Identifying postmenopausal women at risk for cognitive decline within a healthy cohort using a panel of clinical metabolic indicators: Potential for detecting an at-Alzheimer’s risk metabolic phenotype

摘要

Detecting at-risk individuals within a healthy population is critical for preventing or delaying Alzheimer’s disease. The systems biology integration of brain and body metabolism enables peripheral metabolic biomarkers to serve as reporters of brain bioenergetic status. Using clinical metabolic data derived from healthy postmenopausal women in the ELITE trial, we conducted principal components and k-means clustering analyses of nine biomarkers to define metabolic phenotypes. Metabolic clusters were correlated with cognitive performance and analyzed for change over five years. Metabolic biomarkers at baseline generated three clusters, representing women with healthy, high blood pressure, and poor metabolic phenotypes. Compared to healthy women, poor metabolic women had lower verbal memory performance at baseline. Hormone therapy provided metabolic benefit to women in high blood pressure and poor metabolic phenotypes. This panel of well-established clinical peripheral biomarkers represents an initial step towards developing an affordable, rapidly deployable, and clinically relevant strategy to detect an atrisk phenotype of late-onset Alzheimer’s disease.