PNP-08607; No of Pages 6 Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
Progress in Neuro-Psychopharmacology & Biological Psychiatry journal homepage: www.elsevier.com/locate/pnp
F
O
5 6 7
a
8
a r t i c l e
9 10 11 12 13
Article history: Received 1 March 2014 Received in revised form 10 May 2014 Accepted 12 May 2014 Available online xxxx
14 15 16 17 18
Keywords: Amplitude of low-frequency fluctuation Gray matter Major depressive disorder Voxel-based morphometry
Mental Health Center, 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, China Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, Hunan 410011, China
i n f o
a b s t r a c t
Background: Functional and anatomical deficits have been involved in the neurobiology of major depressive disorder (MDD). However, no study has ever been conducted to examine whether and how functional alterations are related to anatomical deficits in MDD. This study aimed to determine the association between brain functional and anatomical deficits in drug-naive MDD. Methods: Forty-four patients with MDD and 44 age-, sex-, and education-matched healthy controls underwent structural and resting-state functional magnetic resonance imaging scanning. The voxel-based morphometry (VBM) and amplitude of low-frequency fluctuation (ALFF) methods were used to analyze the imaging data. Results: VBM analysis showed gray matter volume (GMV) reductions in the parietal–temporal regions (i.e., the right inferior temporal gyrus and the left angular gyrus). Functional alterations revealed by ALFF mainly occurred in the temporal regions (i.e., the left middle temporal gyrus and the right superior temporal gyrus) and the cerebellum (i.e., the culmen). There is no overlap between brain regions with functional alterations and anatomical deficits in the patients and their subgroups (first-episode depression and recurrent depression). The episode number and the illness duration were correlated with the mean GMV values of the left angular gyrus. Conclusions: A dissociation pattern of brain functional and anatomical deficits is observed in MDD. Our findings suggest that brain functional and anatomical deficits contribute independently to the neurobiology of MDD. © 2014 Published by Elsevier Inc.
E
C
c
R O
b
P
4
Wenbin Guo a,⁎, Feng Liu b, Miaoyu Yu a, Jian Zhang a, Zhikun Zhang a, Jianrong Liu a, Changqing Xiao a, Jingping Zhao c
D
3Q1
E
2
Functional and anatomical brain deficits in drug-naive major depressive disorder
T
1
R
34 38 36 35
R
37
1. Introduction
40
Structural and functional magnetic resonance imaging (MRI) indicates that major depressive disorder (MDD) is a disease with abnormal brain structure and function (Drevets et al., 2008; Fitzgerald et al., 2008; Guo et al., 2013a; Liu et al., 2013; Rigucci et al., 2010). Structural MRI studies on MDD found decreased gray matter volume (GMV) in the temporal lobe, basal ganglia, amygdala, hippocampus, and orbitofrontal cortex (Lorenzetti et al., 2009; Zou et al., 2010). Decreased GMV in the temporal gyrus, particularly in the superior and middle temporal gyrus, has been consistently reported (Lorenzetti et al., 2009; Peng et al., 2011). Reduced GMV in the basal ganglia (caudate and putamen) has been also observed in MDD (Hamilton et al., 2008; Koolschijn et al., 2009). Furthermore, treatment-resistant patients have more decreased
45 46 47 48 49 50 51
U
43 44
N C O
39
41 42
19 20 21 22 23 24 25 26 27 28 29 30 31 32 33
Abbreviations: MDD, major depressive disorder; VBM, voxel-based morphometry; ALFF, amplitude of low-frequency fluctuation; MRI, magnetic resonance imaging; fMRI, functional MRI; DSM, Diagnostic and Statistical Manual of Mental Disorders; SPM, statistical parametric mapping; FWHM, full-width at half-maximum; EPI, echo-planar imaging; GMV, gray matter volume; GRF, Gaussian random field. ⁎ Corresponding author. Tel.: +86 771 3277200. E-mail address: [email protected] (W. Guo).
GMV in caudate than treatment-sensitive patients and controls, suggesting that caudate structural deficits may be a contributor of treatment resistance in MDD (Shah et al., 2002). Resting-state functional MRI (fMRI) has been increasingly used to examine brain functional alterations. Low-frequency (0.01 Hz–0.08 Hz) fluctuations at rest are considered physiologically meaningful and associated with intrinsic neural activity (Biswal et al., 1995). Decreased frontal lobe activity (e.g., medial prefrontal cortex) and increased limbic system activity (e.g., amygdala) have been reported in MDD using resting-state fMRI techniques (Chen et al., 2012; Guo et al., 2013c; L et al., 2012; Liu et al., 2012; Sheline et al., 2010). Resting-state fMRI and structural MRI indicate that functional and anatomical brain alterations are linked to the neurobiology of MDD (Drevets et al., 2008; Sheline et al., 2010). However, one important question that remains unsolved is whether and how the functional alterations are related to the anatomical deficits in MDD. If an overlap between the brain regions with functional alterations and anatomical deficits is observed, it may indicate that brain function and GMV of these regions alter synchronously in patients with MDD. In the present study, we used the VBM method to examine anatomical deficits and the amplitude of low-frequency fluctuation (ALFF)
http://dx.doi.org/10.1016/j.pnpbp.2014.05.008 0278-5846/© 2014 Published by Elsevier Inc.
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
84
2. Methods
85
2.1. Subjects
86
102
The subjects included 44 adult patients with MDD from the outpatient clinic of the Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, China, and 44 demographically matched healthy controls recruited from the community. The study was approved by the ethics committee of the First Affiliated Hospital, Guangxi Medical University, China. Written informed consent was obtained from each subject. Depression was diagnosed by the criteria for a current episode of unipolar major depression based on the Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria (First et al., 1997). The Structured Clinical Interview of the DSM-IV was used to confirm the diagnosis. All subjects were right-handed and all patients were drug naive at the scan time. Exclusion criteria for all subjects were other Axis I disorders, such as schizophrenia, bipolar disorder, psychotic depression, substance-induced mood disorder, substance abuse or dependence, acute physical illness, and a history of head injury resulting in loss of consciousness. Hamilton Rating Scale for Depression (17 items) was used to measure depression severity (Hamilton, 1967).
103
2.2. Scan acquisition
104 105
116
Images were obtained on a Siemens 3 T scanner. Subjects were required to lie still with their eyes closed and remain awake. Foam padding and earplugs were used to minimize head motion and scanner noise. A 3D magnetization-prepared rapid acquisition gradient-echo sequence was used to obtain high-resolution whole brain volumetric T1-weighted images with the following parameters: repetition time = 8.5 ms, echo time = 2.98 ms, inversion time = 900 ms, flip angle = 9°, acquisition matrix = 256 × 256, field of view = 240 mm × 240 mm, slice thickness = 1 mm, no gap, and 176 slices. The following parameters were used to acquire resting-state functional images by a gradient-echo echo-planar imaging (EPI) sequence: repetition time/echo time = 2000 ms/30 ms, 30 slices, 64 × 64 matrix, 90° flip angle, 24 cm field of view, 4 mm slice thickness, 0.4 mm gap, and 250 volumes (500 s).
