Abstract
We conducted untargeted metabolomics analysis of plasma samples from a cross-sectional case–control study with 30 healthy controls, 30 patients with diabetes mellitus and normal renal function (DM-N), and 30 early diabetic nephropathy (DKD) patients using liquid chromatography-mass spectrometry (LC-MS). We employed two different modes of MS acquisition on a high-resolution MS instrument for identification and semi-quantification, and analyzed data using an advanced multivariate method for prioritizing differentially abundant metabolites. We obtained semi-quantification data for 1088 unique compounds (~55% lipids), excluding compounds that may be either exogenous compounds or treated as medication. Supervised classification analysis over a confounding-free partial correlation network shows that prostaglandins, phospholipids, nucleotides, sugars, and glycans are elevated in the DM-N and DKD patients, whereas glutamine, phenylacetylglutamine, 3-indoxyl sulfate, acetylphenylalanine, xanthine, dimethyluric acid, and asymmetric dimethylarginine are increased in DKD compared to DM-N. The data recapitulate the well-established plasma metabolome changes associated with DM-N and suggest uremic solutes and oxidative stress markers as the compounds indicating early renal function decline in DM patients.
Original language | English |
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Article number | 228 |
Journal | Metabolites |
Volume | 11 |
Issue number | 4 |
DOIs | |
Publication status | Published - Apr 2021 |
Externally published | Yes |
Keywords
- Data independent acquisition
- Diabetic nephropathy
- Oxidative stress
- Phospholipids
- Prostaglandins
- Uremic toxins
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism
- Biochemistry
- Molecular Biology