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Structural abnormalities of the anterior cingulate cortex (ACC) may interfere with the interaction of cortical and limbic networks involved in emotional regulation and contribute to chronic depressive syndromes in the elderly. This study examined the relationship of regional anterior cingulate cortical volumes to treatment remission of elderly depressed patients. We hypothesized that patients who failed to remit during a 12-week controlled treatment trial of escitalopram would exhibit smaller anterior cingulate gray matter volumes than patients who remitted.
The participants were 41 non-demented individuals with non-psychotic major depression. After a 2-week single blind placebo period, subjects who still had a Hamilton Depression Rating Scale (HDRS) of 18 or greater received escitalopram 10 mg daily for 12 weeks. Remission was defined as a HDRS score of 7 or below for at least 2 consecutive weeks. The patient sample consisted of 22 depressed patients who achieved remission during the study and 19 depressed patients who remained symptomatic. High-resolution MPRAGE sequences were acquired on a 1.5 Tesla scanner and regional ACC volumes were manually outlined (dorsal, rostral, anterior subgenual, and posterior subgenual).
Repeated measures analyses revealed that patients who failed to remit following escitalopram treatment had smaller dorsal and rostral anterior cingulate gray matter volumes than patients who remitted, whereas subgenual cortical volumes did not differ between the groups.
Structural abnormalities of the dorsal and rostral anterior cingulate may perpetuate late-life depression.
Geriatric depression is a syndrome often characterized by a slow response to treatment, a failure to fully remit, and a high propensity for relapse (Dew et al., 2007, Little et al., 1998, Whyte et al., 2004). A number of neurobiological abnormalities, particularly in frontolimbic networks, often are present in the illness; however, the specific contributions of these abnormalities to the clinical presentation and the course of the illness remain unclear. MRI can be used to elucidate the pathophysiology of geriatric depression by identifying structural abnormalities that are not merely present in depressed patients, but are also related to treatment response.
Among the frontolimbic networks that are implicated in depressive syndromes in the elderly, the anterior cingulate cortex (ACC) may play a key role (Alexopoulos et al., 2008a). The anterior cingulate appears to be critical in the interaction of dorsal/cortical and ventral/limbic networks that are integral to the experience and regulation of emotion (Phillips et al., 2003, Phillips et al., 2008). Based on convergent data from cytoarchitectural, lesion, and functional connectivity studies, the ACC can be divided into two major subdivisions: the dorsal ACC (BAs 24b’-c’ and 32′) and the perigenual ACC (rostral BAs 24a–c and 32, and subgenual areas BAs 25 and 33) (Devinsky et al., 1995, Vogt et al., 1992). The dorsal ACC subdivision projects to the prefrontal cortex and plays a critical role in executive functions by influencing multiple cognitive processes that include response selection, cognitive inhibition, conflict monitoring and resolution, novelty detection, working memory, and error detection (Botvinick et al., 2004, Bush et al., 2000, Carter et al., 1998, Carter and van Veen, 2007, Drevets, 1998, Stuss et al., 2001). The perigenual ACC subdivision projects directly to the amygdala, periaqueductal gray, nucleus accumbens, hypothalamus, anterior insula, hippocampus and orbitofrontal cortex (Devinsky et al., 1995). The perigenual ACC is involved in assessing the salience of emotional input and the regulation of emotional responses (Drevets, 1998, Etkin et al., 2006, Whalen et al., 1998)
Structural MRI studies have revealed volume reductions in the ACC of elderly depressed patients (Ballmaier et al., 2004, Elderkin-Thompson et al., 2008, Lavretsky et al., 2007). In addition to smaller volumes, functional neuroimaging suggests that depression is associated with abnormal activation of the ACC that is characterized by increased metabolism/activation in the subgenual and rostral anterior cingulate and hypometabolism/hypoactivation of the dorsal anterior cingulate (Aizenstein et al., 2008, de Asis et al., 2001, Drevets et al., 2002, Holthoff et al., 2004, Kennedy et al., 2001, Mayberg et al., 1999, Smith et al., 1999, Takami et al., 2007)
Neuroimaging studies suggest that the anterior cingulate cortex may play a role in the response of depressive symptoms to treatment. Improvement of depression is often associated with at least partial normalization of abnormal activation of the anterior cingulate (Aizenstein et al., 2008, Drevets et al., 2002, Holthoff et al., 2004, Kennedy et al., 2001, Kennedy et al., 2007, Mayberg et al., 1999, Robertson et al., 2007, Saxena et al., 2002). In young and middle aged adults, smaller volumes of the dorsal and rostral ACC are associated with greater symptom severity during depressive episodes, whereas smaller volumes of the subgenual ACC predict poor treatment response (Chen et al., 2007). Although diffusion tensor imaging (DTI) studies of elderly depressed patients suggest that reduced white matter integrity lateral to the dorsal and rostral ACC is associated with failure to remit with antidepressant treatment (Alexopoulos et al., 2002, Alexopoulos et al., 2008b), studies that examine the relationship between anterior cingulate gray matter volumes and treatment response in geriatric patients are lacking.