117
2.3. Data processing
118
Structural scans were checked for image artifacts and gross anatomical abnormalities. All structural data were processed using the VBM toolbox (VBM8, http://dbm.neuro.uni-jena.de/vbm) with the Statistical Parametric Mapping software package (SPM8, http://www.fil.ion.ucl.ac. uk/spm). The 3D MRI images were spatially normalized to the customized template (1.5 × 1.5 × 1.5 mm3) and registered each of the images to the same template by estimating the 12-parameter affine transformation. Normalized images were then segmented into gray matter, white matter, and cerebrospinal fluid images. Afterwards, the gray matter images were smoothed with an 8 mm full-width at half-maximum (FWHM) Gaussian kernel to reduce the individual differences of brain anatomy and to increase the signal to noise ratio. Functional data were processed with Data Processing Assistant for Resting-State fMRI (Yan and Zang, 2010) in Matlab (Mathworks). The
98 99 100 101
106 107 108 109 110 111 112 113 114 115
119 120 121 122 123 124 125 126 127 128 129 130 131
146
2.4. Statistical analysis
134 135 136 137 138 139 140 141 142 143 144 145
147
3. Results
162
3.1. Characteristics of the subjects
163
P
R O
Two-sample t-tests and Chi-square tests were conducted to estimate the differences in continuous and categorical variables. After assessing normal distributions, the functional and anatomical data were calculated with two-sample t-tests using voxel-wise cross-subject statistics. Age and sex ratio were used as covariates in the functional and anatomical data comparisons to reduce the potential effect of these two variables, although the two subject groups showed no significant difference in age and sex ratio. The significance level was set to the corrected p b 0.001 for multiple comparisons using Gaussian Random Field (GRF) theory (min z N 3.2905, cluster significance: p b 0.001, corrected). Once brain regions with abnormal anatomical or functional abnormalities were detected, the mean GMV values or ALFF values were extracted from these regions. Linear correlation was performed to determine the correlation between abnormal GMV values or ALFF values of the detected brain regions and clinical variables in the patient group.
D
97
132 133
T
95 96
C
93 94
E
91 92
R
89 90
R
87 88
O
80 81
C
79
N
77 78
U
75 76
fMRI images were initially corrected for head motion and slice timing. None of the subjects had more than 2 mm head motion and 2° of rotation during the whole scan. Each voxel was resampled to 3 × 3 × 3 mm3 with the standard Montreal Neurological Institute EPI template in SPM8. The images were then smoothed with an 8 mm FWHM Gaussian kernel. ALFF was calculated using REST software (Song et al., 2011). After band-pass filtering (0.01 Hz–0.08 Hz) and linear trend removing, the time series for each voxel was transformed into frequency domains using a Fast Fourier Transform to obtain the power spectrum. Finally, the power spectrum was square rooted and averaged across 0.01 Hz to 0.08 Hz at each voxel. The averaged square root was taken as ALFF (Zang et al., 2007). For standardization purposes, the ALFF value of each voxel was divided by the global mean ALFF value.
F
82 83
method to identify the regional functional alterations in MDD. VBM is an unbiased and fully automated whole-brain measurement method and is capable of assessing structural deficits (Ashburner and Friston, 2000). ALFF can be used to detect regional neural synchronous activity by assessing the amplitude of power spectrum of low-frequency (0.01 Hz–0.08 Hz) fluctuations (Zang et al., 2007). By far, these two methods have been successfully applied to study anatomical and functional alterations in clinical studies, including MDD (Guo et al., 2012; Zou et al., 2010). This study aimed to investigate the association between the functional alterations and the anatomical deficits, as well as their relationship with clinical variables in drug-naive MDD.
E
73 74
W. Guo et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
O
2
148 149 150 151 152 153 154 155 156 157 158 159 160 161
Age, sex ratio, and years of education were not significantly different 164 between patient and control groups. The detailed characteristics of the 165 enrolled subjects are shown in Table 1. 166
3.2. Anatomical differences between groups
167
Patients with MDD exhibited significantly decreased GMV in the right inferior temporal gyrus and the left angular gyrus compared with healthy controls (Fig. 1 and Table 2). No significantly increased GMV was found in the patient group.
168 169 170 171
t1:1 t1:2
Table 1 Characteristics of the subjects. Demographic data
Patients (n = 44)
Controls (n = 44)
p value
t1:3
Sex (male/female) Age (years) Education (years) HRSD score Illness duration (months) Duration of the current episode (months) Episode number
22/22 27.52 ± 8.57 12.52 ± 3.04 25.18 ± 5.22 19.61 ± 36.50 2.80 ± 1.77
20/24 29.39 ± 6.70 12.11 ± 2.30
0.67a 0.26b 0.48b
t1:4 t1:5 t1:6 t1:7 t1:8 t1:9
2.00 ± 1.60
HRSD = Hamilton Rating Scale for Depression. a The p value for sex distribution was obtained by chi-square test. b The p values were obtained by two-sample t-tests.
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
t1:10 t1:11 t1:12 t1:13
3
P
R O
O
F
W. Guo et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
173 174 175 176
Compared to healthy controls, decreased ALFF was found in the left middle temporal gyrus, right superior temporal gyrus, and culmen in the patient group (Fig. 2 and Table 2). No significantly increased ALFF was found in the patient group.
177
3.4. Association between functional and anatomical results
178
183
To examine the association between functional and anatomical differences, the regions with abnormal GMV or ALFF were overlaid on the same template. However, no overlap of brain regions was observed. In the patient group, the mean GMV values in the regions with anatomical abnormality were not significantly correlated with the mean ALFF values in the regions with functional abnormality.
184 185
3.5. Correlations between clinical variables and functional and anatomical findings
186 187 188
The linear correlation analyses in the patient group showed significantly negative correlations between the illness duration and the mean GMV values of the left angular gyrus (r = − 0.336, p = 0.026)
t2:1 t2:2
Table 2 Differences in GMV and ALFF between patients and controls.
t2:3 t2:4 t2:5 t2:6 t2:7 t2:8 t2:9 t2:10 t2:11 t2:12 t2:13 t2:14 t2:15
C
E
R
R
N C O
181 182
U
179 180
Measure and cluster location
Peak (MNI)
Number of voxelsa
T value
x
y
z
GMV Patients b controls Right inferior temporal gyrus Left angular gyrus
64.5 −43.5
−54 −60
−12 39
57 56
−3.5542 −3.5282
ALFF Patients b controls Left middle temporal gyrus Right superior temporal gyrus Culmen
−42 66 −3
−60 −30 −39
0 3 −12
20 20 25
−3.8910 −4.6814 −4.3394
a For GMV, 1 voxel = 1.5 × 1.5 × 1.5 mm3; for amplitude of low-frequency fluctuation, 1 voxel = 3 × 3 × 3 mm3; GMV = gray matter volume; ALFF = amplitude of low-frequency fluctuation; MNI = Montreal Neurological Institute.
as well as between the episode number and the mean GMV values of the left angular gyrus (r = −0.341, p = 0.023) (Fig. 3). No correlation was found between other clinical variables and functional or anatomical findings in the patient group.
189 190
3.6. Functional and anatomical differences between patients with first-episode/recurrent depression and controls
193 194
As mentioned above, there are significant correlations between the mean GMV values of the left angular gyrus and the illness duration/ episode number, suggesting that the illness duration/episode number might play a role in the neurobiology of MDD. Thus, it is meaningful to compare the functional and anatomical differences between patients with first-episode/recurrent depression and healthy controls. We therefore divided the patients into two subgroups: first-episode depression (male/female, 13/11) and recurrent depression (male/female, 9/11). Post hoc t-tests were performed after ANCOVA to examine the GMV/ ALFF differences between groups (p b 0.001, GRF corrected). The results showed that there was no significant difference in GMV or ALFF between the two patient subgroups. However, patients with firstepisode depression had lower GMV in the right inferior temporal gyrus than healthy controls (Fig. S1 and Table 3), whereas patients with recurrent depression had lower GMV in the left angular gyrus than healthy controls (Fig. S2 and Table 3). Moreover, patients with first-episode depression exhibited decreased ALFF in the left middle temporal gyrus and culmen compared to healthy controls (Fig. S3 and Table 3), whereas patients with recurrent depression exhibited decreased ALFF in culmen compared to healthy controls (Fig. S4 and Table 3). There was no overlap of brain regions with functional and anatomical differences in the two patient subgroups, and the mean GMV values in brain regions with anatomical abnormality was not significantly correlated with the mean ALFF values in brain regions with functional abnormality in each patient subgroup.
