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Methodology and preliminary results from the neurobiology of late-life depression study

Published online by Cambridge University Press:  01 September 2015

David C. Steffens ,
Kevin J. Manning ,
Rong Wu ,
James J. Grady ,
Richard H. Fortinsky  and
Howard A. Tennen
David C. Steffens*
Affiliation:
Departments of Psychiatry (DCS, KJM) and Community Medicine and Healthcare (RW, JJG, HAT) the Center on Aging (RHF), University of Connecticut Health Center, 263 Farmington Ave, Farmington, Connecticut, USA
Kevin J. Manning
Affiliation:
Departments of Psychiatry (DCS, KJM) and Community Medicine and Healthcare (RW, JJG, HAT) the Center on Aging (RHF), University of Connecticut Health Center, 263 Farmington Ave, Farmington, Connecticut, USA
Rong Wu
Affiliation:
Departments of Psychiatry (DCS, KJM) and Community Medicine and Healthcare (RW, JJG, HAT) the Center on Aging (RHF), University of Connecticut Health Center, 263 Farmington Ave, Farmington, Connecticut, USA
James J. Grady
Affiliation:
Departments of Psychiatry (DCS, KJM) and Community Medicine and Healthcare (RW, JJG, HAT) the Center on Aging (RHF), University of Connecticut Health Center, 263 Farmington Ave, Farmington, Connecticut, USA
Richard H. Fortinsky
Affiliation:
Departments of Psychiatry (DCS, KJM) and Community Medicine and Healthcare (RW, JJG, HAT) the Center on Aging (RHF), University of Connecticut Health Center, 263 Farmington Ave, Farmington, Connecticut, USA
Howard A. Tennen
Affiliation:
Departments of Psychiatry (DCS, KJM) and Community Medicine and Healthcare (RW, JJG, HAT) the Center on Aging (RHF), University of Connecticut Health Center, 263 Farmington Ave, Farmington, Connecticut, USA
*
Correspondence should be addressed to: David C. Steffens, M.D., M.H.S., Professor and Chair, Department of Psychiatry, UConn Health Center, 263 Farmington Ave, Farmington, CT 06030-1410, USA. Phone: +1 860-679-4282; Fax: +1 860-679-1296. Email: [email protected].
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Abstract

Background:

We sought to investigate the relationship between neuroticism and depression in an elderly cohort. In this paper, we describe the methods of an National Institute of Mental Health—NIMH-supported study and present findings among the cohort enrolled to date.

Methods:

We used the NEO Personality Inventory to assess neuroticism, and we employed several cognitive neuroscience-based measures to examine emotional control.

Results:

Compared with a group of 27 non-depressed older control subjects, 33 older depressed subjects scored higher on measures of state and trait anxiety and neuroticism. On our experimental neuroscience-based measures, depressed subjects endorsed more negative words compared with controls on an emotional characterization test. In addition, we found a significant group-by-congruency effect on an emotional interference test where subjects were asked to identify the face's emotional expression while ignoring the words “fear” or “happy” labeled across the face.

Conclusion:

Thus, in this preliminary work, we found significant differences in measures of neuroticism and emotional controls among older adults with and without depression.

Keywords

depressionelderlyneuroticismneuroscience
Type
Research Article
Information
International Psychogeriatrics , Volume 27 , Issue 12 , December 2015 , pp. 1987 - 1997
Copyright
Copyright © International Psychogeriatric Association 2015 

