1 H NMR-based metabolomics exploring urinary biomarkers correlated with proteinuria in focal segmental glomerulosclerosis: a pilot study

The nephropathy of sickle cell trait and sickle cell disease

Sickle cell syndromes, including sickle cell disease (SCD) and sickle cell trait, are associated with multiple kidney abnormalities. Young patients with SCD have elevated effective renal plasma flow and glomerular filtration rates, which decrease to normal ranges in young adulthood and subnormal levels with advancing age. The pathophysiology of SCD-related nephropathy is multifactorial - oxidative stress, hyperfiltration and glomerular hypertension are all contributing factors. Albuminuria, which is an early clinical manifestation of glomerular damage, is common in individuals with SCD. Kidney function declines more rapidly in individuals with SCD than in those with sickle cell trait or in healthy individuals. Multiple genetic modifiers, including APOL1, HMOX1, HBA1 and HBA2 variants are also implicated in the development and progression of SCD-related nephropathy. Chronic kidney disease and rapid decline in estimated glomerular filtration rate are associated with increased mortality in adults with SCD. Renin-angiotensin-aldosterone system inhibitors are the standard of care treatment for albuminuria in SCD, despite a lack of controlled studies demonstrating their long-term efficacy. Multiple studies of novel therapeutic agents are ongoing, and patients with SCD and kidney failure should be evaluated for kidney transplantation. Given the high prevalence and severe consequences of kidney disease, additional studies are needed to elucidate the pathophysiology, natural history and treatment of SCD-related nephropathy.

Aristolochic acid I as an emerging biogenic contaminant involved in chronic kidney diseases: A comprehensive review on exposure pathways, environmental health issues and future challenges

Described in the 1950s, Balkan Endemic Nephropathy (BEN) has been recognized as a chronic kidney disease (CKD) with clinical peculiarities and multiple etiological factors. Environmental contaminants - aromatic compounds, mycotoxins and phytotoxins like aristolochic acids (AAs) - polluting food and drinking water sources, were incriminated in BEN, due to their nephrotoxic and carcinogenic properties. The implication of AAs in BEN etiology is currently a highly debated topic due to the fact that they are found within the Aristolochiaceae plants family, used around the globe as traditional medicine and they were also incriminated in Aristolochic Acid Nephropathy (AAN). Exposure pathways have been investigated, but it is unclear to what extent AAs are acting alone or in synergy with other cofactors (environmental, genetics) in triggering kidney damage. Experimental studies strengthen the hypothesis that AAI, the most studied compound in the AAs class, is a significant environmental contaminant and a most important causative factor of BEN. The aim of this review is to compile information about the natural exposure pathways to AAI, via traditional medicinal plants, soil, crop plants, water, food, air. Data that either supports or contradicts the AAI theory concerning BEN etiology was consolidated and available solutions to reduce human exposure were discussed. Because AAI is a phytotoxin with physicochemical properties that allow its transportation in environmental matrices from different types of areas (endemic, nonendemic), and induce CKDs (BEN, AAN) and urinary cancers through bioaccumulation, this review aims to shed a new light on this compound as a biogenic emerging pollutant.

1H Nuclear Magnetic Resonance Spectroscopy-Based Methods for the Quantification of Proteins in Urine

We described several postprocessing methods to measure protein concentrations in human urine from existing ¹H nuclear magnetic resonance (NMR) metabolomic spectra: (1) direct spectral integration, (2) integration of NCD spectra (NCD = 1D NOESY-CPMG), (3) integration of SMolESY-filtered 1D NOESY spectra (SMolESY = Small Molecule Enhancement SpectroscopY), (4) matching protein patterns, and (5) TSP line integral and TSP linewidth. Postprocessing consists of (a) removal of the metabolite signals (demetabolization) and (b) extraction of the protein integral from the demetabolized spectra. For demetabolization, we tested subtraction of the spin-echo 1D spectrum (CPMG) from the regular 1D spectrum and low-pass filtering of 1D NOESY by its derivatives (c-SMolESY). Because of imperfections in the demetabolization, in addition to direct integration, we extracted protein integrals by the piecewise comparison of demetabolized spectra with the reference spectrum of albumin. We analyzed 42 urine samples with protein content known from the bicinchoninic acid (BCA) assay. We found excellent correlation between the BCA assay and the demetabolized NMR integrals. We have provided conversion factors for calculating protein concentrations in mg/mL from spectral integrals in mM. Additionally, we found the trimethylsilyl propionate (TSP, NMR standard) spectral linewidth and the TSP integral to be good indicators of protein concentration. The described methods increase the information content of urine NMR metabolomics spectra by informing clinical studies of protein concentration.

