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Journal of Psychiatry and Brain Science 2016; 1(2): 4; https://doi.org/10.20900/jpbs.20160009

Article

Unipolar and Bipolar Depressions Manifest Different Brain Abnormalities: a Voxel-based Morphometry Study

Aimin Hu1,2* , Zhimin Xue1* , Zhening Liu1, Peng Wang3, Zhong He4

1 Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha 410011, China

2 Department of Medicine, Jishou University, Jishou 416000, China

3 Central Hospital of Xi’an, Xi’an 710000, China

4 Radiology Department of the Second Xiangya Hospital, Central South University, Changsha 410011, China

Correspondence: Zhimin Xue. Email: x.zhimin@163.com; Aimin Hu. Email: huaimin888@163.com.

Published: 6/25/2016

ABSTRACT

Background: Patients with bipolar depression are often misdiagnosed as having unipolar depression due to phenotype similarities of the two diseases. We hypothesize that patients with these two diseases may have differing grey matter volumes.

Methods: Structural magnetic resonance imaging (MRI) data were acquired from 64 subjects, including 17 unipolar depression patients, 19 bipolar depression patients, and 28 healthy controls. Image preprocess was conducted using voxel-based morphometry (VBM). Grey matter volume changes were compared among the groups.

Results: Unipolar and bipolar patients demonstrated significantly decreased grey matter volumes in the right anterior cerebellum lobe compared to healthy controls. Significant right superior temporal gyrus volume decreases in unipolar patients compared to healthy controls and bipolar subjects was also observed.

Conclusion: These results indicate that volume changes in the anterior cerebellum lobe could provide a basis for diagnosis for both unipolar and bipolar depression. Additionally, right superior temporal gyrus volume variations may differ in unipolar and bipolar patients and could be used as a marker for differentiating the two.

1 INTRODUCTION

Black mood, lack of interest, and loss of pleasure are the core symptoms in unipolar depression and bipolar depression patients. There are no biomarkers for distinguishing between the two so misdiagnoses often occur during clinical practice. Accurately identifying and diagnosing unipolar and bipolar depressions creates a challenge in the cross-diagnosis study of affective disorders. Brain dysfunction is usually followed by damage to the brain structure. Identifying damaged brain structures can provide an abnormal neuroanatomical model for diseases[1].

Currently there are few not brain morphologic MRI studies directly comparing unipolar and bipolar depression. The studies showed that the volume of hippocampus and amygdala grey matter and the volume of hippocampus and cerebellum white matter in bipolar depressives decreased. Grey matter volume of the anterior cingulate in the unipolar depression group decreased[2]. Another study found that right inferior frontal gyus grey matter volume in patients with unipolar and bipolar depressions decreased and the dorsal cingulate grey matter volume in patients with bipolar depression decreased[3].

The two studies provide neuroimaging evidence that unipolar and bipolar depressives have different brain volumes in their inferior frontal gyrus, hippocampus, amygdala, cingulate gyrus, and cerebellum, but medication influences were not controlled. However, previous studies showed that the long-term use of antidepressants and affect stabilizers and other treatment methods may affect changes in local brain structures[4, 5]. For example, lithium salt and antidepressant medications may lead to grey matter volume changes in several areas including the hippocampus, the amygdala, and the cerebellum[6, 8].

In this study, unipolar and bipolar patients, and demographically similar, in terms of age, gender and educational attainments, controls were compared in order to provide a reference for diagnosis and treatment. The comparison took place within two weeks of the start of medication-introduction treatment. This timing of testing was chosen to minimize the impacts of medications on brain volume.

2 SUBJECTS AND METHODS

2.1 Objectives

Sixty-four cases (19 with unipolar depression, 17 with bipolar depression and 28 healthy controls) were recruited for this study. All subjects came from the psychiatric clinics and wards of the Second Xiangya Hospital between February 2012 and February 2015. All subjects (Ss) were informed of the risks and benefits before the trials and executed an informed consent. This study was approved by the Medical Research Ethics Committee of the Second Xiangya Hospital of Central South University.