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References

Anda, R. F., Butchart, A., Felitti, V. J. and Brown, D. W. (2010). Building a framework for global surveillance of the public health implications of adverse childhood experiences. American Journal of Preventive Medicine, 39, 93–98.Google Scholar
Benton, A. (1974). Revised Visual Retention Test, 4th edn. New York: The Psychological Corporation.Google Scholar
Benton, A. L., Hamsher, K., Varney, N. and Spreen, O. (1983). Contributions to Neuropsychological Assessment, New York: Oxford University Press.Google Scholar
Bock, C., Bukh, J. D., Vinberg, M., Gether, U. and Kessing, L. V. (2010). The influence of comorbid personality disorder and neuroticism on treatment outcome in first episode depression. Psychopathology, 43, 197–204.Google Scholar
Cano-García, F. J., Padilla-Muñoz, E. M. and Carrasco-Ortiz, M. A. (2005). Personality and contextual variables in teacher burnout. Personality and Individual Differences, 38, 929–940.Google Scholar
Canuto, A., Giannakopoulos, P., Meiler-Mititelu, C., Delaloye, C., Herrmann, F. R. and Weber, K. (2009). Personality traits influence clinical outcome in day hospital-treated elderly depressed patients. American Journal of Geriatric Psychiatry, 17, 335–343.Google Scholar
Carroll, B. J. (1998). Carroll Depression Scales-Revised (CDS-R): Technical Manual, Toronto: Multi-Health Systems.Google Scholar
Carroll, B. J., Feinberg, M., Smouse, P. E., Rawson, S. G. and Greden, J. F. (1981). The carroll rating scale for depression. I. Development, reliability and validation. British Journal of Psychiatry, 138, 194–200.Google Scholar
Chan, S. W., Harmer, C. J., Goodwin, G. M. and Norbury, R. (2008). Risk for depression is associated with neural biases in emotional categorisation. Neuropsychologia, 46, 2896–2903.Google Scholar
Costa, P. T. and McCrae, R. R. (1985). The NEO Personality Inventory Manual, Odessa, FL: Psychological Assessment Resources.Google Scholar
Costa, P. T. and McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) Professional Manual, Odessa, FL: Psychological Assessment Resources.Google Scholar
Costa, P. T. Jr. and McCrae, R. R. (2006). Age changes in personality and their origins: comment on Roberts, Walton, and Viechtbauer (2006). Psychological Bulletin, 132, 26–28.Google Scholar
Cremers, H. R. et al. (2010). Neuroticism modulates amygdala-prefrontal connectivity in response to negative emotional facial expressions. Neuroimage, 49, 963–970.Google Scholar
Denollet, J. (2005). DS14: standard assessment of negative affectivity, social inhibition, and Type D personality. Psychosomatic Medicine, 67, 89–97.Google Scholar
DeYoung, C. G., Hirsh, J. B., Shane, M. S., Papademetris, X., Rajeevan, N. and Gray, J. R. (2010). Testing predictions from personality neuroscience. Brain structure and the big five. Psychological Science, 21, 820–828.Google Scholar
Diniz, B. S., Butters, M. A., Albert, S. M., Dew, M. A. and Reynolds, C. F. 3rd (2013). Late-life depression and risk of vascular dementia and Alzheimer's disease: systematic review and meta-analysis of community-based cohort studies. British Journal of Psychiatry, 202, 329–335.Google Scholar
Egner, T., Elkin, A., Gale, S. and Hirsch, J. (2008). Dissociable neural systems resolve conflict from emotional versus nonemotional distracters. Cerebral Cortex, 18, 1475–1484.Google Scholar
Etkin, A., Egner, T., Peraza, D. M., Kandel, E. R. and Hirsch, J. (2006). Resolving emotional conflict: a role for the rostral anterior cingulate cortex in modulating activity in the amygdala. Neuron, 51, 871–882.CrossRefGoogle ScholarPubMed
Eysenck, H. J. and Eysenck, S. B. G. (1975). Manual of the Eysenck Personality Questionnaire, London: Hodder and Stoughton.Google Scholar
Folstein, M. F., Folstein, S. E. and McHugh, P. R. (1975). Mini-Mental state. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198.Google Scholar
Fortinsky, R. H., Tennen, H. and Steffens, D. C. (2013). Resilience in the face of chronic illness and family caregiving in middle and later life. Psychiatric Annals, 43, 549–554.Google Scholar
Fruhholz, S., Prinz, M. and Herrmann, M. (2010). Affect-related personality traits and contextual interference processing during perception of facial affect. Neuroscience Letters, 469, 260–264.Google Scholar
