Metabolomics study of renal fibrosis and intervention effects of total aglycone extracts of Scutellaria baicalensis in unilateral ureteral obstruction rats

Qianjin Wenwu decoction suppresses renal interstitial fibrosis by enhancing the degradation of extracellular matrix in mice with unilateral ureteral obstruction

Diabetic kidney disease (DKD) is the most common complication of diabetes mellitus (DM). Qianjin Wenwu decoction (QWD), a well-known traditional Korean medicine, has been used for the treatment of DKD, with satisfactory therapeutic effects. This study was designed to investigate the active components and mechanisms of action of QWD in the treatment of DKD. The results demonstrated that a total of 13 active components in five types were found in QWD, including flavonoids, flavonoid glycosides, phenylpropionic acids, saponins, coumarins, and lignins. Two key proteins, TGF-β1 and TIMP-1, were identified as the target proteins through molecular docking. Furthermore, QWD significantly suppressed Scr and BUN levels which increased after unilateral ureteral obstruction (UUO). Hematoxylin & eosin (H&E) and Masson staining results demonstrated that QWD significantly alleviated renal interstitial fibrosis in UUO mice. We also found that QWD promoted ECM degradation by regulating MMP-9/TIMP-1 homeostasis to improve renal tubulointerstitial fibrosis and interfere with the expression and activity of TGF- β1 in DKD treatment. These findings explain the underlying mechanism of QWD for the treatment of DKD, and also provide methodological reference for investigating the mechanism of traditional medicine in the treatment of DKD.

Analysis of the volatile organic compounds of epidural analgesia-ameliorated metabolic disorder in pregnant women with gestational diabetes mellitus based on untargeted metabolomics

Gestational diabetes mellitus (GDM) is a metabolic disease with an increasing annual incidence. Our previous observational study found that pregnant women with gestational diabetes had mild cognitive decline, which may be related to methylglyoxal (MGO). This study aimed to investigate whether labor pain aggravates the increase in MGO and explored the protective effect of epidural analgesia on metabolism in pregnant women with GDM based on solid-phase microextraction gas chromatography/mass spectrometry (SPME/GC-MS). Pregnant women with GDM were divided into a natural birth group (ND group, n = 30) and epidural analgesia group (PD group, n = 30). After fasting for ≥ 10 h overnight, venous blood samples were collected pre- and post-delivery to detect MGO, interleukin-6 (IL-6), and 8-epi-prostaglandin F2 alpha (8-iso-PGF2α) by ELISA. Serum samples were analyzed for volatile organic compounds (VOCs) using SPME-GC-MS. MGO, IL-6, and 8-iso-PGF2α levels in the ND group increased significantly post-delivery (P < 0.05) and were significantly higher in this group than the levels in the PD group (P < 0.05). Compared to the PD group, VOCs in the ND group increased significantly post-delivery. Further results indicated that propionic acid may be associated with metabolic disorders in pregnant women with GDM. Epidural analgesia can effectively improve the metabolism and immune function in pregnant women with GDM.

Exploring the mechanism of Shendi Bushen capsule in anti-renal fibrosis using metabolomics theory and network analysis

Shendi Bushen capsule (SDBS) is a Chinese patent medicine used for the treatment of renal fibrosis (RF).

A metabolomic approach to elucidate the inhibitory effects of baicalin in pulmonary fibrosis

CONTEXT

Baicalin, a major flavonoid extracted from Scutellaria baicalensis Georgi (Lamiaceae), has been shown to exert therapeutic effects on pulmonary fibrosis (PF).

OBJECTIVE

To use serum metabolomics combined with biochemical and histopathological analyses to clarify anti-PF mechanisms of baicalin on metabolic pathways and the levels of potential biomarkers.

MATERIALS AND METHODS

Forty male Sprague-Dawley rats were randomly divided into the control, PF model, prednisolone acetate-treated (4.2 mg/kg/day) and baicalin-treated (25 and 100 mg/kg/day) groups. A rat model of PF was established using a tracheal injection of bleomycin, and the respective drugs were administered intragastrically for 4 weeks. Histomorphology of lung tissue was examined after H&E and Masson's trichrome staining. Biochemical indicators including SOD, MDA and HYP were measured. Serum-metabonomic analysis based on UPLC-Q-TOF/MS was used to clarify the changes in potential biomarkers among different groups of PF rats.

