J Neurol DOI 10.1007/s00415-015-7701-z
ORIGINAL COMMUNICATION
Brain structural abnormalities in patients with major depression with or without generalized anxiety disorder comorbidity Elisa Canu1 • Milutin Kostic´3 • Federica Agosta1 • Ana Munjiza3 • Pilar M. Ferraro1 Danilo Pesic3 • Massimiliano Copetti6 • Amir Peljto3 • Dusica Lecic Tosevski3,4,5 • Massimo Filippi1,2
•
Received: 27 January 2015 / Revised: 4 March 2015 / Accepted: 5 March 2015 Ó Springer-Verlag Berlin Heidelberg 2015
Abstract An overlap frequently occurs between major depression disorder (MDD) and generalized anxiety disorder (GAD). Aim of this study was to assess cortical and white matter (WM) alterations in MDD patients with or without GAD comorbidity. Seventy-one MDD patients and 71 controls were recruited. All subjects underwent T1weighted and diffusion tensor (DT)/MRI. MRI metrics of cortical thickness and WM integrity were obtained from atlas-based cortical regions and the interhemispheric and major long association WM tracts. Between-group MRI comparisons and multiple regressions with clinical scale scores were performed. Compared to controls, both MDD and MDD-GAD patients showed a cortical thinning of the middle frontal cortex bilaterally, left medial frontal gyrus and frontal pole. Compared to controls and MDD patients, MDD-GAD cases also showed a thinning of the right medial orbitofrontal and fusiform gyri, and left temporal pole and Electronic supplementary material The online version of this article (doi:10.1007/s00415-015-7701-z) contains supplementary material, which is available to authorized users. & Massimo Filippi [email protected] 1
Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina, 60, 20132 Milan, Italy
2
Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
3
Institute of Mental Health, Belgrade, Serbia
4
School of Medicine, University of Belgrade, Belgrade, Serbia
5
Serbian Academy of Sciences and Arts, Belgrade, Serbia
6
Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy
lateral occipital cortices. Compared to controls, MDD patients showed DT MRI abnormalities of the right parahippocampal tract and superior longitudinal fasciculus bilaterally, while no WM alterations were found in MDDGAD. In all patients, brain abnormalities were related with symptom severity. MDD and MDD-GAD share a common pattern of cortical alterations located in the frontal regions. However, while both the cortex and WM integrity are affected in MDD, only the former is affected in MDD-GAD. These findings support the notion of MDD-GAD as a distinct clinical entity, providing insights into patient vulnerability for specific networks as well as into patient resilience factors reflected by the integrity of other cerebral circuits. Keywords Depression Anxiety/anxiety disorders Biological markers Brain imaging/neuroimaging Mood disorders
Introduction Major depressive disorder is defined as depressed mood and a loss of interest or pleasure in daily activities, while generalized anxiety disorder (GAD) is characterized by persistent, unrealistic and excessive worries [1, 2]. A great deal of work has been performed on comorbidity of major depressive disorder (MDD) and GAD, as well as anxiety disorders in general. Estimates of comorbidity of depression and anxiety range from 10 to more than 50 % [3, 4]. Such a frequent comorbidity leads to suggest that MDD and anxiety disorders likely belong to the same syndrome spectrum [3– 5]. Nevertheless, some studies have shown worse clinical outcome and more severe psychopathology in patients suffering from both MDD and anxiety disorder, including GAD, than patients with only one of the two disorders [3, 5–7].
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Neuroimaging studies of MDD and GAD have shown both similar brain abnormalities as well as some different patterns of alterations. The most consistent findings are reduced hippocampal volumes in MDD [8–13], reduced cortical volume in the medial and superior temporal gyri in patients with GAD [14, 15], and the involvement of the anterior cingulate cortex (ACC) in both conditions [16], especially in its rostral–ventral affective subdivision [17]. In terms of white matter (WM) involvement, while MDD has been found to be associated with alterations to the uncinate and cingulate fascicule [18] and reduced fiber projection integrity to the prefrontal cortex and thalamus [19]; MDD with GAD is associated with a reduced volume of the anterior cingulate bundle and reduced integrity of the uncinate fasciculus [15, 20]. In summary, these studies support the so-called limbic-cortical model for both MDD and GAD disorders [21]. According to this model, the emotional-related activity in limbic structures, such as the hippocampus and amygdala, is not adequately modulated by the prefrontal areas (due to local damage or failure in the connections with other brain regions), resulting in a depressed mood or anxiety. Within this circuitry, ACC is thought to play a key mediatory role. The additional involvement of temporal areas in GAD presumably reflects an impaired evaluation of interoceptive information and an altered threat processing as shown by functional neuroimaging studies [22]. The majority of these studies, however, did not address the issue of comorbidity [15]. Aims of this study were: (1) to investigate common and distinct patterns of cortical and WM alterations in patients with MDD with or without GAD, and (2) to integrate the relationship between patterns of brain structural alterations and clinical features of these patients. We measured cortical thickness of several atlas-based regions and WM alterations using diffusion tensor (DT) MRI to track the interhemispheric and major long association tracts. We hypothesized that the two groups of patients would share a common pattern of structural alterations in the anterior cingulate region. Furthermore, we expected that MDD patients with GAD would have an additional alteration of the limbic structures in relation to their persistent alertness state and to the temporal lobe reflecting a more severe disconnection between the limbic structures and the frontal cortex. Finally, we hypothesized that the observed patterns of abnormalities were related to patient specific symptoms.
Materials and methods Subjects Seventy-one native Serbian-speaking inpatients with MDD were consecutively recruited at the Institute of Mental
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Health in Belgrade, Serbia. Patients received a comprehensive evaluation including psychiatric history and examination, and MRI. Twenty-one patients (30 %) presented a comorbidity with GAD. All patients were treated with antidepressants: only one patient from the MDD-GAD group was on antidepressant mono therapy (Paroxetine). All other patients were at least on benzodiazepines (mostly Clonazepam) in association with an antidepressant (Selective Serotonin Reuptake Inhibitors being the most prevalent class, followed by Serotonin Norepinephrine Reuptake Inhibitors, Tetracyclic and Tricyclic antidepressants). Since our sample consisted of only inpatients, many of the subjects had treatment resistant depression and a chronic disease course. In these cases, adjunct treatment, like antipsychotics (first or second generation) or stabilizers, was often prescribed (Table 1). Seventy-one native Serbian-speaking, age-matched healthy controls were recruited by word of mouth. Subjects were excluded if they had been previously diagnosed with any psychiatric comorbidity disorder; and if they had any kind of central nervous system disease or other causes of focal or diffuse brain damage, including lacunae, and extensive cerebrovascular disorders at routine MRI. Approval was obtained from the local ethical standards committee on human experimentation and written informed consent from all subjects before enrolment. The study has been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Clinical assessment Sociodemographic characteristics, familial history, and treatment history were obtained during an interview with an experienced psychiatrist unaware of the MRI results (Table 1). The structured clinical interview for DSM IV (SCID I) was used for diagnosis of MDD and GAD. In addition, depression severity was assessed using the Hamilton Depression Rating Scale (HAMD) and the selfreport Beck Depression self-report Inventory (BDI), and anxiety severity using the Hamilton Anxiety Rating Scale (HAMA). HAMD, BDI, and HAMA scales were not used for defining patient diagnosis. MRI acquisition Brain MRI scans were obtained using a 1.5 T scanner (Achieva, Philips Medical Systems, Best, the Netherlands). The following sequences were acquired from all subjects: dual-echo turbo spin echo (TSE); 3D T1-weighted turbo field echo (TFE); and pulsed-gradient SE echo planar with sensitivity encoding and diffusion gradients applied in 65 noncollinear directions. Details on MRI sequences are provided in the Supplement (eMethods).
