Amino Acid Metabolites Associated with Chronic Kidney Disease: An Eight-Year Follow-Up Korean Epidemiology Study

Peripheral Kynurenine Pathway Metabolites in Patients with Psoriasis

Psoriasis is a systemic disease affecting 2-3% of the general population. Tryptophan (TRP) is an amino acid metabolized in the kynurenine pathway (KP). The aim of this study was to assess the kynurenine pathway's metabolites in serum and urine of psoriatic patients and explore the possible interplay with the disease's pathogenesis and its comorbidities. The study involved 60 patients with plaque psoriasis and 30 healthy volunteers matched for gender, age, and BMI. Serum and urine samples were taken from the participants and tested for TRP, indoleamine 2,3-dioxygenase (IDO), 2,3-tryptophan dioxygenase (TDO), kynurenine (KYN), kynurenic acid (KYNA), quinolinic acid (QUIN), and numerous laboratory parameters. Correlations between the metabolites' levels and clinical, laboratory parameters and depression occurrence were statistically evaluated. Concentrations of tryptophan, kynurenic acid, and quinolinic acid in serum and urine were significantly higher among patients with psoriasis (p < 0.05 and p < 0.001, p < 0.05 and p < 0.05 and p < 0.001 and p < 0.001, respectively). A significant stimulation of the kynurenine pathway in serum and urine of patients with psoriasis suggests its role in its pathogenesis and interplay between chronic inflammation or comorbidities. Further research is needed to discover whether the increase in KP metabolites is an indicator of inflammation or a compensatory mechanism in psoriasis.

Targeted Analysis of Serum and Urinary Metabolites for Early Chronic Kidney Disease

Chronic kidney disease (CKD) has become one of the most rapidly advancing diseases of the century, contributing significantly to increased mortality and morbidity. Metabolomics presents a promising approach to understanding CKD pathogenesis and identifying novel biomarkers for early diagnosis. This study evaluated serum and urine metabolomic profiles in CKD patients with declining glomerular filtration rates (eGFR). Using targeted metabolomics, we quantified seven potential metabolites in blood and urine samples from 20 healthy individuals and 99 CKD patients staged by eGFR according to the KDIGO guidelines. The analysis was conducted using ultra-high performance liquid chromatography combined with electrospray ionization quadrupole time-of-flight mass spectrometry. The metabolites investigated included L-phenylalanine, L-methionine, arginine, indoxyl sulfate, kynurenic acid, and L-acetylcarnitine. Quantitative assessments were performed using pure standards and validated through methods such as the limit of detection (LOD) and limit of quantification (LOQ). The findings identified potential biomarkers for early CKD diagnosis: in serum, L-phenylalanine, L-methionine, arginine, kynurenic acid, and indoxyl sulfate, while L-acetylcarnitine was significant in urine. These biomarkers could provide valuable insights into CKD progression and support in developing more effective diagnostic tools for early intervention.

Targeted metabolomics identified novel metabolites, predominantly phosphatidylcholines and docosahexaenoic acid-containing lipids, predictive of incident chronic kidney disease in middle-to-elderly-aged Chinese adults

BACKGROUND

Evidence is limited regarding the association of circulating metabolites with decline of kidney function, letting alone their value in prediction of development of chronic kidney disease (CKD).

METHODS

This study included 3802 participants aged 64.1 ± 7.4 years from the Dongfeng-Tongji cohort, among whom 3327 were CKD-free at baseline (estimated glomerular filtration rate [eGFR] > 60 ml/min per 1.73 m2). We measured baseline levels of 211 metabolites with liquid chromatography coupled with mass spectrometry, including 25 amino acids, 12 acyl-carnitines, 161 lipids, and 13 other metabolites.

RESULTS

The mean (SD) absolute annual change in eGFR was -0.14 ± 4.11 ml/min per 1.73 m2 per year, and a total of 472 participants who were free of CKD at baseline developed incident CKD during follow-up of 4.6 ± 0.2 years (14.2 %). We identified a total of 22 metabolites associated with annual eGFR change and survived Bonferroni correction for multiple testing, including seven metabolites associated with eGFR increase (six being docosahexaenoic acid [DHA]-containing lipids) and 15 associated with eGFR decline (nine being phosphatidylcholines [PCs]). Among them, eight metabolites obtained non-zero coefficients in least absolute shrinkage and selection operator (LASSO) regression on incident CKD, indicating predictive potential, including one amino acid (arginine), one acyl-carnitine (C2), one lysophosphatidylcholine (LPC 22:6), two PCs (32:1 and 34:3), one triacylglycerol (TAG 56:8 [22:6]) and two other metabolites (inosine, niacinamide), and the composite score of these eight metabolites showed an odds ratio (OR) of 8.79 (95 % confidence interval [CI]: 7.49, 10.32; P < 0.001) per SD increase in association with incident CKD. The addition of the metabolite score increased the c-statistic of the reference model of traditional risk factors (including baseline eGFR) by 0.065 (95 % CI: 0.046 to 0.084; P = 3.39 × 10-11) to 0.765 (0.742 to 0.788) in 1000 repetitions of 10-fold cross-validation, while the application of two advanced machine learning algorithms, random forest (RF), and extreme gradient boosting (XGBoost) models produced similar c-statistics, to 0.753 (0.729 to 0.777) and 0.778 (0.733 to 0.824) with increases of 0.074 (0.055 to 0.093; P = 4.11 × 10-14) and 0.073 (0.032 to 0.114; P = 4.00 × 10-4), respectively.

CONCLUSIONS

In this study, we identified 22 metabolites associated with longitudinal eGFR change, nine of which were PCs and six were DHA-containing lipids. We screened out a panel of eight metabolites which improved prediction for the development of CKD by 9 % beyond traditional risk factors including baseline eGFR. Our findings highlighted involvement of lipid metabolism in kidney function impairment, and provided novel predictors for CKD risk.

Amino acid metabolism in kidney health and disease

Amino acids form peptides and proteins and are therefore considered the main building blocks of life. The kidney has an important but under-appreciated role in the synthesis, degradation, filtration, reabsorption and excretion of amino acids, acting to retain useful metabolites while excreting potentially harmful and waste products from amino acid metabolism. A complex network of kidney transporters and enzymes guides these processes and moderates the competing concentrations of various metabolites and amino acid products. Kidney amino acid metabolism contributes to gluconeogenesis, nitrogen clearance, acid-base metabolism and provision of fuel for tricarboxylic acid cycle and urea cycle intermediates, and is thus a central hub for homeostasis. Conversely, kidney disease affects the levels and metabolism of a variety of amino acids. Here, we review the metabolic role of the kidney in amino acid metabolism and describe how different diseases of the kidney lead to aberrations in amino acid metabolism. Improved understanding of the metabolic and communication routes that are affected by disease could provide new mechanistic insights into the pathogenesis of kidney diseases and potentially enable targeted dietary or pharmacological interventions.

Novel Metabolites Associated with Decreased GFR in Finnish Men: A 12-Year Follow-Up of the METSIM Cohort

Identification of the individuals having impaired kidney function is essential in preventing the complications of this disease. We measured 1009 metabolites at the baseline study in 10,159 Finnish men of the METSIM cohort and associated the metabolites with an estimated glomerular filtration rate (eGFR). A total of 7090 men participated in the 12-year follow-up study. Non-targeted metabolomics profiling was performed at Metabolon, Inc. (Morrisville, NC, USA) on EDTA plasma samples obtained after overnight fasting. We applied liquid chromatography mass spectrometry (LC-MS/MS) to identify the metabolites (the Metabolon DiscoveryHD4 platform). We performed association analyses between the eGFR and metabolites using linear regression adjusted for confounding factors. We found 108 metabolites significantly associated with a decrease in eGFR, and 28 of them were novel, including 12 amino acids, 8 xenobiotics, 5 lipids, 1 nucleotide, 1 peptide, and 1 partially characterized molecule. The most significant associations were with five amino acids, N-acetylmethionine, N-acetylvaline, gamma-carboxyglutamate, 3-methylglutaryl-carnitine, and pro-line. We identified 28 novel metabolites associated with decreased eGFR in the 12-year follow-up study of the METSIM cohort. These findings provide novel insights into the role of metabolites and metabolic pathways involved in the decline of kidney function.

