A magnetic resonance imaging study of the entorhinal cortex in treatment-resistant depression

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Psychiatry Research: Neuroimaging 163 (2008) 133 – 142 www.elsevier.com/locate/psychresns

A magnetic resonance imaging study of the entorhinal cortex in treatment-resistant depression Christina P. Furtado, Jerome J. Maller, Paul B. Fitzgerald⁎ Alfred Psychiatry Research Centre, First Floor, Old Baker Building, The Alfred and Monash University School of Psychology, Psychiatry and Psychological Medicine, Commercial Road, Melbourne, Victoria 3004, Australia Received 17 August 2007; received in revised form 14 November 2007; accepted 15 November 2007

Abstract Despite a growing interest in this area, we continue to lack an understanding of the pathophysiology of depression and of treatment-resistant depression (TRD) in particular. The role of the medial temporal lobe, particularly the hippocampus, has been widely implicated in the aetiology of depression. However, related structures such as the entorhinal cortex have not been systematically examined. This research study aimed to examine possible abnormalities in the volume of the entorhinal cortex (ERC) in TRD patients. A group of 45 TRD patients and 30 healthy age- and sex-matched controls underwent magnetic resonance imaging (MRI). ERC volumes were manually traced from MRI data using ANALYZE software. An analysis of variance was conducted between subject groups and in the sexes separately while controlling for the effects of brain size via intracranial volume (ICV). Results revealed significant reductions in the volume of the left ERC of female patients. Although preliminary, our findings suggest that anatomical abnormalities in the ERC may confer vulnerability to treatment resistance. Confirmatory longitudinal studies are required to determine whether these abnormalities predate the onset of depression or are the result of a more chronic, treatment-resistant course of illness. © 2007 Elsevier Ireland Ltd. All rights reserved. Keywords: Psychiatric illness; Imaging; Volumetric analysis

1. Introduction Despite major advances in technology and pharmacology, depression remains one of the most concerning and debilitating mental disorders worldwide (Murray and Lopez, 1997; Montgomery, 2006). Treatment-resistant depression (TRD) is usually conceptualized as a failure to respond to several courses of adequate anti-

⁎ Corresponding author. Tel.: +61 3 9076 6552; fax: +61 3 9076 6558. E-mail address: [email protected] (P.B. Fitzgerald).

depressant treatment (O'Reardon and Amsterdam, 2001). TRD patients account for 15–30% of depressed patients undergoing psychiatric treatment and represent over half of the total annual costs associated with treatment of depression (Petersen et al., 2001). With systematic research it would seem possible to identify the set of unique clinical features that are peculiar to those depressed patients who show resistance to treatment (Fagiolini and Kupfer, 2003). Neuroimaging has been primarily used in depression as a means to ‘investigate the pathophysiologic mechanisms of the disorder and the physiologic basis of the clinical response to antidepressive treatment'

