Metabolites associate with kidney function decline and incident chronic kidney disease in the general population

Blood metabolites and chronic kidney disease: a Mendelian randomization study

BACKGROUND

Human blood metabolites have demonstrated close associations with chronic kidney disease (CKD) in observational studies. Nonetheless, the causal relationship between metabolites and CKD is still unclear. This study aimed to assess the associations between metabolites and CKD risk.

METHODS

We applied a two-sample Mendelian randomization (MR) analysis to evaluate relationships between 1400 blood metabolites and eight phenotypes (outcomes) (CKD, estimated glomerular filtration rate(eGFR), urine albumin to creatinine ratio, rapid progress to CKD, rapid decline of eGFR, membranous nephropathy, immunoglobulin A nephropathy, and diabetic nephropathy). The inverse variance weighted (IVW), MR-Egger, and weighted median were used to investigate the causal relationship. Sensitivity analyses were performed with Cochran's Q, MR-Egger intercept, MR-PRESSO Global test, and leave-one-out analysis. Bonferroni correction was used to test the strength of the causal relationship.

RESULTS

Through the MR analysis of 1400 metabolites and eight clinical phenotypes, a total of 48 metabolites were found to be associated with various outcomes. Among them, N-acetylleucine (OR = 0.923, 95%CI: 0.89-0.957, PIVW = 1.450 × 10-5) has a strong causal relationship with lower risk of CKD after the Bonferroni-corrected test, whereas Glycine to alanine ratio has a strong causal relationship with higher risk of CKD (OR = 1.106, 95%CI: 1.063-1.151, PIVW = 5.850 × 10-7). No horizontal pleiotropy and heterogeneity were detected.

CONCLUSION

Our study offers groundbreaking insights into the integration of metabolomics and genomics to reveal the pathogenesis of and therapeutic strategies for CKD. It underscores 48 metabolites as potential causal candidates, meriting further investigation.

Sex differences in kidney metabolism may reflect sex-dependent outcomes in human diabetic kidney disease

Diabetic kidney disease (DKD) is the main cause of chronic kidney disease (CKD) and progresses faster in males than in females. We identify sex-based differences in kidney metabolism and in the blood metabolome of male and female individuals with diabetes. Primary human proximal tubular epithelial cells (PTECs) from healthy males displayed increased mitochondrial respiration, oxidative stress, apoptosis, and greater injury when exposed to high glucose compared with PTECs from healthy females. Male human PTECs showed increased glucose and glutamine fluxes to the TCA cycle, whereas female human PTECs showed increased pyruvate content. The male human PTEC phenotype was enhanced by dihydrotestosterone and mediated by the transcription factor HNF4A and histone demethylase KDM6A. In mice where sex chromosomes either matched or did not match gonadal sex, male gonadal sex contributed to the kidney metabolism differences between males and females. A blood metabolomics analysis in a cohort of adolescents with or without diabetes showed increased TCA cycle metabolites in males. In a second cohort of adults with diabetes, females without DKD had higher serum pyruvate concentrations than did males with or without DKD. Serum pyruvate concentrations positively correlated with the estimated glomerular filtration rate, a measure of kidney function, and negatively correlated with all-cause mortality in this cohort. In a third cohort of adults with CKD, male sex and diabetes were associated with increased plasma TCA cycle metabolites, which correlated with all-cause mortality. These findings suggest that differences in male and female kidney metabolism may contribute to sex-dependent outcomes in DKD.

Circulating metabolites associated with kidney function decline and incident CKD: a multi-platform population-based study

Background

Investigation of circulating metabolites associated with kidney function and chronic kidney disease (CKD) risk could enhance our understanding of underlying pathways and identify new biomarkers for kidney function.

Methods

We selected participants from the population-based Rotterdam Study with data on circulating metabolites and estimated glomerular filtration rate based on serum creatinine (eGFRcreat) available at the same time point. Data on eGFR based on serum cystatin C (eGFRcys) and urine albumin-to-creatinine ratio (ACR) were also included. CKD was defined as eGFRcreat <60 ml/min per 1.73 m2. Data on circulating metabolites (ntotal = 1381) was obtained from the Nightingale and Metabolon platform. Linear regression, linear mixed, and Cox proportional-hazards regression analyses were conducted to study the associations between metabolites and kidney function. We performed bidirectional two-sample Mendelian randomization analyses to investigate causality of the identified associations.

Results

We included 3337 and 1540 participants with data from Nightingale and Metabolon, respectively. A total of 1381 metabolites (243 from Nightingale and 1138 from Metabolon) were included in the analyses. A large number of metabolites were significantly associated with eGFRcreat, eGFRcys, ACR, and CKD, including 16 metabolites that were associated with all four outcomes. Among these, C-glycosyltryptophan (HR 1.50, 95%CI 1.31;1.71) and X-12026 (HR 1.46, 95%CI 1.26;1.68) were most strongly associated with CKD risk. We revealed sex differences in the associations of 11-ketoetiocholanolone glucuronide and 11-beta-glucuronide with the kidney function assessments. No causal associations between the identified metabolites and kidney function were observed.

Conclusion

Our study indicates that several circulating metabolites are associated with kidney function which are likely to have potential as biomarkers, rather than as molecules involved in the pathophysiology of kidney function decline.

Tubular dysfunction impairs renal excretion of pseudouridine in diabetic kidney disease

Plasma nucleosides-pseudouridine (PU) and N2N2-dimethyl guanosine (DMG) predict the progression of type 2 diabetic kidney disease (DKD) to end-stage renal disease, but the mechanisms underlying this relationship are not well understood. We used a well-characterized model of type 2 diabetes (db/db mice) and control nondiabetic mice (db/m mice) to characterize the production and excretion of PU and DMG levels using liquid chromatography-mass spectrometry. The fractional excretion of PU and DMG was decreased in db/db mice compared with control mice at 24 wk before any changes to renal function. We then examined the dynamic changes in nucleoside metabolism using in vivo metabolic flux analysis with the injection of labeled nucleoside precursors. Metabolic flux analysis revealed significant decreases in the ratio of urine-to-plasma labeling of PU and DMG in db/db mice compared with db/m mice, indicating significant tubular dysfunction in diabetic kidney disease. We observed that the gene and protein expression of the renal tubular transporters involved with nucleoside transport in diabetic kidneys in mice and humans was reduced. In conclusion, this study strongly suggests that tubular handling of nucleosides is altered in early DKD, in part explaining the association of PU and DMG with human DKD progression observed in previous studies.NEW & NOTEWORTHY Tubular dysfunction explains the association between the nucleosides pseudouridine and N2N2-dimethyl guanosine and diabetic kidney disease.

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.

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.

