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Exploring the pattern and neural correlates of neuropsychological impairment in late-life depression

Published online by Cambridge University Press:  26 October 2011

C. E. Sexton ,
L. McDermott ,
U. G. Kalu ,
L. L. Herrmann ,
K. M. Bradley ,
C. L. Allan ,
M. Le Masurier ,
C. E. Mackay  and
K. P. Ebmeier
C. E. Sexton
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
L. McDermott
Affiliation:
School of Psychology, University of Southampton, Southampton, UK
U. G. Kalu
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
L. L. Herrmann
Affiliation:
Royal Hospital of Neuro-disability, London, UK
K. M. Bradley
Affiliation:
Department of Radiology, Oxford Radcliffe Hospitals NHS Trust, Oxford, UK
C. L. Allan
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
M. Le Masurier
Affiliation:
Garburn Unit, Westmorland General Hospital, Burton Road, Kendal, Cumbria, UK
C. E. Mackay
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
K. P. Ebmeier*
Affiliation:
Department of Psychiatry, University of Oxford, Oxford, UK
*
*Address for correspondence: Dr K. P. Ebmeier, Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK. (Email: [email protected])
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Abstract

Background

Neuropsychological impairment is a key feature of late-life depression, with deficits observed across multiple domains. However, it is unclear whether deficits in multiple domains represent relatively independent processes with specific neural correlates or whether they can be explained by cognitive deficits in executive function or processing speed.

Method

We examined group differences across five domains (episodic memory; executive function; language skills; processing speed; visuospatial skills) in a sample of 36 depressed participants and 25 control participants, all aged ⩾60 years. The influence of executive function and processing speed deficits on other neuropsychological domains was also investigated. Magnetic resonance imaging correlates of executive function, processing speed and episodic memory were explored in the late-life depression group.

Results

Relative to controls, the late-life depression group performed significantly worse in the domains of executive function, processing speed, episodic memory and language skills. Impairments in executive function or processing speed were sufficient to explain differences in episodic memory and language skills. Executive function was correlated with anisotropy of the anterior thalamic radiation and uncinate fasciculus; processing speed was correlated with anisotropy of genu of the corpus callosum. Episodic memory was correlated with anisotropy of the anterior thalamic radiation, the genu and body of the corpus callosum and the fornix.

Conclusions

Executive function and processing speed appear to represent important cognitive deficits in late-life depression, which contribute to deficits in other domains, and are related to reductions in anisotropy in frontal tracts.

Keywords

Cognitiondepressiondiffusion tensor imaginglate-lifemagnetic resonance imagingneuropsychology
Type
Original Articles
Information
Psychological Medicine , Volume 42 , Issue 6 , June 2012 , pp. 1195 - 1202
Copyright
Copyright © Cambridge University Press 2011

