Regional brain gray matter volume differences in patients with bipolar disorder as assessed by optimized voxel-based morphometry

Regional Brain Gray Matter Volume Differences in Patients with Bipolar Disorder as Assessed by Optimized Voxel-Based Morphometry Richard A. Lochhead, Ramin V. Parsey, Maria A. Oquendo, and J. John Mann Background: Structural magnetic resonance imaging (MRI) studies of regions of interest in brain have been inconsistent in demonstrating volumetric differences in subjects with bipolar disorder (BD). Voxel-based morphometry (VBM) provides an unbiased survey of the brain, can identify novel brain areas, and validates previously hypothesized regions. We conducted both optimized VBM, comparing MRI gray matter volume, and traditional VBM, comparing MRI gray matter density, in 11 BD subjects and 31 healthy volunteers. To our knowledge, these are the first VBM analyses of BD. Methods: Segmented MRI gray matter images were normalized into standardized stereotactic space, modulated to allow volumetric analysis (optimized only), smoothed, and compared at the voxel level with statistical parametric mapping. Results: Optimized VBM showed that BD subjects had smaller volume in left ventromedial temporal cortex and bilateral cingulate cortex and larger volume in left insular/frontoparietal operculum cortex and left ventral occipitotemporal cortex. Traditional VBM showed that BD subjects had less gray matter density in left ventromedial temporal cortex and greater gray matter density in left insular/frontoparietal operculum cortex and bilateral thalamic cortex. Exploratory analyses suggest that these abnormalities might differ according to gender. Conclusions: Bipolar disorder is associated with volumetric and gray matter density changes that involve brain regions hypothesized to influence mood. Key Words: Magnetic resonance imaging, sex, volume, brain anatomy, circuitry

A

neuroanatomical model for bipolar disorder (BD) has not been as well studied as for major depressive disorder. Abnormalities are reported in a prefrontal cortex (PFC)– limbic–striatopallidal–thalamic circuit (Drevets and Raichle 1992; Mayberg 1997; Soares and Mann 1997) and other similar PFC– subcortical brain circuits (Bearden et al 2001; Beyer and Krishnan 2002; Strakowski et al 2000). It is hypothesized that abnormal ventromedial caudate function is related to bipolar disorder (mood cycling) psychopathology, and abnormal PFC function is associated with manic or depressive symptoms, depending on the location of the abnormality (see Strakowski et al 2000). Even less is known about the etiology of these abnormalities. One hypothesis for the etiology of major depressive disorder might also apply to BD: this hypothesis associates stress, including effects of childhood sexual or physical abuse on adult stress responses, with elevated cortisol and possible secondary hippocampal damage (Lee et al 2002; Sapolsky 2000). Previous structural magnetic resonance imaging (MRI) studies of BD are difficult to interpret because of disagreement as to which regions show differences in volume and the direction of change in regional volume. Generally, smaller volumes are reported in the subgenual PFC (Drevets et al 1997; Hirayasu et al 1999); larger volumes in the amygdala (Altshuler et al 1998, 2000; Strakowski et al 1999), caudate nucleus (Aylward et al 1994; Strakowski et al 1999), and thalamus (Dupont et al 1995; From the Department of Neuroscience (RAL), New York State Psychiatric Institute; and the Departments of Psychiatry (RVP, MAO, JM) and Radiology (JM), Columbia University College of Physicians and Surgeons, New York, New York. Address reprint requests to Ramin V. Parsey, M.D., Ph.D., New York State Psychiatric Institute, Department of Neuroscience, Division of Brain Imaging, 1051 Riverside Drive, Box #42, New York, NY 10032. Received October 28, 2003; revised February 18, 2004; accepted February 20, 2004.

