New insights into uremia-induced alterations in metabolic pathways

Blood Levels of Endocannabinoids, Oxylipins, and Metabolites Are Altered in Hemodialysis Patients

Hemodialysis patients (HDPs) have higher blood pressure, higher levels of inflammation, a higher risk of cardiovascular disease, and unusually low plasma n-3 polyunsaturated fatty acid (PUFA) levels compared to healthy subjects. The objective of our investigation was to examine the levels of endocannabinoids (eCBs) and oxylipins (OxLs) in female HDPs compared to healthy matched female controls, with the underlying hypothesis that differences in specific PUFA levels in hemodialysis patients would result in changes in eCBs and OxLs. Plasma phospholipid fatty acids were analyzed by gas chromatography. Plasma was extracted and analyzed using ultra-performance liquid chromatography followed by electrospray ionization and tandem MS for eCBs and OxLs. The global untargeted metabolite profiling of plasma was performed by GCTOF MS. Compared to the controls, HDPs showed lower levels of plasma EPA and the associated OxL metabolites 5- and 12-HEPE, 14,15-DiHETE, as well as DHA derived 19(20)-EpDPE. Meanwhile, no changes in arachidonylethanolamide or 2-arachidonylglycerol in the open circulation were detected. Higher levels of multiple N-acylethanolamides, monoacylglycerols, biomarkers of progressive kidney disease, the nitric oxide metabolism-linked citrulline, and the uremic toxins kynurenine and creatine were observed in HDP. These metabolic differences in cCBs and OxLs help explain the severe inflammatory and cardiovascular disease manifested by HDPs, and they should be explored in future studies.

Essential and Non-Essential Amino Acids in Dogs at Different Stages of Chronic Kidney Disease

Abnormalities of serum amino acid profile, mostly characterized by a reduction in essential amino acids (EAAs) and an increase in non-essential amino acids (NEAAs), have been documented in human chronic kidney diseases (CKD). Amino acid disorders have been associated with CKD complications, such as metabolic acidosis and malnutrition. The aim of the present study was to evaluate EAAs and NEAAs in dogs affected by CKD at different IRIS stages, with particular reference to calcium−phosphate abnormalities, metabolic acidosis, and protein-energy wasting syndrome (PEW). Serum EAAs (L-histidine, L-isoleucine, L-leucine, L-lysine, methionine, L-phenylalanine, L-threonine, tryptophan, L-valine, and L-arginine) and serum NEAAs (L-alanine, L-aspartic acid, L-cysteine, L-glutamic acid, glycine, proline, L-serine, and L-tyrosine) were analyzed with HPLC in a group of dogs with CKD (n = 62), and in a group of healthy dogs (n = 25). CKD dogs showed significantly lower serum levels of histidine (p < 0.000), isoleucine (p < 0.000), tryptophan (p < 0.000), alanine (p = 0.013), cysteine (p < 0.000), and serine (p = 0.002), and significantly higher levels of proline (p < 0.000), leucine (p = 0.001), lysine (p < 0.000), valine (p < 0.000), arginine (p = 0.002), glutamic acid (p = 0.002), and glycine (p = 0.010) compared to healthy dogs. Dogs with abnormal calcium x phosphate values showed significantly higher levels of cysteine (p = 0.003), and lower levels of tryptophan (p = 0.025) compared to CKD dogs with normal CaxP. Dogs with metabolic acidosis showed significantly higher levels of phenylalanine (p = 0.035) and leucine (p = 0.034) compared to CKD dogs without metabolic acidosis. Dogs with PEW showed significantly lower levels for most of amino acids. In PEW dogs, the median distribution of both EAAs (p = 0.000) and NEAAs (p = 0.001) was significantly lower. The serum pattern of both EAAs and NEAAs was significantly different in CKD dogs compared to healthy dogs, although no association with the progression of the IRIS stage was found.

A surface-enhanced Raman scattering-based approach for rapid and highly sensitive quantitative analysis of 3-carboxy-4-methyl-5-propyl-2-furanpropionate and indole-3-acetic acid in saline, human serum and uremic serum of patients with chronic kidney disease

3-Carboxy-4-methyl-5-propyl-2-furanpropionate (CMPF) and indole-3-acetic acid (IAA) are critical protein-bound uremic toxins that occur during chronic kidney disease (CKD). This study offers the first reported instance of surface-enhanced Raman scattering (SERS) coupled with an Au nanoparticle substrate for the simple quantification of CMPF and IAA in human serum samples. The detection limits of the CMPF and IAA analysis were estimated to be 0.04 nM (S/N = 3) and 0.05 μM (S/N = 3), respectively. The results demonstrate that the SERS technique is fast-acting and highly sensitive when it comes to the simultaneous and individual quantitative detection of CMPF and IAA in biological samples. We believe that this analytical tool could serve as a very useful method for practical applications during the analysis of CMPF and IAA in the serum and urine of patients at all stages of CKD and of healthy volunteers as well as in various reservoirs.

