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Original Article |

Brain Metabolic Alterations in Medication-Free Patients With BipolarDisorder FREE

Stephen R. Dager, MD; Seth D. Friedman, PhD; Aimee Parow, BS; Christina Demopulos, MD; Andrew L. Stoll, MD; In Kyoon Lyoo, MD, PhD; David L. Dunner, MD; Perry F. Renshaw, MD, PhD
[+] Author Affiliations

From the Departments of Radiology (Drs Dager and Friedman), Psychiatryand Behavioral Sciences (Drs Dager and Dunner), and Bioengineering (Dr Dager),University of Washington, Seattle; Consolidated Departments of Psychiatry,Harvard Medical School, Boston, Mass (Ms Parow and Drs Demopulos, Stoll, andRenshaw); and Department of Psychiatry, Seoul National University, Seoul,Korea (Dr Lyoo).


Arch Gen Psychiatry. 2004;61(5):450-458. doi:10.1001/archpsyc.61.5.450.
Text Size: A A A
Published online

Background  Bipolar disorder (BD) has substantial morbidity and incompletely understood neurobiological underpinnings.

Objective  To investigate brain chemistry in medication-free individuals with BD.

Design  Two-dimensional proton echo-planar spectroscopic imaging (PEPSI) (32 × 32, 1-cm3 voxel matrix) acquired axially through the cingulate gyrus was used to quantify regional brain chemistry.

Setting  The Center for Anxiety and Depression at the University of Washington in Seattle and the Bipolar Research Programs at McLean Hospital and the Massachusetts General Hospital in Boston.

Participants  Thirty-two medication-free outpatients with a diagnosis of BD type I (BDI) or BD type II (BDII), predominantly in a depressed or mixed-mood state, were compared with 26 age- and sex-matched healthy controls.

Main Outcome Measures  Tissue type (white and gray) and regional analyses were performed to evaluate distribution of lactate; glutamate, glutamine, and γ-aminobutyric acid (Glx); creatine and phosphocreatine (Cre); choline-containing compounds (Cho); N-acetyl aspartate; and myo-inositol. Chemical relationships for diagnosis and mood state were evaluated.

Results  Patients with BD exhibited elevated gray matter lactate (P = .005) and Glx (P = .007) levels; other gray and white matter chemical measures were not significantly different between diagnostic groups. Isolated regional chemical alterations were found. An inverse correlation between 17-item Hamilton Depression Rating Scale scores and white matter Cre levels was observed for BD patients.

Conclusions  Gray matter lactate and Glx elevations in medication-free BD patients suggest a shift in energy redox state from oxidative phosphorylation toward glycolysis. The possibility of mitochondrial alterations underlying these findings is discussed and may provide a theoretical framework for future targeted treatment interventions.

Figures in this Article

Bipolar disorder (BD) is a psychiatric disorder characterized by mooddisturbances with recurrent episodes of mania, hypomania, and depression.1 Bipolar disorder can be differentiated into clinicalsubtypes of BD type I (BDI), characterized by at least 1 episode of pure mania,and BD type II (BDII), characterized by less clinically severe hypomania andmajor depressive episodes.2,3 Thereis an approximately 1% prevalence rate for BDI among the adult population;the prevalence rate may be somewhat higher for BDII.4,5 Neurobiologicalmechanisms are thought to underlie BD, and there is evidence of a familial,and presumably genetic, predisposition for the disorder.6

Serendipitous observations of the mood-stabilizing effect of lithiumsalts and later certain anticonvulsants, such as valproic acid, have substantiallyimproved the prognosis of patients with BD. Despite this progress, these medicationsare not universally effective, and many individuals are unable to toleratetreatment-related adverse effects.6,7 Inaddition to incomplete clinical response, relapse and recurrence remain commonclinical problems.8,9 A recentsurvey of BD lifetime financial burden in the United States found associatedcosts to be up to $625 000 per patient, depending on treatment refractorinessand chronicity of symptoms.10 Bipolar disordercontinues to be associated with substantial morbidity and mortality, rankingworldwide among psychiatric disorders behind only unipolar depression andalcohol abuse for related disabilities and overall economic load of the illness.11,12

