Systematic variations associated with renal disease uncovered by parallel metabolomics of urine and serum

Role of metabolomic profile as a potential marker to discriminate membranous nephropathy from IgA nephropathy

BACKGROUND

Membranous nephropathy (MN) and IgA nephropathy (IgAN) are the most common primary glomerulopathies worldwide. The systemic metabolic changes in the progression of MN and IgAN are not fully understood.

METHODS

A total of 87 and 70 patients with MN and IgAN, respectively, and 30 healthy controls were enrolled in this study. Untargeted metabolomics was performed to explore the differential metabolites and metabolic pathways in the early stage of MN and IgAN. To judge the diagnostic ability of biomarkers, receiver operating characteristic curve analysis (ROC) were performed.

RESULTS

Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) suggested that patients with MN and IgAN showed an obvious separation trend from the healthy controls. In addition, 155 and 148 metabolites were identified to be significantly altered in the MN and IgAN groups, respectively. Of these, 70 metabolites were markedly altered in both disease groups; six metabolites, including L-tryptophan, L-kynurenine, gamma-aminobutyric acid (GABA), indoleacetaldehyde, 5-hydroxyindoleacetylglycine, and N-alpha-acetyllysine, showed the opposite tendency. The most affected metabolic pathways included the amino acid metabolic pathways, citrate cycle, pantothenate and CoA biosynthesis, and hormone signaling pathways.

CONCLUSIONS

Substantial metabolic disorders occurred during the progression of MN and IgAN. L-tryptophan, L-kynurenine, GABA, indoleacetaldehyde, 5-hydroxyindoleacetylglycine, and N-alpha-acetyllysine may show potential as biomarkers for the identification of MN and IgAN.

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.

Identification of hub genes and their correlation with immune infiltrating cells in membranous nephropathy: an integrated bioinformatics analysis

BACKGROUND

Membranous nephropathy (MN) is a chronic glomerular disease that leads to nephrotic syndrome in adults. The aim of this study was to identify novel biomarkers and immune-related mechanisms in the progression of MN through an integrated bioinformatics approach.

METHODS

The microarray data were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between MN and normal samples were identified and analyzed by the Gene Ontology analysis, the Kyoto Encyclopedia of Genes and Genomes analysis and the Gene Set Enrichment Analysis (GSEA) enrichment. Hub The hub genes were screened and identified by the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithm. The receiver operating characteristic (ROC) curves evaluated the diagnostic value of hub genes. The single-sample GSEA analyzed the infiltration degree of several immune cells and their correlation with the hub genes.

RESULTS

We identified a total of 574 DEGs. The enrichment analysis showed that metabolic and immune-related functions and pathways were significantly enriched. Four co-expression modules were obtained using WGCNA. The candidate signature genes were intersected with DEGs and then subjected to the LASSO analysis, obtaining a total of 6 hub genes. The ROC curves indicated that the hub genes were associated with a high diagnostic value. The CD4+ T cells, CD8+ T cells and B cells significantly infiltrated in MN samples and correlated with the hub genes.

CONCLUSIONS

We identified six hub genes (ZYX, CD151, N4BP2L2-IT2, TAPBP, FRAS1 and SCARNA9) as novel biomarkers for MN, providing potential targets for the diagnosis and treatment.

Urinary Metabolite Profile Predicting the Progression of CKD

Key Points

As a biomarker, urinary metabolites could bridge the gap between genetic abnormalities and phenotypes of diseases. We found that levels of betaine, choline, fumarate, citrate, and glucose were significantly correlated with kidney function and could predict kidney outcomes, providing prognostic biomarkers in CKD.

Background

Because CKD is caused by genetic and environmental factors, biomarker development through metabolomic analysis, which reflects gene-derived downstream effects and host adaptation to the environment, is warranted.

Methods

We measured the metabolites in urine samples collected from 789 patients at the time of kidney biopsy and from urine samples from 147 healthy participants using nuclear magnetic resonance. The composite outcome was defined as a 30% decline in eGFR, doubling of serum creatinine levels, or end-stage kidney disease.

Results

Among the 28 candidate metabolites, we identified seven metabolites showing (1 ) good discrimination between healthy controls and patients with stage 1 CKD and (2 ) a consistent change in pattern from controls to patients with advanced-stage CKD. Among the seven metabolites, betaine, choline, glucose, fumarate, and citrate showed significant associations with the composite outcome after adjustment for age, sex, eGFR, the urine protein–creatinine ratio, and diabetes. Furthermore, adding choline, glucose, or fumarate to traditional biomarkers, including eGFR and proteinuria, significantly improved the ability of the net reclassification improvement (P < 0.05) and integrated discrimination improvement (P < 0.05) to predict the composite outcome.

Conclusion

Urinary metabolites, including betaine, choline, fumarate, citrate, and glucose, were found to be significant predictors of the progression of CKD. As a signature of kidney injury–related metabolites, it would be warranted to monitor to predict the renal outcome.

