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A panel of blood lipids associated with cognitive performance, brain atrophy, and Alzheimer's diagnosis: A longitudinal study of elders without dementia

INTRODUCTION: We sought lipid‐metabolic biomarkers involved in the processes underlying cognitive decline and detected them in association with Alzheimer's disease (AD) phenotypes. METHODS: A least absolute shrinkage and selection operator logistic regression model was used to select lipids tha...

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Detalles Bibliográficos
Autores principales: Ma, Ya‐Hui, Shen, Xue‐Ning, Xu, Wei, Huang, Yu‐Yuan, Li, Hong‐Qi, Tan, Lin, Tan, Chen‐Chen, Dong, Qiang, Tan, Lan, Yu, Jin‐Tai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507431/
https://www.ncbi.nlm.nih.gov/pubmed/32995461
http://dx.doi.org/10.1002/dad2.12041
Descripción
Sumario:INTRODUCTION: We sought lipid‐metabolic biomarkers involved in the processes underlying cognitive decline and detected them in association with Alzheimer's disease (AD) phenotypes. METHODS: A least absolute shrinkage and selection operator logistic regression model was used to select lipids that best classified cognitive decline defined by a fast‐annual rate of cognition. Lipid summary scores were constructed as predictors of cognitive decline by using this model. Multivariable‐adjusted models tested the associations of risk score with AD phenotypes. RESULTS: A model incorporating 17 selected lipids showed good discrimination and calibration. The lipid risk score was positively associated with the baseline Alzheimer Disease Assessment Scale—13‐item cognitive subscale (ADAS‐Cog13) score and cerebrospinal tau protein level, and predicted cognitive diagnoses. Additional results showing that individuals with increased lipid risk scores had rapid change rates of ADAS‐Cog13 and brain atrophy further corroborated the predictive role of lipids. DISCUSSION: A panel of blood lipids instead of individual lipid molecules could better diagnose and predict cognitive decline.