An update of urine and blood metabolomics in chronic kidney disease

Optimization and validation of metabolomics methods for feline urine and serum towards application in veterinary medicine

BACKGROUND

Metabolomics is an emerging and powerful technology that offers a comprehensive view of an organism's physiological status. Although widely applied in human medicine, it is only recently making its introduction in veterinary medicine. As a result, validated metabolomics protocols in feline medicine are lacking at the moment. Since biological interpretation of metabolomics data can be misled by the extraction method used, species and matrix-specific optimized and validated metabolomic protocols are sorely needed.

RESULTS

Systematic optimization was performed using fractional factorial experiments for both serum (n = 57) and urine (n = 24), evaluating dilution for both matrices, and aliquot and solvent volume, protein precipitation time and temperature for serum. For the targeted (n = 76) and untargeted (n = 1949) validation of serum respectively, excellent instrumental, intra-assay and inter-day precision were observed (CV ≤ 15% or 30%, respectively). Linearity deemed sufficient both targeted and untargeted (R2 ≥ 0.99 or 0.90, respectively). An appropriate targeted recovery between 70 and 130% was achieved. For the targeted (n = 69) and untargeted (n = 2348) validation of the urinary protocol, excellent instrumental and intra-assay precision were obtained (CV ≤ 15% or 30%, respectively). Subsequently, the discriminative ability of our metabolomics methods was confirmed for feline chronic kidney disease (CKD) by univariate statistics (n = 41 significant metabolites for serum, and n = 55 for urine, p-value<0.05) and validated OPLS-DA models (R2(Y) > 0.95, Q2(Y) > 0.65, p-value<0.001 for both matrices).

SIGNIFICANCE

This study is the first to present an optimized and validated wholistic metabolomics methods for feline serum and urine using ultra-high performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry. This robust methodology opens avenues for biomarker panel selection and a deeper understanding of feline CKD pathophysiology and other feline applications.

Investigating gut microbiota-blood and urine metabolite correlations in early sepsis-induced acute kidney injury: insights from targeted KEGG analyses

Background

The interplay between gut microbiota and metabolites in the early stages of sepsis-induced acute kidney injury (SA-AKI) is not yet clearly understood. This study explores the characteristics and interactions of gut microbiota, and blood and urinary metabolites in patients with SA-AKI.

Methods

Utilizing a prospective observational approach, we conducted comparative analyses of gut microbiota and metabolites via metabolomics and metagenomics in individuals diagnosed with SA-AKI compared to those without AKI (NCT06197828). Pearson correlations were used to identify associations between microbiota, metabolites, and clinical indicators. The Comprehensive Antibiotic Resistance Database was employed to detect antibiotic resistance genes (ARGs), while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways informed on metabolic processes and microbial resistance patterns.

Results

Our study included analysis of four patients with SA-AKI and five without AKI. Significant disparities in bacterial composition were observed, illustrated by diversity indices (Shannon index: 2.0 ± 0.4 vs. 1.4 ± 0.6, P = 0.230; Simpson index: 0.8 ± 0.1 vs. 0.6 ± 0.2, P = 0.494) between the SA-AKI group and the non-AKI group. N6, N6, N6-Trimethyl-L-lysine was detected in both blood and urine metabolites, and also showed significant correlations with specific gut microbiota (Campylobacter hominis and Bacteroides caccae, R > 0, P < 0.05). Both blood and urine metabolites were enriched in the lysine degradation pathway. We also identified the citrate cycle (TCA cycle) as a KEGG pathway enriched in sets of differentially expressed ARGs in the gut microbiota, which exhibits an association with lysine degradation.

Conclusions

Significant differences in gut microbiota and metabolites were observed between the SA-AKI and non-AKI groups, uncovering potential biomarkers and metabolic changes linked to SA-AKI. The lysine degradation pathway may serve as a crucial link connecting gut microbiota and metabolites.

Associations of Urine and Plasma Metabolites With Kidney Failure and Death in a Chronic Kidney Disease Cohort

RATIONALE & OBJECTIVE

Biomarkers that enable better identification of persons with chronic kidney disease (CKD) who are at higher risk for disease progression and adverse events are needed. This study sought to identify urine and plasma metabolites associated with progression of kidney disease.

STUDY DESIGN

Prospective metabolome-wide association study.

