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A subtle grey-matter increase in first-episode, drug-naive major depressive disorder with panic disorder after 6 weeks' duloxetine therapy

Chien-Han Lai, Yuan-Yu Hsu
DOI: http://dx.doi.org/10.1017/S1461145710000829 225-235 First published online: 1 March 2011

Abstract

We designed this study to investigate the modulating effects of duloxetine on symptoms and grey matter of patients with major depressive disorder combined with panic disorder. We also aimed to discover if there was any persistence of grey-matter deficits after remission and to find ‘trait markers’ for this comorbidity. High-resolution magnetic resonance imaging and voxel-based morphometric measurements were performed on 15 patients at baseline and remitted status (week 6) compared to 15 healthy control subjects who were scanned twice within 6 wk. The rating scales of depressive and panic symptoms improved with statistical significance (corrected p<0.001). A widespread pattern of grey-matter deficits in infero-frontal, limbic, occipital, temporo-parietal, cerebellar areas (trait marker regions) in drug-naive patients were observed compared to controls at baseline (family-wise error corrected p<0.0002). There were no significant changes of grey matter in healthy controls over the 6-wk period. Duloxetine-induced increases of grey matter were very subtle in left infero-frontal cortex, right fusiform gyrus, and right cerebellum VIIIa areas (state marker regions) after 6-wk therapy (uncorrected p<0.0005). Duloxetine did not increase grey matter to the level of control subjects and grey-matter deficits in patients appear largely unaffected by duloxetine. We suggest that short-term duloxetine therapy improved the clinical symptoms of patients with major depressive disorder combined with panic disorder. These improvements might be related to a modest increase of grey matter in state marker regions of the brain. The deficits of trait marker regions were more evident and are likely to be important for pathogenesis.

Key words
  • Duloxetine
  • grey matter
  • major depressive disorder
  • panic disorder

Introduction

Major depressive disorder (MDD) has been reported to be associated with grey-matter density (GMD) deficits in many regions, e.g. dorsolateral prefrontal cortex, amygdala, hippocampus and anterior cingulate cortex (Frodl et al. 2008b). Mayberg and colleagues found that MDD patients had higher metabolism in limbic-paralimbic regions and lower metabolism in cortical regions. This suggested that MDD patients had dysfunctional metabolisms in limbic and higher cortical areas (Mayberg et al. 2002). A reciprocal and bi-directional relationship between limbic and neocortical regions also supports the ‘top-down’ and ‘bottom-up’ hypotheses in this disorder (Mayberg et al. 1999). This limbic-paralimbic regulation in emotional and fearful aspects was also replicated by Kempton et al. (2009) . MDD is also associated with distinct patterns of structural and functional abnormalities in the areas of emotional perception. These regions were classified as two systems: (1) ventral system (amygdala, insula, ventral striatum, ventral anterior cingulate gyrus, prefrontal cortex), for identification of the emotional significance of a stimulus, production of affective states, and automatic regulation of emotional responses; and (2) dorsal system (hippocampus, dorsal anterior cingulate gyrus, prefrontal cortex), for the effortful regulation of affective states and subsequent behaviour (Phillips et al. 2003). In several meta-analytical studies of MDD patients (Hamilton et al. 2008; Koolschijn et al. 2009; Videbech & Ravnkilde, 2004), volumetric reductions were observed in frontal cortex, hippocampus, putamen, amygdala, and caudate nucleus. These regions also included the regional differences of brain volumes in MDD, such as hippocampus, amygdala, and prefrontal cortex, although there were some inconsistent reports (Campbell & MacQueen, 2006).

