Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-11T07:35:09.127Z Has data issue: false hasContentIssue false
  • English
  • Français

Localization of white-matter lesions and effect of vascular risk factors in late-onset major depression

Published online by Cambridge University Press:  09 November 2009

R. B. Dalby ,
M. M. Chakravarty ,
J. Ahdidan ,
L. Sørensen ,
J. Frandsen ,
K. Y. Jonsdottir ,
E. Tehrani ,
R. Rosenberg ,
L. Østergaard  and
P. Videbech
R. B. Dalby*
Affiliation:
Center for Psychiatric Research, Aarhus University Hospital, Risskov, Denmark
M. M. Chakravarty
Affiliation:
Allen Institute for Brain Science, Seattle, WA, USA PET Center, Aarhus University Hospital, Aarhus Sygehus, Aarhus, Denmark Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Aarhus, Denmark
J. Ahdidan
Affiliation:
Center for Psychiatric Research, Aarhus University Hospital, Risskov, Denmark
L. Sørensen
Affiliation:
Department of Neuroradiology, Aarhus University Hospital, Aarhus Sygehus, Aarhus, Denmark
J. Frandsen
Affiliation:
Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Aarhus, Denmark
K. Y. Jonsdottir
Affiliation:
Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Aarhus, Denmark
E. Tehrani
Affiliation:
Center for Psychiatric Research, Aarhus University Hospital, Risskov, Denmark
R. Rosenberg
Affiliation:
Center for Psychiatric Research, Aarhus University Hospital, Risskov, Denmark
L. Østergaard
Affiliation:
Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, Aarhus, Denmark
P. Videbech
Affiliation:
Center for Psychiatric Research, Aarhus University Hospital, Risskov, Denmark
*
*Address for correspondence: Dr R. B. Dalby, Center for Psychiatric Research, Aarhus University Hospital, Skovagervej 2, DK-8240 Risskov, Denmark. (Email: rbdalby@dadlnet.dk)
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Several studies suggest that patients with late-onset major depression (MD) have an increased load of cerebral white-matter lesions (WMLs) compared with age-matched controls. Vascular risk factors such as hypertension and smoking may confound such findings. Our aim was to investigate the association between the localization and load of WMLs in late-onset MD with respect to vascular risk factors.

Method

We examined 22 consecutive patients with late-onset first-episode MD and 22 age- and gender-matched controls using whole-brain magnetic resonance imaging (MRI). The localization, number and volume of WMLs were compared between patients and controls, while testing the effect of vascular risk factors.

Results

Among subjects with one or more WMLs, patients displayed a significantly higher WML density in two white-matter tracts: the left superior longitudinal fasciculus and the right frontal projections of the corpus callosum. These tracts are part of circuitries essential for cognitive and emotional functions. Analyses revealed no significant difference in the total number and volume of WMLs between groups. Patients and controls showed no difference in vascular risk factors, except for smoking. Lesion load was highly correlated with smoking.

Conclusions

Our results indicate that lesion localization rather than lesion load differs between patients with late-onset MD and controls. Increased lesion density in regions associated with cognitive and emotional functions may be crucial in late-onset MD, and vascular risk factors such as smoking may play an important role in the pathophysiology of late-onset MD, consistent with the vascular depression hypothesis.

Keywords

Late-onset major depressionmagnetic resonance imagingwhite-matter hyperintensitieswhite-matter lesionssmokingvascular risk factors
Type
Original Articles
Information
Psychological Medicine , Volume 40 , Issue 8 , August 2010 , pp. 1389 - 1399
Copyright
Copyright © Cambridge University Press 2009

