Blood, urine and faecal metabolite profiles in the study of adult renal disease

Urine metabolite changes after cardiac surgery predict acute kidney injury

Background

Acute kidney injury (AKI) is a serious complication in patients undergoing cardiac surgery, with the underlying mechanism remaining elusive and a lack of specific biomarkers for cardiac surgery-associated AKI (CS-AKI).

Methods

We performed an untargeted metabolomics analysis of urine samples procured from a cohort of patients with or without AKI at 6 and 24 h following cardiac surgery. Based on the differential urinary metabolites discovered, we further examined the expressions of the key metabolic enzymes that regulate these metabolites in kidney during AKI using a mouse model of ischemia-reperfusion injury (IRI) and in hypoxia-treated tubular epithelial cells (TECs).

Results

The urine metabolomic profiles in AKI patients were significantly different from those in non-AKI patients, including upregulation of tryptophan metabolism- and aerobic glycolysis-related metabolites, such as l-tryptophan and d-glucose-1-phosphate, and downregulation of fatty acid oxidation (FAO) and tricarboxylic acid (TCA) cycle-related metabolites. Spearman correlation analysis showed that serum creatinine was positively correlated with urinary l-tryptophan and indole, which had high accuracy for predicting AKI. In animal experiments, we demonstrated that the expression of rate-limiting enzymes in glycolysis, such as hexokinase II (HK2), was significantly upregulated during renal IRI. However, the TCA cycle-related key enzyme citrate synthase was significantly downregulated after IRI. In vitro, hypoxia induced downregulation of citrate synthase in TECs. In addition, FAO-related gene peroxisome proliferator-activated receptor alpha (PPARα) was remarkably downregulated in kidney during renal IRI.

Conclusion

This study presents urinary metabolites related to CS-AKI, indicating the rewiring of the metabolism in kidney during AKI, identifying potential AKI biomarkers.

Metabolomic Profiles in Patients with Cervical Cancer Undergoing Cisplatin and Radiation Therapy

This study was aimed to evaluate endogenous metabolic changes before and after cisplatin and radiation therapy in patients with cervical cancer via untargeted metabolomic analysis using plasma samples. A total of 13 cervical cancer patients were enrolled in this study. Plasma samples were collected from each patient on two occasions: approximately one week before therapy (P1) and after completion of cisplatin and radiation therapy (P2). Of the 13 patients, 12 patients received both cisplatin and radiation therapy, whereas one patient received radiation therapy alone. The samples were analyzed using the Ultimate 3000 coupled with Q ExactiveTM Focus Hybrid Quadrupole-OrbitrapTM mass spectrometry (Thermo Fisher Scientific, Waltham, MA, USA). Chromatographic separation utilized a Kinetex C18 column 2.1×100 mm (2.6 μm) (Phenomenex, Torrance, CA, USA), and the temperature was maintained at 40°C. Following P2, there were statistically significant increases in the concentrations of indoxyl sulfate, phenylacetylglutamine, Lysophosphatidyethanolamine (LysoPE) (18:1), and indole-3-acetic acid compared with the concentrations observed at P1. Specifically, in the human papillomavirus (HPV) noninfection group, indoxyl sulfate, LysoPE (18:1), and phenylacetylglutamine showed statistically significant increases at P2 compared with P1. No significant changes in metabolite concentrations were observed in the HPV infection group. Indoxyl sulfate, LysoPE (18:1), phenylacetylglutamine, and indole-3-acetic acid were significantly increased following cisplatin and radiation therapy.

Participants in the Trans-Antarctic Winter Traverse Expedition Showed Increased Bacterial Load and Diversity in Saliva but Maintained Individual Differences within Stool Microbiota and Across Metabolite Fingerprints

Understanding the impact of long-term physiological and environmental stress on the human microbiota and metabolome may be important for the success of space flight. This work is logistically difficult and has a limited number of available participants. Terrestrial analogies present important opportunities to understand changes in the microbiota and metabolome and how this may impact participant health and fitness. Here, we present work from one such analogy: the Transarctic Winter Traverse expedition, which we believe is the first assessment of the microbiota and metabolome from different bodily locations during prolonged environmental and physiological stress. Bacterial load and diversity were significantly higher during the expedition when compared with baseline levels (p < 0.001) in saliva but not stool, and only a single operational taxonomic unit assigned to the Ruminococcaceae family shows significantly altered levels in stool (p < 0.001). Metabolite fingerprints show the maintenance of individual differences across saliva, stool, and plasma samples when analysed using flow infusion electrospray mass spectrometry and Fourier transform infrared spectroscopy. Significant activity-associated changes in terms of both bacterial diversity and load are seen in saliva but not in stool, and participant differences in metabolite fingerprints persist across all three sample types.

Urine metabolites for preoperative prediction of acute kidney injury after coronary artery bypass graft surgery

OBJECTIVE

Acute kidney injury is a common complication after on-pump coronary artery bypass grafting. Prediction of acute kidney injury remains a challenge. Our study aims to identify a panel of urine metabolites for preoperative warning of acute kidney injury after on-pump coronary artery bypass grafting.

METHODS

A total of 159 patients undergoing isolated on-pump coronary artery bypass grafting were enrolled from July 7, 2017, to May 17, 2019. Preoperative urine samples were analyzed with the approach of liquid chromatography-mass spectrometry-based urine metabolomics. The study end point was the episode of acute kidney injury within 48 hours postoperatively. The predictive performance was determined by the area under the curve and calibration curve. The results were validated using bootstrap resampling.

RESULTS

The acute kidney injury (n = 55) and nonacute kidney injury (n = 104) groups showed significant different metabolic profiling. A total of 28 metabolites showed significant differences between the acute kidney injury and nonacute kidney injury groups. A metabolite panel of 5 metabolites (tyrosyl-gamma-glutamate, deoxycholic acid glycine conjugate, 5-acetylamino-6-amino-3-methyluracil, arginyl-arginine, and L-methionine) was discovered to have a good predicting performance (area under the curve, 0.89; 95% confidence interval, 0.82-0.93), which is higher than the clinical factor-based model (area under the curve, 0.63; 95% confidence interval, 0.53-0.72). Internal validation by bootstrap resampling showed an adjusted area under the curve of 0.88, and the calibration curve demonstrated good agreement between prediction and observation in the probability of postoperative acute kidney injury. Decision curve analysis revealed a superior net benefit of the metabolite model over the traditional clinical factor-based model.