J Neurol Table 1 Sociodemographic and clinical features of patients and healthy controls HC 71
MDD 50
MDD-GAD 21
p
Age
45.3 ± 11.0 (23–63)
45.6 ± 10.2 (22–63)
43.7 ± 10.8 (24–61)
Gender (women)
57 (80 %)
42 (84 %)
15 (68 %)
Education
4.4 ± 1.2 (2–6)a
3.12 ± 1.0 (1–5)
3.1 ± 0.9 (2–5)
BDI total score
2.4 ± 3.5 (0–21)a
32.4 ± 12.6 (7–59)
28.9 ± 11.9 (5–55)
0.100
HAMD total score
–
22.9 ± 4.7 (11–36)
24.1 ± 4.8 (15–33)
0.164
HAMA total score
–
22.1 ± 6.6 (6–37)
28.1 ± 7.7 (12–39)
0.001
Symptom duration (months) Treatment
–
86.8 ± 92.2 (6–348)
107.7 ± 73.6 (18–240)
0.317 0.756
0.860 0.249 \0.001
Treatment duration (months)
–
65.6 ± 81.5 (1–288)
71.7 ± 73.0 (2–228)
SNRIs
–
4 (8 %)
2 (10 %)
1.000
SSRIs
–
25 (50 %)
9 (43 %)
0.613
TCAs
–
9 (18 %)
3 (14 %)
1.000
TeCAs
–
21 (42 %)
9 (43 %)
1.000
Benzodiazepines
–
45 (90 %)
21 (100 %)
0.312
Mood stabilizers
–
22 (44 %)
8 (38 %)
0.794
Antipsychotics, 1st generation
–
12 (24 %)
8 (38 %)
0.257
Antipsychotics, 2nd generation
–
11 (22 %)
4 (19 %)
1.000
Values are means ± standard deviations (minimum–maximum) or frequency (percentage). Education scale: 1 = no school; 2 = primary school; 3 = high school; 4 = college; 5 = university degree; 6 = master degree or doctoral degree. p values refer to ANOVA model BDI beck depression inventory, GAD generalized anxiety disorder, HAMA Hamilton Anxiety Rating scale; HC healthy controls, HAMD Hamilton Depression Rating scale; MDD major depressive disorder, SNRIs serotonin norepinephrine reuptake inhibitors, SSRIs selective serotonin reuptake inhibitors, TCAs tricyclic antidepressants, TeCAs tetracyclic antidepressants a
Significant difference between HC and the patient groups at the pairwise comparisons
MRI analysis A detailed description of MRI analysis is provided in the Supplement (eMethods). Briefly, cortical reconstruction and estimation of cortical thickness were performed on the 3D T1-weighted FFE images using the FreeSurfer image analysis suite, version 5.0 (http://surfer.nmr.mgh.harvard. edu/). DT MRI analysis was performed using the FMRIB software library (FSL) tools (http://www.fmrib.ox.ac.uk/ fsl/fdt/index.html) and the JIM5 software (Version 5.0). The DT was estimated on a voxel-by-voxel basis using DTIfit provided by the FMRIB Diffusion Toolbox. Maps of mean (MD), axial (axD) and radial (radD) diffusivities, and fractional anisotropy (FA) were obtained. The DT is represented by three eigenvectors and corresponding eigenvalues that define an ellipsoid [23]. MD is the average of the three eigenvalues and provides a measure of the degree of restriction to the diffusion of water molecules irrespective of direction. FA measures degree of anisotropy of diffusion. FA values range from zero to one. A value of zero means that diffusion is isotropic, i.e., it is unrestricted (or equally restricted) in all directions. A value of one means that diffusion occurs only along one axis and is fully restricted along all other directions. In anisotropic tissue,
such as WM, the largest eigenvalue represents the diffusivity of water in the direction parallel to the fiber bundles (axD). RadD, the average of the two smallest eigenvalues, measures water diffusion perpendicular to the axonal wall. Seeds for tractography of the anterior cingulate bundle (ACB), parahippocampal tract, corpus callosum (CC-whole tract, as well as genu, body and splenium), superior longitudinal (SLF), inferior longitudinal (ILF) and uncinate fasciculi were defined in the Montreal Neurological Institute (MNI) space on the FA template provided by FSL, as previously described [24]. Fiber tracking was performed using FSL (probtrackx) [25]. For each tract, the average MD, FA, axD, and radD were calculated in the native space. Statistical analysis Demographic, clinical and MRI data were compared between each patient group (MDD and MDD-GAD) and the total group of healthy controls, and between patient groups. Demographic and clinical data Normal distribution assumption was checked by means of Q–Q plot and Shapiro–Wilks and Kolmogorov–Smirnov
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tests. Demographic and clinical group comparisons were performed using ANOVA models, followed by post hoc pairwise comparisons, using SAS Release 9.3.
Results
MRI data
Groups were similar for age and gender. Healthy controls had higher education compared to both groups of patients. Patient groups presented with similar depression severity, treatment type and duration, while they differed in anxiety severity with MDD-GAD patients showing higher HAMA scores (Table 1).
A vertex-by-vertex analysis was used to assess differences of cortical thickness between controls and patients, as well between patient subgroups, in FreeSurfer. Analysis was adjusted for multiple comparisons and threshold at p \ 0.05 using Monte Carlo Z-null simulation. Mean cortical thickness and DT MRI measure comparisons were performed using ANCOVA models followed by post hoc pairwise comparisons. p values were corrected for multiple comparisons using false-discovery rate (FDR) approach. Age and education were added in all models as confounding variables. Correlations In patients, age-adjusted Spearman’s rho correlations between cortical thickness and DT MRI measures, and between all MRI measures and HAMA and HAMD total and sub-scores were computed. p values were FDR corrected.
Demographic and clinical data
Cortical thickness Vertex-wise analysis (see eTable 1, eFigures 1, 2 in the Supplement) Only one peak of cortical thinning in the right rostral middle frontal cortex was detected in MDD patients compared with controls. Peaks of cortical thinning were detected in MDD-GAD patients compared with MDD patients and healthy controls mainly in the frontotemporal cortex. No cortical thinning was observed in MDD compared with MDD-GAD patients.
Table 2 Regional mean cortical thickness measurements in patients and healthy controls HC
MDD
MDD-GAD
p MDD vs HC
p MDD-GAD vs HC
p MDD-GAD vs MDD
Frontal lobe L frontal pole
2.57 ± 0.37
2.36 ± 0.63
2.10 ± 0.85
0.042
0.031
0.091
L medial orbitofrontal R medial orbitofrontal
2.29 ± 0.13 2.28 ± 0.11
2.22 ± 0.13 2.23 ± 0.14
2.19 ± 0.13 2.09 ± 0.48
0.046 0.733
0.021 0.027
0.279 0.027
L rostral middle frontal
2.28 ± 0.09
2.21 ± 0.11
2.23 ± 0.12
0.003
0.024
0.829
R rostral middle frontal
2.28 ± 0.09
2.21 ± 0.12
2.21 ± 0.12
0.021
0.031
0.847
R lateral orbitofrontal
2.43 ± 0.10
2.35 ± 0.14
2.37 ± 0.13
0.031
0.093
0.856
L pars opercularis
2.46 ± 0.11
2.39 ± 0.11
2.28 ± 0.52
0.092
0.006
0.086
R pars orbitalis
2.54 ± 0.16
2.39 ± 0.38
2.27 ± 0.54
0.149
0.036
0.191 0.528
Temporal lobe R hippocampus
3.94 ± 0.36
3.60 ± 0.41
3.65 ± 0.42
0.005
0.079
L temporal pole
3.53 ± 0.26
3.56 ± 0.27
3.29 ± 0.77
0.411
0.088
R fusiform
2.48 ± 0.11
2.43 ± 0.13
2.26 ± 0.52
0.104
\0.001
L inferior parietal
2.38 ± 0.10
2.32 ± 0.13
2.33 ± 0.13
0.038
0.073
L supramarginal
2.46 ± 0.09
2.39 ± 0.14
2.41 ± 0.14
0.028
0.062
0.975
R retrosplenial cortex
2.14 ± 0.14
1.87 ± 0.66
2.07 ± 0.12
0.013
0.459
0.149
2.03 ± 0.44
2.05 ± 0.14
1.75 ± 0.72
0.793
0.025
0.018
0.023 0.01
Parietal lobe 0.991
Occipital lobe L lateral occipital
Values are means ± standard deviations (mm). p values refer to ANCOVA model adjusted for age and education, false-discovery rate corrected for multiple comparisons GAD generalized anxiety disorder, HC healthy controls, MDD major depressive disorder
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J Neurol Fig. 1 Regional cortical thinning and white matter tract damage of MDD and MDDGAD patients compared to healthy controls and compared to each other
Regional cortical thickness measures (Table 2; Fig. 1) Compared with healthy controls, both groups of patients showed a main involvement of the bilateral middle frontal cortex. Furthermore, compared with controls, only MDD patient group showed a reduced thickness of the right hippocampus, left inferior parietal, supramarginal and retrosplenial cortex, while only the MDD-GAD group showed a reduced cortical thickness of the inferior frontal gyrus, bilaterally. Compared with MDD, MDDGAD patients showed cortical thinning of the right medial orbitofrontal cortex, right fusiform cortex, left temporal pole and left lateral occipital cortex. No cortical thinning was observed in MDD compared with MDDGAD patients. DT MRI Tractography Compared with healthy controls, MDD patients had increased MD and axD of the right and left SLF, respectively, and increased radD of the right parahippocampal tract (Tables 3, 4; Fig. 1). No difference was detected
between MDD-GAD and healthy controls, or between patient groups. Correlations between cortical thickness and DT MRI measures In all patients, the cortical thickness of the left inferior parietal cortex was related with WM integrity of the SLF bilaterally (right SLF FA, r = 0.42, pFDR = 0.01; right SLF MD, r = -0.38, pFDR = 0.03; right SLF radD, r = -0.45, pFDR = 0.004; left SLF MD, r = -0.34, p = 0.04; left SLF radD, r = -0.39, pFDR = 0.01). Furthermore, cortical thickness of the left hippocampus was related with the FA of the left parahippocampal tract (r = 0.35, pFDR = 0.02). Correlations between MRI measures and clinical features In all patients, the subscore of HAMA assessing the respiratory symptoms was negatively related with the cortical thickness of the right medial orbitofrontal cortex (r = -0.38, pFDR = 0.03). The subscore of HAMD assessing the loss of weight was positively related with the FA of the left uncinate fasciculus (r = 0.41; pFDR = 0.02).
