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Subtype-Specific Alterations of  -Aminobutyric Acid and Glutamate in Patients With Major Depression
Gerard Sanacora, MD, PhD;
Ralitza Gueorguieva, PhD;
C. Neill Epperson, MD;
Yu-Te Wu, MPH;
Michael Appel, MS;
Douglas L. Rothman, PhD;
John H. Krystal, MD;
Graeme F. Mason, PhD
Arch Gen Psychiatry. 2004;61:705-713.
ABSTRACT
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Background Measurement of cortical  -aminobutyric acid (GABA) and glutamate concentrations is possible using proton magnetic resonance spectroscopy. An initial report, using this technique, suggested that occipital cortex GABA concentrations are reduced in patients with major depressive disorder (MDD) relative to healthy comparison subjects.
Objectives To replicate the GABA findings in a larger sample of MDD patients, to examine the clinical correlates of the GABA reductions in these subjects, and to examine other critical metabolite levels.
Design Study for association.
Setting Academic clinical research program.
Participants The GABA measurements were made on 38 healthy control subjects and 33 depressed subjects.
Interventions Occipital cortex metabolite levels were measured using proton magnetic resonance spectroscopy.
Main Outcome Measures The levels of occipital cortex GABA, glutamate, N-acetylaspartate, aspartate, creatine, and choline-containing compounds, along with several measures of tissue composition, were compared between the 2 groups.
Results Depressed subjects had significantly lower occipital cortex GABA concentrations compared with healthy controls (P = .01). In addition, mean glutamate levels were significantly increased in depressed subjects compared with healthy controls (P<.001). Significant reductions in the percentage of solid tissue (P = .009) and the percentage of white matter (P = .04) in the voxel were also observed. An examination of a combined database including subjects from the original study suggests that GABA and glutamate concentrations differ among MDD subtypes.
Conclusions The study replicates the findings of decreased GABA concentrations in the occipital cortex of subjects with MDD. It also demonstrates that there is a change in the ratio of excitatory-inhibitory neurotransmitter levels in the cortex of depressed subjects that may be related to altered brain function. Last, the combined data set suggests that magnetic resonance spectroscopy GABA measures may serve as a biological marker for a subtype of MDD.
INTRODUCTION
Several lines of evidence from animal and human studies suggest that the -aminobutyric acid (GABA) system contributes to the neurobiological features underlying major depressive disorder (MDD). This subject has been examined by several researchers.1-5 Collectively, the studies suggest MDD is associated with deficits in GABAergic function. This hypothesis has been clearly supported by consistent findings of reduced GABA content in the plasma and cerebrospinal fluid of depressed individuals relative to comparison subjects.6-12
Consistent with reports of widespread reductions in GABA content, in vivo proton magnetic resonance spectroscopy (hydrogen 1 [1H]–MRS) has more recently been used to demonstrate reduced occipital cortex GABA concentrations in a sample of severely depressed subjects.13 Other recent studies14-15 demonstrating that treatment of depression with electroconvulsive therapy or selective serotonin reuptake inhibitor agents increases occipital cortex GABA concentrations in MDD patients suggest that GABA abnormalities may be normalized following treatment. If reproducible, these findings significantly strengthen the association between impaired GABAergic function and MDD, and may provide a novel perspective into the pathophysiological processes related to MDD. The primary objectives of this study were as follows: (1) to replicate the original findings of reduced GABA levels in the occipital cortex of MDD subjects in a larger sample, with a broader range of depression severity, controlling for cortical volume and tissue composition; (2) to expand the analysis to include glutamate and other metabolites detectable by 1H-MRS; and (3) to explore potential clinical correlates to the differences in GABA and metabolite concentrations.
METHODS
SUBJECTS
All subjects provided written informed consent using forms and procedures approved by the Yale Human Investigations Committee. Forty-four depressed subjects meeting DSM-IV criteria for MDD based on the Structured Clinical Interview for DSM-IV Axis I Disorders: Patient Edition16 were recruited through newspaper advertisement and referrals from community physicians. An active substance abuse disorder within the 6 months preceding study enrollment was considered an exclusion criterion. Subjects who were taking medication for the treatment of their depression completed a minimum 2-week medication washout before spectroscopy, with only diphenhydramine hydrochloride, 25 to 50 mg, being administered for insomnia.