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(Fagiolini and Kupfer, 2003, p. 643). However, due to the heterogeneity of major depressive disorders, inconsistent findings have been reported. The limitations of many magnetic resonance imaging (MRI) studies include differences in subject populations such as selection criteria, demographic characteristics and diagnosis, as well as differences in imaging protocol (Coffey et al., 1993; Beyer and Krishnan, 2002). Focusing specifically on groups such as TRD may be one way to limit this heterogeneity. Structural neuroimaging studies that have specifically focused on TRD have reported a range of findings, with several authors concluding that in the elderly, pathologic vascular changes along with frontal lobe dysfunction may play important roles in treatment nonresponse (Baldwin and Simpson, 1997; Simpson et al., 1998; Fagiolini and Kupfer, 2003). In regards to the identification of individual brain regions, studies have identified atrophy in right frontostriatal regions (Shah et al., 2002), reduction in the frontal lobe volumes (Coffey et al., 1993), subcortical gray and white matter hypertensities (Fagiolini and Kupfer, 2003) and temporal lobe atrophy especially in the hippocampus (Shah et al., 1998). Despite the identification of the hippocampus and its common recognition in studies of treatment-resistant populations (Baldwin and Simpson, 1997; Simpson et al., 1998; Fagiolini and Kupfer, 2003), recent research studies have not systematically investigated the potential involvement of related brain regions such as the entorhinal cortex (ERC). The ERC is of particular interest because of its intimate connections with the hippocampus. The entorhinal cortex is considered to be a critical component of the mesial temporal lobe memory system and represents the major excitatory input to the hippocampus, supplying it with information from the multimodal cortical association areas (Bonhilla et al., 2003; Goncharova et al., 2001). The ERC functions as a multilevel buffer, holding ‘real sensory’ information while the hippocampus compares it with internal representations to detect ‘familiarity’ versus ‘novelty’ (Prasad et al., 2004). It has been proposed that volumetric abnormalities in the ERC could lead to impairments of the cortico-hippocampal circuit, which has been implicated in the aetiology of major depression (Nasrallah et al., 1997; Bernstein et al., 1998). Disruption in the functioning of this circuitry has been implicated in the development of abnormal mood in other disorders where the ERC has been investigated, such as in schizophrenia (Prasad et al., 2004). Also ERC pathology in Alzheimer's disease is well established, with many investigations of ERC atrophy in this disease reporting consistent findings (Laakso et al., 2000). Neurodegeneration begins in the ERC and as Alzhei-

mer's pathology develops, degeneration progresses to the hippocampus and eventually the cortex (Juottonen et al., 1998; Dickerson et al., 2001; Killiany et al., 2002; Du et al., 2004; Xu et al., 2006). O'Brien et al. (1997) found that atrophy of the entorhinal cortex, in particular, had a high sensitivity and specificity to differentiate Alzheimer patients from patients with depression. However, of note, analyses of ERC volumes have not been reported previously in TRD, and there are no prior studies of ERC volumes in non-treatment resistant depression in adult populations, thereby warranting further investigation. These findings suggest a possible role of ERC atrophy in TRD, and it may be speculated that ERC damage could occur first and be followed by atrophy progressing to the hippocampus with continual chronic, treatmentresistant depressive episodes. Therefore, the main objective of this present study was to examine possible abnormalities in the volume of the ERC in a group of treatment-resistant depressive patients in comparison to healthy age- and sex-matched controls. Based on previous neuroimaging and neuropsychological studies, it was hypothesized that there would be a significant reduction in the volume of the ERC in female TRD patients compared with female controls. It was also hypothesized that there would be a significant reduction in the volume of the ERC in male TRD patients when compared with male controls. 2. Methods 2.1. Subjects The experimental group comprised 45 patients aged between 18 and 62 years (M =37.53, S.D. = 11.33). Sex breakdown in the patient group was as follows: 22 males (M = 37.29, S.D. = 8.76), among whom 20 were righthanded and two were left-handed, and 23 females (M = 37.47, S.D. = 12.96), among whom 19 were righthanded and four were left-handed. The patients fulfilled DSM-IV (American Psychiatric Association, 1994) criteria for major depressive disorder and research criteria for treatment resistance. All patients were recruited from the outpatient department of a public mental health service (Alfred Psychiatry, Melbourne) and by referral from a variety of private psychiatrists. Exclusion criteria included a concurrent or previous DSM-IVaxis I disorder, current active medical problem and known neurological disease or a contraindication to MRI scanning. The treating psychiatrist and a study psychiatrist assigned a DSMIV diagnosis to every patient, as confirmed by the Mini International Interview for Neuropsychiatric Disorders

