Neurochemistry International 62 (2013) 502–509

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Neurochemistry International

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Quantitative assessment of neurochemical changes in a rat model oflong-term alcohol consumption as detected by in vivo and ex vivo protonnuclear magnetic resonance spectroscopy

Do-Wan Lee a,b, Sang-Young Kim a,b, Jae-Hwa Kim c, Taehyeong Lee d, Changbum Yoo d, Yoon-Ki Nam e,Jin-Young Jung a,b, Hae-Chung Shin e, Hwi-Yool Kim d, Dai-Jin Kim c,f, Bo-Young Choe a,b,⇑a Department of Biomedical Engineering, The Catholic University of Korea, College of Medicine, Seoul, South Koreab Research Institute of Biomedical Engineering, The Catholic University of Korea, Seoul, South Koreac Department of Biomedical Science, The Catholic University of Korea, College of Medicine, Seoul, South Koread Department of Veterinary Surgery, Konkuk University of Korea, Seoul, South Koreae NMR Research Team & Life Science Group, Agilent Technologies Korea Ltd., Seoul, South Koreaf Department of Psychiatry, Seoul St. Mary’s Hospital, The Catholic University of Korea, College of Medicine, Seoul, South Korea

a r t i c l e i n f o

Article history:Received 8 October 2012Received in revised form 18 January 2013Accepted 3 February 2013Available online 11 February 2013

Keywords:High-resolutionMagic angle spinningMetabolismEthanolFrontal cortex

0197-0186/$ - see front matter � 2013 Elsevier Ltd. Ahttp://dx.doi.org/10.1016/j.neuint.2013.02.007

Abbreviations: MRS, magnetic resonance spectroscresonance spectroscopy; HR-MAS, high-resolution maper million; CPMG, Carr-Purcell-Meiboom-Gill; CRLBLCModel, Linear Combination Model; %SD, percentAlanine; Act, acetate; Asp, aspartate; Cho, choline (frphosphocreatine; tCr, Cr + PCr; GABA, gamma-aminoGlu, glutamate; Glc, glucose; GPC, glycerophosphocscyllo-inositol; mI, myo-inositol; Lac, lactate; NAAN-acetylaspartylglutamate; tNAA, NAA + NAAG; PCh,PCh + GPC; Eth, ethanol; Tau, taurine; BALs, blood alc⇑ Corresponding author. Address: Department

Research Institute of Biomedical Engineering, CollegUniversity of Korea, #505 Banpo-Dong, Seocho-Gu,Tel.: +82 2 2258 7233; fax: +82 2 2258 7760.

E-mail address: bychoe@catholic.ac.kr (B.-Y. Choe)

a b s t r a c t

The aim of present study was to quantitatively investigate the neurochemical profile of the frontal cortexregion in a rat model of long-term alcohol consumption, by using in vivo proton magnetic resonance spec-troscopy (1H-MRS) at 4.7 T and ex vivo 1H high-resolution magic angle spinning (HR-MAS) technique at11.7 T. Twenty male rats were divided into two groups and fed a liquid diet for 10 weeks. After 10 weeks,in vivo 1H MRS spectra were acquired from the frontal cortex brain region. After in vivo 1H MRS experi-ments, all animals were sacrificed and 20 frontal cortex tissue samples were harvested. All tissue exam-inations were performed with the 11.7 T HR-MAS spectrometer and high-resolution spectra wereacquired. The in vivo and ex vivo spectra were quantified as absolute metabolite concentrations and nor-malized ratios of total signal-intensity (i.e., metabolitesNorm), respectively. The absolute quantifications ofin vivo spectra showed significantly higher glycerophosphocholine plus phosphocholine (GPC + PCh) andlower myo-inositol (mIns) concentrations in ethanol-treated rats compared to controls. The quantifica-tions of ex vivo spectra showed significantly higher PChNorm, ChoNorm and tChoNorm, and lower GPCNorm

and mInsNorm ratio levels in ethanol-treated rats compared to controls. Our findings suggest that reducedmIns concentrations caused by the long-term alcohol consumption may lead to hypo-osmolarity syn-drome and astrocyte hyponatremia. In addition, increased choline-containing compound concentrationsmay reflect an increased cell turnover rate of phosphatidylcholine and other phospholipids, indicating anadaptive mechanism. Therefore, these results might be utilized as key markers in chronic alcohol intox-ication metabolism.

� 2013 Elsevier Ltd. All rights reserved.

ll rights reserved.

opy; NMRS, nuclear magneticgic angle spinning; ppm, part, Cramér–Rao lower bound;

age standard deviation; Ala,ee choline); Cr, creatine; PCr,butyric acid; Gln, glutamine;holine; GSH, glutathione; sI,, N-acetylaspartate; NAAG,

phosphocholine; tCho, Cho +ohol levels.of Biomedical Engineering,e of Medicine, The CatholicSeoul 137-701, South Korea.

