Recent advances in metabolomics in neurological disease, and future perspectives

Discovery of clinically relevant biomarkers for diseases has revealed metabolomics has potential advantages that classical diagnostic approaches do not. The great asset of metabolomics is that it enables assessment of global metabolic profiles of biofluids and discovery of biomarkers distinguishing disease status, with the possibility of enhancing clinical diagnostics. Most current clinical chemistry tests rely on old technology, and are neither sensitive nor specific for a particular disease. Clinical diagnosis of major neurological disorders, for example Alzheimer’s disease and Parkinson’s disease, on the basis of current clinical criteria is unsatisfactory. Emerging metabolomics is a powerful technique for discovering novel biomarkers and biochemical pathways to improve diagnosis, and for determination of prognosis and therapy. Identifying multiple novel biomarkers for neurological diseases has been greatly enhanced with recent advances in metabolomics that are more accurate than routine clinical practice. Cerebrospinal fluid (CSF), which is known to be a rich source of small-molecule biomarkers for neurological and neurodegenerative diseases, and is in close contact with diseased areas in neurological disorders, could potentially be used for disease diagnosis. Metabolomics will drive CSF analysis, facilitate and improve the development of disease treatment, and result in great benefits to public health in the long-term. This review covers different aspects of CSF metabolomics and discusses their significance in the postgenomic era, emphasizing the potential importance of endogenous small-molecule metabolites in this emerging field.     

Metabolomics approach based on utra-performance liquid chromatography coupled to mass spectrometry with chemometrics methods for high-throughput analysis of metabolite biomarkers to explore the abnormal metabolic pathways associated with myocardial dysfunction

Ultra-performance liquid chromatography/mass spectrometry-based metabolomics can been used for discovery of metabolite biomarkers to explore the metabolic pathway of diseases. Identification of metabolic pathways is key to understanding the pathogenesis and mechanism of disease. Myocardial dysfunction induced by sepsis (SMD) is a severe complication of septic shock and represents major causes of death in intensive care units; however its pathological mechanism is still not clear. In this study, ultrahigh-pressure liquid chromatography with mass spectrometry-based metabolomics with chemometrics anaylsis and multivariate pattern recognition analysis were used to detect urinary metabolic profile changes in a lipopolysaccharide-induced SMD mouse model. Multivariate statistical analysis including principal component analysis and orthogonapartial least squares discriminant analysis for the discrimination of SMD was conducted to identify potential biomarkers. A total of 19 differential metabolites were discovered by high-resolution mass spectrometry-based urinary metabolomics strategy. The altered biochemical pathways based on these metabolites showed that tyrosine metabolism, phenylalanine metabolism, ubiquinone biosynthesis and vitamin B6 metabolism were closely connected to the pathological processes of SMD. Consequently, integrated chemometric analyses of these metabolic pathways are necessary to extract information for the discovery of novel insights into the pathogenesis of disease.     

Metabolomics Approaches and Applications in Prostate Cancer Research

Prostate cancer is a leading cause of cancer deaths in men worldwide. Although prostate-specific antigen (PSA) has been extensively used as a serum biomarker to detect prostate cancer, this screening method has suffered from a lack of specificities and sensitivities. The successful prevention and treatment of prostate cancer relies on the early and accurate detection of the disease; therefore, more sensitive biomarkers are urgently needed. Prostate has long been known to exhibit unique metabolite profiles, fortunately, metabolomics, the study of all metabolites produced in the body, can be considered most closely related to a patient’s phenotype. It may provide clinically useful biomarkers applied toward identifying metabolic alterations in prostate cancer and has introduced new insights into the pathology of prostate cancer. This advanced bioanalytic method may now open door for diagnostics. Metabolomics has a great and largely potential in the field of disease, and the analysis of the cancer metabolome to identify novel biomarkers and targets can now be undertaken in many research laboratories. In this review, we take a closer look at the metabolomics in the field of prostate cancer and highlight the interesting publications as references for the interested reader.     

