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Computerized Cognitive Tests Are Associated with Biomarkers of Alzheimer’s Disease in Cognitively Normal Individuals 10 Years Prior

  • Anja Soldan (a1), Corinne Pettigrew (a1), Abhay Moghekar (a1), Marilyn Albert (a1) and the BIOCARD Research Team...

Abstract

Objectives: Evidence suggests that Alzheimer’s disease (AD) biomarkers become abnormal many years before the emergence of clinical symptoms of AD, raising the possibility that biomarker levels measured in cognitively normal individuals would be associated with cognitive performance many years later. This study examined whether performance on computerized cognitive tests is associated with levels of cerebrospinal fluid (CSF) biomarkers of amyloid, tau, and phosphorylated tau (p-tau) obtained approximately 10 years earlier, when individuals were cognitively normal and primarily middle-aged. Methods: Individuals from the BIOCARD cohort (mean age at testing=69 years) were tested on two computerized tasks hypothesized to rely on brain regions affected by the early accumulation of AD pathology: (1) a Paired Associates Learning (PAL) task (n=67) and (2) a visual search task (n=86). Results: In regression analyses, poorer performance on the PAL task was associated with higher levels of CSF p-tau obtained years earlier, whereas worse performance in the visual search task was associated with lower levels of CSF Aβ1-42. Conclusions: These findings suggest that AD biomarker levels may be differentially predictive of specific cognitive functions many years later. In line with the pattern of early accumulation of AD pathology, the PAL task, hypothesized to rely on medial temporal lobe function, was associated with CSF p-tau, whereas the visual search task, hypothesized to rely on frontoparietal function, was associated with CSF amyloid. Studies using amyloid and tau PET imaging will be useful in examining these hypothesized relationships further. (JINS, 2016, 22, 968–977)

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Corresponding author

Correspondence and reprint requests to: Anja Soldan, Division of Cognitive Neuroscience, 1620 McElderry Street, Reed Hall 1-West, Baltimore, MD 21205. E-mail: asoldan1@jhmi.edu

