JNS-13379; No of Pages 4 Journal of the Neurological Sciences xxx (2014) xxx–xxx
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Disrupted white matter integrity in depressed versus non-depressed Parkinson's disease patients: A tract-based spatial statistics study Peiyu Huang a,1, Xiaojun Xu a,1, Quanquan Gu a, Min Xuan a, Xinfeng Yu a, Wei Luo b, Minming Zhang a,⁎ a b
Department of Radiology, 2nd Affiliated Hospital, Zhejiang University School of Medicine, China Department of Neurology, 2nd Affiliated Hospital, Zhejiang University School of Medicine, China
a r t i c l e
i n f o
Article history: Received 8 February 2014 Received in revised form 25 July 2014 Accepted 8 August 2014 Available online xxxx Keywords: Parkinson's disease Depression Diffusion tensor imaging
a b s t r a c t Depression is a common occurrence in patients with Parkinson's disease (PD), however, its pathophysiology still remains unclear. With increasing evidence suggesting that depression is a disconnection syndrome, we hypothesized that depression in PD is caused by degenerated fiber connections in the brain. We examined whole brain white matter integrity in 15 depressed PD patients and 15 non-depressed PD patients. All the patients were assessed with the Unified Parkinson's Disease Rating Scale, the Hamilton Rating Scale for Depression, and the Mini-Mental State Examination. White matter difference between the two groups and its correlation with disease severity was calculated. In depressed PD patients, decreased fractional anisotropy was found in the left uncinate fasciculus, superior longitudinal fasciculus, anterior thalamic radiation, forceps minor, and the inferior longitudinal fasciculus. Fractional anisotropy in the left deep temporal cortex was negatively correlated with severity of depression (r = −0.671, p = 0.034). Our results suggest that disrupted fiber connections in the anterior part of the left hemisphere may contribute to depression in PD patients. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Parkinson's disease (PD) is frequently accompanied by depressive symptoms [1,2]. Depression can cause functional impairment in PD patients and further reduce their quality of life. The pathophysiological relationship between PD and depression is complicated. Although the negative feelings brought about by disabling symptoms is an important factor, a lot of evidence suggests some underlying brain pathology [3]. The advancement of modern imaging methods has provided useful tools for looking into the neural basis of depression in PD. Early studies using positron emission tomography (PET) found reduced cerebral blood flow in the frontal lobe, cingulate gyrus and caudate in depressed PD (dPD) patients compared with non-depressed PD (ndPD) patients [4–6]. Degeneration of the neurotransmitter systems, especially dopamine and serotonin signaling, was also implicated in PET studies [7–9]. With the application of magnetic resonance imaging (MRI), alterations of cortical gray matter and sub-cortical structures were further revealed in several studies [10–12]. In addition to abnormalities in local areas, fiber connections among different brain regions may also contribute to depression in PD [13]. As emotional regulation involves several brain structures, disrupted
⁎ Corresponding author at: Department of Radiology, 2nd Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District. Hangzhou 310009, China. Tel./fax: +86 0571 87315255. E-mail address: [email protected] (M. Zhang). 1 These two authors contribute equally to this paper.
communications between these structures may lead to uncoordinated and disoriented activities [14,15]. Recent studies on depressed patients in the general population have confirmed that a disturbed emotional network is one underlying cause for the occurrence of depression [16]. Since white matter degeneration is common in PD patients [17], they may also affect emotion-related networks, which may cause depression. Some previous studies have tried to investigate white matter changes in dPD patients. Fractional anisotropy (FA) in the anterior cingulate bundle [18] was found to be reduced in dPD patients compared with that of ndPD patients. White matter hyperintensity in the deep periventricular region was also related to dPD [19]. Despite these findings, some studies did not support white matter deficits. A recent tractography study found no difference in the uncinate fasciculus and corpus callosum between dPD and ndPD patients [20], which are frequently damaged in major depressive disorder (MDD) patients [21]. A potential confounding factor here is that previous studies used region of interest (ROI)-based analysis, by which the derived results were dependent largely on subjective selections. Until now, there was a lack of unbiased automated whole brain inspection of white matter degenerations in dPD patients. In the present study, we performed an investigation on whole brain white matter integrity in dPD patients relative to that of the ndPD patients, by using diffusion tensor imaging (DTI) and tract-based spatial statistics (TBSS) analysis. TBSS is a method proposed by Smith et al. [22]. By using a FA skeleton template derived from a specific research cohort, TBSS can normalize FA images from different subjects with higher precision compared with traditional procedures. Because of this advantage,
http://dx.doi.org/10.1016/j.jns.2014.08.011 0022-510X/© 2014 Elsevier B.V. All rights reserved.
Please cite this article as: Huang P, et al, Disrupted white matter integrity in depressed versus non-depressed Parkinson's disease patients: A tractbased spatial statistics study, J Neurol Sci (2014), http://dx.doi.org/10.1016/j.jns.2014.08.011
2
P. Huang et al. / Journal of the Neurological Sciences xxx (2014) xxx–xxx
TBSS has become a widely used method in DTI studies of neuropsychiatric diseases [23,24]. Here we hypothesize that dPD patients may have deficits in certain white matter tracts, such as the uncinate fasciculus and superior longitudinal fasciculus. 2. Materials and methods 2.1. Subjects Two groups of PD patients (with and without depression, 15 for each group) were recruited from the Department of Neurology, Zhejiang University School of Medicine. Diagnosis of PD was made according to UK PD Brain Bank criteria. Unipolar depression was diagnosed according to the DSM-IV criteria by an experienced psychiatrist. The psychiatrist gathered detailed patient history of the two disease symptoms and decided whether depression was premorbid or postmorbid. For the 15 patients, depression was all diagnosed as postmorbid, and they had not received pharmaceutical treatments before scanning. Scores of the Unified Parkinson's Disease Rating Scale (UPDRS), the Hamilton Rating Scale for Depression (HRSD), and the Mini-Mental State Examination (MMSE) were obtained from all subjects. Anti-parkinsonian medicine was terminated at least 12 h prior to the imaging scans. Table 1 shows detailed characteristics of the two groups. For exclusion criteria, we ruled out any subjects who had other neurologic or psychiatric disorders, or brain trauma at any time of their lives. All the subjects had signed written informed consent before taking part in the study. This research was approved by the Medical Ethic Committee of the Second Affiliated Hospital, Zhejiang University School of Medicine.