Bioanalytical methods for metabolomic profiling: Detection of head and neck cancer,including oral cancer

Metabolomics is an emerging field dealing with the measurement and interpretation of small molecular byproducts of biochemical processes, or metabolites, which can be used to generate profiles from biological samples. Promising for use in pathophysiology, metabolomic profiles give the immediate biological state of a sample. These profiles are altered in diseases and are detectable in biological samples, such as tissue, blood, urine, saliva, and others. Most remarkably, metabolic profiles usually are altered before symptoms appear in a patient. For this reason, metabolomics has potential as a reliable method for an early diagnosis of diseases through disease biomarker identification. This application is most prevalent in cancer, such as head and neck cancer (HNC). Metabolomic studies offer avenues to improve on current medical techniques through the application of mass spectrometry (MS), nuclear magnetic resonance spectroscopy (NMR), and statistical analysis to determine better biomarkers than those currently known. In this review, we discuss the use of MS and NMR tools for detecting biomarkers in tissue and fluid samples, and the appropriateness of metabolomics in analyzing cancer. Advantages, disadvantages, and recent studies on metabolomic profiling techniques in HNC analysis are also discussed herein.     

LC-HRMS/MS-Based Metabolomics Approaches Applied to the Detection of Antifungal Compounds and a Metabolic Dynamic Assessment of Orchidaceae

The liquid chromatography–mass spectrometry (LC-MS)-based metabolomics approach is a powerful technology for discovering novel biologically active molecules. In this study, we investigated the metabolic profiling of Orchidaceae species using LC-HRMS/MS data combined with chemometric methods and dereplication tools to discover antifungal compounds. We analyze twenty ethanolic plant extracts from Vanda and Cattleya (Orchidaceae) genera. Molecular networking and chemometric methods were used to discriminate ions that differentiate healthy and fungal-infected plant samples. Fifty-three metabolites were rapidly annotated through spectral library matching and in silico fragmentation tools. The metabolomic profiling showed a large production of polyphenols, including flavonoids, phenolic acids, chromones, stilbenoids, and tannins, which varied in relative abundance across species. Considering the presence and abundance of metabolites in both groups of samples, we can infer that these constituents are associated with biochemical responses to microbial attacks. In addition, we evaluated the metabolic dynamic through the synthesis of stilbenoids in fungal-infected plants. The tricin derivative flavonoid- and the loliolide terpenoidfound only in healthy plant samples, are promising antifungal metabolites. LC-HRMS/MS, combined with state-of-the-art tools, proved to be a rapid and reliable technique for fingerprinting medicinal plants and discovering new hits and leads.     

Metabolomic characterization of semen from asthenozoospermic patients using ultra-high-performance liquid chromatography–tandem quadrupole time-of-flight mass spectrometry

Asthenozoospermia (AS) is a common factor of male infertility, and its pathogenesis remains unclear. The purpose of this study was to investigate the differential seminal plasma metabolic pattern in asthenozoospermic men and to identify potential biomarkers in relation to spermatogenic dysfunction using sensitive ultra-high-performance liquid chromatography–tandem quadruple time-of-flight MS (UHPLC–Q-TOF/MS). The samples of seminal plasma from patients with AS (n = 20) and healthy controls (n = 20) were checked and differentiated by UHPLC–Q-TOF/MS. Compared with the control group, the AS group showed a total of nine significantly different metabolites, including increases in creatinine, uric acid, N⁶-methyladenosine (m⁶A), uridine, and taurine and decreases in carnitine, nicotinamide, N-acetylputrescine and l -palmitoylcarnitine. By analyzing the correlation among these metabolites and clinical computer-assisted semen analysis reports, we found that m⁶A is significantly correlated with not only the four decreased metabolites but also with sperm count, motility, and curvilinear velocity. Furthermore, nicotinamide was shown to correlate with other identified metabolites, indicating its important role in the metabolic pathway of AS. Current results implied that sensitive untargeted seminal plasma metabolomics could identify distinct metabolic patterns of AS and would help clinicians by offering novel cues for discovering the pathogenesis of male infertility.     

