Advancements, Challenges, and clinical implications of integration of metabolomics technologies in diabetic nephropathy

BACKGROUND

Diabetic nephropathy (DN), a severe complication of diabetes, involves a range of renal abnormalities driven by metabolic derangements. Metabolomics, revealing dynamic metabolic shifts in diseases like DN and offering insights into personalized treatment strategies, emerges as a promising tool for improved diagnostics and therapies.

METHODS

We conducted an extensive literature review to examine how metabolomics contributes to the study of DN and the challenges associated with its implementation in clinical practice. We identified and assessed relevant studies that utilized metabolomics methods, including nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) to assess their efficacy in diagnosing DN.

RESULTS

Metabolomics unveils key pathways in DN progression, highlighting glucose metabolism, dyslipidemia, and mitochondrial dysfunction. Biomarkers like glycated albumin and free fatty acids offer insights into DN nuances, guiding potential treatments. Metabolomics detects small-molecule metabolites, revealing disease-specific patterns for personalized care.

CONCLUSION

Metabolomics offers valuable insights into the molecular mechanisms underlying DN progression and holds promise for personalized medicine approaches. Further research in this field is warranted to elucidate additional metabolic pathways and identify novel biomarkers for early detection and targeted therapeutic interventions in DN.

Green Tea Polyphenols Alleviate Kidney Injury Induced by Di(2-Ethylhexyl) Phthalate in Mice

INTRODUCTION

Di(2-ethylhexyl) phthalate (DEHP) is a common plasticizer. Studies have revealed that DEHP exposure can cause kidney damage. Green tea is among the most popular beverages in China. Green tea polyphenols (GTPs) have been proven to have therapeutic effects on organ damage induced by heavy metal exposure. However, few studies have reported on GTP-relieving DEHP-induced kidney damage.

METHODS

C57BL/6J male mice aged 6-8 weeks were treated with distilled water (control group), 1,500 mg/kg/d DEHP + corn oil (model group), 1,500 mg/kg/d DEHP + corn oil + 70 mg/kg GTP (treatment group), corn oil (oil group), and 70 mg/kg GTP (GTP group) by gavage for 8 weeks, respectively. The renal function of mice and renal tissue histopathology of each group were evaluated. The renal tissues of mice in the model, treatment, and control groups were analyzed using high-throughput sequencing. We calculated the differentially expressed microRNAs (miRNAs) and messenger RNAs (mRNAs) using the limma R package, the CIBERSORT algorithm was used to predict immune infiltration, the starBase database was used to screen the miRNA-mRNA regulatory axis, and immunohistochemical analyses were performed to verify protein expression.

RESULTS

GTP alleviated the deterioration of renal function, renal inflammation and fibrosis, and mitochondrial and endoplasmic reticulum lesions induced by DEHP in mice. Differential immune infiltrations of plasma, dendritic, T, and B cells were noted between the model and treatment groups. We found that three differentially expressed miRNAs (mmu-miR-383-5p, mmu-miR-152-3p, and mmu-miR-144-3p), three differentially expressed mRNAs (Ddit4, Dusp1, and Snx18), and three differentially expressed proteins (Ddit4, Dusp1, and Snx18) played crucial roles in the miRNA-mRNA-protein regulatory axes when GTPs mitigate DEHP-induced kidney damage in mice.

CONCLUSION

GTP can alleviate DEHP-induced kidney damage and regulate immune cell infiltration. We screened four important miRNA-mRNA-protein regulatory axes of GTP, mitigating DEHP-induced kidney damage in mice.

Crosstalk between COVID-19 Infection and Kidney Diseases: A Review on the Metabolomic Approaches

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a respiratory disorder. Various organ injuries have been reported in response to this virus, including kidney injury and, in particular, kidney tubular injury. It has been discovered that infection with the virus does not only cause new kidney disease but also increases treatment difficulty and mortality rates in people with kidney diseases. In individuals hospitalized with COVID-19, urinary metabolites from several metabolic pathways are used to distinguish between patients with acute kidney injury (AKI) and those without. This review summarizes the pathogenesis, pathophysiology, treatment strategies, and role of metabolomics in relation to AKI in COVID-19 patients. Metabolomics is likely to play a greater role in predicting outcomes for patients with kidney disease and COVID-19 with varying levels of severity in the near future as data on metabolic profiles expand rapidly. Here, we also discuss the correlation between COVID-19 and kidney diseases and the available metabolomics approaches.