The rationale for this study is that structural abnormalities of the anterior cingulate may perpetuate depressive symptoms, and, thus, contribute to poor treatment response. Thus, we hypothesized that depressed elders who fail to achieve remission during treatment with escitalopram would have smaller gray matter volumes in the anterior cingulate than those who remit with treatment. Based on the evidence that relatively functionally distinct subregions of the ACC exist, we explored the relationship of treatment response to 4 regions of interest (ROIs); dorsal ACC, rostral ACC, anterior subgenual ACC, and posterior subgenual ACC.
Participants included 41 depressed, elderly (> 60 years) patients from a university-based geriatric psychiatry clinic who were recruited for an escitalopram treatment trial. Scans were performed during a 2-week single blind antidepressant/anxiolytic drug washout/placebo lead-in phase. Participants met DSM-IV-TR criteria for unipolar major depression and had a score > 18 on the 24-item Hamilton Depression Rating Scale (HDRS) (Williams, 1988). Exclusion criteria were 1) major depression with psychotic features (according to DSM-IV-TR); 2) history of other psychiatric disorders (except personality disorders) before the onset of depression; 3) severe medical illness (i.e., metastatic cancer, brain tumors, unstable cardiac, hepatic, or renal disease, myocardial infarction, or stroke) within the 3 months preceding the study; 4) neurological disorders (i.e., dementia or delirium according to DSM-IV criteria, history of head trauma, Parkinson’s disease, and multiple sclerosis); 5) conditions often associated with depression (i.e., endocrinopathies other than diabetes, lymphoma, and pancreatic cancer); 6) drugs causing depression (i.e., steroids, α-methyl-dopa, clonidine, reserpine, tamoxifen, and cimetidine); 7) Mini-Mental State Examination (Folstein et al., 1975) score < 25; and 8) contraindications to MRI scanning. These criteria resulted in a group of elderly patients with non-psychotic unipolar major depression without a diagnosable dementing disorder. Depressive symptoms and severity were assessed using the HDRS and DSM-IV TR criteria. Side effects of escitalopram were monitored with the UKU side effect scale (Lingjaerde et al., 1987). Baseline gross cognitive status was assessed with the Mini-Mental State Examination (Folsten et al., 1975).
The Weill Cornell Medical College and Rockland Psychiatric Center/Nathan S. Kline Institute (NKI) for Psychiatric Research Institutional Review Boards approved all procedures. After complete description of the study to subjects, written informed consent was obtained.
Upon entering the study, patients were informed that they would receive placebo at some point during their 14-week trial. After a 2-week antidepressant/anxiolytic drug wash-out and single blind placebo lead-in, subjects who still met DSM-IV-TR criteria for major depression and had an HDRS score of 18 or greater received treatment with escitalopram 10 mg daily for 12 weeks. Patients were instructed to take a single dose of escitalopram in the morning. Subjects were administered medication in one-week supply blisters that permitted dispensation of their daily dosage separately.
The treatment phase consisted of weekly follow up sessions beginning with the placebo lead-in, until the 12th week of treatment with escitalopram. During each follow-up meeting, a research assistant administered the HDRS, the UKU, obtained vital signs, questioned the subjects about medication adherence, and counted the remaining tablets. The meeting with the research assistant was followed by a brief session with a research psychiatrist to assess the subjects’ clinical status. The session followed a medication clinic model consisting of a review of psychiatric symptoms, including safety aspects, potential study drug side effects, changes in medication or medical status, explanations related to the need for treatment, and encouragement of treatment adherence. No subject received psychotherapy or any other psychiatric treatment during the study. Subjects were considered in remission if they no longer met DSM-IV-TR criteria for depression and had an HDRS score of 7 or below for two consecutive weeks.