CONCLUSIONS

We present 5 urine metabolites related to acute kidney injury after coronary artery bypass grafting. This metabolite model may serve as a preoperative warning of acute kidney injury after on-pump coronary artery bypass grafting.

Altered serum metabolome associated with vascular calcification developed from CKD and the critical pathways

Introduction

Vascular calcification (VC) is more likely to be detected in the chronic kidney disease (CKD) population. The mechanism of VC development from CKD is different from that for simple VC and has always been a major research area. The aim of this study was to detect alterations in the metabolome during development of VC in CKD and to identify the critical metabolic pathways and metabolites involved in its pathogenesis.

Methods

Rats in the model group were given an adenine gavage combined with a high-phosphorus diet to imitate VC in CKD. The aorta calcium content was measured and used to divide the model group into a VC group and non-vascular calcification group (non-VC group). The control group was fed a normal rat diet and given a saline gavage. Ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) was used to determine the altered serum metabolome in the control, VC, and non-VC groups. The identified metabolites were mapped into the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (https://www.genome.jp/kegg/) for pathway and network analyses.

Result

There were 14 metabolites that changed significantly in the VC group, with three metabolic pathways playing critical roles in the pathogenesis of VC in CKD: steroid hormone biosynthesis; valine, leucine and isoleucine biosynthesis; and pantothenate and CoA biosynthesis.

Conclusion

Our results indicated changes in the expression of steroid sulfatase and estrogen sulfotransferase, and down-regulation of the in situ synthesis of estrogens in the VC group. In conclusion, the serum metabolome alters significantly during the pathogenesis of VC in CKD. The key pathways, metabolites, and enzymes we identified are worth further study and may become a promising therapeutic target for the treatment of VC in CKD.

Shenkang Injection for Treating Renal Fibrosis-Metabonomics and Regulation of E3 Ubiquitin Ligase Smurfs on TGF-β/Smads Signal Transduction

At present, TGF-β is the most critical fibrogenic factor known. Smad ubiquitin ligase Smurfs play an important role in the regulation of the TGF-/Smads signaling pathway, which is linked to metabolite changes in renal fibrosis. Previous studies have shown that Shenkang injection can prevent and treat chronic kidney disease through multiple channels of action. However, the precise relationship between Shenkang injection and the regulation of the TGF-/Smads signaling pathway in the treatment of chronic kidney disease is unknown. Here, we evaluated the pharmacological effects of Shenkang injection on ubiquitination and metabolic changes of the TGF-β/Smads signaling pathway in UUO mice using pathology-related indicators, immunoprecipitation, subcellular co-location, and metabonomics analysis. Our findings indicate that Shenkang injection can promote nuclear translocation of Smurf1 and Smurf2 to TGF- membrane receptors TR-I and Smad2 and ubiquitinated degradation of these proteins. Furthermore, the formation of TβR-I/TβR-II, TβR-I/Smad2, and TβR-I/Smad3 complexes was inhibited to negatively regulate the TGF-β/Smad signaling pathway induced renal tubular epithelial transdifferentiation (EMT). The EMT process is not very relevant in vivo, although it is clear that TGF-β induces EMT in cultured cells, which has been demonstrated by numerous teams around the world. However, this is not the case with the in vivo models of kidney fibrosis, especially UUO. In addition, Shenkang injection can improve amino acid metabolism, purine metabolism, and fatty acid metabolism disorders.

The GenoDiabMar Registry: A Collaborative Research Platform of Type 2 Diabetes Patients

The GenoDiabMar registry is a prospective study that aims to provide data on demographic, biochemical, and clinical changes in type 2 diabetic (T2D) patients attending real medical outpatient consultations. This registry is also used to find new biomarkers related to the micro- and macrovascular complications of T2D, with a particular focus on diabetic nephropathy. With this purpose, longitudinal serum and urine samples, DNA banking, and data on 227 metabolomics profiles, 77 immunoglobulin G glycomics traits, and other emerging biomarkers were recorded in this cohort. In this study, we show a detailed longitudinal description of the clinical and analytical parameters of this registry, with a special focus on the progress of renal function and cardiovascular events. The main objective is to analyze whether there are differential risk factors for renal function deterioration between sexes, as well as to analyze cardiovascular events and mortality in this population. In total, 650 patients with a median age of 69 (14) with different grades of chronic kidney disease—G1−G2 (eGFR > 90−60 mL/min/1.73 m2) 50.3%, G3 (eGFR; 59−30 mL/min/1.73 m2) 31.4%, G4 (eGFR; 29−15 mL/min/1.73 m2) 10.8%, and G5 (eGFR < 15 mL/min/1.73 m2) 7.5%—were followed up for 4.7 (0.65) years. Regardless of albuminuria, women lost 0.93 (0.40−1.46) fewer glomerular filtration units per year than men. A total of 17% of the participants experienced rapid deterioration of renal function, 75.2% of whom were men, with differential risk factors between sexes—severe macroalbuminuria > 300 mg/g for men OR [IQ] 2.40 [1.29:4.44] and concomitant peripheral vascular disease 3.32 [1.10:9.57] for women. Overall mortality of 23% was detected (38% of which was due to cardiovascular etiology). We showed that kidney function declined faster in men, with different risk factors compared to women. Patients with T2D and kidney involvement have very high mortality and an important cardiovascular burden. This cohort is proposed as a great tool for scientific collaboration for studies, whether they are focused on T2D, or whether they are interested in comparing differential markers between diabetic and non-diabetic populations.

Acylcarnitines: Can They Be Biomarkers of Diabetic Nephropathy?

Diabetic nephropathy (DN), one of the most serious microvascular complications of diabetes mellitus (DM), may progress to end-stage renal disease (ESRD). Current biochemical biomarkers, such as urinary albumin excretion rate (UAER), have limitations for early screening and monitoring of DN. Recent studies have identified some metabolites as candidate biomarkers for early detection of DN. In this review, we summarize the role of dysregulated acylcarnitines (AcylCNs) in DN pathophysiology. Lower abundance of short- and medium-chain AcylCNs and higher long-chain AcylCNs often occurred in DM with normal albuminuria and microalbuminuria, compared with advanced stages of DN. The increase of long-chain AcylCNs was supposed to be an adaptive compensation in fat acids (FAs) oxidation in the early stage of DN. Conversely, the decrease of long-chain AcylCNs was due to incomplete oxidation of FAs in advanced stage of DN. Thus, AcylCNs may serve as sensitive biomarkers in predicting the risk of DN.

