Identifying longitudinal cognitive resilience from cross-sectional amyloid, tau, and neurodegeneration

Abstract Background Leveraging Alzheimer’s disease (AD) imaging biomarkers and longitudinal cognitive data may allow us to establish evidence of cognitive resilience (CR) to AD pathology in-vivo. Here, we applied latent class mixture modeling, adjusting for sex, baseline age, and neuroimaging biomar...

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Ngā kaituhi matua:	Rory Boyle, Diana L. Townsend, Hannah M. Klinger, Catherine E. Scanlon, Ziwen Yuan, Gillian T. Coughlan, Mabel Seto, Zahra Shirzadi, Wai-Ying Wendy Yau, Roos J. Jutten, Christoph Schneider, Michelle E. Farrell, Bernard J. Hanseeuw, Elizabeth C. Mormino, Hyun-Sik Yang, Kathryn V. Papp, Rebecca E. Amariglio, Heidi I. L. Jacobs, Julie C. Price, Jasmeer P. Chhatwal, Aaron P. Schultz, Michael J. Properzi, Dorene M. Rentz, Keith A. Johnson, Reisa A. Sperling, Timothy J. Hohman, Michael C. Donohue, Rachel F. Buckley, for the Alzheimer’s Disease Neuroimaging Initiative
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	BMC 2024-07-01
Rangatū:	Alzheimer’s Research & Therapy
Ngā marau:	Longitudinal analysis Alzheimer’s disease Amyloid Tau PET MRI
Urunga tuihono:	https://doi.org/10.1186/s13195-024-01510-y
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!

Identifying longitudinal cognitive resilience from cross-sectional amyloid, tau, and neurodegeneration

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