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.

Omics profiling identifies the regulatory functions of the MAPK/ERK pathway in nephron progenitor metabolism

Nephron endowment is defined by fetal kidney growth and crucially dictates renal health in adults. Defects in the molecular regulation of nephron progenitors contribute to only a fraction of reduced nephron mass cases, suggesting alternative causative mechanisms. The importance of MAPK/ERK activation in nephron progenitor maintenance has been previously demonstrated, and here, we characterized the metabolic consequences of MAPK/ERK deficiency. Liquid chromatography/mass spectrometry-based metabolomics profiling identified 42 reduced metabolites, of which 26 were supported by in vivo transcriptional changes in MAPK/ERK-deficient nephron progenitors. Among these, mitochondria, ribosome and amino acid metabolism, together with diminished pyruvate and proline metabolism, were the most affected pathways. In vitro cultures of mouse kidneys demonstrated a dosage-specific function for pyruvate in controlling the shape of the ureteric bud tip, a regulatory niche for nephron progenitors. In vivo disruption of proline metabolism caused premature nephron progenitor exhaustion through their accelerated differentiation in pyrroline-5-carboxylate reductases 1 (Pycr1) and 2 (Pycr2) double-knockout kidneys. Pycr1/Pycr2-deficient progenitors showed normal cell survival, indicating no changes in cellular stress. Our results suggest that MAPK/ERK-dependent metabolism functionally participates in nephron progenitor maintenance by monitoring pyruvate and proline biogenesis in developing kidneys.

Trimethyllysine, vascular risk factors and outcome in acute ischemic stroke (MARK-STROKE)

Trimethyllysine (TML) is involved in the generation of the pro-atherogenic metabolite trimethylamine-N-oxide (TMAO) by gut microbiota. In clinical studies, elevated TML levels predicted major adverse cardiovascular events (MACE) in patients with acute or stable coronary artery disease (CAD). In contrast to cardiovascular patients, the role of TML in patients with acute cerebral ischemia is unknown. Here, we evaluated circulating TML levels in 374 stroke patients from the prospective biomarkers in stroke (MARK-STROKE) study. Compared with 167 matched healthy controls, acute ischemic stroke patients had lower median TML plasma concentrations, i.e. 0.71 vs. 0.47 µmol/L (p < 0.001) and this difference persisted after adjusting for age and sex. TML plasma concentrations were associated with age, serum creatinine, glucose, cholesterol and lysine. Patients with prevalent arterial hypertension, atrial fibrillation or a history of myocardial infarction had increased TML levels, but this observation was not independent of age, sex and GFR. In 274 patients, follow-up data were available. During a median follow-up of 284 [25th-75th percentile: 198, 431] days, TML was not associated with incident MACE (stroke, myocardial infarction, death). In summary, our data suggests a different role of TML in acute ischemic stroke compared with CAD patients.

A Systems-Level View of Renal Metabolomics

The measurement of select circulating metabolites such as creatinine, glucose, and cholesterol are integral to clinical medicine, with implications for diagnosis, prognosis, and treatment. Metabolomics studies in nephrology research seek to build on this paradigm, with the goal to identify novel markers and causal participants in the pathogenesis of kidney disease and its complications. This article reviews three themes pertinent to this goal. Each is rooted in long-established principles of human physiology, with recent updates enabled by metabolomics and other tools. First, the kidney has a broad and heterogeneous impact on circulating metabolites, with progressive loss of kidney function resulting in a multitude of small molecule alterations. Second, an increasing number of circulating metabolites have been shown to possess functional roles, in some cases acting as ligands for specific G-protein-coupled receptors. Third, circulating metabolites traffic through varied, and sometimes complex, interorgan circuits. Taken together, these themes emphasize the importance of viewing renal metabolomics at the systems level, recognizing the diverse origins and physiologic effects of blood metabolites. However, how to synthesize these themes and how to establish clinical relevance remain uncertain and will require further investigation.