0006-3223/04/$30.00 doi:10.1016/j.biopsych.2004.02.026

Strakowski et al 1999); and no volumetric change in hippocampal (Altshuler et al 1998, 2000; Hauser et al 2000; Pearlson et al 1997; Sax et al 1999) and parahippocampal cortex (Altshuler et al 2000; Pearlson et al 1997). For a summary of previous studies, see Table 1. Conflicting results might be attributed to differences in either the population studied or the methodology used. Differences in study populations potentially affecting results include the gender mix (Aylward et al 1994; Frodl et al 2002b; Parsey et al 2002; Swayze et al 1992), treatment status (Gur et al 1998; Madsen et al 1998; Moore et al 2000), or subtype of mood disorder (Strakowski et al 2002). Differences in methodologies can include differences in MRI acquisition protocols, definition of region of interest (ROI), or the selection of ROIs. The anatomical criteria for generating the ROI might vary between studies, and the validity of the ROI is often not documented. ROI validation requires demonstration that the region of change or lack of change is localized within the ROI and does not involve adjacent or contiguous brain areas. An approach that avoids the problems of unvalidated ROIs or selection of the wrong ROI is an unbiased survey of the brain at the voxel level. Software programs, such as Statistical Parametric Mapping 99 (SPM99, Wellcome Department of Cognitive Neurology, University College London, United Kingdom), can be used to survey the entire brain for volumetric differences and create a map of structural differences at the voxel level with optimized voxel-based morphometry (VBM). Additionally, except for the blinded creation of a gray matter mask (see Methods and Materials) and determination of the anterior commissure, this method requires no manual identification of brain anatomy. Traditional VBM has been used to identify abnormal gray matter densities in schizophrenia (Hulshoff Pol et al 2001; Job et al 2002; Paillere-Martinot et al 2001; Suzuki et al 2002; Wilke et al 2001; Wright et al 1995) and in a subset of subjects with a major depressive episode (Shah et al 1998, 2002). Optimized VBM differs from traditional VBM in that it requires a modulation step in image processing (Good et al 2001a) and allows comparison of gray matter volumes. Optimized VBM has been used to assess BIOL PSYCHIATRY 2004;55:1154 –1162 © 2004 Society of Biological Psychiatry

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gray matter volumes in schizophrenic subjects (Ananth et al 2002) and female subjects with borderline personality disorder (Rusch et al 2003). To our knowledge, optimized VBM has not been used to examine gray matter in BD subjects. Using SPM99, we performed traditional and optimized VBM analyses to compare regional gray matter densities and volume in 11 BD subjects and 31 healthy volunteers. This unique and unbiased approach was used to identify the pathologic circuitry of BD.

and healthy volunteers (36 ⫾ 14.0 years) did not differ significantly (two sided t test: p ⫽ .65). The average age of first onset of illness was 24.3 ⫾ 9.2 years for BD subjects. The average number of previous major depressive episodes in BD subjects was 9.0 ⫾ 6.4 (four subjects had too many to accurately count). Six of the BD subjects had previously attempted suicide. Additional Axis I diagnoses included two BD subjects with binge eating disorder, three with narcissistic personality disorder, and two with borderline personality disorder.

Methods and Materials

MRI Acquisition Each MRI was acquired on a GE 1.5-T Signa Advantage system (General Electric Medical Systems, Milwaukee, Wisconsin). A sagittal scout (localizer) was performed to identify the anterior commissure–posterior commissure (AC-PC) plane. A transaxial T1-weighted sequence with 1.5-mm slice thickness was acquired in the coronal plane orthogonal to the AC-PC plane over the brain with the following parameters: three-dimensional spoiled gradient recalled acquisition in the steady state; repetition time 34 msec; echo time 5 msec; flip angle 45°; 124 slices; field of view 22 cm ⫻ 16 cm; with 256 ⫻ 192 matrix, reformatted to 256 ⫻ 256, yielding a voxel size of 1.5 mm ⫻ .9 mm ⫻ .9 mm.

Subjects Subjects were referred from an outside clinic or responded to an advertisement. They were assessed by clinical history, chart review, Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I) (First et al 1995), review of systems, physical examination, routine blood tests, pregnancy test, and urine toxicology. Study entrance criteria for BD subjects included 1) age 18 – 65 years; 2) DSM-IV criteria for BD; 3) absence of lifetime history of alcohol or substance abuse or dependence; 4) absence of significant medical conditions (including any head trauma resulting in loss of consciousness for more than 1 min (Bigler et al 2002); 5) absence of pregnancy; and 6) capacity to provide informed consent. Eleven right-handed (Watkins et al 2001) subjects met DSM-IV criteria for BD (6 men, 5 women). All subjects had not been taking medication for a minimum of 14 days, except for one female BD subject (depakote [250 mg/day] and paroxetine [20 mg/day]). When analyses were performed excluding this subject, results were unchanged, therefore her data were included (Glitz et al 2002). Three patients had no previous history of medication treatment, three patients had a lifetime treatment of one medication (two with sertraline, one with nefazodone), and five patients had a lifetime history of two or more medication treatments (four with carbamazepine, one with divalproex sodium, one with gabapentin, one with lamotrigine, two with methylphenidate, one with nefazodone, one with olanzapine, one with oxcarbazepine, one with paroxetine, two with phenelzine, one with thiothixene, one with topiramate, one with tranylcypromine, one with venlafaxine, and one with zolpidem). Thirty-one right-handed, healthy volunteers (16 men, 15 women) met the study criteria, which included 1) age 18 – 65 years; 2) absence of medical or neurologic illness and psychiatric history (including alcohol and substance use disorder), based on a complete structured psychiatric interview with the SCID-NP (nonpatient version) and the SCID-II (for Axis II disorders), medical examination, and laboratory tests; 3) absence of any psychotropic medications for at least 2 weeks; 4) absence of exposure to 3,4-methylenedioxymethamphetamine (MDMA, ecstasy); 5) absence of a history of head injury with loss of consciousness lasting more than 1 min; and 6) absence of pregnancy. Volunteers with a history of a mood or psychotic disorder in their first-degree relatives were excluded. The institutional review boards of Columbia Presbyterian Medical Center and the New York State Psychiatric Institute approved the protocol. Subjects gave written informed consent after an explanation of the study. Seven BD subjects were diagnosed as BD type I and four as BD type II. Subjects with BD had a mean (⫾ SD) Hamilton Depression Rating Scale (17-item version) score of 18 ⫾ 4.2 and a mean Beck Depression Inventory score of 32.4 ⫾ 9.9 near the time of the scan. Seven BD subjects were inpatients, and four were outpatients. The ages of BD subjects (38.2 ⫾ 10.8 years)

