Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-15T10:28:49.507Z Has data issue: false hasContentIssue false

Characteristics of neurocognitive functions in mild cognitive impairment with depression

Published online by Cambridge University Press:  10 March 2016

Hyun-Seok Dong
Affiliation:
Department of Psychiatry, Korea University Ansan Hospital, Ansan, South Korea
Changsu Han*
Affiliation:
Department of Psychiatry, Korea University Ansan Hospital, Ansan, South Korea
Sang Won Jeon
Affiliation:
Department of Psychiatry, Korea University Ansan Hospital, Ansan, South Korea
Seoyoung Yoon
Affiliation:
Department of Psychiatry, Korea University Ansan Hospital, Ansan, South Korea
Hyun-Ghang Jeong
Affiliation:
Department of Psychiatry, Korea University Guro Hospital, Seoul, South Korea
Yu Jeong Huh
Affiliation:
Department of Psychiatry, Korea University Ansan Hospital, Ansan, South Korea
Chi-Un Pae
Affiliation:
Department of Psychiatry, The Catholic University of Korea College of Medicine, Seoul, South Korea
Ashwin A. Patkar
Affiliation:
Department of Psychiatry and Behavioural Sciences, Duke University Medical Center, Durham, North Carolina, USA
David C. Steffens
Affiliation:
Department of Psychiatry, University of Connecticut Health Center, Farmington, CT, USA
*
Correspondence should be addressed to: Changsu Han, MD, PhD, MHS Department of Psychiatry, Korea University Ansan Hospital, 516, Gojan-dong, Danwon-gu, Ansan-shi, Gyeonggi-do 425–707, South Korea. Phone: +82-31-412-5140; Fax: +82-2-6442-5008. Email: hancs@korea.ac.kr.

Abstract

Background:

Previous studies suggest that there is a strong association between depression and cognitive decline, and that concurrent depressive symptoms in MCI patients could contribute to a difference in neurocognitive characteristics compared to MCI patients without depression. The authors tried to compare neurocognitive functions between MCI patients with and without depression by analyzing the results of neuropsychological tests.

Methods:

Participants included 153 MCI patients. Based on the diagnosis of major depressive disorder, the participants were divided into two groups: depressed MCI (MCI/D+) versus non-depressed MCI (MCI/D−). The general cognitive and functional statuses of participants were evaluated. And a subset of various neuropsychological tests was presented to participants. Demographic and clinical data were analyzed using Student t-test or χ2 test.

Results:

A total of 153 participants were divided into two groups: 94 MCI/D+ patients and 59 MCI/D− patients. Age, sex, and years of education were not significantly different between the two groups. There were no significant differences in general cognitive status between MCI/D+ and MCI/D− patients, but MCI/D+ participants showed significantly reduced performance in the six subtests (Contrasting Program, Go-no-go task, Fist-edge-palm task, Constructional Praxis, Memory Recall, TMT-A) compared with MCI/D− patients.

Conclusions:

There were significantly greater deficits in neurocognitive functions including verbal memory, executive function, attention/processing speed, and visual memory in MCI/D+ participants compared to MCI/D−. Once the biological mechanism is identified, distinct approaches in treatment or prevention will be determined.

Type
Research Article
Copyright
Copyright © International Psychogeriatric Association 2016 