MDD patients with worse clinical outcomes, chronic courses or relapses show further GMD declines compared to those achieving remission during treatment (Frodl et al. 2008 b). This suggested that patients with MDD would have some residual deficits of GMD even after remission. However, some areas of GMD deficits could return to normal after remission, such as prefrontal cortices. Mayberg and colleagues found that fluoxetine was able to reverse the abnormalities in limbic and neocortical regions by increasing activity in neocortical regions and decreasing activity in the limbic system (Mayberg et al. 2000). Antidepressants were found to be associated with an increase of brain structures, such as hippocampal volume (Frodl et al. 2008 a), amygdala volume (Hamilton et al. 2008) and subgenual prefrontal cortex (Yucel et al. 2009). However, there was a study against the neurogenesis effect of antidepressants (Vythilingam et al. 2004). Therefore the impact of antidepressants in MDD brain structure remains controversial. Besides pharmacotherapy, psychotherapy can also produce similar modulations in these regions (Etkin et al. 2005). Even a study of the effect of placebo in MDD patients found similar changes in subcortical and cortical regions with less regions involved (Mayberg et al. 2002). The deep brain stimulation in the ventral limbic system, such as subgenual white matter, can also restore the abnormalities of limbic-cortical circuits in treatment-resistant MDD (Mayberg et al. 2005).

Duloxetine, a serotonin and norepinephrine reuptake inhibitor (SNRI), has been shown to be effective in treating MDD patients (Frampton & Plosker, 2007). Its plasma level is correlated with anxiety and tolerability while receiving duloxetine treatment. The optimal level of duloxetine for anxiolytic effects is usually at the intermediate plasma level (Volonteri et al. 2009). The treatment efficacy of duloxetine is comparable to venlafaxine, a selective serotonin reuptake inhibitor and also a SNRI (Perahia et al. 2008; Thase et al. 2007). However, duloxetine has less adverse events following withdrawal and a lower rise in blood pressure than venlafaxine (Perahia et al. 2008). From the above-mentioned articles, it can be seen that duloxetine is an effective antidepressant for MDD with fewer side-effects than other SNRIs.

There are also several regions of GMD deficits for patients with panic disorder (PD), such as bilateral dorsomedial and right ventromedial prefrontal cortices, right amygdala, anterior cingulate cortex, bilateral insular cortex, occipito-temporal gyrus, and left cerebellar vermis (Asami et al. 2009). Yoo and colleagues also found that PD patients have a grey-matter volume (GMV) decrease over inferior frontal cortex and putamen (Yoo et al. 2005). Part of the limbic system, such as parahippocampal gyrus, was assumed to be abnormal in patients with PD (Massana et al. 2003). Sobanski et al. (2010) found grey-matter loss in nearby regions, such as middle temporal lobe and right frontal cortex. However, Uchida et al. (2008) found a GMD increase in insula and brainstem with a decrease in the right anterior cingulate cortex. Protopopescu et al. (2006) mentioned decreased regional GMV of prefrontal cortex and an increase in brainstem of PD patients. These results support the view that PD has significant deficits of grey-matter or brain-structure volumes compared to healthy controls, although there are some inconsistencies in the literature.

The role of duloxetine in the treatment of PD is still inconclusive. Volonteri and colleagues found a relationship between plasma level and anxiolytic effect (Volonteri et al. 2009). There were just two small sample and open-label studies with significant improvements of panic symptoms and significant anxiolysis (Crippa & Zuardi, 2006; Simon et al. 2009). More randomized controlled studies are needed to confirm the therapeutic effects of duloxetine in PD.

The lifetime prevalences of MDD and PD are highly associated (Kessler et al. 1998). This comorbidity will be associated with more severe symptoms, longer illness duration, treatment resistance, worse outcomes and poorer functions (Grunhaus et al. 1994; Roy-Byrne et al. 2000). Further, comorbid anxiety disorder with MDD is the most powerful clinical factor for treatment-resistant MDD (Souery et al. 2007). The comorbidity between MDD and anxiety disorders is also usually associated with increased suicide attempts (Szadoczky et al. 2000). From these reports, MDD+PD might represent a distinct disorder with a complex syndrome and be more familial-prone (Maier et al. 1995; Mannuzza et al. 1994). The comorbidity should be an important issue for clinical research and treatment. However, there are many research issues unknown in this group of patients, such as brain pathophysiology, duloxetine-modulating effects in brain, any existence of brain defects after remission. We conducted this study to investigate the structural deficits of the brain in MDD+PD patients and the therapeutic effects of duloxetine in the clinical symptoms of the brain. Moreover, the brain pathophysiology of this group of patients and the condition of brain defects after remission will also be addressed.