Urine Metabolomic Signature of People Diagnosed with Balkan Endemic Nephropathy and Other Types of Chronic Kidney Disease Compared with Healthy Subjects in Romania

Metabolomic analysis methods were employed to determine biomarkers for various chronic kidney diseases (CKDs). Modern analytical methods were developed and applied successfully to find a specific metabolomic profile in urine samples from CKD and Balkan endemic nephropathy (BEN) patients. The aim was to explore a specific metabolomic profile defined by feasible/easy-to-identify molecular markers. Urine samples were collected from patients with CKDs and BEN, and from healthy subjects from endemic and nonendemic areas in Romania. Metabolomic analysis of urine samples, extracted by the liquid-liquid extraction (LLE) method, was performed by gas chromatography-mass spectrometry (GC-MS). The statistical exploration of the results was performed through a principal component analysis (PCA) evaluation. Urine samples were statistically analyzed using a classification based on six types of metabolites. Most urinary metabolites are distributed in the center of a loading plot, meaning that these compounds do not represent significant markers for BEN. One of the most frequent and higher-concentration urinary metabolites in BEN patients was p-Cresol, a phenolic compound that implies a severe injury of the renal filtration function. The presence of p-Cresol was associated with protein-bound uremic toxins, which have specific functional groups such as indole and phenyl. In prospective studies for future investigation, prevention, and disease treatment, we suggest a larger sample size, sample extraction using other methods, and analysis using other chromatography techniques coupled with mass spectrometry, which can generate a more significant data set for statistical analysis.

An Untargeted Metabolomics Approach on Carfilzomib-Induced Nephrotoxicity

BACKGROUND

Carfilzomib (Cfz) is an anti-cancer drug related to cardiorenal adverse events, with cardiovascular and renal complications limiting its clinical use. Despite the important progress concerning the discovery of the underlying causes of Cfz-induced nephrotoxicity, the molecular/biochemical background is still not well clarified. Furthermore, the number of metabolomics-based studies concerning Cfz-induced nephrotoxicity is limited.

METHODS

A metabolomics UPLC-HRMS-DIA methodology was applied to three bio-sample types i.e., plasma, kidney, and urine, obtained from two groups of mice, namely (i) Cfz (8 mg Cfz/ kg) and (ii) Control (0.9% NaCl) (n = 6 per group). Statistical analysis, involving univariate and multivariate tools, was applied for biomarker detection. Furthermore, a sub-study was developed, aiming to estimate metabolites' correlation among bio-samples, and to enlighten potential mechanisms.

RESULTS

Cfz mostly affects the kidneys and urine metabolome. Fifty-four statistically important metabolites were discovered, and some of them have already been related to renal diseases. Furthermore, the correlations between bio-samples revealed patterns of metabolome alterations due to Cfz.

CONCLUSIONS

Cfz causes metabolite retention in kidney and dysregulates (up and down) several metabolites associated with the occurrence of inflammation and oxidative stress.

The metabolomics of a protein kinase C delta (PKCδ) knock-out mouse model

INTRODUCTION

PKCδ is ubiquitously expressed in mammalian cells and its dysregulation plays a key role in the onset of several incurable diseases and metabolic disorders. However, much remains unknown about the metabolic pathways and disturbances induced by PKC deficiency, as well as the metabolic mechanisms involved.

OBJECTIVES

This study aims to use metabolomics to further characterize the function of PKC from a metabolomics standpoint, by comparing the full serum metabolic profiles of PKC deficient mice to those of wild-type mice.

METHODS

The serum metabolomes of PKCδ knock-out mice were compared to that of a wild-type strain using a GCxGC-TOFMS metabolomics research approach and various univariate and multivariate statistical analyses.

RESULTS

Thirty-seven serum metabolite markers best describing the difference between PKCδ knock-out and wild-type mice were identified based on a PCA power value > 0.9, a t-test p-value < 0.05, or an effect size > 1. XERp prediction was also done to accurately select the metabolite markers within the 2 sample groups. Of the metabolite markers identified, 78.4% (29/37) were elevated and 48.65% of these markers were fatty acids (18/37). It is clear that a total loss of PKCδ functionality results in an inhibition of glycolysis, the TCA cycle, and steroid synthesis, accompanied by upregulation of the pentose phosphate pathway, fatty acids oxidation, cholesterol transport/storage, single carbon and sulphur-containing amino acid synthesis, branched-chain amino acids (BCAA), ketogenesis, and an increased cell signalling via N-acetylglucosamine.

CONCLUSION

The charaterization of the dysregulated serum metabolites in this study, may represent an additional tool for the early detection and screening of PKCδ-deficiencies or abnormalities.

Metabolomics Profiling of Nephrotic Syndrome towards Biomarker Discovery

Nephrotic syndrome (NS) is a kidney illness characterized by excessive proteinuria, hypoalbuminemia, edema, and hyperlipidemia, which may lead to kidney failure and necessitate renal transplantation. End-stage renal disease, cardiovascular issues, and mortality are much more common in those with NS. Therefore, the present study aimed to identify potential new biomarkers associated with the pathogenesis and diagnosis of NS. The liquid chromatography–mass spectrometry (LC–MS) metabolomics approach was applied to profile the metabolome of human serum of patients with NS. A total of 176 metabolites were significantly altered in NS compared to the control. Arginine, proline, and tryptophan metabolism; arginine, phenylalanine, tyrosine, and tryptophan biosynthesis were the most common metabolic pathways dysregulated in NS. Furthermore, alanyl-lysine and isoleucyl-threonine had the highest discrimination between NS and healthy groups. The candidate biomarkers may lead to understanding the possible metabolic alterations associated with NS and serve as potential diagnostic biomarkers.

Human Milk-Fed Piglets Have a Distinct Small Intestine and Circulatory Metabolome Profile Relative to That of Milk Formula-Fed Piglets

Exclusive HM feeding for newborns is recommended at least for the first 6 months of life. However, when breastfeeding is not possible, MF is recommended as a substitute.

