Cited 34 times in
The impact of demographic, clinical, genetic, and imaging variables on tau PET status
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 | 2021-09-29T01:03:20Z | - |
dc.date.available | 2021-09-29T01:03:20Z | - |
dc.date.issued | 2021-07 | - |
dc.identifier.issn | 1619-7070 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/184166 | - |
dc.description.abstract | Purpose: A substantial proportion of amyloid-β (Aβ)+ patients with clinically diagnosed Alzheimer's disease (AD) dementia and mild cognitive impairment (MCI) are tau PET-negative, while some clinically diagnosed non-AD neurodegenerative disorder (non-AD) patients or cognitively unimpaired (CU) subjects are tau PET-positive. We investigated which demographic, clinical, genetic, and imaging variables contributed to tau PET status. Methods: We included 2338 participants (430 Aβ+ AD dementia, 381 Aβ+ MCI, 370 non-AD, and 1157 CU) who underwent [18F]flortaucipir (n = 1944) or [18F]RO948 (n = 719) PET. Tau PET positivity was determined in the entorhinal cortex, temporal meta-ROI, and Braak V-VI regions using previously established cutoffs. We performed bivariate binary logistic regression models with tau PET status (positive/negative) as dependent variable and age, sex, APOEε4, Aβ status (only in CU and non-AD analyses), MMSE, global white matter hyperintensities (WMH), and AD-signature cortical thickness as predictors. Additionally, we performed multivariable binary logistic regression models to account for all other predictors in the same model. Results: Tau PET positivity in the temporal meta-ROI was 88.6% for AD dementia, 46.5% for MCI, 9.5% for non-AD, and 6.1% for CU. Among Aβ+ participants with AD dementia and MCI, lower age, MMSE score, and AD-signature cortical thickness showed the strongest associations with tau PET positivity. In non-AD and CU participants, presence of Aβ was the strongest predictor of a positive tau PET scan. Conclusion: We identified several demographic, clinical, and neurobiological factors that are important to explain the variance in tau PET retention observed across the AD pathological continuum, non-AD neurodegenerative disorders, and cognitively unimpaired persons. | - |
dc.description.statementOfResponsibility | open | - |
dc.format | application/pdf | - |
dc.language | English | - |
dc.publisher | Springer-Verlag Berlin | - |
dc.relation.isPartOf | EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Alzheimer Disease* / diagnostic imaging | - |
dc.subject.MESH | Alzheimer Disease* / genetics | - |
dc.subject.MESH | Amyloid beta-Peptides | - |
dc.subject.MESH | Cognitive Dysfunction* / diagnostic imaging | - |
dc.subject.MESH | Cognitive Dysfunction* / genetics | - |
dc.subject.MESH | Demography | - |
dc.subject.MESH | Humans | - |
dc.subject.MESH | Positron-Emission Tomography | - |
dc.subject.MESH | tau Proteins | - |
dc.title | The impact of demographic, clinical, genetic, and imaging variables on tau PET status | - |
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 | Antoine Leuzy | - |
dc.contributor.googleauthor | Hanna Cho | - |
dc.contributor.googleauthor | Carole H Sudre | - |
dc.contributor.googleauthor | Olof Strandberg | - |
dc.contributor.googleauthor | Ruben Smith | - |
dc.contributor.googleauthor | Sebastian Palmqvist | - |
dc.contributor.googleauthor | Niklas Mattsson-Carlgren | - |
dc.contributor.googleauthor | Tomas Olsson | - |
dc.contributor.googleauthor | Jonas Jögi | - |
dc.contributor.googleauthor | Erik Stormrud | - |
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 | Edilio Borroni | - |
dc.contributor.googleauthor | Gregory Klein | - |
dc.contributor.googleauthor | Michael J Pontecorvo | - |
dc.contributor.googleauthor | Michael D Devous Sr | - |
dc.contributor.googleauthor | Sylvia Villeneuve | - |
dc.contributor.googleauthor | Chul Hyoung Lyoo | - |
dc.contributor.googleauthor | Gil D Rabinovici | - |
dc.contributor.googleauthor | Oskar Hansson | - |
dc.identifier.doi | 10.1007/s00259-020-05099-w | - |
dc.contributor.localId | A01333 | - |
dc.contributor.localId | A02485 | - |
dc.contributor.localId | A03920 | - |
dc.relation.journalcode | J00833 | - |
dc.identifier.eissn | 1619-7089 | - |
dc.identifier.pmid | 33215319 | - |
dc.subject.keyword | Alzheimer’s disease | - |
dc.subject.keyword | Aβ | - |
dc.subject.keyword | Dementia | - |
dc.subject.keyword | MCI | - |
dc.subject.keyword | PET | - |
dc.subject.keyword | Tau | - |
dc.contributor.alternativeName | Lyoo, Chul Hyoung | - |
dc.contributor.affiliatedAuthor | 류철형 | - |
dc.contributor.affiliatedAuthor | 유영훈 | - |
dc.contributor.affiliatedAuthor | 조한나 | - |
dc.citation.volume | 48 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 2245 | - |
dc.citation.endPage | 2258 | - |
dc.identifier.bibliographicCitation | EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, Vol.48(7) : 2245-2258, 2021-07 | - |
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