A metabolomics approach using juvenile cystic mice to identify urinary biomarkers and altered pathways in polycystic kidney disease

Short salsalate administration affects cell proliferation, metabolism, and inflammation in polycystic kidney disease

Metabolic reprogramming is a driver of autosomal dominant polycystic kidney disease (ADPKD) progression and a potential therapeutic intervention route. We showed before that the AMP-associated protein kinase (AMPK) activator salsalate attenuates cystic disease progression. Here, we aim to study the early, direct effects of short salsalate treatment in adult-onset conditional Pkd1 deletion mice. Cystic mice were treated with salsalate for two weeks, after which NMR metabolomics and RNA sequencing analyses were performed. Pkd1 deletion resulted in clear metabolomic dysregulation. Short salsalate treatment has small, but significant, effects, reverting acetylcarnitine and phosphocholine concentrations back to wildtype levels, and showing associations with altered purine metabolism. RNA sequencing revealed that short salsalate treatment, next to restoring energy metabolism toward wildtype levels, also affects cell proliferation and inflammation, in PKD. We show that salsalate positively affects major dysregulated processes in ADPKD: energy metabolism, cell proliferation, and inflammation, providing more insights into its working mechanisms.

Temporal Profile of Kynurenine Pathway Metabolites in a Rodent Model of Autosomal Recessive Polycystic Kidney Disease

Autosomal recessive polycystic kidney disease (ARPKD) is an early onset genetic disorder characterized by numerous renal cysts resulting in end stage renal disease. Our study aimed to determine if metabolic reprogramming and tryptophan (Trp) metabolism via the kynurenine pathway (KP) is a critical dysregulated pathway in PKD. Using the Lewis polycystic kidney (LPK) rat model of PKD and Lewis controls, we profiled temporal trends for KP metabolites in plasma, urine, and kidney tissues from 6- and 12-week-old mixed sex animals using liquid and gas chromatography, minimum n = 5 per cohort. A greater kynurenine (KYN) concentration was observed in LPK kidney and plasma of 12-week rats compared to age matched Lewis controls (P ⩽ .05). LPK kidneys also showed an age effect (P ⩽ .05) with KYN being greater in 12-week versus 6-week LPK. The metabolites xanthurenic acid (XA), 3-hydroxykynurenine (3-HK), and 3-hydroxyanthranilic acid (3-HAA) were significantly greater in the plasma of 12-week LPK rats compared to age matched Lewis controls (P ⩽ .05). Plasma XA and 3-HK also showed an age effect (P ⩽ .05) being greater in 12-week versus 6-week LPK. We further describe a decrease in Trp levels in LPK plasma and kidney (strain effect P ⩽ .05). There were no differences in KP metabolites in urine between cohorts. Using the ratio of product and substrates in the KP, a significant age-strain effect (P ⩽ .05) was observed in the activity of the KYN/Trp ratio (tryptophan-2,3-dioxygenase [TDO] or indoleamine-2,3-dioxygenase [IDO] activity), kynurenine 3-monooxygenase (KMO), KAT A (kynurenine aminotransferase A), KAT B, total KAT, total KYNU (kynureninase), KYNU A, KYNU B, and total KYNU within LPK kidneys, supporting an activated KP. Confirmation of the activation of these enzymes will require verification through orthogonal techniques. In conclusion, we have demonstrated an up-regulation of the KP in alignment with progression of renal impairment in the LPK rat model, suggesting that KP activation may be a critical contributor to the pathobiology of PKD.

Multi-Omics Studies Unveil Extraciliary Functions of BBS10 and Show Metabolic Aberrations Underlying Renal Disease in Bardet-Biedl Syndrome

Bardet–Biedl syndrome (BBS) is a rare autosomal recessive ciliopathy resulting in multiple organ dysfunctions, including chronic kidney disease (CKD). Despite the recent progress in the ’ciliopathy’ field, there is still little information on the mechanisms underlying renal disease. To elucidate these pathomechanisms, we conducted a translational study, including (i) the characterization of the urine metabolomic pattern of BBS patients and controls in a pilot and confirmation study and (ii) the proteomic analysis of the BBS10 interactome, one of the major mutated BBS genes in patients, in a renal-epithelial-derived cell culture model. The urine metabolomic fingerprinting of BBS patients differed from controls in both pilot and confirmation studies, demonstrating an increased urinary excretion of several monocarboxylates, including lactic acid (LA), at both early and late CKD stages. Increased urine LA was detected in the absence of both increased plasmatic LA levels and generalized proximal tubular dysfunction, suggesting a possible renal-specific defective handling. The inner medulla renal epithelial (IMCD3) cell line, where Bbs10 was stably invalidated, displayed an increased proliferative rate, increased ATP production, and an up-regulation of aerobic glycolysis. A mass spectrometry-based analysis detected several putative BBS10 interactors in vitro, indicating a potential role of BBS10 in several biological processes, including renal metabolism, RNA processing, and cell proliferation. The present study suggests that the urine metabolomic pattern of BBS patients may reflect intra-renal metabolic aberrations. The analysis of BBS10 interactors unveils possible novel functions, including cell metabolism.

Metabolic reprogramming in a slowly developing orthologous model of polycystic kidney disease

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disease and affects 1 in 1,000 individuals. There is accumulating evidence suggesting that there are shared cellular mechanisms responsible for cystogenesis in human and murine PKD and that reprogramming of metabolism is a key disease feature. In this study, we used a targeted metabolomics approach in an orthologous mouse model of PKD (Pkd1RC/RC) to investigate the metabolic modifications a cystic kidney undergoes during disease progression. Using the Kyoto Encyclopedia of Genes and Genomes pathway database, we identified several biologically relevant metabolic pathways that were altered early in this disease (in 3-mo-old Pkd1RC/RC mice), the most highly represented being arginine biosynthesis and metabolism and tryptophan and phenylalanine metabolism. During the next 6 mo of disease progression, multiple uremic solutes accumulated in the kidney of cystic mice, including several established markers of oxidative stress and endothelial dysfunction (allantoin, asymmetric dimethylarginine, homocysteine, malondialdehyde, methionine sulfoxide, and S-adenosylhomocysteine). Levels of kynurenines and polyamines were also augmented in kidneys of Pkd1RC/RC versus wild-type mice, as were the levels of bacteria-produced indoles, whose increase within PKD kidneys suggests microbial dysbiosis. In summary, we confirmed previously published and identified novel metabolic markers and pathways of PKD progression that may prove helpful for diagnosis and monitoring of cystic kidney disease in patients. Furthermore, they provide targets for novel therapeutic approaches that deserve further study and hint toward currently understudied pathomechanisms.NEW & NOTEWORTHY This report delineates the evolution of metabolic changes occurring during autosomal dominant polycystic kidney disease (ADPKD) progression. Using an orthologous model, we performed kidney metabolomics and confirmed dysregulation of metabolic pathways previously found altered in nonorthologous or rapidly-progressive PKD models. Importantly, we identified novel alterations, including augmentation of kynurenines, polyamines, and indoles, suggesting increased inflammation and microbial dysbiosis that provide insights into PKD pathomechanisms and may prove helpful for diagnosing, monitoring, and treating ADPKD.

