Resolvin E3 ameliorates high-fat diet-induced insulin resistance via the phosphatidylinositol-3-kinase/Akt signaling pathway in adipocytes.

Obesity-associated type 2 diabetes mellitus is associated with the development of insulin resistance. Among several metabolites, resolvins that are metabolites of eicosapentaenoic acid have been shown to exert insulin-sensitizing effects; however, the role of resolvin E3 (RvE3) in glucose metabolism has not been studied. In this study, the effect of RvE3 on glucose metabolism in mice with high-fat diet-induced obesity and 3T3L1 adipocytes was studied. C57BL/6 mice fed a high-fat diet were administered RvE3, for which insulin tolerance, oral glucose tolerance tests, and the homeostasis model assessment of insulin resistance, were performed. RvE3 treatment significantly improved insulin sensitivity and glucose tolerance and regulated protein kinase B (Akt) phosphorylation in the adipose tissue. Moreover, RvE3 treatment enhanced the insulin-stimulated glucose transporter 4 (Glut4) translocation, glucose uptake, phosphatidylinositol-3-kinase (PI3K) activity, and Akt phosphorylation in 3T3L1 adipocytes, whereas a PI3K inhibitor inhibited the enhanced insulin-stimulated glucose uptake induced by RvE3. These findings indicate that RvE3 likely improves insulin sensitivity, resulting in the upregulation of glucose uptake in adipocytes by activating the PI3K/Akt signaling pathways. Collectively, the findings of this study show that RvE3 may play a role in glucose homeostasis and could be used as a potential therapeutic target for developing treatments for obesity-associated diabetes.

A metabolomics-based approach for predicting stages of chronic kidney disease.

Chronic kidney disease (CKD) is a major epidemiologic problem and a risk factor for cardiovascular events and cerebrovascular accidents. Because CKD shows irreversible progression, early diagnosis is desirable. Renal function can be evaluated by measuring creatinine-based estimated glomerular filtration rate (eGFR). This method, however, has low sensitivity during early phases of CKD. Cystatin C (CysC) may be a more sensitive predictor. Using a metabolomic method, we previously identified metabolites in CKD and hemodialysis patients. To develop a new index of renal hypofunction, plasma samples were collected from volunteers with and without CKD and metabolite concentrations were assayed by quantitative liquid chromatography/mass spectrometry. These results were used to construct a multivariate regression equation for an inverse of CysC-based eGFR, with eGFR and CKD stage calculated from concentrations of blood metabolites. This equation was able to predict CKD stages with 81.3% accuracy (range, 73.9-87.0% during 20 repeats). This procedure may become a novel method of identifying patients with early-stage CKD.

Exploration of novel predictive markers in rat plasma of the early stages of chronic renal failure.

To identify blood markers for early stages of chronic kidney disease (CKD), blood samples were collected from rats with adenine-induced CKD over 28 days. Plasma samples were subjected to metabolomic profiling by liquid chromatography-mass spectrometry, followed by multivariate analyses. In addition to already-identified uremic toxins, we found that plasma concentrations of N6-succinyl adenosine, lysophosphatidylethanolamine 20:4, and glycocholic acid were altered, and that these changes during early CKD were more sensitive markers than creatinine concentration, a universal indicator of renal dysfunction. Moreover, the increase in plasma indoxyl sulfate concentration occurred earlier than increases in phenyl sulfate and p-cresol sulfate. These novel metabolites may serve as biomarkers in identifying early stage CKD.

Metabolomic analysis of human plasma from haemodialysis patients.

BACKGROUND: Urea and creatinine are widely used as biomarkers for disease. However, these parameters have been criticized as markers for several reasons. Thus, we conducted this study to identify novel biomarkers that can be used as alternatives to urea and creatinine to estimate the adequate dialysis dose by metabolomic analyses of plasma samples from patients undergoing haemodialysis. MATERIAL AND METHODS: Liquid chromatography-electrospray ionization (ESI)-time-of-flight mass spectrometry (MS) was used to analyse low molecular weight molecules present in the plasma samples of 10 patients with end-stage renal disease (ESRD) who were being treated with haemodialysis, and in 16 healthy subjects. RESULTS: In plasma samples obtained after haemodialysis, the relative quantities of 54 peaks were significantly (P < 0·05) decreased when compared with those in the plasma before haemodialysis. The candidate biomarkers were allocated to three groups. Molecules in Group A improved completely with a large variance, molecules in Group B improved partially but with a large variance, and molecules in Group C improved partially with low variance after haemodialysis. Small cohort validation study consisting of the patients with ESRD undergoing haemodialysis indicates that three candidate biomarkers in Group C would be a very useful marker to estimate adequate haemodialysis dose. CONCLUSIONS: 1-Methylinosine and two unknown molecules whose m/z at ESI-positive mode are 257·1033 and 413·1359 were found as effective candidate biomarkers to estimate adequate haemodialysis dose, which has to be confirmed in prospective studies.