Brain structural correlates of depressive symptoms in Parkinson's disease patients at different disease stage

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Brain structural correlates of depressive symptoms in Parkinson’s disease patients at different disease stage Yanxuan Li , Peiyu Huang , Tao Guo , Xiaojun Guan , Ting Gao , Wenshuang Sheng , Cheng Zhou , Jingjing Wu , Zhe Song , Min Xuan , Quanquan Gu , Xiaojun Xu , Yunjun Yang , Minming Zhang PII: DOI: Reference:

S0925-4927(19)30216-1 https://doi.org/10.1016/j.pscychresns.2019.111029 PSYN 111029

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Psychiatry Research: Neuroimaging

Received date: Revised date: Accepted date:

1 August 2019 26 December 2019 27 December 2019

Please cite this article as: Yanxuan Li , Peiyu Huang , Tao Guo , Xiaojun Guan , Ting Gao , Wenshuang Sheng , Cheng Zhou , Jingjing Wu , Zhe Song , Min Xuan , Quanquan Gu , Xiaojun Xu , Yunjun Yang , Minming Zhang , Brain structural correlates of depressive symptoms in Parkinson’s disease patients at different disease stage, Psychiatry Research: Neuroimaging (2019), doi: https://doi.org/10.1016/j.pscychresns.2019.111029

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Highlights: 

Depression occurs frequently in Parkinson’s Disease (PD) patients.



Lewy body accumulation can damage emotion circuit and cause depression.



We studied brain structural correlates of depression in PD at early and middle stages.



Depressive symptoms in middle stage PD were more related to gray matter changes.



The neural basis of depression may be distinct in PD patients at different stages

Brain structural correlates of depressive symptoms in Parkinson’s disease patients at different disease stage Yanxuan Lia,b+, Peiyu Huanga+, Tao Guoa, Xiaojun Guana, Ting Gaoa, Wenshuang Shengb, Cheng Zhoua, Jingjing Wua, Zhe Songc, Min Xuana, Quanquan Gua, Xiaojun Xua, Yunjun Yang*b, and Minming Zhang*a

a

Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of

Medicine, 310000, Hangzhou, China b

Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, 325000,

Wenzhou, China c

Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of

Medicine, 310000, Hangzhou, China

+: These two authors contributed equally to this paper. Corresponding to: *Prof. Minming Zhang, MD, PhD Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, China, 310009; Phone: 86-0571-87315255; Fax: 86-0571-87315255; E-mail: [email protected]. *Dr. Yunjun Yang, MD, PhD Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China, 325000; Phone: 86-13857793972; Fax: 86-0571-87315255; E-mail: [email protected].

Abstract Parkinson’s disease (PD) pathology may damage emotion circuit and cause depression. We investigated whether the neural basis of depressive symptoms varies at different PD stages. Seventy-six healthy controls (HC) and 98 PD patients (divided into early and middle stage groups) underwent brain magnetic resonance imaging (MRI) and general neuropsychological tests. Voxel-based morphometry and tract-based analysis were used to study the association between brain structural alterations and the Hamilton Depression Scale 17 Item (HAMD-17) scores in different groups. Comparing with HC group, PD patients showed widespread brain alterations in both gray and white matter. The HAMD-17 scores were positively correlated with GM volume in the right pre-central gyrus of early PD patients. In the middle stage group, HAMD-17 scores were positively correlated with GM volume in midbrain and right superior temporal gyrus, and negatively associated with GM volume in left anterior cingulate and superior frontal gyrus. In white matter analysis, The HAMD-17 scores were positively correlated with fractional anisotropy value of the bilateral inferior fronto-occipital fasciculus in the early stage group, but not the middle stage group. We concluded that the neural basis of depressive symptoms might be distinct in different stages of PD, implying the need for differential treatments. Keywords:

gray matter;

white

basal-ganglia circuit; reward circuit

matter;

voxel-based

morphometry;

TBSS;