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0.49 ± 0.04
0.47 ± 0.03
L
R
0.45 ± 0.04
0.45 ± 0.05
L
R 0.48 ± 0.05
0.48 ± 0.03
0.44 ± 0.03
0.44 ± 0.04
0.45 ± 0.04
0.46 ± 0.04
0.39 ± 0.04 0.38 ± 0.04
0.36 ± 0.06
0.40 ± 0.05
0.53 ± 0.03
0.47 ± 0.04
0.49 ± 0.03
0.46 ± 0.02
0.47 ± 0.02
0.46 ± 0.03
0.47 ± 0.03
0.41 ± 0.04 0.40 ± 0.04
0.38 ± 0.05
0.40 ± 0.04
0.60 ± 0.03
0.154
0.601
0.366
0.532
0.296
0.210
0.492
0.283 0.091
0.283
0.223
0.605
0.380
0.059
0.506
0.641
0.952
0.532
0.244
0.383
0.749
0.806 0.960
0.980
0.309
0.950
0.538
0.161
0.532
0.814
0.366
0.501
0.061
0.748
0.492
0.381 0.094
0.283
0.878
0.605
0.538
0.791
0.81 ± 0.03
0.82 ± 0.03
0.83 ± 0.03
0.83 ± 0.04
0.78 ± 0.03
0.76 ± 0.02
0.83 ± 0.05 0.82 ± 0.05
0.78 ± 0.08
0.80 ± 0.05
0.92 ± 0.05
0.87 ± 0.06
0.89 ± 0.05
0.92 ± 0.06
0.82 ± 0.04
0.83 ± 0.04
0.84 ± 0.03
0.84 ± 0.03
0.80 ± 0.04
0.78 ± 0.05
0.84 ± 0.05 0.85 ± 0.05
0.74 ± 0.10
0.77 ± 0.09
0.93 ± 0.06
0.87 ± 0.04
0.93 ± 0.07
0.81 ± 0.04
0.82 ± 0.04
0.83 ± 0.03
0.82 ± 0.02
0.78 ± 0.03
0.76 ± 0.03
0.83 ± 0.04 0.84 ± 0.05
0.74 ± 0.06
0.75 ± 0.07
0.92 ± 0.07
0.85 ± 0.04
0.91 ± 0.06
0.91 ± 0.06
MDD-GAD
0.356
0.518
0.306
0.176
0.048
0.568
0.615 0.157
0.205
0.144
0.736
0.786
0.073
0.303
p MDD vs HC
0.918
0.852
0.619
0.548
0.578
0.927
0.772 0.556
0.205
0.127
0.736
0.187
0.384
0.944
p MDDGAD vs HC
0.356
0.519
0.596
0.161
0.226
0.596
0.615 0.470
0.954
0.442
0.736
0.187
0.384
0.303
p MDD vs MDD-GAD
ACB anterior cingulum bundle, CC corpus callosum, FA fractional anisotropy, GAD generalized anxiety disorder, HC healthy controls, ILF inferior longitudinal fasciculus, L left, R right, MD mean diffusivity, MDD major depressive disorder, PH parahippocampal tract, SLF superior longitudinal fasciculus, UNC uncinate fasciculus
Values are means ± standard deviations. p values refer to ANCOVA model adjusted for age and education, false-discovery rate corrected for multiple comparisons
ILF
UNC
0.47 ± 0.03
0.47 ± 0.03
L
R
SLF
0.41 ± 0.04 0.41 ± 0.04
0.38 ± 0.04
L R
R
PH
0.42 ± 0.04
L
ACB
0.60 ± 0.03
0.52 ± 0.03
0.53 ± 0.03
0.60 ± 0.02
CC genu
CC splenium
0.56 ± 0.03 0.53 ± 0.03
0.90 ± 0.04
0.55 ± 0.03 0.53 ± 0.03
0.56 ± 0.02
MDD
0.54 ± 0.02
p MDD vs MDD-GAD
CC
p MDDGAD vs HC
CC body
p MDD vs HC
HC
MDD-GAD
MDD
HC
Side
MD [910-3 mm2 s-1]
Region
FA
Table 3 Mean diffusivity and fractional anisotropy values of white matter tracts in patients and healthy controls
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0.58 ± 0.04
0.58 ± 0.04
L
R
0.61 ± 0.05
0.60 ± 0.05
L
R 0.60 ± 0.04
0.60 ± 0.04
0.62 ± 0.04
0.62 ± 0.04
0.59 ± 0.05
0.58 ± 0.06
0.66 ± 0.06 0.67 ± 0.06
0.57 ± 0.08
0.57 ± 0.07
0.57 ± 0.05
0.59 ± 0.05
0.58 ± 0.05
0.60 ± 0.04
0.59 ± 0.03
0.58 ± 0.04
0.56 ± 0.04
0.64 ± 0.05 0.65 ± 0.06
0.56 ± 0.06
0.56 ± 0.06
0.57 ± 0.06
0.800
0.213
0.258
0.348
0.246
0.053
0.116
0.472 0.033
0.125
0.280
0.717
0.792
0.550
0.803
0.810
0.276
0.372
0.870
0.855 0.579
0.125
0.214
0.717
0.486
0.369
0.416
0.550
0.361
0.348
0.067
0.372
0.116
0.483 0.178
0.704
0.416
0.717
0.486
0.456
1.54 ± 0.06
1.26 ± 0.08
1.30 ± 0.07
1.27 ± 0.04
1.28 ± 0.04
1.20 ± 0.05
1.17 ± 0.03
1.22 ± 0.06 1.20 ± 0.08
1.15 ± 0.11
1.20 ± 0.08
1.62 ± 0.08
1.45 ± 0.08
1.49 ± 0.06
1.56 ± 0.05
1.27 ± 0.06
1.31 ± 0.05
1.28 ± 0.05
1.28 ± 0.04
1.21 ± 0.04
1.19 ± 0.05
1.22 ± 0.05 1.21 ± 0.06
1.09 ± 0.15
1.16 ± 0.14
1.63 ± 0.07
1.44 ± 0.04
1.52 ± 0.06
1.25 ± 0.06
1.31 ± 0.05
1.29 ± 0.05
1.29 ± 0.03
1.19 ± 0.04
1.18 ± 0.02
1.21 ± 0.04 1.22 ± 0.05
1.10 ± 0.09
1.15 ± 0.08
1.62 ± 0.09
1.42 ± 0.04
1.50 ± 0.06
1.54 ± 0.06
MDD-GAD
0.919
0.986
0.264
0.608
0.192
0.042
0.586 0.875
0.239
0.110
0.944
0.280
0.227
0.493
pMDD vs HC
0.574
0.986
0.264
0.608
0.734
0.884
0.586 0.875
0.415
0.110
0.737
0.063
0.846
0.493
pMDDGAD vs HC
0.574
0.986
0.588
0.608
0.192
0.085
0.586 0.875
0.752
0.554
0.737
0.180
0.300
0.471
pMDD vs MDD-GAD
axD axial diffusivity, ACB anterior cingulum bundle, CC corpus callosum GAD generalized anxiety disorder, HC healthy controls, ILF inferior longitudinal fasciculus, L left, R right, MDD major depressive disorder, PH parahippocampal tract, radD radial diffusivity, SLF superior longitudinal fasciculus, UNC uncinate fasciculus
Values are means ± standard deviations. p values refer to ANCOVA model adjusted for age and education, false-discovery rate adjusted for multiple comparisons
ILF
UNC
0.55 ± 0.03
0.56 ± 0.03
L
R
SLF
0.60 ± 0.07
0.64 ± 0.05 0.63 ± 0.05
R
L R
PH
0.60 ± 0.05
L
ACB
0.58 ± 0.06
0.059
0.309
0.59 ± 0.05
0.59 ± 0.06
0.57 ± 0.05
CC genu
CC splenium
0.62 ± 0.06
0.59 ± 0.06
0.61 ± 0.06 0.63 ± 0.07
0.59 ± 0.04
MDD
0.60 ± 0.05
pMDD vs MDD-GAD
CC
pMDDGAD vs HC
CC body
pMDD vs HC
HC
MDD-GAD
MDD
HC
Side
axD [910-3 mm2 s-1]
Region
radD [910-3 mm2 s-1]
Table 4 Radial and axial diffusivity values of white matter tracts in patients and healthy controls
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Discussion This is the first study assessing both cortical and WM integrity in a relatively large cohort of MDD patients with or without comorbidity with GAD. We observed that MDD and MDD-GAD share common features of cortical alterations in the ventral and medial regions of the prefrontal cortex. MDD patients also experienced an involvement of the lateral prefrontal and parietal cortices; whereas those with MDD-GAD showed a more pronounced cortical damage in the ACC, insula, temporal and occipital regions. In addition, only MDD patients showed WM microstructural alterations, which were located in the SLF and parahippocampal tract. Such alterations were related to cortical thinning of the inferior parietal lobe and hippocampus, respectively. Finally, we found that brain structural alterations in all patients were related with the severity of anxiety symptoms. Cortical alterations in MDD and MDD-GAD patients Compared to controls, both MDD and MDD-GAD patients showed a reduced cortical thinning of the bilateral rostral middle frontal cortex, medial frontal gyrus, and frontal pole. Our results are in keeping with previous findings showing a prefrontal cortex involvement in MDD and GAD patients. The ventromedial prefrontal cortex subtends emotional processing, behavior initiative and motivation, and is well known to play a critical role in mood disorders [16]. On the other hand, the dorsolateral prefrontal cortex is mainly associated with the cognitive aspects of behavior and is part of the fronto-parietal brain circuits [26]. In the present study, compared with controls, MDD patients showed a cortical thinning of the lateral prefrontal cortex, the inferior parietal and supramarginal cortices. In MDD, the involvement of the parietal lobe together with the lateral prefrontal cortex has been previously demonstrated [27] and seems to be associated with a poor sustained attention and executive dysfunction, which are typical manifestations of these patients [26]. In MDD, we also observed a reduced hippocampal volume compared to controls. The involvement of the hippocampus in MDD has been previously described [28]. The hippocampus plays a crucial role in mood regulation due to its connections with several regions subtending the emotional processing, such as the prefrontal cortex, amygdala, anterior thalamic nuclei and hypothalamus. Several studies support the theory that hippocampal abnormalities are associated to stress-related environmental conditions in individuals with a specific genetic background [29]. In this context, several associations have been found in MDD between specific polymorphisms of the