Huangjinsan ameliorates adenine-induced chronic kidney disease by regulating metabolic profiling

Chronic kidney disease is an increasingly serious public health problem worldwide. Our recent studies have shown that Huangjinsan has a renal protective effect on chronic kidney disease, but the specific mechanism by which this effect occurs is not clear. To study the therapeutic effect of Huangjinsan on chronic kidney disease and to explore its possible mechanism of action through nontargeted metabolomics methods, a chronic kidney disease rat model was induced by adenine, and the Huangjinsan extract was given by oral gavage. Body weight, the kidney index, pathological sections, and a series of biochemical indicators were measured. High-performance liquid chromatography quadrupole time-of-flight mass spectrometry was used to analyze the changes in the plasma metabolome. Huangjinsan significantly reduced indicators of kidney damage, including total protein, albumin, the total protein to creatinine ratio, and the albumin to creatinine ratio in urine, as well as IL-2, MCP-1α, and blood urea levels in plasma. Based on nontargeted metabolomics, 13 metabolites related to chronic kidney disease were discovered. These metabolites are closely related to glycerophospholipid metabolism, arginine and proline metabolism, and sphingolipid metabolism. We found that Huangjinsan can restore the renal function of adenine-induced chronic kidney disease by regulating the metabolic profile.

Fecal Metabolomics Reveals Distinct Profiles of Kidney Transplant Recipients and Healthy Controls

Monitoring graft recipients remains dependent on traditional biomarkers and old technologies lacking specificity, sensitivity, or accuracy. Recently, metabolomics is becoming a promising approach that may offer to kidney transplants a more effective and specific monitoring. Furthermore, emerging evidence suggested a fundamental role of gut microbiota as an important determinant of patients’ metabolomes. In the current study, we enrolled forty stable renal allografts recipients compared to twenty healthy individuals. Samples were taken at different time points from patient to patient following transplantation surgery, which varied from 3 months to 22 years post-graft. All patients started the immunosuppression therapy immediately following kidney graft (Day 0). Gas chromatography–mass spectrometry (GC–MS) was employed to perform untargeted analysis of fecal metabolites. Globally, the fecal metabolic signature was significantly different between kidney transplants and the control group. Fecal metabolome was dominated by lipids (sterols and fatty acids) in the stable transplant group compared to the controls (p < 0.05). Overall, 18 metabolites were significantly altered within kidney transplant recipients. Furthermore, the most notable altered metabolic pathways in kidney transplants include ubiquinone and other terpenoid-quinone biosynthesis, tyrosine metabolism, tryptophan biosynthesis, and primary bile acid biosynthesis. Fecal metabolites could effectively distinguish stable transplant recipients from controls, supporting the potential utility of metabolomics in rapid and non-invasive diagnosis to produce relevant biomarkers and to help clinicians in monitoring kidney transplants. Further investigations are needed to clarify the physiological relevance of fecal metabolome and to assess the impact of microbiota modulation.

Metabolomic Profiling for Diagnosis and Prognostication in Surgery: A Scoping Review

OBJECTIVE

This review assimilates and critically evaluates available literature regarding the use of metabolomic profiling in surgical decision-making.

BACKGROUND

Metabolomic profiling is performed by nuclear magnetic resonance spectroscopy or mass spectrometry of biofluids and tissues to quantify biomarkers (ie, sugars, amino acids, and lipids), producing diagnostic and prognostic information that has been applied among patients with cardiovascular disease, inflammatory bowel disease, cancer, and solid organ transplants.

METHODS

PubMed was searched from 1995 to 2019 to identify studies investigating metabolomic profiling of surgical patients. Articles were included and assimilated into relevant categories per PRISMA-ScR guidelines. Results were summarized with descriptive analytical methods.

RESULTS

Forty-seven studies were included, most of which were retrospective studies with small sample sizes using various combinations of analytic techniques and types of biofluids and tissues. Results suggest that metabolomic profiling has the potential to effectively screen for surgical diseases, suggest diagnoses, and predict outcomes such as postoperative complications and disease recurrence. Major barriers to clinical adoption include a lack of high-level evidence from prospective studies, heterogeneity in study design regarding tissue and biofluid procurement and analytical methods, and the absence of large, multicenter metabolome databases to facilitate systematic investigation of the efficacy, reproducibility, and generalizability of metabolomic profiling diagnoses and prognoses.

CONCLUSIONS

Metabolomic profiling research would benefit from standardization of study design and analytic approaches. As technologies improve and knowledge garnered from research accumulates, metabolomic profiling has the potential to provide personalized diagnostic and prognostic information to support surgical decision-making from preoperative to postdischarge phases of care.

Metabolome and microbiome in kidney diseases

Despite several decades of intensive research and hard work in nephrology, a void exists in the availability of markers for identifying at-risk individuals, diagnosing diseases at incipient stage, and predicting treatment response. Most of the current widely available diagnostic tools such as creatinine, urine analysis, and imaging studies are quite insensitive such that about half of the kidney function is lost before perceivable changes are observed with these tests. In addition, these parameters are affected by factors other than renal, questioning their specificity. Renal biopsy, though specific, is quite expensive, risky, and invasive. The recent surge in the knowledge of small molecules in the tissue and body fluids, "metabolomics," thanks to the Human Metabolome Database created by the Human Metabolome Project, has opened a new avenue for better understanding the disease pathogenesis and, in parallel, to identify novel biomarkers and druggable targets. Kidney, by virtue of its metabolic machinery and also being a major handler of metabolites generated by other tissues, is very much amenable to the metabolomic approach of studying its various perturbations. The gut microbiome, characterized by the Human Microbiome Project, is one of the principal players in metabolomics. Changes in metabolite profile due to alterations in gut microbiome can occur either as a cause or consequence of renal diseases. Unmasking the renal-metabolome-microbiome link has a great potential to script a new era in the diagnosis and management of renal diseases.