Optimization of kidney dysfunction prediction in diabetic kidney disease using targeted metabolomics

AIMS

Metabolomics have been used to evaluate the role of small molecules in human disease. However, the cost and complexity of the methodology and interpretation of findings have limited the transference of knowledge to clinical practice. Here, we apply a targeted metabolomics approach using samples blotted in filter paper to develop clinical-metabolomics models to detect kidney dysfunction in diabetic kidney disease (DKD).

METHODS

We included healthy controls and subjects with type 2 diabetes (T2D) with and without DKD and investigated the association between metabolite concentrations in blood and urine with eGFR and albuminuria. We also evaluated performance of clinical, biochemical and metabolomic models to improve kidney dysfunction prediction in DKD.

RESULTS

Using clinical-metabolomics models, we identified associations of decreased eGFR with body mass index (BMI), uric acid and C10:2 levels; albuminuria was associated to years of T2D duration, A1C, uric acid, creatinine, protein intake and serum C0, C10:2 and urinary C12:1 levels. DKD was associated with age, A1C, uric acid, BMI, serum C0, C10:2, C8:1 and urinary C12:1. Inclusion of metabolomics increased the predictive and informative capacity of models composed of clinical variables by decreasing Akaike's information criterion, and was replicated both in training and validation datasets.

CONCLUSIONS

Targeted metabolomics using blotted samples in filter paper is a simple, low-cost approach to identify outcomes associated with DKD; the inclusion of metabolomics improves predictive capacity of clinical models to identify kidney dysfunction and DKD-related outcomes.

The metabolomic quest for a biomarker in chronic kidney disease

Chronic kidney disease (CKD) is a growing burden on people and on healthcare for which the diagnostics are niether disease-specific nor indicative of progression. Biomarkers are sought to enable clinicians to offer more appropriate patient-centred treatments, which could come to fruition by using a metabolomics approach. This mini-review highlights the current literature of metabolomics and CKD, and suggests additional factors that need to be considered in this quest for a biomarker, namely the diet and the gut microbiome, for more meaningful advances to be made.

1 H NMR-based metabolomics study for identifying urinary biomarkers and perturbed metabolic pathways associated with severity of IgA nephropathy: a pilot study

The severity of IgA nephropathy (IgAN), the most common primary glomerulonephritis, is judged on the basis of histologic and clinical features. A limited number of studies have considered molecular signature of IgAN for this issue, and no reliable biomarkers have been presented non-invasively for use in patient evaluations. This study aims to identify metabolite markers excreted in the urine and impaired pathways that are associated with a known marker of severity (proteinuria) to predict mild and severe stages of IgAN. Urine samples were analysed using nuclear magnetic resonance from biopsy-proven IgAN patients at mild and severe stages. Multivariate statistical analysis and pathway analysis were performed. The most changed metabolites were acetoacetate, hypotaurine, homocysteine, L-kynurenine and phenylalanine. Nine metabolites were positively correlated with proteinuria, including mesaconic acid, trans-cinnamic acid, fumaric acid, 5-thymidylic acid, anthranilic acid, indole, deoxyguanosine triphosphate, 13-cis-retinoic acid and nicotinamide riboside, while three metabolites were negatively correlated with proteinuria including acetoacetate, hypotaurine and hexanal. 'Phenylalanine metabolism' was the most significant pathway which was impaired in severe stage in comparison to mild stage of IgAN. This study indicates that nuclear magnetic resonance is a versatile technique that is capable of detecting metabolite biomarkers in combination with advanced multivariate statistical analysis. Copyright © 2017 John Wiley & Sons, Ltd.

