in each group was too

small for any definite conclusions. Hence, additional

studies in a larger population are necessary for more

detailed quantitative assessments.

CONCLUSION

In summary, the present study conducted ex vivo 1H HR-

MAS NMR spectroscopy in a rat model to quantitatively

assess the dose-dependent influences of short-term

intermittent ethanol intoxication on cerebral

neurochemical changes in the rat frontal cortex. From

our results and those of previous studies, significantly

lower tNAA levels might reflect that HDE short-term

intermittent ethanol intoxication results in neuronal

degeneration and dysfunction in the frontal cortex of

HDE-exposed rats than in that of the CNTL group and

the LDE-exposed rats. Moreover, the significantly

altered GABA levels between the HDE- and the LDE-

exposed rats may reflect alterations in GABA synthesis

and GABAA receptor densities. Significantly lower GSH

levels possibly indicate that HDE intoxication (ethanol

doses over 2.5 g/kg) may lead to oxidative stress,

possibly due to lipid peroxidation stimulation through the

formation of free radicals and/or abnormalities of the

antioxidant defense system in the frontal cortex of the

HDE-exposed rats. Thus, our ex vivo 1H HR-MAS

NMRS results, which exhibited significant alterations for

normalized tNAA, GABA, and GSH levels among the

CNTL, LDE-, and HDE-exposed rats, might suggest that

these markers can be utilized as key markers of the

dose-dependent influence of short-term intermittent

ethanol intoxication in the frontal cortex.

Acknowledgements—This study was supported by a grant

(2010-0008096) from the Basic Science Research Programs

through the National Research Foundation (NRF) and the pro-

gram of Basic Atomic Energy Research Institute (BAERI)

116 D.-W. Lee et al. / Neuroscience 262 (2014) 107–117

(2009-0078390) and a grant (2012-007883) from the Mid-career

Researcher Program funded by the Ministry of Education, Sci-

ence & Technology (MEST) of Korea. This work was conducted

with the ex vivo 500-MHz high-resolution NMRS system from

Agilent Technologies Korea Ltd., Seoul, Republic of Korea.

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(Accepted 27 December 2013)(Available online 7 January 2014)