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Increase in gray matter and decrease in white matter volumes in the cortex during treatment with atypical neuroleptics in schizophrenia
Schizophrenia Research 80 (2005) 61 – 71 www.elsevier.com/locate/schres
Increase in gray matter and decrease in white matter volumes in the cortex during treatment with atypical neuroleptics in schizophrenia Vicente Molina a,*, Santiago Reig b, Javier Sanz c, Toma´s Palomo c, Carlos Benito d, Javier Sa´nchez b, Fernando Sarramea e, Javier Pascau b, Manuel Desco b a
Department of Psychiatry, Hospital Clı´nico Universitario, P8 S. Vicente, 58-182. Salamanca 37007, Spain b Department of Experimental Medicine, Hospital Gregorio Maran˜o´n, Madrid, Spain c Department of Psychiatry, Hospital Doce de Octubre, Madrid, Spain d Department of Neuroradiology, Hospital Gregorio Maran˜o´n, Madrid, Spain e Department of Psychiatry, Hospital Reina Sofı´a, Co´rdoba, Spain Received 7 May 2005; received in revised form 27 June 2005; accepted 6 July 2005 Available online 16 September 2005
Abstract The effects of atypical antipsychotic treatment on the brain volume deficits associated with schizophrenia are poorly understood. We assessed the brain volumes of eleven healthy controls and 29 patients with schizophrenia, using magnetic resonance imaging at baseline and at follow-up after two years of treatment with atypical neuroleptics. Two groups of patients were analyzed: treatment-naı¨ve patients (n = 17) and chronic treatment-resistant patients (n = 12). Treatment-naı¨ve patients received risperidone during the follow-up period, whereas chronic patients received clozapine. Gray matter (GM) and white matter (WM) volumes in the frontal, parietal, occipital, and temporal lobes were measured. Contrary to the controls, both groups of patients presented GM increases and WM decreases in the parietal and occipital lobes ( p b .005). Frontal GM also increased in the chronic group with clozapine. There was a significant ( p b .001) inverse relationship between the baseline volumes (GM deficit/WM excess) and the longitudinal change. These GM and WM changes were not related to changes in weight. Thus, treatment with risperidone and clozapine in schizophrenia may have an effect on gray and white matter volume and needs further exploration. D 2005 Elsevier B.V. All rights reserved. Keywords: Schizophrenia; MRI; Atypical neuroleptics; DLPF cortex atrophy; Clozapine
1. Introduction
* Corresponding author. Fax: +34 923 291 383. E-mail address: [email protected] (V. Molina). 0920-9964/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2005.07.031
Cortical volume deficit is present in schizophrenia (Shenton et al., 2001), and it is possible that antipsychotic treatments could have an effect on this volume deficit (Harrison, 1999); however, the direction of that
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effect is unclear. On the one hand, it has been reported that typical antipsychotics can induce neuronal apoptosis (Noh et al., 2000) or reduce synaptic density (Kelley et al., 1997), which suggests they play a role in producing volume deficits. A decrease in brainderived neurotrophic factor has also been reported in association with neuroleptic treatment (Angelucci et al., 2000). Moreover, a recent study performed in monkeys suggests that chronic exposure to haloperidol and olanzapine may decrease brain weight and volume (Dorph-Petersen et al., 2005). On the other hand, it has been reported that higher cumulative exposure to conventional neuroleptics is associated with lower ventricular enlargement (DeLisi et al., 1997; Lieberman et al., 2001) and that, in first psychotic episodes, the volume deficit in the superior temporal gyrus may resolve with treatment (Keshavan et al., 1998). In addition, another primate study has shown that treatment with antipsychotics, whether typical or atypical, can induce an increase in cortical volume (Selemon et al., 1999). These data suggest that some antipsychotics can compensate for certain structural effects associated with mental illness. When it comes to determining the possible effect of neuroleptics on alterations in cortical volume, it is necessary to distinguish between conventional and atypical drugs. It has been reported that clozapine has an effect of reversing the increases in basal ganglia volume induced by typical antipsychotics (Chakos et al., 1995). It has also been found that atypical drugs do not produce an increase in basal ganglia volume in treatment-naı¨ve patients (Heitmiller et al., 2004) and that atypical drugs have a greater capacity for increasing NAA levels in the prefrontal (PF) cortex (Bertolino et al., 2001).
To our knowledge, no longitudinal studies have been conducted on structural changes in adult schizophrenia patients during exclusive treatment with atypical drugs. Therefore, we performed a longitudinal analysis of changes in cortical volume in schizophrenia patients treated with atypical neuroleptics. We enrolled two groups of patients, one consisting of treatment-naı¨ve patients receiving risperidone during the follow-up period, and the other of chronic patients previously treated with typical neuroleptics, who were switched to clozapine during the follow-up period. We also analyzed a group of healthy subjects of similar age as a reference control for longitudinal changes in the brain in the absence of disease.
2. Methods 2.1. Subjects Twenty-nine schizophrenia patients (20 males) and 11 controls (6 males), all right-handed Caucasians, were enrolled. The patients were assigned to two groups: neuroleptic-naı¨ve (NN) and chronic-resistant (CR) (Table 1). The NN group included 17 subjects diagnosed with paranoid schizophrenia (DSM-IV criteria). Twelve cases were first psychotic episodes, followed prospectively to confirm the diagnosis after one year. The other five cases already met the above criteria on enrollment. These 17 patients belonged to a sample of 49 first-episode cases, the rest of whom were not included in the longitudinal study for various reasons (diagnosis other than schizophrenia in 15 cases, loss to follow-up in 8 cases, administration of a different
Table 1 Demographic and clinical data on patients and controls, expressed as the mean (SD) Chronic (n = 12) Pre Age (years) Duration (years) Time bet. scans (months) Positive dimension Negative dimension Disorganization Parental socioec. level Education (years)
31.0 7.6 28.7 33.5 34.5 19.3 2.3 8.7
N. naı¨ve (n = 17) Post
(5.9) (4.0) (11.8) (16.3) (15.4) (12.3) (0.9) (8.9)
9.6 (12.5) 28.5 (11.8) 3.7 (4.0)
Pre 25.6 2.3 25.6 25.9 35.4 18.8 2.5 10.8
Controls (n = 11) Post
(4.0) (1.4) (9.9) (14.0) (19.4) (9.4) (0.7) (6.1)
28.4 (6.2) 27.5 (14.0) 5.0 (4.5) 47.5 (26.0) 9.4 (11.5) 2.4 (0.8) 11.2 (9.1)
V. Molina et al. / Schizophrenia Research 80 (2005) 61–71
treatment in 4 cases, and refusal of a repeat MRI in 3 cases). In the NN group of patients, the baseline MRI was done at initiation of treatment, within two weeks following diagnosis of the first psychotic episode. The second MRI was done a mean of 26 months (range: 20–30) later. During this follow-up period, treatment was maintained with risperidone at dosages adjusted according to clinical criteria (mean final dosage: 5 F 2 mg/day). None of the patients received any other treatment, except for one patient who received biperiden, two who received propanolol for extrapyramidal effects, and three who briefly received benzodiazepines for insomnia. The CR patient group comprised 12 cases (8 males), all chronic and refractory to conventional treatment. This group included 7 cases of paranoid schizophrenia and 5 of the undifferentiated subtype (DSM-IV criteria). It was part of a sample of 29 chronic treatment-resistant patients, the rest of whom were not included in this study for the following reasons: loss to follow-up in 10 cases, treatment other than clozapine in 5 cases, and refusal of a repeat imaging study in 2 cases. In the CR group of patients, the baseline MRI was done after maintaining prior haloperidol treatment (dosage: 10 mg/day) for one month, in order to confirm treatment resistance. After the baseline MRI, the treatment was converted to clozapine (initial dosages after escalation: 410 F 339 mg/day; final dosages 260 F 211 mg/day), until a second imaging study was done a mean of 26 months (range: 20–31) later. No patient received any other antipsychotics, antidepressants, or mood stabilizers, except for one patient who received benzodiazepines for insomnia. In all patients, diagnosis was confirmed using a semi-structured interview (SCID, patient version) and information from families and clinical staff. Symptoms were assessed using the SANS (Andreasen, 1983a) and SAPS (Andreasen, 1983b). Scores were calculated for positive, negative, and disorganization dimensions. Changes in weight between the first and second MRI were also measured. Data regarding clinical and demographic characteristics at inclusion are shown in Table 1. A sample of 11 healthy volunteers (6 males) was studied as a reference control for longitudinal changes in a healthy population. These controls had a below college educational level in order to properly match