1. Introduction: Parkinson’s disease (PD) is a progressive neurodegenerative disorder that has attracted intense research attention due to accelerated global aging. Although PD is characterized by distinct motor symptoms, non-motor symptoms lead to patient suffering, decreasing the quality of life. Depression is one of the most frequent non-motor symptom (Tykocki et al., 2013). In addition, PD patients with depression typically display poorer outcomes. Understanding the neural mechanism of PD depression is important for clinical intervention. According to neuroimaging findings, depression is related to disruptions of emotional circuits. PD pathology specifically involves different emotional circuit nodes during disease development (Nestler and Carlezon, 2006). While lewy body accumulation gradually spreads, mid-brain neurotransmitter systems are among the earliest involved areas. Disturbance in the mid-brain dopaminergic and serotoninergic neurons may gradually degenerate and cause depression, although no apparent motor symptoms can be observed at this time (Halliday et al., 1990). Upon the onset of disease, limbic structures become damaged, including important emotional structures such as the hippocampus and amygdala (Qamhawi et al., 2015). During later disease stages, gray matter volume and cortical thickness in the frontal cortex gradually decline, leading to impaired cognitive functions and disturbed emotional regulation. White matter fiber bundles are also affected (Braak et al., 2006), disrupting the connections amongst emotion circuit nodes. Although these pathologies damage the function of emotion circuits, patients at different disease stages may present

differential depressive manifestations and may require different treatments. Previous studies have investigated gray and white matter alterations in PD patients with depression. PD patients with depression showed significantly increased cortical areas in the orbitofrontal regions and insula compared to non-depressed PD patients (Huang et al., 2016). Goto et al. (2018) reported a negative correlation between depression and the bilateral hippocampal volume of PD patients. Van Milelo et al. (2015) found that depression scores were negatively correlated with the bilateral hippocampus and right amygdala volume, but positively correlated with the volume of the anterior cingulate cortex. Chagas et al. (2017) reported a loss of volume in frontal and temporal areas, and in the bilateral amygdala. White matter (WM) abnormities have also been demonstrated. Our previous studies revealed that decreased fractional anisotropy (FA) values in the left uncinate fasciculus, superior longitudinal fasciculus, anterior thalamic radiation, forceps minor, and the inferior longitudinal fasciculus occurred in PD patients (Huang et al., 2014). Wu et al. (2018) found that depression scores were negatively correlated with the FA values in the left cingulum and left superior longitudinal fasciculus in depressed PD patients. Although these studies partly revealed that the neuronal mechanisms were related to PD depression, PD patients were treated as whole groups, possibly due to limitations in sample size. The differential mechanisms underlying depression in PD patients at different disease stages have yet to be elucidated. In this study, we conjecture that the structural foundation of depression differs in PD patients at different disease stages. Through the analysis of both gray matter

volume and white matter diffusion parameters, we hypothesize that lower levels of brain structures, including the amygdala and hippocampus, contribute to depression in early stage patients, while the degeneration of neocortices such as the frontal lobe are more related to depression in later stage patients. 2. Methods 2.1 Participants Seventy-six healthy controls (HC) and ninety-eight PD patients were recruited from the Department of Neurology, Second Affiliated Hospital of Zhejiang University. PD was diagnosed by a senior neurologist according to UK PD Brain Bank criteria. Scores from the Hamilton Depression Rating Scale 17 Item (HAMD-17), Hoehn&Yahr stage (HY), the Hamilton Anxiety Scale (HAMA) and Unified Parkinson’s Disease Rating Scale part-III (UIII) were obtained from all subjects. PD patients were divided into two groups (41 patients in HY1 or HY1.5 were collectively termed early stage, and 57 in HY2 or HY2.5 were collectively termed middle stage). We excluded patients with any history of other neurological disorders, psychiatric disorders, or brain trauma. All subjects signed informed consent prior to participating in the study. This study was approved by the Medical Ethics Committee of 2nd Affiliated Hospital, Zhejiang University. 2.2 Scanning parameters Participants were scanned on a GE Discovery 750 3.0T MR scanner. Ear plugs and foam pads were used to reduce noise and head motion. High resolution 3D T1

weighted structural brain images were acquired using a fast spoiled gradient recalled echo sequence (time repetition: 5.1ms; time echo: 1.2 ms; FOV= 256 x 256 cm; matrix= 256 x 256; slices= 124; thickness=1.2 mm; and space=0 mm). Diffusion tensor images were acquired using the following parameters: TR/TE= 8,000 ms/minimum; acquisition matrix = 128 × 128; field of view = 256 mm × 256 mm; slice thickness = 2 mm, no gap; and 67 contiguous axial slices. Diffusion images were acquired from 30 gradient directions (b = 1000 s/mm2), and included five acquisitions without diffusion weighting (b = 0). Several other sequences were scanned, and the total acquisition time was 50 min for each subject. 2.3 Data processing Images were reviewed by a radiologist to exclude clinical abnormalities and the existence of imaging artifacts from further analysis. Image pre-processing was performed using CAT12 (http://www.neuro.uni-jena.de/cat/index.html), a brain structure analysis toolbox based on the Statistical Parametric Mapping analysis package (SPM12, http://www.fil.ion.ucl.ac.uk/spm/software/spm12). Images were segmented into GM, WM and cerebrospinal fluid (CSF), and normalized to the Montreal Neurological Institute space (Petrovic et al., 2012), with volume information modulated. Cortical maps were smoothed using an 8-mm full width at half maximum kernel, prior to building the statistical model. Diffusion-weighted images were analyzed on a pipeline toolbox PANDA (http://www.nitrc.org/projects/panda) based on FSL (http://fsl.fmrib.ox.ac.uk), including pre-processing and the calculation of diffusion parameters. All images were transformed into the NIfTI format. Skull