The 38 healthy control subjects had no personal, or first-degree family, history of MDD or other DSM-IV diagnoses, per interview.
MAGNETIC RESONANCE SPECTROSCOPY
Studies were performed with a 2.1-T magnet (Oxford Magnet Technology, Oxford, England) with a 1-m bore and a spectrometer (Avance; Bruker Instruments, Billerica, Mass). Subjects lay supine with the occipital surface of the head against a 7-cm distributed capacitance surface coil. Gradient-echo scout images were acquired from 5-mm-thick slices, with a 1-cm center-to-center slice separation and a field of view of 240 mm divided into 128 x 128 pixels. Noniterative shimming was performed using an in vivo automatic method (FASTERMAP)17 in a 3.4-cm-diameter spherical volume. A 3.0 x 3.0 x 1.5-cm volume was selected across the midline of the brain, centered 2 cm from the dura. Localization was achieved with selective excitation; 3-dimensional, image-selected, in vivo spectroscopy; outer volume suppression; and a surface spoiler. After adjusting the radiofrequency power levels, a J-editing sequence18-19 yields pairs of subspectra that are subtracted to obtain the edited GABA signal. Briefly, one subspectrum was acquired with an inversion pulse applied to the GABA C4 proton and one subspectrum was acquired without the inversion pulse. The phase of the coupled GABA C3 proton resonance was inverted in one subspectrum relative to the other, but the other, uncoupled, resonances in the region (creatine and choline) were the same in both spectra. When the 2 subspectra were subtracted, creatine and choline vanished, leaving GABA. The data were acquired in interleaved fashion, toggling between 64-second sets of acquisitions, a set with the inversion pulse and a set without the inversion pulse. The detection was run for 20 minutes to yield 9 pairs of subspectra. Subspectra were acquired with 8000 data points in a 510-millisecond acquisition, with a 2-second repetition time and an echo time of 68 milliseconds.
By using technical computing software (MATLAB; The Mathworks, Inc, Natick, Mass), each sub-free induction decay was line broadened by 3 Hz, zero filled to 32 000 points, and Fourier transformed. The subspectra were phase based on the spectrum with the inversion pulse applied, and the area of the creatine resonance was measured. The 2 subspectra were subtracted, and the area of the GABA resonance was measured. If patients moved during any of the 9 sets of GABA editing scans, the much larger and sharper creatine and choline resonances caused well-defined subtraction errors that prevented the measurement of GABA, and any pairs of subspectra with such patient movement were not processed further. The level of GABA was determined by adding together the scans that showed no signs of patient motion. The concentration of GABA was determined from the ratio of GABA–total creatine resonances according to the following18:
[GABA-] = (AreaGABA/AreaCreatine – 0.07) x (0.93 x 1.01) x (3/2) x [Creatine]
where 0.07 was subtracted to account for the contribution of coedited macromolecules20-23 to the GABA resonance, 0.93 is the integral correction factor for the difference in integration limits due to the 0.03–part per million difference in the chemical shift of creatine and GABA, 1.01 corrects for the editing efficiency, and 3/2 adjusts for the difference of 2 protons detected in GABA vs 3 in creatine. The concentration of creatine was 9 mmol/kg.24
In 55 subjects, spectroscopic measurements of N-acetylaspartate (NAA) and other metabolites were obtained in the same voxel. Some subjects were not able to tolerate the additional time in the scanner. The sequence was applied in pairs to yield subspectra that contain either macromolecules alone or macromolecules combined with the metabolites of interest.25 Briefly, one subspectrum was acquired with a hyperbolic secant inversion pulse applied across the spectral bandwidth, followed by an inversion-recovery delay to null the metabolites, and one subspectrum was acquired without the inversion pulse. The macromolecule subspectrum was subtracted from the other subspectrum to obtain a spectrum of metabolites alone. The data were acquired in interleaved fashion, toggling between individual 48-second sets of inverted and uninverted acquisitions. Each block was stored, and the sequence run for 20 minutes to yield 16 pairs of subspectra. The