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serotonin transporter gene (5-HTTLPR) and/or of the brain-derived neutrophic factor (BDNF) and reduced hippocampal volume [30, 31]. Compared to both MDD patients and healthy controls, MDD-GAD patients showed an additional thinning of the right medial orbitofrontal gyrus and insula, rostral ACC, fusiform gyrus, left temporal pole and occipital cortices, bilateral precentral gyrus, parietal lobe and precuneus. Such additional areas of atrophy in MDD-GAD patients involve the key nodes of the anatomical circuit of anxiety [32]. Briefly, registration and reactivity to a negative emotional stimulus are carried out in the amygdala and insula. These regions can direct the signal to the hippocampus (to record emotional-context memories) and sensory cortex (such as motor and visual cortices). Further monitoring and evaluation of the negative stimuli is carried out by the ACC and dorsal/medial prefrontal cortex. Engagement of these structures leads to a detailed appraisal and conscious awareness of the emotional stimulus, which are not functions of insula, amygdala and hippocampus. ACC and dorsal/medial prefrontal cortex in turn provide feedback for a context-appropriate regulation, which may result in inhibition or enhancement of limbic processing [32]. One could speculate that in MDDGAD the emotional processing cannot be properly registered by the atrophic insula neither modulated by the topdown cortical control (due to atrophy of the ACC and prefrontal cortex) leading to an excessive processing by sensory cortices and a failure of fear inhibition that occurs during periods of anxiety. More severe is atrophy on each part of this circuit and more severe is such a dysregulation [16]. White matter alterations in MDD Compared to controls, only MDD patients showed WM abnormalities in the bilateral SLF and the right parahippocampal tract, while no WM alterations were found in MDD-GAD patients. The SLF is a long associative WM tract which links the dorsolateral prefrontal cortex to the inferior parietal and lateral temporal cortices [33]. We also observed a relationship between the reduced thinning of the inferior parietal cortex and the SLF damage, suggesting that the disconnection of the fronto-parietal circuit has a relevant role in MDD. In line with this hypothesis, several DT MRI studies reported reduced WM integrity of the frontal region [34, 35], WM underneath the angular gyrus [35], and inferior parietal portion of the SLF [36] in MDD. In MDD patients, we also observed a reduced integrity of the parahippocampal WM tract and a relationship between the cortical and WM alterations of hippocampus and parahippocampal regions. As it is the case for hippocampal atrophy, also the parahippocampal WM involvement has
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been observed in association with 5-HTTLPR/BDNF specific polymorphisms in MDD patients [29, 37]. The nature of the WM damage in MDD is still debated. The majority of postmortem studies in MDD considered the prefrontal regions only and revealed a decreased neuron size and density [38], as well as reduced glial [38] and oligodendrocyte density [39], and myelin damage in the adjacent WM [40]. A number of postmortem studies reported ischemic lesions in these patients and supported the theory of depression as a vascular disease [41, 42]. Deep WM hyperintensities have been found more frequently in MDD patients than controls [43] and have been associated with a more severe illness, more pronounced cognitive deficits and a poorer response to antidepressants [44]. In our study, we carefully excluded patients with WM hyperintensities visible on T2-weighted images. Thus, although we cannot rule out a microvascular nature of the WM damage in our sample, the damage we observed in MDD most likely reflects a loss of axons or myelin due to a damage secondary to cortical atrophy [45], as also suggested by the correlation analysis. So far, only a few studies investigated WM damage in GAD patients and none of them considered comorbidity with depression. In addition to the involvement of the ACB [15], the uncinate fasciculus, which links the temporal to the frontal structures involved in the emotional processing, has been found to be damaged in GAD patients [20]. In this study, we did not observe WM damage in MDD-GAD patients in the uncinate fasciculus or in the other investigated tracts, and this could be the main difference which distinguishes these patients from those with pure MDD and pure GAD.
lacking in higher level motivational value, such as the need to eat [48]. The respiratory symptoms assessed with HAMA were related to the involvement of the right medial orbitofrontal cortex. This suggests that the more severe the atrophy of these structures is, the greater is the failure of the previously described emotional circuit to modulate the sensory processing and the anxiety manifestations through the autonomic system. Strengths and limitations A number of factors increase the reliability of our findings. The patient population is large and clinically well defined. Cortical and WM alterations have been investigated with advanced MRI techniques, such as tractography and cortical thickness which are able to detect subtle changes, and a sound statistical methodology with correction for multiple comparisons and for confounding variables. However, there are also some caveats to be considered when interpreting our findings. First, the different sample size of the two patient groups might, at least partially, affect our MRI results. Second, the lack of controlling for treatment type, dosage and duration. Third, a third group of GAD patients without MDD comorbidity would have provided a more exhaustive picture of the common/different patterns of abnormalities. Finally, the amygdala, which is one of the regions most involved in emotional circuits, has not been found involved in our patients. Although it seems that amygdala has more a functional value than a structural one in patients with GAD [49], we cannot exclude this could be a false negative finding since this structure, due to its anatomical shape and position, represents a challenge to segmentation techniques [50].
The relationship between brain structural alterations and clinical features
Conclusions In MDD patients, regardless of the comorbidity with GAD, we found a relationship between the severity of anxiety symptoms and the involvement of ventral frontal regions. Indeed, loss of weight assessed with HAMD and respiratory symptoms assessed with HAMA were related with the extent of WM microstructural damage to the uncinate fasciculus and with thinning of the right medial orbitofrontal cortex, respectively. The uncinate fasciculus is a bidirectional, long-range WM tract that connects lateral orbitofrontal cortex, which provides valence-based decisions, with the anterior temporal lobes, which integrate social personally relevant information [46]. Recent studies suggested that a reduced FA of the uncinate fasciculus is related with the severity of depression [47]. Behavioral changes associated with uncinate fasciculus include social-emotional problems due to people and objects being stripped of personal value and
MDD and MDD-GAD share a common pattern of cortical alterations in the medial prefrontal cortex. In addition, while MDD showed a specific involvement of the cortex and WM of the fronto-parietal circuit, MDD-GAD harbors a more severe pattern of cortical atrophy, but not WM damage, involving the anatomical circuitry related to anxiety. The fact that MDD and MDD-GAD comorbidity are characterized by both common and distinct patterns of damage offers new insights into their pathophysiology: this may explain why comorbidity of these two disorders is so prevalent in the population and why they frequently respond to similar treatments. This also validates the clinical relevance of the comorbidity information and the view of MDD-GAD as a separate entity with distinct clinical and cerebral features. Such an understanding could provide insights into patient vulnerability linked to damage of
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selective brain networks as well as into patient resilience factors reflected by the integrity of other cerebral circuits. Acknowledgments
8.
No outside funding was used for this study.
Conflicts of interest Elisa Canu, Milutin Kostic´, Ana Munjiza, Pilar M Ferraro, Danilo Pesic, Massimiliano Copetti, and Amir Peljto report no disclosures. Federica Agosta serves on the editorial board of the Journal of Neurology; has received speaker honoraria from Biogen Idec, and EXCEMED—Excellence in Medical Education; and receives research supports from the Italian Ministry of Health, and AriSLA (Fondazione Italiana di Ricerca per la SLA). Dusica Lecic Tosevski is Editor-in-Chief of the Journal Psychiatry Today; has received compensation for speaking activites from Janssen-Cylag, Pfizer, Hemopharm, Astra Zeneka; and receives research support from Serbian Ministry of Education and Science and Serbian Academy of Sciences and Arts. Massimo Filippi is Editor-in-Chief of the Journal of Neurology; serves on scientific advisory boards for Teva Pharmaceutical Industries; has received compensation for consulting services and/or speaking activities from Bayer Schering Pharma, Biogen Idec, Merck Serono, Novartis, and Teva Pharmaceutical Industries; and receives research support from Bayer Schering Pharma, Biogen Idec, Merck Serono, Teva Pharmaceutical Industries, Novartis, Italian Ministry of Health, Fondazione Italiana Sclerosi Multipla, Cure PSP, Alzheimer’s Drug Discovery Foundation (ADDF), the Jacques and Gloria Gossweiler Foundation (Switzerland), and ARiSLA (Fondazione Italiana di Ricerca per la SLA). Ethical standard Approval was obtained from the local ethical standards committee on human experimentation and written informed consent from all subjects before enrolment. The study has been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.