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them with the patient group, and received minor compensation for their participation. No differences in parental socioeconomic status (Hollingshead and Frederick, 1953) were detected between groups. As in the patient groups, each subject underwent MRI studies over a similar period (mean interval between studies: 27 months; range: 19–36) (Table 1). There were no significant differences between the age of the controls and the patients. Exclusion criteria for patients and controls were neurological illness, MRI findings judged clinically relevant from a neurological perspective by a radiologist blind to diagnosis, history of cranial trauma with loss of consciousness, substance dependence criteria during the last 3 years (except for caffeine or nicotine), substance abuse during the last 6 months (a urinalysis at intake was used to rule out current consumption), history of axis I psychiatric processes or treatment (except schizophrenia in the case of patients), or any current treatment having known CNS action in addition to neuroleptics and benzodiazepines for insomnia. After receiving full information, the patients and their relatives signed an informed consent form. The independent ethics committee approved the study. 2.2. MRI acquisition and processing MRI scans were acquired with the same Philips Gyroscan 1.5T scanner and the same acquisition protocol at baseline and follow-up, a T1-weighted 3D gradient echo sequence with the following parameters: matrix size 256 256, pixel size 0.9 0.9 mm (FOV 256 mm), flip angle 308, echo time 4.6 ms, slice thickness ranging from 1.1 to 1.5 mm. T2-weighted sequences were also acquired for verification of CSF segmentations and for other clinical purposes (TurboSpin Echo, turbo factor 15, echo time 120 ms, matrix size 256 256, slice thickness 5.5 mm). 2.2.1. Segmentation and ROI definition The MRI processing and volumetric quantification have been described in detail elsewhere (Desco et al., 2001; Molina et al., 2003b). Briefly, to obtain volume measurements of the main brain lobes, we used a method for semi-automated segmentation of the brain based on the Talairach reference system (Fig. 1), similar to the method described in Andreasen et al. (1996) and Kates et al. (1999). This
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Fig. 1. An example of a Talairach grid built upon an MRI scan. Regions of interest are defined by adding grid cells, according to the Talairach Atlas.
method has also been used in similar studies measuring longitudinal volume changes in brain regions (Ho et al., 2003). Basically, it is a two step procedure. The first step involved editing the MRI to remove skull and extracranial tissue using the T2weighted image, and an initial segmentation of cerebral tissues into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) of the T1weighted image. Segmentation of cerebral tissue was performed using an automated method included in the SPM2 (Statistical Parametric Mapping) program (Ashburner and Friston, 1997). The method performs a cluster analysis with a modified mixture model and a priori information about the likelihood of each MRI voxel being one of 4 tissue types: GM, WM, CSF, and bother tissues.Q The a priori information consists of anatomical templates that represent an daverageT brain and provides information about the spatial distribution of the different brain tissues. The algorithm also removes the effect of radiofrequency field inhomogeneities (Ashburner and Friston, 2000). This segmentation was checked for inconsistencies and manually corrected whenever necessary by an experienced radiologist blind to the diagnosis. In a second stage, we applied the Talairach reference system (Talairach and Tournoux, 1988) to define regions of interest (ROIs) and to
obtain volume data. MRI processing was performed using locally developed software that incorporates a variety of image processing and quantification tools (Desco et al., 2001). The validity of the Talairachbased procedure as a suitable automated segmentation tool in schizophrenia research has been previously proven (Andreasen et al., 1996; Ho et al., 2003; Kates et al., 1999). In our study, all manual procedures were performed by a single operator, thus avoiding any potential inter-rater variability. Reliability of the method was assessed by repeating the entire segmentation procedure in a sample of 5 randomly selected cases. ICC values ranged from 0.95 to 0.99 for regional GM and WM measurements, and from 0.89 to 0.99 for CSF data. Again, all manual procedures were performed by a single operator, thus avoiding any potential inter-rater variability. Repeatability of the tissue segmentation procedure was 99% for total volumes of gray and white tissue (Chard et al., 2002; Gispert et al., 2004). In addition to total volumes of GM and WM, the analysis included the frontal, parietal, temporal and occipital lobes, defined using the boundaries described previously for the Talairach method (Andreasen et al., 1996). ROIs were measured bilaterally, adding the left and right sides together. Intracranial volume (ICV) was calculated by adding total
V. Molina et al. / Schizophrenia Research 80 (2005) 61–71
GM, WM, and CSF for each brain (including the cerebellum). 2.3. Statistical analysis Improvement in the three symptom dimensions was studied using Wilcoxon tests for paired samples, comparing the scores before and after the treatment period. 2.3.1. Gross change in volume The longitudinal change in volume was measured as the difference between the initial and final volume of each ROI. To avoid bias due to overall differences in brain size, instead of absolute change values in cc, we used a quotient for total volume of the corresponding ROI. On the other hand, to control for any potential difference between the two scans due to updates of MRI equipment, we calculated a correction factor as a quotient between the initial (baseline) and final intracranial volume (ICV) (E ICV = ICV1 / ICV2), assuming that the total ICV should be equal in both scans (Mathalon et al., 2001). Thus, for each ROI, the magnitude of the relative change in volume between the baseline (Vol1) and final (Vol2) MRI was calculated as follows: Longitudinal change
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models obtained from a group of healthy individuals (n = 31, 17 males), following the procedure of Pfefferbaum et al. (1992). After this correction, volume variables were expressed as deviations from the expected volumes in healthy individuals of the same age as the patient. Thus, negative residuals represent a quantitative measurement of atrophy and vice versa. The regression parameters used for this transformation were obtained from a previous study (Molina et al., 2003b). To analyze the relationship between baseline alterations and longitudinal changes, we calculated the coefficient of correlation (Spearman’s q) between the converted baseline and final GM and WM volume change in the regions with significant longitudinal changes in volume. 2.3.3. Sources of error Of the possible sources of error that potentially affected our results, we found that gender did not affect the measurement of longitudinal changes, since there were no significant differences between men and women in the Mann–Whitney test. Nor did we find any relationship between longitudinal changes in weight and volume, using a Spearman correlation. This relationship was not significant whether each group of patients was analyzed separately or together. Statistical analysis was done using the SPSS software package (version 11).
¼ ½ððVol2 EICV Þ Vol1Þ=Vol1 100 The significance of the differences in the longitudinal change in GM and WM between the patient groups and the controls was analyzed for each ROI using a Mann–Whitney test. The total GM and WM volume was also analyzed, but we did not include data on changes in CSF volume, since those are secondary to the changes in GM or WM volume. 2.3.2. Measurement of baseline atrophy / hypertrophy To evaluate the hypothesis of a relationship between the degree of initial volume alteration and the magnitude of longitudinal change, we converted the volume values to directly indicate a condition of atrophy/hypertrophy as compared to healthy subjects, independent of factors such as age and ICV. Since age and total cranial size are known factors affecting regional cerebral volumes, their effect was removed by using the residuals from the regression
3. Results 3.1. Change in symptoms The group of NN patients presented a significant improvement in positive symptoms (z = 2.9, n = 17, p = .002). There were no significant differences in the disorganization or negative dimensions. The weight of these patients increased significantly (mean 8.5 kg, SD 9.0, t = 2.8, p = .02). In the CR group, the positive dimension (z = 2.3, n = 12, p = .01) and the disorganization dimension (z = 2.1, n = 12, p = .02) improved significantly, but the negative dimension did not. The weight of this group of patients also increased significantly (mean 3.1 kg, SD 4.3, t = 2.0, n = 12, p = .05). 3.2. Gross longitudinal changes There was no significant change in total brain volume (GM plus WM total volume; Table 2) in either group.
