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Assessment of Demographic, Genetic, and Imaging Variables Associated With Brain Resilience and Cognitive Resilience to Pathological Tau in Patients With Alzheimer Disease
Open accessAbstract
Importance: Better understanding is needed of the degree to which individuals tolerate Alzheimer disease (AD)-like pathological tau with respect to brain structure (brain resilience) and cognition (cognitive resilience). Objective: To examine the demographic (age, sex, and educational level), genetic (APOE-ε4 status), and neuroimaging (white matter hyperintensities and cortical thickness) factors associated with interindividual differences in brain and cognitive resilience to tau positron emission tomography (PET) load and to changes in global cognition over time. Design, Setting, an Participants: In this cross-sectional, longitudinal study, tau PET was performed from June 1, 2014, to November 30, 2017, and global cognition monitored for a mean [SD] interval of 2.0 [1.8] years at 3 dementia centers in South Korea, Sweden, and the United States. The study included amyloid-β-positive participants with mild cognitive impairment or AD dementia. Data analysis was performed from October 26, 2018, to December 11, 2019. Exposures: Standard dementia screening, cognitive testing, brain magnetic resonance imaging, amyloid-β PET and cerebrospinal fluid analysis, and flortaucipir (tau) labeled with fluor-18 (18F) PET. Main Outcomes and Measures: Separate linear regression models were performed between whole cortex [18F]flortaucipir uptake and cortical thickness, and standardized residuals were used to obtain a measure of brain resilience. The same procedure was performed for whole cortex [18F]flortaucipir uptake vs Mini-Mental State Examination (MMSE) as a measure of cognitive resilience. Bivariate and multivariable linear regression models were conducted with age, sex, educational level, APOE-ε4 status, white matter hyperintensity volumes, and cortical thickness as independent variables and brain and cognitive resilience measures as dependent variables. Linear mixed models were performed to examine whether changes in MMSE scores over time differed as a function of a combined brain and cognitive resilience variable. Results: A total of 260 participants (145 [55.8%] female; mean [SD] age, 69.2 [9.5] years; mean [SD] MMSE score, 21.9 [5.5]) were included in the study. In multivariable models, women (standardized β = -0.15, P = .02) and young patients (standardized β = -0.20, P = .006) had greater brain resilience to pathological tau. Higher educational level (standardized β = 0.23, P < .001) and global cortical thickness (standardized β = 0.23, P < .001) were associated with greater cognitive resilience to pathological tau. Linear mixed models indicated a significant interaction of brain resilience × cognitive resilience × time on MMSE (β [SE] = -0.235 [0.111], P = .03), with steepest slopes for individuals with both low brain and cognitive resilience. Conclusions and Relevance: Results of this study suggest that women and young patients with AD have relative preservation of brain structure when exposed to neocortical pathological tau. Interindividual differences in resilience to pathological tau may be important to disease progression because participants with both low brain and cognitive resilience had the most rapid cognitive decline over time.
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“50–60% of Alzheimer’s-type dementia (dementia defined clinically as Alzheimer’s disease) is estimated to be attributable to these copathologies.40,42–45”
From Clinical diagnosis of Alzheimer’s disease: Recommendations of the International Working Group (2021) · cites this paper as [43]
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“Alzheimer’s disease can be associated with other brain pathologies, including α-synucleinopathy,56 vascular pathology, non-Alzheimer’s disease tauopathies, and TDP-43 pathology.40,42–44”
From Clinical diagnosis of Alzheimer’s disease: Recommendations of the International Working Group (2021) · cites this paper as [43]
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von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040296 · Cited by 23,020
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2007) · The Lancet · doi:10.1016/s0140-6736(07)61602-x · Cited by 21,320
McKhann, G. M., Knopman, D. S., Chertkow, H., Hyman, B. T., Jack, C. R., Kawas, C. H., Klunk, W. E., Koroshetz, W. J., Manly, J. J., Mayeux, R., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.005 · Cited by 18,657
Albert, M. S., DeKosky, S. T., Dickson, D., Dubois, B., Feldman, H. H., Fox, N. C., Gamst, A., Holtzman, D. M., Jagust, W. J., Petersen, R. C., et al. (2011) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2011.03.008 · Cited by 10,152
Cognitive reserve in ageing and Alzheimer's disease
Stern, Y. (2012) · The Lancet Neurology · doi:10.1016/s1474-4422(12)70191-6 · Cited by 3,557
Nelson, P. T., Alafuzoff, I., Bigio, E. H., Bouras, C., Braak, H., Cairns, N. J., Castellani, R. J., Crain, B. J., Davies, P., Tredici, K. D., et al. (2012) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/nen.0b013e31825018f7 · Cited by 2,050 · cited 1×
“Disorder Clinic of Gangnam Severance Hospital, 12 [4] in the BioFINDER study, and 17 [3] in UCSF).”