stripping and eddy current corrections were performed, diffusion tensors were reconstructed, and diffusion parameters were calculated. The resulting FA images were processed using Tract-based Spatial Statistics (TBSS), which performs voxel-by-voxel whole-brain analysis. Following alignments of the individual FA images to the standard brain templates using non-linear registration, the mean FA image was calculated and compressed to form a mean skeleton representing the topological features of all tracts derived from the whole group. Each subject's aligned FA images were projected onto the fiber skeleton template for statistical analysis. Mean diffusivity maps (MD) were also normalized to the skeleton using TBSS. 2.4 Statistical analysis Genders were compared using chi-square tests. Age, education, UIII, HAMD-17 scores and HAMA scores were compared using two sample t-tests. Statistical analysis of smoothed GM images was performed using GLM models in SPM12. Correlation analysis between the GM images and HAMD scores were independently performed in both early and middle stage groups. Then, an interaction analysis was done to investigate whether the linear relationship between the dependent variable (gray matter volume) and independent variable (HAMD score) differs between the two groups. Further details can be seen in the following link: https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/GLM#Two_Groups_with_continuous_covariate_i nteraction. We additionally implemented a two-sample t-test between pooled PD patients and HC. To correct for multiple-comparisons, the threshold free cluster

enhancement (TFCE) method and permutation tests were used to control false discovery rates below 0.05 (TFCE-FDR-correction), using PALM (Permutation Analysis of Linear Models, https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/PALM). For each analysis, 5000 permutations were performed. As all correlation analysis data did not survive TFCE correction, we used cluster-correction to explore possible correlations, using p values<0.001 and cluster sizes > 50. The effects of age, gender and education were controlled in all analysis. WM statistical analysis was performed as described for GLM and PALM. Two sample t-tests were used to reveal differences in FA and MD between HC and PD patients. Regression analysis was used to estimate the correlation between the volume of GM and HAMD-17 scores during early and middle stages. Finally, two group continuous covariate interaction models were used to demonstrate differences in the correlations between HAMD scores and diffusion parameters across the PD groups. We initially implemented the TFCE method and TFCE-FDR-correction for multiple comparisons, using age, gender and education as covariates. As the data did not survive strict corrections, we performed cluster-correction to explore potential effects. To locate the specific fibers, coordinates of the cluster peak points were referenced using the JHU white-matter atlas and MRI Atlas of Human White Matter, 2nd edition. The effects of age, gender and education were controlled in all analysis. 3. Results As shown in Table 1, age (p=0.346), gender (p=0.442) and education (p=0.057)

showed no significant differences between PD patients and HC. Significant differences in HAMA (p=1*10-6), HAMD-17 (p=1*10-4) and the Unified Parkinson’s Disease Rating Scale part-III (p=2*10-31) between HC and PD patients were observed. No significance differences in gender (p=0.419), education (p=0.058), HAMD-17 (p=0.095) or HAMA (p=0.063) between PD patients in the early and middle stages were observed. Age (p=0.001) and UIII (p=4*10-13) were higher in PD patients in the middle compared to early stages. GM analysis data are shown in Table 2 and Figure 1. Compared with HC, PD patients had decreased GM volumes in several brain regions, most notably in the frontal lobe and sub-lobar areas (FDR corrected). The depression scores of early PD patients showed a positive association with the pre-central gyrus volume. Depression scores of patients in the middle stages were positively correlated with the volume of the right midbrain and right superior temporal gyrus. Depression scores of patients in the middle stages also negatively correlated with the volume of the left anterior cingulate, right superior temporal gyrus and left superior frontal gyrus. Continuous covariate interaction analysis between the patient groups showed that, HAMD-17 scores were related to the volume of the right post-central gyrus in early stage patients, whilst in middle stage patients, depression scores were related to the volume of the left cerebellum and right cuneus. In WM analysis (see Table 3 and Figure 2), PD patients showed higher fractional anisotropy (FA) values than HC at several fibers, including the cingulum, left anterior thalamic radiation, right inferior longitudinal fascicular, and bilateral cortico-spinal

