| Diabetic Nephropathy (DN) is also known as diabetic glomerular sclerosis, isone of the major cardiovascular complications of diabetes, and also is the leadingcause of disability and death of diabetic patients. The incidence of it rise with theduration extension of DM, and40%of type2diabetes patients. For the DN, thecurrent main diagnosis way is renal biopsy and urine protein and urine creatinine testtechnology. However, renal biopsy invasive nature, urine protein and urine creatininetest sensitivity is low, these detection method on the early light of kidney damagedetection of poor. When the patient was diagnosed with DN, kidney damage is moreserious, at this time will not be able to reverse to the development of renal failure anduremia, eventually lead to death. Therefore, early diagnosis, especially fornon-invasive diagnosis of DN and serial for patients with renal failure and livingstandards is of great significance, and looking for diabetic nephropathy earlymonitoring index is now facing an important research subject.Genomic and proteomic tools have been used for years in the studies attemptingto discover clinical markers for a variety of DN. However, they are still not readilyamenable to discover diagnostic tests because large genes and proteins are notgenerally secreted into biofluids．Metabonomics relatively new omics technologies，are more suited for such analysis because small metabolites is frequently secreted intourine. Thus, metabonomics research ultimately may be more clinically translatablethan genomic and proteomic endeavors.In this dissertation, HPLC and GC-MS based urine metabonomics was carriedout for DM and DN. These investigations were introduced briefly as follows:1. A HPLC method was proposed to simultaneously determine four commonnonprotein nitrogen substances, including Creatine (Cr), Creatinine (Cn), Uric Acid(Ua) and Pseudouridine (Pu) in urine. After removed proteins by acetone precipitationmethod, freeze drying and dissolved, the urine samples were analyzed by gradient elution. Chromatographic conditions: column, Waters RP18Column (150mm×4.6mm,3.5μm); detection wavelength,220nm; mobile phase,10.0mmol/L KH2PO4solution (pH4.78) and acetonitrile, flow rate,0.8mL/min. Rapid separation wasachieved within7min. Under the optimized conditions, good linearity of fourcommon nonprotein nitrogen substances were obtained in the range of0.1~250mg/L,0.1~250mg/L,0.1~250mg/L,0.1~250mg/L, the detection limits were9.31,26.19,4.70,6.30μg/L respectively, and the recovery were in the range of90.00%~100.00%with relative standard deviations of0.55~1.78%(n=3). The results demonstrate thatthis method is simple, rapid and accurate with good reproducibility, and can provideearly diagnosis and preliminary judgment for T2DM patients with renal damage.2. In this study, totally23urine samples from T2DM patients and29fromhealthy controls were collected and analyzed by gas chromatography-massspectrometry (GC-MS) based on individual and pooled strategies, respectively.Independent-sample t-Test (two-tailed), principal component analysis and orthogonalpartial least squares discriminant analysis were used to do biostatistics analysis, andresulted in17and23potential biomarkers based on individual and pooled strategies,respectively. After combination, it was found that only5biomarkers wereco-identified, and all of them are directly related to T2DM after previous reports andHuman Metabolome Database validation. This result suggested that the reliability ofidentified biomarkers can be greatly increased and the amount of identifiedbiomarkers was significantly decreased by combining individual and pooled strategiesin metabonomics study.3. To evaluate the application and reduce the error of urinary metabolomics ondiscovering potential biomarkers for Diabetic nephropathy (DN), urine samples from41early DN patients,21middle DN patients,23late DN patients, and29healthycontrols were collected for individual and pooled profiling based on GC-MS. Onlythose compounds presented in results of both individual and pooled profiling were ascertained as metabolomic biomarkers, and totally8potential biomarkers were foundto be disturbed in several metabolic pathways among DN patients, and metabolitesexpression is not the same in the different stages of development of DN, the patienturine metabolites content will be increased, lower and volatility. In summary, the dataobtained may be of great importance for future study, especially the pathology studyof metabolic syndromes, and the change regulation of metabolomics in the study ofDN. |
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