Schizophrenia Research 160 (2014) 51–56
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Altered default mode network functional connectivity in schizotypal personality disorder Qing Zhang a,b, Jing Shen a,c, Jianlin Wu a,b,⁎, Xiao Yu a, Wutao Lou c, Hongyu Fan a, Lin Shi d, Defeng Wang c,e,f,⁎⁎ a
Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China Tianjin Medical University, Tianjin, China Research Center for Medical Image Computing, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong Special Administrative Region d Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, NT, Hong Kong Special Administrative Region e Department of Biomedical Engineering and Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Shatin, NT, Hong Kong Special Administrative Region f Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China b c
a r t i c l e
i n f o
Article history: Received 21 February 2014 Received in revised form 17 September 2014 Accepted 9 October 2014 Available online 4 November 2014 Keywords: Schizotypal personality disorder Default mode network MRI Functional connectivity
a b s t r a c t The default mode network (DMN) has been identified to play a critical role in many mental disorders, but such abnormalities have not yet been determined in patients with schizotypal personality disorder (SPD). The purpose of this study was to analyze the alteration of the DMN functional connectivity in subjects with (SPD) and compared it to healthy control subjects. Eighteen DSM-IV diagnosed SPD subjects (all male, average age: 19.7 ± 0.9) from a pool of 3000 first year college students, and eighteen age and gender matched healthy control subjects were recruited (all male, average age: 20.3 ± 0.9). Independent component analysis (ICA) was used to analyze the DMN functional connectivity alteration. Compared to the healthy control group, SPD subjects had significantly decreased functional connectivity in the frontal areas, including the superior and medial frontal gyrus, and greater functional connectivity in the bilateral superior temporal gyrus and sub-lobar regions, including the bilateral putamen and caudate. Compared to subjects with SPD, the healthy control group showed decreased functional connectivity in the bilateral posterior cingulate gyrus, but showed greater functional connectivity in the right transverse temporal gyrus and left middle temporal gyrus. The healthy control group also showed greater activation in the cerebellum compared to the SPD group. These findings suggest that DMN functional connectivity, particularly that involving cognitive or emotional regulation, is altered in SPD subjects, and thus may be helpful in studying schizophrenia. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Schizotypal personality disorder (SPD) is conceptualized as a “mild” form of chronic schizophrenia, carrying similar phenomenological, cognitive, genetic, physiological, neuroanatomical, and neurofunctional abnormalities to schizophrenia (Siever and Davis, 2004). Generally, symptoms of SPD include ideas of reference, odd beliefs, unusual perceptual experiences, odd thinking, suspiciousness or paranoid ideation, inappropriate affect, odd behavior, and excessive social anxiety (American-PsychiatricAssociation). Despite its similarities with schizophrenia, SPD is difficult to diagnose because patients are considered not as psychotic, are drug naive, and most of SPDs have not been hospitalized. Previous research ⁎ Correspondence to: J. Wu, Department of Radiology, Affiliated ZhongShan Hospital of Dalian University, 116001, No. 6 of Jiefang Road, Zhongshan District, Dalian, China. Tel.: +86 411 62893688. ⁎⁎ Correspondence to: D. Wang, Research Center for Medical Image Computing, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong Special Administrative Region. Tel.: +852 2632 2975. E-mail addresses: [email protected] (J. Wu), [email protected] (D. Wang).
http://dx.doi.org/10.1016/j.schres.2014.10.013 0920-9964/© 2014 Elsevier B.V. All rights reserved.
has demonstrated that symptoms of SPD are correlated with the neurocognitive function in genetic risk schizophrenia patients (Johnson et al., 2003). Because SPD is thought to represent an intermediate schizophrenia-spectrum phenotype, it could be helpful in understanding the pathogenesis of related psychotic illnesses (Rosell et al, 2014). SPD may also be a useful model for studying the schizophrenia spectrum because of its genetic relationship with schizophrenia (Svenn, 1985). Consequently, chronic schizophrenia is more common among individuals with SPD than the general population. Another study concluded that 25% of the SPD subjects sampled developed more severe schizophrenia disorders (Asarnow, 2005). This implied that SPD can be a precursor state for schizophrenia, and indicates why SPD may be a useful model for studying the schizophrenia spectrum. Because of the importance of SPD in schizophrenia research, both structural and functional MRI has been used to study SPD. Several structural MRI studies have shown brain volume reduction in SPD patients. The most obviously affected regions include the frontal lobe and temporal lobe (Dickey et al., 2002; Siever and Davis, 2004; Hazlett et al., 2012; Fervaha and Remington, 2013), but these findings were split. There