BackgroundUnderstanding the odd science of aging
Kirkwood, T. B. L. (2005) · Cell · doi:10.1016/j.cell.2005.01.027 · Cited by 1,984
Whitepaper: Defining and investigating cognitive reserve, brain reserve, and brain maintenance
Stern, Y., Arenaza‐Urquijo, E. M., Bartrés‐Faz, D., Belleville, S., Cantilon, M., Chetelat, G., Ewers, M., Franzmeier, N., Kempermann, G., Kremen, W. S., et al. (2020) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2018.07.219 · Cited by 1,703
Distinct patterns of brain activity in young carriers of the APOE -ε4 allele
Filippini, N., MacIntosh, B. J., Hough, M. G., Goodwin, G. M., Frisoni, G. B., Smith, S. M., Matthews, P. M., Beckmann, C. F., & Mackay, C. E. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811879106 · Cited by 1,613
Prevalence of Cerebral Amyloid Pathology in Persons Without Dementia: A Meta-analysis
Jansen, W. J., Ossenkoppele, R., Knol, D. L., Tijms, B. M., Scheltens, P., Verhey, F. R. J., Visser, P. J., Aalten, P., Aarsland, D., Alcolea, D., et al. (2015) · JAMA · doi:10.1001/jama.2015.4668 · Cited by 1,610
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Ossenkoppele, R., Smith, R., Mattsson-Carlgren, N., Groot, C., Leuzy, A., Strandberg, O., Palmqvist, S., Olsson, T., Jögi, J., Stormrud, E., et al. (2021) · JAMA Neurology · doi:10.1001/jamaneurol.2021.1858 · Cited by 311
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Arenaza‐Urquijo, E. M., Boyle, R., Casaletto, K., Anstey, K. J., Vila‐Castelar, C., Colverson, A., Palpatzis, E., Eissman, J. M., Kheng Siang Ng, T., Raghavan, S., et al. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.13844 · Cited by 223
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Therriault, J., Schindler, S. E., Salvadó, G., Pascoal, T. A., Benedet, A. L., Ashton, N. J., Karikari, T. K., Apostolova, L. G., Murray, M. E., Verberk, I. M. W., et al. (2024) · Nature Reviews Neurology · doi:10.1038/s41582-024-00942-2 · Cited by 225
Metadata
- Authors
- Ossenkoppele, R., Lyoo, C. H., Jester-Broms, J., Sudre, C. H., Cho, H., Ryu, Y. H., Choi, J. Y., Smith, R., Strandberg, O., Palmqvist, S., Kramer, J., Boxer, A. L., Gorno-Tempini, M. L., Miller, B. L., La Joie, R., Rabinovici, G. D., & Hansson, O.
- Affiliations
- Lund University (SE)
- Yonsei University (KR)
- King's College London (GB)
- UCL Queen Square Institute of Neurology (GB)
- University of California, San Francisco (US)
- Memory and Aging Center, Department of Neurology, University of California, San Francisco
- Lawrence Berkeley National Laboratory (US)
- Corresponding author
- Ossenkoppele, Rik
- Hansson, Oskar
- ORCID
- Venue
- JAMA Neurology
- Publisher
- American Medical Association (AMA)
- Published
- 2020-05-01
- Volume
- 77
- Issue
- 5
- Pages
- 632
- ISSN
- 2168-6149 (ISSN-L)
- PMC
- PMC7042808
- OpenAlex
- W3007734058
- Cited by
- 161
- References
- 63
- Citations by year
- 2026: 34 · 2025: 28 · 2024: 18 · 2023: 20 · 2022: 28 · 2021: 21 · 2020: 12
- FWCI
- 14.77
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- JAMA Neurology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
- Pure Amsterdam UMC (acceptedVersion, cc-by)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- YUHSpace (Yonsei University Medical Library) (submittedVersion, cc-by-nc-nd)
- Lund University Publications (Lund University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Alzheimer's Association (AARF-16-443577)
- Korea Health Industry Development Institute
- National Research Foundation of Korea
- Knut och Alice Wallenbergs Stiftelse
- Vetenskapsrådet
- Marcus och Amalia Wallenbergs minnesfond
- National Institute on Aging (R01AG045611, R01AG038791, U01AG052943, P01AG019724, P30AG062422, P50AG023501)
- National Institute on Deafness and Other Communication Disorders (K24DC015544)
- National Institute of Neurological Disorders and Stroke (R01NS100440, R56NS050915, U54NS092089, R01NS050915)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Oncology › Cancer-related cognitive impairment studies
- Keywords
- brain resilience, cognitive resilience, Alzheimer's disease, pathological tau, tau PET, flortaucipir, APOE ε4, white matter hyperintensities, cortical thickness, amyloid-beta, mild cognitive impairment, dementia, sex differences, interindividual variability, cognitive decline, genetic risk factors, neuroimaging biomarkers, longitudinal cognitive change
- MeSH terms
- Positron Emission Tomography Computed Tomography, Age Factors, Aged, Alzheimer Disease, Brain, Cognition, Cross-Sectional Studies, Female, Humans, Image Interpretation, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Male, Risk Factors, Sex Characteristics, tau Proteins, Disease Progression, Cognitive Reserve, Neuroimaging
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