| Abstract
| - BackgroundBacterial endocarditis is a serious disease. Surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) based on serum protein profiling is a powerful approach that can generate biomarkers with diagnostic value MethodsTo identify a protein signature associated with bacterial endocarditis, we retrospectively performed SELDI-TOF MS profiling of serum samples from 88 patients hospitalized because of clinical suspicion of endocarditis. The diagnosis was confirmed by conventional criteria for 34 patients (endocarditis positive) and was excluded for 54 patients (endocarditis negative). Serum samples were incubated with cation-exchange ProteinChip arrays. The protein profiles generated were subjected to biostatistical processing ResultsFifty-nine samples (23 endocarditis positive and 36 endocarditis negative) were randomly selected for a learning set, with the 29 remaining samples (11 endocarditis positive and 18 endocarditis negative) serving as an independent testing (validation) set. Sixty-six protein peaks were differentially expressed between the endocarditis-positive and the endocarditis-negative patients. By combining partial least squares and logistic regression methods, we built a serum protein model that perfectly discriminated between endocarditis-positive and endocarditis-negative patients. Importantly, when this model was tested on the independent testing set, a correct prediction rate of nearly 90% was demonstrated. Overall, sensitivity, specificity, positive predictive value, and negative predictive value were 94%, 98%, 96%, and 96%, respectively ConclusionsSELDI-TOF MS profiling revealed a serum signature with high diagnostic potential for endocarditis
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