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Institute for Ageing and Health, University of Newcastle upon Tyne, UK
Department of Neurological and Psychiatric Sciences, University of Florence, Italy
Memory Research Unit, Department of Neurology, University of Helsinki, Finland
Institute of Clinical Neuroscience, Gothenburg University, Sweden
Karolinska University Hospital, Huddinge, Sweden
Alzheimer Centre and Department of Neurology, VU University Hospital, Amsterdam, The Netherlands
Memory Disorders Research Group, Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Denmark
Department of Neurology and MRI Institute, Medical University Graz, Austria
Serviço de Neurologia, Centro de Estudos Egas Moniz, Hospital de Santa Maria, Lisboa, Portugal
Department of Neurology, Hopital Lariboisiere, Paris, France
Department of Neurology, University of Heidelberg, Universitätsklinikum Mannheim, Germany
Department of Neurological and Psychiatric Sciences, University of Florence, Italy
the LADIS Group
Correspondence: Dr Teodorczuk, Institute for Ageing and Health, Newcastle General Hospital, Westgate Road, Newcastle upon Tyne NE4 6BE, UK. Email: andrew.teodorczuk{at}ncl.ac.uk
Funding detailed in Acknowledgements.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODRESULTSDISCUSSIONAPPENDIXACKNOWLEDGMENTSREFERENCES |
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Aims To investigate age-related white matter changes on magnetic resonance imaging (MRI) as an independent predictor of depressive symptoms at 1 year after controlling for known confounders.
Method In a pan-European multicentre study of 639 older adults without significant disability, MRI white matter changes and demographic and clinical variables, including cognitive scores, quality of life, disability and depressive symptoms, were assessed at baseline. Clinical assessments were repeated at 1 year.
Results Using logistic regression analysis, severity of white matter changes was shown to independently and significantly predict depressive symptoms at 1 year after controlling for baseline depressive symptoms, quality of life and worsening disability (P<0.01).
Conclusions White matter changes pre-date and are associated with the development of depressive symptoms. This has implications for treatment and prevention of depression in later life.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONAPPENDIXACKNOWLEDGMENTSREFERENCES |
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The LADIS (Leukoaraiosis and Disability in the Elderly) Study is a large multicentre pan-European longitudinal study of older adults without significant disability which was established to investigate the relationship between white matter changes on magnetic resonance imaging (MRI) and subsequent development of disability, cognitive impairment and depressive symptoms. We have previously reported cross-sectional associations between white matter changes and depressive symptoms in this sample (Firbank et al, 2005; O'Brien et al, 2006). In this report we examine white matter changes as an independent predictor of future depressive symptoms. We hypothesised that the severity of white matter changes at baseline would be associated with the development of depressive symptoms at 1 year follow-up, irrespective of known confounding variables.
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METHOD |
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In brief, inclusion criteria were: (a) between 65 and 84 years; (b) living in the community; (c) no or mild disability (only one item compromised) as assessed by the Instrumental Activities of Daily Living scale (IADL; Lawton & Brody, 1969); (d) the presence of an informant; (e) any degree of age-related white matter changes on MRI scan according to a revised version of the scale of Fazekas et al (1987).
Exclusion criteria were: (a) the presence of severe illnesses (cardiac, hepatic or renal failure, neoplastic or other relevant systemic disease) which would increase the likelihood of drop-out; (b) severe unrelated neurological diseases; (c) leucoencephalopathies revealed by brain imaging that were of non-vascular origin (immunological, demyelinating, metabolic, toxic or infectious); (e) severe psychiatric disorders; (f) refusal or inability to give informed consent; (g) refusal or inability to undergo cranial MRI scanning.
There were 639 people who fulfilled the criteria and were recruited between July 2001 and January 2003. Most were recruited after presentation to centres with mild cognitive disturbances (n=168), gait disturbances (n=28), psychiatric complaints (n=13), other neurological disturbances (n=129), or minor stroke (n=122). Other participants included those in whom white matter changes were incidentally found on computed tomography or MRI performed in other clinical settings (n=107) and controls from other studies with brain white matter changes (n=72). The total number of participants referred from each centre and the reasons for referral are given in Table DS1 of the data supplement to the online version of this paper. All participants gave informed consent.
