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Macromolecular White Matter Abnormalities in Geriatric Depression: A Magnetization Transfer Imaging Study
REGULAR RESEARCH ARTICLES
Macromolecular White Matter Abnormalities in Geriatric Depression: A Magnetization Transfer Imaging Study Faith M. Gunning-Dixon, Ph.D., Matthew J. Hoptman, Ph.D., Kelvin O. Lim, M.D., Christopher F. Murphy, Ph.D., Sibel Klimstra, M.D., Vassilios Latoussakis, M.D., Magdalena Majcher-Tascio, B.A., Jan Hrabe, Ph.D., Babak A. Ardekani, Ph.D., George S. Alexopoulos, M.D.
Objective: Geriatric depression consists of complex and heterogeneous behaviors unlikely to be caused by a single brain lesion. However, abnormalities in specific brain structures and their interconnections may confer vulnerability to the development of late-life depression. The objective of this study was to identify subtle white matter abnormalities in late-life depression. Design: The authors used magnetization transfer ratio (MTR) imaging, a technique that is thought primarily to reflect myelin integrity, to examine the hypothesis that individuals with late-life depression would exhibit white matter abnormalities in frontostriatal and limbic regions. Setting: The study was conducted in a university-based, geriatric psychiatry clinic. Participants: Fifty-five older patients with major depression and 24 elderly comparison subjects were assessed. Measurement: Voxel-based analysis of MTR data were conducted with a general linear model using age as a covariate. Results: Relative to comparison subjects, patients demonstrated lower MTR in multiple left hemisphere frontostriatal and limbic regions, including white matter lateral to the lentiform nuclei, dorsolateral and dorsomedial prefrontal, dorsal anterior cingulate, subcallosal, periamygdalar, insular, and posterior cingulate regions. Depressed patients had lower MTR in additional left hemisphere locales including the thalamus, splenium of the corpus callosum, inferior parietal, precuneus, and middle occipital white matter regions. Conclusion: These findings suggest that geriatric depression may be characterized by reduced myelin integrity in specific aspects of frontostriatal and limbic networks, and complement diffusion tensor studies of geriatric depression that indicate decreased organization of white matter fibers in specific frontal and temporal regions. (Am J Geriatr Psychiatry 2008; 16:255–262) Key Words: Geriatric depression, magnetization transfer imaging, white matter
Received May 7, 2007; revised September 13, 2007; accepted September 19, 2007. From the Institute of Geriatric Psychiatry and the Department of Psychiatry, Weill Medical College of Cornell University (FMG-D, CFM, SK, VL, MM-T, GSA), Weill Cornell Institute of Geriatric Psychiatry, White Plains; the Division of Clinical Research and the Center for Advanced Brain Imaging, Nathan S. Kline Institute for Psychiatric Research (MJH, JH, BAA), Orangeburg; Department of Psychiatry (MJH, BAA), New York University School of Medicine, NY; and the Department of Psychiatry, University of Minnesota (KOL), Minneapolis, MN. Send correspondence and reprint requests to Faith M. Gunning-Dixon, Ph.D., 21 Bloomingdale Road, White Plains, NY 10605. e-mail: [email protected] © 2008 American Association for Geriatric Psychiatry
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onverging evidence suggests that abnormalities in specific frontostriatal and limbic structures and their interconnections may confer vulnerability to the development of late-life depression. Structural magnetic resonance imaging (MRI) methods can be used to identify and quantify these cerebral network abnormalities predisposing to geriatric depression.1 Earlier, structural MRI studies of late-life depression have provided support for the role of frontostriatal and limbic abnormalities in late-life depression. Gray matter volume reductions are present in multiple frontostriatal–limbic regions of older depressed individuals, including the anterior cingulate, prefrontal cortices, the neostriatum, and the hippocampus.2– 6 White matter hyperintensities (WMH) are more prevalent and severe in depressed older individuals than elderly comparison subjects, mainly occur in subcortical regions and their frontal white matter projections,7–10 and are associated with executive dysfunction.11 Recent advances in MRI techniques allow the in vivo identification of white matter microstructural abnormalities in late-life depression. Diffusion tensor imaging (DTI), a technique used to measure organization of fiber tracts, has revealed that depressed elderly patients exhibit compromised integrity (i.e., reduced fractional anisotropy [FA] of the white matter) of the dorsolateral prefrontal cortex, anterior cingulate, and temporal regions.12–14 Furthermore, in a preliminary DTI study, reduced FA of the white matter lateral to the anterior cingulate gyrus was associated with poor response to citalopram in depressed older patients.15 Magnetization transfer ratio (MTR) imaging is another method that can be used to study white matter abnormalities. MTR imaging provides information about the macromolecular structure of cerebral white matter based on the interaction of the normally observed tissue water signal with protons contained in large macromolecules (including myelin). Macromolecular semisolid structures in the brain, such as myelinated axons, are ordinarily invisible to MRI because of their extremely short transverse relaxation times. However, protons bound to them can transfer magnetization to those of the freely moving tissue water, e.g., by chemical exchange. To achieve MTR contrast, two acquisitions are required. The first obtains a proton density-weighted image with signal proportional to the amount of free water. The
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second employs an additional off-resonance radiofrequency pulse before the basic proton density sequence, which selectively nulls magnetization of the bound protons. Because some of these protons subsequently enter the free water compartment, magnetization available there becomes smaller and the magnetic resonance signal is reduced. Contrast between these two images is usually expressed as the MTR ⫽ (M0 ⫺ MSAT)/M0. Reduction in macromolecular volume fraction is therefore reflected in the reduced MTR. Studies conducted in early development, aging, and multiple sclerosis suggest that DTI and MTR may provide complementary information about white matter integrity with DTI primarily reflecting organization of fibers tracts and MTR being particularly sensitive to myelin and, to a lesser degree, axonal integrity.1,16 MTR may be a particularly informative tool for examining cerebral abnormalities in late-life depression given its apparent reliance on myelin and axonal integrity and its demonstrated effectiveness in examining the effects of both normal aging and aging-related illnesses on the brain.16 Kumar et al.17 demonstrated the value of MTR in a preliminary study of white matter abnormalities in geriatric depression. They examined MTR in eight patients with late-life depression and eight nondepressed comparison subjects. Their results suggest that relative to their elderly counterparts older depressed patients have lower MTR in the genu and splenium of the corpus callosum, the neostriatum, and the occipital white matter. We report here an exploratory analysis employing whole-brain voxelwise methodology to identify brain regions that show reduced MTR in patients with geriatric depression relative to nonpsychiatric comparison participants who were comparable in age. We hypothesized that depressed elders would exhibit lower MTR in frontostriatal and limbic regions than elderly comparison subjects, but used a whole-brain voxelwise analysis to evaluate the specificity of our findings.
