Journal
JOURNAL OF PROTEOME RESEARCH
Volume 8, Issue 2, Pages 1030-1036Publisher
AMER CHEMICAL SOC
DOI: 10.1021/pr800832s
Keywords
biomarkers; prion disease; transmissible spongiform encephalopathy; MALDI-FTMS; machine learning algorithms; support vector machines; proteomics
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Funding
- National Prion Research Program [DAMD17-03-1-0291]
- National Institutes of Health [AI0272588]
- Wisconsin Alumni Research Foundation at the University of Wisconsin-Madison
- Alfred P. Sloan Research Fellowship
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Definitive prion disease diagnosis is currently limited to postmortem assay for the presence of the disease-associated proteinase K-resistant prion protein. Using cerebrospinal fluid (CSF) from prion-infected hamsters, matrix-assisted laser desorption/ionization Fourier transform mass spectrometry (MALDI-FTMS), and support vector machines (SVM), we have identified peptide profiles characteristic of disease state. Using 10-fold leave-one-out cross-validation, we report a predictive accuracy of 72% with a true positive rate of 73% and a false positive rate of 27% demonstrating the suitability of using proteomic profiling and CSF for the development of multiple marker diagnostics of prion disease.
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