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Table 2 Regional volumes in the three groups and their corresponding longitudinal changes
ICV Total brain Total GM Total WM Frontal GM Frontal WM Parietal GM Parietal WM Temporal GM Temporal WM Occipital GM Occipital WM
Chronic patients (n = 12)
N. naive patients (n = 17)
Controls (n = 11)
Baseline (cc)
% change from baseline
Baseline (cc)
% change from baseline
Baseline (cc)
% change from baseline
1463.8 1021.7 733.0 455.7 132.8 112.2 107.7 118.6 138.3 68.1 61.2 50.8
1.3 1.0 4.2 9.0 6.8 7.6 7.3 7.6 1.7 6.4 14.9 9.0
1509.9 1086.4 816.7 438.7 154.3 109.6 120.7 111.7 149.7 68.0 68.4 46.9
0.3 1.3 1.0 3.1 2.7 1.5 1.2 2.6 1.6 5.0 6.2 4.1
1458.2 1038.6 798.9 406.4 154.9 104.8 117.6 110.4 148.2 59.9 68.3 43.2
2.3 0.5 0.5 2.3 0.0 1.7 3.5 4.0 1.2 0.2 1.4 2.9
(113.8) (63.2) (61.2)*** (41.2)* (12.2)*** (12.7) (12.1)*** (12.1)* (10.8)** (7.5) (6.9)*** (5.6)***
(1.9) (4.1) (5.7)* (5.9)*** (8.5)* (6.6)** (11.2)** (7.7)*** (8.3) (10.1) (12.0)*** (7.6)**
(117.6) (96.7) (56.8) (57.6) (12.2)* (15.7) (10.9) (16.6) (10.0) (10.8) (9.1)* (6.9)
(1.6) (3.2) (2.6) (5.0)** (4.8) (6.6) (7.8)* (6.9) (4.3) (7.3) (10.1)* (8.8)*
(123.5) (109.9) (71.9) (54.3) (17.6) (18.4) (17.0) (18.4) (8.4) (6.5) (9.5) (7.8)
(1.8) (3.8) (2.5) (4.8) (4.0) (6.7) (3.6) (7.4) (3.3) (6.5) (6.1) (8.0)
Baseline data expressed as mean (SD) in cc. Change in each structure is expressed as mean (SD) percent of the initial volume of the structure, corrected for intracranial volume (see Methods section). Significance of differences in longitudinal changes between each group of patients and controls and of baseline volume differences relative to expected values from normal populations appear in the corresponding columns of each patient group (see Methods section) (Mann–Whitney test). *p b 0.05; **p b 0.01; ***p b .001.
In the control group, there was a small decrease in GM volume and an increase in WM volume (Table 2, Fig. 2), which followed the pattern expected in healthy individuals (Bartzokis et al., 2001; Coffey et al., 1992; Sowell et al., 2003). This change was not statistically significant (using a t test for one sample, with the null hypothesis of no change), except for the change in parietal GM, which decreased significantly (t = 3.14, p = .01). The group of NN patients presented a significant increase in occipital (U = 47, z = 2.2, p = .02) and parietal (U = 53, z = 1.9, p = .05) GM compared to the healthy individuals. The changes in total GM (U = 56, z = 1.8, p = .08) did not achieve statistical significance, but were in the same direction (Fig. 2). These patients also presented a decrease in total (U = 41, z = 2.4, p = .01) and occipital (U = 48, z = 2.2, p = .03) WM compared to the control group (Table 2, Fig. 2). The group of CR patients presented significant increases in total (U = 30, z = 2.2, p = .02), frontal (U = 33, z = 2.0, p = .04), parietal (U = 21, z = 2.9, p = .004), and occipital (U = 14, z = 3.2, p = .001) GM compared to the controls. In addition, they presented total (U = 3, z = 3.9, p b .001), frontal (U = 20, z = 2.8, p = .004), parietal (U = 16, z = 3.1, p = .001), and occipital (U = 19, z = 2.9, p = .003) WM decreases compared to the controls (Table 2, Fig. 2). 3.3. Longitudinal changes in degree of baseline alterations 3.3.1. Baseline alterations Compared to the expected values in a normal population (see Methods), the NN group presented a statistically sig-
nificant baseline deficit in frontal (U = 246, z = 2.2, p = .03) and occipital (U = 247, z = 2.1, p = .03) GM, but no alterations in WM (Table 2). At baseline, the CR group presented a statistically significant deficit in total (U = 72, z = 4.1, p b .001), frontal (U = 57, z = 4.4, p b .001), parietal (U = 41, z = 4.7, p b .001), temporal (U = 126, z = 3.1, p = .002), and occipital (U = 40, z = 4.7, p b .001) GM, along with an excess in total (U = 125, z = 2.2, p = .03), parietal (U = 122, z = 2.8, p = .03), and occipital (U = 98, z = 3.6, p b .001) WM (Table 2). 3.3.2. Relationship between longitudinal change and degree of baseline alteration In the NN patients, there was a significant inverse relationship (q = .56, p = .02) between the total increase in GM and the baseline deficit, using volume data adjusted for age and ICV. In other words, the greater the initial deficit, the greater the increase in GM. The relationship between the baseline deficit in parietal GM and its change was also significant (q = .80, p b .001). In addition, in these patients, there was a significant relationship between initial WM volume and its change in the total (q = .77, p b .001) and occipital (q = .70, p = .002) regions (the greater the initial excess, the greater the longitudinal decrease). In the CR group, there was also a significant relationship between the baseline alteration and changes in GM in the occipital region (q = .57, p = .05). For total, parietal, and frontal GM, this relationship was not significant. In this group, there was also a significant inverse relationship between the baseline volume and changes in WM in all
V. Molina et al. / Schizophrenia Research 80 (2005) 61–71 30
30
% C h a n g e
C h a n g e
22
14
6
P a r i e t .
–2
C h a n g e
20
10
0
T e m p o r .
–10
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12
4
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6
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F r o n t –12 a l –20 Chronics
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0
W M –6
O c c i p t .
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Fig. 2. Scatter plots of changes in GM and WM in the four lobes. Values represent percentage of change in the corresponding structure, once corrected for the change in ICV between the two MRI studies (see Methods). Bars show standard error for each group.
regions. In other words, the greater the baseline volume excess of WM, the more negative the change (greater decrease) in the total (q = .75, p = .005), frontal (q = .83, p = .001), parietal (q = .74, p = .006), and occipital (q = .84, p = .001) regions. Analyzing the entire patient sample together, we found significant correlations between a baseline deficit in GM and the longitudinal increase in total (q = .62, n = 29, p b .001), frontal (q = .45, n = 29, p = .01), parietal (q = .74, n = 29, p b .001), and occipital (q = .51, n = 29, p = .004) volumes. On the other hand, in the control group, we found no significant relationship between the baseline volumes and their longitudinal change.