195
4. Discussion
220
E
3.3. Functional differences between groups
T
172
D
Fig. 1. Statistical maps showing gray matter volume differences between groups. Blue denotes decreased gray matter volume, and the color bar indicates the T values from twosample t-tests. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
191 192
196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219
Using the VBM and ALFF methods, the present study revealed both 221 functional and anatomical alterations in patients with MDD. GMV 222 reductions were found in the parietal–temporal regions (i.e., the right 223
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
W. Guo et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
P
R O
O
F
4
236 237 238 239 240 241
E
T
C
E
234 235
R
232 233
R
231
O
229 230
long-standing changes, whereas functional alterations measured by the ALFF method may represent physiological changes associated with the acute illness stage (Ren et al., 2013). Since the duration of the current episode of our patients was 2.80 ± 1.77 months, they could be considered to be at the acute stage of illness within the given episode. This possible interpretation is supported by evidence that functional alterations are normalized after achieving clinical remission (L et al., 2012; Norbury et al., 2010), whereas anatomical deficits seem to be stable and possibly decrease progressively over the illness duration (Bora et al., 2012). Our GMV and ALFF results are in line with the previous findings. For example, decreased GMV in the right inferior temporal gyrus was observed in first-episode MDD by using the VBM method (Bora et al., 2012; Peng et al., 2011). GMV in medial temporal region was reduced in MDD patients with comorbid anxiety disorders (for a review, see Bora et al. (2012)). Meanwhile, decreased functional connectivity and regional activity in the superior/middle temporal gyrus were reported previously (Cullen et al., 2009; Guo et al., 2012; Wu et al., 2011). In addition, multiple studies found regional activity
C
227 228
inferior temporal gyrus and the left angular gyrus), and decreased functional activity was mainly found in the temporal regions (i.e., the left middle temporal gyrus and the right superior temporal gyrus) and the cerebellum (i.e., the culmen). There was no overlap of brain regions with functional and anatomical alterations in the patients and their subgroups (first-episode depression and recurrent depression). However, the mean GMV values of the left angular gyrus were negatively correlated with the episode number and the illness duration in the patient group. We observed a dissociation pattern of brain regions with anatomical and functional abnormalities, such as reduced GMV in parietal–temporal regions and decreased ALFF in the temporal regions and the cerebellum. The dissociation pattern may be attributed to the different analysis methods. The VBM method is used to identify the anatomical deficits of gray matter and the ALFF method is used to investigate resting-state functional alterations of gray matter. Therefore, the VBM and ALFF methods measure different aspects of gray matter in MDD. Anatomical deficits measured by the VBM method may represent more stable and
N
225 226
U
224
D
Fig. 2. Statistical maps showing ALFF differences between groups. Blue denotes decreased ALFF, and the color bar indicates the T values from two-sample t-tests, ALFF = amplitude of lowfrequency fluctuation. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 3. Correlation between the mean gray matter volume of the left angular gyrus and the illness duration or the episode number in the patient group. GMV = gray matter volume, AG = angular gyrus.
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259
W. Guo et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302
−12 −3
41 32
−3.5637 −5.9235
−12
20
−3.5452
F
−4.5989
O
166
difference in the cerebellum by a regional homogeneity method (Guo et al., 2011; Liu et al., 2010; Wu et al., 2011). Moreover, a similar dissociation pattern of functional and anatomical abnormalities has also been reported in schizophrenia patients (Lui et al., 2009; Ren et al., 2013; Rubinov and Bassett, 2011) and individuals with mild cognitive impairment (Han et al., 2012). Together with these studies, our results suggest that brain function and structure may alter independently and play a different role in the neurobiology of MDD. Future studies may benefit from the combination of functional and anatomical MRI methods to clarify the causes of functional and anatomical alterations. As supporting information, previous functional studies rarely reported functional alterations in the areas of structural findings in the present study. The progressive decrease of GMV in MDD is further supported by the negative correlations between the mean GMV values of the left angular gyrus and the episode number or the illness duration in the present study. Therefore, GMV of the left angular gyrus might decrease progressively over illness duration in the patient group. It is interesting that the cerebellum (i.e., the culmen) showed decreased ALFF in patients with MDD. Recently, increasing attention has been given to the higher-order functions of the cerebellum, including emotional control and cognitive processing (Desmond, 2010). Using both task-related and resting-state fMRI, previous studies show abnormal cerebellar activity and connectivity in MDD (Frodl et al., 2010; Guo et al., 2013b). The cerebellum has also been detected as part of a functional network involved in the executive process in MDD (Walter et al., 2007). Recently, increased cerebellar activity related to a disease state was observed in a group of first-episode, drug-naive patients with MDD (Guo et al., 2013a). In accordance with these valuable studies, the present study provides insight into the neurobiology of MDD and suggests that the cerebellar functioning may be more complicated than previously assumed. Our post hoc analyses of functional and anatomical alterations between the two patient subgroups and healthy controls showed that patients with first-episode depression and individuals with recurrent depression might have different functional and anatomical alterations. However, these alterations between the two subgroups did not reach the significance level. Inconsistent with our results, gray matter has been reported to decrease progressively over the illness duration and the episode number in MDD (Bora et al., 2012; Janssen et al., 2007). The inconsistency might be due to the similarity of the two patient subgroups. Both subgroups were drug-naive patients with a short duration of the current episode. The inconsistency might also be due to the relatively small sample size of the two subgroups with limited statistical
P
a For gray matter volume, 1 voxel = 1.5 × 1.5 × 1.5 mm3; for amplitude of lowfrequency fluctuation, 1 voxel = 3 × 3 × 3 mm3; GMV = gray matter volume; ALFF = amplitude of low-frequency fluctuation; MNI = Montreal Neurological Institute.
T
268 269
40.5
C
266 267
−3.9544
E
264 265
98
R
262 263
ALFF First-episode patients vs. recurrent patients None Patients b controls First-episode patients b controls Culmen −3 −51 Left middle temporal gyrus −60 −24 Recurrent patients b controls Culmen −3 −39
T value
−16.5
R
260 261
Number of voxelsa
z
N C O
t3:22
y
GMV First-episode patients vs. recurrent patients None First-episode patients b controls Right inferior temporal gyrus 67.5 −51 Recurrent patients b controls Left angular gyrus −43.5 −61.5
U
t3:5 t3:6 t3:7 t3:8 t3:9 t3:10 t3:11 t3:12 t3:13 t3:14 t3:15 t3:16 t3:17 t3:18 t3:19 t3:20 t3:21
Peak (MNI) x
R O
Measure and cluster location
t3:4
D
t3:3
power. Future studies with a large sample size are needed to warrant or refute the present results when comparing the differences of functional and anatomical deficits between the two patient subgroups. The present findings have some limitations. First, a longitudinal study is needed to clarify whether the functional and anatomical deficits remain stable after treatment. Second, some patients were not in their first episode, and the inclusion of recurrent patients might have biased the present results. However, post hoc analyses exhibited that patients with first-episode depression and individuals with recurrent depression had no significant difference in functional and anatomical deficits. Hence, recruitment of recurrent depression seems to have little influence to the present results. Finally, psychological assessments were not conducted in the present study. Thus, we were not able to examine the relationship between functional and anatomical alterations and psychological assessments. To the best of our knowledge, this is the first to investigate anatomical and functional alterations in the same patient sample. A dissociation pattern of brain regions with anatomical and functional alterations is observed in drug-naive MDD, and thus suggesting that brain functional and anatomical deficits contribute independently to the neurobiology of MDD. The present findings document that brain GMV reduction is accompanied with decreased regional function in drug-naive MDD. Future studies with the combination of functional and anatomical MRI methods would clarify the causes of functional and anatomical alterations and the dissociation phenomenon, and provide complementary information for understanding the neurobiology of MDD. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.pnpbp.2014.05.008.
Table 3 Differences in GMV and ALFF between first-episode/recurrent patients and controls.
E
t3:1 t3:2
5
303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 Q2 325 326 327 328 329 330
Contributors
331
Drs. Guo W and Zhao J designed the study. Drs. Liu J, Yu M, Xiao C, and Zhang J collected the original imaging data. Drs. Guo W, Liu F, and Zhang Z managed and analyzed the imaging data. Drs. Guo W and Liu F wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript.
332 333
Acknowledgments
337
The study was supported by grants from the National Natural Science Foundation of China (Grant nos. 81260210 and 30900483), the Natural Science Foundation of Guangxi (Grant no. 2013GXNSFAA019107), and the special funding from the Ministry of Health of the Peoples' Republic of China (Grant no. 201002003). The authors appreciate anonymous reviewers for their suggestions and comments.