References

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Albert, M., Soldan, A., Gottesman, R., McKhann, G., Sacktor, N., Farrington, L., & Selnes, O. (2014). Cognitive changes preceding clinical symptom onset of mild cognitive impairment and relationship to ApoE genotype. Current Alzheimer Research, 11(8), 773784.
Anderson, E.J., Mannan, S.K., Husain, M., Rees, G., Sumner, P., Mort, D.J., & Kennard, C. (2007). Involvement of prefrontal cortex in visual search. Experimental Brain Research, 180(2), 289302.
Anstey, K.J., Wood, J., Kerr, G., Caldwell, H., & Lord, S.R. (2009). Different cognitive profiles for single compared with recurrent fallers without dementia. Neuropsychology, 23(4), 500508.
Aschenbrenner, A.J., Balota, D.A., Fagan, A.M., Duchek, J.M., Benzinger, T.L., & Morris, J.C. (2015). Alzheimer disease cerebrospinal fluid biomarkers moderate baseline differences and predict longitudinal change in attentional control and episodic memory composites in the adult children study. Journal of the International Neuropsychological Society, 21(8), 573583.
Aschenbrenner, A.J., Balota, D.A., Tse, C.S., Fagan, A.M., Holtzman, D.M., Benzinger, T.L., &Morris, J.C. (2015). Alzheimer disease biomarkers, attentional control, and semantic memory retrieval: Synergistic and mediational effects of biomarkers on a sensitive cognitive measure in non-demented older adults. Neuropsychology, 29(3), 368381.
Bennett, I.J., Barnes, K.A., Howard, J.H. Jr., & Howard, D.V. (2009). An abbreviated implicit spatial context learning task that yields greater learning. Behavioral Research Methods, 41(2), 391395.
Bilgel, M., Jedynak, B., Wong, D.F., Resnick, S.M., & Prince, J.L. (2015). Temporal trajectory and progression score estimation from voxelwise longitudinal imaging measures: Application to amyloid imaging. Information Processing in Medical Imaging, 24, 424436.
Blacker, D., Lee, H., Muzikansky, A., Martin, E.C., Tanzi, R., McArdle, J.J., & Albert, M. (2007). Neuropsychological measures in normal individuals that predict subsequent cognitive decline. Archives of Neurology, 64(6), 862871.
Braak, H., Alafuzoff, I., Arzberger, T., Kretzschmar, H., & Del Tredici, K. (2006). Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathologica, 112(4), 389404.
Braak, H., & Braak, E. (1991). Neuropathological stageing of Alzheimer-related changes. Acta Neuropathologica, 82(4), 239259.
Chun, M.M., & Jiang, Y. (1998). Contextual cueing: Implicit learning and memory of visual context guides spatial attention. Cognitive Psychology, 36(1), 2871.
Corbetta, M., & Shulman, G.L. (1998). Human cortical mechanisms of visual attention during orienting and search. Philosophical Transactions of the Royal Society B: Biological Sciences, 353(1373), 13531362.
Cummings, J.L., Mega, M., Gray, K., Rosenberg-Thompson, S., Carusi, D.A., & Gornbein, J. (1994). The Neuropsychiatric Inventory: Comprehensive assessment of psychopathology in dementia. Neurology, 44(12), 23082314.
de Jager, C.A., Milwain, E., & Budge, M. (2002). Early detection of isolated memory deficits in the elderly: The need for more sensitive neuropsychological tests. Psychological Medicine, 32(3), 483491.
de Rover, M., Pironti, V.A., McCabe, J.A., Acosta-Cabronero, J., Arana, F.S., Morein-Zamir, S., & Sahakian, B.J. (2011). Hippocampal dysfunction in patients with mild cognitive impairment: A functional neuroimaging study of a visuospatial paired associates learning task. Neuropsychologia, 49(7), 20602070.
Donner, T.H., Kettermann, A., Diesch, E., Ostendorf, F., Villringer, A., & Brandt, S.A. (2002). Visual feature and conjunction searches of equal difficulty engage only partially overlapping frontoparietal networks. Neuroimage, 15(1), 1625.
Egerhazi, A., Berecz, R., Bartok, E., & Degrell, I. (2007). Automated Neuropsychological Test Battery (CANTAB) in mild cognitive impairment and in Alzheimer’s disease. Progress in Neuropsychopharmacology & Biological Psychiatry, 31(3), 746751.
Fagan, A.M., Head, D., Shah, A.R., Marcus, D., Mintun, M., Morris, J.C., & Holtzman, D.M. (2009). Decreased cerebrospinal fluid Abeta(42) correlates with brain atrophy in cognitively normal elderly. Annals of Neurology, 65(2), 176183.
Fagan, A.M., Roe, C.M., Xiong, C., Mintun, M.A., Morris, J.C., & Holtzman, D.M. (2007). Cerebrospinal fluid tau/beta-amyloid(42) ratio as a prediction of cognitive decline in nondemented older adults. Archives of Neurology, 64(3), 343349.