4. Discussion In the current study, an increase in gray matter and decrease in white matter volume occurred in patients with schizophrenia after treatment with clozapine or risperidone. These changes were more marked in the chronic clozapine-treated group. Furthermore, the
increase in gray matter was not statistically associated with an increase in weight. However, these longitudinal changes in volume were related to the degree of baseline structural alteration. In other words, the greater the gray matter (GM) deficit, the greater the change after treatment with risperidone or clozapine. The observed longitudinal effect suggests a diffuse increase in cortical GM volumes with clozapine and risperidone. In both treatment groups, the most marked GM gain was observed in the occipital region. The location of this longitudinal effect is consistent with the most significant metabolic change observed with positron emission tomography (PET) in a sample including most of the patients participating in the present study (Molina et al., 2005a, 2003a). In these studies, metabolic activity in the visual area (at rest with eyes open) increased in recent-onset and chronic patients treated with risperidone or clozapine, respectively. Similar gains in GM with atypical neuroleptics have been previously reported. In a study of GM changes (frontal cortex only) in adolescents with
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schizophrenia (n = 16, mean age at baseline = 18), a 1.9% increase was reported after 2 years of treatment with atypical drugs (James et al., 2004). That change did not reach statistical significance, perhaps due to the small sample size. Another study performed in first-episode adults described frontal and temporal GM deficits in patients treated with typical drugs for 8 weeks (n = 32) compared to untreated patients (n = 22), while another group of patients treated with atypical drugs (n = 30) presented a thalamic GM excess with no cortical deficit compared to the same untreated group (Dazzan et al., 2004). Longitudinal studies in patients treated exclusively with typical neuroleptics have reported a significant decrease in frontal GM volume (Gur et al., 1998; Mathalon et al., 2001) or hemispheric volume (DeLisi et al., 1997). However, more recent studies, in which some patients were treated with atypical and others with typical neuroleptics, have found no decrease in GM (Dazzan et al., 2004; DeLisi et al., 2004; Ho et al., 2003), with the possible exception of juvenile onset cases (Gogtay et al., 2004). Moreover, our findings are consistent with a study of first-episode patients, which reported that haloperidol-treated patients exhibited significant decreases in GM volume, whereas patients receiving olanzapine showed no significant volume changes (Lieberman et al., 2005). Although the morphologic outcomes were similar in both groups of patients, the gain in GM was greater in the CR group during treatment with clozapine (Table 2, Fig. 2). The relationship between prior degree of structural alteration and treatment-induced change suggests that the greater gain in GM with this drug may be related to the greater initial atrophy in these patients. Our results suggest that such atrophy may be reversible, as previously reported in other ROIs (Keshavan et al., 1998). In a recent study by Dorph-Petersen et al. (2005), macaque monkeys were administered haloperidol or olanzapine for 17 to 27 months to investigate the macroscopic effects of antipsychotics on the brain. They found that both treatments produced a slight, but significant decrease in brain weight and volume, more pronounced in the frontal and parietal regions. However, these results can only be partially associated with our findings because, in their study, both gray and white matter volumes were reduced in treated monkeys compared to controls. This inconsistency may
originate from the higher doses of neuroleptics administered to monkeys to achieve plasma levels similar to those in humans. Moreover, we cannot conclude that the human brain would show the same changes as in monkeys, especially in the case of cerebral illness. In support of this, the association in our patients between basal GM deficit and volume increase with clozapine and risperidone suggests that, in the absence of such a basal deficit, the outcome would have been different. Finally, different treatments (olanzapine and haloperidol versus risperidone and clozapine) might have had different effects on brain morphology. Even though our data suggest that the GM increase was due to the atypical treatment, we cannot be certain of this, since we did not study the outcome in similar groups of patients not treated with atypical neuroleptics. Among other limitations of the study, not all of our chronic patients received the same treatment prior to enrollment in the study and the initiation of clozapine, although all received haloperidol during the preceding month. Therefore, our results could be affected by the withdrawal of drugs received prior to clozapine. However, this problem does not affect the NN patient sample, which presented a similar pattern of changes. Another important limitation was the small sample size, partially offset by a more statistically powerful longitudinal design. In particular, the number of controls was small; however, the observed changes in volume followed the longitudinal pattern expected in the general population (Bartzokis et al., 2001; Coffey et al., 1992; Sowell et al., 2003). We can not rule out the possibility that the observed volumetric differences in this study were not a consequence of treatment and could, instead, be caused by an as-yet unknown epiphenomenon, either related to subject metabolic changes or to MRI scanner artifacts during the longitudinal period of this study. The assertion that atypical neuroleptics have an effect on brain volume has yet to be definitively demonstrated. However, even if we are observing true effects of the medication, we can only speculate about the potential cellular processes underlying the changes observed in the cortex. Relying upon histological data from studies performed in rats and monkeys, two possible explanations arise: proliferation of neuronal elements or of glial cells. Concerning the first, formation of new neuronal elements, such as
V. Molina et al. / Schizophrenia Research 80 (2005) 61–71
synapses, seems more likely than neurogenesis in the adult brain. Synaptogenesis may be indeed an effect of classical treatment in subcortical regions (Konradi and Heckers, 2001). However, a huge increase in connections would be required to explain a GM volume increase capable of MRI detection. On the other hand, in primate cortices, there was no increase of neuronal tissue after treatment with typical or atypical neuroleptics (Selemon et al., 1999). However, another study showed that clozapine induced cell division in the hippocampus, though the resulting neurons did not survive 3 weeks (Halim et al., 2004). Thus, it seems unlikely that the increase in GM observed in our patients was caused by the appearance of new neurons or increased connections. Regarding changes in the glia, proliferation of cells, along with cortical hypertrophy, has been observed in the prefrontal cortex of primates after treatment with typical and atypical neuroleptics (Selemon et al., 1999). Moreover, olanzapine can increase the number of dividing glial cells in the frontal cortex in adult rats (Wang et al., 2004). A similar effect of atypical neuroleptics on glial cells would also be consistent with the increased brain metabolic activity observed in our patients (Molina et al., 2005a; Molina et al., 2003a), given the role of glial cells in PET data (Magistretti, 2000). At any rate, more specific data are needed to demonstrate the histological substrate of the GM changes observed in our study. The co-occurrence of GM increase and WM decrease is consistent with the recent finding of a decrease in WM after four weeks of typical or atypical treatment (Christensen et al., 2004). This WM decrease suggests that GM increase is not due to the production of new healthy cells, as the WM is partly formed by the extension of such cells. The decrease in WM due to atypical treatment could be explained by a blockade of factors stimulating myelin synthesis, the other WM component. We could speculate that such a factor could have to do with a chronic glutamatergic hyperactivation state, since hyperactivity relates to increased myelination in other disease states (Adamsbaum et al., 1996; Krishnan et al., 1994). Such a hyperactivity state might be present in schizophrenia (Molina et al., 2005b; Volk and Lewis, 2002). In summary, the present study found brain gray matter increases and white matter decreases following
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treatment with atypical drugs such as risperidone and clozapine in chronic and neuroleptic-naı¨ve patients. While these changes could be associated with the effects of these drugs on the brain, this phenomenon needs further exploration before this conclusion can be reached. We cannot be sure that the changes observed in our group were solely due to the atypical treatment, as we did not have a control group of patients treated without atypical neuroleptics over the same period of time.
Acknowledgments Supported in part by grants from the bFondo de Investigaciones SanitariasQ (02/3095, Red Tema´tica IM3), bG03/185Q and bFundacio´n La CaixaQ (99/04200). We thank Angel Santos Briz, pathologist from the Neuroscience Institute of Castilla y Leo´n, for his valuable assistance in data interpretation.
