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 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

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