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Does the Framingham Stroke Risk Profile predict white-matter changes in late-life depression?

Published online by Cambridge University Press:  17 November 2011

Charlotte L. Allan ,
Claire E. Sexton ,
Ukwuori G. Kalu ,
Lisa M. McDermott ,
Mika Kivimäki ,
Archana Singh-Manoux ,
Clare E. Mackay  and
Klaus P. Ebmeier
Charlotte L. Allan*
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
Claire E. Sexton
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
Ukwuori G. Kalu
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
Lisa M. McDermott
Affiliation:
Department of Health Psychology, University of Southampton, Southampton, UK
Mika Kivimäki
Affiliation:
Department of Epidemiology & Public Health, University College London, London, UK
Archana Singh-Manoux
Affiliation:
Department of Epidemiology & Public Health, University College London, London, UK INSERM, U1018, Centre for Research in Epidemiology & Population Health, Villejuif, France
Clare E. Mackay
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
Klaus P. Ebmeier
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
*
Correspondence should be addressed to: Dr Charlotte Allan, Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK. Phone: +44 (0)1865 223635; Fax. +44 (0)1865 793101. Email. Charlotte.allan@psych.ox.ac.uk.
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Abstract

Background: Cardiovascular risk factors and diseases are important etiological factors in depression, particularly late-life depression. Brain changes associated with vascular disease and depression can be detected using magnetic resonance imaging. Using diffusion tensor imaging (DTI), we investigated whether the Framingham Stroke Risk Profile (FSRP), a well-validated risk prediction algorithm, is associated with changes in white-matter connectivity. We hypothesized that depressed participants would show reduced white-matter integrity with higher FSRP, and non-depressed controls (matched for mean vascular risk) would show minimal co-variance with white-matter changes.

Methods: Thirty-six participants with major depression (age 71.8 ± 7.7 years, mean FSRP 10.3 ± 7.6) and 25 controls (age 71.8 ± 7.3 years, mean FSRP 10.1 ± 7.7) were clinically interviewed and examined, followed by 60-direction DTI on a 3.0 Tesla scanner. Image analysis was performed using FSL tools (www.fmrib.ox.ac.uk/fsl) to assess the correlation between FSRP and fractional anisotropy (FA). Voxelwise statistical analysis of the FA data was carried out using Tract Based Spatial Statistics. The significance threshold for correlations was set at p < 0.05 using threshold-free cluster-enhancement. Partial correlation analysis investigated significant correlations in each group.

Results: Participants in the depressed group showed highly significant correlations between FSRP and FA within the body of corpus callosum (r = −0.520, p = 0.002), genu of corpus callosum (r = −0.468, p = 0.005), splenium of corpus callosum (r = −0.536, p = 0.001), and cortico-spinal tract (r = −0.473, p = 0.005). In controls, there was only one significant correlation in the body of corpus callosum (r = −0.473, p = 0.023).

Conclusions: FSRP is associated with impairment in white-matter integrity in participants with depression; these results suggest support for the vascular depression hypothesis.

Keywords

mood disorderimagingneuroimaging
Type
2011 IPA JUNIOR RESEARCH AWARDS – SECOND-PRIZE WINNER
Information
International Psychogeriatrics , Volume 24 , Issue 4 , April 2012 , pp. 524 - 531
Copyright
Copyright © International Psychogeriatric Association 2011

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