Metabolic Crosstalk in Multimorbidity: Identifying Compensatory Effects Among Diabetes, Hypertension, and Dyslipidemia

Context

Metabolomics is becoming increasingly popular for detecting markers that indicate the presence of a specific disease. However, it is usually applied to studying individual ailments, yielding results that may not be directly relevant to people with multiple health conditions.

Objective

Our study proposes a different approach to explore metabolic crosstalk between various disease states.

Design Setting and Patients

We conducted a study on subjects at medium to high risk of developing coronary artery disease. We measured the plasma levels of 83 metabolites using nuclear magnetic resonance and analyzed the connections between these metabolites and various risk factors such as diabetes, hypertension, and dyslipidemia. Linear regression and multivariate analysis were combined for this purpose.

Results

Inspection of the metabolic maps created by our analysis helped us efficiently compare profiles. In this way, it was possible to discover opposing metabolic features among single conditions and their combination. Furthermore, we found compensating metabolic effects between diabetes, hypertension, and dyslipidemia involving mainly ketone body metabolism and fatty acid β-oxidation.

Conclusion

Our study introduces a novel approach to investigating how metabolism reacts to the simultaneous presence of multiple health conditions. This has allowed the detection of potential compensatory effects between diabetes, hypertension, and dyslipidemia, highlighting the complexity of metabolic crosstalk in patients with comorbidities. A better understanding of metabolic crosstalk like this could aid in developing focused treatments, resulting in improved therapeutic results.

Sex-Associated Metabolites and Incident Stroke, Incident Coronary Heart Disease, Hypertension, and Chronic Kidney Disease in the REGARDS Cohort

BACKGROUND

Sex disparities exist in cardiometabolic diseases. Metabolomic profiling offers insight into disease mechanisms, as the metabolome is influenced by environmental and genetic factors. We identified metabolites associated with sex and determined if sex-associated metabolites are associated with incident stoke, incident coronary heart disease, prevalent hypertension, and prevalent chronic kidney disease.

METHODS AND RESULTS

Targeted metabolomics was conducted for 357 metabolites in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) case-cohort substudy for incident stroke. Weighted logistic regression models were used to identify metabolites associated with sex in REGARDS. Sex-associated metabolites were replicated in the HyperGEN (Hypertension Genetic Epidemiology Network) and using the literature. Weighted Cox proportional hazard models were used to evaluate associations between metabolites and incident stroke. Cox proportional hazard models were used to evaluate associations between metabolites and incident coronary heart disease. Weighted logistic regression models were used to evaluate associations between metabolites and hypertension and chronic kidney disease. Fifty-one replicated metabolites were associated with sex. Higher levels of 6 phosphatidylethanolamines were associated with incident stroke. No metabolites were associated with incident coronary heart disease. Higher levels of uric acid and leucine and lower levels of a lysophosphatidylcholine were associated with hypertension. Higher levels of indole-3-lactic acid, 7 phosphatidylethanolamines, and uric acid, and lower levels of betaine and bilirubin were associated with chronic kidney disease.

CONCLUSIONS

These findings suggest that the sexual dimorphism of the metabolome may contribute to sex differences in stroke, hypertension, and chronic kidney disease.

Integrated longitudinal multiomics study identifies immune programs associated with acute COVID-19 severity and mortality

BACKGROUNDPatients hospitalized for COVID-19 exhibit diverse clinical outcomes, with outcomes for some individuals diverging over time even though their initial disease severity appears similar to that of other patients. A systematic evaluation of molecular and cellular profiles over the full disease course can link immune programs and their coordination with progression heterogeneity.METHODSWe performed deep immunophenotyping and conducted longitudinal multiomics modeling, integrating 10 assays for 1,152 Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) study participants and identifying several immune cascades that were significant drivers of differential clinical outcomes.RESULTSIncreasing disease severity was driven by a temporal pattern that began with the early upregulation of immunosuppressive metabolites and then elevated levels of inflammatory cytokines, signatures of coagulation, formation of neutrophil extracellular traps, and T cell functional dysregulation. A second immune cascade, predictive of 28-day mortality among critically ill patients, was characterized by reduced total plasma Igs and B cells and dysregulated IFN responsiveness. We demonstrated that the balance disruption between IFN-stimulated genes and IFN inhibitors is a crucial biomarker of COVID-19 mortality, potentially contributing to failure of viral clearance in patients with fatal illness.CONCLUSIONOur longitudinal multiomics profiling study revealed temporal coordination across diverse omics that potentially explain the disease progression, providing insights that can inform the targeted development of therapies for patients hospitalized with COVID-19, especially those who are critically ill.TRIAL REGISTRATIONClinicalTrials.gov NCT04378777.FUNDINGNIH (5R01AI135803-03, 5U19AI118608-04, 5U19AI128910-04, 4U19AI090023-11, 4U19AI118610-06, R01AI145835-01A1S1, 5U19AI062629-17, 5U19AI057229-17, 5U19AI125357-05, 5U19AI128913-03, 3U19AI077439-13, 5U54AI142766-03, 5R01AI104870-07, 3U19AI089992-09, 3U19AI128913-03, and 5T32DA018926-18); NIAID, NIH (3U19AI1289130, U19AI128913-04S1, and R01AI122220); and National Science Foundation (DMS2310836).

Exposome and Metabolome Analysis of Sugarcane Workers Reveals Predictors of Kidney Injury

Introduction

Sugarcane workers are exposed to potentially hazardous agrochemicals, including pesticides, heavy metals, and silica. Such occupational exposures present health risks and have been implicated in a high rate of kidney disease seen in these workers.

Methods

To investigate potential biomarkers and mechanisms that could explain chronic kidney disease (CKD) among this worker population, paired urine samples were collected from sugarcane cutters at the beginning and end of a harvest season in Guatemala. Workers were then separated into 2 groups, namely those with or without kidney function decline (KFD) across the harvest season. Urine samples from these 2 groups underwent elemental analysis and untargeted metabolomics.

Results

Urine profiles demonstrated increases in silicon, certain pesticides, and phosphorus levels in all workers, whereas heavy metals remained low. The KFD group had a reduction in estimated glomerular filtration rate (eGFR) across the harvest season; however, kidney injury marker 1 did not significantly change. Cross-harvest metabolomic analysis found trends of fatty acid accumulation, perturbed amino acid metabolism, presence of pesticides, and other known signs of impaired kidney function.

Conclusion

Silica and certain pesticides were significantly elevated in the urine of sugarcane workers with or without KFD. Future work should determine whether long-term occupational exposure to silica and pesticides across multiple seasons contributes to CKD in these workers. Overall, these results confirmed that multiple exposures are occurring in sugarcane workers and may provide insight into early warning signs of kidney injury and may help explain the increased incidence of CKD among agricultural workers.

Uncovering specific taxonomic and functional alteration of gut microbiota in chronic kidney disease through 16S rRNA data

Introduction

Chronic kidney disease (CKD) is worldwide healthcare burden with growing incidence and death rate. Emerging evidence demonstrated the compositional and functional differences of gut microbiota in patients with CKD. As such, gut microbial features can be developed as diagnostic biomarkers and potential therapeutic target for CKD.

Methods

To eliminate the outcome bias arising from factors such as geographical distribution, sequencing platform, and data analysis techniques, we conducted a comprehensive analysis of the microbial differences between patients with CKD and healthy individuals based on multiple samples worldwide. A total of 980 samples from six references across three nations were incorporated from the PubMed, Web of Science, and GMrepo databases. The obtained 16S rRNA microbiome data were subjected to DADA2 processing, QIIME2 and PICRUSt2 analyses.

Results

The gut microbiota of patients with CKD differs significantly from that of healthy controls (HC), with a substantial decrease in the microbial diversity among the CKD group. Moreover, a significantly reduced abundance of bacteria Faecalibacterium prausnitzii (F. prausnitzii) was detected in the CKD group through linear discriminant analysis effect size (LEfSe) analysis, which may be associated with the alleviating effects against CKD. Notably, we identified CKD-depleted F. prausnitzii demonstrated a significant negative correlation with three pathways based on predictive functional analysis, suggesting its potential role in regulating systemic acidbase disturbance and pro-oxidant metabolism.

