Increasing evidence implicates white matter as a key component of the structural brain changes in major depressive disorder, in which a ‘disconnection’ between regions is purported to be responsible for impairments in emotion processing. Reference Sexton, Mackay and Ebmeier1 White matter integrity is commonly measured using the magnetic resonance imaging (MRI) technique of diffusion tensor imaging. Studies using this technique have reported abnormalities associated with major depressive disorder in adolescent patients, Reference Cullen, Klimes-Dougan, Muetzel, Mueller, Camchong and Houri2 middle-aged patients, Reference Abe, Yamasue, Kasai, Yamada, Aoki and Inoue3,Reference Korgaonkar, Grieve, Koslow, Gabrieli, Gordon and Williams4 elderly patients, Reference Alexopoulos, Kiosses, Choi, Murphy and Lim5–Reference Yuan, Zhang, Bai, Yu, Shi and Qian7 and in adolescents at high familial risk of major depressive disorder. Reference Pierpaoli and Basser8 The most widely used diffusion tensor imaging measure, fractional anisotropy, provides an index of the ‘directionality’ of diffusion within a voxel. The axonal structure of white matter tracts is generally highly linear, hence reductions in fractional anisotropy are thought to reflect pathological microstructural changes related to the integrity of the white matter. Reference Basser9 Reduced fractional anisotropy in major depressive disorder has been reported in a number of frontal, Reference Yuan, Zhang, Bai, Yu, Shi and Qian7,Reference Li, Ma, Li, Tan, Liu and Gong10 temporal and midbrain regions, Reference Yang, Huang, Hong and Yu11 along with fibre tracts such as the corpus callosum, Reference Bae, MacFall, Krishnan, Payne, Steffens and Taylor12 internal capsule, Reference Zhu, Wang, Xiao, Zhong, Liao and Yao13,Reference Zou, Huang, Li, Gong, Li and Ou-yang14 and superior longitudinal fasciculus. Reference Wu, Tang, Xu, Kong, Sun and Wang15 The findings from individual reports indicate a widespread pattern of alterations, but there has been limited reproducibility between studies, perhaps due to methodological differences.
Moreover, the extent of white matter abnormalities may be associated with clinical features. Increased severity of illness and poorer treatment outcomes have been associated with increased white matter hyperintensities, Reference Heiden, Kettenbach, Fischer, Schein, Ba-Ssalamah and Frey16 indicating that patients with greater illness burden are more likely to have microstructural white matter alterations and possibly ischaemic damage. Yet, as a state marker of a depressive episode in major depressive disorder, diffusion tensor imaging studies of fractional anisotropy measures have shown mixed results, with reports of no relationship between depression rating scores and fractional anisotropy, Reference Abe, Yamasue, Kasai, Yamada, Aoki and Inoue3,Reference Li, Ma, Li, Tan, Liu and Gong10–Reference Bae, MacFall, Krishnan, Payne, Steffens and Taylor12,Reference Jia, Huang, Wu, Zhang, Lui and Zhang17–Reference Nobuhara, Okugawa, Minami, Takase, Yoshida and Yagyu20 significant differences between patients in remission and in an acute episode, Reference Alexopoulos, Kiosses, Choi, Murphy and Lim5,Reference Bae, MacFall, Krishnan, Payne, Steffens and Taylor12,Reference Zhou, Qin, Chen, Qian, Tao and Fang21 as well as negative correlations between fractional anisotropy and current illness severity. Reference Zhu, Wang, Xiao, Zhong, Liao and Yao13,Reference Zou, Huang, Li, Gong, Li and Ou-yang14,Reference Lamar, Charlton, Morris and Markus22–Reference Dalby, Frandsen, Chakravarty, Ahdidan, Sorensen and Rosenberg24 In this study we investigated white matter tracts using tract-based spatial statistics in a large and well-characterised group of adult patients with recurrent major depression and a matched healthy control group. Reference Smith, Jenkinson, Johansen-Berg, Rueckert, Nichols and Mackay25 We examined the relationship between depressive symptoms and diffusion-weighted measures of white matter, expecting that reductions in white matter integrity would be found in patients with major depressive disorder and would be greater in those with more severe symptoms.