Precision Medicine in Diabetic Kidney Disease: A Narrative Review Framed by Lived Experience

Purpose of review

Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease (CKD) for which many treatments exist that have been shown to prevent CKD progression and kidney failure. However, DKD is a complex and heterogeneous etiology of CKD with a spectrum of phenotypes and disease trajectories. In this narrative review, we discuss precision medicine approaches to DKD, including genomics, metabolomics, proteomics, and their potential role in the management of diabetes mellitus and DKD. A patient and caregivers of patients with lived experience with CKD were involved in this review.

Sources of information

Original research articles were identified from MEDLINE and Google Scholar using the search terms "diabetes," "diabetic kidney disease," "diabetic nephropathy," "chronic kidney disease," "kidney failure," "dialysis," "nephrology," "genomics," "metabolomics," and "proteomics."

Methods

A focused review and critical appraisal of existing literature regarding the precision medicine approaches to the diagnosis, prognosis, and treatment of diabetes and DKD framed by a patient partner's/caregiver's lived experience.

Key findings

Distinguishing diabetic nephropathy from CKD due to other types of DKD and non-DKD is challenging and typically requires a kidney biopsy for a diagnosis. Biomarkers have been identified to assist with the prediction of the onset and progression of DKD, but they have yet to be incorporated and evaluated relative to clinical standard of care CKD and kidney failure risk prediction tools. Genomics has identified multiple causal genetic variants for neonatal diabetes mellitus and monogenic diabetes of the young that can be used for diagnostic purposes and to specify antiglycemic therapy. Genome-wide-associated studies have identified genes implicated in DKD pathophysiology in the setting of type 1 and 2 diabetes but their translational benefits are lagging beyond polygenetic risk scores. Metabolomics and proteomics have been shown to improve diagnostic accuracy in DKD, have been used to identify novel pathways involved in DKD pathogenesis, and can be used to improve the prediction of CKD progression and kidney failure as well as predict response to DKD therapy.

Limitations

There are a limited number of large, high-quality prospective observational studies and no randomized controlled trials that support the use of precision medicine based approaches to improve clinical outcomes in adults with or at risk of diabetes and DKD. It is unclear which patients may benefit from the clinical use of genomics, metabolomics and proteomics along the spectrum of DKD trajectory.

Implications

Additional research is needed to evaluate the role of the use of precision medicine for DKD management, including diagnosis, differentiation of diabetic nephropathy from other etiologies of DKD and CKD, short-term and long-term risk prognostication kidney outcomes, and the prediction of response to and safety of disease-modifying therapies.

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.

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.

Current and Novel Biomarkers of Progression Risk in Children with Chronic Kidney Disease

BACKGROUND

Due to the complexity of chronic kidney disease (CKD) pathophysiology, biomarkers representing different mechanistic pathways have been targeted for the study and development of novel biomarkers. The discovery of clinically useful CKD biomarkers would allow for the identification of those children at the highest risk of kidney function decline for timely interventions and enrollment in clinical trials.

SUMMARY

Glomerular filtration rate and proteinuria are traditional biomarkers to classify and prognosticate CKD progression in clinical practice but have several limitations. Over the recent decades, novel biomarkers have been identified from blood or urine with metabolomic screening studies, proteomic screening studies, and an improved knowledge of CKD pathophysiology. This review highlights promising biomarkers associated with the progression of CKD that could potentially serve as future prognostic markers in children with CKD.

KEY MESSAGES

Further studies are needed in children with CKD to validate putative biomarkers, particularly candidate proteins and metabolites, for improving clinical management.

Metabolomic profiles in serum and urine uncover novel biomarkers in children with nephrotic syndrome

BACKGROUND

Nephrotic syndrome is common in children and adults worldwide, and steroid-sensitive nephrotic syndrome (SSNS) accounts for 80%. Aberrant metabolism involvement in early SSNS is sparsely studied, and its pathogenesis remains unclear. Therefore, the goal of this study was to investigate the changes in initiated SSNS patients-related metabolites through serum and urine metabolomics and discover the novel potential metabolites and metabolic pathways.

METHODS

Serum samples (27 SSNS and 56 controls) and urine samples (17 SSNS and 24 controls) were collected. Meanwhile, the non-targeted analyses were performed by ultra-high-performance liquid chromatography-quadrupole time of flight-mass spectrometry (UHPLC-QTOF-MS) to determine the changes in SSNS. We applied the causal inference model, the DoWhy model, to assess the causal effects of several selected metabolites. An ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to validate hits (D-mannitol, dulcitol, D-sorbitol, XMP, NADPH, NAD, bilirubin, and α-KG-like) in 41 SSNS and 43 controls. In addition, the metabolic pathways were explored.

RESULTS

Compared to urine, the metabolism analysis of serum samples was more clearly discriminated at SSNS. 194 differential serum metabolites and five metabolic pathways were obtained in the SSNS group. Eight differential metabolites were identified by establishing the diagnostic model for SSNS, and four variables had a positive causal effect. After validation by targeted MS, except XMP, others have similar trends like the untargeted metabolic analysis.

CONCLUSION

With untargeted metabolomics analysis and further targeted quantitative analysis, we found seven metabolites may be new biomarkers for risk prediction and early diagnosis for SSNS.

Uromodulin and its association with urinary metabolites: the German Chronic Kidney Disease Study

BACKGROUND

The progression of chronic kidney disease (CKD), a global public health burden, is accompanied by a declining number of functional nephrons. Estimation of remaining nephron mass may improve assessment of CKD progression. Uromodulin has been suggested as a marker of tubular mass. We aimed to identify metabolites associated with uromodulin concentrations in urine and serum to characterize pathophysiologic alterations of metabolic pathways to generate new hypotheses regarding CKD pathophysiology.

METHODS

We measured urinary and serum uromodulin levels (uUMOD, sUMOD) and 607 urinary metabolites and performed cross-sectional analyses within the German Chronic Kidney Disease study (N = 4628), a prospective observational study. Urinary metabolites significantly associated with uUMOD and sUMOD were used to build weighted metabolite scores for urine (uMS) and serum uromodulin (sMS) and evaluated for time to adverse kidney events over 6.5 years.

RESULTS

Metabolites cross-sectionally associated with uromodulin included amino acids of the tryptophan metabolism, lipids and nucleotides. Higher levels of the sMS [hazard ratio (HR) = 0.73 (95% confidence interval 0.64; 0.82), P = 7.45e-07] and sUMOD [HR = 0.74 (95% confidence interval 0.63; 0.87), P = 2.32e-04] were associated with a lower risk of adverse kidney events over time, whereas uUMOD and uMS showed the same direction of association but were not significant.

CONCLUSIONS

We identified urinary metabolites associated with urinary and serum uromodulin. The sUMOD and the sMS were associated with lower risk of adverse kidney events among CKD patients. Higher levels of sUMOD and sMS may reflect a higher number of functional nephrons and therefore a reduced risk of adverse kidney outcomes.

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.

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.