338 339
References
344
Ashburner J, Friston KJ. Voxel-based morphometry—the methods. Neuroimage 2000;11: 805–21. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995;34:537–41. Bora E, Fornito A, Pantelis C, Yucel M. Gray matter abnormalities in major depressive disorder: a meta-analysis of voxel based morphometry studies. J Affect Disord 2012;138:9–18. Chen JD, Liu F, Xun GL, Chen HF, Hu MR, Guo XF, et al. Early and late onset, first-episode, treatment-naive depression: same clinical symptoms, different regional neural activities. J Affect Disord 2012;143:56–63. Cullen KR, Gee DG, Klimes-Dougan B, Gabbay V, Hulvershorn L, Mueller BA, et al. A preliminary study of functional connectivity in comorbid adolescent depression. Neurosci Lett 2009;460:227–31. Desmond JE. Trends in cerebellar research. Behav Neurol 2010;23:1–2. Drevets WC, Price JL, Furey ML. Brain structural and functional abnormalities in mood disorders: implications for neurocircuitry models of depression. Brain Struct Funct 2008;213:93–118. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV Axis I Disorders (SCID). Washington: DC, American Psychiatric Press; 1997. Fitzgerald PB, Laird AR, Maller J, Daskalakis ZJ. A meta-analytic study of changes in brain activation in depression. Hum Brain Mapp 2008;29:683–95.
345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
334 335 336
340 341 342 343
P
R O
O
F
Lorenzetti V, Allen NB, Fornito A, Yucel M. Structural brain abnormalities in major depressive disorder: a selective review of recent MRI studies. J Affect Disord 2009; 117:1–17. Lui S, Deng W, Huang X, Jiang L, Ma X, Chen H, et al. Association of cerebral deficits with clinical symptoms in antipsychotic-naive first-episode schizophrenia: an optimized voxel-based morphometry and resting state functional connectivity study. Am J Psychiatry 2009;166:196–205. Norbury R, Selvaraj S, Taylor MJ, Harmer C, Cowen PJ. Increased neural response to fear in patients recovered from depression: a 3 T functional magnetic resonance imaging study. Psychol Med 2010;40:425–32. Peng J, Liu J, Nie B, Li Y, Shan B, Wang G, et al. Cerebral and cerebellar gray matter reduction in first-episode patients with major depressive disorder: a voxel-based morphometry study. Eur J Radiol 2011;80:395–9. Ren W, Lui S, Deng W, Li F, Li M, Huang X, et al. Anatomical and functional brain abnormalities in drug-naive first-episode schizophrenia. Am J Psychiatry 2013;170: 1308–16. Rigucci S, Serafini G, Pompili M, Kotzalidis GD, Tatarelli R. Anatomical and functional correlates in major depressive disorder: the contribution of neuroimaging studies. World J Biol Psychiatry 2010;11:165–80. Rubinov M, Bassett DS. Emerging evidence of connectomic abnormalities in schizophrenia. J Neurosci 2011;31:6263–5. Shah PJ, Glabus MF, Goodwin GM, Ebmeier KP. Chronic, treatment-resistant depression and right fronto-striatal atrophy. Br J Psychiatry 2002;180:434–40. Sheline YI, Price JL, Yan Z, Mintun MA. Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proc Natl Acad Sci U S A 2010;107:11020–5. Song XW, Dong ZY, Long XY, Li SF, Zuo XN, Zhu CZ, et al. REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PLoS ONE 2011;6:e25031. Walter H, Vasic N, Hose A, Spitzer M, Wolf RC. Working memory dysfunction in schizophrenia compared to healthy controls and patients with depression: evidence from event-related fMRI. Neuroimage 2007;35:1551–61. Wu QZ, Li DM, Kuang WH, Zhang TJ, Lui S, Huang XQ, et al. Abnormal regional spontaneous neural activity in treatment-refractory depression revealed by resting-state fMRI. Hum Brain Mapp 2011;32:1290–9. Yan C, Zang Y. DPARSF: a MATLAB toolbox for “pipeline” data analysis of resting-state fMRI. Front Syst Neurosci 2010;4:13. Zang YF, He Y, Zhu CZ, Cao QJ, Sui MQ, Liang M, et al. Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev 2007;29: 83–91. Zou K, Deng W, Li T, Zhang B, Jiang L, Huang C, et al. Changes of brain morphometry in first-episode, drug-naive, non-late-life adult patients with major depression: an optimized voxel-based morphometry study. Biol Psychiatry 2010;67:186–8.
D
Frodl T, Bokde AL, Scheuerecker J, Lisiecka D, Schoepf V, Hampel H, et al. Functional connectivity bias of the orbitofrontal cortex in drug-free patients with major depression. Biol Psychiatry 2010;67:161–7. Guo W, Liu F, Liu J, Yu L, Zhang Z, Zhang J, et al. Is there a cerebellar compensatory effort in first-episode, treatment-naive major depressive disorder at rest? Prog Neuropsychopharmacol Biol Psychiatry 2013a;46:13–8. Guo W, Liu F, Xue Z, Gao K, Liu Z, Xiao C, et al. Abnormal resting-state cerebellar–cerebral functional connectivity in treatment-resistant depression and treatment sensitive depression. Prog Neuropsychopharmacol Biol Psychiatry 2013b;44:51–7. Guo W, Liu F, Zhang J, Zhang Z, Yu L, Liu J, et al. Dissociation of regional activity in the default mode network in first-episode, drug-naive major depressive disorder at rest. J Affect Disord 2013c;151:1097–101. Guo WB, Liu F, Xue ZM, Xu XJ, Wu RR, Ma CQ, et al. Alterations of the amplitude of lowfrequency fluctuations in treatment-resistant and treatment-response depression: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 2012;37: 153–60. Guo WB, Sun XL, Liu L, Xu Q, Wu RR, Liu ZN, et al. Disrupted regional homogeneity in treatment-resistant depression: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 2011;35:1297–302. Hamilton JP, Siemer M, Gotlib IH. Amygdala volume in major depressive disorder: a metaanalysis of magnetic resonance imaging studies. Mol Psychiatry 2008;13:993–1000. Hamilton M. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol 1967;6:278–96. Han Y, Lui S, Kuang W, Lang Q, Zou L, Jia J. Anatomical and functional deficits in patients with amnestic mild cognitive impairment. PLoS ONE 2012;7:e28664. Janssen J, Hulshoff Pol HE, de Leeuw FE, Schnack HG, Lampe IK, Kok RM, et al. Hippocampal volume and subcortical white matter lesions in late life depression: comparison of early and late onset depression. J Neurol Neurosurg Psychiatry 2007;78:638–40. Koolschijn PC, van Haren NE, Lensvelt-Mulders GJ, Hulshoff Pol HE, Kahn RS. Brain volume abnormalities in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. Hum Brain Mapp 2009;30:3719–35. L W, D FH, I BH, J L. A systematic review of resting-state functional-MRI studies in major depression. J Affect Disord 2012;142:6–12. Liu F, Guo W, Liu L, Long Z, Ma C, Xue Z, et al. Abnormal amplitude low-frequency oscillations in medication-naive, first-episode patients with major depressive disorder: a resting-state fMRI study. J Affect Disord 2013;146:401–6. Liu F, Hu M, Wang S, Guo W, Zhao J, Li J, et al. Abnormal regional spontaneous neural activity in first-episode, treatment-naive patients with late-life depression: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 2012;39:326–31. Liu Z, Xu C, Xu Y, Wang Y, Zhao B, Lv Y, et al. 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 2010;182:211–5.