We hypothesized that duloxetine therapy would improve the symptoms of MDD+PD within 6 wk. We also used magnetic resonance (MR) imaging to survey and compare brain structures of patients at baseline and healthy controls in order to discover the brain pathophysiology of MDD+PD. The remitted patients and healthy controls received a second MR imaging acquisition at week 6. We hoped to compare the images of baseline and remitted status to find our defined ‘state markers’, i.e. the regions with positive changes of GMV after duloxetine therapy with remission within 6 wk. From the above literature review, we hypothesized that duloxetine might improve GMV deficits of patients over several index regions of MDD+PD, such as prefrontal cortices, etc. Healthy controls should have no significant changes of GMV after 6 wk without medication. We also hypothesized that the remitted patients would still have significant GMV deficits, which would be our defined ‘trait markers’. These trait markers represented those regions with GMV deficits after remission of clinical symptoms.

Materials and methods

Participants

This study was approved by Institute of Review Board, Buddhist Tzu-Chi Hospital Taipei Branch. The selection criteria for patients were as follows. (1) First episode combining concurrent MDD with PD diagnosis, with psychiatric diagnoses made according to DSM-IV criteria and the Structured Clinical Interview for DSM-IV. (2) No other psychiatric illnesses except MDD or PD and no concurrent serious medical illnesses. (3) Severity of MDD and PD was at least moderate: Clinician Global Impression of Severity (CGI-S) >4, Quick Inventory for Depressive Symptoms – Self-Rating 16-item version (QIDS-SR16) >19, Hamilton Rating Scale for Depression (HAMD) >24, Hamilton Rating Scale for Anxiety (HAMA) >22, Panic Disorder Symptom Severity Scale (PDSS) >15, full-blown symptom panic attacks >4 times within previous 4 wk prior to baseline visit. (4) No cognitive behavioural therapy (CBT) or other forms of psychotherapy. (5) Drug-naive for psychotropic medicine (no previous treatments). (6) No alcohol and substance abuse or dependence. (7) No past history of claustrophobia or discomfort while receiving MR scanning. Besides the above scales, all patients also received self-rating questionnaires, such as Integral Inventory of Depression (IID), Sheehan Disability Scale (SDS) and EuroQol life quality scale (EQ-5D). The assessments of rating scales were performed at baseline, week 3 and week 6. We also used the Panic and Agoraphobia Scale to measure and identify comorbid agoraphobia. All patients received duloxetine therapy at 60 mg/d for 6 wk. If the patients’ HAMD scores were <9 and those of PDSS <5, they would be classified as ‘remitted patients’. No concurrent psychotherapies, including CBT or other forms of psychotherapeutic input (including occupational therapy), were performed on these patients. The healthy controls had no psychiatric illnesses or medical illnesses. The controls were all interviewed by a psychiatrist with rating by all the above scales and the scores were lower than symptomatic threshold of MDD or PD. The information regarding physical illness was based on the past history of medical records. At the time of baseline MR imaging, all participating subjects (patients and controls) did not receive any psychotropic medications. Handedness was determined by using the Edinburgh Inventory of Handedness (Oldfield, 1971). The second MR scanning was performed at week 6 and all the patients received duloxetine treatment at that time.

Behavioural data statistical analysis

All the data of rating scales was processed by SPSS version 16 (SPSS Inc., USA). The analysis of variance (ANOVA) test was performed to compare the scores of rating scales at baseline, and at weeks 3 and 6. The post-hoc correction (Scheffé's test) was performed for multiple comparisons between the scores of these time-points and to reduce type I errors.

MR imaging procedure

Data acquisition

The structural MR imaging scans in brains of patients and controls were obtained with a 3 T GE version scanner housed at Buddhist Tzu-Chi Hospital Taipei Branch. Scans with 3-dimensional fast-spoiled gradient-echo recovery (3D-FSPGR) T1W1 (TR=11.2 ms, TE=5.2 ms, matrix=256×256, field of view=260 mm, number of excitations=1, slice thickness=1 mm, 180 slices, no gap) were performed in both groups at first visit and week 6.

