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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

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dc.contributor.author류철형-
dc.contributor.author유영훈-
dc.contributor.author최재용-
dc.date.accessioned2020-09-28T10:37:58Z-
dc.date.available2020-09-28T10:37:58Z-
dc.date.issued2020-05-
dc.identifier.issn2168-6149-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/179169-
dc.description.abstractImportance: 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.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherAmerican Medical Association-
dc.relation.isPartOfJAMA NEUROLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleAssessment of Demographic, Genetic, and Imaging Variables Associated With Brain Resilience and Cognitive Resilience to Pathological Tau in Patients With Alzheimer Disease-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Neurology (신경과학교실)-
dc.contributor.googleauthorRik Ossenkoppele-
dc.contributor.googleauthorChul Hyoung Lyoo-
dc.contributor.googleauthorJonas Jester-Broms-
dc.contributor.googleauthorCarole H Sudre-
dc.contributor.googleauthorHanna Cho-
dc.contributor.googleauthorYoung Hoon Ryu-
dc.contributor.googleauthorJae Yong Choi-
dc.contributor.googleauthorRuben Smith-
dc.contributor.googleauthorOlof Strandberg-
dc.contributor.googleauthorSebastian Palmqvist-
dc.contributor.googleauthorJoel Kramer-
dc.contributor.googleauthorAdam L Boxer-
dc.contributor.googleauthorMaria L Gorno-Tempini-
dc.contributor.googleauthorBruce L Miller-
dc.contributor.googleauthorRenaud La Joie-
dc.contributor.googleauthorGil D Rabinovici-
dc.contributor.googleauthorOskar Hansson-
dc.identifier.doi10.1001/jamaneurol.2019.5154-
dc.contributor.localIdA01333-
dc.contributor.localIdA03920-
dc.contributor.localIdA02485-
dc.contributor.localIdA04695-
dc.relation.journalcodeJ01199-
dc.identifier.eissn2168-6157-
dc.identifier.pmid32091549-
dc.identifier.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042808/?report=printable-
dc.contributor.alternativeNameLyoo, Chul Hyoung-
dc.contributor.affiliatedAuthor류철형-
dc.contributor.affiliatedAuthor유영훈-
dc.contributor.affiliatedAuthor최재용-
dc.citation.volume77-
dc.citation.number5-
dc.citation.startPage632-
dc.citation.endPage642-
dc.identifier.bibliographicCitationJAMA NEUROLOGY, Vol.77(5) : 632-642, 2020-05-
dc.identifier.rimsid67403-
dc.type.rimsART-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Nuclear Medicine (핵의학교실) > 1. Journal Papers

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