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

Abstract

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.