METHODS Participants The depressed participants were 55 (⬎60 years) psychiatric patients from a university-based clinic of
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Gunning-Dixon et al. geriatric psychiatry who were recruited for an escitalopram treatment trial. Scans were performed during a 2-week single blind drug washout and placebo lead-in phase. Participants met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSMIV)-TR criteria and Research Diagnostic Criteria for unipolar major depression and had a score ⬎18 on the 24-item Hamilton Depression Rating Scale.18 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 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, ␣-methyl-dopa, clonidine, reserpine, tamoxifen, and cimetidine); 7) Mini-Mental State Exam19 score ⬍25; and 8) contraindications to MRI scanning. These criteria resulted in a group of elderly patients with nonpsychotic unipolar major depression without a diagnosable dementing disorder (Table 1). Comparison Participants. An elderly group of community-dwelling volunteers were recruited by advertisements using radio and newspaper announcements. Additional exclusion criteria were current or history of Axis I disorders as well as current or previous psychiatric treatment. The Weill Cornell and Rockland Psychiatric Center/Nathan S. Kline Institute for Psychiatric Research
Institutional Review Boards approved all procedures. After complete description of the study to subjects, written informed consent was obtained.
Magnetic Resonance Imaging Scanning took place on a 1.5T Siemens Vision scanner (Erlangen, Germany) housed at Nathan S. Kline Institute’s Center for Advanced Brain Imaging. Scans were performed during a 2-week single blind drug washout or placebo lead-in phase of the treatment trial. Patients received a magnetization prepared rapidly acquired gradient echo scan (repetition time [TR] ⫽ 11.6 milliseconds, echo time [TE] ⫽ 4.8 milliseconds, TI ⫽ 1,018 milliseconds, matrix ⫽ 256 ⫻ 256, field of view [FOV] ⫽ 320 mm, numbers of excitation ⫽ 1, slice thickness ⫽ 1.25 mm, 172 slices), as well as a turbo dual spin echo scan (TR ⫽ 9,000 milliseconds, TE ⫽ 22/90 milliseconds, matrix ⫽ 256 ⫻ 256, FOV ⫽ 240 mm, slice thickness ⫽ 5 mm, 26 slices, no gap). Subjects also received an MTR imaging sequence based on a three-dimensional fast low angle shot method. Slices were positioned identically to the dual turbo spin echo scan, in an oblique axial plane parallel to the anterior commissure–posterior commissure axis. The acquisition parameters were FOV ⫽ 240 mm, 32 slices 5 mm thick, matrix ⫽ 256 ⫻ 256, TR ⫽ 31 milliseconds, and TE ⫽ 6 milliseconds. One acquisition was performed with and another one without the magnetization transfer saturation pulse. This pulse had a Gaussian shape with effective bandwidth of 250 Hz and was offset from the resonance frequency by 1.5 kHz.
Postprocessing TABLE 1. Baseline Demographic and Clinical Characteristics of 55 Elderly Patients with Major Depression and 24 Nondepressed Controls
Variable Age (yr) Education (yr) Male (%) HDRS MMSE
Depressed Elders Mean ⴞ SD
Comparison Group Mean ⴞ SD
69.9 ⫾ 6.1 15.4 ⫾ 2.9 41 23.7 ⫾ 4.0 28.4 ⫾ 1.5
71.8 ⫾ 6.1 16.5 ⫾ 2.4 30 1.5 ⫾ 1.7 28.7 ⫾ 1.1
t value (df ⴝ 77)
p
1.31 1.83
0.20 0.07
26.8 0.82
0.001 0.42
Notes: Values are mean ⫾ standard deviation unless otherwise noted. HDRS: Hamilton Depression Rating Scale; MMSE: Mini-Mental State Exam.