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(M.I.N.I., Sheehan et al., 1998) and a score on the Hamilton Depression Rating Scale (Hamilton, 1960) of at least 20. Age of onset of depressive illness varied from ages 15 years to 46 years (M = 26.16, S.D. = 11.22), with some patients reporting an episodic course of illness (N = 20, M = 3.59 episodes, S.D. = 5.18), while others reported continuous illness presentation since onset of depression (N = 25). All patients had to be in a current major depressive episode with a mean length of current episode being 7.13 years (S.D. = 6.52). Treatment resistance was defined as non-responsiveness to at least two courses of antidepressant medications for at least 6 weeks (mean ± S.D. number of courses, 8.79 ± 14.57). Patients were not deliberately withdrawn from medication before image acquisition, but their doses were not allowed to have changed in the 4 weeks before MRI scanning. Thirty-seven patients were taking medication during the trial: 11 were taking a selective serotonin reuptake inbibitor, two a tricyclic antidepressant, three a noradrenergic and specific serotonergic antidepressant (NaSSA), one a norepinephrine (noradrenaline) reuptake inhibitor (NRI), two a reversible inhibitor of monoamine oxidase A antidepressant (RIMA), seven a serotonin-norepinephrine reuptake inhibitor antidepressant (SNRI), two a SNRI-NaSSA combination antidepressant, five a RIMA-NRI combination antidepressant, and four other combination antidepressants. Eight patients were medication-free. The sample also included 30 normal healthy volunteers matched for age and sex (M = 36.6, S.D. = 11.09). The control group comprised 13 males (M = 39.29, S.D. = 12.67) and 17 females (M = 35.76, S.D. = 11.03), with no lifetime history of psychiatric illness. All subjects were required to provide written informed consent following a protocol approved by the Alfred Human Subjects Research and Ethics Committee. 2.2. Magnetic resonance image acquisition Images were acquired on a 1.5 Tesla GE Signa Imaging System (General Electric Medical Systems, Milwaukee, WI). A total of 128 contiguous images were acquired perpendicular to a line connecting the anterior and posterior commissure (AC-PC). A sagittal SPGR T1-weighted pulse sequence was then performed for volumetric estimations which yielded high-resolution T1-weighted images with good contrast between white and gray matter (TR = 7.984 ms, TE = 1.78 ms, matrix size = 256 × 256, NEX = 1, slice thickness = 1.4 mm, flip angle = 15°). Slices were then converted to be isotropic (0.94 mm3) so that volumetric analysis could be conducted.

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Fig. 1. A coronal MRI slice illustrating the level at which the entorhinal cortex was measured. (Note. Radiological convention: Right = Left).

2.3. Volumetric analysis All scans were de-identified and entered into a database so that volumetric analysis occurred blind to subject group. Image analysis was performed on a PC-compatible computer using ANALYZE software (version 7.1, 2006; Biomedical Imaging Resource, Mayo Foundation, Rochester, MN, USA) and FSL software (fMRIB, Oxford). Cerebrospinal fluid (CSF) volumes, intracranial volumes (ICV; gray matter plus white matter plus CSF) and total brain volumes (TBV; gray matter plus white matter) were computed for each subject using the FSL software for normalization purposes and as measures of brain atrophy; measures are presented in litres. The region of interest (ROI; entorhinal cortex) was manually traced using a module called Regions of Interest within the ANALYZE software. The ROI on all scans was defined by a single researcher trained to correctly locate and outline this region (CF) and validated by another more experienced researcher also trained in the volumetric estimation of this ROI (JM). 2.4. Entorhinal cortex measurement The entorhinal cortex (ERC) was manually outlined on consecutive raw (i.e. not normalized) coronal slices (Figs. 1 and 2) as described by Insausti et al. (1998) with modification as suggested by Goncharova et al. (2001) and verified from axial and sagittal slices. The ERC was traced in a rostral to caudal direction so that the entire length of the structure was measured. The rostral limit of the ERC was defined as the slice where the