tract. HAMD-17 scores were positively correlated with FA value of the inferior fronto-occipital fasciculus in the early stage group, but not the middle stage group. 4. Discussion In this study, we investigated the structural basis of depressive symptoms in PD patients. We found that PD patients had decreased GM volumes in many brain areas, but higher FA values in several fiber bundles compared to HC. Depression scores in early stage PD patients were related to GM volume in the right precentral gyrus, whilst significant correlations were observed in the frontal lobe and midbrain of middle stage patients. 4.1 Gray matter analysis We found that the volumes of left precentral gyrus in early stage patients were positively correlated with HAMD-17 scores. While the function of this area is to control voluntary movements of the contralateral side of the body (Alexander et al., 1986), it may seem odd that we found precentral gyrus is positively correlated with depression scores. A possible explanation is that the correlation was established through the compensating effects of the precentral gyrus on basal ganglia dysfunction. Previous studies demonstrated that with damaged striatum circuits, the directly connected motor cortex compensates. In addition, damaged basal ganglia circuit has been implicated in the occurrence of depression (Morita and Hikida, 2015). This positive correlation therefore implicates that cortical motor areas indirectly mediated the symptoms of depression through compensatory mechanisms.

We further found that the volume of the right superior temporal gyrus (STG) and right periaqueductal gray matter (PAG) positively correlate with the HAMD-17 scores of middle stage patients. The volume of the left anterior cingulate, and left superior frontal gyrus negatively correlated with HAMD-17 scores in middle stage patients. Generally, the frontal cortex (Schiller et al., 2013), PAG (Olmstead and Franklin, 1997; Van der Kooy and Sawchenko, 1982) and anterior cingulate (Remy et al., 2005) are major components of reward circuits. Neural and behavioral studies suggest that depression is associated with a loss of reward sensitivity (Ait Oumeziane and Foti, 2016; Forbes et al., 2009; Keedwell et al., 2005; Knutson et al., 2008; Schaefer et al., 2006). The onset of depression in middle stage PD patients may therefore be more relevant to the dysfunction of reward circuits. The superior frontal gyrus forms part of the prefrontal cortex (PFC), which participates in higher cognitive functions, abnormalities in which are associated with depression (Treadway et al., 2015). Previous functional studies found that the PFC shows abnormal activation during the progression and recovery of depression (Greicius et al., 2007; Koenigs and Grafman, 2009; Mayberg et al., 1999). In addition, the atrophy of neurons and glia during depression may contribute to volume reduction observed in the prefrontal cortex (Duman and Aghajanian, 2012; McEwen et al., 2012). Schiller et al. (2013) similarly found that remitted MDD groups had lower levels of superior frontal gyrus activation during loss anticipation. In this study, we observed a negative correlation between HAMD-17 scores and superior frontal gyrus volume, confirming its role in depression. PAG has reciprocal connections to the prefrontal cortex, in addition to the insula,

hypothalamus, hippocampus, amygdala and spinal cord (Coulombe et al., 2016; Linnman et al., 2012; Tovote et al., 2016). PAG volumes increase during a variety of emotional disorders (Del-Ben and Graeff, 2009; Drevets et al., 2008), although its detailed mechanism still requires further investigation. For the left anterior cingulate, this hub structure plays an important role in the regulation of cognitive and emotional function. The anterior cingulate displays both anatomical and functional connectivity with other prefrontal regions, insular, caudate nucleus and cerebellum. Abnormalities of the anterior cingulate of PD patients both structurally and functionally have been reported. Chagas et al. (2017) observed a volume reduction in the anterior cingulate cortex of depressed PD patients compared to HC. Frosini et al. (2015) reported the relationship between depression and mesolimbic dysfunction represented by the degeneration of dopaminergic afferents to the anterior cingulate cortex in depressed PD patients. Similar to our findings, Hanganu et al. (2017) found that higher depression scores could predict cortical thinning in the anterior cingulate. Depression is common in PD patients and is associated with diminished locus coeruleus projections to the anterior cingulate and limbic thalamus (Remy et al., 2005). The superior temporal gyrus is involved in emotional processing and social cognition together with the frontolimbic areas (orbitofrontal cortex, amygdala, and anterior cingulate cortex) (Allison et al., 2000; Gallagher and Frith, 2003). Previous studies found that dysfunction of the temporal lobe is associated with mood disturbances. For example, patients with temporal lobe epilepsy have a higher likelihood of depression, compared to patients with other types of epilepsy (50%-60%)(Valente and Busatto

