Metabolomics in chronic kidney disease

The current use of proteomics and metabolomics in glomerulonephritis: a systematic literature review

BACKGROUND

Glomerulonephritis inherently leads to the development of chronic kidney disease. It is the second most common diagnosis in patients requiring renal replacement therapy in the United Kingdom. Metabolomics and proteomics can characterise, identify and quantify an individual's protein and metabolite make-up. These techniques have been optimised and can be performed on samples including kidney tissue, blood and urine. Utilising omic techniques in nephrology can uncover disease pathophysiology and transform the diagnostics and treatment options for glomerulonephritis.

OBJECTIVES

To evaluate the utility of metabolomics and proteomics using mass spectrometry and nuclear magnetic resonance in glomerulonephritis.

METHODS

The systematic review was registered on PROSPERO (CRD42023442092). Standard and extensive Cochrane search methods were used. The latest search date was March 2023. Participants were of any age with a histological diagnosis of glomerulonephritis. Descriptive analysis was performed, and data presented in tabular form. An area under the curve or p-value was presented for potential biomarkers discovered.

RESULTS

Twenty-seven studies were included (metabolomics (n = 9)), and (proteomics (n = 18)) with 1818 participants. The samples analysed were urine (n = 19) blood (n = 4) and biopsy (n = 6). The typical outcome themes were potential biomarkers, disease phenotype, risk of progression and treatment response.

CONCLUSION

This review shows the potential of metabolomic and proteomic analysis to discover new disease biomarkers that may influence diagnostics and disease management. Further larger-scale research is required to establish the validity of the study outcomes, including the several proposed biomarkers.

Lipid metabolism disorder in diabetic kidney disease

Diabetic kidney disease (DKD), a significant complication associated with diabetes mellitus, presents limited treatment options. The progression of DKD is marked by substantial lipid disturbances, including alterations in triglycerides, cholesterol, sphingolipids, phospholipids, lipid droplets, and bile acids (BAs). Altered lipid metabolism serves as a crucial pathogenic mechanism in DKD, potentially intertwined with cellular ferroptosis, lipophagy, lipid metabolism reprogramming, and immune modulation of gut microbiota (thus impacting the liver-kidney axis). The elucidation of these mechanisms opens new potential therapeutic pathways for DKD management. This research explores the link between lipid metabolism disruptions and DKD onset.

Cross-sectional analyses of metabolites across biological samples mediating dietary acid load and chronic kidney disease

Chronic kidney disease (CKD) is a major public health burden, with dietary acid load (DAL) and gut microbiota playing crucial roles. As DAL can affect the host metabolome, potentially via the gut microbiota, we cross-sectionally investigated the interplay between DAL, host metabolome, gut microbiota, and early-stage CKD (TwinsUK, n = 1,453). DAL was positively associated with CKD stage G1-G2 (Beta (95% confidence interval) = 0.34 (0.007; 0.7), p = 0.046). After adjusting for covariates and multiple testing, we identified 15 serum, 14 urine, 8 stool, and 7 saliva metabolites, primarily lipids and amino acids, associated with both DAL and CKD progression. Of these, 8 serum, 2 urine, and one stool metabolites were found to mediate the DAL-CKD association. Furthermore, the stool metabolite 5-methylhexanoate (i7:0) correlated with 26 gut microbial species. Our findings emphasize the gut microbiota's therapeutic potential in countering DAL's impact on CKD through the host metabolome. Interventional and longitudinal studies are needed to establish causality.

Identification of novel serum metabolic signatures to predict chronic kidney disease among Chinese elders using UPLC-Orbitrap-MS

BACKGROUND

Chronic kidney disease (CKD) is a major public health concern. However, validated and broadly applicable biomarkers for early CKD diagnosis are currently not available. We aimed to identify serum metabolic signatures at an early stage of CKD to provide a reference for future investigations into the early diagnostic biomarkers.

METHODS

Serum metabolites were extracted from 65 renal dysfunction (RD) patients and 121 healthy controls (discovery cohort: 12 RD patients and 55 health participants; validation cohort: 53 RD patients and 66 health participants). Metabolite extracts were analyzed by ultraperformance liquid chromatography coupled with quadrupole-electrostatic field orbital trap mass spectrometry (UPLC-QE-Orbitrap MS) for untargeted metabolomics. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was performed to detect different compounds between groups. Receiver operating characteristic (ROC) curve analysis was carried out to determine the diagnostic value of the validated differential metabolites between groups. We referred to the Kyoto Encyclopedia of Gene and Genomes (KEGG) to elucidate the metabolic pathways of the validated differential metabolites.

RESULTS

A total of 22 and 23 metabolites had significantly different abundances in the discovery and validation cohort, respectively. Six of them (creatinine, L-proline, citrulline, butyrylcarnitine, 1-methylhistidine, and valerylcarnitine) in the RD group was more abundant than that of the health group in both cohorts. The combination of the six validated differential metabolites were able to accurately detect RD (AUC 0.86). Three of the six metabolites are involved in the metabolism of arginine and proline.

CONCLUSIONS

The present study highlights that creatinine, L-proline, citrulline, butyrylcarnitine, 1-methylhistidine, and valerylcarnitine are metabolite indicators with potential predictive value for CKD.

A systematic review of metabolomic findings in adult and pediatric renal disease

Chronic kidney disease (CKD) affects over 0.5 billion people worldwide across their lifetimes. Despite a growingly ageing world population, an increase in all-age prevalence of kidney disease persists. Adult-onset forms of kidney disease often result from lifestyle-modifiable metabolic illnesses such as type 2 diabetes. Pediatric and adolescent forms of renal disease are primarily caused by morphological abnormalities of the kidney, as well as immunological, infectious and inherited metabolic disorders. Alterations in energy metabolism are observed in CKD of varying causes, albeit the molecular mechanisms underlying pathology are unclear. A systematic indexing of metabolites identified in plasma and urine of patients with kidney disease alongside disease enrichment analysis uncovered inborn errors of metabolism as a framework that links features of adult and pediatric kidney disease. The relationship of genetics and metabolism in kidney disease could be classified into three distinct landscapes: (i) Normal genotypes that develop renal damage because of lifestyle and / or comorbidities; (ii) Heterozygous genetic variants and polymorphisms that result in unique metabotypes that may predispose to the development of kidney disease via synergistic heterozygosity, and (iii) Homozygous genetic variants that cause renal impairment by perturbing metabolism, as found in children with monogenic inborn errors of metabolism. Interest in the identification of early biomarkers of onset and progression of CKD has grown steadily in the last years, though it has not translated into clinical routine yet. This systematic review indexes findings of differential concentration of metabolites and energy pathway dysregulation in kidney disease and appraises their potential use as biomarkers.

Metabolome panels as potential noninvasive biomarkers for primary glomerulonephritis sub-types: meta-analysis of profiling metabolomics studies

Primary glomerulonephritis diseases (PGDs) are known as the top causes of chronic kidney disease worldwide. Renal biopsy, an invasive method, is the main approach to diagnose PGDs. Studying the metabolome profiles of kidney diseases is an inclusive approach to identify the disease's underlying pathways and discover novel non-invasive biomarkers. So far, different experiments have explored the metabolome profiles in different PGDs, but the inconsistencies might hinder their clinical translations. The main goal of this meta-analysis study was to achieve consensus panels of dysregulated metabolites in PGD sub-types. The PGDs-related metabolome profiles from urine samples in humans were selected in a comprehensive search. Amanida package in R software was utilized for performing the meta-analysis. Through sub-type analyses, the consensus list of metabolites in each category was obtained. To identify the most affected pathways, functional enrichment analysis was performed. Also, a gene-metabolite network was constructed to identify the key metabolites and their connected proteins. After a vigorous search, among the 11 selected studies (15 metabolite profiles), 270 dysregulated metabolites were recognized in urine of 1154 PGDs and control samples. Through sub-type analyses by Amanida package, the consensus list of metabolites in each category was obtained. Top dysregulated metabolites (vote score of ≥ 4 or ≤ - 4) in PGDs urines were selected as main panel of meta-metabolites including glucose, leucine, choline, betaine, dimethylamine, fumaric acid, citric acid, 3-hydroxyisovaleric acid, pyruvic acid, isobutyric acid, and hippuric acid. The enrichment analyses results revealed the involvement of different biological pathways such as the TCA cycle and amino acid metabolisms in the pathogenesis of PGDs. The constructed metabolite-gene interaction network revealed the high centralities of several metabolites, including pyruvic acid, leucine, and choline. The identified metabolite panels could shed a light on the underlying pathological pathways and be considered as non-invasive biomarkers for the diagnosis of PGD sub-types.