RESULTS

Both doses of baicalin effectively alleviated bleomycin-induced pathological changes, and increased the levels of SOD (from 69.48 to 99.50 and 112.30, respectively), reduced the levels of MDA (from 10.91 to 5.0 and 7.53, respectively) and HYP (from 0.63 to 0.41 and 0.49, respectively). Forty-eight potential biomarkers associated with PF were identified. Meanwhile, the metabolic profiles and fluctuating metabolite levels were normalized or partially reversed after baicalin treatment. Furthermore, baicalin was found to improve PF potentially by the regulation of four key biomarkers involving taurine and hypotaurine metabolism, glutathione metabolism, and glycerophospholipid metabolism.

CONCLUSIONS

These findings revealed the anti-fibrotic mechanisms of baicalin and it may be considered as an effective therapy for PF.

Metabolomics reveals the renoprotective effect of n-butanol extract and amygdalin extract from Amygdalus mongolica in rats with renal fibrosis

Renal fibrosis (RF) is a pathological process of progression from chronic kidney disease to end-stage renal disease. Amygdalus mongolica is a traditional Chinese medicine, and our previous studies demonstrated that the n-butanol extract (BUT) and amygdalin extract (AMY) from its seeds can prevent RF. However, the underlying mechanism remains unclear. The present study investigated the exact mechanism of the protective effect of A. mongolica on RF. A renal fibrosis rat model was induced with unilateral ureteral obstruction. Biochemical indicators were measured and combined with histopathology of renal tissue to evaluate the anti-RF effects. A serum metabonomic method was used to clarify the changes in the metabolic profile. The tubulointerstitial damage and fibrosis were significantly improved and metabolic perturbations were restored after treatment with BUT and AMY. Thirty-eight metabolites associated with RF progression and related to the regulation of arginine and proline metabolism, nicotinate and nicotinamide metabolism, and histidine metabolism were identified. They were restored to levels similar to those in controls after treatment. Moreover, no significant differences in efficacy were observed between the BUT and AMY groups. This study reveals and compares the potential mechanisms of the renoprotective effects after treatment with BUT and AMY from a metabolomic perspective.

Diminished Systemic Amino Acids Metabolome and Lipid Peroxidation in Ureteropelvic Junction Obstruction (UPJO) Infants Requiring Surgery

Congenital anomalies of the urinary tract, and particularly of obstructive nephropathy such as ureteropelvic junction obstruction (UPJO) in infants, can later lead to chronic kidney disease and hypertension. Fundamental questions regarding underlying mechanisms remain unanswered. The aim of the present study was to quantitate the systemic amino acids metabolome in 21 UPJO infants requiring surgery (Group A) and 21 UPJO infants under conservative treatment (Group B). Nineteen healthy age-matched infants served as controls (Group C). Serum amino acids involved in several pathways and representative metabolites, including the L-arginine-derived nitric oxide (NO) metabolites nitrite and nitrate and the lipid peroxidation biomarker malondialdehyde (MDA) were measured by gas chromatography–mass spectrometry (GC–MS) methods using their stable-isotope labeled analogs as internal standards after derivatization to their methyl esters N-pentafluoropropionic amides (amino acids) and to their pentafluorobenzyl derivatives (nitrite, nitrate, MDA). The concentrations of the majority of the biomarkers were found to be lower in Group A compared to Group B. Statistical analysis revealed clear differentiation between the examined study groups. Univariate statistical analysis highlighted serum homoarginine (q = 0.006), asymmetric dimethylarginine (q = 0.05) and malondialdehyde (q = 0.022) as potential biomarkers for UPJO infants requiring surgery. Group A also differed from Group B with respect to the diameter of the preoperative anterior–posterior renal pelvis (AP) as well as regarding the number and extent of inverse correlations between AP and the serum concentrations of the biomarkers. In Group A, but not in Group B, the AP diameter strongly correlated with hydroxy-proline (r = −0.746, p = 0.0002) and MDA (r = −0.754, p = 0.002). Our results indicate a diminished amino acids metabolome in the serum of UPJO infants requiring surgery comparing to a conservative group.