Hamilton, M. (1960). A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry, 23, 55–61.CrossRefGoogle ScholarPubMed
Hayward, R. D., Taylor, W. D., Smoski, M. J., Steffens, D. C. and Payne, M. E. (2013). Association of five-factor model personality domains and facets with presence, onset, and treatment outcomes of major depression in older adults. American Journal of Geriatric Psychiatry, 21, 88–96.Google Scholar
Hoppe, C. D., Muller, U. D., Werheid, K. D., Thone, A. D. and von Cramon, Y. D. (2000). Digit ordering test: clinical, psychometric, and experimental evaluation of a verbal working memory test. The Clinical Neuropsychologist, 14, 38–55.Google Scholar
Jelicic, M., Bosma, H., Ponds, R. W., van Boxtel, M. P., Houx, P. J. and Jolles, J. (2003). Neuroticism does not affect cognitive functioning in later life. Experimental Aging Research, 29, 73–78.Google Scholar
Kaplan, E. F., Goodlass, H. and Weintraub, S. (1983). The Boston Naming Test, 2nd edn. Philadephia: Lea and Febiger.Google Scholar
Keller, M. B. et al. (1987). The longitudinal interval follow-up evaluation. A comprehensive method for assessing outcome in prospective longitudinal studies. Archives of General Psychiatry, 44, 540–548.Google Scholar
Kendler, K. S., Gatz, M., Gardner, C. O. and Pedersen, N. L. (2006). Personality and major depression: a Swedish longitudinal, population-based twin study. Archives of General Psychiatry, 63, 1113–1120.Google Scholar
Lahey, B. B. (2009). Public health significance of neuroticism. American Psychologist, 64, 241–256.Google Scholar
Landerman, R., George, L. K., Campbell, R. T. and Blazer, D. G. (1989). Alternative models of the stress buffering hypothesis. American Journal of Community Psychology, 17, 626–642.Google Scholar
Linn, B. S., Linn, M. W. and Gurel, L. (1988). Cumulative illness rating scale. Journal of the American Geriatrics Society, 16, 622–626.Google Scholar
Lockwood, K. A., Alexopoulos, G. S. and van Gorp, W. G. (2002). Executive dysfunction in geriatric depression. American Journal of Psychiatry, 159, 1119–1126.Google Scholar
Mah, L., Binns, M. A. and Steffens, D. C. (2015). Anxiety symptoms in amnestic mild cognitive impairment are associated with medial temporal atrophy and predict conversion to Alzheimer disease. American Journal of Geriatric Psychiatry, 23, 466–476.CrossRefGoogle ScholarPubMed
Manning, K. J., Gunning, F. M., McGovern, A. R., Kotbi, N. and Alexopoulos, G. S. (2014). Ventromedial syndrome with normal cognitive functioning in vascular depression. American Journal of Psychiatry, 171, 1337–1338.Google Scholar
McCrae, R. R. and Costa, P. T. (1983). Joint factors in self-reports and ratings: neuroticism, extraversion and openness to experience. Personality and Individual Differences, 4, 245–255.Google Scholar
Miller, M. D. et al. (1992). Rating chronic medical illness burden in geropsychiatric practice and research: application of the cumulative illness rating scale. Psychiatry Research, 41, 237–248.Google Scholar
Montgomery, S. A. and Asberg, M. (1979). A new depression scale designed to be sensitive to change. British Journal of Psychiatry, 134, 382–389.CrossRefGoogle ScholarPubMed
Morimoto, S. S., Kanellopoulos, D., Manning, K. J. and Alexopoulos, G. S. (2015). Diagnosis and treatment of depression and cognitive impairment in late life. Annals of the New York Academy of Sciences, 1345, 36–46.Google Scholar
Morris, J. C. et al. (1989). The consortium to establish a registry for Alzheimer's disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer's disease. Neurology, 39, 1159–1165.Google Scholar
Omura, K., Todd Constable, R. and Canli, T. (2005). Amygdala gray matter concentration is associated with extraversion and neuroticism. Neuroreport, 16, 1905–1908.Google Scholar
Petersen, T. et al. (2002). NEO-FFI factor scores as predictors of clinical response to fluoxetine in depressed outpatients. Psychiatry Research, 109, 9–16.Google Scholar
Potter, G. G., Wagner, H. R., Burke, J. R., Plassman, B. L., Welsh-Bohmer, K. A. and Steffens, D. C. (2013). Neuropsychological predictors of dementia in late-life major depressive disorder. American Journal of Geriatric Psychiatry, 21, 297–306.Google Scholar
Reitan, R. M. (1992). Trail Making Test: Manual for Administration and Scoring, Tucson: Reitan Neuropsychological Laboratory.Google Scholar