T
366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407
W. Guo et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
E
6
U
N
C
O
R
R
E
C
450
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449
Contents lists available at ScienceDirect
Progress in Neuro-Psychopharmacology & Biological Psychiatry journal homepage: www.elsevier.com/locate/pnp
F
O
5 6 7
a
8
a r t i c l e
9 10 11 12 13
Article history: Received 1 March 2014 Received in revised form 10 May 2014 Accepted 12 May 2014 Available online xxxx
14 15 16 17 18
Keywords: Amplitude of low-frequency fluctuation Gray matter Major depressive disorder Voxel-based morphometry
Mental Health Center, 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, China Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, Hunan 410011, China
i n f o
a b s t r a c t
Background: Functional and anatomical deficits have been involved in the neurobiology of major depressive disorder (MDD). However, no study has ever been conducted to examine whether and how functional alterations are related to anatomical deficits in MDD. This study aimed to determine the association between brain functional and anatomical deficits in drug-naive MDD. Methods: Forty-four patients with MDD and 44 age-, sex-, and education-matched healthy controls underwent structural and resting-state functional magnetic resonance imaging scanning. The voxel-based morphometry (VBM) and amplitude of low-frequency fluctuation (ALFF) methods were used to analyze the imaging data. Results: VBM analysis showed gray matter volume (GMV) reductions in the parietal–temporal regions (i.e., the right inferior temporal gyrus and the left angular gyrus). Functional alterations revealed by ALFF mainly occurred in the temporal regions (i.e., the left middle temporal gyrus and the right superior temporal gyrus) and the cerebellum (i.e., the culmen). There is no overlap between brain regions with functional alterations and anatomical deficits in the patients and their subgroups (first-episode depression and recurrent depression). The episode number and the illness duration were correlated with the mean GMV values of the left angular gyrus. Conclusions: A dissociation pattern of brain functional and anatomical deficits is observed in MDD. Our findings suggest that brain functional and anatomical deficits contribute independently to the neurobiology of MDD. © 2014 Published by Elsevier Inc.
E
C
c
R O
b
P
4
Wenbin Guo a,⁎, Feng Liu b, Miaoyu Yu a, Jian Zhang a, Zhikun Zhang a, Jianrong Liu a, Changqing Xiao a, Jingping Zhao c
D
3Q1
E
2
Functional and anatomical brain deficits in drug-naive major depressive disorder
T
1
R
34 38 36 35
R
37
1. Introduction
40
Structural and functional magnetic resonance imaging (MRI) indicates that major depressive disorder (MDD) is a disease with abnormal brain structure and function (Drevets et al., 2008; Fitzgerald et al., 2008; Guo et al., 2013a; Liu et al., 2013; Rigucci et al., 2010). Structural MRI studies on MDD found decreased gray matter volume (GMV) in the temporal lobe, basal ganglia, amygdala, hippocampus, and orbitofrontal cortex (Lorenzetti et al., 2009; Zou et al., 2010). Decreased GMV in the temporal gyrus, particularly in the superior and middle temporal gyrus, has been consistently reported (Lorenzetti et al., 2009; Peng et al., 2011). Reduced GMV in the basal ganglia (caudate and putamen) has been also observed in MDD (Hamilton et al., 2008; Koolschijn et al., 2009). Furthermore, treatment-resistant patients have more decreased
45 46 47 48 49 50 51
U
43 44
N C O
39
41 42
19 20 21 22 23 24 25 26 27 28 29 30 31 32 33
Abbreviations: MDD, major depressive disorder; VBM, voxel-based morphometry; ALFF, amplitude of low-frequency fluctuation; MRI, magnetic resonance imaging; fMRI, functional MRI; DSM, Diagnostic and Statistical Manual of Mental Disorders; SPM, statistical parametric mapping; FWHM, full-width at half-maximum; EPI, echo-planar imaging; GMV, gray matter volume; GRF, Gaussian random field. ⁎ Corresponding author. Tel.: +86 771 3277200. E-mail address: [email protected] (W. Guo).
GMV in caudate than treatment-sensitive patients and controls, suggesting that caudate structural deficits may be a contributor of treatment resistance in MDD (Shah et al., 2002). Resting-state functional MRI (fMRI) has been increasingly used to examine brain functional alterations. Low-frequency (0.01 Hz–0.08 Hz) fluctuations at rest are considered physiologically meaningful and associated with intrinsic neural activity (Biswal et al., 1995). Decreased frontal lobe activity (e.g., medial prefrontal cortex) and increased limbic system activity (e.g., amygdala) have been reported in MDD using resting-state fMRI techniques (Chen et al., 2012; Guo et al., 2013c; L et al., 2012; Liu et al., 2012; Sheline et al., 2010). Resting-state fMRI and structural MRI indicate that functional and anatomical brain alterations are linked to the neurobiology of MDD (Drevets et al., 2008; Sheline et al., 2010). However, one important question that remains unsolved is whether and how the functional alterations are related to the anatomical deficits in MDD. If an overlap between the brain regions with functional alterations and anatomical deficits is observed, it may indicate that brain function and GMV of these regions alter synchronously in patients with MDD. In the present study, we used the VBM method to examine anatomical deficits and the amplitude of low-frequency fluctuation (ALFF)
http://dx.doi.org/10.1016/j.pnpbp.2014.05.008 0278-5846/© 2014 Published by Elsevier Inc.
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72
84
2. Methods
85
2.1. Subjects
86
102
The subjects included 44 adult patients with MDD from the outpatient clinic of the Mental Health Center, the First Affiliated Hospital, Guangxi Medical University, China, and 44 demographically matched healthy controls recruited from the community. The study was approved by the ethics committee of the First Affiliated Hospital, Guangxi Medical University, China. Written informed consent was obtained from each subject. Depression was diagnosed by the criteria for a current episode of unipolar major depression based on the Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV criteria (First et al., 1997). The Structured Clinical Interview of the DSM-IV was used to confirm the diagnosis. All subjects were right-handed and all patients were drug naive at the scan time. Exclusion criteria for all subjects were other Axis I disorders, such as schizophrenia, bipolar disorder, psychotic depression, substance-induced mood disorder, substance abuse or dependence, acute physical illness, and a history of head injury resulting in loss of consciousness. Hamilton Rating Scale for Depression (17 items) was used to measure depression severity (Hamilton, 1967).
103
2.2. Scan acquisition
104 105
116
Images were obtained on a Siemens 3 T scanner. Subjects were required to lie still with their eyes closed and remain awake. Foam padding and earplugs were used to minimize head motion and scanner noise. A 3D magnetization-prepared rapid acquisition gradient-echo sequence was used to obtain high-resolution whole brain volumetric T1-weighted images with the following parameters: repetition time = 8.5 ms, echo time = 2.98 ms, inversion time = 900 ms, flip angle = 9°, acquisition matrix = 256 × 256, field of view = 240 mm × 240 mm, slice thickness = 1 mm, no gap, and 176 slices. The following parameters were used to acquire resting-state functional images by a gradient-echo echo-planar imaging (EPI) sequence: repetition time/echo time = 2000 ms/30 ms, 30 slices, 64 × 64 matrix, 90° flip angle, 24 cm field of view, 4 mm slice thickness, 0.4 mm gap, and 250 volumes (500 s).
117
2.3. Data processing
118
Structural scans were checked for image artifacts and gross anatomical abnormalities. All structural data were processed using the VBM toolbox (VBM8, http://dbm.neuro.uni-jena.de/vbm) with the Statistical Parametric Mapping software package (SPM8, http://www.fil.ion.ucl.ac. uk/spm). The 3D MRI images were spatially normalized to the customized template (1.5 × 1.5 × 1.5 mm3) and registered each of the images to the same template by estimating the 12-parameter affine transformation. Normalized images were then segmented into gray matter, white matter, and cerebrospinal fluid images. Afterwards, the gray matter images were smoothed with an 8 mm full-width at half-maximum (FWHM) Gaussian kernel to reduce the individual differences of brain anatomy and to increase the signal to noise ratio. Functional data were processed with Data Processing Assistant for Resting-State fMRI (Yan and Zang, 2010) in Matlab (Mathworks). The
98 99 100 101
106 107 108 109 110 111 112 113 114 115
119 120 121 122 123 124 125 126 127 128 129 130 131
146
2.4. Statistical analysis
134 135 136 137 138 139 140 141 142 143 144 145
147
3. Results
162
3.1. Characteristics of the subjects
163
P
R O
Two-sample t-tests and Chi-square tests were conducted to estimate the differences in continuous and categorical variables. After assessing normal distributions, the functional and anatomical data were calculated with two-sample t-tests using voxel-wise cross-subject statistics. Age and sex ratio were used as covariates in the functional and anatomical data comparisons to reduce the potential effect of these two variables, although the two subject groups showed no significant difference in age and sex ratio. The significance level was set to the corrected p b 0.001 for multiple comparisons using Gaussian Random Field (GRF) theory (min z N 3.2905, cluster significance: p b 0.001, corrected). Once brain regions with abnormal anatomical or functional abnormalities were detected, the mean GMV values or ALFF values were extracted from these regions. Linear correlation was performed to determine the correlation between abnormal GMV values or ALFF values of the detected brain regions and clinical variables in the patient group.
