ArticleFrontiers in pharmacology2019
Metabolomics Study of Metabolic Changes in Renal Cells in Response to High-Glucose Exposure Based on Liquid or Gas Chromatography Coupled With Mass Spectrometry.
Article in Frontiers in pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 14 citations in OpenAlex.
- Gas Chromatography-Mass Spectrometry (GC-MS) in the Plant Metabolomics Toolbox: Sample Preparation and Instrumental Analysis.Biomolecules · 2025Review
- Systematic metabolomic study on the plasma and urine of a mouse model of Alport syndrome.Scientific reports · 2025Article
- Correction to: YY1 inactivated transcription co-regulator PGC-1α to promote mitochondrial dysfunction of early diabetic nephropathy-associated tubulointerstitial fibrosis.Cell biology and toxicology · 2023Article
- YY1 inactivated transcription co-regulator PGC-1α to promote mitochondrial dysfunction of early diabetic nephropathy-associated tubulointerstitial fibrosis.Cell biology and toxicology · 2023Article
- Metaomics in Clinical Laboratory: Potential Driving Force for Innovative Disease Diagnosis.Frontiers in microbiology · 2022Review
- Comprehensive Lipidome Profiling of the Kidney in Early-Stage Diabetic Nephropathy.Frontiers in endocrinology · 2020Article
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
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Abstract
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.
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