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

Detecting at-risk individuals within a healthy population is critical for preventing or delaying Alzheimer's disease. Systems biology integration of brain and body metabolism enables peripheral metabolic biomarkers to serve as reporters of brain bioenergetic status. Using clinical metabolic dat...

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Bibliographic Details
Published in:Neurobiology of aging Vol. 40; pp. 155 - 163
Main Authors: Rettberg, Jamaica R., Dang, Ha, Hodis, Howard N., Henderson, Victor W., St. John, Jan A., Mack, Wendy J., Brinton, Roberta Diaz
Format: Journal Article
Language:English
Published: United States Elsevier Inc 01.04.2016
Subjects:
Aged
Alzheimer Disease - diagnosis
Alzheimer Disease - metabolism
Alzheimer Disease - prevention & control
Alzheimer Disease - psychology
Alzheimer's disease
Biomarker
Biomarkers
Cognition
Cognitive aging
Cognitive Dysfunction - diagnosis
Cognitive Dysfunction - metabolism
Cognitive Dysfunction - prevention & control
Cognitive Dysfunction - psychology
Cohort Studies
Estradiol - therapeutic use
Executive Function
Female
Hormone therapy
Humans
Internal Medicine
Memory
Menopause
Metabolism
Middle Aged
Neurology
Phenotype
Postmenopause
Randomized Controlled Trials as Topic
Risk
Biomarker
Cognitive aging
Hormone therapy
Metabolism
Alzheimer's disease
Menopause
ISSN:0197-4580, 1558-1497, 1558-1497
Online Access:Get full text
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Summary:Detecting at-risk individuals within a healthy population is critical for preventing or delaying Alzheimer's disease. 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 Early versus Late Intervention Trial with Estradiol (ELITE), we conducted principal components and k-means clustering analyses of 9 biomarkers to define metabolic phenotypes. Metabolic clusters were correlated with cognitive performance and analyzed for change over 5 years. Metabolic biomarkers at baseline generated 3 clusters, representing women with healthy, high blood pressure, and poor metabolic phenotypes. Compared with healthy women, poor metabolic women had significantly lower executive, global and memory cognitive performance. 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 toward developing an affordable, rapidly deployable, and clinically relevant strategy to detect an at-risk phenotype of late-onset Alzheimer's disease.
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ISSN:0197-4580
1558-1497
1558-1497
DOI:10.1016/j.neurobiolaging.2016.01.011