subspectra were acquired with 8000 data points in a 510-millisecond acquisition, with a 5-second repetition time and an echo time of 12 milliseconds. A scan of unsuppressed tissue water was also acquired to evaluate the absolute level of creatine and for eddy current correction of the short-echo sequence. By using technical computing software (MATLAB), each sub-free induction decay was processed using a lorentzian-to-gaussian conversion of –1 and 6 Hz, Fourier transformation, spectral phasing, and subtraction. The peak amplitudes at 3.23, 3.03, 2.75, 2.60, 2.45, 2.29, and 2.02 parts per million were measured and deconvolved using model spectra obtained in solutions of GABA, creatine, glutamate, glutamine, aspartate, and NAA to determine the metabolite levels relative to the resonance of total creatine, deconvolving GABA using its concentration from the subject's J-edited GABA measurement. The concentrations were determined assuming a concentration of 9 mmol/kg for creatine.24
To account for potential changes in tissue composition, a series of 3-mm-thick contiguous images of T1 were used to quantify the amount of gray matter, white matter, and cerebrospinal fluid in the voxel of interest.26 The images of T1 were measured using a series of inversion-recovery images that required images of the spatial distribution of the radiofrequency power to overcome the problems associated with radiofrequency inhomogeneity.27-28 The concentrations of GABA, glutamate, and other metabolites were compared for the 2 groups.
STATISTICAL ANALYSIS
The primary objective of this study was to replicate the finding of reduced occipital cortex GABA concentrations associated with MDD.13 The data for the 71 subjects were analyzed using an analysis of covariance (ANCOVA), with GABA levels as the response variable and diagnosis (depressed vs healthy) as the main predictor variable. Percentage tissue, percentage white matter, and NAA level were individually considered as covariates, then dropped from the model because they were nonsignificant at the P = .05 level. Analysis of covariance was also used to evaluate the effect of diagnosis on the levels of glutamine, glutamate, NAA, aspartate, and choline, the GABA-glutamate ratio, and the percentages of white matter and tissue. The percentages of white matter and tissue and the NAA level were considered as covariates in the models for glutamate, glutamine, and GABA-glutamate ratio. Age and sex were considered as covariates in all models, but when not significant, they were dropped from the models.
Correlations among metabolite levels and measures of tissue composition were computed for depressed subjects and healthy controls (N = 71). Correlations of metabolites and measures of tissue composition with Hamilton Depression Rating Scale scores were computed only for depressed subjects (n = 33). Bonferroni correction was applied.
Most subjects in this study were outpatients with disease in the mild to moderate range of severity, recruited through advertisement, while most subjects in the original study by Sanacora et al13 were recruited from an inpatient research facility and had much more severe levels of depression. We combined the data sets to broaden the range of subjects in an effort to study potential differences in cortical GABA concentration between various subtypes and levels of depression severity (total sample size, 105: 71 from study 2 and 34 from study 1). Analysis of covariance was used to evaluate the GABA measurements, using DSM-IV defined (Structured Clinical Interview for DSM-IV Axis I Disorders: Patient Edition–confirmed) subtype as a cofactor, where the subtypes were melancholic depressed, atypical depressed, depressed with no subtype, and healthy control. Age and sex were included as covariates. The effect of the study (ie, previously published data vs new data) was also included as a cofactor because data from the old study could differ from data from the new study, because of population differences or the technical upgrades in the magnetic resonance system. Multiple comparisons among subtypes were performed using the Tukey-Kramer method.
All statistical tests were performed using  = .05, with the Bonferroni correction when appropriate, and SAS statistical software, version 8.2 (SAS Institute Inc, Cary, NC). Data are given as mean ± SD unless otherwise indicated.