.

1. Introduction

Alcohol is the most repeatedly abused substance in developingcountries worldwide and ranks high as a cause of disability(Geibprasert et al., 2010; Lieber, 1995; Saraceno, 2002). Currently,long-term alcohol use disorders (i.e., alcohol abuse and depen-dence) are one of the most common health problems and a majorcause of mortality (Jung et al., 2011).

Most current literature emphasizes that prolonged alcoholabuse can cause brain disorders, such as loss of brain volume, neu-rological dysfunction, functional abnormalities, and neurochemicalalterations in the anterior frontal region (Dao-Castellana et al.,1998; Kril et al., 1997; Moselhy et al., 2001). Previous studies havealso reported that the anterior frontal region is especially

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vulnerable to the adverse effects of long-term alcohol abuse(Moselhy et al., 2001; Pfefferbaum et al., 1997). Numerous protonmagnetic resonance spectroscopy (1H MRS) studies have investi-gated the brain metabolites in chronic alcohol-dependent patientsversus healthy subjects as well as light versus heavy drinkers(Bartsch et al., 2007; Bendszus et al., 2001; Biller et al., 2009;Bloomer et al., 2004; Meyerhoff et al., 2004).

In humans, previous studies utilizing 1H MRS have identifiedchanges in the metabolite concentrations of N-acetylaspartate(NAA), choline-containing compounds, total creatine (tCr, crea-tine + phosphocreatine), and myo-inositol in chronic alcohol-dependent patients (Biller et al., 2009). Among these metabolites,most studies have reported reduced NAA levels (Bartsch et al.,2007; Bendszus et al., 2001; Bloomer et al., 2004; Meyerhoffet al., 2004; Schweinsburg et al., 2003) and elevated choline-containing compound levels (Ende et al., 2006; Meyerhoff et al.,2004) in chronic alcohol-dependent patients, compared to healthysubjects. The myo-inositol levels have varied results, from reduc-tion or elevation (Biller et al., 2009; Meyerhoff et al., 2004; Parkset al., 2002; Schweinsburg et al., 2001; Seitz et al., 1999), and cre-atine levels are referred to as stable (Biller et al., 2009; Parks et al.,2002; Seitz et al., 1999). However, several previous studies suggestthat the brain metabolism from alcohol abuse has large variationsamong individuals, depending on the consumption pattern of alco-hol, types of alcohol (relative dose of alcohol), and period of alcoholdependence (Geibprasert et al., 2010; Zahr et al., 2010). Thus, astudy of long-term alcohol consumption using an animal modelis necessary for more quantitative investigation.

In vivo 1H MRS provides a noninvasive method for quantifica-tion of specific brain biochemical markers and neurotransmittersthat reflect molecular processes (Hong et al., 2011; Opstad et al.,2010; Zahr et al., 2010). However, quantification of the in vivo 1HMRS technique has been severely limited by overlapping peaks inthe narrow chemical shift range (Kim et al., 2011; Tzika et al.,2002). Therefore, ex vivo proton high-resolution magic angle spin-ning (1H HR-MAS) nuclear magnetic resonance spectroscopy(NMRS) is also necessary for obtaining more detailed cerebral neu-rochemical information (Martínez-Bisbal et al., 2004). HR-MAS is apowerful technique for observing the cerebral neurochemical pro-file and allowing high-resolution spectra to be harvested directlyfrom biopsy tissues (Opstad et al., 2009, 2010). The HR-MAS tech-nique can also provide the narrow line-widths of metabolite sig-nals by reducing the line-broadening effect in semi-solid tissuesthrough rapid sample spinning at a magic angle (54.7 degrees)against the magnetic field (Beckonert et al., 2010).

We hypothesized that the specific neurochemical profile of thefrontal cortex region would be significantly altered in the rat mod-el of long-term alcohol consumption as compared to control rats.The aim of present study was to quantitatively assess neurochem-ical changes in frontal cortex of a rat model of long-term alcoholconsumption, as detected by in vivo 1H MRS at 4.7 T (200 MHz)and by ex vivo 1H HR-MAS at 11.7 T (500 MHz).

Fig. 1. Multislice T2-weighted RARE sagittal (A) and axial (B) images (TR/TE = 5000/90 ms, number of acquisitions = 4) of the rat brain with the volume of interest (VOI)centered in the frontal cortex region. The pink color illustrations on the imagesshow the size of the rectangular volume of interest is 19.2 lL. (For interpretation ofthe references to color in this figure legend, the reader is referred to the web versionof this article.)

2. Materials and methods

2.1. Animals

All animal experiments were approved by the Institutional Ani-mal Care and Use Committee (IACUC Number: 2010-0030-04). Theanimals were maintained according to the ‘‘Guide for the Care andUse of Laboratory Animals’’ (NIH Publications No.80–23) issued byILAR, USA.