Single-cell landscape and spatial transcriptomic analysis reveals macrophage infiltration and glycolytic metabolism in kidney renal clear cell carcinoma

The present study investigates the clinical relevance of glycolytic factors, specifically PGAM1, in the tumor microenvironment of kidney renal clear cell carcinoma (KIRC). Despite the established role of glycolytic metabolism in cancer pathophysiology, the prognostic implications and key targets in KIRC remain elusive. We analyzed GEO and TCGA datasets to identify DEGs in KIRC and studied their relationship with immune gene expression, survival, tumor stage, gene mutations, and infiltrating immune cells. We explored Pgam1 gene expression in different kidney regions using spatial transcriptomics after mouse kidney injury analysis. Single-cell RNA-sequencing was used to assess the association of PGAM1 with immune cells. Findings were validated with tumor specimens from 60 KIRC patients, correlating PGAM1 expression with clinicopathological features and prognosis using bioinformatics and immunohistochemistry. We demonstrated the expression of central gene regulators in renal cancer in relation to genetic variants, deletions, and tumor microenvironment. Mutations in these hub genes were positively associated with distinct immune cells in six different immune datasets and played a crucial role in immune cell infiltration in KIRC. Single-cell RNA-sequencing revealed that elevated PGAM1 was associated with immune cell infiltration, specifically macrophages. Furthermore, pharmacogenomic analysis of renal cancer cell lines indicated that inactivation of PGAM1 was associated with increased sensitivity to specific small-molecule drugs. Altered PGAM1 in KIRC is associated with disease progression and immune microenvironment. It has diagnostic and prognostic implications, indicating its potential in precision medicine and drug screening.

Nephrotoxicity assessment of podophyllotoxin-induced rats by regulating PI3K/Akt/mTOR-Nrf2/HO1 pathway in view of toxicological evidence chain (TEC) concept

Adverse reactions to traditional Chinese medicine have hindered the healthy development and internationalization process of the traditional Chinese medicine industry. The critical issue that needs to be solved urgently is to evaluate the safety of traditional Chinese medicine systematically and effectively. Podophyllotoxin (PPT) is a highly active compound extracted from plants of the genus Podophyllum such as Dysosma versipellis (DV). However, its high toxicity and toxicity to multiple target organs affect the clinical application, such as the liver and kidney. Based on the concurrent effects of PPT's medicinal activity and toxicity, it would be a good example to conduct a systematic review of its safety. Therefore, this study revolves around the Toxicological Evidence Chain (TEC) concept. Based on PPT as the main toxic constituent in DV, observe the objective toxicity impairment phenotype of animals. Evaluate the serum biochemical indicators and pathological tissue sections for substantial toxic damage results. Using metabolomics, lipidomics, and network toxicology to evaluate the nephrotoxicity of PPT from multiple perspectives systematically. The results showed that PPT-induced nephrotoxicity manifested as renal tubular damage, mainly affecting metabolic pathways such as glycerophospholipid metabolism and sphingolipid metabolism. PPT inhibits the autophagy process of kidney cells through the PI3K/Akt/mTOR and Nrf2/HO1 pathways and induces the activation of oxidative stress in the body, thereby causing nephrotoxic injury. This study fully verified the feasibility of the TEC concept for the safety and toxicity evaluation of traditional Chinese medicine. Provide a research template for systematically evaluating the safety of traditional Chinese medicine.

Altered serum metabolic profile in patients with IgA nephropathy

BACKGROUND

We investigated alterations in the serum metabolomic profile of IgA nephropathy (IgAN) patients and screen biomarkers of IgA nephropathy based on ultra-performance liquid chromatography-mass spectrometry (UPLC-MS).

METHODS

Serum samples from 65 IgAN patients and 31 healthy controls were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). Univariate and multivariate analysis were performed to screen the differential metabolites. Differential metabolites should meet both the following two criteria: adjusted P < 0.05 in the univariate analysis and VIP value > 1 in the multivariate model. Pathway analysis was performed to reveal the metabolic pathways that were significantly influenced in IgAN. Spearman correlation analysis was applied to explore the correlation between metabolites and between the metabolites and clinicopathological features of IgAN. A random forest model and Logistics regression analysis were conducted to evaluate the predictive ability of the metabolites.

RESULTS

The metabolic profile was significantly altered in IgAN patients compared with healthy controls. Thirty-nine metabolites were identified, including glycerophospholipids, sphingolipids, vitamin K1, vitamin K2, bile acids and amino acids. Sphingolipid metabolism, ubiquinone and other terpenoid-quinone biosynthesis, and glycerophospholipid metabolism were found to be significantly disturbed in the pathway analysis. Differential metabolites were found to be associated with the clinical and pathological features of IgAN patients. Lanosterol, vitamin K1, vitamin K2, and β-elemonic acid were found to have promising predictive ability for IgAN.

CONCLUSIONS

We confirmed the differences in the metabolic profiles of IgAN patients and healthy controls and identified the differential metabolites of IgAN, which may help with the further exploration of the pathogenesis and treatment of IgAN.

Metabolomics profiling distinctively identified end-stage renal disease patients from chronic kidney disease patients

Chronic kidney disease (CKD) is a serious public health problem characterized by progressive kidney function loss leading to end-stage renal disease (ESRD) that demands dialysis or kidney transplantation. Early detection can prevent or delay progression to ESRD. The study aimed to gain new insights into the perturbed biochemical reactions and to identify novel distinct biomarkers between ESRD and CKD. Serum samples of 32 patients with ESRD (n = 13) and CKD (n = 19) were analyzed using chemical isotope labeling liquid chromatography-mass spectrometry metabolomics approach. A total of 193 metabolites were significantly altered in ESRD compared to CKD and were mainly involved in aminoacyl-tRNA biosynthesis, branched-chain amino acid (BCAA) biosynthesis, taurine metabolism, and tryptophan metabolism. Three kynurenine derivatives, namely, 2-aminobenzoic acid, xanthurenic acid, and hydroxypicolinic acid were upregulated in ESRD compared to CKD due to the significant decrease in glomerular filtration rate with the progression of CKD to ESRD. N-Hydroxy-isoleucine, 2-aminobenzoic acid, and picolinic acid yielded AUC > 0.99 when analyzed using Receiver Operating Characteristic (ROC) analysis. Our findings suggest that inhibiting the kynurenine pathway might be a promising target to delay CKD progression and that metabolites with high discriminative ability might serve as potential prognostic biomarkers to monitor the progression of CKD to ESRD or used in combination with current markers to indicate the status of kidney damage better.

Integrative phosphatidylcholine metabolism through phospholipase A2 in rats with chronic kidney disease

Dysregulation in lipid metabolism is the leading cause of chronic kidney disease (CKD) and also the important risk factors for high morbidity and mortality. Although lipid abnormalities were identified in CKD, integral metabolic pathways for specific individual lipid species remain to be clarified. We conducted ultra-high-performance liquid chromatography-high-definition mass spectrometry-based lipidomics and identified plasma lipid species and therapeutic effects of Rheum officinale in CKD rats. Adenine-induced CKD rats were administered Rheum officinale. Urine, blood and kidney tissues were collected for analyses. We showed that exogenous adenine consumption led to declining kidney function in rats. Compared with control rats, a panel of differential plasma lipid species in CKD rats was identified in both positive and negative ion modes. Among the 50 lipid species, phosphatidylcholine (PC), lysophosphatidylcholine (LysoPC) and lysophosphatidic acid (LysoPA) accounted for the largest number of identified metabolites. We revealed that six PCs had integral metabolic pathways, in which PC was hydrolysed into LysoPC, and then converted to LysoPA, which was associated with increased cytosolic phospholipase A2 protein expression in CKD rats. The lower levels of six PCs and their corresponding metabolites could discriminate CKD rats from control rats. Receiver operating characteristic curves showed that each individual lipid species had high values of area under curve, sensitivity and specificity. Administration of Rheum officinale significantly improved impaired kidney function and aberrant PC metabolism in CKD rats. Taken together, this study demonstrates that CKD leads to PC metabolism disorders and that the dysregulation of PC metabolism is involved in CKD pathology.

CXCL12/CXCR4: An amazing challenge and opportunity in the fight against fibrosis

Fibrosis is a pathological process caused by abnormal wound healing response, which often leads to excessive deposition of extracellular matrix, distortion of organ architecture, and loss of organ function. Aging is an important risk factor for the development of organ fibrosis. C-X-C receptor 4 (CXCR4) is the predominant chemokine receptor on fibrocytes, C-X-C motif ligand 12 (CXCL12) is the only ligand of CXCR4. Accumulated evidence have confirmed that CXCL12/CXCR4 can be involved in multiple pathological mechanisms in fibrosis, such as inflammation, immunity, epithelial-mesenchymal transition, and angiogenesis. In addition, CXCL12/CXCR4 have also been shown to improve fibrosis levels in many organs including the heart, liver, lung and kidney; thus, they are promising targets for anti-fibrotic therapy. Notably, inhibitors of CXCL12 or CXCR4 also play an important role in various fibrosis-related diseases. In summary, this review systematically summarizes the role of CXCL12/CXCR4 in fibrosis, and this information is of great significance for understanding CXCL12/CXCR4. This will also contribute to the design of further studies related to CXCL12/CXCR4 and fibrosis, and shed light on potential therapies for fibrosis.