Voxel-Based Morphometry With MEDx software (Sensor Systems, Sterling, Virginia), each MRI was aligned according to the AC-PC plane and corrected for inhomogeneities. Nonbrain voxels were cropped, and the remaining brain was segmented into gray matter, white matter, and cerebrospinal fluid voxels, as previously described (Abi-Dargham et al 1999). To avoid known complications with the automatic segmentation step in traditional VBM (Ashburner and Friston 2000; Good et al 2001a), we created a gray matter mask by assigning each gray matter voxel a value of 1 and all other voxels a value of 0. Gray matter images prepared for analysis in SPM99 were obtained by multiplying each cropped MRI with its respective gray matter mask (Hulshoff Pol et al 2001) and resectioning into the axial plane with an isotropic voxel size of 1 mm3. The gray matter mask creation is known to be ineffective in the cerebellum owing to different voxel intensity of cerebellar gray matter, and we do not include differences observed in the cerebellum. With the exception of our segmentation method, VBM was performed according to the previously described optimized method (Good et al 2001c). Statistical parametric mapping (with SPM99) was executed in MATLAB 5.3 (MathWorks, Natick, Massachusetts) for all other processing steps. The origin of each image was set at the AC by a single blinded investigator (RAL). Images were spatially normalized to gender- and diagnosisspecific templates (see below) in common stereotactic space (Talairach and Tournoux 1988) with an output voxel size of 1.5 mm ⫻ 1.5 mm ⫻ 1.5 mm. To preserve the volume of a particular tissue compartment, normalized images were modulated by the Jacobian determinants derived from the spatial normalization (Good et al 2001a). To more closely conform to Gaussian random field theory, each image was smoothed with a 12-mm Gaussian kernel (full width at half maximum) (Ananth et al 2002). Customized gray matter templates were created for each group by averaging the smoothed (8-mm Gaussian kernel), segmented, normalized gray matter images (for details see Good et al 2001c). Statistical and Image Analysis The analyses between groups were conducted as analyses of covariance (Friston et al 1990). Age and gender (when applicawww.elsevier.com/locate/biopsych

Author and Year Kasai et al 2003

Subjects

PreSubTem- Temfrontal Dorsal genual Insular poral poral Superior Hippo- AmygCortex Lateral PFC Cortex Cingulate Lobe Pole Temporal campus dala 7

1.5-T MRI 1.5 mm slices 1.5-T MRI

Lenticula Caudate Globus Nuclei Nucleus Pallidus Thalamus

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Pituitary

7

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1.5mm slices 1.5-T MRI

Parahippocampus

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26 AP (BD n ⫽ 24) 29C Lopez-Larson 17 BD et al 2002 12 C Brambilla 22 BD et al 2001 22C Caetano et al 25 BD 2001 39 C Sassi et al 23 BD 2001 34 C Altshuler 24 BD et al 2000 (24 male)a 18 C Hauser et al 47 BD 2000 (25 type I) 19 C Hirayasu et al 24 AD 1999 (BD n ⫽ 21) 20 C Sax et al 17 BD 1999 12C Strakowski 24 BD et al 1999 22 C Altshuler 12 BD et al 1998 18C Roy et al 14 BD 1998 15 C Drevets et al 21 BD 1997 21 C Pearlson et al 27 BD 1997 60 C Dupont et al 36BD 1995 26 C Aylward et al 30 BD 1994 (16 male)b 30 C