Six-week-old male Sprague-Dawley rats (177.0 to 192.0 g,n = 20, Orient Bio Inc., Seongnam, Korea) were divided into twogroups (control group: n = 9; ethanol-treated group: n = 11). All

animals were individually housed in standard plastic cages andmaintained on a 12-h light–dark cycle, in ambient temperatureof 24–25 �C. Before the start of the experiments, rats were allowedfree access to food and water for a week. After a week, all animalswere fed a Lieber-DeCarli liquid diet (Control diet: #710027; Eth-anol diet: #710260, Dyets Inc., Bethlehem, PA, USA) for 10 weeks.The ethanol and control liquid diets were nutritionally completematerial containing 67 mL of 95% pure ethanol per 1 L of the liquiddiet, and 1.0 kcal/mL, of which 35% fat, 11% carbohydrate, 18% pro-tein, and 36% derived from pure ethanol. The control diet contained1.0 kcal/mL, of which 35% fat, 47% carbohydrate, and 18% were de-rived from protein. An equivalent amount of maltose dextrin (eth-anol liquid diet: 25.6 g/L, control liquid diet: 115.2 g/L) was addedfor caloric balance between the control group and ethanol group.The design of the liquid diet exposure studies has been previouslydescribed (Simonyi et al., 2002; Wills et al., 2008).

2.2. In vivo proton MR spectroscopy experiments

Designs of the in vivo 1H MRS studies were previously described(Kim et al., 2010, 2011). In vivo proton spectra were acquired from20 animals using 4.7 T horizontal BIOSPEC MR system (BrukerMedical GmbH, Ettlingen, Germany) with a 400 mm bore magnetand 150 mT/m actively shielded gradient coils. Before the MR im-age and MR spectroscopy data acquisitions, rats were anesthetizedusing an inhalation isoflurane chamber at 4–6% concentrations, ina 5:5 mixture of N2O and O2 gas. The anesthesia concentrations ofisoflurane were maintained at 1–2% during the MR scanning. Anes-thetized rats were placed in the prone position with the headfirmly fixed on a palate holder equipped with an adjustable nosecone. The volume of interest [Fig. 1 (A and B), VOI(4.0 � 1.6 � 3.0 mm3; volume: 19.2 lL)] was positioned in thefrontal cortex based on multi-slice axial T2-weighted MR images[Rapid Acquisition with a Relaxation Enhancement (RARE), TR/TE = 5000/90 ms, number of acquisitions = 4, slice thick-ness = 1.0 mm, matrix = 256 � 256]. The VOI was adjusted to min-imize intracranial lipid contamination. Water suppressed 1H MRSspectra were acquired using a point-resolved spectroscopy (PRESS)pulse sequence (TR/TE = 4000/20 ms, number of acquisitions = 384,number of data points = 2048, scan time = 25 min 36 s). The

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unsuppressed water signal was also acquired (TR/TE = 4000/20 ms,number of acquisitions = 16, scan time = 1 min 4 s).

2.3. NMR sample preparation

After the in vivo 1H MRS experiments, all animals were sacri-ficed using CO2 gas. Twenty frontal cortex tissues were quicklyand carefully harvested using the brain slicer matrix (Brain SlicerMatrix, 1.0-mm coronal section interval; Zivic Instruments Inc.,Pittsburgh, PA, USA). All tissues were immediately stored in liquidnitrogen (at �196 �C) to prevent tissue decomposition and bio-chemical changes. The harvested tissue samples were dissectedquickly and inserted in a 4 mm rotor at room temperature (18–20 �C). All prepared NMR rotors (Agilent Technologies Korea Ltd.,Seoul, Korea) were tightly closed with a zirconium plug (AgilentTechnologies Korea Ltd., Seoul, Korea). The ampoules (1.0 mL) ofD2O containing 0.75 wt.% TSP were used for referencing and scal-ing. A few drops of D2O were added to the NMR rotor to providea locking signal. The mass of brain tissue and D2O + TSP solventwere 13–19 mg and 10–14 mg, respectively.

2.4. Ex vivo proton HR-MAS NMR spectroscopy experiments

1H HR-MAS NMR spectroscopy was performed on the VNMRS-500 spectrometer [11.7 T (500.13 MHz), Agilent Technologies KoreaLtd., Seoul, Korea] with a quadruple nuclei 1H, 2H, 13C, 31P) HR-MASNMR nano-probe. The samples were placed in 4-mm-diameter ro-tors and equipped on top of the nano-probe, and typically spun at4–5 kHz and at 54.7 degrees. The design of the 1H HR-MAS NMRspectroscopic studies was previously described (Beckonert et al.,2010; Woo et al., 2010). All one-dimensional HR-MAS NMR spectrawere acquired with the Carr-Purcell-Meiboom-Gill (CPMG) pulsesequence at 277.15 K (4.0 �C) [complex data number = 16384, spec-tral width = 8012.8 Hz, acquisition time = 2.05 s, relaxation delaytime = 10.0 s, pre-saturation time = 2.0 s, inter-pulse delay (s) =0.4 ms, big-tau (eighty 180-degree refocusing pulses) = 0.064 ms,number of acquisitions = 128, and a total scan time = 25 min 16 s].