Discussion

Our findings demonstrated notable alterations of gut microbiota in CKD patients. Specific gut-beneficial microbiota, especially F. prausnitzii, may be developed as a preventive and therapeutic tool for CKD clinical management.

A population-based urinary and plasma metabolomics study of environmental exposure to cadmium

BACKGROUND

The application of metabolomics-based profiles in environmental epidemiological studies is a promising approach to refine the process of health risk assessment. We aimed to identify potential metabolomics-based profiles in urine and plasma for the detection of relatively low-level cadmium (Cd) exposure in large population-based studies.

METHOD

We analyzed 123 urinary metabolites and 94 plasma metabolites detected in fasting urine and plasma samples collected from 1,412 men and 2,022 women involved in the Tsuruoka Metabolomics Cohort Study. Regression analysis was performed for urinary N-acetyl-beta-D-glucosaminidase (NAG), plasma, and urinary metabolites as dependent variables, and urinary Cd (U-Cd, quartile) as an independent variable. The multivariable regression model included age, gender, systolic blood pressure, smoking, rice intake, BMI, glycated hemoglobin, low-density lipoprotein cholesterol, alcohol consumption, physical activity, educational history, dietary energy intake, urinary Na/K ratio, and uric acid. Pathway-network analysis was carried out to visualize the metabolite networks linked to Cd exposure.

RESULT

Urinary NAG was positively associated with U-Cd, but not at lower concentrations (Q2). Among urinary metabolites in the total population, 45 metabolites showed associations with U-Cd in the unadjusted and adjusted models after adjusting for the multiplicity of comparison with FDR. There were 12 urinary metabolites which showed consistent associations between Cd exposure from Q2 to Q4. Among plasma metabolites, six cations and one anion were positively associated with U-Cd, whereas alanine, creatinine, and isoleucine were negatively associated with U-Cd. Our results were robust by statistical adjustment of various confounders. Pathway-network analysis revealed metabolites and upstream regulator changes associated with mitochondria (ACACB, UCP2, and metabolites related to the TCA cycle).

CONCLUSION

These results suggested that U-Cd was associated with metabolites related to upstream mitochondrial dysfunction in a dose-dependent manner. Our data will help develop environmental Cd exposure profiles for human populations.

Plasma Tryptophan-Kynurenine Pathway Metabolites and Risk for Progression to End-Stage Kidney Disease in Patients With Type 2 Diabetes

OBJECTIVE

We sought to study the associations between plasma metabolites in the tryptophan-kynurenine pathway and the risk of progression to end-stage kidney disease (ESKD) in patients with type 2 diabetes.

RESEARCH DESIGN AND METHODS

Plasma tryptophan, kynurenine, 3-hydroxykynurenine, kynurenic acid, and xanthurenic acid concentrations were measured in discovery (n = 1,915) and replication (n = 346) cohorts. External validation was performed in Chronic Renal Insufficiency Cohort (CRIC) participants with diabetes (n = 1,312). The primary outcome was a composite of incident ESKD (progression to estimated glomerular filtration rate [eGFR] <15 mL/min/1.73 m2, sustained dialysis, or renal death). The secondary outcome was annual eGFR decline.

RESULTS

In the discovery cohort, tryptophan was inversely associated with risk for ESKD, and kynurenine-to-tryptophan ratio (KTR) was positively associated with risk for ESKD after adjustment for clinical risk factors, including baseline eGFR and albuminuria (adjusted hazard ratios [HRs] 0.62 [95% CI 0.51, 0.75] and 1.48 [1.20, 1.84] per 1 SD). High levels of kynurenic acid and xanthurenic acid were associated with low risks of ESKD (0.74 [0.60, 0.91] and 0.74 [0.60, 0.91]). Consistently, high levels of tryptophan, kynurenic acid, and xanthurenic acid were independently associated with a slower eGFR decline, while a high KTR was predictive of a faster eGFR decline. Similar outcomes were obtained in the replication cohort. Furthermore, the inverse association between kynurenic acid and risk of ESKD was externally validated in CRIC participants with diabetes (adjusted HR 0.78 [0.65, 0.93]).

CONCLUSIONS

Accelerated catabolism of tryptophan in the kynurenine pathway may be involved in progressive loss of kidney function. However, shunting the kynurenine pathway toward the kynurenic acid branch may potentially slow renal progression.

Integrated longitudinal multi-omics study identifies immune programs associated with COVID-19 severity and mortality in 1152 hospitalized participants

Hospitalized COVID-19 patients exhibit diverse clinical outcomes, with some individuals diverging over time even though their initial disease severity appears similar. A systematic evaluation of molecular and cellular profiles over the full disease course can link immune programs and their coordination with progression heterogeneity. In this study, we carried out deep immunophenotyping and conducted longitudinal multi-omics modeling integrating ten distinct assays on a total of 1,152 IMPACC participants and identified several immune cascades that were significant drivers of differential clinical outcomes. Increasing disease severity was driven by a temporal pattern that began with the early upregulation of immunosuppressive metabolites and then elevated levels of inflammatory cytokines, signatures of coagulation, NETosis, and T-cell functional dysregulation. A second immune cascade, predictive of 28-day mortality among critically ill patients, was characterized by reduced total plasma immunoglobulins and B cells, as well as dysregulated IFN responsiveness. We demonstrated that the balance disruption between IFN-stimulated genes and IFN inhibitors is a crucial biomarker of COVID-19 mortality, potentially contributing to the failure of viral clearance in patients with fatal illness. Our longitudinal multi-omics profiling study revealed novel temporal coordination across diverse omics that potentially explain disease progression, providing insights that inform the targeted development of therapies for hospitalized COVID-19 patients, especially those critically ill.

The Role of Tryptophan Metabolism in the Occurrence and Progression of Acute and Chronic Kidney Diseases

Acute kidney injury (AKI) and chronic kidney disease (CKD) are common kidney diseases in clinics with high morbidity and mortality, but their pathogenesis is intricate. Tryptophan (Trp) is a fundamental amino acid for humans, and its metabolism produces various bioactive substances involved in the pathophysiology of AKI and CKD. Metabolomic studies manifest that Trp metabolites like kynurenine (KYN), 5-hydroxyindoleacetic acid (5-HIAA), and indoxyl sulfate (IS) increase in AKI or CKD and act as biomarkers that facilitate the early identification of diseases. Meanwhile, KYN and IS act as ligands to exacerbate kidney damage by activating aryl hydrocarbon receptor (AhR) signal transduction. The reduction of renal function can cause the accumulation of Trp metabolites which in turn accelerate the progression of AKI or CKD. Besides, gut dysbiosis induces the expansion of Enterobacteriaceae family to produce excessive IS, which cannot be excreted due to the deterioration of renal function. The application of Trp metabolism as a target in AKI and CKD will also be elaborated. Thus, this study aims to elucidate Trp metabolism in the development of AKI and CKD, and explores the relative treatment strategies by targeting Trp from the perspective of metabolomics to provide a reference for their diagnosis and prevention.

Prognostic Significance of Amino Acid and Biogenic Amines Profiling in Chronic Kidney Disease

There is a pressing need for more precise biomarkers of chronic kidney disease (CKD). Plasma samples from 820 subjects [231 with CKD, 325 with end-stage kidney disease (ESKD) and 264 controls] were analyzed by liquid chromatography with tandem mass spectrometry (LC-MS/MS) to determine a metabolic profile of 28 amino acids (AAs) and biogenic amines to test their value as markers of CKD risk and progression. The kynurenine/tryptophan ratio showed the strongest correlation with estimated glomerular filtration rate values (coefficient = -0.731, p < 0.0001). Models created with orthogonal partial least squares-discriminant analysis (OPLS-DA) containing the metabolic signature showed a high goodness of fit and predictability for controls/CKD (R2X:0.73:R2Y:0.92:Q2:0.92, p < 0.0001) and lower values for CKD/ESKD (R2X:0.56:R2Y:0.59:Q2:0.55, p < 0.0001). Based on generated VIP scores, the most relevant markers for segregating samples into control/CKD and CKD/ESKD groups were citrulline (1.63) and tryptophan (1.47), respectively. ROC analysis showed that the addition of the metabolic profile to a model including CKD classic risk factors improved the AUC from 86.7% (83.6-89.9) to 100% (100-100) for CKD risk (p < 0.0001) and from 63.0% (58.2-67.8) to 96.5% (95.3-97.8) for the risk of progression from CKD to ESKD (p < 0.0001). Plasma concentrations of AAs and related amines may be useful as diagnostic biomarkers of kidney disease, both for CKD risk and for progression of CKD patients to ESKD.