further processed using TBSS, which performs voxel-by-voxel wholebrain analysis. After aligning all of the individual FA images to the standard space template using nonlinear registration, the mean FA image was calculated and compressed to form a mean skeleton representing topological features of all tracts derived from the whole group. An FA threshold of 0.3 was set to remove trivial tracts. Finally, each subject's aligned FA images were projected onto the fiber skeleton template to perform statistical analysis. Mean diffusivity (MD) was also normalized to the skeleton using TBSS. 2.4. Statistical analysis Age, education, disease duration and scale scores were compared between the two groups using two-sample t-test. Chi-square tests were performed to compare the sex and side-of-onset differences. The image data were analyzed using independent two-sample t-test, by the FSL randomize procedure with 5000 permutations. Although age and disease characteristics were not significantly different between groups, they were included as covariates to avoid any interference. Correction for multiple comparisons was carried out using a cluster-based thresholding method (p b 0.01 with 100 contiguous voxels). To label fiber locations, the coordinates of the clusters' peak points were referenced by the JHU white-matter atlas and MRI Atlas of Human White Matter, 2nd edition. To investigate whether these differences correlated with disease characteristics, average regional values from significant clusters of the dPD patients were then extracted to perform correlation analysis with the scale scores. 3. Results
2.2. Acquisition parameters 3.1. Demographic data All the scans were performed on a 3.0 T GE Signa MR scanner in the Department of Radiology, Second Affiliated Hospital of Zhejiang University. Ear plugs and foam pads were used to reduce noise and head motion. High resolution axial T1- and T2-weighted anatomic images were first obtained to exclude any dormant neurologic diseases. Diffusion tensor imaging was acquired using a GRE-EPI sequence. The scan parameters were as follows: repetition time = 12,000 ms; echo time = 105 ms; acquisition matrix = 128 × 128; field of view = 240 mm × 240 mm; slice thickness = 3 mm, no gap; and 37 contiguous axial slices. Diffusion images were acquired from 31 gradient directions (b = 1000 s/mm2) with an acquisition without diffusion weighting (b = 0). 2.3. Data processing Diffusion-weighted images were analyzed using the brain fMRI software library (FSL, version 4.1.0; http://www.fmrib.ox.ac.uk/fsl). The original data were first converted to compressed FSL NIFTI format. Then skull stripping was performed using the brain extraction toolbox. After eddy current correction, diffusion tensors were reconstructed and diffusion parameters were calculated. The resulting FA images were
Table 1 Demographic data.
Age (y) M/F Education (y) Duration (y) UPDRS H&Y Side of onset (L/R) HRSD MMSE **
dPD
ndPD
P
54.5 ± 12.2 9/6 8.7 ± 3.1 5.3 ± 4.8 54.6 ± 23.7 2.7 ± 0.8 5/10 19.9 ± 7.4 26.9 ± 3.2
54.8 ± 10.1 9/6 9.3 ± 4.4 4.2 ± 4.0 45.3 ± 26.1 2.5 ± 1 8/7 2.3 ± 1.8 25.1 ± 5.7
0.948 1.000 0.635 0.470 0.317 0.687 0.462 0.000** 0.297
indicates statistical difference between the two groups.
As shown in Table 1, there was no difference in age, gender, or education between the two groups. Disease characteristics such as duration, Hoehn–Yahr stages, side-of-onset, UPDRS scores and MMSE scores were also not different between the two groups. The only difference was the HRSD score. In all PD patients, the correlation between HRSD score and UPDRS score was not statistically significant (Pearson correlation, r = 0.284, p = 0.289), nor was it significant for age (r = − 0.055, p = 0.774), MMSE (r = 0.106, p = 0.576), and duration (r = 0.117, p = 0.537). 3.2. Imaging results Comparison between the two groups revealed lower FA in several brain regions in the dPD group (Fig. 1, Table 2). Damaged fibers were located in the left uncinate fasciculus (UF), the left superior longitudinal fasciculus (SLF), left anterior thalamic radiation, left forceps minor and the inferior longitudinal fasciculus. Subsequent ROI analysis showed that the FA values in the deep temporal cortex of the dPD group were negatively correlated with HRSD scores (Pearson correlation, r = −0.542, p = 0.037, Fig. 2). However, no other correlation was found between the disease characteristics (age, duration, UPDRS, MMSE) and FA of this cluster. After controlling for other factors, partial correlation between regional FA and HRSD was more robust (r = −0.671, p = 0.034). Comparison of MD maps revealed no differences between the two groups. 4. Discussion To the best of our knowledge, this is the first study investigating whole brain white matter integrity in dPD patients using DTI and TBSS methods. Besides the regions reported in previous studies on dPD patients, we also found degenerations in several important fibers, such as the UF and the SLF. These results are consistent with our hypothesis that disruption of white matter integrity in certain fibers may contribute to depression in PD.
Please cite this article as: Huang P, et al, Disrupted white matter integrity in depressed versus non-depressed Parkinson's disease patients: A tractbased spatial statistics study, J Neurol Sci (2014), http://dx.doi.org/10.1016/j.jns.2014.08.011
P. Huang et al. / Journal of the Neurological Sciences xxx (2014) xxx–xxx
3
Fig. 1. Damaged fibers in dPD patients. Blue indicates brain regions where dPD patients showed lower FA values compared with that of ndPD patients. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.).
White matter volume reduction in the orbitofrontal area of dPD patients has previously been reported by Kostić [25]. Here we found reduced FA in this area, confirming its role in dPD. The orbitofrontal cortex connects with various sensory areas, such as the visual cortex and the somatic sensory cortex. Neurons in the orbitofrontal network respond to multimodal sensory stimuli and are responsible for assessing the value of those stimuli [26]. Malfunction of this area may cause disturbance in decision making and evaluation of emotional stimuli [27], giving rise to various psychotic disorders, such as depression, and borderline personality [28]. It has been reported that patients with orbitofrontal lesions often exhibit disinhibited or inappropriate behaviors and emotional changes [29]. Here we revealed white matter deficits in this area, suggesting that abnormal sensory integration and evaluation might be an important reason for dPD. We also detected sites of damage in the UF, which connects the frontal lobe and subcortical structures, indicating reduced fronto-subcortical communication in dPD patients. The fronto-subcortical decoupling hypothesis is a popular theory used to explain the neural mechanism underlying depression [14]. It has been suggested that impaired communication between the frontal lobe and subcortical regions may impede top-down controls, resulting in unmodulated activities in the lower regions such as the amygdala, causing emotional disturbances. Many neuroimaging studies have provided evidence for this theory. Zhang et al. [21] quantitatively measured UF in MDD patients and healthy control subjects, and found significantly decreased fractional anisotropy of the UF in MDD patients. Disease severity is also associated with reduced number of UF fibers. Jiao et al. [30] measured correlations between activities of the frontal cortex and the limbic-striatal regions, which revealed an increased imbalance between the two areas. Furthermore, alleviation of depressive symptoms is related to balanced activities of these regions [31].