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have also been several task-related fMRI studies on patients with SPD, but again, differences in the pattern of activation were inconclusive (Dickey et al., 2008; Hazlett et al., 2008; Fervaha and Remington, 2013). One of these studies showed increased activation in the region of the superior temporal gyrus in SPD patients compared to healthy subjects when given an auditory task (Dickey et al., 2008). In another taskrelated fMRI study, SPD patients had greater than normal frontal– striatal–thalamic (FST) activation during prepulse inhibition stimulus (Hazlett et al., 2008). On the other hand, there has been little study on functional brain altering during the early course of SPD during restingstate. These findings further supported the need to investigate functional connectivity in patients with SPD. The default mode network (DMN) has been identified to play a critical role in the resting state of brain function, consisting of the medial prefrontal cortex (PFC), the posterior cingulated/retrosplenial cortex, the inferior parietal lobule (IPL), and the medial temporal lobes (Andreasen et al., 1995; Raichle et al., 2001). Default mode activity represents underlying physiological processes of the brain that are unrelated to any particular thought or thoughts (Raichle and Snyder, 2007). DMN can reflect activation of subjects during the resting state, and it is a detectable and reproducible network that can test activation without task influences. The advantage of this method is that it allows us to examine task-independent network activity (Michael et al., 2004). Research shows that psychosis may be a network disturbance that disrupts the fragile balance between the default network and competing brain systems (Buckner, 2013). DMN abnormalities have been reported in many mental disorders, including schizophrenia (Brown and Thompson, 2010; Gur and Gur, 2010; van den Heuvel and Hulshoff Pol, 2010), autism spectrum disorder (Assaf et al., 2010), and hyperactivity disorder (Broyd et al., 2009). Altered functional connectivity within the DMN is characteristic of altered network integrity. Several studies have previously been performed to analyze the major functional deficits in prefrontal, temporal, and parietal lobes revealed by fMRI in schizophrenia patients (Brown and Thompson, 2010; Gur and Gur, 2010; van den Heuvel and Hulshoff Pol, 2010). The altered DMN connectivity is significantly correlated with the specific clinical features of schizophrenia (Broyd et al., 2009; Huang et al., 2010; Rotarska-Jagiela et al., 2010). The functional disconnectivity is considered as an endophenotype related genetic risk of schizophrenia (Karbasforoushan and Woodward, 2012). Group independent component analysis (ICA) has been successfully used to identify the DMN and other resting-state networks. ICA can identify the spatially independent components of a special network with highly synchronous time courses (Calhoun et al., 2009), and it has the advantage of identifying the networks without predefined specific ROI restriction (Assaf et al., 2010). Despite there being a number of task-related fMRI studies on patients with SPD, no pattern of activation has been discovered. DMN abnormalities during the resting state are prevalent in many disorders, but such abnormalities have not yet been determined in patients with SPD. The goal of this study was to determine if patients with SPD have altered DMN functional connectivity in comparison to a healthy control group. 2. Methods and materials 2.1. Subjects Eighteen individuals with DSM-IV diagnosed SPD (all male, average age: 19.7 ± 0.9 years, 18–21 years) and eighteen healthy control subjects were recruited (all male, average age: 20.3 ± 0.9 years, 19–22 years). The diagnosis was do by clinical psychologists according to a full diagnostic structured interview for DSM-IV Personality Disorders (Millon and Davis, 1996). All subjects were assessed by the Scale for the Assessment of Negative Symptoms (SANS) and the Scale for the Assessment of Positive Symptoms (SAPS) (Andreasen, 1981, 1984). All participants were screened from a pool of 3000 first year university students. None of the
SPD patients were previously hospitalized or prescribed antipsychotic medications. Written informed consents were obtained before the test. Medical or neurological illness and head injury by comprehensive medical history were taken to exclude the possible influence factors. 2.2. Image acquisition and processing The resting-state fMRI images were obtained from a 3 T MR scanner (Siemens, Verio, Germany) using the 8 channel head coil. All subjects were instructed to relax and keep their eyes closed during the scanning procedure, and they did not fall asleep which was confirmed immediately after the scanning session. The subjects' heads were fixed by the foam pads to avoid the head movement. Functional image parameters included gradient-echo planar imaging (EPI) sensitive to BOLD (TR = 2000 ms, TE = 30 ms, flip angle = 90°, 32 contiguous axial slices with 4 mm thickness, with 1 mm gap, yielding 3.75 × 3.75 × 4 mm3 voxels for 180 time points, matrix = 64 × 64). In addition, a 3D MPRAGE sequence with 176 contiguous sagittal slices of 1 mm thickness was obtained (TR = 2300 ms; TE = 3 ms; TI = 900 ms; echo time = 8.9 ms; flip angle = 9°; matrix size = 256 × 256). T2WI was also taken to exclude pathology changes of the head. Data analysis was performed using Data Processing Assistant for Resting-State fMRI (DPARSF) (Yan & Zang, 2010, http://www.restfmri. net) (Chao-Gan and Yu-Feng, 2010) based on Statistical Parametric Mapping (SPM8) (http://www.fil.ion.ucl.ac.uk/spm) and Resting-state fMRI Data Analysis Toolkit (REST, http://www.restfmri.net) (Song et al., 2011). The first 10 volumes of each functional time series were discarded because of the instability of the initial MRI signal, and finally 170 time points of imaging were analyzed. The images were subsequently corrected for slice timing and realigned to the first image for rigid-body head movement correction (patient data exhibiting movement greater than 3.0 mm, rotation than 3° were discarded). The echo-planar images were re-sampled into 3 × 3 × 3 mm3, and data were then spatially normalized into standard Montreal Neurological Institute space, and smoothed using an isotropic Gaussian filter of 8 × 8 × 8 mm3 full width at half maximum. 