Method
The study participants included 66 persons with recurrent major depressive disorder and a control group of 66 healthy individuals matched for age, gender, IQ score and years of full-time education. All patients had experienced two or more depressive episodes of at least moderate severity and met DSM-IV diagnostic criteria for recurrent major depressive disorder, 26 assessed using the Schedules for Clinical Assessment in Neuropsychiatry (SCAN). Reference Wing, Babor, Brugha, Burke, Cooper and Giel27 Control group participants were interviewed to ensure they had never experienced depressive symptoms. All participants were screened for contraindications to MRI; other exclusion criteria were a diagnosis of neurological disorder, head injury leading to loss of consciousness or conditions known to affect brain structure or function (including alcohol or substance misuse), ascertained during clinical interview. Potential participants were also excluded if they or a first-degree relative had ever fulfilled criteria for mania, hypomania, schizophrenia or mood-incongruent psychosis. Current depressive symptoms were measured using the Beck Depression Inventory (BDI). Reference Beck, Ward, Mendelson, Mock and Erbaugh28 The participants’ IQ scores were assessed using the Wechsler Abbreviated Scale of Intelligence. Reference Wechsler29 Information regarding current use of antidepressant medication was also obtained from the participants with depressive disorder. All participants had previously participated in genetic association studies, Reference Cohen-Woods, Gaysina, Craddock, Farmer, Gray and Gunasinghe30,Reference Uher, Perroud, Ng, Hauser, Henigsberg and Maier31 and were of White European ancestry. The study received local ethics committee approval and all participants gave written informed consent.
Image acquisition and pre-processing
Diffusion-weighted acquisition data were collected using a 1.5 T Signa HDx system (General Electric, Milwaukee, Wisconsin, USA). Reference Jones, Williams, Gasston, Horsfield, Simmons and Howard32 Sixty contiguous near-axial slice locations with a 24 cm2 field of view and isotropic (2.5 mm3) voxels were imaged with the following parameters: echo time 101.3 ms, effective repetition time varied between participants (12–20 R–R intervals), diffusion gradient duration 17.3 ms, diffusion weighting 1300 mm2. At each location, 60 diffusion-weighted directions were acquired plus 7 B0 images per individual.
Diffusion-weighted data were corrected for eddy current distortions and head movements, then masked to remove non-brain voxels using Brain Extraction Tool. Reference Smith33 A single tensor model was fitted to the data to generate measures of fractional anisotropy, mean diffusivity, radial diffusivity, axial diffusivity and mode of anisotropy (FMRIB Software Library, www.fmrib.ox.ac.uk/fsl/). Reference Smith, Jenkinson, Woolrich, Beckmann, Behrens and Johansen-Berg34 Fractional anisotropy was the main dependent variable, whereas mean, radial and axial diffusivity offered complementary information about the pattern of diffusion to aid in the interpretation of fractional anisotropic changes. Mode of anisotropy is a relative measure of the ‘linearity’ of the diffusion, Reference Ennis and Kindlmann35 and is mathematically orthogonal to fractional anisotropy. Reference Douaud, Jbabdi, Behrens, Menke, Gass and Monsch36 Lower mode of anisotropy indicates more planar diffusion, likely to be found in areas of crossing fibres, whereas higher mode is thought to reflect more linear diffusion, indicative of regions where a single fibre orientation predominates.