A Noninvasive Urine Metabolome Panel as Potential Biomarkers for Diagnosis of T Cell-Mediated Renal Transplant Rejection

Acute T cell-mediated rejection (TCMR) is a major complication after renal transplantation. TCMR diagnosis is very challenging and currently depends on invasive renal biopsy and nonspecific markers such as serum creatinine. A noninvasive metabolomics panel could allow early diagnosis and improved accuracy and specificity. We report, in this study, on urine metabolome changes in renal transplant recipients diagnosed with TCMR, with a view to future metabolomics-based diagnostics in transplant medicine. We performed urine metabolomic analyses in three study groups: (1) 7 kidney transplant recipients with acute TCMR, (2) 15 kidney transplant recipients without rejection but with impaired kidney function, and (3) 6 kidney transplant recipients with stable renal function, using ¹H-nuclear magnetic resonance. Multivariate modeling of metabolites suggested a diagnostic panel where the diagnostic accuracy of each metabolite was calculated by receiver operating characteristic curve analysis. The impaired metabolic pathways associated with TCMR were identified by pathway analysis. In all, a panel of nine differential metabolites encompassing nicotinamide adenine dinucleotide, 1-methylnicotinamide, cholesterol sulfate, gamma-aminobutyric acid (GABA), nicotinic acid, nicotinamide adenine dinucleotide phosphate, proline, spermidine, and alpha-hydroxyhippuric acid were identified as novel potential metabolite biomarkers of TCMR. Proline, spermidine, and GABA had the highest area under the curve (>0.7) and were overrepresented in the TCMR group. Nicotinate and nicotinamide metabolism was the most important pathway in TCMR. These findings call for clinical validation in larger study samples and suggest that urinary metabolomics warrants future consideration as a noninvasive research tool for TCMR diagnostic innovation.

Toxicological Risks of Renqingchangjue in Rats Evaluated by 1H NMR-Based Serum and Urine Metabolomics Analysis

Renqingchangjue (RQCJ), a kind of Traditional Tibetan Medicine, has been widely utilized to treat various gastroenteritis diseases. However, the biosafety and toxicity of RQCJ was still indefinite because of toxic components in RQCJ, which included a variety of heavy metals. Thus, this study was aimed to evaluate the toxicity and expound the toxicological mechanism of RQCJ. In this study, rats were intragastrically administered with different doses of RQCJ for 15 days, and then, the restorative observation period lasted for 15 days. Liver and kidney tissues were collected for histopathological examination, and simultaneously serum and urine samples were collected for 1H nuclear magnetic resonance (1H NMR) spectroscopy analysis and biochemical analysis combined with inductively coupled plasma mass spectrometry (ICP-MS) measurement. The 1H NMR-based metabolomics analysis revealed that the administration of RQCJ significantly altered the concentrations of 14 serum metabolites and 14 urine metabolites, which implied disturbances in energy metabolism, amino acid metabolism, intestinal flora environment, and membrane damage. Besides, the biochemical analysis of serum samples was consistent with the histopathological results, which indicated slight hepatotoxicity and nephrotoxicity. The quantification of As and Hg in urine and serum samples by ICP-MS provided more evidence about the toxicity of RQCJ. This work provided an effective method to systematically and dynamically evaluate the toxicity of RQCJ and suggested that precautions should be taken in the clinic to monitor the potential toxicity of RQCJ.

Urine and serum NMR-based metabolomics in pre-procedural prediction of contrast-induced nephropathy

Contrast induced nephropathy (CIN) has been reported to be the third foremost cause of acute renal failure. Metabolomics is a robust technique that has been used to identify potential biomarkers for the prediction of renal damage. We aim to analyze the serum and urine metabolites changes, before and after using contrast for coronary angiography, to determine if metabolomics can predict early development of CIN. 66 patients undergoing elective coronary angiography were eligible for enrollment. Urine and serum samples were collected prior to administration of CM and 72 h post procedure and analyzed by nuclear magnetic resonance. The significant differential metabolites between patients who develop CIN and patients who have stable renal function after angiography were identified using U test and receiver operating characteristic analysis was performed for each metabolite candidate. Potential susceptible pathways to cytotoxic effect of CM were investigated by pathway analysis. A predictive panel composed of six urinary metabolites had the best area under the curve. Glutamic acid, uridine diphosphate, glutamine and tyrosine were the most important serum predictive biomarkers. Several pathways related to amino acid and nicotinamide metabolism were suggested as impaired pathways in CIN prone patients. Changes exist in urine and serum metabolomics patterns in patients who do and do not develop CIN after coronary angiography hence metabolites may be potential predictive identifiers of CIN.