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The MTR was computed for each voxel as: MTR ⫽ (M0 ⫺ MSAT)/M0, where M0 is the image intensity without the off-resonance saturation pulse and MSAT is the signal with the saturation pulse.20The MTR was computed for each voxel using FMRIB Software Library programs (http://www.fmrib.ox.ac.uk/fsl/ bet2/index.html). MTR images were placed into Talairach space using methods described elsewhere.21 Intersubject registration was carried out using the Automatic Registration Toolbox software. We have recently shown this method to be superior to registrations performed by Statistical Parametric Map-
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White Matter Abnormalities in Geriatric Depression ping (99) and Automatic Image Registration software.22 The T1-weighted template used for the registrations was derived from a subject whose intracranial content volume was the closest to the mean for the first five subjects. The volumes were computed in MEDx (Sensor Systems, Sterling, VA) after skull stripping, which was done using FMRIB Software Library’s BET (http://www.fmrib.ox.ac.uk/fsl/bet/ index.html) program. The case we chose to use as a template was placed into Talairach space using the AFNI software23 using the standard Talairach piecewise linear landmark-based normalization. To limit the number of statistical comparisons, we created a white mask based on the average FA map obtained from DTI on the same subjects. The DTI scan (TR ⫽ 6000 milliseconds, TE ⫽ 100 milliseconds, matrix ⫽ 128 ⫻ 128, FOV ⫽ 320 mm, numbers of excitation ⫽ 7, slice thickness ⫽ 5 mm, 19 slices, no gap) sampled eight noncollinear diffusion sensitization directions (with b ⫽ 1,000 second/mm2). In addition, an image with no diffusion weighting (b ⫽ 0 second/mm2) was acquired. For each subject, FA was computed using AFNI’s nonlinear algorithm (3dDWItoDT). The resulting FA maps were placed into standard space as described above. An average map was computed from the normalized FA maps and was threshold using a nonparametric histogrambased segmentation.24 The obtained white matter threshold was applied to the mean FA image, and the resulting white matter mask was used in the analysis on MTR data. The FA image was used to create the mask because of its excellent gray-white contrast. Voxel-based analysis of MTR data with respect to group membership (depressed patients, comparison subjects) was conducted using a general linear model. To reduce error variance that may be related to age, we included age as a covariate in the analysis. To control for Type I error, we used a modified version of the thresholding method described by Baudewig et al.25 of detecting adjacent voxels that are statistically significant and applying a constraint that one of the voxels must be significant at a more stringent p value. In addition, we applied the constraint that at least 100 neighboring voxels must reach significance. Thus, our approach finds clusters of voxels (100 mm3) each with significant group differences (p ⬍0.05) and then applies the constraint
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that one of the voxels in the cluster must be significant at p ⬍0.005. The thresholded correlation maps were superimposed onto a magnetization prepared rapidly acquired gradient echo image in Talairach space using AFNI.
RESULTS Relative to elderly comparison subjects, patients demonstrated lower MTR in multiple left hemisphere frontostriatal and limbic white matter regions, including white matter lateral to the lentiform nuclei, dorsomedial and dorsolateral prefrontal, dorsal anterior cingulate, periamygdalar, subcallosal, lentiform, insular, and posterior cingulate regions (Table 2). Depressed patients had lower MTR in additional left hemisphere locations including the thalamus, splenium of the corpus callosum, inferior parietal, precuneus, and middle occipital regions. In contrast, comparison subjects had lower MTR in a right postcentral region (Figure 1).
DISCUSSION The main finding of this study is that late-life depression is characterized by reduced MTR in multiple left hemisphere frontostriatal and limbic white matter regions including white matter lateral to the lentiform nuclei, dorsolateral and dorsomedial prefrontal, dorsal anterior cingulate, insula, periamygdalar, subcallosal, and posterior cingulate white matter regions. Our findings extend the report of Kumar et al. of lower MTR in the genu and splenium of the corpus callosum, the neostriatum, and the occipital white matter in a small sample of elderly depressed patients.17 The MTR observations are consistent with evidence from MRI findings of volume reductions in frontal, striatal, and limbic regions as well as increased prevalence and severity of WMH in geriatric depression.1 Furthermore, these findings complement diffusion tensor studies of geriatric depression that indicate the presence of decreased organization of white matter fibers in select frontal and temporal regions,12–14 as well as activation studies that have detected hypoactivation of the dorsal anterior cingulate, hippocampus, dorsolateral prefrontal cortex,
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Gunning-Dixon et al.
TABLE 2. Clusters of Significant MTR Differences Between Elderly Depressed Patients and Elderly Comparison Subjects After Controlling for Age X (ⴙRight) ⫺29 ⫺14 ⫺7 ⫺28 ⫺33 ⫺29 ⫺24 ⫺33 ⫺22 ⫺13 ⫺22 ⫺27 ⫺44 ⫺16 ⫺18 ⫺4 ⫺30 28
Y (ⴙAnterior)
Z (ⴙSuperior)
Cluster Size
Mean t Value
Anatomical Region
4 35 4 ⫺8 17 ⫺19 11 ⫺14 ⫺50 ⫺36 ⫺59 ⫺53 ⫺22 ⫺21 ⫺9 ⫺35 ⫺60 ⫺33
⫺7 29 30 39 15 17 ⫺5 1 15 31 25 30 29 3 13 20 4 45
377 102 161 206 399 101 224 278 211 276 368 261 283 235 223 120 218 139
⫺2.36 ⫺2.43 ⫺2.53 ⫺2.30 ⫺2.50 ⫺2.30 ⫺2.57 ⫺2.35 ⫺2.36 ⫺2.55 ⫺2.48 ⫺2.37 ⫺2.33 ⫺2.38 ⫺2.33 ⫺2.39 ⫺2.40 2.26
L periamygdalar/subcallosal/lentiform L dorsomedial prefrontal L dorsal anterior cingulate L middle frontal/dorsal anterior cingulate L insula L insula L lentiform L lentiform L posterior cingulate L posterior cingulate L posterior cingulate/precuneus L precuneus L inferior parietal L thalamus L thalamus L splenium L middle occipital R postcentral
Notes: Talairach coordinates reflect peak of cluster. t value is the mean t value of each cluster. All voxels in each cluster were significant at a two-tailed p ⬍0.05 with at least one voxel in each cluster significant at p ⬍0.005. df for all t values ⫽ 77. Cluster size is in number of voxels.