Methods and Resolution

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Table 1. Results from Previous Structural MRI Studies Analyzing Volumetric Differences Between BD Subjects and Healthy Volunteers

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7 7

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10-mm slices .15-T MRI 8-mm slices

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Johnstone et al 1989

26 BD 34C 47 BD 60 C 17 FEP 16 C 48 BD 47 C 10 BD 10 C 17 AD (BD n ⫽ 15) 21 C 20 BD 21 C Harvey et al 1994 Schlaepfer et al 1994 Strakowski et al 1993 Swayze et al 1992 Altshuler et al 1991 Hauser et al 1989

There are several contradictory results, although general trends appear, showing that BD subjects have smaller frontal cortical structures and no change or larger volumes in basal ganglia and temporal lobe structures. MRI, magnetic resonance imaging; BD, bipolar disorder; PFC, prefrontal cortex; AP, affective psychosis; C, control; AD, affective disorder; FEP, first-episode mania; 7 no volumetric difference observed; 1 increased volume observed; 2 decreased volume observed. a Included number of male BD subjects in study because all or part of results were gender specific. b Results observed in male BD subjects only.

7 7

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Figure 1. Results from an optimized voxel-based morphometry (VBM) analysis, showing that bipolar disorder (BD) subjects had smaller volume in left ventromedial temporal cortex (also observed in the traditional VBM analysis) and cingulate cortex bilaterally. The study compared 11 BD subjects with 31 healthy volunteers, with gender as a covariate of interest. Crosshairs placed at x ⫽ ⫺.1, y ⫽ ⫺18.9, z ⫽ 40.4. Color scale: 0 – 6 represents Z score.

ble) were initially treated as covariates of interest, because of their known influence on brain morphology (Coffey et al 1998). When the analyses were performed with age as a covariate, no correlation was found between age and regional gray matter changes. Previous studies in subjects of comparable age range also found no correlation with age (Botteron et al 2002; Frodl et al 2002a; Sheline et al 1999). Consequently, we report results with gender but not age as a covariate of interest. Volumes were compared according to two linear contrasts (more or less gray matter volume between subject groups). Voxel values for each contrast constitute a statistical parametric map of the t statistic, with a threshold value set at puncorrected ⬍ .001 (Ananth et al 2002). Significance of clusters was determined by a Z score greater than 4.00 (threshold of puncorrected ⬍ .001) and pcorrected value less than .05 (Wright et al 1995). The location of significant clusters was determined by overlaying clusters onto a normalized MRI.

Results Optimized VBM: Volumetric Differences in BD Subjects Optimized VBM analyses showed that BD subjects had smaller volumes in cingulate bilaterally (x ⫽ 0, y ⫽ 27, z ⫽ 21 through x ⫽ ⫺3, y ⫽ ⫺8, z ⫽ 45; Z ⫽ 4.28, pcorrected ⫽ .003) and left ventromedial temporal cortex (x ⫽ ⫺20, y ⫽ ⫺21, z ⫽ ⫺21; Z ⫽ 5.08, pcorrected ⬍ .001) (Figure 1, Table 2) when compared with healthy volunteers. Larger volumes in BD subjects were seen in left insular/frontoparietal cortex (x ⫽ ⫺45, y ⫽ ⫺18, z ⫽ 28; Z ⫽ 5.47, pcorrected ⫽ .028) (Figure 2, Table 2) and left ventral occipitotemporal cortex (x ⫽ ⫺30, y ⫽ ⫺52, z ⫽ 4; Z ⫽ 4.06, pcorrected ⫽ .037) (Figure 3, Table 2). Traditional VBM: Gray Matter Densities Differences in BD Subjects Traditional VBM analyses showed that BD subjects had less gray matter densities in left ventromedial temporal cortex (x ⫽ www.elsevier.com/locate/biopsych

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Table 2. Results of Optimized and Traditional VBM Analysis Comparing BD Subjects with Healthy Volunteers VBM Method Optimized

Neuroanatomical Differences in BD Subjects Compared with Control Subjects Smaller bilateral cingulate cortex Smaller left ventromedial temporal cortex Larger left insular/frontoparietal operculum cortex Larger left ventral occipitotemporal cortex

Traditional

Decreased left ventromedial temporal cortex Increased left insular/frontoparietal operculum cortex Increased bilateral thalamic cortex