Research conducted over several decades investigating biomarkers relatedto BD provides evidence for widespread alterations of multiple neurotransmitteror signal induction systems and physiological processes associated with thedisorder, as reviewed by Manji and Lenox.13 Increasingly,imaging techniques are being applied to better establish brain mechanismsunderlying the etiology of BD. Positron emission tomography studies, usedto characterize patterns of regional metabolism or cerebral blood flow inmood disorders, typically find regional or widely distributed abnormalitiesof reduced blood flow and metabolism in association with depressed mood states,including BD-related depression.1417 Magneticresonance (MR) imaging studies, as reviewed by Strakowski et al,18 variablyfind evidence of reduced regional gray matter volumes associated with BD.16,1923 Differingsubcortical patterns of structural abnormalities may occur across the spectrumof affective disorders; for example, basal ganglia and amygdalar enlargementare observed in BD,19,24 whereasvolumes of these structures may be reduced in unipolar depression.25,26 Similarly, neuroanatomic findingshave been reported to distinguish BD clinical subtypes, such as the observationof lateral ventricular enlargement in BDI but not BDII patients.27

Magnetic resonance spectroscopy, an imaging modality related to MR imaging,provides an in vivo tissue-based measure of brain chemistry using clinicalMR image scanners that is safe, noninvasive, and reproducible.28,29 Forneuropsychiatric applications at 1.5 T, as reviewed elsewhere,3032 hydrogenH1 (1H) MR spectroscopy can detect and identify subtle alterationsin brain chemical composition, despite normal-appearing structure, throughquantifying the resonance frequency of certain 1H-containing chemicalcompounds that include the combined resonances of creatine and phosphocreatine(Cre); choline-containing compounds (Cho); N-acetylmoieties predominately composed of N-acetyl aspartate(NAA); myo-inositol (mI), which also contains somecontribution from scyllo-inositol at 1.5 T; the overlapping resonances ofglutamine, glutamate, and γ-aminobutyric acid (Glx); and lactate. Thedevelopment of rapid MR spectroscopy techniques, such as proton echo-planarspectroscopic imaging (PEPSI), allows fast, clinically feasible acquisitionof 2-dimensional images of brain chemical composition.33 Short-echotime (TE) measurements (eg, 20 milliseconds) can be acquired using PEPSI thatprovide a more accurate appraisal of brain chemical concentration, particularlyas some disease states, such as autism, can alter tissue relaxation characteristicsand substantially affect spectral quantification at longer TEs.34

The purpose of this study was to characterize brain chemical compositionin medication-free BD patients compared with age- and sex-matched healthycontrols (HCs). To ensure adequate numbers of medication-free participants,a dual-site study was conducted between Boston, Mass, and Seattle, Wash. Medication-freeBD patients were studied, because prior work3541 suggestssecondary effects of mood stabilizers or antidepressants on MR spectroscopy–detectablechemicals and gray matter volume that could confound interpretation of findings.We evaluated diagnostic relationships for chemicals detectable by 1H-MRspectroscopy, including Cho, Cre, mI, Glx, and NAA, to extend prior work thatfound metabolic alterations in mood disorders. The present investigation furthersought to exploit the within-subject multiple voxel sampling acquired withPEPSI to evaluate whether lactate, a potential indicator of redox status butwith a low signal-to-noise ratio in the resting state, was altered in BD.To assess tissue-type specificity for chemical findings, gray and white mattercompartments were evaluated separately using established regression methods.4244 We report tissue-specificand regional brain chemical findings in BD patients vs HCs, relationshipsto mood state, and clinical subtypes of BDI and BDII.

PARTICIPANTS

Participants were 32 adults with BD (14 men, 18 women; mean ±SD age, 30.3 ± 10.8 years) and 26 HCs (12 men, 14 women; mean ±SD age, 31.9 ± 7.7 years). Participants were recruited through theBipolar Research Programs at McLean Hospital and the Massachusetts GeneralHospital (BD patients = 15; HCs = 16) or the University of Washington Centerfor Anxiety and Depression (BD patients = 17; HCs = 10). Written, informedconsent, approved by either McLean Hospital and Massachusetts General Hospital,Harvard University, or the University of Washington Human Subjects ReviewBoards, was obtained from each participant before study enrollment. All participantstolerated the scanning procedure, but 3 BD patients (1 man, 2 women) and 2HCs (2 men) had invalid studies due to technical acquisition problems or movementartifacts and were not included in the statistical analyses. Additionally,only long-echo MR spectroscopy data (lactate) were acquired for 1 BD patient.There were no significant differences in sex distribution (χ21 = 0.11, P = .75) or age (t51 = 0.73, P = .47) between diagnosticgroups.