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Fig. 2. Consecutive coronal MRI scans on which the entorhinal cortex was manually traced. Outline of the right ERC (left-hand side of each section), starting from the fundus of the sulcus semianularis (arrow in slice 4), along the medial aspect of the parahippocampal gyrus (PHG) down to the medial edge of the lateral branch of the rhinal sulcus (represented by ⁎ in slices 1–5). The tracing of the ‘outer’ border was stopped at the medial edge of the collateral sulcus (indicated by arrow in slices 5–6). The ‘inner’ border was traced along the PHG gray/ white matter interface and the rest of the inner border was then interpolated by drawing a straight line to the fundus of the sulcus semianularis.

gyrus ambiens, amygdala and white matter of the parahippocampal gyrus (PHG) are first visible. All landmarks were confirmed with Duvernoy's (1999) anatomic atlas which was present for all tracings of the ERC. The ERC was outlined supero-medially by tracing the contour of the gyrus ambiens beginning from the fundus of the sulcus semianularis, and downward along the medial aspect of the PHG following the tissue-CSF interface. The tracing of this ‘outer’ border was stopped at the medial edge of the collateral sulcus. The lateral border of the ERC was determined as a line perpendicular to the surface of the PHG starting at the medial edge of the sulcus. Finally, the ‘inner’ border was traced along the PHG gray/white matter interface, which is clearly visible up to the level of the uncal notch. The rest of the inner border was then interpolated by drawing a straight line to the fundus of the sulcus semianularis (Goncharova et al., 2001).

This protocol was repeated for each slice, bilaterally leading up to and including the caudal limit of the ERC, which was defined by the appearance of the gray matter of the lateral geniculate nucleus and the protrusion of the optic nerve (Goncharova et al., 2001). ERC volumes for both the left and right hemispheres were then generated by the ROI program and are expressed in mm3. It must be noted that our sample size for the ERC was reduced due to the inhomogeneity caused by the presence of the petrous bone in some MRI scans. Due to bone showing up bright white in MRI images, the presence of the petrous bone caused an artefact and prevented accurate tracing of the ERC. Thus some scans could only be traced unilaterally (either left or right ERC), while others could not be traced at all. Therefore, our sample for tracing of the ERC bilaterally consisted of 26 controls (M = 36.69, S.D. = 11.28) and 25 depressed subjects

Table 1 Means and standard deviations for ICV, TBV in liters and TBV/ICV * 100 (%) Subjects Males

Females

Control (N = 13)

ICV TBV TBV/ICV

Clinical (N = 22)

Control (N = 17)

Clinical (N = 23)

M

S.D.

M

S.D.

M

S.D.

M

S.D.

1.49 1.23 82.4

1.35 1.29 2.29

1.57 1.26 80.3

8.33 8.58 2.86

1.45 1.19 82.4

1.13 9.67 1.97

1.39 1.13 81.2

9.55 9.81 2.91

Statistical findings are reported in Section 3.

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(M = 35.96, S.D. = 12.93). There were three controls (M = 38.67, S.D. = 12.20) and two depressed subjects (M = 32.50, S.D. = 12.02) who had only their right ERC traced and only one depressed subject (M = 45) who had their left ERC traced. Seventeen depressed subjects and one control did not have their ERC traced at all, due to the presence of an artifact in their scans. 2.5. Intra-rater and inter-rater reliability Reliability of the regional volumetric measures was assessed by an intra- and inter-class correlation (ICC) formula that presumes random selection of raters (Shrout and Fleiss, 1979). ICCs were computed approximately 3 months after the initial tracing of the ERC. Five bilaterally traced scans were randomly selected and re-traced and the volumes in mm3 were compared to the original tracings to determine rater error. A Pearson's correlation was performed to determine intra-rater reliability. The correlation data revealed that the two measurements for the ERC were significantly related, r = 0. 99, P b 0.01. ICCs were above 0.95. Thus, the measurements showed a high degree of consistency. 2.6. Data analysis Analysis of covariance (ANCOVA) was used to compare volumetrics between and within subject groups, using age as a covariable. Analysis revealed a positive gender by diagnosis interaction. Post hoc tests were therefore carried out to yield separate values for males and females. A oneway ANOVA was conducted on the intracranial volume (ICV; gray matter plus white matter plus CSF) and total brain volume (TBV; gray matter plus white matter) data for each subject. Both of these may be used as a means of

