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Accuracy of Tau Positron Emission Tomography as a Prognostic Marker in Preclinical and Prodromal Alzheimer Disease: A Head-to-Head Comparison Against Amyloid Positron Emission Tomography and Magnetic Resonance Imaging
DC Field | Value | Language |
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dc.contributor.author | 류철형 | - |
dc.contributor.author | 유영훈 | - |
dc.contributor.author | 조한나 | - |
dc.contributor.author | 최재용 | - |
dc.date.accessioned | 2021-09-29T02:19:29Z | - |
dc.date.available | 2021-09-29T02:19:29Z | - |
dc.date.issued | 2021-08 | - |
dc.identifier.issn | 2168-6149 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/184830 | - |
dc.description.abstract | Importance: Tau positron emission tomography (PET) tracers have proven useful for the differential diagnosis of dementia, but their utility for predicting cognitive change is unclear. Objective: To examine the prognostic accuracy of baseline fluorine 18 (18F)-flortaucipir and [18F]RO948 (tau) PET in individuals across the Alzheimer disease (AD) clinical spectrum and to perform a head-to-head comparison against established magnetic resonance imaging (MRI) and amyloid PET markers. Design, setting, and participants: This prognostic study collected data from 8 cohorts in South Korea, Sweden, and the US from June 1, 2014, to February 28, 2021, with a mean (SD) follow-up of 1.9 (0.8) years. A total of 1431 participants were recruited from memory clinics, clinical trials, or cohort studies; 673 were cognitively unimpaired (CU group; 253 [37.6%] positive for amyloid-β [Aβ]), 443 had mild cognitive impairment (MCI group; 271 [61.2%] positive for Aβ), and 315 had a clinical diagnosis of AD dementia (315 [100%] positive for Aβ). Exposures: [18F]Flortaucipir PET in the discovery cohort (n = 1135) or [18F]RO948 PET in the replication cohort (n = 296), T1-weighted MRI (n = 1431), and amyloid PET (n = 1329) at baseline and repeated Mini-Mental State Examination (MMSE) evaluation. Main outcomes and measures: Baseline [18F]flortaucipir/[18F]RO948 PET retention within a temporal region of interest, MRI-based AD-signature cortical thickness, and amyloid PET Centiloids were used to predict changes in MMSE using linear mixed-effects models adjusted for age, sex, education, and cohort. Mediation/interaction analyses tested whether associations between baseline tau PET and cognitive change were mediated by baseline MRI measures and whether age, sex, and APOE genotype modified these associations. Results: Among 1431 participants, the mean (SD) age was 71.2 (8.8) years; 751 (52.5%) were male. Findings for [18F]flortaucipir PET predicted longitudinal changes in MMSE, and effect sizes were stronger than for AD-signature cortical thickness and amyloid PET across all participants (R2, 0.35 [tau PET] vs 0.24 [MRI] vs 0.17 [amyloid PET]; P < .001, bootstrapped for difference) in the Aβ-positive MCI group (R2, 0.25 [tau PET] vs 0.15 [MRI] vs 0.07 [amyloid PET]; P < .001, bootstrapped for difference) and in the Aβ-positive CU group (R2, 0.16 [tau PET] vs 0.08 [MRI] vs 0.08 [amyloid PET]; P < .001, bootstrapped for difference). These findings were replicated in the [18F]RO948 PET cohort. MRI mediated the association between [18F]flortaucipir PET and MMSE in the groups with AD dementia (33.4% [95% CI, 15.5%-60.0%] of the total effect) and Aβ-positive MCI (13.6% [95% CI, 0.0%-28.0%] of the total effect), but not the Aβ-positive CU group (3.7% [95% CI, -17.5% to 39.0%]; P = .71). Age (t = -2.28; P = .02), but not sex (t = 0.92; P = .36) or APOE genotype (t = 1.06; P = .29) modified the association between baseline [18F]flortaucipir PET and cognitive change, such that older individuals showed faster cognitive decline at similar tau PET levels. Conclusions and relevance: The findings of this prognostic study suggest that tau PET is a promising tool for predicting cognitive change that is superior to amyloid PET and MRI and may support the prognostic process in preclinical and prodromal stages of AD. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | American Medical Association | - |
dc.relation.isPartOf | JAMA NEUROLOGY | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | Accuracy of Tau Positron Emission Tomography as a Prognostic Marker in Preclinical and Prodromal Alzheimer Disease: A Head-to-Head Comparison Against Amyloid Positron Emission Tomography and Magnetic Resonance Imaging | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Neurology (신경과학교실) | - |
dc.contributor.googleauthor | Rik Ossenkoppele | - |
dc.contributor.googleauthor | Ruben Smith | - |
dc.contributor.googleauthor | Niklas Mattsson-Carlgren | - |
dc.contributor.googleauthor | Colin Groot | - |
dc.contributor.googleauthor | Antoine Leuzy | - |
dc.contributor.googleauthor | Olof Strandberg | - |
dc.contributor.googleauthor | Sebastian Palmqvist | - |
dc.contributor.googleauthor | Tomas Olsson | - |
dc.contributor.googleauthor | Jonas Jögi | - |
dc.contributor.googleauthor | Erik Stormrud | - |
dc.contributor.googleauthor | Hanna Cho | - |
dc.contributor.googleauthor | Young Hoon Ryu | - |
dc.contributor.googleauthor | Jae Yong Choi | - |
dc.contributor.googleauthor | Adam L Boxer | - |
dc.contributor.googleauthor | Maria L Gorno-Tempini | - |
dc.contributor.googleauthor | Bruce L Miller | - |
dc.contributor.googleauthor | David Soleimani-Meigooni | - |
dc.contributor.googleauthor | Leonardo Iaccarino | - |
dc.contributor.googleauthor | Renaud La Joie | - |
dc.contributor.googleauthor | Suzanne Baker | - |
dc.contributor.googleauthor | Edilio Borroni | - |
dc.contributor.googleauthor | Gregory Klein | - |
dc.contributor.googleauthor | Michael J Pontecorvo | - |
dc.contributor.googleauthor | Michael D Devous Sr | - |
dc.contributor.googleauthor | William J Jagust | - |
dc.contributor.googleauthor | Chul Hyoung Lyoo | - |
dc.contributor.googleauthor | Gil D Rabinovici | - |
dc.contributor.googleauthor | Oskar Hansson | - |
dc.identifier.doi | 10.1001/jamaneurol.2021.1858 | - |
dc.contributor.localId | A01333 | - |
dc.contributor.localId | A02485 | - |
dc.contributor.localId | A03920 | - |
dc.contributor.localId | A04695 | - |
dc.relation.journalcode | J01199 | - |
dc.identifier.eissn | 2168-6157 | - |
dc.identifier.pmid | 34180956 | - |
dc.identifier.url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8240013/ | - |
dc.contributor.alternativeName | Lyoo, Chul Hyoung | - |
dc.contributor.affiliatedAuthor | 류철형 | - |
dc.contributor.affiliatedAuthor | 유영훈 | - |
dc.contributor.affiliatedAuthor | 조한나 | - |
dc.contributor.affiliatedAuthor | 최재용 | - |
dc.citation.volume | 78 | - |
dc.citation.number | 8 | - |
dc.citation.startPage | 961 | - |
dc.citation.endPage | 971 | - |
dc.identifier.bibliographicCitation | JAMA NEUROLOGY, Vol.78(8) : 961-971, 2021-08 | - |
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