2.2 Unipolar Depression Disorder

Inclusion Criteria: 1. comply with the diagnosis criteria of major depression of the Diagnostic and Statistical Manual of Mental Disorders, DSM-IV[9] and have more than two depressive episodes; 2. be 18 - 45 years old; 3. have an educational level of 9 or more years; 4. have a Hamilton Rating Scale for Depression, (HRSD, 17 items) over 17[10]; 5. have a Young Manic rating scale (YMRS) of less than 6[11]; 6. have dextromanuality; 7. Han ethnicity; 8. comprehend experimental contents and provide informed consent. Exclusion Criteria: 1. patients suffering from any other diseases of DSM-IV axis I or axis II; 2. patients with a history of alcohol, or substance, abuse; 3. patients with neurological disorders, loss of consciousness, severe physical illness, or are pregnant; 4. patients with a history of electric shock treatment; and, 5. patients contraindicated against the MRI tests and patients with brain abnormalities in the inspection of MRI.

Bipolar Depression Disorder Inclusion Criteria: 1. meet the diagnosis criteria of bipolar depression episodes of the Diagnostic and Statistical Manual of Mental Disorders, DSM-IV[9]; 2. be 18 - 45 years old; 3. possess an educational level of 9 or more years; 4. have a Hamilton Rating Scale for Depression, HRSD (17 items) score over 17[10]; 5. have a Young Manic Rating scale score of less than 6[11]; 6. possess extromanuality; 7. Han ethnicity; and, 8. comprehend the experimental contents and execute an informed consent. Exclusion Criteria: 1. patients with any other diseases of DSM-IV axis I or axis II; 2. patients with a history of alcohol, or substance, abuse; 3. patients with neurological disorders, loss of consciousness, severe physical illness, or are pregnant; 4. patients with a history of electric shock treatment; 5. patients contraindicated against the MRI tests and patients with brain abnormalities in the inspection of MRI.

2.3 Healthy Controls

Inclusion Criteria: 1. Be 18 - 45 years old; 2. possess an educational level of 9, or more, years; 3. have dextromanuality; 4. Han nationality; 5. gender matched the patient; 6. have no mental illness history for individual or first-degree relatives of the probands; 7. comprehend experimental contents and execute an informed consent. Exclusion Criteria: 1. a history of alcohol, or substance, abuse; 2, a history of mental illness for individual or family; 3. suffer from neurological disorders, loss of consciousness, severe physical illness, or are pregnant; 4. a history of electric shock treatment; 5. contraindicated against the MRI tests and patients with brain abnormalities in the inspection of MRI.

2.4 Clinical Assessment and MRI Data Acquisition

Clinical Assessment DSM-IV-TR Axis I disorder clinical interview (for patients) (SCID-I / P)[12] was used to assess patient condition; DSM-IV-TR Axis I disorder clinical interview (not for patients) (SCID-NP)[13] was used to screen normal controls; the Oldfield inventory[14] was used to assess handedness; subject demographic and basic clinical data was collected, including, age, gender, educational level, onset age, and disease course. HADS and YMRS were used to assess the depression and manic symptoms of the patients with affective disorders in the week prior to testing.

2.5 Acquisition of MRI Data

MRI data was acquired in the MRI room of the Second Xiangya Hospital of Central South University. A 3.0 T magnetic resonance imaging system (Achieva, Philips, The Netherlands) was used to scan in a standardized head coil. The subject was on his/her back with eyes closed. A supportive foam pad was used to limit head movement. The subject was instructed to remain motionless and relax, but not fall asleep. The structure MRI data used the sequence of T1W-3D-TFE. A whole brain structure image of a high resolution was scanned from the sagittal plane. Scanning parameters were: repetition time (7.5 ms); echo time (3.7 ms); flip angle (8 degrees); field of view (24 × 24 cm); matrix (256 × 200); slice thickness (2 mm); gap (1 mm); and, 180 slices.