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normalization, in that they control for individual differences between subjects in head and brain size. In view of the fact, however, that TBV has been directly correlated in the peer-reviewed literature with disease-related atrophy, the ICV was selected as the normalization variable because it has been found to exert no significant effects on tracing of ROIs. Analyses were two-tailed and evaluated for significance at the 0.05 alpha level using SPSS for Windows version 14.0 (SPSS Inc, Chicago, Illinois). 3. Results There were no significant differences between the total group of patients and controls in relation to age (F (1, 73) = 0.12, P = 0.73) or gender (F (1, 73) = 0.003, P = 0.96). There were also no differences in the analyzed subject groups in these variables (once subjects were excluded based on scan artifact). The means and standard deviations of the normalization variables, ICV and TBV and TBV/ICV (expressed as a percentage), are presented in Table 1. There were significant differences between groups in ICV for males (F (1, 33) = 4.29, P = 0.04), but not for females (P = 0.09) such that the male patients had lower intracranial volumes than male controls. For TBV, female patients showed reduced volumes compared with controls (F (1, 38) = 3.96, P = 0.05), but no differences were found for males (P = 0.42). Finally, significant differences were found between groups for TBV/ICV in males (F (1, 33) = 4.89, P = 0.03), such that male controls had a greater percentage of brain tissue (gray matter plus white matter) in their head space than male patients. Again no significant differences between groups for females (P = 0.15) were found. The significant differences found in ICV confirmed the use of this variable for normalization.

Table 2 Means and standard deviations of raw and normalized right and left entorhinal cortex volumes in mm3 Subjects Males

Females

Control M

Clinical S.D.

M

M

1099.69 745.28

154.92 100.06

1154.30 741.53

172.14 106.15

M

S.D.

M

145.41 104.95

1154.93 740.79

(N = 12) ERC (R) volume-raw 1099.69 ERC (R) volume/ICV

1132.59 773.59

Clinical S.D.

M

1075.17 743.74

177.14 113.11

936.89 683.25

205.74 153.69

S.D.

M

S.D.

M

S.D.

214.64 132.84

1095.90 762.20

212.53 147.40

908.12 658.02

(N = 12)

(N = 10) ERC (L) volume-raw ERC (L) volume/ICV

Control S.D.

(N = 17)

(N = 12)

S.D.

(N = 15)

(N = 16)

(N =14) 123.98 80.84

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Fig. 3. Estimated marginal means of raw left entorhinal cortex volumes in mm3.

Presented in Table 2 are the means and standard deviations of the raw and normalized right and left ERC volumes in mm3. The one-way between-groups ANCOVA, controlling for the effect of age (F (1, 47) = 0.891, P = 0.35) on the volume of the left entorhinal cortex showed a significant positive gender diagnosis interaction (F (1, 47) = 3.93, P = 0.05) and can be clearly seen in Fig. 3. Analysis also revealed a significant main effect of gender on the volume of the left ERC, F (1, 47) = 8.29, P = 0.01, such that males have larger left ERC volumes in comparison to females. No significant difference was found between patient groups (F (1, 47) = 2.74, P = 0.11). For the right ERC, an ANCOVA that controlled for the effect of age (F (1, 51) = 0.16, P = 0.70) also revealed a positive gender by diagnosis interaction (F (1, 51) = 3.955, P = 0.05). A significant main effect of gender was also found (F (1, 51) = 5.98, P = 0.02), demonstrating that right ERC volume is again larger in males compared with females, and is shown in Fig. 4. No significant difference was found between patient groups (F (1, 51) = 0.68, P = 0.41). As brain volumes and the structures contained within differ between males and females and our results support such a conclusion, a oneway ANOVA was conducted to determine whether

