- Email: [email protected]
Abnormal regional homogeneity and its correlations with personality in first-episode, treatment-naive somatization disorder
International Journal of Psychophysiology 97 (2015) 108–112
Contents lists available at ScienceDirect
International Journal of Psychophysiology journal homepage: www.elsevier.com/locate/ijpsycho
Abnormal regional homogeneity and its correlations with personality in first-episode, treatment-naive somatization disorder Yan Song a,1, Qinji Su a,1, Muliang Jiang b, Feng Liu c, Dapeng Yao a, Yi Dai b, Liling Long b, Miaoyu Yu a, Jianrong Liu a, Zhikun Zhang a, Jian Zhang a, Changqing Xiao a, Wenbin Guo a,⁎ a b c
Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi 530021, China Department of Radiology, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi 530021, China Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China
a r t i c l e
i n f o
Article history: Received 21 January 2015 Received in revised form 23 April 2015 Accepted 24 May 2015 Available online 27 May 2015 Keywords: Somatization disorder Regional homogeneity Functional magnetic resonance imaging Personality
a b s t r a c t Background: Structural and functional abnormalities of the default mode network (DMN) and their correlations with personality have been found in somatization disorder (SD). However, no study is conducted to identify regional neural activity and its correlations with personality in SD. In this study, regional homogeneity (ReHo) was applied to explore whether abnormal regional neural activity is present in patients with SD and its correlations with personality measured by Eysenck Personality Questionnaire (EPQ). Methods: Twenty-five first-episode, treatment-naive patients with SD and 28 sex-, age-, and education-matched healthy controls participated in the whole study. During the scanning, all subjects were instructed to lie still with their eyes closed and remain awake. A ReHo approach was employed to analyze the data. Results: The SD group had a significantly increased ReHo in the left angular gyrus (AG) compared to healthy controls. The increased ReHo positively correlated to the neuroticism scores of EPQ (EPQ-N). No other correlations were detected between the ReHo values and other related factors, such as symptom severity and education level. Conclusions: Our results suggest that abnormal regional neural activity of the DMN may play a key role in SD with clinical implications and emphasize the importance of the DMN in the pathophysiological process of SD. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Somatization disorder (SD) is characterized by a set of unexplained somatic symptoms with a prevalence of 4–7% in general population (Rief et al., 2001). The diagnosis of SD is somewhat difficult for physicians, which causes repetitively medical examinations to patients and increases health care utilization. Recent advances in neuroimaging techniques improve the possibility to explore the neural activity abnormalities associated with SD and promote the understanding of the pathophysiology of SD (Browning et al., 2011). During the last decade, limited neuroimaging evidence has been acquired in patients with SD. Garcia-Campayo et al. found that 7 patients with SD in all of 11 patients had hypoperfusion in the right cerebellum, frontal and prefrontal regions, and temporoparietal areas using single photon emission computed tomography (SPECT) (Garcia‐ Campayo et al., 2001). Structural magnetic resonance imaging (MRI) studies have proposed that SD is associated with gray matter volume changes of brain regions, such as caudate nuclei (Hakala et al., 2004), amygdala (Atmaca et al., 2011), and pituitary (Yildirim et al., 2012). ⁎ Corresponding author. Tel.: +86 771 3277200. E-mail address: [email protected] (W. Guo). 1 These authors contributed equally to this work.
http://dx.doi.org/10.1016/j.ijpsycho.2015.05.012 0167-8760/© 2015 Elsevier B.V. All rights reserved.
Evaluating glucose metabolism of four brain regions of interest, Hakala et al. observed that patients with SD had decreased glucose metabolism in caudate, putamen nuclei and thalamus (Hakala et al., 2006). Also, the dysfunction in posterior cingulate cortex, a crucial zone of the defaultmode network (DMN), is disrupted during pain perception and underlies the cognitive and behavioral impairments in patients with SD accompanying with chronic pain (Fayed et al., 2012). Meanwhile, Lemche et al. found that patients with SD had altered activity of anterior ventral precuneus, posterior cingulate cortex and anteromedial thalamus when they were in happy and sad emotional states (Lemche et al., 2013). Su et al. observed that patients with SD displayed significantly increased functional connectivity strength in the right inferior temporal gyrus (Su et al., 2015), and altered neural activity in the superior medial prefrontal cortex and left precuneus (Su et al., 2014). These studies indicate that patients with SD have brain structural and functional abnormalities, especially in the DMN. Recently, extensive work has been done in the area of resting-state fMRI. Functional connectivity is one of the most widely used methods to explore the fMRI data (Battaglia et al., 1995) and provides important information for a number of psychiatric disorders, such as schizophrenia (Anderson and Cohen, 2013; Guo et al., 2015a), depression (Guo et al., 2015b; Ma et al., 2012) and attention deficit hyperactivity disorder (Hoekzema et al., 2014). However, this method cannot provide
Y. Song et al. / International Journal of Psychophysiology 97 (2015) 108–112
information of the local regional neural activity abnormality when one region shows functional connectivity abnormality with the others. Therefore, studies are needed to examine the regional activity in patients with SD. Regional homogeneity (ReHo) is designed to measure the similarity or synchronization of the time series of the nearest neighboring voxels. In the present study, we used Kendall's coefficient of concordance (KCC) to measure the ReHo values of the time series of a given voxel with its nearest voxels. Higher ReHo may represent neural hyperactivity in the regional area, and vice versa (Zang et al., 2004). Abnormal ReHo may indicate the disruption of temporal aspects of neural activity (He et al., 2007) and is associated with the pathophysiology of psychiatric disorders (Liu et al., 2010). The ReHo approach was well applied in psychiatric disorders such as schizophrenia, ADHD and depression (Cao et al., 2006; Chen et al., 2012; Guo et al., 2011a,b; Huang et al., 2014; Liu et al., 2006; Wu et al., 2011; Yao et al., 2009). However, no study is conducted in patients with SD using the ReHo method. Clinically, personality traits have been revealed to correlate with the phenomenon of somatization. For example, neuroticism, a broad dimension of individual differences in the tendency to experience negative distressing emotions, is high in SD patients and related to somatization (De Gucht, 2003). Besides, the scores of Symptom Checklist 90 (SCL-90) subscales including somatization factor show a significantly positive correlation to neuroticism scores of Eysenck Personality Questionnaire (EPQ-N) (Zhang et al., 2012). Interestingly, Adelstein et al. (2011) found that extraversion and neuroticism were encoded between seed regions and the lateral paralimbic regions and dorsomedial prefrontal cortex, respectively. Lei et al. (2013) proposed that the relation between individual differences in personality and scaling dynamics in the DMN was linked with introspective cognition by resting-state fMRI. However, it remains unclear to the relationship between personality and brain activity in patients with SD. Here, we conducted a study to explore the regional brain homogeneity in patients with SD. We hypothesized that abnormal ReHo would exist in certain brain regions in SD patients. Since the DMN activity is altered in SD patients (Su et al., 2014), we expected the DMN to be particularly affected. We also expected that abnormal ReHo was correlated to personality, especially neuroticism assessed by EPQ.
2. Materials and methods 2.1. Subjects We recruited 26 first-episode, treatment-naive patients with SD (aged from 18 to 60), and 30 age-, sex-, education-matched, righthanded healthy controls. All patients were diagnosed based on the Structured Clinical Interview of the DSM-IV (SCID) (First et al., 2012). Exclusion criteria for the participants included any history of loss consciousness, mental retardation, serious medical or neurological illness. Individuals with other psychiatric disorders such as schizophrenia, bipolar disorder or personality disorders were also excluded. Since depression is a common comorbidity in patients with SD, comorbidity with depression is allowed. None of healthy controls had serious medical or neuropsychiatric disease or major psychiatric or neurological illness in their first-degree relatives. All subjects were assessed with EPQ (Eysenck and Eysenck, 1972) to measure personality dimensions. Hamilton depression scale (HAMD) (Hamilton, 1960), Hamilton anxiety scale (HAMA) (Hamilton, 1959) and the somatization subscale of SCL-90 (Derogatis et al., 1976) were respectively applied to assess the severity of depression, anxiety and somatic symptoms at the scan day. These scales have been validated in the Chinese patient population with high reliability and validity. Each subject signed an informed consent and the study was approved by the Ethics Committee of the First Affiliated Hospital, Guangxi Medical University.