While some studies in PD patients suggest reduced FA in the local frontal areas, the integrity of the UF in dPD was only evaluated in one study, by Surdhar et al. [20]. This diffusion tensor imaging study tracked UF in PD patients with mild depressive symptoms. FA, MD and length values of the reconstructed fibers were used to explore the difference between groups. The results showed that the uncinate UF was intact in dPD patients compared with ndPD patients. However, several weaknesses in the study limited its validity. The sample size was small, with only 6 dPD and 6 ndPD patients. Diffusion images were acquired from only 6 directions. In addition, the use of whole tract average FA may ignore minor changes in the fiber path. In our study, a larger sample size and better comparison method enabled us to reveal the degenerations in the UF. This finding suggests that dPD may share a similar frontolimbic decoupling mechanism with MDD. Furthermore, negative correlation between disease severity and FA decrease was found at the deep temporal white matter. This cluster is near the left amygdala, probably reflecting deficits in fibers projected into, or from, the amygdala. As mentioned above, communication between higher cortices and the amygdala is critical for assessing stimuli and regulating emotions. With more severely damaged fibers in this
Table 2 TBSS results showing differential regions between the dPD and ndPD group. Fibers
Voxels
Peak p
MNI coordinates
Nearest gray matter
UF, ILF UF ATR, SLF SLF SLF ATR, UF FM, UF, ATR ILF
899 293 786 511 249 252 103 134
0.001 0.002 0.000 0.002 0.001 0.001 0.001 0.001
−24 21 13 −28 30 −8 −32 22 23 −17 32 33 −36 0 33 −27 34 21 −12 49 −14 −37 5 −32
– Orbitofrontal gyrus Middle frontal gyrus Superior frontal gyrus Precentral gyrus Middle frontal gyrus Orbitofrontal gyrus Inferior temporal gyrus
(UF: uncinate fasciculus, ILF: inferior longitudinal fasciculus, ATR: anterior thalamic radiation, SLF: superior longitudinal fasciculus, FM: forceps minor).
Fig. 2. Fractional anisotropy in the deep left temporal white matter of the dPD patients negatively correlates with HRSD score (r = −0.542, p = 0.037).
Please cite this article as: Huang P, et al, Disrupted white matter integrity in depressed versus non-depressed Parkinson's disease patients: A tractbased spatial statistics study, J Neurol Sci (2014), http://dx.doi.org/10.1016/j.jns.2014.08.011
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region, which leads to decreased communications, emotional activities may be more disturbed. The fact that FA in this region did not correlate with other disease factors suggests that it is depression-specific. We also found degenerated fibers which were not reported in previous ROI studies, such as the left SLF. The SLF is a major brain bundle connecting the frontal lobe and posterior regions. Degeneration in the SLF has been frequently reported in MDD. A recent meta-analysis showed consistent FA decrease in the SLF of patients with MDD compared with healthy subjects [32]. Negative correlations between SLF damage and depression severity were also found [32]. The current findings of decreased FA in the SLF, near the middle and superior frontal lobe, suggest that dorsolateral prefrontal circuits were damaged in dPD patients. These types of damage may underlie the abnormal cognitive and executive functions that commonly exist in depressed patients [33]. In summary, we found disrupted fibers widely across the anterior part of the left hemisphere. These results are in agreement with previous concepts that depression and anxiety are associated with left frontal lobe dysfunction [34], and the evidence that PD patients with right onset are prone to depression [35]. While white matter involvement in PD patients is common [17], the lesion location may be very important for the occurrence of depression. Our research provides some insight into this issue, which may potentially help with the diagnosis and treatment of depression in PD. A major limitation of the present study is the small sample size, and that depression was postmorbid in all our patients, thus increasing the probability of finding “reactive” changes. Therefore, it should be pointed out that the fiber deficits we found may either be the result of right-onset effect, or inherent deficits of these subjects. More sophisticated experimental designs and a larger sample size are needed in future studies to disentangle these two factors. Conflict of interest We declare no conflict of interest. Acknowledgments This work was supported by the Key Projects in the National Science & Technology Pillar Program during the Twelfth Five-Year Plan Period (No. 2012BAI10B04), National Natural Science Foundation of China (Nos. 81301190 & 81371519), Zhejiang Provincial Natural Science Foundation of China (LY12H18002 & LY12H09006), Scientific Research Project of Zhejiang Province (2011C37025), Medical Scientific Research Foundation of Zhejiang Province (2009QN005). References [1] Chaudhuri KR, Healy D, Schapira A. Non-motor symptoms of Parkinson's disease. Diagnosis and management. Lancet Neurol 2006;5:235–45. [2] Moussavi S, Chatterji S, Verdes E, Tandon A, Patel V, Ustun B. Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet 2007;370:851–8. [3] Blonder LX, Slevin JT. Emotional dysfunction in Parkinson's disease. Behav Neurol 2011;24:201–17. [4] Mayberg HS, Starkstein SE, Sadzot B, Preziosi T, Andrezejewski PL, Dannals RF, et al. Selective hypometabolism in the inferior frontal lobe in depressed patients with Parkinson's disease. Ann Neurol 1990;28:57–64. [5] Ring H, Bench C, Trimble M, Brooks D, Frackowiak R, Dolan R. Depression in Parkinson's disease. A positron emission study. Br J Psychiatry 1994;165:333–9. [6] Matsui H, Nishinaka K, Oda M, Komatsu K, Kubori T, Udaka F. Minor depression and brain perfusion images in Parkinson's disease. Mov Disord 2006;21:1169–74. [7] Remy P, Doder M, Lees A, Turjanski N, Brooks D. Depression in Parkinson's disease: loss of dopamine and noradrenaline innervation in the limbic system. Brain 2005; 128:1314–22.
