Metabolomics Approaches for the Understanding, Diagnosis and Monitoring of Chronic Kidney Diseases

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Integrative Metabolomics".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 26097

Special Issue Editor

Institute of Genetic Epidemiology, Universität Freiburg im Breisgau, Freiburg im Breisgau, Germany
Interests: (genetic) epidemiology; chronic kidney diseases; metabolites

Special Issue Information

Dear Colleagues,

Chronic kidney disease (CKD) represents a global public health burden due to its high prevalence and increasing incidence. Kidney function is described by estimating glomerular filtration rate (GFR) and is used to diagnose CKD and estimate its stage. There are different causes of CKD. During the course of disease, CKD patients may suffer from progression and some may eventually experience kidney failure (KF). In addition, patients are at high risk of morbidity and mortality, such as acute kidney injury and cardiovascular events. In spite of the global health burden, the understanding of (patho-)physiology in healthy and diseased humans is incomplete.

Due to the roles of the kidneys, there is a close link to the human metabolome. Among others, kidneys not only filtrate metabolites present in the blood but also generate metabolites themselves (anabolism), break them down (catabolism) and actively secrete or reabsorb them along the nephron. Evaluation of the metabolome are thus of high interest to the field of nephrology. Among others, the areas of interest in research are:

  • Identification of novel/complementary filtration markers: For the estimation of GFR, serum creatinine levels are commonly used. However, due to the limitations of serum creatinine as a filtration marker, estimations of GFR can be inaccurate and thereby the diagnosis and stage of CKD.
  • Identification of causes of CKD: Metabolites may be causal for the development of kidney diseases, such as chronically increased levels of blood glucose as a cause of diabetic kidney disease. Metabolites may thus help to differentiate CKD patients.
  • Identification of novel/complementary risk factors for CKD and CKD progression: Research can reveal metabolites as useful markers of severity and progression in addition to known markers. They may even allow the improvement in the prediction of CKD patients at high risk for progression and adverse outcomes.
  • Assessment of metabolites in advanced CKD: Due to the decreased kidney function, some metabolites accumulate in the human body and may affect various systems in the human body (uremic toxins).

This Special Issue of Metabolites will be dedicated to, but is not limited to, topics around metabolites and CKD as described above. Objects of research could include humans, animals, and cell cultures, among others. The scientific community is also invited to provide overview papers and discussions related to methodological challenges.

Dr. Peggy Sekula
Guest Editor

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Keywords

  • chronic kidney disease 
  • cause, diagnosis, prognosis 
  • biomarker 
  • metabolite

Published Papers (9 papers)

