| Objective:In order to clarify the saliva-specific micro-features at the level of the saliva proteome in diseases and traditional chinese medicine deficiency syndrome; use bioinformatics tools to filtrate and optimize protein composition and then set up the combination of disease and symptom diagnosis model on diseases and traditional chinese medicine deficiency syndrome. Afterwards, conduct a preliminary study with a modern scientific basis on traditional chinese medicine in different syndromes of the same diseases, and different diseases with same syndrome from the level of proteome. At the same time, set up with saliva proteome noninvasive diagnostic techniques of chinese medicinal characteristics, to promote the development of micro-differentiation study and modernization of traditional chinese medicine diagnosis. We used the technology matrix-assisted laser desorption/ionization time of flight mass spectrometry(MALDI-TOF-MS), and selected patients with chronic glomerulonephritis(CGN). They were grouped according to principle combination of disease and symptom of traditional chinese medicine. The study groups were formed with diseases and normal controls on saliva proteome with a combination of disease and symptoms.Methods:88 cases of saliva specimens were collected, including 45 normal controls. All the patients have to undergo a histopathological diagnosis. By the combination of diseases and symptoms, all objects were divided into the following two main groups:(1)grouping by diseases, to compare the differences of the protein expression spectrum between chronic glomerulonephritis group and the normal controls.(2)Grouping by different syndromes, in accordance with deficiency syndrome standards, were divided into spleen deficiency, kidney deficiency, asthenia of both the spleen and kidney and other syndromes to be comparative studied with the normal control group. Using the WCX magnetic beads and MALDI-TOF-MS to detect the relative content of protein in saliva of the two major groups. Set all the saliva samples with collected protein molecular weight range of 2000~25000Da. Analyzing the same mass/charge and different protein content in each combination; finding that the combination of protein content have significant differences in the mass/charge. Set up a class prediction model by using the protein peaks that have significant differences(P<0.05) to establish a combination of disease and symptom diagnosis model. Using the random sampling methods, verify the validity of the model(an average of specificity sensitivity, and accuracy).Results:(1)Grouping by diseases: 88 cases of samples of the normal control group and the chronic glomerulonephritis group were collected for mass spectrometry analysis. The two groups were compared, and 410 of protein peaks were obtained with 224 statistical significant differences between the protein peaks(P<0.05), and select mass/charge(m/z) are: 7101.90 Da and 2616.91 Da with these two protein peaks for modeling. The class prediction model was set up by analyzing the differences in protein: identification rate was 93.02%, with a 91.11% prediction ability. Back to test the clinical results, 35 of the 43 cases of chronic glomerulonephritis patients were accurately detected. Out of the 45 cases of normal group, 36 cases were identified as non-chronic glomerulonephritis. The results show that the accuracy of this model was 80.68%(71/88), sensitivity was 81.40%(35/43) and specificity was 80.00%(36/45).(2)Grouping by the same diseases and different syndromes: chronic glomerulonephritis was divided into spleen deficiency, kidney deficiency, and asthenia of both the spleen and kidney. A normal group total of 81 cases, including 45 cases of samples were collected for mass spectrometry analysis and comparison. ①Comparison between deficiency group and normal controls: 1)the spleen deficiency group and normal controls were compared, and a total of 155 protein peaks were found, with the adoption of genetic algorithm 3 significantly different protein peaks between that mass/charge(m/z) are: 7101.905Da、3641.061Da、3931.962Da; 2)comparing kidney deficiency group and normal controls, and a total of 227 protein peaks were found, with the adoption of genetic algorithm 3 significantly different protein peaks between that mass/charge(m/z) are: 2431.66Da、4660.73Da、7101.90 Da.It was found that three protein peaks were highly expressed in kidney deficiency group, select for modeling. The class prediction model was set up by analyzing the differences in protein: identification rate was 90.00%, with a 97.78% prediction ability. Back to test the clinical results, 18 of the 20 cases of chronic glomerulonephritis kidney deficiency patients were accurately detected. Out of the 45 cases of normal group, 42 cases were identified as non-kidney deficiency. The results show that the accuracy of this model was 90.91%(60/66), sensitivity was 85.71%(18/21) and specificity was 93.33%(42/45); 3)the asthenia of both the spleen and kidney group and normal controls were compared, and a total of 103 protein peaks were found, with the adoption of genetic algorithm 2 significantly different protein peaks between that mass/charge(m/z) are: 7101.905Da、2616.913 Da. ②Comparison among deficiency groups: 1)the spleen deficiency group and kidney deficiency group were compared, and a total of 35 protein peaks were found, with the adoption of genetic algorithm 1 significantly different protein peaks between that mass/charge(m/z) are: 2952.974Da; 2)the spleen deficiency group and asthenia of both the spleen and kidney group were compared, and a total of 32 protein peaks were found, with the adoption of genetic algorithm 1 significantly different protein peaks between that mass/charge(m/z) are: 2102.998Da; 3)the kidney group and asthenia of both the spleen and kidney group were compared, and a total of 12 protein peaks were found, with the adoption of genetic algorithm 1 significantly different protein peaks between that mass/charge(m/z) are: 3872.561 Da.Conclusions:In this study, the use of MALDI-TOF-MS technology for liquid protein expression spectra in patients with the chronic glomerulonephritis and normal control group were detected expression profiles from saliva proteome preliminary screening may be used in conjunction with chronic glomerulonephritis syndrome diagnosed with specific of biomarkers, to explore and to establish a diagnostic model of the relevant disease and syndrome. This method is compared with the traditional method for detecting disease- related biomarkers, with non-invasive, simple, fast, and high sensitivity and specificity, the screening biomarkers for quickly and accurately diagnose diseases, syndromes identification, prognosis has important clinical implications. Therefore, this study of chronic glomerulonephritis early diagnosis and identification of symptoms has opened up new avenues, as well as research and development of traditional Chinese medicine syndrome microscopic study opens up new ideas and research in the field. |
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