[8] Strecker K, Wegner F, Hesse S, Becker GA, Patt M, Meyer PM, et al. Preserved serotonin transporter binding in de novo Parkinson's disease: negative correlation with the dopamine transporter. J Neurol 2011;258:19–26. [9] Ballanger B, Klinger H, Eche J, Lerond J, Vallet AE, Le Bars D, et al. Role of serotonergic 1A receptor dysfunction in depression associated with Parkinson's disease. Mov Disord 2012;27:84–9. [10] Li W, Liu J, Skidmore F, Liu Y, Tian J, Li K. White matter microstructure changes in the thalamus in Parkinson disease with depression: a diffusion tensor MR imaging study. Am J Neuroradiol 2010;31:1861–6. [11] Cardoso EF, Maia FM, Fregni F, Myczkowski ML, Melo LM, Sato JR, et al. Depression in Parkinson's disease: convergence from voxel-based morphometry and functional magnetic resonance imaging in the limbic thalamus. Neuroimage 2009;47:467–72. [12] Feldmann A, Illes Z, Kosztolanyi P, Illes E, Mike A, Kover F, et al. Morphometric changes of gray matter in Parkinson's disease with depression: a voxel-based morphometry study. Mov Disord 2008;23:42–6. [13] Kostic VS, Filippi M. Neuroanatomical correlates of depression and apathy in Parkinson's disease: magnetic resonance imaging studies. J Neurol Sci 2011;310: 61–3. [14] DeRubeis RJ, Siegle GJ, Hollon SD. Cognitive therapy versus medication for depression: treatment outcomes and neural mechanisms. Nat Rev Neurosci 2008;9: 788–96. [15] Disner SG, Beevers CG, Haigh EAP, Beck AT. Neural mechanisms of the cognitive model of depression. Nat Rev Neurosci 2011;12:467–77. [16] Liao Y, Huang X, Wu Q, Yang C, Kuang W, Du M, et al. Is depression a disconnection syndrome? Meta-analysis of diffusion tensor imaging studies in patients with MDD. J Psychiatry Neurosci 2012;37:110180. [17] Gattellaro G, Minati L, Grisoli M, Mariani C, Carella F, Osio M, et al. White matter involvement in idiopathic Parkinson disease: a diffusion tensor imaging study. Am J Neuroradiol 2009;30:1222–6. [18] Matsui H, Nishinaka K, Oda M, Niikawa H, Komatsu K, Kubori T, et al. Depression in Parkinson's disease. J Neurol 2007;254:1170–3. [19] Petrovic IN, Stefanova E, Kozic D, Semnic R, Markovic V, Daragasevic NT, et al. White matter lesions and depression in patients with Parkinson's disease. J Neurol Sci 2012;22:132–6. [20] Surdhar I, Gee M, Bouchard T, Coupland N, Malykhin N, Camicioli R. Intact limbicprefrontal connections and reduced amygdala volumes in Parkinson's disease with mild depressive symptoms. Parkinsonism Relat Disord 2012;18:809–13. [21] Zhang A, Leow A, Ajilore O, Lamar M, Yang S, Joseph J, et al. Quantitative tractspecific measures of uncinate and cingulum in major depression using diffusion tensor imaging. Neuropsychopharmacology 2011;37:959–67. [22] Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 2006;31:1487–505. [23] Qiu Y, Jiang G, Su H, Lv X, Zhang X, Tian J, et al. Progressive white matter microstructure damage in male chronic heroin dependent individuals: A DTI and TBSS study. PLoS One 2013;8:e63212. [24] Kieseppä T, Eerola M, Mäntylä R, Neuvonen T, Poutanen V-P, Luoma K, et al. Major depressive disorder and white matter abnormalities: a diffusion tensor imaging study with tract-based spatial statistics. J Affect Disord 2010;120:240–4. [25] Kostić V, Agosta F, Petrović I, Galantucci S, Špica V, Ječmenica-Lukic M, et al. Regional patterns of brain tissue loss associated with depression in Parkinson disease. Neurology 2010;75:857–63. [26] Rolls ET. Convergence of sensory systems in the orbitofrontal cortex in primates and brain design for emotion. Anat Rec A Discov Mol Cell Evol Biol 2004;281:1212–25. [27] Bechara A, Damasio H, Damasio AR. Emotion, decision making and the orbitofrontal cortex. Cereb Cortex 2000;10:295–307. [28] Berlin HA, Rolls ET, Iversen SD. Borderline personality disorder, impulsivity, and the orbitofrontal cortex. Am J Psychiatry 2005;162:2360–73. [29] Berlin H, Rolls E, Kischka U. Impulsivity, time perception, emotion and reinforcement sensitivity in patients with orbitofrontal cortex lesions. Brain 2004;127: 1108–26. [30] Jiao Q, Ding J, Lu G, Su L, Zhang Z, Wang Z, et al. Increased activity imbalance in fronto-subcortical circuits in adolescents with major depression. PLoS One 2011;6: e25159. [31] Buchheim A, Viviani R, Kessler H, Kächele H, Cierpka M, Roth G, et al. Changes in prefrontal-limbic function in major depression after 15 months of long-term psychotherapy. PLoS One 2012;7:e33745. [32] Murphy ML, Frodl T. Meta-analysis of diffusion tensor imaging studies shows altered fractional anisotropy occurring in distinct brain areas in association with depression. Biol Mood Anxiety Disord 2011;1:1–12. [33] Rogers MA, Kasai K, Koji M, Fukuda R, Iwanami A, Nakagome K, et al. Executive and prefrontal dysfunction in unipolar depression: a review of neuropsychological and imaging evidence. Neurosci Res 2004;50:1–11. [34] Hama S, Yamashita H, Shigenobu M, Watanabe A, Kurisu K, Yamawaki S, et al. Poststroke affective or apathetic depression and lesion location: left frontal lobe and bilateral basal ganglia. Eur Arch Psychiatry Clin Neurosci 2007;257:149–52. [35] Foster PS, Drago V, Crucian GP, Sullivan WK, Rhodes RD, Shenal BV, et al. Anxiety and depression severity are related to right but not left onset Parkinson's disease duration. J Neurol Sci 2011;305:131–5.