Lipidic profiles of patients starting peritoneal dialysis suggest an increased cardiovascular risk beyond classical dyslipidemia biomarkers

Patients on peritoneal dialysis (PD) have an increased risk of cardiovascular disease (CVD) and an atherogenic lipid profile generated by exposure to high glucose dialysis solutions. In the general population, the reduction of classic lipids biomarkers is associated with improved clinical outcomes; however, the same results have not been seen in PD population, a lack of data this study aims to fulfill. Single-center prospective observational study of a cohort of CKD patients who started renal replacement therapy with continuous ambulatory peritoneal dialysis. The differences in the lipid profile and analytical variables before and 6 months after the start of peritoneal dialysis were analyzed. Samples were analyzed on an Ultra-Performance Liquid Chromatography system. Thirty-nine patients were enrolled in this study. Their mean age was 57.9 ± 16.3 years. A total of 157 endogenous lipid species of 11 lipid subclasses were identified. There were significant increases in total free fatty acids (p < 0.05), diacylglycerides (p < 0.01), triacylglycerides, (p < 0.01), phosphatidylcholines (p < 0.01), phosphatidylethanolamines (p < 0.01), ceramides (p < 0.01), sphingomyelins (p < 0.01), and cholesterol esters (p < 0.01) from baseline to 6 months. However, there were no differences in the classical lipid markers, neither lysophosphatidylcholines, monoacylglycerides, and sphingosine levels. 6 months after the start of the technique, PD patients present changes in the lipidomic profile beyond the classic markers of dyslipidemia.

Membranous nephropathy: Systems biology-based novel mechanism and traditional Chinese medicine therapy

Membranous nephropathy (MN) is a renal-limited non-inflammatory autoimmune disease in the glomerulus, which is the second or third main cause of end-stage kidney diseases in patients with primary glomerulonephritis. Substantial achievements have increased our understanding of the aetiology and pathogenesis of murine and human MN. The identification of nephritogenic autoantibodies against neutral endopeptidase, phospholipase A₂ receptor (PLA₂R) and thrombospondin type-1 domain-containing 7A (THSD7A) antigens provide more specific concept-driven intervention strategies for treatments by specific B cell-targeting monoclonal antibodies to inhibit antibody production and antibody-antigen immune complex deposition. Furthermore, additional antibody specificities for antigens have been discovered, but their pathogenic effects are uncertain. Although anti-PLA₂R and anti-THSD7A antibodies as a diagnostic marker is widely used in MN patients, many questions including autoimmune response development, antigenic epitopes, and podocyte damage signalling pathways remain unresolved. This review describes the current available evidence regarding both established and novel molecular mechanisms based on systems biology approaches (gut microbiota, long non-coding RNAs, metabolite biomarkers and DNA methylation) in MN, with an emphasis on clinical findings. This review further summarizes the applications of traditional Chinese medicines such as Tripterygium wilfordii and Astragalus membranaceus for MN treatment. Lastly, this review considers how the identification of novel antibodies/antigens and unresolved questions and future challenges reveal the pathogenesis of MN.

Urinary metabolomics to develop predictors for pediatric acute kidney injury

BACKGROUND

Acute kidney injury (AKI) is characterized by an abrupt decline in glomerular filtration rate (GFR). We sought to identify separate early urinary metabolomic signatures at AKI onset (with-AKI) and prior to onset of functional impairment (pre-AKI).

METHODS

Pre-AKI (n=15), AKI (n=22), and respective controls (n=30) from two prospective PICU cohort studies provided urine samples which were analyzed by GC-MS and DI-MS mass spectrometry (193 metabolites). The cohort (n=58) was 8.7±6.4 years old and 66% male. AKI patients had longer PICU stays, higher PRISM scores, vasopressors requirement, and respiratory diagnosis and less commonly had trauma or post-operative diagnosis. Urine was collected within 2-3 days after admission and daily until day 5 or 14.

RESULTS

The metabolite classifiers for pre-AKI samples (1.5±1.1 days prior to AKI onset) had a cross-validated area under receiver operator curve (AUC)=0.93 (95%CI 0.85-1.0); with-AKI samples had an AUC=0.94 (95%CI 0.87-1.0). A parsimonious pre-AKI classifier with 13 metabolites was similarly robust (AUC=0.96, 95%CI 0.89-1.0). Both classifiers were similar and showed modest correlation of high-ranking metabolites (tau=0.47, p<0.001).

CONCLUSIONS

This exploratory study demonstrates the potential of a urine metabolite classifier to detect AKI-risk in pediatric populations earlier than the current standard of diagnosis with the need for external validation. A higher resolution version of the Graphical abstract is available as Supplementary information with inner reference to ESM for GA.

Host/microbiota interactions-derived tryptophan metabolites modulate oxidative stress and inflammation via aryl hydrocarbon receptor signaling

Aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that induces the expression of a broad range of downstream genes such as cytochromes P450 enzymes and cyclooxygenase-2. Recent research focuses are shifting from AhR activation induced by xenobiotics to its response patterns to physiological ligands that expand our understanding of how endogenous metabolites as ligands to modulate AhR signaling pathway under homeostasis and pathological conditions. With increasing interest in AhR and its endogenous ligands, it would seem advisable to summarize a variety of endogenous ligands especially host/gut microbiota-derived tryptophan metabolites. Mounting evidence has indicated that AhR play a critical role in the regulation of redox homeostasis and immune responses. In this review, we outline the canonical and non-canonical AhR signalling pathway that is mediated by host/gut microbiota-derived tryptophan metabolites. Through several typical endogenous AhR ligands, we investigated the molecular mechanisms of AhR-induced oxidative stress and inflammation in the pathological milieu, including diabetes, diabetic kidney disease and end-stage renal disease. Finally, we summarize and emphasize the limitations and breakthrough of endogenous AhR ligands from host/microbial tryptophan catabolites. This review might provide novel diagnostic and prognostic approach for refractory human diseases and establish new therapeutic strategies for AhR activation.

Emerging Biomarkers for Early Detection of Chronic Kidney Disease

Chronic kidney disease (CKD) is a major and serious global health problem that leads to kidney damage as well as multiple systemic diseases. Early diagnosis and treatment are two major measures to prevent further deterioration of kidney function and to delay adverse outcomes. However, the paucity of early, predictive and noninvasive biomarkers has undermined our ability to promptly detect and treat this common clinical condition which affects more than 10% of the population worldwide. Despite all limitations, kidney function is still measured by serum creatinine, cystatin C, and albuminuria, as well as estimating glomerular filtration rate using different equations. This review aims to provide comprehensive insight into diagnostic methods available for early detection of CKD. In the review, we discuss the following topics: (i) markers of glomerular injury; (ii) markers of tubulointerstitial injury; (iii) the role of omics; (iv) the role of microbiota; (v) and finally, the role of microRNA in the early detection of CKD. Despite all novel findings, none of these biomarkers have met the criteria of an ideal early marker. Since the central role in CKD progression is the proximal tubule (PT), most data from the literature have analyzed biomarkers of PT injury, such as KIM-1 (kidney injury molecule-1), NGAL (neutrophil gelatinase-associated lipocalin), and L-FABP (liver fatty acid-binding protein).

In-depth characterisation of the urine metabolome in cats with and without urinary tract diseases

INTRODUCTION

Our understanding of the urine metabolome and its association with urinary tract disease is limited in cats.

OBJECTIVES

We conducted a case-control study to characterise the feline urine metabolome, investigate its association with chronic kidney disease (CKD) and feline idiopathic cystitis (FIC), and assess its compositional relationship with the urine microbiome.

METHODS

The urine metabolome of 45 owned cats, including 23 controls, 16 CKD, and 6 FIC cases, was characterised by an untargeted metabolomics approach using high-performance chemical isotope labelling liquid chromatography-mass spectrometry.

RESULTS

We detected 9411 unique compounds in the urine of controls and cases and identified 1037 metabolites with high confidence. Amino acids, peptides, and analogues dominated these metabolites (32.2%), followed by carbonyl compounds (7.1%) and carbohydrates (6.5%). Seven controls from one household showed a significant level of metabolome clustering, with a distinct separation from controls from other households (p value < 0.001). Owner surveys revealed that this cluster of cats was fed dry food only, whereas all but one other control had wet food in their diet. Accordingly, the diet type was significantly associated with the urine metabolome composition in our multivariate model (p value = 0.001). Metabolites significantly altered in this cluster included taurine, an essential amino acid in cats. Urine metabolome profiles were not significantly different in CKD and FIC cases compared with controls, and no significant compositional relationship was detected between the urine metabolome and microbiome.

CONCLUSION

Our study reveals in-depth diversity of the feline urine metabolome composition, and suggests that it can vary considerably depending on environmental factors.

Urinary and plasma metabolome of farm mink (Neovison vison) after an intervention with raw or cooked poultry offal: a 1H NMR investigation

The introduction of high amounts of cooked poultry offal in mink feed has been associated with health problems in growing mink. Cooking mink feed is a convenient way of reducing microbiological activity, but it may have a negative effect on raw material quality and animal welfare. This study investigates growth and health of mink fed raw or cooked poultry offal and describes urinary and blood plasma metabolic changes related to the feeding. A total of 65 male mink were divided in three feeding groups, two fed cooked offal and one group fed raw offal, and the plasma and urine samples were collected at 3 time points during the growth. Both bio-fluids and feed samples were measured by ¹H NMR spectroscopy and resulted metabolomics data were analysed using univariate and multivariate statistical methods that revealed dominating effect of the mink growth stages and to a less extent the feeding regime. Metabolome differences in relation to low body mass index (BMI) and kidney lesions were observed in plasma. Disease and decrease in BMI was associated with high creatinine and dimethylglycine content in plasma. These molecules were also particularly indicative of the cooked feeds. Moreover, low urinary taurine levels were also associated with disease and low BMI. Individual mink appeared to show negative effects of the cooked feed diet, including impaired growth and gross pathological lesions involving the kidneys. This may be related to the absorption of essential metabolites such as amino acids and fats, necessary for mink growth, that are negatively impacted by the cooking process.