RESULTS
DESCRIPTIVE SAMPLE DATA
Of the 44 depressed subjects enrolled in the study, 33 successfully completed the baseline GABA 1H-MRS study, resulting in spectra of acceptable quality for evaluation. Two subjects were dropped from the study after being given medications by another physician between the time of enrollment and the 1H-MRS study. Three subjects aborted the study while in the magnet because of anxiety and claustrophobia, and data were lost for 6 subjects due to either movement artifact or system malfunction (primarily software errors). Twenty-nine subjects completed the short-echo 1H-MRS study, providing quality spectra allowing for measures of other metabolites, including glutamate. Thirty-eight healthy controls completed the GABA study and 28 completed the short-echo study.
The mean age of the depressed subjects was 41.87 ± 9.88 years, and was significantly higher than that of the controls (35.74 ± 11.40 years; t69 = –2.40, P = .02). The median (range) ages were 41.13 (19.08-57.13) and 31.98 (19.51-62.60) years, respectively. There was also a trend for men to compose more of the depressed group (22 [67%] of 33 subjects) than the control group (15 [39%] of 38 subjects) ( 21 = 5.23, P = .02). Therefore, age and sex were considered as covariates in all further analyses.
Depression ranged from mild to severe, as reflected by the 25-item Hamilton Depression Rating Scale scores. A complete summary of the patients' clinical histories is provided in Table 1.
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Table 1. Characteristics of the 33 Depressed Subjects
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1H-MRS MEASURES
Cortical GABA Concentrations
Magnetic resonance spectroscopic measures of GABA levels (Figure 1) were analyzed for an effect of diagnosis. As shown in Figure 2, the magnetic resonance spectra showed that the concentration of cortical GABA was significantly lower for depressed subjects (1.20 ± 0.42 mmol/kg) than for controls (1.42 ± 0.28 mmol/kg) (F1,69 = 6.79, P = .01). The percentages of tissue (P = .26) and white matter (P = .36), the NAA level (P = .80), age (P = .83), and sex (P = .97) did not have a significant effect on GABA levels. Of specific interest was the fact that only 1 of the 38 healthy controls had GABA concentrations below 1 mmol/kg of brain tissue, while 15 of the 33 depressed subjects had GABA concentrations in this range. There was no evidence to suggest a medication washout effect is related to the decreased GABA content because the GABA concentration for the 8 subjects who required a washout was actually higher than for the MDD group as a whole (1.40 ± 0.50 mmol/kg of tissue).
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Figure 1. A J-edited measurement of cortical -aminobutyric acid (GABA) in representative healthy (A) and depressed (B) subjects. Upper spectra show unedited spectra; and bottom spectra, subtraction spectra with creatine (Cr) and choline (Cho) resonances canceled. The scale of the subtraction spectra is magnified 8-fold. NAA indicates N-acetylaspartate; ppm, parts per million.
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Figure 2. Occipital cortex -aminobutyric acid (GABA) concentrations measured in 38 healthy and 33 depressed subjects. Mean ± SD concentrations were 1.42 ± 0.28 and 1.20 ± 0.42 mmol/kg, respectively. The shaded area highlights the large percentage of depressed subjects with GABA concentrations below 1 mmol/kg of tissue relative to healthy subjects.
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Cortical Glutamate and Other Metabolite Concentrations
Levels of glutamate, glutamine, NAA, aspartate, and choline, the GABA-glutamate ratio, and tissue composition were evaluated for an effect of diagnosis. Glutamate concentrations were significantly higher in the patients (9.20 ± 1.26 mmol/kg) than in the control subjects (7.99 ± 1.13 mmol/kg) (ANCOVA F1,54 = 29.8, P<.001) (Figure 3), with no effect of age or sex but a significant effect of NAA (t54 = 4.72, P<.001). The ratio of GABA-glutamate was also significantly higher in patients than in control subjects (ANCOVA F1,55 = 10.3, P = .002). Chemicals other than glutamate and GABA did not show significant differences at P = .05. After Bonferroni correction (P = .05/8), the glutamate level and the GABA-glutamate ratio were still significantly (P = .001) higher for patients than for controls.