Scanning took place on a 1.5T Siemens Vision scanner (Erlangen, Germany) housed at NKI’s Center for Advanced Brain Imaging. Scans were performed during the 2-week single blind drug washout/placebo lead-in phase of the treatment trial. Patients received a magnetization prepared rapidly acquired gradient echo (MPRAGE) scan (TR=11.6 ms, TE=4.9 ms, matrix=256×256, FOV=320 mm, NEX=1, slice thickness = 1.25 mm, 172 slices, no gap), as well as a turbo dual spin echo scan (TSE; TR= ms, TE=22/90 ms, matrix=256×256, FOV=240 mm, slice thickness = 5 mm, 26 slices, no gap).
After acquisition, all MR images were processed using MedX 3.23 (Sensor Systems, Sterling, VA). The MPRAGE images were reformatted off-line and corrected for undesirable effects of head tilt, pitch, and rotation using standard neuroanatomical landmarks. The realignment process consisted of the following steps. First, to correct for head pitch, the axial plane was tilted so it passed through the anterior and posterior commissures (incorporating the AC-PC line). In the next step, head tilt was adjusted using the coronal plane, which was fixed interactively by forcing it through the orbits in such a way that the coronal cross section of the orbits on the right and the left side of the head was level and of equal diameter. After correcting for head tilt, the mid-sagittal plane was moved to pass along the straight line drawn through the interhemispheric fissure.
Images were displayed on a 21 in. monitor and each ROI was traced manually. All questionable cases were resolved by consulting the corresponding images in MRI neuroanatomy atlases. Interrater reliability was computed from measures by two trained operators who traced a random sample of 10 brains. The intraclass correlation formula for two random raters (ICC(2) (Shrout and Fleiss, 1979) was used, and the resulting reliability estimates for all ROIs exceeded 0.90. All structures were measured separately for each hemisphere. The ROIs for ACC subregional volume estimation were modified from guidelines established by McCormick and colleagues (McCormick et al., 2006). The examples of traced ROIs are depicted in Fig. 1. Manual tracing of subregions was performed on every coronal slice of the ACC according to the boundaries defined below, starting from the most anterior slice and moving posterior. A region of interest (ROI) was created by circling the entire gyrus, including white matter. Next, to obtain gray matter volumes, each ROI was multiplied by the individual subject’s whole brain gray matter mask that was created using FSL’s Brain Extraction Tool (BET) and FMRIB’s Automated Segmentation Tool (FAST) software (www.fmrib.ox.ac.uk/fsl; (Zhang et al., 2001). A whole brain volume was calculated for each subject by summing the total white matter and gray matter volumes that were obtained using FAST. When sulcal variations arose, we distinguished a true second cingulate from a paracingulate gyrus by determining whether the second cingulate sulcus CS became the deepest sulcus within the dorsal or rostral regions when viewed on the coronal view. The deepest sulcus was used to determine the boundaries of the ACC. Any secondary or external sulci that were not deepest were considered to be a paracingulate gyrus and were not included in the ACC.
The volume of the rostral ACC was computed from coronal slices located anterior to the genu of the corpus callosum. The anterior boundary was the first slice on which the cingulate gyrus appeared and extended posteriorly to include the slice just anterior to the appearance of the genu of the corpus callosum. The inferior boundary was the inferior branch of the cingulate, whereas the superior boundary was the superior branch of the cingulate sulcus. The rostral ACC covers Brodmann areas 24a, 24b, and 24c.
Measurement of the dorsal ACC began on the most anterior slice containing the genu of the corpus callosum. The most posterior slice of the ACC was located in the sagittal plane as the coronal slice through the middle of the first superior gyrus anterior to the joining of the ascending marginal sulcus and the prominent cingulate sulcus. This boundary approximates the boundaries between the BA 23 (posterior cingulate) and BA 24 of the anterior cingulate. The inferior boundary was the deepest point of the callosal sulcus, whereas the superior boundary was the deepest point of the cingulate sulcus. The dorsal ACC is comprised of Brodmann areas 24b’-c’ and 32′.
The anterior boundary of the anterior subgenual ACC was the most anterior slice on which the genu of the corpus callosum was present. The posterior boundary was one slice anterior to where the putamen first became visible within the basal ganglia. A secondary gyrus was included only if the secondary sulcus was the deepest sulcus seen on the coronal plane and the secondary gyrus was not deemed to be the medial frontal cortex. When the deepest sulcus ventral to the corpus callosum included the medial frontal cortex, the inferior boundary of the anterior subgenual ACC (the ventral CS) was defined by a smaller sulcus. This inferior boundary was continuous with the ventral portion of the rostral ACC. The superior boundary was defined at the margin where the gray matter intersected with the white matter of the corpus callosum. The anterior subgenual region included the continuation of the rostral cingulate gyrus (BA 24a and 24b) wrapping around the corpus callosum and generally corresponded to the subgenual region identified previously by Drevets and colleagues 2002 (Drevets et al., 2002).