Artemether Alleviates Diabetic Kidney Disease by Modulating Amino Acid Metabolism

Diabetes is a worldwide metabolic disease with rapid growing incidence, characterized by hyperglycemia. Diabetic kidney disease (DKD), the leading cause of chronic kidney disease (CKD), has a high morbidity according to the constantly increasing diabetic patients and always develops irreversible deterioration of renal function. Though different in pathogenesis, clinical manifestations, and therapies, both type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) can evolve into DKD. Since amino acids are both biomarkers and causal agents, rarely report has been made about its metabolism which lies in T1DM- and T2DM-related kidney disease. This study was designed to investigate artemether in adjusting renal amino acid metabolism in T1DM and T2DM mice. Artemether was applied as treatment in streptozotocin (STZ) induced T1DM mice and db/db T2DM mice, respectively. Artemether-treated mice showed lower FBG and HbA1c and reduced urinary albumin excretion, as well as urinary NAG. Both types of diabetic mice showed enlarged kidneys, as confirmed by increased kidney weight and the ratio of kidney weight to body weight. Artemether normalized kidney size and thus attenuated renal hypertrophy. Kidney tissue UPLC-MS analysis showed that branched-chain amino acids (BCAAs) and citrulline were upregulated in diabetic mice without treatment and downregulated after being treated with artemether. Expressions of glutamine, glutamic acid, aspartic acid, ornithine, glycine, histidine, phenylalanine and threonine were decreased in both types of diabetic mice whereas they increased after artemether treatment. The study demonstrates the initial evidence that artemether exerted renal protection in DKD by modulating amino acid metabolism.

Two point Dixon-based chemical exchange saturation transfer (CEST) MRI in renal transplant patients on 3 T

PURPOSE

To assess the performance of two point (2-pt) Dixon-based chemical exchange saturation transfer (CEST) imaging for fat suppression in renal transplant patients.

METHODS

The 2-pt Dixon-based CEST MRI was validated in an egg-phantom and in fourteen renal transplant recipients (5 females and 9 males; age range: 23-78 years; mean age: 51 ± 16.8). All CEST experiments were performed on a 3 T clinical MRI scanner using a dual-echo CEST sequence. The 2-pt Dixon technique was applied to generate water-only CEST images at different frequency offsets, which were further used to calculate the z-spectra. The magnetization transfer ratio asymmetry (MTR_asym) values in the frequency ranges of hydroxyl, amine and amide protons were estimated in the renal cortex and medulla.

RESULTS

Results of the in vitro experiments suggest that the 2-pt Dixon technique enables effective fat peak removal and does not introduce additional asymmetries to the z-spectrum. Accordingly, our results in vivo show that the fat-corrected amide proton transfer (APT) effect in the kidney is significantly higher compared to that obtained from the CEST data acquired close to the in-phase condition both in the renal cortex (-0.1 [0.7] vs. -0.7 [1.2], P = 0.029) and medulla (0.3 [0.8] vs. 0.01 [1.3], P = 0.049), indicating that the 2-pt Dixon-based CEST method increases the specificity of the APT contrast by correcting the fat-induced artifacts.

CONCLUSION

Combination of the dual-echo CEST acquisition with Dixon post-processing provides effective water-fat separation, allowing more accurate quantification of the APT CEST effect in the transplanted kidney.

Urinary metabolomic profiling from spontaneous tolerant kidney transplanted recipients shows enrichment in tryptophan-derived metabolites

Background

Operational tolerance is the holy grail in solid organ transplantation. Previous reports showed that the urinary compartment of operationally tolerant recipients harbor a specific and unique profile. We hypothesized that spontaneous tolerant kidney transplanted recipients (KTR) would have a specific urinary metabolomic profile associated to operational tolerance.

Methods

We performed metabolomic profiling on urine samples from healthy volunteers, stable KTR under standard and minimal immunosuppression and spontaneous tolerant KTR using liquid chromatography in tandem with mass spectrometry. Supervised and unsupervised multivariate computational analyses were used to highlight urinary metabolomic profile and metabolite identification thanks to workflow4metabolomic platform.

Findings

The urinary metabolome was composed of approximately 2700 metabolites. Raw unsupervised clustering allowed us to separate healthy volunteers and tolerant KTR from others. We confirmed by two methods a specific urinary metabolomic signature in tolerant KTR mainly driven by kynurenic acid independent of immunosuppressive drugs, serum creatinine and gender.

Interpretation

Kynurenic acid and tryptamine enrichment allowed the identification of putative pathways and metabolites associated with operational tolerance like IDO, GRP35 and AhR and indole alkaloids.

Funding

This study was supported by the ANR, IRSRPL and CHU de Nantes.

Impact of Metabolomics Technologies on the Assessment of Peritoneal Membrane Profiles in Peritoneal Dialysis Patients: A Systematic Review

Peritoneal dialysis (PD) is an effective and frequent dialysis modality in adults, particularly preferred in infants and young children with end-stage renal disease (ESRD). Long-term exposure of the peritoneal membrane to dialysis solutions results in severe morphologic and functional alterations. Peritoneal dialysis effluent biomarkers are based on omics technologies, which could predict the onset or confirm the diagnosis of peritoneal membrane dysfunction, would allow the development of accurate early prognostic tools and, potentially, the identification of future therapeutic targets. The purpose of our study was to critically review the literature on the impact and the effectiveness of metabolomics technologies in peritoneal health. The main search was performed in electronic databases (PubMed/MEDLINE, Embase and Cochrane Central Register of Controlled Trials) from inception to December 2020, using various combinations of Medical Subject Headings (MeSH). The main search highlighted nine studies, of which seven were evaluated in detail. Metabolomics technologies may provide significant input in the recognition of peritoneal membrane dysfunction in PD patients and provide evidence of early intervention strategies that could protect peritoneum health and function.

Changes in glomerular filtration rate and metabolomic differences in severely ill coronavirus disease survivors 3 months after discharge

To explore the recovery of renal function in severely ill coronavirus disease (COVID-19) survivors and determine the plasma metabolomic profile of patients with different renal outcomes 3 months after discharge, we included 89 severe COVID-19 survivors who had been discharged from Wuhan Union Hospital for 3 months. All patients had no underlying kidney disease before admission. At patient recruitment, renal function assessment, laboratory examination, chest computed tomography (CT) were performed. Liquid chromatography-mass spectrometry was used to detect metabolites in the plasma. We analyzed the longitudinally change in the estimated glomerular filtration rate (eGFR) based on serum creatinine and cystatin-c levels using the CKD-EPI equation and explored the metabolomic differences in patients with different eGFR change patterns from hospitalization to 3 months after discharge. Lung CT showed good recovery; however, the median eGFR significantly decreased at the 3-month follow-up. Among the 89 severely ill COVID-19 patients, 69 (77.5%) showed abnormal eGFR (<90 mL/min per 1.73 m²) at 3 months after discharge. Age (odds ratio [OR] = 1.26, 95% confidence interval [CI] = 1.08-1.47, p = 0.003), body mass index (OR = 1.97, 95% CI = 1.20-3.22, p = 0.007), and cystatin-c level (OR = 1.22, 95% CI = 1.07-1.39, p = 0.003) at discharge were independent risk factors for post-discharge abnormal eGFR. Plasma metabolomics at the 3-months follow-up revealed that β-pseudouridine, uridine, and 2-(dimethylamino) guanosine levels gradually increased with an abnormal degree of eGFR. Moreover, the kynurenine pathway in tryptophan metabolism, vitamin B6 metabolism, cysteine and methionine metabolism, and arginine biosynthesis were also perturbed in survivors with abnormal eGFR.