Effect of Added Dietary Betaine and Soluble Fiber on Metabolites and Fecal Microbiome in Dogs with Early Renal Disease

Renal diets are recommended for dogs with chronic kidney disease (CKD). This study examined the effects of foods with added betaine and fiber on the plasma and fecal metabolome and fecal microbiome in dogs with early stage CKD. At baseline, several metabolites differed between healthy dogs and those with CKD. Dogs with CKD (n = 28) received a control food, low soluble fiber plus betaine food (0.5% betaine, 0.39% oat beta-glucan, and 0.27% short-chain fructooligosaccharides (scFOS)), or high soluble fiber plus betaine food (0.5% betaine, 0.59% oat beta-glucan, and 0.41% scFOS) each for 10 weeks in different sequences. Consumption of test foods led to several favorable, significant changes in the plasma metabolome, including decreases of several uremic toxins and other deleterious metabolites, and increases in favorable metabolites compared with the control food. Only 7 fecal metabolites significantly changed with consumption of the test foods compared with the control food, largely increases in polyphenols and lignans. Few changes were seen in the fecal microbiome, though some taxa that significantly changed in response to the test foods have beneficial effects on health, with some negatively correlating with uremic toxins. Overall, foods with added betaine and soluble fiber showed positive effects on the plasma and fecal metabolomes.

Longitudinal analysis of fecal microbiome and metabolome during renal fibrotic progression in a unilateral ureteral obstruction animal model

Renal fibrosis is a major pathological process in the progression of various chronic kidney diseases to end-stage renal disease (ESRD). Growing evidence has suggested that gut microbiota dysbiosis is closely related to ESRD. However, the interplay between altered fecal microbiome and metabolome during the renal fibrotic process remains unclear. Herein, an integrated approach of 16S ribosomal DNA sequencing combined with an ultra-high performance liquid chromatography-mass spectrometry-based metabolomics platform was applied to investigate the dynamic changes of fecal microbiota and metabolites throughout renal fibrosis progression in a mouse model of unilateral ureteral obstruction (UUO). The composition of gut microbiota changed markedly before and after UUO surgery. UUO mice showed a decrease in short-chain fatty acids-producing genera, including Bacteroides, Prevotellaceae_UCG-001, Roseburia, and Lachnospiraceae_NK4A136_group, as well as an increase in the genera Parasutterella and Alistipes, which changed dynamically over time. Additionally, 41 differential metabolites, mainly involved in 12 metabolic pathways, including inositol phosphate metabolism, primary bile acid biosynthesis, biosynthesis of unsaturated fatty acids, taurine and hypotaurine metabolism, purine metabolism, were identified in the UUO mice before and after surgery. Four fecal metabolites, myo-inositol, dodecanoic acid, N-acetylputrescine, and anthranilic acid, were positively associated with the progression of renal fibrosis. Moreover, by using multi-omics analyses, we found the alteration in UUO-related gut microbiota was correlated with a change in fecal metabolites. Therefore, our results provide insights into disturbances of the microbiome-metabolome interface in the progression of UUO-related renal fibrosis.

Changes in the Fecal Metabolome Are Associated with Feeding Fiber Not Health Status in Cats with Chronic Kidney Disease

The objective was to determine the effects of feeding different fiber sources to cats with chronic kidney disease (CKD) compared with healthy cats (both n = 10) on fecal metabolites. A cross-over within split-plot study design was performed using healthy and CKD cats (IRIS stage 1, 2, and 3). After cats were fed a complete and balanced dry food designed to aid in the management of renal disease for 14 days during a pre-trial period, they were randomly assigned to two fiber treatments for 4 weeks each. The treatment foods were formulated similar to pre-trial food and contained 0.500% betaine, 0.586% oat beta glucan, and either 0.407% short chain fructooligosaccharides (scFOS) fiber or 3.44% apple pomace. Both treatment foods had similar crude fiber (2.0 and 2.1% for scFOS and apple pomace, respectively) whereas soluble fiber was 0.8 and 1.6%, respectively. At baseline, CKD had very little impact on the fecal metabolome. After feeding both fiber sources, some fecal metabolite concentrations were significantly different compared with baseline. Many fecal uremic toxins decreased, although in healthy cats some increased; and some more so when feeding apple pomace compared with scFOS, e.g., hippurate, 4-hydroxyhippurate, and 4-methylcatechol sulfate; the latter was also increased in CKD cats. Changes in secondary bile acid concentrations were more numerous in healthy compared with CKD cats, and cats in both groups had greater increases in some secondary bile acids after consuming apple pomace compared with scFOS, e.g., tauroursodeoxycholate and hyocholate. Although changes associated with feeding fiber were more significant than changes associated with disease status, differential modulation of the gut-kidney axis using dietary fiber may benefit cats.

A metabolomics-based molecular pathway analysis of how the sodium-glucose co-transporter-2 inhibitor dapagliflozin may slow kidney function decline in patients with diabetes

AIM

To investigate which metabolic pathways are targeted by the sodium-glucose co-transporter-2 inhibitor dapagliflozin to explore the molecular processes involved in its renal protective effects.

METHODS

An unbiased mass spectrometry plasma metabolomics assay was performed on baseline and follow-up (week 12) samples from the EFFECT II trial in patients with type 2 diabetes with non-alcoholic fatty liver disease receiving dapagliflozin 10 mg/day (n = 19) or placebo (n = 6). Transcriptomic signatures from tubular compartments were identified from kidney biopsies collected from patients with diabetic kidney disease (DKD) (n = 17) and healthy controls (n = 30) from the European Renal cDNA Biobank. Serum metabolites that significantly changed after 12 weeks of dapagliflozin were mapped to a metabolite-protein interaction network. These proteins were then linked with intra-renal transcripts that were associated with DKD or estimated glomerular filtration rate (eGFR). The impacted metabolites and their protein-coding transcripts were analysed for enriched pathways.

RESULTS

Of all measured (n = 812) metabolites, 108 changed (P < 0.05) during dapagliflozin treatment and 74 could be linked to 367 unique proteins/genes. Intra-renal mRNA expression analysis of the genes encoding the metabolite-associated proteins using kidney biopsies resulted in 105 genes that were significantly associated with eGFR in patients with DKD, and 135 genes that were differentially expressed between patients with DKD and controls. The combination of metabolites and transcripts identified four enriched pathways that were affected by dapagliflozin and associated with eGFR: glycine degradation (mitochondrial function), TCA cycle II (energy metabolism), L-carnitine biosynthesis (energy metabolism) and superpathway of citrulline metabolism (nitric oxide synthase and endothelial function).

