Discovery of Potential Biomarkers with Dose- and Time-Dependence in Cisplatin-Induced Nephrotoxicity Using Metabolomics Integrated with a Principal Component-Based Area Calculation Strategy

Identification of Novel and Early Biomarkers for Cisplatin-induced Nephrotoxicity and the Nephroprotective Role of Cimetidine using a Pharmacometabolomic-based Approach Coupled with In Vitro Toxicodynamic Modeling and Simulation

Cisplatin is widely used for the treatment of various types of cancer. However, cisplatin-induced nephrotoxicity (CIN) is frequently observed in patients receiving cisplatin therapy which poses a challenge in its clinical utility. Currently used clinical biomarkers for CIN are not adequate for early detection of nephrotoxicity, hence there is a need to identify potential early biomarkers in predicting CIN. In the current study, a combination of in vitro toxicodynamic (TD) modeling and untargeted global metabolomics approach was used to identify novel potential metabolite biomarkers for early detection of CIN. In addition, we investigated the protective role of cimetidine (CIM), an inhibitor of the organic cation transporter 2 (OCT2), in suppressing CIN. We first characterized the time-course of nephrotoxic effects of cisplatin (CIS) and the protective effects of CIM in a human pseudo-immortalized renal proximal tubule epithelial cell line (RPTEC), SA7K cell line. Secondly, we used a mathematical cell-level, in vitro TD modeling approach to quantitatively characterize the time-course effects of CIS and CIM as single agents and combination in SA7K cells. Based on the experimental and modeling results, we selected relevant concentrations of CIS and CIM for our metabolomics study. With the help of PCA (Principal Component Analysis) and PLS-DA (Projection to Latent Structure - Discriminate Analysis) analyses, we confirmed global metabolome changes for different groups (CIS, CIM, CIS+CIM vs control) in SA7K cells. Based on the criterion of a p-value ≤ 0.05 and a fold change ≥ 2 or ≤ 0.5, we identified 20 top metabolites that were significantly changed during the early phase i.e. within first 12 h of CIS treatment. Finally, pathway analysis was conducted that revealed the key metabolic pathways that were most impacted in CIN.

Stepwise solid phase extraction integrated with chemical derivatization for all-in-one injection LC-MS/MS analysis of metabolome and lipidome

The metabolome and lipidome are critical components in illustrating biological processes and pathological mechanisms. Generally, two or more independent methods are required to analyze the two compound panels due to their distinct chemical properties and polarity differences. Here, a novel strategy integrating stepwise solid-phase extraction (SPE) and dansyl chemical derivatization was proposed for all-in-one injection LC-MS/MS analysis of serum metabolome and lipidome. In this workflow, a stepwise elution procedure was firstly optimized to separate the metabolome and lipidome fractions using an Ostro plate. Dansyl chemical derivatization was then applied to label amine/phenol, carboxyl, and carbonyl-containing sub-metabolomes. Our results demonstrated that the dansyl labeling could significantly improve chromatographic separation, enhance the MS response, and overcome the matrix effect of co-eluting lipids. Ultimately, an all-in-one injection LC-MS/MS method measuring 256 lipids (covering 20 subclasses) and 212 metabolites (including amino acids, bile acids, fatty acids, acylcarnitines, indole derivatives, ketones and aldehydes, nucleic acid metabolism, polyamines, etc.) was established. This method was applied to investigate the metabolic changes in cisplatin-induced nephrotoxicity in rats and the results were compared with previous untargeted metabolomics. The presented strategy could predominantly improve the analytical coverage and throughput and can be of great use in discovering reliable potential biomarkers in various applications.

Integrated analysis of comprehensive metabolomics and network pharmacology to reveal the mechanisms of abelmoschus manihot (L.) medik. in the treatment of cisplatin-induced chronic kidney disease

Background: Abelmoschus manihot (L.) Medik (“Huangkui” in Chinese, HK) has been widely used for the treatment of kidney diseases. Nephrotoxicity is the side effect of cisplatin (CDDP), which greatly limits its clinical application. Therefore, CDDP could be used to establish the chronic kidney disease (CKD) model. However, the protective effects of HK on CDDP-induced CKD have not been investigated.

Purpose: To explore the protective effect and underlying mechanisms of HK on multiple low-dose CDDP-induced CKD in rats by the integrated analysis of serum, kidney, and urine metabolomics and network pharmacology.