Psychiatric diagnosis was established through a DSM-IV–based structured psychiatric interview by skilled clinicians (D.L.D.,C.D., A.L.S.). These clinicians also established diagnostic agreement betweensites before study inception and consensus for individual subject inclusionthroughout the study. The BD patients did not meet other DSM-IV Axis I diagnoses, including lifetime alcohol and/or other drugdependency or abuse within 6 months of study entrance. All participants weremedication free for 8 weeks or longer before the study. Participants wereoutpatients seeking treatment and had not stopped treatment to participatein the study. Of the 29 BD patients with valid studies, 26 had never beentreated with mood-stabilizing medications, and the 3 previously treated BDpatients (2 taking lithium and 1 taking valproic acid) had not been takingmood stabilizers for at least 1 year. Twelve BD patients, including the 3previously taking mood stabilizers, had been prescribed antidepressants inthe past but had not been taking them for at least 8 weeks or longer beforethe study. No patients had previously been treated with antipsychotic medication.The results of urine toxicology screening obtained before the study were negativefor psychoactive substances. Evidence of clinically significant medical problemsthrough medical history, laboratory workup, including thyroid studies, andphysical examination that evaluated for cerebral vascular disease, pulmonarydisease, endocrine disorders, severe sensory or motor impairments (deaf orblind), documented head trauma, or metal implants was exclusionary for participation.Healthy controls had no current symptoms or medical history consistent witha DSM-IV Axis I diagnosis, and there was no historyof clinically significant psychiatric disorders in their first-degree relatives.

Subtype classification of BD patients into BDI (n = 11; 5 men, 6 women;mean ± SD age, 31.9 ± 6.1 years) or BDII (n = 17; 7 men, 10women; mean ± SD age, 28.9 ± 10.5 years) was determined at studyentrance by structured psychiatric interview. One participant was not classifiedand excluded from further analysis. Mood state before MR imaging or MR spectroscopywas assessed using the 17-item Hamilton Depression Rating Scale (HAM-D)45 and the Young Mania Rating Scale (YMRS).46 The mean ± SD HAM-D score for the BD patientswas 17.7 ± 8.6 (BDI, 20.0 ± 8.2; BDII, 16.1 ± 9.0) comparedwith 1.2 ± 1.1 for the HCs. The mean ± SD YMRS score for theBD patients was 6.5 ± 7.7 (BDI, 9.7 ± 9.1; BDII, 4.6 ±6.4) compared with 0.3 ± 0.5 for HCs. The BD patients had an averageillness duration of 13.5 ± 10.2 years (range, 0.5-33.0 years), with13.6 ± 18.1 depressive episodes and 7.3 ± 7.6 hypomanic manicepisodes.

MR IMAGING AND MR SPECTROSCOPY ACQUISITION

The PEPSI studies were performed using clinical 1.5-T SIGNA whole-bodyscanners (GE Medical Systems, Milwaukee, Wis), both equipped with version5.8 Genesis operating software. Experimental receive-only linear birdcagecoils, designed and built at the University of Washington, that provided approximately√√2 enhanced signal-to-noise ratio and improved coil homogeneityover conventional quadrature head coils (Cecil Hayes, PhD, unpublished data,1996) were used at both sites. The coil design incorporates a built-in headholder to minimize head motion during scanning.

Axial proton density and T2-weighted MR images were used for anatomiclocalization and tissue segmentation (TE, 13/91 milliseconds; repetition time[TR], 2000 milliseconds; field of view (FOV), 22 cm; matrix, 256 × 160;slice thickness, 3 mm). For PEPSI studies, anatomic volumes were acquiredfrom an axial section centered on the anterior cingulate (Figure 1). The PEPSI pulse sequence has been described in detailelsewhere.33,47 Two TEs and standardparameters were used for data acquisition (TE, 20/272 milliseconds; TR, 2000milliseconds; spatial matrix, 32 × 32; nominal voxel size, 1 cm3; FOV, 22 cm; slice thickness, 20 mm). Magnetic resonance spectroscopydata were acquired in scan blocks (20-millisecond chemical image: 4 numbersof excitation/[NEX]; 4-minute scan time; 272-millisecond chemical image: 8NEX; 8-minute scan time; 20-millisecond water image: 2 NEX; 2-minute scantime), totaling approximately 20 minutes, including shimming and scan setup.A full echo was collected for 20-millisecond chemical data and a partial echofor 272-millisecond chemical data, the latter necessitating a magnitude calculation(√[real2 + imaginary2]) for data reconstruction.47 Unsuppressed short-echo water scans were also collectedfrom the identical axial slice location (TE, 20 milliseconds; TR, 2000 milliseconds)for referencing both metabolite scans as previously described.34

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Figure 1.

