Journal
JOURNAL OF ALZHEIMERS DISEASE
Volume 24, Issue 1, Pages 47-59Publisher
IOS PRESS
DOI: 10.3233/JAD-2010-101722
Keywords
Amyloid-beta; biomarkers; blood; copper; diagnostics; SELDI-TOF-MS
Categories
Funding
- National Health and Medical Research Council of Australia
Ask authors/readers for more resources
Diagnostic measures for Alzheimer's disease (AD) commonly rely on evaluating the levels of amyloid-beta (A beta) peptides within the cerebrospinal fluid (CSF) of affected individuals. These levels are often combined with levels of an additional non-A beta marker to increase predictive accuracy. Recent efforts to overcome the invasive nature of CSF collection led to the observation of A beta species within the blood cellular fraction, however, little is known of what additional biomarkers may be found in this membranous fraction. The current study aimed to undertake a discovery-based proteomic investigation of the blood cellular fraction from AD patients (n = 18) and healthy controls (HC; n = 15) using copper immobilized metal affinity capture and Surface Enhanced Laser Desorption/Ionisation Time-Of-Flight Mass Spectrometry. Three candidate biomarkers were observed which could differentiate AD patients from HC (ROC AUC > 0.8). Bivariate pairwise comparisons revealed significant correlations between these markers and measures of AD severity including; MMSE, composite memory, brain amyloid burden, and hippocampal volume. A partial least squares regression model was generated using the three candidate markers along with blood levels of A beta. This model was able to distinguish AD from HC with high specificity (90%) and sensitivity (77%) and was able to separate individuals with mild cognitive impairment (MCI) who converted to AD from MCI non-converters. While requiring further characterization, these candidate biomarkers reaffirm the potential efficacy of blood-based investigations into neurodegenerative conditions. Furthermore, the findings indicate that the incorporation of non-amyloid markers into predictive models, function to increase the accuracy of the diagnostic potential of A beta.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available