Neuroscience Letters 579 (2014) 7–11
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Altered structural connectivity and trait anhedonia in patients with schizophrenia Jung Suk Lee a,b , Kiwan Han a , Seung-Koo Lee c , Jeong-Ho Seok a,d , Jae-Jin Kim a,c,d,∗ a
Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea Department of Psychiatry, Bundang Jesaeng Hospital, Seongnam, Gyeonggi, Republic of Korea Department of Radiology, Yonsei University College of Medicine, Seoul, Republic of Korea d Department of Psychiatry, Yonsei University College of Medicine, Seoul, Republic of Korea b c
h i g h l i g h t s • The FA in the left cingulum and SLF were positively correlated with trait anhedonia. • The FA in the reward system was not correlated with trait anhedonia. • Alterations in connectivity within the DMN and CEN may be a basis of trait anhedonia.
a r t i c l e
i n f o
Article history: Received 4 April 2014 Received in revised form 21 May 2014 Accepted 1 July 2014 Available online 10 July 2014 Keywords: Schizophrenia Trait anhedonia Diffusion tensor imaging Cingulum Superior longitudinal fasciculus
a b s t r a c t This study tested association between anhedonia scores and white matter integrity in order to investigate the neural basis of trait anhedonia in schizophrenia. A total of 31 patients with schizophrenia and 33 healthy controls underwent diffusion weighted imaging and scoring of trait anhedonia using the Physical Anhedonia Scale. Using tract-based spatial statistics, we found that fractional anisotropy values of some white matter regions were differently correlated with Physical Anhedonia Scale scores between the two groups. The white matter regions that were more significantly correlated with trait anhedonia in patients than in controls included the left side of the cingulum, splenium of the corpus callosum, inferior longitudinal fasciculus, superior longitudinal fasciculus I and II, anterior thalamic radiation, and optic radiation. Of these regions, fractional anisotropy values in the cingulum and superior longitudinal fasciculus II were positively correlated with trait anhedonia in patients with schizophrenia. These findings suggest that alterations in structural connectivity within large-scale brain networks, including the default mode and central executive networks, may contribute to the development of trait anhedonia in patients with schizophrenia. © 2014 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Disrupted connections within and between brain regions have been implicated as a central abnormality in schizophrenia [1]. In particular, growing evidence has suggested that alterations in white matter organization may play an important role in this disconnection [2]. Diffusion tensor imaging (DTI) has enabled in vivo study of white matter alterations in patients with schizophrenia. Among the measures that reflect white matter properties, fractional
∗ Corresponding author at: Department of Psychiatry, Yonsei University, Gangnam Severance Hospital, 211 Eonjuro, Gangnam-gu, Seoul 135-720, Korea. Tel.: +82 2 2019 3341; fax: +82 2 3462 4304. E-mail address: [email protected] (J.-J. Kim). http://dx.doi.org/10.1016/j.neulet.2014.07.001 0304-3940/© 2014 Elsevier Ireland Ltd. All rights reserved.
anisotropy (FA), the extent to which water diffusion is directiondependent within the tissue microstructure, is the most widely used parameter [3]. FA has been reported to reflect the structural integrity of fibers, degree of myelination, and fiber coherence as decreases in FA imply damage of the myelin or axons and/or loss of coherence [3]. White matter disruptions measured by FA are widespread throughout the brain in schizophrenia, particularly in frontal and temporal regions [4]. Although most studies revealed decreased FA, some studies found increased FA in specific white matter tracts in patients with schizophrenia, compared to controls [3]. These findings of increased FA in schizophrenia were thought to reflect hyperconnectivity [5] or deficient axonal pruning [6]. Furthermore, studies using DTI have shown that white matter abnormalities are associated with specific symptoms of schizophrenia. For example, FA values of the superior longitudinal
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fasciculus were correlated with the severity of auditory hallucinations in schizophrenia [7]. Anhedonia, or reduced capacity to experience pleasure, is one of the cardinal symptoms of schizophrenia [8]. As a component of negative symptoms, anhedonia is a significant determinant of functional capacity and long-term outcome in schizophrenia [9]. The Physical Anhedonia Scale [10], which measures the extent of a decreased capacity to enjoy physical sensations, has been regarded as the standard anhedonia questionnaire in the field of psychiatry [11]. Anhedonia scores measured by the Physical Anhedonia Scale have been shown to be consistently elevated in patients with schizophrenia and have thus been identified as a trait of schizophrenia [12]. Recent neuroimaging studies have revealed that abnormalities in several brain networks in patients with schizophrenia are related to anhedonia. The reward system is known to be associated with responses to rewarding or pleasurable stimuli, and it comprises a network of brain regions including the ventral tegmental area, ventral striatum, amygdala, and orbitofrontal cortex [13]. Reduced activation in key structures of the reward system such as the ventral striatum [14–16], amygdala [14], and orbitofrontal cortex [15] have been related to more severe anhedonia. In addition, our group found that functional and structural abnormalities in the default mode network (DMN) were related to trait anhedonia in schizophrenia [17,18]. The DMN includes the ventromedial prefrontal cortex and posterior cingulate/retrosplenial cortex and is known to be responsible for self-referential processing [19]. Therefore, it was suggested to be involved in the self-referential aspect of anhedonia [17]. Considering that these brain networks require coordinated functioning of gray matter regions, it is possible that anhedonia may be the result of disrupted connectivity between gray matter regions. To date, however, the relationship between trait anhedonia and white matter abnormality has not been investigated in patients with schizophrenia. This study was designed to investigate whether white matter alterations are associated with trait anhedonia in patients with schizophrenia. We used the Physical Anhedonia Scale to evaluate trait anhedonia and utilized FA values from DTI data as an index of the white matter integrity. We hypothesized that disruptions in white matter tracts connecting gray matter regions in the reward system and DMN are related to trait anhedonia in patients with schizophrenia.