Central sagittal prescriptionimage (B) with the proton echo-planar spectroscopic imaging (PEPSI) axialslab (20-mm thickness) overlaid in blue. The central PEPSI slab axial T2-weightedimage (A) shows valid spectral voxels outlined in white; anatomic voxel locationsfor right anterior cingulate (a), right caudate nucleus (b), and left parietalwhite matter (c) are also identified. Short-echo (20-millisecond [ms]) (C-E)and long-echo (272-ms) (F-H) spectra corresponding to these voxel locationsare shown; raw data are visible as the black fine line in the lower panelof each spectrum and the LCModel spectral fit is in red (baseline corrected),with the fit residual shown in the top panels. Metabolites measured at 20ms: myo-inositol (mI); choline-containing compounds(Cho); creatine and phosphocreatine (Cre); glutamate, glutamine, and γ-aminobutyricacid (Glx); and N-acetyl aspartate (NAA). Metabolitesmeasured at 272 ms: lactate.

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MR SPECTROSCOPY ANALYSES

The PEPSI chemical images were analyzed using software developed atthe University of Washington that used the LCModel package for spectral fitting48 (Figure 1).Consistent with our prior work to optimize LCModel parameters34 andto standardize measurements between sites, phantoms with known concentrationsof brain chemicals were prepared at McLean Hospital and scanned at variousacquisition parameters, and basis sets were created as detailed in the LCModelmanual. All data sets were analyzed unbiased by user interaction on workstations(SGI Octane; Silicon Graphics Inc, Mountain View, Calif) running IRIX system6.5.8.

To calculate chemical concentrations and relaxation estimates, LCModelwater amplitudes were adjusted by water molarity estimates and attenuationconstants were then multiplied by the partial volume tissue fraction. Chemicalamplitude maps were adjusted for the differential relaxation between in vitro(phantoms) and in vivo estimates for Cre, Cho, and NAA, which served to scalechemical output similar to our previous work.34 Metaboliteswere then multiplied by the inverted partial-volume–corrected waterterm to yield chemical concentration.49

Absolute T2 calculations from the short- and long-echo PEPSI data couldnot be accurately determined, because long-echo data were acquired as a partialecho, requiring a magnitude calculation for reconstruction. Thus, a relativemeasure of T2 relaxation (T2r) for each region was calculated from chemicalsmeasured at both short and long TEs (Cre, Cho, and NAA), as previously described.34

Because short-echo data afford the least biased estimation of chemicalconcentration, long-echo data were used only for lactate measurements andT2 relaxation time calculations.28,34,47 Chemicalmeasures from each spectral array were determined from all valid voxels foreach individual participant to achieve maximum signal-to-noise ratios. Thenumber of valid voxels from the 32 × 32 spectra array acquired per subjectwas not significantly different comparing BD and HC groups for all chemicalmeasurements (t<0.86 and P>.38for all).

TISSUE SEGMENTATION

Dual-echo axial images were skull stripped and then segmented usingmultispectral analytic tools within an image manipulation and visualizationpackage (Analyze; Mayo Clinic, Rochester, Minn). Specifically, sample regionsof gray matter, white matter, and cerebrospinal fluid (CSF) (eg, intraventricularCSF) were manually selected by a single rater (I.K.L.) blinded to patientdiagnosis. These pure exemplars, unbiased by partial volume, were used asstarting points for gaussian classification. Following segmentation, a secondscript written in MATLAB, a computer language used for array computation andvisualization, was used to offset the images to magnet center using MR imageheader coordinates and extract images within the PEPSI volume. Because PEPSIdata sets are acquired at magnet center, aligning anatomic images in thisway results in accurate registration.

The CSF and tissue maps were processed as previously detailed,34,50 including summation of images withinthe PEPSI volume, spatial filtering, and array reduction to match the chemicalarray spatial resolution (32 × 32). On a voxel-by-voxel basis, CSF datawere used for partial volume correction of metabolite quantification. Partialvolume tissue estimates of the PEPSI slab were similar between groups (BDpatients, 0.95 ± 0.02; HCs, 0.96 ± 0.01; t50 = 0.62; P = .54). For regressionanalyses, white and gray matter maps were used. The percentage of gray mattercomprising the axial slab studied using PEPSI was also similar between groups(BD patients, 52.96% ± 4.71%; HCs, 51.78% ± 4.98%; t50 = .88; P = .38). For each participant,using all valid spectroscopy voxels, regression analyses were performed comparingthe fractional tissue volume (percentage of gray or white matter per voxel)to concentration and relaxation values. This approach, similar to that usedby other investigators,4244 takesadvantage of the large number of voxel samples obtained using spectroscopicimaging to calculate estimates of pure tissue neurochemistry (regression intercepts)and the relationship between tissue classes (regression slope). Characteristicchemical regression plots from an individual BD patient are shown in Figure 2.

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Figure 2.