Circulating metabolites improve the prediction of renal impairment in patients with type 2 diabetes

INTRODUCTION

Low glomerular filtration rate (GFR) is a leading cause of reduced lifespan in type 2 diabetes. Unravelling biomarkers capable to identify high-risk patients can help tackle this burden. We investigated the association between 188 serum metabolites and kidney function in type 2 diabetes and then whether the associated metabolites improve two established clinical models for predicting GFR decline in these patients.

RESEARCH DESIGN AND METHODS

Two cohorts comprising 849 individuals with type 2 diabetes (discovery and validation samples) and a follow-up study of 575 patients with estimated GFR (eGFR) decline were analyzed.

RESULTS

Ten metabolites were independently associated with low eGFR in the discovery sample, with nine of them being confirmed also in the validation sample (ORs range 1.3-2.4 per 1SD, p values range 1.9×10-2-2.5×10-9). Of these, five metabolites were also associated with eGFR decline (ie, tiglylcarnitine, decadienylcarnitine, total dimethylarginine, decenoylcarnitine and kynurenine) (β range -0.11 to -0.19, p values range 4.8×10-2 to 3.0×10-3). Indeed, tiglylcarnitine and kynurenine, which captured all the information of the other three markers, improved discrimination and reclassification (all p<0.01) of two clinical prediction models of GFR decline in people with diabetes.

CONCLUSIONS

Further studies are needed to validate our findings in larger cohorts of different clinical, environmental and genetic background.

Association of amino acids and parameters of bone metabolism with endothelial dysfunction and vasculopathic changes in limited systemic sclerosis

Objectives

Pathways contributing to endothelial dysfunction in patients with limited cutaneous systemic sclerosis (lcSSc) are largely unknown. The aim of this study was to investigate potential associations of amino acids and parameters of bone metabolism with endothelial dysfunction and vasculopathy-related changes in patients with lcSSc and early-stage vasculopathy.

Methods

Amino acids, calciotropic parameters, including 25-hydroxyvitamin D and parathyroid hormone (PTH), and bone turnover parameters, including osteocalcin and N-terminal peptide of procollagen-3 (P3NP), were measured in 38 lcSSc patients and 38 controls. Endothelial dysfunction was assessed by biochemical parameters, pulse-wave analysis, flow-mediated and nitroglycerine-mediated dilation. Additionally, vasculopathy-related and SSc-specific clinical changes including capillaroscopic, skin, renal, pulmonary, gastrointestinal and periodontal parameters were recorded.

Results

No significant differences in amino acids, calciotropic and bone turnover parameters were observed between lcSSc patients and controls. In patients with lcSSc, several significant correlations were found between selected amino acids, parameters of endothelial dysfunction, vasculopathy-related and SSc-specific clinical changes (all with p < 0.05). In addition, significant correlations were observed between PTH and 25-hydroxyvitamin D with homoarginine, and between osteocalcin, PTH and P3NP with modified Rodnan skin score and selected periodontal parameters (all with p < 0.05). Vitamin D deficiency defined as 25-hydroxyvitamin D < 20 ng/ml was associated with the presence of puffy finger (p = 0.046) and early pattern (p = 0.040).

Conclusion

Selected amino acids may affect endothelial function and may be associated to vasculopathy-related and clinical changes in lcSSc patients, while the association with parameters of bone metabolism seems to be minor.

MultiNEP: a multi-omics network enhancement framework for prioritizing disease genes and metabolites simultaneously

MOTIVATION

Many studies have successfully used network information to prioritize candidate omics profiles associated with diseases. The metabolome, as the link between genotypes and phenotypes, has accumulated growing attention. Using a "multi-omics" network constructed with a gene-gene network, a metabolite-metabolite network, and a gene-metabolite network to simultaneously prioritize candidate disease-associated metabolites and gene expressions could further utilize gene-metabolite interactions that are not used when prioritizing them separately. However, the number of metabolites is usually 100 times fewer than that of genes. Without accounting for this imbalance issue, we cannot effectively use gene-metabolite interactions when simultaneously prioritizing disease-associated metabolites and genes.

RESULTS

Here, we developed a Multi-omics Network Enhancement Prioritization (MultiNEP) framework with a weighting scheme to reweight contributions of different sub-networks in a multi-omics network to effectively prioritize candidate disease-associated metabolites and genes simultaneously. In simulation studies, MultiNEP outperforms competing methods that do not address network imbalances and identifies more true signal genes and metabolites simultaneously when we down-weight relative contributions of the gene-gene network and up-weight that of the metabolite-metabolite network to the gene-metabolite network. Applications to two human cancer cohorts show that MultiNEP prioritizes more cancer-related genes by effectively using both within- and between-omics interactions after handling network imbalance.

AVAILABILITY AND IMPLEMENTATION

The developed MultiNEP framework is implemented in an R package and available at: https://github.com/Karenxzr/MultiNep.

Metabolomic Investigation of Blood and Urinary Amino Acids and Derivatives in Patients with Type 2 Diabetes Mellitus and Early Diabetic Kidney Disease

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease; however, few biomarkers of its early identification are available. The aim of the study was to assess new biomarkers in the early stages of DKD in type 2 diabetes mellitus (DM) patients. This cross-sectional pilot study performed an integrated metabolomic profiling of blood and urine in 90 patients with type 2 DM, classified into three subgroups according to albuminuria stage from P1 to P3 (30 normo-, 30 micro-, and 30 macroalbuminuric) and 20 healthy controls using high-performance liquid chromatography and mass spectrometry (UPLC-QTOF-ESI* MS). From a large cohort of separated and identified molecules, 33 and 39 amino acids and derivatives from serum and urine, respectively, were selected for statistical analysis using Metaboanalyst 5.0. online software. The multivariate and univariate algorithms confirmed the relevance of some amino acids and derivatives as biomarkers that are responsible for the discrimination between healthy controls and DKD patients. Serum molecules such as tiglylglycine, methoxytryptophan, serotonin sulfate, 5-hydroxy lysine, taurine, kynurenic acid, and tyrosine were found to be more significant in the discrimination between group C and subgroups P1-P2-P3. In urine, o-phosphothreonine, aspartic acid, 5-hydroxy lysine, uric acid, methoxytryptophan, were among the most relevant metabolites in the discrimination between group C and DKD group, as well between subgroups P1-P2-P3. The identification of these potential biomarkers may indicate their involvement in the early DKD and 2DM progression, reflecting kidney injury at specific sites along the nephron, even in the early stages of DKD.

Identification of Genetic Markers Linked to The Activity of Indoleamine 2,3-Dioxygenase and Kidney Function

Indoleamine 2,3-dioxygenase (IDO) is a tryptophan-degrading enzyme belonging to the kynurenine pathway. IDO activity has been suggested as a potential biomarker for early diagnosis of chronic kidney disease (CKD). The aim of this study was to perform coincident association analysis to gain genetic insights into the correlation between IDO activity and CKD. This study evaluated the association between IDO activity and CKD using the Korea Association REsource (KARE) cohort. Logistic and linear regression were used to analyze CKD and quantitative phenotypes such as IDO and estimated glomerular filtration rate (eGFR). Our results identified 10 single nucleotide polymorphisms (SNPs) that were coincidently associated with both IDO and CKD (p < 0.001). Among them, rs6550842, rs77624055, and rs35651150 were selected as potential candidates after excluding SNPs with insufficient evidence for having an association with IDO or CKD. Further expression quantitative trait loci (eQTL) analysis for variants at selected loci showed that rs6550842 and rs35651150 significantly affected the expression of NKIRAS1 and SH2D4A genes in human tissues, respectively. Additionally, we highlighted that the NKIRAS1 and BMP6 genes were correlated with IDO activity and CKD through signaling pathways associated with inflammation. Our data suggest that NKIRAS1, SH2D4A, and BMP6 were potential causative genes affecting IDO activity and CKD through integrated analysis. Identifying these genes could aid in early detection and treatment by predicting the risk of CKD associated with IDO activity.