2.5. In vivo and ex vivo spectral analyses

Acquired in vivo and ex vivo raw data were analyzed in a fullyautomated spectral process, using the Linear Combination Modelsoftware (LC Model, Version 6.2–1L and Copyright: Stephen W.Provencher) with 2 basis sets (for in vivo and ex vivo) containing17 metabolite spectra, as follows: In vivo basis set: Alanine (Ala),aspartate (Asp), choline (Cho), creatine (Cr), phosphocreatine(PCr), gamma-aminobutyric acid (GABA), glutamine (Gln), gluta-mate (Glu), glucose (Glc), glycerophosphocholine (GPC), scyllo-inositol (sI), myo-inositol (mIns), lactate (Lac), N-acetylaspartate(NAA), N-acetylaspartylglutamate (NAAG), phosphocholine (PCh),taurine (Tau), total NAA (NAA + NAAG), and total Cr (Cr + PCr);ex vivo basis set: includes the in vivo basis set plus glutathione(GSH) and acetate (Act). Signal intensities from in vivo spectra wereprocessed with water scaling (WS) for absolute quantification ofthe metabolic concentrations and eddy current correction. Theex vivo data were processed by the total signal intensity normaliza-tion method as previously described (Lentz et al., 2008). The rela-tive signal intensity levels of each metabolite were calculated bydividing peaks area by the total area of all metabolites of interest.All metabolites were fitted in the chemical shift range from 3.85 to0.20 ppm. Analyzed ex vivo data were expressed as normalizedmetabolite ratio levels (i.e., metaboliteNorm).

The standard error estimates and Cramer-Rao lower bounds(CRLBs) are used to provide useful estimates of reliability anduncertainty in each metabolite peak of the LCModel spectra

(Provencher, 2001). CRLBs have been used as acceptable reliabilityfor estimates of fitting uncertainty.

2.6. Statistical analyses

All statistical analyses were performed with the PASW Statistics18 software (SPSS Inc., IBM Company, Chicago, IL, USA). From thenumeric CRLBs (% SD), we only used the range of acceptable reli-ability values (In vivo 1H-MRS CRLBs: below than 40% SD; ex vivo1H NMRS CRLBs: below than 10% SD). An independent t-test ofthe in vivo 1H MRS experiment was used for comparison of themean values of the absolute concentrations by internal water ref-erence between the control and the ethanol-treated group. Anindependent t-test of the ex vivo 1H NMRS experiment was alsoused for comparison of the mean values of the normalized ratiosby the total signal intensity between the control and the ethanol-treated group.

3. Results

3.1. In vivo and ex vivo proton NMR spectra

The in vivo and ex vivo spectra provide a large amount of neuro-chemical information available from the absolute metabolite con-centration and high-resolution spectrum. The in vivo spectrawere assigned the brain metabolites NAA + NAAG (tNAA),Glu + Gln (Glx), Cr + PCr (tCr), GPC + PCh, Tau, Asp, and mIns. Inthe ex vivo spectra, brain metabolite signal assignments are tCr,GABA, tNAA, Act, Ala, Glx, Glu, Gln, Asp, GSH, GPC + PCh + Cho(tCho), Tau, and mIns. Fig. 2 (panels A–D) shows the representativefitted in vivo MR spectra (A and B) and ex vivo HR-MAS NMR spec-tra (C and D) of the frontal cortex between the two groups. Thescale of the chemical shift range was equally matched (3.85 to0.20 ppm) between the in vivo and the ex vivo spectra. The signalintensities are proportionally represented by the cerebral metabo-lite concentrations. The in vivo spectra [Fig. 2 (A and B)] show thatthe total choline-containing compound (tCho) signal intensitieswere higher in the ethanol-treated group compared to the controlgroup. In our results of the 4.7 T in vivo 1H-MRS experiment, the1CH (3.522 ppm), 3CH (3.522 ppm), 4CH (3.614 ppm), and 6CH(3.614 ppm) protons of mIns are mostly observed as a singlet ordoublet peak at approximately 3.56 ppm and overlapped with gly-cine (3.55 ppm). In the 11.7 T ex vivo 1H HR-MAS NMRS spectra[Fig. 2 (C and D)], the mIns peak shows as a doublet of doubletshape at 3.522 and 3.614 ppm.

