Study on Proteinum in Clear Supernatant Liquid of Tongue Coating of Chronic Renal Failure Based on Protein Chip
基于蛋白芯片的慢性肾衰舌苔上清液中蛋白研究

This study aimed to screen proteinum markers of tongue coating related to chronic renal failure (CRF) and establish the predictive model by comparing differences of protein spectrum expression in clear supernatant liquid of tongue coating between CRF patients and normal controls in order to explore its significance in the diagnosis of CRF. Clear supernatant liquid of tongue coating samples of 67 CRF patients and 38 normal controls were used in the study. Proteinum markers of tongue coating were selected according to CRF with technique of SELDI-TOF-MS.The predictive model was established and verified by bioinformatics analysis. Results showed that tongue coating samples of 67 CRF patients and 38 normal samples in the control group were determined by technique of SELDITOF-MS. All 242 proteinum peaks have been detected at 1000-20000 e/m. And 13 distinct mass spectrum peaks have been analyzed by bioinformatics with statistical significance (P< 0.01). Seven distinct mass spectrum peaks,such as m/z 1092.68 and m/z 1508.26, show high expression in CRF group. Six distinct mass spectrum peaks, such as m/z 13302.5 and m/z 14330.7, show low expression in CRF group. Fuzzy grouping algorithm was used in the fuzzy grouping analysis and principal component analysis (PCA) between CRF group and normal control group. The result showed discrimination, but partly overlapping. The predictive model of CRF is analyzed and established by bioinformatics with biological markers which are constituted with 7 distinct mass spectrum peaks, such as m/z1049.61, m/z 1076.94, m/z 15295.7, and etc. The predictive model can be used in the sample classification between CRF group and normal control group. (The sensitivity of predictive model is 61.4%. The specificity is 57.3%. And predictive exactitude rate is 64.4%.) It is concluded that using technique of SELDI-TOF-MS, the proteinum markers of tongue coating of CRF have been preliminarily screened. The established predictive model provides objectiveevidence for the study on CRF diagnosis.