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Increase in gray matter and decrease in white matter volumes in the cortex during treatment with atypical neuroleptics in schizophrenia Vicente Molina a,*, Santiago Reig b, Javier Sanz c, Toma´s Palomo c, Carlos Benito d, Javier Sa´nchez b, Fernando Sarramea e, Javier Pascau b, Manuel Desco b a
Department of Psychiatry, Hospital Clı´nico Universitario, P8 S. Vicente, 58-182. Salamanca 37007, Spain b Department of Experimental Medicine, Hospital Gregorio Maran˜o´n, Madrid, Spain c Department of Psychiatry, Hospital Doce de Octubre, Madrid, Spain d Department of Neuroradiology, Hospital Gregorio Maran˜o´n, Madrid, Spain e Department of Psychiatry, Hospital Reina Sofı´a, Co´rdoba, Spain Received 7 May 2005; received in revised form 27 June 2005; accepted 6 July 2005 Available online 16 September 2005
Abstract The effects of atypical antipsychotic treatment on the brain volume deficits associated with schizophrenia are poorly understood. We assessed the brain volumes of eleven healthy controls and 29 patients with schizophrenia, using magnetic resonance imaging at baseline and at follow-up after two years of treatment with atypical neuroleptics. Two groups of patients were analyzed: treatment-naı¨ve patients (n = 17) and chronic treatment-resistant patients (n = 12). Treatment-naı¨ve patients received risperidone during the follow-up period, whereas chronic patients received clozapine. Gray matter (GM) and white matter (WM) volumes in the frontal, parietal, occipital, and temporal lobes were measured. Contrary to the controls, both groups of patients presented GM increases and WM decreases in the parietal and occipital lobes ( p b .005). Frontal GM also increased in the chronic group with clozapine. There was a significant ( p b .001) inverse relationship between the baseline volumes (GM deficit/WM excess) and the longitudinal change. These GM and WM changes were not related to changes in weight. Thus, treatment with risperidone and clozapine in schizophrenia may have an effect on gray and white matter volume and needs further exploration. D 2005 Elsevier B.V. All rights reserved. Keywords: Schizophrenia; MRI; Atypical neuroleptics; DLPF cortex atrophy; Clozapine
1. Introduction
* Corresponding author. Fax: +34 923 291 383. E-mail address: [email protected] (V. Molina). 0920-9964/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2005.07.031
Cortical volume deficit is present in schizophrenia (Shenton et al., 2001), and it is possible that antipsychotic treatments could have an effect on this volume deficit (Harrison, 1999); however, the direction of that
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effect is unclear. On the one hand, it has been reported that typical antipsychotics can induce neuronal apoptosis (Noh et al., 2000) or reduce synaptic density (Kelley et al., 1997), which suggests they play a role in producing volume deficits. A decrease in brainderived neurotrophic factor has also been reported in association with neuroleptic treatment (Angelucci et al., 2000). Moreover, a recent study performed in monkeys suggests that chronic exposure to haloperidol and olanzapine may decrease brain weight and volume (Dorph-Petersen et al., 2005). On the other hand, it has been reported that higher cumulative exposure to conventional neuroleptics is associated with lower ventricular enlargement (DeLisi et al., 1997; Lieberman et al., 2001) and that, in first psychotic episodes, the volume deficit in the superior temporal gyrus may resolve with treatment (Keshavan et al., 1998). In addition, another primate study has shown that treatment with antipsychotics, whether typical or atypical, can induce an increase in cortical volume (Selemon et al., 1999). These data suggest that some antipsychotics can compensate for certain structural effects associated with mental illness. When it comes to determining the possible effect of neuroleptics on alterations in cortical volume, it is necessary to distinguish between conventional and atypical drugs. It has been reported that clozapine has an effect of reversing the increases in basal ganglia volume induced by typical antipsychotics (Chakos et al., 1995). It has also been found that atypical drugs do not produce an increase in basal ganglia volume in treatment-naı¨ve patients (Heitmiller et al., 2004) and that atypical drugs have a greater capacity for increasing NAA levels in the prefrontal (PF) cortex (Bertolino et al., 2001).
To our knowledge, no longitudinal studies have been conducted on structural changes in adult schizophrenia patients during exclusive treatment with atypical drugs. Therefore, we performed a longitudinal analysis of changes in cortical volume in schizophrenia patients treated with atypical neuroleptics. We enrolled two groups of patients, one consisting of treatment-naı¨ve patients receiving risperidone during the follow-up period, and the other of chronic patients previously treated with typical neuroleptics, who were switched to clozapine during the follow-up period. We also analyzed a group of healthy subjects of similar age as a reference control for longitudinal changes in the brain in the absence of disease.
2. Methods 2.1. Subjects Twenty-nine schizophrenia patients (20 males) and 11 controls (6 males), all right-handed Caucasians, were enrolled. The patients were assigned to two groups: neuroleptic-naı¨ve (NN) and chronic-resistant (CR) (Table 1). The NN group included 17 subjects diagnosed with paranoid schizophrenia (DSM-IV criteria). Twelve cases were first psychotic episodes, followed prospectively to confirm the diagnosis after one year. The other five cases already met the above criteria on enrollment. These 17 patients belonged to a sample of 49 first-episode cases, the rest of whom were not included in the longitudinal study for various reasons (diagnosis other than schizophrenia in 15 cases, loss to follow-up in 8 cases, administration of a different
Table 1 Demographic and clinical data on patients and controls, expressed as the mean (SD) Chronic (n = 12) Pre Age (years) Duration (years) Time bet. scans (months) Positive dimension Negative dimension Disorganization Parental socioec. level Education (years)
31.0 7.6 28.7 33.5 34.5 19.3 2.3 8.7
N. naı¨ve (n = 17) Post
(5.9) (4.0) (11.8) (16.3) (15.4) (12.3) (0.9) (8.9)
9.6 (12.5) 28.5 (11.8) 3.7 (4.0)
Pre 25.6 2.3 25.6 25.9 35.4 18.8 2.5 10.8
Controls (n = 11) Post
(4.0) (1.4) (9.9) (14.0) (19.4) (9.4) (0.7) (6.1)
28.4 (6.2) 27.5 (14.0) 5.0 (4.5) 47.5 (26.0) 9.4 (11.5) 2.4 (0.8) 11.2 (9.1)
V. Molina et al. / Schizophrenia Research 80 (2005) 61–71
treatment in 4 cases, and refusal of a repeat MRI in 3 cases). In the NN group of patients, the baseline MRI was done at initiation of treatment, within two weeks following diagnosis of the first psychotic episode. The second MRI was done a mean of 26 months (range: 20–30) later. During this follow-up period, treatment was maintained with risperidone at dosages adjusted according to clinical criteria (mean final dosage: 5 F 2 mg/day). None of the patients received any other treatment, except for one patient who received biperiden, two who received propanolol for extrapyramidal effects, and three who briefly received benzodiazepines for insomnia. The CR patient group comprised 12 cases (8 males), all chronic and refractory to conventional treatment. This group included 7 cases of paranoid schizophrenia and 5 of the undifferentiated subtype (DSM-IV criteria). It was part of a sample of 29 chronic treatment-resistant patients, the rest of whom were not included in this study for the following reasons: loss to follow-up in 10 cases, treatment other than clozapine in 5 cases, and refusal of a repeat imaging study in 2 cases. In the CR group of patients, the baseline MRI was done after maintaining prior haloperidol treatment (dosage: 10 mg/day) for one month, in order to confirm treatment resistance. After the baseline MRI, the treatment was converted to clozapine (initial dosages after escalation: 410 F 339 mg/day; final dosages 260 F 211 mg/day), until a second imaging study was done a mean of 26 months (range: 20–31) later. No patient received any other antipsychotics, antidepressants, or mood stabilizers, except for one patient who received benzodiazepines for insomnia. In all patients, diagnosis was confirmed using a semi-structured interview (SCID, patient version) and information from families and clinical staff. Symptoms were assessed using the SANS (Andreasen, 1983a) and SAPS (Andreasen, 1983b). Scores were calculated for positive, negative, and disorganization dimensions. Changes in weight between the first and second MRI were also measured. Data regarding clinical and demographic characteristics at inclusion are shown in Table 1. A sample of 11 healthy volunteers (6 males) was studied as a reference control for longitudinal changes in a healthy population. These controls had a below college educational level in order to properly match