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Research

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18 pages, 32045 KiB  
Article
Assessment of Physiological Rat Kidney Ageing—Implications for the Evaluation of Allograft Quality Prior to Renal Transplantation
by Andreas Baumgartner, Simone Reichelt-Wurm, Wolfram Gronwald, Claudia Samol, Josef A. Schröder, Claudia Fellner, Kathrin Holler, Andreas Steege, Franz Josef Putz, Peter J. Oefner, Bernhard Banas and Miriam C. Banas
Metabolites 2022, 12(2), 162; https://doi.org/10.3390/metabo12020162 - 08 Feb 2022
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Abstract
Due to organ shortage and rising life expectancy the age of organ donors and recipients is increasing. Reliable biomarkers of organ quality that predict successful long-term transplantation outcomes are poorly defined. The aim of this study was the identification of age-related markers of [...] Read more.
Due to organ shortage and rising life expectancy the age of organ donors and recipients is increasing. Reliable biomarkers of organ quality that predict successful long-term transplantation outcomes are poorly defined. The aim of this study was the identification of age-related markers of kidney function that might accurately reflect donor organ quality. Histomorphometric, biochemical and molecular parameters were measured in young (3-month-old) and old (24-month-old) male Sprague Dawley rats. In addition to conventional methods, we used urine metabolomics by NMR spectroscopy and gene expression analysis by quantitative RT-PCR to identify markers of ageing relevant to allograft survival. Beside known markers of kidney ageing like albuminuria, changes in the concentration of urine metabolites such as trimethylamine-N-oxide, trigonelline, 2-oxoglutarate, citrate, hippurate, glutamine, acetoacetate, valine and 1-methyl-histidine were identified in association with ageing. In addition, expression of several genes of the toll-like receptor (TLR) pathway, known for their implication in inflammaging, were upregulated in the kidneys of old rats. This study led to the identification of age-related markers of biological allograft age potentially relevant for allograft survival in the future. Among those, urine metabolites and markers of immunity and inflammation, which are highly relevant to immunosuppression in transplant recipients, are promising and deserve further investigation in humans. Full article
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31 pages, 6262 KiB  
Article
Urinary Metabolomic Changes Accompanying Albuminuria Remission following Gastric Bypass Surgery for Type 2 Diabetic Kidney Disease
by William P. Martin, Daniel Malmodin, Anders Pedersen, Martina Wallace, Lars Fändriks, Cristina M. Aboud, Tarissa B. Zanata Petry, Lívia P. Cunha da Silveira, Ana C. Calmon da Costa Silva, Ricardo V. Cohen, Carel W. le Roux and Neil G. Docherty
Metabolites 2022, 12(2), 139; https://doi.org/10.3390/metabo12020139 - 02 Feb 2022
Cited by 6 | Viewed by 2738
Abstract
In the Microvascular Outcomes after Metabolic Surgery randomised clinical trial (MOMS RCT, NCT01821508), combined metabolic surgery (gastric bypass) plus medical therapy (CSM) was superior to medical therapy alone (MTA) as a means of achieving albuminuria remission at 2-year follow-up in patients with obesity [...] Read more.
In the Microvascular Outcomes after Metabolic Surgery randomised clinical trial (MOMS RCT, NCT01821508), combined metabolic surgery (gastric bypass) plus medical therapy (CSM) was superior to medical therapy alone (MTA) as a means of achieving albuminuria remission at 2-year follow-up in patients with obesity and early diabetic kidney disease (DKD). In the present study, we assessed the urinary 1H-NMR metabolome in a subgroup of patients from both arms of the MOMS RCT at baseline and 6-month follow-up. Whilst CSM and MTA both reduced the urinary excretion of sugars, CSM generated a distinctive urinary metabolomic profile characterised by increases in host–microbial co-metabolites (N-phenylacetylglycine, trimethylamine N-oxide, and 4-aminobutyrate (GABA)) and amino acids (arginine and glutamine). Furthermore, reductions in aromatic amino acids (phenylalanine and tyrosine), as well as branched-chain amino acids (BCAAs) and related catabolites (valine, leucine, 3-hydroxyisobutyrate, 3-hydroxyisovalerate, and 3-methyl-2-oxovalerate), were observed following CSM but not MTA. Improvements in BMI did not correlate with improvements in metabolic and renal indices following CSM. Conversely, urinary metabolites changed by CSM at 6 months were moderately to strongly correlated with improvements in blood pressure, glycaemia, triglycerides, and albuminuria up to 24 months following treatment initiation, highlighting the potential involvement of these shifts in the urinary metabolomic profile in the metabolic and renoprotective effects of CSM. Full article
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13 pages, 921 KiB  
Article
Estimated Renal Metabolomics at Reperfusion Predicts One-Year Kidney Graft Function
by Thomas Verissimo, Anna Faivre, Sebastian Sgardello, Maarten Naesens, Sophie de Seigneux, Gilles Criton and David Legouis
Metabolites 2022, 12(1), 57; https://doi.org/10.3390/metabo12010057 - 10 Jan 2022
Cited by 1 | Viewed by 1969
Abstract
Renal transplantation is the gold-standard procedure for end-stage renal disease patients, improving quality of life and life expectancy. Despite continuous advancement in the management of post-transplant complications, progress is still needed to increase the graft lifespan. Early identification of patients at risk of [...] Read more.