Voxel-based morphometry (VBM) pre-processing and statistical analysis

After manually reorienting and centring the images on the anterior commissure, the pre-processing of data was performed based on the optimized VBM approach. Structural MR images were also preprocessing with the FSLVBM (http://www.fmrib.ox.ac.uk/fsl/fslvbm/, version 1.1) function of FSL (FMRIB Software Library; version 4.1.1) to compare the differences of GMV between patients and healthy controls. The theory of the FSLVBM method consists of four major steps. First, brain skull or other non-brain tissue was removed by the ‘brain extraction tool’ to discard the confounding factors of non-brain tissues in subsequent steps for the following analysis. Second, the FSL automated segmentation tool v. 4 performed tissue-specific segmentation to produce partial volume images of grey matter with better uniform intensity values with softer edges (Thomas et al. 2009). Next the images were aligned to the Montreal Neurological Institute 152 template through the affine registration. The registered images were averaged and concatenated to establish a 4D self-template of grey matter from all participants in this study. Third, brain would be nonlinearly registered to the study-specific template and all the registered images were visually inspected by Dr Lai to check the quality of registration. All the segmented images of grey matter were concatenated into a 4D multi-subject concatenated image, which was modulated by Jacobian determination of the warp field to compensate for the nonlinear transformation-induced contraction or enlargement. The modulated 4D image was smoothed by Gaussian kernels (sigma 3 mm). Further, a grey-matter mask was created by unsmoothed segmentations and unmodulated normalized segmentations. The FSLVBM mask included voxels which meant that the minimum of grey-matter probability over segmentation was larger than the minimal threshold (0) and the maximum of grey-matter probability was larger than the maximal threshold (100 for FSL images). The smoothing 4D modulated imaging and grey-matter mask were necessary for the following step of permutations. Fourth, a permutation-based non-parametric inference (the randomize function of FSL; http://www.fmrib.ox.ac.uk/fsl/randomise, version 2.1) was performed with grey-matter mask and 4D image by the threshold-free cluster enhancement (TFCE) method to compare the GMVs of the two groups. The randomize function used a general linear model for permutations and we included age, gender and global brain volumes as covariates to control possible confounding factors. TFCE is a new method for finding clusters in data without having to define clusters in a binary way, which can avoid the bias related to the arbitrary threshold. Cluster-like structures were enhanced but the image remained fundamentally voxel-wise. This procedure is able to produce test statistic images and sets of p value images. The neighbourhood-connectivity parameters were optimized and should be left unchanged to avoid edge effects of the border between grey matter and white matter. TFCE solved the multiple comparisons by using a multi-threshold meta-analysis of random-field theory cluster p values. We used family-wise error (FWE) to obtain results for continuous random processes to find p values. ‘FWE-corrected’ means that the FWE rate is controlled. If only FWE-corrected p values <0.05 are accepted, the chance of one or more false positives occurring over space is ⩽5%. Equivalently, there is 95% confidence of no false positives in the image. For the control of comorbid agoraphobia in these patients, we also included agoraphobia as a covariate in the design matrix for TFCE analysis. The statistical image after multiple comparisons was explored to find regions of GMV deficits. The statistical threshold was set as FWE p value <0.002 to find the locations of significant GMV differences between controls and patients at baseline and week 6. Moreover, paired non-parametric t test was also performed between baseline and remitted patients to explore if there was an increase of GMV after 6-wk duloxetine therapy (statistical threshold as uncorrected p<0.0005).

We attempted to correlate the scores of clinical rating scales (HAMD and PDSS) with GMV values in order to explore the relationship between GMV and clinical symptoms (with gender, age and intracranial volume controlled). This step helped to make connections between brain structure and MDD+PD.

Moreover, GMV increases were estimated in order to explore the correlation with improvements of HAMD or PDSS scores (with gender, age and intracranial volume controlled). This helped confirm the relationship between clinical improvements and grey-matter changes, which might be related to duloxetine treatment.