The impact of human milk (HM) feeding compared with cow’s milk formula (MF) feeding on small intestinal and circulatory metabolome patterns has not been fully investigated. Therefore, 2-day-old male piglets were fed HM or MF (n = 26/group) from postnatal day 2 (PND 2) through 21 and were weaned to a solid diet until PND 51. The small intestine (gastrointestinal [GI]) contents, serum, and urine were collected from subsets of piglets at PND 21 and PND 51. Samples were subjected to primary metabolomics analyses at the West Coast Metabolomics Center, UC Davis. The metabolome data assessment and the statistical analyses were performed with MetaboAnalyst software. Compared with MF feeding, at PND 21, HM feeding resulted in a higher abundance of fucose in the jejunum and urine and a greater concentration of myo-inositol in serum. In HM-fed piglets, 1,5-anhydroglucitol was higher in the duodenum, serum, and urine at PND 21. Additionally, the HM group had higher levels of urinary kynurenic acid at PND 21. Correlations between bacterial genera and altered metabolites in ileum revealed that Turicibacter sp. and Campylobacter sp. were positively correlated with maltotriose and panose at PND 21, while ileal Campylobacter sp. was negatively correlated with fumaric acid. At PND 51, no significant metabolites were identified between HM and MF diet groups. The metabolites associated with the neonatal diets may serve as the substrates and signals that contribute to the physiological effects in HM and MF during infancy, with a subset reflecting diet-associated differences in microbial metabolism and ecology.

IMPORTANCE Exclusive HM feeding for newborns is recommended at least for the first 6 months of life. However, when breastfeeding is not possible, MF is recommended as a substitute. Due to the challenges associated with sample collection from infants fed HM or MF, their gut metabolism is poorly understood. Thus, an established piglet model from our team was used to determine the metabolite profile in relation to host, diet, and microbiota. The current study is the first to provide novel insights across the small intestine metabolism and its association with circulatory metabolites in the HM group relative to the MF group at the weaning and postweaning period. Data also demonstrate that during the neonatal period, diet, host, and microbial metabolism contribute to the lumen and circulatory metabolite profile. Furthermore, small intestinal lumen metabolome can be tracked in the urine as a biomarker of dietary differences, which would be a useful tool for clinical interventions.

Targeted Metabolomics With Ultraperformance Liquid Chromatography-Mass Spectrometry (UPLC-MS) Highlights Metabolic Differences in Healthy and Atopic Staffordshire Bull Terriers Fed Two Different Diets, A Pilot Study

Background: While anecdotal evidence has long claimed that a raw meat-based diet (RMBD) improves the metabolic health of canines, no rigorous scientific study has clarified this issue. Canine atopic dermatitis (CAD) has also been linked to metabolic health, but its relation to diet remains poorly understood. This study investigates whether dietary choice is linked to metabolic health in healthy and CAD-diagnosed canines via targeted serum and urine metabolomic analysis of polar, non-ionic metabolites, as well as whether the underlying CAD condition modulates the response to nutritional intake. Materials and Methods: Serum metabolites of client-owned Staffordshire bull terriers, divided into CAD-diagnosed (n = 14) and healthy (n = 6) cohorts, were studied. Urine metabolites of a subset of the CAD-diagnosed canines (n = 8) were also studied. The canines were split into two cohorts based on diet. The first cohort were fed a commercially available high-fat, moderate-protein, low-carbohydrate RMBD (n = 11, CAD diagnosed n = 8, healthy n = 3). Those in the second cohort were fed a commercially available moderate-fat, moderate-protein, high-carbohydrate kibble diet (KD) (n = 9: CAD diagnosed n = 6, healthy n = 3). The diet intervention period lasted approximately 4.5 months (median 135 days). Statistical analyses of the serum profiles across all dogs (n = 20) and the urine profiles of the CAD-diagnosed subset (n = 8) were performed. Results and Discussion: The KD cohort was found to have higher concentrations of methionine than the RMBD cohort, both in serum (all dogs, p < 0.0001) and in urine (CAD-only cohort, p < 0.0002), as well as cystathionine and 4-pyridoxic acid. Methionine plays important roles in homocysteine metabolism, and elevated levels have been implicated in various pathologies. The CAD (n = 14) cohort dogs showed starker metabolic changes in response to diet regarding these pathways compared to the healthy (n = 6) cohort. However, there was no significant change in CAD severity as a result of either diet. Likely due to the higher meat content of the RMBD, higher concentrations of several carnitines and creatine were found in the RMBD cohort. Citrulline was found in higher concentrations in the KD cohort. Our findings provide insight into the relationship between diet and the serum and urine metabolite profiles of canines. They also suggest that neither diet significantly affected CAD severity.

Characterizing metabolites and potential metabolic pathways changes to understanding the mechanism of medicinal plant Phellodendri Amurensis cortex against doxorubicin-induced nephritis rats using UPLC-Q/TOF-MS metabolomics