Dissecting Efficacy and Metabolic Characteristic Mechanism of Taxifolin on Renal Fibrosis by Multivariate Approach and Ultra-Performance Liquid Chromatography Coupled With Mass Spectrometry-Based Metabolomics Strategy

Taxifolin (TFN) is an important natural compound with antifibrotic activity; however, its pharmacological mechanism is not clear. In this study, our aim is to gain insight into the effects of TFN and its potential mechanisms in unilateral ureteral obstruction (UUO) animal model using metabolomics approach to identify the metabolic biomarkers and perturbed pathways. Serum metabolomics analysis by UPLC-Q-TOF/MS was carried out to discover the changes in the metabolic profile. It showed that TFN has a significant protective effect on UUO-induced renal fibrosis and a total of 32 potential biomarkers were identified and related to RF progression. Of note, 27 biomarkers were regulated by TFN treatment, which participate in eight metabolic pathways, including phenylalanine, tyrosine and tryptophan biosynthesis, and phenylalanine metabolism. It also showed that metabolomics was a promising strategy to better dissect metabolic characteristics and pharmacological mechanisms of natural compounds by multivariate approach and ultra-performance liquid chromatography coupled with mass spectrometry.

Inhibition of ROCK2 alleviates renal fibrosis and the metabolic disorders in the proximal tubular epithelial cells

Non-specific inhibition of Rho-associated kinases (ROCKs) alleviated renal fibrosis in the unilateral ureteral obstruction (UUO) model, while genetic deletion of ROCK1 did not affect renal pathology in mice. Thus, whether ROCK2 plays a role in renal tubulointerstitial fibrosis needs to be clarified. In the present study, a selective inhibitor against ROCK2 or genetic approach was used to investigate the role of ROCK2 in renal tubulointerstitial fibrosis. In the fibrotic kidneys of chronic kidney diseases (CKDs) patients, we observed an enhanced expression of ROCK2 with a positive correlation with interstitial fibrosis. In mice, the ROCK2 protein level was time-dependently increased in the UUO model. By treating CKD animals with KD025 at the dosage of 50 mg/kg/day via intraperitoneal injection, the renal fibrosis shown by Masson's trichrome staining was significantly alleviated along with the reduced expression of fibrotic genes. In vitro, inhibiting ROCK2 by KD025 or ROCK2 knockdown/knockout significantly blunted the pro-fibrotic response in transforming growth factor-β1 (TGF-β1)-stimulated mouse renal proximal tubular epithelial cells (mPTCs). Moreover, impaired cellular metabolism was reported as a crucial pathogenic factor in CKD. By metabolomics analysis, we found that KD025 restored the metabolic disturbance, including the impaired glutathione metabolism in TGF-β1-stimulated tubular epithelial cells. Consistently, KD025 increased antioxidative stress enzymes and nuclear erythroid 2-related factor 2 (Nrf2) in fibrotic models. In addition, KD025 decreased the infiltration of macrophages and inflammatory response in fibrotic kidneys and blunted the activation of macrophages in vitro. In conclusion, inhibition of ROCK2 may serve as a potential novel therapy for renal tubulointerstitial fibrosis in CKD.

Protective effects of Amygdalus mongolica on rats with renal fibrosis based on serum metabolomics

ETHNOPHARMACOLOGICAL RELEVANCE

Renal fibrosis (RF) is a common outcome of various progressive chronic kidney diseases (CKDs) and, thus, seriously endangers human health. As the active ingredient of Amygdalus mongolica, amygdalin inhibits RF. Furthermore, our previous studies demonstrated that n-butanol extract (BUT) and petroleum ether extract (PET), which are effective components of A. mongolica, have an anti-renal fibrosis effect. However, their potential mechanisms of action are unclear and need further verification.

AIMS OF THE STUDY

The aims of this study were to further investigate the effects and potential mechanisms of A. mongolica extracts in the treatment of RF.

MATERIALS AND METHODS

The animals were divided into the control group, RF model group, PET group and BUT group. The RF rat model was established through unilateral ureteral obstruction (UUO). Biochemical indicators, including blood urea nitrogen (BUN), serum creatinine (Scr), and hydroxyproline (HYP, a routine marker of fibrosis), and the antioxidant index (including superoxide dismutase (SOD) and malondialdehyde (MDA)) were measured to evaluate the anti-RF effects of the extracts of A. mongolica. The histomorphology of renal tissue was observed and scored by HE and Masson staining. A serum metabonomic analysis based on UPLC-Q-TOF/MS was performed to assess the changes in the metabolic profile among the different groups.