Application of machine learning techniques to understand ethnic differences and risk factors for incident chronic kidney disease in Asians

INTRODUCTION

Chronic kidney disease (CKD) is increasing in Asia, but there are sparse data on incident CKD among different ethnic groups. We aimed to describe the incidence and risk factors associated with CKD in the three major ethnic groups in Asia: Chinese, Malays and Indians.

RESEARCH DESIGN AND METHODS

Prospective cohort study of 5580 general population participants age 40-80 years (2234 Chinese, 1474 Malays and 1872 Indians) who completed both baseline and 6-year follow-up visits. Incident CKD was defined as an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m² in those free of CKD at baseline.

RESULTS

The 6-year incidence of CKD was highest among Malays (10.0%), followed by Chinese (6.1%) and Indians (5.8%). Logistic regression showed that older age, diabetes, higher systolic blood pressure and lower eGFR were independently associated with incident CKD in all three ethnic groups, while hypertension and cardiovascular disease were independently associated with incident CKD only in Malays. The same factors were identified by machine learning approaches, gradient boosted machine and random forest to be the most important for incident CKD. Adjustment for clinical and socioeconomic factors reduced the excess incidence in Malays by 60% compared with Chinese but only 13% compared with Indians.

CONCLUSION

Incidence of CKD is high among the main Asian ethnic groups in Singapore, ranging between 6% and 10% over 6 years; differences were partially explained by clinical and socioeconomic factors.

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.

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.

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.

Development and validation of the dialysis dementia risk score: A retrospective, population-based, nested case-control study

Background

Dementia is prevalent and underdiagnosed in the dialysis population. We aimed to develop and validate a simple dialysis dementia scoring system to facilitate identification of individuals who are at high risk for dementia.

Methods

We applied a retrospective, nested case‐control study design using a national dialysis cohort derived from the National Health Insurance Research Database in Taiwan. Patients aged between 40 and 80 years were included and 2940 patients with incident dementia were matched to 29,248 non‐dementia controls. All subjects were randomly divided into the derivation and validation sets with a ratio of 4:1. Conditional logistic regression models were used to identify factors contributing to the risk score. The cutoff value of the risk score was determined by Youden's J statistic and the graphic method.

Results

The dialysis dementia risk score (DDRS) finally included age and 10 comorbidities as risk predictors. The C‐statistic of the model was 0.71 (95% confidence interval [CI] 0.70–0.72). Calibration revealed a strong linear relationship between predicted and observed dementia risk (R² = 0.99). At a cutoff value of 50 points, the high‐risk patients had an approximately three‐fold increased risk of having dementia compared to those with low risk (odds ratio [OR] 3.03, 95% CI 2.78–3.31). The DDRS performance, including discrimination (C‐statistic 0.71, 95% CI 0.69–0.73) and calibration (p value of Hosmer−Lemeshow test for goodness of fit = 0.18), was acceptable during validation. The OR value (2.82, 95% CI 2.37–3.35) was similar to those in the derivation set.

Conclusion

The DDRS system has the potential to serve as an easily accessible screening tool to determine the high‐risk groups who deserve subsequent neurological evaluation in daily clinical practice.

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.

Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses

Kidney diseases still pose one of the biggest challenges for global health, and their heterogeneity and often high comorbidity load seriously hinders the unraveling of their underlying pathomechanisms and the delivery of optimal patient care. Metabolomics, the quantitative study of small organic compounds, called metabolites, in a biological specimen, is gaining more and more importance in nephrology research. Conducting a metabolomics study in human kidney disease cohorts, however, requires thorough knowledge about the key workflow steps: study planning, sample collection, metabolomics data acquisition and preprocessing, statistical/bioinformatics data analysis, and results interpretation within a biomedical context. This review provides a guide for future metabolomics studies in human kidney disease cohorts. We will offer an overview of important a priori considerations for metabolomics cohort studies, available analytical as well as statistical/bioinformatics data analysis techniques, and subsequent interpretation of metabolic findings. We will further point out potential research questions for metabolomics studies in the context of kidney diseases and summarize the main results and data availability of important studies already conducted in this field.

Urinary Spermidine Predicts and Associates with In-Hospital Acute Kidney Injury after Cardiac Surgery

Acute Kidney Injury (AKI) affects up to 30% of the patients who undergo cardiac surgery (CVS) and is related to higher mortality. We aim to investigate molecular features associated with in-hospital AKI development and determine the predictive value of these features when analyzed preoperatively. This is a case-control study. From an initial cohort of 110 recruited subjects, a total of 60 patients undergoing cardiac surgery were included: 20 (33%) developed in-hospital AKI (CVS-AKI) and 40 did not (controls, CVS-C). Pre- and post-surgery samples were collected and a prospective study was carried out. A total of 312 serum samples and 258 urine samples were analyzed by nuclear magnetic resonance, mass spectrometry and ELISA. Six features predicted AKI development in pre-surgery samples: urinary kidney functional loss marker kidney injury molecule-1 (uKIM-1), 2-hydroxybutyric acid, 2-hydroxyphenylacetic acid, hippuric acid, phosphoethanolamine and spermidine. Two of them stood out as powerful predictors. Pre-surgery uKIM-1 levels were increased in CVS-AKI vs. CVS-C (AUC = 0.721, p-value = 0.0392) and associated strongly with the outcome (OR = 5.333, p-value = 0.0264). Spermidine showed higher concentration in CVS-AKI (p-value < 0.0001, AUC = 0.970) and had a strong association with the outcome (OR = 69.75, p-value < 0.0001). uKIM-1 and particularly spermidine predict in-hospital AKI associated with CVS in preoperative samples. These findings may aid in preventing postoperative AKI and improve prognosis of CVS.

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.

Urine Metabolite Levels, Adverse Kidney Outcomes, and Mortality in CKD Patients: A Metabolome-wide Association Study

RATIONALE & OBJECTIVE

Mechanisms underlying the variable course of disease progression in patients with chronic kidney disease (CKD) are incompletely understood. The aim of this study was to identify novel biomarkers of adverse kidney outcomes and overall mortality, which may offer insights into pathophysiologic mechanisms.

STUDY DESIGN

Metabolome-wide association study.

SETTING & PARTICIPANTS

5,087 patients with CKD enrolled in the observational German Chronic Kidney Disease Study.

EXPOSURES

Measurements of 1,487 metabolites in urine.