Robins, N., Helzer, J. E., Croughan, J. and Ratcliff, K. S. (1981). National institute of mental health diagnostic interview schedule. Archives of General Psychiatry, 38, 381–389.Google Scholar
Roelofs, J., Huibers, M., Peeters, F., Arntz, A. and van Os, J. (2008). Rumination and worrying as possible mediators in the relation between neuroticism and symptoms of depression and anxiety in clinically depressed individuals. Behaviour Research and Therapy, 46, 1283–1289.Google Scholar
Sackheim, H. A., Prudic, J., Devanand, D. P., Decina, P., Kerr, B. and Malitz, S. (1990). The impact of medication resistance and continuation pharmacotherapy on relapse following response to electroconvulsive therapy in major depression. Journal of Clinical Psychopharmacology, 10, 96–104.Google Scholar
Scheier, M. F., Carver, C. S. and Bridges, M. W. (1994). Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): a reevaluation of the life orientation test. Journal of Personality and Social Psychology, 67, 1063–1078.Google Scholar
Sheline, Y. I. et al. (2006). Cognitive function in late life depression: relationships to depression severity, cerebrovascular risk factors and processing speed. Biological Psychiatry, 60, 58–65.Google Scholar
Smith, A. (1982). Symbol Digit Modalities Test-Manual, Los Angeles: Western Psychological Services.Google Scholar
Smith, B. W., Dalen, J., Wiggins, K., Tooley, E., Christopher, P. and Bernard, J. (2008). The brief resilience scale: assessing the ability to bounce back. International Journal of Behavioral Medicine, 15, 194–200.Google Scholar
Spielberger, C. D., Gorssuch, R. L., Lushene, P. R., Vagg, P. R. and Jacobs, G. A. (1983). Manual for the State-Trait Anxiety Inventory, Palo Alto, CA: Consulting Psychologists Press, Inc.Google Scholar
Steffens, D. C., McQuoid, D. R. and Krishnan, K. R. (2002). The duke somatic treatment algorithm for geriatric depression (STAGED) approach. Psychopharmacology Bulletin, 36, 58–68.Google Scholar
Steffens, D. C., McQuoid, D. R., Smoski, M. J. and Potter, G. G. (2013). Clinical outcomes of older depressed patients with and without comorbid neuroticism. International Psychogeriatrics, 25, 1985–1990.CrossRefGoogle ScholarPubMed
Tschanz, J. T., Norton, M. C., Zandi, P. P. and Lyketsos, C. G. (2013). The cache county study on memory in aging: factors affecting risk of Alzheimer's disease and its progression after onset. International Review of Psychiatry, 25, 673–685.Google Scholar
Weber, K. et al. (2013). Stressful life events and neuroticism as predictors of late-life versus early-life depression. Psychogeriatrics, 13, 221–228.CrossRefGoogle ScholarPubMed
Wechsler, D. (1987). Wechsler Memory Scale-Revised Manual, San Antonio: Psychological Corporation.Google Scholar
Weissman, M. M., Sholomskas, D., Pottenger, M., Prusoff, B. A. and Locke, B. Z. (1977). Assessing depressive symptoms in five psychiatric populations: a validation study. American Journal of Epidemiology, 106, 203–214.Google Scholar
Welsh, K. A. et al. (1994). The consortium to establish a registry of Alzheimer's disease (CERAD) part V: a normative study of the neuropsychological battery. Neurology, 44, 609–614.Google Scholar
Wetherell, J. L., Reynolds, C. A., Gatz, M. and Pedersen, N. L. (2002). Anxiety, cognitive performance, and cognitive decline in normal aging. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 57, 246–255.Google Scholar
Wilson, R. S., Begeny, C. T., Boyle, P. A., Schneider, J. A. and Bennett, D. A. (2011). Vulnerability to stress, anxiety, and development of dementia in old age. American Journal of Geriatric Psychiatry, 19, 327–334.Google Scholar
Wilson, R. S., Bennett, D. A., Mendes de Leon, C. F., Bienias, J. L., Morris, M. C. and Evans, D. A. (2005). Distress proneness and cognitive decline in a population of older persons. Psychoneuroendocrinology, 30, 11–17.Google Scholar
Wright, C. I. et al. (2006). Neuroanatomical correlates of extraversion and neuroticism. Cerebral Cortex, 16, 1809–1819.Google Scholar
Zachary, R. A. (1991). Shipley Institute of Living Scale - Revised Manual, Los Angeles: Western Psychological Services.Google Scholar
Zannas, A. S. et al. (2013). Negative life stress and longitudinal hippocampal volume changes in older adults with and without depression. Journal of Psychiatric Research, 47, 829–834.CrossRefGoogle ScholarPubMed