Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-02T18:59:50.407Z Has data issue: false hasContentIssue false
  • English
  • Français

Location and progression of cerebral small-vessel disease and atrophy, and depressive symptom profiles: The Second Manifestations of ARTerial disease (SMART)-Medea study

Published online by Cambridge University Press:  11 August 2011

A. M. Grool ,
Y. van der Graaf ,
W. P. Th. M. Mali ,
Th. D. Witkamp ,
K. L. Vincken  and
M. I. Geerlings
A. M. Grool
Affiliation:
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
Y. van der Graaf
Affiliation:
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
W. P. Th. M. Mali
Affiliation:
Department of Radiology, University Medical Center Utrecht, The Netherlands
Th. D. Witkamp
Affiliation:
Department of Radiology, University Medical Center Utrecht, The Netherlands
K. L. Vincken
Affiliation:
Image Sciences Institute, University Medical Center Utrecht, The Netherlands
M. I. Geerlings*
Affiliation:
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
*
*Address for correspondence: M. I. Geerlings, Ph.D., University Medical Center Utrecht, Julius Center for Health Sciences and Primary Care, Stratenum 6.131, PO Box 85500, 3508 GA Utrecht, The Netherlands. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

The ‘vascular depression’ hypothesis states that brain changes located in frontal-subcortical pathways increase vulnerability for specific depressive symptom profiles, but studies examining locations of small-vessel and degenerative changes with individual symptoms are scarce. We examined whether location and progression of white-matter lesions (WMLs), lacunar infarcts and atrophy were associated with motivational and mood symptoms in patients with symptomatic atherosclerotic disease.

Method

In 578 patients [63 (s.d.=8) years] of the Second Manifestations of ARTerial disease (SMART)-Medea study, volumes of WMLs and atrophy and visually rated infarcts were obtained with 1.5 T magnetic resonance imaging at baseline and after 3.9 (s.d.=0.4) years' follow-up. Depressive symptoms were assessed with Patient Health Questionnaire-9 at follow-up and categorized into motivational and mood symptoms.

Results

Regression analyses adjusted for age, gender, education, Mini-Mental State Examination, physical functioning, antidepressant use and vascular risk factors showed that location in mainly deep white-matter tracts and progression of WMLs were associated with symptoms of anhedonia, concentration problems, psychomotor retardation and appetite disturbance. Lacunar infarcts in deep white matter were associated with greater motivational [Incidence rate ratio (IRR) 1.7, 95% confidence interval (CI) 1.2–2.4] and mood (IRR 1.7, 95% CI 1.1–2.6) sumscores, and with symptoms of psychomotor retardation, energy loss and depressed mood; lacunar infarcts in the thalamus were associated with psychomotor retardation only. Cortical atrophy was associated with symptoms of anhedonia and appetite disturbance. Excluding patients with major depression did not materially change the results.

Conclusions

Our findings suggest that disruption of frontal-subcortical pathways by small-vessel lesions leads to a symptom profile that is mainly characteristic of motivational problems, also in the absence of major depression.