Untargeted Metabolomics by Ultra-High-Performance Liquid Chromatography Coupled with Electrospray Ionization-Quadrupole-Time of Flight-Mass Spectrometry Analysis Identifies a Specific Metabolomic Profile in Patients with Early Chronic Kidney Disease

Chronic kidney disease (CKD) has emerged as one of the most progressive diseases with increased mortality and morbidity. Metabolomics offers new insights into CKD pathogenesis and the discovery of new biomarkers for the early diagnosis of CKD. The aim of this cross-sectional study was to assess metabolomic profiling of serum and urine samples obtained from CKD patients. Untargeted metabolomics followed by multivariate and univariate analysis of blood and urine samples from 88 patients with CKD, staged by estimated glomerular filtration rate (eGFR), and 20 healthy control subjects was performed using ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry. Serum levels of Oleoyl glycine, alpha-lipoic acid, Propylthiouracil, and L-cysteine correlated directly with eGFR. Negative correlations were observed between serum 5-Hydroxyindoleacetic acid, Phenylalanine, Pyridoxamine, Cysteinyl glycine, Propenoylcarnitine, Uridine, and All-trans retinoic acid levels and eGFR. In urine samples, the majority of molecules were increased in patients with advanced CKD as compared with early CKD patients and controls. Amino acids, antioxidants, uremic toxins, acylcarnitines, and tryptophane metabolites were found in all CKD stages. Their dual variations in serum and urine may explain their impact on both glomerular and tubular structures, even in the early stages of CKD. Patients with CKD display a specific metabolomic profile. Since this paper represents a pilot study, future research is needed to confirm our findings that metabolites can serve as indicators of early CKD.

Metabolite Profiling of the Gut–Renal–Cerebral Axis Reveals a Particular Pattern in Early Diabetic Kidney Disease in T2DM Patients

Type 2 diabetes mellitus (T2DM) represents an important microvascular disease concerning the kidney and the brain. Gut dysbiosis and microbiota-derived metabolites may be in relation with early pathophysiological changes in diabetic kidney disease (DKD). The aim of the study was to find new potential gut-derived biomarkers involved in the pathogenesis of early DKD, with a focus on the complex interconnection of these biomarkers with podocyte injury, proximal tubule dysfunction, renal and cerebrovascular endothelial dysfunction. The study design consisted of metabolite profiling of serum and urine of 90 T2DM patients (subgroups P1-normoalbuminuria, P2-microalbuminuria, P3-macroalbuminuria) and 20 healthy controls (group C), based on ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry analysis (UHPLC-QTOF-ESI+-MS). By multivariate and univariate analyses of serum and urine, which included Partial Least Squares Discriminant Analysis (PLSDA), Variable Importance Plots (VIP), Random Forest scores, One Way ANOVA and Biomarker analysis, there were discovered metabolites belonging to nitrogen metabolic pathway and retinoic acid signaling pathway which differentiate P1 group from P2, P3, C groups. Tyrosine, phenylalanine, indoxyl sulfate, serotonin sulfate, and all-trans retinoic acid express the metabolic fingerprint of P1 group vs. P2, P3, C groups, revealing a particular pattern in early DKD in T2DM patients.

Identification of region-specific amino acid signatures for doxorubicin-induced chemo brain

Doxorubicin (DOX) is a cornerstone of chemotherapy for solid tumors and leukemias. DOX-induced cognitive impairment, termed chemo brain, has been reported in cancer survivors, whereas its mechanism remains poorly understood. Here we initially evaluated the cognitive impairments of mice treated with clinically relevant, long-term, low-dosage of DOX. Using HILIC-MS/MS-based targeted metabolomics, we presented the changes of 21 amino acids across six anatomical brain regions of mice with DOX-induced chemo brain. By mapping the altered amino acids to the human metabolic network, we constructed an amino acid-based network module for each brain region. We identified phenylalanine, tyrosine, methionine, and γ-aminobutyric acid as putative signatures of three regions (hippocampus, prefrontal cortex, and neocortex) highly associated with cognition. Relying on the reported mouse brain metabolome atlas, we found that DOX might perturb the amino acid homeostasis in multiple brain regions, similar to the changes in the aging brain. Correlation analysis suggested the possible indirect neurotoxicity of DOX that altered the brain levels of phenylalanine, tyrosine, and methionine by causing metabolic disorders in the liver and kidney. In summary, we revealed the region-specific amino acid signatures as actionable targets for DOX-induced chemo brain, which might provide safer treatment and improve the quality of life among cancer survivors.

Associations of serum amino acids related to urea cycle with risk of chronic kidney disease in Chinese with type 2 diabetes

OBJECTIVE

Serum levels of amino acids related to urea cycle are associated with risk of type 2 diabetes mellitus (T2DM). Our study aimed to explore whether serum levels of amino acids related to urea cycle, i.e., arginine, citrulline, and ornithine, are also associated with increased risk of chronic kidney disease (CKD) in T2DM.

METHODS

We extracted medical records of 1032 consecutive patients with T2DM from the Electronic Administrative System of Liaoning Medical University First Affiliated Hospital (LMUFAH) system from May 2015 to August 2016. Of them, 855 patients with completed data available were used in the analysis. CKD was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m². Serum amino acids were measured by mass spectrometry (MS) technology. Binary logistic regression was performed to obtain odds ratios (ORs) and their 95% confidence intervals (CIs).

RESULTS

52.3% of the 855 T2DM patients were male, and 143 had CKD. In univariable analysis, high serum citrulline, high ratio of arginine to ornithine, and low ratio of ornithine to citrulline were associated with markedly increased risk of CKD (OR of top vs. bottom tertile: 2.87, 95%CI, 1.79-4.62 & 1.98, 95%CI,1.25-3.14 & 2.56, 95%CI, 1.61-4.07, respectively). In multivariable analysis, the ORs of citrulline and ornithine/citrulline ratio for CKD remained significant (OR of top vs. bottom tertile: 2.22, 95%CI, 1.29-3.82 & 2.24, 1.29-3.87, respectively).

CONCLUSIONS

In Chinese patients with T2DM, high citrulline and low ornithine/citrulline ratio were associated with increased risk of CKD.

Nitric-oxide precursors and dimethylarginines as risk markers for accelerated measured GFR decline in the general population

Introduction

Nitric oxide (NO) deficiency is associated with endothelial dysfunction, hypertension, atherosclerosis, and chronic kidney disease (CKD). Reduced NO bioavailability is hypothesized to play a vital role in kidney function impairment and CKD. We investigated the association of serum levels of endogenous inhibitors of NO, asymmetric dimethylarginine (ADMA) and symmetric dimethylarginine (SDMA), and precursors of NO, arginine, citrulline, and ornithine, with a decline in glomerular filtration rate (GFR) and new-onset CKD.

Methods

In a prospective cohort study of 1407 healthy, middle-aged participants of Northern European origin in the Renal Iohexol Clearance Survey (RENIS), GFR was measured repeatedly with iohexol clearance during a median follow-up time of 11 years. GFR decline rates were analyzed using a linear mixed model, new-onset CKD (GFR < 60 ml/min per 1.73 m²) was analyzed with interval-censored Cox regression, and accelerated GFR decline (the 10% with the steepest GFR decline) was analyzed with logistic regression.

Results

Higher SDMA was associated with slower annual GFR decline. Higher levels of citrulline and ornithine were associated with accelerated GFR decline (odds ratio [OR], 1.43; 95% confidence interval [CI] 1.16-1.76 per SD higher citrulline and OR 1.23; 95% CI 1.01 to 1.49 per SD higher ornithine). Higher citrulline was associated with new-onset CKD, with a hazard ratio of 1.33 (95% CI 1.07-1.66) per SD higher citrulline.