109
2.2. Scan acquisition Magnetic resonance images were collected using a Siemens 3.0 T scanner (Siemens, Erlangen, Germany). All participants were required to keep motionless with their eyes closed, and remain awake during image acquisition. Resting-state fMRI was performed using an echoplanar imaging sequence with the following parameters: repetition time/echo time (TR/TE) = 2000/30 ms, number of slice = 30, 64 × 64 matrix, 90° flip angle, 24 cm × 24 cm FOV, 4 mm slice thickness, 0.4 mm gap, and number of volumes = 250 (500 s). 2.3. Data processing Statistical parametric mapping software (SPM8, http://www.fil.ion. ucl.ac.uk/spm) was used to preprocess image. The first 10 volumes were discarded to allow for the signal reaching equilibrium. The remaining 240 volumes were slice acquisition correction and realigned for the head motion. Participants with head movement exceeding 2.0 mm of maximum displacement in x, y, or z directions and 2.0° of angular motion were excluded. Then the fMRI images were normalized to the standard SPM8 echo-planar imaging template, and resampled to 3 × 3 × 3 mm3. The resulting fMRI data were temporally band-pass filtered (0.01–0.08 Hz) and linear detrended to reduce low-frequency drift and physiological high frequency noise. ReHo was performed using software REST (Song et al., 2011). The formula used to calculate the KCC value has been reported previously (Zang et al., 2004). In order to reduce the effect of individual variations in KCC values, normalization of ReHo maps was done by dividing KCC among each voxel by the averaged KCC of the entire brain. The data were smoothed with a Gaussian kernel of 8 mm full-width at halfmaximum. 2.4. Statistical analyses Chi-square test was used to compare sex ratio. Distributions of age and years of education were compared by two sample t-tests. Voxelbased comparisons of whole-brain ReHo maps were performed by using two sample t-tests. The resulting statistical maps were set at a threshold of p b 0.05 (corrected for multiple comparisons with a combined threshold of p b 0.005 and a minimum continuous cluster number of 74 voxels) using Monte Carlo simulations in the AFNI AlphaSim program (http://afni.nih.gov/afni/docpdf/AlphaSim.pdf). Linear correlations were conducted between abnormal ReHo values and psychological performances after assessing the data normality. The significance level was set at p b 0.05. 3. Results 3.1. Subjects Twenty-five patients and twenty-eight healthy controls were enrolled in the study. One patient and two healthy controls were excluded due to excessive head movement. Patients with SD and healthy controls did not have significant differences in age (t-tests t = 0.82, df = 51, p = 0.42), sex ratio (chi-square test x2 = 0.25, df = 1, p = 0.61), and educational level (t-tests t = −0.10, df = 51, p = 0.92). Demographic information and clinical characteristics were shown in Table 1. 3.2. ReHo: patients versus controls Compared with healthy controls, patients with SD exhibited a significantly increased ReHo in the left angular gyrus (AG) (t = 3.6875, cluster size = 96 voxels). There is no decreased ReHo in any brain regions relative to healthy controls (Table 2 and Fig. 1).
110
Y. Song et al. / International Journal of Psychophysiology 97 (2015) 108–112
Table 1 Demographics and clinical characteristics of patients and healthy controls. Variables (mean ± standard deviation)
Patients
Controls
p value
Gender (female/male) Age, years Education, years Illness duration, months HAMD HAMA Somatization subscale of SCL-90 Personality traits scores of EPQ Extraversion Psychoticism Neuroticism Lie
21/4 41.00 ± 10.76 7.72 ± 4.39 59.12 ± 62.22 18.84 ± 7.31 22.96 ± 10.95 28.48 ± 10.37
22/6 38.71 ± 9.59 7.82 ± 2.59
0.732a 0.417b 0.920b
2.60 ± 1.83 0.53 ± 0.99 14.32 ± 3.44
b0.001b b0.001b b0.001b
46.84 ± 11.02 50.52 ± 9.01 57.36 ± 9.18 49.44 ± 12.31
49.75 ± 9.65 45.00 ± 8.54 46.78 ± 10.24 47.96 ± 11.01
0.311b 0.026b b0.001b 0.647b
HAMD: Hamilton depression scale; HAMA: Hamilton anxiety scale; SCL-90: Symptom Check List-90; EPQ: Eysenck Personality Questionnaire. a The p value for gender distribution in the two groups was obtained by chi-square test. b The p values were obtained by two sample t-tests.
Table 2 Brain regions with increased ReHo in SD. Brain regions
Patients N Controls Left angular gyrus
Voxels
96
MNI coordinates (mm) x
y
z
-42
-66
48
t value
3.6875
x, y, z, coordinates of primary peak locations in the MNI space; t statistical value of peak voxel shows ReHo differences between the SD group and control group. SD: somatization disorder.
Fig. 2. Positive correlation between the ReHo values in left angular gyrus and the neuroticism scores of EPQ in the patient group. ReHo = regional homogeneity; EPQ = Eysenck Personality Questionnaire.
psychoticism, and lie) in the patients. No other factors, such as symptom severity and education level, were detected to be related to abnormal ReHo values or the domains of EPQ (neuroticism, extraversion, psychoticism, and lie) in the patients. In healthy controls, no correlations were found between the ReHo values and other related variables, such as the EPQ (neuroticism, extraversion, psychoticism, and lie) scores and HAMD/HAMA scores.
3.3. The correlations between ReHo values in the left AG and related factors 4. Discussion Significantly positive correlation between increased ReHo in the left AG and the scores of EPQ-N was found in the patient group (r = 0.428, p = 0.033) (Fig. 2). There were also no correlations between increased ReHo in the left AG and the other domains of EPQ (extraversion,
The primary finding of this study was that abnormal ReHo in the DMN was observed in drug-naive, first-episode SD patients. Consistent with our hypothesis, patients with SD had a significantly increased
Fig. 1. ReHo differences between patients with SD and controls. The region with increased ReHo in SD patients was the left angular gyrus. The color bar represents the t values of the group analysis. ReHo = regional homogeneity.
Y. Song et al. / International Journal of Psychophysiology 97 (2015) 108–112
ReHo in the left AG compared to healthy controls. Furthermore, increased ReHo values in the left AG were significantly correlated to EPQ-N in the patient group, implying that EPQ-N might have clinical implications for psychopathology of SD. Previous studies reported neural abnormalities in patients with SD using a variety of neuroimaging approaches. Stoeter et al. (2007) found increased brain activations in pain processing areas, such as basal ganglia, thalamus and opercular insular area in somatoform pain disorder while an episode of pain was induced by a pin prick. In structural MRI studies, patients with SD showed significantly decreased volumes in the bilateral amygdala involved in emotional perception (Atmaca et al., 2011). Based on the assumptions that pituitary volumes might be involved in the occurrence of somatoform symptoms, Yildirim et al. (2012) found that SD patients had smaller pituitary volumes than healthy controls. In the present study, increased ReHo was found in the left AG in SD patients. AG is a crucial area of the DMN and involved in a lot of processes associated with language, number processing, memory retrieval and attention (Raichle et al., 2001); it is also important in making semantic associations in reading, comprehension of speech and written language (Obleser and Kotz, 1991), and integrating conceptual understanding of the language term “left” or “right” with its location in space (Hirnstein et al., 2011). Located at the crossroads of processing touch, hearing and vision, AG is critical to conceptual metaphors and cross-modal abstractions (Rosenthal et al., 2009). Moreover, AG has other important functions in mental constructs, like thoughts, cognition, and beliefs related to oneself or others (Frith and Frith, 2003). Besides, the spatial fractionation of the AG is divided into multiple subdivisions that contribute to “bottom-up” and “top-down” mechanisms across numerous tasks (Seghier, 2013). The neural activity abnormality in the AG may affect the “top-down” regulation and causes emotional, awareness and behavioral alterations (Liu et al., 2015; Liu et al., 2012). Furthermore, an interesting experiment exhibited that a woman perceived a phantom existence behind her when AG was stimulated, suggesting that AG may be apt to cause uncomfortable feelings in perceived location of the body but not the actual position of the body (Arzy et al., 2006). It may also explain why somatic symptoms are unexplained in patients with SD. Another finding of this study was left-sided affected brain regions in SD. Lack of normal symmetry in AG has been long observed. The left AG is in charge of semantic access and arithmetic skills, and the right AG contributes to spatiovisual attention, maintenance and control of covert reorienting of attention (Sack, 2009; Seghier, 2013). In task-related fMRI, the right AG is stirred up by the conflict tasks, while the left AG is activated especially in a sentence comprehension task (Ye and Zhou, 2009). The left AG may act as a memory buffer for intention maintenance (Kalpouzos et al., 2010), and may play a role in the verbal coding of numbers (Dehaene et al., 2003) and the arithmetic operations (Ischebeck et al., 2009). Consistent with the previous findings, our results suggest that left-sided affected asymmetry may be a characteristic for patients with SD. Eysenck conceptualized personality as extroversion/introversion, neuroticism and psychoticism using factor analysis. Extraversion represents sociability, being outgoing, talkative, and in need of external stimulation; neuroticism is characterized by high levels of negative affect such as depression and anxiety; and psychoticism is associated with psychotic episode (or break with reality) and aggressiveness. A fourth dimension, the lie scale, represents social naivety or deliberately attempting to control their scores (Eysenck and Eysenck, 1975). Compared with healthy controls, higher scores of HAMD and HAMA were found in the patient group. These results are consistent with previous findings that comorbidities exist among depression, anxiety and somatization with a high ratio (Mergl et al., 2007). Moreover, Fink et al. (2004) found that 36% of SD patients had another psychiatric disorder, 11% with depression and 25% with anxiety disorder. Leiknes et al. (2007) reported that about 45% of SD patients had comorbidities with anxiety/depression.