Please cite this article as: Huang P, et al, Disrupted white matter integrity in depressed versus non-depressed Parkinson's disease patients: A tractbased spatial statistics study, J Neurol Sci (2014), http://dx.doi.org/10.1016/j.jns.2014.08.011
Contents lists available at ScienceDirect
Journal of the Neurological Sciences journal homepage: www.elsevier.com/locate/jns
Disrupted white matter integrity in depressed versus non-depressed Parkinson's disease patients: A tract-based spatial statistics study Peiyu Huang a,1, Xiaojun Xu a,1, Quanquan Gu a, Min Xuan a, Xinfeng Yu a, Wei Luo b, Minming Zhang a,⁎ a b
Department of Radiology, 2nd Affiliated Hospital, Zhejiang University School of Medicine, China Department of Neurology, 2nd Affiliated Hospital, Zhejiang University School of Medicine, China
a r t i c l e
i n f o
Article history: Received 8 February 2014 Received in revised form 25 July 2014 Accepted 8 August 2014 Available online xxxx Keywords: Parkinson's disease Depression Diffusion tensor imaging
a b s t r a c t Depression is a common occurrence in patients with Parkinson's disease (PD), however, its pathophysiology still remains unclear. With increasing evidence suggesting that depression is a disconnection syndrome, we hypothesized that depression in PD is caused by degenerated fiber connections in the brain. We examined whole brain white matter integrity in 15 depressed PD patients and 15 non-depressed PD patients. All the patients were assessed with the Unified Parkinson's Disease Rating Scale, the Hamilton Rating Scale for Depression, and the Mini-Mental State Examination. White matter difference between the two groups and its correlation with disease severity was calculated. In depressed PD patients, decreased fractional anisotropy was found in the left uncinate fasciculus, superior longitudinal fasciculus, anterior thalamic radiation, forceps minor, and the inferior longitudinal fasciculus. Fractional anisotropy in the left deep temporal cortex was negatively correlated with severity of depression (r = −0.671, p = 0.034). Our results suggest that disrupted fiber connections in the anterior part of the left hemisphere may contribute to depression in PD patients. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Parkinson's disease (PD) is frequently accompanied by depressive symptoms [1,2]. Depression can cause functional impairment in PD patients and further reduce their quality of life. The pathophysiological relationship between PD and depression is complicated. Although the negative feelings brought about by disabling symptoms is an important factor, a lot of evidence suggests some underlying brain pathology [3]. The advancement of modern imaging methods has provided useful tools for looking into the neural basis of depression in PD. Early studies using positron emission tomography (PET) found reduced cerebral blood flow in the frontal lobe, cingulate gyrus and caudate in depressed PD (dPD) patients compared with non-depressed PD (ndPD) patients [4–6]. Degeneration of the neurotransmitter systems, especially dopamine and serotonin signaling, was also implicated in PET studies [7–9]. With the application of magnetic resonance imaging (MRI), alterations of cortical gray matter and sub-cortical structures were further revealed in several studies [10–12]. In addition to abnormalities in local areas, fiber connections among different brain regions may also contribute to depression in PD [13]. As emotional regulation involves several brain structures, disrupted
⁎ Corresponding author at: Department of Radiology, 2nd Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District. Hangzhou 310009, China. Tel./fax: +86 0571 87315255. E-mail address: [email protected] (M. Zhang). 1 These two authors contribute equally to this paper.
communications between these structures may lead to uncoordinated and disoriented activities [14,15]. Recent studies on depressed patients in the general population have confirmed that a disturbed emotional network is one underlying cause for the occurrence of depression [16]. Since white matter degeneration is common in PD patients [17], they may also affect emotion-related networks, which may cause depression. Some previous studies have tried to investigate white matter changes in dPD patients. Fractional anisotropy (FA) in the anterior cingulate bundle [18] was found to be reduced in dPD patients compared with that of ndPD patients. White matter hyperintensity in the deep periventricular region was also related to dPD [19]. Despite these findings, some studies did not support white matter deficits. A recent tractography study found no difference in the uncinate fasciculus and corpus callosum between dPD and ndPD patients [20], which are frequently damaged in major depressive disorder (MDD) patients [21]. A potential confounding factor here is that previous studies used region of interest (ROI)-based analysis, by which the derived results were dependent largely on subjective selections. Until now, there was a lack of unbiased automated whole brain inspection of white matter degenerations in dPD patients. In the present study, we performed an investigation on whole brain white matter integrity in dPD patients relative to that of the ndPD patients, by using diffusion tensor imaging (DTI) and tract-based spatial statistics (TBSS) analysis. TBSS is a method proposed by Smith et al. [22]. By using a FA skeleton template derived from a specific research cohort, TBSS can normalize FA images from different subjects with higher precision compared with traditional procedures. Because of this advantage,
http://dx.doi.org/10.1016/j.jns.2014.08.011 0022-510X/© 2014 Elsevier B.V. All rights reserved.
Please cite this article as: Huang P, et al, Disrupted white matter integrity in depressed versus non-depressed Parkinson's disease patients: A tractbased spatial statistics study, J Neurol Sci (2014), http://dx.doi.org/10.1016/j.jns.2014.08.011
2
P. Huang et al. / Journal of the Neurological Sciences xxx (2014) xxx–xxx
TBSS has become a widely used method in DTI studies of neuropsychiatric diseases [23,24]. Here we hypothesize that dPD patients may have deficits in certain white matter tracts, such as the uncinate fasciculus and superior longitudinal fasciculus. 2. Materials and methods 2.1. Subjects Two groups of PD patients (with and without depression, 15 for each group) were recruited from the Department of Neurology, Zhejiang University School of Medicine. Diagnosis of PD was made according to UK PD Brain Bank criteria. Unipolar depression was diagnosed according to the DSM-IV criteria by an experienced psychiatrist. The psychiatrist gathered detailed patient history of the two disease symptoms and decided whether depression was premorbid or postmorbid. For the 15 patients, depression was all diagnosed as postmorbid, and they had not received pharmaceutical treatments before scanning. Scores of the Unified Parkinson's Disease Rating Scale (UPDRS), the Hamilton Rating Scale for Depression (HRSD), and the Mini-Mental State Examination (MMSE) were obtained from all subjects. Anti-parkinsonian medicine was terminated at least 12 h prior to the imaging scans. Table 1 shows detailed characteristics of the two groups. For exclusion criteria, we ruled out any subjects who had other neurologic or psychiatric disorders, or brain trauma at any time of their lives. All the subjects had signed written informed consent before taking part in the study. This research was approved by the Medical Ethic Committee of the Second Affiliated Hospital, Zhejiang University School of Medicine.
