MRI subcortical hyperintensities in old and very old depressed outpatients

Journal of the Neurological Sciences 203 – 204 (2002) 227 – 233 www.elsevier.com/locate/jns

MRI subcortical hyperintensities in old and very old depressed outpatients: The important role of age in late-life depression Stephen Salloway a,*, Stephen Correia a, Patricia Boyle a, Paul Malloy a, Lon Schneider b, Helen Lavretsky c, Harold Sackheim d, Steven Roose d, K. Ranga Rama Krishnan e a Brown Medical School, Providence, RI, USA University of Southern California, Los Angeles, CA, USA c University of California-Los Angeles, Los Angeles, CA, USA d Columbia University, New York, NY, USA e Duke University, Durham, NC, USA b

Abstract Objective: There is increasing evidence that cerebrovascular factors play a key role in the etiology of late-life depression. This study examined the severity of subcortical hyperintensities (SH) and the relationship between SH and depression characteristics in two samples of elderly depressed outpatients differing in age. Methods: The samples consisted of 59 subjects age 60 and over, (69 F 5.6 years), who participated in a trial of sertraline, and 111 subjects age 75 and over, (79 F 4.1 years), who participated in a trial of citalopram. Results: The citalopram group was significantly older than the sertraline group and had more severe SH (72% vs. 42% high ratings). The High SH group was significantly older than the Low SH group in the sertraline study but there was no difference in age in the SH groups in the citalopram sample. There was no relationship between SH severity and baseline depression or age of onset. However, age strongly correlated with later age of onset. There was no relationship between SH severity and cardiovascular risk factors or treatment response in the sertraline sample. Conclusion: Age is a major factor for the development of SH and late-life depression. There may not be an association between SH and depression severity, cardiovascular risk factors, or treatment response in geriatric depressed outpatients. The etiologic factors and clinical course of late-life depression requires further study. D 2002 Elsevier Science B.V. All rights reserved. Keywords: Subcortical hyperintensities; Vascular depression; Geriatric depression; MRI; Sertraline; Citalopram; Cardiovascular risk factors

1. Introduction Depression affects approximately 15% of individuals who are 65 years of age or older [1,2] and is associated with diminished quality of life [3– 5], increased risk of suicide [6], and elevated health care expenditures [7]. Although the pathogenesis of late-life depression is likely to be multifactorial [2], vascular factors, including subcortical hyperintensities (SH), may play an important etiologic and/or prognostic role. SH are areas of high signal in subcortical gray, deep white matter, and periventricular brain regions on T2-weighted magnetic resonance imaging scans. SH are common in older adults with depression [8– 10], and are * Corresponding author. Department of Neurology, Butler Hospital, 345 Blackstone Blvd., Providence, RI 02906, USA. Tel.: +1-401-455-6403; fax: +1-401-455-6405. E-mail address: [email protected] (S. Salloway).

associated with an increased risk of developing depression [11]. Alexopoulos et al. [8] and Krishnan et al. [2] have hypothesized that SH contributes to late-life depression by disrupting frontal cortical/subcortical circuits and associated neurotransmitter systems, and some support for this hypothesis has emerged. For example, MacFall et al. [12] reported that depression severity in elderly patients was correlated with lesions in the medial orbital region. Also, in an autopsy series, O’Brien et al. (personal communication, 2002) showed more ischemic lesions in the dorsolateral prefrontal cortex in elderly depressed subjects compared to agematched controls. Alexopoulos et al. [8] proposed a ‘vascular depression’ hypothesis, the cardinal features of which are clinical and/or laboratory evidence of cerebrovascular disease and late-onset depression (age 65 or older) or, for patients with early-onset depression, a change in the course of depression after the development of cerebrovascular disease.

