Abstract
Imaging markers of cerebrovascular disease and Alzheimer’s disease (AD) are implicated in mobility impairment in older adults, but few studies have examined these relationships longitudinally in a racially-diverse population-based sample. At Visit 5 (2011–13) of the ARIC Study, 1859 participants had usual pace gait speed (cm/s) assessed and brain MRI (mean age = 76.3, 28.5% Black) and PET (n = 343; mean age = 75.9, 42.6% Black) measures including total/regional brain volume (cm3), white matter hyperintensities (WMH; cm3), infarcts (present/absent), microbleeds (count) and global beta-amyloid (Aβ). Participants returned at Visit 6 (n = 1264, 2016–17) and Visit 7 (n = 1108, 2018–19) for follow-up gait speed assessments. We used linear regression to estimate effects of baseline infarct presence, higher microbleed count, and a one interquartile range (IQR) poorer measures of continuous predictors (−1 IQR total brain volume, temporal-parietal lobe meta region of interest(ROI); +1 IQR WMH volume, global Aβ SUVR) on cross-sectional gait speed and change in gait speed adjusting for age, sex, education, study site, APOE e4, estimated intracranial volume, BMI, and cardiovascular risk factors. Cross-sectionally, slower gait speed outcome was associated with higher WMH volume, −3.38 cm/s (95%CI:-4.71, −2.04), infarct presence, −5.60 cm/s (−7.69, −3.51), microbleed count, −2.20 cm/s (−3.20, −0.91), smaller total brain volume, −9.26 cm/s (−12.1, −6.43), and smaller temporal-parietal lobe ROI -6.28 cm/s (−8.28, −4.28). Longitudinally, faster gait speed outcome decline was associated with higher WMH volume, −0.27 cm/s/year, (−0.51, −0.03) and higher global Aβ SUVR, −0.62 cm/s/year (−1.20, −0.03). Both cerebrovascular and AD pathology may contribute to mobility decline commonly seen with aging.
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References
Ambrose, A. F., Paul, G., & Hausdorff, J. M. (2013). Risk factors for falls among older adults: A review of the literature. Maturitas, 75(1), 51–61. https://doi.org/10.1016/j.maturitas.2013.02.009.
Buracchio, T., Dodge, H. H., Howieson, D., Wasserman, D., & Kaye, J. (2010). The trajectory of gait speed preceding mild cognitive impairment. Archives of Neurology, 67(8), 980–986. https://doi.org/10.1001/archneurol.2010.159.
Callisaya, M. L., Beare, R., Phan, T. G., Blizzard, L., Thrift, A. G., Chen, J., & Srikanth, V. K. (2013). Brain structural change and gait decline: A longitudinal population-based study. Journal of the American Geriatrics Society, 61(7), 1074–1079. https://doi.org/10.1111/jgs.12331.
Camicioli, R., Moore, M. M., Sexton, G., Howieson, D. B., & Kaye, J. A. (1999). Age-related brain changes associated with motor function in healthy older people. Journal of the American Geriatrics Society, 47(3), 330–334. https://doi.org/10.1111/j.1532-5415.1999.tb02997.x.
Davis, J. C., Bryan, S., Best, J. R., Li, L. C., Hsu, C. L., Gomez, C., Vertes, K. A., & Liu-Ambrose, T. (2015). Mobility predicts change in older adults' health-related quality of life: Evidence from a Vancouver falls prevention prospective cohort study. Health and Quality of Life Outcomes, 13, 101. https://doi.org/10.1186/s12955-015-0299-0.
de Laat, K. F., van Norden, A. G., Gons, R. A., van Oudheusden, L. J., van Uden, I. W., Bloem, B. R., et al. (2010). Gait in elderly with cerebral small vessel disease. Stroke, 41(8), 1652–1658. https://doi.org/10.1161/STROKEAHA.110.583229.
DeCarli, C., Miller, B. L., Swan, G. E., Reed, T., Wolf, P. A., Garner, J., Jack, L., & Carmelli, D. (1999). Predictors of brain morphology for the men of the NHLBI twin study. Stroke, 30(3), 529–536. https://doi.org/10.1161/01.str.30.3.529.
Del Campo, N., Payoux, P., Djilali, A., Delrieu, J., Hoogendijk, E. O., Rolland, Y., et al. (2016). Relationship of regional brain beta-amyloid to gait speed. Neurology, 86(1), 36–43. https://doi.org/10.1212/WNL.0000000000002235.