3.2. Quantification of in vivo proton MR spectra

Fig. 3A illustrates the metabolite concentrations (lmol/g) thatwere quantified from the twenty analyzed in vivo spectra of thefrontal cortex region. The concentration of GPC + PCh (p < 0.01)was significantly higher in the ethanol-treated group comparedto the control group. The GPC + PCh concentration of the ethanol-treated group was 15.79% higher than the control group. However,the mIns concentration (p < 0.05) of the ethanol-treated group was15.91% lower than the control group. All processed in vivo CRLBlevels except GABA were below 40% SD in the control group andethanol-treated group (Fig. 3B).

3.3. Quantification of ex vivo proton HR-MAS NMR spectra

Fig. 4A shows the levels of normalized metabolites (total signalintensity ratios) that were quantified from 18 frontal cortex tissuesamples in the control group and ethanol-treated group. The meanvalues and standard deviations of the normalized metabolic ratio

Fig. 2. The in vivo spectra (A and B) acquired at 4.7 T from the long-term ethanol treated group and control group, in the frontal cortex (PRESS sequence, TR/TE = 4000/20 ms,number of acquisitions = 384, number of data points = 2048). Ex vivo HR-MAS NMR spectra (C and D) acquired at 11.7 T from the tissue samples of the frontal cortex region(CPMG sequence, number of acquisitions = 128, number of data points = 16384, number of data points = 2048, s = 0.4 ms, relaxation delay time = 10.0 s, pre-saturationtime = 2.0 s). The fitted LC Model spectra are represented in bold red. The residues are positioned under the fitted spectra. The chemical shift range is from 0.20 to 3.85 ppm.(For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 3. Concentrations of the brain metabolites (A) and corresponding Cramer-Raolower bound levels (B) quantified by LC Model software in the frontal cortex(control group: n = 9; ethanol-treated group: n = 11). Metabolite concentration andCRLB level units are expressed as lmol/g and percentage standard deviation (%SD),respectively. Vertical lines on each of the bars indicate the (+) standard deviation ofthe mean values. Significance levels (independent t-test): ⁄: p < 0.05, ⁄⁄: p < 0.01.

Fig. 4. Normalized metabolic ratio levels (A) and corresponding Cramer-Rao lowerbound levels (B) quantified by LC Model software in the frontal cortex (controlgroup: n = 9; ethanol-treated group: n = 9). Normalized metabolite levels analyzedby the total signal intensity ratios of the 1-D ex vivo proton NMR spectra. Verticallines on each of the bars indicate the (+) standard deviation of the mean values.Significance levels (independent t-test): ⁄p < 0.05, ⁄⁄p < 0.01, ⁄⁄⁄p < 0.005.

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levels are shown. The GPCNorm (p < 0.05) and mInsNorm (p < 0.05)ratio levels were significantly lower in the ethanol-treated groupcompared to the control group. However, the PChNorm (p < 0.05),ChoNorm (p < 0.005), and tChoNorm (p < 0.01) ratio levels were sig-nificantly higher in the ethanol-treated group than controls. Table 1indicates the significant differences in 11 of the metabolites be-tween the 2 groups in the in vivo and ex vivo experiments.Fig. 4B also shows the mean CRLB levels for estimation of the fit-ting error in the 1H HR-MAS spectra. The processed ex vivo CRLBlevels, except GPC and PCh, were below than 10% SD in the controland ethanol-treated group.

4. Discussion

The present study conducted 1H MRS and HR-MAS NMR spec-troscopy in a rat model for long-term alcohol exposure using theliquid diet technique in order to assess the neurochemical changesin the frontal cortex region. To the best of our knowledge, thisstudy is the first to use in vivo 1H MRS in combination withex vivo 1H HR-MAS NMR spectroscopy techniques in the frontalcortex region of long-term ethanol exposed rats. Moreover, wequantitatively assessed the neurochemical alterations (particularlythe mIns and GPC + PCh metabolic levels) induced by long-termethanol consumption. In this study, acquired in vivo MRS resultsare in good agreement with ex vivo HR-MAS results as well as withother previous studies, such as chronic alcohol dependent patientsand long-term ethanol exposed rats (Braunová et al., 2000; Leeet al., 2003; Schweinsburg et al., 2000; Zahr et al., 2009).