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Figure 3. Occipital cortex glutamate concentrations measured in 28 healthy and 29 depressed subjects. Mean ± SD concentrations were 7.99 ± 1.13 and 9.20 ± 1.26 mmol/kg, respectively.
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The NAA concentration was not significantly different between the depressed and healthy groups (P = .16). Age was significantly associated with NAA concentrations (ANCOVA F1,55 = 4.69, P = .03). Sex had a significant effect on choline level (ANCOVA F1,55 = 6.21, P = .01), with women and men having choline levels of 1.48 ± 0.15 and 1.39 ± 0.12 mmol/kg, respectively.
The ratio of creatine–tissue water (x100 000) was 0.27 ± 0.03 and 0.26 ± 0.06, respectively, in the 27 control subjects and 28 patients from whom the water measure was obtained. A 2-sample t test showed no significant difference between groups (P = .66). Pairwise t tests of the subtypes showed no significant difference in the ratio of creatine–tissue water among control subjects and subtypes (lowest value, P = .67).
Measures of Tissue Composition
Depressed subjects had significantly less solid tissue in the voxel (93.9% ± 4.1%) than did controls (96.2% ± 2.2%) (ANCOVA F1,65 = 7.22, P = .009), with neither age nor sex reaching a significance level of .05. Voxels from depressed subjects also contained a significantly smaller proportion of white matter (36.3% ± 5.4%) than from the healthy controls (39.7% ± 7.1%) (ANCOVA F1,64 = 7.32, P = .009), even after controlling for age (ANCOVA F1,64 = 4.44, P = .04), and a significantly larger portion of gray matter (ANCOVA F1,64 = 6.25, P = .02) controlling for age (ANCOVA F1,64 = 7.29, P = .009) (Table 2).
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Table 2. The MRS Measures
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CORRELATION ANALYSIS
After Bonferroni correction for multiple tests (P = .05/45), only 3 significant correlations remained between the variables in this study. These were the negative correlation between GABA and glutamate (r = –0.60, P<.001) (Figure 4), the positive correlation between percentage tissue and percentage white matter in the MRS voxel (r = 0.50, P<.001), and the positive correlation between NAA and aspartate (r = 0.60, P<.001). The latter relationship was most likely accounted for by spectral overlap of the metabolites, which, therefore, confounded any biological meaning of the correlation. Although not meeting the conservative Bonferroni correction test for significance, there were also correlations at the .01 significance level between GABA and glutamine (r = 0.37, P = .005), between NAA and glutamate (r = 0.36, P = .006), and between NAA and percentage tissue (r = 0.40, P = .003).
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Figure 4. Correlation of occipital cortex -aminobutyric acid (GABA) and glutamate concentrations in healthy and depressed subjects.
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EFFECT OF DEPRESSIVE SUBTYPE: COMBINED DATA SET
By combining the data from this study with the data from the initial previously published study,13 we were able to increase our sample size sufficiently to allow us to better explore clinical correlates, including the difference between the various DSM-IV–defined subtypes of MDD.29 Multiple linear regression analysis was used to evaluate the GABA measurements in the old study and the present data, looking at melancholic depression, atypical depression, depression with no subtype, and control subjects, controlling for age, sex, and a study effect. By using this model, we found a significant subtype effect (ANCOVA F3,100 = 11.09, P<.001), and a multiple comparison by Tukey-Kramer showed that the GABA levels were significantly lower in patients with melancholic depression compared with controls (P<.001) and in patients with no subtype compared with controls (P = .002), but not in patients with atypical depression (Figure 5). Interestingly, the melancholic subjects with psychotic features all had GABA concentrations below 0.8 mmol/kg of tissue. There was also a significant study effect (ANCOVA F1,100 = 5.08, P = .03), but this was largely accounted for by differences in the depressed group because there was no difference in GABA concentrations between the control subjects from study 1 (1.45 ± 0.39 mmol/kg) and from study 2 (1.42 ± 0.28 mmol/kg). Pairwise t tests of the subtypes did not show any significant differences in the ratio of creatine–tissue water among controls and subtypes (lowest value, P = .67).