Physical Anhedonia Scale scores than controls (patients: 19.6 ± 9.3, controls: 11.9 ± 7.2, t = 3.8, df = 62, p < 0.001). Clinical symptoms of patients were rated using the Positive and Negative Syndrome Scale (PANSS) [21], and the mean ratings of positive, negative, and general symptom subscale scores were 15.7 ± 6.6, 16.6 ± 6.3, and 31.3 ± 10.9, respectively. The study was approved by the institutional review board, and written informed consent was obtained from all participants. 2.2. Magnetic resonance imaging MR images were acquired using a Philips 3T scanner (Intra Achieva; Philips Medical System, Best, The Netherlands). Head motion was minimized with restraining foam pads provided by the manufacturer. Diffusion-encoded images parallel to the anterior commissure–posterior commissure line were obtained using a single-shot echo-planar acquisition with the following parameters: 128 × 128 acquisition matrix, 224-mm field of view, 1.72 × 1.72 × 2 mm3 voxels, 70 axial slices, TE 71 ms, TR 7196 ms, flip angle 90◦ , slice gap 0 mm, 1 averaging per slice, b-factor of 600 s mm−2 , and non-cardiac gating. Diffusion-weighted images were acquired from 32 different directions with the baseline image obtained without diffusion weighting. 2.3. Image processing Diffusion-weighted images were preprocessed using the FMRIB Software Library (FSL) 5.0.6 (http://www.fmrib.ox.ac.uk/fsl) [22]. Source data were corrected for eddy currents and head motion. FA maps were first created for each subject using the FSL. A voxelwise statistical analysis of FA data was carried out using Tract-Based Spatial Statistics (TBSS, version 1.2) [23] implemented in the FSL. The FA data were aligned into 1 mm × 1 mm × 1 mm Montreal Neurological Institute (MNI) 152 spaces using the FMRIB’s Nonlinear Image Registration Tool (FNIRT). Then, a mean FA image (threshold of 0.2) was created and narrowed to create a mean FA skeleton, taking only the centers of white matter tracts common to all subjects. Voxel value for the FA data of each subject was then projected onto this skeleton, and resulting data were used in the following voxelwise statistical analyses. 2.4. Statistical analysis
2. Methods 2.1. Subjects Thirty-one patients with schizophrenia (including 17 males) and 33 healthy volunteers (including 14 males) participated in this study. The two groups had no significant difference in gender or age (30.7 ± 5.9 years and 31.0 ± 7.0 years, respectively). The diagnosis of schizophrenia in patients and the exclusion of any psychiatric disorders in controls were made using the Structural Clinical Interview for the Diagnostic and Statistical Manual (DSM-IV) [20]. All participants were right-handed, and none reported any past or present medical or neurological illness or drug or alcohol abuse. The mean years of education in patients and controls (13.4 ± 2.1 years and 15.7 ± 2.6 years, respectively) were significantly different (t = −3.8, df = 62, p < 0.001). The mean duration of illness in patients was 8.1 ± 6.7 years. All patients were taking one or two antipsychotic medications, and the mean chlorpromazine-equivalent dose was 398.4 ± 409.8 mg. Trait anhedonia was assessed with the Physical Anhedonia Scale [10], which comprised 61 true or false questions, with higher scores representing more severe anhedonia. Patients had significantly higher
Voxelwise statistics were conducted with FSL Randomize program using permutation-based statistical analysis with 5000 permutations. To investigate possible confounding effects, associations in education level with FA values were tested by regression model in FSL in patients and controls, separately. In patients, association of antipsychotic doses with FA values was also tested. Then, we found that fractional anisotropy values of some white matter regions were differently correlated with Physical Anhedonia Scale scores between the two groups. FA values were regressed on anhedonia scores, along with group variable. For each voxel, the interaction between anhedonia scores and group variable was tested. Significant interaction indicates that the linear relationship between FA values and anhedonia scores significantly differs between the two groups. The results were corrected for multiple comparisons using the threshold-free cluster enhancement (TFCE) method. The threshold for significance was set at p < 0.05. To further elucidate the clinical meaning of the findings, we calculated Pearson’s correlations between regional FA values and anhedonia scores in patients and controls, separately. The regions showing a significant interaction between anhedonia scores and group variable were selected for this analysis.
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Table 1 White matter regions in which fractional anisotropy (FA) values showed significantly higher correlation with trait anhedonia in patients than in controls and the corresponding correlation coefficients between regional FA values and trait anhedonia in each group. Regions
L anterior thalamic radiation L inferior longitudinal fasciculus L splenium of corpus callosum L optic radiation L superior longitudinal fasciculus I L superior longitudinal fasciculus II L cingulum
Cluster characteristics Cluster size
p
44 4574 98 41 334 388 142
0.045 0.003 0.039 0.047 0.010 0.026 0.044
Correlation coefficient with trait anhedonia (p) MNI coordinates x
y
z
−31 −46 −11 −19 −18 −24 −26
41 −16 −39 −61 15 −60 −63
5 −7 18 −1 43 28 0
Patients
Controls
0.18 (0.38) 0.08 (0.71) 0.14 (0.50) 0.24 (0.22) 0.37 (0.06) 0.40 (0.04* ) 0.47 (0.01* )
0.12 (0.51) 0.05 (0.78) −0.13 (0.48) −0.05 (0.80) −0.05 (0.77) −0.42 (0.02* ) 0.12 (0.36)
MNI: Montreal Neurological Institute, R: right, and L: left. a p-Values are corrected for multiple comparisons using the threshold-free cluster enhancement (TFCE) method. * p < 0.05.