In vivo 1H MRS is a clinically useful diagnostic tool with prom-ising contributions to noninvasive evaluations based on its abilityto discriminate between various biochemical characteristics in hu-mans (Martínez-Bisbal et al., 2004). To understand the spectralcharacteristics of brain disorders using MR spectroscopy, the peaksof the biochemical compounds in in vivo spectra must be clearly re-solved in narrow chemical shift range (0.0–4.0 ppm) (Tzika et al.,2002). For this, high-resolution spectra are required. However, atthe magnetic field strengths typically used for clinical MRI system(�3.0 T), numerous metabolite peaks and macromolecule signalsstrongly overlap, and may cause inaccurate quantification of thebiochemical information (Wilson et al., 2009). Ex vivo HR-MAS dataimproves the spectral resolution, thus clearly separating peaks inthe narrow chemical shift range than those for in vivo MRS (Wilsonet al., 2009). Previous studies suggest that the generally goodagreement between in vivo MRS and ex vivo HR-MAS results canbe used to reliably estimate the metabolite quantities in variousbrain disorders (Tzika et al., 2002; Wilson et al., 2009). Impor-tantly, the choline-containing compound signals shown as GPCcombined with PCh for in vivo spectra due to small chemical shiftdifference between the metabolites are clearly separated as the

Table 1The mean values of the in vivo metabolite concentrations (lmol/g ±SD) and ex vivo normalwith the probability values (p-value). Significance levels of the p-values as follows: ⁄p < 0

In vivo 1H-MRS

Control group Ethanol-treated group p-

GABA 2.699 ± 0.643 2.374 ± 0.574Gln 6.628 ± 1.764 5.296 ± 1.230tNAA 13.695 ± 1.181 13.097 ± 0.841tCr 10.013 ± 1.276 8.741 ± 0.749mIns 5.119 ± 0.657 4.374 ± 0.748 ⁄

Glu 15.977 ± 1.546 15.030 ± 0.934GPC + PCh 1.602 ± 0.159 1.910 ± 0.248 ⁄⁄

GPC – – –PCh – – –Cho – – –GPC + PCh + Cho – – –

free Cho, GPC, and PCh signals in ex vivo HR-MAS spectra. The sig-nificantly lower mIns and higher GPC + PCh concentrations in long-term ethanol-intoxicated rats compared to controls for in vivoexperiments were also observed as significantly lower mInsNorm

and GPCNorm, and higher PChNorm and ChoNorm levels in ex vivoHR-MAS experiments, supporting in vivo MRS findings. Thus, exvivo HR-MAS could be used as complementary methodology tosupport the in vivo MRS data and improve analytical accuracy.

The choline containing compound signals are composed of ace-tylcholine (ACh), free-choline (Cho), phosphocholine (PCh), andglycerophosphocholine (GPC) (Ende et al., 2005). Most of the cho-line peak signal arises from the PCh and GPC signals (Ende et al.,2005, 2006; Parks et al., 2002). Previous studies reported that al-tered choline-containing compound levels were observed in thebrain of the ethanol-intoxicated rodent models as well as alco-hol-dependent patients (Lee et al., 2003; Seitz et al., 1999). Simi-larly, we found that the GPC + PCh concentration wassignificantly higher in the ethanol-treated rats compared to con-trols. We additionally studied the ex vivo 1H HR-MAS NMR spectrafrom the frontal cortex tissue samples after termination of thein vivo experiment. Interestingly, from our ex vivo 1H HR-MASNMRS results, the GPCNorm level was significantly lower in the eth-anol-treated rats than the controls. Unlike the significantly higherGPC + PCh concentrations in the ethanol-treated rats in the in vivostudy, the significantly lower GPCNorm levels may suggest that theGPC concentration might be reduced by long-term alcohol con-sumption in the ethanol-treated rats compared to controls. Never-theless, we consider the possibility that the significantly higherGPC + PCh concentrations may reflect the substantially increasedPCh concentrations. In fact, the PChNorm and tChoNorm ratios weresignificantly higher in the ethanol treated rats than controls. More-over, we also found that the quantified ChoNorm was significantlyhigher. Thus, significantly higher GPC + PCh concentrations andtChoNorm ratios may contribute to substantially increased PChsignals.

Previous studies conducted in ethanol-intoxicated rodent mod-els and alcohol-dependent patients reported increased choline-containing compound signals in the brain (Lee et al., 2003; Seitzet al., 1999; Zahr et al., 2009, 2010). Lee and colleagues reportedinitially increased choline-containing compound signals in ratschronically exposed to alcohol at 16 weeks. However, choline-con-taining compound signals significantly decreased with increasedduration of alcohol consumption over 44 weeks (Lee et al., 2003).Zahr et al. investigated the brain of rats chronically exposed to eth-anol using in vivo MRS (Scan 1: at the 0th [baseline], scan 2: at the16th week, and scan 3: at the 24th week [Zahr et al., 2009]). Similarto a Lee et al. study (Lee et al., 2003), chronic ethanol-treated ratsshowed significantly increased choline signals with increasedduration of alcohol consumption over 24 weeks (Zahr et al.,

ized metabolite ratio levels (MetaboliteNorm ±SD) in the frontal cortex of the rat brain.05; ⁄⁄p < 0.01; ⁄⁄⁄p < 0.005.