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Figure 5. Occipital cortex -aminobutyric acid (GABA) concentrations for all subjects in the combined data set broken down by DSM-IV subtypes of major depressive disorder. Boxed symbols represent subjects who also met the criteria for psychotic features.
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There was no correlation between cortical GABA concentrations and the Hamilton Depression Rating Scale score based only on the present study (n = 33) (Pearson product moment correlation coefficient r = –0.15, P = .41). There was a trend based only on the subjects in the original study (n = 14) (Pearson product moment correlation coefficient r = –0.51, P = .07). Based on the combined data set, there is a significant correlation (r = –0.38, P = .01). However, controlling for the study (Pearson product moment partial correlation coefficient r = –0.22, P = .15) reduces the finding back to a trend level.
By using the short-echo data collected primarily in the second study, glutamate differed significantly among the 4 groups (ANCOVA F3,59 = 8.59, P<.001). The multiple comparisons by Tukey-Kramer showed significant differences in glutamate between patients with melancholic depression and controls (P<.001) and between patients with no subtype and controls (P = .03) (Figure 6). The comparison between the melancholic depressed group and the no subtype group was a trend (P = .05). Patients with atypical depression did not have significantly different GABA (P = .10) and glutamate (P = .11) levels when compared with controls and patients not meeting either subtype criteria. However, this is likely because of the limited sample size.
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Figure 6. Occipital cortex glutamate concentrations broken down by DSM-IV subtypes of major depressive disorder.
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COMMENT
The present study yielded 3 principal findings. (1) A reduction in occipital cortical GABA levels was found in a new and less severely ill group of patients with MDD, controlling for differences in cortical tissue composition. (2) Increased cortical glutamate levels and GABA-glutamate ratios were observed in the occipital cortex of MDD subjects. (3) The reductions in cortical GABA levels and increased glutamate levels were particularly associated with melancholic and psychotic features in the MDD subjects.
The finding of significantly reduced occipital cortex GABA concentrations in the depressed subjects relative to the control subjects is consistent with that of the previous 1H-MRS study. The difference in the magnitude of the mean reduction between the 2 studies is likely related to differences in the clinical characteristics of the MDD subjects recruited into the 2 studies. The first study examined a cohort of more severely depressed subjects recruited mostly from an inpatient psychiatric unit. The GABA levels in these patients were reduced by 52%, with almost no overlap between the MDD and control subjects' levels. Subjects in the present study, recruited primarily through newspaper advertisements, included a broader range of illness severity, and showed a smaller group difference in GABA levels. However, the many depressed subjects compared with control subjects with GABA concentrations below 1 mmol/kg of brain tissue suggests the existence of a subgroup of depressed subjects with markedly decreased levels of GABA in the occipital cortex, similar to those in the first study. Thus, we believe the greater heterogeneity among the clinical characteristics of the MDD subjects in the second sample likely explains the larger range and higher mean GABA concentrations that were observed in the study.
Analyzing the combined data sets from the original and present studies supports this hypothesis. The post hoc analysis of the combined data set provides strong evidence that differences exist in cortical GABA concentrations between subsets of depressed subjects. Depressed subjects with melancholic features seem to have the largest and most consistent GABA reductions. This seems to be especially clear in the subset of melancholic subjects who also have psychotic features. In contrast, normal or near-normal GABA concentrations were found in most atypically depressed subjects. This finding is not completely unprecedented. Roy et al11 reported only finding a significant difference in cerebrospinal fluid GABA concentrations between depressed and control subjects when they limited the comparison to the 13 melancholic patients in the study and the controls. Petty et al6 also reported that the lowest plasma GABA concentrations appeared in subjects likely to meet the current diagnosis of melancholic depression.