Tract-based spatial statistics
Between-group diffusion tensor imaging comparisons were conducted using TBSS version 1.2. Reference Smith, Jenkinson, Johansen-Berg, Rueckert, Nichols and Mackay25 Fractional anisotropic images from all participants were aligned to the Johns Hopkins University – International Consortium of Brain Mapping DTI-81 white matter atlas (JHU DTI atlas), Reference Mori, Oishi, Jiang, Jiang, Li and Akhter37 using FMRIB's non-linear image registration tool (FNIRT) in FSL. A mean voxel-wise fractional anisotropic image was generated and subsequently skeletonised and thresholded (optimised to include white matter only at fractional anisotropy ⩾0.3). This procedure generates a mean fractional anisotropic ‘skeleton’, representing the centres of tracts common to all participants. The aligned maps were then projected onto this skeleton, allowing voxel-wise statistical analysis to be conducted. The individual mean, radial and axial diffusivity and mode of anisotropy maps were projected on the skeleton for each individual, in order to ensure that analyses were restricted to the centre of the all common tracts.
Randomise in FSL was used to investigate differences between the depressive disorder and control groups in all diffusion measures across the skeletonised brain maps. The analysis used threshold-free cluster enhancement and conducted 5000 permutations per contrast to generate voxel-wise probability values corrected for multiple testing (significant at P<0.05, family-wise error corrected). To examine the influence of clinical characteristics on white matter integrity, current symptom severity (i.e. BDI score), antidepressant use and the presence of melancholic characteristics were analysed within the major depressive disorder group. All Randomise contrasts included age, gender and IQ score as nuisance variables, which were ‘de-meaned’ prior to analysis.
Regions of crossing fibres can result in fractional anisotropy reductions that are unrelated to white matter integrity; hence, mode of anisotropy data were employed to obviate this problem. A voxel-wise mean mode of anisotropy map, generated by averaging across all participants, was then masked by the mean fractional anisotropic skeleton to ensure that the former map was limited to common white matter tracts. This mean mode of anisotropy skeleton was then thresholded (mode of anisotropy ⩾0.5) and overlaid on the fractional anisotropic P-value map for the group contrast. Significant between-group differences in fractional anisotropy that survive the high mode of anisotropy threshold are likely to be highly linear, giving greater confidence that such differences are due to systematically differing white matter integrity rather than crossing fibres.
Statistical analysis
To localise significant voxel effects post hoc, contrast maps were subdivided according to the 48 regions of the JHU DTI atlas (online Table DS1). This allowed quantification of the number of significantly different voxels per region, along with identification of the peak voxel. Independent t-tests were run for the effect of group on each skeletonised region, producing values that were then used to calculate regional effect sizes (Cohen's d). Raw diffusion metrics across the fractional anisotropic skeleton were extracted per participant and analysed in SPSS version 19.0 on Windows XP to test for relationships with demographic and clinical variables: age, gender, IQ score, treatment resistance, history of electroconvulsive therapy (ECT) and number of melancholic symptoms.
Results
There was no significant difference in age, gender, IQ score or years of education between the depressive disorder and control groups, but a significant difference in BDI score (P<0.001) was found as expected (Table 1). Significant widespread reductions in fractional anisotropy were found in the participants with major depressive disorder compared with controls, including brain regions in the splenium, genu and body of the corpus callosum, bilateral superior longitudinal fasciculus, anterior and posterior corona radiata, and anterior and posterior limbs of the internal capsule (online Fig. DS1, Table DS2). Significantly higher radial diffusivity was found in similarly widespread regions (Fig. DS2A), along with increased mean diffusivity in the corpus callosum and several right hemisphere regions in the depressive disorder group compared with controls (Fig. DS2B). There was no significant group difference in axial diffusivity or mode of anisotropy. This pattern of increased radial and mean diffusivity without alteration in axial diffusivity indicates that abnormally high levels of diffusion were occurring in the white matter tracts of the participants with major depressive disorder, and that these changes were perpendicular to the primary diffusion direction.
Application of a mode of anisotropy threshold (⩾0.5) to the fractional anisotropy analysis revealed greater specificity in the fractional anisotropy reductions in the depressive disorder group (Fig. DS3, Table DS3). In particular, all three subregions of the corpus callosum, the left internal capsule and the posterior thalamic radiation showed persistent significant fractional anisotropic reductions consistent with deficits in white matter integrity rather than potential contamination due to the effects of crossing fibres. Conversely, the bilateral superior longitudinal fasciculi, right external capsule and all corona radiata regions contained substantially fewer significant voxels when using the mode of anisotropy mask, potentially indicating that these fractional anisotropy alterations might be due to increased numbers of crossing fibres rather than pathological mechanisms affecting white matter structure.