CONCLUSION

The observed molecular pathways targeted by dapagliflozin and associated with DKD suggest that modifying molecular processes related to energy metabolism, mitochondrial function and endothelial function may contribute to its renal protective effect.

Urinary proteome and metabolome in dogs (Canis lupus familiaris): The effect of chronic kidney disease

Chronic kidney disease (CKD) is a progressive and irreversible disease. Although urine is an ideal biological sample for proteomics and metabolomics studies, sensitive and specific biomarkers are currently lacking in dogs. This study characterised dog urine proteome and metabolome aiming to identify and possibly quantify putative biomarkers of CKD in dogs. Twenty-two healthy dogs and 28 dogs with spontaneous CKD were selected and urine samples were collected. Urinary proteome was separated by SDS-PAGE and analysed by mass spectrometry, while urinary metabolome was analysed in protein-depleted samples by 1D ¹H NMR spectra. The most abundant proteins in urine samples from healthy dogs were uromodulin, albumin and, in entire male dogs, arginine esterase. In urine samples from CKD dogs, the concentrations of uromodulin and albumin were significantly lower and higher, respectively, than in healthy dogs. In addition, these samples were characterised by a more complex protein pattern indicating mixed glomerular (protein bands ≥65 kDa) and tubular (protein bands <65 kDa) proteinuria. Urine spectra acquired by NMR allowed the identification of 86 metabolites in healthy dogs, belonging to 49 different pathways mainly involved in amino acid metabolism, purine and aminoacyl-tRNA biosynthesis or tricarboxylic acid cycle. Seventeen metabolites showed significantly different concentrations when comparing healthy and CKD dogs. In particular, carnosine, trigonelline, and cis-aconitate, might be suggested as putative biomarkers of CKD in dogs. SIGNIFICANCE: Urine is an ideal biological sample, however few proteomics and metabolomics studies investigated this fluid in dogs and in the context of CKD (chronic kidney disease). In this research, applying a multi-omics approach, new insights were gained regarding the molecular changes triggered by this disease in canine urinary proteome and metabolome. In particular, the involvement of the tubular component was highlighted, suggesting uromodulin, trigonelline and carnosine as possible biomarkers of CKD in dogs.

Metabolomic Analysis Reveals Distinct Profiles in the Plasma and Urine Associated with IgE Reactions in Childhood Asthma

Several metabolomics studies have identified altered metabolic pathways that are related to asthma. However, an integrative analysis of the metabolic responses across blood and urine for a comprehensive framework of asthma in early childhood remains lacking. Fifty-four age-matched children with asthma (n = 28) and healthy controls (n = 26) were enrolled. Metabolome analysis of the plasma and urine samples was performed using ¹H-nuclear magnetic resonance (NMR) spectroscopy coupled with partial least-squares discriminant analysis (PLS-DA). Integrated analysis of blood and urine metabolic profiling related to IgE reactions for childhood asthma was investigated. A significantly higher plasma histidine level was found, in parallel with lower urinary 1-methylnicotinamide and trimethylamine N-oxide (TMAO) levels, in children with asthma compared to healthy controls. Compared to children without allergic sensitization, 11 (92%) plasma metabolites and 8 (80%) urinary metabolites were found to be significantly different in children with IgE and food sensitization respectively. There were significant correlations between the plasma 3-hydroxybutyric acid and excreted volumes of the hydroxy acids, which were strongly correlated to plasma leucine and valine levels. Urine N-phenylacetylglycine, a microbial-host co-metabolite, was strongly correlated with total serum and food allergen-specific IgE levels. Plasma pyruvate and urine valine, leucine, and isoleucine degradation metabolisms were significantly associated with allergic sensitization for childhood asthma. In conclusion, blood and urine metabolome reflect different metabolic pathways in allergic reactions. Plasma pyruvate metabolism to acetic acid appears to be associated with serum IgE production, whereas urine branched-chain amino acid metabolism primarily reflects food allergic reactions against allergies.

Metabolomics for Investigating Physiological and Pathophysiological Processes

Metabolomics uses advanced analytical chemistry techniques to enable the high-throughput characterization of metabolites from cells, organs, tissues, or biofluids. The rapid growth in metabolomics is leading to a renewed interest in metabolism and the role that small molecule metabolites play in many biological processes. As a result, traditional views of metabolites as being simply the "bricks and mortar" of cells or just the fuel for cellular energetics are being upended. Indeed, metabolites appear to have much more varied and far more important roles as signaling molecules, immune modulators, endogenous toxins, and environmental sensors. This review explores how metabolomics is yielding important new insights into a number of important biological and physiological processes. In particular, a major focus is on illustrating how metabolomics and discoveries made through metabolomics are improving our understanding of both normal physiology and the pathophysiology of many diseases. These discoveries are yielding new insights into how metabolites influence organ function, immune function, nutrient sensing, and gut physiology. Collectively, this work is leading to a much more unified and system-wide perspective of biology wherein metabolites, proteins, and genes are understood to interact synergistically to modify the actions and functions of organelles, organs, and organisms.

Urinary myo-inositol is associated with the clinical outcome in focal segmental glomerulosclerosis

Focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) have similar initial histological findings; however, their prognoses are distinct. Therefore, it is of great importance to discriminate FSGS from MCD in the early phase of disease and predict clinical prognosis. A discovery set of 184 urine samples (61 healthy control, 80 MCD, and 43 FSGS) and a validation set of 61 urine samples (12 healthy control, 26 MCD, and 23 FSGS) were collected at the time of kidney biopsy. Metabolic profiles were examined using nuclear magnetic resonance spectroscopy. Of 70 urinary metabolites, myo-inositol was significantly higher in FSGS patients than in control patients (discovery set, 2.34-fold, P < 0.001; validation set, 2.35-fold, P = 0.008) and MCD patients (discovery set, 2.48-fold, P = 0.002; validation set, 1.69-fold, P = 0.042). Myo-inositol showed an inverse relationship with the initial estimated glomerular filtration rate (eGFR) and was associated with the plasma level of soluble urokinase-type plasminogen activator receptor in FSGS patients. Myo-inositol treatment ameliorated the decreased expression of ZO-1 and synaptopodin in an in vitro FSGS model, and as myo-inositol increased, myo-inositol oxygenase tissue expression decreased proportionally to eGFR. Furthermore, urinary myo-inositol exhibited an increase in the power to discriminate FSGS patients, and its addition could better predict the response to initial treatment. In conclusion, urinary myo-inositol may be an important indicator in the diagnosis and treatment of FSGS patients.

