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Amyloid Burden, Neuronal Function, and Cognitive Decline in Middle-Aged Adults at Risk for Alzheimer's Disease

Published online by Cambridge University Press:  11 March 2014

Ozioma C. Okonkwo
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, Madison, Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Jennifer M. Oh
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, Madison, Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Rebecca Koscik
Affiliation:
Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Erin Jonaitis
Affiliation:
Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Caitlin A. Cleary
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, Madison, Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
N. Maritza Dowling
Affiliation:
Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Department of Biostatistics & Medical Informatics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Barbara B. Bendlin
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, Madison, Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Asenath LaRue
Affiliation:
Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Bruce P. Hermann
Affiliation:
Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Todd E. Barnhart
Affiliation:
Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Dhanabalan Murali
Affiliation:
Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Howard A. Rowley
Affiliation:
Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Cynthia M. Carlsson
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, Madison, Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Catherine L. Gallagher
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, Madison, Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Sanjay Asthana
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, Madison, Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Mark A. Sager
Affiliation:
Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Brad T. Christian
Affiliation:
Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Sterling C. Johnson
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial VA Hospital, Madison, Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin Wisconsin Alzheimer's Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Corresponding
E-mail address:

Abstract

The relative influence of amyloid burden, neuronal structure and function, and prior cognitive performance on prospective memory decline among asymptomatic late middle-aged individuals at risk for Alzheimer's disease (AD) is currently unknown. We investigated this using longitudinal cognitive data from 122 middle-aged adults (21 “Decliners” and 101 “Stables”) enrolled in the Wisconsin Registry for Alzheimer's Prevention who underwent multimodality neuroimaging [11C-Pittsburgh Compound B (PiB), 18F-fluorodeoxyglucose (FDG), and structural/functional magnetic resonance imaging (fMRI)] 5.7 ± 1.4 years (range = 2.9–8.9) after their baseline cognitive assessment. Covariate-adjusted regression analyses revealed that the only imaging measure that significantly distinguished Decliners from Stables (p = .027) was a Neuronal Function composite derived from FDG and fMRI. In contrast, several cognitive measures, especially those that tap episodic memory, significantly distinguished the groups (p's<.05). Complementary receiver operating characteristic curve analyses identified the Brief Visuospatial Memory Test-Revised (BVMT-R) Total (.82 ± .05, p < .001), the BVMT-R Delayed Recall (.73 ± .06, p = .001), and the Reading subtest from the Wide-Range Achievement Test-III (.72 ± .06, p = .002) as the top three measures that best discriminated the groups. These findings suggest that early memory test performance might serve a more clinically pivotal role in forecasting future cognitive course than is currently presumed. (JINS, 2014, 20, 1–12)