2.3. Component identification Independent component analyses (ICA) were preprocessed in eighteen SPD subjects and eighteen matched healthy controls. Group ICA was conducted on all subjects using the Infomax algorithm within the GIFT software (http://mialab.mrn.org/software/gift/index.html, version 3.0a). Minimum description length algorithm was used to estimate the number of spatially independent components (Li et al., 2007). The mean dimension estimation was 20 for both groups. Individual DMN related components were selected by computing the correlations of each component's spatial map with mask map provided by WFU Pickatlas (Maldjian et al., 2003). For each subject, two DMN-related components were selected and then converted to z value which were proposed by Tang et al. (2013) in their early onset schizophrenia research, and separated the DMN into anterior and posterior regions which were consistent with the previous studies (Damoiseaux et al., 2006; Esposito et al., 2006; Calhoun et al., 2008, 2009; Kim et al., 2009; Stevens et al., 2009; Tang et al., 2013). Individual components' maps were entered into one-sample t-test in REST software (Song et al., 2011) to create a sample specific component mask. A p b 0.05 with false discovery rate (FDR) corrected was considered as significant. 2.4. Statistical analysis 2.4.1. Group comparison Individual DMN component maps were entered into REST for group analyses. A two-sample t-test was applied to analyze the functional connectivity strength of each voxel to the whole spatial component. A combination of SPD and healthy control maps was used as mask of
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DMN component group analyses. The statistical maps were analyzed using the combination mask to ensure the analysis of the DMN relevant alteration only. Clusters larger than 20 voxels and p b 0.05 with FDR correction were considered significant. 3. Results 3.1. Component identification The two highest DMN related components (A) anterior component of DMN and (B) posterior component of DMN were selected as DMN components by independent component analysis. The two components of DMN included the posterior cingulate cortex (PCC), bilateral IPL, PFC and Precuneus (PrC), as shown in Fig. 1. 3.2. Results of DMN connectivity study Two-sample t-test of DMN correlation maps revealed significant inter-group differences in clusters. For component A, healthy control subjects showed an increased default mode functional connectivity in both medial frontal lobes and cerebellum anterior lobe. The SPD subjects showed an increased default mode functional connectivity in the bilateral superior temporal gyrus and sub-gyral regions. For component B, the healthy control subjects showed a decreased functional connectivity in bilateral posterior cingulate gyrus, but greater in the cerebellum posterior lobe, right transverse temporal gyrus, and left middle temporal gyrus compared to SPD subjects (Table 1 and Fig. 2).
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Table 1 SPD and HC group comparison of default mode network activity at rest. Regions Component Aa SPD N HC Bilateral superior temporal gyrus Sub-lobarb HC N SPD Left superior frontal gyrus Left medial frontal gyrus Cerebellum anterior lobe Component B SPD N HC Bilateral posterior cingulate gyrus HC N SPD Cerebellum posterior lobe Left middle temporal gyrus Right transverse temporal gyrus
Peak MNI Cluster size left/ coordinate left/right right (voxels)
Peak t value left/right
−36 24 −30/36 15 −36 −6 9 −9
101/55
8.83/6.84
219
7.36
−21 51 42
31
−8.31
−3 42 −18
18
−7.52
0 −48 −30
42
−4.14
−21 −60 15/18 −57 12
17/26
3.94/5.93
−39 −63 −57
63
−6.72
−60 −27 −9
21
−4.41
60 −12 12
15
−5.08
a Component A: anterior component of DMN; component B: posterior component of DMN. b Sub-lobar includes bilateral putamen (cluster left: 59, right: 6), bilateral caudate (cluster left: 36, right: 33).
4. Discussion This study clearly demonstrates differences in regional DMN activation between SPD subjects and healthy control subjects in both component A and component B during resting-state. Specifically, there are three new findings. First, in component A of SPD subjects, clusters of deactivations were found in the frontal gyrus, while greater activations were found in the bilateral superior temporal gyrus and sub-lobar. Second, in component B of SPD subjects, increased activations in the bilateral posterior cingulate gyrus were found, and decreased activations in the left middle temporal gyrus and right transverse temporal gyrus were found. Last, the cerebellum showed greater activation in the healthy control group compared to the SPD group. These findings suggest that SPD subjects have an altered default mode network in comparison to healthy control subjects. The two-sample t-test of DMN correlation maps showed clusters of deactivations in the frontal areas including the superior and medial
frontal gyrus, and showed greater activations in the bilateral superior temporal gyrus and sub-lobar for component A of SPD subjects. Previous research has identified similar deactivations in prefrontal lobes on resting state and activation tasks in patients with schizophrenia (Hill et al., 2004; Garrity et al., 2007). This may explain why the prefrontal deactivation can contribute to cognitive disorganization, formal thought disorder, and attention deficits of schizophrenia (Perlstein et al., 2001; Assaf et al., 2006). Specific alteration in the dMPFC subsystem suggested that FC patterns were altered even in the early stages of psychosis (Alonso-Solis et al., 2012). In contrast, the frontal area's deactivation could reflect the SPD symptoms such as thought disorder and cognitive disorganization. The temporal lobe was considered as a high implicated region of SPD, and correlated with working memory deficits of SPD (Vu et al., 2013). Koenigsberg et al (2002) found reduced activation of left superior temporal gyrus in SPD during visuospatial working
Fig. 1. Two highest DMN related components. A: Healthy control subjects (n = 18), B: SPD subjects (n = 18). Red: component A, blue: component B.