Metabolomics Profiling of Cystic Renal Disease towards Biomarker Discovery

Simple Summary

Cystic renal disease (CRD) is a group of diseases characterized by abnormal sacs, or cysts, in the kidneys. CRD can be detected using certain imaging modalities (i.e., ultrasound). Patients with CRD might be symptoms-free, while others can show symptoms long after cysts development. Although these cysts represent structural changes, we hypothesized that they have an underlying biochemical alteration. If so, this would open the floor for potential biomarker discovery, which would aid in CRD diagnosis and, possibly, treatment. On that basis, this study focuses on identifying biomarkers for CRD. To achieve that, we employed a metabolomics-based approach to identify intermediate molecules inside the cells that are byproducts of biochemical reactions. We used dry blood spots and serum samples of CRD patients and healthy controls to study the differences in their metabolomic profile. Our results suggest that certain metabolites, including uridine diphosphate, cystine-5-diphosphate, and morpholine, are potential biomarkers for CRD. The affected biochemical pathways in CRD include aminoacyl-tRNA biosynthesis, purine, pyrimidine, glutathione, TCA cycle, and some amino acid metabolism. These preliminary results could be the starting point for possible diagnostic and therapeutic approaches for CRD in the future.

Abstract

Cystic renal disease (CRD) comprises a heterogeneous group of genetic and acquired disorders. The cystic lesions are detected through imaging, either incidentally or after symptoms develop, due to an underlying disease process. In this study, we aim to study the metabolomic profiles of CRD patients for potential disease-specific biomarkers using unlabeled and labeled metabolomics using low and high-resolution mass spectrometry (MS), respectively. Dried-blood spot (DBS) and serum samples, collected from CRD patients and healthy controls, were analyzed using the unlabeled and labeled method. The metabolomics profiles for both sets of samples and groups were collected, and their data were processed using the lab’s standard protocol. The univariate analysis showed (FDR p < 0.05 and fold change 2) was significant to show a group of potential biomarkers for CRD discovery, including uridine diphosphate, cystine-5-diphosphate, and morpholine. Several pathways were involved in CRD patients based on the metabolic profile, including aminoacyl-tRNA biosynthesis, purine and pyrimidine, glutathione, TCA cycle, and some amino acid metabolism (alanine, aspartate and glutamate, arginine and tryptophan), which have the most impact. In conclusion, early CRD detection and treatment is possible using a metabolomics approach that targets alanine, aspartate, and glutamate pathway metabolites.

Diet, obesity, and the gut microbiome as determinants modulating metabolic outcomes in a non-human primate model

BACKGROUND

The objective of this study was to increase understanding of the complex interactions between diet, obesity, and the gut microbiome of adult female non-human primates (NHPs). Subjects consumed either a Western (n=15) or Mediterranean (n=14) diet designed to represent human dietary patterns for 31 months. Body composition was determined using CT, fecal samples were collected, and shotgun metagenomic sequencing was performed. Gut microbiome results were grouped by diet and adiposity.

RESULTS

Diet was the main contributor to gut microbiome bacterial diversity. Adiposity within each diet was associated with subtle shifts in the proportional abundance of several taxa. Mediterranean diet-fed NHPs with lower body fat had a greater proportion of Lactobacillus animalis than their higher body fat counterparts. Higher body fat Western diet-fed NHPs had more Ruminococcus champaneliensis and less Bacteroides uniformis than their low body fat counterparts. Western diet-fed NHPs had significantly higher levels of Prevotella copri than Mediterranean diet NHPs. Western diet-fed subjects were stratified by P. copri abundance (P. copri^HIGH versus P. copri^LOW), which was not associated with adiposity. Overall, Western diet-fed animals in the P. copri^HIGH group showed greater proportional abundance of B. ovatus, B. faecis, P. stercorea, P. brevis, and Faecalibacterium prausnitzii than those in the Western P. copri^LOW group. Western diet P. copri^LOW subjects had a greater proportion of Eubacterium siraeum. E. siraeum negatively correlated with P. copri proportional abundance regardless of dietary consumption. In the Western diet group, Shannon diversity was significantly higher in P. copri^LOW when compared to P. copri^HIGH subjects. Furthermore, gut E. siraeum abundance positively correlated with HDL plasma cholesterol indicating that those in the P. copri^LOW population may represent a more metabolically healthy population. Untargeted metabolomics on urine and plasma from Western diet-fed P. copri^HIGH and P. copri^LOW subjects suggest early kidney dysfunction in Western diet-fed P. copri^HIGH subjects.

CONCLUSIONS

In summary, the data indicate diet to be the major influencer of gut bacterial diversity. However, diet and adiposity must be considered together when analyzing changes in abundance of specific bacterial taxa. Interestingly, P. copri appears to mediate metabolic dysfunction in Western diet-fed NHPs. Video abstract.

Metabolic profiling in children and young adults with autosomal dominant polycystic kidney disease

Autosomal dominant polycystic kidney disease (ADPKD) is the most commonly inherited kidney disease. Although children with ADPKD show normal renal function, cyst development is already occurring. In this study, we aimed to identify markers and associated molecular pathways of disease progression in children and young adults with ADPKD. Plasma samples were collected during a 3-year randomized, double-blind, placebo-controlled, phase III clinical trial that was designed to test the efficacy of pravastatin on slowing down ADPKD progression in pediatric patients. Samples from 58 patients were available at baseline and at the 3-year endpoint of the study, respectively. Furthermore, plasma samples from 98 healthy children were used as controls. Metabolomic analysis was performed using liquid chromatography-tandem mass spectrometry and differences in metabolic profiles over time and within study groups were evaluated. While pravastatin therapy led to a decrease in a percent change of total kidney volume (HtTKV) in ADPKD patients, it had minimal effects on metabolite changes. Oxidative stress, endothelial dysfunction, inflammation and immune response were the most affected signaling pathways that distinguished healthy from diseased children. Pathway analysis revealed that metabolites in the arginine metabolism (urea and nitric oxide cycles), asparagine and glutamine metabolism, in the methylation cycle and kynurenine pathway were significantly changed between healthy and children with ADPDK and continued to diverge from the control levels while the disease progressed. Detected metabolite changes were primarily governed by disease progression, and less by pravastatin treatment. Identified metabolic pathways, from arginine and asparagine to kynurenine metabolism could present therapeutic targets and should be further investigated for potential to treat ADPKD progression at an early stage.