D
97
132 133
T
95 96
C
93 94
E
91 92
R
89 90
R
87 88
O
80 81
C
79
N
77 78
U
75 76
fMRI images were initially corrected for head motion and slice timing. None of the subjects had more than 2 mm head motion and 2° of rotation during the whole scan. Each voxel was resampled to 3 × 3 × 3 mm3 with the standard Montreal Neurological Institute EPI template in SPM8. The images were then smoothed with an 8 mm FWHM Gaussian kernel. ALFF was calculated using REST software (Song et al., 2011). After band-pass filtering (0.01 Hz–0.08 Hz) and linear trend removing, the time series for each voxel was transformed into frequency domains using a Fast Fourier Transform to obtain the power spectrum. Finally, the power spectrum was square rooted and averaged across 0.01 Hz to 0.08 Hz at each voxel. The averaged square root was taken as ALFF (Zang et al., 2007). For standardization purposes, the ALFF value of each voxel was divided by the global mean ALFF value.
F
82 83
method to identify the regional functional alterations in MDD. VBM is an unbiased and fully automated whole-brain measurement method and is capable of assessing structural deficits (Ashburner and Friston, 2000). ALFF can be used to detect regional neural synchronous activity by assessing the amplitude of power spectrum of low-frequency (0.01 Hz–0.08 Hz) fluctuations (Zang et al., 2007). By far, these two methods have been successfully applied to study anatomical and functional alterations in clinical studies, including MDD (Guo et al., 2012; Zou et al., 2010). This study aimed to investigate the association between the functional alterations and the anatomical deficits, as well as their relationship with clinical variables in drug-naive MDD.
E
73 74
W. Guo et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
O
2
148 149 150 151 152 153 154 155 156 157 158 159 160 161
Age, sex ratio, and years of education were not significantly different 164 between patient and control groups. The detailed characteristics of the 165 enrolled subjects are shown in Table 1. 166
3.2. Anatomical differences between groups
167
Patients with MDD exhibited significantly decreased GMV in the right inferior temporal gyrus and the left angular gyrus compared with healthy controls (Fig. 1 and Table 2). No significantly increased GMV was found in the patient group.
168 169 170 171
t1:1 t1:2
Table 1 Characteristics of the subjects. Demographic data
Patients (n = 44)
Controls (n = 44)
p value
t1:3
Sex (male/female) Age (years) Education (years) HRSD score Illness duration (months) Duration of the current episode (months) Episode number
22/22 27.52 ± 8.57 12.52 ± 3.04 25.18 ± 5.22 19.61 ± 36.50 2.80 ± 1.77
20/24 29.39 ± 6.70 12.11 ± 2.30
0.67a 0.26b 0.48b
t1:4 t1:5 t1:6 t1:7 t1:8 t1:9
2.00 ± 1.60
HRSD = Hamilton Rating Scale for Depression. a The p value for sex distribution was obtained by chi-square test. b The p values were obtained by two-sample t-tests.
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
t1:10 t1:11 t1:12 t1:13
3
P
R O
O
F
W. Guo et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
173 174 175 176
Compared to healthy controls, decreased ALFF was found in the left middle temporal gyrus, right superior temporal gyrus, and culmen in the patient group (Fig. 2 and Table 2). No significantly increased ALFF was found in the patient group.
177
3.4. Association between functional and anatomical results
178
183
To examine the association between functional and anatomical differences, the regions with abnormal GMV or ALFF were overlaid on the same template. However, no overlap of brain regions was observed. In the patient group, the mean GMV values in the regions with anatomical abnormality were not significantly correlated with the mean ALFF values in the regions with functional abnormality.
184 185
3.5. Correlations between clinical variables and functional and anatomical findings
186 187 188
The linear correlation analyses in the patient group showed significantly negative correlations between the illness duration and the mean GMV values of the left angular gyrus (r = − 0.336, p = 0.026)
t2:1 t2:2
Table 2 Differences in GMV and ALFF between patients and controls.
t2:3 t2:4 t2:5 t2:6 t2:7 t2:8 t2:9 t2:10 t2:11 t2:12 t2:13 t2:14 t2:15
C
E
R
R
N C O
181 182
U
179 180
Measure and cluster location
Peak (MNI)
Number of voxelsa
T value
x
y
z
GMV Patients b controls Right inferior temporal gyrus Left angular gyrus
64.5 −43.5
−54 −60
−12 39
57 56
−3.5542 −3.5282
ALFF Patients b controls Left middle temporal gyrus Right superior temporal gyrus Culmen
−42 66 −3
−60 −30 −39
0 3 −12
20 20 25
−3.8910 −4.6814 −4.3394
a For GMV, 1 voxel = 1.5 × 1.5 × 1.5 mm3; for amplitude of low-frequency fluctuation, 1 voxel = 3 × 3 × 3 mm3; GMV = gray matter volume; ALFF = amplitude of low-frequency fluctuation; MNI = Montreal Neurological Institute.
as well as between the episode number and the mean GMV values of the left angular gyrus (r = −0.341, p = 0.023) (Fig. 3). No correlation was found between other clinical variables and functional or anatomical findings in the patient group.
189 190
3.6. Functional and anatomical differences between patients with first-episode/recurrent depression and controls
193 194
As mentioned above, there are significant correlations between the mean GMV values of the left angular gyrus and the illness duration/ episode number, suggesting that the illness duration/episode number might play a role in the neurobiology of MDD. Thus, it is meaningful to compare the functional and anatomical differences between patients with first-episode/recurrent depression and healthy controls. We therefore divided the patients into two subgroups: first-episode depression (male/female, 13/11) and recurrent depression (male/female, 9/11). Post hoc t-tests were performed after ANCOVA to examine the GMV/ ALFF differences between groups (p b 0.001, GRF corrected). The results showed that there was no significant difference in GMV or ALFF between the two patient subgroups. However, patients with firstepisode depression had lower GMV in the right inferior temporal gyrus than healthy controls (Fig. S1 and Table 3), whereas patients with recurrent depression had lower GMV in the left angular gyrus than healthy controls (Fig. S2 and Table 3). Moreover, patients with first-episode depression exhibited decreased ALFF in the left middle temporal gyrus and culmen compared to healthy controls (Fig. S3 and Table 3), whereas patients with recurrent depression exhibited decreased ALFF in culmen compared to healthy controls (Fig. S4 and Table 3). There was no overlap of brain regions with functional and anatomical differences in the two patient subgroups, and the mean GMV values in brain regions with anatomical abnormality was not significantly correlated with the mean ALFF values in brain regions with functional abnormality in each patient subgroup.