The relationship between blood metabolites of the tryptophan pathway and kidney function: a bidirectional Mendelian randomization analysis

Blood metabolites of the tryptophan pathway were found to be associated with kidney function and disease in observational studies. In order to evaluate causal relationship and direction, we designed a study using a bidirectional Mendelian randomization approach. The analyses were based on published summary statistics with study sizes ranging from 1,960 to 133,413. After correction for multiple testing, results provided no evidence of an effect of metabolites of the tryptophan pathway on estimated glomerular filtration rate (eGFR). Conversely, lower eGFR was related to higher levels of four metabolites: C-glycosyltryptophan (effect estimate = − 0.16, 95% confidence interval [CI] (− 0.22; − 0.1); p = 9.2e−08), kynurenine (effect estimate = − 0.18, 95% CI (− 0.25; − 0.11); p = 1.1e−06), 3-indoxyl sulfate (effect estimate = − 0.25, 95% CI (− 0.4; − 0.11); p = 6.3e−04) and indole-3-lactate (effect estimate = − 0.26, 95% CI (− 0.38; − 0.13); p = 5.4e−05). Our study supports that lower eGFR causes higher blood metabolite levels of the tryptophan pathway including kynurenine, C-glycosyltryptophan, 3-indoxyl sulfate, and indole-3-lactate. These findings aid the notion that metabolites of the tryptophan pathway are a consequence rather than a cause of reduced eGFR. Further research is needed to specifically examine relationships with respect to chronic kidney disease (CKD) progression among patients with existing CKD.

Genetic studies of urinary metabolites illuminate mechanisms of detoxification and excretion in humans

The kidneys integrate information from continuous systemic processes related to the absorption, distribution, metabolism and excretion (ADME) of metabolites. To identify underlying molecular mechanisms, we performed genome-wide association studies of the urinary concentrations of 1,172 metabolites among 1,627 patients with reduced kidney function. The 240 unique metabolite-locus associations (metabolite quantitative trait loci, mQTLs) that were identified and replicated highlight novel candidate substrates for transport proteins. The identified genes are enriched in ADME-relevant tissues and cell types, and they reveal novel candidates for biotransformation and detoxification reactions. Fine mapping of mQTLs and integration with single-cell gene expression permitted the prioritization of causal genes, functional variants and target cell types. The combination of mQTLs with genetic and health information from 450,000 UK Biobank participants illuminated metabolic mediators, and hence, novel urinary biomarkers of disease risk. This comprehensive resource of genetic targets and their substrates is informative for ADME processes in humans and is relevant to basic science, clinical medicine and pharmaceutical research.

Gut Microbiota and Cardiovascular Uremic Toxicities

Cardiovascular disease (CVD) remains a major cause of high morbidity and mortality in patients with chronic kidney disease (CKD). Numerous CVD risk factors in CKD patients have been described, but these do not fully explain the high pervasiveness of CVD or increased mortality rates in CKD patients. In CKD the loss of urinary excretory function results in the retention of various substances referred to as "uremic retention solutes". Many of these molecules have been found to exert toxicity on virtually all organ systems of the human body, leading to the clinical syndrome of uremia. In recent years, an increasing body of evidence has been accumulated that suggests that uremic toxins may contribute to an increased cardiovascular disease (CVD) burden associated with CKD. This review examined the evidence from several clinical and experimental studies showing an association between uremic toxins and CVD. Special emphasis is addressed on emerging data linking gut microbiota with the production of uremic toxins and the development of CKD and CVD. The biological toxicity of some uremic toxins on the myocardium and the vasculature and their possible contribution to cardiovascular injury in uremia are also discussed. Finally, various therapeutic interventions that have been applied to effectively reduce uremic toxins in patients with CKD, including dietary modifications, use of prebiotics and/or probiotics, an oral intestinal sorbent that adsorbs uremic toxins and precursors, and innovative dialysis therapies targeting the protein-bound uremic toxins are also highlighted. Future studies are needed to determine whether these novel therapies to reduce or remove uremic toxins will reduce CVD and related cardiovascular events in the long-term in patients with chronic renal failure.

Plasma metabolite profiles in children with current asthma

BACKGROUND

Identifying metabolomic profiles of children with asthma has the potential to increase understanding of asthma pathophysiology.