RESULTS

The results showed that PET and BUT significantly improved tubulointerstitial damage and fibrosis by reducing the levels of Scr, BUN, HYP, and MDA and increasing the level of SOD. Moreover, no significant differences in efficacy were observed between the BUT and PET groups. According to the metabolomics analysis, seventy-four potential biomarkers were identified, and eight crucial biomarkers were further selected. These key biomarkers significantly contributed to RF progression by participating in six metabolic pathways, including pathways involved in arginine and proline metabolism, histidine metabolism, nicotinamide metabolism, pentose and glucuronate interconversion, ascorbate and aldarate metabolism, and amino sugar and nucleotide sugar metabolism. In addition, eight key biomarkers and six crucial biomarkers were restored to levels similar to those observed in controls following the treatment with PET and BUT, respectively.

CONCLUSIONS

The outcomes of these studies demonstrate the renoprotective effects of A. mongolica extracts in rats with RF and revealed the mechanism underlying these antifibrotic effects on metabolic activity for the first time.

Serum-Targeted HILIC-MS Metabolomics-Based Analysis in Infants with Ureteropelvic Junction Obstruction

Ureteropelvic junction obstruction (UPJO) constitutes the predominant cause of obstructive nephropathy in both neonates and infants. Fundamental questions regarding UPJO's mechanism, assessment, and treatment still remain unanswered. The aim of the present study was to elucidate potential differences through serum metabolic profiling of surgical cases of infants with UPJO compared to both nonsurgical cases and healthy age-matched controls. Early diagnosis of renal dysfunction in this cohort based on highlighted biomarkers was the ultimate goal. Thus, serum samples were collected from 20 patients preoperatively, 19 patients with mild stenosis treated conservatively, and 17 healthy controls. All samples were subjected to targeted metabolomics analysis by hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC LC-MS/MS). Both univariate and multivariate statistical analyses were performed. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) score plots showed that the studied groups differed significantly, with a panel of metabolites, including creatinine, tryptophan, choline, and aspartate, distinguishing patients who required surgery from those followed by systematical monitoring as well as from healthy controls, showing high performance as indicators of UPJO disease.

Chronic kidney disease: Biomarker diagnosis to therapeutic targets

Chronic kidney disease (CKD), characterized as renal dysfunction, is recognized as a major public health problem with high morbidity and mortality worldwide. Unfortunately, there are no obvious clinical symptoms in early stage disease until severe damage has occurred. Further complicating early diagnosis and treatment is the lack of sensitive and specific biomarkers. As such, novel biomarkers are urgently needed. Metabolomics has shown an increasing potential for identifying underlying disease mechanisms, facilitating clinical diagnosis and developing pharmaceutical treatments for CKD. Recent advances in metabolomics revealed that CKD was closely associated with the dysregulation of numerous metabolites, such as amino acids, lipids, nucleotides and glycoses, that might be exploited as potential biomarkers. In this review, we summarize recent metabolomic applications based on animal model studies and in patients with CKD and highlight several biomarkers that may play important roles in diagnosis, intervention and development of new therapeutic strategies.

Overoptimism in cross-validation when using partial least squares-discriminant analysis for omics data: a systematic study

Advances in analytical instrumentation have provided the possibility of examining thousands of genes, peptides, or metabolites in parallel. However, the cost and time-consuming data acquisition process causes a generalized lack of samples. From a data analysis perspective, omics data are characterized by high dimensionality and small sample counts. In many scenarios, the analytical aim is to differentiate between two different conditions or classes combining an analytical method plus a tailored qualitative predictive model using available examples collected in a dataset. For this purpose, partial least squares-discriminant analysis (PLS-DA) is frequently employed in omics research. Recently, there has been growing concern about the uncritical use of this method, since it is prone to overfitting and may aggravate problems of false discoveries. In many applications involving a small number of subjects or samples, predictive model performance estimation is only based on cross-validation (CV) results with a strong preference for reporting results using leave one out (LOO). The combination of PLS-DA for high dimensionality data and small sample conditions, together with a weak validation methodology is a recipe for unreliable estimations of model performance. In this work, we present a systematic study about the impact of the dataset size, the dimensionality, and the CV technique used on PLS-DA overoptimism when performance estimation is done in cross-validation. Firstly, by using synthetic data generated from a same probability distribution and with assigned random binary labels, we have obtained a dataset where the true classification rate (CR) is 50%. As expected, our results confirm that internal validation provides overoptimistic estimations of the classification accuracy (i.e., overfitting). We have characterized the CR estimator in terms of bias and variance depending on the internal CV technique used and sample to dimensionality ratio. In small sample conditions, due to the large bias and variance of the estimator, the occurrence of extremely good CRs is common. We have found that overfitting peaks when the sample size in the training subset approaches the feature vector dimensionality minus one. In these conditions, the models are neither under- or overdetermined with a unique solution. This effect is particularly intense for LOO and peaks higher in small sample conditions. Overoptimism is decreased beyond this point where the abundance of noisy produces a regularization effect leading to less complex models. In terms of overfitting, our study ranks CV methods as follows: Bootstrap produces the most accurate estimator of the CR, followed by bootstrapped Latin partitions, random subsampling, K-Fold, and finally, the very popular LOO provides the worst results. Simulation results are further confirmed in real datasets from mass spectrometry and microarrays.