For an individual patient withbipolar disorder, metabolite concentration arrays are plotted relative tothe percentage of white matter in each voxel. Regression lines, shown in redfor each metabolite, illustrate chemical distribution by tissue type. Choindicates choline-containing compounds; Cre, creatine and phosphocreatine;NAA, N-acetyl aspartate; Ins, inositol; and Glx,glutamate, glutamine, and γ-aminobutyric acid (Glx).

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REGION-OF-INTEREST ANALYSES

For region-of-interest (ROI) selection, the PEPSI voxel grid (32 ×32 matrix) was graphically overlaid onto the axial MR image data set for selectinganatomic loci: frontal white matter left and right, cingulate left and right,caudate left and right, putamen left and right, thalamus left and right, insulaleft and right, parietal white matter left and right, and midline occiput(Figure 3). A rater (S.D.F.) blindedto patient diagnosis recorded the voxel position for each ROI into a texttemplate, and a MATLAB script was used to extract concentration data by regioninto a tabulated text file. For nuclei, the voxel chosen was centered on theanatomic target structure; if no corresponding voxel could be selected, amissing value was entered. In other larger anatomic regions, ROIs were averagedacross contiguous voxels to maximize signal-to-noise ratio.

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Figure 3.

The central axial prescriptionimage shows anatomic locations for regions-of-interest (ROI) selection. aand b indicate frontal white matter right and left; c and d, cingulate rightand left; e and f, caudate right and left; g and h, putamen right and left;i and j, insula right and left; k and l, thalamus right and left; m and n,parietal white matter right and left; and o, occiput.

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STATISTICAL ANALYSIS

Stepwise multivariate linear regression using SPSS statistical softwareversion 11 (SPSS Inc, Chicago, Ill) assessed interrelationships between categoricalvariables of psychiatric diagnosis and clinical subtype diagnosis with continuouspredictor variables of chemical concentrations (20 milliseconds for Cho, Cre,NAA, mI, and Glx; 272 milliseconds for lactate). Chemical T2r (Cho, Cre, andNAA) was separately modeled. Regional chemical composition by diagnosis wasevaluated using independent t tests. For BD patients,mood state rating scales in relationship to chemical measures were evaluatedusing the Pearson r. Significance was fixed at a2-tailed α of .05. Bonferroni correction for ROI analyses was appliedby dividing the α level by number of regions assessed (adjusted α= .003) and for mood assessment by number of gray-white chemical measures(adjusted α = .004). Values are presented as mean ± SD. Regionaland diagnostic subgroup analyses by mood were not performed because of powerconsiderations.

Brain chemical concentrations by tissue type are given for each diagnosticgroup in Table 1. A significantmodel observed for gray matter chemical measures and diagnosis (BD patientsvs HCs) (F2,51 = 8.34, P = .001) was bestpredicted by elevated lactate (19.75% increase, β = .37, t = 2.96, P = .005) and Glx levels (10.01%increase, β = .35, t = 2.83, P = .007) in BD patients; other gray matter chemicals were nonsignificantwithin the model (β<.28, t≤1.07, P ≥.32 for all). The model for white matter chemicalsand diagnosis did not reach statistical significance (F1,51 = 3.61, P = .06). The models for diagnosis and gray matter T2r(F1,51 = 1.06, P = .31) or white matterT2r (F1,51 = 3.59, P = .07) also did notreach statistical significance. Similarly, the models for diagnosis and chemicalregression slopes (F1,51 = 3.12, P = .08)(Table 1) or T2r regression slopes(F1,51 = 0.30, P = .59) did not reachstatistical significance.

Table Graphic Jump LocationTable 1. Brain Chemical Concentrations by Tissue Type*

Brain chemical ROI relationships were assessed (Figure 3). Chemical alterations included increased Glx levels inthe left cingulate (t39 = 2.09, P = .04) and increased Cho levels in the left caudate (t37 = 2.71, P = .01)in BD patients. The BD group also exhibited increased Cho levels in the rightputamen (t50 = 2.43, P = .02), increased NAA levels in the left putamen (t52 = 3.57, P = .001), and increasedGlx levels in the left insula (t51 = 3.32, P = .002). After Bonferroni correction for the multipleregions compared (adjusted α = .003), only putamen and insula findingsremained statistically significant.

The BD patients differentiated into BDI and BDII clinical subtypes werefurther evaluated for gray and white matter chemical differences (Table 2). Comparing BDI patients and HCs,a significant model for gray matter chemicals (F1,33 = 12.24, P = .001) was predicted by elevated lactate levels in theBDI subgroup (31.45% increase, β = .53, t =3.50, P = .001); other gray matter chemicals didnot significantly contribute to the model (β<.19, t≤1.25, P≥.22 for all). No significantmodel for white matter chemicals and BDI vs HC diagnosis was found (F1,33 = 0.59, P = .74). There were also no statisticallysignificant models for gray or white matter T2r and diagnosis (F<1.23, P>.27 for all). Modeling chemical regression slopes, asignificant model (F1,33 = 6.39, P = .02)was predicted by an increased lactate white-gray regression slope in BDI patients(0.06 ± 0.50 vs −0.35 ± 0.51, β = .41, t = 2.53, P = .02).

