Diagnosis of chronic kidney diseases based on surface-enhanced Raman spectroscopy and multivariate analysis

A simple and fast non-invasive diagnostic method based on surface-enhanced Raman spectroscopy (SERS) and multivariate analysis for diagnosis of chronic kidney diseases (CKD) is presented in this paper. Silver nanoparticles were utilized as the SERS substrate and mixed with the serum samples to enhance the Raman signals of various biomolecular in serum samples. SERS spectra were obtained from serum samples of normal subjects (n = 50) and CKD patients (n = 60). Principal component analysis and linear discriminate analysis were performed to classify the normal and CKD patients. Then, the training set database and the classification model were constructed. The classification model was further validated with the spectra of independent 10 normal subjects and 11 CKD patients serum samples with a sensitivity and specificity of 100%. These results establish that this non-invasive diagnostic method is able to directly diagnose CKD and has a significant potential in clinical diagnosis applications.