SETTING & PARTICIPANTS

Persons with CKD enrolled in the GCKD (German CKD) study with metabolite measurements, with external validation within the ARIC (Atherosclerosis Risk in Communities) Study.

EXPOSURES

1,513 urine and 1,416 plasma metabolites (Metabolon Inc) measured at study entry using untargeted mass spectrometry.

OUTCOMES

Main end points were kidney failure (KF) and a composite kidney end point (CKE) of KF, estimated glomerular filtration rate<15mL/min/1.73m2, or a 40% decrease in estimated glomerular filtration rate. Death from any cause was a secondary end point. After a median of 6.5 years of follow-up, 500 persons had experienced KF, 1,083 had experienced the CKE, and 680 had died.

ANALYTICAL APPROACH

Time-to-event analyses using multivariable proportional hazard regression models in a discovery-replication design with external validation.

RESULTS

5,088 GCKD study participants were included in analyses of urine metabolites, and 5,144 were included in analyses of plasma metabolites. Among 182 unique metabolites, 30 were significantly associated with KF, 49 with the CKE, and 163 with death. The strongest association with KF was observed for plasma hydroxyasparagine (HR, 1.95; 95% CI, 1.68-2.25). An unnamed metabolite measured in plasma and urine was significantly associated with KF, the CKE, and death. External validation of the identified associations of metabolites with KF or the CKE revealed directional consistency for 88% of observed associations. Selected associations of 18 metabolites with study outcomes have not been previously reported.

LIMITATIONS

Use of observational data and semiquantitative metabolite measurements at a single time point.

CONCLUSIONS

The observed associations between metabolites and KF, the CKE, or death in persons with CKD confirmed previously reported findings and also revealed several associations not previously described. These findings warrant confirmatory research in other study cohorts.

PLAIN-LANGUAGE SUMMARY

Incomplete understanding of the variability of chronic kidney disease (CKD) progression motivated the search for new biomarkers that would help identify people at increased risk. We explored metabolites in plasma and urine for their association with unfavorable kidney outcomes or death in persons with CKD. Metabolomic analyses revealed 182 metabolites significantly associated with CKD progression or death. Many of these associations confirmed previously reported findings or were validated by analysis in an external study population. Our comprehensive screen of the metabolome serves as a valuable foundation for future investigations into biomarkers associated with CKD progression.

Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations

Circulating metabolite levels may reflect the state of the human organism in health and disease, however, the genetic architecture of metabolites is not fully understood. We have performed a whole-genome sequencing association analysis of both common and rare variants in up to 11,840 multi-ethnic participants from five studies with up to 1666 circulating metabolites. We have discovered 1985 novel variant-metabolite associations, and validated 761 locus-metabolite associations reported previously. Seventy-nine novel variant-metabolite associations have been replicated, including three genetic loci located on the X chromosome that have demonstrated its involvement in metabolic regulation. Gene-based analysis have provided further support for seven metabolite-replicated loci pairs and their biologically plausible genes. Among those novel replicated variant-metabolite pairs, follow-up analyses have revealed that 26 metabolites have colocalized with 21 tissues, seven metabolite-disease outcome associations have been putatively causal, and 7 metabolites might be regulated by plasma protein levels. Our results have depicted the genetic contribution to circulating metabolite levels, providing additional insights into understanding human disease.

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.

The Geroprotective Drug Candidate CMS121 Alleviates Diabetes, Liver Inflammation, and Renal Damage in db/db Leptin Receptor Deficient Mice

db/db mice, which lack leptin receptors and exhibit hyperphagia, show disturbances in energy metabolism and are a model of obesity and type 2 diabetes. The geroneuroprotector drug candidate CMS121 has been shown to be effective in animal models of Alzheimer's disease and aging through the modulation of metabolism. Thus, the hypothesis was that CMS121 could protect db/db mice from metabolic defects and thereby reduce liver inflammation and kidney damage. The mice were treated with CMS121 in their diet for 6 months. No changes were observed in food and oxygen consumption, body mass, or locomotor activity compared to control db/db mice, but a 5% reduction in body weight was noted. Improved glucose tolerance and reduced HbA1c and insulin levels were also seen. Blood and liver triglycerides and free fatty acids decreased. Improved metabolism was supported by lower levels of fatty acid metabolites in the urine. Markers of liver inflammation, including NF-κB, IL-18, caspase 3, and C reactive protein, were lowered by the CMS121 treatment. Urine markers of kidney damage were improved, as evidenced by lower urinary levels of NGAL, clusterin, and albumin. Urine metabolomics studies provided further evidence for kidney protection. Mitochondrial protein markers were elevated in db/db mice, but CMS121 restored the renal levels of NDUFB8, UQCRC2, and VDAC. Overall, long-term CMS121 treatment alleviated metabolic imbalances, liver inflammation, and reduced markers of kidney damage. Thus, this study provides promising evidence for the potential therapeutic use of CMS121 in treating metabolic disorders.

