Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-23T04:20:28.220Z Has data issue: false hasContentIssue false

Cardiorespiratory Fitness Attenuates the Influence of Amyloid on Cognition

Published online by Cambridge University Press:  19 November 2015

Stephanie A. Schultz
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 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
Elizabeth A. Boots
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 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
Rodrigo P. Almeida
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 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 Fluminense Federal University, Niterói, RJ 24220Brazil
Jennifer M. Oh
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 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
Jean Einerson
Affiliation:
Division of Cardiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Claudia E. Korcarz
Affiliation:
Division of Cardiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Dorothy F. Edwards
Affiliation:
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 Department of Kinesiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Rebecca L. Koscik
Affiliation:
Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Maritza N. Dowling
Affiliation:
Department of Biostatistics & Medical Informatics, 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 Veterans Hospital, Madison, Wisconsin 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
Barbara B. Bendlin
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 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
Bradley T. Christian
Affiliation:
Wisconsin 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
Henrik Zetterberg
Affiliation:
Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden Institute of Neurology, University College, London, United Kingdom
Kaj Blennow
Affiliation:
Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
Cynthia M. Carlsson
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Sanjay Asthana
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Bruce P. Hermann
Affiliation:
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 Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Mark A. Sager
Affiliation:
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
Sterling C. Johnson
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 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
James H. Stein
Affiliation:
Division of Cardiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
Ozioma C. Okonkwo*
Affiliation:
Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 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
*
Correspondence and reprint requests to: Ozioma C. Okonkwo, Department of Medicine and Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792. E-mail: [email protected]

Abstract

The aim of this study was to examine cross-sectionally whether higher cardiorespiratory fitness (CRF) might favorably modify amyloid-β (Aβ)-related decrements in cognition in a cohort of late-middle-aged adults at risk for Alzheimer’s disease (AD). Sixty-nine enrollees in the Wisconsin Registry for Alzheimer’s Prevention participated in this study. They completed a comprehensive neuropsychological exam, underwent 11C Pittsburgh Compound B (PiB)-PET imaging, and performed a graded treadmill exercise test to volitional exhaustion. Peak oxygen consumption (VO2peak) during the exercise test was used as the index of CRF. Forty-five participants also underwent lumbar puncture for collection of cerebrospinal fluid (CSF) samples, from which Aβ42 was immunoassayed. Covariate-adjusted regression analyses were used to test whether the association between Aβ and cognition was modified by CRF. There were significant VO2peak*PiB-PET interactions for Immediate Memory (p=.041) and Verbal Learning & Memory (p=.025). There were also significant VO2peak*CSF Aβ42 interactions for Immediate Memory (p<.001) and Verbal Learning & Memory (p<.001). Specifically, in the context of high Aβ burden, that is, increased PiB-PET binding or reduced CSF Aβ42, individuals with higher CRF exhibited significantly better cognition compared with individuals with lower CRF. In a late-middle-aged, at-risk cohort, higher CRF is associated with a diminution of Aβ-related effects on cognition. These findings suggest that exercise might play an important role in the prevention of AD. (JINS, 2015, 21, 841–850)

Type
Research Article
Copyright
Copyright © The International Neuropsychological Society 2015 