OUTCOMES

End points of interest were time to kidney failure (KF), a combined end point of KF and acute kidney injury (KF+AKI), and overall mortality.

ANALYTICAL APPROACH

Statistical analysis was based on a discovery-replication design (ratio 2:1) and multivariable-adjusted Cox regression models.

RESULTS

After a median follow-up of 4 years, 362 patients died, 241 experienced KF, and 382 experienced KF+AKI. Overall, we identified 55 urine metabolites whose levels were significantly associated with adverse kidney outcomes and/or mortality. Higher levels of C-glycosyltryptophan were consistently associated with all 3 main end points (hazard ratios of 1.43 [95% CI, 1.27-1.61] for KF, 1.40 [95% CI, 1.27-1.55] for KF+AKI, and 1.47 [95% CI, 1.33-1.63] for death). Metabolites belonging to the phosphatidylcholine pathway showed significant enrichment. Members of this pathway contributed to the improvement of the prediction performance for KF observed when multiple metabolites were added to the well-established Kidney Failure Risk Equation.

LIMITATIONS

Findings among patients of European ancestry with CKD may not be generalizable to the general population.

CONCLUSIONS

Our comprehensive screen of the association between urine metabolite levels and adverse kidney outcomes and mortality identifies metabolites that predict KF and represents a valuable resource for future studies of biomarkers of CKD progression.

Oxidative stress increases 1-deoxysphingolipid levels in chronic kidney disease

Chronic kidney disease (CKD) leads to deep changes in lipid metabolism and obvious dyslipidemia. The dysregulation of lipid metabolism in turn results in CKD progression and the complications of cardiovascular diseases. To obtain a profound insight into the associated dyslipidemia in CKD, we performed lipidomic analysis to measure lipid metabolites in the serum from a rat 5/6 nephrectomy (5/6 Nx) model of CKD as well as in the serum from CKD patients. HK-2 cells were also used to examine oxidative stress-induced sphingolipid changes. Totally 182 lipid species were identified in 5/6 Nx rats. We found glycerolipids, total free fatty acids, and sphingolipids levels were significantly upregulated in 5/6 Nx rats. The atypical sphingolipids, 1-deoxysphingolipids, were significantly altered in both CKD animals and human CKD patients. The levels of 1-deoxysphingolipids directly relevant to the level of oxidative stress in vivo and in vitro. These results demonstrate that 1-deoxysphingolipid levels are increased in CKD and this increase directly correlates with increased kidney oxidative stress.

Polyamine biomarkers as indicators of human disease

The significant increase of periodontitis, chronic kidney disease (CKD), Alzheimer's disease and cancer can be attributed to an ageing population. Each disease produces a range of biomarkers that can be indicative of disease onset and progression. Biomarkers are defined as cellular (intra/extracellular components and whole cells), biochemical (metabolites, ions and toxins) or molecular (nucleic acids, proteins and lipids) alterations which are measurable in biological media such as human tissues, cells or fluids. An interesting group of biomarkers that merit further investigation are the polyamines. Polyamines are a group of molecules consisting of cadaverine, putrescine, spermine and spermidine and have been implicated in the development of a range of systemic diseases, in part due to their production in periodontitis. Cadaverine and putrescine within the periodontal environment have demonstrated cell signalling interfering abilities, by way of leukocyte migration disruption. The polyamines spermine and spermidine in tumour cells have been shown to inhibit cellular apoptosis, effectively prolonging tumorigenesis and continuation of cancer within the host. Polyamine degradation products such as acrolein have been shown to exacerbate renal damage in CKD patients. Thus, the use of such molecules has merit to be utilized in the early indication of such diseases in patients.

Plasma metabolites associated with chronic kidney disease and renal function in adults from the Baltimore Longitudinal Study of Aging

INTRODUCTION

Chronic kidney disease (CKD) is an important cause of disability and death, but its pathogenesis is poorly understood. Plasma metabolites can provide insights into underlying processes associated with CKD.

OBJECTIVES

To clarify the relationship of plasma metabolites with CKD and renal function in human.

METHODS

We used a targeted metabolomics approach to characterize the relationship of 450 plasma metabolites with CKD and estimated glomerular filtration rate (eGFR) in 616 adults, aged 38-94 years, who participated in the Baltimore Longitudinal Study of Aging.

RESULTS

There were 74 (12.0%) adults with CKD. Carnitine, acetylcarnitine, propionylcarnitine, butyrylcarnitine, trigonelline, trimethylamine N-oxide (TMAO), 1-methylhistidine, citrulline, homoarginine, homocysteine, sarcosine, symmetric dimethylarginine, aspartate, phenylalanine, taurodeoxycholic acid, 3-indolepropionic acid, phosphatidylcholines (PC).aa.C40:2, PC.aa.C40:3, PC.ae.C40:6, triglycerides (TG) 20:4/36:3, TG 20:4/36:4, and choline were associated with higher odds of CKD in multivariable analyses adjusting for potential confounders and using a false discovery rate (FDR) to address multiple testing. Six acylcarnitines, trigonelline, TMAO, 18 amino acids and biogenic amines, taurodeoxycholic acid, hexoses, cholesteryl esters 22:6, dehydroepiandrosterone sulfate, 3-indolepropionic acid, 2 PCs, 17 TGs, and choline were negatively associated with eGFR, and hippuric acid was positively associated with eGFR in multivariable analyses adjusting for potential confounders and using a FDR approach.

CONCLUSION

The metabolites associated with CKD and reduced eGFR suggest that several pathways, such as the urea cycle, the arginine-nitric oxide pathway, the polyamine pathway, and short chain acylcarnitine metabolism are altered in adults with CKD and impaired renal function.

Machine Learning Approaches Reveal Metabolic Signatures of Incident Chronic Kidney Disease in Individuals With Prediabetes and Type 2 Diabetes

Early and precise identification of individuals with prediabetes and type 2 diabetes (T2D) at risk for progressing to chronic kidney disease (CKD) is essential to prevent complications of diabetes. Here, we identify and evaluate prospective metabolite biomarkers and the best set of predictors of CKD in the longitudinal, population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort by targeted metabolomics and machine learning approaches. Out of 125 targeted metabolites, sphingomyelin C18:1 and phosphatidylcholine diacyl C38:0 were identified as candidate metabolite biomarkers of incident CKD specifically in hyperglycemic individuals followed during 6.5 years. Sets of predictors for incident CKD developed from 125 metabolites and 14 clinical variables showed highly stable performances in all three machine learning approaches and outperformed the currently established clinical algorithm for CKD. The two metabolites in combination with five clinical variables were identified as the best set of predictors, and their predictive performance yielded a mean area value under the receiver operating characteristic curve of 0.857. The inclusion of metabolite variables in the clinical prediction of future CKD may thus improve the risk prediction in people with prediabetes and T2D. The metabolite link with hyperglycemia-related early kidney dysfunction warrants further investigation.