Demirovic, J., Prineas, R., Loewenstein, D., Bean, J., Duara, R., Sevush, S., & Szapocznik, J. (2003). Prevalence of dementia in three ethnic groups: The South Florida program on aging and health. Annals of Epidemiology, 13(6), 472–478. https://doi.org/10.1016/s1047-2797(02)00437-4.
Ganguli, M., Albanese, E., Seshadri, S., Bennett, D. A., Lyketsos, C., Kukull, W. A., Skoog, I., & Hendrie, H. C. (2018). Population neuroscience: Dementia epidemiology serving precision medicine and population Health. Alzheimer Disease and Associated Disorders, 32(1), 1–9. https://doi.org/10.1097/WAD.0000000000000237.
Gottesman, R. F., Rawlings, A. M., Sharrett, A. R., Albert, M., Alonso, A., Bandeen-Roche, K., Coker, L. H., Coresh, J., Couper, D. J., Griswold, M. E., Heiss, G., Knopman, D. S., Patel, M. D., Penman, A. D., Power, M. C., Selnes, O. A., Schneider, A. L. C., Wagenknecht, L. E., Windham, B. G., Wruck, L. M., & Mosley, T. H. (2014). Impact of differential attrition on the association of education with cognitive change over 20 years of follow-up: The ARIC neurocognitive study. American Journal of Epidemiology, 179(8), 956–966. https://doi.org/10.1093/aje/kwu020.
Gottesman, R. F., Schneider, A. L., Zhou, Y., Chen, X., Green, E., Gupta, N., et al. (2016). The ARIC-PET amyloid imaging study: Brain amyloid differences by age, race, sex, and APOE. Neurology, 87(5), 473–480. https://doi.org/10.1212/WNL.0000000000002914.
Guralnik, J. M., Ferrucci, L., Simonsick, E. M., Salive, M. E., & Wallace, R. B. (1995). Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. The New England Journal of Medicine, 332(9), 556–561. https://doi.org/10.1056/NEJM199503023320902.
Ince, P. G., Minett, T., Forster, G., Brayne, C., Wharton, S. B., Medical Research Council Cognitive, F, & Ageing Neuropathology, S. (2017). Microinfarcts in an older population-representative brain donor cohort (MRC CFAS): Prevalence, relation to dementia and mobility, and implications for the evaluation of cerebral small vessel Disease. Neuropathology and Applied Neurobiology, 43(5), 409–418. https://doi.org/10.1111/nan.12363.
Knopman, D. S., Penman, A. D., Catellier, D. J., Coker, L. H., Shibata, D. K., Sharrett, A. R., & Mosley Jr., T. H. (2011). Vascular risk factors and longitudinal changes on brain MRI: The ARIC study. Neurology, 76(22), 1879–1885. https://doi.org/10.1212/WNL.0b013e31821d753f.
Knopman, D. S., Griswold, M. E., Lirette, S. T., Gottesman, R. F., Kantarci, K., Sharrett, A. R., et al. (2015). Vascular imaging abnormalities and cognition: Mediation by cortical volume in nondemented individuals: Atherosclerosis risk in communities-neurocognitive study. Stroke, 46(2), 433–440. https://doi.org/10.1161/STROKEAHA.114.007847.
Knopman, D. S., Gottesman, R. F., Sharrett, A. R., Wruck, L. M., Windham, B. G., Coker, L., Schneider, A. L. C., Hengrui, S., Alonso, A., Coresh, J., Albert, M. S., & Mosley Jr., T. H. (2016). Mild cognitive impairment and dementia prevalence: The atherosclerosis risk in communities neurocognitive study (ARIC-NCS). Alzheimers Dement (Amst), 2, 1–11. https://doi.org/10.1016/j.dadm.2015.12.002.
Kurian, A. K., & Cardarelli, K. M. (2007). Racial and ethnic differences in cardiovascular disease risk factors: A systematic review. Ethnicity & Disease, 17(1), 143–152.
La Grow, S., Yeung, P., Towers, A., Alpass, F., & Stephens, C. (2013). The impact of mobility on quality of life among older persons. Journal of Aging and Health, 25(5), 723–736. https://doi.org/10.1177/0898264313490198.
Macpherson, H., Teo, W. P., Schneider, L. A., & Smith, A. E. (2017). A life-long approach to physical activity for brain Health. Frontiers in Aging Neuroscience, 9, 147. https://doi.org/10.3389/fnagi.2017.00147.