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them with the patient group, and received minor compensation for their participation. No differences in parental socioeconomic status (Hollingshead and Frederick, 1953) were detected between groups. As in the patient groups, each subject underwent MRI studies over a similar period (mean interval between studies: 27 months; range: 19–36) (Table 1). There were no significant differences between the age of the controls and the patients. Exclusion criteria for patients and controls were neurological illness, MRI findings judged clinically relevant from a neurological perspective by a radiologist blind to diagnosis, history of cranial trauma with loss of consciousness, substance dependence criteria during the last 3 years (except for caffeine or nicotine), substance abuse during the last 6 months (a urinalysis at intake was used to rule out current consumption), history of axis I psychiatric processes or treatment (except schizophrenia in the case of patients), or any current treatment having known CNS action in addition to neuroleptics and benzodiazepines for insomnia. After receiving full information, the patients and their relatives signed an informed consent form. The independent ethics committee approved the study. 2.2. MRI acquisition and processing MRI scans were acquired with the same Philips Gyroscan 1.5T scanner and the same acquisition protocol at baseline and follow-up, a T1-weighted 3D gradient echo sequence with the following parameters: matrix size 256 256, pixel size 0.9 0.9 mm (FOV 256 mm), flip angle 308, echo time 4.6 ms, slice thickness ranging from 1.1 to 1.5 mm. T2-weighted sequences were also acquired for verification of CSF segmentations and for other clinical purposes (TurboSpin Echo, turbo factor 15, echo time 120 ms, matrix size 256 256, slice thickness 5.5 mm). 2.2.1. Segmentation and ROI definition The MRI processing and volumetric quantification have been described in detail elsewhere (Desco et al., 2001; Molina et al., 2003b). Briefly, to obtain volume measurements of the main brain lobes, we used a method for semi-automated segmentation of the brain based on the Talairach reference system (Fig. 1), similar to the method described in Andreasen et al. (1996) and Kates et al. (1999). This
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Fig. 1. An example of a Talairach grid built upon an MRI scan. Regions of interest are defined by adding grid cells, according to the Talairach Atlas.
method has also been used in similar studies measuring longitudinal volume changes in brain regions (Ho et al., 2003). Basically, it is a two step procedure. The first step involved editing the MRI to remove skull and extracranial tissue using the T2weighted image, and an initial segmentation of cerebral tissues into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) of the T1weighted image. Segmentation of cerebral tissue was performed using an automated method included in the SPM2 (Statistical Parametric Mapping) program (Ashburner and Friston, 1997). The method performs a cluster analysis with a modified mixture model and a priori information about the likelihood of each MRI voxel being one of 4 tissue types: GM, WM, CSF, and bother tissues.Q The a priori information consists of anatomical templates that represent an daverageT brain and provides information about the spatial distribution of the different brain tissues. The algorithm also removes the effect of radiofrequency field inhomogeneities (Ashburner and Friston, 2000). This segmentation was checked for inconsistencies and manually corrected whenever necessary by an experienced radiologist blind to the diagnosis. In a second stage, we applied the Talairach reference system (Talairach and Tournoux, 1988) to define regions of interest (ROIs) and to
obtain volume data. MRI processing was performed using locally developed software that incorporates a variety of image processing and quantification tools (Desco et al., 2001). The validity of the Talairachbased procedure as a suitable automated segmentation tool in schizophrenia research has been previously proven (Andreasen et al., 1996; Ho et al., 2003; Kates et al., 1999). In our study, all manual procedures were performed by a single operator, thus avoiding any potential inter-rater variability. Reliability of the method was assessed by repeating the entire segmentation procedure in a sample of 5 randomly selected cases. ICC values ranged from 0.95 to 0.99 for regional GM and WM measurements, and from 0.89 to 0.99 for CSF data. Again, all manual procedures were performed by a single operator, thus avoiding any potential inter-rater variability. Repeatability of the tissue segmentation procedure was 99% for total volumes of gray and white tissue (Chard et al., 2002; Gispert et al., 2004). In addition to total volumes of GM and WM, the analysis included the frontal, parietal, temporal and occipital lobes, defined using the boundaries described previously for the Talairach method (Andreasen et al., 1996). ROIs were measured bilaterally, adding the left and right sides together. Intracranial volume (ICV) was calculated by adding total
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GM, WM, and CSF for each brain (including the cerebellum). 2.3. Statistical analysis Improvement in the three symptom dimensions was studied using Wilcoxon tests for paired samples, comparing the scores before and after the treatment period. 2.3.1. Gross change in volume The longitudinal change in volume was measured as the difference between the initial and final volume of each ROI. To avoid bias due to overall differences in brain size, instead of absolute change values in cc, we used a quotient for total volume of the corresponding ROI. On the other hand, to control for any potential difference between the two scans due to updates of MRI equipment, we calculated a correction factor as a quotient between the initial (baseline) and final intracranial volume (ICV) (E ICV = ICV1 / ICV2), assuming that the total ICV should be equal in both scans (Mathalon et al., 2001). Thus, for each ROI, the magnitude of the relative change in volume between the baseline (Vol1) and final (Vol2) MRI was calculated as follows: Longitudinal change
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models obtained from a group of healthy individuals (n = 31, 17 males), following the procedure of Pfefferbaum et al. (1992). After this correction, volume variables were expressed as deviations from the expected volumes in healthy individuals of the same age as the patient. Thus, negative residuals represent a quantitative measurement of atrophy and vice versa. The regression parameters used for this transformation were obtained from a previous study (Molina et al., 2003b). To analyze the relationship between baseline alterations and longitudinal changes, we calculated the coefficient of correlation (Spearman’s q) between the converted baseline and final GM and WM volume change in the regions with significant longitudinal changes in volume. 2.3.3. Sources of error Of the possible sources of error that potentially affected our results, we found that gender did not affect the measurement of longitudinal changes, since there were no significant differences between men and women in the Mann–Whitney test. Nor did we find any relationship between longitudinal changes in weight and volume, using a Spearman correlation. This relationship was not significant whether each group of patients was analyzed separately or together. Statistical analysis was done using the SPSS software package (version 11).
¼ ½ððVol2 EICV Þ Vol1Þ=Vol1 100 The significance of the differences in the longitudinal change in GM and WM between the patient groups and the controls was analyzed for each ROI using a Mann–Whitney test. The total GM and WM volume was also analyzed, but we did not include data on changes in CSF volume, since those are secondary to the changes in GM or WM volume. 2.3.2. Measurement of baseline atrophy / hypertrophy To evaluate the hypothesis of a relationship between the degree of initial volume alteration and the magnitude of longitudinal change, we converted the volume values to directly indicate a condition of atrophy/hypertrophy as compared to healthy subjects, independent of factors such as age and ICV. Since age and total cranial size are known factors affecting regional cerebral volumes, their effect was removed by using the residuals from the regression
3. Results 3.1. Change in symptoms The group of NN patients presented a significant improvement in positive symptoms (z = 2.9, n = 17, p = .002). There were no significant differences in the disorganization or negative dimensions. The weight of these patients increased significantly (mean 8.5 kg, SD 9.0, t = 2.8, p = .02). In the CR group, the positive dimension (z = 2.3, n = 12, p = .01) and the disorganization dimension (z = 2.1, n = 12, p = .02) improved significantly, but the negative dimension did not. The weight of this group of patients also increased significantly (mean 3.1 kg, SD 4.3, t = 2.0, n = 12, p = .05). 3.2. Gross longitudinal changes There was no significant change in total brain volume (GM plus WM total volume; Table 2) in either group.
