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Urinary Peptidomic Biomarkers of Metabolic Syndrome with Early Renal Injury

Author: GaoBiXia
Tutor: LiXueWang;LiMingXi
School: Beijing Union Medical College
Course: Internal Medicine
Keywords: Metabolic syndrome Kidney damage Urine polypeptide spectrum Magnetic bead separation combined with matrix assisted laser desorption ionization time-of-flight mass spectrometry Genetic Algorithms Random Forests Support Vector Machine Urinary peptide markers The liquid chromatography Joint tandem mass spectrometry
CLC: R692
Type: PhD thesis
Year: 2011
Downloads: 110
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Objective To optimize the weak cation exchange beads (MB-WCX) joint matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to establish urine polypeptide spectrum of experimental methods, the establishment of the metabolic syndrome (MS) early renal damage in urine polypeptide spectrum. Explore urine collection method (1), the solution temperature, pH value of the sample in the sample, the sample target and mass spectrometry data acquisition bead joint matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MB-MALDI-TOF-MS) to establish urine polypeptide spectrum, to evaluate the reproducibility of the experimental methods; (2) urine samples from 2008 to 2009 in Beijing Pinggu epidemiological studies of the metabolic syndrome kidney damage. MS according to the U.S. National Cholesterol Education Program Adult Treatment Panel Ⅲ (ATP Ⅲ) diagnostic criteria for MS patients 20μg/min ≤ urinary albumin excretion rate (UAE) lt; 200μg/min and estimated glomerular filtration rate (eGFR) ≥ 60ml/min.1.73m2 compared with early renal damage. The selected candidates are divided into healthy controls (group Ⅰ), MS merge normal albuminuria group (group Ⅱ) merger microalbuminuria group (group Ⅲ) and MS. Application MB-MALDI-TOF-MS method for the establishment of the three sets of samples of urine polypeptide spectrum. The results (1) MB-MALDI-TOF-MS urine polypeptide spectrum optimization experiments process including: the experimental method of collecting overnight paragraph urine specimens, at room temperature dissolved sample volume 30μL point target Polished steel target and manual mode data collection; The coefficient of variation of 7.7% to 14.2%, day coefficients of variation of 7.9% to 23.0%. (2) of 165 patients were enrolled in group Ⅰ 65 cases, group Ⅱ 54 cases, group Ⅲ 46 cases, using the optimized MB-MALDI-TOF-MS established three groups urine polypeptide spectrum. Conclusion The establishment of a high sensitivity, good stability of MB-MALDI-TOF-MS laboratory procedures, suitable for high-throughput clinical proteomics research. The application of the technology to create a normal, MS merge normoalbuminuria and MS merger microalbuminuria urine polypeptide spectrum. The purpose of application of bioinformatics screening differences polypeptide peak urine diagnostic model of MS early renal damage, urine polypeptide marker sequence identification. Method two methods of data analysis: (1) three sets of samples were divided into training group and testing group ClinProTools 2.1 statistical methods filter differences in the polypeptide peak, genetic algorithm (GA), respectively for group I and group III, group II and build a diagnostic model the group Ⅲ training set of data, using 10-fold cross-validation assessment model diagnostic capabilities; external validation assessment model predictive ability testing set of data; (2) Matlab7.10.0-random forest (RF) algorithm screening differences polypeptide peak, support vector machine (SVM) algorithm to group Ⅰ and group Ⅲ, group Ⅱ and group Ⅲ and three sets of data were constructed diagnostic model, using 10-fold cross-validation and ROC curve assessment model diagnostic capabilities. Using a linear ion trap Orbitrap mass spectrometer (LTQ Orbitrap Velos) urine differences polypeptide peak identification, analysis of the biological function of the peptide markers. Results (1) group Ⅰ and group III polypeptide spectrum compare GA algorithm to construct the 10-fold cross-validation of the diagnostic model sensitivity 100%, specificity of 92.1%, 95.9% accuracy, external validation sensitivity 76.2%, specificity 80%, accuracy sexual 78.4%; SVM algorithm to build the model sensitivity 82.0%, specificity 90.9%, accuracy 87.3%, ROC area under the curve (AUC) was 0.924. Two models to contain the four polypeptides peak: m / z 2755.97,3016.72,9076.41 and 11728.45; (2) group Ⅱ and group Ⅲ peptide spectrum compare GA algorithm to construct the 10-fold cross-validation of the diagnostic model sensitivity 100%, specificity 87.5 %, accuracy of 93.4%, and external validation sensitivity 71.4%, specificity 73.1%, accuracy 72.3%; SVM algorithm to construct the model sensitivity 89.2%, specificity 81.1%, accuracy of 85.5%, the AUC was 0.911. Two models to contain four polypeptide peak: m / z 2755.97,3016.72,9076.41,10052.09; (3) three groups of polypeptides spectral comparison SVM algorithm to construct diagnostic model accuracy of 64.5%, and contains eight polypeptides peak: m / z 2048.72 2562.67,2755.97,8779.30,9076.41,10052.09,10530.43 and 11728.45. (4) The three polypeptides peak at m / z 1884.33,2562.67 and 2661.41 are fibrinogen alpha chain peptides. m / z 2562.67 in group Ⅱ and group Ⅲ upregulation, m / z 1884.33 and 2661.41 in group Ⅱ expression raised. The conclusion by two bioinformatics method to build the model have better diagnostic capabilities. The identification differences peptides m / z 1884.33,2562.67 and 2661.41 sequence and identification Fibrinogen alpha chain of the peptide fragments, may be the pathogenic process of MS early markers of kidney damage urine polypeptide involved in MS and MS kidney damage.

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CLC: > Medicine, health > Surgery > Urology ( urinary and reproductive system diseases) > Kidney disease
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