Conclusions

Associations between NO precursors and the outcomes suggest that NO metabolism plays a significant role in the pathogenesis of age-related GFR decline and the development of CKD in middle-aged people.

NAD+ Metabolism and Interventions in Premature Renal Aging and Chronic Kidney Disease

Premature aging causes morphological and functional changes in the kidney, leading to chronic kidney disease (CKD). CKD is a global public health issue with far-reaching consequences, including cardio-vascular complications, increased frailty, shortened lifespan and a heightened risk of kidney failure. Dialysis or transplantation are lifesaving therapies, but they can also be debilitating. Currently, no cure is available for CKD, despite ongoing efforts to identify clinical biomarkers of premature renal aging and molecular pathways of disease progression. Kidney proximal tubular epithelial cells (PTECs) have high energy demand, and disruption of their energy homeostasis has been linked to the progression of kidney disease. Consequently, metabolic reprogramming of PTECs is gaining interest as a therapeutic tool. Preclinical and clinical evidence is emerging that NAD+ homeostasis, crucial for PTECs' oxidative metabolism, is impaired in CKD, and administration of dietary NAD+ precursors could have a prophylactic role against age-related kidney disease. This review describes the biology of NAD+ in the kidney, including its precursors and cellular roles, and discusses the importance of NAD+ homeostasis for renal health. Furthermore, we provide a comprehensive summary of preclinical and clinical studies aimed at increasing NAD+ levels in premature renal aging and CKD.

Identifying Genetic Variants and Metabolites Associated with Rapid Estimated Glomerular Filtration Rate Decline in Korea Based on Genome-Metabolomic Integrative Analysis

Identifying the predisposing factors to chronic or end-stage kidney disease is essential to preventing or slowing kidney function decline. Therefore, here, we investigated the genetic variants related to a rapid decline in the estimated glomerular filtration rate (eGFR) (i.e., a loss of >5 mL/min/1.73 m2 per year) and verified the relationships between variant-related diseases and metabolic pathway signaling in patients with chronic kidney disease. We conducted a genome-wide association study that included participants with diabetes, hypertension, and rapid eGFR decline from two Korean data sources (N = 115 and 69 for the discovery and the validation cohorts, respectively). We identified a novel susceptibility locus: 4q32.3 (rs10009742 in the MARCHF1 gene, beta = −3.540, P = 4.11 × 10−8). Fine-mapping revealed 19 credible, causal single-nucleotide polymorphisms, including rs10009742. The pimelylcarnitine and octadecenoyl carnitine serum concentrations were associated with rs10009742 (beta = 0.030, P = 7.10 × 10−5, false discovery rate (FDR) = 0.01; beta = 0.167, P = 8.11 × 10−4, FDR = 0.08). Our results suggest that MARCHF1 is associated with a rapid eGFR decline in patients with hypertension and diabetes. Furthermore, MARCHF1 affects the pimelylcarnitine metabolite concentration, which may mediate chronic kidney disease progression by inducing oxidative stress in the endoplasmic reticulum.

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.

The Footprint of Kynurenine Pathway in Cardiovascular Diseases

Kynurenine pathway is the main route of tryptophan metabolism and produces several metabolites with various biologic properties. It has been uncovered that several cardiovascular diseases are associated with the overactivation of kynurenine pathway and kynurenine and its metabolites have diagnostic and prognostic value in cardiovascular diseases. Furthermore, it was found that several kynurenine metabolites can differently affect cardiovascular health. For instance, preclinical studies have shown that kynurenine, xanthurenic acid and cis-WOOH decrease blood pressure; kynurenine and 3-hydroxyanthranilic acid prevent atherosclerosis; kynurenic acid supplementation and kynurenine 3-monooxygenase (KMO) inhibition improve the outcome of stroke. Indoleamine 2,3-dioxygenase (IDO) overactivity and increased kynurenine levels improve cardiac and vascular transplantation outcomes, whereas exacerbating the outcome of myocardial ischemia, post-ischemic myocardial remodeling, and abdominal aorta aneurysm. IDO inhibition and KMO inhibition are also protective against viral myocarditis. In addition, dysregulation of kynurenine pathway is observed in several conditions such as senescence, depression, diabetes, chronic kidney disease (CKD), cirrhosis, and cancer closely connected to cardiovascular dysfunction. It is worth defining the exact effect of each metabolite of kynurenine pathway on cardiovascular health. This narrative review is the first review that separately discusses the involvement of kynurenine pathway in different cardiovascular diseases and dissects the underlying molecular mechanisms.

A Fluorescence-Based Competitive Antibody Binding Assay for Kynurenine, a Potential Biomarker of Kidney Transplant Failure

Kynurenine is a tryptophan metabolite linked to several inflammatory processes including transplant failure, a significant challenge in transplant medicine. The detection of small molecules such as kynurenine, however, is often complex and time consuming. Herein, we report the successful synthesis of a fluorescently labelled kynurenine derivative, showing proper fluorescence and anti-kynurenine antibody binding behavior in a magnetic bead immunoassay (MIA). The fluorescent kynurenine–rhodamine B conjugate shows a KD-value of 5.9 µM as well as IC50 values of 4.0 µM in PBS and 10.2 µM in saliva. We thus introduce a rapid test for kynurenine as a potential biomarker for kidney transplant failure.

Plasma Kynurenine: A Promising Marker for the Assessment of Renal Functions

Background:

Chronic kidney disease (CKD) is a worldwide issue due to the high prevalence and the serious complications, including death. Kidney functions are routinely evaluated by measuring creatinine levels, which are influenced by many factors (age, sex, diet, race, and body mass). Kynurenine is the first stable metabolite in the kynurenine pathway, which is activated in the course of CKD. Kynurenine levels in plasma can be correlated to kidney functions in CKD patients. We investigated the relationship between kynurenine levels and kidney functions indicators, and the influence of some variables (sex, age, and preexisting hypertension or diabetes) on its levels in CKD patients.

Material And Methods:

The study included 66 CKD patients in stages 3 to 5 seen at Tishreen University Hospital, and 22 subjects served as control. Kynurenine levels were measured by using a kynurenine ELISA kit (IDK® immundiagnostik).

Results:

Kynurenine levels were significantly increased with the increase in CKD stage ( P < .001), and were correlated with eGFR ( r = −.631, P < .001), creatinine levels ( r = −.464, P < .001), and urea levels ( r = .528, P < .001). Kynurenine plasma levels were not influenced by age, sex, diabetes, and hypertension in CKD patients.

Conclusion:

Kynurenine is a promising marker for estimating kidney functions, and its relation with kidney functions is not affected by age, sex, and presence of hypertension or diabetes in CKD patients.

Early Metabolomic Markers of Acute Low-Dose Exposure to Uranium in Rats

Changes in metabolomics over time were studied in rats to identify early biomarkers and highlight the main metabolic pathways that are significantly altered in the period immediately following acute low-dose uranium exposure. A dose response relationship study was established from urine and plasma samples collected periodically over 9 months after the exposure of young adult male rats to uranyl nitrate. LC-MS and biostatistical analysis were used to identify early discriminant metabolites. As expected, low doses of uranium lead to time-based non-toxic biological effects, which can be used to identify early and delayed markers of exposure in both urine and plasma samples. A combination of surrogate markers for uranium exposure was validated from the most discriminant early markers for making effective predictions. N-methyl-nicotinamide, kynurenic acid, serotonin, tryptophan, tryptamine, and indole acetic acid associated with the nicotinate–nicotinamide and tryptophan pathway seem to be one of the main biological targets, as shown previously for chronic contaminations and completed, among others, by betaine metabolism. This study can be considered as a proof of concept for the relevance of metabolomics in the field of low-dose internal contamination by uranium, for the development of predictive diagnostic tests usable for radiotoxicological monitoring.