2.6 Data Processing and Statistical Analysis

MRI data were analyzed based on MATLAB 7.1. SPM8 (http://www.fil.ion.ucl.ac.uk/spm) and VBM8 software data packages were used to process brain structure images. The “unified partitioning method” of voxel-based morphometry (VBM) was used to pre-process the 3D structure MRI data, including: standardization; partitioning; adjustment; and, translation. An EPI template was used for standardization to obtain adjusted brain grey matter, white matter, and cerebrospinal fluid images, which represent the volumes of the three tissue types respectively. Isotropic 8mm (full-width at half-maximum) Gaussian kernel was used to translate the images. Volumes fo brain grey matter, brain white matter, and cerebrospinal fluid for each subject was calculated. Intracranial volume was the sum of the three volumes. Total intracranial volume served as a coviarate and the statistical model of covariance (analysis of covariance, ANCOVA) was used to detect differences in brain grey matter volumes for the three groups. The threshold value of significant difference of brain grey matter volume was set as p < 0.001 (uncorrected), and k > 100. Software Rest was used to obtain the absolute values of cerebral areas of the three subject groups with significant difference of brain grey matter volumes. Based on SPSS20, Post-hoc (LSD) was used to compare the differences of brain grey matter volumes among the three groups. Pearson’s correlation analysis method was used to test and check the correlation between patient demographic, clinical symptoms, and cerebral area with significant difference of brain grey matter volumes (p < 0.05).

3 RESULTS

3.1 Demographic and Clinical Symptoms

Bipolar depression, unipolar depression and healthy control group demographic and clinical symptoms are shown in Table. There were no significant differences in the ages, gender, or educational level of the three groups. There was no significant difference in the total HADS score, the total YMRS score, onset age, or disease course among the patients with unipolar and bipolar depression.

TABLE 1
Table 1. Demographic and Clinical Symptoms of Bipolar Depression Group, Unipolar Depression Group and Healthy Control Group (M±SD)

Notes: a. ANAVO Test; b. Chi-square test; c. t test; HRSD: Hamilton Rating Scale for Depression; YMRS: Young Manic Rating Scale.

Voxel-based Morphologic Analysis: A comparison of brain grey matter volumes of the subjects showed that there was a significant difference of grey matter volumes in the right lobus anterior cerebelli and right superior temporal gyrus. The coordinate value and value Z of the cerebral areas with significant differences of brain grey matter volumes are shown in Table 2. Bipolar and unipolar depression disorders showed a significant decrease of grey matter volumes of the right lobus anterior cerebelli compared to healthy controls. Unipolar depressives showed a significant decrease of grey matter volumes of right superior temporal gyrus when compared to the two other groups (Table 3., see attached figures).

TABLE 2
Table 2. Cerebral Areas with significant differences in grey matter volumes for Bipolar, Unipolar, and Healthy Controls

Note: MNI - Montreal Neurological Institute

TABLE 3
Table 3. Comparison of cerebral areas with significant differences in grey matter volumes for Bipolar, Unipolar, and Healthy Control
FIGURE 1
Fig. A+B Right Lobus anterior cerebelli of the three groups with significant differences in grey matter volumes; Fig. B: Right superior temporal gyrus of groups with significant differences in grey matter volumes; Fig. C: Post-hoc comparison results of right lobus anterior cerebelli of the groups; Fig. D: Post-hoc comparison result of right superior temporal gyrus of the groups.

Note: Fig. A and Fig. B: p < 0.001 (uncorrected), and cluster > 100, color strip represents Value F; Fig. C and Fig. D: *p < 0.05.

TABLE 4
Table 4. Correlated analysis between demographic and clinical features and grey matter volume of Right Lobus Anterior Cerebelli and Right Superior Temporal Gyrus of unipolar depressives and bipolar depressives

