Mass spectrometry-based proteomic analysis of Kashin-Beck disease

Kashin-Beck disease (KBD) is a degenerative osteoarticular disease of unknown etiology. The management of KBD would benefit from the identification of the biomarkers related to this disease. In this study, mass spectrometry (MS)-based proteomic profiling was used to identify potential biomarkers of the disease. One hundred and sixteen serum samples of KBD cases and healthy controls were collected and analyzed. A framework for data analysis was implemented, which included normalization, denoising using undecimated discrete wavelet transforms, baseline subtraction, peak detection and alignment, non-parametric testing and classification by support vector machine. The method identified correlative mass points and obtained a discriminative pattern with 90.91% sensitivity and 82.61% specificity. The results of this study, although preliminary, suggest that further proteomics study may be useful with a larger number of appropriate specimens, careful experiment manipulation and improved MS techniques.