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

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

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

The discovery of metabolomics-based biomarkers has been a focus of recent kidney dysfunction research. In the present study, we aimed to identify metabolites associated with chronic kidney disease (CKD) in the general population using a cross-sectional study design. At baseline, 6.5% of subjects had CKD. Pearson correlation analysis showed that 28 metabolites were significantly associated with estimated glomerular filtration rate (eGFR) after Bonferroni correction. Among these metabolites, 4 acylcarnitines, 12 amino acids, 4 biogenic amines, 1 phosphatidylcholine, and 1 sphingolipid were associated with CKD (p < 0.05). After eight years, 13.5% of subjects had CKD. Three amino acid metabolites were positively associated with new-onset CKD: citrulline [odds ratio (OR): 2.41, 95% confidence interval (CI): 1.26–4.59], kynurenine (OR: 1.98, 95% CI: 1.05–3.73), and phenylalanine (OR: 2.68, 95% CI: 1.00–7.16). The kynurenine:tryptophan ratio was also associated with CKD (OR: 3.20; 95% CI: 1.57–6.51). The addition of multiple metabolites significantly improved the CKD prediction by C statistics (0.756–0.85, p < 0.0001), and the net reclassification improvement was 0.84 (95% CI: 0.72–0.96). Elevated hs-C reactive protein (CRP) was associated with new-onset CKD (OR: 1.045, 95% CI: 1.005–1.086); however, this association disappeared following adjustment with the kynurenine:tryptophan ratio. The levels of citrulline and kynurenine and their ratio to tryptophan in CKD patients with proteinuria were worse than those with one or neither characteristic. Together, the results of this study demonstrate that amino acid metabolites are associated with CKD eight years after initial metabolite assessment. These results could improve the identification of subjects at high risk of CKD who have modified amino acid metabolism.

Urine 6-Bromotryptophan: Associations with Genetic Variants and Incident End-Stage Kidney Disease

Higher serum 6-bromotryptophan has been associated with lower risk of chronic kidney disease (CKD) progression, implicating mechanisms beyond renal clearance. We studied genetic determinants of urine 6-bromotryptophan and its association with CKD risk factors and incident end-stage kidney disease (ESKD) in 4,843 participants of the German Chronic Kidney Disease (GCKD) study. 6-bromotryptophan was measured from urine samples using mass spectrometry. Patients with higher levels of urine 6-bromotryptophan had higher baseline estimated glomerular filtration rate (eGFR, p < 0.001). A genome-wide association study of urine 6-bromotryptophan identified two significant loci possibly related to its tubular reabsorption, SLC6A19, and its production, ERO1A, which was also associated with serum 6-bromotryptophan in an independent study. The association between urine 6-bromotryptophan and time to ESKD was assessed using Cox regression. There were 216 ESKD events after four years of follow-up. Compared with patients with undetectable levels, higher 6-bromotryptophan levels were associated with lower risk of ESKD in models unadjusted and adjusted for ESKD risk factors other than eGFR ( Collapse

Key Words

• prognostic markers
• kidney diseases
• biomarkers
• epidemiology
• genetics research
• outcomes research
• risk factors

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MESH Headings

• Amino Acid Transport Systems, Neutral/genetics
• Female
• Genetic Predisposition to Disease/genetics
• Genetic Variation/genetics
• Glomerular Filtration Rate/genetics
• Humans
• Kidney Failure, Chronic/epidemiology
• Kidney Failure, Chronic/genetics
• Kidney Failure, Chronic/urine
• Male
• Membrane Glycoproteins/genetics
• Middle Aged
• Oxidoreductases/genetics
• Proportional Hazards Models
• Risk Factors
• Tryptophan/analogs & derivatives
• Tryptophan/urine

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Grants

• R21 DK112087 NIDDK NIH HHS
• UL1 RR025005 NCRR NIH HHS
• R01 HL086694 NHLBI NIH HHS
• U01 HG004402 NHGRI NIH HHS
• HHSN268201700002C NHLBI NIH HHS
• HHSN268201700001I NHLBI NIH HHS
• HHSN268201700004I NHLBI NIH HHS
• HHSN268201700004C NHLBI NIH HHS
• R01 HL087641 NHLBI NIH HHS
• HHSN268201700003I NHLBI NIH HHS
• HHSN268201700005C NHLBI NIH HHS
• HHSN268201700001C NHLBI NIH HHS
• HHSN268201700003C NHLBI NIH HHS
• HHSN268201700002I NHLBI NIH HHS
• HHSN268201700005I NHLBI NIH HHS

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Affiliation(s)

Peggy Sekula Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
Adrienne Tin Division of Nephrology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA The Memory Impairment and Neurodegenerative Dementia Center, University of Mississippi Medical Center, Jackson, MS, USA
Ulla T Schultheiss Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany Division of Nephrology, Department of Medicine, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
Seema Baid-Agrawal Department of Nephrology and Transplant Center, Sahlgrenska University Hospital, University of Gothenburg, Gothenburg, Sweden
Robert P Mohney Metabolon Inc., Durham, NC, USA
Inga Steinbrenner Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
Bing Yu School of Public Health, The University of Texas Health Science Center at Houston, Houston, USA
Shengyuan Luo Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
Eric Boerwinkle School of Public Health, The University of Texas Health Science Center at Houston, Houston, USA
Kai-Uwe Eckardt Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany Department of Nephrology and Hypertension, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054, Erlangen, Germany
Josef Coresh Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
Morgan E Grams Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA Division of Nephrology, Johns Hopkins School of Medicine, Baltimore, MD, USA
Anna Kӧttgen Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

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Machine learning distilled metabolite biomarkers for early stage renal injury

INTRODUCTION

With chronic kidney disease (CKD), kidney becomes damaged overtime and fails to clean blood. Around 15% of US adults have CKD and nine in ten adults with CKD do not know they have it.

OBJECTIVE

Early prediction and accurate monitoring of CKD may improve care and decrease the frequent progression to end-stage renal disease. There is an urgent demand to discover specific biomarkers that allow for monitoring of early-stage CKD, and response to treatment.

METHOD

To discover such biomarkers, shotgun high throughput was applied to the detection of serum metabolites biomarker discovery for early stages of CKD from 703 participants. Ultra performance liquid chromatography coupled with high-definition mass spectrometry (UPLC-HDMS)-based metabolomics was used for the determination of 703 fasting serum samples from five stages of CKD patients and age-matched healthy controls.

RESULTS AND CONCLUSION

We discovered a set of metabolite biomarkers using a series of classic and neural network based machine learning techniques. This set of metabolites can separate early CKD stage patents from normal subjects with high accuracy. Our study illustrates the power of machine learning methods in metabolite biomarker study.

Indoxyl sulfate associates with cardiovascular phenotype in children with chronic kidney disease

BACKGROUND

Cardiovascular disease is the leading cause of death in children with chronic kidney disease (CKD). Serum levels of gut-derived uremic toxins increase with deterioration of kidney function and are associated with cardiac comorbidities in adult CKD patients.