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, Meyers, BS, Young, RC, Campbell, S, Silbersweig, D, Charlson, M (1997 a). ‘Vascular depression’ hypothesis. Archives of General Psychiatry 54, 915–922.CrossRefGoogle ScholarPubMed
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
APA (2000). Diagnostic and Statistical Manual of Mental Disorders, 4th edn, text revision. American Psychiatric Association: Washington, DC.Google Scholar
Austin, MP, Mitchell, P, Goodwin, GM (2001). Cognitive deficits in depression: possible implications for functional neuropathology. British Journal of Psychiatry 178, 200–206.CrossRefGoogle ScholarPubMed
Awad, IA, Spetzler, RF, Hodak, JA, Awad, CA, Carey, R (1986). Incidental subcortical lesions identified on magnetic resonance imaging in the elderly. I. Correlation with age and cerebrovascular risk factors. Stroke 17, 1084–1089.CrossRefGoogle ScholarPubMed
Bech, P (2002). The Bech–Rafaelsen Melancholia Scale (MES) in clinical trials of therapies in depressive disorders: a 20-year review of its use as outcome measure. Acta Psychiatrica Scandinavica 106, 252–264.CrossRefGoogle ScholarPubMed
Breteler, MMB, van Swieten, JC, Bots, ML, Grobbee, DE, Claus, JJ, van den Hout, JHW, van Harskamp, F, Tanghe, HLJ, de Jong, PTVM, van Gijn, J, Hofman, A (1994). Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam Study. Neurology 44, 1246–1252.CrossRefGoogle Scholar
Brodmann, K, Gary, LJ (2006). Brodmann's Localisation in the Cerebral Cortex: The Principles of Comparative Localisation in the Cerebral Cortex based on Cytoarchitectonics. Springer: New York, NY.Google Scholar
Cao, J (1999). The size of the connected components of excursion sets of x2, T and F fields. Advances in Applied Probability 31, 579–595.CrossRefGoogle Scholar
Chen, PS, McQuoid, DR, Payne, ME, Steffens, DC (2006). White matter and subcortical gray matter lesion volume changes and late-life depression outcome: a 4-year magnetic resonance imaging study. International Psychogeriatrics 18, 445–456.CrossRefGoogle ScholarPubMed
Chouinard, PA, Paus, T (2006). The primary motor and premotor areas of the human cerebral cortex. Neuroscientist 12, 143–152.CrossRefGoogle ScholarPubMed
Collins, DL, Holmes, CJ, Peters, TM, Evans, AC (1995). Automatic 3-D model-based neuroanatomical segmentation. Human Brain Mapping 3, 190–208.CrossRefGoogle Scholar
Collins, DL, Neelin, P, Peters, TM, Evans, AC (1994). Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. Journal of Computer Assisted Tomography 18, 192–205.CrossRefGoogle ScholarPubMed
de Leeuw, FE, de Groot, JC, Achten, E, Oudkerk, M, Ramos, LM, Heijboer, R, Hofman, A, Jolles, J, van Gijn, J, Breteler, MM (2001). Prevalence of cerebral white matter lesions in elderly people: a population based magnetic resonance imaging study. The Rotterdam Scan Study. Journal of Neurology, Neurosurgery and Psychiatry 70, 9–14.CrossRefGoogle Scholar
Drevets, WC (2007). Orbitofrontal cortex function and structure in depression. Annals of the New York Academy of Sciences 1121, 499–527.CrossRefGoogle ScholarPubMed
Evans, AC, Collins, DL, Mills, SR, Brown, ED, Kelly, RL, Peters, TM (1994). 3D statistical neuroanatomical models from 305 MRI volumes. In Proceedings of the 1993 IEEE Nuclear Science Symposium & Medical Imaging Conference. San Francisco, CA, USA: IEEE, pp. 1813–1817.Google Scholar
Fazekas, F, Barkhof, F, Wahlund, LO, Pantoni, L, Erkinjuntti, T, Scheltens, P, Schmidt, R (2002). CT and MRI rating of white matter lesions. Cerebrovascular Diseases 13 (Suppl. 2), 31–36.CrossRefGoogle ScholarPubMed