further processed using TBSS, which performs voxel-by-voxel wholebrain analysis. After aligning all of the individual FA images to the standard space template using nonlinear registration, the mean FA image was calculated and compressed to form a mean skeleton representing topological features of all tracts derived from the whole group. An FA threshold of 0.3 was set to remove trivial tracts. Finally, each subject's aligned FA images were projected onto the fiber skeleton template to perform statistical analysis. Mean diffusivity (MD) was also normalized to the skeleton using TBSS. 2.4. Statistical analysis Age, education, disease duration and scale scores were compared between the two groups using two-sample t-test. Chi-square tests were performed to compare the sex and side-of-onset differences. The image data were analyzed using independent two-sample t-test, by the FSL randomize procedure with 5000 permutations. Although age and disease characteristics were not significantly different between groups, they were included as covariates to avoid any interference. Correction for multiple comparisons was carried out using a cluster-based thresholding method (p b 0.01 with 100 contiguous voxels). To label fiber locations, the coordinates of the clusters' peak points were referenced by the JHU white-matter atlas and MRI Atlas of Human White Matter, 2nd edition. To investigate whether these differences correlated with disease characteristics, average regional values from significant clusters of the dPD patients were then extracted to perform correlation analysis with the scale scores. 3. Results
2.2. Acquisition parameters 3.1. Demographic data All the scans were performed on a 3.0 T GE Signa MR scanner in the Department of Radiology, Second Affiliated Hospital of Zhejiang University. Ear plugs and foam pads were used to reduce noise and head motion. High resolution axial T1- and T2-weighted anatomic images were first obtained to exclude any dormant neurologic diseases. Diffusion tensor imaging was acquired using a GRE-EPI sequence. The scan parameters were as follows: repetition time = 12,000 ms; echo time = 105 ms; acquisition matrix = 128 × 128; field of view = 240 mm × 240 mm; slice thickness = 3 mm, no gap; and 37 contiguous axial slices. Diffusion images were acquired from 31 gradient directions (b = 1000 s/mm2) with an acquisition without diffusion weighting (b = 0). 2.3. Data processing Diffusion-weighted images were analyzed using the brain fMRI software library (FSL, version 4.1.0; http://www.fmrib.ox.ac.uk/fsl). The original data were first converted to compressed FSL NIFTI format. Then skull stripping was performed using the brain extraction toolbox. After eddy current correction, diffusion tensors were reconstructed and diffusion parameters were calculated. The resulting FA images were
Table 1 Demographic data.
Age (y) M/F Education (y) Duration (y) UPDRS H&Y Side of onset (L/R) HRSD MMSE **
dPD
ndPD
P
54.5 ± 12.2 9/6 8.7 ± 3.1 5.3 ± 4.8 54.6 ± 23.7 2.7 ± 0.8 5/10 19.9 ± 7.4 26.9 ± 3.2
54.8 ± 10.1 9/6 9.3 ± 4.4 4.2 ± 4.0 45.3 ± 26.1 2.5 ± 1 8/7 2.3 ± 1.8 25.1 ± 5.7
0.948 1.000 0.635 0.470 0.317 0.687 0.462 0.000** 0.297
indicates statistical difference between the two groups.
As shown in Table 1, there was no difference in age, gender, or education between the two groups. Disease characteristics such as duration, Hoehn–Yahr stages, side-of-onset, UPDRS scores and MMSE scores were also not different between the two groups. The only difference was the HRSD score. In all PD patients, the correlation between HRSD score and UPDRS score was not statistically significant (Pearson correlation, r = 0.284, p = 0.289), nor was it significant for age (r = − 0.055, p = 0.774), MMSE (r = 0.106, p = 0.576), and duration (r = 0.117, p = 0.537). 3.2. Imaging results Comparison between the two groups revealed lower FA in several brain regions in the dPD group (Fig. 1, Table 2). Damaged fibers were located in the left uncinate fasciculus (UF), the left superior longitudinal fasciculus (SLF), left anterior thalamic radiation, left forceps minor and the inferior longitudinal fasciculus. Subsequent ROI analysis showed that the FA values in the deep temporal cortex of the dPD group were negatively correlated with HRSD scores (Pearson correlation, r = −0.542, p = 0.037, Fig. 2). However, no other correlation was found between the disease characteristics (age, duration, UPDRS, MMSE) and FA of this cluster. After controlling for other factors, partial correlation between regional FA and HRSD was more robust (r = −0.671, p = 0.034). Comparison of MD maps revealed no differences between the two groups. 4. Discussion To the best of our knowledge, this is the first study investigating whole brain white matter integrity in dPD patients using DTI and TBSS methods. Besides the regions reported in previous studies on dPD patients, we also found degenerations in several important fibers, such as the UF and the SLF. These results are consistent with our hypothesis that disruption of white matter integrity in certain fibers may contribute to depression in PD.
Please cite this article as: Huang P, et al, Disrupted white matter integrity in depressed versus non-depressed Parkinson's disease patients: A tractbased spatial statistics study, J Neurol Sci (2014), http://dx.doi.org/10.1016/j.jns.2014.08.011
P. Huang et al. / Journal of the Neurological Sciences xxx (2014) xxx–xxx
3
Fig. 1. Damaged fibers in dPD patients. Blue indicates brain regions where dPD patients showed lower FA values compared with that of ndPD patients. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.).
White matter volume reduction in the orbitofrontal area of dPD patients has previously been reported by Kostić [25]. Here we found reduced FA in this area, confirming its role in dPD. The orbitofrontal cortex connects with various sensory areas, such as the visual cortex and the somatic sensory cortex. Neurons in the orbitofrontal network respond to multimodal sensory stimuli and are responsible for assessing the value of those stimuli [26]. Malfunction of this area may cause disturbance in decision making and evaluation of emotional stimuli [27], giving rise to various psychotic disorders, such as depression, and borderline personality [28]. It has been reported that patients with orbitofrontal lesions often exhibit disinhibited or inappropriate behaviors and emotional changes [29]. Here we revealed white matter deficits in this area, suggesting that abnormal sensory integration and evaluation might be an important reason for dPD. We also detected sites of damage in the UF, which connects the frontal lobe and subcortical structures, indicating reduced fronto-subcortical communication in dPD patients. The fronto-subcortical decoupling hypothesis is a popular theory used to explain the neural mechanism underlying depression [14]. It has been suggested that impaired communication between the frontal lobe and subcortical regions may impede top-down controls, resulting in unmodulated activities in the lower regions such as the amygdala, causing emotional disturbances. Many neuroimaging studies have provided evidence for this theory. Zhang et al. [21] quantitatively measured UF in MDD patients and healthy control subjects, and found significantly decreased fractional anisotropy of the UF in MDD patients. Disease severity is also associated with reduced number of UF fibers. Jiao et al. [30] measured correlations between activities of the frontal cortex and the limbic-striatal regions, which revealed an increased imbalance between the two areas. Furthermore, alleviation of depressive symptoms is related to balanced activities of these regions [31].