Methods: The CKD model was induced by multiple low-dose CDDP. Body weight, organ index, serum biochemical, and kidney histology were examined to evaluate the effect of HK. Serum, kidney, and urine were collected and profiled by HILIC/RPLC-Q-TOF/MS-based metabolomics. Potential biomarkers (PBs) were screened according to the criteria of VIP >1, p < 0.01, and FC > 2, and then identified or assigned. The pathway analysis and PBs enrichment were conducted by MetaboAnalyst and ChemRICH. Furthermore, network pharmacology was adopted to dig out the active components and targets. Finally, the results from metabolomics and network pharmacology were integrated to confirm each other.

Results: HK could recover the CDDP-induced abnormal pharmacological and metabolic profile changes. A total of 187 PBs were screened and identified from the serum, kidney, and urine metabolomics. Pathway analysis showed that multiple metabolic pathways, mainly related to amino acid and lipid metabolisms, were involved in the nephroprotective effect of HK, and especially, HK could significantly alleviate the disorder of tryptophan metabolism pathway in serum, kidney, and urine. Meanwhile, network pharmacology analysis revealed that 5 components in HK and 4 key genes could be responsible for the nephroprotection of HK, which also indicated that the metabolism of tryptophan played an important role in HK against CKD.

Conclusion: HK has a nephroprotection on CDDP-induced CKD, mainly by restoring the dysregulation of tryptophan metabolism. Integrated analysis of serum, kidney, and urine metabolomics and network pharmacology was a powerful method for exploring pharmacological mechanisms and screening active components and targets of traditional Chinese medicine.

Tryptophan Pathway-Targeted Metabolomics Study on the Mechanism and Intervention of Cisplatin-Induced Acute Kidney Injury in Rats

Cisplatin is a chemotherapeutic agent widely employed in the treatment of various solid tumors. However, its use is often restricted by acute kidney injury (AKI) which is the dose-limiting adverse effect of cisplatin. While numerous studies aiming to alleviate the AKI have been conducted, there are no effective remedies in clinical practice. In this paper, a targeted metabolomics study was performed to reveal the potential relationship between tryptophan metabolism and cisplatin-induced AKI. A chemical derivatization integrated liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) approach was utilized to quantify 29 metabolites in the tryptophan pathway in rat kidney medulla and cortex after cisplatin administration. Results showed that tryptophan metabolism was remarkably disturbed both in the medulla and cortex after cisplatin administration. We also found that the tryptophan pathway in the medulla was more sensitive to cisplatin exposure compared with the cortex. Among these metabolites, indoxyl sulfate was focused for further study because it accumulated most significantly in the kidney cortex and medulla in a dose-dependent manner. A function verification study proved that chlormethiazole, a widely used CYP2E1 inhibitor, could reduce the production of indoxyl sulfate in the liver and attenuate cisplatin-induced AKI in rats. In conclusion, our study depicted the tryptophan pathway in cisplatin-induced AKI for the first time and demonstrated tryptophan metabolism is closely associated with the renal toxicity caused by cisplatin, which can be of great use for the discovery of renal toxicity attenuating remedies.

Identification of Novel Biomarkers for Predicting Kidney Injury Due to Drugs Using "Omic" Strategies

Drug-induced kidney injury accounts for 20% of community- and hospital-acquired cases of acute kidney injury (AKI). The incidence is higher among older individuals, who often have co-existing morbidities and are exposed to more diagnostic procedures and therapies. While demographic and clinical components have been identified as risk factors, the proposed cellular mechanisms of drug-induced kidney injury are numerous and complicated. There are also limitations recognized in the use of traditional biomarkers, such as serum creatinine and blood urea nitrogen, to provide high sensitivity, specificity, and timeliness to identification of drug-induced kidney injury. Therefore, novel biomarkers are currently being investigated, identified, developed, and validated for their performance over the traditional biomarkers. This review will provide an overview of drug-induced kidney injury and will discuss what is known regarding "omic" (proteomic, genomic, transcriptomic, and metabolomic) biomarker strategies for drugs known to induce nephrotoxicity.