Ex vivo 1H HR-MAS NMRS

Value Control group Ethanol-treated group p-Value

0.249 0.048 ± 0.007 0.046 ± 0.002 0.5570.076 0.036 ± 0.005 0.039 ± 0.005 0.1380.222 0.084 ± 0.014 0.085 ± 0.006 0.8760.069 0.073 ± 0.014 0.071 ± 0.004 0.7020.029 0.085 ± 0.014 0.074 ± 0.004 ⁄0.0470.132 0.112 ± 0.016 0.117 ± 0.007 0.4110.004 – – –

0.007 ± 0.005 0.003 ± 0.001 ⁄0.0230.007 ± 0.004 0.010 ± 0.001 ⁄0.0120.010 ± 0.001 0.013 ± 0.001 ⁄⁄⁄0.0010.024 ± 0.002 0.027 ± 0.001 ⁄⁄0.006

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2009). Our results are in good agreement with the spectroscopicfindings of Lee et al. and Zahr et al. (Lee et al., 2003; Zahr et al.,2009). The increased choline-containing compound signals wereobserved in the non-abstinent chronic heavy drinkers (Endeet al., 2005), as well as in the chronic ethanol exposed rodent mod-el (Lee et al., 2003). The authors emphasized that alcohol consump-tion can lead to an increased choline signals. Other previousstudies have also reported that significantly decreased cholineand choline-containing compound signals were observed in detox-ified alcoholic patients (Bendszus et al., 2001; Ende et al., 2005;Parks et al., 2002). The authors interpreted that increased cholinesignals may reflect an increased turnover of phosphatidylcholineand other phospholipids and thus an adaptive brain mechanism(Ende et al., 2006; Lee et al., 2003).

Previous studies have reported that phosphatidylcholine andganglioside actions are most interesting connections with the alco-hol mechanism in the brain, and these actions are potential mark-ers of synaptic membrane development and alteration in chronicalcohol intoxication (Harris et al., 1984; Klemm, 1998). Moreover,Harris and colleagues interpreted that some of the changes in thephysical properties of synaptic membranes produced by long-termalcohol exposure may be due to subtle alterations of gangliosidearrangement or synaptic membrane metabolism (Harris et al.,1984; Klemm, 1998). Thus, from our results and previous studies,significantly increased choline-containing compound signals mightindicate that long-term intoxication of alcohol may lead to changesin synaptic membrane component turnover of the phosphatidyl-choline and phospholipids, possibly due to subtle alterations inganglioside arrangements or synaptic membrane metabolism inthe frontal cortex of long-term alcohol exposed rats.

Our results showed that mIns concentrations were significantlylower (approximately 15.91%) in the ethanol-treated group com-pared to the control group. In the ex vivo 1H HR-MAS NMR results,the mInsNorm ratio levels were also significantly lower. Braunováand colleagues have reported a similar result in the chronic etha-nol-treated rat model (Braunová et al., 2000). The mIns/tCr ratiosdecreased significantly (approximately 19%) in the central brain re-gion of the rats exposed to ethanol for 8 weeks, compared to con-trols (Braunová et al., 2000). The myo-inositol is mainly found inglial cells, functions in osmoregulation, and its concentration is al-tered in many brain disorders (Brand et al., 1993; Haris et al., 2011;Schweinsburg et al., 2000; Thurston et al., 1989). The release ofmyo-inositol from brain cells serves to counteract cell swelling(Häussinger et al., 1994). Accordingly, Häussinger and colleaguessuggested that myo-inositol concentrations may be reduced underconditions of hypo-osmolarity (Häussinger et al., 1994). It has alsobeen emphasized that chronic alcohol dependence can cause ahypo-osmolarity syndrome with severe hyponatremia (Edwardsand Mosher, 1980). Previous studies have reported that hyponatre-mia is caused by the hypo-osmolality of the extracellular fluid,leading to cell swelling (Putterman et al., 1993; Trimarchi et al.,1999). In a clinical study, it was reported that myo-inositol levelswere significantly increased in recently detoxified alcoholics(mean abstinence period: 41.5 days) compared to healthy subjects(Schweinsburg et al., 2000). Schweinsburg and colleagues foundthat increased myo-inositol levels might indicate proliferation oractivation of glial cells (Schweinsburg et al., 2000). However, de-creased myo-inositol levels were reflected in reduced osmolar sta-bility in glial cell activation (Schweinsburg et al., 2000). Thus, theresults of the present study might indicate that decreased myo-inositol levels reflect the hypo-osmolarity and hyponatremia ofthe astrocytes.