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

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

Association of Plasma Branched-Chain and Aromatic Amino Acids with Reduction in Kidney Function Evaluated in Apparently Healthy Adults

The published literature on the association of circulatory branched-chain amino acids (BCAAs) and aromatic amino acids (AAAs) with reduced kidney function is inconsistent or conflicting. Clarification of it might help to better understand the underlying pathophysiology and to determine potential biomarkers for early detection and evaluation of kidney function decline. Our main purpose was to explore and clarify the potential relationships of individual BCAAs and AAAs with estimated glomerular filtration rate (eGFR) decline. We included the data from 2804 healthy subjects and categorized them into three groups based on eGFR tertiles. The associations between individual amino acids and eGFR were explored by covariate-adjusted logistic regression models. There was a progressive increase in the concentrations of BCAAs and AAAs from the upper to the lower tertiles. We revealed significant positive associations of isoleucine, leucine, and phenylalanine with lower tertiles of eGFR in the adjusted models (p < 0.01-0.001). The findings hold a promising potential of using plasma isoleucine, leucine, and phenylalanine levels for evaluation of kidney function decline. Future longitudinal studies should investigate the causal association between altered levels of these amino acids and impaired kidney function and also the utility of the former as potential biomarkers for evaluating the risk and early detection of the latter.

The Kynurenine Pathway in Acute Kidney Injury and Chronic Kidney Disease

BACKGROUND

The kynurenine pathway (KP) is the major catabolic pathway for tryptophan degradation. The KP plays an important role as the sole de novo nicotinamide adenine dinucleotide (NAD+) biosynthetic pathway in normal human physiology and functions as a counter-regulatory mechanism to mitigate immune responses during inflammation. Although the KP has been implicated in a variety of disorders including Huntington's disease, seizures, cardiovascular disease, and osteoporosis, its role in renal diseases is seldom discussed.

SUMMARY

This review summarizes the roles of the KP and its metabolites in acute kidney injury (AKI) and chronic kidney disease (CKD) based on current literature evidence. Metabolomics studies demonstrated that the KP metabolites were significantly altered in patients and animal models with AKI or CKD. The diagnostic and prognostic values of the KP metabolites in AKI and CKD were highlighted in cross-sectional and longitudinal human observational studies. The biological impact of the KP on the pathophysiology of AKI and CKD has been studied in experimental models of different etiologies. In particular, the activation of the KP was found to confer protection in animal models of glomerulonephritis, and its immunomodulatory mechanism may involve the regulation of T cell subsets such as Th17 and regulatory T cells. Manipulation of the KP to increase NAD+ production or diversion toward specific KP metabolites was also found to be beneficial in animal models of AKI. Key Messages: KP metabolites are reported to be dysregulated in human observational and animal experimental studies of AKI and CKD. In AKI, the magnitude and direction of changes in the KP depend on the etiology of the damage. In CKD, KP metabolites are altered with the onset and progression of CKD all the way to advanced stages of the disease, including uremia and its related vascular complications. The activation of the KP and diversion to specific sub-branches are currently being explored as therapeutic strategies in these diseases, especially with regards to the immunomodulatory effects of certain KP metabolites. Further elucidation of the KP may hold promise for the development of biomarkers and targeted therapies for these kidney diseases.

Comparison of Kit-Based Metabolomics with Other Methodologies in a Large Cohort, towards Establishing Reference Values

Metabolic profiling is an omics approach that can be used to observe phenotypic changes, making it particularly attractive for biomarker discovery. Although several candidate metabolites biomarkers for disease expression have been identified in recent clinical studies, the reference values of healthy subjects have not been established. In particular, the accuracy of concentrations measured by mass spectrometry (MS) is unclear. Therefore, comprehensive metabolic profiling in large-scale cohorts by MS to create a database with reference ranges is essential for evaluating the quality of the discovered biomarkers. In this study, we tested 8700 plasma samples by commercial kit-based metabolomics and separated them into two groups of 6159 and 2541 analyses based on the different ultra-high-performance tandem mass spectrometry (UHPLC-MS/MS) systems. We evaluated the quality of the quantified values of the detected metabolites from the reference materials in the group of 2541 compared with the quantified values from other platforms, such as nuclear magnetic resonance (NMR), supercritical fluid chromatography tandem mass spectrometry (SFC-MS/MS) and UHPLC-Fourier transform mass spectrometry (FTMS). The values of the amino acids were highly correlated with the NMR results, and lipid species such as phosphatidylcholines and ceramides showed good correlation, while the values of triglycerides and cholesterol esters correlated less to the lipidomics analyses performed using SFC-MS/MS and UHPLC-FTMS. The evaluation of the quantified values by MS-based techniques is essential for metabolic profiling in a large-scale cohort.

Fisetin Improves Hyperuricemia-Induced Chronic Kidney Disease via Regulating Gut Microbiota-Mediated Tryptophan Metabolism and Aryl Hydrocarbon Receptor Activation

The intestinal flora serves a critical role in the development of hyperuricemia-induced chronic kidney disease (CKD). We previously found that natural flavonol fisetin exhibited nephroprotective effects in hyperuricemic mice. However, the mechanism remains largely unknown. To investigate the underlying mechanism of fisetin, mice were fed with potassium oxonate and adenine to introduce hyperuricemia-induced CKD. Fisetin improved kidney function, ameliorated renal fibrosis, and restored enteric dysbacteriosis in hyperuricemia-induced CKD mice. Meanwhile, gut microbiota-derived tryptophan metabolites, especially l-kynurenine, showed correlations with nephroprotective profiles of fisetin. Additionally, the kidney expression of the aryl hydrocarbon receptor (AHR), an endogenous receptor of l-kynurenine, was enhanced in hyperuricemic mice and further reduced in fisetin-treated mice. Finally, in vitro results showed that inhibition of AHR activation attenuated l-kynurenine-induced fibrosis. These results highlighted that fisetin protected against hyperuricemia-induced CKD via modulating gut microbiota-mediated tryptophan metabolism and AHR activation.

Local Inhibition of Indoleamine 2,3-Dioxygenase Mitigates Renal Fibrosis

Chronic kidney disease (CKD) is a major global health concern and renal fibrosis is an integral part of the pathophysiological mechanism underlying disease progression. In CKD patients, the majority of metabolic pathways are in disarray and perturbations in enzyme activity most likely contribute to the wide variety of comorbidities observed in these patients. To illustrate, catabolism of tryptophan by indoleamine 2,3-dioxygenase (IDO) gives rise to numerous biologically active metabolites implicated in CKD progression. Here, we evaluated the effect of antagonizing IDO on renal fibrogenesis. To this end, we antagonized IDO using 1-methyl-D-tryptophan (1-MT) and BMS-98620 in TGF-β-treated murine precision-cut kidney slices (mPCKS) and in mice subjected to unilateral ureteral obstruction (UUO). The fibrotic response was evaluated on both the gene and protein level using qPCR and western blotting. Our results demonstrated that treatment with 1-MT or BMS-985205 markedly reduced TGF-β-mediated fibrosis in mPCKS, as seen by a decreased expression of collagen type 1, fibronectin, and α-smooth muscle actin. Moreover, IDO protein expression clearly increased following UUO, however, treatment of UUO mice with either 1-MT or BMS-986205 did not significantly affect the gene and protein expression of the tested fibrosis markers. However, both inhibitors significantly reduced the renal deposition of collagen in UUO mice as shown by Sirius red and trichrome staining. In conclusion, this study demonstrates that IDO antagonism effectively mitigates fibrogenesis in mPCKS and reduces renal collagen accumulation in UUO mice. These findings warrant further research into the clinical application of IDO inhibitors for the treatment of renal fibrosis.

Serum-Urine Matched Metabolomics for Predicting Progression of Henoch-Schonlein Purpura Nephritis

Henoch-Schonlein purpura nephritis (HSPN) is a common glomerulonephritis secondary to Henoch-Schonlein purpura (HSP) that affects systemic metabolism. Currently, there is a rarity of biomarkers to predict the progression of HSPN. This work sought to screen metabolic markers to predict the progression of HSPN via serum-urine matched metabolomics. A total of 90 HSPN patients were enrolled, including 46 HSPN (+) patients with severe kidney damage (persistent proteinuria >0.3 g/day) and 44 HSPN (–) patients without obvious symptoms (proteinuria < 0.3 g/day). Untargeted metabolomics was determined by liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-Q/TOF-MS). A total of 38 and 50 differential metabolites were, respectively, identified in serum and urine from the comparison between HSPN (+) and HSPN (–) patients. Altered metabolic pathways in HSPN (+) mainly included glycerophospholipid metabolism, pyruvate metabolism, and citrate cycle. A panel of choline and cis-vaccenic acid gave areas under the curve of 92.69% in serum and 72.43% in urine for differential diagnosis between HSPN (+) and HSPN (–). In addition, the two metabolites showed a significant association with clinical indices of HSPN. These results suggest that serum-urine matched metabolomics comprehensively characterized the metabolic differences between HSPN (+) and HSPN (–), and choline and cis-vaccenic acid could serve as biomarkers to predict HSPN progression.