such differences could be localized to a particular patient group. There were no significant between-group differences found for males in raw and normalized ERC volumes for both right and left hemispheres (P N 0.05), in that male controls, overall, have similar ERC volumes when compared with male patients. For the left ERC in females, a significant between-group difference was found for raw (F (1, 30) = 8.40, P = 0.00) or normalized (F (1, 30) = 5.52, P = 0.03) volumes, such that in both circumstances controls had larger left ERC volumes than patients. A significant between-group difference for females was also found for the raw volume of the right ERC (F (1, 32) = 4.18, P = 0.05), but this finding was not replicated for the right normalized ERC volume (P N 0.05), demonstrating that female controls have larger right ERC volumes than female patients only in analyses that do not control for individual differences in brain size. 4. Discussion The objective of this study was to investigate possible abnormalities in the volume of the ERC in a group of TRD patients when compared with healthy age- and

Fig. 4. Estimated marginal means of raw right entorhinal cortex volumes in mm3.

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sex-matched controls. From the analysis, female TRD patients were found to have significantly smaller ERC volumes than female controls. No significant differences in ERC volumes were found for males. There are a few technical issues in relationship to the analysis conducted in this study that are worthy of comment. First, there has been much debate in MRI morphology studies about correction for brain size. Mackay et al. (2000) suggested that correction for brain size in patients would be inadvisable because of the possibility of disease-related atrophy. That is, patients with major depression have been found to have reduced total brain volumes due to atrophy of neurostructural areas that have been implicated in the pathophysiology of their illness (Saylam et al., 2006). Correcting for individual differences via total brain volume would cause inconsistencies in our results by influencing the measurements of the ROIs unfairly. Clearly, the overall size of an individual's head or brain has some influence on the size of the structures contained within (Cowell, 2003). In research in which the effects of brain size, in its many possible forms of measurement such as total brain volume (TBV) or intracranial volume (ICV), are not considered, it is possible that group differences simply reflect variations in the size of the whole brain (Clarke, 2003; Cowell, 2003). Cook et al. (1992; as cited in Saylam et al., 2006), however, found no significant relationship between ROI volumes and total ICV in major depressive patients. Thereby, demonstrating that correction for brain size via ICV is possible and does not influence the measurements of structures within the brain unfairly. Second, it is well established that gender differences are also present in certain brain structures (Halbreich and Lumley, 1993). Male brains are, on average, about 10% heavier and larger than female brains (Clarke, 2003). Therefore, an examination of neuroanatomic abnormalities in the sexes separately allows for genuine differences to be found. With significant differences between groups being observed for TBV in females and ICV in males, it was necessary to normalize for brain size as this measurement considerably differed between patients and controls. However, considering the complications associated with normalization for TBV, it was decided to select ICV as the normalization variable because past research has shown no significant association of this variable with major depressive pathology (Cook et al., 1992, as cited in Saylam et al., 2006). Thus, normalization via the ICV should not have affected the measurements of our ROIs. The major finding of this study is reduced ERC volumes in female TRD patients in comparison to healthy female controls. Research into ERC morphology