Estimated Renal Metabolomics at Reperfusion Predicts One-Year Kidney Graft Function

Renal transplantation is the gold-standard procedure for end-stage renal disease patients, improving quality of life and life expectancy. Despite continuous advancement in the management of post-transplant complications, progress is still needed to increase the graft lifespan. Early identification of patients at risk of rapid graft failure is critical to optimize their management and slow the progression of the disease. In 42 kidney grafts undergoing protocol biopsies at reperfusion, we estimated the renal metabolome from RNAseq data. The estimated metabolites' abundance was further used to predict the renal function within the first year of transplantation through a random forest machine learning algorithm. Using repeated K-fold cross-validation we first built and then tuned our model on a training dataset. The optimal model accurately predicted the one-year eGFR, with an out-of-bag root mean square root error (RMSE) that was 11.8 ± 7.2 mL/min/1.73 m2. The performance was similar in the test dataset, with a RMSE of 12.2 ± 3.2 mL/min/1.73 m2. This model outperformed classic statistical models. Reperfusion renal metabolome may be used to predict renal function one year after allograft kidney recipients.

OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction

Chronic kidney disease (CKD) patients are characterized by a high residual risk for cardiovascular (CV) events and CKD progression. This has prompted the implementation of new prognostic and predictive biomarkers with the aim of mitigating this risk. The ‘omics’ techniques, namely genomics, proteomics, metabolomics, and transcriptomics, are excellent candidates to provide a better understanding of pathophysiologic mechanisms of disease in CKD, to improve risk stratification of patients with respect to future cardiovascular events, and to identify CKD patients who are likely to respond to a treatment. Following such a strategy, a reliable risk of future events for a particular patient may be calculated and consequently the patient would also benefit from the best available treatment based on their risk profile. Moreover, a further step forward can be represented by the aggregation of multiple omics information by combining different techniques and/or different biological samples. This has already been shown to yield additional information by revealing with more accuracy the exact individual pathway of disease.

Shenkang Injection and Its Three Anthraquinones Ameliorates Renal Fibrosis by Simultaneous Targeting IƙB/NF-ƙB and Keap1/Nrf2 Signaling Pathways

Oxidative stress and inflammation are important and critical mediators in the development and progression of chronic kidney disease (CKD) and its complications. Shenkang injection (SKI) has been widely used to treat patients with CKD. Although the anti-oxidative and anti-inflammatory activity was involved in SKI against CKD, its bioactive components and underlying mechanism remain enigmatic. A rat model of adenine-induced chronic renal failure (CRF) is associated with, and largely driven by, oxidative stress and inflammation. Hence, we identified the anti-oxidative and anti-inflammatory components of SKI and further revealed their underlying mechanism in the adenine-induced CRF rats. Compared with control rats, the levels of creatinine, urea, uric acid, total cholesterol, triglyceride, and low-density lipoprotein cholesterol in serum were significantly increased in the adenine-induced CRF rats. However, treatment with SKI and its three anthraquinones including chrysophanol, emodin, and rhein could reverse these aberrant changes. They could significantly inhibit pro-fibrotic protein expressions including collagen I, α-SMA, fibronectin, and vimentin in the kidney tissues of the adenine-induced CRF rats. Of note, SKI and rhein showed the stronger inhibitory effect on these pro-fibrotic protein expressions than chrysophanol and emodin. Furthermore, they could improve dysregulation of IƙB/NF-ƙB and Keap1/Nrf2 signaling pathways. Chrysophanol and emodin showed the stronger inhibitory effect on the NF-κB p65 protein expression than SKI and rhein. Rhein showed the strongest inhibitory effect on p65 downstream target gene products including NAD(P)H oxidase subunits (p47phox, p67phox, and gp91phox) and COX-2, MCP-1, iNOS, and 12-LO in the kidney tissues. However, SKI and rhein showed the stronger inhibitory effect on the significantly downregulated anti-inflammatory and anti-oxidative protein expression nuclear Nrf2 and its target gene products including HO-1, catalase, GCLC, and NQO1 in the Keap1/Nrf2 signaling pathway than chrysophanol and emodin. This study first demonstrated that SKI and its major components protected against renal fibrosis by inhibiting oxidative stress and inflammation via simultaneous targeting IƙB/NF-ƙB and Keap1/Nrf2 signaling pathways, which illuminated the potential molecular mechanism of anti-oxidative and anti-inflammatory effects of SKI.

A knock-in rat model unravels acute and chronic renal toxicity in glutaric aciduria type I

Glutaric aciduria type I (GA-I, OMIM # 231670) is an autosomal recessive inborn error of metabolism caused by deficiency of the mitochondrial enzyme glutaryl-CoA dehydrogenase (GCDH). The principal clinical manifestation in GA-I patients is striatal injury most often triggered by catabolic stress. Early diagnosis by newborn screening programs improved survival and reduced striatal damage in GA-I patients. However, the clinical phenotype is still evolving in the aging patient population. Evaluation of long-term outcome in GA-I patients recently identified glomerular filtration rate (GFR) decline with increasing age. We recently created the first knock-in rat model for GA-I harboring the mutation p.R411W (c.1231 C>T), corresponding to the most frequent GCDH human mutation p.R402W. In this study, we evaluated the effect of an acute metabolic stress in form of high lysine diet (HLD) on young Gcdh^ki/ki rats. We further studied the chronic effect of GCDH deficiency on kidney function in a longitudinal study on a cohort of Gcdh^ki/ki rats by repetitive ⁶⁸Ga-EDTA positron emission tomography (PET) renography, biochemical and histological analyses. In young Gcdh^ki/ki rats exposed to HLD, we observed a GFR decline and biochemical signs of a tubulopathy. Histological analyses revealed lipophilic vacuoles, thinning of apical brush border membranes and increased numbers of mitochondria in proximal tubular (PT) cells. HLD also altered OXPHOS activities and proteome in kidneys of Gcdh^ki/ki rats. In the longitudinal cohort, we showed a progressive GFR decline in Gcdh^ki/ki rats starting at young adult age and a decline of renal clearance. Histopathological analyses in aged Gcdh^ki/ki rats revealed tubular dilatation, protein accumulation in PT cells and mononuclear infiltrations. These observations confirm that GA-I leads to acute and chronic renal damage. This raises questions on indication for follow-up on kidney function in GA-I patients and possible therapeutic interventions to avoid renal damage.

Metabolite Genome-Wide Association Study for Indoleamine 2,3-Dioxygenase Activity Associated with Chronic Kidney Disease

Chronic kidney disease (CKD) causes progressive damage to kidney function with increased inflammation. This process contributes to complex amino acid changes. Indoleamine 2,3-dioxygenase (IDO) has been proposed as a new biomarker of CKD in previous studies. In our research, we performed a metabolite genome-wide association study (mGWAS) to identify common and rare variants associated with IDO activity in a Korean population. In addition, single-nucleotide polymorphisms (SNPs) selected through mGWAS were further analyzed for associations with the estimated glomerular filtration rate (eGFR) and CKD. A total of seven rare variants achieved the genome-wide significance threshold (p < 1 × 10-8). Among them, four genes (TNFRSF19, LOC105377444, LOC101928535, and FSTL5) associated with IDO activity showed statistically significant associations with eGFR and CKD. Most of these rare variants appeared specifically in an Asian geographic region. Furthermore, 15 common variants associated with IDO activity were detected in this study and five novel genes (RSU1, PDGFD, SNX25, LOC107984031, and UBASH3B) associated with CKD and eGFR were identified. This study discovered several loci for IDO activity via mGWAS and provided insight into the underlying mechanisms of CKD through association analysis with CKD. To the best of our knowledge, this is the first study to suggest a genetic link between IDO activity and CKD through comparative and integrated analysis.

Serum metabolomics of end-stage renal disease patients with depression: potential biomarkers for diagnosis

Background

End-stage renal disease (ESRD) is the final stage during the development of renal failure. Depression is the most common psychiatric disorder in patients with ESRD, which in turn aggravates the progression of renal failure, however, its underlying mechanism remains unclear. This study aimed to reveal the pathogenesis and to discover novel peripheral biomarkers for ESRD patients with depression through metabolomic analysis.

Methods

Ultra-high-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) was used to explore changes of serum metabolites among healthy controls, ESRD patients with or without depression. The differential metabolites between groups were subjected to clustering analysis, pathway analysis, receiver operating characteristic (ROC) curve analysis.