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Fig. 2. Areas with altered DMN activations of SPD versus HC are shown in red. A–B for component A, healthy control subjects demonstrated increased default mode functional connectivity in both medial frontal lobes and cerebellum anterior lobe. The SPD subjects showed increased functional connectivity in bilateral superior temporal gyrus and sub-gyral regions. C–D for component B, the healthy control subjects showed decreased connectivity in bilateral posterior cingulate gyrus, but greater in the cerebellum posterior lobe, right transverse temporal gyrus and left middle temporal gyrus compared to SPD subjects.
memory task, but Dickey et al (2008) found increased STG activation in SPD during an auditory processing. Due to the limited number of studies on DMN alterations of SPD, a reduced or increased activation during resting state required further analysis. Our findings showing greater activation of sub-lobar regions for SPD patients were consistent with the results of Shihabuddin et al. (2001) in their positron emission tomography (PET) study. Their research revealed that the glucose metabolic rate of putamen was significantly elevated in SPD compared to that in the healthy subjects group. Sublobar including caudate and putamen, played a central role in the frontal–striatal brain circuitry of SPD, they served as an important input nuclei from the cortex, motor and cognitive circuits, which were anatomically linked to the prefrontal cortex to the basal ganglia (Levitt et al., 2004). Similar fMRI research also showed that basal ganglia were activated during working memory task in schizophrenia patients (Manoach et al., 2000). Abnormalities in any of the core components of the frontal basal ganglia-thalamo-cortical circuits might cause functional disconnection from the feedback loops, resulting in behavioral abnormality that resembled damage to the prefrontal cortex itself (Cummings, 1993; Bhatia and Marsden, 1994; Calabresi et al., 1997; Kawagoe et al., 1998; Levitt et al., 2002). These kinds of alterations could be related to the shield of patients with SPD from frank psychosis (Shihabuddin et al., 2001).
The SPD subjects showed increased activation in bilateral posterior cingulate gyrus, decreased activation in the left middle temporal gyrus, and right transverse temporal gyrus during resting-state for component B. These findings were also consistent with previous PET results, which revealed higher glucose metabolic rates in the posterior cingulate gyrus of the SPD subjects than the healthy controls (Haznedar et al., 2004). Similar significantly higher activity and connectivity were found in the posterior cingulate gyrus in the schizophrenia patients compared to those in healthy control group in the DMN homogeneity research (Woodward et al., 2011; Guo et al., 2013). However, SalgadoPineda's research showed opposite results of deactivated posterior cingulate gyrus of schizophrenia (Salgado-Pineda et al., 2011). The cingulate gyrus is involved in emotion, cognition, and higher executive functions and has been considered as a dysfunctional region in schizophrenia and schizotypal disorder (Haznedar et al., 2004; Hazlett et al., 2011). The posterior cingulate has modulated SPD-relevant function, such as self-referential processing, which may explain why the activation was different between SPD and HC. For the left and right temporal gyri, the HC group showed deactivation compared to the SPD group. There is no consistent conclusion whether the temporal gyrus should increase or decrease activation. It was also found that the anterior lobe and posterior lobe of the cerebellum showed greater activation in the HC group compared to
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the SPD group. Although the cerebellum has traditionally been known to coordinate motor function, it is also thought of as playing an important role in psychological function in schizophrenia through the corticocerebellar–thalamic–cortical (CCTC) circuit, and cerebellar dysfunction can cause broader impairment in schizophrenia (Forsyth et al., 2012). The cerebellum was the only area consistently activated across various cognitive processes in PET and fMRI studies (Cabeza and Nyberg, 2000). Therefore, the alterations in greater activation of the cerebellum can help us better understand the psychological changes of SPD. In conclusion, our research demonstrated that there is altered DMN activity in SPD subjects. Our findings showed that there are specific regional alterations in the DMN, and that these affected areas may explain symptoms of SPD. This research has limitations. First, the research was conducted on a small sample of subjects; therefore, a larger sample of subjects should be studied to confirm our findings. Second, the results showed alterations of DMN in the SPD subjects, but whether the SPD subjects develop into schizophrenia will need to be studied in future research. Role of funding source This work was supported by the National Natural Science Foundation of China (Grant No. 30870699, No. 81201157), by a grant from the Dalian Science and Technology Bureau (2010E15SF166), grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project Nos.: CUHK 475711, 416712), and a project BMEp2-13 of the Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong. Contributors Qing Zhang and Jing Shen analyzed the data and wrote the manuscript. Xiao Yu and Hongyu Fan recruited the subjects and collection. Wutao Lou and Lin Shi assisted in the data analysis. Jing Shen, Jianlin Wu and Defeng Wang assisted in the paradigm design and manuscript preparation. Conflict of interest We declare that all authors have no conflict of interest. Acknowledgments This work was supported by the National Natural Science Foundation of China (Grant No.30870699, No. 81201157), by a grant from the Dalian Science and Technology Bureau (2010E15SF166), grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project Nos.: CUHK 475711, 416712), and a project BMEp2-13 of the Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong.
