↓ Skip to main content

PLOS

Evaluation of a Previously Suggested Plasma Biomarker Panel to Identify Alzheimer's Disease

Overview of attention for article published in PLOS ONE, January 2012
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
105 Dimensions

Readers on

mendeley
127 Mendeley
Title
Evaluation of a Previously Suggested Plasma Biomarker Panel to Identify Alzheimer's Disease
Published in
PLOS ONE, January 2012
DOI 10.1371/journal.pone.0029868
Pubmed ID
Authors

Maria Björkqvist, Mattias Ohlsson, Lennart Minthon, Oskar Hansson

Abstract

There is an urgent need for biomarkers in plasma to identify Alzheimer's disease (AD). It has previously been shown that a signature of 18 plasma proteins can identify AD during pre-dementia and dementia stages (Ray et al, Nature Medicine, 2007). We quantified the same 18 proteins in plasma from 174 controls, 142 patients with AD, and 88 patients with other dementias. Only three of these proteins (EGF, PDGF-BB and MIP-1δ) differed significantly in plasma between controls and AD. The 18 proteins could classify patients with AD from controls with low diagnostic precision (area under the ROC curve was 63%). Moreover, they could not distinguish AD from other dementias. In conclusion, independent validation of results is important in explorative biomarker studies.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 127 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Sweden 1 <1%
France 1 <1%
Belgium 1 <1%
United Kingdom 1 <1%
Unknown 121 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 24%
Student > Ph. D. Student 25 20%
Student > Master 16 13%
Student > Bachelor 15 12%
Other 7 6%
Other 13 10%
Unknown 21 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 24%
Medicine and Dentistry 16 13%
Neuroscience 14 11%
Biochemistry, Genetics and Molecular Biology 14 11%
Chemistry 7 6%
Other 22 17%
Unknown 23 18%