Fazekas, F, Kleinert, R, Offenbacher, H, Schmidt, R, Kleinert, G, Payer, F, Radner, H, Lechner, H (1993). Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology 43, 1683–1689.CrossRefGoogle ScholarPubMed
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
Goodwin, GM (1997). Neuropsychological and neuroimaging evidence for the involvement of the frontal lobes in depression. Journal of Psychopharmacology 11, 115–122.CrossRefGoogle ScholarPubMed
Greenwald, BS, Kramer-Ginsberg, E, Krishnan, KR, Ashtari, M, Auerbach, C, Patel, M (1998). Neuroanatomic localization of magnetic resonance imaging signal hyperintensities in geriatric depression. Stroke 29, 613–617.CrossRefGoogle ScholarPubMed
Gunning-Dixon, FM, Raz, N (2000). The cognitive correlates of white matter abnormalities in normal aging: a quantitative review. Neuropsychology 14, 224–232.CrossRefGoogle ScholarPubMed
Haggard, P (2008). Human volition: towards a neuroscience of will. Nature Reviews Neuroscience 9, 934–946.CrossRefGoogle ScholarPubMed
Herrmann, LL, Goodwin, GM, Ebmeier, KP (2007). The cognitive neuropsychology of depression in the elderly. Psychological Medicine 37, 1693–1702.CrossRefGoogle ScholarPubMed
Herrmann, LL, Le Masurier, M, Ebmeier, KP (2008). White matter hyperintensities in late life depression: a systematic review. Journal of Neurology, Neurosurgery and Psychiatry 79, 619–624.CrossRefGoogle ScholarPubMed
Hickie, I, Scott, E, Mitchell, P, Wilhelm, K, Austin, MP, Bennett, B (1995). Subcortical hyperintensities on magnetic resonance imaging: clinical correlates and prognostic significance in patients with severe depression. Biological Psychiatry 37, 151–160.CrossRefGoogle ScholarPubMed
Hudson, CG (2005). Socioeconomic status and mental illness: tests of the social causation and selection hypotheses. American Journal of Orthopsychiatry 75, 3–18.CrossRefGoogle ScholarPubMed
Iosifescu, DV, Renshaw, PF, Lyoo, IK, Lee, HK, Perlis, RH, Papakostas, GI, Nierenberg, AA, Fava, M (2006). Brain white-matter hyperintensities and treatment outcome in major depressive disorder. British Journal of Psychiatry 188, 180–185.CrossRefGoogle ScholarPubMed
Jane-Llopis, E, Matytsina, I (2006). Mental health and alcohol, drugs and tobacco: a review of the comorbidity between mental disorders and the use of alcohol, tobacco and illicit drugs. Drug and Alcohol Review 25, 515–536.CrossRefGoogle ScholarPubMed
Kales, HC, Maixner, DF, Mellow, AM (2005). Cerebrovascular disease and late-life depression. American Journal of Geriatric Psychiatry 13, 88–98.CrossRefGoogle ScholarPubMed
Kendler, KS, Neale, MC, MacLean, CJ, Heath, AC, Eaves, LJ, Kessler, RC (1993). Smoking and major depression. A causal analysis. Archives of General Psychiatry 50, 36–43.CrossRefGoogle ScholarPubMed
Krawczyk, DC (2002). Contributions of the prefrontal cortex to the neural basis of human decision making. Neuroscience and Biobehavioral Reviews 26, 631–664.CrossRefGoogle Scholar
Krishnan, KR, Hays, JC, Blazer, DG (1997). MRI-defined vascular depression. American Journal of Psychiatry 154, 497–501.Google ScholarPubMed
Krishnan, KR, McDonald, WM (1995). Arteriosclerotic depression. Medical Hypotheses 44, 111–115.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Krishnan, MS, O'Brien, JT, Firbank, MJ, Pantoni, L, Carlucci, G, Erkinjuntti, T, Wallin, A, Wahlund, LO, Scheltens, P, van Straaten, EC, Inzitari, D (2006). Relationship between periventricular and deep white matter lesions and depressive symptoms in older people. The LADIS Study. International Journal of Geriatric Psychiatry 21, 983–989.CrossRefGoogle ScholarPubMed