Demographic and clinical characteristics of participantsy
| MDD groupFootnote a (n = 66) | Control group (n = 66) | |
|---|---|---|
| Age, years: mean (s.d.) | 48.6 (8.2) | 50.4 (7.9) |
| Male/female, n/n | 23/43 | 30/36 |
| Full-scale IQ, mean (s.d.) | 119.4 (10.1) | 120.5 (8.7) |
| Education, years: mean (s.d.) | 14.6 (3.2) | 15.2 (2.7) |
| BDI score, mean (s.d.) | 15.9 (11.6) | 1.8 (2.1) |
| Antidepressants (unmedicated/medicated), n/n | 19/47 | |
| Years since illness onset, mean (s.d.) | 21.3 (10.4) | |
| History of ECT (yes/no), n/n | 3/63 | |
| Melancholic/non-melancholic, n/n | 19/46 | |
| Number of melancholic symptoms, mean (s.d.) | 3.3 (1.4) |
BDI, Beck Depression Inventory; ECT, electroconvulsive therapy; MDD, major depressive disorder.
a There was no significant group difference in age (t = 1.36, P = 0.18), gender (χ2 = 1.55, P = 0.21), full-scale IQ (t = 0.67, P = 0.50) or years of education (t = 1.17, P = 0.24), but there was an expected significant difference in BDI score (t = 9.78, P < 0.001).
Effect of depression severity on white matter integrity
Voxel-wise regression analysis indicated that there was a significant negative linear relationship between BDI score and fractional anisotropy in several regions (Fig. 1), including the corpus callosum and right posterior tracts, whereby fractional anisotropy decreased as BDI score increased (Fig. DS4A, Table DS2). Furthermore, a positive linear relationship between BDI score and radial diffusivity was found in an overlapping set of white matter regions, although not for mean or axial diffusivity, indicating that greater symptom severity is associated with white matter disruptions in these regions (Fig. DS4B, Table DS3). Extracting mean fractional anisotropy within JHU DTI atlas regions showed further negative correlations with BDI score of a relatively widespread nature (Table DS4). Scores on the BDI ranged from 0 to 51 with a median of 14, indicating that half of the patients were experiencing at least a mild depressive episode at the time of the MRI scan. Demographic analysis indicated that BDI score was negatively correlated with IQ score in the major depressive disorder group (r = –0.33, P = 0.007) but not in controls (r = –0.11, P = 0.38), justifying the removal of variance explained by IQ score in the within-patients regression model. The BDI score was not significantly related to age or gender within the major depressive disorder group.
Clinical characteristics and white matter measures
At the time of the study, 47 of the 66 patients with major depressive disorder were taking antidepressants, whereas 19 had not taken an antidepressant for at least 4 weeks prior to scanning (Table DS5). There was a significant effect of medication status on fractional anisotropy, whereby patients currently taking antidepressants showed fractional anisotropy reductions in the corpus callosum and left posterior white matter (see Table DS3, Fig. DS5A) and widespread increases in radial diffusivity across several regions, including the corpus callosum, bilateral corona radiata and cingulum (Table DS3, Fig. DS5B). There was a trend towards increased BDI scores in patients with major depressive disorder taking antidepressant medications compared with unmedicated patients (t = 1.84, P = 0.072), but no other significant difference between groups in terms of age, gender or IQ score.
The depressive disorder group consisted of 19 persons with melancholic disorder and 46 with no melancholic symptoms (1 patient unspecified owing to insufficient data). Reference Uher, Dernovsek, Mors, Hauser, Souery and Zobel38 There was no significant voxel-wise fractional anisotropic difference between these two subgroups, nor did melancholic symptoms correlate with mean skeleton-wise fractional anisotropy or radial, mean or axial diffusivity. There was a significant correlation of the sum of melancholic symptoms with BDI score (r = 0.328, P = 0.008).