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in major depression is very limited, with only one known study by Bell-McGinty et al. (2002) investigating this structure in major depressive patients. These authors found a reduction of right hippocampal–entorhinal cortex volume with voxel-based morphometry in patients with geriatric depression but did not specifically present analysis of ERC volumes independent of the hippocampus. There also exists abundant research into ERC abnormalities in other neuropsychiatric disorders such as Alzheimer's disease and schizophrenia. Our findings are consistent with many of those studies that have also found reductions of ERC volumes in patients compared with healthy controls in these disorders (Bernstein et al., 1998; Juottonen et al., 1998; Laakso et al., 2000; Dickerson et al., 2001; Killiany et al., 2002; Prasad et al., 2004). However, many studies of Alzheimer's disease have not investigated volumetric abnormalities of the ERC in the sexes separately and have also not controlled for the effects of brain size. Difficulties arise in interpretation of their results as it is unknown whether significant reductions are genuine or due to confounding individual differences. Interpretation of our results is enhanced by the normalization of all subjects for ICV, allowing only for actual differences between subject populations to be detected. Also analysis of the results in the sexes separately enabled the determination of which sex is more affected by depression-related atrophy. Thus, our results demonstrate clearly that female TRD patients are more severely affected by depression-related atrophy of their ERC than their male counterparts. Although there were laterality differences in regards to ERC volumes in the female patients in our study, this finding may be the result of inadequate study power. Significant reductions in ERC volumes between female subject groups were found only for the left hemisphere when correcting for brain size. This finding was not replicated in the right hemisphere, although the raw volume of the right ERC was found to be significantly smaller in female patients than female controls. Corrected right ERC volume may well prove to be smaller in TRD patients than controls in a larger patient sample that better accounts for inter-individual variability. However, it is possible that there are true laterality differences in this structure and this would be consistent with a range of other lateralized abnormalities found in depressed patients (Hopkins and Rilling, 2000; Shah et al., 2002; Fagiolini and Kupfer, 2003; Videbech and Ravnkilde, 2004). The finding of depression-related atrophy in the ERC of only female patients is worthy of note. One of the most consistent findings in the epidemiology of mental

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disorders is the higher prevalence of depressive illness in women than men, which is probably due to a complex interplay of genetic, neuroendocrine, psychosocial and stress factors (Marcus et al., 2001; Sherwin, 2001). Women face earlier onset, longer duration and increased severity of major depressive episodes with more complications such as treatment resistance (Kendler et al., 2000, 2004). A greater degree of localized atrophy may be the result of a longer course of illness. Conversely, the greater direct involvement of a specific brain structure such as the ERC may underlie a worse prognosis of the disorder in female patients. Atrophy of the ERC in TRD patients may be related to various aetiologies. For example, previous studies have postulated excitatory connections between the ERC and hippocampus which could mediate a process by which damage in one structure produces damage in the connected structure (Kanner, 2003; Sheline, 2003). The hippocampus is one of the best studied brain areas in major depressive disorder, and several studies have reported significant reductions in hippocampal volumes in this disorder (Sheline, 2003; Neumeister et al., 2005; Saylam et al., 2006). Inverse correlations between the total amount of time patients have been depressed and hippocampal volume have also been reported (Bremner et al., 2000; Campbell et al., 2004). Hippocampal atrophy has been found in the aftermath of highly stressful life periods and notably in subjects with recurrent depression (Shah et al., 1998; Bell-McGinty et al., 2002; Sheline et al., 2003). As the ERC is the major excitatory input to the hippocampus, it is possible that atrophy in the ERC may arise secondary to atrophy in the hippocampus. In contrast, pathogenic changes in medial temporal lobe in depression or TRD may arise primarily in the ERC with secondary effects produced on the hippocampus. Many studies of Alzheimer's disease have found that atrophy begins in the ERC and progresses to the hippocampus as degeneration continues (Du et al., 2004; Xu et al., 2006). In addition, Sunanda et al. (1997) found that by lesioning the ERC they could prevent 70% of the damage produced by stress and complete removal of the ERC was found to protect hippocampal CA1 neurons from ischemic damage. Therefore, it is possible that structural changes in TRD may also possibly arise in the ERC with later changes occurring in the hippocampus raising the possibility that studying this region may have greater potential in the detection of early signs of the emergence of depression or treatment resistance. A third possibility is that a single pathogenic process results in changes in both of these brain regions simultaneously. In this regard, Sunanda et al. (1997) found that severe stress exerts the same mechanisms of