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Altered default mode network functional connectivity in schizotypal personality disorder Qing Zhang a,b, Jing Shen a,c, Jianlin Wu a,b,⁎, Xiao Yu a, Wutao Lou c, Hongyu Fan a, Lin Shi d, Defeng Wang c,e,f,⁎⁎ a
Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, China Tianjin Medical University, Tianjin, China Research Center for Medical Image Computing, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong Special Administrative Region d Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, NT, Hong Kong Special Administrative Region e Department of Biomedical Engineering and Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Shatin, NT, Hong Kong Special Administrative Region f Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China b c
a r t i c l e
i n f o
Article history: Received 21 February 2014 Received in revised form 17 September 2014 Accepted 9 October 2014 Available online 4 November 2014 Keywords: Schizotypal personality disorder Default mode network MRI Functional connectivity
a b s t r a c t The default mode network (DMN) has been identified to play a critical role in many mental disorders, but such abnormalities have not yet been determined in patients with schizotypal personality disorder (SPD). The purpose of this study was to analyze the alteration of the DMN functional connectivity in subjects with (SPD) and compared it to healthy control subjects. Eighteen DSM-IV diagnosed SPD subjects (all male, average age: 19.7 ± 0.9) from a pool of 3000 first year college students, and eighteen age and gender matched healthy control subjects were recruited (all male, average age: 20.3 ± 0.9). Independent component analysis (ICA) was used to analyze the DMN functional connectivity alteration. Compared to the healthy control group, SPD subjects had significantly decreased functional connectivity in the frontal areas, including the superior and medial frontal gyrus, and greater functional connectivity in the bilateral superior temporal gyrus and sub-lobar regions, including the bilateral putamen and caudate. Compared to subjects with SPD, the healthy control group showed decreased functional connectivity in the bilateral posterior cingulate gyrus, but showed greater functional connectivity in the right transverse temporal gyrus and left middle temporal gyrus. The healthy control group also showed greater activation in the cerebellum compared to the SPD group. These findings suggest that DMN functional connectivity, particularly that involving cognitive or emotional regulation, is altered in SPD subjects, and thus may be helpful in studying schizophrenia. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Schizotypal personality disorder (SPD) is conceptualized as a “mild” form of chronic schizophrenia, carrying similar phenomenological, cognitive, genetic, physiological, neuroanatomical, and neurofunctional abnormalities to schizophrenia (Siever and Davis, 2004). Generally, symptoms of SPD include ideas of reference, odd beliefs, unusual perceptual experiences, odd thinking, suspiciousness or paranoid ideation, inappropriate affect, odd behavior, and excessive social anxiety (American-PsychiatricAssociation). Despite its similarities with schizophrenia, SPD is difficult to diagnose because patients are considered not as psychotic, are drug naive, and most of SPDs have not been hospitalized. Previous research ⁎ Correspondence to: J. Wu, Department of Radiology, Affiliated ZhongShan Hospital of Dalian University, 116001, No. 6 of Jiefang Road, Zhongshan District, Dalian, China. Tel.: +86 411 62893688. ⁎⁎ Correspondence to: D. Wang, Research Center for Medical Image Computing, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong Special Administrative Region. Tel.: +852 2632 2975. E-mail addresses: [email protected] (J. Wu), [email protected] (D. Wang).
http://dx.doi.org/10.1016/j.schres.2014.10.013 0920-9964/© 2014 Elsevier B.V. All rights reserved.
has demonstrated that symptoms of SPD are correlated with the neurocognitive function in genetic risk schizophrenia patients (Johnson et al., 2003). Because SPD is thought to represent an intermediate schizophrenia-spectrum phenotype, it could be helpful in understanding the pathogenesis of related psychotic illnesses (Rosell et al, 2014). SPD may also be a useful model for studying the schizophrenia spectrum because of its genetic relationship with schizophrenia (Svenn, 1985). Consequently, chronic schizophrenia is more common among individuals with SPD than the general population. Another study concluded that 25% of the SPD subjects sampled developed more severe schizophrenia disorders (Asarnow, 2005). This implied that SPD can be a precursor state for schizophrenia, and indicates why SPD may be a useful model for studying the schizophrenia spectrum. Because of the importance of SPD in schizophrenia research, both structural and functional MRI has been used to study SPD. Several structural MRI studies have shown brain volume reduction in SPD patients. The most obviously affected regions include the frontal lobe and temporal lobe (Dickey et al., 2002; Siever and Davis, 2004; Hazlett et al., 2012; Fervaha and Remington, 2013), but these findings were split. There