Age was negatively correlated with fractional anisotropy (r = –0.26, P = 0.003) and mode of anisotropy (r = –0.27, P = 0.002), and positively correlated with radial (r = 0.28, P = 0.001) and mean diffusivity (r = 0.25, P = 0.004); IQ score was positively correlated with fractional anisotropy (r = 0.18, P = 0.03). Men and women in the sample did not differ significantly on any diffusion measure. The BDI score for all individuals was negatively correlated with skeleton-wise fractional anisotropy (r = –0.34, P<0.001) and was positively correlated with radial (r = 0.30, P = 0.001) and mean diffusivity (r = 0.24, P = 0.007), indicating that higher current symptom severity is associated with decreases in the integrity of major white matter fibre bundles.
Individual Beck Depression Inventory (BDI) scores plotted against mean skeleton-wise fractional anisotropy (FA) for each participant.
The blue line derived from the regression analysis illustrates the linear relationship between increasing symptom severity and decreasing fractional anisotropy (R linear 0.093).
Discussion
Widespread alterations in white matter integrity were evident in participants with major depressive disorder in comparison with a healthy control group. Impairments were observed in 75% of white matter regions (36 of 48 atlas regions), probably reflecting reduced axonal density, axonal diameter and dysmyelination. Reference Song, Sun, Ramsbottom, Chang, Russell and Cross39 Moreover, increasing severity of depression was associated with greater disruptions in white matter integrity. The findings from the large and well-characterised groups in our study, importantly using improved acquisition and analysis procedures, demonstrate the extent of white matter abnormalities in major depressive disorder and lend weight to models of major depressive disorder as a disorder of neurocircuitry. Reference Sexton, Mackay and Ebmeier1,Reference Price and Drevets40
White matter abnormalities in depression
The most pronounced white matter reductions were observed in the main body and genu of the corpus callosum, consistent with some, Reference Korgaonkar, Grieve, Koslow, Gabrieli, Gordon and Williams4,Reference Shimony, Sheline, D'Angelo, Epstein, Benzinger and Mintun41 but not all, Reference Abe, Yamasue, Kasai, Yamada, Aoki and Inoue3,Reference Bae, MacFall, Krishnan, Payne, Steffens and Taylor12,Reference Nobuhara, Okugawa, Sugimoto, Minami, Tamagaki and Takase23,Reference Versace, Almeida, Quevedo, Thompson, Terwilliger and Hassel42 diffusion tensor imaging reports in depression. Corpus callosum abnormalities may be reflected in the aberrant interhemispheric synchrony reported in male major depressive disorder, Reference Knott, Mahoney, Kennedy and Evans43 whereas reduced corpus callosum volume has been associated with impaired working memory capacity and speed in older adults, Reference Fling, Chapekis, Reuter-Lorenz, Anguera, Bo and Langan44 resembling the cognitive characteristics of major depressive disorder. Reference Walsh, Williams, Brammer, Bullmore, Kim and Suckling45 Reduced volume and deformations in the corpus callosum have been observed in major depressive disorder, Reference Walterfang, Yucel, Barton, Reutens, Wood and Chen46 suicidal behaviour, Reference Cyprien, Courtet, Malafosse, Maller, Meslin and Bonafe47 bipolar depression, Reference Benedetti, Yeh, Bellani, Radaelli, Nicoletti and Poletti48 dysthymia, Reference Lyoo, Kwon, Lee, Han, Chang and Seo49 and in adolescents with a parental history of depression, Reference Pierpaoli and Basser8 as well as in schizophrenia and Alzheimer's disease. Reference Sun, Maller, Daskalakis, Furtado and Fitzgerald50,Reference Lyoo, Satlin, Lee and Renshaw51 Together, these findings suggest that impairments in corpus callosum tracts may be involved in the aetiology of depressive symptoms, not only in major depressive disorder itself but also in other psychiatric disorders that contain a depressive component in their symptomatology.