Z Score 4.28 5.08 5.47 4.06 5.65 6.43 5.16

pcorrected .003 ⬍.001 .028 .037 ⬍.001 .001 .001

x, y, z 0, 27, 21 ⫺20, ⫺21, ⫺21 ⫺45, ⫺18, 28 ⫺30, ⫺52, 4 ⫺20, ⫺18, ⫺20 ⫺45, ⫺21, 30 ⫾14, ⫺26, 21

BD subjects, n ⫽ 11; healthy volunteers, n ⫽ 31. Both optimized and traditional VBM analyses show BD subjects have respectively smaller volume and decreased densities in left ventromedial temporal cortex and larger volume and increased densities in left insular/frontoparietal operculum cortex. The optimized VBM analysis also shows smaller bilateral cingulate cortex and larger left ventral occipitotemporal cortex in BD subjects. The traditional VBM analysis shows larger bilateral thalamic cortex in BD subjects. VBM, voxel-based morphometry; BD, bipolar disorder.

⫺20, y ⫽ ⫺18, z ⫽ ⫺20; Z ⫽ 5.65, pcorrected ⫽ ⬍ .001) (Table 2) when compared with healthy volunteers. Greater gray matter densities in BD subjects were seen in left insular/frontoparietal cortex (x ⫽ ⫺45, y ⫽ ⫺21, z ⫽ 30; Z ⫽ 6.43, pcorrected ⫽ .001) (Table 2) and bilateral thalami (x ⫽ ⫾14, y ⫽ ⫺26, z ⫽ 21; Z ⫽ 5.16, pcorrected ⫽ .001) (Figure 4, Table 2). Optimized and Traditional VBM: Gender-Specific Analyses We covaried for gender in the previously described analyses, but the results are slightly different when each subject group is examined according to gender. Given the small sample size, these findings should be considered exploratory. In the optimized VBM analysis, male BD subjects were observed to have smaller volume in cingulate cortex bilaterally (x ⫽ 0, y ⫽ ⫺4, z ⫽ 38; Z ⫽ 5.14, pcorrected ⬍ .001), and larger volumes in right insular/frontoparietal operculum cortex (x ⫽ 38, y ⫽ ⫺18, z ⫽ 27; Z ⫽ 4.99, pcorrected ⫽ .038), left ventral occipitotemporal cortex (x ⫽ ⫺33, y ⫽ ⫺51, z ⫽ 3; Z ⫽ 5.54, pcorrected ⬍ .001). In male BD subjects, there is a strong trend for

larger volume in left insular/frontoparietal operculum cortex (x ⫽ ⫺48, y ⫽ ⫺24, z ⫽ 32; Z ⫽ 5.09, pcorrected ⫽ .055) when compared with male healthy volunteers. In female BD subjects, we observed no significant volumetric differences in brain structures compared with female healthy volunteers. In the traditional VBM analyses, female BD subjects had greater gray matter density in left thalamic cortex (x ⫽ ⫺12, y ⫽ ⫺26, z ⫽ 21; Z ⫽ 4.81, pcorrected ⫽ .012) and a strong trend for greater density in right thalamic cortex (x ⫽ 15, y ⫽ ⫺28, z ⫽ 21; Z ⫽ 3.77, pcorrected ⫽ .023) when compared with female healthy volunteers. Compared with male healthy volunteers, male BD subjects had less gray matter densities in cingulate cortex bilaterally (x ⫽ ⫺9, y ⫽ ⫺2, z ⫽ 45; Z ⫽ 4.63, pcorrected ⫽ .002), left occipitoparietal cortex (x ⫽ ⫺40, y ⫽ ⫺52, z ⫽ 48; Z ⫽ 5.06, pcorrected ⫽ .012), and left superior temporal/inferior insular cortex (x ⫽ ⫺36, y ⫽ ⫺28, z ⫽ 18; Z ⫽ 4.95, pcorrected ⫽ .048). Male BD subjects had greater gray matter densities in the left insular/frontoparietal operculum cortex (x ⫽ ⫺45, y ⫽ ⫺21, z ⫽ 30; Z ⫽ 5.44, pcorrected ⫽ .008), ventral occipitotemporal cortex

Figure 2. Results from an optimized voxel-based morphometry (VBM) analysis, showing that bipolar disorder (BD) subjects had larger left insular/ frontoparietal operculum cortex (also observed in the traditional VBM analysis). The study compared 11 BD subjects with 31 healthy volunteers, with gender as a covariate of interest. Crosshairs placed at x ⫽ ⫺47.5, y ⫽ ⫺18.8, z ⫽ 28.9. Color scale: 0 – 6 represents Z score.

