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

Identifying postmenopausal women at risk for cognitive decline within a healthy cohort using a... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Neurobiology of Aging Elsevier

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

Loading next page...
 
/lp/elsevier/identifying-postmenopausal-women-at-risk-for-cognitive-decline-within-ZdRNamHt9F
Publisher
Elsevier
Copyright
Copyright © 2016 The Authors
ISSN
0197-4580
D.O.I.
10.1016/j.neurobiolaging.2016.01.011
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Neurobiology of AgingElsevier

Published: Apr 1, 2016

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from
Google Scholar,
PubMed
Create lists to
organize your research
Export lists, citations
Read DeepDyve articles
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off