111
It is noteworthy that increased ReHo values in the left AG were positively correlated to the EPQ-N in patients with SD. The neuroticism subscale represents the experience of negative affect, emotional unstableness, depressive symptomatology, obsessiveness, and anxietybased problems (Eysenck and Eysenck, 1971). Increased cardiac vagal tone in response to pain is relevant to neuroticism, suggesting that personality trait may influence pain perception (Paine et al., 2009). Subjects with higher neuroticism score reported more somatic symptoms resulting in more health care-seeking behavior, which in turn affected their health-related life quality (Kempen et al., 1997; VanderZee et al., 1996). The current correlations indicate that individuals with higher neuroticism scores may be apt to suffer from SD in their lifetime. Apart from the relatively small sample size, there are a few limitations that should be acknowledged. First, depression and somatization are comorbid at a high ratio (Bjelland et al., 2002; Clark et al., 1994; Simon et al., 1996). Depression may be an accompany characteristic of SD which could not be removed in the present study. Therefore, depression might have biased the present results. Second, SD is more likely present in the females, and high percentage of females in our study might limit the ability to explore sex difference in patients with SD. Third, physiological noises such as respiratory and heart rhythm cannot be completely eliminated by using a relatively low sampling rate (TR = 2 s). More comprehensive methods are needed to remove such physiological noises. In summary, the present study first found that increased ReHo in the left AG might act as a key role in SD with clinical implications, and emphasized the importance of DMN in the physiological processes of SD. More comprehensive ReHo studies are required to observe the abnormality referred to trait or state alterations in SD. Contributors Drs. Guo W and Xiao C designed the study. Drs. Song Y, Yao D, Jiang M, Dai Y, Liu J, Yu L, Su Q, and Zhang J collected the original imaging data. Drs. Liu F, Zhang Z and Long L managed and analyzed the imaging data, and Drs. Song Y and Su Q wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript. Acknowledgments This study was supported by grants from the National Natural Science Foundation of China (Grant No. 81260210), the Natural Science Foundation of Guangxi Province for Distinguished Young Scientists (Grant No. 2014GXNSFGA118010), and the Natural Science Foundation of Guangxi Province (Grant No. 2013GXNSFAA019107). We thank all the individuals who served as the research participants. References Adelstein, J.S., Shehzad, Z., Mennes, M., DeYoung, C.G., Zuo, X.-N., Kelly, C., Margulies, D.S., Bloomfield, A., Gray, J.R., Castellanos, F.X., 2011. Personality is reflected in the brain's intrinsic functional architecture. PLoS ONE 6, e27633. Anderson, A., Cohen, M.S., 2013. Decreased small-world functional network connectivity and clustering across resting state networks in schizophrenia: an fMRI classification tutorial. Front. Hum. Neurosci. 7. Arzy, S., Seeck, M., Ortigue, S., Spinelli, L., Blanke, O., 2006. Induction of an illusory shadow person. Nature 443, 287-287. Atmaca, M., Sirlier, B., Yildirim, H., Kayali, A., 2011. Hippocampus and amygdalar volumes in patients with somatization disorder. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 35, 1699–1703. Battaglia, M., Bernardeschi, L., Politi, E., Bertella, S., Bellodi, L., 1995. Comorbidity of panic and somatization disorder: a genetic–epidemiological approach. Compr. Psychiatry 36, 411–420. Bjelland, I., Dahl, A.A., Haug, T.T., Neckelmann, D., 2002. The validity of the Hospital Anxiety and Depression Scale: an updated literature review. J. Psychosom. Res. 52, 69–77. Browning, M., Fletcher, P., Sharpe, M., 2011. Can neuroimaging help us to understand and classify somatoform disorders? A systematic and critical review. Psychosom. Med. 73, 173. Cao, Q., Zang, Y., Sun, L., Sui, M., Long, X., Zou, Q., Wang, Y., 2006. Abnormal neural activity in children with attention deficit hyperactivity disorder: a resting-state functional magnetic resonance imaging study. Neuroreport 17, 1033–1036.
112
Y. Song et al. / International Journal of Psychophysiology 97 (2015) 108–112
Chen, J.D., Liu, F., Xun, G.L., Chen, H.F., Hu, M.R., Guo, X.F., Xiao, C.Q., Wooderson, S.C., Guo, W.B., Zhao, J.P., 2012. Early and late onset, first-episode, treatment-naive depression: same clinical symptoms, different regional neural activities. J. Affect. Disord. 143, 56–63. Clark, D.A., Steer, R.A., Beck, A.T., 1994. Common and specific dimensions of self-reported anxiety and depression: implications for the cognitive and tripartite models. J. Abnorm. Psychol. 103, 645. De Gucht, V., 2003. Stability of neuroticism and alexithymia in somatization. Compr. Psychiatry 44, 466–471. Dehaene, S., Piazza, M., Pinel, P., Cohen, L., 2003. Three parietal circuits for number processing. Cogn. Neuropsychol. 20, 487–506. Derogatis, L.R., Rickels, K., Rock, A.F., 1976. The SCL-90 and the MMPI: a step in the validation of a new self-report scale. Br. J. Psychiatry 128, 280–289. Eysenck, S., Eysenck, H., 1971. Attitudes to sex, personality and lie scale scores. Percept. Mot. Skills 33, 216–218. Eysenck, S., Eysenck, H., 1972. The questionnaire measurement of psychoticism. Psychol. Med. 2, 50–55. Eysenck, H.J., Eysenck, S.B.G., 1975. Manual of the Eysenck Personality Questionnaire (junior and adult). Hodder and Stoughton. Fayed, N., Andres, E., Rojas, G., Moreno, S., Serrano‐Blanco, A., Roca, M., Garcia‐Campayo, J., 2012. Brain dysfunction in fibromyalgia and somatization disorder using proton magnetic resonance spectroscopy: a controlled study. Acta Psychiatr. Scand. 126, 115–125. Fink, P., Hansen, M.S., Oxhoj, M.-L., 2004. The prevalence of somatoform disorders among internal medical inpatients. J. Psychosom. Res. 56, 413–418. First, M.B., Spitzer, R.L., Gibbon, M., Williams, J.B., 2012. Structured Clinical Interview for DSM-IV® Axis I Disorders (SCID-I), Clinician Version. Administration Booklet, American Psychiatric Pub. Frith, U., Frith, C.D., 2003. Development and neurophysiology of mentalizing. Phil. Trans. R. Soc. Lond. B Biol. Sci. 358, 459–473. Garcia‐Campayo, J., Sanz‐Carrillo, C., Baringo, T., Ceballos, C., 2001. SPECT scan in somatization disorder patients: an exploratory study of eleven cases. Aust. N. Z. J. Psychiatry 35, 359–363. Guo, W.B., Liu, F., Xue, Z.M., Yu, Y., Ma, C.Q., Tan, C.L., Sun, X.L., Chen, J.D., Liu, Z.N., Xiao, C.Q., Chen, H.F., Zhao, J.P., 2011a. Abnormal neural activities in first-episode, treatment-naive, short-illness-duration, and treatment-response patients with major depressive disorder: a resting-state fMRI study. J. Affect. Disord. 135, 326–331. Guo, W.B., Sun, X.L., Liu, L., Xu, Q., Wu, R.R., Liu, Z.N., Tan, C.L., Chen, H.F., Zhao, J.P., 2011b. Disrupted regional homogeneity in treatment-resistant depression: a resting-state fMRI study. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 35, 1297–1302. Guo, W., Liu, F., Liu, J., Yu, L., Zhang, J., Zhang, Z., Xiao, C., Zhai, J., Zhao, J., 2015a. Abnormal causal connectivity by structural deficits in first-episode, drug-naive schizophrenia at rest. Schizophr. Bull. 41, 57–65. Guo, W., Liu, F., Liu, J., Yu, M., Zhang, Z., Liu, G., Xiao, C., Zhao, J., 2015b. Increased cerebellar-default-mode-network connectivity in drug-naive major depressive disorder at rest. Medicine 94, e560. Hakala, M., Karlsson, H., Kurki, T., Aalto, S., Koponen, S., Vahlberg, T., Niemi, P.M., 2004. Volumes of the caudate nuclei in women with somatization disorder and healthy women. Psychiatry Res. Neuroimaging 131, 71–78. Hakala, M., Vahlberg, T., NIEMI, P.M., Karlsson, H., 2006. Brain glucose metabolism and temperament in relation to severe somatization. Psychiatry Clin. Neurosci. 60, 669–675. Hamilton, M., 1959. The assessment of anxiety states by rating. Br. J. Med. Psychol. 32, 50–55. Hamilton, M., 1960. A rating scale for depression. J. Neurol. Neurosurg. Psychiatry 23, 56. He, Y., Wang, L., Zang, Y., Tian, L., Zhang, X., Li, K., Jiang, T., 2007. Regional coherence changes in the early stages of Alzheimer's disease: a combined structural and resting-state functional MRI study. NeuroImage 35, 488–500. Hirnstein, M., Bayer, U., Ellison, A., Hausmann, M., 2011. TMS over the left angular gyrus impairs the ability to discriminate left from right. Neuropsychologia 49, 29–33. Hoekzema, E., Carmona, S., Ramos‐Quiroga, J.A., Richarte Fernández, V., Bosch, R., Soliva, J.C., Rovira, M., Bulbena, A., Tobeña, A., Casas, M., 2014. An independent components and functional connectivity analysis of resting state fMRI data points to neural network dysregulation in adult ADHD. Hum. Brain Mapp. 35, 1261–1272. Huang, X., Huang, P., Li, D., Zhang, Y., Wang, T., Mu, J., Li, Q., Xie, P., 2014. Early brain changes associated with psychotherapy in major depressive disorder revealed by resting-state fMRI: evidence for the top-down regulation theory. Int. J. Psychophysiol. 94, 437–444. Ischebeck, A., Zamarian, L., Schocke, M., Delazer, M., 2009. Flexible transfer of knowledge in mental arithmetic—an fMRI study. NeuroImage 44, 1103–1112. Kalpouzos, G., Eriksson, J., Sjölie, D., Molin, J., Nyberg, L., 2010. Neurocognitive systems related to real-world prospective memory. PLoS ONE 5, e13304. Kempen, G.I., Jelicic, M., Ormel, J., 1997. Personality, chronic medical morbidity, and health-related quality of life among older persons. Health Psychol. 16, 539. Lei, X., Zhao, Z., Chen, H., 2013. Extraversion is encoded by scale-free dynamics of default mode network. NeuroImage 74, 52–57.