Biomarker identification and pathway analysis of Astragalus membranaceus and Curcuma zedoaria couplet medicines on adenine-induced chronic kidney disease in rats based on metabolomics

Background: Chronic kidney disease (CKD) is usually insidious, and most affected individuals are asymptomatic until the disease becomes advanced. The effective treatment of CKD would rely on the incorporation of multidisciplinary approaches. Astragalus membranaceus (AM) and Curcuma zedoaria (CZ) have been widely used in the treatment of CKD. However, the mechanism of AM and CZ in the treatment of CKD is still unclear.

Methods: This study was designed to evaluate the effects of AM and CZ on adenine-induced rats and to investigate the underlying mechanism by using metabolomic analysis. Addition of 0.75% adenine to the diet of rats for 3 weeks induced the animal model of CKD. The rats in the treatment group were treated with AM and CZ (2.1 g/kg/day) for 4 weeks. Blood and kidney samples were collected for biochemical and histological examination. Ultra-high-performance liquid chromatography/Q Exactive HFX mass spectrometer (UHPLC-QE-MS) was applied to analyze metabolic profiling variations in the kidney.

Results: The results showed that AM and CZ could significantly reduce serum creatinine (Scr) and blood urea nitrogen (BUN) levels in CKD rats and alleviate renal pathological injury. By comparing the endogenous components of the normal group and the model group in positive ion mode and negative ion mode, a total of 365 and 155 different metabolites were screened, respectively. A total of 117 and 73 metabolites with significantly different expressions were identified between model group and AM and CZ group in positive ion mode and negative ion mode, respectively. The pivotal pathways affected by AM and CZ included nicotinate and nicotinamide metabolism, and glycine, serine and threonine metabolism. Furthermore, significant changes in metabolites in CKD rats after AM and CZ therapies were observed, including L-Threonine, D-pantothenic acid, and nicotinamide. Moreover, we found that AM and CZ significantly reduced renal fibrosis and inflammation in CKD rats, which may be related to the regulation of SIRT1/JNK signaling pathway.

Conclusion: In conclusion, AM and CZ significantly reduced renal fibrosis and inflammation in CKD rats, which may be related to the regulation of SIRT1/JNK signaling pathway. Furthermore, L-Threonine, D-pantothenic acid, and nicotinamide may be potential biomarkers for the progression and treatment of CKD.

Urine metabolites for preoperative prediction of acute kidney injury after coronary artery bypass graft surgery

OBJECTIVE

Acute kidney injury is a common complication after on-pump coronary artery bypass grafting. Prediction of acute kidney injury remains a challenge. Our study aims to identify a panel of urine metabolites for preoperative warning of acute kidney injury after on-pump coronary artery bypass grafting.

METHODS

A total of 159 patients undergoing isolated on-pump coronary artery bypass grafting were enrolled from July 7, 2017, to May 17, 2019. Preoperative urine samples were analyzed with the approach of liquid chromatography-mass spectrometry-based urine metabolomics. The study end point was the episode of acute kidney injury within 48 hours postoperatively. The predictive performance was determined by the area under the curve and calibration curve. The results were validated using bootstrap resampling.

RESULTS

The acute kidney injury (n = 55) and nonacute kidney injury (n = 104) groups showed significant different metabolic profiling. A total of 28 metabolites showed significant differences between the acute kidney injury and nonacute kidney injury groups. A metabolite panel of 5 metabolites (tyrosyl-gamma-glutamate, deoxycholic acid glycine conjugate, 5-acetylamino-6-amino-3-methyluracil, arginyl-arginine, and L-methionine) was discovered to have a good predicting performance (area under the curve, 0.89; 95% confidence interval, 0.82-0.93), which is higher than the clinical factor-based model (area under the curve, 0.63; 95% confidence interval, 0.53-0.72). Internal validation by bootstrap resampling showed an adjusted area under the curve of 0.88, and the calibration curve demonstrated good agreement between prediction and observation in the probability of postoperative acute kidney injury. Decision curve analysis revealed a superior net benefit of the metabolite model over the traditional clinical factor-based model.