Phellodendri Amurensis cortex (PAC), a famous traditional Chinese herb with good anti-inflammatory efficacy, is used to treat various liver and kidney sickness in clinical practice. However, the potential mechanisms protecting against nephritis of PAC have not been comprehensively elucidated. The aim of this research was to explore the mechanism of PAC against doxorubicin- induced nephritis in rats by characterizing metabolites and potential metabolic pathways changes. The rat models of nephritis were established using 6.5 mg/kg doxorubicin injection from caudal vein for five weeks. The rats in the treatment group were respectively received PAC extract at the dose of 216, 432, and 864 mg/kg once a day during the experiment. Then, urine metabolomics strategy based on ultra-performance liquid chromatography-quadrupole time of flight-tandem mass spectrometry (UPLC-Q/TOF-MS) has been employed to discover the possible significant metabolites and metabolic pathway of nephritis rats. At the end of the experiment, serum, urine and kidney tissue were collected for biochemical and pathological examination. The results showed that PAC treatment notably decreased urinary protein, serum Cr content and renal tissue lesions, and increased serum TP and ALB content. A total of potential twenty- eight metabolites such as 5'-methylthioadenosine, cGMP, dehydroepiandrosterone sulfate, salbuta, 2-phenylaminoadenosine contributing to nephritis rat model were selected and identified in the urine samples. Compared with the model group, the high-dose PAC group can recall 18 metabolites level, the medium-dose group can recall 13 metabolites level, and the low-dose PAC group can recall 8 metabolites level, which were involved in nine primary metabolic pathways such as steroid hormone biosynthesis, alanine,aspartate and glutamate metabolism, cysteine and methionine metabolism as well as glyoxylate and dicarboxylate metabolism. The protein expressions of key enzymes involving methylthioadenosine phosphorylase (Mtap), cytidine deaminase (Cda), thymidine kinase (Tk), argininosuccinate synthase (Ass) in metabolic pathways were further verified by Western blot. The results showed that Phellodendron chinense up-regulated the protein expressions of Cda and Tk and down-regulated the protein expressions of Mtap and Ass. In conclusion, PAC possesses renoprotective effect against doxorubicin-induced nephritis, which may be mediated via regulating differential metabolites, reducing oxidative stress response, improving renal function, enhancing the ability of the immune system, regulating the role of key enzymes.

Predicting and Defining Steroid Resistance in Pediatric Nephrotic Syndrome Using Plasma Metabolomics

INTRODUCTION

Nephrotic syndrome (NS) is a kidney disease that affects both children and adults. Glucocorticoids have been the primary therapy for >60 years but are ineffective in approximately 20% of children and approximately 50% of adult patients. Unfortunately, patients with steroid-resistant NS (SRNS; vs. steroid-sensitive NS [SSNS]) are at high risk for both glucocorticoid-induced side effects and disease progression.

METHODS

We performed proton nuclear magnetic resonance (1H NMR) metabolomic analyses on plasma samples (n = 86) from 45 patients with NS (30 SSNS and 15 SRNS) obtained at initial disease presentation before glucocorticoid initiation and after approximately 7 weeks of glucocorticoid therapy to identify candidate biomarkers able to either predict SRNS before treatment or define critical molecular pathways/targets regulating steroid resistance.

RESULTS

Stepwise logistic regression models identified creatinine concentration and glutamine concentration (odds ratio [OR]: 1.01; 95% confidence interval [CI]: 0.99-1.02) as 2 candidate biomarkers predictive of SRNS, and malonate concentration (OR: 0.94; 95% CI: 0.89-1.00) as a third candidate predictive biomarker using a similar model (only in children >3 years). In addition, paired-sample analyses identified several candidate biomarkers with the potential to identify mechanistic molecular pathways/targets that regulate clinical steroid resistance, including lipoproteins, adipate, pyruvate, creatine, glucose, tyrosine, valine, glutamine, and sn-glycero-3-phosphcholine.

CONCLUSION

Metabolomic analyses of serial plasma samples from children with SSNS and SRNS identified elevated creatinine and glutamine concentrations, and reduced malonate concentrations, as auspicious candidate biomarkers to predict SRNS at disease onset in pediatric NS, as well as additional candidate biomarkers with the potential to identify mechanistic molecular pathways that may regulate clinical steroid resistance.

Chronic kidney disease: a review of proteomic and metabolomic approaches to membranous glomerulonephritis, focal segmental glomerulosclerosis, and IgA nephropathy biomarkers

Chronic Kidney Disease (CKD) is a global health problem annually affecting millions of people around the world. It is a comprehensive syndrome, and various factors may contribute to its occurrence. In this study, it was attempted to provide an accurate definition of chronic kidney disease; followed by focusing and discussing on molecular pathogenesis, novel diagnosis approaches based on biomarkers, recent effective antigens and new therapeutic procedures related to high-risk chronic kidney disease such as membranous glomerulonephritis, focal segmental glomerulosclerosis, and IgA nephropathy, which may lead to end-stage renal diseases. Additionally, a considerable number of metabolites and proteins that have previously been discovered and recommended as potential biomarkers of various CKD_s using ‘-omics-’ technologies, proteomics, and metabolomics were reviewed.

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

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

Metabolomics profiles of patients with Wilson disease reveal a distinct metabolic signature

INTRODUCTION

Wilson disease (WD) is characterized by excessive intracellular copper accumulation in liver and brain due to defective copper biliary excretion. With highly varied phenotypes and a lack of biomarkers for the different clinical manifestations, diagnosis and treatment can be difficult.

OBJECTIVE

The aim of the present study was to analyze serum metabolomics profiles of patients with Wilson disease compared to healthy subjects, with the goal of identifying differentially abundant metabolites as potential biomarkers for this condition.

METHODS

Hydrophilic interaction liquid chromatography-quadrupole time of flight mass spectrometry was used to evaluate the untargeted serum metabolome of 61 patients with WD (26 hepatic and 25 neurologic subtypes, 10 preclinical) compared to 15 healthy subjects. We conducted analysis of covariance with potential confounders (body mass index, age, sex) as covariates and partial least-squares analysis.