Table Graphic Jump LocationTable 2. Gray and White Matter Chemical Differences*

Comparing BDII patients and HCs, a statistically significant model forgray matter chemicals (F2,40 = 7.13, P =.002) was predicted by elevated Glx levels (13.97% increase, β = .47, t = 3.29, P = .002) and trendelevated lactate levels (11.3% increase, β = .24, t = 1.70, P = .10) in the BDII subgroup; othergray matter chemicals did not contribute to the model (β<.11, t≤0.69, P>.49 for all). A significantmodel for BDII compared with HCs for white matter chemicals (F1,40 =5.47, P = .03) was predicted by elevated Glx levelsin the BDII subgroup (11.6% increase, β = .35, t =2.34, P = .03); other white matter chemicals didnot contribute to the model (β<.23, t<1.39, P>.17 for all). Additionally, significant models observedfor gray matter T2r (F1,40 = 5.27, P =.03) were predicted by shortened Cho T2r (decreased 15.1% from HCs, β= .35, t = 2.30, P = .03)and white matter T2r (F1,40 = 4.13, P =.05) predicted by shortened Cho T2r (decreased 9.9% from HCs, β= .31, t = 2.03, P = .05)in BDII patients. The model for white-gray regression slope and BDII vs HCdiagnosis did not reach statistical significance (F1,40 = 3.21, P = .08).

Clinical mood state of BD patients at time of scanning was evaluatedin relationship to averaged gray-white matter chemical measures using thePearson r. An inverse correlation with HAM-D scoreswas found for white matter Cre (r28 =−0.55, P = .003); no significant interactionswere observed between HAM-D scores and other gray or white matter chemicals(r<.33, P>.09). The YMRSscores were inversely correlated with mI levels both in gray matter (r28 = −0.46, P =.01) and white matter (r28 = −0.42, P = .03); no significant relationships were observed forother gray or white matter chemicals (r<.36, P≥.06). After Bonferroni correction for the number ofgray and white matter chemical measures (adjusted α = .004), a significantinteraction between white matter Cre and HAM-D scores remained (Figure 4).

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Figure 4.

The relationship between whitematter concentrations of creatine and phosphocreatine (Cre) and the HamiltonDepression Rating Scale (HAM-D) scores is shown, demonstrating an inverserelationship.

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Medication-free BD patients demonstrated elevated lactate and Glx levelsin gray matter compared with the HC group; other gray-white matter chemicalconcentrations, chemical T2r measures, and chemical regression slopes betweenwhite and gray matter were not significantly different between groups. TheBDI patients demonstrated elevated gray matter lactate and altered lactatetissue distribution that was shifted toward gray matter compared with HCs;the BDII patients exhibited elevated Glx and trend elevated lactate levelsin gray matter, as well as elevated white matter Glx levels. The BDII patientsadditionally demonstrated shortening of Cho T2r in both gray and white matter.Chemical differences for BDI and BDII patients may reflect intrinsic diagnosticdifferences or illness severity, because BDI patients had higher HAM-D andYMRS scores. A significant inverse correlation also was found for white matterCre and HAM-D scores in BD patients. We believe that this is the first reportof elevated gray matter lactate levels in BD. Several recent single-voxel 1H-MR spectroscopy studies of BD also have reported elevated Glx levels.51,52 Lactate levels in those studies werenot reported because of characteristics of the acquisition parameters andsignal-to-noise ratio considerations.

Although our line-fitting analyses fit the separate components of Glx,we did not report individual values because of the substantial overlap ofthese multiplets at 1.5 T. Thus, we cannot identify what component of Glxwas elevated in BD patients. However, findings of decreased Glx measured inthe anterior cingulate cortex of medicated major depressive disorder patientshave been suggested to primarily reflect lowered glutamate levels.53 Future investigation using higher-field scannersmay improve deconvolution of the Glx spectral peaks and better address limitationsof spectral resolution at 1.5 T.

Other brain chemicals and T2r measures in both gray and white matterwere not significantly different between diagnostic groups. White-gray regressionslopes for chemical distributions between tissues are compatible with priorwork4244 anddid not differentiate diagnostic groups, although BDI patients demonstratedan increased slope for lactate distribution between white and gray matter.Regional findings, although somewhat overlapping with the anatomic distributionfound in previous work,38,5356 shouldbe interpreted conservatively. Further studies would be necessary to confirmregional Glx and NAA elevations observed in this BD sample.