Keywords

AtherosclerosiscerebrovasculardepressionMRI
Type
Original Articles
Information
Psychological Medicine , Volume 42 , Issue 2 , February 2012 , pp. 359 - 370
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alexopoulos, GS (2001). ‘The depression–executive dysfunction syndrome of late life’: a specific target for D3 agonists? American Journal of Geriatric Psychiatry 9, 22–29.Google ScholarPubMed
Alexopoulos, GS, Kiosses, DN, Klimstra, S, Kalayam, B, Bruce, ML (2002). Clinical presentation of the ‘depression–executive dysfunction syndrome’ of late life. American Journal of Geriatric Psychiatry 10, 98–106.Google ScholarPubMed
Alexopoulos, GS, Meyers, BS, Young, RC, Campbell, S, Silbersweig, D, Charlson, M (1997 a). ‘Vascular depression’ hypothesis. Archives of General Psychiatry 54, 915–922.Google Scholar
Alexopoulos, GS, Meyers, BS, Young, RC, Kakuma, T, Silbersweig, D, Charlson, M (1997 b). Clinically defined vascular depression. American Journal of Psychiatry 154, 562–565.Google ScholarPubMed
Anbeek, P, Vincken, KL, van Bochove, GS, van Osch, MJ, van der Grond, J (2005). Probabilistic segmentation of brain tissue in MR imaging. Neuroimage 27, 795–804.CrossRefGoogle ScholarPubMed
Anbeek, P, Vincken, KL, van Osch, MJ, Bisschops, RH, van der Grond, J (2004). Probabilistic segmentation of white matter lesions in MR imaging. Neuroimage 21, 1037–1044.Google Scholar
APA (1994). American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, DSM-IV. APA: Washington, DC.Google Scholar
Barros, AJ, Hirakata, VN (2003). Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Medical Research Methodology 3, 21.CrossRefGoogle ScholarPubMed
Blizzard, L, Hosmer, DW (2006). Parameter estimation and goodness-of-fit in log binomial regression. Biometrical Journal 48, 5–22.CrossRefGoogle ScholarPubMed
Brickman, AM, Schupf, N, Manly, JJ, Luchsinger, JA, Andrews, H, Tang, MX, Reitz, C, Small, SA, Mayeux, R, DeCarli, C, Brown, TR (2008). Brain morphology in older African Americans, Caribbean Hispanics, and whites from northern Manhattan. Archives of Neurology 65, 1053–1061.CrossRefGoogle ScholarPubMed
Burgess, PW, Shallice, T (1996). Bizarre responses, rule detection and frontal lobe lesions. Cortex 32, 241–259.Google Scholar
de Groot, JC, de Leeuw, FE, Oudkerk, M, Hofman, A, Jolles, J, Breteler, MM (2000). Cerebral white matter lesions and depressive symptoms in elderly adults. Archives of General Psychiatry 57, 1071–1076.Google Scholar
Folstein, MF, Folstein, SE, McHugh, PR (1975). ‘Mini-mental state’: a practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research 12, 189–198.CrossRefGoogle Scholar
Forsell, Y, Jorm, AF, Fratiglioni, L, Grut, M, Winblad, B (1993). Application of DSM-III-R criteria for major depressive episode to elderly subjects with and without dementia. American Journal of Psychiatry 150, 1199–1202.Google ScholarPubMed
Freeman, SH, Kandel, R, Cruz, L, Rozkalne, A, Newell, K, Frosch, MP, Hedley-Whyte, ET, Locascio, JJ, Lipsitz, LA, Hyman, BT (2008). Preservation of neuronal number despite age-related cortical brain atrophy in elderly subjects without Alzheimer disease. Journal of Neuropathology and Experimental Neurology 67, 1205–1212.Google Scholar
Geerlings, MI, Appelman, AP, Vincken, KL, Algra, A, Witkamp, TD, Mali, WP, van der Graaf, Y (2010). Brain volumes and cerebrovascular lesions on MRI in patients with atherosclerotic disease. The SMART-MR study. Atherosclerosis 210, 130–136.CrossRefGoogle ScholarPubMed
Grool, AM, Van der Graaf, Y, Mali, WP, Geerlings, MI; on behalf of the SMART Study Group (2011). Location of cerebrovascular and degenerative changes, depressive symptoms and cognitive functioning in later life: the SMART-Medea study. Journal of Neurology, Neurosurgery and Psychiatry. Published online: 1 April 2011. doi:10.1136/jnnp.2010.232413.Google Scholar
Ikram, MA, Luijendijk, HJ, Vernooij, MW, Hofman, A, Niessen, WJ, van der Lugt, A, Tiemeier, H, Breteler, MM (2010). Vascular brain disease and depression in the elderly. Epidemiology 21, 78–81.Google Scholar
Janzing, J, Teunisse, R, Bouwens, P, van ‘t Hof, M, Zitman, F (1999). Mood and motivation disturbance in elderly subjects with and without dementia: a replication study. Journal of Nervous and Mental Disease 187, 117–119.Google Scholar
Krishnan, KR, Hays, JC, Blazer, DG (1997). MRI-defined vascular depression. American Journal of Psychiatry 154, 497–501.Google Scholar
Krishnan, KR, Taylor, WD, McQuoid, DR, MacFall, JR, Payne, ME, Provenzale, JM, Steffens, DC (2004). Clinical characteristics of magnetic resonance imaging-defined subcortical ischemic depression. Biological Psychiatry 55, 390–397.Google Scholar
Kroenke, K, Spitzer, RL, Williams, JB (2001). The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine 16, 606–613.CrossRefGoogle ScholarPubMed