Screening inhibitors of xanthine oxidase from natural products using enzyme immobilized magnetic beads by high-performance liquid chromatography coupled with tandem mass spectrometry

In this study, high-performance liquid chromatography coupled with tandem mass spectrometry was used to assess the results of bioactive compound screening from natural products using immobilized enzyme magnetic beads. We compared three commercial magnetic beads with modified amino, carboxy, and N-hydroxysuccinimide groups, respectively. Amino magnetic beads performed best for immobilization and were selected for further experiments. Xanthine oxidase was immobilized on amino magnetic beads and applied to screen potential inhibitors in fresh Zingiber officinale Roscoe, extracts of Scutellaria baicalensis Georgi, and Pueraria lobata Ohwi. In total, 12 potential xanthine oxidase ligands were identified from fresh Zingiber root and Scutellaria root extracts, of which eight were characterized and the concentration required for 50% inhibition was determined. Preliminary structure-function relationships were discussed based on these results. A convenient and effective method was therefore developed for the identification of active compounds from complex natural product mixtures.

A simple and rapid infrared-assisted self enzymolysis extraction method for total flavonoid aglycones extraction from Scutellariae Radix and mechanism exploration

A new, simple, and fast infrared-assisted self enzymolysis extraction (IRASEE) approach for the extraction of total flavonoid aglycones (TFA) mainly including baicalein, wogonin, and oroxylin A from Scutellariae Radix is presented to enhance extraction yield. Extraction enzymolysis temperature, enzymolysis liquid-to-solid ratio, enzymolysis pH, enzymolysis time and infrared power, the factors affecting IRASEE procedure, were investigated in a newly designed, temperature-controlled infrared-assisted extraction (TC-IRAE) system to acquire the optimum analysis conditions. The results illustrated that IRASEE possessed great advantages in terms of efficiency and time compared with other conventional extraction techniques. Furthermore, the mechanism of IRASEE was preliminarily explored by observing the microscopic change of the samples surface structures, studying the main chemical compositions change of the samples before and after extraction and investigating the kinetics and thermodynamics at three temperature levels during the IRASEE process. These findings revealed that IRASEE can destroy the surface microstructures to accelerate the mass transfer and reduce the activation energy to intensify the chemical process. This integrative study presents a simple, rapid, efficient, and environmental IRASEE method for TFA extraction which has promising prospects for other similar herbal medicines. Graphical Abstract ᅟ.

Metabolomics combined with pattern recognition and bioinformatics analysis methods for the development of pharmacodynamic biomarkers on liver fibrosis

Metabolomics combined with pattern recognition and network analysis maybe an attractive strategy for the pharmacodynamics biomarkers development on liver fibrosis.

High-throughput and multi-dimensional omics approach uncovers a huaxian capsule to ameliorate the dysregulated expression profiling of severe sepsis rats

Multi-dimensional omics could be helpful to interpret the underlying mechanisms of disease.

Kidney Tissue Targeted Metabolic Profiling of Unilateral Ureteral Obstruction Rats by NMR

Renal interstitial fibrosis is a common pathological process in the progression of kidney disease. A nuclear magnetic resonance (NMR) based metabolomic approach was used to analyze the kidney tissues of rats with renal interstitial fibrosis (RIF), induced by unilateral ureteral obstruction (UUO). The combination of a variety of statistical methods were used to screen out 14 significantly changed potential metabolites, which are related with multiple biochemical processes including amino acid metabolism, adenine metabolism, energy metabolism, osmolyte change and induced oxidative stress. The exploration of the contralateral kidneys enhanced the understanding of the disease, which was also supported by serum biochemistry and kidney histopathology results. In addition, the pathological parameters (clinical chemistry, histological and immunohistochemistry results) were correlated with the significantly changed differential metabolites related with RIF. This study showed that targeted tissue metabolomic analysis can be used as a useful tool to understand the mechanism of the disease and provide a novel insight in the pathogenesis of RIF.