Investigations of mood disorders using single-voxel 1H-MRspectroscopy have largely tested hypotheses of Cho alterations wherein bothregional elevations39,56,57 anddecreased Cho levels38,40,58 havebeen reported in association with depressed mood state. In our study, tissue-specificCho levels were not found to be altered in relationship to either BD diagnosisor mood state. We also did not find evidence of tissue-specific or regionalNAA reductions that have been reported in association with BD and perhapsmore specifically with psychosis.52,5961 Variablefindings reported in the literature may reflect differences in clinical populations,medication status, brain regions studied, or MR spectroscopy acquisition parametersthat, in the setting of disease state–related T2 changes, as found forCho in this study, could substantially influence chemical concentration estimates.

In this study, mood-related findings of an inverse correlation for whitematter Cre with HAM-D scores are comparable with prior work that found decreasedphosphocreatine/Cre levels in association with depression.62,63 Inthis sample, the predominantly depressed or mixed-mood state of the BD patientslimits any relationship being identified between manic symptoms and chemicalalterations. A growing MR spectroscopy literature supports the presence ofbrain metabolic alterations in BD with variable relationships to mood state.Initial MR spectroscopy studies of BD used phosphorus P31 (31P)–labeledMR spectroscopy to evaluate brain energy and phospholipid metabolism.37 A meta-analysis of 8 31P-MR spectroscopystudies provides support for state-specific alterations of phospholipid membranesand high-energy phosphates in BD that primarily reflect increased phosphomonoesterlevels and decreased phosphocreatinine levels in the depressed state.54 Decreased phosphomonoester levels also have beenobserved in euthymic BDI patients, although not BDII patients, compared withHCs.62 More generally, findings of decreased βand total nucleotide triphosphate (primarily composed of adenosine triphosphate)provide evidence for abnormal brain energy metabolism in mood disorders.55,64 Because brain intracellular pH determinedby 31P-MR spectroscopy is found to be decreased in medication-freeBD patients in both manic and depressed mood states, as well as in euthymicBD patients stabilized with lithium treatment, metabolic aberrations may beintrinsic to the underlying pathophysiology of BD.65,66 Findingsof decreased frontal lobe intracellular pH in BD patients,65 consistentwith lactate acidosis, are postulated by those investigators to reflect underlyingmitochondrial dysfunction.66

It is possible that lactate elevations observed in this study couldreflect nonspecific manifestations of state-dependent anxiety, although participantsin our study did not report anxiety or any particular discomfort with beingin the scanner. Despite substantial baseline anxiety, we also do not typicallyobserve elevated baseline lactate levels in patients with panic disorder aboutto undergo a lactate infusion designed to induce panic.47,50,67,68 However,the diagnostic specificity of lactate and Glx findings remains uncertain.In a study using essentially the same methods, we observed no alterationsin either lactate or Glx in young children with autism.34 Onthe other hand, elevated lactate levels have also recently been found in associationwith first-break psychosis.69

Our findings of elevated gray matter lactate levels in the BD patientssuggest a shift in redox state from oxidative toward glycolytic energy utilization.Although its role in brain metabolism and homeostasis remains unresolved,70,71 earlier considerations of lactatebeing solely the by-product of anaerobic metabolism have been substantiallymodified by more recent work suggesting an important role for lactate in brainbioenergetics.7274 Normalneuronal activation requires that some fraction of the energy expended comesfrom glycolysis. During rapid neuronal firing, coupled to increased extracellularglutamate levels, approximately one third of energy expenditure is estimatedto be contributed via glycolysis and increased lactate production.75 It is conceivable that increased or more sustainedrapid neuronal firing, possibly reflecting neuroexcitatory effects of increasedextracellular glutamate, with a resultant increased fraction of energy utilizationvia glycolysis, could explain the elevated gray matter lactate levels observedin BD patients. Because hypoperfusion is among the more consistent brain metabolicalterations found in BD,14,15,17 thisfactor could also contribute to, or account for, a shift in redox state towardglycolysis. Alternatively, or in conjunction with these considerations, recentin vivo evidence supports an association between elevated brain lactate andGlx levels and cyanide-induced inhibition of mitochondrial oxidative metabolism;mechanisms underlying brain glutamate increases are postulated to reflectalterations in the release and reuptake of glutamate that are dependent onintact oxidative metabolism.76