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ORIGINAL COMMUNICATION
Brain structural abnormalities in patients with major depression with or without generalized anxiety disorder comorbidity Elisa Canu1 • Milutin Kostic´3 • Federica Agosta1 • Ana Munjiza3 • Pilar M. Ferraro1 Danilo Pesic3 • Massimiliano Copetti6 • Amir Peljto3 • Dusica Lecic Tosevski3,4,5 • Massimo Filippi1,2
•
Received: 27 January 2015 / Revised: 4 March 2015 / Accepted: 5 March 2015 Ó Springer-Verlag Berlin Heidelberg 2015
Abstract An overlap frequently occurs between major depression disorder (MDD) and generalized anxiety disorder (GAD). Aim of this study was to assess cortical and white matter (WM) alterations in MDD patients with or without GAD comorbidity. Seventy-one MDD patients and 71 controls were recruited. All subjects underwent T1weighted and diffusion tensor (DT)/MRI. MRI metrics of cortical thickness and WM integrity were obtained from atlas-based cortical regions and the interhemispheric and major long association WM tracts. Between-group MRI comparisons and multiple regressions with clinical scale scores were performed. Compared to controls, both MDD and MDD-GAD patients showed a cortical thinning of the middle frontal cortex bilaterally, left medial frontal gyrus and frontal pole. Compared to controls and MDD patients, MDD-GAD cases also showed a thinning of the right medial orbitofrontal and fusiform gyri, and left temporal pole and Electronic supplementary material The online version of this article (doi:10.1007/s00415-015-7701-z) contains supplementary material, which is available to authorized users. & Massimo Filippi [email protected] 1
Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Via Olgettina, 60, 20132 Milan, Italy
2
Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
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Institute of Mental Health, Belgrade, Serbia
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School of Medicine, University of Belgrade, Belgrade, Serbia
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Serbian Academy of Sciences and Arts, Belgrade, Serbia
6
Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy
lateral occipital cortices. Compared to controls, MDD patients showed DT MRI abnormalities of the right parahippocampal tract and superior longitudinal fasciculus bilaterally, while no WM alterations were found in MDDGAD. In all patients, brain abnormalities were related with symptom severity. MDD and MDD-GAD share a common pattern of cortical alterations located in the frontal regions. However, while both the cortex and WM integrity are affected in MDD, only the former is affected in MDD-GAD. These findings support the notion of MDD-GAD as a distinct clinical entity, providing insights into patient vulnerability for specific networks as well as into patient resilience factors reflected by the integrity of other cerebral circuits. Keywords Depression Anxiety/anxiety disorders Biological markers Brain imaging/neuroimaging Mood disorders
Introduction Major depressive disorder is defined as depressed mood and a loss of interest or pleasure in daily activities, while generalized anxiety disorder (GAD) is characterized by persistent, unrealistic and excessive worries [1, 2]. A great deal of work has been performed on comorbidity of major depressive disorder (MDD) and GAD, as well as anxiety disorders in general. Estimates of comorbidity of depression and anxiety range from 10 to more than 50 % [3, 4]. Such a frequent comorbidity leads to suggest that MDD and anxiety disorders likely belong to the same syndrome spectrum [3– 5]. Nevertheless, some studies have shown worse clinical outcome and more severe psychopathology in patients suffering from both MDD and anxiety disorder, including GAD, than patients with only one of the two disorders [3, 5–7].
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Neuroimaging studies of MDD and GAD have shown both similar brain abnormalities as well as some different patterns of alterations. The most consistent findings are reduced hippocampal volumes in MDD [8–13], reduced cortical volume in the medial and superior temporal gyri in patients with GAD [14, 15], and the involvement of the anterior cingulate cortex (ACC) in both conditions [16], especially in its rostral–ventral affective subdivision [17]. In terms of white matter (WM) involvement, while MDD has been found to be associated with alterations to the uncinate and cingulate fascicule [18] and reduced fiber projection integrity to the prefrontal cortex and thalamus [19]; MDD with GAD is associated with a reduced volume of the anterior cingulate bundle and reduced integrity of the uncinate fasciculus [15, 20]. In summary, these studies support the so-called limbic-cortical model for both MDD and GAD disorders [21]. According to this model, the emotional-related activity in limbic structures, such as the hippocampus and amygdala, is not adequately modulated by the prefrontal areas (due to local damage or failure in the connections with other brain regions), resulting in a depressed mood or anxiety. Within this circuitry, ACC is thought to play a key mediatory role. The additional involvement of temporal areas in GAD presumably reflects an impaired evaluation of interoceptive information and an altered threat processing as shown by functional neuroimaging studies [22]. The majority of these studies, however, did not address the issue of comorbidity [15]. Aims of this study were: (1) to investigate common and distinct patterns of cortical and WM alterations in patients with MDD with or without GAD, and (2) to integrate the relationship between patterns of brain structural alterations and clinical features of these patients. We measured cortical thickness of several atlas-based regions and WM alterations using diffusion tensor (DT) MRI to track the interhemispheric and major long association tracts. We hypothesized that the two groups of patients would share a common pattern of structural alterations in the anterior cingulate region. Furthermore, we expected that MDD patients with GAD would have an additional alteration of the limbic structures in relation to their persistent alertness state and to the temporal lobe reflecting a more severe disconnection between the limbic structures and the frontal cortex. Finally, we hypothesized that the observed patterns of abnormalities were related to patient specific symptoms.
Materials and methods Subjects Seventy-one native Serbian-speaking inpatients with MDD were consecutively recruited at the Institute of Mental
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Health in Belgrade, Serbia. Patients received a comprehensive evaluation including psychiatric history and examination, and MRI. Twenty-one patients (30 %) presented a comorbidity with GAD. All patients were treated with antidepressants: only one patient from the MDD-GAD group was on antidepressant mono therapy (Paroxetine). All other patients were at least on benzodiazepines (mostly Clonazepam) in association with an antidepressant (Selective Serotonin Reuptake Inhibitors being the most prevalent class, followed by Serotonin Norepinephrine Reuptake Inhibitors, Tetracyclic and Tricyclic antidepressants). Since our sample consisted of only inpatients, many of the subjects had treatment resistant depression and a chronic disease course. In these cases, adjunct treatment, like antipsychotics (first or second generation) or stabilizers, was often prescribed (Table 1). Seventy-one native Serbian-speaking, age-matched healthy controls were recruited by word of mouth. Subjects were excluded if they had been previously diagnosed with any psychiatric comorbidity disorder; and if they had any kind of central nervous system disease or other causes of focal or diffuse brain damage, including lacunae, and extensive cerebrovascular disorders at routine MRI. Approval was obtained from the local ethical standards committee on human experimentation and written informed consent from all subjects before enrolment. The study has been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. Clinical assessment Sociodemographic characteristics, familial history, and treatment history were obtained during an interview with an experienced psychiatrist unaware of the MRI results (Table 1). The structured clinical interview for DSM IV (SCID I) was used for diagnosis of MDD and GAD. In addition, depression severity was assessed using the Hamilton Depression Rating Scale (HAMD) and the selfreport Beck Depression self-report Inventory (BDI), and anxiety severity using the Hamilton Anxiety Rating Scale (HAMA). HAMD, BDI, and HAMA scales were not used for defining patient diagnosis. MRI acquisition Brain MRI scans were obtained using a 1.5 T scanner (Achieva, Philips Medical Systems, Best, the Netherlands). The following sequences were acquired from all subjects: dual-echo turbo spin echo (TSE); 3D T1-weighted turbo field echo (TFE); and pulsed-gradient SE echo planar with sensitivity encoding and diffusion gradients applied in 65 noncollinear directions. Details on MRI sequences are provided in the Supplement (eMethods).