Folstein, M.F., Folstein, S.E., & 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(3), 189198.
Glodzik, L., de Santi, S., Tsui, W.H., Mosconi, L., Zinkowski, R., Pirraglia, E., & de Leon, M.J. (2011). Phosphorylated tau 231, memory decline and medial temporal atrophy in normal elders. Neurobiology of Aging, 32(12), 21312141.
Glodzik, L., Mosconi, L., Tsui, W., de Santi, S., Zinkowski, R., Pirraglia, E., & de Leon, M.J. (2012). Alzheimer’s disease markers, hypertension, and gray matter damage in normal elderly. Neurobiology of Aging, 33(7), 12151227.
Heitz, R.P. (2014). The speed-accuracy tradeoff: History, physiology, methodology, and behavior. Frontiers in Neuroscience, 8, 150.
Howieson, D.B., Carlson, N.E., Moore, M.M., Wasserman, D., Abendroth, C.D., Payne-Murphy, J., &Kaye, J.A. (2008). Trajectory of mild cognitive impairment onset. Journal of the International Neuropsychological Society, 14(2), 192198.
Hughes, C.P., Berg, L., Danziger, W.L., Coben, L.A., & Martin, R.L. (1982). A new clinical scale for the staging of dementia. British Journal of Psychiatry, 140, 566572.
Insel, P.S., Mattsson, N., Mackin, R.S., Kornak, J., Nosheny, R., Tosun-Turgut, D., & Weiner, M.W. (2015). Biomarkers and cognitive endpoints to optimize trials in Alzheimer’s disease. Annals of Clinical and Translational Neurology, 2(5), 534547.
Jack, C.R. Jr., Knopman, D.S., Jagust, W.J., Petersen, R.C., Weiner, M.W., Aisen, P.S., & Trojanowski, J.Q. (2013). Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurology, 12(2), 207216.
Junkkila, J., Oja, S., Laine, M., & Karrasch, M. (2012). Applicability of the CANTAB-PAL computerized memory test in identifying amnestic mild cognitive impairment and Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders, 34(2), 8389.
Lenehan, M.E., Summers, M.J., Saunders, N.L., Summers, J.J., & Vickers, J.C. (2016). Does the Cambridge Automated Neuropsychological Test Battery (CANTAB) distinguish between cognitive domains in healthy older adults? Assessment, 15, 192195.
Li, G., Millard, S.P., Peskind, E.R., Zhang, J., Yu, C.E., Leverenz, J.B., & Montine, T.J. (2014). Cross-sectional and longitudinal relationships between cerebrospinal fluid biomarkers and cognitive function in people without cognitive impairment from across the adult life span. JAMA Neurology, 71(6), 742751.
Manelis, A., & Reder, L.M. (2012). Procedural learning and associative memory mechanisms contribute to contextual cueing: Evidence from fMRI and eye-tracking. Learning & Memory, 19(11), 527534.
Mattsson, N., Insel, P., Nosheny, R., Trojanowski, J.Q., Shaw, L.M., Jack, C.R. Jr., & Weiner, M. (2014). Effects of cerebrospinal fluid proteins on brain atrophy rates in cognitively healthy older adults. Neurobiology of Aging, 35(3), 614622.
Mattsson, N., Insel, P.S., Nosheny, R., Tosun, D., Trojanowski, J.Q., Shaw, L.M., & Weiner, M.W. (2014). Emerging beta-amyloid pathology and accelerated cortical atrophy. JAMA Neurology, 71(6), 725734.
McLaughlin, P.M., Borrie, M.J., & Murtha, S.J. (2010). Shifting efficacy, distribution of attention and controlled processing in two subtypes of mild cognitive impairment: Response time performance and intraindividual variability on a visual search task. Neurocase, 16(5), 408417.
Moghekar, A., Goh, J., Li, M., Albert, M., & O’Brien, R.J. (2012). Cerebrospinal fluid Abeta and tau level fluctuation in an older clinical cohort. Archives of Neurology, 69(2), 246250.
Moghekar, A., Li, S., Lu, Y., Li, M., Wang, M.C., Albert, M., &O’Brien, R. (2013). CSF biomarker changes precede symptom onset of mild cognitive impairment. Neurology, 81(20), 17531758.
Morris, J.C. (1993). The Clinical Dementia Rating (CDR): Current version and scoring rules. Neurology, 43(11), 24122414.
Muller-Oehring, E.M., Schulte, T., Rohlfing, T., Pfefferbaum, A., & Sullivan, E.V. (2013). Visual search and the aging brain: Discerning the effects of age-related brain volume shrinkage on alertness, feature binding, and attentional control. Neuropsychology, 27(1), 4859.
Pettigrew, C., Soldan, A., Moghekar, A., Wang, M.C., Gross, A.L., O’Brien, R., & Albert, M. (2015). Relationship between cerebrospinal fluid biomarkers of Alzheimer’s disease and cognition in cognitively normal older adults. Neuropsychologia, 78, 6372.