The Use of Genomics and Pathway Analysis in Our Understanding and Prediction of Clinical Renal Transplant Injury

The development and application of high-throughput molecular profiling have transformed the study of human diseases. The problem of handling large, complex data sets has been facilitated by advances in complex computational analysis. In this review, the recent literature regarding the application of transcriptional genomic information to renal transplantation, with specific reference to acute rejection, acute kidney injury in allografts, chronic allograft injury, and tolerance is discussed, as is the current published data regarding other "omics" strategies-proteomics, metabolomics, and the microRNA transcriptome. These data have shed new light on our understanding of the pathogenesis of specific disease conditions after renal transplantation, but their utility as a biomarker of disease has been hampered by study design and sample size. This review aims to highlight the opportunities and obstacles that exist with genomics and other related technologies to better understand and predict renal allograft outcome.

Epigenetics of kidney disease

DNA methylation and histone modifications determine renal programming and the development and progression of renal disease. The identification of the way in which the renal cell epigenome is altered by environmental modifiers driving the onset and progression of renal diseases has extended our understanding of the pathophysiology of kidney disease progression. In this review, we focus on current knowledge concerning the implications of epigenetic modifications during renal disease from early development to chronic kidney disease progression including renal fibrosis, diabetic nephropathy and the translational potential of identifying new biomarkers and treatments for the prevention and therapy of chronic kidney disease and end-stage kidney disease.

Make Precision Medicine Work for Chronic Kidney Disease

Precision medicine is based on accurate diagnosis and tailored intervention through the use of omics and clinical data together with epidemiology and environmental exposures. Precision medicine should be achieved with minimum adverse events and maximum efficacy in patients with chronic kidney disease (CKD). In this review, the breakthroughs of omics in CKD and the application of systems biology are reviewed. The potential role of transforming growth factor-β1 in the targeted intervention of renal fibrosis is discussed as an example of how to make precision medicine work for CKD.

Nuclear Magnetic Resonance Metabolomic Profiling of Mouse Kidney, Urine and Serum Following Renal Ischemia/Reperfusion Injury

Background

Ischemia/reperfusion (I/R) is the most common cause of acute kidney injury (AKI). Its pathophysiology remains unclear. Metabolomics is dedicated to identify metabolites involved in (patho)physiological changes of integrated living systems. Here, we performed ¹H-Nuclear Magnetic Resonance metabolomics using urine, serum and kidney samples from a mouse model of renal I/R.

Methods

Renal 30-min ischemia was induced in 12-week-old C57BL/6J male mice by bilaterally clamping vascular pedicles, and was followed by 6, 24 or 48-hour reperfusion (n = 12/group). Sham-operated mice were used as controls. Statistical discriminant analyses, i.e. principal component analysis and orthogonal projections to latent structures (OPLS-DA), were performed on urine, serum and kidney lysates at each time-point. Multivariate receiver operating characteristic (ROC) curves were drawn, and sensitivity and specificity were calculated from ROC confusion matrix (with averaged class probabilities across 100 cross-validations).

Results

Urine OPLS-DA analysis showed a net separation between I/R and sham groups, with significant variations in levels of taurine, di- and tri-methylamine, creatine and lactate. Such changes were observed as early as 6 hours post reperfusion. Major metabolome modifications occurred at 24h post reperfusion. At this time-point, correlation coefficients between urine spectra and conventional AKI biomarkers, i.e. serum creatinine and urea levels, reached 0.94 and 0.95, respectively. The area under ROC curve at 6h, 24h and 48h post surgery were 0.73, 0.98 and 0.97, respectively. Similar discriminations were found in kidney samples, with changes in levels of lactate, fatty acids, choline and taurine. By contrast, serum OPLS-DA analysis could not discriminate sham-operated from I/R-exposed animals.

Conclusions

Our study demonstrates that renal I/R in mouse causes early and sustained metabolomic changes in urine and kidney composition. The most implicated pathways at 6h and 24h post reperfusion include gluconeogenesis, taurine and hypotaurine metabolism, whereas protein biosynthesis, glycolysis, and galactose and arginine metabolism are key at 48h post reperfusion.