J Neurol Table 1 Sociodemographic and clinical features of patients and healthy controls HC 71
MDD 50
MDD-GAD 21
p
Age
45.3 ± 11.0 (23–63)
45.6 ± 10.2 (22–63)
43.7 ± 10.8 (24–61)
Gender (women)
57 (80 %)
42 (84 %)
15 (68 %)
Education
4.4 ± 1.2 (2–6)a
3.12 ± 1.0 (1–5)
3.1 ± 0.9 (2–5)
BDI total score
2.4 ± 3.5 (0–21)a
32.4 ± 12.6 (7–59)
28.9 ± 11.9 (5–55)
0.100
HAMD total score
–
22.9 ± 4.7 (11–36)
24.1 ± 4.8 (15–33)
0.164
HAMA total score
–
22.1 ± 6.6 (6–37)
28.1 ± 7.7 (12–39)
0.001
Symptom duration (months) Treatment
–
86.8 ± 92.2 (6–348)
107.7 ± 73.6 (18–240)
0.317 0.756
0.860 0.249 \0.001
Treatment duration (months)
–
65.6 ± 81.5 (1–288)
71.7 ± 73.0 (2–228)
SNRIs
–
4 (8 %)
2 (10 %)
1.000
SSRIs
–
25 (50 %)
9 (43 %)
0.613
TCAs
–
9 (18 %)
3 (14 %)
1.000
TeCAs
–
21 (42 %)
9 (43 %)
1.000
Benzodiazepines
–
45 (90 %)
21 (100 %)
0.312
Mood stabilizers
–
22 (44 %)
8 (38 %)
0.794
Antipsychotics, 1st generation
–
12 (24 %)
8 (38 %)
0.257
Antipsychotics, 2nd generation
–
11 (22 %)
4 (19 %)
1.000
Values are means ± standard deviations (minimum–maximum) or frequency (percentage). Education scale: 1 = no school; 2 = primary school; 3 = high school; 4 = college; 5 = university degree; 6 = master degree or doctoral degree. p values refer to ANOVA model BDI beck depression inventory, GAD generalized anxiety disorder, HAMA Hamilton Anxiety Rating scale; HC healthy controls, HAMD Hamilton Depression Rating scale; MDD major depressive disorder, SNRIs serotonin norepinephrine reuptake inhibitors, SSRIs selective serotonin reuptake inhibitors, TCAs tricyclic antidepressants, TeCAs tetracyclic antidepressants a
Significant difference between HC and the patient groups at the pairwise comparisons
MRI analysis A detailed description of MRI analysis is provided in the Supplement (eMethods). Briefly, cortical reconstruction and estimation of cortical thickness were performed on the 3D T1-weighted FFE images using the FreeSurfer image analysis suite, version 5.0 (http://surfer.nmr.mgh.harvard. edu/). DT MRI analysis was performed using the FMRIB software library (FSL) tools (http://www.fmrib.ox.ac.uk/ fsl/fdt/index.html) and the JIM5 software (Version 5.0). The DT was estimated on a voxel-by-voxel basis using DTIfit provided by the FMRIB Diffusion Toolbox. Maps of mean (MD), axial (axD) and radial (radD) diffusivities, and fractional anisotropy (FA) were obtained. The DT is represented by three eigenvectors and corresponding eigenvalues that define an ellipsoid [23]. MD is the average of the three eigenvalues and provides a measure of the degree of restriction to the diffusion of water molecules irrespective of direction. FA measures degree of anisotropy of diffusion. FA values range from zero to one. A value of zero means that diffusion is isotropic, i.e., it is unrestricted (or equally restricted) in all directions. A value of one means that diffusion occurs only along one axis and is fully restricted along all other directions. In anisotropic tissue,
such as WM, the largest eigenvalue represents the diffusivity of water in the direction parallel to the fiber bundles (axD). RadD, the average of the two smallest eigenvalues, measures water diffusion perpendicular to the axonal wall. Seeds for tractography of the anterior cingulate bundle (ACB), parahippocampal tract, corpus callosum (CC-whole tract, as well as genu, body and splenium), superior longitudinal (SLF), inferior longitudinal (ILF) and uncinate fasciculi were defined in the Montreal Neurological Institute (MNI) space on the FA template provided by FSL, as previously described [24]. Fiber tracking was performed using FSL (probtrackx) [25]. For each tract, the average MD, FA, axD, and radD were calculated in the native space. Statistical analysis Demographic, clinical and MRI data were compared between each patient group (MDD and MDD-GAD) and the total group of healthy controls, and between patient groups. Demographic and clinical data Normal distribution assumption was checked by means of Q–Q plot and Shapiro–Wilks and Kolmogorov–Smirnov
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J Neurol
tests. Demographic and clinical group comparisons were performed using ANOVA models, followed by post hoc pairwise comparisons, using SAS Release 9.3.
Results
MRI data
Groups were similar for age and gender. Healthy controls had higher education compared to both groups of patients. Patient groups presented with similar depression severity, treatment type and duration, while they differed in anxiety severity with MDD-GAD patients showing higher HAMA scores (Table 1).
A vertex-by-vertex analysis was used to assess differences of cortical thickness between controls and patients, as well between patient subgroups, in FreeSurfer. Analysis was adjusted for multiple comparisons and threshold at p \ 0.05 using Monte Carlo Z-null simulation. Mean cortical thickness and DT MRI measure comparisons were performed using ANCOVA models followed by post hoc pairwise comparisons. p values were corrected for multiple comparisons using false-discovery rate (FDR) approach. Age and education were added in all models as confounding variables. Correlations In patients, age-adjusted Spearman’s rho correlations between cortical thickness and DT MRI measures, and between all MRI measures and HAMA and HAMD total and sub-scores were computed. p values were FDR corrected.
Demographic and clinical data
Cortical thickness Vertex-wise analysis (see eTable 1, eFigures 1, 2 in the Supplement) Only one peak of cortical thinning in the right rostral middle frontal cortex was detected in MDD patients compared with controls. Peaks of cortical thinning were detected in MDD-GAD patients compared with MDD patients and healthy controls mainly in the frontotemporal cortex. No cortical thinning was observed in MDD compared with MDD-GAD patients.
Table 2 Regional mean cortical thickness measurements in patients and healthy controls HC
MDD
MDD-GAD
p MDD vs HC
p MDD-GAD vs HC
p MDD-GAD vs MDD
Frontal lobe L frontal pole
2.57 ± 0.37
2.36 ± 0.63
2.10 ± 0.85
0.042
0.031
0.091
L medial orbitofrontal R medial orbitofrontal
2.29 ± 0.13 2.28 ± 0.11
2.22 ± 0.13 2.23 ± 0.14
2.19 ± 0.13 2.09 ± 0.48
0.046 0.733
0.021 0.027
0.279 0.027
L rostral middle frontal
2.28 ± 0.09
2.21 ± 0.11
2.23 ± 0.12
0.003
0.024
0.829
R rostral middle frontal
2.28 ± 0.09
2.21 ± 0.12
2.21 ± 0.12
0.021
0.031
0.847
R lateral orbitofrontal
2.43 ± 0.10
2.35 ± 0.14
2.37 ± 0.13
0.031
0.093
0.856
L pars opercularis
2.46 ± 0.11
2.39 ± 0.11
2.28 ± 0.52
0.092
0.006
0.086
R pars orbitalis
2.54 ± 0.16
2.39 ± 0.38
2.27 ± 0.54
0.149
0.036
0.191 0.528
Temporal lobe R hippocampus
3.94 ± 0.36
3.60 ± 0.41
3.65 ± 0.42
0.005
0.079
L temporal pole
3.53 ± 0.26
3.56 ± 0.27
3.29 ± 0.77
0.411
0.088
R fusiform
2.48 ± 0.11
2.43 ± 0.13
2.26 ± 0.52
0.104
\0.001
L inferior parietal
2.38 ± 0.10
2.32 ± 0.13
2.33 ± 0.13
0.038
0.073
L supramarginal
2.46 ± 0.09
2.39 ± 0.14
2.41 ± 0.14
0.028
0.062
0.975
R retrosplenial cortex
2.14 ± 0.14
1.87 ± 0.66
2.07 ± 0.12
0.013
0.459
0.149
2.03 ± 0.44
2.05 ± 0.14
1.75 ± 0.72
0.793
0.025
0.018
0.023 0.01
Parietal lobe 0.991
Occipital lobe L lateral occipital
Values are means ± standard deviations (mm). p values refer to ANCOVA model adjusted for age and education, false-discovery rate corrected for multiple comparisons GAD generalized anxiety disorder, HC healthy controls, MDD major depressive disorder
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J Neurol Fig. 1 Regional cortical thinning and white matter tract damage of MDD and MDDGAD patients compared to healthy controls and compared to each other
Regional cortical thickness measures (Table 2; Fig. 1) Compared with healthy controls, both groups of patients showed a main involvement of the bilateral middle frontal cortex. Furthermore, compared with controls, only MDD patient group showed a reduced thickness of the right hippocampus, left inferior parietal, supramarginal and retrosplenial cortex, while only the MDD-GAD group showed a reduced cortical thickness of the inferior frontal gyrus, bilaterally. Compared with MDD, MDDGAD patients showed cortical thinning of the right medial orbitofrontal cortex, right fusiform cortex, left temporal pole and left lateral occipital cortex. No cortical thinning was observed in MDD compared with MDDGAD patients. DT MRI Tractography Compared with healthy controls, MDD patients had increased MD and axD of the right and left SLF, respectively, and increased radD of the right parahippocampal tract (Tables 3, 4; Fig. 1). No difference was detected
between MDD-GAD and healthy controls, or between patient groups. Correlations between cortical thickness and DT MRI measures In all patients, the cortical thickness of the left inferior parietal cortex was related with WM integrity of the SLF bilaterally (right SLF FA, r = 0.42, pFDR = 0.01; right SLF MD, r = -0.38, pFDR = 0.03; right SLF radD, r = -0.45, pFDR = 0.004; left SLF MD, r = -0.34, p = 0.04; left SLF radD, r = -0.39, pFDR = 0.01). Furthermore, cortical thickness of the left hippocampus was related with the FA of the left parahippocampal tract (r = 0.35, pFDR = 0.02). Correlations between MRI measures and clinical features In all patients, the subscore of HAMA assessing the respiratory symptoms was negatively related with the cortical thickness of the right medial orbitofrontal cortex (r = -0.38, pFDR = 0.03). The subscore of HAMD assessing the loss of weight was positively related with the FA of the left uncinate fasciculus (r = 0.41; pFDR = 0.02).