Leiknes, K.A., Finset, A., Moum, T., Sandanger, I., 2007. Current somatoform disorders in Norway: prevalence, risk factors and comorbidity with anxiety, depression and musculoskeletal disorders. Soc. Psychiatry Psychiatr. Epidemiol. 42, 698–710. Lemche, E., Giampietro, V.P., Brammer, M.J., Surguladze, S.A., Williams, S.C., Phillips, M.L., 2013. Somatization severity associated with postero-medial complex structures. Sci. Rep. 3. Liu, H., Liu, Z., Liang, M., Hao, Y., Tan, L., Kuang, F., Yi, Y., Xu, L., Jiang, T., 2006. Decreased regional homogeneity in schizophrenia: a resting state functional magnetic resonance imaging study. Neuroreport 17, 19–22. Liu, Z., Xu, C., Xu, Y., Wang, Y., Zhao, B., Lv, Y., Cao, X., Zhang, K., Du, C., 2010. Decreased regional homogeneity in insula and cerebellum: a resting-state fMRI study in patients with major depression and subjects at high risk for major depression. Psychiatry Res. Neuroimaging 182, 211–215. Liu, F., Hu, M., Wang, S., Guo, W., Zhao, J., Li, J., Xun, G., Long, Z., Zhang, J., Wang, Y., Zeng, L., Gao, Q., Wooderson, S.C., Chen, J., Chen, H., 2012. Abnormal regional spontaneous neural activity in first-episode, treatment-naive patients with late-life depression: a resting-state fMRI study. Prog. Neuropsychopharmacol. Biol. Psychiatry 39, 326–331. Liu, F., Guo, W., Fouche, J.P., Wang, Y., Wang, W., Ding, J., Zeng, L., Qiu, C., Gong, Q., Zhang, W., Chen, H., 2015. Multivariate classification of social anxiety disorder using whole brain functional connectivity. Brain Struct. Funct. 220, 101–115. Ma, C., Ding, J., Li, J., Guo, W., Long, Z., Liu, F., Gao, Q., Zeng, L., Zhao, J., Chen, H., 2012. Resting-state functional connectivity bias of middle temporal gyrus and caudate with altered gray matter volume in major depression. PLoS ONE 7, e45263. Mergl, R., Seidscheck, I., Allgaier, A.K., Möller, H.J., Hegerl, U., Henkel, V., 2007. Depressive, anxiety, and somatoform disorders in primary care: prevalence and recognition. Depression Anxiety 24, 185–195. Obleser, J., Kotz, S.A., 1991. Expectancy constraints in degraded speech modulate the language comprehension network. Cereb. Cortex 20, 633–640 (New York, N.Y.). Paine, P., Worthen, S., Gregory, L., Thompson, D., Aziz, Q., 2009. Personality differences affect brainstem autonomic responses to visceral pain. Neurogastroenterol. Motil. 21, 1155–e1198. Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L., 2001. A default mode of brain function. Proc. Natl. Acad. Sci. 98, 676–682. Rief, W., Hessel, A., Braehler, E., 2001. Somatization symptoms and hypochondriacal features in the general population. Psychosom. Med. 63, 595–602. Rosenthal, C.R., Roche-Kelly, E.E., Husain, M., Kennard, C., 2009. Response-dependent contributions of human primary motor cortex and angular gyrus to manual and perceptual sequence learning. J. Neurosci. 29, 15115–15125. Sack, A.T., 2009. Parietal cortex and spatial cognition. Behav. Brain Res. 202, 153–161. Seghier, M.L., 2013. The angular gyrus multiple functions and multiple subdivisions. Neuroscientist 19, 43–61. Simon, G., Gater, R., Kisely, S., Piccinelli, M., 1996. Somatic symptoms of distress: an international primary care study. Psychosom. Med. 58, 481–488. Song, X.W., Dong, Z.Y., Long, X.Y., Li, S.F., Zuo, X.N., Zhu, C.Z., He, Y., Yan, C.G., Zang, Y.F., 2011. REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PLoS ONE 6, e25031. Stoeter, P., Bauermann, T., Nickel, R., Corluka, L., Gawehn, J., Vucurevic, G., Vossel, G., Egle, U., 2007. Cerebral activation in patients with somatoform pain disorder exposed to pain and stress: an fMRI study. NeuroImage 36, 418–430. Su, Q., Yao, D., Jiang, M., Liu, F., Jiang, J., Xu, C., Dai, Y., Yu, M., Long, L., Li, H., 2014. Dissociation of regional activity in default mode network in medication-naive, firstepisode somatization disorder. PLoS ONE 9, e99273. Su, Q., Yao, D., Jiang, M., Liu, F., Jiang, J., Xu, C., Dai, Y., Yu, M., Long, L., Li, H., 2015. Increased functional connectivity strength of right inferior temporal gyrus in first-episode, drug-naive somatization disorder. Aust. N. Z. J. Psychiatry 49, 74–81. VanderZee, K.I., Sanderman, R., Heyink, J., 1996. A comparison of two multidimensional measures of health status: the Nottingham Health Profile and the RAND 36-Item Health Survey 1.0. Qual. Life Res. 5, 165–174. Wu, Q.Z., Li, D.M., Kuang, W.H., Zhang, T.J., Lui, S., Huang, X.Q., Chan, R.C., Kemp, G.J., Gong, Q.Y., 2011. Abnormal regional spontaneous neural activity in treatment‐refractory depression revealed by resting‐state fMRI. Hum. Brain Mapp. 32, 1290–1299. Yao, Z., Wang, L., Lu, Q., Liu, H., Teng, G., 2009. Regional homogeneity in depression and its relationship with separate depressive symptom clusters: a resting-state fMRI study. J. Affect. Disord. 115, 430–438. Ye, Z., Zhou, X., 2009. Conflict control during sentence comprehension: fMRI evidence. NeuroImage 48, 280–290. Yildirim, H., Atmaca, M., Sirlier, B., Kayali, A., 2012. Pituitary volumes are reduced in patients with somatization disorder. Psychiatr. Investig. 9, 278–282. Zang, Y., Jiang, T., Lu, Y., He, Y., Tian, L., 2004. Regional homogeneity approach to fMRI data analysis. NeuroImage 22, 394–400. Zhang, L., Liu, X., Zheng, G.-J., Zhou, L., Lin, D.-Y., Wang, X.-D., He, H., 2012. Eysenck personality and psychosocial status of adult patients with malocclusion. Asian Pac. J. Trop. Med. 5, 151–156.