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References

Alexander, GE, DeLong, MR, Strick, PL (1986). Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annual Review of Neuroscience 9, 357–381.CrossRefGoogle ScholarPubMed
Alexopoulos, GS (2002). Frontostriatal and limbic dysfunction in late-life depression. American Journal of Geriatric Psychiatry 10, 687–695.CrossRefGoogle ScholarPubMed
Alexopoulos, GS (2003). Role of executive function in late-life depression. Journal of Clinical Psychiatry 64 (Suppl. 14), 18–23.Google ScholarPubMed
Avila, R, Ribeiz, S, Duran, FL, Arrais, JP, Moscoso, MA, Bezerra, DM, Jaluul, O, Castro, CC, Busatto, GF, Bottino, CM (2011). Effect of temporal lobe structure volume on memory in elderly depressed patients. Neurobiology of Aging 32, 1857–1867.CrossRefGoogle ScholarPubMed
Ballmaier, M, Narr, KL, Toga, AW, Elderkin-Thompson, V, Thompson, PM, Hamilton, L, Haroon, E, Pham, D, Heinz, A, Kumar, A (2008). Hippocampal morphology and distinguishing late-onset from early-onset elderly depression. American Journal of Psychiatry 165, 229–237.CrossRefGoogle ScholarPubMed
Bhalla, RK, Butters, MA, Mulsant, BH, Begley, AE, Zmuda, MD, Schoderbek, B, Pollock, BG, Reynolds, CF 3rd, Becker, JT (2006). Persistence of neuropsychologic deficits in the remitted state of late-life depression. American Journal of Geriatric Psychiatry 14, 419–427.Google Scholar
Brandt, J (1991). The Hopkins Verbal Learning Test: development of a new memory test with six equivalent forms. Clinical Neuropsychology 5, 125–142.Google Scholar
Briggs, GG, Nebes, RD (1975). Patterns of hand preference in a student population. Cortex 11, 230–238.Google Scholar
Buckner, RL (2004). Memory and executive function in aging and AD: multiple factors that cause decline and reserve factors that compensate. Neuron 44, 195–208.CrossRefGoogle Scholar
Butters, MA, Becker, JT, Nebes, RD, Zmuda, MD, Mulsant, BH, Pollock, BG, Reynolds, CF 3rd (2000). Changes in cognitive functioning following treatment of late-life depression. American Journal of Psychiatry 157, 1949–1954.Google Scholar
Butters, MA, Whyte, EM, Nebes, RD, Begley, AE, Dew, MA, Mulsant, BH, Zmuda, MD, Bhalla, R, Meltzer, CC, Pollock, BG, Reynolds, ICF II, Becker, JT (2004). The nature and determinants of neuropsychological functioning in late-life depression. Archives of General Psychiatry 61, 587–595.CrossRefGoogle ScholarPubMed
Dickerson, BC, Eichenbaum, H (2010). The episodic memory system: neurocircuitry and disorders. Neuropsychopharmacology 35, 86–104.Google Scholar
Dillon, C, Allegri, RF, Serrano, CM, Iturry, M, Salgado, P, Glaser, FB, Taragano, FE (2009). Late- versus early-onset geriatric depression in a memory research center. Neuropsychiatric Disease and Treatment 5, 517–526.Google Scholar
Elderkin-Thompson, V, Mintz, J, Haroon, E, Lavretsky, H, Kumar, A (2007). Executive dysfunction and memory in older patients with major and minor depression. Archives of Clinical Neuropsychology 22, 261–270.CrossRefGoogle ScholarPubMed
First, MB, Spitzer, RL, Gibbon, M, Williams, JBW (2007). Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Non-Patient Edition. Biometrics Research, New York State Psychiatric Institute: New York.Google Scholar
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.Google Scholar
Hamilton, M (1967). Development of a rating scale for primary depressive illness. British Journal of Social & Clinical Psychology 6, 278–296.Google Scholar
Herrmann, LL, Goodwin, GM, Ebmeier, KP (2007). The cognitive neuropsychology of depression in the elderly. Psychological Medicine 37, 1693–1702.Google Scholar
Kennedy, KM, Raz, N (2009). Aging white matter and cognition: differential effects of regional variations in diffusion properties on memory, executive functions, and speed. Neuropsychologia 47, 916–927.Google Scholar
Kochunov, P, Coyle, T, Lancaster, J, Robin, DA, Hardies, J, Kochunov, V, Bartzokis, G, Stanley, J, Royall, D, Schlosser, AE, Null, M, Fox, PT (2010). Processing speed is correlated with cerebral health markers in the frontal lobes as quantified by neuroimaging. NeuroImage 49, 1190–1199.CrossRefGoogle ScholarPubMed
Kohler, S, Thomas, AJ, Barnett, NA, O'Brien, JT (2010). The pattern and course of cognitive impairment in late-life depression. Psychological Medicine 40, 591–602.CrossRefGoogle ScholarPubMed
McGurn, B, Starr, JM, Topfer, JA, Pattie, A, Whiteman, MC, Lemmon, HA, Whalley, LJ, Deary, IJ (2004). Pronunciation of irregular words is preserved in dementia, validating premorbid IQ estimation. Neurology 62, 1184–1186.Google Scholar
McKenna, P, Warrington, EK (1980). Testing for nominal dysphasia. Journal of Neurology, Neurosurgery, and Psychiatry 43, 781–788.Google Scholar
Mayberg, HS (1997). Limbic-cortical dysregulation: a proposed model of depression. Journal of Neuropsychiatry and Clinical Neurosciences 9, 471–481.Google ScholarPubMed