While some studies in PD patients suggest reduced FA in the local frontal areas, the integrity of the UF in dPD was only evaluated in one study, by Surdhar et al. [20]. This diffusion tensor imaging study tracked UF in PD patients with mild depressive symptoms. FA, MD and length values of the reconstructed fibers were used to explore the difference between groups. The results showed that the uncinate UF was intact in dPD patients compared with ndPD patients. However, several weaknesses in the study limited its validity. The sample size was small, with only 6 dPD and 6 ndPD patients. Diffusion images were acquired from only 6 directions. In addition, the use of whole tract average FA may ignore minor changes in the fiber path. In our study, a larger sample size and better comparison method enabled us to reveal the degenerations in the UF. This finding suggests that dPD may share a similar frontolimbic decoupling mechanism with MDD. Furthermore, negative correlation between disease severity and FA decrease was found at the deep temporal white matter. This cluster is near the left amygdala, probably reflecting deficits in fibers projected into, or from, the amygdala. As mentioned above, communication between higher cortices and the amygdala is critical for assessing stimuli and regulating emotions. With more severely damaged fibers in this
Table 2 TBSS results showing differential regions between the dPD and ndPD group. Fibers
Voxels
Peak p
MNI coordinates
Nearest gray matter
UF, ILF UF ATR, SLF SLF SLF ATR, UF FM, UF, ATR ILF
899 293 786 511 249 252 103 134
0.001 0.002 0.000 0.002 0.001 0.001 0.001 0.001
−24 21 13 −28 30 −8 −32 22 23 −17 32 33 −36 0 33 −27 34 21 −12 49 −14 −37 5 −32
– Orbitofrontal gyrus Middle frontal gyrus Superior frontal gyrus Precentral gyrus Middle frontal gyrus Orbitofrontal gyrus Inferior temporal gyrus
(UF: uncinate fasciculus, ILF: inferior longitudinal fasciculus, ATR: anterior thalamic radiation, SLF: superior longitudinal fasciculus, FM: forceps minor).
Fig. 2. Fractional anisotropy in the deep left temporal white matter of the dPD patients negatively correlates with HRSD score (r = −0.542, p = 0.037).
Please cite this article as: Huang P, et al, Disrupted white matter integrity in depressed versus non-depressed Parkinson's disease patients: A tractbased spatial statistics study, J Neurol Sci (2014), http://dx.doi.org/10.1016/j.jns.2014.08.011
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P. Huang et al. / Journal of the Neurological Sciences xxx (2014) xxx–xxx
region, which leads to decreased communications, emotional activities may be more disturbed. The fact that FA in this region did not correlate with other disease factors suggests that it is depression-specific. We also found degenerated fibers which were not reported in previous ROI studies, such as the left SLF. The SLF is a major brain bundle connecting the frontal lobe and posterior regions. Degeneration in the SLF has been frequently reported in MDD. A recent meta-analysis showed consistent FA decrease in the SLF of patients with MDD compared with healthy subjects [32]. Negative correlations between SLF damage and depression severity were also found [32]. The current findings of decreased FA in the SLF, near the middle and superior frontal lobe, suggest that dorsolateral prefrontal circuits were damaged in dPD patients. These types of damage may underlie the abnormal cognitive and executive functions that commonly exist in depressed patients [33]. In summary, we found disrupted fibers widely across the anterior part of the left hemisphere. These results are in agreement with previous concepts that depression and anxiety are associated with left frontal lobe dysfunction [34], and the evidence that PD patients with right onset are prone to depression [35]. While white matter involvement in PD patients is common [17], the lesion location may be very important for the occurrence of depression. Our research provides some insight into this issue, which may potentially help with the diagnosis and treatment of depression in PD. A major limitation of the present study is the small sample size, and that depression was postmorbid in all our patients, thus increasing the probability of finding “reactive” changes. Therefore, it should be pointed out that the fiber deficits we found may either be the result of right-onset effect, or inherent deficits of these subjects. More sophisticated experimental designs and a larger sample size are needed in future studies to disentangle these two factors. Conflict of interest We declare no conflict of interest. Acknowledgments This work was supported by the Key Projects in the National Science & Technology Pillar Program during the Twelfth Five-Year Plan Period (No. 2012BAI10B04), National Natural Science Foundation of China (Nos. 81301190 & 81371519), Zhejiang Provincial Natural Science Foundation of China (LY12H18002 & LY12H09006), Scientific Research Project of Zhejiang Province (2011C37025), Medical Scientific Research Foundation of Zhejiang Province (2009QN005). References [1] Chaudhuri KR, Healy D, Schapira A. Non-motor symptoms of Parkinson's disease. Diagnosis and management. Lancet Neurol 2006;5:235–45. [2] Moussavi S, Chatterji S, Verdes E, Tandon A, Patel V, Ustun B. Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet 2007;370:851–8. [3] Blonder LX, Slevin JT. Emotional dysfunction in Parkinson's disease. Behav Neurol 2011;24:201–17. [4] Mayberg HS, Starkstein SE, Sadzot B, Preziosi T, Andrezejewski PL, Dannals RF, et al. Selective hypometabolism in the inferior frontal lobe in depressed patients with Parkinson's disease. Ann Neurol 1990;28:57–64. [5] Ring H, Bench C, Trimble M, Brooks D, Frackowiak R, Dolan R. Depression in Parkinson's disease. A positron emission study. Br J Psychiatry 1994;165:333–9. [6] Matsui H, Nishinaka K, Oda M, Komatsu K, Kubori T, Udaka F. Minor depression and brain perfusion images in Parkinson's disease. Mov Disord 2006;21:1169–74. [7] Remy P, Doder M, Lees A, Turjanski N, Brooks D. Depression in Parkinson's disease: loss of dopamine and noradrenaline innervation in the limbic system. Brain 2005; 128:1314–22.