Type
Research Articles
Copyright
Copyright © The International Neuropsychological Society 2014 

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References

Alzheimer's Association. (2012). 2012 Alzheimer's disease facts and figures. Alzheimer's & Dementia, 8(2), 131168. doi:10.1016/j.jalz.2012.02.001 CrossRefGoogle ScholarPubMed
Benedict, R.H.B. (1997). Brief Visuospatial Memory Test-Revised. Odessa, FL: Psychological Assessment Resources, Inc.Google Scholar
Benton, A.L. (1994). Neuropsychological assessment. Annual Review of Psychology, 45, 123. doi:10.1146/annurev.ps.45.020194.000245 CrossRefGoogle ScholarPubMed
Benton, A.L., Hamsher, K., Sivan, A.B. (1976). Multilingual Aphasia Examination. Iowa City, IA: AJA Associates.Google Scholar
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. doi:10.1001/archneur.64.6.862 CrossRefGoogle ScholarPubMed
Buckner, R.L., Snyder, A.Z., Shannon, B.J., LaRossa, G., Sachs, R., Fotenos, A.F., Mintun, M.A. (2005). Molecular, structural, and functional characterization of Alzheimer's disease: Evidence for a relationship between default activity, amyloid, and memory. Journal of Neuroscience, 25(34), 77097717. doi:10.1523/JNEUROSCI.2177-05.2005 CrossRefGoogle ScholarPubMed
Cairns, N.J., Ikonomovic, M.D., Benzinger, T., Storandt, M., Fagan, A.M., Shah, A.R., Morris, J.C. (2009). Absence of Pittsburgh compound B detection of cerebral amyloid beta in a patient with clinical, cognitive, and cerebrospinal fluid markers of Alzheimer disease: A case report. Archives of Neurology, 66(12), 15571562. doi:10.1001/archneurol.2009.279 CrossRefGoogle Scholar
Chetelat, G. (2013). Alzheimer disease: Abeta-independent processes-rethinking preclinical AD. Nature Reviews Neurology, 9(3), 123124. doi:10.1038/nrneurol.2013.21 CrossRefGoogle Scholar
Chételat, G., La Joie, R., Villain, N., Perrotin, A., de La Sayette, V., Eustache, F., Vandenberghe, R. (2013). Amyloid imaging in cognitively normal individuals, at-risk populations and preclinical Alzheimer's disease. Neuroimage: Clinical, 2, 356365. doi:http://dx.doi.org/10.1016/j.nicl.2013.02.006 CrossRefGoogle Scholar
Christian, B.T., Vandehey, N.T., Floberg, J.M., Mistretta, C.A. (2010). Dynamic PET denoising with HYPR processing. Journal of Nuclear Medicine, 51(7), 11471154. doi:10.2967/jnumed.109.073999 CrossRefGoogle ScholarPubMed
Corder, E.H., Ghebremedhin, E., Taylor, M.G., Thal, D.R., Ohm, T.G., Braak, H. (2004). The biphasic relationship between regional brain senile plaque and neurofibrillary tangle distributions: Modification by age, sex, and APOE polymorphism. Annals of the New York Academy of Sciences, 1019, 2428. doi:10.1196/annals.1297.005 CrossRefGoogle ScholarPubMed
Desikan, R.S., McEvoy, L.K., Thompson, W.K., Holland, D., Brewer, J.B., Aisen, P.S., Dale, A.M. (2012). Amyloid-beta—associated clinical decline occurs only in the presence of elevated P-tau. Archives of Neurology, 69(6), 709713. doi:10.1001/archneurol.2011.3354 CrossRefGoogle ScholarPubMed
Drachman, D.A. (2006). Aging of the brain, entropy, and Alzheimer disease. Neurology, 67(8), 13401352. doi:10.1212/01.wnl.0000240127.89601.83 CrossRefGoogle ScholarPubMed
Elias, M.F., Beiser, A., Wolf, P.A., Au, R., White, R.F., D'Agostino, R.B. (2000). The preclinical phase of alzheimer disease: A 22-year prospective study of the Framingham Cohort. Archives of Neurology, 57(6), 808813.CrossRefGoogle Scholar
Ewers, M., Insel, P., Jagust, W.J., Shaw, L., Trojanowski, J.Q., Aisen, P., Weiner, M.W. (2012). CSF biomarker and PIB-PET-derived beta-amyloid signature predicts metabolic, gray matter, and cognitive changes in nondemented subjects. Cerebral Cortex, 22(9), 19932004. doi:10.1093/cercor/bhr271 CrossRefGoogle ScholarPubMed
Floberg, J.M., Mistretta, C.A., Weichert, J.P., Hall, L.T., Holden, J.E., Christian, B.T. (2012). Improved kinetic analysis of dynamic PET data with optimized HYPR-LR. Medical Physics, 39(6), 33193331. doi:10.1118/1.4718669 CrossRefGoogle ScholarPubMed