Contents lists available at ScienceDirect
International Journal of Psychophysiology journal homepage: www.elsevier.com/locate/ijpsycho
Abnormal regional homogeneity and its correlations with personality in first-episode, treatment-naive somatization disorder Yan Song a,1, Qinji Su a,1, Muliang Jiang b, Feng Liu c, Dapeng Yao a, Yi Dai b, Liling Long b, Miaoyu Yu a, Jianrong Liu a, Zhikun Zhang a, Jian Zhang a, Changqing Xiao a, Wenbin Guo a,⁎ a b c
Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi 530021, China Department of Radiology, the First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi 530021, China Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China
a r t i c l e
i n f o
Article history: Received 21 January 2015 Received in revised form 23 April 2015 Accepted 24 May 2015 Available online 27 May 2015 Keywords: Somatization disorder Regional homogeneity Functional magnetic resonance imaging Personality
a b s t r a c t Background: Structural and functional abnormalities of the default mode network (DMN) and their correlations with personality have been found in somatization disorder (SD). However, no study is conducted to identify regional neural activity and its correlations with personality in SD. In this study, regional homogeneity (ReHo) was applied to explore whether abnormal regional neural activity is present in patients with SD and its correlations with personality measured by Eysenck Personality Questionnaire (EPQ). Methods: Twenty-five first-episode, treatment-naive patients with SD and 28 sex-, age-, and education-matched healthy controls participated in the whole study. During the scanning, all subjects were instructed to lie still with their eyes closed and remain awake. A ReHo approach was employed to analyze the data. Results: The SD group had a significantly increased ReHo in the left angular gyrus (AG) compared to healthy controls. The increased ReHo positively correlated to the neuroticism scores of EPQ (EPQ-N). No other correlations were detected between the ReHo values and other related factors, such as symptom severity and education level. Conclusions: Our results suggest that abnormal regional neural activity of the DMN may play a key role in SD with clinical implications and emphasize the importance of the DMN in the pathophysiological process of SD. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Somatization disorder (SD) is characterized by a set of unexplained somatic symptoms with a prevalence of 4–7% in general population (Rief et al., 2001). The diagnosis of SD is somewhat difficult for physicians, which causes repetitively medical examinations to patients and increases health care utilization. Recent advances in neuroimaging techniques improve the possibility to explore the neural activity abnormalities associated with SD and promote the understanding of the pathophysiology of SD (Browning et al., 2011). During the last decade, limited neuroimaging evidence has been acquired in patients with SD. Garcia-Campayo et al. found that 7 patients with SD in all of 11 patients had hypoperfusion in the right cerebellum, frontal and prefrontal regions, and temporoparietal areas using single photon emission computed tomography (SPECT) (Garcia‐ Campayo et al., 2001). Structural magnetic resonance imaging (MRI) studies have proposed that SD is associated with gray matter volume changes of brain regions, such as caudate nuclei (Hakala et al., 2004), amygdala (Atmaca et al., 2011), and pituitary (Yildirim et al., 2012). ⁎ Corresponding author. Tel.: +86 771 3277200. E-mail address: [email protected] (W. Guo). 1 These authors contributed equally to this work.
http://dx.doi.org/10.1016/j.ijpsycho.2015.05.012 0167-8760/© 2015 Elsevier B.V. All rights reserved.
Evaluating glucose metabolism of four brain regions of interest, Hakala et al. observed that patients with SD had decreased glucose metabolism in caudate, putamen nuclei and thalamus (Hakala et al., 2006). Also, the dysfunction in posterior cingulate cortex, a crucial zone of the defaultmode network (DMN), is disrupted during pain perception and underlies the cognitive and behavioral impairments in patients with SD accompanying with chronic pain (Fayed et al., 2012). Meanwhile, Lemche et al. found that patients with SD had altered activity of anterior ventral precuneus, posterior cingulate cortex and anteromedial thalamus when they were in happy and sad emotional states (Lemche et al., 2013). Su et al. observed that patients with SD displayed significantly increased functional connectivity strength in the right inferior temporal gyrus (Su et al., 2015), and altered neural activity in the superior medial prefrontal cortex and left precuneus (Su et al., 2014). These studies indicate that patients with SD have brain structural and functional abnormalities, especially in the DMN. Recently, extensive work has been done in the area of resting-state fMRI. Functional connectivity is one of the most widely used methods to explore the fMRI data (Battaglia et al., 1995) and provides important information for a number of psychiatric disorders, such as schizophrenia (Anderson and Cohen, 2013; Guo et al., 2015a), depression (Guo et al., 2015b; Ma et al., 2012) and attention deficit hyperactivity disorder (Hoekzema et al., 2014). However, this method cannot provide
Y. Song et al. / International Journal of Psychophysiology 97 (2015) 108–112
information of the local regional neural activity abnormality when one region shows functional connectivity abnormality with the others. Therefore, studies are needed to examine the regional activity in patients with SD. Regional homogeneity (ReHo) is designed to measure the similarity or synchronization of the time series of the nearest neighboring voxels. In the present study, we used Kendall's coefficient of concordance (KCC) to measure the ReHo values of the time series of a given voxel with its nearest voxels. Higher ReHo may represent neural hyperactivity in the regional area, and vice versa (Zang et al., 2004). Abnormal ReHo may indicate the disruption of temporal aspects of neural activity (He et al., 2007) and is associated with the pathophysiology of psychiatric disorders (Liu et al., 2010). The ReHo approach was well applied in psychiatric disorders such as schizophrenia, ADHD and depression (Cao et al., 2006; Chen et al., 2012; Guo et al., 2011a,b; Huang et al., 2014; Liu et al., 2006; Wu et al., 2011; Yao et al., 2009). However, no study is conducted in patients with SD using the ReHo method. Clinically, personality traits have been revealed to correlate with the phenomenon of somatization. For example, neuroticism, a broad dimension of individual differences in the tendency to experience negative distressing emotions, is high in SD patients and related to somatization (De Gucht, 2003). Besides, the scores of Symptom Checklist 90 (SCL-90) subscales including somatization factor show a significantly positive correlation to neuroticism scores of Eysenck Personality Questionnaire (EPQ-N) (Zhang et al., 2012). Interestingly, Adelstein et al. (2011) found that extraversion and neuroticism were encoded between seed regions and the lateral paralimbic regions and dorsomedial prefrontal cortex, respectively. Lei et al. (2013) proposed that the relation between individual differences in personality and scaling dynamics in the DMN was linked with introspective cognition by resting-state fMRI. However, it remains unclear to the relationship between personality and brain activity in patients with SD. Here, we conducted a study to explore the regional brain homogeneity in patients with SD. We hypothesized that abnormal ReHo would exist in certain brain regions in SD patients. Since the DMN activity is altered in SD patients (Su et al., 2014), we expected the DMN to be particularly affected. We also expected that abnormal ReHo was correlated to personality, especially neuroticism assessed by EPQ.
2. Materials and methods 2.1. Subjects We recruited 26 first-episode, treatment-naive patients with SD (aged from 18 to 60), and 30 age-, sex-, education-matched, righthanded healthy controls. All patients were diagnosed based on the Structured Clinical Interview of the DSM-IV (SCID) (First et al., 2012). Exclusion criteria for the participants included any history of loss consciousness, mental retardation, serious medical or neurological illness. Individuals with other psychiatric disorders such as schizophrenia, bipolar disorder or personality disorders were also excluded. Since depression is a common comorbidity in patients with SD, comorbidity with depression is allowed. None of healthy controls had serious medical or neuropsychiatric disease or major psychiatric or neurological illness in their first-degree relatives. All subjects were assessed with EPQ (Eysenck and Eysenck, 1972) to measure personality dimensions. Hamilton depression scale (HAMD) (Hamilton, 1960), Hamilton anxiety scale (HAMA) (Hamilton, 1959) and the somatization subscale of SCL-90 (Derogatis et al., 1976) were respectively applied to assess the severity of depression, anxiety and somatic symptoms at the scan day. These scales have been validated in the Chinese patient population with high reliability and validity. Each subject signed an informed consent and the study was approved by the Ethics Committee of the First Affiliated Hospital, Guangxi Medical University.