Nadkarni, N. K., Nunley, K. A., Aizenstein, H., Harris, T. B., Yaffe, K., Satterfield, S., et al. (2014). Association between cerebellar gray matter volumes, gait speed, and information-processing ability in older adults enrolled in the Health ABC study. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 69(8), 996–1003. https://doi.org/10.1093/gerona/glt151.
Nadkarni, N. K., Perera, S., Snitz, B. E., Mathis, C. A., Price, J., Williamson, J. D., DeKosky, S. T., Klunk, W. E., & Lopez, O. L. (2017). Association of Brain Amyloid-beta with Slow Gait in elderly individuals without dementia: Influence of cognition and Apolipoprotein E epsilon4 genotype. JAMA Neurology, 74(1), 82–90. https://doi.org/10.1001/jamaneurol.2016.3474.
Odden, M. C., Peralta, C. A., Berlowitz, D. R., Johnson, K. C., Whittle, J., Kitzman, D. W., et al. (2017). Effect of intensive blood pressure control on gait speed and mobility limitation in adults 75 years or older: A randomized clinical trial. JAMA Internal Medicine, 177(4), 500–507. https://doi.org/10.1001/jamainternmed.2016.9104.
Okoro, C. A., Hollis, N. D., Cyrus, A. C., & Griffin-Blake, S. (2018). Prevalence of disabilities and Health care access by disability status and type among adults - United States, 2016. MMWR. Morbidity and Mortality Weekly Report, 67(32), 882–887. https://doi.org/10.15585/mmwr.mm6732a3.
Perera, S., Mody, S. H., Woodman, R. C., & Studenski, S. A. (2006). Meaningful change and responsiveness in common physical performance measures in older adults. Journal of the American Geriatrics Society, 54(5), 743–749. https://doi.org/10.1111/j.1532-5415.2006.00701.x.
Peters, R. (2006). Ageing and the brain. Postgraduate Medical Journal, 82(964), 84–88. https://doi.org/10.1136/pgmj.2005.036665.
Pinter, D., Ritchie, S. J., Doubal, F., Gattringer, T., Morris, Z., Bastin, M. E., del C. Valdés Hernández, M., Royle, N. A., Corley, J., Muñoz Maniega, S., Pattie, A., Dickie, D. A., Staals, J., Gow, A. J., Starr, J. M., Deary, I. J., Enzinger, C., Fazekas, F., & Wardlaw, J. (2017). Impact of small vessel disease in the brain on gait and balance. Scientific Reports, 7, 41637. https://doi.org/10.1038/srep41637.
Pruzin, J. J., Nelson, P. T., Abner, E. L., & Arvanitakis, Z. (2018). Review: Relationship of type 2 diabetes to human brain pathology. Neuropathology and Applied Neurobiology, 44(4), 347–362. https://doi.org/10.1111/nan.12476.
Qiao, Y., Suri, F. K., Zhang, Y., Liu, L., Gottesman, R., Alonso, A., Guallar, E., & Wasserman, B. A. (2017). Racial differences in prevalence and risk for intracranial atherosclerosis in a US Community-based population. JAMA Cardiology, 2(12), 1341–1348. https://doi.org/10.1001/jamacardio.2017.4041.
Rosano, C., Kuller, L. H., Chung, H., Arnold, A. M., Longstreth Jr., W. T., & Newman, A. B. (2005). Subclinical brain magnetic resonance imaging abnormalities predict physical functional decline in high-functioning older adults. Journal of the American Geriatrics Society, 53(4), 649–654. https://doi.org/10.1111/j.1532-5415.2005.53214.x.
Rosano, C., Brach, J., Studenski, S., Longstreth Jr., W. T., & Newman, A. B. (2007). Gait variability is associated with subclinical brain vascular abnormalities in high-functioning older adults. Neuroepidemiology, 29(3–4), 193–200. https://doi.org/10.1159/000111582.
Rosano, C., Studenski, S. A., Aizenstein, H. J., Boudreau, R. M., Longstreth Jr., W. T., & Newman, A. B. (2012). Slower gait, slower information processing and smaller prefrontal area in older adults. Age and Ageing, 41(1), 58–64. https://doi.org/10.1093/ageing/afr113.