Results

Participating subjects

Twenty-five patients were enrolled and all supplied signed informed consent. However, five patients refused to continue duloxetine treatment due to side-effects and five patients quit due to non-response to treatment. They all refused to receive the second MR acquisition. Fifteen patients (5 male, 10 female; age 35.87±9.59 yr; illness duration 14.27±12.16 wk) and 15 healthy controls (4 male, 11 female; age 34.30±9.87 yr) were all right-handed and the 15 patients completed the trial in 6 wk. All participants (including controls) received the acquisitions of MR imaging as mentioned in the Materials and methods section (without any benzodiazepine use) at baseline and week 6. No obvious changes of physical activity levels were stated by patients or their family members.

Behavioural data

All patients had improvements of symptoms after 6-wk duloxetine therapy. The rating scales of life qualities and symptoms all showed statistically significant improvement between baseline and week 6 Fig. 1: all scales (except SDS) p<0.001, SDS as p<0.005, post-hoc correction; scales – standard error (95% confidence interval): CGI-S 0.37 (1.25–3.14); EQ-5D 0.62 (0.96–4.13), SDS 4.70 (1.04–25.09), QIDS-SR16 3.11 (3.75–19.6), IID 2.60 (3.67–16.99), HAMD 2.77 (15.50–29.66), HAMA 2.34 (17.12–29.10), PDSS 1.29 (9.48–16.08). The scales included self-reports and clinician rating reports. This represented that these patients have subjective and objective improvements of symptoms and quality of life after treatment with 60 mg/d duloxetine.

Fig. 1

Major depressive disorder patients with panic disorder had significant improvement of symptoms after 6-wk duloxetine therapy (p<0.001; except SDS as p<0.005; post-hoc correction of Scheffé's test). For abbreviations in key see main text.

Brain MR imaging data

Patients had significant deficits of GMV over infero-frontal, limbic, temporo-parietal and cerebellar regions at baseline (Fig. 2: FWE-corrected p<0.0002). The baseline GMV was positively correlated with the scores of HAMD (r=0.750, two-tailed p=0.001) and PDSS (r=0.890, two-tailed p<0.001) with age and gender corrected. The deficits of GMV still existed even when patients achieved significant improvements of symptoms. The remitted patients still had similar deficits of GMV over infero-frontal, limbic, occipital, temporal-parietal, and cerebellar regions (Fig. 3: FWE corrected p<0.0002). However, remitted patients had a possible increase of GMV over left inferior frontal cortex, right occipital fusiform gyrus, and right cerebellum VIIIa regions compared to baseline (Fig. 4 and Table 1, uncorrected p<0.0005). The healthy controls had no significant changes of brain structures at baseline and week 6. No significant differences of GMV in healthy controls between baseline and week 6 were noted (uncorrected p<0.5), which excluded the bias of GMV increase in healthy status. No significant losses of GMV after duloxetine therapy were observed (Table 1). The changes of GMV were well correlated with improvements of HAMD scores (r=0.899; Spearman's rho p=0.000; age, gender, week corrected p=0.002). The increases of GMV were also well correlated with changes of PDSS scores (r=0.695; Spearman's rho p=0.004; age, gender, week corrected p=0.006).

Fig. 2

Patients had significant widespread grey-matter volume deficits (family-wise error p<0.0002) compared to healthy controls.

Fig. 3

Remitted patients still had significant grey-matter volume deficits (family-wise error p<0.0002) compared to healthy controls.

Fig. 4

Subtle increases of grey-matter volume in left infero-frontal cortex, right fusiform gyrus, and right cerebellum VIIIa areas after 6-wk duloxetine therapy (uncorrected p<0.0005).