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, 189198.CrossRefGoogle ScholarPubMed
Heaton, R.K., Chelune, G.J., Talley, J.L., Kay, G.G., Curtiss, G. (1993). Wisconsin Card Sorting Test Manual. Odessa, FL: Psychological Assessment Resources, Inc.Google Scholar
Hedden, T., Oh, H., Younger, A.P., Patel, T.A. (2013). Meta-analysis of amyloid-cognition relations in cognitively normal older adults. Neurology, 80(14), 13411348. doi:10.1212/WNL.0b013e31828ab35d CrossRefGoogle Scholar
Huijbers, W., Vannini, P., Sperling, R.A., C.M.P., , Cabeza, R., Daselaar, S.M. (2012). Explaining the encoding/retrieval flip: Memory-related deactivations and activations in the posteromedial cortex. Neuropsychologia, 50(14), 37643774. doi:10.1016/j.neuropsychologia.2012.08.021 CrossRefGoogle ScholarPubMed
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. doi:10.1016/S1474-4422(12)70291-0 CrossRefGoogle ScholarPubMed
Jack, C.R. Jr., Knopman, D.S., Jagust, W.J., Shaw, L.M., Aisen, P.S., Weiner, M.W., Trojanowski, J.Q. (2010). Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurology, 9(1), 119128. doi:10.1016/S1474-4422(09)70299-6 CrossRefGoogle ScholarPubMed
Jack, C.R. Jr., Lowe, V.J., Weigand, S.D., Wiste, H.J., Senjem, M.L., Knopman, D.S., Petersen, R.C. (2009). Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: Implications for sequence of pathological events in Alzheimer's disease. Brain, 132(Pt 5), 13551365. doi:10.1093/brain/awp062 CrossRefGoogle ScholarPubMed
Jagust, W.J., Bandy, D., Chen, K., Foster, N.L., Landau, S.M., Mathis, C.A., Koeppe, R.A. (2010). The Alzheimer's Disease Neuroimaging Initiative positron emission tomography core. Alzheimer's & Dementia, 6(3), 221229. doi:10.1016/j.jalz.2010.03.003 CrossRefGoogle Scholar
Johnson, S.C., Schmitz, T.W., Moritz, C.H., Meyerand, M.E., Rowley, H.A., Alexander, A.L., Alexander, G.E. (2006). Activation of brain regions vulnerable to Alzheimer's disease: The effect of mild cognitive impairment. Neurobiology of Aging, 27(11), 16041612. doi:10.1016/j.neurobiolaging.2005.09.017 CrossRefGoogle ScholarPubMed
Kaplan, E., Goodglass, H., Weintraub, S. (1983). Boston Naming Test. Philadelphia: Lea & Febiger.Google Scholar
Kawas, C.H., Corrada, M.M., Brookmeyer, R., Morrison, A., Resnick, S.M., Zonderman, A.B., Arenberg, D. (2003). Visual memory predicts Alzheimer's disease more than a decade before diagnosis. Neurology, 60(7), 10891093.CrossRefGoogle ScholarPubMed
Landau, S.M., Harvey, D., Madison, C.M., Koeppe, R.A., Reiman, E.M., Foster, N.L., Jagust, W.J. (2011). Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiology of Aging, 32(7), 12071218. doi:10.1016/j.neurobiolaging.2009.07.002 CrossRefGoogle Scholar
Landau, S.M., Harvey, D., Madison, C.M., Reiman, E.M., Foster, N.L., Aisen, P.S., Jagust, W.J. (2010). Comparing predictors of conversion and decline in mild cognitive impairment. Neurology, 75(3), 230238. doi:10.1212/WNL.0b013e3181e8e8b8 CrossRefGoogle ScholarPubMed
Landau, S.M., Mintun, M.A., Joshi, A.D., Koeppe, R.A., Petersen, R.C., Aisen, P.S., Jagust, W.J. (2012). Amyloid deposition, hypometabolism, and longitudinal cognitive decline. Annals of Neurology, 72(4), 578586. doi:10.1002/ana.23650 CrossRefGoogle ScholarPubMed
Leech, R., Sharp, D.J. (2013). The role of the posterior cingulate cortex in cognition and disease. Brain. doi:10.1093/brain/awt162 Google ScholarPubMed
Lim, Y.Y., Ellis, K.A., Pietrzak, R.H., Ames, D., Darby, D., Harrington, K., Maruff, P. (2012). Stronger effect of amyloid load than APOE genotype on cognitive decline in healthy older adults. Neurology, 79(16), 16451652. doi:10.1212/WNL.0b013e31826e9ae6 CrossRefGoogle ScholarPubMed