Renal transplantation is the gold-standard procedure for end-stage renal disease patients, improving quality of life and life expectancy. Despite continuous advancement in the management of post-transplant complications, progress is still needed to increase the graft lifespan. Early identification of patients at risk of rapid graft failure is critical to optimize their management and slow the progression of the disease. In 42 kidney grafts undergoing protocol biopsies at reperfusion, we estimated the renal metabolome from RNAseq data. The estimated metabolites’ abundance was further used to predict the renal function within the first year of transplantation through a random forest machine learning algorithm. Using repeated K-fold cross-validation we first built and then tuned our model on a training dataset. The optimal model accurately predicted the one-year eGFR, with an out-of-bag root mean square root error (RMSE) that was 11.8 ± 7.2 mL/min/1.73 m2. The performance was similar in the test dataset, with a RMSE of 12.2 ± 3.2 mL/min/1.73 m2. This model outperformed classic statistical models. Reperfusion renal metabolome may be used to predict renal function one year after allograft kidney recipients. Full article
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27 pages, 5832 KiB  
Article
Lipidomic and Metabolomic Signature of Progression of Chronic Kidney Disease in Patients with Severe Obesity
by Borja Lanzon, Marina Martin-Taboada, Victor Castro-Alves, Rocio Vila-Bedmar, Ignacio González de Pablos, Daniel Duberg, Pilar Gomez, Elias Rodriguez, Matej Orešič, Tuulia Hyötyläinen, Enrique Morales, Francisco J. Ruperez and Gema Medina-Gomez
Metabolites 2021, 11(12), 836; https://doi.org/10.3390/metabo11120836 - 03 Dec 2021
Cited by 18 | Viewed by 3855
Abstract
Severe obesity is a major risk for chronic kidney disease (CKD). Early detection and careful monitoring of renal function are critical for the prevention of CKD during obesity, since biopsies are not performed in patients with CKD and diagnosis is dependent on the [...] Read more.
Severe obesity is a major risk for chronic kidney disease (CKD). Early detection and careful monitoring of renal function are critical for the prevention of CKD during obesity, since biopsies are not performed in patients with CKD and diagnosis is dependent on the assessment of clinical parameters. To explore whether distinct lipid and metabolic signatures in obesity may signify early stages of pathogenesis toward CKD, liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-high resolution accurate mass-mass spectrometry (GC-HRAM-MS) analyses were performed in the serum and the urine of severely obese patients with and without CKD. Moreover, the impact of bariatric surgery (BS) in lipid and metabolic signature was also studied, through LC-MS and GC-HRAM-MS analyses in the serum and urine of patients with severe obesity and CKD before and after undergoing BS. Regarding patients with severe obesity and CKD compared to severely obese patients without CKD, serum lipidome analysis revealed significant differences in lipid signature. Furthermore, serum metabolomics profile revealed significant changes in specific amino acids, with isoleucine and tyrosine, increased in CKD patients compared with patients without CKD. LC-MS and GC-HRAM-MS analysis in serum of patients with severe obesity and CKD after BS showed downregulation of levels of triglycerides (TGs) and diglycerides (DGs) as well as a decrease in branched-chain amino acid (BCAA), lysine, threonine, proline, and serine. In addition, BS removed most of the correlations in CKD patients against biochemical parameters related to kidney dysfunction. Concerning urine analysis, hippuric acid, valine and glutamine were significantly decreased in urine from CKD patients after surgery. Interestingly, bariatric surgery did not restore all the lipid species, some of them decreased, hence drawing attention to them as potential targets for early diagnosis or therapeutic intervention. Results obtained in this study would justify the use of comprehensive mass spectrometry-based lipidomics to measure other lipids aside from conventional lipid profiles and to validate possible early markers of risk of CKD in patients with severe obesity. Full article
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13 pages, 1099 KiB  
Article
Healthy and Chronic Kidney Disease (CKD) Dogs Have Differences in Serum Metabolomics and Renal Diet May Have Slowed Disease Progression
by Marcio Antonio Brunetto, Bruna Ruberti, Doris Pereira Halfen, Douglas Segalla Caragelasco, Thiago Henrique Annibale Vendramini, Vivian Pedrinelli, Henrique Tobaro Macedo, Juliana Toloi Jeremias, Cristiana Fonseca Ferreira Pontieri, Fernanda Maria Marins Ocampos, Luis Alberto Colnago and Marcia Mery Kogika
Metabolites 2021, 11(11), 782; https://doi.org/10.3390/metabo11110782 - 16 Nov 2021
Cited by 3 | Viewed by 2713
Abstract
Chronic kidney disease (CKD) is highly prevalent in dogs, and metabolomics investigation has been recently introduced for a better understanding of the role of diet in CKD. This study aimed to compare the serum metabolomic profile of healthy dogs (CG) and dogs with [...] Read more.
Chronic kidney disease (CKD) is highly prevalent in dogs, and metabolomics investigation has been recently introduced for a better understanding of the role of diet in CKD. This study aimed to compare the serum metabolomic profile of healthy dogs (CG) and dogs with CKD (CKD-T0 and CKD-T6) to evaluate whether the diet would affect metabolites. Six dogs (5 females; 1 male; 7.47 ± 2.31 years old) with CKD stage 3 or 4 (IRIS) were included. CG consisted of 10 healthy female dogs (5.89 ± 2.57 years old) fed a maintenance diet. Serum metabolites were analyzed by 1H nuclear magnetic resonance (1H NMR) spectra. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed to assess differences in metabolomic profiles between groups and before (CKD-T0) and after renal diet (CKD-T6). Data analysis was performed on SIMCA-P software. Dogs with CKD showed an altered metabolic profile with increased urea, creatinine, creatine, citrate, and lipids. Lactate, branched-chain amino acids (BCAAs), and glutamine were decreased in the CKD group. However, after 6 months of diet, the metabolite profiles of CKD-T0 and CKD-T6 were similar. Metabolomics profile may be useful to evaluate and recognize metabolic dysfunction and progression of CKD, and the diet may have helped maintain and retard the progression of CKD. Full article