Results

A total of 57 significant serum differential metabolites were identified between ESRD patients with or without depression, which were involved in 19 metabolic pathways, such as energy metabolism, glycerolipid metabolism, and glutamate-centered metabolism. Moreover, the area under the ROC curve of gentisic acid, uric acid, 5-hydroxytryptamine, 2-phosphoglyceric acid, leucyl-phenylalanine, propenyl carnitine, naloxone, pregnenolone, 6-thioxanthene 5'-monophosphate, hydroxyl ansoprazole, zileuton O-glucuronide, cabergoline, PA(34:2), PG(36:1), probucol and their combination was greater than 0.90.

Conclusions

Inflammation, oxidative stress and energy metabolism abnormalities, glycerolipid metabolism, and glutamate-centered metabolism are associated with the pathogenesis of ESRD with depression, which may be promising targets for therapy. Furthermore, the identified differential metabolites may serve as biomarkers for the diagnosis of ESRD patients with depression.

1-Hydroxypyrene mediates renal fibrosis through aryl hydrocarbon receptor signalling pathway

BACKGROUND AND PURPOSE

In chronic kidney disease (CKD), patients inevitably reach end-stage renal disease and require renal transplant. Evidence suggests that CKD is associated with metabolite disorders. However, the molecular pathways targeted by metabolites remain enigmatic. Here, we describe roles of 1-hydroxypyrene in mediating renal fibrosis.

EXPERIMENTAL APPROACH

We analysed 5406 urine and serum samples from patients with Stage 1-5 CKD using metabolomics, and 1-hydroxypyrene was identified and validated using longitudinal and drug intervention cohorts as well as 5/6 nephrectomised and adenine-induced rats.

KEY RESULTS

We identified correlations between the urine and serum levels of 1-hydroxypyrene and the estimated GFR in patients with CKD onset and progression. Moreover, increased 1-hydroxypyrene levels in serum and kidney tissues correlated with decreased renal function in two rat models. Up-regulated mRNA expression of aryl hydrocarbon receptor and its target genes, including CYP1A1, CYP1A2 and CYP1B1, were observed in patients and rats with progressive CKD. Further we showed up-regulated mRNA expression of aryl hydrocarbon receptor and its three target genes, plus up-regulated nuclear aryl hydrocarbon receptor protein levels in mice and HK-2 cells treated with 1-hydroxypyrene, which caused accumulation of extracellular matrix components. Treatment with aryl hydrocarbon receptor short hairpin RNA or flavonoids inhibited mRNA expression of aryl hydrocarbon receptor and its target genes in 1-hydroxypyrene-induced HK-2 cells and mice.

CONCLUSION AND IMPLICATIONS

Metabolite 1-hydroxypyrene was demonstrated to mediate renal fibrosis through activation of the aryl hydrocarbon receptor signalling pathway. Targeting aryl hydrocarbon receptor may be an alternative therapeutic strategy for CKD progression.

Integrated metabolomics coupled with pattern recognition and pathway analysis to reveal molecular mechanism of cadmium-induced diabetic nephropathy

Diabetic nephropathy (DN) is becoming a worldwide public health problem and its pathophysiological mechanism is not well understood. Emerging evidences indicated that cadmium (Cd), an industrial material but also an environmental toxin, may be involved in the development and progression of diabetes and diabetes-related kidney disease. However, the underlying mechanism is still unclear. Herein, a DN animal model was constructed by exposing to Cd, the metabolomic profiling of DN mice were obtained by using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS), pattern recognition and pathway analysis were performed to screen potential biomarker. Moreover, western blotting was employed to verify the possible mechanism involved in the occurrence of Cd-induced DN. A total of 66 metabolites in serum have been screened out and identified as biomarkers, including free fatty acids, phospholipids, sphingomyelins, glycerides, and others. Significant differences were demonstrated between the metabolic profiles, including decreased levels of phospholipid and increased content of triglyceride, diacylglycerols, ceramide, lysophosphatidylcholine in Cd-induced DN mice compared with control. Protein expression level of p38 MAPK and Wnt/β-catenin were significantly increased. UPLC-Q-TOF/MS-based serum metabolomics coupled with pattern recognition methods and pathway analysis provide a powerful approach to identify potential biomarkers and is a new strategy to predict the underlying mechanism of disease caused by environmental toxicant.

Reduced uremic metabolites are prominent feature of sarcopenia, distinct from antioxidative markers for frailty

Due to global aging, frailty and sarcopenia are increasing. Sarcopenia is defined as loss of volume and strength of skeletal muscle in elderlies, while frailty involves multiple domains of aging-related dysfunction, impaired cognition, hypomobility, and decreased social activity. However, little is known about the metabolic basis of sarcopenia, either shared with or discrete from frailty. Here we analyzed comprehensive metabolomic data of human blood in relation to sarcopenia, previously collected from 19 elderly participants in our frailty study. Among 131 metabolites, we identified 22 sarcopenia markers, distinct from 15 frailty markers, mainly including antioxidants, although sarcopenia overlaps clinically with physical frailty. Notably, 21 metabolites that decline in sarcopenia or low SMI are uremic compounds that increase in kidney dysfunction. These comprise TCA cycle, urea cycle, nitrogen, and methylated metabolites. Sarcopenia markers imply a close link between muscle and kidney function, while frailty markers define a state vulnerable to oxidative stress.

Metabolomics Profiling of Cystic Renal Disease towards Biomarker Discovery

Simple Summary

Cystic renal disease (CRD) is a group of diseases characterized by abnormal sacs, or cysts, in the kidneys. CRD can be detected using certain imaging modalities (i.e., ultrasound). Patients with CRD might be symptoms-free, while others can show symptoms long after cysts development. Although these cysts represent structural changes, we hypothesized that they have an underlying biochemical alteration. If so, this would open the floor for potential biomarker discovery, which would aid in CRD diagnosis and, possibly, treatment. On that basis, this study focuses on identifying biomarkers for CRD. To achieve that, we employed a metabolomics-based approach to identify intermediate molecules inside the cells that are byproducts of biochemical reactions. We used dry blood spots and serum samples of CRD patients and healthy controls to study the differences in their metabolomic profile. Our results suggest that certain metabolites, including uridine diphosphate, cystine-5-diphosphate, and morpholine, are potential biomarkers for CRD. The affected biochemical pathways in CRD include aminoacyl-tRNA biosynthesis, purine, pyrimidine, glutathione, TCA cycle, and some amino acid metabolism. These preliminary results could be the starting point for possible diagnostic and therapeutic approaches for CRD in the future.

Abstract

Cystic renal disease (CRD) comprises a heterogeneous group of genetic and acquired disorders. The cystic lesions are detected through imaging, either incidentally or after symptoms develop, due to an underlying disease process. In this study, we aim to study the metabolomic profiles of CRD patients for potential disease-specific biomarkers using unlabeled and labeled metabolomics using low and high-resolution mass spectrometry (MS), respectively. Dried-blood spot (DBS) and serum samples, collected from CRD patients and healthy controls, were analyzed using the unlabeled and labeled method. The metabolomics profiles for both sets of samples and groups were collected, and their data were processed using the lab’s standard protocol. The univariate analysis showed (FDR p < 0.05 and fold change 2) was significant to show a group of potential biomarkers for CRD discovery, including uridine diphosphate, cystine-5-diphosphate, and morpholine. Several pathways were involved in CRD patients based on the metabolic profile, including aminoacyl-tRNA biosynthesis, purine and pyrimidine, glutathione, TCA cycle, and some amino acid metabolism (alanine, aspartate and glutamate, arginine and tryptophan), which have the most impact. In conclusion, early CRD detection and treatment is possible using a metabolomics approach that targets alanine, aspartate, and glutamate pathway metabolites.

Untargeted serum metabolomics and tryptophan metabolism profiling in type 2 diabetic patients with diabetic glomerulopathy

Diabetic glomerulopathy (DG) remains the prevalent microvascular complication and leading cause of shortened lifespan in type-2 diabetes mellitus (T2DM) despite improvement in hyperglycemia control. Considering the pivotal role of kidney in metabolism, using untargeted metabolomic techniques to globally delineate the serum metabolite profiles will help advance understanding pathogenetic underpinnings of renal biopsy-confirmed DG from the perspective of metabolism specifically. Fourteen pathologically diagnosed DG patients secondary to T2DM and 14 age- and gender-matched healthy controls (HCs) were recruited for study. We employed mass spectrometry-based untargeted metabolomic methods to reveal the metabolite profiles of serum samples collected from all included subjects. We identified a total of 334 and 397 metabolites in positive and negative ion mode respectively. One hundred and eighty-two important differential metabolites whose variable importance in projection (VIP) > 1 and p value <0.05 were selected and annotated to metabolic pathways. KEGG pathway enrichment analysis revealed tryptophan metabolism enriched most significantly. Among the tryptophan derivatives, L-tryptophan (L-Trp) and serotonin were relatively accumulated in DGs compared with HCs, while 5-hydroxyindoleacetic acid (5-HIAA) and indole-3-acetamide were depleted. Correlation analysis showed serotonin and L-Trp are negatively correlated with 24 h urine protein and glycosylated hemoglobin (Ghb). To exclude the interference of preexisting T2DM on DG exacerbation, we selected 5-HIAA and 3-(3-hydroxyphenyl) propionic acid (3-OHPPA) which are not correlated with Ghb and analyzed their correlation relationship with crucial renal indices. We found 3-OHPPA is positively correlated with urine total protein and creatinine ratio (T/Cr) and 24 h urine protein, 5-HIAA is positively correlated with serum creatinine and urea.