Demanet and coworkers emphasized that hypo-osmolality andhyponatremia can be induced by severe neurological disorders andbiological anomalies (Demanet et al., 1971). One study showedthat hyponatremia and hypo-osmolality were likely due to water

intoxication (i.e., overhydration), low sodium content of alcohol,and poor dietary intake of sodium and potassium (Karthigasu,1977). From these previous studies (Demanet et al., 1971; Karthigasu,1977), the factors may lead to hypo-osmolality and hyponatremia,which result in significantly lower levels of myo-inositol than thatin the control rats, due to long-term alcohol intoxication. Otherstudies have also shown hyperosmolality condition in which acutealcohol intoxicated patients present elevated osmolality levelswith increased blood alcohol levels (BALs) (Champion et al.,1975; Vonghia et al., 2008). And, they have reported that theelevated serum osmolality conditions can be influenced by variousfactors, including dehydration, renal impairment, vomiting anddiarrhea (Champion et al., 1975; Vonghia et al., 2008). Thus, serumosmolality levels (hypo-osmolality and hyperosmolality) could beaffected by several factors, such as subjects (alcoholic patientsand alcohol-intoxicated animals) as well as various healthconditions.

Some limitations of our methodologic approach should be dis-cussed. First, we did not quantitate BALs because the ethanol liquiddiet cannot control the self-administration timing in rodent mod-els (Gil-Mohapel et al., 2010). Thus, the ethanol liquid diet haslow and stable BALs (Gil-Mohapel et al., 2010). Nonetheless, theethanol liquid diet has proven to be a very effective techniquefor self-administration of ethanol in rodent models (Gil-Mohapelet al., 2010). Although the ethanol liquid diet has low stable BALs,it has provided advantages including continuous delivery of bothethanol and essential nutrients without triggering aversion in ani-mals (Gil-Mohapel et al., 2010; Lee et al., 2012). In addition, oneimportant advantage of the liquid diet is the absence of side effectscaused by poor nutrition (Lee et al., 2012). Hence, further study isneeded to acquire more stable BALs in long-term ethanol-intoxi-cated rats using a quantitatively ethanol exposure method, suchas vaporized ethanol inhalation technique. Second, previous stud-ies showed different behavior patterns like the decreased locomo-tor activity (in open-field test), seizure susceptibility (in seizurethresholds test), and anxiety-related behavior (elevated plus mazetest) in long-term ethanol-treated rats compared to controls(Kampov-Polevoy et al., 2000; Li et al., 2008). Because we focusedon quantifying neurochemical changes induced by long-termethanol consumption, we did not conducted behavior test usingpreviously described methods. However, we could observe abnor-mal behavioral patterns over the time (i.e., loss of balance and noself-grooming) that commonly seen in alcohol-intoxicated rodentmodel (Van Erp and Miczek, 1997; Kampov-Polevoy et al., 2000).Third, ethanol-treated rats have a relatively short period of ethanolintake. Previous studies have investigated longer periods of etha-nol intake, up to 60 and 24 weeks (Lee et al., 2003; Zahr et al.,2009). These studies were likely long enough to observe significantchanges of cerebral metabolism in the chronic ethanol exposedrats compared with control rats. Therefore, further study withlonger period of ethanol intake is required to strengthen our find-ings. Finally, the number of experimental animals is too small forany definite conclusions. Hence, additional study on a larger popu-lation is necessary for more quantitative assessments.

5. Conclusion

In summary, the present study demonstrated that in vivo MRSand ex vivo HR-MAS spectra provide valuable information to inter-pret brain metabolism in the long-term ethanol-exposed rats. De-creased mIns concentrations in long-term alcohol exposed ratsmay reflect hypo-osmolarity and hyponatremia of astrocytes.Moreover, an increase in choline-containing compounds may indi-cate an increased turnover rate of phosphatidylcholine and otherphospholipids, reflecting an adaptive mechanism of the brain.

508 D.-W. Lee et al. / Neurochemistry International 62 (2013) 502–509

Thus, long-term alcohol consumption may cause functional andmetabolic dysfunction in the frontal cortex region of the rat brain.Therefore, altered mIns and choline-containing compound levelsmight be utilized as key markers in chronic alcohol intoxicationand provide useful neurochemical information about humanchronic alcoholism-related brain damage.

Acknowledgements

This study was supported by a grant (2010-0008096) from theBasic Science Research Programs through the National ResearchFoundation (NRF) and the program of Basic Atomic Energy Re-search Institute (BAERI) (2009-0078390) and a grant (2012-007883) from the Mid-career Researcher Program funded by theMinistry of Education, Science & Technology (MEST) of Korea. Thiswork was conducted with the ex vivo 500 MHz high-resolutionNMRS system from Agilent Technologies Korea Ltd. Seoul, Korea,and with the in vivo 4.7 T animal MRI system from Korea Basic Sci-ence Institute (KBSI), Ochang Center, Korea.

This paper was presented at The 20th Annual Scientific Meetingand Exhibition of the International Society of Magnetic Resonancein Medicine (ISMRM) at Melbourne, Australia, May 5-11, 2012.

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