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There has been considerable interest in determining the clinical characteristics of older depressed patients with SH. Previous works suggest that compared to non-vascular depression, vascular depression is more strongly associated with later age of depression onset [13], more apathy and less guilt [2,8], more functional disability [2], and more cognitive impairment [13,14]. Although recent research has focused on the relationship between SH and geriatric depression, risk factors for SH have not been clearly determined. Studies have consistently shown that the prevalence and severity of SH increases with age [15 – 18]. Hypertension also appears to be a strong risk factor for developing SH in older people [15,18 –20], but the relationship between SH and hypertension in geriatric depression has not been firmly established. Further, it is not clear if there is a relationship between SH and other cardiovascular risk factors in either geriatric depressed individuals or community dwelling elderly without depression [16,17,20,21]. High levels of SH may negatively impact antidepressant treatment response. Some studies have shown that elderly depressed subjects with SH have a poorer response to antidepressant treatment [22 – 24]. Conflicting reports exist, however, and placebo-controlled trials evaluating the effect of SH on antidepressant treatment response are lacking. Moreover, majority of the available studies have involved uncontrolled trials in severely depressed geriatric inpatients, and results may not apply to mildly depressed outpatients. The primary aim of this study was to provide new information about the imaging and clinical characteristics of late-life depression from two placebo-controlled trials using MRI in depressed geriatric outpatients that differ significantly in age (69 vs. 79 years). We evaluated differences in severity of SH between old and very old depressed samples and studied the relationship between SH status and severity of baseline depression and age of onset of depression. A secondary aim was to report on the relationship between SH status and vascular risk factors and between SH severity and antidepressant treatment response in the younger of the two samples (sertraline). We hypothesized that the citalopram sample would have a higher burden of SH, and that subjects with high levels of SH would have a later age of onset of depression, a higher rate of hypertension and other vascular risk factors, and a poorer response to antidepressant treatment.

2. Methods The old sample consisted of 59 subjects with major depression who were 60 years old and older (35 males, 24 females) with a mean ( F S.D.) age 69.22 F 5.63 years (range: 60 –82) from seven sites participating in a larger 8-week, placebo-controlled trial of sertraline (n = 752) for outpatient geriatric depression. The very old sample

included 111 subjects with major depression who were 75 years old and older (43 males, 68 females) with a mean age of 79.43 F 4.13 years enrolled in a larger placebo-controlled trial of citalopram (n = 178) for major depression in outpatients aged 75 and older. The age range of the citalopram sample was 74 – 98 years but 80 subjects (72%) were between 75 and 80 years old. More than 85% of subjects in both samples were Caucasian. Subjects in both studies met DSM-IV criteria for major depression without psychotic features, had a 17-item Hamilton Depression score (Ham-D) of >18 (sertraline) or 24 item Ham-D of >20 (citalopram) and had major depression for at least 4 weeks. Subjects who were suicidal or required ECT, had another psychiatric disorder, current dementia; alcohol or drug abuse in the past 6 months; MMSE score < 24 (sertraline) or < 18 (citalopram); and clinically significant unstable medical condition(s) were excluded. The results of the larger sertraline trial have been reported elsewhere [25]. 2.1. MRI protocol Standardized non-contrast brain MRI scans were obtained on all subjects and quality control procedures were instituted to ensure consistency of scan acquisition between sites. Sertraline MRI protocol: SH ratings were made on axial 5 mm continuous fluid attenuated inversion recovery (FLAIR) slices (TE 145, TR 10000, TI 2200, FOV 22 cm). Citalopram MRI protocol: SH ratings were performed on axial fast spin-echo images (TR 4000 ms, TE 30, 80 ms, 16 kHz imaging bandwidth, echo train length = 16) with a 256  256 matrix 3-mm section thickness (contiguous) and 1 excitation per phase encoding increment. 2.2. MRI ratings SH ratings were done using a visual rating scale reported by Krishnan et al. [26]. SH severity was rated on all axial slices above the brainstem and the highest rating on any one slice was used to determine the severity for each region. SH ratings for the sertraline sample were performed at Brown University by two trained raters who established high interrater reliability (kappa = 0.89; p < 0.001). Trained expert raters at Duke University scored the MRI scans for the citalopram sample. Interrater reliability for the sertraline and citalopram ratings is not available. Ratings were made as follows: (a) Periventricular (PV) hyperintensity, graded as 0 = absent, 1 = caps, 2 = smooth halo, 3 = irregular periventricular hyperintensity extending into the deep white matter. (b) Deep white matter (DWM) hyperintensity, graded as 0 = absent, 1 = punctate foci, 2 = beginning confluence of foci, and 3 = large confluent areas. (c) Changes in subcortical gray matter (SCG) nuclei, graded as 0 = absent, 1 = punctate, 2 = multipunctate, and 3 = diffuse.