Serum metabolomics study of patients with allergic rhinitis

Allergic rhinitis (AR) negatively affects the healthy lives of many individuals. Most previous studies on AR focused on the expression of cytokines, with only a few analyzing cytokine expression from a metabolomics viewpoint. Therefore, it is worthwhile to study AR at the metabolic level. Consequently, we aimed to identify differential serum biomarkers by metabolomics. In this study, the orthogonal partial least squares discriminant analysis (OPLS-DA) model was applied to characterize the differences in serum samples collected from patients with AR and healthy volunteers. Ten metabolites (except hexadecanoic acid) were found to be altered significantly (p < .05) in the former group, according to results of principal component analysis and OPLS-DA, indicating that these metabolites could be potential biomarkers. MetaboAnalyst 4.0 and pathway enrichment analysis showed that these changes in metabolites mainly involved three pathways, namely, porphyrin and chlorophyll metabolism, arachidonic acid metabolism, and purine metabolism. Our findings may contribute to a better understanding of the potential pathogenesis mechanisms and provide a metabolic evidence for in-depth studies of AR.     

A novel kernel Fisher discriminant analysis: constructing informative kernel by decision tree ensemble for metabolomics data analysis

Large amounts of data from high-throughput metabolomics experiments become commonly more and more complex, which brings an enormous amount of challenges to existing statistical modeling. Thus there is a need to develop statistically efficient approach for mining the underlying metabolite information contained by metabolomics data under investigation. In the work, we developed a novel kernel Fisher discriminant analysis (KFDA) algorithm by constructing an informative kernel based on decision tree ensemble. The constructed kernel can effectively encode the similarities of metabolomics samples between informative metabolites/biomarkers in specific parts of the measurement space. Simultaneously, informative metabolites or potential biomarkers can be successfully discovered by variable importance ranking in the process of building kernel. Moreover, KFDA can also deal with nonlinear relationship in the metabolomics data by such a kernel to some extent. Finally, two real metabolomics datasets together with a simulated data were used to demonstrate the performance of the proposed approach through the comparison of different approaches.     

Urinary metabolomic study of systemic lupus erythematosus based on gas chromatography/mass spectrometry

Systemic lupus erythematosus (SLE) is an autoimmune disease with heterogeneous organ and system manifestations. In this study, urinary metabolic alterations related to SLE were investigated by performing gas chromatography/mass spectrometry (GC/MS) based metabolomics and multivariate statistical analysis. Patients with SLE and healthy controls could be clearly differentiated in view of the metabolic abnormity in urine. Among 70 identified endogenous metabolites, 23 metabolites were dramatically increased in SLE patients, which involved in several key metabolic pathways including energy metabolism, nucleotide metabolism, oxidative stress and gut‐microbiome‐derived metabolism. This noninvasive and GC/MS‐based metabolomic technique is a promising and potent strategy for identifying novel biomarkers and understanding pathogenesis of SLE. Copyright © 2016 John Wiley & Sons, Ltd.     

Metabolomics of lung cancer: Analytical platforms and their applications

Lung cancer is the leading type of cancer worldwide in terms of the number of new cases and is responsible for the largest number of deaths due to poor prognosis and difficult early detection. Due to its ability to detect numerous small molecular metabolites simultaneously, metabolomics has been widely used for the assessment of global metabolic changes in a living organism to discover candidate biomarkers for cancer diagnosis, investigate the development of cancer, and provide insights into the underlying pathophysiology. This review will mainly describe recent developments in lung cancer metabolomics in terms of early‐stage detection, biomarker discovery and mechanism exploration by using nuclear magnetic resonance, liquid chromatography–mass spectrometry, gas chromatography–mass spectrometry, and capillary electrophoresis–mass spectrometry in the last 10 years. The sample collection and metabolite extraction methods are also summarized.     

Effects of Tao‐Hong‐Si‐Wu decoction on acute blood stasis in rats based on a LC‐Q/TOF‐MS metabolomics and network approach

A novel approach using metabolomics coupled with a metabolic network was used to investigate the effects of Tao‐Hong‐Si‐Wu decoction (THSWD) on the rat model of acute blood stasis syndrome. Acute blood stasis syndrome was induced by placing the rats in ice‐cold water following two injections with epinephrine. The hemorheological indicators [whole blood viscosity (WBV) and plasma viscosity (PV)] and the blood coagulation indicators [thrombin time (TT), prothrombin time (PT), activated partial thromboplastin time (APTT) and fibrinogen (FIB)] were detected. The nonparametric univariate method and multivariate statistical analysis were performed for determining the potential biomarkers. A correlation map was structured between biochemical indicators and hub metabolites to explain the effects mechanism of THSWD. After the administration of THSWD, the levels of WBV, PV, TT, APTT and FIB returned to levels observed in the control group. According to metabolomics coupled with metabolic network analysis, the intervention of THSWD in rats with acute blood stasis syndrome induced substantial and characteristic changes in their metabolic profiles. Fifteen metabolites were screened, which mainly involved 10 pathways and five hub metabolites, namely, l ‐glutamate, l ‐phenylalanine, N‐acylsphingosine, arachidonic acid and phosphatidate. The biochemical indicators and hub metabolites could be adjusted to close to normal levels by THSWD. Therefore, combining metabolomics and metabolic network helped to evaluate the effects of THSWD on acute blood stasis.     