and neostriatum in elderly depressed patients relative to comparison subjects.26,27 Models of the neurobiology of emotion have identified two neuroanatomical systems, a ventral and a dorsal, that appear critical to the processing of emotional stimuli.28 The ventral system, which includes the amygdala, insula, ventral striatum, ventral anterior cingulate, and orbitofrontal cortex, is important for the evaluation of the emotional significance of incoming stimuli and generation of an affective response.28 The dorsal system, comprised of the dorsal anterior cingulate, dorsolateral prefrontal cortex, and the hippocampus, is critical for the cognitive regulation of affective responses. The ventral and dorsal systems have reciprocal connections, and dysfunction in either network may result in poor emotional regulation. Depression is believed to be characterized by increased negative bias in the assessment of incoming stimuli within the ventral system, accompanied by decreased regulation of the affective response by the dorsal system.29 We propose that reduced MTR in older depressed individuals may confer vulnerability to late-life depression. The reductions of MTR in frontostriatal and limbic regions in older depressed individuals overlap with the systems described above including the dorsolateral prefrontal regions, lentiform nuclei, dor-
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sal anterior cingulate, periamygdalar regions, and insula. MTR decreases in white matter are typically observed in diseases associated with myelin or axon loss.16 Histopathological data from postmortem multiple sclerosis brains suggest that MTR correlates with both axonal and myelin count, with myelin count being a primary, but not sole determinant, of reduced MTR.30 Furthermore, the developmental neuroimaging literature indicates that increases in MTR coincide with brain myelination during the early years of life.16 Thus, reductions observed in MTR of white matter appear to be primarily an index of reduced myelin integrity. These converging lines of evidence support the premise that MTR reductions in late-life depression may reflect compromised white matter in frontostriatal and limbic pathways that may lead to a “disconnection-syndrome,” which interferes with the reciprocal regulation of dorsal cortical-ventral limbic systems (for reviews see Refs. 31 and 32). Notably, reduced MTR in late-life depression was more diffuse than we expected as it not only occurred in frontostriatal and limbic regions, but also occurred in select posterior regions. These findings of decreased MTR in posterior regions, specifically the thalamus, posterior cingulate, and precuneus, converge with resting state metabolic studies of young and middle-aged individuals that have detected met-
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FIGURE 1.
Clusters of Significant Magnetization Transfer Ratio Differences Between Patients and Comparison Subjects
Notes: Axial and sagittal maps of significant MTR differences between comparison subjects and depressed patients (orange indicates areas in which MTR is lower for patients). Images are in radiological convention. Sagittal images are presented from left to right. Group differences are thresholded such that 100 mm3 clusters of voxels all significant at p ⬍0.05 are identified, with the additional criterion that within each cluster, at least one voxel is significant at p ⬍0.005.
abolic abnormalities in similar regions among depressed patients or during induced sadness.33–36 Furthermore, reduced metabolism in the posterior cingulate and the precuneus has been reported in presymptomatic nondemented individuals who had at least a single Apo epsilon 4 allele.37 Similarly, decreased metabolism in the posterior cingulate, hippocampus, and temporoparietal association areas has
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been observed in patients with mild cognitive impairment who converted to dementia.38 Although our participants were screened for dementia, given the relationship of geriatric depression to increased risk for mild cognitive impairment or dementia it is possible that the inclusion of presymptomatic individuals in the depressed sample may contribute to the macromolecular white matter abnormalities we observed.
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Gunning-Dixon et al. The findings of reduced MTR in patients relative to comparison subjects were observed almost entirely in the left hemisphere. The presence of left hemisphere MTR reductions is consistent with the literature suggesting that left hemisphere stroke is more likely to be accompanied by depression than right hemisphere stroke.39 In addition, some studies of geriatric depression have reported greater diagnostic significance of WMH in left than right hemisphere (e.g., Ref. 7). Furthermore, in an electrophysiological study of 22 older patients with major depression who received controlled treatment with citalopram,40 the nine subjects who remained symptomatic after treatment had larger left frontal error negative waves than the subjects who achieved remission. These electrophysiological findings suggest inefficiency of left hemisphere frontolimbic networks in these individuals. Thus, although we did not predict the lateralized MTR reductions in this study, this intriguing finding should be explored in future MRI studies of cerebral white matter in geriatric depression. Interpretation of the current results is limited by the fact that the large number of comparisons in the voxelwise analysis increases the risk of Type I error. We used a white matter mask to mask the images, which greatly reduced the number of comparisons. We also combined a two-level statistical thresholding technique with a relatively conservative spatial extent requirement of a minimum of 100 voxels in each cluster. Another limitation is that the use of a voxelwise approach requires registration of all of the subjects MTR scans into the same space. Given the known variability in atrophy rates in the elderly, registration of the scans of our sample into the same space may be a source of error in our findings. The identification of macromolecular white matter abnormalities associated with geriatric depression can
guide future studies of specific pathways associated with the pathophysiology of geriatric depression. In light of the relatively diffuse nature of our findings, combining structural and functional imaging methods may help distinguish those white matter abnormalities predisposing to geriatric depression from incidental abnormalities. Furthermore, the examination of the relationship of MTR reductions in late-life depression to clinical features of the illness would allow us to identify those macromolecular abnormalities that are critical to the presentation of the illness. MTR studies, for example, can be used to identify the location of macromolecular white matter abnormalities that are associated with cognitive dysfunction or predict treatment response. The identification of specific pathway abnormalities associated with treatment response can generate investigations of specifically targeted novel therapeutic interventions. The authors thank Raj Sangoi, RT(R) MR for his work as chief MR technologist. Presented at the American College of Neuropsychopharmacology Meeting; December 3, 2006 to December 7, 2006; Hollywood, FL, and the American Association of Geriatric Psychiatry Meeting; March 1, 2007 to March 4, 2007; New Orleans, LA. This work was supported by National Institute of Mental Health grants P30 MH68638, RO1 MH65653, and T32 MH19132 (to GSA), K23 MH074818 (to FGD), K23 MH067702 (to CFM), and RO1 MH64783 (to MJH), the Sanchez Foundation and Forest Pharmaceuticals. GSA has received research grants by Forest Pharmaceuticals, Inc. and Cephalon and participated in scientific advisory board meetings of Forest Pharmaceuticals. He has given lectures supported by Forest, Cephalon, Bristol Meyers, Janssen, and Lilly and has received support by Comprehensive Neuroscience, Inc. for the development of treatment guidelines in late-life psychiatric disorders.