195
4. Discussion
220
E
3.3. Functional differences between groups
T
172
D
Fig. 1. Statistical maps showing gray matter volume differences between groups. Blue denotes decreased gray matter volume, and the color bar indicates the T values from twosample t-tests. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
191 192
196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219
Using the VBM and ALFF methods, the present study revealed both 221 functional and anatomical alterations in patients with MDD. GMV 222 reductions were found in the parietal–temporal regions (i.e., the right 223
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
W. Guo et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
P
R O
O
F
4
236 237 238 239 240 241
E
T
C
E
234 235
R
232 233
R
231
O
229 230
long-standing changes, whereas functional alterations measured by the ALFF method may represent physiological changes associated with the acute illness stage (Ren et al., 2013). Since the duration of the current episode of our patients was 2.80 ± 1.77 months, they could be considered to be at the acute stage of illness within the given episode. This possible interpretation is supported by evidence that functional alterations are normalized after achieving clinical remission (L et al., 2012; Norbury et al., 2010), whereas anatomical deficits seem to be stable and possibly decrease progressively over the illness duration (Bora et al., 2012). Our GMV and ALFF results are in line with the previous findings. For example, decreased GMV in the right inferior temporal gyrus was observed in first-episode MDD by using the VBM method (Bora et al., 2012; Peng et al., 2011). GMV in medial temporal region was reduced in MDD patients with comorbid anxiety disorders (for a review, see Bora et al. (2012)). Meanwhile, decreased functional connectivity and regional activity in the superior/middle temporal gyrus were reported previously (Cullen et al., 2009; Guo et al., 2012; Wu et al., 2011). In addition, multiple studies found regional activity
C
227 228
inferior temporal gyrus and the left angular gyrus), and decreased functional activity was mainly found in the temporal regions (i.e., the left middle temporal gyrus and the right superior temporal gyrus) and the cerebellum (i.e., the culmen). There was no overlap of brain regions with functional and anatomical alterations in the patients and their subgroups (first-episode depression and recurrent depression). However, the mean GMV values of the left angular gyrus were negatively correlated with the episode number and the illness duration in the patient group. We observed a dissociation pattern of brain regions with anatomical and functional abnormalities, such as reduced GMV in parietal–temporal regions and decreased ALFF in the temporal regions and the cerebellum. The dissociation pattern may be attributed to the different analysis methods. The VBM method is used to identify the anatomical deficits of gray matter and the ALFF method is used to investigate resting-state functional alterations of gray matter. Therefore, the VBM and ALFF methods measure different aspects of gray matter in MDD. Anatomical deficits measured by the VBM method may represent more stable and
N
225 226
U
224
D
Fig. 2. Statistical maps showing ALFF differences between groups. Blue denotes decreased ALFF, and the color bar indicates the T values from two-sample t-tests, ALFF = amplitude of lowfrequency fluctuation. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 3. Correlation between the mean gray matter volume of the left angular gyrus and the illness duration or the episode number in the patient group. GMV = gray matter volume, AG = angular gyrus.
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259
W. Guo et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302
−12 −3
41 32
−3.5637 −5.9235
−12
20
−3.5452
F
−4.5989
O
166
difference in the cerebellum by a regional homogeneity method (Guo et al., 2011; Liu et al., 2010; Wu et al., 2011). Moreover, a similar dissociation pattern of functional and anatomical abnormalities has also been reported in schizophrenia patients (Lui et al., 2009; Ren et al., 2013; Rubinov and Bassett, 2011) and individuals with mild cognitive impairment (Han et al., 2012). Together with these studies, our results suggest that brain function and structure may alter independently and play a different role in the neurobiology of MDD. Future studies may benefit from the combination of functional and anatomical MRI methods to clarify the causes of functional and anatomical alterations. As supporting information, previous functional studies rarely reported functional alterations in the areas of structural findings in the present study. The progressive decrease of GMV in MDD is further supported by the negative correlations between the mean GMV values of the left angular gyrus and the episode number or the illness duration in the present study. Therefore, GMV of the left angular gyrus might decrease progressively over illness duration in the patient group. It is interesting that the cerebellum (i.e., the culmen) showed decreased ALFF in patients with MDD. Recently, increasing attention has been given to the higher-order functions of the cerebellum, including emotional control and cognitive processing (Desmond, 2010). Using both task-related and resting-state fMRI, previous studies show abnormal cerebellar activity and connectivity in MDD (Frodl et al., 2010; Guo et al., 2013b). The cerebellum has also been detected as part of a functional network involved in the executive process in MDD (Walter et al., 2007). Recently, increased cerebellar activity related to a disease state was observed in a group of first-episode, drug-naive patients with MDD (Guo et al., 2013a). In accordance with these valuable studies, the present study provides insight into the neurobiology of MDD and suggests that the cerebellar functioning may be more complicated than previously assumed. Our post hoc analyses of functional and anatomical alterations between the two patient subgroups and healthy controls showed that patients with first-episode depression and individuals with recurrent depression might have different functional and anatomical alterations. However, these alterations between the two subgroups did not reach the significance level. Inconsistent with our results, gray matter has been reported to decrease progressively over the illness duration and the episode number in MDD (Bora et al., 2012; Janssen et al., 2007). The inconsistency might be due to the similarity of the two patient subgroups. Both subgroups were drug-naive patients with a short duration of the current episode. The inconsistency might also be due to the relatively small sample size of the two subgroups with limited statistical
P
a For gray matter volume, 1 voxel = 1.5 × 1.5 × 1.5 mm3; for amplitude of lowfrequency fluctuation, 1 voxel = 3 × 3 × 3 mm3; GMV = gray matter volume; ALFF = amplitude of low-frequency fluctuation; MNI = Montreal Neurological Institute.
T
268 269
40.5
C
266 267
−3.9544
E
264 265
98
R
262 263
ALFF First-episode patients vs. recurrent patients None Patients b controls First-episode patients b controls Culmen −3 −51 Left middle temporal gyrus −60 −24 Recurrent patients b controls Culmen −3 −39
T value
−16.5
R
260 261
Number of voxelsa
z
N C O
t3:22
y
GMV First-episode patients vs. recurrent patients None First-episode patients b controls Right inferior temporal gyrus 67.5 −51 Recurrent patients b controls Left angular gyrus −43.5 −61.5
U
t3:5 t3:6 t3:7 t3:8 t3:9 t3:10 t3:11 t3:12 t3:13 t3:14 t3:15 t3:16 t3:17 t3:18 t3:19 t3:20 t3:21
Peak (MNI) x
R O
Measure and cluster location
t3:4
D
t3:3
power. Future studies with a large sample size are needed to warrant or refute the present results when comparing the differences of functional and anatomical deficits between the two patient subgroups. The present findings have some limitations. First, a longitudinal study is needed to clarify whether the functional and anatomical deficits remain stable after treatment. Second, some patients were not in their first episode, and the inclusion of recurrent patients might have biased the present results. However, post hoc analyses exhibited that patients with first-episode depression and individuals with recurrent depression had no significant difference in functional and anatomical deficits. Hence, recruitment of recurrent depression seems to have little influence to the present results. Finally, psychological assessments were not conducted in the present study. Thus, we were not able to examine the relationship between functional and anatomical alterations and psychological assessments. To the best of our knowledge, this is the first to investigate anatomical and functional alterations in the same patient sample. A dissociation pattern of brain regions with anatomical and functional alterations is observed in drug-naive MDD, and thus suggesting that brain functional and anatomical deficits contribute independently to the neurobiology of MDD. The present findings document that brain GMV reduction is accompanied with decreased regional function in drug-naive MDD. Future studies with the combination of functional and anatomical MRI methods would clarify the causes of functional and anatomical alterations and the dissociation phenomenon, and provide complementary information for understanding the neurobiology of MDD. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.pnpbp.2014.05.008.
Table 3 Differences in GMV and ALFF between first-episode/recurrent patients and controls.
E
t3:1 t3:2
5
303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 Q2 325 326 327 328 329 330
Contributors
331
Drs. Guo W and Zhao J designed the study. Drs. Liu J, Yu M, Xiao C, and Zhang J collected the original imaging data. Drs. Guo W, Liu F, and Zhang Z managed and analyzed the imaging data. Drs. Guo W and Liu F wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript.
332 333
Acknowledgments
337
The study was supported by grants from the National Natural Science Foundation of China (Grant nos. 81260210 and 30900483), the Natural Science Foundation of Guangxi (Grant no. 2013GXNSFAA019107), and the special funding from the Ministry of Health of the Peoples' Republic of China (Grant no. 201002003). The authors appreciate anonymous reviewers for their suggestions and comments.