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

ACSM (2012). American College of Sports Medicine. ACSM’s resource manual for guidelines for exercise testing and prescription (7th ed.). Philadelphia: Lippincott Williams and Wilkins.Google Scholar
ACSM (2014). ACSM’s Guidelines for Exercise Testing and Prescription (9th ed.). Philadelphia: Wolters Kluwer/ Lippincott Williams and Wilkins.Google Scholar
Balke, B., & Ware, R.W. (1959). An experimental study of physical fitness of Air Force personnel. United States Armed Forces Medical Journal, 10(6), 675688.Google ScholarPubMed
Barnes, D.E., Yaffe, K., Satariano, W.A., & Tager, I.B. (2003). A longitudinal study of cardiorespiratory fitness and cognitive function in healthy older adults. Journal of the American Geriatric Society, 51(4), 459465.CrossRefGoogle ScholarPubMed
Benton, A.L. (1994). Neuropsychological assessment. Annual Review of Psychology, 45, 123. doi:10.1146/annurev.ps.45.020194.000245 CrossRefGoogle ScholarPubMed
Billinger, S.A., Vidoni, E.D., Honea, R.A., & Burns, J.M. (2011). Cardiorespiratory response to exercise testing in individuals with Alzheimer’s disease. Archives of Physical Medicine and Rehabilitation, 92(12), 20002005. doi:10.1016/j.apmr.2011.07.194 CrossRefGoogle ScholarPubMed
Boots, E.A., Schultz, S.A., Oh, J.M., Larson, J., Edwards, D., Cook, D., & Okonkwo, O.C. (2014). Cardiorespiratory fitness is associated with brain structure, cognition, and mood in a middle-aged cohort at risk for Alzheimer’s disease. Brain Imaging and Behavior. doi:10.1007/s11682-014-9325-9 Google Scholar
Brown, B.M., Peiffer, J.J., Taddei, K., Lui, J.K., Laws, S.M., Gupta, V.B., & Martins, R.N. (2013). Physical activity and amyloid-beta plasma and brain levels: Results from the Australian Imaging, Biomarkers and Lifestyle Study of Ageing. Molecular Psychiatry, 18(8), 875881. doi:10.1038/mp.2012.107 CrossRefGoogle ScholarPubMed
Bugg, J.M., & Head, D. (2011). Exercise moderates age-related atrophy of the medial temporal lobe. Neurobiology of Aging, 32(3), 506514. doi:10.1016/j.neurobiolaging.2009.03.008 CrossRefGoogle ScholarPubMed
Degerman Gunnarsson, M., Lindau, M., Wall, A., Blennow, K., Darreh-Shori, T., Basu, S., & Kilander, L. (2010). Pittsburgh compound-B and Alzheimer’s disease biomarkers in CSF, plasma and urine: An exploratory study. Dementia and Geriatric Cognitive Disorders, 29(3), 204212. doi:10.1159/000281832 Google Scholar
Erickson, K.I., Voss, M.W., Prakash, R.S., Basak, C., Szabo, A., Chaddock, L., & Kramer, A.F. (2011). Exercise training increases size of hippocampus and improves memory. Proceedings of the National Academy of Sciences of the United States of America, 108(7), 30173022. doi:10.1073/pnas.1015950108 CrossRefGoogle ScholarPubMed
Fagan, A.M., Mintun, M.A., Mach, R.H., Lee, S.Y., Dence, C.S., Shah, A.R., & Holtzman, D.M. (2006). Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans. Annals of Neurology, 59(3), 512519. doi:10.1002/ana.20730 Google Scholar
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. doi:10.1001/archneur.64.3.noc60123 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 Google Scholar
Gidicsin, C.M., Maye, J.E., Locascio, J.J., Pepin, L.C., Philiossaint, M., Becker, J.A., & Johnson, K.A. (2015). Cognitive activity relates to cognitive performance but not to Alzheimer disease biomarkers. Neurology, 85, 4855. doi:10.1212/WNL.0000000000001704 CrossRefGoogle ScholarPubMed
Gustafson, D.R., Skoog, I., Rosengren, L., Zetterberg, H., & Blennow, K. (2007). Cerebrospinal fluid beta-amyloid 1-42 concentration may predict cognitive decline in older women. Journal of Neurology, Neurosurgery, and Psychiatry, 78(5), 461464. doi:10.1136/jnnp.2006.100529 Google Scholar
Hansson, O., Zetterberg, H., Buchhave, P., Londos, E., Blennow, K., & Minthon, L. (2006). Association between CSF biomarkers and incipient Alzheimer’s disease in patients with mild cognitive impairment: A follow-up study. Lancet Neurology, 5(3), 228234. doi:10.1016/S1474-4422(06)70355-6 Google Scholar