Metabolomics Analysis Reveals the Protection Mechanism of Huangqi-Danshen Decoction on Adenine-Induced Chronic Kidney Disease in Rats

Huangqi-Danshen decoction (HDD) is a commonly used drug pair for clinical treatment of chronic kidney disease (CKD) in traditional Chinese medicine with good efficacy. However, the potential mechanisms of this action have not been well elucidated. The aim of this study was to explore the metabolic profiling variations in response to HDD treatment in a CKD rat model. CKD rat model was induced by adding 0.75% adenine to the diet for 4 weeks. The rats in the treatment group received HDD extract orally at the dose of 4.7 g/kg/day during the experiment. At the end of the experiment, serum and kidney samples were collected for biochemical and pathological examination. Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS) was used to analyze metabolic profiling variations in the kidney. The results showed that treatment with HDD markedly attenuated kidney injury and improved renal function. A total of 28 metabolites contributing to CKD phenotype were found and identified in the kidney samples. The primary metabolic pathways disordered in the kidney of CKD rats were glycerophospholipid metabolism, glycosylphosphatidylinositol-anchor biosynthesis, and citrate cycle. Partial least squares discriminant analysis (PLS-DA) score plot showed that the three groups of renal samples were obviously divided into three categories, and the metabolic trajectory of the HDD treatment group moved to the control group. (E)-Piperolein A, phosphatidylcholines (PC) (18:1/22:6), phosphatidylinositols (PI) (13:0/18:1), PI (15:0/20:3), phosphatidylserines (PS) (O-20:0/12:0), and triglyceride (TG) (22:4/24:0/O-18:0) represented potential biomarkers of the renoprotective effects of HDD against CKD. In conclusion, HDD has renoprotective effect against adenine-induced CKD, which may be mediated via partially restoration of perturbed metabolism in the kidney.

An update of urine and blood metabolomics in chronic kidney disease

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

Metabolomics and Communication Skills Development in Children; Evidence from the Ages and Stages Questionnaire

We hypothesized metabolomic profiling could be utilized to identify children who scored poorly on the communication component of the Ages and Stages Questionnaire (ASQ); which assesses development in childhood, and to provide candidate biomarkers for autism spectrum disorders (ASD). In a population of three-year-old children, 15 plasma metabolites, were significantly (p < 0.05) different between children who were categorized as having communication skills that were “on schedule” (n = 365 (90.6%)) as compared to those “requiring further monitoring/evaluation” (n = 38 (9.4%)) according to multivariable regression models. Five of these metabolites, including three endocannabinoids, were also dysregulated at age one (n = 204 “on schedule”, n = 24 “further monitoring/evaluation”) in the same children. Stool metabolomic profiling identified 11 significant metabolites. Both the plasma and stool results implicated a role for tryptophan and tyrosine metabolism; in particular, higher levels of N-formylanthranilic acid were associated with an improved communication score in both biosample types. A model based on the significant plasma metabolites demonstrated high sensitivity (88.9%) and specificity (84.5%) for the prediction of autism by age 8. These results provide evidence that ASQ communication score and metabolomic profiling of plasma and/or stool may provide alternative approaches for early diagnosis of ASD, as well as insights into the pathobiology of these conditions.

Targeted Metabolomic Profiling of Peritoneal Dialysis Effluents Shows Anti-oxidative Capacity of Alanyl-Glutamine

Readily available peritoneal dialysis (PD) effluents from PD patients in the course of renal replacement therapy are a potentially rich source for molecular markers for predicting clinical outcome, monitoring the therapy, and therapeutic interventions. The complex clinical phenotype of PD patients might be reflected in the PD effluent metabolome. Metabolomic analysis of PD effluent might allow quantitative detection and assessment of candidate PD biomarkers for prognostication and therapeutic monitoring. We therefore subjected peritoneal equilibration test effluents from 20 stable PD patients, obtained in a randomized controlled trial (RCT) to evaluate cytoprotective effects of standard PD solution (3.86% glucose) supplemented with 8 mM alanyl-glutamine (AlaGln) to targeted metabolomics analysis. One hundred eighty eight pre-defined metabolites, including free amino acids, acylcarnitines, and glycerophospholipids, as well as custom metabolic indicators calculated from these metabolites were surveyed in a high-throughput assay requiring only 10 μl of PD effluent. Metabolite profiles of effluents from the cross-over trial were analyzed with respect to AlaGln status and clinical parameters such as duration of PD therapy and history of previous episodes of peritonitis. This targeted approach detected and quantified 184 small molecules in PD effluent, a larger number of detected metabolites than in all previous metabolomic studies in PD effluent combined. Metabolites were clustered within substance classes regarding concentrations after a 4-h dwell. PD effluent metabolic profiles were differentiated according to PD patient sub-populations, revealing novel changes in small molecule abundance during PD therapy. AlaGln supplementation of PD fluid altered levels of specific metabolites, including increases in alanine and glutamine but not glutamate, and reduced levels of small molecule indicators of oxidative stress, such as methionine sulfoxide. Our study represents the first application of targeted metabolomics to PD effluents. The observed metabolomic changes in PD effluent associated with AlaGln-supplementation during therapy suggested an anti-oxidant effect, and were consistent with the restoration of important stress and immune processes previously noted in the RCT. High-throughput detection of PD effluent metabolomic signatures and their alterations by therapeutic interventions offers new opportunities for metabolome-clinical correlation in PD and for prescription of personalized PD therapy.

Blood and urinary metabolomic evidence validating traditional Chinese medicine diagnostic classification of major depressive disorder

Background

Major depressive disorder (MDD) is a highly heterogeneous disease. Further classification may characterize its heterogeneity. The purpose of this study was to examine whether metabolomic variables could differentiate traditional Chinese medicine (TCM) diagnostic subtypes of MDD.

Methods

Fifty medication-free patients who were experiencing a recurrent depressive episode were classified into Liver Qi Stagnation (LQS, n = 30) and Heart and Spleen Deficiency (HSD, n = 20) subtypes according to TCM diagnosis. Healthy volunteers (n = 28) were included as controls. Gas chromatography-mass spectrometry (GC–MS) was used to examine serum and urinary metabolomic profiles.