The anterior boundary of the posterior subgenual ACC began where the putamen was first visible. This typically corresponded to the point of transition between the horizontally oriented posterior subgenual continuation of the cingulate gyrus and the beginning of the paraterminal gyrus. The posterior boundary was the coronal slice where the paraterminal gyrus was no longer present medially. As with the anterior subgenual ACC, the superior boundary was identified where gray matter joined with white matter of the corpus callosum. The inferior boundary was located at the inferior tip of the lower-most gyrus on the medial surface. The posterior subgenual ROI included BA25.
The study sample was derived from a larger sample of 55 patients who met study eligibility criteria and entered the 2-week single-blind, placebo lead-in period. Of these, 41 completed the MPRAGE sequence of the MRI scan, met symptom severity criteria after the 2-week placebo phase, and entered the 12-week escitalopram treatment phase. Of these 41 subjects, 33 completed the 12-week treatment trial. There were 8 subjects who did not complete the treatment trial. Of these subjects, 2 had 4 weeks of treatment (both exited due to worsening of their depression), 2 had 7 weeks of treatment (1 exited because he found the treatment ineffective and 1 withdrew because she developed hyponatremia), 1 had 8 weeks of treatment and exited because he found the treatment ineffective, 1 had 9 weeks of treatment and exited because of worsening depression and 2 had 11 weeks of treatment with escitalopram and exited because they found the treatment ineffective). All but one of these eight patients failed to achieve remission. The sample for the current study overlapped substantially with that reported in (Alexopoulos et al., 2008b).
The sample consisted of depressed patients who achieved remission during the study (Remitters, N = 22), and depressed patients who failed to achieve remission (Non-Remitters, N = 19). Although at baseline HDRS did not differ between Remitters and Non-Remitters, at study exit Remitters had significantly lower HDRS ratings than did Non-Remitters ( t (28.5) = 7.12, p < .001).
The descriptive statistics for the volumes of the 4 ACC ROIs are presented for each hemisphere in Table 2. The relationship of remissions status to differences in regional ACC volumes was examined within the framework of a mixed general linear model. In the model, remission status was a two-level categorical variable (Remitter, Non-Remitter, whereas hemisphere (Right, Left) and ACC ROI (rostral, dorsal, anterior subgenual, posterior subgenual) were within subjects repeated measures. In addition, age and whole brain volume were entered as covariates to statistically control for their influence.
The full linear model for the regional volumes revealed a significant interaction: Remission Status × ROI (F[3, 35]= 6.19, P<0.01), meaning the relationship of Remission Status to volume of ACC cortex differed across regions. In addition, there was a significant main effect of ROI (F[3,35]=3.95, P < 0.05). As expected, the largest volumes were observed in the dorsal ROI, followed by the rostral ROI, then the anterior subgenual and posterior subgenual ROIs.
To examine the pattern of the observed influence of remission status on each ROI, we decomposed the Remission Status × ROI interaction into simple effects and ran separate MANCOVA’s for each ROI, with age and whole brain volume as covariates, remission status as a between subject variable, and hemisphere as a within subject repeated measure. Dorsal ACC: This model revealed a significant main effect of Remission Status (F[1,37]=6.65, P < 0.05). Relative to Non-Remitters, Remitters had significantly larger dorsal ACC gray matter volumes. There were no significant interactions. Rostral ACC: This analysis revealed a significant main effect of Remission Status (F[1,37]=7.86, P < 0.01). Relative to Non-Remitters, Remitters had significantly larger rostral ACC gray matter volumes. There were no significant interactions. Anterior Subgenual ACC: This model revealed a significant hemisphere × age interaction (F[1,37]= 4.90, P < 0.05), but no significant main effects; Remission Status F[1,37]= 0,02, P = 0.91). Posterior Subgenual ACC: This model did not yield a significant effect of Remission Status (F[1,37]= 0,85, P = 0.37).
The main observation of this study is that depressed elderly patients who did not remit after treatment with escitalopram had smaller volumes of the dorsal and rostral anterior cingulate cortex compared with depressed elders who achieved remission. To our knowledge, this is the first study to identify a relationship between ACC gray matter volumes and geriatric depression response to antidepressant treatment.
