Antibiotic-induced intestinal microbiota depletion can attenuate the acute kidney injury to chronic kidney disease transition via NADPH oxidase 2 and trimethylamine-N-oxide inhibition.

Intestinal microbiota and their metabolites affect systemic inflammation and kidney disease outcomes. Here, we investigated the key metabolites associated with the acute kidney injury (AKI)-to chronic kidney disease (CKD) transition and the effect of antibiotic-induced microbiota depletion (AIMD) on this transition. In 61 patients with AKI, 59 plasma metabolites were assessed to determine the risk of AKI-to-CKD transition. An AKI-to-CKD transition murine model was established four weeks after unilateral ischemia-reperfusion injury (IRI) to determine the effects of AIMD on the gut microbiome, metabolites, and pathological responses related to CKD transition. Human proximal tubular epithelial cells were challenged with CKD transition-related metabolites, and inhibitory effects of NADPH oxidase 2 (NOX2) signals were tested. Based on clinical metabolomics, plasma trimethylamine N-oxide (TMAO) was associated with a significantly increased risk for AKI-to-CKD transition [adjusted odds ratio 4.389 (95% confidence interval 1.106-17.416)]. In vivo, AIMD inhibited a unilateral IRI-induced increase in TMAO, along with a decrease in apoptosis, inflammation, and fibrosis. The expression of NOX2 and oxidative stress decreased after AIMD. In vitro, TMAO induced fibrosis with NOX2 activation and oxidative stress. NOX2 inhibition successfully attenuated apoptosis, inflammation, and fibrosis with suppression of G2/M arrest. NOX2 inhibition (in vivo) showed improvement in pathological changes with a decrease in oxidative stress without changes in TMAO levels. Thus, TMAO is a key metabolite associated with the AKI-to-CKD transition, and NOX2 activation was identified as a key regulator of TMAO-related AKI-to-CKD transition both in vivo and in vitro.

Fumarate modulates phospholipase A2 receptor autoimmunity-induced podocyte injury in membranous nephropathy.

Downstream mechanisms that lead to podocyte injury following phospholipase A2 receptor (PLA2R) autoimmunity remain elusive. To help define this we compared urinary metabolomic profiles of patients with PLA2R-associated membranous nephropathy (MN) at the time of kidney biopsy with those of patients with minimal change disease (MCD) and to healthy individuals. Among the metabolites differentially expressed in patients with PLA2R-associated MN compared to healthy individuals, fumarate was the only significant differentially expressed metabolite in PLA2R-associated MN compared to MCD [fold-difference vs. healthy controls and vs. MCD: 1.76 and 1.60, respectively]. High urinary fumarate levels could predict the composite outcome of PLA2R-associated MN. Fumarate hydratase, which hydrolyzes fumarate, colocalized with podocalyxin, and its expression was lower in glomerular sections from patients with PLA2R-associated MN than in those from healthy individuals, patients with non-PLA2R-associated MN or MCD. Podocytes stimulated with IgG purified from serum with a high anti-PLA2R titer (MN-IgG) decreased expression of fumarate hydratase and increased fumarate levels. These changes were coupled to alterations in the expression of molecules involved in the phenotypic profile of podocytes (WT1, ZO-1, Snail, and fibronectin), an increase in albumin flux across the podocyte layer and the production of reactive oxygen species in podocytes. However, overexpression of fumarate hydratase ameliorated these alterations. Furthermore, knockdown of fumarate hydratase exhibited synergistic effects with MN-IgG treatment. Thus, fumarate may promote changes in the phenotypic profiles of podocytes after the development of PLA2R autoimmunity. These findings suggest that fumarate could serve as a potential target for the treatment of PLA2R-associated MN.

Urinary Metabolomic Profiling in Streptozotocin-Induced Diabetic Mice after Treatment with Losartan.