Rosso, A. L., Studenski, S. A., Chen, W. G., Aizenstein, H. J., Alexander, N. B., Bennett, D. A., Black, S. E., Camicioli, R., Carlson, M. C., Ferrucci, L., Guralnik, J. M., Hausdorff, J. M., Kaye, J., Launer, L. J., Lipsitz, L. A., Verghese, J., & Rosano, C. (2013). Aging, the central nervous system, and mobility. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 68(11), 1379–1386. https://doi.org/10.1093/gerona/glt089.
Savica, R., Wennberg, A. M., Hagen, C., Edwards, K., Roberts, R. O., Hollman, J. H., et al. (2017). Comparison of gait parameters for predicting cognitive decline: The Mayo Clinic study of aging. Journal of Alzheimer's Disease, 55(2), 559–567. https://doi.org/10.3233/JAD-160697.
Scherder, E., Eggermont, L., Swaab, D., van Heuvelen, M., Kamsma, Y., de Greef, M., van Wijck, R., & Mulder, T. (2007). Gait in ageing and associated dementias; its relationship with cognition. Neuroscience and Biobehavioral Reviews, 31(4), 485–497. https://doi.org/10.1016/j.neubiorev.2006.11.007.
Schneider, A. L. C., Selvin, E., Sharrett, A. R., Griswold, M., Coresh, J., Jack Jr., C. R., Knopman, D., Mosley, T., & Gottesman, R. F. (2017). Diabetes, Prediabetes, and brain volumes and subclinical cerebrovascular Disease on MRI: The atherosclerosis risk in communities neurocognitive study (ARIC-NCS). Diabetes Care, 40(11), 1514–1521. https://doi.org/10.2337/dc17-1185.
Schwarz, C. G., Gunter, J. L., Wiste, H. J., Przybelski, S. A., Weigand, S. D., Ward, C. P., et al. (2016). A large-scale comparison of cortical thickness and volume methods for measuring Alzheimer's disease severity. Neuroimage Clin, 11, 802–812. https://doi.org/10.1016/j.nicl.2016.05.017.
Smith, E. E., O'Donnell, M., Dagenais, G., Lear, S. A., Wielgosz, A., Sharma, M., et al. (2015). Early cerebral small vessel disease and brain volume, cognition, and gait. Annals of Neurology, 77(2), 251–261. https://doi.org/10.1002/ana.24320.
Sorond, F. A., Cruz-Almeida, Y., Clark, D. J., Viswanathan, A., Scherzer, C. R., De Jager, P., et al. (2015). Aging, the central nervous system, and mobility in older adults: Neural mechanisms of mobility impairment. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 70(12), 1526–1532. https://doi.org/10.1093/gerona/glv130.
Studenski, S., Perera, S., Patel, K., Rosano, C., Faulkner, K., Inzitari, M., Brach, J., Chandler, J., Cawthon, P., Connor, E. B., Nevitt, M., Visser, M., Kritchevsky, S., Badinelli, S., Harris, T., Newman, A. B., Cauley, J., Ferrucci, L., & Guralnik, J. (2011). Gait speed and survival in older adults. JAMA, 305(1), 50–58. https://doi.org/10.1001/jama.2010.1923.
Suttanon, P., Hill, K. D., Said, C. M., Logiudice, D., Lautenschlager, N. T., & Dodd, K. J. (2012). Balance and mobility dysfunction and falls risk in older people with mild to moderate Alzheimer disease. American Journal of Physical Medicine & Rehabilitation, 91(1), 12–23. https://doi.org/10.1097/PHM.0b013e31823caeea.
The SPRINT MIND Investigators for the SPRINT Research Group. (2019). Association of Intensive vs standard blood pressure control with cerebral White matter lesions. JAMA, 322(6), 524–534. https://doi.org/10.1001/jama.2019.10551.
Tian, Q., Resnick, S. M., Bilgel, M., Wong, D. F., Ferrucci, L., & Studenski, S. A. (2017). Beta-amyloid burden predicts lower extremity performance decline in cognitively unimpaired older adults. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 72(5), 716–723. https://doi.org/10.1093/gerona/glw183.
Welmer, A. K., Angleman, S., Rydwik, E., Fratiglioni, L., & Qiu, C. (2013). Association of cardiovascular burden with mobility limitation among elderly people: A population-based study. PLoS One, 8(5), e65815. https://doi.org/10.1371/journal.pone.0065815.