The addition of a short-echo scan to the protocol allowed us to collect other measures in addition to GABA level in this study. Of all the other compounds examined, only glutamate was significantly different between the groups after controlling for multiple comparisons. Because of the increased noise and significant overlap with glutamine, the measurement of glutamate is associated with increased variability in the concentrations obtained. However, there again seems to be a maximum value that is rarely breached by control subjects but frequently violated in a subgroup of depressed subjects. Again, most markedly outlying concentrations were from the subjects with the melancholic subtype of MDD. This finding is of interest in light of the fact that glutamatergic abnormalities have previously been reported in several studies30-35 of depressed subjects. Although these studies have failed to show a consistent direction to the glutamate abnormalities in the varied brain regions examined, the growing series of studies36-41 demonstrating antidepressant effects in several agents with antiglutamatergic activity further suggest that the abnormal glutamate concentrations may have clinical relevance.
In sum, these results suggest the existence of a subgroup of MDD subjects with coexistent abnormalities in the major excitatory and inhibitory neurotransmitter systems. These findings add further to the mounting evidence suggesting that GABA and glutamate contribute to the pathophysiological features and treatment of mood disorders.42 The large increase in the ratio of GABA-glutamate in this subgroup of MDD subjects may have significant implications regarding neurophysiological processes, such as cortical excitability, and potential excitotoxicity that may be directly related to the pathophysiological features and pathogenesis of the disorder.
We are left to speculate on the mechanisms that could account for the combined abnormalities in the amino acid neurotransmitter systems. The metabolic pathways regulating the synthesis and cycling of GABA and glutamate are tightly coupled,43-45 suggesting that a single alteration in a shared pathway may account for the elevated glutamate and reduced GABA concentrations. The growing number of postmortem studies demonstrating decreased glial cell number and density associated with MDD46-54 provides one interesting possibility to account for the observed amino acid abnormalities. Astrocytes play a critical role in the function and regulation of the amino acid neurotransmitter systems. They provide the primary source of energy to neurons,55 and furnish the major pathway for neuronal glutamate and GABA synthesis.45, 56 Reports57-59 of abnormally elevated levels of S100B, a calcium-binding peptide produced by astrocytes, in patients with melancholic depression further support a potential relationship among astrocyte pathological features, altered amino acid neurotransmitter function, and MDD.
Decreased astrocytic function would be expected to result in decreased flux through the glutamate-glutamine cycle and, because glutamine generated through this cycle is the primary precursor of GABA synthesis,45 decreased GABA synthesis as well. This could account for the consistent findings of reduced GABA concentrations in the brain, cerebrospinal fluid, and plasma specimens of depressed subjects. What effect this would have on static glutamate and glutamine levels is much more difficult to predict because release may also be significantly reduced in this situation, resulting in increased intracellular stores. Unfortunately, the 1H-MRS measures used in this study provide only a static picture of metabolites measured, and do not allow us to determine rates of metabolism or cycling that may help to further isolate a specific site or sites in the metabolic pathways that may be disrupted. However, preliminary results using carbon 13 (13C)–MRS measures of glucose incorporation into the carbon skeleton of the metabolites suggest that the rates of GABA synthesis and glutamate-glutamine cycling are reduced in depressed subjects, in a manner consistent with this hypothesis.60 Future explorations using this approach are likely to provide additional information regarding the specific mechanisms related to the observed abnormalities associated with MDD.
A recent preliminary report61 indicating that the glial reductions in the amygdala of depressed subjects are due, at least in part, to decreases in oligodendrocytic density suggests that more than one glial cell type may be altered in patients with depression. The potential loss of oligodendrocytic material is consistent with the significantly lower content of white matter that was observed in the depressed subjects, and may suggest more diffuse glial cell pathological features. Interestingly, we also observed an increased percent gray matter in the depressed subjects. While unanticipated, this finding is consistent with a recent report by Ballmaier et al,62 and may be related to complex structural changes resulting in altered T1 relaxation properties of the tissue.