3. Results There was no white matter region that showed a significant correlation with years of education in patients and controls and with antipsychotic doses in patients. Significant interaction between anhedonia scores and group variable was found in seven white matter regions. More specifically, FA values in these white matter regions of patients showed higher correlations with anhedonia scores than those of controls (Table 1). These regions included the left side of the cingulum, splenium of the corpus callosum, inferior longitudinal fasciculus, superior longitudinal fasciculus I, superior longitudinal fasciculus II, anterior thalamic radiation, and optic radiation. There was no white matter region that showed significantly lower correlations with anhedonia scores in patients than in controls. For correlation analysis, FA values in the left cingulum and anhedonia scores were positively correlated in patients (r = 0.47, p = 0.01), but were not significantly correlated in controls (Fig. 1). FA values in the left superior longitudinal fasciculus II and anhedonia scores were positively correlated in patients (r = 0.40, p = 0.04), whereas they were negatively correlated in controls (r = −0.42, p = 0.02). There was no significant correlation between FA values and anhedonia scores in any other white matter regions in either group. 4. Discussion To the best of our knowledge, this is the first study to examine the relationship between trait anhedonia and white matter alterations in schizophrenia. The results suggest that abnormalities in two white matter regions may play an important role in trait anhedonia in schizophrenia; FA values in the left cingulum and superior longitudinal fasciculus II were positively correlated with Physical Anhedonia Scale scores in patients. Interestingly, anhedonia-related white matter regions were confined to the left hemisphere. This finding is consistent with a previous study that reported that patients with negative symptoms might show left-sided functional impairments [24]. This is also supported by the findings that left-sided activation of the prefrontal cortex was more involved in goal-directed or appetitive behaviors, whereas right sided activation was implicated in avoidance behavior [25]. However, this finding contrasts with the finding of a previous study that showed that reduced FA in deficit schizophrenic patients was restricted to the right hemisphere [26]. Thus, further studies are needed to determine if white matter tracts in the left or right hemisphere are more highly related to trait anhedonia. Consistent with our hypothesis, FA values in the left cingulum showed a positive correlation with anhedonia scores in patients. The cingulum is known to play an important role in
connecting regions of the DMN including the medial prefrontal cortex and posterior cingulate cortex [27]. This is in line with previous findings that patients with schizophrenia showed increased functional connectivity of the DMN; greater DMN connectivity was correlated with more severe schizophrenic psychopathology [28–30]. Relatively high FA within the cingulum may reflect greater connectivity within the DMN [5], thus leading to hyperactivation of the DMN. Because the DMN may be involved in self-referential processing [19], hyperactivation of the DMN may cause excessive self-referential processing and exaggerated selfconsciousness. According to Sass and Parnas [31], exaggerated self-consciousness was proposed to be a possible cause of anhedonia in schizophrenia and a main aspect of self-disorder, which is regarded as the core abnormality of schizophrenia and characterized by complementary distortions of the act of awareness. Hyperactivation of the DMN may also be relevant to the impairment in emotional experience or anhedonia in schizophrenia because the DMN is normally deactivated during cognitive tasks [19]. The relationship between increased FA in the cingulum and trait anhedonia is partly supported by a previous DTI study [32] showing that FA values in the cingulum were inversely correlated with the activity level, which may reflect negative symptoms of schizophrenia [33]. FA values in the left superior longitudinal fasciculus II and anhedonia scores were also positively correlated in patients, whereas they were negatively correlated in controls. The superior longitudinal fasciculus II forms the connection between the inferior parietal lobule and dorsolateral prefrontal cortex [34]. These two structures together form the central-executive network (CEN), which is crucial for the active maintenance and manipulation of information in working memory and for decision making in the context of goaldirected behavior [35]. Because executive functioning impairments were found to be related to anhedonia in patients with schizophrenia [36] and healthy controls [37], it is plausible that abnormalities in structural connectivity between the inferior parietal lobule and dorsolateral prefrontal cortex may be a contributing factor to trait anhedonia in both patients and controls. However, the opposite direction of the correlations (i.e., positive in patients and negative in controls) between FA values in the superior longitudinal fasciculus II and anhedonia scores might indicate that the underlying mechanisms of the correlations are different for the two groups. Because reduction of FA values is interpreted as disruption of the tissue structure [4], the negative correlation in controls would imply that white matter microstructural disorganization in the CEN might contribute to anhedonia in healthy controls, whereas the positive correlation in patients may be considered in terms of deficient axonal pruning. A previous study suggested that increased FA in schizophrenia might reflect aberrant axonal pruning through neurodevelopment leading to inefficient/redundant neural networks [6]. Since redundant neural networks might indicate decreased
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Fig. 1. Correlations between regional fractional anisotropy (FA) values and Physical Anhedonia Scale scores in patients and controls. FA values in the left cingulum (A) and superior longitudinal fasciculus II (B) were positively correlated with Physical Anhedonia Scale scores in patients. To aid in visualization, results are highlighted using the TBSS fill script implemented in FSL (red–yellow). Results are shown overlaid on the Montreal Neurological Institute 1-mm template and the mean FA skeleton (green). Left–right orientation is according to radiological convention; * p < 0.05. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