Results

Twenty-eight metabolites were identified for good separations between TCM subtypes and healthy controls in serum samples. Both TCM subtypes had similar profiles in proteinogenic branched-chain amino acids (BCAAs) (valine, leucine, and isoleucine) and energy metabolism-related metabolites that were differentiated from healthy controls. The LQS subtype additionally differed from healthy controls in multiple amino acid metabolites that are involved in biosynthesis of monoamine and amino acid neurotransmitters, including phenylalanine, 3-hydroxybutric acid, o-tyrosine, glycine, l-tryptophan, and N-acetyl-l-aspartic acid. Threonic acid, methionine, stearic acid, and isobutyric acid are differentially associated with the two subtypes.

Conclusions

While both TCM subtypes are associated with aberrant BCAA and energy metabolism, the LQS subtype may represent an MDD subpopulation characterized by abnormalities in the biosynthesis of monoamine and amino acid neurotransmitters and closer associations with stress-related pathophysiology. The metabolites differentially associated with the two subtypes are promising biomarkers for predicting TCM subtype-specific antidepressant response [registered at http://www.clinicaltrials.gov (NCT02346682) on January 27, 2015].

Electronic supplementary material

The online version of this article (10.1186/s13020-018-0211-z) contains supplementary material, which is available to authorized users.

Gene Expression Studies and Targeted Metabolomics Reveal Disturbed Serine, Methionine, and Tyrosine Metabolism in Early Hypertensive Nephrosclerosis

Introduction

Hypertensive nephrosclerosis is among the leading causes of end-stage renal disease, but its pathophysiology is poorly understood. We wanted to explore early metabolic changes using gene expression and targeted metabolomics analysis.

Methods

We analyzed gene expression in kidneys biopsied from 20 patients with nephrosclerosis and 31 healthy controls with an Affymetrix array. Thirty-one amino acids were measured by liquid chromatography coupled with mass spectrometry (LC-MS) in urine samples from 62 patients with clinical hypertensive nephrosclerosis and 33 age- and sex-matched healthy controls, and major findings were confirmed in an independent cohort of 45 cases and 15 controls.

Results

Amino acid catabolism and synthesis were strongly underexpressed in hypertensive nephrosclerosis (13- and 7-fold, respectively), and these patients also showed gene expression patterns indicating decreased fatty acid oxidation (12-fold) and increased interferon gamma (10-fold) and cellular defense response (8-fold). Metabolomics analysis revealed significant distribution differences in 11 amino acids in hypertensive nephrosclerosis, among them tyrosine, phenylalanine, dopamine, homocysteine, and serine, with 30% to 70% lower urine excretion. These findings were replicated in the independent cohort. Integrated gene-metabolite pathway analysis showed perturbations of renal dopamine biosynthesis. There were also significant differences in homocysteine/methionine homeostasis and the serine pathway, which have strong influence on 1-carbon metabolism. Several of these disturbances could be interconnected through reduced regeneration of tetrahydrofolate and tetrahydrobiopterin.

Conclusion

Early hypertensive nephrosclerosis showed perturbations of intrarenal biosynthesis of dopamine, which regulates natriuresis and blood pressure. There were also disturbances in serine/glycine and methionine/homocysteine metabolism, which may contribute to endothelial dysfunction, atherosclerosis, and renal fibrosis.

Circulating metabolic biomarkers of renal function in diabetic and non-diabetic populations

Using targeted NMR spectroscopy of 227 fasting serum metabolic traits, we searched for novel metabolic signatures of renal function in 926 type 2 diabetics (T2D) and 4838 non-diabetic individuals from four independent cohorts. We furthermore investigated longitudinal changes of metabolic measures and renal function and associations with other T2D microvascular complications. 142 traits correlated with glomerular filtration rate (eGFR) after adjusting for confounders and multiple testing: 59 in diabetics, 109 in non-diabetics with 26 overlapping. The amino acids glycine and phenylalanine and the energy metabolites citrate and glycerol were negatively associated with eGFR in all the cohorts, while alanine, valine and pyruvate depicted opposite association in diabetics (positive) and non-diabetics (negative). Moreover, in all cohorts, the triglyceride content of different lipoprotein subclasses showed a negative association with eGFR, while cholesterol, cholesterol esters (CE), and phospholipids in HDL were associated with better renal function. In contrast, phospholipids and CEs in LDL showed positive associations with eGFR only in T2D, while phospholipid content in HDL was positively associated with eGFR both cross-sectionally and longitudinally only in non-diabetics. In conclusion, we provide a wide list of kidney function-associated metabolic traits and identified novel metabolic differences between diabetic and non-diabetic kidney disease.

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.

Metabolomics in chronic kidney disease: Strategies for extended metabolome coverage

Chronic kidney disease (CKD) is becoming a major public health issue as prevalence is increasing worldwide. It also represents a major challenge for the identification of new early biomarkers, understanding of biochemical mechanisms, patient monitoring and prognosis. Each metabolite contained in a biofluid or tissue may play a role as a signal or as a driver in the development or progression of the pathology. Therefore, metabolomics is a highly valuable approach in this clinical context. It aims to provide a representative picture of a biological system, making exhaustive metabolite coverage crucial. Two aspects can be considered: analytical and biological coverage. From an analytical point of view, monitoring all metabolites within one run is currently impossible. Multiple analytical techniques providing orthogonal information should be carried out in parallel for coverage improvement. The biological aspect of metabolome coverage can be enhanced by using multiple biofluids or tissues for in-depth biological investigation, as the analysis of a single sample type is generally insufficient for whole organism extrapolation. Hence, recording of signals from multiple sample types and different analytical platforms generates massive and complex datasets so that chemometric tools, including data fusion approaches and multi-block analysis, are key tools for extracting biological information and for discovery of relevant biomarkers. This review presents the recent developments in the field of metabolomic analysis, from sampling and analytical strategies to chemometric tools, dedicated to the generation and handling of multiple complementary metabolomic datasets enabling extended metabolite coverage to improve our biological knowledge of CKD.