Figure 3. Results from an optimized voxel-based morphometry (VBM) analysis, showing that bipolar disorder (BD) subjects had larger left ventral occipitotemporal cortex. The study compared 11 BD subjects with 31 healthy volunteers, with gender as a covariate of interest. Crosshairs placed at x ⫽ ⫺29.2, y ⫽ ⫺55.4, z ⫽ ⫺.7. Color scale: 0 – 6 represents Z score.

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Figure 4. Results from a traditional voxel-based morphometry (VBM) analysis, showing that bipolar disorder (BD) subjects had decreased left insular/ frontoparietal operculum cortex (also observed in the optimized VBM analysis) and thalamic cortex bilaterally. The study compared BD subjects with 31 healthy volunteers, with gender as a covariate of interest. Crosshairs placed at x ⫽ 11.6, y ⫽ ⫺27.3, z ⫽ 19.0. Color scale: 0 – 8 represents Z score.

(x ⫽ ⫺39, y ⫽ ⫺48, z ⫽ ⫺3; Z ⫽ 5.67, pcorrected ⬍ .001), and lateral temporal cortex (x ⫽ ⫺62, y ⫽ ⫺63, z ⫽ 16; Z ⫽ 4.44, pcorrected ⫽ .005). A strong trend was found for greater gray matter density in right insular/frontoparietal operculum (x ⫽ 40, y ⫽ ⫺16, z ⫽ 27; Z ⫽ 4.48, pcorrected ⫽ .054) when compared with male healthy volunteers.

Discussion Neuroanatomical Differences in BD Subjects Compared with Healthy Volunteers Previous structural MRI studies in BD subjects have been inconsistent. Generally, BD subjects have smaller PFC structures, larger amygdala, and possibly larger basal ganglia structures. Other temporal lobe structures have failed to show consistent volumetric change (for a summary see Table 1). It has been proposed that neuroanatomical abnormalities in limbic structures might represent a disruption in limbic circuitry and a consequent predisposition for depression, mania, and/or cycling affective symptoms (Benke et al 2002; Strakowski et al 2000). A neuroanatomical model of BD disorder has not been proposed, but it might involve a disorder in the prefrontal cortex–limbic–striatopallidal–thalamic circuit (Drevets and Raichle 1992; Mayberg 1997; Soares and Mann 1997). The optimized VBM analyses in our study showed that BD subjects had larger volume in left ventral occipitotemporal cortex, which seems to include posterior hippocampal cortex (Figure 2). Our traditional VBM analyses showed greater gray matter densities in bilateral thalamic cortex (Figure 4). Previous studies generally showed larger volumes in thalamus (Dupont et al 1995; Strakowski et al 1999), as well as in the amygdala (Altshuler et al 1998, 2000; Strakowski et al 1999) and caudate nucleus (Aylward et al 1994; Strakowski et al 1999). Functional neuroanatomical studies of depressed BD subjects have shown increased metabolism in ventral striatum, right amygdala, and thalamus (Ketter et al 2001). Manic BD subjects demonstrated