109
2.2. Scan acquisition Magnetic resonance images were collected using a Siemens 3.0 T scanner (Siemens, Erlangen, Germany). All participants were required to keep motionless with their eyes closed, and remain awake during image acquisition. Resting-state fMRI was performed using an echoplanar imaging sequence with the following parameters: repetition time/echo time (TR/TE) = 2000/30 ms, number of slice = 30, 64 × 64 matrix, 90° flip angle, 24 cm × 24 cm FOV, 4 mm slice thickness, 0.4 mm gap, and number of volumes = 250 (500 s). 2.3. Data processing Statistical parametric mapping software (SPM8, http://www.fil.ion. ucl.ac.uk/spm) was used to preprocess image. The first 10 volumes were discarded to allow for the signal reaching equilibrium. The remaining 240 volumes were slice acquisition correction and realigned for the head motion. Participants with head movement exceeding 2.0 mm of maximum displacement in x, y, or z directions and 2.0° of angular motion were excluded. Then the fMRI images were normalized to the standard SPM8 echo-planar imaging template, and resampled to 3 × 3 × 3 mm3. The resulting fMRI data were temporally band-pass filtered (0.01–0.08 Hz) and linear detrended to reduce low-frequency drift and physiological high frequency noise. ReHo was performed using software REST (Song et al., 2011). The formula used to calculate the KCC value has been reported previously (Zang et al., 2004). In order to reduce the effect of individual variations in KCC values, normalization of ReHo maps was done by dividing KCC among each voxel by the averaged KCC of the entire brain. The data were smoothed with a Gaussian kernel of 8 mm full-width at halfmaximum. 2.4. Statistical analyses Chi-square test was used to compare sex ratio. Distributions of age and years of education were compared by two sample t-tests. Voxelbased comparisons of whole-brain ReHo maps were performed by using two sample t-tests. The resulting statistical maps were set at a threshold of p b 0.05 (corrected for multiple comparisons with a combined threshold of p b 0.005 and a minimum continuous cluster number of 74 voxels) using Monte Carlo simulations in the AFNI AlphaSim program (http://afni.nih.gov/afni/docpdf/AlphaSim.pdf). Linear correlations were conducted between abnormal ReHo values and psychological performances after assessing the data normality. The significance level was set at p b 0.05. 3. Results 3.1. Subjects Twenty-five patients and twenty-eight healthy controls were enrolled in the study. One patient and two healthy controls were excluded due to excessive head movement. Patients with SD and healthy controls did not have significant differences in age (t-tests t = 0.82, df = 51, p = 0.42), sex ratio (chi-square test x2 = 0.25, df = 1, p = 0.61), and educational level (t-tests t = −0.10, df = 51, p = 0.92). Demographic information and clinical characteristics were shown in Table 1. 3.2. ReHo: patients versus controls Compared with healthy controls, patients with SD exhibited a significantly increased ReHo in the left angular gyrus (AG) (t = 3.6875, cluster size = 96 voxels). There is no decreased ReHo in any brain regions relative to healthy controls (Table 2 and Fig. 1).
110
Y. Song et al. / International Journal of Psychophysiology 97 (2015) 108–112
Table 1 Demographics and clinical characteristics of patients and healthy controls. Variables (mean ± standard deviation)
Patients
Controls
p value
Gender (female/male) Age, years Education, years Illness duration, months HAMD HAMA Somatization subscale of SCL-90 Personality traits scores of EPQ Extraversion Psychoticism Neuroticism Lie
21/4 41.00 ± 10.76 7.72 ± 4.39 59.12 ± 62.22 18.84 ± 7.31 22.96 ± 10.95 28.48 ± 10.37
22/6 38.71 ± 9.59 7.82 ± 2.59
0.732a 0.417b 0.920b
2.60 ± 1.83 0.53 ± 0.99 14.32 ± 3.44
b0.001b b0.001b b0.001b
46.84 ± 11.02 50.52 ± 9.01 57.36 ± 9.18 49.44 ± 12.31
49.75 ± 9.65 45.00 ± 8.54 46.78 ± 10.24 47.96 ± 11.01
0.311b 0.026b b0.001b 0.647b
HAMD: Hamilton depression scale; HAMA: Hamilton anxiety scale; SCL-90: Symptom Check List-90; EPQ: Eysenck Personality Questionnaire. a The p value for gender distribution in the two groups was obtained by chi-square test. b The p values were obtained by two sample t-tests.
Table 2 Brain regions with increased ReHo in SD. Brain regions
Patients N Controls Left angular gyrus
Voxels
96
MNI coordinates (mm) x
y
z
-42
-66
48
t value
3.6875
x, y, z, coordinates of primary peak locations in the MNI space; t statistical value of peak voxel shows ReHo differences between the SD group and control group. SD: somatization disorder.
Fig. 2. Positive correlation between the ReHo values in left angular gyrus and the neuroticism scores of EPQ in the patient group. ReHo = regional homogeneity; EPQ = Eysenck Personality Questionnaire.
psychoticism, and lie) in the patients. No other factors, such as symptom severity and education level, were detected to be related to abnormal ReHo values or the domains of EPQ (neuroticism, extraversion, psychoticism, and lie) in the patients. In healthy controls, no correlations were found between the ReHo values and other related variables, such as the EPQ (neuroticism, extraversion, psychoticism, and lie) scores and HAMD/HAMA scores.
3.3. The correlations between ReHo values in the left AG and related factors 4. Discussion Significantly positive correlation between increased ReHo in the left AG and the scores of EPQ-N was found in the patient group (r = 0.428, p = 0.033) (Fig. 2). There were also no correlations between increased ReHo in the left AG and the other domains of EPQ (extraversion,
The primary finding of this study was that abnormal ReHo in the DMN was observed in drug-naive, first-episode SD patients. Consistent with our hypothesis, patients with SD had a significantly increased
Fig. 1. ReHo differences between patients with SD and controls. The region with increased ReHo in SD patients was the left angular gyrus. The color bar represents the t values of the group analysis. ReHo = regional homogeneity.
Y. Song et al. / International Journal of Psychophysiology 97 (2015) 108–112
ReHo in the left AG compared to healthy controls. Furthermore, increased ReHo values in the left AG were significantly correlated to EPQ-N in the patient group, implying that EPQ-N might have clinical implications for psychopathology of SD. Previous studies reported neural abnormalities in patients with SD using a variety of neuroimaging approaches. Stoeter et al. (2007) found increased brain activations in pain processing areas, such as basal ganglia, thalamus and opercular insular area in somatoform pain disorder while an episode of pain was induced by a pin prick. In structural MRI studies, patients with SD showed significantly decreased volumes in the bilateral amygdala involved in emotional perception (Atmaca et al., 2011). Based on the assumptions that pituitary volumes might be involved in the occurrence of somatoform symptoms, Yildirim et al. (2012) found that SD patients had smaller pituitary volumes than healthy controls. In the present study, increased ReHo was found in the left AG in SD patients. AG is a crucial area of the DMN and involved in a lot of processes associated with language, number processing, memory retrieval and attention (Raichle et al., 2001); it is also important in making semantic associations in reading, comprehension of speech and written language (Obleser and Kotz, 1991), and integrating conceptual understanding of the language term “left” or “right” with its location in space (Hirnstein et al., 2011). Located at the crossroads of processing touch, hearing and vision, AG is critical to conceptual metaphors and cross-modal abstractions (Rosenthal et al., 2009). Moreover, AG has other important functions in mental constructs, like thoughts, cognition, and beliefs related to oneself or others (Frith and Frith, 2003). Besides, the spatial fractionation of the AG is divided into multiple subdivisions that contribute to “bottom-up” and “top-down” mechanisms across numerous tasks (Seghier, 2013). The neural activity abnormality in the AG may affect the “top-down” regulation and causes emotional, awareness and behavioral alterations (Liu et al., 2015; Liu et al., 2012). Furthermore, an interesting experiment exhibited that a woman perceived a phantom existence behind her when AG was stimulated, suggesting that AG may be apt to cause uncomfortable feelings in perceived location of the body but not the actual position of the body (Arzy et al., 2006). It may also explain why somatic symptoms are unexplained in patients with SD. Another finding of this study was left-sided affected brain regions in SD. Lack of normal symmetry in AG has been long observed. The left AG is in charge of semantic access and arithmetic skills, and the right AG contributes to spatiovisual attention, maintenance and control of covert reorienting of attention (Sack, 2009; Seghier, 2013). In task-related fMRI, the right AG is stirred up by the conflict tasks, while the left AG is activated especially in a sentence comprehension task (Ye and Zhou, 2009). The left AG may act as a memory buffer for intention maintenance (Kalpouzos et al., 2010), and may play a role in the verbal coding of numbers (Dehaene et al., 2003) and the arithmetic operations (Ischebeck et al., 2009). Consistent with the previous findings, our results suggest that left-sided affected asymmetry may be a characteristic for patients with SD. Eysenck conceptualized personality as extroversion/introversion, neuroticism and psychoticism using factor analysis. Extraversion represents sociability, being outgoing, talkative, and in need of external stimulation; neuroticism is characterized by high levels of negative affect such as depression and anxiety; and psychoticism is associated with psychotic episode (or break with reality) and aggressiveness. A fourth dimension, the lie scale, represents social naivety or deliberately attempting to control their scores (Eysenck and Eysenck, 1975). Compared with healthy controls, higher scores of HAMD and HAMA were found in the patient group. These results are consistent with previous findings that comorbidities exist among depression, anxiety and somatization with a high ratio (Mergl et al., 2007). Moreover, Fink et al. (2004) found that 36% of SD patients had another psychiatric disorder, 11% with depression and 25% with anxiety disorder. Leiknes et al. (2007) reported that about 45% of SD patients had comorbidities with anxiety/depression.