(Xeno)metabolomics for the evaluation of aquatic organism’s exposure to field contaminated water

Environmental (xeno)metabolomics offers a major advantage compared to other approaches for the evaluation of aquatic organism’s exposure to contaminated water because its allows the simultaneous profiling of the xenometabolome (chemical xenobiotics and their metabolites accumulated in an organism exposed to environmental contaminants) and the metabolome (endogenous metabolites whose levels are altered due to an external stressor). This approach has been widely explored in lab exposure experiments, however in field studies environmental (xeno)metabolomics has only started in the last years. In this review, the papers published so far that have performed different (xeno)metabolomics approaches for the evaluation of aquatic organisms exposed to contaminated water are presented, together with their main achievements, current limitations, and future perspectives. The different analytical methods applied including sample pre-treatment (considering matrix type), platforms used (Nuclear Magnetic Resonance (NMR) and low- or high-resolution Mass Spectrometry (MS or HRMS)), and the analytical strategy (target vs non-target analysis) are discussed. The application of (xeno)metabolomics to provide information of xenobiotics mixtures accumulated in exposed organisms, either in lab or field studies, as well as biomarkers of exposure and biomarkers of effect are debated, and finally, the most commonly metabolic pathways disrupted by chemical contamination are highlighted.     

Nontargeted urine metabolomics analysis of the protective and therapeutic effects of Citri Reticulatae Chachiensis Pericarpium on high-fat feed-induced hyperlipidemia in rats

In this study, we focused on studying the changes in urine metabolites in hyperlipidemic rats using ultra-performance liquid chromatography coupled with quadrupole time-of-fight mass spectrometry (UPLC–Q-TOF/MS) and metabolomics, as well as the effect of Citri Reticulatae Chachiensis Pericarpium (CRCP) on hyperlipidemia. These urine samples were examined by UPLC–Q-TOF/MS to obtain MS data. The MS data were analyzed by principal component analysis and partial least squares-discriminant analysis to identify the differential metabolites. CRCP reduced the body weight and levels of triglycerides, total cholesterol and low-density lipoprotein cholesterol and abnormally decreased high-density lipoprotein cholesterol in hyperlipidemic rats, which were significantly raised by a high-fat diet. Twenty-seven potential biomarkers were identified within the complex sample matrix of urine. Fourteen biomarkers increased in the hyperlipidemia rats compared with normal rats. Meanwhile, 13 biomarkers decreased. CRCP reversed abnormal changes in biomarkers, including 5-l -glutamyl-taurine, 5-aminopentanoic acid, cis-4-octenedioic acid and 2-octenedioic acid. These biomarkers show that hyperlipidemia is related to the metabolic pathways of taurine and hypotaurine metabolism, fatty acid biosynthesis , and arginine and proline metabolism . CRCP mainly prevents hyperlipidemia by intervening in these metabolic pathways.     

Comparison of Widely Targeted Metabolomics and Untargeted Metabolomics of Wild Ophiocordyceps sinensis

The authors of this paper conducted a comparative metabolomic analysis of Ophiocordyceps sinensis (OS), providing the metabolic profiles of the stroma (OSBSz) and sclerotia (OSBSh) of OS by widely targeted metabolomics and untargeted metabolomics. The results showed that 778 and 1449 metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. The metabolites in OSBSz and OSBSh are significantly differentiated; 71 and 96 differentially expressed metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. This suggests that these 71 metabolites (riboflavine, tripdiolide, bromocriptine, lumichrome, tetrahymanol, citrostadienol, etc.) and 96 metabolites (sancycline, vignatic acid B, pirbuterol, rubrophen, epalrestat, etc.) are potential biomarkers. 4-Hydroxybenzaldehyde, arginine, and lumichrome were common differentially expressed metabolites. Using the widely targeted metabolomics approach, the key pathways identified that are involved in creating the differentiation between OSBSz and OSBSh may be nicotinate and nicotinamide metabolism, thiamine metabolism, riboflavin metabolism, glycine, serine, and threonine metabolism, and arginine biosynthesis. The differentially expressed metabolites identified using the untargeted metabolomics approach were mainly involved in arginine biosynthesis, terpenoid backbone biosynthesis, porphyrin and chlorophyll metabolism, and cysteine and methionine metabolism. The purpose of this research was to provide support for the assessment of the differences between the stroma and sclerotia, to furnish a material basis for the evaluation of the physical effects of OS, and to provide a reference for the selection of detection methods for the metabolomics of OS.     