338 339
References
344
Ashburner J, Friston KJ. Voxel-based morphometry—the methods. Neuroimage 2000;11: 805–21. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995;34:537–41. Bora E, Fornito A, Pantelis C, Yucel M. Gray matter abnormalities in major depressive disorder: a meta-analysis of voxel based morphometry studies. J Affect Disord 2012;138:9–18. Chen JD, Liu F, Xun GL, Chen HF, Hu MR, Guo XF, et al. Early and late onset, first-episode, treatment-naive depression: same clinical symptoms, different regional neural activities. J Affect Disord 2012;143:56–63. Cullen KR, Gee DG, Klimes-Dougan B, Gabbay V, Hulvershorn L, Mueller BA, et al. A preliminary study of functional connectivity in comorbid adolescent depression. Neurosci Lett 2009;460:227–31. Desmond JE. Trends in cerebellar research. Behav Neurol 2010;23:1–2. Drevets WC, Price JL, Furey ML. Brain structural and functional abnormalities in mood disorders: implications for neurocircuitry models of depression. Brain Struct Funct 2008;213:93–118. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV Axis I Disorders (SCID). Washington: DC, American Psychiatric Press; 1997. Fitzgerald PB, Laird AR, Maller J, Daskalakis ZJ. A meta-analytic study of changes in brain activation in depression. Hum Brain Mapp 2008;29:683–95.
345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
334 335 336
340 341 342 343
P
R O
O
F
Lorenzetti V, Allen NB, Fornito A, Yucel M. Structural brain abnormalities in major depressive disorder: a selective review of recent MRI studies. J Affect Disord 2009; 117:1–17. Lui S, Deng W, Huang X, Jiang L, Ma X, Chen H, et al. Association of cerebral deficits with clinical symptoms in antipsychotic-naive first-episode schizophrenia: an optimized voxel-based morphometry and resting state functional connectivity study. Am J Psychiatry 2009;166:196–205. Norbury R, Selvaraj S, Taylor MJ, Harmer C, Cowen PJ. Increased neural response to fear in patients recovered from depression: a 3 T functional magnetic resonance imaging study. Psychol Med 2010;40:425–32. Peng J, Liu J, Nie B, Li Y, Shan B, Wang G, et al. Cerebral and cerebellar gray matter reduction in first-episode patients with major depressive disorder: a voxel-based morphometry study. Eur J Radiol 2011;80:395–9. Ren W, Lui S, Deng W, Li F, Li M, Huang X, et al. Anatomical and functional brain abnormalities in drug-naive first-episode schizophrenia. Am J Psychiatry 2013;170: 1308–16. Rigucci S, Serafini G, Pompili M, Kotzalidis GD, Tatarelli R. Anatomical and functional correlates in major depressive disorder: the contribution of neuroimaging studies. World J Biol Psychiatry 2010;11:165–80. Rubinov M, Bassett DS. Emerging evidence of connectomic abnormalities in schizophrenia. J Neurosci 2011;31:6263–5. Shah PJ, Glabus MF, Goodwin GM, Ebmeier KP. Chronic, treatment-resistant depression and right fronto-striatal atrophy. Br J Psychiatry 2002;180:434–40. Sheline YI, Price JL, Yan Z, Mintun MA. Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proc Natl Acad Sci U S A 2010;107:11020–5. Song XW, Dong ZY, Long XY, Li SF, Zuo XN, Zhu CZ, et al. REST: a toolkit for resting-state functional magnetic resonance imaging data processing. PLoS ONE 2011;6:e25031. Walter H, Vasic N, Hose A, Spitzer M, Wolf RC. Working memory dysfunction in schizophrenia compared to healthy controls and patients with depression: evidence from event-related fMRI. Neuroimage 2007;35:1551–61. Wu QZ, Li DM, Kuang WH, Zhang TJ, Lui S, Huang XQ, et al. Abnormal regional spontaneous neural activity in treatment-refractory depression revealed by resting-state fMRI. Hum Brain Mapp 2011;32:1290–9. Yan C, Zang Y. DPARSF: a MATLAB toolbox for “pipeline” data analysis of resting-state fMRI. Front Syst Neurosci 2010;4:13. Zang YF, He Y, Zhu CZ, Cao QJ, Sui MQ, Liang M, et al. Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev 2007;29: 83–91. Zou K, Deng W, Li T, Zhang B, Jiang L, Huang C, et al. Changes of brain morphometry in first-episode, drug-naive, non-late-life adult patients with major depression: an optimized voxel-based morphometry study. Biol Psychiatry 2010;67:186–8.
D
Frodl T, Bokde AL, Scheuerecker J, Lisiecka D, Schoepf V, Hampel H, et al. Functional connectivity bias of the orbitofrontal cortex in drug-free patients with major depression. Biol Psychiatry 2010;67:161–7. Guo W, Liu F, Liu J, Yu L, Zhang Z, Zhang J, et al. Is there a cerebellar compensatory effort in first-episode, treatment-naive major depressive disorder at rest? Prog Neuropsychopharmacol Biol Psychiatry 2013a;46:13–8. Guo W, Liu F, Xue Z, Gao K, Liu Z, Xiao C, et al. Abnormal resting-state cerebellar–cerebral functional connectivity in treatment-resistant depression and treatment sensitive depression. Prog Neuropsychopharmacol Biol Psychiatry 2013b;44:51–7. Guo W, Liu F, Zhang J, Zhang Z, Yu L, Liu J, et al. Dissociation of regional activity in the default mode network in first-episode, drug-naive major depressive disorder at rest. J Affect Disord 2013c;151:1097–101. Guo WB, Liu F, Xue ZM, Xu XJ, Wu RR, Ma CQ, et al. Alterations of the amplitude of lowfrequency fluctuations in treatment-resistant and treatment-response depression: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 2012;37: 153–60. Guo WB, Sun XL, Liu L, Xu Q, Wu RR, Liu ZN, et al. Disrupted regional homogeneity in treatment-resistant depression: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 2011;35:1297–302. Hamilton JP, Siemer M, Gotlib IH. Amygdala volume in major depressive disorder: a metaanalysis of magnetic resonance imaging studies. Mol Psychiatry 2008;13:993–1000. Hamilton M. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol 1967;6:278–96. Han Y, Lui S, Kuang W, Lang Q, Zou L, Jia J. Anatomical and functional deficits in patients with amnestic mild cognitive impairment. PLoS ONE 2012;7:e28664. Janssen J, Hulshoff Pol HE, de Leeuw FE, Schnack HG, Lampe IK, Kok RM, et al. Hippocampal volume and subcortical white matter lesions in late life depression: comparison of early and late onset depression. J Neurol Neurosurg Psychiatry 2007;78:638–40. Koolschijn PC, van Haren NE, Lensvelt-Mulders GJ, Hulshoff Pol HE, Kahn RS. Brain volume abnormalities in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. Hum Brain Mapp 2009;30:3719–35. L W, D FH, I BH, J L. A systematic review of resting-state functional-MRI studies in major depression. J Affect Disord 2012;142:6–12. Liu F, Guo W, Liu L, Long Z, Ma C, Xue Z, et al. Abnormal amplitude low-frequency oscillations in medication-naive, first-episode patients with major depressive disorder: a resting-state fMRI study. J Affect Disord 2013;146:401–6. Liu F, Hu M, Wang S, Guo W, Zhao J, Li J, et al. Abnormal regional spontaneous neural activity in first-episode, treatment-naive patients with late-life depression: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 2012;39:326–31. Liu Z, Xu C, Xu Y, Wang Y, Zhao B, Lv Y, et al. 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 2010;182:211–5.
T
366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407
W. Guo et al. / Progress in Neuro-Psychopharmacology & Biological Psychiatry xxx (2014) xxx–xxx
E
6
U
N
C
O
R
R
E
C
450
Please cite this article as: Guo W, et al, Functional and anatomical brain deficits in drug-naive major depressive disorder, Prog NeuroPsychopharmacol Biol Psychiatry (2014), http://dx.doi.org/10.1016/j.pnpbp.2014.05.008
408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449