Filho, 2013). Functional MRI studies found that depressed patients display decreased functional connectivity in this region and abnormal activation (Lou et al., 2015). Similar to the major depression disorder (MDD), depression in PD reduces the ability to modulate behavior as a function of reward (Pizzagalli et al., 2008; Vrieze et al., 2013). In this study, a positive correlation between STG volume and HAMD-17 scores was observed, due to the production of negative stimuli to compensate for defective reward circuits. Finally, interaction analysis showed that the volume of left cerebellum was more relevant to the HAMD-17 scores of patients in the middle stage compared to early stage patient. The cerebellum forms connections with limbic regions and the mono-aminergic nuclei of the brain stem mediate emotional processing (Schmahmann and Pandya, 2007). Ma et al. (2018) found that cerebellar changes were associated with depressive symptom in PD. Zhu et al. (2016) found that depressed PD patients show lower levels of voxel-mirrored homotopic connectivity in the cerebellum posterior lobe compared to HC. In depressed PD patients, the increased volume of the cerebellum serves to compensate both motor and non-motor symptoms through the cerebello-thalamo-cortical circuit (Middleton and Strick, 2000). Payoux et al. (2004) found that the regional cerebral blood flow of the cerebellum diminished upon improved motor signs, due to deep brain stimulation of the subthalamic nucleus. GM volumes in the cunues and postcentral gyrus also differed between early and middle PD groups, suggesting they may contribute to visual and somatosensory disturbances observed during PD depression.

4.2 White matter results We found that the HAMD-17 scores correlated with FA values in the bilateral fronto-occipital fascicular (FOF) of early stage PD patients, but no such correlation was observed in the middle stage group. The FOF is a large fiber bundle that starts from the frontal lobe, ending in the occipital-temporal cortex (Schmahmann and Pandya, 2007). The specific functions of the FOF require clarification, although evidence suggests a role in visual processing (Bagga et al., 2014) such as reading (Rollans et al., 2017), attention (Leng et al., 2016) and emotional recognition (Crespi et al., 2014). Two Meta-analyses showed that the FA in FOF was altered in depressed patients, although the directions of the changes were variable (Liao et al., 2013; Murphy and Frodl, 2011). It is interesting that no significant correlation was observed between FA values and depression scores in middle stage patients, as depression is closely associated with fiber connectivity. Considering that GM alterations in many brain areas were related to HAMD-17 in middle stage patients, it is possible that the neuron cell body alterations had become greater and covered the effect of white matter alterations. 4.3 Other considerations There is a discrepancy between our hypothesis and results. We hypothesized that hippocampus and amygdala structural changes might contribute to depressive symptoms in early stage PD patients, but we failed to find such associations. There might be several reasons for this discrepancy. Firstly, volumetric changes of

hippocampus and amygdala may occur only in late stage depression. Many studies reported that decreased hippocampal and amygdala function was associated with depression (Hu et al., 2015; Huang et al., 2015; Luo et al., 2014; Skidmore et al., 2013; Wen et al., 2013; Zhang et al., 2019), but amygdala did not change in PD patients who developed depression (Chang et al., 2017; Kostic and Filippi, 2011; Martinez-Horta et al., 2017). Secondly, as depression is a heterogeneous disease, the neural mechanism of PD depression may differ from depression in general populations. PD is characterized by the imbalance of basal ganglia circuit, which connects with cortex, midbrain and cerebellum structures. Disturbed function in this circuit may also contribute to depression, and induce compensatory changes, as suggested by our results. Nevertheless, the results supported our assumption that the different brain regions were associated with depressive symptoms across different PD stages. One limitation of this study is all PD patients in this study were under HY 2.5 stage. Depressive symptoms related to the brain structures of patients at higher HY stages require exploration in large cohort studies. 4.4 Conclusions In summary, we reported that the structural foundations of depressive symptoms are different in early and middle stage PD patients. Whilst early stage patients show a correlation between HAMD-17 scores and GM volume in the motor areas, correlation analysis in middle stage patients showed widespread brain areas, mainly in reward circuits. The correlation between fiber integrity and HAMD-17 scores was only

observed in early stage patients, indicating that gray matter alterations were more important for depressive symptoms in middle stage PD patients. The neural basis of depression may therefore be distinct in PD patients at different disease stages. Further confirmation of these data may provide useful information for differential and targeted clinical treatments for PD depression.