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Macromolecular White Matter Abnormalities in Geriatric Depression: A Magnetization Transfer Imaging Study Faith M. Gunning-Dixon, Ph.D., Matthew J. Hoptman, Ph.D., Kelvin O. Lim, M.D., Christopher F. Murphy, Ph.D., Sibel Klimstra, M.D., Vassilios Latoussakis, M.D., Magdalena Majcher-Tascio, B.A., Jan Hrabe, Ph.D., Babak A. Ardekani, Ph.D., George S. Alexopoulos, M.D.
Objective: Geriatric depression consists of complex and heterogeneous behaviors unlikely to be caused by a single brain lesion. However, abnormalities in specific brain structures and their interconnections may confer vulnerability to the development of late-life depression. The objective of this study was to identify subtle white matter abnormalities in late-life depression. Design: The authors used magnetization transfer ratio (MTR) imaging, a technique that is thought primarily to reflect myelin integrity, to examine the hypothesis that individuals with late-life depression would exhibit white matter abnormalities in frontostriatal and limbic regions. Setting: The study was conducted in a university-based, geriatric psychiatry clinic. Participants: Fifty-five older patients with major depression and 24 elderly comparison subjects were assessed. Measurement: Voxel-based analysis of MTR data were conducted with a general linear model using age as a covariate. Results: Relative to comparison subjects, patients demonstrated lower MTR in multiple left hemisphere frontostriatal and limbic regions, including white matter lateral to the lentiform nuclei, dorsolateral and dorsomedial prefrontal, dorsal anterior cingulate, subcallosal, periamygdalar, insular, and posterior cingulate regions. Depressed patients had lower MTR in additional left hemisphere locales including the thalamus, splenium of the corpus callosum, inferior parietal, precuneus, and middle occipital white matter regions. Conclusion: These findings suggest that geriatric depression may be characterized by reduced myelin integrity in specific aspects of frontostriatal and limbic networks, and complement diffusion tensor studies of geriatric depression that indicate decreased organization of white matter fibers in specific frontal and temporal regions. (Am J Geriatr Psychiatry 2008; 16:255–262) Key Words: Geriatric depression, magnetization transfer imaging, white matter
Received May 7, 2007; revised September 13, 2007; accepted September 19, 2007. From the Institute of Geriatric Psychiatry and the Department of Psychiatry, Weill Medical College of Cornell University (FMG-D, CFM, SK, VL, MM-T, GSA), Weill Cornell Institute of Geriatric Psychiatry, White Plains; the Division of Clinical Research and the Center for Advanced Brain Imaging, Nathan S. Kline Institute for Psychiatric Research (MJH, JH, BAA), Orangeburg; Department of Psychiatry (MJH, BAA), New York University School of Medicine, NY; and the Department of Psychiatry, University of Minnesota (KOL), Minneapolis, MN. Send correspondence and reprint requests to Faith M. Gunning-Dixon, Ph.D., 21 Bloomingdale Road, White Plains, NY 10605. e-mail: [email protected] © 2008 American Association for Geriatric Psychiatry
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onverging evidence suggests that abnormalities in specific frontostriatal and limbic structures and their interconnections may confer vulnerability to the development of late-life depression. Structural magnetic resonance imaging (MRI) methods can be used to identify and quantify these cerebral network abnormalities predisposing to geriatric depression.1 Earlier, structural MRI studies of late-life depression have provided support for the role of frontostriatal and limbic abnormalities in late-life depression. Gray matter volume reductions are present in multiple frontostriatal–limbic regions of older depressed individuals, including the anterior cingulate, prefrontal cortices, the neostriatum, and the hippocampus.2– 6 White matter hyperintensities (WMH) are more prevalent and severe in depressed older individuals than elderly comparison subjects, mainly occur in subcortical regions and their frontal white matter projections,7–10 and are associated with executive dysfunction.11 Recent advances in MRI techniques allow the in vivo identification of white matter microstructural abnormalities in late-life depression. Diffusion tensor imaging (DTI), a technique used to measure organization of fiber tracts, has revealed that depressed elderly patients exhibit compromised integrity (i.e., reduced fractional anisotropy [FA] of the white matter) of the dorsolateral prefrontal cortex, anterior cingulate, and temporal regions.12–14 Furthermore, in a preliminary DTI study, reduced FA of the white matter lateral to the anterior cingulate gyrus was associated with poor response to citalopram in depressed older patients.15 Magnetization transfer ratio (MTR) imaging is another method that can be used to study white matter abnormalities. MTR imaging provides information about the macromolecular structure of cerebral white matter based on the interaction of the normally observed tissue water signal with protons contained in large macromolecules (including myelin). Macromolecular semisolid structures in the brain, such as myelinated axons, are ordinarily invisible to MRI because of their extremely short transverse relaxation times. However, protons bound to them can transfer magnetization to those of the freely moving tissue water, e.g., by chemical exchange. To achieve MTR contrast, two acquisitions are required. The first obtains a proton density-weighted image with signal proportional to the amount of free water. The
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second employs an additional off-resonance radiofrequency pulse before the basic proton density sequence, which selectively nulls magnetization of the bound protons. Because some of these protons subsequently enter the free water compartment, magnetization available there becomes smaller and the magnetic resonance signal is reduced. Contrast between these two images is usually expressed as the MTR ⫽ (M0 ⫺ MSAT)/M0. Reduction in macromolecular volume fraction is therefore reflected in the reduced MTR. Studies conducted in early development, aging, and multiple sclerosis suggest that DTI and MTR may provide complementary information about white matter integrity with DTI primarily reflecting organization of fibers tracts and MTR being particularly sensitive to myelin and, to a lesser degree, axonal integrity.1,16 MTR may be a particularly informative tool for examining cerebral abnormalities in late-life depression given its apparent reliance on myelin and axonal integrity and its demonstrated effectiveness in examining the effects of both normal aging and aging-related illnesses on the brain.16 Kumar et al.17 demonstrated the value of MTR in a preliminary study of white matter abnormalities in geriatric depression. They examined MTR in eight patients with late-life depression and eight nondepressed comparison subjects. Their results suggest that relative to their elderly counterparts older depressed patients have lower MTR in the genu and splenium of the corpus callosum, the neostriatum, and the occipital white matter. We report here an exploratory analysis employing whole-brain voxelwise methodology to identify brain regions that show reduced MTR in patients with geriatric depression relative to nonpsychiatric comparison participants who were comparable in age. We hypothesized that depressed elders would exhibit lower MTR in frontostriatal and limbic regions than elderly comparison subjects, but used a whole-brain voxelwise analysis to evaluate the specificity of our findings.