McDermott, LM, Ebmeier, KP (2009). A meta-analysis of depression severity and cognitive function. Journal of Affective Disorders 119, 1–8.Google Scholar
Mioshi, E, Dawson, K, Mitchell, J, Arnold, R, Hodges, JR (2006). The Addenbrooke's Cognitive Examination revised (ACE-R): a brief cognitive test battery for dementia screening. International Journal of Geriatric Psychiatry 21, 1078–1085.Google Scholar
Murphy, CF, Alexopoulos, GS (2004). Longitudinal association of initiation/perseveration and severity of geriatric depression. American Journal of Geriatric Psychiatry 12, 50–56.CrossRefGoogle ScholarPubMed
Murphy, CF, Gunning-Dixon, FM, Hoptman, MJ, Lim, KO, Ardekani, B, Shields, JK, Hrabe, J, Kanellopoulos, D, Shanmugham, BR, Alexopoulos, GS (2007). White-matter integrity predicts stroop performance in patients with geriatric depression. Biological Psychiatry 61, 1007–1010.CrossRefGoogle ScholarPubMed
Nebes, RD, Pollock, BG, Houck, PR, Butters, MA, Mulsant, BH, Zmuda, MD, Reynolds, CF 3rd (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, 99–108.CrossRefGoogle ScholarPubMed
Nichols, TE, Holmes, AP (2002). Nonparametric permutation tests for functional neuroimaging: a primer with examples. Human Brain Mapping 15, 1–25.Google Scholar
Osterrieth, PA (1944). Le test de copie d'une figure complexe. Archives de Psychologie 30, 206–356.Google Scholar
Patenaude, B, Smith, SM, Kennedy, DN, Jenkinson, M (2011). A Bayesian model of shape and appearance for subcortical brain segmentation. NeuroImage 56, 907–922.CrossRefGoogle ScholarPubMed
Reitan, R (1958). Validity of the Trail Making Test as an indicator of organic brain damage. Perceptual and Motor Skills 8, 271–276.Google Scholar
Sahakian, BJ, Owen, AM, Morant, NJ, Eagger, SA, Boddington, S, Crayton, L, Crockford, HA, Crooks, M, Hill, K, Levy, R (1993). Further analysis of the cognitive effects of tetrahydroaminoacridine (THA) in Alzheimer's disease: assessment of attentional and mnemonic function using CANTAB. Psychopharmacology 110, 395–401.Google Scholar
Schermuly, I, Fellgiebel, A, Wagner, S, Yakushev, I, Stoeter, P, Schmitt, R, Knickenberg, RJ, Bleichner, F, Beutel, ME (2010). Association between cingulum bundle structure and cognitive performance: an observational study in major depression. European Psychiatry 25, 355–360.CrossRefGoogle ScholarPubMed
Sheline, YI, Barch, DM, Garcia, K, Gersing, K, Pieper, C, Welsh-Bohmer, K, Steffens, DC, Doraiswamy, PM (2006). Cognitive function in late life depression: relationships to depression severity, cerebrovascular risk factors and processing speed. Biological Psychiatry 60, 58–65.CrossRefGoogle ScholarPubMed
Shimony, JS, Sheline, YI, d'Angelo, G, Epstein, AA, Benzinger, TL, Mintun, MA, McKinstry, RC, Snyder, AZ (2009). Diffuse microstructural abnormalities of normal-appearing white matter in late life depression: a diffusion tensor imaging study. Biological Psychiatry 66, 245–252.Google Scholar
Smith, SM (2002). Fast robust automated brain extraction. Human Brain Mapping 17, 143–155.Google Scholar
Smith, SM, Jenkinson, M, Johansen-Berg, H, Rueckert, D, Nichols, TE, Mackay, CE, Watkins, KE, Ciccarelli, O, Cader, MZ, Matthews, PM, Behrens, TEJ (2006). Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. NeuroImage 31, 1487–1505.Google Scholar
Smith, SM, Jenkinson, M, Woolrich, MW, Beckmann, CF, Behrens, TE, Johansen-Berg, H, Bannister, PR, de Luca, M, Drobnjak, I, Flitney, DE, Niazy, RK, Saunders, J, Vickers, J, Zhang, Y, de Stefano, N, Brady, JM, Matthews, PM (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23 (Suppl. 1), S208–S219.CrossRefGoogle ScholarPubMed
Veiel, HO (1997). A preliminary profile of neuropsychological deficits associated with major depression. Journal of Clinical & Experimental Neuropsychology 19, 587–603.CrossRefGoogle ScholarPubMed
Wechsler, D (1997). Wechsler Adult Intelligence Scale. The Psychological Corporation: San Antonio, TX.Google Scholar
Yesavage, JA, Brink, TL, Rose, TL, Lum, O, Huang, V, Adey, M, Leirer, VO (1982). Development and validation of a geriatric depression screening scale: a preliminary report. Journal of Psychiatric Research 17, 37–49.CrossRefGoogle Scholar
Yuan, Y, Zhang, Z, Bai, F, Yu, H, Shi, Y, Qian, Y, Zang, Y, Zhu, C, Liu, W, You, J (2007). White matter integrity of the whole brain is disrupted in first-episode remitted geriatric depression. Neuroreport 18, 1845–1849.Google Scholar
Yuan, Y, Zhu, W, Zhang, Z, Bai, F, Yu, H, Shi, Y, Qian, Y, Liu, W, Jiang, T, You, J, Liu, Z (2008). Regional gray matter changes are associated with cognitive deficits in remitted geriatric depression: an optimized voxel-based morphometry study. Biological Psychiatry 64, 541–544.CrossRefGoogle ScholarPubMed
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