Proteomics and metabolomics studies exploring the pathophysiology of renal dysfunction in autosomal dominant polycystic kidney disease and other ciliopathies

The primary cilium (PC) was considered as a vestigial organelle with no significant physiological importance, until the discovery that PC perturbation disturbs several signalling pathways and results in the dysfunction of a variety of organs. Genetic studies have demonstrated that mutations affecting PC proteins or its anchoring structure, the basal body, underlie a class of human disorders (known as ciliopathies) characterized by a constellation of clinical signs. Further investigations have demonstrated that the PC is involved in a broad range of biological processes, in both developing and mature tissues. Kidney disease is a common clinical feature of cilia disorders, supporting the hypothesis of a crucial role of the PC in kidney homoeostasis. Clinical proteomics and metabolomics are an expanding research area. Interestingly, the application of these methodologies to the analysis of urine, a biological sample that can be collected in a non-invasive fashion and possibly in large amounts, makes these studies feasible also in patients. The present article describes the most recent proteomic and metabolomic studies exploring kidney dysfunction in the setting of ciliopathies, showing the potential of these methodologies in the elucidation of disease pathophysiology and in the discovery of biomarkers.

Urinary metabolites associate with the rate of kidney function decline in patients with autosomal dominant polycystic kidney disease

Background

The variable course of autosomal dominant polycystic kidney disease (ADPKD), and the advent of renoprotective treatment require early risk stratification. We applied urinary metabolomics to explore differences associated with estimated glomerular filtration rate (eGFR; CKD-EPI equation) and future eGFR decline.

Methods

Targeted, quantitative metabolic profiling (¹H NMR-spectroscopy) was performed on baseline spot urine samples obtained from 501 patients with ADPKD. The discovery cohort consisted of 338 patients (56% female, median values for age 46 [IQR 38 to 52] years, eGFR 62 [IQR 45 to 85] ml/min/1.73m², follow-up time 2.5 [range 1 to 3] years, and annual eGFR slope –3.3 [IQR –5.3 to –1.3] ml/min/1.73m²/year). An independent cohort (n = 163) was used for validation. Multivariate modelling and linear regression were used to analyze the associations between urinary metabolites and eGFR, and eGFR decline over time.

Results

Twenty-nine known urinary metabolites were quantified from the spectra using a semi-automatic quantification routine. The model optimization routine resulted in four metabolites that most strongly associated with actual eGFR in the discovery cohort (F = 128.9, P = 7×10⁻⁵⁴, R² = 0.724). A model using the ratio of two other metabolites, urinary alanine/citrate, showed the best association with future annual change in eGFR (F = 51.07, P = 7.26×10⁻¹², R² = 0.150). This association remained significant after adjustment for clinical risk markers including height-adjusted total kidney volume (htTKV). Results were confirmed in the validation cohort.

Conclusions

Quantitative NMR profiling identified urinary metabolic markers that associated with actual eGFR and future rate of eGFR decline. The urinary alanine/citrate ratio showed additional value beyond conventional risk markers.

Alterations of Proximal Tubular Secretion in Autosomal Dominant Polycystic Kidney Disease

BACKGROUND AND OBJECTIVES

In autosomal dominant polycystic kidney disease (ADPKD), the GFR often remains normal despite significant nephron loss. Proximal tubular secretory clearance may be reduced in ADPKD before detectable changes in GFR.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

We used targeted mass spectrometry to quantify secretory solutes from blood and urine samples from 31 patients with ADPKD and preserved GFR (mean eGFR =111±11 ml/min per 1.73 m²) and 25 healthy control individuals as well as from 95 patients with ADPKD and reduced GFR (mean eGFR =53±21 ml/min per 1.73 m²) and 92 individuals with non-ADPKD CKD. We used linear regression to compare the fractional excretion of each solute between ADPKD and control groups. Among 112 patients with ADPKD, we used linear regression to determine associations of solute fractional excretion with height-adjusted total kidney volume.

RESULTS

After adjusting for demographics, clinical characteristics, and kidney function measures, the fractional excretions of three secretory solutes were lower in patients with ADPKD and preserved GFR compared with healthy individuals: 52% lower cinnamoylglycine excretion (95% confidence interval, 24% to 70%), 53% lower tiglylglycine excretion (95% confidence interval, 23% to 71%), and 91% lower xanthosine excretion (95% confidence interval, 83% to 95%). In addition to lower excretions of tiglylglycine and xanthosine, patients with ADPKD and reduced GFR also demonstrated 37% lower dimethyluric acid excretion (95% confidence interval, 21% to 50%), 58% lower hippurate excretion (95% confidence interval, 48% to 66%), 48% lower isovalerylglycine excretion (95% confidence interval, 37% to 56%), and 31% lower pyridoxic acid excretion (95% confidence interval, 16% to 42%) compared with patients with non-ADPKD CKD and comparable eGFR. Among patients with ADPKD, solute fractional excretions were not associated with differences in kidney volume.

CONCLUSIONS

Patients with ADPKD and preserved and reduced GFR demonstrate lower tubular secretory solute excretion compared with healthy controls and patients with non-ADPKD CKD. Our results suggest that tubular secretion is impaired in ADPKD independent of GFR.

Plasma metabolites and lipids associate with kidney function and kidney volume in hypertensive ADPKD patients early in the disease course

Background

Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease and is characterized by gradual cyst growth and expansion, increase in kidney volume with an ultimate decline in kidney function leading to end stage renal disease (ESRD). Given the decades long period of stable kidney function while cyst growth occurs, it is important to identify those patients who will progress to ESRD. Recent data from our and other laboratories have demonstrated that metabolic reprogramming may play a key role in cystic epithelial proliferation resulting in cyst growth in ADPKD. Height corrected total kidney volume (ht-TKV) accurately reflects cyst burden and predicts future loss of kidney function. We hypothesize that specific plasma metabolites will correlate with eGFR and ht-TKV early in ADPKD, both predictors of disease progression, potentially indicative of early physiologic derangements of renal disease severity.

