advantage of applying osc to 1h nmr-based metabonomic data of celiac disease

background celiac disease (cd) is a disorder associated with body reaction to gluten. after the gluten intake, an immune reaction against the protein occurs and damages villi of small intestine in celiac patients gradually. objectives the osc, a filtering method for minimization of inter- and intra-spectrometer variations that influence on data acquisition, was applied to biofluid nmr data of cd patients. patients and methods in this study, metabolites of total 56 serum samples from 12 cd patients, 15 cd patients taking gluten-free diet (gfd), and 29 healthy cases were analyzed using nuclear magnetic resonance (nmr) and associated theoretical analysis. employing prometab (version prometab_v3_3) software, data obtained from nmr spectra were reduced and orthogonal signal correction (osc) effect on celiac disease metabonomics before and after the separation by principle component analysis (pca) was investigated. results the three groups were separated by osc and findings were analyzed by partial least squares discriminant analysis (pls-da) method. root mean square error of calibration (rmsec) and correlation coefficient of calibration (rc) for pls-da referred to an efficient group separation filtered by osc. conclusions the applied leave-one-out cross-validation to pls-da method performed along with osc confirmed validation of data analysis. finally four metabolites are introduced as cd biomarkers.