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Lipidomics Reveals Serum Specific Lipid Alterations in Diabetic Nephropathy.

ABSTRACT: In diabetes mellitus (DM), disorders of glucose and lipid metabolism are significant causes of the onset and progression of diabetic nephropathy (DN). However, the exact roles of specific lipid molecules in the pathogenesis of DN remain unclear. This study recruited 577 participants, including healthy controls (HCs), type-2 DM (2-DM) patients, and DN patients, from the clinic. Serum samples were collected under fasting conditions. Liquid chromatography-mass spectrometry-based lipidomics methods were used to explore the lipid changes in the serum and identify potential lipid biomarkers for the diagnosis of DN. Lipidomics revealed that the combination of lysophosphatidylethanolamine (LPE) (16:0) and triacylglycerol (TAG) 54:2-FA18:1 was a biomarker panel for predicting DN. The receiver operating characteristic analysis showed that the panel had a sensitivity of 89.1% and 73.4% with a specificity of 88.1% and 76.7% for discriminating patients with DN from HCs and 2-DM patients. Then, we divided the DN patients in the validation cohort into microalbuminuria (diabetic nephropathy at an early stage, DNE) and macroalbuminuria (diabetic nephropathy at an advanced stage, DNA) groups and found that LPE(16:0), phosphatidylethanolamine (PE) (16:0/20:2), and TAG54:2-FA18:1 were tightly associated with the stages of DN. The sensitivity of the biomarker panel to distinguish between patients with DNE and 2-DM, DNA, and DNE patients was 65.6% and 85.9%, and the specificity was 76.7% and 75.0%, respectively. Our experiment showed that the combination of LPE(16:0), PE(16:0/20:2), and TAG54:2-FA18:1 exhibits excellent performance in the diagnosis of DN.

SUBMITTER: Xu T

PROVIDER: S-EPMC8695735 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMembrane nephropathy (MN) often presents as nephrotic syndrome with characteristic lipid metabolism that could not be explained by lipid indicators commonly used in clinical practice. Studies have shown that invigorating spleen and qi, activating blood and detoxication in the treatment of MN is an effective method proved by randomized controlled clinical trial. However, the alterations of lipid profile before and after traditional Chinese medicine (TCM) treatment and the related lipid markers that affect the therapeutic effect have not been fully clarified.MethodsWe analyzed plasma lipid profiles of 92 patients with MN before and after TCM treatment by high-coverage targeted lipidomics.Results675 lipids were identified, of which 368 stably expressed lipids (coefficient of variation less than 30% and deletion value less than 10%) were eventually included for statistical analysis. 105 lipids were altered mainly including spingolipids, glycerides, glycerophosholipid, fatty acyl and steroids, among which, the abundance of ceramides (Cers), sphingomyelins (SMs), diacylglycerols (DGs), phosphatidylcholines (PCs) were lower than those before treatment with statistically significant difference. The WGCNA network to analyze the correlation between the collective effect and the therapeutic effect showed that the triglyceride (TG) molecules were most relevant to the therapeutic effect. Analysis of 162 triglyceride molecules showed that 11 TGs were significantly down-regulated in the effective group which were concentrated in carbon atom number of 52-56 and double bond number of 0-4. TGs molecules including TG56:2-FA20:0, TG56:2-FA20:1, TG56:3-FA20:0 and TG56:5-FA20:2 were most closely related to the therapeutic effect of TCM after adjusting the influence of clinical factors. ROC curve analysis showed that these four lipids could further improve the predictive efficacy of treatment based on clinical indicators.ConclusionOur work demonstrated that the therapeutic effect of invigorating spleen and qi, activating blood and detoxication in the treatment of MN may be exerted by regulating lipid metabolism. High-coverage targeted lipidomics provided a non-invasive tool for discovery of lipid markers to improve the predictive efficacy of TCM therapy.

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Lipidomics Reveals Serum Specific Lipid Alterations in Diabetic Nephropathy.

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