Lee, SJ, Kim, JS, Chung, SW, Kim, BS, Ahn, KJ, Lee, KS (2010). White matter hyperintensities (WMH) are associated with intracranial atherosclerosis rather than extracranial atherosclerosis. Archives of Gerontology and Geriatrics. Published online: 26 August 2010. doi:10.1016/j.archger.2010.07.008.Google ScholarPubMed
Licht-Strunk, E, Bremmer, MA, van Marwijk, HW, Deeg, DJ, Hoogendijk, WJ, de Haan, M, van Tilburg, W, Beekman, AT (2004). Depression in older persons with versus without vascular disease in the open population: similar depressive symptom patterns, more disability. Journal of Affective Disorders 83, 155–160.CrossRefGoogle ScholarPubMed
McNutt, LA, Wu, C, Xue, X, Hafner, JP (2003). Estimating the relative risk in cohort studies and clinical trials of common outcomes. American Journal of Epidemiology 157, 940–943.Google Scholar
Muller, M, Appelman, AP, van der Graaf, Y, Vincken, KL, Mali, WP, Geerlings, MI (2011). Brain atrophy and cognition: interaction with cerebrovascular pathology? Neurobiology of Aging 32, 885–893.Google Scholar
Naarding, P, Tiemeier, H, Breteler, MM, Schoevers, RA, Jonker, C, Koudstaal, PJ, Beekman, AT (2007). Clinically defined vascular depression in the general population. Psychological Medicine 37, 383–392.CrossRefGoogle ScholarPubMed
Nebes, RD, Vora, IJ, Meltzer, CC, Fukui, MB, Williams, RL, Kamboh, MI, Saxton, J, Houck, PR, DeKosky, ST, Reynolds, CF III (2001). Relationship of deep white matter hyperintensities and apolipoprotein E genotype to depressive symptoms in older adults without clinical depression. American Journal of Psychiatry 158, 878–884.CrossRefGoogle ScholarPubMed
Newson, RS, Hek, K, Luijendijk, HJ, Hofman, A, Witteman, JC, Tiemeier, H (2010). Atherosclerosis and incident depression in late life. Archives of General Psychiatry 67, 1144–1150.Google Scholar
Pantoni, L (2002). Pathophysiology of age-related cerebral white matter changes. Cerebrovascular Diseases 13 (Suppl. 2), 7–10.Google Scholar
Robbins, AS, Chao, SY, Fonseca, VP (2002). What's the relative risk? A method to directly estimate risk ratios in cohort studies of common outcomes. Annals of Epidemiology 12, 452–454.CrossRefGoogle ScholarPubMed
Robertson, IH, Ward, T, Ridgeway, V, Nimmo-Smith, I (1996). The structure of normal human attention: the test of every attention. Journal of the International Neuropsychological Society 2, 525–534.CrossRefGoogle Scholar
Robins, LN, Wing, J, Wittchen, HU, Helzer, JE, Babor, TF, Burke, J, Farmer, A, Jablenski, A, Pickens, R, Regier, DA (1988). The Composite International Diagnostic Interview. An epidemiologic instrument suitable for use in conjunction with different diagnostic systems and in different cultures. Archives of General Psychiatry 45, 1069–1077.Google Scholar
Steffens, DC, Krishnan, KR, Crump, C, Burke, GL (2002). Cerebrovascular disease and evolution of depressive symptoms in the cardiovascular health study. Stroke 33, 1636–1644.Google Scholar
Taylor, WD, Steffens, DC, Krishnan, KR (2006). Psychiatric disease in the twenty-first century: the case for subcortical ischemic depression. Biological Psychiatry 60, 1299–1303.Google Scholar
Thombs, BD, Ziegelstein, RC, Whooley, MA (2008). Optimizing detection of major depression among patients with coronary artery disease using the patient health questionnaire: data from the Heart and Soul Study. Journal of General Internal Medicine 23, 2014–2017.Google Scholar
van den Heuvel, DM, ten Dam, V, de Craen, AJ, Admiraal-Behloul, F, van Es, AC, Palm, WM, Spilt, A, Bollen, EL, Blauw, GJ, Launer, L, Westendorp, RG, van Buchem, MA (2006). Measuring longitudinal white matter changes: comparison of a visual rating scale with a volumetric measurement. American Journal of Neuroradiology 27, 875–878.Google Scholar
van der Flier, WM, van Straaten, EC, Barkhof, F, Verdelho, A, Madureira, S, Pantoni, L, Inzitari, D, Erkinjuntti, T, Crisby, M, Waldemar, G, Schmidt, R, Fazekas, F, Scheltens, P (2005). Small vessel disease and general cognitive function in nondisabled elderly: the LADIS study. Stroke 36, 2116–2120.Google Scholar
Ware, JE, Kosinski, M, Keller, SD (1996). A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Medical Care 34, 220–233.Google Scholar
Yoshita, M, Fletcher, E, DeCarli, C (2005). Current concepts of analysis of cerebral white matter hyperintensities on magnetic resonance imaging. Topics in Magnetic Resonance Imaging 16, 399–407.Google Scholar
Zgaljardic, DJ, Borod, JC, Foldi, NS, Mattis, P (2003). A review of the cognitive and behavioral sequelae of Parkinson's disease: relationship to frontostriatal circuitry. Cognitive and Behavioural Neurology 16, 193–210.Google Scholar
Zuithoff, NP, Vergouwe, Y, King, M, Nazareth, I, van Wezep, MJ, Moons, KG, Geerlings, MI (2010). The Patient Health Questionnaire-9 for detection of major depressive disorder in primary care: consequences of current thresholds in a cross-sectional study. BMC Family Practice 11, 98.Google Scholar