RESULTS

After adjusting for clinical covariates and multiple testing, we identified 99 significantly different metabolites (FDR < 0.05) between WD and healthy subjects. Subtype comparisons also revealed significantly different metabolites compared to healthy subjects: WD hepatic subtype (67), WD neurologic subtype (57), WD hepatic-neurologic combined (77), and preclinical (36). Pathway analysis revealed these metabolites are involved in amino acid metabolism, the tricarboxylic acid cycle, choline metabolism, and oxidative stress.

CONCLUSIONS

Patients with WD are characterized by a distinct metabolomics profile providing new insights into WD pathogenesis and identifying new potential diagnostic biomarkers.

Proteomic and metabolomic approaches in the search for biomarkers in chronic kidney disease

Chronic kidney disease (CKD) is an aging-related disorder that represents a major global public health burden. Current biochemical biomarkers, such as serum creatinine and urinary albumin, have important limitations when used to identify the earliest indication of CKD or in tracking the progression to more advanced CKD. These issues underline the importance of finding and testing new molecular biomarkers that are capable of successfully meeting this clinical need. The measurement of changes in nature and/or levels of proteins and metabolites in biological samples from patients provide insights into pathophysiological processes. Proteomic and metabolomic techniques provide opportunities to record dynamic chemical signatures in patients over time. This review article presents an overview of the recent developments in the fields of metabolomics and proteomics in relation to CKD. Among the many different proteomic biomarkers proposed, there is particular interest in the CKD273 classifier, a urinary proteome biomarker reported to predict CKD progression and with implementation potential. Other individual non-invasive peptidomic biomarkers that are potentially relevant for CKD detection include type 1 collagen, uromodulin and mucin-1. Despite the limited sample sizes and variability of the metabolomics studies, some metabolites such as trimethylamine N-oxide, kynurenine and citrulline stand out as potential biomarkers in CKD.

Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases

Diseases of the kidney are difficult to diagnose and treat. This review summarises the definition, cause, epidemiology and treatment of some of these diseases including chronic kidney disease, diabetic nephropathy, acute kidney injury, kidney cancer, kidney transplantation and polycystic kidney diseases. Numerous studies have adopted a metabolomics approach to uncover new small molecule biomarkers of kidney diseases to improve specificity and sensitivity of diagnosis and to uncover biochemical mechanisms that may elucidate the cause and progression of these diseases. This work includes a description of mass spectrometry-based metabolomics approaches, including some of the currently available tools, and emphasises findings from metabolomics studies of kidney diseases. We have included a varied selection of studies (disease, model, sample number, analytical platform) and focused on metabolites which were commonly reported as discriminating features between kidney disease and a control. These metabolites are likely to be robust indicators of kidney disease processes, and therefore potential biomarkers, warranting further investigation.

Gene Expression Studies and Targeted Metabolomics Reveal Disturbed Serine, Methionine, and Tyrosine Metabolism in Early Hypertensive Nephrosclerosis

Introduction

Hypertensive nephrosclerosis is among the leading causes of end-stage renal disease, but its pathophysiology is poorly understood. We wanted to explore early metabolic changes using gene expression and targeted metabolomics analysis.

Methods

We analyzed gene expression in kidneys biopsied from 20 patients with nephrosclerosis and 31 healthy controls with an Affymetrix array. Thirty-one amino acids were measured by liquid chromatography coupled with mass spectrometry (LC-MS) in urine samples from 62 patients with clinical hypertensive nephrosclerosis and 33 age- and sex-matched healthy controls, and major findings were confirmed in an independent cohort of 45 cases and 15 controls.

Results

Amino acid catabolism and synthesis were strongly underexpressed in hypertensive nephrosclerosis (13- and 7-fold, respectively), and these patients also showed gene expression patterns indicating decreased fatty acid oxidation (12-fold) and increased interferon gamma (10-fold) and cellular defense response (8-fold). Metabolomics analysis revealed significant distribution differences in 11 amino acids in hypertensive nephrosclerosis, among them tyrosine, phenylalanine, dopamine, homocysteine, and serine, with 30% to 70% lower urine excretion. These findings were replicated in the independent cohort. Integrated gene-metabolite pathway analysis showed perturbations of renal dopamine biosynthesis. There were also significant differences in homocysteine/methionine homeostasis and the serine pathway, which have strong influence on 1-carbon metabolism. Several of these disturbances could be interconnected through reduced regeneration of tetrahydrofolate and tetrahydrobiopterin.

Conclusion

Early hypertensive nephrosclerosis showed perturbations of intrarenal biosynthesis of dopamine, which regulates natriuresis and blood pressure. There were also disturbances in serine/glycine and methionine/homocysteine metabolism, which may contribute to endothelial dysfunction, atherosclerosis, and renal fibrosis.

Metabolomics: A High-Throughput Platform for Metabolite Profile Exploration

Metabolomics aims to quantitatively measure small-molecule metabolites in biological samples, such as bodily fluids (e.g., urine, blood, and saliva), tissues, and breathe exhalation, which reflects metabolic responses of a living system to pathophysiological stimuli or genetic modification. In the past decade, metabolomics has made notable progresses in providing useful systematic insights into the underlying mechanisms and offering potential biomarkers of many diseases. Metabolomics is a complementary manner of genomics and transcriptomics, and bridges the gap between genotype and phenotype, which reflects the functional output of a biological system interplaying with environmental factors. Recently, the technology of metabolomics study has been developed quickly. This review will discuss the whole pipeline of metabolomics study, including experimental design, sample collection and preparation, sample detection and data analysis, as well as mechanism interpretation, which can help understand metabolic effects and metabolite function for living organism in system level.

