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Plasma Biomarkers of Brain Atrophy in Alzheimer's Disease

Overview of attention for article published in PLOS ONE, December 2011
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Title
Plasma Biomarkers of Brain Atrophy in Alzheimer's Disease
Published in
PLOS ONE, December 2011
DOI 10.1371/journal.pone.0028527
Pubmed ID
Authors

Madhav Thambisetty, Andrew Simmons, Abdul Hye, James Campbell, Eric Westman, Yi Zhang, Lars-Olof Wahlund, Anna Kinsey, Mirsada Causevic, Richard Killick, Iwona Kloszewska, Patrizia Mecocci, Hilkka Soininen, Magda Tsolaki, Bruno Vellas, Christian Spenger, Simon Lovestone

Abstract

Peripheral biomarkers of Alzheimer's disease (AD) reflecting early neuropathological change are critical to the development of treatments for this condition. The most widely used indicator of AD pathology in life at present is neuroimaging evidence of brain atrophy. We therefore performed a proteomic analysis of plasma to derive biomarkers associated with brain atrophy in AD. Using gel based proteomics we previously identified seven plasma proteins that were significantly associated with hippocampal volume in a combined cohort of subjects with AD (N = 27) and MCI (N = 17). In the current report, we validated this finding in a large independent cohort of AD (N = 79), MCI (N = 88) and control (N = 95) subjects using alternative complementary methods-quantitative immunoassays for protein concentrations and estimation of pathology by whole brain volume. We confirmed that plasma concentrations of five proteins, together with age and sex, explained more than 35% of variance in whole brain volume in AD patients. These proteins are complement components C3 and C3a, complement factor-I, γ-fibrinogen and alpha-1-microglobulin. Our findings suggest that these plasma proteins are strong predictors of in vivo AD pathology. Moreover, these proteins are involved in complement activation and coagulation, providing further evidence for an intrinsic role of these pathways in AD pathogenesis.

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Geographical breakdown

Country Count As %
United Kingdom 2 2%
France 2 2%
Chile 1 <1%
South Africa 1 <1%
Unknown 111 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 21%
Student > Master 17 15%
Student > Ph. D. Student 16 14%
Student > Bachelor 7 6%
Professor 6 5%
Other 19 16%
Unknown 28 24%
Readers by discipline Count As %
Neuroscience 24 21%
Agricultural and Biological Sciences 21 18%
Medicine and Dentistry 17 15%
Psychology 7 6%
Chemistry 5 4%
Other 10 9%
Unknown 33 28%