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Atrophy and High Intensity Lesions Complementary Neurobiological Mechanisms in Late-Life Major Depression
Abstract
The primary objective of our study was to examine the role of atrophy, high intensity lesions and medical comorbidity in the pathophysiology of major depressive disorder in the elderly (late-life MDD). Our sample was comprised of 51 patients with late-life MDD and 30 non-depressed controls. All subjects were scanned on 1.5 tesla magnetic resonance imaging scanner (MRI) and absolute and normalized measures of brain and lesion volumes were obtained and used for comparison between groups. Patients with MDD had significantly smaller frontal lobe volumes, together with larger whole brain lesion volumes when compared with controls (p < .05). Whole brain lesion volumes correlated significantly (r = 0.41, p = .006) with overall medical comorbidity. The odds ratio (OR) for existing MDD increases significantly with a decrease in frontal lobe volume and an increase in whole brain lesion volumes (p < .05). Our findings suggest that atrophy and high intensity lesions represent relatively independent pathways to late-life MDD. While medical disorders lead to neuropathological changes that are captured on MR imaging as high intensity signals, atrophy may represent a relatively autonomous phenomenon. These findings have broad implications for the pathophysiology of mood disorders and suggest that complementary neurobiological processes may lead to cumulative neuronal injury thereby predisposing to clinical depression.
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“MDD subjects have smaller normalized frontal lobe volumes when compared with the nondepressed controls after controlling for age, gender and “total cumulative illness rating scale score” [61].”
From Preclinical and Clinical Evidence of Antioxidant Effects of Antidepressant Agents: Implications for the Pathophysiology of Major Depressive Disorder (2012) · cites this paper as [61]
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Harper, D. G., Joe, E., Jensen, J. E., Ravichandran, C. T., & Forester, B. P. (2016) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4439 · Cited by 48
Smith, G. S., Gunning‐Dixon, F. M., Lotrich, F. E., Taylor, W. D., & Evans, J. D. (2007) · Neuropsychopharmacology · doi:10.1038/sj.npp.1301333 · Cited by 45
Olesen, P. J., Gustafson, D. R., Simoni, M., Pantoni, L., Östling, S., Guo, X., & Skoog, I. (2010) · Neuropsychopharmacology · doi:10.1038/npp.2010.176 · Cited by 42
Multimodal Brain Connectivity Analysis in Unmedicated Late-Life Depression
Tadayonnejad, R., Yang, S., Kumar, A., & Ajilore, O. (2014) · PLoS ONE · doi:10.1371/journal.pone.0096033 · Cited by 42
Self-citationData From the VITA Study Do Not Support the Concept of Vascular Depression
Rainer, M. K., Mucke, H. A., Zehetmayer, S., Krampla, W. W., Kuselbauer, T., Weissgram, S., Jungwirth, S., Tragl, K., & Fischer, P. A. (2006) · American Journal of Geriatric Psychiatry · doi:10.1097/01.jgp.0000218326.91287.66 · Cited by 41
Gudmundsson, P., Olesen, P. J., Simoni, M., Pantoni, L., Östling, S., Kern, S., Guo, X., & Skoog, I. G. (2015) · European Journal of Neurology · doi:10.1111/ene.12651 · Cited by 38
Aging and brain activation with working memory tasks: an fMRI study of connectivity
Cook, I. A., Bookheimer, S. Y., Mickes, L., Leuchter, A. F., & Kumar, A. (2007) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.1678 · Cited by 39
Self-citationAge of onset of depression and quantitative neuroanatomic measures: absence of specific correlates
Kumar, A., Bilker, W. B., Jin, Z., Udupa, J. K., & Gottlieb, G. L. (1999) · Psychiatry Research Neuroimaging · doi:10.1016/s0925-4927(99)00021-9 · Cited by 37
Self-citationCurrent Understanding of the Neurobiology and Longitudinal Course of Geriatric Depression
Weisenbach, S. L., & Kumar, A. (2014) · Current Psychiatry Reports · doi:10.1007/s11920-014-0463-y · Cited by 37
Self-citationStructural Neuroimaging of Geriatric Depression
Benjamin, S., & Steffens, D. C. (2011) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2011.02.001 · Cited by 36
Structural MRI Changes of the Brain in Depression
Kanner, A. M. (2004) · Clinical EEG and Neuroscience · doi:10.1177/155005940403500111 · Cited by 36
Grool, A. M., van der Graaf, Y., Mali, W. P. T. M., Geerlings, M. I., & on behalf of the SMART Study Group (2011) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.2010.232413 · Cited by 35
Tollkötter, M., Pfleiderer, B., Sörös, P., & Michael, N. (2005) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2005.09.003 · Cited by 35
Metadata
- Authors
- Kumar, A.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Kumar, A
- Venue
- Neuropsychopharmacology
- Published
- 2000-03
- Volume
- 22
- Issue
- 3
- Pages
- 264-274
- ISSN
- 0893-133X (ISSN-L)
- OpenAlex
- W2004128631
- Cited by
- 181
- References
- 71
- Citations by year
- 2025: 3 · 2023: 1 · 2022: 2 · 2021: 1 · 2020: 1 · 2019: 4 · 2018: 3 · 2017: 6 · 2016: 1 · 2015: 3 · 2014: 5 · 2013: 9 · 2012: 9
- FWCI
- 8.21
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neuropsychopharmacology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Mental Health (MH-52129, P30MH052129, MH-55115, R01MH055115)
- Topics
- Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- brain atrophy, comorbidities, frontal lobe volume, neurodegeneration, mood disorders, depression pathophysiology, older adults
- MeSH terms
- Aged, Atrophy, Brain, Depressive Disorder, Female, Humans, Magnetic Resonance Imaging, Male, Reference Values, Regression Analysis, Sex Characteristics, Age of Onset
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