DataSheet_1_Metabolomics Study of Metabolic Changes in Renal Cells in Response to High-Glucose Exposure Based on Liquid or Gas Chromatography Coupled .docx (3.67 MB)

DataSheet_1_Metabolomics Study of Metabolic Changes in Renal Cells in Response to High-Glucose Exposure Based on Liquid or Gas Chromatography Coupled With Mass Spectrometry.docx

Download (3.67 MB)
dataset
posted on 20.08.2019, 13:34 by Liang Wang, Yan Du, Bing-ju Xu, Xu Deng, Qing-hua Liu, Qiao-qiao Zhong, Chen-xiang Wang, Shuai Ji, Meng-zhe Guo, Dao-quan Tang

Diabetic nephropathy (DN) is one of the most serious microvascular complications and the leading causes of death in diabetes mellitus (DM). To find biomarkers for prognosing the occurrence and development of DN has significant clinical value for its prevention, diagnosis, and treatment. In this study, a non-targeted cell metabolomics–based ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry and gas chromatography coupled with mass spectrometry was developed and performed the dynamic metabolic profiles of rat renal cells including renal tubular epithelial cells (NRK-52E) and glomerular mesangial cells (HBZY-1) in response to high glucose at time points of 12 h, 24 h, 36 h, and 48 h. Some potential biomarkers were then verified using clinical plasma samples collected from 55 healthy volunteers, 103 DM patients, and 57 DN patients. Statistical methods, such as principal component analysis and partial least squares to latent structure-discriminant analysis were recruited for data analyses. As a result, palmitic acid and linoleic acid (all-cis-9,12) were the potential indicators for the occurrence and development of DN, and valine, leucine, and isoleucine could be used as the prospective biomarkers for DM. In addition, rise and fall of leucine and isoleucine levels in plasma could be used for prognosing DN in DM patients. Through this study, we established a novel non-targeted cell dynamic metabolomics platform and identified potential biomarkers that may be applied for the diagnosis and prognosis of DM and DN.

History

Licence

Exports