METHODS Participants The depressed participants were 55 (⬎60 years) psychiatric patients from a university-based clinic of
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Gunning-Dixon et al. geriatric psychiatry who were recruited for an escitalopram treatment trial. Scans were performed during a 2-week single blind drug washout and placebo lead-in phase. Participants met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSMIV)-TR criteria and Research Diagnostic Criteria for unipolar major depression and had a score ⬎18 on the 24-item Hamilton Depression Rating Scale.18 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 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, ␣-methyl-dopa, clonidine, reserpine, tamoxifen, and cimetidine); 7) Mini-Mental State Exam19 score ⬍25; and 8) contraindications to MRI scanning. These criteria resulted in a group of elderly patients with nonpsychotic unipolar major depression without a diagnosable dementing disorder (Table 1). Comparison Participants. An elderly group of community-dwelling volunteers were recruited by advertisements using radio and newspaper announcements. Additional exclusion criteria were current or history of Axis I disorders as well as current or previous psychiatric treatment. The Weill Cornell and Rockland Psychiatric Center/Nathan S. Kline Institute for Psychiatric Research
Institutional Review Boards approved all procedures. After complete description of the study to subjects, written informed consent was obtained.
Magnetic Resonance Imaging Scanning took place on a 1.5T Siemens Vision scanner (Erlangen, Germany) housed at Nathan S. Kline Institute’s Center for Advanced Brain Imaging. Scans were performed during a 2-week single blind drug washout or placebo lead-in phase of the treatment trial. Patients received a magnetization prepared rapidly acquired gradient echo scan (repetition time [TR] ⫽ 11.6 milliseconds, echo time [TE] ⫽ 4.8 milliseconds, TI ⫽ 1,018 milliseconds, matrix ⫽ 256 ⫻ 256, field of view [FOV] ⫽ 320 mm, numbers of excitation ⫽ 1, slice thickness ⫽ 1.25 mm, 172 slices), as well as a turbo dual spin echo scan (TR ⫽ 9,000 milliseconds, TE ⫽ 22/90 milliseconds, matrix ⫽ 256 ⫻ 256, FOV ⫽ 240 mm, slice thickness ⫽ 5 mm, 26 slices, no gap). Subjects also received an MTR imaging sequence based on a three-dimensional fast low angle shot method. Slices were positioned identically to the dual turbo spin echo scan, in an oblique axial plane parallel to the anterior commissure–posterior commissure axis. The acquisition parameters were FOV ⫽ 240 mm, 32 slices 5 mm thick, matrix ⫽ 256 ⫻ 256, TR ⫽ 31 milliseconds, and TE ⫽ 6 milliseconds. One acquisition was performed with and another one without the magnetization transfer saturation pulse. This pulse had a Gaussian shape with effective bandwidth of 250 Hz and was offset from the resonance frequency by 1.5 kHz.
Postprocessing TABLE 1. Baseline Demographic and Clinical Characteristics of 55 Elderly Patients with Major Depression and 24 Nondepressed Controls
Variable Age (yr) Education (yr) Male (%) HDRS MMSE
Depressed Elders Mean ⴞ SD
Comparison Group Mean ⴞ SD
69.9 ⫾ 6.1 15.4 ⫾ 2.9 41 23.7 ⫾ 4.0 28.4 ⫾ 1.5
71.8 ⫾ 6.1 16.5 ⫾ 2.4 30 1.5 ⫾ 1.7 28.7 ⫾ 1.1
t value (df ⴝ 77)
p
1.31 1.83
0.20 0.07
26.8 0.82
0.001 0.42
Notes: Values are mean ⫾ standard deviation unless otherwise noted. HDRS: Hamilton Depression Rating Scale; MMSE: Mini-Mental State Exam.