View this table:
Table 1

Discussion

The present study found significant GMV deficits in MDD+PD patients at baseline and week 6 after duloxetine treatment. The deficits remained significant after multiple comparisons at a very conservative statistical threshold, which means that the brain pathophysiology and residual GMV deficits of these patients were evident and significant. The areas of grey-matter deficits in our study replicated previous significant brain deficits of MDD or PD patients, such as orbitofrontal cortex (Li et al. 2010), hippocampus (Asami et al. 2009), amygdala (Asami et al. 2009; Frodl et al. 2008 b), thalamus (Asami et al. 2009), parietal cortex (Asami et al. 2009), ventromedial prefrontal cortex (Asami et al. 2009), superior temporal gyrus (Asami et al. 2009), parahippocampal gyrus (Massana et al. 2003) and putamen (Yoo et al. 2005). The persistent GMV deficits of patients might correspond to the findings that tratit marker of grey-matter deficits might exist even after remission of MDD patients (Frodl et al. 2008 b). There were no such long-term observed experiments in patients with PD. Our patients had more severe symptoms and comorbidity with PD. These residual GMV deficits should also represent the brain morphological changes for this group of relatively severe patients. The residual GMV deficits might not be able to be reversed with short-term duloxetine therapy, except for left inferior frontal cortex, right fusiform gyrus, and right cerebellum VIIIa regions. A long-term study of these patients is warranted in the future to observe if GMV-deficit areas recover and if trait markers are still preserved after remission.

The differences of GMV in the present study appeared much larger and widespread compared to those reported in the previous VBM study of MDD (Frodl et al. 2008 b) or PD (Asami et al. 2009; Yoo et al. 2005) patients. The differences still remained significant after improvements of symptoms in these patients. Since the number of subjects was relatively small and all patients were first episode and drug-naive, it was expected that the differences of GMV should be smaller than these previous studies. One possible explanation for these significant findings might represent a specific pattern of GMV deficits for this type of comorbid patients. Further, baseline unnormalized GMV was positively correlated with the severity of MDD and PD symptoms at a statistically significant level. This suggested that these GMV deficits might be correlated with clinical symptoms. These large and significant differences of GMV might support the underlying theory for worse outcome, longer duration, more severe symptoms and poorer prognosis of MDD+PD patients. The relatively severe brain morphological deficits might predict these relatively severe clinical representations of these patients than pure MDD or pure PD patients.

Our study of GMV changes in patients receiving duloxetine treatment for 6 wk did not remain significant after corrections of multiple comparisons, which was necessary due to the large number of voxels in MR images. The results just remained significant at the uncorrected statistical threshold of 0.0005, which might suggest that our results were probably negative and the effects were not so significant. However, if we can increase our study sample to 30 in each group in the future, the result perhaps will achieve significance. The results of GMV changes could be interpreted as a modest increase of GMV in the fronto-occipito-cerebellar regions after 6-wk duloxetine therapy in MDD+PD patients. However, this interpretation should be viewed with caution as the results are preliminary. Our study also enrolled healthy controls which were scanned twice within 6 wk. This design might help us avoid the possibility that the result of treatment is merely a result of repeat testing. Moreover, the changes of GMV were significantly correlated with improvements of HAMD and PDSS scores. This result could support the view that GMV changes might be associated with improvements of clinical symptom, which might be related to duloxetine treatment. Psychotherapeutic treatments, such as CBT, can lead to a significant increase in GMV in the lateral prefrontal cortex of chronic fatigue patients (de Lange et al. 2008). Because our patients did not receive other forms of psychotherapeutic treatments, such as psychotherapies and occupational therapies, this might help us exclude other contributing reasons for GMV increase. Activity is also associated with neuroplastic changes by stimulating granulocyte colony-stimulating factors which probably contributes to the increase of cerebral gray matter in the prefrontal and cingulate cortices (Floel et al. 2010). Our patients did not receive the measurements of physical activity level, which might bias our findings of GMV changes. However, as mentioned in the Materials and methods and Results sections, there were no arranged occupational or any other promotion of physical activities in our treatment programme and no obvious changes of physical activities after treatment. After controlling several confounding factors in our study design, we suggest that the GMV changes are possibly related to duloxetine treatment.