efficiency in information transmission [6], a possible interpretation of positive correlation in patients is that increased FA in white matter tract connecting the inferior parietal lobule and dorsolateral prefrontal cortex may lead to deficient information transmission of the tract, thus further contributing to executive dysfunctions. It is interesting to note that white matter tracts correlating with trait anhedonia in schizophrenia in our study were different from those related to negative symptoms in other studies. Negative symptom scores in patients with schizophrenia have been reported to be correlated with white matter disruptions in the insula [38,39], inferior fronto-occipital fasciculus [5], and fornix [40]. This discrepancy may be because the structure of negative symptoms in schizophrenia is not unidimensional [41]. Factor analytic studies demonstrated that the most consistently emerged factors for negative symptoms in schizophrenia are diminished expression/blunted affect and anhedonia/asociality factors [41], suggesting that some symptoms belonging to negative symptoms might have little relationship with anhedonia. An alternative interpretation is that this discrepancy may reflect measurement differences. For example, negative symptoms in the PANSS are measured by raters on the basis of observation of behaviors and reports
from care-givers, while the Physical Anhedonia Scale relies on selfreports from patients [11]. Contrary to our expectations, FA values in white matter regions related to the reward system were not correlated with trait anhedonia in patients. This finding suggests that trait anhedonia in schizophrenia may not be related to alterations in white matter tracts connecting with the reward system but rather functional deficits in gray matter regions of the reward system [14–16]. Another possibility is that differences in the methods for analyzing DTI data may account for this finding. Previous DTI studies of patients showed FA reduction in white matter pathways related to the reward system, such as the anterior limb of the internal capsule [42], anterior thalamic radiation [43], and fornix [44]. Because these studies used methods such as region of interest or tractography approaches, limitations of TBSS [23] in analyzing small fiber tracts, data with within-scan head motion, and regions of crossing fibers or tract junctions may be relevant to this finding. Several limitations should be considered in our study. First, all patients were taking antipsychotic medications. Although no regional FA values were significantly correlated with antipsychotic doses in patients, the possibility of confounding effects due to antipsychotic use could not be excluded. To address the effect
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of antipsychotics on white matter structure, systematic studies with a larger sample size designed to investigate the relationships between FA and medication are needed. Second, depressive symptoms were not evaluated in this study. Because depression was correlated with trait anhedonia in patients with schizophrenia [45], further studies including the assessment of depressive symptoms are also warranted. 5. Conclusions We found that white matter changes in the cingulum and superior longitudinal fasciculus II were related to trait anhedonia in schizophrenia. These findings suggest that alterations of structural connectivity within large-scale brain networks, including the DMN and CEN, may contribute to the development of anhedonia in schizophrenia. To elucidate the relationship between brain connectivity and trait anhedonia, further studies using other modalities such as functional MRI are needed. Acknowledgement This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MEST) (No. NRF-2013R1A2A2A03068342). References [1] J. Fitzsimmons, M. Kubicki, M.E. Shenton, Review of functional and anatomical brain connectivity findings in schizophrenia, Curr. Opin. Psychiatry 26 (2013) 172–187. [2] N. Takahashi, T. Sakurai, K.L. Davis, J.D. Buxbaum, Linking oligodendrocyte and myelin dysfunction to neurocircuitry abnormalities in schizophrenia, Prog. Neurobiol. 93 (2011) 13–24. [3] M. Kubicki, R. McCarley, C.F. Westin, H.J. Park, S. Maier, R. Kikinis, F.A. Jolesz, M.E. Shenton, A review of diffusion tensor imaging studies in schizophrenia, J. Psychiatr. Res. 41 (2007) 15–30. [4] M. Kyriakopoulos, T. Bargiotas, G.J. Barker, S. Frangou, Diffusion tensor imaging in schizophrenia, Eur. Psychiatry 23 (2008) 255–273. [5] S.H. Lee, M. Kubicki, T. Asami, L.J. Seidman, J.M. Goldstein, R.I. MesholamGately, R.W. McCarley, M.E. Shenton, Extensive white matter abnormalities in patients with first-episode schizophrenia: a Diffusion Tensor Imaging (DTI) study, Schizophr. Res. 143 (2013) 231–238. [6] L.M. Alba-Ferrara, G.A. de Erausquin, What does anisotropy measure? Insights from increased and decreased anisotropy in selective fiber tracts in schizophrenia, Front. Integr. Neurosci. 7 (9.) (2013). [7] J.H. Seok, H.J. Park, J.W. Chun, S.K. Lee, H.S. Cho, J.S. Kwon, J.J. Kim, White matter abnormalities associated with auditory hallucinations in schizophrenia: a combined study of voxel-based analyses of diffusion tensor imaging and structural magnetic resonance imaging, Psychiatry Res. Neuroimaging 156 (2007) 93–104. [8] J.J. Blanchard, K.T. Mueser, A.S. Bellack, Anhedonia, positive and negative affect, and social functioning in schizophrenia, Schizophr. Bull. 24 (1998) 413–424. [9] P. Milev, B.C. Ho, S. Arndt, N.C. Andreasen, Predictive values of neurocognition and negative symptoms on functional outcome in schizophrenia: a longitudinal first-episode study with 7-year follow-up, Am. J. Psychiatry 162 (2005) 495–506. [10] L.J. Chapman, J.P. Chapman, M.L. Raulin, Scales for physical and social anhedonia, J. Abnorm. Psychol. 85 (1976) 374–382. [11] W.P. Horan, A.M. Kring, J.J. Blanchard, Anhedonia in schizophrenia: a review of assessment strategies, Schizophr. Bull. 32 (2006) 259–273. [12] E.S. Herbener, M. Harrow, S.K. Hill, Change in the relationship between anhedonia and functional deficits over a 20-year period in individuals with schizophrenia, Schizophr. Res. 75 (2005) 97–105. [13] S.N. Haber, B. Knutson, The reward circuit: linking primate anatomy and human imaging, Neuropsychopharmacology 35 (2010) 4–26. [14] E.C. Dowd, D.M. Barch, Anhedonia and emotional experience in schizophrenia: neural and behavioral indicators, Biol. Psychiatry 67 (2010) 902–911. [15] P.O. Harvey, J. Armony, A. Malla, M. Lepage, Functional neural substrates of self-reported physical anhedonia in non-clinical individuals and in patients with schizophrenia, J. Psychiatr. Res. 44 (2010) 707–716. [16] J.S. Lee, J.W. Chun, J.I. Kang, D.I. Kang, H.J. Park, J.J. Kim, Hippocampus, nucleus accumbens activity during neutral word recognition related to trait physical anhedonia in patients with schizophrenia: an fMRI study, Psychiatry Res. Neuroimaging 203 (2012) 46–53. [17] I.H. Park, J.J. Kim, J. Chun, Y.C. Jung, J.H. Seok, H.J. Park, J.D. Lee, Medial prefrontal default-mode hypoactivity affecting trait physical anhedonia in schizophrenia, Psychiatry Res. Neuroimaging 171 (2009) 155–165.