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123
0.49 ± 0.04
0.47 ± 0.03
L
R
0.45 ± 0.04
0.45 ± 0.05
L
R 0.48 ± 0.05
0.48 ± 0.03
0.44 ± 0.03
0.44 ± 0.04
0.45 ± 0.04
0.46 ± 0.04
0.39 ± 0.04 0.38 ± 0.04
0.36 ± 0.06
0.40 ± 0.05
0.53 ± 0.03
0.47 ± 0.04
0.49 ± 0.03
0.46 ± 0.02
0.47 ± 0.02
0.46 ± 0.03
0.47 ± 0.03
0.41 ± 0.04 0.40 ± 0.04
0.38 ± 0.05
0.40 ± 0.04
0.60 ± 0.03
0.154
0.601
0.366
0.532
0.296
0.210
0.492
0.283 0.091
0.283
0.223
0.605
0.380
0.059
0.506
0.641
0.952
0.532
0.244
0.383
0.749
0.806 0.960
0.980
0.309
0.950
0.538
0.161
0.532
0.814
0.366
0.501
0.061
0.748
0.492
0.381 0.094
0.283
0.878
0.605
0.538
0.791
0.81 ± 0.03
0.82 ± 0.03
0.83 ± 0.03
0.83 ± 0.04
0.78 ± 0.03
0.76 ± 0.02
0.83 ± 0.05 0.82 ± 0.05
0.78 ± 0.08
0.80 ± 0.05
0.92 ± 0.05
0.87 ± 0.06
0.89 ± 0.05
0.92 ± 0.06
0.82 ± 0.04
0.83 ± 0.04
0.84 ± 0.03
0.84 ± 0.03
0.80 ± 0.04
0.78 ± 0.05
0.84 ± 0.05 0.85 ± 0.05
0.74 ± 0.10
0.77 ± 0.09
0.93 ± 0.06
0.87 ± 0.04
0.93 ± 0.07
0.81 ± 0.04
0.82 ± 0.04
0.83 ± 0.03
0.82 ± 0.02
0.78 ± 0.03
0.76 ± 0.03
0.83 ± 0.04 0.84 ± 0.05
0.74 ± 0.06
0.75 ± 0.07
0.92 ± 0.07
0.85 ± 0.04
0.91 ± 0.06
0.91 ± 0.06
MDD-GAD
0.356
0.518
0.306
0.176
0.048
0.568
0.615 0.157
0.205
0.144
0.736
0.786
0.073
0.303
p MDD vs HC
0.918
0.852
0.619
0.548
0.578
0.927
0.772 0.556
0.205
0.127
0.736
0.187
0.384
0.944
p MDDGAD vs HC
0.356
0.519
0.596
0.161
0.226
0.596
0.615 0.470
0.954
0.442
0.736
0.187
0.384
0.303
p MDD vs MDD-GAD
ACB anterior cingulum bundle, CC corpus callosum, FA fractional anisotropy, GAD generalized anxiety disorder, HC healthy controls, ILF inferior longitudinal fasciculus, L left, R right, MD mean diffusivity, MDD major depressive disorder, PH parahippocampal tract, SLF superior longitudinal fasciculus, UNC uncinate fasciculus
Values are means ± standard deviations. p values refer to ANCOVA model adjusted for age and education, false-discovery rate corrected for multiple comparisons
ILF
UNC
0.47 ± 0.03
0.47 ± 0.03
L
R
SLF
0.41 ± 0.04 0.41 ± 0.04
0.38 ± 0.04
L R
R
PH
0.42 ± 0.04
L
ACB
0.60 ± 0.03
0.52 ± 0.03
0.53 ± 0.03
0.60 ± 0.02
CC genu
CC splenium
0.56 ± 0.03 0.53 ± 0.03
0.90 ± 0.04
0.55 ± 0.03 0.53 ± 0.03
0.56 ± 0.02
MDD
0.54 ± 0.02
p MDD vs MDD-GAD
CC
p MDDGAD vs HC
CC body
p MDD vs HC
HC
MDD-GAD
MDD
HC
Side
MD [910-3 mm2 s-1]
Region
FA
Table 3 Mean diffusivity and fractional anisotropy values of white matter tracts in patients and healthy controls
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0.58 ± 0.04
0.58 ± 0.04
L
R
0.61 ± 0.05
0.60 ± 0.05
L
R 0.60 ± 0.04
0.60 ± 0.04
0.62 ± 0.04
0.62 ± 0.04
0.59 ± 0.05
0.58 ± 0.06
0.66 ± 0.06 0.67 ± 0.06
0.57 ± 0.08
0.57 ± 0.07
0.57 ± 0.05
0.59 ± 0.05
0.58 ± 0.05
0.60 ± 0.04
0.59 ± 0.03
0.58 ± 0.04
0.56 ± 0.04
0.64 ± 0.05 0.65 ± 0.06
0.56 ± 0.06
0.56 ± 0.06
0.57 ± 0.06
0.800
0.213
0.258
0.348
0.246
0.053
0.116
0.472 0.033
0.125
0.280
0.717
0.792
0.550
0.803
0.810
0.276
0.372
0.870
0.855 0.579
0.125
0.214
0.717
0.486
0.369
0.416
0.550
0.361
0.348
0.067
0.372
0.116
0.483 0.178
0.704
0.416
0.717
0.486
0.456
1.54 ± 0.06
1.26 ± 0.08
1.30 ± 0.07
1.27 ± 0.04
1.28 ± 0.04
1.20 ± 0.05
1.17 ± 0.03
1.22 ± 0.06 1.20 ± 0.08
1.15 ± 0.11
1.20 ± 0.08
1.62 ± 0.08
1.45 ± 0.08
1.49 ± 0.06
1.56 ± 0.05
1.27 ± 0.06
1.31 ± 0.05
1.28 ± 0.05
1.28 ± 0.04
1.21 ± 0.04
1.19 ± 0.05
1.22 ± 0.05 1.21 ± 0.06
1.09 ± 0.15
1.16 ± 0.14
1.63 ± 0.07
1.44 ± 0.04
1.52 ± 0.06
1.25 ± 0.06
1.31 ± 0.05
1.29 ± 0.05
1.29 ± 0.03
1.19 ± 0.04
1.18 ± 0.02
1.21 ± 0.04 1.22 ± 0.05
1.10 ± 0.09
1.15 ± 0.08
1.62 ± 0.09
1.42 ± 0.04
1.50 ± 0.06
1.54 ± 0.06
MDD-GAD
0.919
0.986
0.264
0.608
0.192
0.042
0.586 0.875
0.239
0.110
0.944
0.280
0.227
0.493
pMDD vs HC
0.574
0.986
0.264
0.608
0.734
0.884
0.586 0.875
0.415
0.110
0.737
0.063
0.846
0.493
pMDDGAD vs HC
0.574
0.986
0.588
0.608
0.192
0.085
0.586 0.875
0.752
0.554
0.737
0.180
0.300
0.471
pMDD vs MDD-GAD
axD axial diffusivity, ACB anterior cingulum bundle, CC corpus callosum GAD generalized anxiety disorder, HC healthy controls, ILF inferior longitudinal fasciculus, L left, R right, MDD major depressive disorder, PH parahippocampal tract, radD radial diffusivity, SLF superior longitudinal fasciculus, UNC uncinate fasciculus
Values are means ± standard deviations. p values refer to ANCOVA model adjusted for age and education, false-discovery rate adjusted for multiple comparisons
ILF
UNC
0.55 ± 0.03
0.56 ± 0.03
L
R
SLF
0.60 ± 0.07
0.64 ± 0.05 0.63 ± 0.05
R
L R
PH
0.60 ± 0.05
L
ACB
0.58 ± 0.06
0.059
0.309
0.59 ± 0.05
0.59 ± 0.06
0.57 ± 0.05
CC genu
CC splenium
0.62 ± 0.06
0.59 ± 0.06
0.61 ± 0.06 0.63 ± 0.07
0.59 ± 0.04
MDD
0.60 ± 0.05
pMDD vs MDD-GAD
CC
pMDDGAD vs HC
CC body
pMDD vs HC
HC
MDD-GAD
MDD
HC
Side
axD [910-3 mm2 s-1]
Region
radD [910-3 mm2 s-1]
Table 4 Radial and axial diffusivity values of white matter tracts in patients and healthy controls
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Discussion This is the first study assessing both cortical and WM integrity in a relatively large cohort of MDD patients with or without comorbidity with GAD. We observed that MDD and MDD-GAD share common features of cortical alterations in the ventral and medial regions of the prefrontal cortex. MDD patients also experienced an involvement of the lateral prefrontal and parietal cortices; whereas those with MDD-GAD showed a more pronounced cortical damage in the ACC, insula, temporal and occipital regions. In addition, only MDD patients showed WM microstructural alterations, which were located in the SLF and parahippocampal tract. Such alterations were related to cortical thinning of the inferior parietal lobe and hippocampus, respectively. Finally, we found that brain structural alterations in all patients were related with the severity of anxiety symptoms. Cortical alterations in MDD and MDD-GAD patients Compared to controls, both MDD and MDD-GAD patients showed a reduced cortical thinning of the bilateral rostral middle frontal cortex, medial frontal gyrus, and frontal pole. Our results are in keeping with previous findings showing a prefrontal cortex involvement in MDD and GAD patients. The ventromedial prefrontal cortex subtends emotional processing, behavior initiative and motivation, and is well known to play a critical role in mood disorders [16]. On the other hand, the dorsolateral prefrontal cortex is mainly associated with the cognitive aspects of behavior and is part of the fronto-parietal brain circuits [26]. In the present study, compared with controls, MDD patients showed a cortical thinning of the lateral prefrontal cortex, the inferior parietal and supramarginal cortices. In MDD, the involvement of the parietal lobe together with the lateral prefrontal cortex has been previously demonstrated [27] and seems to be associated with a poor sustained attention and executive dysfunction, which are typical manifestations of these patients [26]. In MDD, we also observed a reduced hippocampal volume compared to controls. The involvement of the hippocampus in MDD has been previously described [28]. The hippocampus plays a crucial role in mood regulation due to its connections with several regions subtending the emotional processing, such as the prefrontal cortex, amygdala, anterior thalamic nuclei and hypothalamus. Several studies support the theory that hippocampal abnormalities are associated to stress-related environmental conditions in individuals with a specific genetic background [29]. In this context, several associations have been found in MDD between specific polymorphisms of the
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serotonin transporter gene (5-HTTLPR) and/or of the brain-derived neutrophic factor (BDNF) and reduced hippocampal volume [30, 31]. Compared to both MDD patients and healthy controls, MDD-GAD patients showed an additional thinning of the right medial orbitofrontal gyrus and insula, rostral ACC, fusiform gyrus, left temporal pole and occipital cortices, bilateral precentral gyrus, parietal lobe and precuneus. Such additional areas of atrophy in MDD-GAD patients involve the key nodes of the anatomical circuit of anxiety [32]. Briefly, registration and reactivity to a negative emotional stimulus are carried out in the amygdala and insula. These regions can direct the signal to the hippocampus (to record emotional-context memories) and sensory cortex (such as motor and visual cortices). Further monitoring and evaluation of the negative stimuli is carried out by the ACC and dorsal/medial prefrontal cortex. Engagement of these structures leads to a detailed appraisal and conscious awareness of the emotional stimulus, which are not functions of insula, amygdala and hippocampus. ACC and dorsal/medial prefrontal cortex in turn provide feedback for a context-appropriate regulation, which may result in inhibition or enhancement of limbic processing [32]. One could speculate