A new method providing complementary explanation of the blood-enriching function and mechanism of unprocessed Angelica sinensis and its four kinds of processed products based on tissue-integrated metabolomics and confirmatory analysis

Angelica sinensis (AS) is a common Traditional Chinese Medicine used for tonifying blood in China. Unprocessed AS and its four kinds of processed products (ASs) are used to treat blood deficiency syndrome in the country. The different blood-tonifying mechanisms of ASs remain unclear. In this work, a novel method integrating metabolomics and hematological and biochemical parameters was established to provide a complementary explanation of blood supplementation mechanism of ASs. Our results revealed that different ASs exhibited various blood supplementation effect, and that AS parched with alcohol demonstrated the best blood supplementation effect. Eight metabolites from liver tissue and 12 metabolites from spleen tissue were considered to be potential biomarkers. These biomarkers were involved in four metabolic pathways. Correlation analysis results showed that l -aspartic acid and l -alanine (spleen tissue), linoleic acid, and l -cystathionine (liver tissue) exhibited a high positive or negative correlation with the aforesaid biochemical indicators. The blood-supplementation effect mechanism of ASs were related to four metabolic pathways. l -Aspartic acid and l -alanine (spleen tissue), linoleic acid, and l -cystathionine (liver tissue) were the four key metabolites associated with the blood supplementation effect of ASs. This study gives a complementary explanation of the blood supplementation effect and mechanism of action of ASs.     

Serum metabolomics as a novel diagnostic approach for disease: a systematic review

Metabolomics is a promising "omics" field in systems biology; its objective is comprehensive analysis of low-molecular-weight endogenous metabolites in a biological sample. It could enable mapping of perturbations of early biochemical changes in diseases and hence provide an opportunity to develop predictive biomarkers that could result in earlier intervention and provide valuable insights into the mechanisms of diseases. Because of the possible discovery of clinically relevant biomarkers, metabolomics has potential advantages that routine approaches to clinical diagnosis do not. Monitoring specific metabolite levels in serum, the most commonly used biofluid in metabolomics, has become an important way of detecting the early stages of a disease. Serum is a readily accessible and informative biofluid, making it ideal for early detection of a wide range of diseases, and analysis of serum has several advantages over analysis of other biofluids. Metabolite profiles of serum can be regarded as important indicators of physiological and pathological states and may aid understanding of the mechanism of disease occurrence and progression on the metabolic level, and provide information enabling identification of early and differential metabolic markers of disease. Analysis of these crucial metabolites in serum has become important in monitoring the state of biological organisms and is widely used for diagnosis of disease. Emerging metabolomics will drive serum analysis, facilitate and improve the development of disease treatments, and provide great benefits for public health in the long-term.     

Exploratory urinary metabolic biomarkers and pathways using UPLC-Q-TOF-HDMS coupled with pattern recognition approach