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Altered structural connectivity and trait anhedonia in patients with schizophrenia Jung Suk Lee a,b , Kiwan Han a , Seung-Koo Lee c , Jeong-Ho Seok a,d , Jae-Jin Kim a,c,d,∗ a
Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea Department of Psychiatry, Bundang Jesaeng Hospital, Seongnam, Gyeonggi, Republic of Korea Department of Radiology, Yonsei University College of Medicine, Seoul, Republic of Korea d Department of Psychiatry, Yonsei University College of Medicine, Seoul, Republic of Korea b c
h i g h l i g h t s • The FA in the left cingulum and SLF were positively correlated with trait anhedonia. • The FA in the reward system was not correlated with trait anhedonia. • Alterations in connectivity within the DMN and CEN may be a basis of trait anhedonia.
a r t i c l e
i n f o
Article history: Received 4 April 2014 Received in revised form 21 May 2014 Accepted 1 July 2014 Available online 10 July 2014 Keywords: Schizophrenia Trait anhedonia Diffusion tensor imaging Cingulum Superior longitudinal fasciculus
a b s t r a c t This study tested association between anhedonia scores and white matter integrity in order to investigate the neural basis of trait anhedonia in schizophrenia. A total of 31 patients with schizophrenia and 33 healthy controls underwent diffusion weighted imaging and scoring of trait anhedonia using the Physical Anhedonia Scale. Using tract-based spatial statistics, we found that fractional anisotropy values of some white matter regions were differently correlated with Physical Anhedonia Scale scores between the two groups. The white matter regions that were more significantly correlated with trait anhedonia in patients than in controls included the left side of the cingulum, splenium of the corpus callosum, inferior longitudinal fasciculus, superior longitudinal fasciculus I and II, anterior thalamic radiation, and optic radiation. Of these regions, fractional anisotropy values in the cingulum and superior longitudinal fasciculus II were positively correlated with trait anhedonia in patients with schizophrenia. These findings suggest that alterations in structural connectivity within large-scale brain networks, including the default mode and central executive networks, may contribute to the development of trait anhedonia in patients with schizophrenia. © 2014 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Disrupted connections within and between brain regions have been implicated as a central abnormality in schizophrenia [1]. In particular, growing evidence has suggested that alterations in white matter organization may play an important role in this disconnection [2]. Diffusion tensor imaging (DTI) has enabled in vivo study of white matter alterations in patients with schizophrenia. Among the measures that reflect white matter properties, fractional
∗ Corresponding author at: Department of Psychiatry, Yonsei University, Gangnam Severance Hospital, 211 Eonjuro, Gangnam-gu, Seoul 135-720, Korea. Tel.: +82 2 2019 3341; fax: +82 2 3462 4304. E-mail address: [email protected] (J.-J. Kim). http://dx.doi.org/10.1016/j.neulet.2014.07.001 0304-3940/© 2014 Elsevier Ireland Ltd. All rights reserved.
anisotropy (FA), the extent to which water diffusion is directiondependent within the tissue microstructure, is the most widely used parameter [3]. FA has been reported to reflect the structural integrity of fibers, degree of myelination, and fiber coherence as decreases in FA imply damage of the myelin or axons and/or loss of coherence [3]. White matter disruptions measured by FA are widespread throughout the brain in schizophrenia, particularly in frontal and temporal regions [4]. Although most studies revealed decreased FA, some studies found increased FA in specific white matter tracts in patients with schizophrenia, compared to controls [3]. These findings of increased FA in schizophrenia were thought to reflect hyperconnectivity [5] or deficient axonal pruning [6]. Furthermore, studies using DTI have shown that white matter abnormalities are associated with specific symptoms of schizophrenia. For example, FA values of the superior longitudinal
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fasciculus were correlated with the severity of auditory hallucinations in schizophrenia [7]. Anhedonia, or reduced capacity to experience pleasure, is one of the cardinal symptoms of schizophrenia [8]. As a component of negative symptoms, anhedonia is a significant determinant of functional capacity and long-term outcome in schizophrenia [9]. The Physical Anhedonia Scale [10], which measures the extent of a decreased capacity to enjoy physical sensations, has been regarded as the standard anhedonia questionnaire in the field of psychiatry [11]. Anhedonia scores measured by the Physical Anhedonia Scale have been shown to be consistently elevated in patients with schizophrenia and have thus been identified as a trait of schizophrenia [12]. Recent neuroimaging studies have revealed that abnormalities in several brain networks in patients with schizophrenia are related to anhedonia. The reward system is known to be associated with responses to rewarding or pleasurable stimuli, and it comprises a network of brain regions including the ventral tegmental area, ventral striatum, amygdala, and orbitofrontal cortex [13]. Reduced activation in key structures of the reward system such as the ventral striatum [14–16], amygdala [14], and orbitofrontal cortex [15] have been related to more severe anhedonia. In addition, our group found that functional and structural abnormalities in the default mode network (DMN) were related to trait anhedonia in schizophrenia [17,18]. The DMN includes the ventromedial prefrontal cortex and posterior cingulate/retrosplenial cortex and is known to be responsible for self-referential processing [19]. Therefore, it was suggested to be involved in the self-referential aspect of anhedonia [17]. Considering that these brain networks require coordinated functioning of gray matter regions, it is possible that anhedonia may be the result of disrupted connectivity between gray matter regions. To date, however, the relationship between trait anhedonia and white matter abnormality has not been investigated in patients with schizophrenia. This study was designed to investigate whether white matter alterations are associated with trait anhedonia in patients with schizophrenia. We used the Physical Anhedonia Scale to evaluate trait anhedonia and utilized FA values from DTI data as an index of the white matter integrity. We hypothesized that disruptions in white matter tracts connecting gray matter regions in the reward system and DMN are related to trait anhedonia in patients with schizophrenia.