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Study participants were classified into High and Low SH groups according to ratings across all three SH indices. Subjects receiving a score of 2 or greater on any single region were classified as having high SH. Subjects with scores < 2 on all regions were classified as having low SH. 2.2.1. Depression baseline data and outcome measures Baseline depression measures included the 17-item HamD (sertraline study) and 24-item Ham-D (citalopram study) and the Clinical Global Impressions of Severity Scale (CGIS). Age of onset of first depressive episode was obtained by interview of the patient and family and review of medical records. 2.2.2. Vascular risk factors and treatment outcome measures (sertraline sample only) The subjects’ vascular risk factors were obtained by interviewing the patient and his/her family and by reviewing his/her medical records. Vascular risk factors included: hypertension, diabetes mellitus, hypercholesterolemia, smoking (current or within the last 5 years), and cardiac disease (i.e., myocardial infarction, coronary artery disease, or arrhythmia). The total number of specific vascular risk factors was summed to create a cumulative estimate of vascular risk. Vascular risk data is pending in the citalopram trial. Treatment response was evaluated using Ham-D and CGI-S change scores (pre-treatment minus post-treatment total scores). 2.2.3. Data analysis Chi-square (v2) analyses were used to compare sample differences in the number of subjects classified as having high or low levels of SH, and in the number of subjects receiving scores of 2 or greater in PV, DWM, and SCGM regions. ANOVA and Student’s t-tests were used to compare

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the samples on baseline depression variables and on age at onset of first depressive episode, respectively. In a secondary analysis, v2 and ANOVA procedures were employed to analyze vascular risk factors and depression outcome variables in the sertraline-MRI sample.

3. Results 3.1. Demographic information, SH status, and baseline depression ratings Table 1 shows that the citalopram sample was significantly older than the sertraline sample (69.22 F 5.63 vs. 79.43 F 4.13 years, t = 13.48, p < 0.001). In the sertraline sample, subjects with high SH were significantly older than were those with low SH. In contrast, in the citalopram sample the High and Low SH groups did not differ significantly by age, probably due to the restricted age range in this sample. 3.2. MRI differences between the sertraline and citalopram groups Figs. 1 and 2 compare the SH ratings for periventricular (PVH), deep white matter (DWM), subcortical gray hyperintensities (SCG), and overall severity ratings for the sertraline and citalopram groups. A significantly greater percentage of subjects in the citalopram group were classified as having high SH (72%) than in the sertraline group (42%) (v2 = 14.39, p < 0.001). Compared with the sertraline sample, a significantly higher percentage of subjects in the citalopram sample had high ratings in the DWM (74/111, 67% vs. 23/59, 39%; v2 = 12.68, p < 0.001) and in the SCGM (46/111, 41% vs. 8/59, 14%; v2 = 14.01,

Table 1 Baseline variables for the sertraline (old) and citalopram (very old) samples

Age Baseline Ham-D Baseline CGI-S Age at first depression

Sertraline (n = 59)

Citalopram (n = 111)

p

69.22 F 5.63 20.97 F 2.88 (17-item) 4.25 F 0.58 51.02 F 17.71

79.43 F 4.13 24.21 F 4.29 (24-item) 4.21 F 0.49 69.02 F 17.73

< 0.001a N/Ab 0.575 < 0.001c

Sertraline Low SH (n = 34) Age Ham-D total baseline CGI-S baseline Age at first depression a b c d e f g

67.15 F 4.90 21.18 F 3.05 4.22 F 0.43 48.24 F 15.30

Citalopram High SH (n = 25) 72.04 F 5.40 20.68 F 2.66 4.33 F 0.65 57.16 F 19.72

t[1, 167] = 13.48. Analysis not done due to differences in Ham-D form (17- vs. 24-item). t[1, 165] = 5.92. t[1, 57] = 3.63. t[1, 57] = 1.96. n = 29. n = 79.

p d

0.001 0.517 0.872 0.055e

Low SH (n = 31)

High SH (n = 80)

p

79.83 F 4.37 24.13 F 4.44 4.31 F 0.70 68.17 F 15.55f

78.42 F 3.30 24.24 F 4.26 4.15 F 0.55 69.33 F 18.55g

0.108 0.902 0.139 0.765

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Fig. 1. Percentage of subjects in each sample receiving high SH ratings (scores of 2 or 3) and low SH ratings (scores of 0 or 1) by brain region. PV = periventricular; DWM = deep white matter. * v2 = 12.68, p < 0.001.

p < 0.001). The samples did not differ significantly in terms of the percentage of subjects who received high ratings in the PV region. 3.3. Depression ratings and first onset of depression The sertraline and citalopram groups did not differ in baseline severity of depression as measured by the CGI-S (Table 1) and the High and Low SH groups in each sample did not differ on either the Ham-D or CGI-S (Table 1). The citalopram sample had a significantly older age of onset of first depressive episode (69.02 F 17.73 years) than the sertraline sample (52.02 F 17.71, years) (t[1, 165] = 5.92, p < 0.001). There was no relationship between SH severity and age of onset. difference in age of onset. To further explore the relationship between age and age of onset of depression, the sertraline and citalopram samples were combined to maximize the age range. Multiple regression analysis with age and total SH score (the sum of scores in PV, DWM, and SCGM regions) as independent variables and age of onset as the dependent variable revealed that age