CONCLUSIONS

We present 5 urine metabolites related to acute kidney injury after coronary artery bypass grafting. This metabolite model may serve as a preoperative warning of acute kidney injury after on-pump coronary artery bypass grafting.

Nuclear Magnetic Resonance-Based Metabolomics Approach Revealed the Intervention Effect of Using Complementary and Alternative Medicine (CAM) by CKD Patients

Chronic kidney disease (CKD) is the end point of a number of systemic chronic diseases. The prevalence of CKD is increasing worldwide and recent epidemiological studies are showing the high prevalence of renal failure in CKD patients using complementary and alternative medicines (CAMs). Clinicians believe that biochemical profiles of CKD patients using CAM (referred here to as CAM-CKD) may be different compared to those on standard clinical treatment and should be managed differently. The present study aims to explore the potential of the NMR-based metabolomics approach to reveal the serum metabolic disparity between CKD and CAM-CKD patients with respect to normal control (NC) subjects and if the differential metabolic patterns can provide rationale for the efficacy and safety of standard and/or alternative therapies. Serum samples were obtained from 30 CKD patients, 43 CAM-CKD patients, and 47 NC subjects. The quantitative serum metabolic profiles were measured using 1D 1H CPMG NMR experiments performed at 800 MHz NMR spectrometer. The serum metabolic profiles were compared using various multivariate statistical analysis tools available on MetaboAnalyst (freely available web-based software) such as partial least-squares discriminant analysis (PLS-DA) and random forest (a machine learning) classification method. The discriminatory metabolites were identified based on variable importance in projection (VIP) statistics and further evaluated for statistical significance (i.e., p < 0.05) using either Student t-test or ANOVA statistics. PLS-DA models were capable of clustering CKD and CAM-CKD with considerably high values of Q 2 and R 2. Compared to CAM-CKD patients, the sera of CKD patients were characterized by (a) elevated levels of urea, creatinine, citrate, glucose, glycerol, and phenylalanine and phenylalanine-to-tyrosine ratio (PTR) and (b) decreased levels of various amino acids (such leucine, isoleucine, valine, and alanine), high-density lipoproteins, lactate, and acetate. These changes suggested that CKD patients manifest severe oxidative stress, hyperglycemia (with dampened glycolysis), increased protein energy wasting, and reduced lipid/membrane metabolism. Statistically significant and strong positive correlation of PTR with serum creatinine levels suggested the role of oxidative stress in the progression of kidney disease. Significant differences in metabolic patterns between CKD and CAM-CKD patients were observed. With respect to NC subjects, the serum metabolic changes were more aberrant in CKD patients compared to CAM-CKD patients. The aberrant metabolic changes in CKD patients with manifestations of higher oxidative stress compared to CAM-CKD patients could explain clinical discrepancies between CKD and CAM-CKD patients and further advocate the use of different treatment strategies for CKD and CAM-CKD patients.

The metabolomic differential plasma profile between dialysates. Pursuing to understand the mechanisms of citrate dialysate clinical benefits

Background: Currently, bicarbonate-based dialysate needs a buffer to prevent precipitation of bicarbonate salts with the bivalent cations, and acetate at 3-4 mmol/L is the most used. However, citrate is being postulated as a preferred option because of its association with better clinical results by poorly understood mechanisms. In that sense, this hypothesis-generating study aims to identify potential metabolites that could biologically explain these improvements found in patients using citrate dialysate. Methods: A unicentric, cross-over, prospective untargeted metabolomics study was designed to analyze the differences between two dialysates only differing in their buffer, one containing 4 mmol/L of acetate (AD) and the other 1 mmol/L of citrate (CD). Blood samples were collected in four moments (i.e., pre-, mid-, post-, and 30-min-post-dialysis) and analyzed in an untargeted metabolomics approach based on UPLC-Q-ToF mass spectrometry. Results: The 31 most discriminant metabolomic variables from the plasma samples of the 21 participants screened by their potential clinical implications show that, after dialysis with CD, some uremic toxins appear to be better cleared, the lysine degradation pathway is affected, and branched-chain amino acids post-dialysis levels are 9-10 times higher than with AD; and, on its part, dialysis with AD affects acylcarnitine clearance. Conclusion: Although most metabolic changes seen in this study could be attributable to the dialysis treatment itself, this study successfully identifies some metabolic variables that differ between CD and AD, which raise new hypotheses that may unveil the mechanisms involved in the clinical improvements observed with citrate in future research.