Physical Anhedonia Scale scores than controls (patients: 19.6 ± 9.3, controls: 11.9 ± 7.2, t = 3.8, df = 62, p < 0.001). Clinical symptoms of patients were rated using the Positive and Negative Syndrome Scale (PANSS) [21], and the mean ratings of positive, negative, and general symptom subscale scores were 15.7 ± 6.6, 16.6 ± 6.3, and 31.3 ± 10.9, respectively. The study was approved by the institutional review board, and written informed consent was obtained from all participants. 2.2. Magnetic resonance imaging MR images were acquired using a Philips 3T scanner (Intra Achieva; Philips Medical System, Best, The Netherlands). Head motion was minimized with restraining foam pads provided by the manufacturer. Diffusion-encoded images parallel to the anterior commissure–posterior commissure line were obtained using a single-shot echo-planar acquisition with the following parameters: 128 × 128 acquisition matrix, 224-mm field of view, 1.72 × 1.72 × 2 mm3 voxels, 70 axial slices, TE 71 ms, TR 7196 ms, flip angle 90◦ , slice gap 0 mm, 1 averaging per slice, b-factor of 600 s mm−2 , and non-cardiac gating. Diffusion-weighted images were acquired from 32 different directions with the baseline image obtained without diffusion weighting. 2.3. Image processing Diffusion-weighted images were preprocessed using the FMRIB Software Library (FSL) 5.0.6 (http://www.fmrib.ox.ac.uk/fsl) [22]. Source data were corrected for eddy currents and head motion. FA maps were first created for each subject using the FSL. A voxelwise statistical analysis of FA data was carried out using Tract-Based Spatial Statistics (TBSS, version 1.2) [23] implemented in the FSL. The FA data were aligned into 1 mm × 1 mm × 1 mm Montreal Neurological Institute (MNI) 152 spaces using the FMRIB’s Nonlinear Image Registration Tool (FNIRT). Then, a mean FA image (threshold of 0.2) was created and narrowed to create a mean FA skeleton, taking only the centers of white matter tracts common to all subjects. Voxel value for the FA data of each subject was then projected onto this skeleton, and resulting data were used in the following voxelwise statistical analyses. 2.4. Statistical analysis
2. Methods 2.1. Subjects Thirty-one patients with schizophrenia (including 17 males) and 33 healthy volunteers (including 14 males) participated in this study. The two groups had no significant difference in gender or age (30.7 ± 5.9 years and 31.0 ± 7.0 years, respectively). The diagnosis of schizophrenia in patients and the exclusion of any psychiatric disorders in controls were made using the Structural Clinical Interview for the Diagnostic and Statistical Manual (DSM-IV) [20]. All participants were right-handed, and none reported any past or present medical or neurological illness or drug or alcohol abuse. The mean years of education in patients and controls (13.4 ± 2.1 years and 15.7 ± 2.6 years, respectively) were significantly different (t = −3.8, df = 62, p < 0.001). The mean duration of illness in patients was 8.1 ± 6.7 years. All patients were taking one or two antipsychotic medications, and the mean chlorpromazine-equivalent dose was 398.4 ± 409.8 mg. Trait anhedonia was assessed with the Physical Anhedonia Scale [10], which comprised 61 true or false questions, with higher scores representing more severe anhedonia. Patients had significantly higher
Voxelwise statistics were conducted with FSL Randomize program using permutation-based statistical analysis with 5000 permutations. To investigate possible confounding effects, associations in education level with FA values were tested by regression model in FSL in patients and controls, separately. In patients, association of antipsychotic doses with FA values was also tested. Then, we found that fractional anisotropy values of some white matter regions were differently correlated with Physical Anhedonia Scale scores between the two groups. FA values were regressed on anhedonia scores, along with group variable. For each voxel, the interaction between anhedonia scores and group variable was tested. Significant interaction indicates that the linear relationship between FA values and anhedonia scores significantly differs between the two groups. The results were corrected for multiple comparisons using the threshold-free cluster enhancement (TFCE) method. The threshold for significance was set at p < 0.05. To further elucidate the clinical meaning of the findings, we calculated Pearson’s correlations between regional FA values and anhedonia scores in patients and controls, separately. The regions showing a significant interaction between anhedonia scores and group variable were selected for this analysis.
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Table 1 White matter regions in which fractional anisotropy (FA) values showed significantly higher correlation with trait anhedonia in patients than in controls and the corresponding correlation coefficients between regional FA values and trait anhedonia in each group. Regions
L anterior thalamic radiation L inferior longitudinal fasciculus L splenium of corpus callosum L optic radiation L superior longitudinal fasciculus I L superior longitudinal fasciculus II L cingulum
Cluster characteristics Cluster size
p
44 4574 98 41 334 388 142
0.045 0.003 0.039 0.047 0.010 0.026 0.044
Correlation coefficient with trait anhedonia (p) MNI coordinates x
y
z
−31 −46 −11 −19 −18 −24 −26
41 −16 −39 −61 15 −60 −63
5 −7 18 −1 43 28 0
Patients
Controls
0.18 (0.38) 0.08 (0.71) 0.14 (0.50) 0.24 (0.22) 0.37 (0.06) 0.40 (0.04* ) 0.47 (0.01* )
0.12 (0.51) 0.05 (0.78) −0.13 (0.48) −0.05 (0.80) −0.05 (0.77) −0.42 (0.02* ) 0.12 (0.36)
MNI: Montreal Neurological Institute, R: right, and L: left. a p-Values are corrected for multiple comparisons using the threshold-free cluster enhancement (TFCE) method. * p < 0.05.