We also found significant white matter integrity reductions in the left superior longitudinal fasciculus, consistent with other reports in major depressive disorder. Reference Zou, Huang, Li, Gong, Li and Ou-yang14,Reference Wu, Tang, Xu, Kong, Sun and Wang15,Reference Dalby, Frandsen, Chakravarty, Ahdidan, Sorensen and Rosenberg24 This is the major association pathway connecting frontal regions with all other cerebral lobes, in particular from the dorsolateral prefrontal cortex, itself an important region in an emotion-regulating circuit. Reference Drevets, Price and Furey52 Ischaemic changes in the dorsolateral prefrontal cortex predispose elderly individuals to major depressive disorder, and imaging findings indicate that more subtle microstructural and functional alterations in this region's connectivity may also be a contributory factor to depression in earlier adulthood. Reference Blood, Iosifescu, Makris, Perlis, Kennedy and Dougherty53,Reference Vasic, Walter, Sambataro and Wolf54 Interestingly, Versace et al found fractional anisotropy decreases in the superior longitudinal fasciculus of patients with bipolar disorder but not major depressive disorder. Reference Versace, Almeida, Quevedo, Thompson, Terwilliger and Hassel42 Although not a direct comparison of major depressive disorder and bipolar disorder, our results indicate that abnormalities of the superior longitudinal fasciculus are not specific to bipolar disorder, perhaps underlying depressive symptoms in both disorders. Furthermore, we observed widespread disruptions in white matter integrity between cortical and limbic regions, including association fibres such as the sagittal stratum and external capsule, and projection fibres including the internal capsule, corona radiata and thalamic radiation, supporting the notion of aberrant neurocircuitry in major depressive disorder. Reference Price and Drevets40
White matter deficits and symptom severity
In participants with major depressive disorder there was a significant negative correlation between fractional anisotropy and the severity of depression, indicating greater deficits in white matter integrity with greater severity of symptoms. A positive correlation between BDI score and radial diffusivity was also found, implicating increases in diffusivity parallel to the tracts in line with increased severity. This indicates that demyelination, as opposed to abnormalities in axonal diameter or density, might occur more frequently in patients with more severe current symptom severity. The relationship between symptom severity and white matter integrity was strongest in the corpus callosum but also included the corona radiata and posterior thalamic radiation. Lamar et al found a correlation between decreased integrity and increased severity in a large region of interest that included the corpus callosum; Reference Lamar, Charlton, Morris and Markus22 however, our tract-based analysis gives considerably greater precision in characterising the regions involved. Interestingly, Lamar et al studied a sample consisting solely of euthymic patients with major depressive disorder, indicating that the relationship persists into remission. Other similar findings of increased severity with decreased integrity have been reported for inferior frontal regions, Reference Nobuhara, Okugawa, Sugimoto, Minami, Tamagaki and Takase23 the anterior limb of the internal capsule, Reference Zhu, Wang, Xiao, Zhong, Liao and Yao13,Reference Zou, Huang, Li, Gong, Li and Ou-yang14 left superior longitudinal fasciculus and right uncinate, Reference Dalby, Frandsen, Chakravarty, Ahdidan, Sorensen and Rosenberg24 as well as for decreased grey matter volume in prefrontal and cingulate regions. Reference Chen, Ridler, Suckling, Williams, Fu and Merlo-Pich55 The varied pattern of brain regions implicated by the literature indicates that further research is necessary to improve our understanding of the specificity of the relationship between depressive symptom severity and brain changes and how this relates to functional impairments in people with major depressive disorder.