METHODS

Indoxyl sulfate (IS) and p-cresyl sulfate (pCS) were measured by high-performance liquid chromatography in serum of children participating in the Cardiovascular Comorbidity in Children with CKD (4C) Study. Results were correlated with measurements of the carotid intima-media thickness (cIMT), central pulse wave velocity (PWV), and left ventricular mass index (LVMI) in children aged 6-17 years with initial eGFR of 10-60 ml/min per 1.73 m².

RESULTS

The median serum levels of total IS and of pCS, measured in 609 patients, were 5.3 μmol/l (8.7) and 17.0 μmol/l (21.6), respectively. In a multivariable regression model, IS and pCS showed significant positive associations with urea and negative associations with eGFR and uric acid. Furthermore, positive associations of pCS with age, serum albumin, and non-Mediterranean residency and a negative association with glomerular disease were observed. By multivariable regression analysis, only IS was significantly associated with a higher cIMT SDS at baseline and progression of PWV SDS within 12 months, independent of other risk factors.

CONCLUSIONS

Serum levels of gut-derived uremic toxins IS and pCS correlated inversely with eGFR in children. Only IS was significantly associated with surrogate markers of cardiovascular disease in this large pediatric CKD cohort.

Microbiome-metabolomics reveals gut microbiota associated with glycine-conjugated metabolites and polyamine metabolism in chronic kidney disease

Dysbiosis of the gut microbiome and related metabolites in chronic kidney disease (CKD) have been intimately associated with the prevalence of cardiovascular diseases. Unfortunately, thus far, there is a paucity of sufficient knowledge of gut microbiome and related metabolites on CKD progression partly due to the severely limited investigations. Using a 5/6 nephrectomized (NX) rat model, we carried out 16S rRNA sequence and untargeted metabolomic analyses to explore the relationship between colon's microbiota and serum metabolites. Marked decline in microbial diversity and richness was accompanied by significant changes in 291 serum metabolites, which were mediated by altered enzymatic activities and dysregulations of lipids, amino acids, bile acids and polyamines metabolisms. Interestingly, CCr was directly associated with some microbial genera and polyamine metabolism. However, SBP was directly related to certain microbial genera and glycine-conjugated metabolites in CKD rats. Administration of poricoic acid A (PAA) and Poria cocos (PC) ameliorated microbial dysbiosis as well as attenuated hypertension and renal fibrosis. In addition, treatments with PAA and PC lowered serum levels of microbial-derived products including glycine-conjugated compounds and polyamine metabolites. Collectively, the present study confirmed the CKD-associated gut microbial dysbiosis and identified a novel dietary and therapeutic strategy to improve the gut microbial dysbiosis and the associated metabolomic disorders and retarded the progression of kidney disease in the rat model of CKD.

Novel associations between blood metabolites and kidney function among Bogalusa Heart Study and Multi-Ethnic Study of Atherosclerosis participants

INTRODUCTION

Chronic kidney disease (CKD) is a major public health challenge given its high global prevalence and associated risks of cardiovascular disease and progression to end stage renal disease. Although it is known that numerous metabolic changes occur in CKD patients, identifying novel metabolite associations with kidney function may enhance our understanding of the physiologic pathways relating to CKD.

OBJECTIVES

The objective of this study was to elucidate novel metabolite associations with kidney function among participants of two community-based cohorts with carefully ascertained metabolomics, kidney function, and covariate data.

METHODS

Untargeted ultrahigh-performance liquid chromatography-tandem mass spectrometry was used to detect and quantify blood metabolites. We used multivariate adjusted linear regression to examine associations between single metabolites and creatinine-based estimated glomerular filtration rate (eGFRcr) among 1243 Bogalusa Heart Study (BHS) participants (median eGFRcr: 94.4, 5th-95th percentile: 66.0-119.6 mL/min/1.73 m²). Replication, determined by statistical significance and consistent effect direction, was tested using gold standard measured glomerular filtration rate (mGFR) among 260 Multi-Ethnic Study of Atherosclerosis (MESA) participants (median mGFR: 72.0, 5th-95th percentile: 43.5-105.0 mL/min/1.73 m²). All analyses used Bonferroni-corrected alpha thresholds.

RESULTS

Fifty-one novel metabolite associations with kidney function were identified, including 12 from previously unrelated sub-pathways: N6-carboxymethyllysine, gulonate, quinolinate, gamma-CEHC-glucuronide, retinol, methylmalonate, 3-hydroxy-3-methylglutarate, 3-aminoisobutyrate, N-methylpipecolate, hydroquinone sulfate, and glycine conjugates of C₁₀H₁₂O₂ and C₁₀H₁₄O₂(1). Significant metabolites were generally inversely associated with kidney function and smaller in mass-to-charge ratio than non-significant metabolites.

CONCLUSION

The 51 novel metabolites identified may serve as early, clinically relevant, kidney function biomarkers.

NAD+ homeostasis in renal health and disease

The mammalian kidney relies on abundant mitochondria in the renal tubule to generate sufficient ATP to provide the energy required for constant reclamation of solutes from crude blood filtrate. The highly metabolically active cells of the renal tubule also pair their energetic needs to the regulation of diverse cellular processes, including energy generation, antioxidant responses, autophagy and mitochondrial quality control. Nicotinamide adenine dinucleotide (NAD⁺) is essential not only for the harvesting of energy from substrates but also for an array of regulatory reactions that determine cellular health. In acute kidney injury (AKI), substantial decreases in the levels of NAD⁺ impair energy generation and, ultimately, the core kidney function of selective solute transport. Conversely, augmentation of NAD⁺ may protect the kidney tubule against diverse acute stressors. For example, NAD⁺ augmentation can ameliorate experimental AKI triggered by ischaemia–reperfusion, toxic injury and systemic inflammation. NAD⁺-dependent maintenance of renal tubular metabolic health may also attenuate long-term profibrotic responses that could lead to chronic kidney disease. Further understanding of the genetic, environmental and nutritional factors that influence NAD⁺ biosynthesis and renal resilience may lead to novel approaches for the prevention and treatment of kidney disease.

Here, the authors discuss evidence for a role of NAD⁺ imbalance in the pathogenesis of acute kidney injury (AKI) and chronic kidney disease (CKD). They suggest that disruption of NAD⁺ metabolism may contribute to mechanistic links among AKI, CKD and ageing.

NAD⁺ has critical roles in the generation of ATP from fuel substrates and as a substrate for important enzymes that regulate cellular health and stress responses.

The renal tubule is highly metabolically active and requires a constant supply of ATP to provide the energy required to pump solutes across unfavourable gradients.

Experimental acute kidney injury (AKI) induced by various insults rapidly leads to a decrease in NAD⁺ levels that probably results from a combination of reduced NAD⁺ biosynthesis and increased NAD⁺ consumption.

Renal NAD⁺ levels can be augmented using vitamin B₃ analogues and related nutritional precursors.