111
It is noteworthy that increased ReHo values in the left AG were positively correlated to the EPQ-N in patients with SD. The neuroticism subscale represents the experience of negative affect, emotional unstableness, depressive symptomatology, obsessiveness, and anxietybased problems (Eysenck and Eysenck, 1971). Increased cardiac vagal tone in response to pain is relevant to neuroticism, suggesting that personality trait may influence pain perception (Paine et al., 2009). Subjects with higher neuroticism score reported more somatic symptoms resulting in more health care-seeking behavior, which in turn affected their health-related life quality (Kempen et al., 1997; VanderZee et al., 1996). The current correlations indicate that individuals with higher neuroticism scores may be apt to suffer from SD in their lifetime. Apart from the relatively small sample size, there are a few limitations that should be acknowledged. First, depression and somatization are comorbid at a high ratio (Bjelland et al., 2002; Clark et al., 1994; Simon et al., 1996). Depression may be an accompany characteristic of SD which could not be removed in the present study. Therefore, depression might have biased the present results. Second, SD is more likely present in the females, and high percentage of females in our study might limit the ability to explore sex difference in patients with SD. Third, physiological noises such as respiratory and heart rhythm cannot be completely eliminated by using a relatively low sampling rate (TR = 2 s). More comprehensive methods are needed to remove such physiological noises. In summary, the present study first found that increased ReHo in the left AG might act as a key role in SD with clinical implications, and emphasized the importance of DMN in the physiological processes of SD. More comprehensive ReHo studies are required to observe the abnormality referred to trait or state alterations in SD. Contributors Drs. Guo W and Xiao C designed the study. Drs. Song Y, Yao D, Jiang M, Dai Y, Liu J, Yu L, Su Q, and Zhang J collected the original imaging data. Drs. Liu F, Zhang Z and Long L managed and analyzed the imaging data, and Drs. Song Y and Su Q wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript. Acknowledgments This study was supported by grants from the National Natural Science Foundation of China (Grant No. 81260210), the Natural Science Foundation of Guangxi Province for Distinguished Young Scientists (Grant No. 2014GXNSFGA118010), and the Natural Science Foundation of Guangxi Province (Grant No. 2013GXNSFAA019107). We thank all the individuals who served as the research participants. References Adelstein, J.S., Shehzad, Z., Mennes, M., DeYoung, C.G., Zuo, X.-N., Kelly, C., Margulies, D.S., Bloomfield, A., Gray, J.R., Castellanos, F.X., 2011. Personality is reflected in the brain's intrinsic functional architecture. PLoS ONE 6, e27633. Anderson, A., Cohen, M.S., 2013. Decreased small-world functional network connectivity and clustering across resting state networks in schizophrenia: an fMRI classification tutorial. Front. Hum. Neurosci. 7. Arzy, S., Seeck, M., Ortigue, S., Spinelli, L., Blanke, O., 2006. Induction of an illusory shadow person. Nature 443, 287-287. Atmaca, M., Sirlier, B., Yildirim, H., Kayali, A., 2011. Hippocampus and amygdalar volumes in patients with somatization disorder. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 35, 1699–1703. Battaglia, M., Bernardeschi, L., Politi, E., Bertella, S., Bellodi, L., 1995. Comorbidity of panic and somatization disorder: a genetic–epidemiological approach. Compr. Psychiatry 36, 411–420. Bjelland, I., Dahl, A.A., Haug, T.T., Neckelmann, D., 2002. The validity of the Hospital Anxiety and Depression Scale: an updated literature review. J. Psychosom. Res. 52, 69–77. Browning, M., Fletcher, P., Sharpe, M., 2011. Can neuroimaging help us to understand and classify somatoform disorders? A systematic and critical review. Psychosom. Med. 73, 173. Cao, Q., Zang, Y., Sun, L., Sui, M., Long, X., Zou, Q., Wang, Y., 2006. Abnormal neural activity in children with attention deficit hyperactivity disorder: a resting-state functional magnetic resonance imaging study. Neuroreport 17, 1033–1036.
112
Y. Song et al. / International Journal of Psychophysiology 97 (2015) 108–112
Chen, J.D., Liu, F., Xun, G.L., Chen, H.F., Hu, M.R., Guo, X.F., Xiao, C.Q., Wooderson, S.C., Guo, W.B., Zhao, J.P., 2012. Early and late onset, first-episode, treatment-naive depression: same clinical symptoms, different regional neural activities. J. Affect. Disord. 143, 56–63. Clark, D.A., Steer, R.A., Beck, A.T., 1994. Common and specific dimensions of self-reported anxiety and depression: implications for the cognitive and tripartite models. J. Abnorm. Psychol. 103, 645. De Gucht, V., 2003. Stability of neuroticism and alexithymia in somatization. Compr. Psychiatry 44, 466–471. Dehaene, S., Piazza, M., Pinel, P., Cohen, L., 2003. Three parietal circuits for number processing. Cogn. Neuropsychol. 20, 487–506. Derogatis, L.R., Rickels, K., Rock, A.F., 1976. The SCL-90 and the MMPI: a step in the validation of a new self-report scale. Br. J. Psychiatry 128, 280–289. Eysenck, S., Eysenck, H., 1971. Attitudes to sex, personality and lie scale scores. Percept. Mot. Skills 33, 216–218. Eysenck, S., Eysenck, H., 1972. The questionnaire measurement of psychoticism. Psychol. Med. 2, 50–55. Eysenck, H.J., Eysenck, S.B.G., 1975. Manual of the Eysenck Personality Questionnaire (junior and adult). Hodder and Stoughton. Fayed, N., Andres, E., Rojas, G., Moreno, S., Serrano‐Blanco, A., Roca, M., Garcia‐Campayo, J., 2012. Brain dysfunction in fibromyalgia and somatization disorder using proton magnetic resonance spectroscopy: a controlled study. Acta Psychiatr. Scand. 126, 115–125. Fink, P., Hansen, M.S., Oxhoj, M.-L., 2004. The prevalence of somatoform disorders among internal medical inpatients. J. Psychosom. Res. 56, 413–418. First, M.B., Spitzer, R.L., Gibbon, M., Williams, J.B., 2012. Structured Clinical Interview for DSM-IV® Axis I Disorders (SCID-I), Clinician Version. Administration Booklet, American Psychiatric Pub. Frith, U., Frith, C.D., 2003. Development and neurophysiology of mentalizing. Phil. Trans. R. Soc. Lond. B Biol. Sci. 358, 459–473. Garcia‐Campayo, J., Sanz‐Carrillo, C., Baringo, T., Ceballos, C., 2001. SPECT scan in somatization disorder patients: an exploratory study of eleven cases. Aust. N. Z. J. Psychiatry 35, 359–363. Guo, W.B., Liu, F., Xue, Z.M., Yu, Y., Ma, C.Q., Tan, C.L., Sun, X.L., Chen, J.D., Liu, Z.N., Xiao, C.Q., Chen, H.F., Zhao, J.P., 2011a. Abnormal neural activities in first-episode, treatment-naive, short-illness-duration, and treatment-response patients with major depressive disorder: a resting-state fMRI study. J. Affect. Disord. 135, 326–331. Guo, W.B., Sun, X.L., Liu, L., Xu, Q., Wu, R.R., Liu, Z.N., Tan, C.L., Chen, H.F., Zhao, J.P., 2011b. Disrupted regional homogeneity in treatment-resistant depression: a resting-state fMRI study. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 35, 1297–1302. Guo, W., Liu, F., Liu, J., Yu, L., Zhang, J., Zhang, Z., Xiao, C., Zhai, J., Zhao, J., 2015a. Abnormal causal connectivity by structural deficits in first-episode, drug-naive schizophrenia at rest. Schizophr. Bull. 41, 57–65. Guo, W., Liu, F., Liu, J., Yu, M., Zhang, Z., Liu, G., Xiao, C., Zhao, J., 2015b. Increased cerebellar-default-mode-network connectivity in drug-naive major depressive disorder at rest. Medicine 94, e560. Hakala, M., Karlsson, H., Kurki, T., Aalto, S., Koponen, S., Vahlberg, T., Niemi, P.M., 2004. Volumes of the caudate nuclei in women with somatization disorder and healthy women. Psychiatry Res. Neuroimaging 131, 71–78. Hakala, M., Vahlberg, T., NIEMI, P.M., Karlsson, H., 2006. Brain glucose metabolism and temperament in relation to severe somatization. Psychiatry Clin. Neurosci. 60, 669–675. Hamilton, M., 1959. The assessment of anxiety states by rating. Br. J. Med. Psychol. 32, 50–55. Hamilton, M., 1960. A rating scale for depression. J. Neurol. Neurosurg. Psychiatry 23, 56. He, Y., Wang, L., Zang, Y., Tian, L., Zhang, X., Li, K., Jiang, T., 2007. Regional coherence changes in the early stages of Alzheimer's disease: a combined structural and resting-state functional MRI study. NeuroImage 35, 488–500. Hirnstein, M., Bayer, U., Ellison, A., Hausmann, M., 2011. TMS over the left angular gyrus impairs the ability to discriminate left from right. Neuropsychologia 49, 29–33. Hoekzema, E., Carmona, S., Ramos‐Quiroga, J.A., Richarte Fernández, V., Bosch, R., Soliva, J.C., Rovira, M., Bulbena, A., Tobeña, A., Casas, M., 2014. An independent components and functional connectivity analysis of resting state fMRI data points to neural network dysregulation in adult ADHD. Hum. Brain Mapp. 35, 1261–1272. Huang, X., Huang, P., Li, D., Zhang, Y., Wang, T., Mu, J., Li, Q., Xie, P., 2014. Early brain changes associated with psychotherapy in major depressive disorder revealed by resting-state fMRI: evidence for the top-down regulation theory. Int. J. Psychophysiol. 94, 437–444. Ischebeck, A., Zamarian, L., Schocke, M., Delazer, M., 2009. Flexible transfer of knowledge in mental arithmetic—an fMRI study. NeuroImage 44, 1103–1112. Kalpouzos, G., Eriksson, J., Sjölie, D., Molin, J., Nyberg, L., 2010. Neurocognitive systems related to real-world prospective memory. PLoS ONE 5, e13304. Kempen, G.I., Jelicic, M., Ormel, J., 1997. Personality, chronic medical morbidity, and health-related quality of life among older persons. Health Psychol. 16, 539. Lei, X., Zhao, Z., Chen, H., 2013. Extraversion is encoded by scale-free dynamics of default mode network. NeuroImage 74, 52–57.