Gaining Insights Into Metabolic Networks Using Chemometrics and Bioinformatics: Chronic Kidney Disease as a Clinical Model

Because of its ability to generate biological hypotheses, metabolomics offers an innovative and promising approach in many fields, including clinical research. However, collecting specimens in this setting can be difficult to standardize, especially when groups of patients with different degrees of disease severity are considered. In addition, despite major technological advances, it remains challenging to measure all the compounds defining the metabolic network of a biological system. In this context, the characterization of samples based on several analytical setups is now recognized as an efficient strategy to improve the coverage of metabolic complexity. For this purpose, chemometrics proposes efficient methods to reduce the dimensionality of these complex datasets spread over several matrices, allowing the integration of different sources or structures of metabolic information. Bioinformatics databases and query tools designed to describe and explore metabolic network models offer extremely useful solutions for the contextualization of potential biomarker subsets, enabling mechanistic hypotheses to be considered rather than simple associations. In this study, network principal component analysis was used to investigate samples collected from three cohorts of patients including multiple stages of chronic kidney disease. Metabolic profiles were measured using a combination of four analytical setups involving different separation modes in liquid chromatography coupled to high resolution mass spectrometry. Based on the chemometric model, specific patterns of metabolites, such as N-acetyl amino acids, could be associated with the different subgroups of patients. Further investigation of the metabolic signatures carried out using genome-scale network modeling confirmed both tryptophan metabolism and nucleotide interconversion as relevant pathways potentially associated with disease severity. Metabolic modules composed of chemically adjacent or close compounds of biological relevance were further investigated using carbon transfer reaction paths. Overall, the proposed integrative data analysis strategy allowed deeper insights into the metabolic routes associated with different groups of patients to be gained. Because of their complementary role in the knowledge discovery process, the association of chemometrics and bioinformatics in a common workflow is therefore shown as an efficient methodology to gain meaningful insights in a clinical context.

Diagnostic value of phosphatidylethanolamine binding protein 4 levels in patients receiving nursing interventions for advanced chronic kidney disease

OBJECTIVE

To explore the diagnostic role of phosphatidylethanolamine binding protein 4 (PEBP4) in patients with chronic kidney disease (CKD) receiving nursing interventions.

METHODS

ELISA was used to evaluate serum PEBP4 levels. Receiver-operating characteristic curve analysis was used to assess diagnostic accuracy. Spearman correlation analysis was used to assess the relationships between PEBP4 levels and biochemical indexes.

RESULTS

Serum PEBP4 was high in CKD patients compared with healthy individuals. PEBP4 levels were positively correlated with pathological stage in CKD patients. PEBP4 had higher sensitivity for diagnosis of CKD than common indexes including blood urea nitrogen, creatinine and C-reactive protein. Among CKD patients treated with calcium channel blockers, serum PEBP4 levels declined notably and were associated with concentrations of K+, Na+, Cl- and Ca2+. Nursing interventions significantly decreased serum PEBP4 levels. A significant association between serum PEBP4 level and ionic concentration was observed in CKD patients receiving nursing interventions.

CONCLUSIONS

This prospective study demonstrated that PEBP4 level might represent an effective diagnostic biomarker in CKD patients. PEBP4 also acted as a valuable care compliance factor for determining the necessity for nursing interventions. Nursing interventions restored ion channel function and subsequently resulted in decreased PEBP4 levels and proteinuria.

Gut microbiota-derived tryptophan metabolism mediates renal fibrosis by aryl hydrocarbon receptor signaling activation

The gut microbiota has a crucial effect on regulating the intestinal mucosal immunity and maintaining intestinal homeostasis both in health and in disease state. Many effects are mediated by gut microbiota-derived metabolites and tryptophan, an essential aromatic amino acid, is considered important among many metabolites in the crosstalk between gut microbiota and the host. Kynurenine, serotonin, and indole derivatives are derived from the three major tryptophan metabolism pathways modulated by gut microbiota directly or indirectly. Aryl hydrocarbon receptor (AHR) is a cytoplasmic ligand-activated transcription factor involved in multiple cellular processes. Tryptophan metabolites as ligands can activate AHR signaling in various diseases such as inflammation, oxidative stress injury, cancer, aging-related diseases, cardiovascular diseases (CVD), and chronic kidney diseases (CKD). Accumulated uremic toxins in the body fluids of CKD patients activate AHR and affect disease progression. In this review, we will elucidate the relationship between gut microbiota-derived uremic toxins by tryptophan metabolism and AHR activation in CKD and its complications. This review will provide therapeutic avenues for targeting CKD and concurrently present challenges and opportunities for designing new therapeutic strategies against renal fibrosis.

Long non-coding RNAs: A double-edged sword in aging kidney and renal disease

Aging as one of intrinsic biological processes is a risk factor for many chronic diseases. Kidney disease is a global problem and health care burden worldwide. The diagnosis of kidney disease is currently based on serum creatinine and urea levels. Novel biomarkers may improve diagnostic accuracy, thereby allowing early prevention and treatment. Over the past few years, advances in genome analyses have identified an emerging class of noncoding RNAs that play critical roles in the regulation of gene expression and epigenetic reprogramming. Long noncoding RNAs (lncRNAs) are pervasively transcribed in the genome and could bind DNA, RNA and protein. Emerging evidence has demonstrated that lncRNAs played an important role in all stages of kidney disease. To date, only some lncRNAs were well identified and characterized, but the complexity of multilevel regulation of transcriptional programs involved in these processes remains undefined. In this review, we summarized the lncRNA expression profiling of large-scale identified lncRNAs on kidney diseases including acute kidney injury, chronic kidney disease, diabetic nephropathy and kidney transplantation. We further discussed a number of annotated lncRNAs linking with complex etiology of kidney diseases. Finally, several lncRNAs were highlighted as diagnostic biomarkers and therapeutic targets. Targeting lncRNAs may represent a precise therapeutic strategy for progressive renal fibrosis.

Metabolome and microbiome in kidney diseases

Despite several decades of intensive research and hard work in nephrology, a void exists in the availability of markers for identifying at-risk individuals, diagnosing diseases at incipient stage, and predicting treatment response. Most of the current widely available diagnostic tools such as creatinine, urine analysis, and imaging studies are quite insensitive such that about half of the kidney function is lost before perceivable changes are observed with these tests. In addition, these parameters are affected by factors other than renal, questioning their specificity. Renal biopsy, though specific, is quite expensive, risky, and invasive. The recent surge in the knowledge of small molecules in the tissue and body fluids, "metabolomics," thanks to the Human Metabolome Database created by the Human Metabolome Project, has opened a new avenue for better understanding the disease pathogenesis and, in parallel, to identify novel biomarkers and druggable targets. Kidney, by virtue of its metabolic machinery and also being a major handler of metabolites generated by other tissues, is very much amenable to the metabolomic approach of studying its various perturbations. The gut microbiome, characterized by the Human Microbiome Project, is one of the principal players in metabolomics. Changes in metabolite profile due to alterations in gut microbiome can occur either as a cause or consequence of renal diseases. Unmasking the renal-metabolome-microbiome link has a great potential to script a new era in the diagnosis and management of renal diseases.

Impact of gut microbiota: How it could play roles beyond the digestive system on development of cardiovascular and renal diseases

In recent years, a significant interest in gut microbiota-host crosstalk has increased due to the involvement of gut bacteria on host health and diseases. Gut dysbiosis, a change in the gut microbiota composition alters host-microbiota interactions and induces gut immune dysregulation that have been associated with pathogenesis of several diseases, including cardiovascular diseases (CVD) and chronic kidney diseases (CKD). Gut microbiota affect the host, mainly through the immunological and metabolism-dependent and metabolism-independent pathways. In addition to these, the production of trimethylamine (TMA)/trimethylamine N-oxide (TMAO), uremic toxins and lipopolysaccharides (LPS) by gut microbiota are involved in the pathogenesis of CVD and CKD. Given the current approaches and challenges that can reshape the bacterial composition by restoring the balance between host and microbiota. In this review, we discuss the complex interplay between the gut microbiota, and the heart and the kidney, and explain the gut-cardiovascular axis and gut-kidney axis on the development and progression of cardiovascular diseases and chronic kidney diseases. In addition, we discuss the interplay between gut and kidney on hypertension or cardiovascular pathology.

Poricoic acid A as a modulator of TPH-1 expression inhibits renal fibrosis via modulating protein stability of β-catenin and β-catenin-mediated transcription

Background

Renal fibrosis is the common feature of chronic kidney disease (CKD). However, few drugs specifically target fibrogenesis due to the lack of an effective therapeutic target. Hence, it is urgent to find a therapeutic strategy that inhibits renal fibrosis. Here, we identified that poricoic acid A (PAA) as the modulator of tryptophan hydroxylase-1 (TPH-1), the key enzyme in tryptophan metabolism, exerted potent anti-fibrotic effects in the kidney.