Methods

To investigate the predictive role of plasma metabolites on eGFR and/or ht-TKV, we used a non-targeted GC-TOF/MS-based metabolomics approach on hypertensive ADPKD patients in the early course of their disease. Patient data was obtained from the HALT-A randomized clinical trial at baseline including estimated glomerular filtration rate (eGFR) and measured ht-TKV. To identify individual metabolites whose intensities are significantly correlated with eGFR and ht-TKV, association analyses were performed using linear regression with each metabolite signal level as the primary predictor variable and baseline eGFR and ht-TKV as the continuous outcomes of interest, while adjusting for covariates. Significance was determined by Storey’s false discovery rate (FDR) q-values to correct for multiple testing.

Results

Twelve metabolites significantly correlated with eGFR and two triglycerides significantly correlated with baseline ht-TKV at FDR q-value < 0.05. Specific significant metabolites, including pseudo-uridine, indole-3-lactate, uric acid, isothreonic acid, and creatinine, have been previously shown to accumulate in plasma and/or urine in both diabetic and cystic renal diseases with advanced renal insufficiency.

Conclusions

This study identifies metabolic derangements in early ADPKD which may be prognostic for ADPKD disease progression.

Clinical trial

HALT Progression of Polycystic Kidney Disease (HALT PKD) Study A; Clinical www.clinicaltrials.gov identifier: NCT00283686; first posted January 30, 2006, last update posted March 19, 2015.

Electronic supplementary material

The online version of this article (10.1186/s12882-019-1249-6) contains supplementary material, which is available to authorized users.

Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases

Diseases of the kidney are difficult to diagnose and treat. This review summarises the definition, cause, epidemiology and treatment of some of these diseases including chronic kidney disease, diabetic nephropathy, acute kidney injury, kidney cancer, kidney transplantation and polycystic kidney diseases. Numerous studies have adopted a metabolomics approach to uncover new small molecule biomarkers of kidney diseases to improve specificity and sensitivity of diagnosis and to uncover biochemical mechanisms that may elucidate the cause and progression of these diseases. This work includes a description of mass spectrometry-based metabolomics approaches, including some of the currently available tools, and emphasises findings from metabolomics studies of kidney diseases. We have included a varied selection of studies (disease, model, sample number, analytical platform) and focused on metabolites which were commonly reported as discriminating features between kidney disease and a control. These metabolites are likely to be robust indicators of kidney disease processes, and therefore potential biomarkers, warranting further investigation.

The incessant search for renal biomarkers: is it really justified?

PURPOSE OF REVIEW

This review summarizes the most recent and relevant findings in the search for novel biomarkers for the most common renal diseases.

RECENT FINDINGS

Unprecedented, fast-paced technical advances in biomedical research have offered an opportunity to identify novel and more specific renal biomarkers in several clinical settings. However, despite the huge efforts made, the molecules identified so far have generally failed to provide relevant information beyond what has already been generated by established biomarkers, such as serum creatinine and proteinuria, whereas the complexity and costs of these technology platforms hamper their widespread implementation.

SUMMARY

No novel renal biomarkers have added clear-cut additional value in clinical decision-making. The only exception is anti-phospholipase A2 receptor antibodies, which have been implemented successfully as a diagnostic and prognostic biomarker of membranous nephropathy. This achievement, along with the large number of ongoing collaborative projects worldwide, should lead the renal community to be quite confident regarding the successful qualification of novel and effective diagnostic, prognostic and therapeutic response biomarkers for kidney diseases, hopefully in the next few years.

Dissection of metabolic reprogramming in polycystic kidney disease reveals coordinated rewiring of bioenergetic pathways

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a genetic disorder caused by loss-of-function mutations in PKD1 or PKD2. Increased glycolysis is a prominent feature of the disease, but how it impacts on other metabolic pathways is unknown. Here, we present an analysis of mouse Pkd1 mutant cells and kidneys to investigate the metabolic reprogramming of this pathology. We show that loss of Pkd1 leads to profound metabolic changes that affect glycolysis, mitochondrial metabolism, and fatty acid synthesis (FAS). We find that Pkd1-mutant cells preferentially use glutamine to fuel the TCA cycle and to sustain FAS. Interfering with either glutamine uptake or FAS retards cell growth and survival. We also find that glutamine is diverted to asparagine via asparagine synthetase (ASNS). Transcriptional profiling of PKD1-mutant human kidneys confirmed these alterations. We find that silencing of Asns is lethal in Pkd1-mutant cells when combined with glucose deprivation, suggesting therapeutic approaches for ADPKD.

Christine Podrini et al. present a comprehensive analysis of Pkd1 mutant mouse cells and kidneys, providing new insight into autosomal dominant polycystic kidney disease (ADPKD). They find that Pkd1 loss leads to profound metabolic changes, including asparagine synthase-driven glutamine anaplerosis.

Arginine reprogramming in ADPKD results in arginine-dependent cystogenesis

Research into metabolic reprogramming in cancer has become commonplace, yet this area of research has only recently come of age in nephrology. In light of the parallels between cancer and autosomal dominant polycystic kidney disease (ADPKD), the latter is currently being studied as a metabolic disease. In clear cell renal cell carcinoma (RCC), which is now considered a metabolic disease, we and others have shown derangements in the enzyme arginosuccinate synthase 1 (ASS1), resulting in RCC cells becoming auxotrophic for arginine and leading to a new therapeutic paradigm involving reducing extracellular arginine. Based on our earlier finding that glutamine pathways are reprogrammed in ARPKD, and given the connection between arginine and glutamine synthetic pathways via citrulline, we investigated the possibility of arginine reprogramming in ADPKD. We now show that, in a remarkable parallel to RCC, ASS1 expression is reduced in murine and human ADPKD, and arginine depletion results in a dose-dependent compensatory increase in ASS1 levels as well as decreased cystogenesis in vitro and ex vivo with minimal toxicity to normal cells. Nontargeted metabolomics analysis of mouse kidney cell lines grown in arginine-deficient versus arginine-replete media suggests arginine-dependent alterations in the glutamine and proline pathways. Thus, depletion of this conditionally essential amino acid by dietary or pharmacological means, such as with arginine-degrading enzymes, may be a novel treatment for this disease.