MDD has been reported to be associated with the deficiency of neurotrophic factors, such as brain-derived neurotrophic factor (BDNF) (Perroud et al. 2009). BDNF is a key cellular mechanism in preventing atrophy and cell loss of brain in depressed subjects (Duman, 2004). Duloxetine is associated with neural plasticity and the stimulating effects of BDNF in frontal cortex of animal models (Mannari et al. 2008). Some reports indicated that serotonin and norepinephrine would increase mature BDNF release and produce grey-matter growth through the effects of neurogenesis (Brody et al. 2001). The modulating effects of duloxetine over BDNF might support our findings of a modest increase in GMV over the left inferior frontal cortex, right fusiform gyrus, and right cerebellum VIIIa areas of remitted patients. Besides BDNF, some possibilities, such as astrocytic protein increase, might also induce glial growth and subsequent brain volume increase (Manev et al. 2003). The proliferation of glial cells and improvement of long-term survival of progenitor stem cells (Kodama et al. 2004) by antidepressants might activate the neurons by the neuron–glia coupling mechanism (Magistretti, 2000), which is possibly related to GMV changes in our remitted patients. The synaptic remodelling effects of antidepressant could also alter the GMV (Guest et al. 2004). Apart from these possible hypotheses, duloxetine probably also alters GMV by prevention of oxidative stress related to MDD (Kornhuber et al. 2009) or modulation of glutamate receptor function (Witkin et al. 2007).

Inferior frontal cortex was also correlated with MDD symptoms and executive function in MDD patients (Vasic et al. 2008). In a cross-sectional study, the exposures of antidepressant seemed to prevent depressed subjects from atrophy of the frontal cortex (Lavretsky et al. 2005). Protopopescu et al. (2006) mentioned decreased regional GMV of prefrontal cortex in PD patients. The right fusiform gyrus has been reported to be associated with attention bias towards mood-congruent information (Leung et al. 2009). This suggests that the right fusiform gyrus plays a role in modulation for emotion and attention in MDD patients. However, for PD patients, the role of fusiform gyrus was inconclusive. The cerebellar GMV was also negatively correlated with MDD severity (Pillay et al. 1997). Sakai et al. (2005) proposed that the cerebellum is a part of the fear or panic network and dysfunction of this network should be associated with PD. These results suggested that the left inferior frontal cortex, right fusiform gyrus, and right cerebellum VIIIa should be important structures for pathogenesis of MDD+PD. We suggest that these three regions might be state markers for improvement in symptoms of MDD+PD patients under short-term duloxetine treatment. However, it should be acknowledged that the GMV increase in these regions is modest and still not significant after multiple comparisons.

Limitations

There were several limitations of our study. (1) A relatively small sample size for a voxel-based morphometric study limits our results in explaining the medication effects and pathogenesis of brain structure. Our results must be seen as preliminary. (2) A relatively weak statistical power regarding the structural change after 6 wk might make the increase of GMV not very conclusive. (3) The onset age of our patients was older than typical onset age of MDD (20–30 yr) and PD (20–25 yr). This might be explained that this onset age will be more typical for these patients of comorbid disorders. (4) An open-label treatment of duloxetine might bias the behavioural data improvements and our image analysis. However, our study had several strengths. (1) Our patients were first episode and drug-naive, which could exclude the confounding effects of past medication and illness impact over brain structures. (2) The comorbid type could provide a specific model of GMV deficits for this type of patient. (3) A strong statistical power regarding the specific GMV deficits of these patients could provide a possible pathogenic model for these patients and might correspond to their relatively severe symptoms. (4) A prospective study of GMV in pre-treated and remitted patients might be valuable for confirming the effects of duloxetine in brain structures. Further, the persistent GMV deficits after treatment would offer trait markers of MDD+PD patients. (5) The healthy controls might strengthen our point about changes of state markers and persistent deficits of trait markers.

Conclusions

Short-term duloxetine therapy improved the clinical symptoms of patients with MDD and PD. These improvements might be related to a modest increase of GMV in state marker regions of the brain. The GMV deficits of trait marker regions were more evident and are likely to be important for pathogenesis.

Acknowledgements

We thank the Buddhist Tzu-Chi General Hospital, Taipei Branch hospital project TCRD-TPE-97-02 for grant support.

Statement of Interest

None.

References

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