Methods

Lentiviral vector, luciferase reporter activity assay and co-immunoprecipitation were used. The animal model of unilateral ureteral obstruction and adenine-induced chronic renal failure as well as transforming growth factor (TGF)-β1-treated epithelial cells NRK-52E and fibroblasts NRK-49F were used.

Results

TPH-1 was gradually decreased during CKD progression, while PAA treatment significantly increased TPH-1 expression to suppress renal fibrosis. Pharmacological overexpression of TPH-1 by PAA treatment exhibited anti-fibrosis and was linked to Wnt/β-catenin signaling activity. TPH-1 exhibited anti-fibrotic effects by suppressing epithelial cell injury and fibroblast activation, and PAA promoted TPH-1 expression and then suppressed the Wnt/β-catenin signaling pathway via regulating the protein stability of β-catenin and β-catenin-mediated transcription. TPH-1 overexpression enhanced the anti-fibrotic effects of PAA, while TPH-1 deficiency weakened the anti-fibrotic effects of PAA, indicating that TPH-1 was required for the anti-fibrotic effects of PAA.

Conclusion

PAA as a modulator of TPH-1 expression attenuated renal fibrosis through regulating the Wnt/β-catenin signaling pathway by acting on the protein stability of β-catenin and β-catenin-mediated transcription. TPH-1 was required for PAA to exert anti-fibrosis.

A GC-MS-Based Metabolomics Investigation of the Protective Effect of Liu-Wei-Di-Huang-Wan in Type 2 Diabetes Mellitus Mice

Materials and Methods

MKR mice were used for the development of diabetes with high-fat diet feeding. These mice were further injected with streptozocin (STZ) to aggravate kidney failure. Fasting blood glucose (FBG) and urinary albumin-to-creatinine ratio (ACR values) were determined to validate the successful establishment of diabetic models with desired kidney dysfunction. Metabolomics approach coupled with gas chromatography-mass spectrometry (GC-MS) and random forest (RF) algorithm was proposed to discover the metabolic differences among model group and control group as well as to examine the therapeutic efficacy of traditional Chinese medicine, Liu-Wei-Di-Huang-Wan (LWDHW), in diabetes and associated kidney failure.

Results

Some metabolites such as 3-hydroxybutyric acid, citric acid, hexadecanoic acid, and octadecanoic acid showed significant differences between the control group and model group. Treatment with LWDHW resulted in a significant decrease in FBG and ACR values. These results suggested that LWDHW could have beneficial effects in diabetes-associated renal failure.

Advances and challenges in pursuing biomarkers for obstructive sleep apnea: Implications for the cardiovascular risk

Obstructive sleep apnea (OSA) is a common clinical condition associated with increased cardiovascular morbidity and mortality. Recent evidence from clinical studies and animal models suggest that OSA can promote cardiovascular disease by inducing autonomic, hemodynamic, inflammatory and metabolic dysregulation. However, most of the evidence addressing hard endpoints in humans is derived from observational studies. Several challenges have been noted in the pursuit of a comprehensive knowledge base about the impact of OSA including: 1) the precise mechanisms by which OSA causes metabolic and cardiovascular consequences are not clear, which limits our current ability to address potential targets in OSA; 2) several patients with OSA, even with severe forms, present with no or mild daytime symptoms. Beyond the obvious challenges for obtaining good adherence for conventional OSA treatments, there is evidence that symptomatic vs. asymptomatic patients with OSA do not necessarily have the same metabolic and cardiovascular outcomes; and 3) the cardiovascular response to OSA treatment may vary even in those patients with good adherence. In this scenario, there is an obvious need to develop biomarkers in the OSA research area. This review focuses on describing the advances that have occurred so far in exploring potential OSA biomarkers with clear emphasis for the cardiovascular risk. Particular attention will be devoted to discuss molecular biomarkers including the potential role of microRNAs, proteomics and metabolomics. We also discuss the major challenges and perspectives in this growing research field.

Non-targeted urinary metabolomics in pregnancy and associations with fetal growth restriction

Our objective was to identify metabolites associated with fetal growth restriction (FGR) by examining early and late pregnancy differences in non-targeted urinary metabolites among FGR cases and non-FGR controls. An exploratory case-control study within LIFECODES birth cohort was performed. FGR cases (N = 30), defined as birthweight below the 10^th percentile, were matched with controls (N = 30) based on maternal age, race, pre-pregnancy body mass index, and gestational age at delivery. Gas chromatography/electron-ionization mass spectrometry was performed on urine samples collected at 10 and 26 weeks of gestation. Differences in urinary metabolite levels in cases and controls at each time point and between the two time points were calculated and then changes compared across pregnancy. 137 unique urinary metabolites were annotated, and several identified that were higher in cases compared to controls. For example, urinary concentrations of benzoic acid were higher in cases compared to controls at both study visits (3.01-fold higher in cases at visit 1, p < 0.01; 3.10-fold higher in cases at visit 3, p = 0.05). However, these findings from our exploratory analysis were not robust to false-discovery-rate adjustment. In conclusion, using a high-resolution, non-targeted approach, we found specific urinary organic acids differed over pregnancy by FGR case status.

UPLC-HDMS-based on serum metabolomics reveals the toxicity of arecae semen

ETHNOPHARMACOLOGICAL RELEVANCE

Arecae semen has been used as vermifuge and digestant in traditional Chinese medicine (TCM) for more than one thousand years. However, the toxicity effect of areca semen and its underlying mechanism are still unclear.

THE AIM OF THE STUDY

This study was aimed to investigate the toxicity of arecae semen and to explore its mechanisms by serum metabolomics.

MATERIALS AND METHODS

The male Wistar rats were divided into the control group and treated group (n = 6 in each group), which were given by gavage with distill water or arecae semen aqueous extract (ASAE) once a day for 30 days, respectively. Serum samples were collected from all the rats after treatment of 7-day, 14-day and 30-day for metabolomics analysis. Moreover, biochemistry analysis and histopathological examination were performed at the end of study.

RESULTS

The phenomenon of diarrhea, less physical activity, tremors and body curl up were observed in the treated group. Additionally, the body weights of treated rats were significantly decreased compared with control rats from the 8th day after oral administration. Except the level of creatinekinase (CK) in the treated group significantly increased compared with the control group, there were no differences on biochemistry parameters and histopathological test in the two groups. Combined with the methods of principal component analysis (PCA), orthogonal projection to latent structure-discrimination analysis (OPLS-DA) and available databases, the treated and control rats were clearly distinguished from each other and 19 metabolites were identified as the potential biomarkers in the arecae semen treated rats. The identified biomarkers indicated that there were perturbations of the phospholipid metabolism, amino acid metabolism and fat acid metabolism in the treated group.

CONCLUSIONS

This indicated that arecae semen possessed certain cardiotoxicity and inhibited the normal growth in Wistar male rats. In addition, the metabolomics approach is a useful tool to study the toxicity in TCM.

DESI-MSI and METASPACE indicates lipid abnormalities and altered mitochondrial membrane components in diabetic renal proximal tubules

INTRODUCTION

Diabetic kidney disease (DKD) is the most prevalent complication in diabetic patients, which contributes to high morbidity and mortality. Urine and plasma metabolomics studies have been demonstrated to provide valuable insights for DKD. However, limited information on spatial distributions of metabolites in kidney tissues have been reported.

OBJECTIVES

In this work, we employed an ambient desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) coupled to a novel bioinformatics platform (METASPACE) to characterize the metabolome in a mouse model of DKD.

METHODS

DESI-MSI was performed for spatial untargeted metabolomics analysis in kidneys of mouse models (F1 C57BL/6J-Ins2Akita male mice at 17 weeks of age) of type 1 diabetes (T1D, n = 5) and heathy controls (n = 6).

RESULTS

Multivariate analyses (i.e., PCA and PLS-DA (a 2000 permutation test: P < 0.001)) showed clearly separated clusters for the two groups of mice on the basis of 878 measured m/z's in kidney cortical tissues. Specifically, mice with T1D had increased relative abundances of pseudouridine, accumulation of free polyunsaturated fatty acids (PUFAs), and decreased relative abundances of cardiolipins in cortical proximal tubules when compared with healthy controls.

CONCLUSION

Results from the current study support potential key roles of pseudouridine and cardiolipins for maintaining normal RNA structure and normal mitochondrial function, respectively, in cortical proximal tubules with DKD. DESI-MSI technology coupled with METASPACE could serve as powerful new tools to provide insight on fundamental pathways in DKD.