The cpk model of recessive PKD shows glutamine dependence associated with the production of the oncometabolite 2-hydroxyglutarate

Since polycystic kidney disease (PKD) was first noted over 30 years ago to have neoplastic parallels, there has been a resurgent interest in elucidating neoplasia-relevant pathways in PKD. Taking a nontargeted metabolomics approach in the B6(Cg)-Cys1(cpk/)J (cpk) mouse model of recessive PKD, we have now characterized metabolic reprogramming in these tissues, leading to a glutamine-dependent TCA cycle shunt toward total 2-hydroxyglutarate (2-HG) production in cpk compared with B6 wild-type kidney tissue. After confirmation of increased 2-HG expression in immortalized collecting duct cpk cells as well as in human autosomal recessive PKD tissue using targeted analysis, we show that the increase in 2-HG is likely due to glutamine-sourced α-ketoglutarate. In addition, cpk cells require exogenous glutamine for growth such that inhibition of glutaminase-1 decreases cell viability as well as proliferation. This study is a demonstration of the striking parallels between recessive PKD and cancer metabolism. Our data, once confirmed in other PKD models, suggest that future therapeutic approaches targeting this pathway, such as using glutaminase inhibitors, have the potential to open novel treatment options for renal cystic disease.

The urinary proteome and metabonome differ from normal in adults with mitochondrial disease

We studied the extent and nature of renal involvement in a cohort of 117 adult patients with mitochondrial disease, by measuring urinary retinol-binding protein (RBP) and albumin; established markers of tubular and glomerular dysfunction, respectively. Seventy-five patients had the m.3243A>G mutation and the most frequent phenotypes within the entire cohort were 14 with MELAS, 33 with MIDD, and 17 with MERRF. Urinary RBP was increased in 29 of 75 of m.3243A>G patients, whereas albumin was increased in 23 of the 75. The corresponding numbers were 16 and 14, respectively, in the 42 non-m.3243A>G patients. RBP and albumin were higher in diabetic m.3243A>G patients than in nondiabetics, but there were no significant differences across the three major clinical phenotypes. The urine proteome (mass spectrometry) and metabonome (nuclear magnetic resonance) in a subset of the m.3243A>G patients were markedly different from controls, with the most significant alterations occurring in lysosomal proteins, calcium-binding proteins, and antioxidant defenses. Differences were also found between asymptomatic m.3243A>G carriers and controls. No patients had an elevated serum creatinine level, but 14% had hyponatremia, 10% had hypophosphatemia, and 14% had hypomagnesemia. Thus, abnormalities in kidney function are common in adults with mitochondrial disease, exist in the absence of elevated serum creatinine, and are not solely explained by diabetes.

Unraveling heterogeneous susceptibility and the evolution of breast cancer using a systems biology approach

Background

An essential question in cancer is why individuals with the same disease have different clinical outcomes. Progress toward a more personalized medicine in cancer patients requires taking into account the underlying heterogeneity at different molecular levels.

Results

Here, we present a model in which there are complex interactions at different cellular and systemic levels that account for the heterogeneity of susceptibility to and evolution of ERBB2-positive breast cancers. Our model is based on our analyses of a cohort of mice that are characterized by heterogeneous susceptibility to ERBB2-positive breast cancers. Our analysis reveals that there are similarities between ERBB2 tumors in humans and those of backcross mice at clinical, genomic, expression, and signaling levels. We also show that mice that have tumors with intrinsically high levels of active AKT and ERK are more resistant to tumor metastasis. Our findings suggest for the first time that a site-specific phosphorylation at the serine 473 residue of AKT1 modifies the capacity for tumors to disseminate. Finally, we present two predictive models that can explain the heterogeneous behavior of the disease in the mouse population when we consider simultaneously certain genetic markers, liver cell signaling and serum biomarkers that are identified before the onset of the disease.

Conclusions

Considering simultaneously tumor pathophenotypes and several molecular levels, we show the heterogeneous behavior of ERBB2-positive breast cancer in terms of disease progression. This and similar studies should help to better understand disease variability in patient populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0599-z) contains supplementary material, which is available to authorized users.

Systems biology of polycystic kidney disease: a critical review

The proliferation and diminishing costs of 'omics' approaches have finally opened the doors for small and medium laboratories to enter the 'systems biology era'. This is a welcome evolution that requires a new framework to design, interpret, and validate studies. Here, we highlight some of the challenges, contributions, and prospects of the 'cyst-ems biology' of polycystic kidney disease.

Stability of miRNA in human urine supports its biomarker potential

AIM

miRNAs are showing utility as biomarkers in urologic disease, however, a rigorous evaluation of their stability in urine is lacking. Here, we evaluate the stability of miRNAs in urine under clinically relevant storage procedures.

MATERIALS & METHODS

Eight healthy individuals provided clean catch urine samples that were stored at room temperature or at 4°C for 5 days, or subjected to ten freeze-thaw cycles at -80°C. For each condition, two miRNAs, miR-16 and miR-21, were quantitated by quantitative real-time PCR.

RESULTS

All conditions demonstrated a surprising degree of stability of miRNAs in the urine: by the end of ten freeze-thaw cycles, 23-37% of the initial amount remained; over the 5-day period of storage at room temperature, 35% of the initial amount remained; and at 4°C, 42-56% of the initial amount remained. Both miRNAs also showed degradation at approximately the same rate.

CONCLUSION

miRNAs are relatively stable in urine under a variety of storage conditions, which supports their utility as urinary biomarkers.

The calcium-activated chloride channel Anoctamin 1 contributes to the regulation of renal function

The role of calcium-activated chloride channels for renal function is unknown. By immunohistochemistry we demonstrate dominant expression of the recently identified calcium-activated chloride channels, Anoctamin 1 (Ano1, TMEM16A) in human and mouse proximal tubular epithelial (PTE) cells, with some expression in podocytes and other tubular segments. Ano1-null mice had proteinuria and numerous large reabsorption vesicles in PTE cells. Selective knockout of Ano1 in podocytes (Ano1-/-/Nphs2-Cre) did not impair renal function, whereas tubular knockout in Ano1-/-/Ksp-Cre mice increased urine protein excretion and decreased urine electrolyte concentrations. Purinergic stimulation activated calcium-dependent chloride currents in isolated proximal tubule epithelial cells from wild-type but not from Ano1-/-/Ksp-Cre mice. Ano1 currents were activated by acidic pH, suggesting parallel stimulation of Ano1 chloride secretion with activation of the proton-ATPase. Lack of calcium-dependent chloride secretion in cells from Ano1-/-/Ksp-Cre mice was paralleled by attenuated proton secretion and reduced endosomal acidification, which compromised proximal tubular albumin uptake. Tubular knockout of Ano1 enhanced serum renin and aldosterone concentrations, probably leading to enhanced compensatory distal tubular reabsorption, thus maintaining normal blood pressure levels. Thus, Ano1 has a role in proximal tubular proton secretion and protein reabsorption. The results correspond to regulation of the proton-ATPase by the Ano1-homolog Ist2 in yeast.