alone accounted for 23.4% (Beta = 0.484) of the variance and SH accounted for an additional 0.2% (Beta = 0.041) of the variance; the total model therefore accounted for 23.6% of the variance in age of onset, ( p < 0.001). The bivariate correlation between age and total SH was moderate (r = 0.305, p < 0.01). 3.4. SH and vascular risk factors (sertraline sample only) There were no significant differences between the High and Low SH groups in terms of the history of hypertension, individual vascular risk factors, or the cumulative number of vascular risk factors. Data on vascular risk factors between the High and Low SH groups in the citalopram sample are pending. 3.5. SH and antidepressant treatment response (sertraline sample only) In our sertraline sample of 59 subjects, 30 received active drug and 29 received placebo. Depression outcome varia-

Fig. 2. Percentage of subjects in each sample receiving high SH ratings (scores of 2 or 3) and low SH ratings (scores of 0 or 1) by brain region. SCGM = subcortical gray matter; TOTAL = final SH classification. * v2 = 14.01, p < 0.001. * * v2 = 14.39, p < 0.001.

S. Salloway et al. / Journal of the Neurological Sciences 203 – 204 (2002) 227–233 Table 2 Treatment outcome variables for the sertraline-MRI sample only (mean F S.D.) Drug Low SH (n = 18)

Placebo High SH (n = 12)

Low SH (n = 16)

p High SH (n = 13)

Outcome variables Ham-D 8.39 F 6.40 6.0 F 6.56 4.38 F 5.52 5.62 F 6.23 0.471 change at week 8 CGI-S 1.00 F 1.19 1.08 F 1.31 0.56 F 0.81 0.85 F 1.14 0.759 change at week 8 Modified from Salloway et al. [35], American Journal of Geriatric Psychiatry (2002). Reprinted by permission.

bles for the High and Low SH groups by drug condition are presented in Table 2. Contrary to our expectations, 2  2 ANOVAs (SH group by treatment condition with age as a covariate) showed no major effects of SH, drug condition, or interaction term on the Ham-D or CGI-S change scores (corrected overall F[4,54] = 0.94, p = 0.451 for the Ham-D; corrected overall F[4,54] = 0.47, p = 0.759 for the CGI-S). Data on treatment response in the citalopram sample is pending.

4. Discussion This is the first study to compare SH and depression characteristics using standardized MRI in two samples of depressed geriatric outpatients that differ by age and that include a sample comprising of subjects 75 years old and older. Our results show that age is an important risk factor for the development of SH in geriatric depression. Findings revealed a significantly higher burden of SH among the citalopram group than the sertraline group. Moreover, even in the younger sertraline sample, subjects with higher levels of SH were significantly older. These results were consistent with our expectations and with previous reports (e.g., Ref. [21]) of a positive association between SH and age. The lack of a significant age difference between the citalopram High and Low SH groups most likely reflects the sample’s restricted age distribution. SH comparisons between the sertraline and citalopram groups were made by experienced raters using the same visual rating scale, but the comparisons between the samples should be interpreted with caution because interrater reliability was not established between the sertraline and citalopram raters. However, our results are in line with prior reports that consistently show an association between SH and age [15 – 18]. Another limitation of the study is that the SH ratings were made on FLAIR images in the sertraline sample, and spin-echo proton-density images in the citalopram sample. FLAIR is more sensitive to SH than spin-echo proton-density [27], but both techniques are commonly used