Assessment
All participants had a comprehensive baseline demographic assessment by
trained personnel. Information was collected on age, gender, education,
occupational status, living conditions, previous medical conditions, including
stroke (as defined according to the World Health Organization;
Hatano, 1976) and hypertension
(Chalmers et al,
1999), prescribed medication, lifestyle (alcohol and smoking) and
vascular risk factors.
Further baseline clinical assessments included the following.
Participants were re-evaluated at 1 year and clinical assessments were repeated. To increase reliability, investigators were issued with a specifically designed handbook which contained guidelines for applying tools.
Magnetic resonance imaging
Participants had a baseline MRI scan at their respective centres. All
centres used MRI scanners with a field strength of 1.5 T, except for one which
had a 0.5 T system. A standard protocol was used
(Pantoni et al,
2005). For the white matter rating, a FLAIR sequence was acquired
with the following parameters: 250 mm field of vision; 256x256 or
256x192 matrix; 5 mm slice thickness; 0.5 mm slice gap; 19–28
slices; time to echo 100–140 ms; time to repetition 6000–10 000
ms; inversion time 2000–2500 ms, and echoes per shot 7–24.
Volumetric analysis of age-related white matter changes was performed on a Sparc 5 workstation (Sun, Palo Alto, California, USA; van Straaten et al, 2006). Lesions were marked using a `seed' and local thresholding was performed using home-developed software (Show Images, version 3.6.1 using a Canay filter) on each slice. When necessary, borders could be adjusted by the operator by changing thresholds for upper and lower intensity values. If all lesions are delineated, the program calculates the total surface of the outlined area. By multiplying with the interslice distance, total volume of age-related white matter changes is established (Gouw et al, 2006).
Statistical analysis
Data were collected in each centre and entered into a central electronic
database on a specifically developed website
(http://www.unifi.it/LADIS).
In a community-dwelling population it is normal for depression rating scales
to be heavily skewed towards low values. Hence for analysis we divided our
baseline and 1-year data into quintiles, using the same GDS range for each
quintile as in our previous study (O'Brien
et al, 2006). For the volume of age-related white matter
changes we used a logarithmic transformation to produce normally distributed
data.
Univariate analysis was used to examine correlations between different variables and depressive symptoms at 1 year. As depressive symptoms (as measured by GDS) are on an ordinal scale, we used Spearman's rank order correlation coefficient (r2) to determine the correlation between depressive symptoms at 1 year, the dependent variable and various independent demographic, clinical and MRI variables. Baseline independent variables included age, gender, baseline depressive symptoms (GDS), educational level, smoking status, MMSE score, stroke, hypertension, QoL and log total volume of white matter changes. Incident stroke (a new stroke over the study year) and worsening disability (an IADL score at 1 year less than at baseline) were included as further independent variables.
Multivariate analysis used ordinal logistic regression to determine predictors of the quintile of depression scale score at 1 year. The variables chosen were those which were significant in the univariate analysis and included GDS baseline quintile, worsening disability, QoL, MMSE score, years of education, incident stroke and total volume of white matter changes. We constructed a further binary logistic regression to compare predictors of a depressive episode over the year using history of depression (instead of GDS quintile) together with the other significant independent variables as predictors.
Values of P<0.05 were considered statistically significant.
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RESULTS |
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As expected for a community population, the group GDS score remained stable over time. The median GDS score was 2 at baseline and at 1 year (Wilcoxon signed-rank Z=-1.77, P=0.077). At baseline, 141 people had a history of depression for which medical help had been sought. Over the year, 85 people had an episode of depression. The number of people in each quintile of GDS at baseline and 1 year is given in Table DS2 of the data supplement to the online version of this paper.
Table 1 shows the demographic, clinical and MRI characteristics of the participants at baseline. Over the year, 14 participants had an incident stroke and 56 had worsening disability.
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Univariate analysis
Table 2 shows the results of
the univariate analysis. As expected, the GDS quintile at baseline, incident
stroke and worsening disability were significantly positively correlated with
GDS quintile at 1 year. MMSE score, number of years education and QoL score
were significantly negatively correlated with GDS quintile at 1 year.
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Log total volume of white matter changes was also significantly positively correlated with GDS quintile at 1 year (Fig. 1).