Microextraction by Packed Sorbent (MEPS) and Solid-Phase Microextraction (SPME) as Sample Preparation Procedures for the Metabolomic Profiling of Urine

For a long time, sample preparation was unrecognized as a critical issue in the analytical methodology, thus limiting the performance that could be achieved. However, the improvement of microextraction techniques, particularly microextraction by packed sorbent (MEPS) and solid-phase microextraction (SPME), completely modified this scenario by introducing unprecedented control over this process. Urine is a biological fluid that is very interesting for metabolomics studies, allowing human health and disease characterization in a minimally invasive form. In this manuscript, we will critically review the most relevant and promising works in this field, highlighting how the metabolomic profiling of urine can be an extremely valuable tool for the early diagnosis of highly prevalent diseases, such as cardiovascular, oncologic and neurodegenerative ones.

Effect of huanglianjiedu tang on fever in rats induced by 2, 4-dinitrophenol

OBJECTIVE

To study metabolic characteristics of fever in rats induced by 2, 4-dinitrophenol (DNP) and the effect of Huanglianjiedu Tang (HLJDT) on the fever.

METHODS

The urine samples were analyzed by ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry (UPLC/ESI-Q-TOF-MS) at the positive ion mode scanning, and experimental data were analyzed by the principal component analysis.

RESULTS

Eight potential biomarkers indicating the occurrence and evolvement of fever were determined according to ions in urine samples. Five of them were found increased, while the other three decreased. After HLJDD intervention, the increased five were reduced significantly in high dose group, compared with model group, while the decreased three had no obvious change. Five of the eight biomakers were identified with formyl-5-hydroxykynurenamine, gentisic acid, aminoadipic acid, phenylacetic acid, L-phenylalanyl-L-hydroxyproline on the basis of MS/MS. These biomarkers are associated with the metabolism of 5-hydroxytryptamine, tyrosine, lysine, phenylalanine and collagen protein, respectively.

CONCLUSION

HLJDT had significant effect on DNP-induced fever in rats. The effect was performed possibly by acting on 5-hydroxytryptamine in hypothalamus and some amino acid metabolism. These results suggested that HLJDT relieved fever by acting on multi-targets.

Metabolomic profiling of tumor-bearing mice

Metabolomics is one of the newcomers among the "omics" techniques, perhaps also constituting the most relevant for the study of pathophysiological conditions. Metabolomics may indeed yield not only disease-specific biomarkers but also profound insights into the etiology and progression of a variety of human disorders. Various metabolomic approaches are currently available to study oncogenesis and tumor progression in vivo, in murine tumor models. Many of these models rely on the xenograft of human cancer cells into immunocompromised mice. Understanding how the metabolism of these cells evolves in vivo is critical to evaluate the actual pertinence of xenograft models to human pathology. Here, we discuss various tumor xenograft models and methods for their metabolomic profiling to provide a short guide to investigators interested in this field of research.

Metabolomics insights into pathophysiological mechanisms of nephrology

Kidney diseases (KD), a major public health problem that affects about 10 % of the general population, manifest in progressive loss of renal function, which ultimately leads to complete kidney failure. However, current approaches based on renal histopathological results and clinical parameters lack sensitivity and are not sufficient to characterize the category and progression of nephrology or to predict nephrology progression risk reliably or to guide preventive interventions. The high incidence and financial burden of KD make it imperative to diagnose KD at early stages when therapeutic interventions are far more effective. Nowadays, the appearance of metabolomics (the high-throughput measurement and analysis of metabolites) has provided the framework for a comprehensive analysis of KD and serves as a starting point for generating novel molecular diagnostic tools for use in nephrology. Changes in the concentration profiles of a number of small-molecule metabolites found in either blood or urine can be used to localize kidney damage or assess kidneys suffering from injury. The power of metabolomics allows unparalleled opportunity to query the molecular mechanisms of KD. Novel metabolomics technologies have the ability to provide a deeper understanding of the disease beyond classical histopathology, redefine the characteristics of the disease state, and identify novel approaches to reduce renal failure. This review gives an overview of its application to important areas in clinical nephrology, with a particular focus on biomarker discovery. Great strides forward are being made in breaking down important barriers to the successful prevention and treatment of this devastating disorder.

Metabolomics in chronic kidney disease

Chronic kidney disease (CKD) represents a major challenge to public healthcare. Traditional clinical biomarkers of renal function (blood urea nitrogen and serum creatinine) are not sensitive or specific enough and only increase significantly after the presence of substantial CKD. Therefore, more sensitive biomarkers of CKD are needed. CKD-specific biomarkers at an early disease stage and early diagnosis of specific renal diseases would enable improved therapeutic treatment and reduced the personal and financial burdens. The goal of metabolomics is to identify non-targeted, global small-molecule metabolite profiles of complex samples, such as biofluids and tissues. This method offers the potential for a holistic approach to clinical medicine, as well as improvements in disease diagnoses and the understanding of pathological mechanisms. This review article presents an overview of the recent developments in the field of metabolomics, followed by an in-depth discussion of its application to the study of CKD (primary, chronic glomerulonephritis such as IgA nephropathy; secondary, chronic renal injury such as diabetic nephropathy; chronic renal failure including end-stage kidney disease with and without undergoing replacement therapies, etc), including metabolomic analytical technologies, chemometrics, and metabolomics in experimental and clinical research. We describe the current status of the identification of metabolic biomarkers in CKD. Several markers have been confirmed across multiple studies to detect CKD earlier than traditional clinical chemical and histopathological methods. The application of metabolomics in CKD studies provides researchers the opportunity to gain new insights into metabolic profiling and pathophysiological mechanisms. Particular challenges in the field are presented and placed within the context of future applications of metabolomic approaches to the studies of CKD.