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

Abas, M. A., Sahakian, B. J. and Levy, R. (1990). Neuropsychological deficits and CT scan changes in elderly depressives. Psychological Medicine, 20, 507–20.CrossRefGoogle ScholarPubMed
American Psychiatric Association (APA). (2000). Diagnostic and Statistical Manual of Mental Disorders. 4th edn text revision (DSM-IV-TR), Washington, DC: APA.Google Scholar
Ashford, J. W., Kolm, P., Colliver, J. A., Bekian, C. and Hsu, L. N. (1989). Alzheimer patient evaluation and the mini-mental state: item characteristic curve analysis. Journal of Gerontology, 44, P139–46.CrossRefGoogle ScholarPubMed
Boeve, B. et al. (2004). Mild cognitive impairment preceding dementia with Lewy bodies. Neurology, 62, 8687.Google Scholar
Brunet, J. et al. (2011). The relation between depressive symptoms and semantic memory in amnestic mild cognitive impairment and in late-life depression. Journal of International Neuropsychological Society, 17, 865–74.CrossRefGoogle ScholarPubMed
Butters, M. A. et al. (2004). The nature and determinants of neuropsychological functioning in late-life depression. Archives of General Psychiatry, 61, 587–95.CrossRefGoogle ScholarPubMed
Butters, M. A. et al. (2008). Pathways linking late-life depression to persistent cognitive impairment and dementia. Dialogues in Clinical Neuroscience, 10, 345–57.CrossRefGoogle ScholarPubMed
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences, 2nd edn. Hillsdale, NJ: Lawrence A. Erlbaum Associates.Google Scholar
Ellison, J. M., Harper, D. G., Berlow, Y. and Zeranski, L. (2008). Beyond the “C” in MCI: noncognitive symptoms in amnestic and non-amnestic mild cognitive impairment. CNS Spectrums, 13, 6672.CrossRefGoogle ScholarPubMed
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, 189–98.CrossRefGoogle ScholarPubMed
Heaton, R. K. (1993). Wisconsin card sorting test: computer version 2. Odessa: Psychological Assessment Resources.Google Scholar
Hickie, I., Scott, E., Mitchell, P., Wilhelm, K., Austin, M. P. and Bennett, B. (1995). Subcortical hyperintensities on magnetic resonance imaging: clinical correlates and prognostic significance in patients with severe depression. Biological Psychiatry, 37, 151–60.CrossRefGoogle ScholarPubMed
Hudon, C., Belleville, S. and Gauthier, S. (2008). The association between depressive and cognitive symptoms in amnestic mild cognitive impairment. International Psychogeriatrics, 20, 710–23.CrossRefGoogle ScholarPubMed
Johnson, L. A. et al. (2013). Cognitive differences among depressed and non-depressed MCI participants: a project FRONTIER study. International Journal of Geriatriatric Psychiatry, 28, 377–82.CrossRefGoogle ScholarPubMed
Kang, S. J., Choi, S. H., Lee, B. H., Kwon, J. C., Na, D. L. and Han, S. H. C. N. K. D. R. G. (2002). The reliability and validity of the korean instrumental activities of daily living (K-IADL). Journal of the Korean Neurological Association, 20, 814.Google Scholar
Kang, Y. and Na, D. (2003). Seoul Neuropsychological Screening Battery. Incheon: Human Brain Research & Consulting Co.Google Scholar
Kramer-Ginsberg, E. et al. (1999). Neuropsychological functioning and MRI signal hyperintensities in geriatric depression. The American Journal of Psychiatry, 156, 438–44.CrossRefGoogle ScholarPubMed
Lecrubier, Y. et al. (1997). The mini international neuropsychiatric interview (MINI). A short diagnostic structured interview: reliability and validity according to the CIDI. European Psychiatry, 12, 224231.CrossRefGoogle Scholar
Lee, J. H. et al. (2002). Development of the Korean version of the consortium to establish a registry for Alzheimer's disease assessment packet (CERAD-K): clinical and neuropsychological assessment batteries. Journal of Gerontology. Series B, Psychological Sciences and Social Science, 57, P47–53.CrossRefGoogle Scholar
Lim, J. et al. (2013). Sensitivity of cognitive tests in four cognitive domains in discriminating MDD patients from healthy controls: a meta-analysis. International Psychogeriatrics, 25, 1543–57.CrossRefGoogle ScholarPubMed
Mahoney, F. I. and Barthel, D. W. (1965). Functional evaluation: the Barthel index. Maryland State Medical Journal, 14, 61–5.Google ScholarPubMed
Murata, T. et al. (2001). MRI white matter hyperintensities, (1)H-MR spectroscopy and cognitive function in geriatric depression: a comparison of early- and late-onset cases. International Journal of Geriatric Psychiatry, 16, 1129–35.CrossRefGoogle ScholarPubMed
Nasreddine, Z. S. et al. (2005). The montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53, 695–9.CrossRefGoogle Scholar
Nebes, R. D. et al. (2000). Decreased working memory and processing speed mediate cognitive impairment in geriatric depression. Psychological Medicine, 30, 679–91.CrossRefGoogle ScholarPubMed
Nebes, R. D. et al. (2003). Persistence of cognitive impairment in geriatric patients following antidepressant treatment: a randomized, double-blind clinical trial with nortriptyline and paroxetine. Journal of Psychiatric Research, 37, 99108.CrossRefGoogle ScholarPubMed
Petersen, R. C. (2004). Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine, 256, 183–94.CrossRefGoogle ScholarPubMed
Reisberg, B., Ferris, S. H., De Leon, M. J. and Crook, T. (1982). The global deterioration scale for assessment of primary degenerative dementia. The American Journal of Psychiatry, 139, 1136–9.Google ScholarPubMed
Reitan, R. M. (1955). The relation of the trail making test to organic brain damage. Journal of Consulting Psychology, 19, 393–4.CrossRefGoogle ScholarPubMed
Richard, E. et al. (2013). Late-life depression, mild cognitive impairment, and dementia. JAMA Neurology, 70, 374–82.CrossRefGoogle ScholarPubMed
Sanchez-Cubillo, I. et al. (2009). Construct validity of the trail making test: role of task-switching, working memory, inhibition/interference control, and visuomotor abilities. Journal of the International Neuropsychological Society, 15, 438–50.CrossRefGoogle ScholarPubMed
Sander, R. D. (2010). Motor examinations in psychiatry. Psychiatry (Edgmont), 7, 3741.Google ScholarPubMed
Schermuly, I. et al. (2010). Association between cingulum bundle structure and cognitive performance: an observational study in major depression. European Psychiatry, 25, 355–60.CrossRefGoogle ScholarPubMed
Sheline, Y. I. et al. (2008). Regional white matter hyperintensity burden in automated segmentation distinguishes late-life depressed subjects from comparison subjects matched for vascular risk factors. The American Journal of Psychiatry, 165, 524–32.CrossRefGoogle ScholarPubMed
Spangenberg, K. B., Henderson, S. and Wagner, M. T. (1997). Validity of a recall and recognition condition to assess visual memory in the CERAD battery. Applied Neuropsychology, 4, 154–9.CrossRefGoogle ScholarPubMed
Spitzer, R. L., Kroenke, K. and Williams, J. B. (1999). Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. JAMA, 282, 1737–44.CrossRefGoogle ScholarPubMed
Steffens, D. C. et al. (2006). Perspectives on depression, mild cognitive impairment, and cognitive decline. Archives of General Psychiatry, 63, 130–8.CrossRefGoogle ScholarPubMed
Taylor, W. D., Aizenstein, H. J. and Alexopoulos, G. S. (2013). The vascular depression hypothesis: mechanisms linking vascular disease with depression. Molecular Psychiatry, 18, 963974.CrossRefGoogle ScholarPubMed
Van Reekum, R., Simard, M., Clarke, D., Binns, M. A. and Conn, D. (1999). Late-life depression as a possible predictor of dementia: cross-sectional and short-term follow-up results. The American Journal of Geriatrric Psychiatry, 7, 151–9.Google ScholarPubMed
Wechsler, D. (1958). The Measurement and Appraisal of Adult Intelligence, 4th edn. Baltimore, MD: Williams & Wilkins.Google Scholar