Leiknes, K.A., Finset, A., Moum, T., Sandanger, I., 2007. Current somatoform disorders in Norway: prevalence, risk factors and comorbidity with anxiety, depression and musculoskeletal disorders. Soc. Psychiatry Psychiatr. Epidemiol. 42, 698–710. Lemche, E., Giampietro, V.P., Brammer, M.J., Surguladze, S.A., Williams, S.C., Phillips, M.L., 2013. Somatization severity associated with postero-medial complex structures. Sci. Rep. 3. Liu, H., Liu, Z., Liang, M., Hao, Y., Tan, L., Kuang, F., Yi, Y., Xu, L., Jiang, T., 2006. Decreased regional homogeneity in schizophrenia: a resting state functional magnetic resonance imaging study. Neuroreport 17, 19–22. Liu, Z., Xu, C., Xu, Y., Wang, Y., Zhao, B., Lv, Y., Cao, X., Zhang, K., Du, C., 2010. Decreased regional homogeneity in insula and cerebellum: a resting-state fMRI study in patients with major depression and subjects at high risk for major depression. Psychiatry Res. Neuroimaging 182, 211–215. Liu, F., Hu, M., Wang, S., Guo, W., Zhao, J., Li, J., Xun, G., Long, Z., Zhang, J., Wang, Y., Zeng, L., Gao, Q., Wooderson, S.C., Chen, J., Chen, H., 2012. Abnormal regional spontaneous neural activity in first-episode, treatment-naive patients with late-life depression: a resting-state fMRI study. Prog. Neuropsychopharmacol. Biol. Psychiatry 39, 326–331. Liu, F., Guo, W., Fouche, J.P., Wang, Y., Wang, W., Ding, J., Zeng, L., Qiu, C., Gong, Q., Zhang, W., Chen, H., 2015. Multivariate classification of social anxiety disorder using whole brain functional connectivity. Brain Struct. Funct. 220, 101–115. Ma, C., Ding, J., Li, J., Guo, W., Long, Z., Liu, F., Gao, Q., Zeng, L., Zhao, J., Chen, H., 2012. Resting-state functional connectivity bias of middle temporal gyrus and caudate with altered gray matter volume in major depression. PLoS ONE 7, e45263. Mergl, R., Seidscheck, I., Allgaier, A.K., Möller, H.J., Hegerl, U., Henkel, V., 2007. Depressive, anxiety, and somatoform disorders in primary care: prevalence and recognition. Depression Anxiety 24, 185–195. Obleser, J., Kotz, S.A., 1991. Expectancy constraints in degraded speech modulate the language comprehension network. Cereb. Cortex 20, 633–640 (New York, N.Y.). Paine, P., Worthen, S., Gregory, L., Thompson, D., Aziz, Q., 2009. Personality differences affect brainstem autonomic responses to visceral pain. Neurogastroenterol. Motil. 21, 1155–e1198. Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L., 2001. A default mode of brain function. Proc. Natl. Acad. Sci. 98, 676–682. Rief, W., Hessel, A., Braehler, E., 2001. Somatization symptoms and hypochondriacal features in the general population. Psychosom. Med. 63, 595–602. Rosenthal, C.R., Roche-Kelly, E.E., Husain, M., Kennard, C., 2009. Response-dependent contributions of human primary motor cortex and angular gyrus to manual and perceptual sequence learning. J. Neurosci. 29, 15115–15125. Sack, A.T., 2009. Parietal cortex and spatial cognition. Behav. Brain Res. 202, 153–161. Seghier, M.L., 2013. The angular gyrus multiple functions and multiple subdivisions. Neuroscientist 19, 43–61. Simon, G., Gater, R., Kisely, S., Piccinelli, M., 1996. Somatic symptoms of distress: an international primary care study. Psychosom. Med. 58, 481–488. Song, X.W., Dong, Z.Y., Long, X.Y., Li, S.F., Zuo, X.N., Zhu, C.Z., He, Y., Yan, C.G., Zang, Y.F., 2011. REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PLoS ONE 6, e25031. Stoeter, P., Bauermann, T., Nickel, R., Corluka, L., Gawehn, J., Vucurevic, G., Vossel, G., Egle, U., 2007. Cerebral activation in patients with somatoform pain disorder exposed to pain and stress: an fMRI study. NeuroImage 36, 418–430. Su, Q., Yao, D., Jiang, M., Liu, F., Jiang, J., Xu, C., Dai, Y., Yu, M., Long, L., Li, H., 2014. Dissociation of regional activity in default mode network in medication-naive, firstepisode somatization disorder. PLoS ONE 9, e99273. Su, Q., Yao, D., Jiang, M., Liu, F., Jiang, J., Xu, C., Dai, Y., Yu, M., Long, L., Li, H., 2015. Increased functional connectivity strength of right inferior temporal gyrus in first-episode, drug-naive somatization disorder. Aust. N. Z. J. Psychiatry 49, 74–81. VanderZee, K.I., Sanderman, R., Heyink, J., 1996. A comparison of two multidimensional measures of health status: the Nottingham Health Profile and the RAND 36-Item Health Survey 1.0. Qual. Life Res. 5, 165–174. Wu, Q.Z., Li, D.M., Kuang, W.H., Zhang, T.J., Lui, S., Huang, X.Q., Chan, R.C., Kemp, G.J., Gong, Q.Y., 2011. Abnormal regional spontaneous neural activity in treatment‐refractory depression revealed by resting‐state fMRI. Hum. Brain Mapp. 32, 1290–1299. Yao, Z., Wang, L., Lu, Q., Liu, H., Teng, G., 2009. Regional homogeneity in depression and its relationship with separate depressive symptom clusters: a resting-state fMRI study. J. Affect. Disord. 115, 430–438. Ye, Z., Zhou, X., 2009. Conflict control during sentence comprehension: fMRI evidence. NeuroImage 48, 280–290. Yildirim, H., Atmaca, M., Sirlier, B., Kayali, A., 2012. Pituitary volumes are reduced in patients with somatization disorder. Psychiatr. Investig. 9, 278–282. Zang, Y., Jiang, T., Lu, Y., He, Y., Tian, L., 2004. Regional homogeneity approach to fMRI data analysis. NeuroImage 22, 394–400. Zhang, L., Liu, X., Zheng, G.-J., Zhou, L., Lin, D.-Y., Wang, X.-D., He, H., 2012. Eysenck personality and psychosocial status of adult patients with malocclusion. Asian Pac. J. Trop. Med. 5, 151–156.