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.

An update of urine and blood metabolomics in chronic kidney disease

Chronic kidney disease is considered as a serious obstacle in global health, with increasing incidence and prevalence. In spite of numerous attempts by using recent omics technologies, specially metabolomics, for understanding pathophysiology, molecular mechanism and identification reliable consensus biomarkers for diagnosis and prognosis of this complex disease, the current biomarkers are still insensitive and many questions about its pathomechanism are still to be unanswered. This review is focused on recent findings about urine and serum/plasma metabolite biomarkers and changes in the pathways that occurs in the disease conditions. The urine and blood metabolome content in the normal and disease state is investigated based on the current metabolomics studies and well known metabolite candidate biomarkers for chronic kidney disease are discussed.

Biomarker of Aflatoxin Ingestion: ¹H NMR-Based Plasma Metabolomics of Dairy Cows Fed Aflatoxin B₁ with or without Sequestering Agents

The study applied ¹H NMR-based plasma metabolomics to identify candidate biomarkers of aflatoxin B1 (AFB₁) ingestion in dairy cows fed no sequestering agents and evaluate the effect of supplementing clay and/or a Saccharomyces cerevisiae fermentation product (SCFP) on such biomarkers. Eight lactating cows were randomly assigned to 1 of 4 treatments in a balanced 4 × 4 Latin square design with 2 squares. Treatments were: control, toxin (T; 1725 µg AFB₁/head/day), T with clay (CL; 200 g/head/day), and CL with SCFP (CL + SCFP; 35 g of SCFP/head/day). Cows in T, CL, and CL + SCFP were dosed with AFB₁ from d 26 to 30. The sequestering agents were top-dressed from d 1 to 33. On d 30 of each period, 15 mL of blood was taken from the coccygeal vessels and plasma samples were prepared by centrifugation. Compared to the control, T decreased plasma concentrations of alanine, acetic acid, leucine, arginine and valine. In contrast, T increased plasma ethanol concentration 3.56-fold compared to control. Treatment with CL tended to reduce sarcosine concentration, whereas treatment with CL + SCFP increased concentrations of mannose and 12 amino acids. Based on size of the area under the curve (AUC) of receiver operating characteristic and fold change (FC) analyses, ethanol was the most significantly altered metabolite in T (AUC = 0.88; FC = 3.56); hence, it was chosen as the candidate biomarker of aflatoxin ingestion in dairy cows fed no sequestering agent.

Network analysis of membranous glomerulonephritis based on metabolomics data

Membranous glomerulonephritis (MGN) is one of the most frequent causes of nephrotic syndrome in adults. It is characterized by the thickening of the glomerular basement membrane in the renal tissue. The current diagnosis of MGN is based on renal biopsy and the detection of antibodies to the few podocyte antigens. Due to the limitations of the current diagnostic methods, including invasiveness and the lack of sensitivity of the current biomarkers, there is a requirement to identify more applicable biomarkers. The present study aimed to identify diagnostic metabolites that are involved in the development of the disease using topological features in the component‑reaction‑enzyme‑gene (CREG) network for MGN. Significant differential metabolites in MGN compared with healthy controls were identified using proton nuclear magnetic resonance and gas chromatography‑mass spectrometry techniques, and multivariate analysis. The CREG network for MGN was constructed, and metabolites with a high centrality and a striking fold‑change in patients, compared with healthy controls, were introduced as putative diagnostic biomarkers. In addition, a protein‑protein interaction (PPI) network, which was based on proteins associated with MGN, was built and analyzed using PPI analysis methods, including molecular complex detection and ClueGene Ontology. A total of 26 metabolites were identified as hub nodes in the CREG network, 13 of which had salient centrality and fold‑changes: Dopamine, carnosine, fumarate, nicotinamide D‑ribonucleotide, adenosine monophosphate, pyridoxal, deoxyguanosine triphosphate, L‑citrulline, nicotinamide, phenylalanine, deoxyuridine, tryptamine and succinate. A total of 13 subnetworks were identified using PPI analysis. In total, two of the clusters contained seed proteins (phenylalanine‑4‑hydroxlylase and cystathionine γ‑lyase) that were associated with MGN based on the CREG network. The following biological processes associated with MGN were identified using gene ontology analysis: 'Pyrimidine‑containing compound biosynthetic process', 'purine ribonucleoside metabolic process', 'nucleoside catabolic process', 'ribonucleoside metabolic process' and 'aromatic amino acid family metabolic process'. The results of the present study may be helpful in the diagnostic and therapeutic procedures of MGN. However, validation is required in the future.