Diabetic kidney disease (DKD) is the leading cause of chronic kidney disease and end-stage kidney disease. Renin-angiotensin system inhibitors such as losartan are the predominant therapeutic options in clinical practice to treat DKD. Therefore, it is necessary to identify DKD-related metabolic profiles that are affected by losartan. To investigate the change in metabolism associated with the development of DKD, we performed global and targeted metabolic profiling using 800 MHz nuclear magnetic resonance spectroscopy of urine samples from streptozotocin-induced diabetic mice (DM) with or without losartan administration. A principal component analysis plot showed that the metabolic pattern in the losartan-treated diabetic mice returned from that in the DM group toward that in the control mice (CM). We found that 33 urinary metabolites were significantly changed in DM compared with CM, and the levels of 16 metabolites among them, namely, glucose, mannose, myo-inositol, pyruvate, fumarate, 2-hydroxyglutarate, isobutyrate, glycine, threonine, dimethylglycine, methyldantoin, isoleucine, leucine, acetylcarnitine, 3-hydroxy-3-methylglutarate, and taurine, shifted closer to the control level in response to losartan treatment. Pathway analysis revealed that these metabolites were associated with branched-chain amino acid degradation; taurine and hypotaurine metabolism; glycine, serine, and threonine metabolism; the tricarboxylic acid cycle; and galactose metabolism. Our results demonstrate that metabolomic analysis is a useful tool for identifying the metabolic pathways related to the development of DKD affected by losartan administration and may contribute to the discovery of new therapeutic agents for DKD.

Metabolic changes in urine and serum during progression of diabetic kidney disease in a mouse model.

Diabetic kidney disease (DKD) involves various pathogenic processes during progression to end stage renal disease, and activated metabolic pathways might be changing based on major pathophysiologic mechanisms as DKD progresses. In this study, nuclear magnetic resonance spectroscopy (NMR)-based metabolic profiling was performed in db/db mice to suggest potential biomarkers for early detection and its progression. We compared concentrations of serum and urinary metabolites between db/m and db/db mice at 8 or 20 weeks of age and investigated whether changes between 8 and 20 weeks in each group were significant. The metabolic profiles demonstrated significantly increased urine levels of glucose and tricarboxylic acid cycle intermediates at both 8 and 20 weeks of age in db/db mice. These intermediates also exhibited strong positive associations with urinary albumin excretion, suggesting that they may be potential biomarkers for early diagnosis. On the contrary, branched chain amino acid and homocysteine-methionine metabolism were activated early in the disease, whereas ketone and fatty acid metabolism were significantly changed in the late phase of the disease. We demonstrated phase-specific alterations in metabolites during progression of DKD. This study provides insights into perturbed mechanisms during evolution of the disease and identifies potential novel biomarkers for DKD.

Inhibition of Wnt/ß-Catenin Pathway by Dehydrocostus Lactone and Costunolide in Colon Cancer Cells.

Abnormal activation of ß-catenin has been reported in 90% in the sporadic and hereditary colorectal cancer. The suppression of abnormally activated ß-catenin is one of the good strategies for chemoprevention and treatment of colorectal cancer. In this study, we have isolated two main compounds from root of Saussurea lappa, dehydrocostus lactone (DCL) and costunolide (CL), and investigated their anti-colorectal cancer activities. DCL and CL suppressed cyclin D1 and survivin through inhibiting nuclear translocation of ß-catenin. They also suppressed the nuclear translocation of galectin-3 that is one of the coactivators of ß-catenin in SW-480 colon cancer cells. Furthermore, DCL and CL suppressed proliferation and survival of SW-480 colon cancer cells through the induction of cell cycle arrest and cell death. Taken together, DCL and CL from root of S. lappa have anti-colorectal cancer activities through inhibiting Wnt/ß-catenin pathway.

Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance.

BACKGROUND: As a leading cause of chronic kidney disease, clinical demand for noninvasive biomarkers of diabetic kidney disease (DKD) beyond proteinuria is increasing. Metabolomics is a popular method to identify mechanisms and biomarkers. We investigated urinary targeted metabolomics in DKD patients. METHODS: We conducted a targeted metabolomics study of 26 urinary metabolites in consecutive patients with DKD stage 1 to 5 (n = 208) and healthy controls (n = 26). The relationships between estimated glomerular filtration rate (eGFR) or urine protein-creatinine ratio (UPCR) and metabolites were evaluated. Multivariate Cox analysis was used to estimate relationships between urinary metabolites and the target outcome, end-stage renal disease (ESRD). C statistics and time-dependent receiver operating characteristics (ROC) were used to assess diagnostic validity. RESULTS: During a median 4.5 years of follow-up, 103 patients (44.0%) progressed to ESRD and 65 (27.8%) died. The median fold changes of nine metabolites belonged to monosaccharide and tricarboxylic acid (TCA) cycle metabolites tended to increase with DKD stage. Myo-inositol, choline, and citrates were correlated with eGFR and choline, while mannose and myo-inositol were correlated with UPCR. Elevated urinary monosaccharide and TCA cycle metabolites showed associations with increased morality and ESRD progression. The predictive power of ESRD progression was high, in the order of choline, myo-inositol, and citrate. Although urinary metabolites alone were less predictive than serum creatinine or UPCR, myo-inositol had additive effect with serum creatinine and UPCR. In time-dependent ROC, myo-inositol was more predictive than UPCR of 1-year ESRD progression prediction. CONCLUSION: Myo-inositol can be used as an additive biomarker of ESRD progression in DKD.