Liao, D, Cooper, L, Cai, J, Toole, J, Bryan, N, Burke, G, Shahar, E, Nieto, J, Mosley, T, Heiss, G (1997). The prevalence and severity of white matter lesions, their relationship with age, ethnicity, gender, and cardiovascular disease risk factors: the ARIC Study. Neuroepidemiology 16, 149–162.CrossRefGoogle ScholarPubMed
MacFall, JR, Payne, ME, Provenzale, JE, Krishnan, KR (2001). Medial orbital frontal lesions in late-onset depression. Biological Psychiatry 49, 803–806.CrossRefGoogle ScholarPubMed
Mazziotta, J, Toga, A, Evans, A, Fox, P, Lancaster, J, Zilles, K, Woods, R, Paus, T, Simpson, G, Pike, B, Holmes, C, Collins, L, Thompson, P, MacDonald, D, Iacoboni, M, Schormann, T, Amunts, K, Palomero-Gallagher, N, Geyer, S, Parsons, L, Narr, K, Kabani, N, Le Goualher, G, Boomsma, D, Cannon, T, Kawashima, R, Mazoyer, B (2001). A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philosophical Transactions of the Royal Society B: Biological Sciences 356, 1293–1322.CrossRefGoogle Scholar
Naranjo, CA, Tremblay, LK, Busto, UE (2001). The role of the brain reward system in depression. Progress in Neuro-Psychopharmacology and Biological Psychiatry 25, 781–823.CrossRefGoogle ScholarPubMed
O'Brien, J, Desmond, P, Ames, D, Schweitzer, I, Harrigan, S, Tress, B (1996). A magnetic resonance imaging study of white matter lesions in depression and Alzheimer's disease. British Journal of Psychiatry 168, 477–485.CrossRefGoogle ScholarPubMed
O'Brien, JT, Firbank, MJ, Krishnan, MS, van Straaten, EC, van der Flier, WM, Petrovic, K, Pantoni, L, Simoni, M, Erkinjuntti, T, Wallin, A, Wahlund, LO, Inzitari, D (2006). White matter hyperintensities rather than lacunar infarcts are associated with depressive symptoms in older people: the LADIS study. American Journal of Geriatric Psychiatry 14, 834–841.CrossRefGoogle ScholarPubMed
Pantoni, L, Garcia, JH (1997). Pathogenesis of leukoaraiosis: a review. Stroke 28, 652–659.CrossRefGoogle ScholarPubMed
Phillips, ML, Ladouceur, CD, Drevets, WC (2008). A neural model of voluntary and automatic emotion regulation: implications for understanding the pathophysiology and neurodevelopment of bipolar disorder. Molecular Psychiatry 13, 829–857.CrossRefGoogle ScholarPubMed
Robbins, S, Evans, AC, Collins, DL, Whitesides, S (2004). Tuning and comparing spatial normalization methods. Medical Image Analysis 8, 311–323.CrossRefGoogle ScholarPubMed
Rogers, MA, Kasai, K, Koji, M, Fukuda, R, Iwanami, A, Nakagome, K, Fukuda, M, Kato, N (2004). Executive and prefrontal dysfunction in unipolar depression: a review of neuropsychological and imaging evidence. Neuroscience Research 50, 1–11.CrossRefGoogle ScholarPubMed
Rolls, ET (2000). The orbitofrontal cortex and reward. Cerebral Cortex 10, 284–294.CrossRefGoogle ScholarPubMed
Sachdev, P, Chen, X, Wen, W (2008). White matter hyperintensities in mid-adult life. Current Opinion in Psychiatry 21, 268–274.CrossRefGoogle ScholarPubMed
Sachdev, PS, Parslow, R, Wen, W, Anstey, KJ, Easteal, S (2007). Sex differences in the causes and consequences of white matter hyperintensities. Neurobiology of Aging 30, 946–956.CrossRefGoogle ScholarPubMed
Salloway, S, Malloy, P, Duffy, JD (2001). The Frontal Lobes and Neuropsychiatric Illness, 1st edn. American Psychiatric Publishing: Washington, DC.Google Scholar
Sheline, YI, Price, JL, Vaishnavi, SN, Mintun, MA, Barch, DM, Epstein, AA, Wilkins, CH, Snyder, AZ, Couture, L, Schechtman, K, McKinstry, RC (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, 524–532.CrossRefGoogle ScholarPubMed