The current findings extend previous reports that structural alterations of the ACC are present in late-life depression and may be implicated in some of the clinical features and course of the illness. That is, smaller ACC volumes have been reported in elderly depressed patients relative to age-matched controls (Ballmaier et al., 2004, Elderkin-Thompson et al., 2008, Lavretsky et al., 2007). Smaller ACC gray matter volumes are associated with more apathy in elderly depressed patients (Lavretsky et al., 2007). In addition, smaller volumes of the ACC cortex are associated with poorer performance on tasks of working memory and abstract reasoning (Elderkin-Thompson et al., 2008), whereas low fractional anisotropy lateral to the dorsal ACC and in striatal regions is associated with poor performance on a task of cognitive inhibition (Murphy et al., 2007). Furthermore, the findings from this study complement our recently reported DTI findings from an overlapping sample, which suggest that, in addition to other cortico-striatal-limbic regions, reduced white matter integrity lateral to the dorsal and rostral ACC (Alexopoulos et al., 2008b) predicts failure to remit with antidepressant treatment.
Functional neuroimaging studies, primarily of young and middle aged depressed patients, indicate that metabolism/activation of dorsal and rostral cingulate during depressive states is abnormal and predicts subsequent response to antidepressant treatment. Specifically, the dorsal ACC often is hypometabolic during depression while the perigenual ACC is hypermetabolic (Aizenstein et al., 2008, de Asis et al., 2001, Drevets et al., 2002, Mayberg, 2003, Seminowicz et al., 2004, Takami et al., 2007). Greater activation of the rostral and dorsal cingulate at baseline predicts better subsequent treatment response of depression (Chen et al., 2007, Davidson et al., 2003, Langenecker et al., 2007). Furthermore, remission of depression is often associated with at least partial normalization of ACC activation/metabolic abnormalities (Holthoff et al., 2004, Kennedy et al., 2001, Kennedy et al., 2007, Mayberg et al., 1999, Robertson et al., 2007, Saxena et al., 2002, Wu et al., 1999). One explanation of our current findings is that the observed volumetric differences in Non-Remitters in the dorsal and rostral ACC interfere with the normalization of ACC activity which, in turn, reduces the ACC’s efficiency in the reciprocal regulation of dorsal neocortical-ventral limbic structures.
One limitation of the current study is the lack of a placebo control group. In addition, given that remission status was based on both a fixed dose of escitalopram and 12-week course of treatment, it is possible that some subjects may have remitted if either treated with higher dosages of escitalopram or longer treatment were offered. However, 6 out of 8 non-remitted subjects who exited the trial had 7-11 weeks of escitalopram treatment and 2 had 4 weeks of treatment. Another limitation of the study is that fewer neuronal bodies, smaller neuronal size, and decreases in dendritic arborization are all potential sources of smaller gray matter volumes on T1-weighted images; however, the specific neurohistologic processes that account for the observed volume differences between Remitters and Non-Remitters cannot be distinguished. Furthermore, the present study can only speak to the relationship of volumes of the ACC to treatment remission of depressive symptoms in the elderly and cannot address the potential relationship of other structures (e.g., amygdala, orbitofrontal cortex) to treatment response.
In conclusion, this study indicates that smaller cortical volumes of the dorsal and rostral ACC increase the risk for chronicity of geriatric depression. Anterior cingulate abnormalities may perpetuate late-life depression by interfering with the interaction of limbic-cortical systems critical for emotional regulation. These findings set the stage to explore the relationship of structural abnormalities of the anterior cingulate to treatment outcomes within the context of a functional neuroimaging study of geriatric depression. The identification of specific structure/function network abnormalities associated with treatment response can generate investigations of specifically targeted novel therapeutic interventions.
This work was supported by National Institute of Mental Health grants P30 MH68638 (GSA), R01 MH65653 (GSA), and K23 MH074818 (FGD), the Sanchez Foundation, the TRU Foundation, and Forest Pharmaceuticals. The authors thank Raj Sangoi RT ( R ) MR for his work as chief MR technologist.
Conflict of Interest: None
Disclosures: Dr. Alexopoulos has received a research grant by Forest Pharmaceuticals, Inc. for support for this study and is a consultant for Forest Pharmaceuticals. In addition, Dr Alexopoulos has the following financial interests to disclose: A research grant from Cephalon. Financial compensation as a speaker for Cephalon, Forest, Sanofi-Aventis, Novartis, Lilly, Bristol Meyers Squibb, Glaxo-Smith Kline, Pfizer, and Janssen; Financial compensation as a consultant for Sanofi-Aventis, and Novartis. Dr. Klimstra has received financial compensation from Eisai Medical Research Inc. for professional service unrelated to the work presented here. Drs. Gunning-Dixon, Murphy, Morimoto, and Hoptman, Ms. Cheng, Acuna, and Kanellopoulos, and Mr. Weinberg have no financial interests to disclose.