Impact of Acetate versus Citrate Dialysates on Intermediary Metabolism-A Targeted Metabolomics Approach

Acetate is widely used as a dialysate buffer to avoid the precipitation of bicarbonate salts. However, even at low concentrations that wouldn’t surpass the metabolic capacity of the Krebs tricarboxylic acid (TCA) cycle, other metabolic routes are activated, leading to undesirable clinical consequences by poorly understood mechanisms. This study aims to add information that could biologically explain the clinical improvements found in patients using citrate dialysate. A unicentric, cross-over, prospective targeted metabolomics study was designed to analyze the differences between two dialysates, one containing 4 mmol/L of acetate (AD) and the other 1 mmol/L of citrate (CD). Fifteen metabolites were studied to investigate changes induced in the TCA cycle, glycolysis, anaerobic metabolism, ketone bodies, and triglyceride and aminoacidic metabolism. Twenty-one patients completed the study. Citrate increased during the dialysis sessions when CD was used, without surpassing normal values. Other differences found in the next TCA cycle steps showed an increased substrate accumulation when using AD. While lactate decreased, pyruvate remained stable, and ketogenesis was boosted during dialysis. Acetylcarnitine and myo-inositol were reduced during dialysis, while glycerol remained constant. Lastly, glutamate and glutarate decreased due to the inhibition of amino acidic degradation. This study raises new hypotheses that need further investigation to understand better the biochemical processes that dialysis and the different dialysate buffers induce in the patient’s metabolism.

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.

Proteomic and metabolomic profiling of urine uncovers immune responses in patients with COVID-19

The utility of the urinary proteome in infectious diseases remains unclear. Here, we analyzed the proteome and metabolome of urine and serum samples from patients with COVID-19 and healthy controls. Our data show that urinary proteins effectively classify COVID-19 by severity. We detect 197 cytokines and their receptors in urine, but only 124 in serum using TMT-based proteomics. The decrease in urinary ESCRT complex proteins correlates with active SARS-CoV-2 replication. The downregulation of urinary CXCL14 in severe COVID-19 cases positively correlates with blood lymphocyte counts. Integrative multiomics analysis suggests that innate immune activation and inflammation triggered renal injuries in patients with COVID-19. COVID-19-associated modulation of the urinary proteome offers unique insights into the pathogenesis of this disease. This study demonstrates the added value of including the urinary proteome in a suite of multiomics analytes in evaluating the immune pathobiology and clinical course of COVID-19 and, potentially, other infectious diseases.

Advances in the Progression and Prognosis Biomarkers of Chronic Kidney Disease

Chronic kidney disease (CKD) is one of the increasingly serious public health concerns worldwide; the global burden of CKD is increasingly due to high morbidity and mortality. At present, there are three key problems in the clinical treatment and management of CKD. First, the current diagnostic indicators, such as proteinuria and serum creatinine, are greatly interfered by the physiological conditions of patients, and the changes in the indicator level are not synchronized with renal damage. Second, the established diagnosis of suspected CKD still depends on biopsy, which is not suitable for contraindication patients, is also traumatic, and is not sensitive to early progression. Finally, the prognosis of CKD is affected by many factors; hence, it is ineviatble to develop effective biomarkers to predict CKD prognosis and improve the prognosis through early intervention. Accurate progression monitoring and prognosis improvement of CKD are extremely significant for improving the clinical treatment and management of CKD and reducing the social burden. Therefore, biomarkers reported in recent years, which could play important roles in accurate progression monitoring and prognosis improvement of CKD, were concluded and highlighted in this review article that aims to provide a reference for both the construction of CKD precision therapy system and the pharmaceutical research and development.