A Metabolomics Profiling Study in Hand-Foot-and-Mouth Disease and Modulated Pathways of Clinical Intervention Using Liquid Chromatography/Quadrupole Time-of-Flight Mass Spectrometry

Hand-foot-and-mouth disease (HFMD), with poorly understood pathogenesis, has become a major public health threat across Asia Pacific. In order to characterize the metabolic changes of HFMD and to unravel the regulatory role of clinical intervention, we have performed a metabolomics approach in a clinical trial. In this study, metabolites profiling was performed by liquid chromatography/quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) platform from the HFMD clinical patient samples. The outcome of this study suggested that 31 endogenous metabolites were mainly involved and showed marked perturbation in HFMD patients. In addition, combination therapy intervention showed normalized tendency in HFMD patients in differential pathway. Taken together, these results indicate that metabolomics approach can be used as a complementary tool for the detection and the study of the etiology of HFMD.

Applications of metabolomics for kidney disease research: from biomarkers to therapeutic targets

Metabolomics is one of the relative newcomers of the omics techniques and is likely the one most closely related to actual real-time disease pathophysiology. Hence, it has the power to yield not only specific biomarkers but also insight into the pathophysiology of disease. Despite this power, metabolomics as applied to kidney disease is still in its early adolescence and has not yet reached the mature stage of clinical application, i.e., specific biomarker and therapeutic target discovery. On the other hand, the insight gained from hints into what makes these diseases tick, as is evident from the metabolomics pathways which have been found to be altered in kidney cancer, are now beginning to bear fruit in leading to potential therapeutic targets. It is quite likely that, with greater numbers of clinical materials and with more investigators jumping into the field, metabolomics may well change the course of kidney disease research.

Network analysis of a Pkd1-mouse model of autosomal dominant polycystic kidney disease identifies HNF4α as a disease modifier

Autosomal Dominant Polycystic Kidney Disease (ADPKD; MIM ID's 173900, 601313, 613095) leads to end-stage kidney disease, caused by mutations in PKD1 or PKD2. Inactivation of Pkd1 before or after P13 in mice results in distinct early- or late-onset disease. Using a mouse model of ADPKD carrying floxed Pkd1 alleles and an inducible Cre recombinase, we intensively analyzed the relationship between renal maturation and cyst formation by applying transcriptomics and metabolomics to follow disease progression in a large number of animals induced before P10. Weighted gene co-expression network analysis suggests that Pkd1-cystogenesis does not cause developmental arrest and occurs in the context of gene networks similar to those that regulate/maintain normal kidney morphology/function. Knowledge-based Ingenuity Pathway Analysis (IPA) software identifies HNF4α as a likely network node. These results are further supported by a meta-analysis of 1,114 published gene expression arrays in Pkd1 wild-type tissues. These analyses also predict that metabolic pathways are key elements in postnatal kidney maturation and early steps of cyst formation. Consistent with these findings, urinary metabolomic studies show that Pkd1 cystic mutants have a distinct profile of excreted metabolites, with pathway analysis suggesting altered activity in several metabolic pathways. To evaluate their role in disease, metabolic networks were perturbed by inactivating Hnf4α and Pkd1. The Pkd1/Hnf4α double mutants have significantly more cystic kidneys, thus indicating that metabolic pathways could play a role in Pkd1-cystogenesis.

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most common genetic cause of polycystic kidney disease and is responsible for 4.6% of the end-stage renal disease (ESRD) cases in the United States. It is most often caused by mutation in the PKD1 gene. To understand this disease, we made a mouse model in which we could delete the Pkd1 gene and study the animal as its kidney becomes cystic. Using this model, we had previously found that the maturation status of the animal determines whether cysts form within days or within months, and we had narrowed down this switch to a two-day interval. In the current study, we used the rapid cyst-forming model to analyze the expression pattern of thousands of genes in mutant and control kidneys, and metabolites excreted in the urine. Our results identify a number of genes that may be involved in cyst formation and suggest that metabolic changes may play a role in ADPKD and could alter disease progression. These analyses also predict that metabolic pathways are key elements in normal postnatal kidney maturation.

Low-dose ionizing radiation-induced blood plasma metabolic response in a diverse genetic mouse population

Understanding the biological effects and biochemical mechanisms of low-dose ionizing radiation (LDIR) is important for setting exposure limits for the safe use of nuclear power and medical diagnostic procedures. Although several studies have highlighted the effects of ionizing radiation on metabolism, most studies have focused on uniform genetic mouse populations. Here, we report the metabolic response to LDIR (10 cGy X ray) on a genetically diverse mouse population (142 mice) generated from a cross of radiation-sensitive (BALB/c) and radiation-resistant (SPRET/EiJ) parental strains. GC-TOF profiling of plasma metabolites was used to compare exposed vs. sham animals. From this, 16 metabolites were significantly altered in the LDIR treated vs. sham group. Use of two significantly altered metabolites, thymine and 2-monostearin, was found to effectively segregate the two treatments. Multivariate statistical analysis was used to identify genetic polymorphisms correlated with metabolite abundance (e.g., amino acids, fatty acids, nucleotides and TCA cycle intermediates). Genetic analysis of metabolic phenotypes showed suggestive linkages for fatty acid and amino acid metabolism. However, metabolite abundance was found to be a function of low-dose ionizing radiation exposure, and not of the underlying genetic variation.

Systematic variations associated with renal disease uncovered by parallel metabolomics of urine and serum

Background

Membranous nephropathy is an important glomerular disease characterized by podocyte injury and proteinuria, but no metabolomics research was reported as yet. Here, we performed a parallel metabolomics study, based on human urine and serum, to comprehensively profile systematic metabolic variations, identify differential metabolites, and understand the pathogenic mechanism of membranous nephropathy.

Results

There were obvious metabolic distinctions between the membranous nephropathy patients with urine protein lower than 3.5 g/24 h (LUPM) and those higher than 3.5 g/24 h (HUPM) by Partial Least Squares Discriminant Analysis (PLS-DA) model analysis. In total, 26 urine metabolites and 9 serum metabolites were identified to account for such differences, and the majority of metabolites were significantly increased in HUPM patients for both urines and serums. Combining the results of urine with serum, all differential metabolites were classified to 5 classes. This classification helps globally probe the systematic metabolic alterations before and after blood flowing through kidney. Citric acid and 4 amino acids were markedly increased only in the serum samples of HUPM patients, implying more impaired filtration function of kidneys of HUPM patients than LUPM patients. The dicarboxylic acids, phenolic acids, and cholesterol were significantly elevated only in urines of HUPM patients, suggesting more severe oxidative attacks than LUPM patients.