Steffens, DC, Conway, CR, Dombeck, CB, Wagner, HR, Tupler, LA, Weiner, RD (2001). Severity of subcortical gray matter hyperintensity predicts ECT response in geriatric depression. Journal of ECT 17, 45–49.CrossRefGoogle ScholarPubMed
Steffens, DC, Potter, GG, McQuoid, DR, MacFall, JR, Payne, ME, Burke, JR, Plassman, BL, Welsh-Bohmer, KA (2007). Longitudinal magnetic resonance imaging vascular changes, apolipoprotein E genotype, and development of dementia in the neurocognitive outcomes of depression in the elderly study. American Journal of Geriatric Psychiatry 15, 839–849.CrossRefGoogle ScholarPubMed
Swan, GE, Lessov-Schlaggar, CN (2007). The effects of tobacco smoke and nicotine on cognition and the brain. Neuropsychology Review 17, 259–273.CrossRefGoogle ScholarPubMed
Taylor, WD, MacFall, JR, Steffens, DC, Payne, ME, Provenzale, JM, Krishnan, KR (2003 a). Localization of age-associated white matter hyperintensities in late-life depression. Progress in Neuro-Psychopharmacology and Biological Psychiatry 27, 539–544.CrossRefGoogle ScholarPubMed
Taylor, WD, Steffens, DC, MacFall, JR, McQuoid, DR, Payne, ME, Provenzale, JM, Krishnan, KR (2003 b). White matter hyperintensity progression and late-life depression outcomes. Archives of General Psychiatry 60, 1090–1096.CrossRefGoogle ScholarPubMed
Thomas, AJ, O'Brien, JT, Barber, R, McMeekin, W, Perry, R (2003). A neuropathological study of periventricular white matter hyperintensities in major depression. Journal of Affective Disorders 76, 49–54.CrossRefGoogle ScholarPubMed
Thomas, AJ, O'Brien, JT, Davis, S, Ballard, C, Barber, R, Kalaria, RN, Perry, RH (2002). Ischemic basis for deep white matter hyperintensities in major depression: a neuropathological study. Archives of General Psychiatry 59, 785–792.CrossRefGoogle ScholarPubMed
Videbech, P (1997). MRI findings in patients with affective disorder: a meta-analysis. Acta Psychiatrica Scandinavica 96, 157–168.CrossRefGoogle ScholarPubMed
Videbech, P, Ravnkilde, B, Gammelgaard, L, Egander, A, Clemmensen, K, Rasmussen, NA, Gjedde, A, Rosenberg, R (2004). The Danish PET/depression project: performance on Stroop's test linked to white matter lesions in the brain. Psychiatry Research 130, 117–130.CrossRefGoogle ScholarPubMed
Videbech, P, Ravnkilde, B, Pedersen, TH, Hartvig, H, Egander, A, Clemmensen, K, Rasmussen, NA, Andersen, F, Gjedde, A, Rosenberg, R (2002). The Danish PET/depression project: clinical symptoms and cerebral blood flow. A regions-of-interest analysis. Acta Psychiatrica Scandinavica 106, 35–44.CrossRefGoogle ScholarPubMed
WHO (1993). The ICD-10 Classification of Mental and Behavioural Disorders. Diagnostic Criteria for Research. World Health Organization: Geneva.Google Scholar
Widlöcher, DJ (1983). Psychomotor retardation: clinical, theoretical, and psychometric aspects. Psychiatric Clinics of North America 6, 27–40.CrossRefGoogle ScholarPubMed
Wing, JK, Sartorius, N, Üstün, TB (1998). Diagnosis and Clinical Measurement in Psychiatry. A Reference Manual for SCAN. Cambridge University Press: Cambridge.CrossRefGoogle Scholar
Wolf, PA, D'Agostino, RB, Belanger, AJ, Kannel, WB (1991). Probability of stroke: a risk profile from the Framingham Study. Stroke 22, 312–318.CrossRefGoogle ScholarPubMed
Worsley, KJ, Liao, CH, Aston, J, Petre, V, Duncan, GH, Morales, F, Evans, AC (2002). A general statistical analysis for fMRI data. NeuroImage 15, 1–15.CrossRefGoogle Scholar
Worsley, KJ, Marrett, S, Neelin, P, Vandal, AC, Friston, KJ, Evans, AC (1996). A unified statistical approach for determining significant signals in images of cerebral activation. Human Brain Mapping 4, 58–73.3.0.CO;2-O>CrossRefGoogle ScholarPubMed