that in MDDGAD the emotional processing cannot be properly registered by the atrophic insula neither modulated by the topdown cortical control (due to atrophy of the ACC and prefrontal cortex) leading to an excessive processing by sensory cortices and a failure of fear inhibition that occurs during periods of anxiety. More severe is atrophy on each part of this circuit and more severe is such a dysregulation [16]. White matter alterations in MDD Compared to controls, only MDD patients showed WM abnormalities in the bilateral SLF and the right parahippocampal tract, while no WM alterations were found in MDD-GAD patients. The SLF is a long associative WM tract which links the dorsolateral prefrontal cortex to the inferior parietal and lateral temporal cortices [33]. We also observed a relationship between the reduced thinning of the inferior parietal cortex and the SLF damage, suggesting that the disconnection of the fronto-parietal circuit has a relevant role in MDD. In line with this hypothesis, several DT MRI studies reported reduced WM integrity of the frontal region [34, 35], WM underneath the angular gyrus [35], and inferior parietal portion of the SLF [36] in MDD. In MDD patients, we also observed a reduced integrity of the parahippocampal WM tract and a relationship between the cortical and WM alterations of hippocampus and parahippocampal regions. As it is the case for hippocampal atrophy, also the parahippocampal WM involvement has
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been observed in association with 5-HTTLPR/BDNF specific polymorphisms in MDD patients [29, 37]. The nature of the WM damage in MDD is still debated. The majority of postmortem studies in MDD considered the prefrontal regions only and revealed a decreased neuron size and density [38], as well as reduced glial [38] and oligodendrocyte density [39], and myelin damage in the adjacent WM [40]. A number of postmortem studies reported ischemic lesions in these patients and supported the theory of depression as a vascular disease [41, 42]. Deep WM hyperintensities have been found more frequently in MDD patients than controls [43] and have been associated with a more severe illness, more pronounced cognitive deficits and a poorer response to antidepressants [44]. In our study, we carefully excluded patients with WM hyperintensities visible on T2-weighted images. Thus, although we cannot rule out a microvascular nature of the WM damage in our sample, the damage we observed in MDD most likely reflects a loss of axons or myelin due to a damage secondary to cortical atrophy [45], as also suggested by the correlation analysis. So far, only a few studies investigated WM damage in GAD patients and none of them considered comorbidity with depression. In addition to the involvement of the ACB [15], the uncinate fasciculus, which links the temporal to the frontal structures involved in the emotional processing, has been found to be damaged in GAD patients [20]. In this study, we did not observe WM damage in MDD-GAD patients in the uncinate fasciculus or in the other investigated tracts, and this could be the main difference which distinguishes these patients from those with pure MDD and pure GAD.
lacking in higher level motivational value, such as the need to eat [48]. The respiratory symptoms assessed with HAMA were related to the involvement of the right medial orbitofrontal cortex. This suggests that the more severe the atrophy of these structures is, the greater is the failure of the previously described emotional circuit to modulate the sensory processing and the anxiety manifestations through the autonomic system. Strengths and limitations A number of factors increase the reliability of our findings. The patient population is large and clinically well defined. Cortical and WM alterations have been investigated with advanced MRI techniques, such as tractography and cortical thickness which are able to detect subtle changes, and a sound statistical methodology with correction for multiple comparisons and for confounding variables. However, there are also some caveats to be considered when interpreting our findings. First, the different sample size of the two patient groups might, at least partially, affect our MRI results. Second, the lack of controlling for treatment type, dosage and duration. Third, a third group of GAD patients without MDD comorbidity would have provided a more exhaustive picture of the common/different patterns of abnormalities. Finally, the amygdala, which is one of the regions most involved in emotional circuits, has not been found involved in our patients. Although it seems that amygdala has more a functional value than a structural one in patients with GAD [49], we cannot exclude this could be a false negative finding since this structure, due to its anatomical shape and position, represents a challenge to segmentation techniques [50].
The relationship between brain structural alterations and clinical features
Conclusions In MDD patients, regardless of the comorbidity with GAD, we found a relationship between the severity of anxiety symptoms and the involvement of ventral frontal regions. Indeed, loss of weight assessed with HAMD and respiratory symptoms assessed with HAMA were related with the extent of WM microstructural damage to the uncinate fasciculus and with thinning of the right medial orbitofrontal cortex, respectively. The uncinate fasciculus is a bidirectional, long-range WM tract that connects lateral orbitofrontal cortex, which provides valence-based decisions, with the anterior temporal lobes, which integrate social personally relevant information [46]. Recent studies suggested that a reduced FA of the uncinate fasciculus is related with the severity of depression [47]. Behavioral changes associated with uncinate fasciculus include social-emotional problems due to people and objects being stripped of personal value and
MDD and MDD-GAD share a common pattern of cortical alterations in the medial prefrontal cortex. In addition, while MDD showed a specific involvement of the cortex and WM of the fronto-parietal circuit, MDD-GAD harbors a more severe pattern of cortical atrophy, but not WM damage, involving the anatomical circuitry related to anxiety. The fact that MDD and MDD-GAD comorbidity are characterized by both common and distinct patterns of damage offers new insights into their pathophysiology: this may explain why comorbidity of these two disorders is so prevalent in the population and why they frequently respond to similar treatments. This also validates the clinical relevance of the comorbidity information and the view of MDD-GAD as a separate entity with distinct clinical and cerebral features. Such an understanding could provide insights into patient vulnerability linked to damage of
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selective brain networks as well as into patient resilience factors reflected by the integrity of other cerebral circuits. Acknowledgments
8.
No outside funding was used for this study.
Conflicts of interest Elisa Canu, Milutin Kostic´, Ana Munjiza, Pilar M Ferraro, Danilo Pesic, Massimiliano Copetti, and Amir Peljto report no disclosures. Federica Agosta serves on the editorial board of the Journal of Neurology; has received speaker honoraria from Biogen Idec, and EXCEMED—Excellence in Medical Education; and receives research supports from the Italian Ministry of Health, and AriSLA (Fondazione Italiana di Ricerca per la SLA). Dusica Lecic Tosevski is Editor-in-Chief of the Journal Psychiatry Today; has received compensation for speaking activites from Janssen-Cylag, Pfizer, Hemopharm, Astra Zeneka; and receives research support from Serbian Ministry of Education and Science and Serbian Academy of Sciences and Arts. Massimo Filippi is Editor-in-Chief of the Journal of Neurology; serves on scientific advisory boards for Teva Pharmaceutical Industries; has received compensation for consulting services and/or speaking activities from Bayer Schering Pharma, Biogen Idec, Merck Serono, Novartis, and Teva Pharmaceutical Industries; and receives research support from Bayer Schering Pharma, Biogen Idec, Merck Serono, Teva Pharmaceutical Industries, Novartis, Italian Ministry of Health, Fondazione Italiana Sclerosi Multipla, Cure PSP, Alzheimer’s Drug Discovery Foundation (ADDF), the Jacques and Gloria Gossweiler Foundation (Switzerland), and ARiSLA (Fondazione Italiana di Ricerca per la SLA). Ethical standard Approval was obtained from the local ethical standards committee on human experimentation and written informed consent from all subjects before enrolment. The study has been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.
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