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Depression Clinical and Research Program, Massachusetts General Hospital, Boston, Massachusetts, USA
Brain Imaging Center, McLean Hospital, Harvard Medical School, Boston, Massachusetts, USA
Department of Radiology, Sung Kyun Kwan University, Seoul, Korea
Depression Clinical and Research Program, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
Correspondence: Dr Dan V. Iosifescu, Massachusetts General Hospital, 50 Staniford Street, suite 401, Boston, Massachusetts 02114, USA.Tel: +1 617 724 7741; fax: +1 617 724 3028; e-mail: diosifescu{at}partners.org
Declaration of interest None. Funding detailed in Acknowledgements.
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ABSTRACT |
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Aims To investigate the relationship of brain white-matter hyperintensities with cardiovascular risk factors and with treatment outcome in younger people with major depressive disorder.
Method We assessed brain white-matter hyperintensities and cardiovascular risk factors in 84 people with major depressive disorder prior to initiating antidepressant treatment. We also assessed hyperintensities in 35 matched controls.
Results We found no significant difference in the prevalence of white-matter hyperintensities between the depression and the control groups. Left-hemisphere subcortical hyperintensities correlated with lower rates of treatment response. We found no correlation between global hyperintensity measures and clinical outcome. Brain white-matter hyperintensities correlated with hypertension and age and withtotal cardiovascular risk score.
Conclusions Subcortical white-matter hyperintensities in the left hemisphere (but notin other brain areas) maybe associated with poor response to antidepressant treatment in major depression.
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INTRODUCTION |
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METHOD |
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Non-treatment-resistant major depressive disorder
The study group with non-treatment-resistant major depressive disorder
comprised 65 people aged 1865 years (mean age 40.7, s.d.=10.2),
recruited through advertisements and clinical referrals for a clinical trial
beginning with open-label fluoxetine treatment
(Fava et al, 2002).
All participants, 24 (37%) of whom were women, met criteria for major
depressive disorder, diagnosed by the physician-administered Structured
Clinical Interview for DSMIIIR Axis I Disorders Patient
edition (SCIDP; Spitzer et
al, 1989). Participants were required to have a score of 16
or over on the 17-item Hamilton Rating Scale for Depression (HRSD;
Hamilton, 1967) at the
screening visit. We excluded people who failed to respond during the current
episode of depression to at least one adequate antidepressant trial.
Treatment-resistant major depressive disorder
Nineteen participants (mean age 39.6 years, s.d.=9.8), of whom 10 (52.6%)
were women, were recruited at the Depression Clinical and Research Program at
Massachusetts General Hospital for a clinical trial in people with
treatment-resistant depression, beginning with open-label nortriptyline
(Nierenberg et al,
2003). Patients eligible for inclusion were men and women aged
1870 years with major depressive disorder diagnosed using the
SCIDP and a score on the HRSD of at least 18. Treatment resistance was
defined as non-response to at least one, but no more than five, adequate
antidepressant trials during the current depressive episode.
Exclusion criteria
For both the depressive disorder samples, exclusion criteria were bipolar
disorder, psychotic disorder, a history of organic mental or seizure disorder,
serious or unstable medical illness, substance misuse or dependence disorder
active within the past 12 months, acute suicidal risk, pregnancy, lactation,
history of adverse reaction or allergy to the study medications, concomitant
use of psychotropic medications, clinical or laboratory evidence of thyroid
abnormalities, an existing diagnosis of dementia or a score below 27 on the
Mini-Mental State Examination (Folstein
et al, 1975), and any contraindication to magnetic
resonance imaging, including metallic implants or severe claustrophobia.
Controls
We also recruited through advertisements 35 healthy volunteers, matched for
age and gender (40% females; mean age 39.3 years, s.d.=9.8). These volunteers
underwent the physician-administered SCIDP to rule out any Axis I
psychopathology.
Tests and procedures
We assessed cardiovascular risk factors in all participants with major
depressive disorder following the National Institutes of Health Adult
Treatment Panel III guidelines, based on the Framingham Heart Study
(Wilson et al, 1998;
Expert Panel on Detection, Evaluation and
Treatment of High Blood Cholesterol in Adults, 2001). We recorded,
for each person in the two depression groups, age, gender, smoking status,
family history of cardiovascular disease, total serum cholesterol, personal
history of arterial hypertension and diabetes, and concomitant medications. We
calculated a cumulated cardiovascular risk score (range 06) by
assigning a point for each of the following six factors:
After the initial evaluation the non-treatment-resistant sample entered 8 weeks of open-label treatment with fluoxetine 20 mg daily, following a 1-week wash-out phase. The HRSD was administered at each study visit (screen, baseline and then every other week for 8 weeks). The treatment-resistant group were prescribed nortriptyline at an initial dosage of 25 mg, which was increased by 25 mg per day until a dosage of 100 mg was reached, unless patients were unable to tolerate the dosage increase because of side-effects. Blood levels of nortriptyline were measured at weeks 2 and 6, and dosage adjustments were made after the second week if blood levels were below 400 nmol/l. Participants then maintained their dosage of nortriptyline for 6 weeks. The HRSD was administered at each study visit (screen, baseline and then weekly for 6 weeks).