Classification of Chronic Kidney Disease in Sonography Using the GLCM and Artificial Neural Network

Chronic kidney disease (CKD) can be treated if it is detected early, but as the disease progresses, recovery becomes impossible. Eventually, renal replacement therapy such as transplantation or dialysis is necessary. Ultrasound is a test method with which to diagnose kidney cancer, inflammatory disease, nodular disease, chronic kidney disease, etc. It is used to determine the degree of inflammation using information such as the kidney size and internal echo characteristics. The degree of the progression of chronic kidney disease in the current clinical trial is based on the value of the glomerular filtration rate. However, changes in the degree of inflammation and disease can even be observed with ultrasound. In this study, from a total of 741 images, 251 normal kidney images, 328 mild and moderate CKD images, and 162 severe CKD images were tested. In order to diagnose CKD in clinical practice, three ROIs were set: the cortex of the kidney, the boundary between the cortex and medulla, and the medulla, which are areas examined to obtain information from ultrasound images. Parameters were extracted from each ROI using the GLCM algorithm, which is widely used in ultrasound image analysis. When each parameter was extracted from the three areas, a total of 57 GLCM parameters were extracted. Finally, a total of 58 parameters were used by adding information on the size of the kidney, which is important for the diagnosis of chronic kidney disease. The artificial neural network (ANN) was composed of 58 input parameters, 10 hidden layers, and 3 output layers (normal, mild and moderate CKD, and severe CKD). Using the ANN model, the final classification rate was 95.4%, the epoch needed for training was 38 times, and the misclassification rate was 4.6%.

Skeletal muscle metabolic responses to physical activity are muscle type specific in a rat model of chronic kidney disease

Chronic kidney disease (CKD) leads to musculoskeletal impairments that are impacted by muscle metabolism. We tested the hypothesis that 10-weeks of voluntary wheel running can improve skeletal muscle mitochondria activity and function in a rat model of CKD. Groups included (n = 12-14/group): (1) normal littermates (NL); (2) CKD, and; (3) CKD-10 weeks of voluntary wheel running (CKD-W). At 35-weeks old the following assays were performed in the soleus and extensor digitorum longus (EDL): targeted metabolomics, mitochondrial respiration, and protein expression. Amino acid-related compounds were reduced in CKD muscle and not restored by physical activity. Mitochondrial respiration in the CKD soleus was increased compared to NL, but not impacted by physical activity. The EDL respiration was not different between NL and CKD, but increased in CKD-wheel rats compared to CKD and NL groups. Our results demonstrate that the soleus may be more susceptible to CKD-induced changes of mitochondrial complex content and respiration, while in the EDL, these alterations were in response the physiological load induced by mild physical activity. Future studies should focus on therapies to improve mitochondrial function in both types of muscle to determine if such treatments can improve the ability to adapt to physical activity in CKD.

Healthcare Data for Achieving a More Personalized Treatment of Chronic Kidney Disease

The current concept of healthcare incites a more personalized treatment of diseases. To this aim, biomarkers are needed to improve decision-making facing chronic kidney disease (CKD) patients. Prognostic markers provided by real-world (observational) evidence are proposed in this Special Issue entitled "Biomarkers in Chronic Kidney Disease", with the intention to identify high-risk patients. These markers do not target measurable parameters in patients but clinical endpoints that may be in turn transformed to benefits under the effect of future interventions.

Diminished Systemic Amino Acids Metabolome and Lipid Peroxidation in Ureteropelvic Junction Obstruction (UPJO) Infants Requiring Surgery

Congenital anomalies of the urinary tract, and particularly of obstructive nephropathy such as ureteropelvic junction obstruction (UPJO) in infants, can later lead to chronic kidney disease and hypertension. Fundamental questions regarding underlying mechanisms remain unanswered. The aim of the present study was to quantitate the systemic amino acids metabolome in 21 UPJO infants requiring surgery (Group A) and 21 UPJO infants under conservative treatment (Group B). Nineteen healthy age-matched infants served as controls (Group C). Serum amino acids involved in several pathways and representative metabolites, including the L-arginine-derived nitric oxide (NO) metabolites nitrite and nitrate and the lipid peroxidation biomarker malondialdehyde (MDA) were measured by gas chromatography–mass spectrometry (GC–MS) methods using their stable-isotope labeled analogs as internal standards after derivatization to their methyl esters N-pentafluoropropionic amides (amino acids) and to their pentafluorobenzyl derivatives (nitrite, nitrate, MDA). The concentrations of the majority of the biomarkers were found to be lower in Group A compared to Group B. Statistical analysis revealed clear differentiation between the examined study groups. Univariate statistical analysis highlighted serum homoarginine (q = 0.006), asymmetric dimethylarginine (q = 0.05) and malondialdehyde (q = 0.022) as potential biomarkers for UPJO infants requiring surgery. Group A also differed from Group B with respect to the diameter of the preoperative anterior–posterior renal pelvis (AP) as well as regarding the number and extent of inverse correlations between AP and the serum concentrations of the biomarkers. In Group A, but not in Group B, the AP diameter strongly correlated with hydroxy-proline (r = −0.746, p = 0.0002) and MDA (r = −0.754, p = 0.002). Our results indicate a diminished amino acids metabolome in the serum of UPJO infants requiring surgery comparing to a conservative group.

Tissue-Specific 1H-NMR Metabolomic Profiling in Mice with Adenine-Induced Chronic Kidney Disease

Chronic kidney disease (CKD) results in the impaired filtration of metabolites, which may be toxic or harmful to organs/tissues. The objective of this study was to perform unbiased 1H nuclear magnetic resonance (NMR)-based metabolomics profiling of tissues from mice with CKD. Five-month-old male C57BL6J mice were placed on either a casein control diet or adenine-supplemented diet to induce CKD for 24 weeks. CKD was confirmed by significant increases in blood urea nitrogen (24.1 ± 7.7 vs. 105.3 ± 18.3 mg/dL, p < 0.0001) in adenine-fed mice. Following this chronic adenine diet, the kidney, heart, liver, and quadriceps muscles were rapidly dissected; snap-frozen in liquid nitrogen; and the metabolites were extracted. Metabolomic profiling coupled with multivariate analyses confirm clear separation in both aqueous and organic phases between control and CKD mice. Severe energetic stress and apparent impaired mitochondrial metabolism were observed in CKD kidneys evidenced by the depletion of ATP and NAD+, along with significant alterations in tricarboxylic acid (TCA) cycle intermediates. Altered amino acid metabolism was observed in all tissues, although significant differences in specific amino acids varied across tissue types. Taken together, this study provides a metabolomics fingerprint of multiple tissues from mice with and without severe CKD induced by chronic adenine feeding.

New Potential Biomarkers for Chronic Kidney Disease Management-A Review of the Literature

The prevalence of chronic kidney disease (CKD) is increasing worldwide, and the mortality rate continues to be unacceptably high. The biomarkers currently used in clinical practice are considered relevant when there is already significant renal impairment compromising the early use of potentially successful therapeutic interventions. More sensitive and specific biomarkers to detect CKD earlier on and improve patients' prognoses are an important unmet medical need. The aim of this review is to summarize the recent literature on new promising early CKD biomarkers of renal function, tubular lesions, endothelial dysfunction and inflammation, and on the auspicious findings from metabolomic studies in this field. Most of the studied biomarkers require further validation in large studies and in a broad range of populations in order to be implemented into routine CKD management. A panel of biomarkers, including earlier biomarkers of renal damage, seems to be a reasonable approach to be applied in clinical practice to allow earlier diagnosis and better disease characterization based on the underlying etiologic process.