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Table 2 Regional volumes in the three groups and their corresponding longitudinal changes
ICV Total brain Total GM Total WM Frontal GM Frontal WM Parietal GM Parietal WM Temporal GM Temporal WM Occipital GM Occipital WM
Chronic patients (n = 12)
N. naive patients (n = 17)
Controls (n = 11)
Baseline (cc)
% change from baseline
Baseline (cc)
% change from baseline
Baseline (cc)
% change from baseline
1463.8 1021.7 733.0 455.7 132.8 112.2 107.7 118.6 138.3 68.1 61.2 50.8
1.3 1.0 4.2 9.0 6.8 7.6 7.3 7.6 1.7 6.4 14.9 9.0
1509.9 1086.4 816.7 438.7 154.3 109.6 120.7 111.7 149.7 68.0 68.4 46.9
0.3 1.3 1.0 3.1 2.7 1.5 1.2 2.6 1.6 5.0 6.2 4.1
1458.2 1038.6 798.9 406.4 154.9 104.8 117.6 110.4 148.2 59.9 68.3 43.2
2.3 0.5 0.5 2.3 0.0 1.7 3.5 4.0 1.2 0.2 1.4 2.9
(113.8) (63.2) (61.2)*** (41.2)* (12.2)*** (12.7) (12.1)*** (12.1)* (10.8)** (7.5) (6.9)*** (5.6)***
(1.9) (4.1) (5.7)* (5.9)*** (8.5)* (6.6)** (11.2)** (7.7)*** (8.3) (10.1) (12.0)*** (7.6)**
(117.6) (96.7) (56.8) (57.6) (12.2)* (15.7) (10.9) (16.6) (10.0) (10.8) (9.1)* (6.9)
(1.6) (3.2) (2.6) (5.0)** (4.8) (6.6) (7.8)* (6.9) (4.3) (7.3) (10.1)* (8.8)*
(123.5) (109.9) (71.9) (54.3) (17.6) (18.4) (17.0) (18.4) (8.4) (6.5) (9.5) (7.8)
(1.8) (3.8) (2.5) (4.8) (4.0) (6.7) (3.6) (7.4) (3.3) (6.5) (6.1) (8.0)
Baseline data expressed as mean (SD) in cc. Change in each structure is expressed as mean (SD) percent of the initial volume of the structure, corrected for intracranial volume (see Methods section). Significance of differences in longitudinal changes between each group of patients and controls and of baseline volume differences relative to expected values from normal populations appear in the corresponding columns of each patient group (see Methods section) (Mann–Whitney test). *p b 0.05; **p b 0.01; ***p b .001.
In the control group, there was a small decrease in GM volume and an increase in WM volume (Table 2, Fig. 2), which followed the pattern expected in healthy individuals (Bartzokis et al., 2001; Coffey et al., 1992; Sowell et al., 2003). This change was not statistically significant (using a t test for one sample, with the null hypothesis of no change), except for the change in parietal GM, which decreased significantly (t = 3.14, p = .01). The group of NN patients presented a significant increase in occipital (U = 47, z = 2.2, p = .02) and parietal (U = 53, z = 1.9, p = .05) GM compared to the healthy individuals. The changes in total GM (U = 56, z = 1.8, p = .08) did not achieve statistical significance, but were in the same direction (Fig. 2). These patients also presented a decrease in total (U = 41, z = 2.4, p = .01) and occipital (U = 48, z = 2.2, p = .03) WM compared to the control group (Table 2, Fig. 2). The group of CR patients presented significant increases in total (U = 30, z = 2.2, p = .02), frontal (U = 33, z = 2.0, p = .04), parietal (U = 21, z = 2.9, p = .004), and occipital (U = 14, z = 3.2, p = .001) GM compared to the controls. In addition, they presented total (U = 3, z = 3.9, p b .001), frontal (U = 20, z = 2.8, p = .004), parietal (U = 16, z = 3.1, p = .001), and occipital (U = 19, z = 2.9, p = .003) WM decreases compared to the controls (Table 2, Fig. 2). 3.3. Longitudinal changes in degree of baseline alterations 3.3.1. Baseline alterations Compared to the expected values in a normal population (see Methods), the NN group presented a statistically sig-
nificant baseline deficit in frontal (U = 246, z = 2.2, p = .03) and occipital (U = 247, z = 2.1, p = .03) GM, but no alterations in WM (Table 2). At baseline, the CR group presented a statistically significant deficit in total (U = 72, z = 4.1, p b .001), frontal (U = 57, z = 4.4, p b .001), parietal (U = 41, z = 4.7, p b .001), temporal (U = 126, z = 3.1, p = .002), and occipital (U = 40, z = 4.7, p b .001) GM, along with an excess in total (U = 125, z = 2.2, p = .03), parietal (U = 122, z = 2.8, p = .03), and occipital (U = 98, z = 3.6, p b .001) WM (Table 2). 3.3.2. Relationship between longitudinal change and degree of baseline alteration In the NN patients, there was a significant inverse relationship (q = .56, p = .02) between the total increase in GM and the baseline deficit, using volume data adjusted for age and ICV. In other words, the greater the initial deficit, the greater the increase in GM. The relationship between the baseline deficit in parietal GM and its change was also significant (q = .80, p b .001). In addition, in these patients, there was a significant relationship between initial WM volume and its change in the total (q = .77, p b .001) and occipital (q = .70, p = .002) regions (the greater the initial excess, the greater the longitudinal decrease). In the CR group, there was also a significant relationship between the baseline alteration and changes in GM in the occipital region (q = .57, p = .05). For total, parietal, and frontal GM, this relationship was not significant. In this group, there was also a significant inverse relationship between the baseline volume and changes in WM in all
V. Molina et al. / Schizophrenia Research 80 (2005) 61–71 30
30
% C h a n g e
C h a n g e
22
14
6
P a r i e t .
–2
C h a n g e
20
10
0
T e m p o r .
–10
C h a n g e
12
4
C h a n g e
6
–4
P a r i e t .
F r o n t –12 a l –20 Chronics
N. Naive
Controls
O c c i p t .
–10
-6
T e m p o r .
-18
-30 Chronics
N. Naive
Controls
16
4
–8
–20 Chronics N. Naive
Controls
20
% C h a n g e
18
6
W M
W M
W M
0
30
18
28
G M
%
%
%
10
–20 Chronics N. Naive Controls
Controls
30
20
C h a n g e
20
G M
–20 Chronics N. Naive
Controls
%
%
G M
–10 Chronics N. Naive
C h a n g e
40 30
%
G M F r o n t a l
67
10
0
W M –6
O c c i p t .
–18
–30 Chronics
N. Naive
Controls
–10
–20
–30 Chronics
N. Naive
Controls
Fig. 2. Scatter plots of changes in GM and WM in the four lobes. Values represent percentage of change in the corresponding structure, once corrected for the change in ICV between the two MRI studies (see Methods). Bars show standard error for each group.
regions. In other words, the greater the baseline volume excess of WM, the more negative the change (greater decrease) in the total (q = .75, p = .005), frontal (q = .83, p = .001), parietal (q = .74, p = .006), and occipital (q = .84, p = .001) regions. Analyzing the entire patient sample together, we found significant correlations between a baseline deficit in GM and the longitudinal increase in total (q = .62, n = 29, p b .001), frontal (q = .45, n = 29, p = .01), parietal (q = .74, n = 29, p b .001), and occipital (q = .51, n = 29, p = .004) volumes. On the other hand, in the control group, we found no significant relationship between the baseline volumes and their longitudinal change.