BIOL PSYCHIATRY 2004;55:1154 –1162 1159 increased caudate activity (Blumberg et al 2000). Subjects with BD demonstrated increased amygdalar activation in response to fearful facial expressions (Yurgelun-Todd et al 2000). The optimized analyses showed that BD subjects had less gray matter volume in an area extending from the cingulate body to the anterior cingulate bilaterally (Figure 1). Although one previous study showed no volumetric change in cingulate gyrus (Strakowski et al 1993), postmortem studies in bipolar disorder indicate a loss of anterior cingulate neurons (Benes et al 2001). In addition, previous volumetric studies showed that BD subjects had smaller volumes in several prefrontal structures (Drevets et al 1997; Hirayasu et al 1999). Functional neuroanatomical studies in depressed BD subjects showed reduced metabolism in dorsolateral and dorsomedial PFC (Ketter et al 2001) and decreased blood flow in subgenual PFC (Drevets et al 1997). Manic BD subjects demonstrated decreased prefrontal activity (O’Connell et al 1995) and increased dorsal anterior cingulate (Blumberg et al 2000; Goodwin et al 1997; Rubinsztein et al 2001). Subjects with BD demonstrated decreased PFC activation in response to fearful facial expressions (Yurgelun-Todd et al 2000). The optimized and traditional VBM analyses showed, respectively, that BD subjects had larger volume and greater gray matter density in left insular/frontoparietal operculum (Figure 2) and smaller volume and less gray matter densities in left ventromedial temporal lobe, which area includes parahippocampal and/or entorhinal cortex (Figure 1). Previous studies have tended to show no volumetric change in hippocampal (Altshuler et al 1998, 2000; Hauser et al 2000; Pearlson et al 1997; Sax et al 1999), parahippocampal (Altshuler et al 2000; Pearlson et al 1997), and insular cortex (Kasai et al 2003), although a postmortem analysis has shown BD subjects to have fewer ␥-aminobutyric acid (GABA)ergic or nonpyramidal neurons in CA2 and in the entorhinal cortex (Benes et al 1998). Our findings regarding loss of gray matter might reflect the loss of GABAergic interneurons reported in neuropathologic studies. Functional neuroimaging studies have shown that sad affect seems to be associated with activation of bilateral anterior temporal pole and midbrain, left amygdala, left insula, and right ventrolateral prefrontal cortex (Levesque et al 2003). In addition insular cortex has been shown to interact with limbic circuits, specifically orbitofrontal, operculum, cingulate cortex, amygdala, and parahippocampal cortex (Augustine 1996). Conflicting structural MRI results from published studies in which the ROI method was used might be attributable to methodologic differences, such as variable ROI specifications and image resolution. These differences are avoidable by our voxel-based approach. It is uncertain whether the observed structural abnormalities cause BD or result from the illness and/or its treatment. Several pathologic processes might result in a smaller or larger gray matter volume on MRI, including changes in neuronal or glial volume, direct cell loss, or changes in fluid accumulation (Ongur et al 1998). Social, cognitive, and affective behavior might depend on connections between anterior cingulate/medial orbitofrontal cortex and subcortical structures, which include the striatum, basal ganglia, amygdala, and thalamus (Cummings 1998; Tekin and Cummings 2002). Our results and previous studies showed structural and functional abnormalities in regions important for emotional processing. It is possible that these abnormalities represent an oversensitive and dysfunctional neuronal system, a system that abnormally identifies emotional significance and affect (Phillips et al 2003). www.elsevier.com/locate/biopsych

1160 BIOL PSYCHIATRY 2004;55:1154 –1162 Traditional Versus Optimized VBM In our hands, the optimized and traditional analyses produced similar as well as different results, depending on the brain region. Most regions showed similar results, although the thalami showed only a gray matter and not a volumetric change. The reason for this is unclear. Postmortem studies have revealed a loss of GABAergic neurons in anterior cingulate and entorhinal cortex that can explain our gray matter deficit (Ongur et al 1998). Other studies in which optimized and traditional VBM were used also reported differences in results for brain volume versus gray matter intensity (Good et al 2001c), and it is unclear why this occurs. The nonlinear spatial normalization step determines the relative shape and size of each voxel. The traditional VBM analysis does not modulate for the change in voxel size and compares the proportion of gray matter in each voxel. The optimized VBM analyses include a step that modulates each voxel with Jacobian determinants derived from the spatial normalization step, thus allowing the absolute volume of each voxel to be compared (Good et al 2001a). The nonlinear spatial normalization does not attempt to perfectly match each gyrus and sulcus but rather accounts for global brain shape differences. Modulated analyses include information about the brain deformations. This might allow the modulated analyses to be more sensitive to regional structural change than the unmodulated analyses because the normalization step might reduce the regional gray matter difference (Good et al 2001b). Possible Effects of Gender on Volumetric Differences When separated by gender, both the optimized and traditional VBM analyses show most of the differences are observed in the entire group, but primarily in male BD subjects. We had equal numbers of men and women, which rules out a difference in statistical power as the explanation. Previous ROI analyses found that male BD subjects had larger amygdala (Altshuler et al 1998) and larger caudate nucleus (Aylward et al 1994). Other previous studies showed that male subjects with major depressive disorder (Frodl et al 2002b) and schizophrenia (Nopoulos et al 1997a, 1997b; Pearlson and Marsh 1999) had greater brain abnormalities than female subjects. Factors that influence normal sexual dimorphisms (Frederikse et al 1999; Goldstein et al 2001; Gur et al 2002; Nopoulos et al 2000; Sowell et al 2002) might contribute to possible gender-dependent brain abnormalities in BD subjects (Goldstein et al 2001, 2002). Normal mechanisms include hormone effects, particularly androgen, in regulation of apoptosis brain development both early and late in life (Cooke et al 1999; Kawata 1995; McEwen 1999). Estrogen has been shown to have a neuroprotective effect in animal studies (Miller et al 1998) and stroke patients (Alkayed et al 1998), in contrast to testosterone (Nishino et al 1998). The effects of hormones at the time of an insult might vary with differing plasticity and neuronal distribution (Cooke et al 1999; McEwen 1999). Other mechanisms include gender-specific genetic influences on brain structure and development (Kawata 1995; Thompson et al 2001). Study Limitations The primary limiting factor of this study, particularly when the subjects are separated by gender, is the small sample size, and therefore the results should be considered preliminary. This study included both type 1 and type 2 bipolar subjects. These subgroups might have different pathophysiology. We were unable to separate subjects by gender and BD subtypes, and future work needs to be done with a sufficiently large subject group to allow for this subdivision. In addition, not all subjects were in a www.elsevier.com/locate/biopsych