The metabolomic quest for a biomarker in chronic kidney disease

Chronic kidney disease (CKD) is a growing burden on people and on healthcare for which the diagnostics are niether disease-specific nor indicative of progression. Biomarkers are sought to enable clinicians to offer more appropriate patient-centred treatments, which could come to fruition by using a metabolomics approach. This mini-review highlights the current literature of metabolomics and CKD, and suggests additional factors that need to be considered in this quest for a biomarker, namely the diet and the gut microbiome, for more meaningful advances to be made.

Application of metabolomics to preeclampsia diagnosis

Preeclampsia is a multifactorial disorder defined by hypertension and increased urinary protein excretion during pregnancy. It is a significant cause of maternal and neonatal deaths worldwide. Despite various research efforts to clarify pathogenies of preeclampsia and predict this disease before beginning of symptoms, the pathogenesis of preeclampsia is unclear. Early prediction and diagnosis of women at risk of preeclampsia has not markedly improved. Therefore, the objective of this study was to perform a review on metabolomic articles assessing predictive and diagnostic biomarkers of preeclampsia. Four electronic databases including PubMed/Medline, Web of Science, Sciencedirect, and Scopus were searched to identify studies of preeclampsia in humans using metabolomics from inception to March 2018. Twenty-one articles in a variety of biological specimens and analytical platforms were included in the present review. Metabolite profiles may assist in the diagnosis of preeclampsia and discrimination of its subtypes. Lipids and their related metabolites were the most generally detected metabolites. Although metabolomic biomarkers of preeclampsia are not routinely used, this review suggests that metabolomics has the potential to be developed into a clinical tool for preeclampsia diagnosis and could contribute to an improved understanding of disease mechanisms.

ABBREVIATIONS

PE: preeclampsia; sFlt-1: soluble FMS-like tyrosine kinase-1; PlGF: placental growth factor; GC-MS: gas chromatography-mass spectrometry; LC-MS: liquid chromatography-mass spectrometry; NMR: nuclear magnetic resonance spectroscopy; HMDB: human metabolome database; RCT: randomized control trial; e-PE: early-onset PE; l-PE: late-onset PE; PLS-DA: partial least-squares-discriminant analysis; CRL: crown-rump length; UtPI: uterine artery Doppler pulsatility index; BMI: body mass index; MAP: mean arterial pressure; OS: oxidative stress; PAPPA: plasma protein A; FTIR: Fourier transform infrared; BCAA: branched chain amino acids; Arg: arginine; NO: nitric oxide.

1 H NMR-based metabolomics study for identifying urinary biomarkers and perturbed metabolic pathways associated with severity of IgA nephropathy: a pilot study

The severity of IgA nephropathy (IgAN), the most common primary glomerulonephritis, is judged on the basis of histologic and clinical features. A limited number of studies have considered molecular signature of IgAN for this issue, and no reliable biomarkers have been presented non-invasively for use in patient evaluations. This study aims to identify metabolite markers excreted in the urine and impaired pathways that are associated with a known marker of severity (proteinuria) to predict mild and severe stages of IgAN. Urine samples were analysed using nuclear magnetic resonance from biopsy-proven IgAN patients at mild and severe stages. Multivariate statistical analysis and pathway analysis were performed. The most changed metabolites were acetoacetate, hypotaurine, homocysteine, L-kynurenine and phenylalanine. Nine metabolites were positively correlated with proteinuria, including mesaconic acid, trans-cinnamic acid, fumaric acid, 5-thymidylic acid, anthranilic acid, indole, deoxyguanosine triphosphate, 13-cis-retinoic acid and nicotinamide riboside, while three metabolites were negatively correlated with proteinuria including acetoacetate, hypotaurine and hexanal. 'Phenylalanine metabolism' was the most significant pathway which was impaired in severe stage in comparison to mild stage of IgAN. This study indicates that nuclear magnetic resonance is a versatile technique that is capable of detecting metabolite biomarkers in combination with advanced multivariate statistical analysis. Copyright © 2017 John Wiley & Sons, Ltd.