UPLC-Q-TOF/MS-based metabonomic studies on the intervention effects of aspirin eugenol ester in atherosclerosis hamsters

Based on the pro-drug principle, aspirin and eugenol were used to synthesize aspirin eugenol ester (AEE) by esterification reaction. In present study, the anti-atherosclerosis effects of AEE were investigated in hamsters with the utilization of metabonomic approach based on UPLC-Q-TOF/MS. Biochemical parameters and histopathological injures in stomach, liver and aorta were evaluated. In atherosclerotic hamster, oral administration of AEE normalized biochemical profile such as reducing TG, TCH and LDL, and significantly reduced body weight gain, alleviated hepatic steatosis and improved pathological lesions in aorta. Slight damages in stomach mucous were found in AEE group. Plasma and urine samples in control, model and AEE groups were scattered in the partial least squares-discriminate analysis (PLS-DA) score plots. Thirteen endogenous metabolites in plasma such as lysophosphatidylcholine (LysoPC), leucine and valine, and seventeen endogenous metabolites in urine such as citric acid, phenol sulphate and phenylacetylglycine were selected as potential biomarkers associated with atherosclerosis. They were considered to be in response to anti-atherosclerosis effects of AEE, mainly involved in glycerophospholipid metabolism, amino acid metabolism and energy metabolism. This study extended the understanding of endogenous alterations of atherosclerosis and offered insights into the pharmacodynamic activity of AEE.

A comprehensive narrative review of diagnostic biomarkers in human primary membranous nephropathy

Membranous nephropathy (MN) is relatively major cause of nephrotic syndrome in adults which is recognized as an organ-specific autoimmune disease. The etiology of most cases is idiopathic, whereas the secondary MN is caused by systemic autoimmune diseases, infections, medications and malignancies. The idiopathic disease is developed by the formation of sub-epithelial immune complex deposits most likely due to binding the circulating auto-antibodies to intrinsic antigen on podocytes. The major auto antibody is the anti-phospholipase A2 receptor (anti-PLA2R), however, it is not enough sensitive. Several attempts for diagnostic biomarker identification by modern analytical technologies have been devoted recently. This article reviews the biomarker candidates for primary type of MN that are detected by different approaches on human subjects.

Linking sources to early effects by profiling urine metabolome of residents living near oil refineries and coal-fired power plants

BACKGROUND

This study aims at identifying metabolic changes linking external exposure to industrial air toxics with oxidative stress biomarkers.

METHODS

We classified 252 study subjects as 111 high vs. 141 low exposure subjects by the distance from their homes to the two main emission sources, oil refineries and coal-fired power plants. We estimated individual's external exposure to heavy metals and polycyclic aromatic hydrocarbons (PAHs) by dispersion and kriging models, respectively. We measured urinary levels of heavy metals and 1-hydroxypyrene (1-OHP) as biomarkers of internal exposure, and 8-OHdG, HNE-MA, 8-isoPGF_2α, and 8-NO₂Gua as biomarkers of early health effects. We used two-dimensional gas chromatography time-of-flight mass spectrometry to identify urine metabolomics. We applied "meet-in-the-middle" approach to identify potential metabolites as putative intermediate biomarkers linking multiple air toxics exposures to oxidative stress with plausible exposures-related pathways.

RESULTS

High exposure subjects showed elevated ambient concentrations of vanadium and PAHs, increased urine concentrations of 1-OHP, vanadium, nickel, copper, arsenic, strontium, cadmium, mercury, and thallium, and higher urine concentrations of all four urine oxidative stress biomarkers compared to low exposure subjects. We identified a profile of putative intermediate biomarkers that were associated with both exposures and oxidative stress biomarkers in participants. Urine metabolomics identified age-dependent biological pathways, including tryptophan metabolism and phenylalanine metabolism in children subjects (aged 9-11), and glycine, serine, and threonine metabolism in elderly subjects (aged>55), that could associate multiple exposures with oxidative stress.

CONCLUSION

By profiling urine biomarkers and metabolomics in children and elderly residents living near a petrochemical complex, we can link their internal exposure to oxidative stress biomarkers through biological pathways associated with common complex chronic diseases and allergic respiratory diseases. The internal exposure may possibly be traced to multiple air toxics emitted from specific sources of oil refineries and coal-fired power plants.

Metabolomics for clinical use and research in chronic kidney disease

Chronic kidney disease (CKD) has a high prevalence in the general population and is associated with high mortality; a need therefore exists for better biomarkers for diagnosis, monitoring of disease progression and therapy stratification. Moreover, very sensitive biomarkers are needed in drug development and clinical research to increase understanding of the efficacy and safety of potential and existing therapies. Metabolomics analyses can identify and quantify all metabolites present in a given sample, covering hundreds to thousands of metabolites. Sample preparation for metabolomics requires a very fast arrest of biochemical processes. Present key technologies for metabolomics are mass spectrometry and proton nuclear magnetic resonance spectroscopy, which require sophisticated biostatistic and bioinformatic data analyses. The use of metabolomics has been instrumental in identifying new biomarkers of CKD such as acylcarnitines, glycerolipids, dimethylarginines and metabolites of tryptophan, the citric acid cycle and the urea cycle. Biomarkers such as c-mannosyl tryptophan and pseudouridine have better performance in CKD stratification than does creatinine. Future challenges in metabolomics analyses are prospective studies and deconvolution of CKD biomarkers from those of other diseases such as metabolic syndrome, diabetes mellitus, inflammatory conditions, stress and cancer.