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The MTR was computed for each voxel as: MTR ⫽ (M0 ⫺ MSAT)/M0, where M0 is the image intensity without the off-resonance saturation pulse and MSAT is the signal with the saturation pulse.20The MTR was computed for each voxel using FMRIB Software Library programs (http://www.fmrib.ox.ac.uk/fsl/ bet2/index.html). MTR images were placed into Talairach space using methods described elsewhere.21 Intersubject registration was carried out using the Automatic Registration Toolbox software. We have recently shown this method to be superior to registrations performed by Statistical Parametric Map-
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White Matter Abnormalities in Geriatric Depression ping (99) and Automatic Image Registration software.22 The T1-weighted template used for the registrations was derived from a subject whose intracranial content volume was the closest to the mean for the first five subjects. The volumes were computed in MEDx (Sensor Systems, Sterling, VA) after skull stripping, which was done using FMRIB Software Library’s BET (http://www.fmrib.ox.ac.uk/fsl/bet/ index.html) program. The case we chose to use as a template was placed into Talairach space using the AFNI software23 using the standard Talairach piecewise linear landmark-based normalization. To limit the number of statistical comparisons, we created a white mask based on the average FA map obtained from DTI on the same subjects. The DTI scan (TR ⫽ 6000 milliseconds, TE ⫽ 100 milliseconds, matrix ⫽ 128 ⫻ 128, FOV ⫽ 320 mm, numbers of excitation ⫽ 7, slice thickness ⫽ 5 mm, 19 slices, no gap) sampled eight noncollinear diffusion sensitization directions (with b ⫽ 1,000 second/mm2). In addition, an image with no diffusion weighting (b ⫽ 0 second/mm2) was acquired. For each subject, FA was computed using AFNI’s nonlinear algorithm (3dDWItoDT). The resulting FA maps were placed into standard space as described above. An average map was computed from the normalized FA maps and was threshold using a nonparametric histogrambased segmentation.24 The obtained white matter threshold was applied to the mean FA image, and the resulting white matter mask was used in the analysis on MTR data. The FA image was used to create the mask because of its excellent gray-white contrast. Voxel-based analysis of MTR data with respect to group membership (depressed patients, comparison subjects) was conducted using a general linear model. To reduce error variance that may be related to age, we included age as a covariate in the analysis. To control for Type I error, we used a modified version of the thresholding method described by Baudewig et al.25 of detecting adjacent voxels that are statistically significant and applying a constraint that one of the voxels must be significant at a more stringent p value. In addition, we applied the constraint that at least 100 neighboring voxels must reach significance. Thus, our approach finds clusters of voxels (100 mm3) each with significant group differences (p ⬍0.05) and then applies the constraint
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that one of the voxels in the cluster must be significant at p ⬍0.005. The thresholded correlation maps were superimposed onto a magnetization prepared rapidly acquired gradient echo image in Talairach space using AFNI.
RESULTS Relative to elderly comparison subjects, patients demonstrated lower MTR in multiple left hemisphere frontostriatal and limbic white matter regions, including white matter lateral to the lentiform nuclei, dorsomedial and dorsolateral prefrontal, dorsal anterior cingulate, periamygdalar, subcallosal, lentiform, insular, and posterior cingulate regions (Table 2). Depressed patients had lower MTR in additional left hemisphere locations including the thalamus, splenium of the corpus callosum, inferior parietal, precuneus, and middle occipital regions. In contrast, comparison subjects had lower MTR in a right postcentral region (Figure 1).
DISCUSSION The main finding of this study is that late-life depression is characterized by reduced MTR in multiple left hemisphere frontostriatal and limbic white matter regions including white matter lateral to the lentiform nuclei, dorsolateral and dorsomedial prefrontal, dorsal anterior cingulate, insula, periamygdalar, subcallosal, and posterior cingulate white matter regions. Our findings extend the report of Kumar et al. of lower MTR in the genu and splenium of the corpus callosum, the neostriatum, and the occipital white matter in a small sample of elderly depressed patients.17 The MTR observations are consistent with evidence from MRI findings of volume reductions in frontal, striatal, and limbic regions as well as increased prevalence and severity of WMH in geriatric depression.1 Furthermore, these findings complement diffusion tensor studies of geriatric depression that indicate the presence of decreased organization of white matter fibers in select frontal and temporal regions,12–14 as well as activation studies that have detected hypoactivation of the dorsal anterior cingulate, hippocampus, dorsolateral prefrontal cortex,
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Gunning-Dixon et al.
TABLE 2. Clusters of Significant MTR Differences Between Elderly Depressed Patients and Elderly Comparison Subjects After Controlling for Age X (ⴙRight) ⫺29 ⫺14 ⫺7 ⫺28 ⫺33 ⫺29 ⫺24 ⫺33 ⫺22 ⫺13 ⫺22 ⫺27 ⫺44 ⫺16 ⫺18 ⫺4 ⫺30 28
Y (ⴙAnterior)
Z (ⴙSuperior)
Cluster Size
Mean t Value
Anatomical Region
4 35 4 ⫺8 17 ⫺19 11 ⫺14 ⫺50 ⫺36 ⫺59 ⫺53 ⫺22 ⫺21 ⫺9 ⫺35 ⫺60 ⫺33
⫺7 29 30 39 15 17 ⫺5 1 15 31 25 30 29 3 13 20 4 45
377 102 161 206 399 101 224 278 211 276 368 261 283 235 223 120 218 139
⫺2.36 ⫺2.43 ⫺2.53 ⫺2.30 ⫺2.50 ⫺2.30 ⫺2.57 ⫺2.35 ⫺2.36 ⫺2.55 ⫺2.48 ⫺2.37 ⫺2.33 ⫺2.38 ⫺2.33 ⫺2.39 ⫺2.40 2.26
L periamygdalar/subcallosal/lentiform L dorsomedial prefrontal L dorsal anterior cingulate L middle frontal/dorsal anterior cingulate L insula L insula L lentiform L lentiform L posterior cingulate L posterior cingulate L posterior cingulate/precuneus L precuneus L inferior parietal L thalamus L thalamus L splenium L middle occipital R postcentral
Notes: Talairach coordinates reflect peak of cluster. t value is the mean t value of each cluster. All voxels in each cluster were significant at a two-tailed p ⬍0.05 with at least one voxel in each cluster significant at p ⬍0.005. df for all t values ⫽ 77. Cluster size is in number of voxels.