White matter impairments in bilateral frontal regions have been associated with a poorer clinical outcome. Reference Alexopoulos, Kiosses, Choi, Murphy and Lim5,Reference Alexopoulos, Murphy, Gunning-Dixon, Latoussakis, Kanellopoulos and Klimstra56 The degree and extent of white matter disruptions may implicate a more treatment-resistant form of depression, complementary to structural and functional abnormalities that are predictive of clinical response. Reference Costafreda, Chu, Ashburner and Fu57–Reference Costafreda, Khanna, Mourao-Miranda and Fu60 Dynamic changes to white matter tracts have been reported in response to training, with working memory training correlating with increases in the intraparietal sulcus and corpus callosum, Reference Takeuchi, Sekiguchi, Taki, Yokoyama, Yomogida and Komuro61 and fractional anisotropy increases in the corona radiata evident after meditation training. Reference Tang, Lu, Geng, Stein, Yang and Posner62 If white matter integrity is measurably plastic and related to both symptom severity and cognitive performance, this has implications for the potential use of diffusion tensor imaging in a clinical setting. Longitudinal effects of treatment on white matter integrity in adult major depressive disorder have not been examined to date, but it may be postulated that successful treatment would be accompanied by a normalisation of white matter integrity, as reported in some structural and functional MRI studies. Reference Soriano-Mas, Hernandez-Ribas, Pujol, Urretavizcaya, Deus and Harrison63–Reference Fu, Williams, Cleare, Brammer, Walsh and Kim66 This normalisation might be region-specific, as our findings indicate that although widespread changes distinguish between patients and controls, fewer regions correlate with severity. For example, the corpus callosum might be more responsive to depressive states than other areas, with heightened impairments in tandem with increasing severity and improvements during periods of remission, with the more substantive widespread abnormalities perhaps reflecting a trait feature of depression.
Clinical features and white matter integrity
We found greater disruptions of white matter integrity in participants who were currently taking antidepressants. This could be interpreted to show that decreased fractional anisotropy is a marker of antidepressant use, and it has previously been reported that increased white matter lesions have been associated with long-term antidepressant use in elderly people with major depressive disorder. Reference Steffens, Chung, Krishnan, Longstreth, Carlson and Burke67 Nevertheless, fractional anisotropy reductions have also been reported in young adults with major depressive disorder who have never taken antidepressant medication. Reference Zhu, Wang, Xiao, Zhong, Liao and Yao13,Reference Wu, Tang, Xu, Kong, Sun and Wang15,Reference Ma, Li, Shu, Liu, Gong and He19 Additionally, in our sample there was a trend towards increased symptom severity in medicated patients which may explain this apparent antidepressant effect. We did not detect any difference between patients with melancholic and non-melancholic disorder or a relationship between number of melancholic symptoms and white matter integrity. In contrast to the findings of Korgaonkar et al, Reference Korgaonkar, Grieve, Koslow, Gabrieli, Gordon and Williams4 group differences were not limited to melancholic major depressive disorder, as we found widespread abnormalities in all patients with recurrent major depressive disorder. Furthermore, it appears that a relationship with melancholic depression may be more likely to be a function of the trend towards increased severity in this group, rather than the melancholic symptoms per se.
Limitations
The study is limited in its cross-sectional design, preventing inferences of causality in the relationship between current illness severity and decreased white matter integrity. It is possible that the relationship between severity and brain structure is bi-directional, or may result from changes in correlated latent variables. The sample included patients with somewhat heterogeneous medication histories; nonetheless, we were able to examine differences between patients taking antidepressants and those who were not. Three participants also had a history of ECT, which may affect white matter structure. Much of the extant research into white matter in major depressive disorder has been conducted in people over 65 years old, Reference Yuan, Zhang, Bai, Yu, Shi and Qian7,Reference Yang, Huang, Hong and Yu11,Reference Bae, MacFall, Krishnan, Payne, Steffens and Taylor12,Reference Alexopoulos, Murphy, Gunning-Dixon, Latoussakis, Kanellopoulos and Klimstra56,Reference Taylor, Macfall, Boyd, Payne, Sheline and Krishnan68,Reference Taylor, Macfall, Gerig and Krishnan69 which may offer greater sensitivity to detect abnormalities in white matter, particularly for associations with age-related neurovascular changes.