Red blood cell abnormalities and the pathogenesis of anemia in end-stage renal disease

Anemia is the most common hematologic complication in end-stage renal disease (ESRD). It is ascribed to decreased erythropoietin production, shortened red blood cell (RBC) lifespan, and inflammation. Uremic toxins severely affect RBC lifespan; however, the implicated molecular pathways are poorly understood. Moreover, current management of anemia in ESRD is controversial due to the "anemia paradox" phenomenon, which underlines the need for a more individualized approach to therapy. RBCs imprint the adverse effects of uremic, inflammatory, and oxidative stresses in a context of structural and functional deterioration that is associated with RBC removal signaling and morbidity risk. RBCs circulate in hostile plasma by raising elegant homeostatic defenses. Variability in primary defect, co-morbidity, and therapeutic approaches add complexity to the pathophysiological background of the anemic ESRD patient. Several blood components have been suggested as biomarkers of anemia-related morbidity and mortality risk in ESRD. However, a holistic view of blood cell and plasma modifications through integrated omics approaches and high-throughput studies might assist the development of new diagnostic tests and therapies that will target the underlying pathophysiologic processes of ESRD anemia.

Metabolomics and renal disease

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

Cross-sectional examination of metabolites and metabolic phenotypes in uremia

BACKGROUND

Although metabolomic approaches have begun to document numerous changes that arise in end stage renal disease (ESRD), how these alterations relate to established metabolic phenotypes in uremia is unknown.

METHODS

In 200 incident hemodialysis patients we used partial least squares discriminant analysis to identify which among 166 metabolites could best discriminate individuals with or without diabetes, and across tertiles of body mass index, serum albumin, total cholesterol, and systolic blood pressure.

RESULTS

Our data do not recapitulate metabolomic signatures of diabetes and obesity identified among individuals with normal renal function (e.g. elevations in branched chain and aromatic amino acids) and highlight several potential markers of diabetes status specific to ESRD, including xanthosine-5-phosphate and vanillylmandelic acid. Further, our data identify significant associations between elevated tryptophan and long-chain acylcarnitine levels and both decreased total cholesterol and systolic blood pressure in ESRD. Higher tryptophan levels were also associated with higher serum albumin levels, but this may reflect tryptophan's significant albumin binding. Finally, an examination of the uremic retention solutes captured by our platform in relation to 24 clinical phenotypes provides a framework for investigating mechanisms of uremic toxicity.

CONCLUSIONS

In sum, these studies leveraging metabolomic and metabolic phenotype data acquired in a well-characterized ESRD cohort demonstrate striking differences from metabolomics studies in the general population, and may provide clues to novel functional pathways in the ESRD population.

Genetic and epigenetic factors influencing chronic kidney disease

Chronic kidney disease (CKD) has become a serious public health problem because of its associated morbidity, premature mortality, and attendant healthcare costs. The rising number of persons with CKD is linked with the aging population structure and an increased prevalence of diabetes, hypertension, and obesity. There is an inherited risk associated with developing CKD, as evidenced by familial clustering and differing prevalence rates across ethnic groups. Previous studies to determine the inherited risk factors for CKD rarely identified genetic variants that were robustly replicated. However, improvements in genotyping technologies and analytic methods are now helping to identify promising genetic loci aided by international collaboration and multiconsortia efforts. More recently, epigenetic modifications have been proposed to play a role in both the inherited susceptibility to CKD and, importantly, to explain how the environment dynamically interacts with the genome to alter an individual's disease risk. Genome-wide, epigenome-wide, and whole transcriptome studies have been performed, and optimal approaches for integrative analysis are being developed. This review summarizes recent research and the current status of genetic and epigenetic risk factors influencing CKD using population-based information.

Chronic kidney disease (CKD) as a systemic disease: whole body autoregulation and inter-organ cross-talk

The inter-organ cross-talk and the functional integration of organ systems is an exceedingly complex process which until now has been investigated with a reductionist approach. CKD perturbs the inter-organ cross-talk and demands central resetting of autonomic (nervous) control of organ systems. Due to limitations inherent to the reductionist approach, we currently identify CKD-related pseudo-syndromes and largely fail at describing the complex systemic inter-relationships set into motion by renal damage and renal dysfunction. A mature technology for a system-analysis approach to physiology and pathophysiology of CKD now exists. System biology will allow in depth understanding of complex diseases like CKD and will set the stage for predictive, preventive and personalized medicine, a long-standing dream of doctors and patients alike.