[8] Strecker K, Wegner F, Hesse S, Becker GA, Patt M, Meyer PM, et al. Preserved serotonin transporter binding in de novo Parkinson's disease: negative correlation with the dopamine transporter. J Neurol 2011;258:19–26. [9] Ballanger B, Klinger H, Eche J, Lerond J, Vallet AE, Le Bars D, et al. Role of serotonergic 1A receptor dysfunction in depression associated with Parkinson's disease. Mov Disord 2012;27:84–9. [10] Li W, Liu J, Skidmore F, Liu Y, Tian J, Li K. White matter microstructure changes in the thalamus in Parkinson disease with depression: a diffusion tensor MR imaging study. Am J Neuroradiol 2010;31:1861–6. [11] Cardoso EF, Maia FM, Fregni F, Myczkowski ML, Melo LM, Sato JR, et al. Depression in Parkinson's disease: convergence from voxel-based morphometry and functional magnetic resonance imaging in the limbic thalamus. Neuroimage 2009;47:467–72. [12] Feldmann A, Illes Z, Kosztolanyi P, Illes E, Mike A, Kover F, et al. Morphometric changes of gray matter in Parkinson's disease with depression: a voxel-based morphometry study. Mov Disord 2008;23:42–6. [13] Kostic VS, Filippi M. Neuroanatomical correlates of depression and apathy in Parkinson's disease: magnetic resonance imaging studies. J Neurol Sci 2011;310: 61–3. [14] DeRubeis RJ, Siegle GJ, Hollon SD. Cognitive therapy versus medication for depression: treatment outcomes and neural mechanisms. Nat Rev Neurosci 2008;9: 788–96. [15] Disner SG, Beevers CG, Haigh EAP, Beck AT. Neural mechanisms of the cognitive model of depression. Nat Rev Neurosci 2011;12:467–77. [16] Liao Y, Huang X, Wu Q, Yang C, Kuang W, Du M, et al. Is depression a disconnection syndrome? Meta-analysis of diffusion tensor imaging studies in patients with MDD. J Psychiatry Neurosci 2012;37:110180. [17] Gattellaro G, Minati L, Grisoli M, Mariani C, Carella F, Osio M, et al. White matter involvement in idiopathic Parkinson disease: a diffusion tensor imaging study. Am J Neuroradiol 2009;30:1222–6. [18] Matsui H, Nishinaka K, Oda M, Niikawa H, Komatsu K, Kubori T, et al. Depression in Parkinson's disease. J Neurol 2007;254:1170–3. [19] Petrovic IN, Stefanova E, Kozic D, Semnic R, Markovic V, Daragasevic NT, et al. White matter lesions and depression in patients with Parkinson's disease. J Neurol Sci 2012;22:132–6. [20] Surdhar I, Gee M, Bouchard T, Coupland N, Malykhin N, Camicioli R. Intact limbicprefrontal connections and reduced amygdala volumes in Parkinson's disease with mild depressive symptoms. Parkinsonism Relat Disord 2012;18:809–13. [21] Zhang A, Leow A, Ajilore O, Lamar M, Yang S, Joseph J, et al. Quantitative tractspecific measures of uncinate and cingulum in major depression using diffusion tensor imaging. Neuropsychopharmacology 2011;37:959–67. [22] Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 2006;31:1487–505. [23] Qiu Y, Jiang G, Su H, Lv X, Zhang X, Tian J, et al. Progressive white matter microstructure damage in male chronic heroin dependent individuals: A DTI and TBSS study. PLoS One 2013;8:e63212. [24] Kieseppä T, Eerola M, Mäntylä R, Neuvonen T, Poutanen V-P, Luoma K, et al. Major depressive disorder and white matter abnormalities: a diffusion tensor imaging study with tract-based spatial statistics. J Affect Disord 2010;120:240–4. [25] Kostić V, Agosta F, Petrović I, Galantucci S, Špica V, Ječmenica-Lukic M, et al. Regional patterns of brain tissue loss associated with depression in Parkinson disease. Neurology 2010;75:857–63. [26] Rolls ET. Convergence of sensory systems in the orbitofrontal cortex in primates and brain design for emotion. Anat Rec A Discov Mol Cell Evol Biol 2004;281:1212–25. [27] Bechara A, Damasio H, Damasio AR. Emotion, decision making and the orbitofrontal cortex. Cereb Cortex 2000;10:295–307. [28] Berlin HA, Rolls ET, Iversen SD. Borderline personality disorder, impulsivity, and the orbitofrontal cortex. Am J Psychiatry 2005;162:2360–73. [29] Berlin H, Rolls E, Kischka U. Impulsivity, time perception, emotion and reinforcement sensitivity in patients with orbitofrontal cortex lesions. Brain 2004;127: 1108–26. [30] Jiao Q, Ding J, Lu G, Su L, Zhang Z, Wang Z, et al. Increased activity imbalance in fronto-subcortical circuits in adolescents with major depression. PLoS One 2011;6: e25159. [31] Buchheim A, Viviani R, Kessler H, Kächele H, Cierpka M, Roth G, et al. Changes in prefrontal-limbic function in major depression after 15 months of long-term psychotherapy. PLoS One 2012;7:e33745. [32] Murphy ML, Frodl T. Meta-analysis of diffusion tensor imaging studies shows altered fractional anisotropy occurring in distinct brain areas in association with depression. Biol Mood Anxiety Disord 2011;1:1–12. [33] Rogers MA, Kasai K, Koji M, Fukuda R, Iwanami A, Nakagome K, et al. Executive and prefrontal dysfunction in unipolar depression: a review of neuropsychological and imaging evidence. Neurosci Res 2004;50:1–11. [34] Hama S, Yamashita H, Shigenobu M, Watanabe A, Kurisu K, Yamawaki S, et al. Poststroke affective or apathetic depression and lesion location: left frontal lobe and bilateral basal ganglia. Eur Arch Psychiatry Clin Neurosci 2007;257:149–52. [35] Foster PS, Drago V, Crucian GP, Sullivan WK, Rhodes RD, Shenal BV, et al. Anxiety and depression severity are related to right but not left onset Parkinson's disease duration. J Neurol Sci 2011;305:131–5.
Please cite this article as: Huang P, et al, Disrupted white matter integrity in depressed versus non-depressed Parkinson's disease patients: A tractbased spatial statistics study, J Neurol Sci (2014), http://dx.doi.org/10.1016/j.jns.2014.08.011