Lo, R.Y., Hubbard, A.E., Shaw, L.M., Trojanowski, J.Q., Petersen, R.C., Aisen, P.S., Jagust, W.J. (2011). Longitudinal change of biomarkers in cognitive decline. Archives of Neurology, 68(10), 12571266. doi:10.1001/archneurol.2011.123 CrossRefGoogle ScholarPubMed
Maldjian, J.A., Laurienti, P.J., Kraft, R.A., Burdette, J.H. (2003). An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. Neuroimage, 19, 12331239. doi:S1053811903001691 [pii]CrossRefGoogle ScholarPubMed
Manly, J.J., Schupf, N., Tang, M.X., Stern, Y. (2005). Cognitive decline and literacy among ethnically diverse elders. Journal of Geriatric Psychiatry and Neurology, 18(4), 213217. doi:10.1177/0891988705281868 CrossRefGoogle Scholar
Morris, J.C. (1993). The Clinical Dementia Rating (CDR): Current version and scoring rules. Neurology, 43, 24122414.CrossRefGoogle Scholar
Morris, J.C., Roe, C.M., Grant, E.A., Head, D., Storandt, M., Goate, A.M., Mintun, M.A. (2009). Pittsburgh compound B imaging and prediction of progression from cognitive normality to symptomatic Alzheimer disease. Archives of Neurology, 66(12), 14691475. doi:10.1001/archneurol.2009.269 CrossRefGoogle Scholar
Mosconi, L., Mistur, R., Switalski, R., Brys, M., Glodzik, L., Rich, K., de Leon, M.J. (2009). Declining brain glucose metabolism in normal individuals with a maternal history of Alzheimer disease. Neurology, 72(6), 513520. doi:10.1212/01.wnl.0000333247.51383.43 CrossRefGoogle ScholarPubMed
O'Brien, J.L., O'Keefe, K.M., LaViolette, P.S., DeLuca, A.N., Blacker, D., Dickerson, B.C., Sperling, R.A. (2010). Longitudinal fMRI in elderly reveals loss of hippocampal activation with clinical decline. Neurology, 74(24), 19691976. doi:10.1212/WNL.0b013e3181e3966e CrossRefGoogle ScholarPubMed
Okonkwo, O.C., Xu, G., Dowling, N.M., Bendlin, B.B., Larue, A., Hermann, B.P., Johnson, S.C. (2012). Family history of Alzheimer disease predicts hippocampal atrophy in healthy middle-aged adults. Neurology, 78(22), 17691776. doi:10.1212/WNL.0b013e3182583047 CrossRefGoogle ScholarPubMed
Okonkwo, O.C., Xu, G., Oh, J.M., Dowling, N.M., Carlsson, C.M., Gallagher, C.L., Johnson, S.C. (2012). Cerebral blood flow is diminished in asymptomatic middle-aged adults with maternal history of Alzheimer's disease. Cerebral Cortex [Epub ahead of print].Google ScholarPubMed
Price, J.C., Klunk, W.E., Lopresti, B.J., Lu, X., Hoge, J.A., Ziolko, S.K., Mathis, C.A. (2005). Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B. Journal of Cerebral Blood Flow and Metabolism, 25(11), 15281547. doi:10.1038/sj.jcbfm.9600146 CrossRefGoogle ScholarPubMed
Rami, L., Sala-Llonch, R., Sole-Padulles, C., Fortea, J., Olives, J., Llado, A., Molinuevo, J.L. (2012). Distinct functional activity of the precuneus and posterior cingulate cortex during encoding in the preclinical stage of Alzheimer's disease. Journal of Alzheimer's Disease, 31(3), 517526. doi:10.3233/JAD-2012-120223 Google ScholarPubMed
Reitan, R., Wolfson, D. (1993). The Halstead-Reitan Neuropsychological Test Battery: Theory and clinical interpretation. Tucson: Neuropsychology Press.Google Scholar
Rentz, D.M., Locascio, J.J., Becker, J.A., Moran, E.K., Eng, E., Buckner, R.L., Johnson, K.A. (2010). Cognition, reserve, and amyloid deposition in normal aging. Annals of Neurology, 67(3), 353364. doi:10.1002/ana.21904 Google ScholarPubMed
Resnick, S.M., Sojkova, J., Zhou, Y., An, Y., Ye, W., Holt, D.P., Wong, D.F. (2010). Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [11C]PiB. Neurology, 74(10), 807815. doi:10.1212/WNL.0b013e3181d3e3e9 CrossRefGoogle Scholar
Sager, M.A., Hermann, B., La Rue, A. (2005). Middle-aged children of persons with Alzheimer's disease: APOE genotypes and cognitive function in the Wisconsin Registry for Alzheimer's Prevention. Journal of Geriatric Psychiatry and Neurology, 18(4), 245249. doi:10.1177/0891988705281882 CrossRefGoogle ScholarPubMed
Schmidt, M. (1996). Rey Auditory Verbal Learning Test: A handbook. Torrance, CA: Western Psychological Services.Google Scholar