Contributors Minming Zhang and Yunjun Yang direct the experiment’s overall thinking and design. Yanxuan Li and Peiyu Huang conceived of the design’ details and analytic plan and performed statistical analyses, then drafted the manuscript together. Yanxuan Li, Xiaojun Guan, Ting Gao, Tao Guo, Wenshuang Sheng, Cheng Zhou, Jingjing Wu, Zhe Song, Min Xuan, Quanquan Gu and Xiaojun Xu led data collection. All authors contributed to and approved the final manuscript.

Role of funding source This study was supported by the 13th Five-year Plan for National Key Research and Development Program of China (Grant No. 2016YFC1306600), the National Natural Science Foundation of China (Grant Nos. 81571654, 81771820 and 81701647), the Fundamental Research Funds for the Central Universities of China (Grant No. 2017XZZX001-01), the Health Foundation for Creative Talents in Zhejiang Province (2016), the Cooperative Project by Ministry of Health and Provincial Department

(Grant No. 2016149022)， and the Natural Science Foundation of Zhejiang Province (Grant No. LSZ19H180001).

Conflict of Interest The authors have no conflicts of interest to declare.

Figure legends

Figure 1. A. Differences between PD patients and HC (TFCE-FDR-correction). Yellow-red areas represent larger GM volumes in HC compared to PD patients. B. Correlation between regional brain volumes and depression scores of early stage patients (cluster-correction). C. Correlation between regional brain volumes and

depression scores of the middle stage patients. Warm and cold colors represent positive and negative relationships, respectively (cluster-correction). D. Continuous covariate interactions between early and middle stages (blue: correlation between regional volume and depression scores were higher in early stage patients; red: higher correlation in the middle stage group) (cluster-correction).

Figure2. A. Fibers where PD patients had higher FA values compared to HC (cluster-correction); B. Fibers in which the FA of PD patients in the early stages correlated with the HAMD-17 scores (cluster-correction).

Table1. Demographic characteristics. Index

early stage

middle stage

p value

HC HC vs. PD

early vs. middle

age

56.08±7.43

61.46±7.75

60.3±6.94

0.346#

0.001#

gender

21/20

24/33

47/29

0.422##

0.419##

education

9.51±4.05

7.86±4.32

9.64±2.82

0.057#

0.058#

HAMD-17

3.76±3.70

5.33±4.35

2.96±3.90

0.000#

0.095#

HAMA

4.59±4.04

6.18±5.30

2.07±2.70

0.000#

0.063#

UIII

13.68±4.89

29.88±12.76

0.54±1.16

0.000#

0.000#

# for t value ## for chi-square

Table2. Results of gray matter analysis. contrast

L/R

peak region

BA

cluster size

MNI coordinate x

y

z

Early stage

R

pre-central gyrus

161

46.5

-18

72

Middle stage

R

midbrain(periaqueductal

139

1.5

-27

-1.5

grey matter)

interaction

HC-PD

R

superior temporal gyrus

79

36

-40.5

15

L

cingulate gyrus

209

-16.5

25.5

27

L

superior frontal gyrus

9

214

-22.5

48

31.5

L

superior frontal gyrus

8

208

-22.5

33

51

L

cerebellum

110

-34.5

-67.5

-30

R

cuneus

17

659

15

-76.5

7.5

R

postcentral gyrus

3

245

33

-34.5

79.5

L

Cerebellum Posterior Lobe

64

-22.5

-67.5

-39

L&R

Sub-lobar

3713

0

-27

-12

BA for brodmann area

Table3. Results of white matter analysis. contrast

early stage

PD-HC

L/R

peak region

clustersize

MNI coordinate x

y

z

L

inferior fronto-occipital fascicular

98

32

-50

14

R

inferior fronto-occipital fascicular

65

-31

-45

13

L

anterior thalamic radiation

119

8

-32

21

R

corticospinal tract (cerebellum)

78

14

-64

-27

L

corticospinal tract

77

-8

-13

-17

R

cingulum (hippocampus)

65

25

-48

22

R

inferior longitudinal fascicular

57

25

-24

-7

Conflict of Interest: The authors have no conflicts of interest to declare.

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