neurotoxicity in the ERC as it does in the hippocampus by causing ‘enhanced glutamatergic transmission which leads to death of neurons which have postsynaptic glutamate receptors' (p. 302). In a recent investigation into the effects of early-life stress, it was found that exposure to juvenile stress exerted enduring effects on behavior and neurosteroid concentrations in the ERC (Avital et al., 2006). Therefore, a fundamental characteristic of atrophy in both structures may be chronic stress, which has been widely implicated in the aetiology of major depression. There were a few limitations encountered by this study that require discussion. First, due to the broad age range of our patients, there could be a variety of possible contributing aetiologies associated with their treatment resistance. For example, an earlier onset of depression is associated with an elevated genetic risk and individuals are more likely to be ‘exposed to higher rates of childhood adversity, to have higher levels of neuroticism, to possess higher rates of early-onset anxiety disorders and substance abuse, and to subject themselves to more difficulties and stressful life events in adulthood, all of which in turn increase their risk for depressive outcome’ (Kendler et al., 2006, p 123). In contrast, late-onset depression is associated with poor physical health or bereavement and is often co-morbid with medical illnesses such as diabetes or cardiovascular disease (Greden, 2001). With many potential distinct aetiologies, the significant results attained cannot be attributed to a particular course of depression such as early onset or increased stressful life events as analysis was conducted across the entire age range where there are many contributing factors. A closer analysis of each age range (young adults, middle-aged and older adults) is warranted, whereby contributing factors such as life experiences and global neurodegeneration due to normal aging can be controlled for. A second issue is that causation cannot be inferred. That is, our findings cannot determine whether the abnormalities found in the ERC of patients necessarily result from treatment resistance/persistent illness or predated the onset of depression. The exact time course of these changes in relation to illness duration and severity needs to be determined by future investigations (Shah et al., 2002). These issues are related to our choice of population to study, that is, patients with TRD. TRD is a ‘subtype’ of depression only distinguishable by treatment response, rather than phenomenological characteristics. However, investigating the aetiology of depression based on symptoms and other clinical features has not proved overly successful and treatment response is a very important clinical variable. Whilst it is possible that a variety of

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‘depressions’ with differing causes could become treatment resistant with a range of biological causes of the treatment resistance, it is also possible that there is a relatively consistent pattern of biological change that may be related to treatment resistance, potentially independent of the primary cause of the illness. Our results suggest that the medial temporal lobe may be a site of focus in exploring this question. Another important limitation of this study is that the number of patients with traceable ERCs was limited due to MRI artifact created by bone-air interface inhomogeneity. Whilst this is common, due to the location of the temporal bone with respect to the medial temporal lobe, the sample size in the current study is greater than those in the majority of published ERC volumetric studies in patients with major depressive disorder. However, with respect to treatment resistance, this is the first study to present ERC volumes in a sample of patients with this type of major depressive disorder. As the patients with major depressive disorder in the current study were treatment resistant, a strength of the results is that they are free from the influence of treatment factors such as type and dosage of current medications and time on current medications. In summary, this research has contributed to the growing body of literature concerning the neuroanatomical abnormalities associated with the phenomena of TRD. In particular, the study clearly suggests that the ERC is involved in the pathophysiology of this disorder. The results of the study also suggest that there is a gender-specific aspect of the involvement of this brain region. Although one must be cautious in interpretation of these results due to the limited sample size, it appears that the ERC is more involved in female patients. Replication using a larger sample is required. Although preliminary, our findings suggest that anatomical abnormalities in the ERC may confer vulnerability to treatment resistance. Confirmatory longitudinal studies are required to determine whether these abnormalities predate the onset of depression or are the result of a more chronic, treatment-resistant course of illness, and consideration of the disorder should also involve investigation into the role of a range of medial temporal lobe structures. References American Psychiatric Association, 1994. Diagnostic and Statistical Manual of Mental Disorders, 4th ed. American Psychiatric Association, Washington. Avital, A., Ram, E., Maayan, R., Weizman, A., Richter-Levin, G., 2006. Effects of early-life stress on behaviour and neurosteroid levels in the rat hypothalamus and enthorhinal cortex. Brain Research Bulletin 68, 419–424.

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