OBJECTIVE

To identify differences in plasma metabolites between children with and without current asthma at mid-childhood.

METHODS

We used untargeted mass spectrometry to measure plasma metabolites in 237 children (46 current asthma cases and 191 controls) in Project Viva, a birth cohort from eastern Massachusetts, USA. Current asthma was assessed at mid-childhood (mean age 8.0 years). The ability of a broad spectrum metabolic profile to distinguish between cases and controls was assessed using partial least squares discriminant analysis. We used logistic regression models to identify individual metabolites that were differentially abundant by case-control status. We tested significant metabolites for replication in 411 children from the VDAART clinical trial.

RESULTS

There was no evidence of a systematic difference in the metabolome of children reporting current asthma vs. healthy controls according to partial least squares discriminant analysis. However, several metabolites were associated with odds of current asthma at a nominally significant threshold (P < .05), including a metabolite of nicotinamide (N1-Methyl-2-pyridone-5-carboxamide (Odds Ratio (OR) = 2.8 (95% CI 1.1-8.0)), a pyrimidine metabolite (5,6-dihydrothymine (OR = 0.4 (95% CI 0.2-0.9)), bile constituents (biliverdin (OR = 0.4 (95%CI 0.1-0.9), taurocholate (OR = 2.0 (95% CI 1.2-3.4)), two peptides likely derived from fibrinopeptide A (ORs from 1.6 to 1.7), and a gut microbiome metabolite (p-cresol sulphate OR = 0.5 (95% CI 0.2-0.9)). The associations for N1-Methyl-2-pyridone-5-carboxamide and p-cresol sulphate replicated in the independent VDAART population (one-sided P values = .03-.04).

CONCLUSIONS AND CLINICAL RELEVANCE

Current asthma is nominally associated with altered levels of several metabolites, including metabolites in the nicotinamide pathway, and a bacterial metabolite derived from the gut microbiome.

Co-Expression Analysis of Blood Cell Genome Expression to Preliminary Investigation of Regulatory Mechanisms in Uremia

Background

Uremia involves a series of clinical manifestations and is a common syndrome that occurs in nearly all end-stage kidney diseases. However, the exact genetic and/or molecular mechanisms that underlie uremia remain poorly understood.

Material/Methods

In this case-control study, we analyzed whole-genome microarray of 75 uremia patients and 20 healthy controls to investigate changes in gene expression and cellular mechanisms relevant to uremia. Gene co-expression network analysis was performed to construct co-expression networks using differentially expressed genes (DEGs) in uremia. We then determined hub models of co-expressed gene networks by MCODE, and we used miRNA enrichment analysis to detect key miRNAs in each hub module.

Results

We found nine co-expressed hub modules implicated in uremia. These modules were enriched in specific biological functions, including “proteolysis”, “membrane-enclosed lumen”, and “apoptosis”. Finally, miRNA enrichment analysis to detect key miRNAs in each hub module found 15 miRNAs that were specifically targeted to uremia-related hub modules. Of these, miRNA-21-3p and miRNA-210-3p have been identified in other studies as being important for uremia.

Conclusions

In summary, our study connected biological functions, genes, and miRNAs that underpin the network modules that can be used to elucidate the molecular mechanisms involved in uremia.

Integration of metabolomic and transcriptomic networks in pregnant women reveals biological pathways and predictive signatures associated with preeclampsia

INTRODUCTION

Preeclampsia is a leading cause of maternal and fetal mortality worldwide, yet its exact pathogenesis remains elusive.

OBJECTIVES

This study, nested within the Vitamin D Antenatal Asthma Reduction Trial (VDAART), aimed to develop integrated omics models of preeclampsia that have utility in both prediction and in the elucidation of underlying biological mechanisms.

METHODS

Metabolomic profiling was performed on first trimester plasma samples of 47 pregnant women from VDAART who subsequently developed preeclampsia and 62 controls with healthy pregnancies, using liquid-chromatography tandem mass-spectrometry. Metabolomic profiles were generated based on logistic regression models and assessed using Received Operator Characteristic Curve analysis. These profiles were compared to profiles from generated using third trimester samples. The first trimester metabolite profile was then integrated with a pre-existing transcriptomic profile using network methods.