Associations between local acidosis induced by renal LDHA and renal fibrosis and mitochondrial abnormalities in patients with diabetic kidney disease.

During the progression of diabetic kidney disease (DKD), renal lactate metabolism is rewired. The relationship between alterations in renal lactate metabolism and renal fibrosis in patients with diabetes has only been partially established due to a lack of biopsy tissues from patients with DKD and the intricate mechanism of lactate homeostasis. The role of lactate dehydrogenase A (LDHA)-mediated lactate generation in renal fibrosis and dysfunction in human and animal models of DKD was explored in this study. Measures of lactate metabolism (urinary lactate levels and LDHA expression) and measures of DKD progression (estimated glomerular filtration rate and Wilms' tumor-1 expression) were strongly negatively correlated in patients with DKD. Experiments with streptozotocin-induced DKD rat models and the rat renal mesangial cell model confirmed our findings. We found that the pathogenesis of DKD is linked to hypoxia-mediated lactic acidosis, which leads to fibrosis and mitochondrial abnormalities. The pathogenic characteristics of DKD were significantly reduced when aerobic glycolysis or LDHA expression was inhibited. Further studies will aim to investigate whether local acidosis caused by renal LDHA might be exploited as a therapeutic target in patients with DKD.

Urinary myo-inositol is associated with the clinical outcome in focal segmental glomerulosclerosis.

Focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) have similar initial histological findings; however, their prognoses are distinct. Therefore, it is of great importance to discriminate FSGS from MCD in the early phase of disease and predict clinical prognosis. A discovery set of 184 urine samples (61 healthy control, 80 MCD, and 43 FSGS) and a validation set of 61 urine samples (12 healthy control, 26 MCD, and 23 FSGS) were collected at the time of kidney biopsy. Metabolic profiles were examined using nuclear magnetic resonance spectroscopy. Of 70 urinary metabolites, myo-inositol was significantly higher in FSGS patients than in control patients (discovery set, 2.34-fold, P < 0.001; validation set, 2.35-fold, P = 0.008) and MCD patients (discovery set, 2.48-fold, P = 0.002; validation set, 1.69-fold, P = 0.042). Myo-inositol showed an inverse relationship with the initial estimated glomerular filtration rate (eGFR) and was associated with the plasma level of soluble urokinase-type plasminogen activator receptor in FSGS patients. Myo-inositol treatment ameliorated the decreased expression of ZO-1 and synaptopodin in an in vitro FSGS model, and as myo-inositol increased, myo-inositol oxygenase tissue expression decreased proportionally to eGFR. Furthermore, urinary myo-inositol exhibited an increase in the power to discriminate FSGS patients, and its addition could better predict the response to initial treatment. In conclusion, urinary myo-inositol may be an important indicator in the diagnosis and treatment of FSGS patients.

Software-assisted serum metabolite quantification using NMR.

The goal of metabolomics is to analyze a whole metabolome under a given set of conditions, and accurate and reliable quantitation of metabolites is crucial. Absolute concentration is more valuable than relative concentration; however, the most commonly used method in NMR-based serum metabolic profiling, bin-based and full data point peak quantification, provides relative concentration levels of metabolites and are not reliable when metabolite peaks overlap in a spectrum. In this study, we present the software-assisted serum metabolite quantification (SASMeQ) method, which allows us to identify and quantify metabolites in NMR spectra using Chenomx software. This software uses the ERETIC2 utility from TopSpin to add a digitally synthesized peak to a spectrum. The SASMeQ method will advance NMR-based serum metabolic profiling by providing an accurate and reliable method for absolute quantification that is superior to bin-based quantification.