Elevated brain lactate is considered to be a sensitive marker for mitochondrialcompromise,77 but severe clinical manifestations(eg, MELAS [mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke]syndrome) also are variably associated with reduced NAA levels.78 Althoughwe did not find evidence for reduced NAA in BD patients, this might reflectthe lesser severity of mitochondrial compromise speculated to account forlactate and Glx level elevations observed in our sample. The spectrum of clinicaland metabolic manifestations of mitochondrial dysfunction may reflect variableloading of mitochondrial DNA polymorphisms, some possibly linked to BD,79 that exhibit differing threshold response to oxidativestress.80 Phospholipid membrane alterationsfound in association with BD may also interfere with mitochondrial function,just as mitochondrial dysfunction can alter phospholipid metabolism.8184

Considerations regarding the possible role of mitochondrial compromisein BD have important treatment implications; for example, evidence of thepossible neuroprotective properties of lithium,35,36,41 alsoobserved under conditions of elevated glutamate levels or ischemia, are hypothesized,in part, to be mediated through bcl-2 elevation, a neuroprotective proteinthat also has mitochondrial membrane-stabilizing effects.85 Althoughthe demonstration of causal relationships remains challenging, the presentwork suggests subtle alterations of energy metabolism in BD.

To summarize, gray matter lactate and Glx level elevations in medication-freeBD patients suggest altered cellular energy metabolism. These chemical alterations,suggestive of a redox shift toward glycolysis, may reflect a generalized patternof compromised mitochondrial metabolism in BD.

Corresponding author and reprints: Stephen R. Dager, MD, Universityof Washington Neuroimaging Research Group and the Center for Anxiety and Depression,1100 NE 45th Street, Suite 555, Seattle, WA 98105 (e-mail: srd@u.washington.edu).

Submitted for publication March 10, 2003; final revision received December18, 2003; accepted January 18, 2004.

This study was supported in part by grant RO1 MH58681 from the NationalInstitute of Mental Health, Bethesda, Md, and the Poitras Foundation and theStanley Foundation Bipolar Disorders Research Center at McLean Hospital, Boston,Mass.

We thank Marie Domsalla, Chris Budech, and Carolyn Bea for assistancein recruiting participants and organizational assistance. We also thank DeniseEchelard, Gerald Ortiz, and James Anderson for MR technical support.

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PubMed
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Link to Article
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PubMed Link to Article
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PubMed
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PubMed Link to Article
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PubMed
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PubMed Link to Article
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PubMed Link to Article
Baxter  LRSchwartz  JMPhelps  MEMazziotta  JCGuze  BHSelin  CEGerner  RHSumida  RM Reduction of prefrontal cortex glucose metabolism common to three typesof depression. Arch Gen Psychiatry. 1989;46243- 250
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Figures

Place holder to copy figure label and caption
Figure 1.

Central sagittal prescriptionimage (B) with the proton echo-planar spectroscopic imaging (PEPSI) axialslab (20-mm thickness) overlaid in blue. The central PEPSI slab axial T2-weightedimage (A) shows valid spectral voxels outlined in white; anatomic voxel locationsfor right anterior cingulate (a), right caudate nucleus (b), and left parietalwhite matter (c) are also identified. Short-echo (20-millisecond [ms]) (C-E)and long-echo (272-ms) (F-H) spectra corresponding to these voxel locationsare shown; raw data are visible as the black fine line in the lower panelof each spectrum and the LCModel spectral fit is in red (baseline corrected),with the fit residual shown in the top panels. Metabolites measured at 20ms: myo-inositol (mI); choline-containing compounds(Cho); creatine and phosphocreatine (Cre); glutamate, glutamine, and γ-aminobutyricacid (Glx); and N-acetyl aspartate (NAA). Metabolitesmeasured at 272 ms: lactate.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

For an individual patient withbipolar disorder, metabolite concentration arrays are plotted relative tothe percentage of white matter in each voxel. Regression lines, shown in redfor each metabolite, illustrate chemical distribution by tissue type. Choindicates choline-containing compounds; Cre, creatine and phosphocreatine;NAA, N-acetyl aspartate; Ins, inositol; and Glx,glutamate, glutamine, and γ-aminobutyric acid (Glx).

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

The central axial prescriptionimage shows anatomic locations for regions-of-interest (ROI) selection. aand b indicate frontal white matter right and left; c and d, cingulate rightand left; e and f, caudate right and left; g and h, putamen right and left;i and j, insula right and left; k and l, thalamus right and left; m and n,parietal white matter right and left; and o, occiput.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 4.

The relationship between whitematter concentrations of creatine and phosphocreatine (Cre) and the HamiltonDepression Rating Scale (HAM-D) scores is shown, demonstrating an inverserelationship.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Brain Chemical Concentrations by Tissue Type*
Table Graphic Jump LocationTable 2. Gray and White Matter Chemical Differences*

References

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