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Multiple regression analysis
Table 3 shows logistic
ordinal regression with GDS quintile at 1 year as the dependent variable and
baseline GDS quintile, QoL score, worsening IADL, MMSE score, years of
education, incident stroke and log total volume of white matter changes as
independent variables. Baseline GDS quintile, QoL, worsening IADL and log
total volume of white matter changes were significantly and independently
associated with GDS quintile at 1 year.
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To control for the effect of MRI centre as a potential confounder we constructed a further logistic regression model including MRI centre as an additional independent variable, and found that baseline log total volume of white matter changes still significantly and independently predicted GDS quintile at 1 year (P=0.046).
Table 4 shows a further binary regression with occurrence of depression over the year as the dependent variable and baseline history of depression, QoL score, worsening IADL, MMSE score, years of education, incident stroke and log total volume of white matter changes as independent variables. Baseline history of depression, QoL and worsening IADL were significantly and independently associated with depression at 1 year. The association for log total volume of white matter changes did not quite reach statistical significance (OR=1.63, P=0.1).
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DISCUSSION |
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Baseline white matter changes did not, however, significantly predict depressive episodes over the following year. The fact that we were unable to demonstrate that age-related change in white matter volume was a significant independent predictor of this clinically important measure might have been because of a lack of power in this study to detect such an effect. Incident depression may have been underreported because of the method used to screen for mood disorders. This is supported by the relatively low number of participants with incident depression (85) over the year and the fact that there was a trend towards significance (P=0.1).
Finally we established that QoL, worsening IADL and baseline GDS were significant and independent predictors of depressive symptoms, whereas incident stroke, MMSE score or years of education were not.
Previous studies
Our results support the findings of cross-sectional studies that white
matter changes are of aetiological significance for depressive symptoms in
older adults. Already a strong association between white matter changes and
depressive symptoms has been established in both hospital patients
(O'Brien et al, 1996)
and those living in the community
(Steffens et al,
1999; de Groot et al,
2000). White matter changes are also known to predict poorer
outcome (O'Brien et al,
1998) and treatment response
(Hickie et al, 1997)
in elderly people with depression. Neuropathological study has shown deep
white matter changes to have an ischaemic basis
(Thomas et al, 2002)
and it is thought that these changes represent a marker for vascular pathology
in clinically important areas of the brain. Following on from these findings
the vascular depression hypothesis has been proposed
(Baldwin & O'Brien, 2002;
Alexopoulos, 2005), which
states that disruption of fronto-striatal circuits (which reciprocally link
prefrontal cortex to basal ganglia) by vascular changes predisposes,
perpetuates or exacerbates depressive syndromes. Our study suggests that white
matter changes are associated with the development of depressive symptoms in
older adults and hence supports the vascular depression hypothesis.
Despite the convergence of evidence from cross-sectional studies, results from longitudinal studies remain unclear. In a large community population, the Cardiovascular Health Study (Steffens et al, 2002) found that small basal ganglia lesions and large cerebral cortical white matter changes at baseline predicted persistence of depressive symptoms; furthermore, subcortical white matter changes predicted worsening of depressive symptoms over time. Our data are in line with these results. However they are at variance with the findings of the study from the National Institute of Mental Health (NIMH; Taylor et al, 2003). In a cohort of 133 participants with severe depression, an increase in severity of white matter changes over 2 years, but not static baseline white matter change, predicted depressive outcome scores after controlling for baseline depressive symptoms (Taylor et al, 2003). We did not assess lesion progression; however, potential reasons for these discrepancies may be the different and highly selected population used in the smaller NIMH cohort.
Another longitudinal study, the PROSPER study (Versluis et al, 2006), rather surprisingly found that white matter changes were not related to baseline depressive features or development of depressive symptoms at follow-up. Furthermore, no association was found between progression of white matter changes and the progression of depressive symptoms. This is clearly in contrast to our results and those of other studies. Discrepancies with the current evidence may have been because of a relatively low total volume of white matter changes of participants in the PROSPER study (median 1.7 v. 13 ml in this study) and the low rate of participation of people with depressive symptoms (8% with GDS score >3 v. 35% in this study).