3. Results There was no white matter region that showed a significant correlation with years of education in patients and controls and with antipsychotic doses in patients. Significant interaction between anhedonia scores and group variable was found in seven white matter regions. More specifically, FA values in these white matter regions of patients showed higher correlations with anhedonia scores than those of controls (Table 1). These regions included the left side of the cingulum, splenium of the corpus callosum, inferior longitudinal fasciculus, superior longitudinal fasciculus I, superior longitudinal fasciculus II, anterior thalamic radiation, and optic radiation. There was no white matter region that showed significantly lower correlations with anhedonia scores in patients than in controls. For correlation analysis, FA values in the left cingulum and anhedonia scores were positively correlated in patients (r = 0.47, p = 0.01), but were not significantly correlated in controls (Fig. 1). FA values in the left superior longitudinal fasciculus II and anhedonia scores were positively correlated in patients (r = 0.40, p = 0.04), whereas they were negatively correlated in controls (r = −0.42, p = 0.02). There was no significant correlation between FA values and anhedonia scores in any other white matter regions in either group. 4. Discussion To the best of our knowledge, this is the first study to examine the relationship between trait anhedonia and white matter alterations in schizophrenia. The results suggest that abnormalities in two white matter regions may play an important role in trait anhedonia in schizophrenia; FA values in the left cingulum and superior longitudinal fasciculus II were positively correlated with Physical Anhedonia Scale scores in patients. Interestingly, anhedonia-related white matter regions were confined to the left hemisphere. This finding is consistent with a previous study that reported that patients with negative symptoms might show left-sided functional impairments [24]. This is also supported by the findings that left-sided activation of the prefrontal cortex was more involved in goal-directed or appetitive behaviors, whereas right sided activation was implicated in avoidance behavior [25]. However, this finding contrasts with the finding of a previous study that showed that reduced FA in deficit schizophrenic patients was restricted to the right hemisphere [26]. Thus, further studies are needed to determine if white matter tracts in the left or right hemisphere are more highly related to trait anhedonia. Consistent with our hypothesis, FA values in the left cingulum showed a positive correlation with anhedonia scores in patients. The cingulum is known to play an important role in
connecting regions of the DMN including the medial prefrontal cortex and posterior cingulate cortex [27]. This is in line with previous findings that patients with schizophrenia showed increased functional connectivity of the DMN; greater DMN connectivity was correlated with more severe schizophrenic psychopathology [28–30]. Relatively high FA within the cingulum may reflect greater connectivity within the DMN [5], thus leading to hyperactivation of the DMN. Because the DMN may be involved in self-referential processing [19], hyperactivation of the DMN may cause excessive self-referential processing and exaggerated selfconsciousness. According to Sass and Parnas [31], exaggerated self-consciousness was proposed to be a possible cause of anhedonia in schizophrenia and a main aspect of self-disorder, which is regarded as the core abnormality of schizophrenia and characterized by complementary distortions of the act of awareness. Hyperactivation of the DMN may also be relevant to the impairment in emotional experience or anhedonia in schizophrenia because the DMN is normally deactivated during cognitive tasks [19]. The relationship between increased FA in the cingulum and trait anhedonia is partly supported by a previous DTI study [32] showing that FA values in the cingulum were inversely correlated with the activity level, which may reflect negative symptoms of schizophrenia [33]. FA values in the left superior longitudinal fasciculus II and anhedonia scores were also positively correlated in patients, whereas they were negatively correlated in controls. The superior longitudinal fasciculus II forms the connection between the inferior parietal lobule and dorsolateral prefrontal cortex [34]. These two structures together form the central-executive network (CEN), which is crucial for the active maintenance and manipulation of information in working memory and for decision making in the context of goaldirected behavior [35]. Because executive functioning impairments were found to be related to anhedonia in patients with schizophrenia [36] and healthy controls [37], it is plausible that abnormalities in structural connectivity between the inferior parietal lobule and dorsolateral prefrontal cortex may be a contributing factor to trait anhedonia in both patients and controls. However, the opposite direction of the correlations (i.e., positive in patients and negative in controls) between FA values in the superior longitudinal fasciculus II and anhedonia scores might indicate that the underlying mechanisms of the correlations are different for the two groups. Because reduction of FA values is interpreted as disruption of the tissue structure [4], the negative correlation in controls would imply that white matter microstructural disorganization in the CEN might contribute to anhedonia in healthy controls, whereas the positive correlation in patients may be considered in terms of deficient axonal pruning. A previous study suggested that increased FA in schizophrenia might reflect aberrant axonal pruning through neurodevelopment leading to inefficient/redundant neural networks [6]. Since redundant neural networks might indicate decreased
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Fig. 1. Correlations between regional fractional anisotropy (FA) values and Physical Anhedonia Scale scores in patients and controls. FA values in the left cingulum (A) and superior longitudinal fasciculus II (B) were positively correlated with Physical Anhedonia Scale scores in patients. To aid in visualization, results are highlighted using the TBSS fill script implemented in FSL (red–yellow). Results are shown overlaid on the Montreal Neurological Institute 1-mm template and the mean FA skeleton (green). Left–right orientation is according to radiological convention; * p < 0.05. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