RESULTS

In total, 72 (0.9%) metabolite features were associated (p<0.01) with preeclampsia after adjustment for maternal age, race, and gestational age. These features had moderate to good discriminatory ability; in ROC curve analyses a summary score based on these features displayed an area under the curve (AUC) of 0.794 (95%CI 0.700, 0.888). This profile retained the ability to distinguish preeclamptic from healthy pregnancies in the third trimester (AUC:0.762 (95% CI 0.663, 0.860)). Additionally, metabolite set enrichment analysis identified common pathways, including glycerophospholipid metabolism, at the two time-points. Integration with the transcriptomic signature refined these results suggesting a particular role for lipid imbalance, immune function and the circulatory system.

CONCLUSIONS

These findings suggest it is possible to develop a predictive metabolomic profile of preeclampsia. This profile is characterized by changes in lipid and amino acid metabolism and dysregulation of immune response and can be refined through interaction with transcriptomic data. However validation in larger and more diverse populations is required.

Mitochondrial Dysfunction in the Diabetic Kidney

The role of mitochondria in diabetic complications has been viewed as a source of excess superoxide production leading to cell dysfunction. However, with the lack of benefit of non-specific anti-oxidant approaches this view needs to be re-evaluated. With recent studies using real-time imaging of superoxide, metabolomics, flux studies, transcriptomics and proteomics a new appreciation for the role of mitochondria in the evolution of diabetic kidney disease has emerged. Ongoing studies to further unravel the time course and mechanisms that reduce mitochondrial function will be relevant to novel therapies that could have a major impact on diabetic kidney disease and other diabetic complications.

Metabolomics and renal disease

PURPOSE OF REVIEW

This review summarizes recent metabolomics studies of renal disease, outlining some of the limitations of the literature to date.

RECENT FINDINGS

The application of metabolomics in nephrology research has expanded from the initial analyses of uremia to include both cross-sectional and longitudinal studies of earlier stages of kidney disease. Although these studies have nominated several potential markers of incident chronic kidney disease (CKD) and CKD progression, a lack of overlap in metabolite coverage has limited the ability to synthesize results across groups. Furthermore, direct examination of renal metabolite handling has underscored the substantial impact kidney function has on these potential markers (and many other circulating metabolites). In experimental studies, metabolomics has been used to identify a signature of decreased mitochondrial function in diabetic nephropathy and a preference for aerobic glucose metabolism in polycystic kidney disease. In each case, these studies have outlined novel therapeutic opportunities. Finally, as a complement to the longstanding interest in renal metabolite clearance, the microbiome has been increasingly recognized as the source of many plasma metabolites, including some with potential functional relevance to CKD and its complications.

SUMMARY

The high-throughput, high-resolution phenotyping enabled by metabolomics technologies has begun to provide insight on renal disease in clinical, physiologic, and experimental contexts.

The metabolomics of asthma control: a promising link between genetics and disease

Short-acting β agonists (e.g., albuterol) are the most commonly used medications for asthma, a disease that affects over 300 million people in the world. Metabolomic profiling of asthmatics taking β agonists presents a new and promising resource for identifying the molecular determinants of asthma control. The objective is to identify novel genetic and biochemical predictors of asthma control using an integrative "omics" approach. We generated lipidomic data by liquid chromatography tandem mass spectrometry (LC-MS), - using plasma samples from 20 individuals with asthma. The outcome of interest was a binary indicator of asthma control defined by the use of albuterol inhalers in the preceding week. We integrated metabolomic data with genome-wide genotype, gene expression, and methylation data of this cohort to identify genomic and molecular indicators of asthma control. A Conditional Gaussian Bayesian Network (CGBN) was generated using the strongest predictors from each of these analyses. Integrative and metabolic pathway over-representation analyses (ORA) identified enrichment of known biological pathways within the strongest molecular determinants. Of the 64 metabolites measured, 32 had known identities. The CGBN model based on four SNPs (rs9522789, rs7147228, rs2701423, rs759582) and two metabolites-monoHETE_0863 and sphingosine-1-phosphate (S1P) could predict asthma control with an AUC of 95%. Integrative ORA identified 17 significantly enriched pathways related to cellular immune response, interferon signaling, and cytokine-related signaling, for which arachidonic acid, PGE2 and S1P, in addition to six genes (CHN1, PRKCE, GNA12, OASL, OAS1, and IFIT3) appeared to drive the pathway results. Of these predictors, S1P, GNA12, and PRKCE were enriched in the results from integrative and metabolic ORAs. Through an integrative analysis of metabolomic, genomic, and methylation data from a small cohort of asthmatics, we implicate altered metabolic pathways, related to sphingolipid metabolism, in asthma control. These results provide insight into the pathophysiology of asthma control.