Head, D., Bugg, J.M., Goate, A.M., Fagan, A.M., Mintun, M.A., Benzinger, T., & Morris, J.C. (2012). Exercise engagement as a moderator of the effects of APOE genotype on amyloid deposition. Archives of Neurology, 69(5), 636643. doi:10.1001/archneurol.2011.845 Google Scholar
Hyman, B.T., Phelps, C.H., Beach, T.G., Bigio, E.H., Cairns, N.J., Carrillo, M.C., & Montine, T.J. (2012). National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease. Alzheimers & Dementia, 8(1), 113. doi:10.1016/j.jalz.2011.10.007 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 Google Scholar
Jagust, W.J., Landau, S.M., Shaw, L.M., Trojanowski, J.Q., Koeppe, R.A., & Reiman, E.M., Alzheimer’s Disease Neuroimaging Inititive (2009). Relationships between biomarkers in aging and dementia. Neurology, 73(15), 11931199. doi:10.1212/WNL.0b013e3181bc010c Google Scholar
Johnson, S.C., Christian, B.T., Okonkwo, O.C., Oh, J.M., Harding, S., Xu, G., & Sager, M.A. (2014). Amyloid burden and neural function in people at risk for Alzheimer’s Disease. Neurobiology of Aging, 35(3), 576584. doi:10.1016/j.neurobiolaging.2013.09.028 CrossRefGoogle ScholarPubMed
Kaplan, E., Goodglass, H., & Weintraub, S. (1983). Boston Naming Test. Philadelphia: Lea & Febiger.Google Scholar
Ke, H.C., Huang, H.J., Liang, K.C., & Hsieh-Li, H.M. (2011). Selective improvement of cognitive function in adult and aged APP/PS1 transgenic mice by continuous non-shock treadmill exercise. Brain Research, 1403, 111. doi:10.1016/j.brainres.2011.05.056 Google Scholar
Kim, B.K., Shin, M.S., Kim, C.J., Baek, S.B., Ko, Y.C., & Kim, Y.P. (2014). Treadmill exercise improves short-term memory by enhancing neurogenesis in amyloid beta-induced Alzheimer disease rats. Journal of Exercise Rehabilitation, 10(1), 28. doi:10.12965/jer.140086 Google Scholar
Koscik, R.L., La Rue, A., Jonaitis, E.M., Okonkwo, O.C., Johnson, S.C., Bendlin, B.B., & Sager, M.A. (2014). Emergence of mild cognitive impairment in late middle-aged adults in the wisconsin registry for Alzheimer’s prevention. Dementia and Geriatric Cognitive Disorders, 38(1-2), 1630. doi:10.1159/000355682 CrossRefGoogle ScholarPubMed
Landau, S.M., Lu, M., Joshi, A.D., Pontecorvo, M., Mintun, M.A., & Trojanowski, J.Q., Alzheimer’s Disease Neuroimaging Inititive (2013). Comparing positron emission tomography imaging and cerebrospinal fluid measurements of beta-amyloid. Annals of Neurology, 74(6), 826836. doi:10.1002/ana.23908 CrossRefGoogle ScholarPubMed
Lautenschlager, N.T., Cox, K.L., Flicker, L., Foster, J.K., van Bockxmeer, F.M., Xiao, J., & Almeida, O.P. (2008). Effect of physical activity on cognitive function in older adults at risk for Alzheimer disease: A randomized trial. Journal of the American Medical Association, 300(9), 10271037. doi:10.1001/jama.300.9.1027 CrossRefGoogle ScholarPubMed
Liang, K.Y., Mintun, M.A., Fagan, A.M., Goate, A.M., Bugg, J.M., Holtzman, D.M., & Head, D. (2010). Exercise and Alzheimer’s disease biomarkers in cognitively normal older adults. Annals of Neurology, 68(3), 311318. doi:10.1002/ana.22096 Google Scholar
Mattsson, N., Insel, P.S., Donohue, M., Landau, S., Jagust, W.J., Shaw, L.M., … Alzheimer’s Disease Neuroimaging Inititive. (2015). Independent information from cerebrospinal fluid amyloid-beta and florbetapir imaging in Alzheimer’s disease. Brain, 138(3), 772783. doi:10.1093/brain/awu367 Google 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 Google Scholar
Okonkwo, O.C., Schultz, S.A., Oh, J.M., Larson, J., Edwards, D., Cook, D., & Sager, M.A. (2014). Physical activity attenuates age-related biomarker alterations in preclinical AD. Neurology, 83(19), 17531760. doi:10.1212/WNL.0000000000000964 Google Scholar
Palmqvist, S., Zetterberg, H., Blennow, K., Vestberg, S., Andreasson, U., Brooks, D.J., & Hansson, O. (2014). Accuracy of brain amyloid detection in clinical practice using cerebrospinal fluid beta-amyloid 42: A cross-validation study against amyloid positron emission tomography. JAMA Neurology, 71(10), 12821289. doi:10.1001/jamaneurol.2014.1358 Google Scholar