Wennberg, A. M. V., Savica, R., Hagen, C. E., Roberts, R. O., Knopman, D. S., Hollman, J. H., Vemuri, P., Jack Jr., C. R., Petersen, R. C., & Mielke, M. M. (2017). Cerebral amyloid deposition is associated with gait parameters in the Mayo Clinic study of aging. Journal of the American Geriatrics Society, 65(4), 792–799. https://doi.org/10.1111/jgs.14670.
Wennberg, A. M. V., Lesnick, T. G., Schwarz, C. G., Savica, R., Hagen, C. E., Roberts, R. O., Knopman, D. S., Hollman, J. H., Vemuri, P., Jack Jr., C. R., Petersen, R. C., & Mielke, M. M. (2018). Longitudinal association between brain amyloid-Beta and Gait in the Mayo Clinic study of aging. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 73(9), 1244–1250. https://doi.org/10.1093/gerona/glx240.
White, D. K., Neogi, T., Nevitt, M. C., Peloquin, C. E., Zhu, Y., Boudreau, R. M., Cauley, J. A., Ferrucci, L., Harris, T. B., Satterfield, S. M., Simonsick, E. M., Strotmeyer, E. S., & Zhang, Y. (2013). Trajectories of gait speed predict mortality in well-functioning older adults: The Health, aging and body composition study. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 68(4), 456–464. https://doi.org/10.1093/gerona/gls197.
Windham, B. G., Griswold, M. E., Wang, W., Kucharska-Newton, A., Demerath, E. W., Gabriel, K. P., Pompeii, L. A., Butler, K., Wagenknecht, L., Kritchevsky, S., & Mosley Jr., T. H. (2017a). The importance of mid-to-late-life body mass index trajectories on late-life gait speed. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 72(8), 1130–1136. https://doi.org/10.1093/gerona/glw200.
Windham, B. G., Harrison, K. L., Lirette, S. T., Lutsey, P. L., Pompeii, L. A., Gabriel, K. P., Koton, S., Steffen, L. M., Griswold, M. E., & Mosley Jr., T. H. (2017b). Relationship between midlife cardiovascular Health and late-life physical performance: The ARIC study. Journal of the American Geriatrics Society, 65(5), 1012–1018. https://doi.org/10.1111/jgs.14732.
Windham, B. G., Lirette, S. T., Fornage, M., Benjamin, E. J., Parker, K. G., Turner, S. T., Jack Jr., C. R., Griswold, M. E., & Mosley, T. H. (2017c). Associations of brain structure with adiposity and changes in adiposity in a middle-aged and older biracial population. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 72(6), 825–831. https://doi.org/10.1093/gerona/glw239.
Zheng, J. J., Delbaere, K., Close, J. C., Sachdev, P. S., & Lord, S. R. (2011). Impact of white matter lesions on physical functioning and fall risk in older people: A systematic review. Stroke, 42(7), 2086–2090. https://doi.org/10.1161/STROKEAHA.110.610360.
Acknowledgements
The authors thank the staff and participants of the ARIC study for their important contributions. Author contributions included study conceptualization and manuscript authorship (KJS, BGW, MEG, and THM), data analysis (RR, DS, and MEG), and critical revision of the manuscript for intellectual content (BRN, TMH, CEH, SNL, DFW, CRJ, and RFG).
Funding
The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under Contract nos. (HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, HHSN268201700004I). Neurocognitive data and imaging data is collected by U01 2U01HL096812, 2U01HL096814, 2U01HL096899, 2U01HL096902, 2U01HL096917, from the NIH (NHLBI, NINDS, NIA and NIDCD) and R01 AG040282 and K24 AG052573 from the NIA. Avid Radiopharmaceuticals provided the florbetapir isotope for the ARIC-PET study but had no role in study design or interpretation.
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Dr. Wong reports non-monetary assistance from Avid and Eli Lilly on NIH grants. Dr. Jack serves on an independent data monitoring board for Roche, has served as a speaker for Eisai, and consulted for Biogen, but he receives no personal compensation from any commercial entity. He receives research support from NIH and the Alexander Family Alzheimer’s Disease Research Professorship of the Mayo Clinic. Dr. Gottesman recently served as the Associate Editor for the journal Neurology. All other authors have no conflicts of interest to disclose.
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Sullivan, K.J., Ranadive, R., Su, D. et al. Imaging-based indices of Neuropathology and gait speed decline in older adults: the atherosclerosis risk in communities study. Brain Imaging and Behavior 15, 2387–2396 (2021). https://doi.org/10.1007/s11682-020-00435-y
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DOI: https://doi.org/10.1007/s11682-020-00435-y