Alterations in Glycerolipid and Fatty Acid Metabolic Pathways in Alzheimer's Disease Identified by Urinary Metabolic Profiling: A Pilot Study

An easily accessible and non-invasive biomarker for the early detection of Alzheimer's disease (AD) is needed. Evidence suggests that metabolic dysfunction underlies the pathophysiology of AD. While urine is a non-invasively collectable biofluid and a good source for metabolomics analysis, it is not yet widely used for this purpose. This small-scale pilot study aimed to examine whether the metabolic profile of urine from AD patients reflects the metabolic dysfunction reported to underlie AD pathology, and to identify metabolites that could distinguish AD patients from cognitively healthy controls. Spot urine of 18 AD patients (AD group) and 18 age- and sex-matched, cognitively normal controls (control group) were analyzed by mass spectrometry (MS). Capillary electrophoresis time-of-flight MS and liquid chromatography–Fourier transform MS were used to cover a larger range of molecules with ionic as well as lipid characteristics. A total of 304 ionic molecules and 81 lipid compounds of 12 lipid classes were identified. Of these, 26 molecules showed significantly different relative concentrations between the AD and control groups (Wilcoxon's rank-sum test). Moreover, orthogonal partial least-squares discriminant analysis revealed significant discrimination between the two groups. Pathway searches using the KEGG database, and pathway enrichment and topology analysis using Metaboanalyst software, suggested alterations in molecules relevant to pathways of glycerolipid and glycerophospholipid metabolism, thermogenesis, and caffeine metabolism in AD patients. Further studies of urinary metabolites will contribute to the early detection of AD and understanding of its pathogenesis.

Metabolites Associated with Coffee Consumption and Incident Chronic Kidney Disease

BACKGROUND AND OBJECTIVES

Moderate coffee consumption has been associated with lower risk of CKD; however, the exact biologic mechanisms underlying this association are unknown. Metabolomic profiling may identify metabolic pathways that explain the association between coffee and CKD. The goal of this study was to identify serum metabolites associated with coffee consumption and examine the association between these coffee-associated metabolites and incident CKD.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Using multivariable linear regression, we identified coffee-associated metabolites among 372 serum metabolites available in two subsamples of the Atherosclerosis Risk in Communities study (ARIC; n=3811). Fixed effects meta-analysis was used to pool the results from the two ARIC study subsamples. Associations between coffee and metabolites were replicated in the Bogalusa Heart Study (n=1043). Metabolites with significant associations with coffee in both cohorts were then evaluated for their prospective associations with incident CKD in the ARIC study using Cox proportional hazards regression.

RESULTS

In the ARIC study, mean (SD) age was 54 (6) years, 56% were daily coffee drinkers, and 32% drank >2 cups per day. In the Bogalusa Heart Study, mean (SD) age was 48 (5) years, 57% were daily coffee drinkers, and 38% drank >2 cups per day. In a meta-analysis of two subsamples of the ARIC study, 41 metabolites were associated with coffee consumption, of which 20 metabolites replicated in the Bogalusa Heart Study. Three of these 20 coffee-associated metabolites were associated with incident CKD in the ARIC study.

CONCLUSIONS

We detected 20 unique serum metabolites associated with coffee consumption in both the ARIC study and the Bogalusa Heart Study, and three of these 20 candidate biomarkers of coffee consumption were associated with incident CKD. One metabolite (glycochenodeoxycholate), a lipid involved in primary bile acid metabolism, may contribute to the favorable kidney health outcomes associated with coffee consumption. Two metabolites (O-methylcatechol sulfate and 3-methyl catechol sulfate), both of which are xenobiotics involved in benzoate metabolism, may represent potential harmful aspects of coffee on kidney health.

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

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

The synergic renoprotective effect of Rehmanniae Radix Preparata and Corni Fructus on adenine-induced chronic kidney disease rats based on integrated plasma metabolomics and network pharmacology approach

AIMS

Rehmanniae Radix Preparata (RR) and Corni Fructus (CF) are commonly used together for the treatment of chronic kidney disease (CKD) in the clinical practices for thousands of years. However, little information on their synergy mechanism is available.

MAIN METHODS

In this study, an integrated approach combining ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS)-based metabonomics and network pharmacology was adopted to elucidate the cooperation mechanism of RR and CF on the amelioration of CKD. Furthermore, the targets from network pharmacology and metabolism pathways were jointly analyzed. Finally, the activities of key metabolic enzymes were experimentally validated by ELISA.

KEY FINDINGS

Metabolic profiling indicated that the metabolic disturbance in plasma was markedly alleviated after treatment. Nine putative biomarkers mainly involving in phenylalanine, tyrosine and tryptophan biosynthesis and tyrosine metabolism were identified. Moreover, the compound-target-pathway network of RR and CF for CKD treatment was constructed by network pharmacology, which was related to tyrosine metabolism and arginine and proline metabolism. The results were partly consistent with the findings of plasma metabolomics.

