Skip to main content
    • Aa
    • Aa
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 4
  • Cited by
    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Allan, Charlotte L. Sexton, Claire E. Filippini, Nicola Topiwala, Anya Mahmood, Abda Zsoldos, Enikő Singh-Manoux, Archana Shipley, Martin J. Kivimaki, Mika Mackay, Clare E. and Ebmeier, Klaus P. 2016. Sub-threshold depressive symptoms and brain structure: A magnetic resonance imaging study within the Whitehall II cohort. Journal of Affective Disorders, Vol. 204, p. 219.

    Foguet-Boreu, Quintí Fernandez San Martin, Maria Isabel Flores Mateo, Gemma Zabaleta del Olmo, Edurne Ayerbe García-Morzon, Luís Perez-Piñar López, Maria Martin-López, Luis Miguel Montes Hidalgo, Javier and Violán, Concepción 2016. Cardiovascular risk assessment in patients with a severe mental illness: a systematic review and meta-analysis. BMC Psychiatry, Vol. 16, Issue. 1,

    Zsoldos, E. and Ebmeier, K.P. 2016. Stress: Concepts, Cognition, Emotion, and Behavior.

    Charlton, Rebecca A. Lamar, Melissa Ajilore, Olusola and Kumar, Anand 2014. Associations Between Vascular Risk and Mood in Euthymic Older Adults: Preliminary Findings. The American Journal of Geriatric Psychiatry, Vol. 22, Issue. 9, p. 936.


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

  • Charlotte L. Allan (a1), Claire E. Sexton (a1), Ukwuori G. Kalu (a1), Lisa M. McDermott (a2), Mika Kivimäki (a3), Archana Singh-Manoux (a3) (a4), Clare E. Mackay (a1) and Klaus P. Ebmeier (a1)
  • DOI:
  • Published online: 17 November 2011

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 ( 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.

Corresponding author
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.
Linked references
Hide All

This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

G. S. Alexopoulos , B. S. Meyers , R. C. Young , S. Campbell , D. Silbersweig and M. Charlson (1997). “Vascular depression” hypothesis. Archives of General Psychiatry, 54, 915922.

R. L. Buckner (2004). Memory and executive function in aging and AD: multiple factors that cause decline and reserve factors that compensate. Neuron, 44, 195208.

C. S. Chen , C. C. Chen , Y. T. Kuo , I. C. Chiang , C. H. Ko and H. F. Lin (2006). Carotid intima-media thickness in late-onset major depressive disorder. International Journal of Geriatric Psychiatry, 21, 3642.

K. Christensen , G. Doblhammer , R. Rau and J. W. Vaupel (2009). Ageing populations: the challenges ahead. Lancet, 374, 11961208.

E. Crimmins (2004). Trends in the health of the elderly. Annual Review of Public Health, 25, 7998.

R. B. D'Agostino , P. A. Wolf , A. J. Belanger and W. B. Kannel (1994). Stroke risk profile: adjustment for antihypertensive medication: the Framingham Study. Stroke, 25, 4043.

R. B. D'Agostino (2008). General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation, 117, 743753.

M. F. Folstein , S. E. Folstein and P. R. McHugh (1975). “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189198.

I. Hajjar (2011). Hypertension, white matter hyperintensities, and concurrent impairments in mobility, cognition, and mood: the cardiovascular health study. Circulation, 123, 858865.

M. Hamilton (1967). Development of a rating scale for primary depressive illness. British Journal Social and Clinical Psychology, 6, 278296.

L. Herrmann , M. Le Masurier and K. Ebmeier (2008). White matter hyperintensities in late life depression: A systematic review. Journal of Neurology Neurosurgery and Psychiatry, 79, 619624.

M. J. Hoptman (2009). Blood pressure and white matter integrity in geriatric depression. Journal of Affective Disorders, 115, 171176.

T. Jeerakathil (2004). Stroke risk profile predicts white matter hyperintensity volume: the Framingham Study. Stroke, 35, 18571861.

D. K. Jones (2004). The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study. Magnetic Resonance in Medicine, 51, 807815.

B. McGurn (2004). Pronunciation of irregular words is preserved in dementia, validating premorbid IQ estimation. Neurology, 62, 11841186.

E. Mioshi , K. Dawson , J. Mitchell , R. Arnold and J. R. Hodges (2006). The Addenbrooke's Cognitive Examination revised (ACE-R): a brief cognitive test battery for dementia screening. International Journal of Geriatric Psychiatry, 21, 10781085.

T. E. Nichols and A. P. Holmes (2002). Nonparametric permutation tests for functional neuroimaging: a primer with examples. Human Brain Mapping, 15, 125.

D. C. Park and P. Reuter-Lorenz (2009). The adaptive brain: aging and neurocognitive scaffolding. Annual Review of Psychology, 60, 173196.

G. C. Roman (1996). From UBOs to Binswanger's disease: impact of magnetic resonance imaging on vascular dementia research. Stroke, 27, 12691273.

C. E. Sexton , C. E. Mackay and K. P. Ebmeier (2009). A systematic review of diffusion tensor imaging studies in affective disorders. Biological Psychiatry, 66, 814823.

Y. I. Sheline (2008). Regional white matter hyperintensity burden in automated segmentation distinguishes late-life depressed subjects from comparison subjects matched for vascular risk factors. American Journal of Psychiatry, 165, 524532.

Y. I. Sheline (2010). Support for the vascular depression hypothesis in late-life depression: results of a 2-site, prospective, antidepressant treatment trial. Archives of General Psychiatry, 67, 277285.

J. S. Shimony (2009). Diffuse microstructural abnormalities of normal-appearing white matter in late life depression: a diffusion tensor imaging study. Biological Psychiatry, 66, 245252.

P. J. Smith (2009). Intima-media thickness and age of first depressive episode. Biological Psychology, 80, 361364.

P. J. Smith (2010). Cerebrovascular risk factors and cerebral hyperintensities among middle-aged and older adults with major depression. American Journal of Geriatric Psychiatry, 18, 848852.

S. M. Smith (2002). Fast robust automated brain extraction. Human Brain Mapping, 17, 143155.

S. M. Smith (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23 (Suppl. 1), S208S219.

S. M. Smith (2006). Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. NeuroImage, 31, 14871505.

S. M. Smith and T. E. Nichols (2009). Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. NeuroImage, 44, 8398.

A. J. Thomas (2002). Ischemic basis for deep white matter hyperintensities in major depression: a neuropathological study. Archives of General Psychiatry, 59, 785792.

A. J. Thomas , R. Perry , R. N. Kalaria , A. Oakley , W. McMeekin and J. T. O'Brien (2003). Neuropathological evidence for ischemia in the white matter of the dorsolateral prefrontal cortex in late-life depression. International Journal of Geriatric Psychiatry, 18, 713.

A. J. Thomas , R. N. Kalaria and J. T. O'Brien (2004). Depression and vascular disease: what is the relationship? Journal of Affective Disorders, 79, 8195.

P. W. Wilson , R. B. D'Agostino , D. Levy , A. M. Belanger , H. Silbershatz and W. B. Kannel (1998). Prediction of coronary heart disease using risk factor categories. Circulation, 97, 18371847.

J. A. Yesavage (1982). Development and validation of a geriatric depression screening scale: a preliminary report. Journal of Psychiatric Research, 17, 3749.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

International Psychogeriatrics
  • ISSN: 1041-6102
  • EISSN: 1741-203X
  • URL: /core/journals/international-psychogeriatrics
Please enter your name
Please enter a valid email address
Who would you like to send this to? *