Treatment Course With Antidepressant Therapy in Late-Life Depression
Open accessAbstract
OBJECTIVE: In order to assess the effect of gray matter volumes and cortical thickness on antidepressant treatment response in late-life depression, the authors examined the relationship between brain regions identified a priori and Montgomery-Åsberg Depression Rating Scale (MADRS) scores over the course of an antidepressant treatment trial. METHOD: In a nonrandomized prospective trial, 168 patients who were at least 60 years of age and met DSM-IV criteria for major depression underwent MRI and were enrolled in a 12-week treatment study. Exclusion criteria included cognitive impairment or severe medical disorders. The volumes or cortical thicknesses of regions of interest that differed between the depressed group and a comparison group (N=50) were determined. These regions of interest were used in analyses of the depressed group to predict antidepressant treatment outcome. Mixed-model analyses adjusting for age, education, age at depression onset, race, baseline MADRS score, scanner, and interaction with time examined predictors of MADRS scores over time. RESULTS: Smaller hippocampal volumes predicted a slower response to treatment. With the inclusion of white matter hyper-intensity severity and neuropsychological factor scores, the best model included hippocampal volume and cognitive processing speed to predict rate of response over time. A secondary analysis showed that hippocampal volume and frontal pole thickness differed between patients who achieved remission and those who did not. CONCLUSIONS: These data expand our understanding of the prediction of treatment course in late-life depression. The authors propose that the primary variables of hippocampal volume and cognitive processing speed, subsuming other contributing variables (episodic memory, executive function, language processing) predict antidepressant response.
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In depression of older adults, treatment with a combination of pharmacotherapy and psychotherapy, especially learning-based forms such as cognitive behavioral therapies (CBT), has been shown to be effective.
“In depression of older adults, treatment with a combination of pharmacotherapy and psychotherapy, especially learning‐based forms such as cognitive behavioral therapies (CBT), has been shown to be effective5, 6.”
From Mental health care for older adults: recent advances and new directions in clinical practice and research (2022) · cites this paper as [5]
Combined treatment (antidepressant medication plus depression-specific psychotherapy) may be more effective than either alone in some populations, but side effect risks and patient demands/burdens may be greater.
“Combined treatment (antidepressant medication plus depression‐specific psychotherapy) may be more effective than either alone in some populations, but side effect risks and patient demands/burdens may be greater5, 6, 195, 217.”
From Mental health care for older adults: recent advances and new directions in clinical practice and research (2022) · cites this paper as [5]
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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
A new depression scale designed to be sensitive to change
Montgomery, S. A., & Åsberg, M. (1979) · British Journal of Psychiatry · doi:10.1192/bjp.134.4.382 · Cited by 13,962 · see citing works
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324 · see citing works
Cortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910 · see citing works
Atrial fibrillation as an independent risk factor for stroke: the Framingham study
Wolf, P. A., Abbott, R. D., & Kannel, W. B. (1991) · Stroke · doi:10.1161/01.str.22.8.983 · Cited by 7,388 · see citing works
Automatically Parcellating the Human Cerebral Cortex
Fischl, B. R. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg087 · Cited by 4,208 · see citing works
Alexopoulos, G. S. (2005) · The Lancet · doi:10.1016/s0140-6736(05)66665-2 · Cited by 2,024 · see citing works
'Vascular Depression' Hypothesis
Alexopoulos, G. S. (1997) · Archives of General Psychiatry · doi:10.1001/archpsyc.1997.01830220033006 · Cited by 1,843 · see citing works
Morris, J. C. (1997) · International Psychogeriatrics · doi:10.1017/s1041610297004870 · Cited by 1,641 · see citing works
Jovicich, J., Czanner, S., Greve, D. N., Haley, E., van der Kouwe, A. J. W., Gollub, R. L., Kennedy, D. N., Schmitt, F., Brown, G. G., MacFall, J. R., et al. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.09.046 · Cited by 1,269 · see citing works
Self-citationAging and measures of processing speed
Salthouse, T. A. (2000) · Biological Psychology · doi:10.1016/s0301-0511(00)00052-1 · Cited by 1,114 · see citing works
MRI-defined vascular depression
(1997) · American Journal of Psychiatry · doi:10.1176/ajp.154.4.497 · Cited by 770 · see citing works