High-throughput metabolomics approach reveals new mechanistic insights for drug response of phenotypes of geniposide towards alcohol-induced liver injury by using liquid chromatography coupled to high resolution mass spectrometry

Alcohol-induced liver injury (ALD) shows obvious metabolic disorders, categorized by a wide range of metabolite abnormalities.

Impact of Early Postnatal Nutrition on the NMR Urinary Metabolic Profile of Infant

NMR-based metabolomics was used to compare the metabolic urinary profiles of exclusively breast-fed term infants (n = 11) with those of a double-blinded controlled trial with 49 formula-fed term newborns randomized to receive either an infant formula enriched by functional ingredients (n = 24) or a standard formula (n = 25). Anthropometric measurements and urine samples were taken at enrollment (within the first month of life), at around 60 days of life, and at the end of study period (average age of 130 days). The metabolic profiles were examined in relation to time and diet strategy. A common age-dependent modification of the urine metabolome was observed for the three types of nutrition, mainly characterized by similar temporal trends of choline, betaine, myoinositol, taurine, and citrate. Contrariwise, differences in the metabolic profiles were identified according to the type of diet (human versus formula milk), while no significant difference was observed between the two formulas. These modifications are discussed mainly in terms of the different milk compositions. Despite the low number of enrolled infants (n = 60), these findings pointed out the potential of the metabolomics approach for neonatal nutritional science, in particular to provide important contributions to the optimization of formula milk.

Imbalance of plasma amino acids, metabolites and lipids in patients with lysinuric protein intolerance (LPI)

BACKGROUND

Lysinuric protein intolerance (LPI [MIM 222700]) is an aminoaciduria with defective transport of cationic amino acids in epithelial cells in the small intestine and proximal kidney tubules due to mutations in the SLC7A7 gene. LPI is characterized by protein malnutrition, failure to thrive and hyperammonemia. Many patients also suffer from combined hyperlipidemia and chronic kidney disease (CKD) with an unknown etiology.

METHODS

Here, we studied the plasma metabolomes of the Finnish LPI patients (n=26) and healthy control individuals (n=19) using a targeted platform for analysis of amino acids as well as two analytical platforms with comprehensive coverage of molecular lipids and polar metabolites.

RESULTS

Our results demonstrated that LPI patients have a dichotomy of amino acid profiles, with both decreased essential and increased non-essential amino acids. Altered levels of metabolites participating in pathways such as sugar, energy, amino acid and lipid metabolism were observed. Furthermore, of these metabolites, myo-inositol, threonic acid, 2,5-furandicarboxylic acid, galactaric acid, 4-hydroxyphenylacetic acid, indole-3-acetic acid and beta-aminoisobutyric acid associated significantly (P<0.001) with the CKD status. Lipid analysis showed reduced levels of phosphatidylcholines and elevated levels of triacylglycerols, of which long-chain triacylglycerols associated (P<0.01) with CKD.

CONCLUSIONS

This study revealed an amino acid imbalance affecting the basic cellular metabolism, disturbances in plasma lipid composition suggesting hepatic steatosis and fibrosis and novel metabolites correlating with CKD in LPI. In addition, the CKD-associated metabolite profile along with increased nitrite plasma levels suggests that LPI may be characterized by increased oxidative stress and apoptosis, altered microbial metabolism in the intestine and uremic toxicity.

Blood, urine and faecal metabolite profiles in the study of adult renal disease

Chronic kidney disease (CKD) is a major public health burden and to date traditional biomarkers of renal function (such as serum creatinine and cystatin C) are unable to identify at-risk individuals before the disease process is well under way. To help preventive strategies and maximize the potential for effective interventions, it is important to characterise the molecular changes that take place in the development of renal damage. Metabolomics is a promising tool to identify markers of renal disease since the kidneys are involved in the handling of major biochemical classes of metabolites. These metabolite levels capture a snap-shot of the metabolic profile of the individual, allowing for the potential identification of early biomarkers, and the monitoring of real-time kidney function. In this review, we describe the current status of the identification of blood/urine/faecal metabolic biomarkers in different entities of kidney diseases including: acute kidney injury, chronic kidney disease, renal transplant, diabetic nephropathy and other disorders.

Volatile Organic Metabolites Identify Patients with Mesangial Proliferative Glomerulonephritis, IgA Nephropathy and Normal Controls

Urinary volatile organic compounds (VOCs) analysis for kidney diseases has attracted a large amount of scientific interest recently, and urinary metabolite analysis has already been applied to many diseases. Urine was collected from 15 mesangial proliferative glomerulonephritis (MsPGN) patients, 21 IgA nephropathy (IgAN) patients and 15 healthy controls. Solid phase microextraction-chromatography- mass spectrometry (SPME-GC-MS) was used to analyse the urinary metabolites. The statistical methods principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLSDA) were performed to process the final data. Five metabolites were significantly greater in the group of MsPGN patients than in the normal control group (P < 0.05) while three metabolites were found at increased levels in the group of IgAN patients compared with the normal controls (P < 0.05). In addition, five metabolites were significantly increased in the group of IgAN patients compared with the MsPGN patients (P < 0.05). These five metabolites may be specific biomarkers for distinguishing between MsPGN and IgAN. The analysis of urinary VOCs appears to have potential clinical applications as a diagnostic tool.