4. Discussion In the current study, an increase in gray matter and decrease in white matter volume occurred in patients with schizophrenia after treatment with clozapine or risperidone. These changes were more marked in the chronic clozapine-treated group. Furthermore, the
increase in gray matter was not statistically associated with an increase in weight. However, these longitudinal changes in volume were related to the degree of baseline structural alteration. In other words, the greater the gray matter (GM) deficit, the greater the change after treatment with risperidone or clozapine. The observed longitudinal effect suggests a diffuse increase in cortical GM volumes with clozapine and risperidone. In both treatment groups, the most marked GM gain was observed in the occipital region. The location of this longitudinal effect is consistent with the most significant metabolic change observed with positron emission tomography (PET) in a sample including most of the patients participating in the present study (Molina et al., 2005a, 2003a). In these studies, metabolic activity in the visual area (at rest with eyes open) increased in recent-onset and chronic patients treated with risperidone or clozapine, respectively. Similar gains in GM with atypical neuroleptics have been previously reported. In a study of GM changes (frontal cortex only) in adolescents with
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V. Molina et al. / Schizophrenia Research 80 (2005) 61–71
schizophrenia (n = 16, mean age at baseline = 18), a 1.9% increase was reported after 2 years of treatment with atypical drugs (James et al., 2004). That change did not reach statistical significance, perhaps due to the small sample size. Another study performed in first-episode adults described frontal and temporal GM deficits in patients treated with typical drugs for 8 weeks (n = 32) compared to untreated patients (n = 22), while another group of patients treated with atypical drugs (n = 30) presented a thalamic GM excess with no cortical deficit compared to the same untreated group (Dazzan et al., 2004). Longitudinal studies in patients treated exclusively with typical neuroleptics have reported a significant decrease in frontal GM volume (Gur et al., 1998; Mathalon et al., 2001) or hemispheric volume (DeLisi et al., 1997). However, more recent studies, in which some patients were treated with atypical and others with typical neuroleptics, have found no decrease in GM (Dazzan et al., 2004; DeLisi et al., 2004; Ho et al., 2003), with the possible exception of juvenile onset cases (Gogtay et al., 2004). Moreover, our findings are consistent with a study of first-episode patients, which reported that haloperidol-treated patients exhibited significant decreases in GM volume, whereas patients receiving olanzapine showed no significant volume changes (Lieberman et al., 2005). Although the morphologic outcomes were similar in both groups of patients, the gain in GM was greater in the CR group during treatment with clozapine (Table 2, Fig. 2). The relationship between prior degree of structural alteration and treatment-induced change suggests that the greater gain in GM with this drug may be related to the greater initial atrophy in these patients. Our results suggest that such atrophy may be reversible, as previously reported in other ROIs (Keshavan et al., 1998). In a recent study by Dorph-Petersen et al. (2005), macaque monkeys were administered haloperidol or olanzapine for 17 to 27 months to investigate the macroscopic effects of antipsychotics on the brain. They found that both treatments produced a slight, but significant decrease in brain weight and volume, more pronounced in the frontal and parietal regions. However, these results can only be partially associated with our findings because, in their study, both gray and white matter volumes were reduced in treated monkeys compared to controls. This inconsistency may
originate from the higher doses of neuroleptics administered to monkeys to achieve plasma levels similar to those in humans. Moreover, we cannot conclude that the human brain would show the same changes as in monkeys, especially in the case of cerebral illness. In support of this, the association in our patients between basal GM deficit and volume increase with clozapine and risperidone suggests that, in the absence of such a basal deficit, the outcome would have been different. Finally, different treatments (olanzapine and haloperidol versus risperidone and clozapine) might have had different effects on brain morphology. Even though our data suggest that the GM increase was due to the atypical treatment, we cannot be certain of this, since we did not study the outcome in similar groups of patients not treated with atypical neuroleptics. Among other limitations of the study, not all of our chronic patients received the same treatment prior to enrollment in the study and the initiation of clozapine, although all received haloperidol during the preceding month. Therefore, our results could be affected by the withdrawal of drugs received prior to clozapine. However, this problem does not affect the NN patient sample, which presented a similar pattern of changes. Another important limitation was the small sample size, partially offset by a more statistically powerful longitudinal design. In particular, the number of controls was small; however, the observed changes in volume followed the longitudinal pattern expected in the general population (Bartzokis et al., 2001; Coffey et al., 1992; Sowell et al., 2003). We can not rule out the possibility that the observed volumetric differences in this study were not a consequence of treatment and could, instead, be caused by an as-yet unknown epiphenomenon, either related to subject metabolic changes or to MRI scanner artifacts during the longitudinal period of this study. The assertion that atypical neuroleptics have an effect on brain volume has yet to be definitively demonstrated. However, even if we are observing true effects of the medication, we can only speculate about the potential cellular processes underlying the changes observed in the cortex. Relying upon histological data from studies performed in rats and monkeys, two possible explanations arise: proliferation of neuronal elements or of glial cells. Concerning the first, formation of new neuronal elements, such as
V. Molina et al. / Schizophrenia Research 80 (2005) 61–71
synapses, seems more likely than neurogenesis in the adult brain. Synaptogenesis may be indeed an effect of classical treatment in subcortical regions (Konradi and Heckers, 2001). However, a huge increase in connections would be required to explain a GM volume increase capable of MRI detection. On the other hand, in primate cortices, there was no increase of neuronal tissue after treatment with typical or atypical neuroleptics (Selemon et al., 1999). However, another study showed that clozapine induced cell division in the hippocampus, though the resulting neurons did not survive 3 weeks (Halim et al., 2004). Thus, it seems unlikely that the increase in GM observed in our patients was caused by the appearance of new neurons or increased connections. Regarding changes in the glia, proliferation of cells, along with cortical hypertrophy, has been observed in the prefrontal cortex of primates after treatment with typical and atypical neuroleptics (Selemon et al., 1999). Moreover, olanzapine can increase the number of dividing glial cells in the frontal cortex in adult rats (Wang et al., 2004). A similar effect of atypical neuroleptics on glial cells would also be consistent with the increased brain metabolic activity observed in our patients (Molina et al., 2005a; Molina et al., 2003a), given the role of glial cells in PET data (Magistretti, 2000). At any rate, more specific data are needed to demonstrate the histological substrate of the GM changes observed in our study. The co-occurrence of GM increase and WM decrease is consistent with the recent finding of a decrease in WM after four weeks of typical or atypical treatment (Christensen et al., 2004). This WM decrease suggests that GM increase is not due to the production of new healthy cells, as the WM is partly formed by the extension of such cells. The decrease in WM due to atypical treatment could be explained by a blockade of factors stimulating myelin synthesis, the other WM component. We could speculate that such a factor could have to do with a chronic glutamatergic hyperactivation state, since hyperactivity relates to increased myelination in other disease states (Adamsbaum et al., 1996; Krishnan et al., 1994). Such a hyperactivity state might be present in schizophrenia (Molina et al., 2005b; Volk and Lewis, 2002). In summary, the present study found brain gray matter increases and white matter decreases following
69
treatment with atypical drugs such as risperidone and clozapine in chronic and neuroleptic-naı¨ve patients. While these changes could be associated with the effects of these drugs on the brain, this phenomenon needs further exploration before this conclusion can be reached. We cannot be sure that the changes observed in our group were solely due to the atypical treatment, as we did not have a control group of patients treated without atypical neuroleptics over the same period of time.
Acknowledgments Supported in part by grants from the bFondo de Investigaciones SanitariasQ (02/3095, Red Tema´tica IM3), bG03/185Q and bFundacio´n La CaixaQ (99/04200). We thank Angel Santos Briz, pathologist from the Neuroscience Institute of Castilla y Leo´n, for his valuable assistance in data interpretation.
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