and neostriatum in elderly depressed patients relative to comparison subjects.26,27 Models of the neurobiology of emotion have identified two neuroanatomical systems, a ventral and a dorsal, that appear critical to the processing of emotional stimuli.28 The ventral system, which includes the amygdala, insula, ventral striatum, ventral anterior cingulate, and orbitofrontal cortex, is important for the evaluation of the emotional significance of incoming stimuli and generation of an affective response.28 The dorsal system, comprised of the dorsal anterior cingulate, dorsolateral prefrontal cortex, and the hippocampus, is critical for the cognitive regulation of affective responses. The ventral and dorsal systems have reciprocal connections, and dysfunction in either network may result in poor emotional regulation. Depression is believed to be characterized by increased negative bias in the assessment of incoming stimuli within the ventral system, accompanied by decreased regulation of the affective response by the dorsal system.29 We propose that reduced MTR in older depressed individuals may confer vulnerability to late-life depression. The reductions of MTR in frontostriatal and limbic regions in older depressed individuals overlap with the systems described above including the dorsolateral prefrontal regions, lentiform nuclei, dor-
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sal anterior cingulate, periamygdalar regions, and insula. MTR decreases in white matter are typically observed in diseases associated with myelin or axon loss.16 Histopathological data from postmortem multiple sclerosis brains suggest that MTR correlates with both axonal and myelin count, with myelin count being a primary, but not sole determinant, of reduced MTR.30 Furthermore, the developmental neuroimaging literature indicates that increases in MTR coincide with brain myelination during the early years of life.16 Thus, reductions observed in MTR of white matter appear to be primarily an index of reduced myelin integrity. These converging lines of evidence support the premise that MTR reductions in late-life depression may reflect compromised white matter in frontostriatal and limbic pathways that may lead to a “disconnection-syndrome,” which interferes with the reciprocal regulation of dorsal cortical-ventral limbic systems (for reviews see Refs. 31 and 32). Notably, reduced MTR in late-life depression was more diffuse than we expected as it not only occurred in frontostriatal and limbic regions, but also occurred in select posterior regions. These findings of decreased MTR in posterior regions, specifically the thalamus, posterior cingulate, and precuneus, converge with resting state metabolic studies of young and middle-aged individuals that have detected met-
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FIGURE 1.
Clusters of Significant Magnetization Transfer Ratio Differences Between Patients and Comparison Subjects
Notes: Axial and sagittal maps of significant MTR differences between comparison subjects and depressed patients (orange indicates areas in which MTR is lower for patients). Images are in radiological convention. Sagittal images are presented from left to right. Group differences are thresholded such that 100 mm3 clusters of voxels all significant at p ⬍0.05 are identified, with the additional criterion that within each cluster, at least one voxel is significant at p ⬍0.005.
abolic abnormalities in similar regions among depressed patients or during induced sadness.33–36 Furthermore, reduced metabolism in the posterior cingulate and the precuneus has been reported in presymptomatic nondemented individuals who had at least a single Apo epsilon 4 allele.37 Similarly, decreased metabolism in the posterior cingulate, hippocampus, and temporoparietal association areas has
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been observed in patients with mild cognitive impairment who converted to dementia.38 Although our participants were screened for dementia, given the relationship of geriatric depression to increased risk for mild cognitive impairment or dementia it is possible that the inclusion of presymptomatic individuals in the depressed sample may contribute to the macromolecular white matter abnormalities we observed.
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Gunning-Dixon et al. The findings of reduced MTR in patients relative to comparison subjects were observed almost entirely in the left hemisphere. The presence of left hemisphere MTR reductions is consistent with the literature suggesting that left hemisphere stroke is more likely to be accompanied by depression than right hemisphere stroke.39 In addition, some studies of geriatric depression have reported greater diagnostic significance of WMH in left than right hemisphere (e.g., Ref. 7). Furthermore, in an electrophysiological study of 22 older patients with major depression who received controlled treatment with citalopram,40 the nine subjects who remained symptomatic after treatment had larger left frontal error negative waves than the subjects who achieved remission. These electrophysiological findings suggest inefficiency of left hemisphere frontolimbic networks in these individuals. Thus, although we did not predict the lateralized MTR reductions in this study, this intriguing finding should be explored in future MRI studies of cerebral white matter in geriatric depression. Interpretation of the current results is limited by the fact that the large number of comparisons in the voxelwise analysis increases the risk of Type I error. We used a white matter mask to mask the images, which greatly reduced the number of comparisons. We also combined a two-level statistical thresholding technique with a relatively conservative spatial extent requirement of a minimum of 100 voxels in each cluster. Another limitation is that the use of a voxelwise approach requires registration of all of the subjects MTR scans into the same space. Given the known variability in atrophy rates in the elderly, registration of the scans of our sample into the same space may be a source of error in our findings. The identification of macromolecular white matter abnormalities associated with geriatric depression can
guide future studies of specific pathways associated with the pathophysiology of geriatric depression. In light of the relatively diffuse nature of our findings, combining structural and functional imaging methods may help distinguish those white matter abnormalities predisposing to geriatric depression from incidental abnormalities. Furthermore, the examination of the relationship of MTR reductions in late-life depression to clinical features of the illness would allow us to identify those macromolecular abnormalities that are critical to the presentation of the illness. MTR studies, for example, can be used to identify the location of macromolecular white matter abnormalities that are associated with cognitive dysfunction or predict treatment response. The identification of specific pathway abnormalities associated with treatment response can generate investigations of specifically targeted novel therapeutic interventions. The authors thank Raj Sangoi, RT(R) MR for his work as chief MR technologist. Presented at the American College of Neuropsychopharmacology Meeting; December 3, 2006 to December 7, 2006; Hollywood, FL, and the American Association of Geriatric Psychiatry Meeting; March 1, 2007 to March 4, 2007; New Orleans, LA. This work was supported by National Institute of Mental Health grants P30 MH68638, RO1 MH65653, and T32 MH19132 (to GSA), K23 MH074818 (to FGD), K23 MH067702 (to CFM), and RO1 MH64783 (to MJH), the Sanchez Foundation and Forest Pharmaceuticals. GSA has received research grants by Forest Pharmaceuticals, Inc. and Cephalon and participated in scientific advisory board meetings of Forest Pharmaceuticals. He has given lectures supported by Forest, Cephalon, Bristol Meyers, Janssen, and Lilly and has received support by Comprehensive Neuroscience, Inc. for the development of treatment guidelines in late-life psychiatric disorders.
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