efficiency in information transmission [6], a possible interpretation of positive correlation in patients is that increased FA in white matter tract connecting the inferior parietal lobule and dorsolateral prefrontal cortex may lead to deficient information transmission of the tract, thus further contributing to executive dysfunctions. It is interesting to note that white matter tracts correlating with trait anhedonia in schizophrenia in our study were different from those related to negative symptoms in other studies. Negative symptom scores in patients with schizophrenia have been reported to be correlated with white matter disruptions in the insula [38,39], inferior fronto-occipital fasciculus [5], and fornix [40]. This discrepancy may be because the structure of negative symptoms in schizophrenia is not unidimensional [41]. Factor analytic studies demonstrated that the most consistently emerged factors for negative symptoms in schizophrenia are diminished expression/blunted affect and anhedonia/asociality factors [41], suggesting that some symptoms belonging to negative symptoms might have little relationship with anhedonia. An alternative interpretation is that this discrepancy may reflect measurement differences. For example, negative symptoms in the PANSS are measured by raters on the basis of observation of behaviors and reports
from care-givers, while the Physical Anhedonia Scale relies on selfreports from patients [11]. Contrary to our expectations, FA values in white matter regions related to the reward system were not correlated with trait anhedonia in patients. This finding suggests that trait anhedonia in schizophrenia may not be related to alterations in white matter tracts connecting with the reward system but rather functional deficits in gray matter regions of the reward system [14–16]. Another possibility is that differences in the methods for analyzing DTI data may account for this finding. Previous DTI studies of patients showed FA reduction in white matter pathways related to the reward system, such as the anterior limb of the internal capsule [42], anterior thalamic radiation [43], and fornix [44]. Because these studies used methods such as region of interest or tractography approaches, limitations of TBSS [23] in analyzing small fiber tracts, data with within-scan head motion, and regions of crossing fibers or tract junctions may be relevant to this finding. Several limitations should be considered in our study. First, all patients were taking antipsychotic medications. Although no regional FA values were significantly correlated with antipsychotic doses in patients, the possibility of confounding effects due to antipsychotic use could not be excluded. To address the effect
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of antipsychotics on white matter structure, systematic studies with a larger sample size designed to investigate the relationships between FA and medication are needed. Second, depressive symptoms were not evaluated in this study. Because depression was correlated with trait anhedonia in patients with schizophrenia [45], further studies including the assessment of depressive symptoms are also warranted. 5. Conclusions We found that white matter changes in the cingulum and superior longitudinal fasciculus II were related to trait anhedonia in schizophrenia. These findings suggest that alterations of structural connectivity within large-scale brain networks, including the DMN and CEN, may contribute to the development of anhedonia in schizophrenia. To elucidate the relationship between brain connectivity and trait anhedonia, further studies using other modalities such as functional MRI are needed. Acknowledgement This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MEST) (No. NRF-2013R1A2A2A03068342). References [1] J. Fitzsimmons, M. Kubicki, M.E. Shenton, Review of functional and anatomical brain connectivity findings in schizophrenia, Curr. Opin. Psychiatry 26 (2013) 172–187. [2] N. Takahashi, T. Sakurai, K.L. Davis, J.D. Buxbaum, Linking oligodendrocyte and myelin dysfunction to neurocircuitry abnormalities in schizophrenia, Prog. Neurobiol. 93 (2011) 13–24. [3] M. Kubicki, R. McCarley, C.F. Westin, H.J. Park, S. Maier, R. Kikinis, F.A. Jolesz, M.E. Shenton, A review of diffusion tensor imaging studies in schizophrenia, J. Psychiatr. Res. 41 (2007) 15–30. [4] M. Kyriakopoulos, T. Bargiotas, G.J. Barker, S. Frangou, Diffusion tensor imaging in schizophrenia, Eur. Psychiatry 23 (2008) 255–273. [5] S.H. Lee, M. Kubicki, T. Asami, L.J. Seidman, J.M. Goldstein, R.I. MesholamGately, R.W. McCarley, M.E. Shenton, Extensive white matter abnormalities in patients with first-episode schizophrenia: a Diffusion Tensor Imaging (DTI) study, Schizophr. Res. 143 (2013) 231–238. [6] L.M. Alba-Ferrara, G.A. de Erausquin, What does anisotropy measure? Insights from increased and decreased anisotropy in selective fiber tracts in schizophrenia, Front. Integr. Neurosci. 7 (9.) (2013). [7] J.H. Seok, H.J. Park, J.W. Chun, S.K. Lee, H.S. Cho, J.S. Kwon, J.J. Kim, White matter abnormalities associated with auditory hallucinations in schizophrenia: a combined study of voxel-based analyses of diffusion tensor imaging and structural magnetic resonance imaging, Psychiatry Res. Neuroimaging 156 (2007) 93–104. [8] J.J. Blanchard, K.T. Mueser, A.S. Bellack, Anhedonia, positive and negative affect, and social functioning in schizophrenia, Schizophr. Bull. 24 (1998) 413–424. [9] P. Milev, B.C. Ho, S. Arndt, N.C. Andreasen, Predictive values of neurocognition and negative symptoms on functional outcome in schizophrenia: a longitudinal first-episode study with 7-year follow-up, Am. J. Psychiatry 162 (2005) 495–506. [10] L.J. Chapman, J.P. Chapman, M.L. Raulin, Scales for physical and social anhedonia, J. Abnorm. Psychol. 85 (1976) 374–382. [11] W.P. Horan, A.M. Kring, J.J. Blanchard, Anhedonia in schizophrenia: a review of assessment strategies, Schizophr. Bull. 32 (2006) 259–273. [12] E.S. Herbener, M. Harrow, S.K. Hill, Change in the relationship between anhedonia and functional deficits over a 20-year period in individuals with schizophrenia, Schizophr. Res. 75 (2005) 97–105. [13] S.N. Haber, B. Knutson, The reward circuit: linking primate anatomy and human imaging, Neuropsychopharmacology 35 (2010) 4–26. [14] E.C. Dowd, D.M. Barch, Anhedonia and emotional experience in schizophrenia: neural and behavioral indicators, Biol. Psychiatry 67 (2010) 902–911. [15] P.O. Harvey, J. Armony, A. Malla, M. Lepage, Functional neural substrates of self-reported physical anhedonia in non-clinical individuals and in patients with schizophrenia, J. Psychiatr. Res. 44 (2010) 707–716. [16] J.S. Lee, J.W. Chun, J.I. Kang, D.I. Kang, H.J. Park, J.J. Kim, Hippocampus, nucleus accumbens activity during neutral word recognition related to trait physical anhedonia in patients with schizophrenia: an fMRI study, Psychiatry Res. Neuroimaging 203 (2012) 46–53. [17] I.H. Park, J.J. Kim, J. Chun, Y.C. Jung, J.H. Seok, H.J. Park, J.D. Lee, Medial prefrontal default-mode hypoactivity affecting trait physical anhedonia in schizophrenia, Psychiatry Res. Neuroimaging 171 (2009) 155–165.
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