Combined systems pharmacology and fecal metabonomics to study the biomarkers and therapeutic mechanism of type 2 diabetic nephropathy treated with Astragalus and Leech

In our study, systems pharmacology was used to predict the molecular targets of Astragalus and Leech, and explore the therapeutic mechanism of type 2 diabetic nephropathy (T2DN) treated with Astragalus and Leech. Simultaneously, to reveal the systemic metabolic changes and biomarkers associated with T2DN, we performed 1H NMR-based metabonomics and multivariate analysis to analyze fecal samples obtained from model T2DN rats. In addition, ELISA kits and histopathological studies were used to examine biochemical parameters and kidney tissue, respectively. Striking differences in the Pearson's correlation of 22 biomarkers and 9 biochemical parameters were also observed among control, T2DN and treated rats. Results of systems pharmacology analysis revealed that 9 active compounds (3,9-di-O-methylnissolin; (6aR,11aR)-9,10-dimethoxy-6a,11a-dihydro-6H-benzofurano[3,2-c]chromen-3-ol; hirudin; l-isoleucine; phenylalanine; valine; hirudinoidine A-C) and 9 target proteins (l-serine dehydratase; 3-hydroxyacyl-CoA dehydrogenase; tyrosyl-tRNA synthetase; tryptophanyl-tRNA synthetase; branched-chain amino acid aminotransferase; acetyl-CoA C-acetyltransferase; isovaleryl-CoA dehydrogenase; pyruvate dehydrogenase E1 component alpha subunit; hydroxyacylglutathione hydrolase) of Astragalus and Leech were closely associated with the treatment of T2DN. Using fecal metabonomics analysis, 22 biomarkers were eventually found to be closely associated with the occurrence of T2DN. Combined with systems pharmacology and fecal metabonomics, these biomarkers were found to be mainly associated with 6 pathways, involving amino acid metabolism (leucine, valine, isoleucine, alanine, lysine, glutamate, taurine, phenylalanine, tryptophan); energy metabolism (lactate, succinate, creatinine, α-glucose, glycerol); ketone body and fatty acid metabolism (3-hydroxybutyrate, acetate, n-butyrate, propionate); methylamine metabolism (dimethylamine, trimethylamine); and secondary bile acid metabolism and urea cycle (deoxycholate, citrulline). The underlying mechanisms of action included protection of the liver and kidney, enhancement of insulin sensitivity and antioxidant activity, and improvement of mitochondrial function. To the best of our knowledge, this is the first time that systems pharmacology combined with fecal metabonomics has been used to study T2DN. 6 metabolites (n-butyrate, deoxycholate, propionate, tryptophan, taurine and glycerol) associated with T2DN were newly discovered in fecal samples. These 6 metabolites were mainly derived from the intestinal flora, and related to amino acid metabolism, fatty acid metabolism, and secondary bile acid metabolism. We hope the results of this study could be inspirational and helpful for further exploration of T2DN treatment. Meanwhile, our results highlighted that exploring the biomarkers of T2DN and therapeutic mechanisms of Traditional Chinese Medicine (TCM) formulas on T2DN by combining systems pharmacology and fecal metabonomics methods was a promising strategy.

Combined Clinical Phenotype and Lipidomic Analysis Reveals the Impact of Chronic Kidney Disease on Lipid Metabolism

Chronic kidney disease (CKD) results in significant dyslipidemia and profound changes in lipid and lipoprotein metabolism. The associated dyslipidemia, in turn, contributes to progression of CKD and its cardiovascular complications. To gain an in-depth insight into the disorders of lipid metabolism in advanced CKD, we applied UPLC-HDMS-based lipidomics to measure serum lipid metabolites in 180 patients with advanced CKD and 120 age-matched healthy controls. We found significant increases in the levels of total free fatty acids, glycerolipids, and glycerophospholipids in patients with CKD. The levels of free fatty acids, glycerolipids, and glycerophospholipids directly correlated with the level of serum triglyceride and inversely correlated with the levels of total cholesterol and eGFR. A total of 126 lipid species were identified from positive and negative ion modes. Out of 126, 113 identified lipid species were significantly altered in patients with CKD based on the adjusted FDR method. These results pointed to profound disturbance of fatty acid and triglyceride metabolisms in patients with CKD. Logistic regression analysis showed strong correlations between serum methyl hexadecanoic acid, LPC(24:1), 3-oxooctadecanoic acid, and PC(20:2/24:1) levels with eGFR and serum creatinine levels (R > 0.8758). In conclusion, application of UPLC-HDMS-based lipidomic technique revealed profound changes in lipid metabolites in patients with CKD. The observed increases in serum total fatty acids, glycerolipids, and glycerophospholipids levels directly correlated with increased serum triglyceride level and inversely correlated with the eGFR and triglyceride levels.

Novel chinmedomics strategy for discovering effective constituents from ShenQiWan acting on ShenYangXu syndrome

Elucidation of the efficacy of traditional Chinese medicine (TCM) is of importance for scientists of modern medicine to understand the value of TCM clinical experience, and it is necessary to have a biological language to scientifically describe the efficacy of TCM. With this background?Chinmedomics has been proposed by our team, which includes integrating serum pharmacochemistry and metabolomics technology, defining theory and research methods for expressing the efficacy of TCMs based on the biomarkers discovery of TCM syndrome and elucidating the efficacy of TCM formulae, discovering effective constituents, and finally elucidating the scientific value of TCM. In the present study, the innovative chinmedomics strategy was conducted to evaluate the therapeutic effects of ShenQiWan (SQW) acting on ShenYangXu (kidney-yang deficiency syndrome, KYDS). We analyzed the urine metabolic trajectory between the model and control groups, and identified the biomarkers by the multivariate analysis. We found that SQW caused significant restoration of abnormal metabolism of KYDs. Using the method of metabolomics, 17 potential urine biomarkers were analyzed through 4 repeated tests in our serial studies on SQW and KYDS. Under the premise of therapeutic efficacy, a total of 56 peaks were tentatively characterized in vivo by the use of serum pharmacochemistry. Correlation analysis between marker metabolites and in vivo constituents of SQW showed that 28 compositions had a close relationship with urine biomarkers of therapeutic effects, whichmight play a key role in the therapeutic effect of SQW. These compounds were imported into an online database to predict their targets. Twenty-three important potential targets were identified, which were related to the metabolism of steroid hormone, tryptophan utilization, and thyroid hormone. In conclusion, chinmedomics is a useful strategy for discovery of potentially effective constituents from complex TCM formulae.