Our use of tract-based spatial statistics focused solely on white matter regions from a ‘skeleton’ template, causing the exclusion of potentially interesting areas of peripheral white matter. However, this approaches benefits considerably by being less susceptible to partial volume effects and does not require arbitrary spatial smoothing, Reference Smith, Jenkinson, Johansen-Berg, Rueckert, Nichols and Mackay25 in contrast to voxel-based diffusion tensor imaging analysis. Reference Yuan, Zhang, Bai, Yu, Shi and Qian7,Reference Zou, Huang, Li, Gong, Li and Ou-yang14,Reference Ma, Li, Shu, Liu, Gong and He19,Reference Zhou, Qin, Chen, Qian, Tao and Fang21 Additional tractographic analysis could be used to follow up our findings to characterise fibre tract architecture and assess integrity of individual tracts. The interpretation of diffusion tensor images can also be limited by the presence of crossing white matter fibres which may result in reductions in fractional anisotropy that are not pathological in origin. Nevertheless, our novel implementation of a ‘mode of anisotropy’ mask of the fractional anisotropy results indicates that in the corpus callosum in particular, the microstructural configuration is highly linear, thus any anisotropy reductions are unlikely to be the result of crossing fibre orientations. Furthermore, we employed a protocol with 60 diffusion gradient directions. Increasing the number of gradient directions has been shown to increase contrast-to-signal variance ratio and improve visualisation of white matter structures, and our figure far surpasses the minimum 20 directions recommended for accurate diffusion tensor calculation by Giannelli et al. Reference Giannelli, Cosottini, Michelassi, Lazzarotti, Belmonte and Bartolozzi70 In fact, only a few diffusion tensor imaging studies of major depressive disorder have exceeded Giannelli et al's quality threshold, Reference Cullen, Klimes-Dougan, Muetzel, Mueller, Camchong and Houri2,Reference Korgaonkar, Grieve, Koslow, Gabrieli, Gordon and Williams4,Reference Yuan, Zhang, Bai, Yu, Shi and Qian7,Reference Pierpaoli and Basser8,Reference Yang, Huang, Hong and Yu11,Reference Dalby, Frandsen, Chakravarty, Ahdidan, Sorensen and Rosenberg24,Reference Li, Liu, Skidmore, Liu, Tian and Li71,Reference Matthews, Strigo, Simmons, O'Connell, Reinhardt and Moseley72 and in these studies sample sizes have been small, the largest being that of Yang et al (n = 31). Reference Yang, Huang, Hong and Yu11 Sparse acquisition of gradient directions or small samples may have considerably hampered the statistical power to detect widespread white matter changes, particularly in studies that used a whole brain approach. Region of interest studies have included larger samples, although some a priori excluded the corpus callosum, Reference Taylor, Kuchibhatla, Payne, Macfall, Sheline and Krishnan6,Reference Bae, MacFall, Krishnan, Payne, Steffens and Taylor12,Reference Shimony, Sheline, D'Angelo, Epstein, Benzinger and Mintun41 the area where we report the strongest effects. Our use of ‘high-directional’ data acquisition combined with a relatively large sample size and tract-based spatial statistical analysis is likely to have improved statistical power and thus the sensitivity to microstructural effects, adding credence to the findings.
In summary, we examined diffusion tensor imaging-derived measures of white matter integrity in patients with recurrent major depressive disorder. We demonstrated widespread disruptions to several white matter pathways, most notably the corpus callosum and superior longitudinal fasciculi. The majority of the group differences occurred in regions unlikely to contain a high density of crossing fibres, hence are more likely to reflect neuropathological changes. Moreover, we found a correlation between increased depressive symptom severity and decreased white matter integrity, indicating that white matter disruptions are heightened in those with a greater current illness burden, reflecting both trait predispositions and state alterations in the neurocircuitry of depression.
Funding
J.C. was funded by a Medical Research Council studentship and a Wellcome Trust Value In People award for the duration of this work. The study was funded in part by GlaxoSmithKline UK and by the National Institute of Health Research Biomedical Research Centre for Mental Health at South London and Maudsley National Health Service Foundation Trust and King's College London, Institute of Psychiatry, UK.
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