Metabolomics represents an emerging and powerful discipline concerned with the comprehensive analysis of small molecules and provides a powerful approach to discover biomarkers in biological systems. Recent development of biomarkers for diagnosis and therapeutic monitoring of liver-stagnation and spleen-deficiency syndrome (LSS)-type disease remains challenging. This study was undertaken to discover novel potential biomarkers for the non-invasive early diagnosis of human LSS. Urine samples which are potentially a rich source of metabolites were collected from patients with LSS, together with healthy control samples. Metabolite profiling was performed by ultra-performance liquid-chromatography/electrospray-ionization synapt high-definition mass spectrometry (UPLC-Q-TOF-HDMS) in conjunction with multivariate data analysis and ingenuity pathway analysis that were used to select the metabolites to be used for the non-invasive diagnosis of LSS. Twelve urinary differential metabolites contributing to the complete separation of LSS patients from matched healthy controls were identified involving several key metabolic pathways such as pentose and glucuronate interconversions, ascorbate, aldarate, cysteine, methionine, tyrosine, tryptophan, amino sugar and nucleotide sugar metabolism. More importantly, of the 12 differential metabolites, 4 metabolite markers, prolylhydroxyproline, l-homocystine, 2-octenoylcarnitine and α-N-phenylacetyl-l-glutamine, were effective for the diagnosis of human LSS, with an achieved sensitivity of 93.0%. These results demonstrate that robust metabolomics has the potential as a non-invasive strategy and promising screening tool to evaluate the potential of these metabolites in the early diagnosis of LSS patients and provides new insight into pathophysiological mechanisms.     

Urinary biomarker and treatment mechanism of Rhizoma Alismatis on hyperlipidemia

Rhizoma Alismatis (RA), a diuretic in Asia and Europe, was found to possess anti‐hyperlipidemic activity. Since the biomarkers and mechanisms of RA in the treatment of hyperlipidemia are inadequate, ultra‐performance liquid chromatography coupled with quadrupole time‐of‐flight synapt high‐definition mass spectrometry and multivariate data analysis were employed to investigate the urinary metabolomics of RA on hyperlipidemic rats induced by high‐fat diet. The metabolic profile of RA‐treated hyperlipidemic group located between control and diet‐induced hyperlipidemic groups. Nineteen metabolites with significant fluctuations were identified as potential biomarkers related to the hyperlipidemia and anti‐hyperlipidemia of RA using partial least‐squares‐discriminate analysis, heatmap analysis and correlation coefficient analysis. The fluctuations of these biomarkers represented disturbances in amino acid metabolism, purine metabolism, pyrimidine metabolism and energy metabolism. After RA treatment, these perturbed metabolites were restored to normal or nearly normal levels. RA can alleviate high‐fat diet‐induced dysfunctions in these metabolic pathways.     

Evaluation of Cocaine Effect on Endogenous Metabolites of HepG2 Cells Using Targeted Metabolomics

Cocaine toxicity has been a subject of study because cocaine is one of the most common and potent drugs of abuse. In the current study the effect of cocaine on human liver cancer cell line (HepG2) was assessed. Cocaine toxicity (IC50) on HepG2 cells was experimentally calculated using an XTT assay at 2.428 mM. The metabolic profile of HepG2 cells was further evaluated to investigate the cytotoxic activity of cocaine at 2 mM at three different time points. Cell medium and intracellular material samples were analyzed with a validated HILIC-MS/MS method for targeted metabolomics on an ACQUITY Amide column in gradient mode with detection on a triple quadrupole mass spectrometer in multiple reaction monitoring. About 106 hydrophilic metabolites from different metabolic pathways were monitored. Multivariate analysis clearly separated the studied groups (cocaine-treated and control samples) and revealed potential biomarkers in the extracellular and intracellular samples. A predominant effect of cocaine administration on alanine, aspartate, and glutamate metabolic pathway was observed. Moreover, taurine and hypotaurine metabolism were found to be affected in cocaine-treated cells. Targeted metabolomics managed to reveal metabolic changes upon cocaine administration, however deciphering the exact cocaine cytotoxic mechanism is still challenging.     

基于液相色谱-质谱技术的肾脏代谢组学分析方法研究

建立了一种基于高效液相色谱-超高分辨质谱技术的肾脏代谢组学分析方法。肾脏组织于液氮中研磨成粉后,采用甲基叔丁基醚/甲醇/水溶剂体系进行提取,分别得到强极性部分(下层)和弱极性部分(上层)提取物,依次采用HILIC亲水色谱柱和反相C18色谱柱进行梯度洗脱分离后,进行高分辨质谱分析。采用电喷雾离子源(ESI),正、负离子模式检测,扫描方式为全扫描,扫描范围为100~1000 Da,质量分辨率为120000。结果表明,该方法灵敏度高,专属性强,稳定性良好,可同时获取肾脏组织中的强极性和弱极性代谢物信息,可为肾脏疾病和药物肾毒性生物标志物的发现提供一种新的方法。