Nature of the relationship
Our longitudinal results provide an important demonstration that white
matter changes pre-date, and therefore may be causally related to, the
development of depressive symptoms. We cannot, however, dismiss the
possibility that depressive symptoms may also pre-date white matter changes.
The relationship may be bidirectional, just as it is with vascular risk
factors and depression in older adults
(Thomas et al, 2004;
Baldwin, 2005). It is known
that baseline vascular burden independently predicts depression
(Mast, 2004) and yet it is
also clear from longitudinal studies that depression is an independent risk
factor for later developing coronary artery disease
(Pratt et al, 1996),
stroke (Everson et al,
1998) and cardiac mortality post-myocardial infarction
(Frasure-Smith et al,
1999). The relationship is likely to be complex, although we have
helped to unravel one aspect.
Interestingly, the temporal association demonstrated remained significant even after controlling for baseline cognitive scores and worsening disability. This suggests that this effect is not simply mediated through disability or secondary to a psychological reaction to declining cognitive performance, as has also been suggested (Cahn et al, 1996; Paterniti et al, 2002).
Strengths and limitations of the study
The strengths of the LADIS Study are the large number of community-based
participants without significant disability and its multicentre design.
Further strengths include the central measurement of all scans by a single
operator and the use of a robust measure of the volume of age-related white
matter changes which is less operator dependent and less susceptible to
ceiling effects (van Straaten et
al, 2006). Finally, a strong model for logistic analysis was
constructed controlling for many potential confounders, including putative
mediators of depressive features such as cognition, QoL, incident stroke and
worsening disability.
Limitations include the recruitment of only those with white matter changes: consequently people with minimal or no health problems might have been excluded (although evidence suggests that up to 95% of older adults have some white matter changes; de Leeuw et al, 2001). Another potential limitation arises from the fact that some symptoms measured by the GDS, such as apathy and withdrawal, are not exclusive to a depressive syndrome and may also be manifestations of a mild cognitive dysexecutive syndrome. Despite this weakness we were able to demonstrate a significant association between white matter changes and depressive symptoms not only after controlling for cognitive confounders but also at higher GDS scores, when the symptoms are more likely to reflect a depressive syndrome. Finally, our results might have been influenced by sampling bias as the study population represents a heterogeneous group with a variety of different complaints but without significant disability. However, such bias is unavoidable in large multicentre studies and this heterogeneity might actually increase the generalisability of our findings.
Clinical implications
The most important implications concern the prevention of late-life
depressive symptoms. These extend more widely to the elderly population as a
whole because most participants had less disability and less depression than
seen routinely in clinical practice. Recent evidence shows that treatment of
hypertension slows progression of white matter changes
(Schiffrin, 2005). We would
therefore advocate tighter control of vascular risk factors to prevent the
development of late-life depressive symptoms.
The presence of white matter changes on MRI, if considered alone, is of little clinical value in predicting future depressive symptoms. However, when white matter changes are taken along with other independent predictors such as quality of life and previous depressive episodes, they raise the index of suspicion for further depressive symptoms. Thus in clinical practice it is wise to take account of the presence of white matter changes on MRI when attempting to predict future depressive symptoms, and this might influence decisions regarding the frequency of clinical monitoring and the need for prophylactic antidepressants.
Future research
Large studies in a community population are indicated to establish whether
static lesion volume, rate of progression, or both are the important
determinants in predicting future depressive symptoms. Further research should
also be directed at looking more precisely at the time course of emergence of
changes and of mood symptoms, and whether modification of white matter changes
influences the course of depressive symptoms.
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APPENDIX |
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The LADIS Steering Committee comprises Domenico Inzitari, MD (Study Coordinator), Timo Erkinjuntti, MD, PhD, Philip Scheltens, MD, PhD, Marieke Visser, MD, PhD, Peter Langhorne, MD, BSC, PhD, FRCP who replaced Kjell Asplund, MD, PhD in 2005.
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ACKNOWLEDGMENTS |
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TOPABSTRACTINTRODUCTIONMETHODRESULTSDISCUSSIONAPPENDIXACKNOWLEDGMENTSREFERENCES |
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Received for publication February 9, 2007. Revision received April 26, 2007. Accepted for publication June 27, 2007.
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