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have also been several task-related fMRI studies on patients with SPD, but again, differences in the pattern of activation were inconclusive (Dickey et al., 2008; Hazlett et al., 2008; Fervaha and Remington, 2013). One of these studies showed increased activation in the region of the superior temporal gyrus in SPD patients compared to healthy subjects when given an auditory task (Dickey et al., 2008). In another taskrelated fMRI study, SPD patients had greater than normal frontal– striatal–thalamic (FST) activation during prepulse inhibition stimulus (Hazlett et al., 2008). On the other hand, there has been little study on functional brain altering during the early course of SPD during restingstate. These findings further supported the need to investigate functional connectivity in patients with SPD. The default mode network (DMN) has been identified to play a critical role in the resting state of brain function, consisting of the medial prefrontal cortex (PFC), the posterior cingulated/retrosplenial cortex, the inferior parietal lobule (IPL), and the medial temporal lobes (Andreasen et al., 1995; Raichle et al., 2001). Default mode activity represents underlying physiological processes of the brain that are unrelated to any particular thought or thoughts (Raichle and Snyder, 2007). DMN can reflect activation of subjects during the resting state, and it is a detectable and reproducible network that can test activation without task influences. The advantage of this method is that it allows us to examine task-independent network activity (Michael et al., 2004). Research shows that psychosis may be a network disturbance that disrupts the fragile balance between the default network and competing brain systems (Buckner, 2013). DMN abnormalities have been reported in many mental disorders, including schizophrenia (Brown and Thompson, 2010; Gur and Gur, 2010; van den Heuvel and Hulshoff Pol, 2010), autism spectrum disorder (Assaf et al., 2010), and hyperactivity disorder (Broyd et al., 2009). Altered functional connectivity within the DMN is characteristic of altered network integrity. Several studies have previously been performed to analyze the major functional deficits in prefrontal, temporal, and parietal lobes revealed by fMRI in schizophrenia patients (Brown and Thompson, 2010; Gur and Gur, 2010; van den Heuvel and Hulshoff Pol, 2010). The altered DMN connectivity is significantly correlated with the specific clinical features of schizophrenia (Broyd et al., 2009; Huang et al., 2010; Rotarska-Jagiela et al., 2010). The functional disconnectivity is considered as an endophenotype related genetic risk of schizophrenia (Karbasforoushan and Woodward, 2012). Group independent component analysis (ICA) has been successfully used to identify the DMN and other resting-state networks. ICA can identify the spatially independent components of a special network with highly synchronous time courses (Calhoun et al., 2009), and it has the advantage of identifying the networks without predefined specific ROI restriction (Assaf et al., 2010). Despite there being a number of task-related fMRI studies on patients with SPD, no pattern of activation has been discovered. DMN abnormalities during the resting state are prevalent in many disorders, but such abnormalities have not yet been determined in patients with SPD. The goal of this study was to determine if patients with SPD have altered DMN functional connectivity in comparison to a healthy control group. 2. Methods and materials 2.1. Subjects Eighteen individuals with DSM-IV diagnosed SPD (all male, average age: 19.7 ± 0.9 years, 18–21 years) and eighteen healthy control subjects were recruited (all male, average age: 20.3 ± 0.9 years, 19–22 years). The diagnosis was do by clinical psychologists according to a full diagnostic structured interview for DSM-IV Personality Disorders (Millon and Davis, 1996). All subjects were assessed by the Scale for the Assessment of Negative Symptoms (SANS) and the Scale for the Assessment of Positive Symptoms (SAPS) (Andreasen, 1981, 1984). All participants were screened from a pool of 3000 first year university students. None of the
SPD patients were previously hospitalized or prescribed antipsychotic medications. Written informed consents were obtained before the test. Medical or neurological illness and head injury by comprehensive medical history were taken to exclude the possible influence factors. 2.2. Image acquisition and processing The resting-state fMRI images were obtained from a 3 T MR scanner (Siemens, Verio, Germany) using the 8 channel head coil. All subjects were instructed to relax and keep their eyes closed during the scanning procedure, and they did not fall asleep which was confirmed immediately after the scanning session. The subjects' heads were fixed by the foam pads to avoid the head movement. Functional image parameters included gradient-echo planar imaging (EPI) sensitive to BOLD (TR = 2000 ms, TE = 30 ms, flip angle = 90°, 32 contiguous axial slices with 4 mm thickness, with 1 mm gap, yielding 3.75 × 3.75 × 4 mm3 voxels for 180 time points, matrix = 64 × 64). In addition, a 3D MPRAGE sequence with 176 contiguous sagittal slices of 1 mm thickness was obtained (TR = 2300 ms; TE = 3 ms; TI = 900 ms; echo time = 8.9 ms; flip angle = 9°; matrix size = 256 × 256). T2WI was also taken to exclude pathology changes of the head. Data analysis was performed using Data Processing Assistant for Resting-State fMRI (DPARSF) (Yan & Zang, 2010, http://www.restfmri. net) (Chao-Gan and Yu-Feng, 2010) based on Statistical Parametric Mapping (SPM8) (http://www.fil.ion.ucl.ac.uk/spm) and Resting-state fMRI Data Analysis Toolkit (REST, http://www.restfmri.net) (Song et al., 2011). The first 10 volumes of each functional time series were discarded because of the instability of the initial MRI signal, and finally 170 time points of imaging were analyzed. The images were subsequently corrected for slice timing and realigned to the first image for rigid-body head movement correction (patient data exhibiting movement greater than 3.0 mm, rotation than 3° were discarded). The echo-planar images were re-sampled into 3 × 3 × 3 mm3, and data were then spatially normalized into standard Montreal Neurological Institute space, and smoothed using an isotropic Gaussian filter of 8 × 8 × 8 mm3 full width at half maximum. 