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for detecting SH [26] and we do not think that the use of different MR sequences substantially affected our results. The sertraline and citalopram groups did not differ in terms of baseline depression severity, as measured by the CGI-S, nor did the High and Low SH groups within each sample. Therefore, while age and SH may be important determinants of geriatric depression, our results suggest that age and SH are not directly related to the severity of late-life depression. Older age is associated with later age of onset of the first depressive episode, as the citalopram group had a significantly later onset of depression than the sertraline group. Regression analysis in the combined sample showed that age contributed significantly to age of onset, but SH did not. We interpret these findings to mean that even though age and SH correlate moderately (r = 0.31), older age is a stronger risk factor for the development of late onset depression than SH. The lack of association between SH severity and age of onset is consistent with a study by Kumar et al. [28] that also failed to find an association between SH or atrophy and age of onset. Our hypothesis that subjects in the High SH group would have more hypertension was not supported in the sertraline sample. There also was no association between SH severity and other cardiovascular risk factors. These findings are consistent with those of Lyness et al. [29,30], Kumar et al. [31], and Krishnan et al. [32] who found no difference in cardiovascular risk factors among subjects with early and late onset depression, but differ from other reports indicating significant associations between vascular risk factors and SH. The studies by Lyness et al. [29,30], Kumar et al. [31], and Krishnan et al. [32] did not use MRI to assess SH and therefore they do not directly shed light on the relationship between SH and cardiovascular risk factors in late-life depression. Our hypothesis that subjects in the sertraline-MRI sample with high SH would have a poorer response to antidepressant treatment was not supported. This finding contrasts with previous reports, the majority of which involved severely depressed inpatients, and found that higher SH levels attenuate response to antidepressant medication and ECT. The discrepancy in the findings suggests that higher SH levels may not exert as powerful an effect on antidepressant treatment response in geriatric outpatients as it does in inpatients. This may have to do with differences between inpatient and outpatient samples in terms of depression severity, SH severity, and cognitive impairment. In our small sample, which included mostly individuals with mild SH, the use of a visual SH rating scale rather than quantitative ratings, and the modest difference in treatment response between drug and placebo in the larger sertraline study may have limited our ability to detect a relationship between SH status and treatment outcome. In summary, age exerts a significant effect on the development of both late-onset depression and SH. Many factors may contribute to late-life onset of depression including

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degenerative brain changes, medical illness burden, psychological factors such as decline in functional status, grief over loss of friends and relatives, and financial hardship. There is growing evidence that late-life onset of depression is associated with cognitive dysfunction [33] and may be an early sign of incipient dementia, especially Alzheimer’s disease (AD) [34]. We propose that there may be an age gradient associated with the development of late-life depression as there is with the development of AD. Specifically, agerelated brain changes such as deposition of amyloid plaques, neuronal loss, SH, and decline in neurotransmitter function, might increase vulnerability to depression. These neurodegenerative changes might, in turn, interact with the medical and psychosocial factors listed above thereby raising the risk of depression with increasing age. Many questions still remain to be addressed about the role of age, SH, and other factors in late-life onset depression. Longitudinal studies using neuropathological examination and newer imaging and neurochemical techniques should shed important light on the interaction between neurobiological and psychosocial factors in the clinical course of late-life depression. Given the lack of association between hypertension and other cardiovascular risk factors in the development of SH in our sample, the mechanism between age and the development of SH needs to be better elucidated. The absence of an association between SH severity and antidepressant treatment response in the sertraline sample raises questions about the effect of SH on treatment response in depressed elderly outpatients. A larger, controlled trial in elderly with a broad range of ages and medical problems using quantitative MRI analysis would help better evaluate the effect of SH on antidepressant treatment response in geriatric depression. The following sites and investigators participated in the sertraline and citalopram MRI studies. Sertraline study: Brown University—Stephen Salloway, M.D., Paul Malloy, PhD, Patricia Boyle, PhD, Stephen Correia, PhD, Deborah Cahn-Weiner, PhD, Robert Kohn, M.D., M.Ph.; Duke University—Ranga Krishnan, M.D., Murali Doraiswamy, M.D., MaryAnn Muir; Pfizer—Cathryn Clary, M.D.; Stanford University/Palto Alto VA—Javaid Sheikh, M.D., Elin Baird; UCLA—Gary Small, M.D., Helen Lavretsky, M.D.; USC—Lon Schneider, M.D., Nansi Taggart; Vanderbilt University—Ron Solomon, M.D., Kerry Hook; Washington University—Raj Nakra, M.D., Pat Deppen. Citalopram study: Brown University—Stephen Salloway, M.D., Paul Malloy, PhD, Patricia Boyle, PhD, Stephen Correia,PhD, Robert Kohn, M.D., Martin Keller, M.D.; Columbia University— Steven Roose, M.D., PI citalopram study, Harold Sackeim, PhD; Cornell University—George Alexopoulos, M.D.; Duke University—Ranga Krishnan, M.D.; Forest Laboratories, Inc.—Heikki Hakkarainen; Harvard University—Carl Salzman, M.D.; St. Louis University—George Grossberg, M.D.; UCLA—Gary Small, M.D., Helen Lav-

retsky, M.D.; University of Pennsylvania—Ira Katz, M.D.; University of Pittsburgh—Bruce Pollock, M.D., Benoit Mulsant, M.D.; Yale University—Craig Nelson, M.D.

Acknowledgements This study was supported by an unrestricted research grant from Pfizer, Forest Laboratories and by NIMH MH01487 and NIA AG05898.

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