The Nature and Determinants of Neuropsychological Functioning in Late-LifeDepression
Butters, M. A., Whyte, E. M., Nebes, R. D., Begley, A. E., Dew, M. A., Mulsant, B. H., Zmuda, M. D., Bhalla, R., Meltzer, C. C., Pollock, B. G., et al. (2004) · Archives of General Psychiatry · doi:10.1001/archpsyc.61.6.587 · Cited by 622 · see citing works
Jovicich, J., Czanner, S., Han, X., Salat, D. H., van der Kouwe, A. J. W., Quinn, B. T., Pacheco, J., Albert, M., Killiany, R., & Blacker, D. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.02.010 · Cited by 549 · see citing works
Sheline, Y. I., Barch, D. M., Garcia, K., Gersing, K., Pieper, C., Welsh-Bohmer, K., Steffens, D. C., & Doraiswamy, P. M. (2006) · Biological Psychiatry · doi:10.1016/j.biopsych.2005.09.019 · Cited by 421 · see citing works
Self-citationO'Brien, J. T. (2004) · American Journal of Psychiatry · doi:10.1176/appi.ajp.161.11.2081 · Cited by 409 · see citing works
Ballmaier, M., Toga, A. W., Blanton, R. E., Sowell, E. R., Lavretsky, H., Peterson, J. R., Pham, D. L., & Kumar, A. (2004) · American Journal of Psychiatry · doi:10.1176/appi.ajp.161.1.99 · Cited by 384 · see citing works
Hippocampal volume in geriatric depression
Steffens, D. C., Byrum, C. E., McQuoid, D. R., Greenberg, D. L., Payne, M. E., Blitchington, T. F., MacFall, J. R., & Krishnan, K. R. R. (2000) · Biological Psychiatry · doi:10.1016/s0006-3223(00)00829-5 · Cited by 375 · see citing works
Self-citationExecutive dysfunction and the course of geriatric depression
Alexopoulos, G. S., Kiosses, D. N., Heo, M., Murphy, C. F., Shanmugham, B., & Gunning-Dixon, F. (2005) · Biological Psychiatry · doi:10.1016/j.biopsych.2005.04.024 · Cited by 317 · see citing works
Sheline, Y. I., Pieper, C. F., Barch, D. M., Welsh-Boehmer, K., McKinstry, R. C., MacFall, J. R., D’Angelo, G., Garcia, K. S., Gersing, K., Wilkins, C., et al. (2010) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2009.204 · Cited by 291 · see citing works
Self-citationNeurogenesis and affective disorders
Samuels, B. A., & Hen, R. (2011) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2011.07614.x · Cited by 286 · see citing works
Depression and vascular disease: what is the relationship?
Thomas, A. J. (2003) · Journal of Affective Disorders · doi:10.1016/s0165-0327(02)00349-x · Cited by 267 · see citing works
Sheline, Y. I., Price, J. L., Vaishnavi, S. N., Mintun, M. A., Barch, D. M., Epstein, A. A., Wilkins, C. H., Snyder, A. Z., Couture, L., Schechtman, K., et al. (2008) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2007.07010175 · Cited by 213 · see citing works
Self-citationDepression and the hippocampus: cause or effect?
Sheline, Y. I. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.06.006 · Cited by 159 · see citing works
Self-citationGray Matter Changes in Late Life Depression—a Structural MRI Analysis
Andreescu, C., Butters, M. A., Begley, A. E., Rajji, T. K., Wu, M., MELTZER, C. C., Reynolds, C. F., & Aizenstein, H. J. (2007) · Neuropsychopharmacology · doi:10.1038/sj.npp.1301655 · Cited by 145 · see citing works
Lavretsky, H., Ballmaier, M., Pham, D., Toga, A., & Kumar, A. (2007) · The American Journal of Geriatric Psychiatry · doi:10.1097/jgp.0b013e3180325a16 · Cited by 143 · see citing works
Dotson, V. M., Davatzikos, C. A., Kraut, M. A., & Resnick, S. M. (2009) · Journal of Psychiatry and Neuroscience · doi:10.1139/jpn.0948 · Cited by 136 · see citing works
Hippocampal volume and antidepressant response in geriatric depression
Hsieh, M., McQuoid, D. R., Levy, R. M., Payne, M. E., MacFall, J. R., & Steffens, D. C. (2002) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.611 · Cited by 136 · see citing works
Self-citationTeodorczuk, A., Firbank, M. J., Pantoni, L., et al. (2009) · Psychological Medicine · doi:10.1017/s0033291709990857 · Cited by 135 · see citing works
Shimony, J. S., Sheline, Y. I., D’Angelo, G., Epstein, A. A., Benzinger, T. L. S., Mintun, M. A., McKinstry, R. C., & Snyder, A. Z. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2009.02.032 · Cited by 130 · see citing works
Self-citationA comparison of neurocognitive impairment in younger and older adults with major depression
Thomas, A. J., Gallagher, P., Robinson, L. J., Porter, R., Young, A. H., Ferrier, I. N., & O'Brien, J. T. (2008) · Psychological Medicine · doi:10.1017/s0033291708004042 · Cited by 123 · see citing works
Anterior cingulate cortical volumes and treatment remission of geriatric depression
Gunning, F. M., Cheng, J., Murphy, C. F., Kanellopoulos, D., Acuna, J., Hoptman, M. J., Klimstra, S., Morimoto, S., Weinberg, J., & Alexopoulos, G. S. (2009) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.2290 · Cited by 106 · see citing works
How Late-Life Depression Affects Cognition: Neural Mechanisms
Crocco, E. A., Castro, K., & Loewenstein, D. A. (2010) · Current Psychiatry Reports · doi:10.1007/s11920-009-0081-2 · Cited by 82 · see citing works