Metabolomics in pediatric nephrology: emerging concepts

Metabolomics, the latest of the "omics" sciences, refers to the systematic study of metabolites and their changes in biological samples due to physiological stimuli and/or genetic modification. Because metabolites represent the downstream expression of genome, transcriptome, and proteome, they can closely reflect the phenotype of an organism at a specific time. As an emerging field in analytical biochemistry, metabolomics has the potential to play a major role in monitoring real-time kidney function and detecting adverse renal events. Additionally, small molecule metabolites can provide mechanistic insights into novel biomarkers of kidney diseases, given the limitations of the current traditional markers. The clinical utility of metabolomics in the field of pediatric nephrology includes biomarker discovery, defining as yet unrecognized biological therapeutic targets, linking of metabolites to relevant standard indices and clinical outcomes, and providing a window of opportunity to investigate the intricacies of environment/genetic interplay in specific disease states.

Serum metabolomic signatures of lymph node metastasis of esophageal squamous cell carcinoma

Lymph node metastasis was recently proven to be the single most important prognostic factor for esophageal cancer, an important malignant tumor with poor prognosis. A global metabolomics approach was applied to study lymph node metastasis of esophageal squamous cell carcinoma (ESCC). Metabolomics analyses were performed using gas chromatography/mass spectrometry together with univariate and multivariate statistical analyses. There were clear metabolic distinctions between ESCC patients and healthy subjects. ESCC patients could be well-classified according to lymph node metastasis. We further identified a series of differential serum metabolites for ESCC and lymph node metastatic ESCC patients, suggesting metabolic dysfunction in proliferation (aerobic glycolysis, glutaminolysis, fatty acid metabolism, and branched-chain amino acid consumption), apoptosis, migration, immune escape, and oxidative stress of cancer cells in metastatic ESCC patients. In total, three serum metabolites (valine, γ-aminobutyric acid, and pyrrole-2-carboxylic acid) were selected by binary logistic regression analysis, and their combined use resulted in high diagnostic capacity for ESCC metastasis by receiver operating characteristic analysis. The present metabolomics study staged ESCC patients by lymph node metastasis, and the results suggest promising applications of this approach in prognostic prediction, tailored therapeutics, and understanding the pathological mechanisms of poor prognosis of ESCC patients.

The primary glomerulonephritides: a systems biology approach

Our understanding of the pathogenesis of most primary glomerular diseases, including IgA nephropathy, membranous nephropathy and focal segmental glomerulosclerosis, is limited. Advances in molecular technology now permit genome-wide, high-throughput characterization of genes and gene products from biological samples. Comprehensive examinations of the genome, transcriptome, proteome and metabolome (collectively known as omics analyses), have been applied to the study of IgA nephropathy, membranous nephropathy and focal segmental glomerulosclerosis in both animal models and human patients. However, most omics studies of primary glomerular diseases, with the exception of large genomic studies, have been limited by inadequate sample sizes and the lack of kidney-specific data sets derived from kidney biopsy samples. Collaborative efforts to develop a standardized approach for prospective recruitment of patients, scheduled monitoring of clinical outcomes, and protocols for sampling of kidney tissues will be instrumental in uncovering the mechanisms that drive these diseases. Integration of molecular data sets with the results of clinical and histopathological studies will ultimately enable these diseases to be characterized in a comprehensive and systematic manner, and is expected to improve the diagnosis and treatment of these diseases.

Metabolomics in adult and pediatric nephrology

Metabolomics, the latest of the “omics” sciences, has a non-selective approach and can thus lead to the identification of all the metabolites (molecules < 1 kDa) in a biological system. The metabolomic profile can be considered the most predictive phenotype capable of evaluating epigenetic modifications determined by external factors. It is so close to the phenotype as to be considered the phenotype itself in its unique individuality (fingerprinting), both in health (phenome), and disease (diseasome). Urine, compared to other biological liquids, has the advantage of being a complex fluid with many components, including intermediate metabolites. Metabolomics may thus play a role in the study of different kidney diseases and overcome diagnostic difficulties. We shall present the studies that to our knowledge have been published on Nephrology and Pediatric Nephrology. Some are experimental while others are clinical. We have not considered carcinomas and transplantations. Although scarce, the data on adults and the very few ones in pediatrics are quite interesting. Further studies on kidneys are needed to determine the practical clinical impact of metabolomics in kidney renal pathologies. The “multiplatform” “omic” study of urine and namely metabolomics can contribute to improving early diagnosis and the outcome of kidney diseases.

Differences in metabolites of different tongue coatings in patients with chronic hepatitis B

Tongue coating is one of the important foundations of tongue diagnosis in traditional Chinese medicine (TCM) and plays an important role in reflecting the occurrence, development, and prognosis of the disease. However, its material basis is still poorly understood. In this study, a urinary metabonomic method based on gas chromatography coupled to mass spectrometry (GC/MS) was developed. The distinct clustering in metabolic profile was observed from Group A (thick yellow coating in patients with chronic hepatitis B), Group B (thick white coating in patients with chronic hepatitis B), and Group C (thin white coating with healthy humans) using orthogonal projections to latent structures (OPLS). Based on the variable of importance in the project (VIP) values, some significantly changed metabolites have been identified. These changes were related to the disturbance in energy metabolism, amino acid metabolism, nucleotide metabolism, and gut microflora, which were helpful to understand the material basis leading to the formation of tongue coating. This study demonstrated that tongue coating may have an objective material basis.