Parachikova, A., Nichol, K.E., & Cotman, C.W. (2008). Short-term exercise in aged Tg2576 mice alters neuroinflammation and improves cognition. Neurobiology of Disease, 30(1), 121129. doi:10.1016/j.nbd.2007.12.008 Google Scholar
Pizzie, R., Hindman, H., Roe, C.M., Head, D., Grant, E., Morris, J.C., & Hassenstab, J.J. (2014). Physical activity and cognitive trajectories in cognitively normal adults: The adult children study. Alzheimer Disease and Associated Disorders, 28(1), 5057. doi:10.1097/WAD.0b013e31829628d4 Google Scholar
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
Reitan, R.M. (1958). Validity of the trail making test as an indicator of organic brain damage. Perceptual and Motor Skills, 8, 271276.CrossRefGoogle Scholar
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 Google Scholar
Roe, C.M., Fagan, A.M., Grant, E.A., Hassenstab, J., Moulder, K.L., Maue Dreyfus, D., & Morris, J.C. (2013). Amyloid imaging and CSF biomarkers in predicting cognitive impairment up to 7.5 years later. Neurology, 80(19), 17841791. doi:10.1212/WNL.0b013e3182918ca6 Google Scholar
Rosario, B.L., Weissfeld, L.A., Laymon, C.M., Mathis, C.A., Klunk, W.E., Berginc, M.D., & Price, J.C. (2011). Inter-rater reliability of manual and automated region-of-interest delineation for PiB PET. Neuroimage, 55(3), 933941. doi:10.1016/j.neuroimage.2010.12.070 Google 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 Google Scholar
Schmidt, M. (1996). Rey Auditory Verbal Learning Test: A Handbook. Torrance, CA: Western Psychological Services.Google Scholar
Skoog, I., Davidsson, P., Aevarsson, O., Vanderstichele, H., Vanmechelen, E., & Blennow, K. (2003). Cerebrospinal fluid beta-amyloid 42 is reduced before the onset of sporadic dementia: A population-based study in 85-year-olds. Dementia and Geriatric Cognitive Disorders, 15(3), 169176. doi:68478 Google Scholar
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. Alzheimers & Dementia, 7(3), 280292. doi:10.1016/j.jalz.2011.03.003 CrossRefGoogle ScholarPubMed
Tabachnick, B.G., & Fidell, L.S. (2007). Using multivariate statistics (5th ed.). Boston: Pearson/Allyn & Bacon.Google Scholar
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.Google Scholar
Tolboom, N., van der Flier, W.M., Yaqub, M., Boellaard, R., Verwey, N.A., Blankenstein, M.A., & van Berckel, B.N. (2009). Relationship of cerebrospinal fluid markers to 11C-PiB and 18F-FDDNP binding. Journal of Nuclear Medicine, 50(9), 14641470. doi:10.2967/jnumed.109.064360 Google Scholar
Trenerry, M., Crosson, B., DeBoe, J., & Leber, L. (1989). Stroop Neuropsychological Screening Test. Odessa, FL: Psychological Assessment Resources, Inc.Google Scholar
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., & Joliot, M. (2002). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage, 15(1), 273289. doi:10.1006/nimg.2001.0978 Google Scholar
Vemuri, P., Lesnick, T.G., Przybelski, S.A., Knopman, D.S., Roberts, R.O., Lowe, V.J., & Jack, C.R. Jr. (2012). Effect of lifestyle activities on Alzheimer disease biomarkers and cognition. Annals of Neurology, 72(5), 730738. doi:10.1002/ana.23665 Google Scholar
Villemagne, V.L., Pike, K.E., Chetelat, G., Ellis, K.A., Mulligan, R.S., Bourgeat, P., & Rowe, C.C. (2011). Longitudinal assessment of Abeta and cognition in aging and Alzheimer disease. Annals of Neurology, 69(1), 181192. doi:10.1002/ana.22248 Google Scholar
Wang, Q., Xu, Z., Tang, J., Sun, J., Gao, J., Wu, T., & Xiao, M. (2013). Voluntary exercise counteracts Abeta25–35-induced memory impairment in mice. Behaviour Brain Research, 256, 618625. doi:10.1016/j.bbr.2013.09.024 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: Wide Range Incorporated.Google Scholar
Zhu, N., Jacobs, D.R. Jr., Schreiner, P.J., Yaffe, K., Bryan, N., Launer, L.J., & Sternfeld, B. (2014). Cardiorespiratory fitness and cognitive function in middle age: The CARDIA study. Neurology, 82(15), 13391346. doi: 10.1212/WNL.0000000000000310 CrossRefGoogle ScholarPubMed