The reciprocal relationship between glutamate and GABA that is seen could also be the result of other causes of reduced glutamatergic function. In the context of reports of reduced glucose use63-64 and reduced cortical activity65 associated with MDD, it may be that the low GABA level is related to long-term decreased glutamate release. A similar phenomenon has previously been observed following light deprivation66 and deafferation.67 It is possible that lower glutamatergic activity leads to a reduction in cortical GABA level by a regulatory metabolic process, such as changes in the saturation of enzymes involved in neurotransmitter cycling or control mechanisms imposed by the brain in reaction to reduced glutamate release.68-69
These data must be interpreted in light of several limitations. Some data were lost because of poor spectra quality associated with movement artifact. This loss of data may have introduced a systematic error into the analyses if subjects who moved more tended to have some consistent level of cortical GABA. It is also possible that differences in the macromolecular contributions to the spectra between the depressed and control subjects might account for differences in GABA and glutamate. However, it seems unlikely given that the only reports of macromolecular changes are in diseases with severe structural damage, like multiple sclerosis and stroke.70-72 We also limited the region of interest to the occipital cortex because of technical limitations in the method. This has not been a region thought to be closely associated with the symptoms most commonly characterizing MDD. However, recent studies have demonstrated abnormalities in serotonin1A receptor binding73-74 and signal transduction pathways,75 along with reduced metabolic activity76 in the occipital cortex of depressed subjects. Nevertheless, the limitation of the region-specific analysis further limits our ability to draw any causative relationships between the observed changes and the clinical manifestations of the disorder. Last, the 1H-MRS technique only provides static measures of metabolite concentrations and does not provide specific information about the synthesis or degradation of the metabolites. Future studies exploring additional brain regions, such as the prefrontal cortex, should provide information about the regional generalizability of the findings, and studies using 13C-MRS methods allow us to specifically probe the metabolic pathways regulating GABA and glutamate synthesis and degradation in the brain.
In conclusion, the findings of this study are consistent with those of a previous 1H-MRS study demonstrating lower GABA concentrations in the occipital cortex. The new observation of elevated glutamate levels in the same region is consistent with emerging evidence that suggests both amino acid neurotransmitter systems contribute to the pathophysiological features of MDD. It also suggests that a metabolic pathway common to both systems may be a primary site of pathological features in MDD. Continued advances in our understanding of the physiological features associated with these systems are likely to provide new targets for investigation and may help guide future drug development. Last, the finding that GABA and glutamate abnormalities seem limited to a subset of MDD patients with identifiable clinical correlates suggests that the 1H-MRS measures may have potential value as diagnostic tools.
AUTHOR INFORMATION
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Correspondence: Gerard Sanacora, MD, PhD, Clinical Neuroscience Research Unit, Abraham Ribicoff Research Facilities, Connecticut Mental Health Center, 34 Park St, New Haven, CT 06519 (gerard.sanacora{at}yale.edu).
Submitted for publication November 12, 2003; final revision received February 6, 2004; accepted February 13, 2004.
This study was supported by grant DF99-067 from The Patrick and Catherine Weldon Donaghue Medical Research Foundation (Dr Sanacora); grants K02 AA00261-01 (Dr Krystal) and K02 AA13430-01 (Dr Mason) from the National Institute on Alcohol Abuse and Alcoholism, Bethesda, Md; the Veterans Affairs Research Enhancement Award Program (Drs Sanacora and Krystal); National Alliance for Research on Schizophrenia and Depression, Great Neck, NY (Drs Sanacora and Mason); grant KO8MH01715-01 from the National Institute of Mental Health, Rockville, Md (Dr Sanacora); the Dana Foundation, New York, NY (Drs Sanacora and Epperson); grant P50AA12870 from the National Institute on Alcohol Abuse and Alcoholism, Bethesda (Dr Krystal), grant K23 MH01830 from the National Institute of Mental Health, Rockville (Dr Epperson); grant MH30929-21 from the Mental Health Clinical Research Center at Yale (Drs Krystal and Mason); and The Stanley Foundation, Muscatine, Iowa (Dr Mason).
This study was presented in part at the Annual Meeting of the Society for Biological Psychiatry; May 17, 2003; San Francisco, Calif.
From the Departments of Psychiatry (Drs Sanacora, Gueorguieva, Epperson, Krystal, and Mason), Epidemiology and Public Health (Dr Gueorguieva and Ms Wu), and Diagnostic Radiology (Mr Appel and Drs Rothman and Mason), Yale University School of Medicine, New Haven, Conn.
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