NAD⁺ augmentation can prevent and/or treat various aetiologies of experimental AKI and might also attenuate long-term profibrotic responses following AKI, suggesting a potential role in the treatment of chronic kidney disease.

Chronic kidney disease: Biomarker diagnosis to therapeutic targets

Chronic kidney disease (CKD), characterized as renal dysfunction, is recognized as a major public health problem with high morbidity and mortality worldwide. Unfortunately, there are no obvious clinical symptoms in early stage disease until severe damage has occurred. Further complicating early diagnosis and treatment is the lack of sensitive and specific biomarkers. As such, novel biomarkers are urgently needed. Metabolomics has shown an increasing potential for identifying underlying disease mechanisms, facilitating clinical diagnosis and developing pharmaceutical treatments for CKD. Recent advances in metabolomics revealed that CKD was closely associated with the dysregulation of numerous metabolites, such as amino acids, lipids, nucleotides and glycoses, that might be exploited as potential biomarkers. In this review, we summarize recent metabolomic applications based on animal model studies and in patients with CKD and highlight several biomarkers that may play important roles in diagnosis, intervention and development of new therapeutic strategies.

The gut microbiota and the brain-gut-kidney axis in hypertension and chronic kidney disease

Crosstalk between the gut microbiota and the host has attracted considerable attention owing to its involvement in diverse diseases. Chronic kidney disease (CKD) is commonly associated with hypertension and is characterized by immune dysregulation, metabolic disorder and sympathetic activation, which are all linked to gut dysbiosis and altered host-microbiota crosstalk. In this Review, we discuss the complex interplay between the brain, the gut, the microbiota and the kidney in CKD and hypertension and explain our brain-gut-kidney axis hypothesis for the pathogenesis of these diseases. Consideration of the role of the brain-gut-kidney axis in the maintenance of normal homeostasis and of dysregulation of this axis in CKD and hypertension could lead to the identification of novel therapeutic targets. In addition, the discovery of unique microbial communities and their associated metabolites and the elucidation of brain-gut-kidney signalling are likely to fill fundamental knowledge gaps leading to innovative research, clinical trials and treatments for CKD and hypertension.

Tissue, urine and blood metabolite signatures of chronic kidney disease in the 5/6 nephrectomy rat model

INTRODUCTION

Progressive chronic kidney disease (CKD) is an important cause of morbidity and mortality. It has a long asymptomatic phase, where routine blood tests cannot identify early functional losses, and therefore identifying common mechanisms across the many etiologies is an important goal.

OBJECTIVES

Our aim was to characterize serum, urine and tissue (kidney, lung, heart, spleen and liver) metabolomics changes in a rat model of CKD.

METHODS

A total of 17 male Wistar rats underwent 5/6 nephrectomy, whilst 13 rats underwent sham operation. Urine samples were collected weekly, for 6 weeks; blood was collected at weeks 0, 3 and 6; and tissue samples were collected at week 6. Samples were analyzed on a nuclear magnetic resonance spectroscopy platform with multivariate and univariate data analysis.

RESULTS

Changes in several metabolites were statistically significant. Allantoin was affected in all compartments. Renal asparagine, creatine, hippurate and trimethylamine were significantly different; in other tissues creatine, dimethylamine, dimethylglycine, trigonelline and trimethylamine were significant. Benzoate, citrate, dimethylglycine, fumarate, guanidinoacetate, malate, myo-inositol and oxoglutarate were altered in urine or serum.

CONCLUSION

Although the metabolic picture is complex, we suggest oxidative stress, the gut-kidney axis, acid-base balance, and energy metabolism as promising areas for future investigation.

Metabolic signature associated with parameters of the complete blood count in apparently healthy individuals

Metabolomics studies now approach large sample sizes and the health characterization of the study population often include complete blood count (CBC) results. Upon careful interpretation the CBC aids diagnosis and provides insight into the health status of the patient within a clinical setting. Uncovering metabolic signatures associated with parameters of the CBC in apparently healthy individuals may facilitate interpretation of metabolomics studies in general and related to diseases. For this purpose 879 subjects from the population‐based Study of Health in Pomerania (SHIP)‐TREND were included. Using metabolomics data resulting from mass‐spectrometry based measurements in plasma samples associations of specific CBC parameters with metabolites were determined by linear regression models. In total, 118 metabolites significantly associated with at least one of the CBC parameters. Strongest associations were observed with metabolites of heme degradation and energy production/consumption. Inverse association seen with mean corpuscular volume and mean corpuscular haemoglobin comprised metabolites potentially related to kidney function. The presently identified metabolic signatures are likely derived from the general function and formation/elimination of blood cells. The wealth of associated metabolites strongly argues to consider CBC in the interpretation of metabolomics studies, in particular if mutual effects on those parameters by the disease of interest are known.

An update of urine and blood metabolomics in chronic kidney disease

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

Metabolomic profiling to improve glomerular filtration rate estimation: a proof-of-concept study

BACKGROUND

Estimation of glomerular filtration rate (GFR) using estimated glomerular filtration rate creatinine (eGFRcr) is central to clinical practice but has limitations. We tested the hypothesis that serum metabolomic profiling can identify novel markers that in combination can provide more accurate GFR estimates.

METHODS

We performed a cross-sectional study of 200 African American Study of Kidney Disease and Hypertension (AASK) and 265 Multi-Ethnic Study of Atherosclerosis (MESA) participants with measured GFR (mGFR). Untargeted gas chromatography/dual mass spectrometry- and liquid chromatography/dual mass spectrometry-based quantification was followed by the development of targeted assays for 15 metabolites. On the log scale, GFR was estimated from single- and multiple-metabolite panels and compared with eGFR using the Chronic Kidney Disease Epidemiology equations with creatinine and/or cystatin C using established metrics, including the proportion of errors >30% of mGFR (1-P30), before and after bias correction.

RESULTS

Of untargeted metabolites in the AASK and MESA, 283 of 780 (36%) and 387 of 1447 (27%), respectively, were significantly correlated (P ≤ 0.001) with mGFR. A targeted metabolite panel eGFR developed in the AASK and validated in the MESA was more accurate (1-P30 3.7 and 1.9%, respectively) than eGFRcr [11.2 and 18.5%, respectively (P < 0.001 for both)] and estimating GFR using cystatin C (eGFRcys) [10.6% (P = 0.02) and 9.1% (P < 0.05), respectively] but was not consistently better than eGFR using both creatinine and cystatin C [3.7% (P > 0.05) and 9.1% (P < 0.05), respectively]. A panel excluding creatinine and demographics still performed well [1-P30 6.4% (P = 0.11) and 3.4% (P < 0.001) in the AASK and MESA] versus eGFRcr.

CONCLUSIONS

Multimetabolite panels can enable accurate GFR estimation. Metabolomic equations, preferably excluding creatinine and demographic characteristics, should be tested for robustness and generalizability as a potential confirmatory test when eGFRcr is unreliable.