Metallodrugs are unique: opportunities and challenges of discovery and development

Metals play vital roles in nutrients and medicines and provide chemical functionalities that are not accessible to purely organic compounds. At least 10 metals are essential for human life and about 46 other non-essential metals (including radionuclides) are also used in drug therapies and diagnostic agents. These include platinum drugs (in 50% of cancer chemotherapies), lithium (bipolar disorders), silver (antimicrobials), and bismuth (broad-spectrum antibiotics). While the quest for novel and better drugs is now as urgent as ever, drug discovery and development pipelines established for organic drugs and based on target identification and high-throughput screening of compound libraries are less effective when applied to metallodrugs. Metallodrugs are often prodrugs which undergo activation by ligand substitution or redox reactions, and are multi-targeting, all of which need to be considered when establishing structure-activity relationships. We focus on early-stage in vitro drug discovery, highlighting the challenges of evaluating anticancer, antimicrobial and antiviral metallo-pharmacophores in cultured cells, and identifying their targets. We highlight advances in the application of metal-specific techniques that can assist the preclinical development, including synchrotron X-ray spectro(micro)scopy, luminescence, and mass spectrometry-based methods, combined with proteomic and genomic (metallomic) approaches. A deeper understanding of the behavior of metals and metallodrugs in biological systems is not only key to the design of novel agents with unique mechanisms of action, but also to new understanding of clinically-established drugs.

Integrated Metabolomics and Network Pharmacology Strategy-Driven Active Traditional Chinese Medicine Ingredients Discovery for the Alleviation of Cisplatin Nephrotoxicity

Renal injury is the main adverse reaction of cisplatin, and many traditional Chinese medicines (TCMs) were proven active against renal toxicity. Here, an integrated metabolomics and network pharmacology strategy was proposed to discover active TCM ingredients for the alleviation of cisplatin nephrotoxicity. First, by interrogating the Human Metabolome Database (HMDB) we collected targets connected to 149 cisplatin nephrotoxicity-related metabolites. Second, targets of kidney damage were obtained from the Therapeutic Target Database (TTD), PharmGKB, Online Mendelian Inheritance in Man (OMIM), and Genetic Association Database (GAD). Common targets of both dysregulated metabolites and kidney damage were then used for TCM active ingredient screening by applying the network pharmacology approach. Eventually, 22 ingredients passed screening criteria, and their antinephrotoxicity activity was assessed in human kidney tubular epithelial (HK2) cells. As a result, 14 ingredients were found to be effective, in which kaempferol showed relatively better activity. Further metabolomics analysis revealed that kaempferol exerted an antinephrotoxicity effect in rats by regulating amino acid, pyrimidine, and purine metabolism as well as lipid metabolism. Collectively, this proposed integrated strategy would promote the transformation of metabolomics research in the field of drug pair discovery for the purpose of reduced toxicity and increased efficiency.

Multi-Organ NMR Metabolomics to Assess In Vivo Overall Metabolic Impact of Cisplatin in Mice

This work describes, to our knowledge, the first NMR metabolomics analysis of mice kidney, liver, and breast tissue in response to cisplatin exposure, in search of early metabolic signatures of cisplatin biotoxicity. Balb/c mice were exposed to a single 3.5 mg/kg dose of cisplatin and then euthanized; organs (kidney, liver, breast tissue) were collected at 1, 12, and 48 h. Polar tissue extracts were analyzed by NMR spectroscopy, and the resulting spectra were studied by multivariate and univariate analyses. The results enabled the identification of the most significant deviant metabolite levels at each time point, and for each tissue type, and showed that the largest metabolic impact occurs for kidney, as early as 1 h post-injection. Kidney tissue showed a marked depletion in several amino acids, comprised in an overall 13-metabolites signature. The highest number of changes in all tissues was noted at 12 h, although many of those recovered to control levels at 48 h, with the exception of some persistently deviant tissue-specific metabolites, thus enabling the identification of relatively longer-term effects of cDDP. This work reports, for the first time, early (1-48 h) concomitant effects of cDDP in kidney, liver, and breast tissue metabolism, thus contributing to the understanding of multi-organ cDDP biotoxicity.

Metabolomic and biochemical characterization of a new model of the transition of acute kidney injury to chronic kidney disease induced by folic acid

Background

Renal diseases represent a major public health problem. The demonstration that maladaptive repair of acute kidney injury (AKI) can lead to the development of chronic kidney disease (CKD) and end-stage renal disease has generated interest in studying the pathophysiological pathways involved. Animal models of AKI–CKD transition represent important tools to study this pathology. We hypothesized that the administration of multiple doses of folic acid (FA) would lead to a progressive loss of renal function that could be characterized through biochemical parameters, histological classification and nuclear magnetic resonance (NMR) profiling.