SIGNIFICANCE

In conclusion, this study solidly supported and enhanced current understanding of the synergy effects of RR and CF on CKD. Meanwhile, it also confirmed the feasibility of combining metabolomics and network pharmacology to identify active components and elucidate the pharmacological effects of traditional Chinese medicines (TCMs).

Fecal Metabolomics Reveals Distinct Profiles of Kidney Transplant Recipients and Healthy Controls

Monitoring graft recipients remains dependent on traditional biomarkers and old technologies lacking specificity, sensitivity, or accuracy. Recently, metabolomics is becoming a promising approach that may offer to kidney transplants a more effective and specific monitoring. Furthermore, emerging evidence suggested a fundamental role of gut microbiota as an important determinant of patients’ metabolomes. In the current study, we enrolled forty stable renal allografts recipients compared to twenty healthy individuals. Samples were taken at different time points from patient to patient following transplantation surgery, which varied from 3 months to 22 years post-graft. All patients started the immunosuppression therapy immediately following kidney graft (Day 0). Gas chromatography–mass spectrometry (GC–MS) was employed to perform untargeted analysis of fecal metabolites. Globally, the fecal metabolic signature was significantly different between kidney transplants and the control group. Fecal metabolome was dominated by lipids (sterols and fatty acids) in the stable transplant group compared to the controls (p < 0.05). Overall, 18 metabolites were significantly altered within kidney transplant recipients. Furthermore, the most notable altered metabolic pathways in kidney transplants include ubiquinone and other terpenoid-quinone biosynthesis, tyrosine metabolism, tryptophan biosynthesis, and primary bile acid biosynthesis. Fecal metabolites could effectively distinguish stable transplant recipients from controls, supporting the potential utility of metabolomics in rapid and non-invasive diagnosis to produce relevant biomarkers and to help clinicians in monitoring kidney transplants. Further investigations are needed to clarify the physiological relevance of fecal metabolome and to assess the impact of microbiota modulation.

Asymmetric dimethylarginine compartmental behavior during high-flux hemodialysis

AIM

The accumulation of uremic toxins, such as asymmetric dimethylarginine (ADMA), has emerged as one of the major cardiovascular disease-related risk factors in patients with end-stage renal disease (ESRD). Based on the low molecular weight of ADMA, hemodialysis (HD) should theoretically effectively remove ADMA. In this study, we investigated the clearance behavior of ADMA during high-flux HD.

METHODS

Eight HD patients without residual renal function were included. Blood samples were collected at 0, 30, 60, 120 and 240 min after dialysis started, as well as 1 h and 48 h after dialysis. ADMA level was detected by HPLC-MS/MS. Herein, the ADMA level in blood cells and the ADMA protein binding rate were measured. Accordingly, the dialyzer extraction ratio was also determined.

RESULTS

The reduction ratio (RR) of ADMA (corrected for hemoconcentration) was significantly lower, at only 37.21 ± 6.44%, than that of urea and creatinine (p < .05). Interestingly, its clearance from plasma was precipitous early in dialysis and became slowly from 60 to 240 min. Additionally, a greater inlet erythrocyte than plasma concentration was found for ADMA. The dialyzer extraction ratio was comparable between ADMA and creatinine or urea (83 ± 5% for ADMA vs. 84 ± 3% and 88 ± 2% for creatinine and urea, respectively; both p>.05). Urea and creatinine had a slight rebound ratio of less than 10% at 1 h after the completion of HD. In contrast, considerable rebound of approximately 30% was detected in ADMA.

CONCLUSION

This study suggests that ADMA may present a multicompartmental distribution that cannot be representatively reflected by the urea kinetics model.

Prognostic value of endogenous and exogenous metabolites in liver transplantation

Liver transplantation has been widely accepted as an effective intervention for end-stage liver diseases and early hepatocellular carcinomas. However, a variety of postoperative complications and adverse reactions have baffled medical staff and patients. Currently, transplantation monitoring relies primarily on nonspecific biochemical tests, whereas diagnosis of multiple complications depends on invasive pathological examination. Therefore, a noninvasive monitoring method with high selectivity and specificity is desperately needed. This review summarized the potential of endogenous small-molecule metabolites as biomarkers for assessing graft function, ischemia-reperfusion injury and liver rejection. Exogenous metabolites, mainly those immunosuppressive agents with high intra- and inter-individual variability, were also discussed for transplantation monitoring.