Cardiovascular disease relates to intestinal uptake of p-cresol in patients with chronic kidney disease

Background

Serum p-cresyl sulfate (PCS) associates with cardiovascular disease in patients with chronic kidney disease. PCS concentrations are determined by intestinal uptake of p-cresol, human metabolism to PCS and renal clearance. Whether intestinal uptake of p-cresol itself is directly associated with cardiovascular disease in patients with renal dysfunction has not been studied to date.

Methods

We performed a prospective study in patients with chronic kidney disease stage 1 – 5 (NCT00441623). Intestinal uptake of p-cresol, under steady state conditions, was estimated from 24 h urinary excretion of PCS. Primary endpoint was time to first cardiovascular event, i.e., cardiac death, myocardial infarction/ischemia, ventricular arrhythmia, cardiovascular surgery, ischemic stroke or symptomatic peripheral arterial disease. Statistical analysis was done using Kaplan-Meier estimates and Cox proportional hazard analyses.

Results

In a cohort of 200 patients, median 24 h urinary excretion of PCS amounted to 457.47 μmol (IQR 252.68 – 697.17). After a median follow-up of 52 months, 25 patients reached the primary endpoint (tertile 1/2/3: 5/6/14 events, log rank P 0.037). Higher urinary excretion of PCS was directly associated with cardiovascular events (univariate hazard ratio per 100 μmol increase: 1.112, P 0.002). In multivariate analysis, urinary excretion of PCS remained a predictor of cardiovascular events, independent of eGFR (hazard ratio 1.120, P 0.002).

Conclusions

In patients with chronic kidney disease, intestinal uptake of p-cresol associates with cardiovascular disease independent of renal function. The intestinal generation and absorption of p-cresol may be therapeutic targets to reduce cardiovascular disease risk in patients with renal dysfunction.

Metabolomics insights into pathophysiological mechanisms of nephrology

Kidney diseases (KD), a major public health problem that affects about 10 % of the general population, manifest in progressive loss of renal function, which ultimately leads to complete kidney failure. However, current approaches based on renal histopathological results and clinical parameters lack sensitivity and are not sufficient to characterize the category and progression of nephrology or to predict nephrology progression risk reliably or to guide preventive interventions. The high incidence and financial burden of KD make it imperative to diagnose KD at early stages when therapeutic interventions are far more effective. Nowadays, the appearance of metabolomics (the high-throughput measurement and analysis of metabolites) has provided the framework for a comprehensive analysis of KD and serves as a starting point for generating novel molecular diagnostic tools for use in nephrology. Changes in the concentration profiles of a number of small-molecule metabolites found in either blood or urine can be used to localize kidney damage or assess kidneys suffering from injury. The power of metabolomics allows unparalleled opportunity to query the molecular mechanisms of KD. Novel metabolomics technologies have the ability to provide a deeper understanding of the disease beyond classical histopathology, redefine the characteristics of the disease state, and identify novel approaches to reduce renal failure. This review gives an overview of its application to important areas in clinical nephrology, with a particular focus on biomarker discovery. Great strides forward are being made in breaking down important barriers to the successful prevention and treatment of this devastating disorder.

Plasma metabolomic profiles in different stages of CKD

BACKGROUND AND OBJECTIVES

CKD is a common public health problem. Identifying biomarkers adds prognostic/diagnostic value by contributing to an understanding of CKD at the molecular level and possibly defining new drug targets. Metabolomics provides a snapshot of biochemical events at a particular time in the progression of CKD. This cross-sectional metabolomics study ascertained whether plasma metabolite profiles are significantly different in CKD stages 2, 3, and 4.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

An analysis of plasma metabolites, using gas and liquid chromatography coupled to mass spectrometry, was conducted on 30 nondiabetic men ages 40-52 years, with 10 participants each in CKD stages 2, 3, and 4 based on their estimated GFR (calculated by the Modified Diet in Renal Disease formula). Participants were recruited in late 2008, and plasma samples were tested at Metabolon Inc and analyzed in 2012.

RESULTS

Comparison of stage 3/stage 2 identified 62 metabolites that differed (P ≤ 0.05), with 39 higher and 23 lower in stage 3 compared with stage 2; comparisons of stage 4/stage 2 identified 111 metabolites, with 66 higher and 45 lower; and comparisons of stage 4/stage 3 identified 11 metabolites, with 7 higher and 4 lower. Major differences in metabolite profiles with increasing stage of CKD were observed, including altered arginine metabolism, elevated coagulation/inflammation, impaired carboxylate anion transport, and decreased adrenal steroid hormone production.

CONCLUSIONS

Global metabolite profiling of plasma uncovered potential biomarkers of stages of CKD. Moreover, these biomarkers provide insight into possible pathophysiologic processes that may contribute to progression of CKD.