R.A. Lochhead et al depressed mood. It is unknown whether mood state effects volume, and we cannot rule this out as a possible contributing factor. The impact of past medication treatment on brain structures was not accounted for in this study. All subjects but one had not been taking medication for at least 14 days; however, extensive prior courses of lithium treatment have been associated with increased subgenual cingulate gyrus (Manji et al 2000). The effect of long-term therapy on brain morphometry is unknown, and only a study of medication-naive patients can effectively rule out the effect of medication. Future studies should examine effects of course of illness, successful treatment, and genetic and childhood factors on brain morphology in bipolar disorder. We have presented the first voxel-based volumetric analysis of BD subjects. Our results support theories presented regarding the PFC–limbic–striatopallidal–thalamic circuitry (Drevets and Raichle 1992; Mayberg 1997; Soares and Mann 1997) of mood disorders, confirming findings of previous ROI-based structural studies and functional studies. In addition, our results suggest novel structures (i.e., insular cortex) that should be considered in future models. Funding was provided by The Stanley Medical Research Institute, American Foundation for Suicide Prevention, U.S. Public Health Service grants National Institute of Mental Health P30 MH46745 and MH40695, and the National Alliance for Research on Schizophrenia and Depression. We thank the staff of the Brain Imaging Division, and the Department of Neuroscience. Abi-Dargham A, Simpson N, Kegeles L, Parsey R, Hwang DR, Anjilvel S, et al (1999): PET studies of binding competition between endogenous dopamine and the D1 radiotracer [11C]NNC 756. Synapse 32:93–109. Alkayed NJ, Harukuni I, Kimes AS, London ED, Traystman RJ, Hurn PD (1998): Gender-linked brain injury in experimental stroke. Stroke 29:159 –165; discussion 166. Altshuler LL, Bartzokis G, Grieder T, Curran J, Jimenez T, Leight K, et al (2000): An MRI study of temporal lobe structures in men with bipolar disorder or schizophrenia. Biol Psychiatry 48:147–162. Altshuler LL, Bartzokis G, Grieder T, Curran J, Mintz J (1998): Amygdala enlargement in bipolar disorder and hippocampal reduction in schizophrenia: An MRI study demonstrating neuroanatomic specificity. Arch Gen Psychiatry 55:663–664. Altshuler LL, Conrad A, Hauser P, Li XM, Guze BH, Denikoff K, et al (1991): Reduction of temporal lobe volume in bipolar disorder: A preliminary report of magnetic resonance imaging. Arch Gen Psychiatry 48:482–483. Ananth H, Popescu I, Critchley HD, Good CD, Frackowiak RS, Dolan RJ (2002): Cortical and subcortical gray matter abnormalities in schizophrenia determined through structural magnetic resonance imaging with optimized volumetric voxel-based morphometry. Am J Psychiatry 159:1497– 1505. Ashburner J, Friston KJ (2000): Voxel-based morphometry—the methods. Neuroimage 11:805–821. Augustine JR (1996): Circuitry and functional aspects of the insular lobe in primates including humans. Brain Res Brain Res Rev 22:229 –44. Aylward EH, Roberts-Twillie JV, Barta PE, Kumar AJ, Harris GJ, Geer M, et al (1994): Basal ganglia volumes and white matter hyperintensities in patients with bipolar disorder. Am J Psychiatry 151:687–693. Bearden CE, Hoffman KM, Cannon TD (2001): The neuropsychology and neuroanatomy of bipolar affective disorder: A critical review. Bipolar Disord 3:106 –150; discussion 151–153. Benes FM, Kwok EW, Vincent SL, Todtenkopf MS (1998): A reduction of nonpyramidal cells in sector CA2 of schizophrenics and manic depressives. Biol Psychiatry 44:88 –97. Benes FM, Vincent SL, Todtenkopf M (2001): The density of pyramidal and nonpyramidal neurons in anterior cingulate cortex of schizophrenic and bipolar subjects. Biol Psychiatry 50:395–406.

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