Conclusions

Parallel metabolomics of urine and serum revealed the systematic metabolic variations associated with LUPM and HUPM patients, where HUPM patients suffered more severe injury of kidney function and oxidative stresses than LUPM patients. This research exhibited a promising application of parallel metabolomics in renal diseases.

Metabolomics in the study of kidney diseases

Metabolomics--the nontargeted measurement of all metabolites produced by the body--is beginning to show promise in both biomarker discovery and, in the form of pharmacometabolomics, in aiding the choice of therapy for patients with specific diseases. In its two basic forms (pattern recognition and metabolite identification), this developing field has been used to discover potential biomarkers in several renal diseases, including acute kidney injury (attributable to a variety of causes), autosomal dominant polycystic kidney disease and kidney cancer. NMR and gas chromatography or liquid chromatography, together with mass spectrometry, are generally used to separate and identify metabolites. Many hurdles need to be overcome in this field, such as achieving consistency in collection of biofluid samples, controlling for batch effects during the analysis and applying the most appropriate statistical analysis to extract the maximum amount of biological information from the data obtained. Pathway and network analyses have both been applied to metabolomic analysis, which vastly extends its clinical relevance and effects. In addition, pharmacometabolomics analyses, in which a metabolomic signature can be associated with a given therapeutic effect, are beginning to appear in the literature, which will lead to personalized therapies. Thus, metabolomics holds promise for early diagnosis, increased choice of therapy and the identification of new metabolic pathways that could potentially be targeted in kidney disease.

Metabolomics in the study of kidney diseases

Metabolomics--the nontargeted measurement of all metabolites produced by the body--is beginning to show promise in both biomarker discovery and, in the form of pharmacometabolomics, in aiding the choice of therapy for patients with specific diseases. In its two basic forms (pattern recognition and metabolite identification), this developing field has been used to discover potential biomarkers in several renal diseases, including acute kidney injury (attributable to a variety of causes), autosomal dominant polycystic kidney disease and kidney cancer. NMR and gas chromatography or liquid chromatography, together with mass spectrometry, are generally used to separate and identify metabolites. Many hurdles need to be overcome in this field, such as achieving consistency in collection of biofluid samples, controlling for batch effects during the analysis and applying the most appropriate statistical analysis to extract the maximum amount of biological information from the data obtained. Pathway and network analyses have both been applied to metabolomic analysis, which vastly extends its clinical relevance and effects. In addition, pharmacometabolomics analyses, in which a metabolomic signature can be associated with a given therapeutic effect, are beginning to appear in the literature, which will lead to personalized therapies. Thus, metabolomics holds promise for early diagnosis, increased choice of therapy and the identification of new metabolic pathways that could potentially be targeted in kidney disease.

Urine metabolomics for kidney cancer detection and biomarker discovery

Renal cell carcinoma (RCC) is one of the few human cancers whose incidence is increasing. The disease regularly progresses asymptomatically and is frequently metastatic upon presentation, thereby necessitating the development of an early method of detection. A metabolomic approach for biomarker detection using urine as a biofluid is appropriate since the tumor is located in close proximity to the urinary space. By comparing the composition of urine from individuals with RCC to control individuals, differences in metabolite composition of this biofluid can be identified, and these data can be utilized to create a clinically applicable and, possibly, bedside assay. Recent studies have shown that sample handling and processing greatly influences the variability seen in the urinary metabolome of both cancer and control patients. Once a standard method of collection is developed, identifying metabolic derangements associated with RCC will also lead to the investigation of novel targets for therapeutic intervention. The objective of this review is to discuss existing methods for sample collection, processing, data analysis, and recent findings in this emerging field.

Untargeted metabolomics identifies enterobiome metabolites and putative uremic toxins as substrates of organic anion transporter 1 (Oat1)

Untargeted metabolomics on the plasma and urine from wild-type and organic anion transporter-1 (Oat1/Slc22a6) knockout mice identified a number of physiologically important metabolites, including several not previously linked to Oat1-mediated transport. Several, such as indoxyl sulfate, derive from Phase II metabolism of enteric gut precursors and accumulate in chronic kidney disease (CKD). Other compounds included vitamins (pantothenic acid, 4-pyridoxic acid), urate, and metabolites in the tryptophan and nucleoside pathways. Three metabolites, indoxyl sulfate, kynurenine, and xanthurenic acid, were elevated in the plasma and interacted strongly and directly with Oat1 in vitro with IC50 of 18, 12, and 50 μM, respectively. A pharmacophore model based on several identified Oat1 substrates was used to screen the NCI database and candidate compounds interacting with Oat1 were validated in an in vitro assay. Together, the data suggest a complex, previously unidentified remote communication between the gut microbiome, Phase II metabolism in the liver, and elimination via Oats of the kidney, as well as indicating the importance of Oat1 in the handling of endogenous toxins associated with renal failure and uremia. The possibility that some of the compounds identified may be part of a larger remote sensing and signaling pathway is also discussed.

Detection of autosomal dominant polycystic kidney disease by NMR spectroscopic fingerprinting of urine

Autosomal dominant polycystic kidney disease (ADPKD) is a frequent cause of kidney failure; however, urinary biomarkers for the disease are lacking. In a step towards identifying such markers, we used multidimensional-multinuclear nuclear magnetic resonance (NMR) spectroscopy with support vector machine-based classification and analyzed urine specimens of 54 patients with ADPKD and slightly reduced estimated glomerular filtration rates. Within this cohort, 35 received medication for arterial hypertension and 19 did not. The results were compared with NMR profiles of 46 healthy volunteers, 10 ADPKD patients on hemodialysis with residual renal function, 16 kidney transplant patients, and 52 type 2 diabetic patients with chronic kidney disease. Based on the average of 51 out of 701 NMR features, we could reliably discriminate ADPKD patients with moderately advanced disease from ADPKD patients with end-stage renal disease, patients with chronic kidney disease of other etiologies, and healthy probands with an accuracy of >80%. Of the 35 patients with ADPKD receiving medication for hypertension, most showed increased excretion of proteins and also methanol. In contrast, elevated urinary methanol was not found in any of the control and other patient groups. Thus, we found that NMR fingerprinting of urine differentiates ADPKD from several other kidney diseases and individuals with normal kidney function. The diagnostic and prognostic potential of these profiles requires further evaluation.