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12 pages, 1726 KiB  
Article
Kidney Allograft Function Is a Confounder of Urine Metabolite Profiles in Kidney Allograft Recipients
by Karsten Suhre, Darshana M. Dadhania, John Richard Lee, Thangamani Muthukumar, Qiuying Chen, Steven S. Gross and Manikkam Suthanthiran
Metabolites 2021, 11(8), 533; https://doi.org/10.3390/metabo11080533 - 11 Aug 2021
Cited by 4 | Viewed by 2436
Abstract
Noninvasive biomarkers of kidney allograft status can help minimize the need for standard of care kidney allograft biopsies. Metabolites that are measured in the urine may inform about kidney function and health status, and potentially identify rejection events. To test these hypotheses, we [...] Read more.
Noninvasive biomarkers of kidney allograft status can help minimize the need for standard of care kidney allograft biopsies. Metabolites that are measured in the urine may inform about kidney function and health status, and potentially identify rejection events. To test these hypotheses, we conducted a metabolomics study of biopsy-matched urine cell-free supernatants from kidney allograft recipients who were diagnosed with two major types of acute rejections and no-rejection controls. Non-targeted metabolomics data for 674 metabolites and 577 unidentified molecules, for 192 biopsy-matched urine samples, were analyzed. Univariate and multivariate analyses identified metabolite signatures for kidney allograft rejection. The replicability of a previously developed urine metabolite signature was examined. Our study showed that metabolite profiles can serve as biomarkers for discriminating rejection biopsies from biopsies without rejection features, but also revealed a role of estimated Glomerular Filtration Rate (eGFR) as a major confounder of the metabolite signal. Full article
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11 pages, 1124 KiB  
Communication
Urinary 2-Hydroxyglutarate Enantiomers Are Markedly Elevated in a Murine Model of Type 2 Diabetic Kidney Disease
by Judy Baek and Subramaniam Pennathur
Metabolites 2021, 11(8), 469; https://doi.org/10.3390/metabo11080469 - 21 Jul 2021
Cited by 4 | Viewed by 2387
Abstract
Metabolic reprogramming is a hallmark of diabetic kidney disease (DKD); nutrient overload leads to increased production of metabolic byproducts that may become toxic at high levels. One metabolic byproduct may be 2-hydroxyglutarate (2-HG), a metabolite with many regulatory functions that exists in both [...] Read more.
Metabolic reprogramming is a hallmark of diabetic kidney disease (DKD); nutrient overload leads to increased production of metabolic byproducts that may become toxic at high levels. One metabolic byproduct may be 2-hydroxyglutarate (2-HG), a metabolite with many regulatory functions that exists in both enantiomeric forms physiologically. We quantitatively determined the levels of L and D-2HG enantiomers in the urine, plasma, and kidney cortex of db/db mice, a pathophysiologically relevant murine model of type 2 diabetes and DKD. We found increased fractional excretion of both L and D-2HG enantiomers, suggesting increased tubular secretion and/or production of the two metabolites in DKD. Quantitation of TCA cycle metabolites in db/db cortex suggests that TCA cycle overload and an increase in 2-HG precursor substrate, α-ketoglutarate, drive the increased L and D-2HG production in DKD. In conclusion, we demonstrated increased 2-HG enantiomer production and urinary excretion in murine type 2 DKD, which may contribute to metabolic reprogramming and progression of diabetic kidney disease. Full article
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15 pages, 584 KiB  
Article
An R-Package for the Deconvolution and Integration of 1D NMR Data: MetaboDecon1D
by Martina Häckl, Philipp Tauber, Frank Schweda, Helena U. Zacharias, Michael Altenbuchinger, Peter J. Oefner and Wolfram Gronwald
Metabolites 2021, 11(7), 452; https://doi.org/10.3390/metabo11070452 - 13 Jul 2021
Cited by 9 | Viewed by 3629
Abstract
NMR spectroscopy is a widely used method for the detection and quantification of metabolites in complex biological fluids. However, the large number of metabolites present in a biological sample such as urine or plasma leads to considerable signal overlap in one-dimensional NMR spectra, [...] Read more.
NMR spectroscopy is a widely used method for the detection and quantification of metabolites in complex biological fluids. However, the large number of metabolites present in a biological sample such as urine or plasma leads to considerable signal overlap in one-dimensional NMR spectra, which in turn hampers both signal identification and quantification. As a consequence, we have developed an easy to use R-package that allows the fully automated deconvolution of overlapping signals in the underlying Lorentzian line-shapes. We show that precise integral values are computed, which are required to obtain both relative and absolute quantitative information. The algorithm is independent of any knowledge of the corresponding metabolites, which also allows the quantitative description of features of yet unknown identity. Full article
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Review

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30 pages, 5528 KiB  
Review
Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses
by Ulla T. Schultheiss, Robin Kosch, Fruzsina Kotsis, Michael Altenbuchinger and Helena U. Zacharias
Metabolites 2021, 11(7), 460; https://doi.org/10.3390/metabo11070460 - 16 Jul 2021
Cited by 4 | Viewed by 3221
Abstract
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, [...] Read more.
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. Full article
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