Brain imaging procedures
All participants underwent brain magnetic resonance imaging using a 1.5 T
(Signa, General Electric, Milwaukee, Wisconsin, USA) whole-body imaging
device. We obtained axial proton-density images,
T2-weighted images (echo time TE=30/80 ms, repetition time
TR=3000 ms, 256x192 matrix; field of view 24 cm, flip angle 45°, Nex
value 0.5, 3 mm thick slices, no skip) and fluid-attenuated inversion recovery
(FLAIR) axial images (TE=133 ms, TR=9002 ms, inversion time TI=2200 ms,
256x192 matrix; field of view 22 cm, 5 mm thick slices, 2 mm skip).
Voxel dimensions were 0.975 mmx0.975 mmx3.0 mm. Analysis of the
images was performed offline using a SUN Microsystems (Mountain-view,
California, USA) Sparc2 workstation and the radiological film. Lesions were
classified according to the Fazekas classification system
(Fazekas et al, 1987), which provides an assessment of severity of the white-matter hyperintensities,
rated separately for the subcortical white matter (range 03) and the
periventricular white matter (range 03). The total white-matter
hyperintensity score was considered to be the higher of the subcortical score
and the periventricular score, following previous classifications of
white-matter hyperintensity in people with major depressive disorder
(Krishnan et al,
1997). All ratings of white-matter hyperintensities were done by
an experienced neuroradiologist (H.K.L.), who was unaware of participant
identity and clinical status. Another investigator in the study (D.V.I.)
assessed independently a selection of 111 magnetic resonance images using the
same rating criteria, for measurement of interrater reliability. This was very
good: the number of observed agreements was 98 (88.3%) and weighted
k=0.82.
The presence of severe hyperintensities was defined as a Fazekas scale score of 2 or over, whereas scores below 2 were categorised as not severe, following previous classifications in people with major depressive disorder (Krishnan et al, 1997). In addition to the Fazekas scale scores, we determined the localisation of hyperintensities by hemisphere (left or right). Subcortical hyperintensities were also localised as being in the frontal lobe or not in the frontal lobe area, using the central sulcus as a boundary.
Data analyses
The clinical outcome variables were response (reduction in HRSD score of
50% or more) and remission (final HRSD score of 7 or less). We analysed the
clinical data using the last observation carried forward method. Group
differences in demographic and clinical variables involving continuous data
were computed using analysis of variance (ANOVA) (age) or unpaired
t-tests (HRSD scores, percentage change in HRSD scores).
The differences in the severity of white-matter hyperintensities between
participants in the two depression groups and the healthy comparison sample
were analysed using
2-tests. We used multiple ordinal logistic
regression to test the association between hyperintensity scores and
cardiovascular risk factors. Analysis of variance was used to test the
association between hyperintensity scores and the total cardiovascular risk
score (sum of the six cardiovascular risk factors). Since age is one of the
cardiovascular risk factors, these analyses were not adjusted for age.
Correlations between clinical outcome variables (response and remission) and
hyperintensity scores were tested using logistic regression, adjusted for age.
Statistical significance was defined as P<0.05, two-tailed.
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RESULTS |
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The incidence of total brain white-matter hyperintensities in the group
with non-treatment-resistant depressive disorder (63%) was not statistically
different from that of the treatment-resistant group (53%) or the control
group (60%);
2=0.881, P=0.83. Also, the incidence of
severe brain hyperintensities in the non-treatment-resistant group (8%) was
not statistically different from that of the treatment-resistant group (5%) or
the control group (6%);
2=0.364, P=0.95. As expected,
the individuals age correlated with the severity of brain
hyperintensities (ANOVA, d.f.=117, F=11.0, P=0.0012). In all
three study groups the majority of subcortical hyperintensities were localised
in the frontal lobe area: 87% of lesions in the treatment-resistant group were
in the frontal lobe, 79% of lesions in the non-treatment-resistant group and
100% in the control group, with no statistically significant difference
between groups (
2=0.825, P=0.22).