Sheline, Y.I., Morris, J.C., Snyder, A.Z., Price, J.L., Yan, Z., D'Angelo, G., Mintun, M.A. (2010). APOE4 allele disrupts resting state fMRI connectivity in the absence of amyloid plaques or decreased CSF Abeta42. Journal of Neuroscience, 30(50), 1703517040. doi:10.1523/JNEUROSCI.3987-10.2010 CrossRefGoogle Scholar
Snitz, B.E., Weissfeld, L.A., Lopez, O.L., Kuller, L.H., Saxton, J., Singhabahu, D.M., Dekosky, S.T. (2013). Cognitive trajectories associated with beta-amyloid deposition in the oldest-old without dementia. Neurology, 80, 13781384. doi:10.1212/WNL.0b013e31828c2fc8 CrossRefGoogle ScholarPubMed
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. doi:10.1016/j.jalz.2011.03.003 CrossRefGoogle ScholarPubMed
Stern, Y. (2012). Cognitive reserve in ageing and Alzheimer's disease. Lancet Neurology, 11(11), 10061012. doi:10.1016/S1474-4422(12)70191-6 CrossRefGoogle ScholarPubMed
Strauss, E., Sherman, E.M.S., Spreen, O. (2006). A compendium of neuropsychological tests (3rd ed). Oxford: Oxford University Press.Google Scholar
Trenerry, M., Crosson, B., DeBoe, J., Leber, L. (1989). Stroop Neuropsychological Screening Test. Odessa, FL: Psychological Assessment Resources, Inc.Google Scholar
Vannini, P., O'Brien, J., O'Keefe, K., Pihlajamaki, M., Laviolette, P., Sperling, R.A. (2011). What goes down must come up: Role of the posteromedial cortices in encoding and retrieval. Cerebral Cortex, 21(1), 2234. doi:10.1093/cercor/bhq051 CrossRefGoogle Scholar
Villemagne, V.L., Burnham, S., Bourgeat, P., Brown, B., Ellis, K.A., Salvado, O., Masters, C.L. (2013). Amyloid beta deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: A prospective cohort study. Lancet Neurology, 12(4), 357367. doi:10.1016/S1474-4422(13)70044-9 CrossRefGoogle Scholar
Vina, J., Lloret, A. (2010). Why women have more Alzheimer's disease than men: Gender and mitochondrial toxicity of amyloid-beta peptide. Journal of Alzheimer's Disease, 20(Suppl 2), S527S533. doi:10.3233/JAD-2010-100501 CrossRefGoogle ScholarPubMed
Wechsler, D. (1987). Wechsler Memory Scale—Revised edition. San Antonio, TX: The Psychological Corporation.Google Scholar
Wechsler, D. (1997). WAIS-III: Wechsler Adult Intelligence Scale—3rd edition. San Antonio, TX: The Psychological Corporation.Google Scholar
Wechsler, D. (1999). Wechsler Abbreviated Scale of Intelligence. San Antonio, TX: The Psychological Corporation.Google Scholar
Wilkinson, G. (1993). Wide Range Achievement Test Administration Manual (3rd ed). Wilmington, Delaware: Wide Range Incorporated.Google Scholar
Wirth, M., Madison, C.M., Rabinovici, G.D., Oh, H., Landau, S.M., Jagust, W.J. (2013). Alzheimer's disease neurodegenerative biomarkers are associated with decreased cognitive function but not beta-amyloid in cognitively normal older individuals. Journal of Neuroscience, 33(13), 55535563. doi:10.1523/JNEUROSCI.4409-12.2013 CrossRefGoogle Scholar
Wirth, M., Oh, H., Mormino, E.C., Markley, C., Landau, S.M., Jagust, W.J. (2013). The effect of amyloid beta on cognitive decline is modulated by neural integrity in cognitively normal elderly. Alzheimer's & Dementia. doi:10.1016/j.jalz.2012.10.012 CrossRefGoogle ScholarPubMed
Xu, G., McLaren, D.G., Ries, M.L., Fitzgerald, M.E., Bendlin, B.B., Rowley, H.A., Johnson, S.C. (2009). The influence of parental history of Alzheimer's disease and apolipoprotein E epsilon4 on the BOLD signal during recognition memory. Brain, 132(Pt 2), 383391. doi:10.1093/brain/awn254 CrossRefGoogle ScholarPubMed
Zhou, X., Obuchowski, N., McClish, D. (2011). Statistical methods in diagnostic medicine (2nd ed). Hoboken, NJ: John Wiley & Sons, Inc.CrossRefGoogle Scholar
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Amyloid Burden, Neuronal Function, and Cognitive Decline in Middle-Aged Adults at Risk for Alzheimer's Disease
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