2.3. Component identification Independent component analyses (ICA) were preprocessed in eighteen SPD subjects and eighteen matched healthy controls. Group ICA was conducted on all subjects using the Infomax algorithm within the GIFT software (http://mialab.mrn.org/software/gift/index.html, version 3.0a). Minimum description length algorithm was used to estimate the number of spatially independent components (Li et al., 2007). The mean dimension estimation was 20 for both groups. Individual DMN related components were selected by computing the correlations of each component's spatial map with mask map provided by WFU Pickatlas (Maldjian et al., 2003). For each subject, two DMN-related components were selected and then converted to z value which were proposed by Tang et al. (2013) in their early onset schizophrenia research, and separated the DMN into anterior and posterior regions which were consistent with the previous studies (Damoiseaux et al., 2006; Esposito et al., 2006; Calhoun et al., 2008, 2009; Kim et al., 2009; Stevens et al., 2009; Tang et al., 2013). Individual components' maps were entered into one-sample t-test in REST software (Song et al., 2011) to create a sample specific component mask. A p b 0.05 with false discovery rate (FDR) corrected was considered as significant. 2.4. Statistical analysis 2.4.1. Group comparison Individual DMN component maps were entered into REST for group analyses. A two-sample t-test was applied to analyze the functional connectivity strength of each voxel to the whole spatial component. A combination of SPD and healthy control maps was used as mask of
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DMN component group analyses. The statistical maps were analyzed using the combination mask to ensure the analysis of the DMN relevant alteration only. Clusters larger than 20 voxels and p b 0.05 with FDR correction were considered significant. 3. Results 3.1. Component identification The two highest DMN related components (A) anterior component of DMN and (B) posterior component of DMN were selected as DMN components by independent component analysis. The two components of DMN included the posterior cingulate cortex (PCC), bilateral IPL, PFC and Precuneus (PrC), as shown in Fig. 1. 3.2. Results of DMN connectivity study Two-sample t-test of DMN correlation maps revealed significant inter-group differences in clusters. For component A, healthy control subjects showed an increased default mode functional connectivity in both medial frontal lobes and cerebellum anterior lobe. The SPD subjects showed an increased default mode functional connectivity in the bilateral superior temporal gyrus and sub-gyral regions. For component B, the healthy control subjects showed a decreased functional connectivity in bilateral posterior cingulate gyrus, but greater in the cerebellum posterior lobe, right transverse temporal gyrus, and left middle temporal gyrus compared to SPD subjects (Table 1 and Fig. 2).
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Table 1 SPD and HC group comparison of default mode network activity at rest. Regions Component Aa SPD N HC Bilateral superior temporal gyrus Sub-lobarb HC N SPD Left superior frontal gyrus Left medial frontal gyrus Cerebellum anterior lobe Component B SPD N HC Bilateral posterior cingulate gyrus HC N SPD Cerebellum posterior lobe Left middle temporal gyrus Right transverse temporal gyrus
Peak MNI Cluster size left/ coordinate left/right right (voxels)
Peak t value left/right
−36 24 −30/36 15 −36 −6 9 −9
101/55
8.83/6.84
219
7.36
−21 51 42
31
−8.31
−3 42 −18
18
−7.52
0 −48 −30
42
−4.14
−21 −60 15/18 −57 12
17/26
3.94/5.93
−39 −63 −57
63
−6.72
−60 −27 −9
21
−4.41
60 −12 12
15
−5.08
a Component A: anterior component of DMN; component B: posterior component of DMN. b Sub-lobar includes bilateral putamen (cluster left: 59, right: 6), bilateral caudate (cluster left: 36, right: 33).
4. Discussion This study clearly demonstrates differences in regional DMN activation between SPD subjects and healthy control subjects in both component A and component B during resting-state. Specifically, there are three new findings. First, in component A of SPD subjects, clusters of deactivations were found in the frontal gyrus, while greater activations were found in the bilateral superior temporal gyrus and sub-lobar. Second, in component B of SPD subjects, increased activations in the bilateral posterior cingulate gyrus were found, and decreased activations in the left middle temporal gyrus and right transverse temporal gyrus were found. Last, the cerebellum showed greater activation in the healthy control group compared to the SPD group. These findings suggest that SPD subjects have an altered default mode network in comparison to healthy control subjects. The two-sample t-test of DMN correlation maps showed clusters of deactivations in the frontal areas including the superior and medial
frontal gyrus, and showed greater activations in the bilateral superior temporal gyrus and sub-lobar for component A of SPD subjects. Previous research has identified similar deactivations in prefrontal lobes on resting state and activation tasks in patients with schizophrenia (Hill et al., 2004; Garrity et al., 2007). This may explain why the prefrontal deactivation can contribute to cognitive disorganization, formal thought disorder, and attention deficits of schizophrenia (Perlstein et al., 2001; Assaf et al., 2006). Specific alteration in the dMPFC subsystem suggested that FC patterns were altered even in the early stages of psychosis (Alonso-Solis et al., 2012). In contrast, the frontal area's deactivation could reflect the SPD symptoms such as thought disorder and cognitive disorganization. The temporal lobe was considered as a high implicated region of SPD, and correlated with working memory deficits of SPD (Vu et al., 2013). Koenigsberg et al (2002) found reduced activation of left superior temporal gyrus in SPD during visuospatial working
Fig. 1. Two highest DMN related components. A: Healthy control subjects (n = 18), B: SPD subjects (n = 18). Red: component A, blue: component B.