Reitan, R.M. (1958). Validity of the trail making test as an indicator of organic brain damage. Perceptual and Motor Skills, 8, 271276.
Rey, A. (1941). L’examen psychologique dans les cas d’encephalopathie traumatique. Archives de Psychologie, 28, 286340.
Roe, C.M., Fagan, A.M., Grant, E.A., Marcus, D.S., Benzinger, T.L., Mintun, M.A., & Morris, J.C. (2011). Cerebrospinal fluid biomarkers, education, brain volume, and future cognition. Archives of Neurology, 68(9), 11451151.
Rosler, A., Mapstone, M.E., Hays, A.K., Mesulam, M.M., Rademaker, A., Gitelman, D.R., &Weintraub, S. (2000). Alterations of visual search strategy in Alzheimer’s disease and aging. Neuropsychology, 14(3), 398408.
Sahakian, B.J., Morris, R.G., Evenden, J.L., Heald, A., Levy, R., Philpot, M., & Robbins, T.W. (1988). A comparative study of visuospatial memory and learning in Alzheimer-type dementia and Parkinson’s disease. Brain, 111(Pt 3), 695718.
Soldan, A., Pettigrew, C., Li, S., Wang, M.C., Moghekar, A., Selnes, O.A., & O’Brien, R. (2013). Relationship of cognitive reserve and cerebrospinal fluid biomarkers to the emergence of clinical symptoms in preclinical Alzheimer’s disease. Neurobiology of Aging, 34(12), 28272834.
Soldan, A., Pettigrew, C., Wang, M.C., Moghekar, A., O’Brien, R., Selnes, O., & Albert, M. (in press). Hypothetical preclinical Alzheimer’s disease groups and longitudinal cognitive change. JAMA Neurology.
Sperling, R.A., Aisen, P.S., Beckett, L.A., Bennett, D.A., Craft, S., Fagan, A.M., & Phelps, C.H. (2011). Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7(3), 280292.
Steenland, K., Zhao, L., Goldstein, F., Cellar, J., & Lah, J. (2014). Biomarkers for predicting cognitive decline in those with normal cognition. Journal of Alzheimer’s Disease, 40(3), 587594.
Stricker, N.H., Dodge, H.H., Dowling, N.M., Han, S.D., Erosheva, E.A., & Jagust, W.J. (2012). CSF biomarker associations with change in hippocampal volume and precuneus thickness: Implications for the Alzheimer’s pathological cascade. Brain Imaging and Behavior, 6(4), 599609.
Sutphen, C.L., Jasielec, M.S., Shah, A.R., Macy, E.M., Xiong, C., Vlassenko, A.G., & Fagan, A.M. (2015). Longitudinal cerebrospinal fluid biomarker changes in preclinical Alzheimer disease during middle age. JAMA Neurology, 72(9), 10291042.
Tales, A., Bayer, A.J., Haworth, J., Snowden, R.J., Philips, M., & Wilcock, G. (2011). Visual search in mild cognitive impairment: A longitudinal study. Journal of Alzheimer’s Disease, 24(1), 151160.
Tales, A., Haworth, J., Nelson, S., Snowden, R.J., & Wilcock, G. (2005). Abnormal visual search in mild cognitive impairment and Alzheimer’s disease. Neurocase, 11(1), 8084.
Thal, D.R., Rub, U., Orantes, M., & Braak, H. (2002). Phases of A beta-deposition in the human brain and its relevance for the development of AD. Neurology, 58(12), 17911800.
Tosun, D., Schuff, N., Shaw, L.M., Trojanowski, J.Q., & Weiner, M.W. (2011). Relationship between CSF biomarkers of Alzheimer’s disease and rates of regional cortical thinning in ADNI data. Journal of Alzheimer’s Disease, 26(Suppl. 3), 7790.
Viskontas, I.V., Boxer, A.L., Fesenko, J., Matlin, A., Heuer, H.W., Mirsky, J., &Miller, B.L. (2011). Visual search patterns in semantic dementia show paradoxical facilitation of binding processes. Neuropsychologia, 49(3), 468478.
Vos, S.J., Xiong, C., Visser, P.J., Jasielec, M.S., Hassenstab, J., Grant, E.A., & Fagan, A.M. (2013). Preclinical Alzheimer’s disease and its outcome: A longitudinal cohort study. The Lancet Neurology, 12(10), 957965.
Whelan, R. (2008). Effective analysis of reaction time data. The Psychological Record, 58, 475482.
Wilson, R.S., Leurgans, S.E., Boyle, P.A., & Bennett, D.A. (2011). Cognitive decline in prodromal Alzheimer disease and mild cognitive impairment. Archives of Neurology, 68(3), 351356.
Yesavage, J.A., Brink, T.L., Rose, T.L., Lum, O., Huang, V., Adey, M., & Leirer, V.O. (1982). Development and validation of a geriatric depression screening scale: A preliminary report. Journal of Psychiatric Research, 17(1), 3749.
Yotter, R.A., Doshi, J., Clark, V., Sojkova, J., Zhou, Y., Wong, D.F., & Davatzikos, C. (2013). Memory decline shows stronger associations with estimated spatial patterns of amyloid deposition progression than total amyloid burden. Neurobiology of Aging, 34(12), 28352842.

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