Subcortical lesion severity and orbitofrontal cortex volume in geriatric depression
Lee, S., Payne, M. E., Steffens, D. C., McQuoid, D. R., Lai, T., Provenzale, J. M., & Krishnan, K. (2003) · Biological Psychiatry · doi:10.1016/s0006-3223(03)00063-5 · Cited by 74 · see citing works
Self-citationAmygdala Volume in Late-Life Depression: Relationship with Age of Onset
Burke, J., McQuoid, D. R., Payne, M. E., Steffens, D. C., Krishnan, R. R., & Taylor, W. D. (2011) · American Journal of Geriatric Psychiatry · doi:10.1097/jgp.0b013e318211069a · Cited by 71 · see citing works
Self-citationPrefrontal brain morphology and executive function in healthy and depressed elderly
Elderkin‐Thompson, V., Hellemann, G., Pham, D. L., & Kumar, A. (2008) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.2137 · Cited by 64 · see citing works
Three-Dimensional Surface Mapping of the Caudate Nucleus in Late-Life Depression
Butters, M. A., Aizenstein, H. J., Hayashi, K. M., MELTZER, C. C., Seaman, J., Reynolds, C. F., Toga, A. W., Thompson, P. M., & Becker, J. T. (2008) · American Journal of Geriatric Psychiatry · doi:10.1097/jgp.0b013e31816ff72b · Cited by 61 · see citing works
Janssen, J., Pol, H. E. H., Schnack, H. G., Kok, R., Lampe, I. K., de Leeuw, F., Kahn, R. S., & Heeren, T. J. (2007) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.1790 · Cited by 55 · see citing works
Goveas, J. S., Espeland, M. A., Hogan, P. E., Dotson, V. M., Tarima, S. S., Coker, L. H., Ockene, J. K., Brunner, R. L., Woods, N. F., Wassertheil-Smoller, S. W., et al. (2011) · Journal of Affective Disorders · doi:10.1016/j.jad.2011.01.020 · Cited by 51 · see citing works
Taylor, W. D., Zhao, Z., Ashley‐Koch, A., Payne, M. E., Steffens, D. C., Krishnan, R. R., Hauser, E., & MacFall, J. R. (2013) · Human Brain Mapping · doi:10.1002/hbm.21445 · Cited by 50 · see citing works
Self-citationAmygdalae morphometry in late-life depression
Tamburo, R., Siegle, G., Stetten, G., Cois, C. A., Butters, M., Reynolds, C., & Aizenstein, H. (2009) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.2167 · Cited by 40 · see citing works
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Reynolds, C. F., Jeste, D. V., Sachdev, P. S., & Blazer, D. G. (2022) · World Psychiatry · doi:10.1002/wps.20996 · Cited by 465 · see citing works
Geerlings, M. I., & Gerritsen, L. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.12.032 · Cited by 138 · see citing works
Oluboka, O. J., Katzman, M. A., Habert, J., McIntosh, D., MacQueen, G. M., Milev, R. V., McIntyre, R. S., & Blier, P. (2018) · International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyx081 · Cited by 104 · see citing works
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Abdallah, C. G., Jackowski, A., Sato, J. R., Mao, X., Kang, G., Cheema, R., Coplan, J. D., Mathew, S. J., & Shungu, D. C. (2015) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2015.04.025 · Cited by 67 · see citing works
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- Authors
- Sheline, Y. I., Disabato, B. M., Hranilovich, J., Morris, C., D’Angelo, G., Pieper, C., Toffanin, T., Taylor, W. D., MacFall, J. R., Wilkins, C., Barch, D. M., Welsh-Bohmer, K. A., Steffens, D. C., Krishnan, R. R., & Doraiswamy, P. M.
- Affiliations
- Duke University (US)
- ORCID
- Venue
- American Journal of Psychiatry
- Published
- 2012-11
- Volume
- 169
- Issue
- 11
- Pages
- 1185-1193
- ISSN
- 0002-953X (ISSN-L)
- 1535-7228
- PMC
- PMC3752387
- OpenAlex
- W2121579891
- Cited by
- 86
- References
- 41
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 2 · 2023: 4 · 2022: 7 · 2021: 2 · 2020: 4 · 2019: 4 · 2018: 12 · 2017: 5 · 2016: 9 · 2015: 15 · 2014: 7 · 2013: 8 · 2012: 3
- FWCI
- 7.76
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- American Journal of Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Institutional Research Information System University of Ferrara (University of Ferrara) (submittedVersion)
- Funders
- National Institute of Mental Health (K24 MH79510-09, R01 MH62158, R01-MH60697, R01MH074916, R01MH060697, K24MH079510, R01MH062158)
- National Center for Research Resources (RR.00036, M01RR000036)
- Topics
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- geriatric depression, antidepressant response, hippocampal volume, cortical thickness, white matter hyperintensities, processing speed, treatment response prediction, remission, gray matter volume
- MeSH terms
- Aged, Amygdala, Antidepressive Agents, Brain, Caudate Nucleus, Cerebral Cortex, Cognition Disorders, Major Depressive Disorder, Depressive Disorder, Major, Female, Frontal Lobe, Hippocampus, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Neural Pathways, Neuropsychological Tests, Organ Size, Personality Inventory, Prospective Studies, Psychometrics, Reaction Time, Treatment Outcome, Sertraline, Parahippocampal Gyrus
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