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Fig. 2. Areas with altered DMN activations of SPD versus HC are shown in red. A–B for component A, healthy control subjects demonstrated increased default mode functional connectivity in both medial frontal lobes and cerebellum anterior lobe. The SPD subjects showed increased functional connectivity in bilateral superior temporal gyrus and sub-gyral regions. C–D for component B, the healthy control subjects showed decreased connectivity in bilateral posterior cingulate gyrus, but greater in the cerebellum posterior lobe, right transverse temporal gyrus and left middle temporal gyrus compared to SPD subjects.
memory task, but Dickey et al (2008) found increased STG activation in SPD during an auditory processing. Due to the limited number of studies on DMN alterations of SPD, a reduced or increased activation during resting state required further analysis. Our findings showing greater activation of sub-lobar regions for SPD patients were consistent with the results of Shihabuddin et al. (2001) in their positron emission tomography (PET) study. Their research revealed that the glucose metabolic rate of putamen was significantly elevated in SPD compared to that in the healthy subjects group. Sublobar including caudate and putamen, played a central role in the frontal–striatal brain circuitry of SPD, they served as an important input nuclei from the cortex, motor and cognitive circuits, which were anatomically linked to the prefrontal cortex to the basal ganglia (Levitt et al., 2004). Similar fMRI research also showed that basal ganglia were activated during working memory task in schizophrenia patients (Manoach et al., 2000). Abnormalities in any of the core components of the frontal basal ganglia-thalamo-cortical circuits might cause functional disconnection from the feedback loops, resulting in behavioral abnormality that resembled damage to the prefrontal cortex itself (Cummings, 1993; Bhatia and Marsden, 1994; Calabresi et al., 1997; Kawagoe et al., 1998; Levitt et al., 2002). These kinds of alterations could be related to the shield of patients with SPD from frank psychosis (Shihabuddin et al., 2001).
The SPD subjects showed increased activation in bilateral posterior cingulate gyrus, decreased activation in the left middle temporal gyrus, and right transverse temporal gyrus during resting-state for component B. These findings were also consistent with previous PET results, which revealed higher glucose metabolic rates in the posterior cingulate gyrus of the SPD subjects than the healthy controls (Haznedar et al., 2004). Similar significantly higher activity and connectivity were found in the posterior cingulate gyrus in the schizophrenia patients compared to those in healthy control group in the DMN homogeneity research (Woodward et al., 2011; Guo et al., 2013). However, SalgadoPineda's research showed opposite results of deactivated posterior cingulate gyrus of schizophrenia (Salgado-Pineda et al., 2011). The cingulate gyrus is involved in emotion, cognition, and higher executive functions and has been considered as a dysfunctional region in schizophrenia and schizotypal disorder (Haznedar et al., 2004; Hazlett et al., 2011). The posterior cingulate has modulated SPD-relevant function, such as self-referential processing, which may explain why the activation was different between SPD and HC. For the left and right temporal gyri, the HC group showed deactivation compared to the SPD group. There is no consistent conclusion whether the temporal gyrus should increase or decrease activation. It was also found that the anterior lobe and posterior lobe of the cerebellum showed greater activation in the HC group compared to
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the SPD group. Although the cerebellum has traditionally been known to coordinate motor function, it is also thought of as playing an important role in psychological function in schizophrenia through the corticocerebellar–thalamic–cortical (CCTC) circuit, and cerebellar dysfunction can cause broader impairment in schizophrenia (Forsyth et al., 2012). The cerebellum was the only area consistently activated across various cognitive processes in PET and fMRI studies (Cabeza and Nyberg, 2000). Therefore, the alterations in greater activation of the cerebellum can help us better understand the psychological changes of SPD. In conclusion, our research demonstrated that there is altered DMN activity in SPD subjects. Our findings showed that there are specific regional alterations in the DMN, and that these affected areas may explain symptoms of SPD. This research has limitations. First, the research was conducted on a small sample of subjects; therefore, a larger sample of subjects should be studied to confirm our findings. Second, the results showed alterations of DMN in the SPD subjects, but whether the SPD subjects develop into schizophrenia will need to be studied in future research. Role of funding source This work was supported by the National Natural Science Foundation of China (Grant No. 30870699, No. 81201157), by a grant from the Dalian Science and Technology Bureau (2010E15SF166), grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project Nos.: CUHK 475711, 416712), and a project BMEp2-13 of the Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong. Contributors Qing Zhang and Jing Shen analyzed the data and wrote the manuscript. Xiao Yu and Hongyu Fan recruited the subjects and collection. Wutao Lou and Lin Shi assisted in the data analysis. Jing Shen, Jianlin Wu and Defeng Wang assisted in the paradigm design and manuscript preparation. Conflict of interest We declare that all authors have no conflict of interest. Acknowledgments This work was supported by the National Natural Science Foundation of China (Grant No.30870699, No. 81201157), by a grant from the Dalian Science and Technology Bureau (2010E15SF166), grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project Nos.: CUHK 475711, 416712), and a project BMEp2-13 of the Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong.
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