White-matter hyperintensities and treatment outcome
After adjusting for age there was no statistically significant relationship
between the total hyperintensity severity score and the clinical outcome
measures of response to treatment and remission
(Table 2). However, after
adjusting for age, subcortical white-matter hyperintensities in the left
hemisphere (and not in the right hemisphere) were correlated with lower rates
of response (logistic regression coefficient 2.31,
2=4.37,
P=0.036, odds ratio 10.1, 95% CI 1.1687.71) and remission
(logistic regression coefficient 2.69,
2=4.04,
P=0.045, OR=14.7, 95% CI 1.07202.7) after antidepressant
treatment. When treatment resistance status was used as a stratification
variable in the analysis, subcortical white-matter hyperintensities in the
left hemisphere were significantly correlated with lower rates of treatment
response (logistic regression coefficient 2.46,
2=4.11,
P=0.042, OR=11.6, 95% CI 1.09125.2), but the correlation
between remission and subcortical hyperintensities in the left hemisphere did
not reach statistical significance (logistic regression coefficient
2.34,
2=3.19, P=0.074, OR=10.4, 95% CI
0.8135.1). Of note, there was no significant difference in the
incidence of subcortical hyperintensities in the left hemisphere between the
treatment-resistant and the non-treatment-resistant depression groups (26%
v. 23%; P>0.05).
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After adjusting for age there was no statistically significant relationship between periventricular white-matter hyperintensities and response to treatment or remission (Table 2).
Correlation between white-matter hyperintensities and cardiovascular risk factors
The white-matter hyperintensity score was significantly correlated with the
cardiovascular risk score (P=0.037;
Table 3). In a multiple ordinal
logistic regression analysis examining individual cardiovascular risk factors
as predictors, greater total brain white-matter hyperintensity score was
associated with age (P=0.016) and with hypertension
(P=0.001). Two other cardiovascular risk factors did not reach
statistical significance in relation to total hyperintensity score:
cholesterol level (P=0.053) and family history of cardiovascular
disease (P=0.098). The presence of diabetes and smoking status were
not correlated with the total hyperintensity score. The presence of severe
hyperintensities also correlated with age (P=0.012) and with
hypertension (P=0.041), as well as with the total cardiovascular risk
score (P=0.011).
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The total cardiovascular risk score was correlated with the severity of periventricular hyperintensities (P=0.008) and of subcortical hyperintensities (P=0.047). In a multiple logistic regression, the severity of periventricular hyperintensity correlated with age (P=0.023) and hypercholesterolaemia (P=0.017), whereas hypertension did not reach statistical significance (P=0.088). Hypertension also did not reach statistical significance in relation to subcortical hypertensities (P=0.078). Other cardiovascular risk factors did not correlate with the severity of periventricular or subcortical white-matter hyperintensities.
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DISCUSSION |
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A second important finding in our study was that brain white-matter hyperintensities were correlated with cardiovascular risk factors in non-elderly people with major depressive disorder. It is therefore possible that a large proportion of brain hyperintensities in this younger population might be vascular in origin. Our result is consistent with findings in non-psychiatric populations, where brain white-matter hyperintensities have been associated with age, cerebrovascular disease (Awad et al, 1986; Fazekas et al, 1993) and cardiovascular risk factors such as smoking, arterial hypertension and increased serum cholesterol (Breteler et al, 1994; Liao et al, 1997; Schmidt et al, 1997). In neuropathological analyses of brains from people with major depressive disorder, subcortical white-matter hyperintensities were all ischaemic (Thomas et al, 2002), whereas periventricular lesions had multiple causes (Thomas et al, 2003).
One possible interpretation of our results is that cardiovascular risk factors correlate with a higher severity of subcortical white-matter lesions, which in turn correlates with poor treatment outcome in depression. This interpretation would be consistent with the vascular depression model. However, the vascular depression hypothesis would call for a higher prevalence of hyperintensities in patients with depression compared with normal controls, which was not found in our study. Also, the vascular depression model would suggest a relationship between global measures of brain white-matter hyperintensities and treatment outcome, whereas in our sample only subcortical hyperintensities in the left hemisphere (and no other hyperintensities) were associated with poor response to antidepressant treatment. Other factors, such as interruption by white-matter hyperintensities of specific white-matter tracts involved in mood regulation, may explain our observed result of a selective impact of left-hemisphere subcortical hyperintensities on treatment outcome. Other predictors of treatment outcome, which may mediate the relationship between white-matter hyperintensity and treatment response, might have been missed in this study owing to the relatively small sample size.
There are several limitations to our study. First, we used a whole-brain rating scale (Fazekas et al, 1987) to assess the severity of brain white-matter hyperintensities. Although most studies on this topic reported using modified versions of the Fazekas scale, this method does not allow for a detailed morphological and volumetric analysis of brain white-matter hyperintensity (Taylor et al, 2003). We did not measure hyperintensity localisations such as basal ganglia, which have been previously described as associated with treatment outcome in major depressive disorder (Simpson et al, 1998). Second, we measured only total cholesterol and not fractions of cholesterol, therefore our results may not reflect the full impact of this cardiovascular risk factor. Third, we have a potential sampling bias, as we enrolled participants from two antidepressant trials with specific inclusion and exclusion criteria and with different treatments (fluoxetine and nortriptyline); as a result, this sample may not directly reflect the typical out-patient population.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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Received for publication September 29, 2004. Revision received February 14, 2005. Accepted for publication February 18, 2005.
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