4 DISCUSSION

The results of this study showed that the grey matter volume of right superior temporal gyrus of subjects with unipolar depression significantly decreased compared to the healthy controls. There was no significant difference for bipolar depressives. It was also reported that grey matter volumes of the right superior temporal gyrus of subjects with unipolar depression significantly decreased[15]. There was no significant difference for the subjects with bipolar depression[16]. The superior temporal gyrus mainly contains the cerebral areas for hearing and auditory-associated cortex, involving in the auditory system and speech disorders. The superior temporal gyrus is connected to the medial frontal lobe and dorsal frontal lobe and plays an important role in constituting the behavior state related to the affective disorders[17-18]. The studies showed that the superior temporal gyrus constituted the brain default network with medial prefrontal lobes, front / rear cingulate, entorhinal area and para-hippocampus[19]. The decrease of grey matter volume of superior temporal gyrus might lead to the dysfunction of default network of the unipolar depression, and the dysfunction of default network was however associated with the abnormal functions such as situational memory, self-related thinking, emotional processing[20, 21]. The significant decrease of grey matter volume in right superior temporal gyrus of the subjects with unipolar depression indicates that it might associate with the auditory system and speech disorder dysfunction and the default network dysfunction of the subject with unipolar depression. It displayed that there existed a difference of grey matter volume of right superior temporal gyrus between the unipolar depressives and bipolar depressives, which may be associated with different depression states.

Moreover, compared to healthy controls, the study showed that the grey matter volumes of right lobus anterior cerebelli of unipolar and bipolar depressives significantly decreases. This has been reported in previous studies of brain structure[22, 23]. Brain function studies also showed that the activation of cerebellum function of depressives was reduced, but improved after antidepressant treatment[24]. At the molecular level, some evidence indicates a reduction in the neurotrophic factor signals expressed in cerebellum granule cells and molecular layer which may potentially cause synaptic plasticity of affective disorder[25]. These results confirm the abnormal reduction of cerebellum grey matter volume of depressives. The lobus anterior cerebelli is the primary sensorimotor area, and is responsible for coordinating movement and motor learning. It is associated with movement control and sensorimotor integration[26, 27]. Andreasen et al. reported the neural circuit of cortex-thalamic-cerebral-cortical circuit forms the classic sensorimotor circuit. Movement defect is associated with the different development of the Lobus anterior cerebelli[28] and the cerebellum was correlated with the inferior colliculus to promote the combination with a wide range of neural circuits of emotions and autonomic functions in addition to the sensorimotor control[29]. The significant decrease of grey matter volume of right lobus anterior cerebelli in unipolar and bipolar depressives might be associated with the atrophy of grey matter volume of lobus anterior cerebelli. It might lead to the reduction of sensorimotor and control ability of the patients and result in the depressive symptoms such as, emotional depression, lack of interest, and, loss of pleasure. The decrease of grey matter volume of right lobus anterior cerebelli occurred in both unipolar and bipolar depressives, which was reflected in their common characteristics. The difference of grey matter volumes of unipolar and bipolar depressives in the right superior temporal gyrus reflects the characteristics of different disease states, which may help distinguish the two diseases. The decrease of grey matter volumes of right lobus anterior cerebelli in patients with unipolar and bipolar depressions may reflect the trait characteristics of depressive disorders and result in a reduction of sensorimotor and control abilities related to depressive symptoms. Correlated analyses showed that the grey matter volume of right lobus anterior cerebelli of subjects with bipolar depression was significantly negatively correlated with the total score of HRSD. This indicates that the decrease of grey matter volume of right lobus anterior cerebelli of bipolar depressives may associate with an increased severity of depression. In unipolar depressives, there was no correlation with the grey matter volume of right lobus anterior cerebelli or the right superior temporal gyrus. It was possibly associated with sample quantity and other factors and should be further verified in the studies in the future.

FUNDING

This work is supported by 1) Natural Science Fund of Hunan Province: A Study on MRI-Based Brain Network of Mental Retardation (program No.: 13JJ3029); 2) National Natural Science Fund of China: A Control Study on Brain Network of Manic Phase and Depressive Phase (program No.: 81171287); 3) National Natural Science Fund of China: A Study on Prefrontal Neurodevelopment of Youth with High-Risk Schizophrenia (program No.: 81271485); and 4) National Natural Science Fund of China: Functional MRI Study of Hate Circuit of Depressive Disorder (program No.: 81301161).

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How to Cite This Article

Hu A, Xue Z, Liu Z, Wang P, He Z. Unipolar and Bipolar Depressions Manifest Different Brain Abnormalities: a Voxel-based Morphometry Study. J Psychiatry Brain Sci. 2016; 1(2): 4; https://doi.org/10.20900/jpbs.20160009

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