Corticosterone-mediated physiological stress modulates hepatic lipid metabolism, metabolite profiles, and systemic responses in chickens

The impact of physiological stress on lipid metabolism, the metabolome, and systemic responses was examined in chickens. To incite a stress response, birds were continuously administered corticosterone (CORT) in their drinking water at three doses (0 mg/L, 10 mg/L, and 30 mg/L), and they were sampled 1, 5, and 12 days after commencement of CORT administration. Corticosterone administration to birds differentially regulated lipogenesis genes (i.e. FAS, ACC, ME, and SREBF1), and histopathological examination indicated lipid deposition in hepatocytes. In addition, CORT affected water-soluble metabolite profiles in the liver, as well as in kidney tissue and breast muscle; thirteen unique metabolites were distinguished in CORT-treated birds and this was consistent with the dysregulation of lipid metabolism due to physiological stress. Acute phase responses (APRs) were also altered by CORT, and in particular, expression of SAA1 was decreased and expression of CP was increased. Furthermore, CORT administration caused lymphoid depletion in the bursa of Fabricius and elevated IL6 and TGFβ2 mRNA expression after 5 and 12 days of CORT administration. Collectively, incitement of physiological stress via administration of CORT in chickens modulated host metabolism and systemic responses, which indicated that energy potentials are diverted from muscle anabolism during periods of stress.

Machine learning distilled metabolite biomarkers for early stage renal injury

INTRODUCTION

With chronic kidney disease (CKD), kidney becomes damaged overtime and fails to clean blood. Around 15% of US adults have CKD and nine in ten adults with CKD do not know they have it.

OBJECTIVE

Early prediction and accurate monitoring of CKD may improve care and decrease the frequent progression to end-stage renal disease. There is an urgent demand to discover specific biomarkers that allow for monitoring of early-stage CKD, and response to treatment.

METHOD

To discover such biomarkers, shotgun high throughput was applied to the detection of serum metabolites biomarker discovery for early stages of CKD from 703 participants. Ultra performance liquid chromatography coupled with high-definition mass spectrometry (UPLC-HDMS)-based metabolomics was used for the determination of 703 fasting serum samples from five stages of CKD patients and age-matched healthy controls.

RESULTS AND CONCLUSION

We discovered a set of metabolite biomarkers using a series of classic and neural network based machine learning techniques. This set of metabolites can separate early CKD stage patents from normal subjects with high accuracy. Our study illustrates the power of machine learning methods in metabolite biomarker study.

Uraemic syndrome of chronic kidney disease: altered remote sensing and signalling

Uraemic syndrome (also known as uremic syndrome) in patients with advanced chronic kidney disease involves the accumulation in plasma of small-molecule uraemic solutes and uraemic toxins (also known as uremic toxins), dysfunction of multiple organs and dysbiosis of the gut microbiota. As such, uraemic syndrome can be viewed as a disease of perturbed inter-organ and inter-organism (host-microbiota) communication. Multiple biological pathways are affected, including those controlled by solute carrier (SLC) and ATP-binding cassette (ABC) transporters and drug-metabolizing enzymes, many of which are also involved in drug absorption, distribution, metabolism and elimination (ADME). The remote sensing and signalling hypothesis identifies SLC and ABC transporter-mediated communication between organs and/or between the host and gut microbiota as key to the homeostasis of metabolites, antioxidants, signalling molecules, microbiota-derived products and dietary components in body tissues and fluid compartments. Thus, this hypothesis provides a useful perspective on the pathobiology of uraemic syndrome. Pathways considered central to drug ADME might be particularly important for the body's attempts to restore homeostasis, including the correction of disturbances due to kidney injury and the accumulation of uraemic solutes and toxins. This Review discusses how the remote sensing and signalling hypothesis helps to provide a systems-level understanding of aspects of uraemia that could lead to novel approaches to its treatment.

LC-MS-based metabolomics analysis to identify meprin-β-associated changes in kidney tissue from mice with STZ-induced type 1 diabetes and diabetic kidney injury

Meprin metalloproteases have been implicated in the pathophysiology of diabetic kidney disease (DKD). Single-nucleotide polymorphisms in the meprin-β gene have been associated with DKD in Pima Indians, a Native American ethnic group with an extremely high prevalence of DKD. In African American men with diabetes, urinary meprin excretion positively correlated with the severity of kidney injury. In mice, meprin activity decreased at the onset of diabetic kidney injury. Several studies have identified meprin targets in the kidney. However, it is not known how proteolytic processing of the targets by meprins impacts the metabolite milieu in kidneys. In the present study, global metabolomics analysis identified differentiating metabolites in kidney tissues from wild-type and meprin-β knockout mice with streptozotocin (STZ)-induced type 1 diabetes. Kidney tissues were harvested at 8 wk post-STZ and analyzed by hydrophilic interaction liquid chromatography ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Principal component analysis identified >200 peaks associated with diabetes. Meprin expression-associated metabolites with strong variable importance of projection scores were indoxyl sulfate, N-γ-l-glutamyl-l-aspartic acid, N-methyl-4-pyridone-3-carboxamide, inosine, and cis-5-decenedioic acid. N-methyl-4-pyridone-3-carboxamide has been previously implicated in kidney injury, and its isomers, 4-PY and 2-PY, are markers of peroxisome proliferation and inflammation that correlate with creatinine clearance and glucose tolerance. Meprin deficiency-associated differentiating metabolites with high variable importance of projection scores were cortisol, hydroxymethoxyphenylcarboxylic acid-O-sulfate, and isovaleryalanine. The data suggest that meprin-β activity enhances diabetic kidney injury in part by altering the metabolite balance in kidneys, favoring high levels of uremic toxins such as indoxyl sulfate and N-methyl-pyridone-carboxamide.

Metabolomics Analysis Reveals the Protection Mechanism of Huangqi-Danshen Decoction on Adenine-Induced Chronic Kidney Disease in Rats

Huangqi-Danshen decoction (HDD) is a commonly used drug pair for clinical treatment of chronic kidney disease (CKD) in traditional Chinese medicine with good efficacy. However, the potential mechanisms of this action have not been well elucidated. The aim of this study was to explore the metabolic profiling variations in response to HDD treatment in a CKD rat model. CKD rat model was induced by adding 0.75% adenine to the diet for 4 weeks. The rats in the treatment group received HDD extract orally at the dose of 4.7 g/kg/day during the experiment. At the end of the experiment, serum and kidney samples were collected for biochemical and pathological examination. Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS) was used to analyze metabolic profiling variations in the kidney. The results showed that treatment with HDD markedly attenuated kidney injury and improved renal function. A total of 28 metabolites contributing to CKD phenotype were found and identified in the kidney samples. The primary metabolic pathways disordered in the kidney of CKD rats were glycerophospholipid metabolism, glycosylphosphatidylinositol-anchor biosynthesis, and citrate cycle. Partial least squares discriminant analysis (PLS-DA) score plot showed that the three groups of renal samples were obviously divided into three categories, and the metabolic trajectory of the HDD treatment group moved to the control group. (E)-Piperolein A, phosphatidylcholines (PC) (18:1/22:6), phosphatidylinositols (PI) (13:0/18:1), PI (15:0/20:3), phosphatidylserines (PS) (O-20:0/12:0), and triglyceride (TG) (22:4/24:0/O-18:0) represented potential biomarkers of the renoprotective effects of HDD against CKD. In conclusion, HDD has renoprotective effect against adenine-induced CKD, which may be mediated via partially restoration of perturbed metabolism in the kidney.

Aryl hydrocarbon receptor activation mediates kidney disease and renal cell carcinoma

The aryl hydrocarbon receptor (AhR) is a well-known ligand-activated cytoplasmic transcription factor that contributes to cellular responses against environmental toxins and carcinogens. AhR is activated by a range of structurally diverse compounds from the environment, microbiome, natural products, and host metabolism, suggesting that AhR possesses a rather promiscuous ligand binding site. Increasing studies have indicated that AhR can be activated by a variety of endogenous ligands and induce the expression of a battery of genes. AhR regulates a variety of physiopathological events, including cell proliferation, differentiation, apoptosis, adhesion and migration. These new roles have expanded our understanding of the AhR signalling pathways and endogenous metabolites interacting with AhR under homeostatic and pathological conditions. Recent studies have demonstrated that AhR is linked to cardiovascular disease (CVD), chronic kidney disease (CKD) and renal cell carcinoma (RCC). In this review, we summarize gut microbiota-derived ligands inducing AhR activity in patients with CKD, CVD, diabetic nephropathy and RCC that may provide a new diagnostic and prognostic approach for complex renal damage. We further highlight polyphenols from natural products as AhR agonists or antagonists that regulate AhR activity. A better understanding of structurally diverse polyphenols and AhR biological activities would allow us to illuminate their molecular mechanism and discover potential therapeutic strategies targeting AhR activation.

Discrimination of Different Parts of Saffron by Metabolomic-Based Ultra-Performance Liquid Chromatography Coupled with High-Definition Mass Spectrometry

In this study, the metabolite profiling of three different parts of Crocus sativus L. was measured by using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTof-MS/MS). Multivariate statistical analysis was used to distinguish among the samples from different parts. A total of 54 compounds were identified in tepals, stigmas and stamens by UPLC-QTof-MS/MS. The results stated that chemical characteristics of saffron were obviously diverse in terms of the parts of flower. Through analysis, coniferin and crocin-2 were special components in stigmas when compared to tepals and stamens. The content of flavonoids was high in tepals when compared with the stigmas. The tepal of saffron may processed as a source of flavonoids in the future. The research provided the basis for the theory that only the stigma can be used as medicine.