Methods

Wistar rats were divided into groups: the control group received a daily intraperitoneal (I.P.) injection of double-distilled water, the experimental group received a daily I.P. injection of FA (250 mg kg body weight⁻¹). Disease was classified according to blood urea nitrogen level: mild (40–80 mg dL⁻¹), moderate (100–200 mg dL⁻¹) and severe (>200 mg dL⁻¹). We analyzed through biochemical parameters, histological classification and NMR profiling.

Results

Biochemical markers, pro-inflammatory cytokines and kidney injury biomarkers differed significantly (P < 0.05) between control and experimental groups. Histology revealed that as damage progressed, the degree of tubular injury increased, and the inflammatory infiltrate was more evident. NMR metabolomics and chemometrics revealed differences in urinary metabolites associated with CKD progression. The main physiological pathways affected were those involved in energy production and amino-acid metabolism, together with organic osmolytes. These data suggest that multiple administrations of FA induce a reproducible model of the induction of CKD. This model could help to evaluate new strategies for nephroprotection that could be applied in the clinic.

Pharmacometabolomic prediction of individual differences of gastrointestinal toxicity complicating myelosuppression in rats induced by irinotecan

Pharmacometabolomics has been already successfully used in toxicity prediction for one specific adverse effect. However in clinical practice, two or more different toxicities are always accompanied with each other, which puts forward new challenges for pharmacometabolomics. Gastrointestinal toxicity and myelosuppression are two major adverse effects induced by Irinotecan (CPT-11), and often show large individual differences. In the current study, a pharmacometabolomic study was performed to screen the exclusive biomarkers in predose serums which could predict late-onset diarrhea and myelosuppression of CPT-11 simultaneously. The severity and sensitivity differences in gastrointestinal toxicity and myelosuppression were judged by delayed-onset diarrhea symptoms, histopathology examination, relative cytokines and blood cell counts. Mass spectrometry-based non-targeted and targeted metabolomics were conducted in sequence to dissect metabolite signatures in predose serums. Eventually, two groups of metabolites were screened out as predictors for individual differences in late-onset diarrhea and myelosuppression using binary logistic regression, respectively. This result was compared with existing predictors and validated by another independent external validation set. Our study indicates the prediction of toxicity could be possible upon predose metabolic profile. Pharmacometabolomics can be a potentially useful tool for complicating toxicity prediction. Our findings also provide a new insight into CPT-11 precision medicine.

Zebrafish Larvae Are a Suitable Model to Investigate the Metabolic Phenotype of Drug-Induced Renal Tubular Injury

Prevention and treatment of drug-induced renal injury (DIRI) rely on the availability of sensitive and specific biomarkers of early kidney injury and predictive animal models of human pathophysiology. This study aimed to evaluate the potential of zebrafish larvae as translational model in metabolic profiling of DIRI. Zebrafish larvae were exposed to the lethal concentration for 10% of the larvae (LC10) or ½ LC10 of gentamicin, paracetamol and tenofovir as tenofovir disoproxil fumarate (TDF) and tenofovir (TFV). Metabolites were extracted from whole larvae and analyzed by liquid chromatography-mass spectrometry. Principal component analysis showed that drug exposition to the LC10 of paracetamol, TFV, and TDF was the main source of the variance of the data. To identify the metabolites responsible for the toxic effects of the drugs, partial least squares discriminant analyses were built between the LC10 and ½ LC10 for each drug. Features with variable importance in projection> 1.0 were selected and Venn diagrams were built to differentiate between the common and drug specific metabolites of DIRI. Creatine, tyrosine, glutamine, guanosine, hypoxanthine were identified as common metabolites, adenosine and tryptophan as paracetamol-specific and xanthine and oxidized glutathione as tenofovir-specific. Those metabolic changes can be associated with alterations in energy metabolism, xenobiotic detoxification and protein catabolism, all described in the human pathophysiology of DIRI. Thus, zebrafish proved to be a suitable model to characterize the metabolic changes associated with DIRI. This information can be useful to early diagnose DIRI and to improve our knowledge on the mechanisms of DIRI.

Metabolomics Reveals the Efficacy of Caspase Inhibition for Saikosaponin D-Induced Hepatotoxicity

Saikosaponin d (SSd) is a major hepatoprotective component of saikosaponins derived from Radix Bupleuri, which was also linked to hepatotoxicity. Previous studies have demonstrated that caspases play a key role in SSd-induced liver cell death. Our in vitro and in vivo studies also showed that treatment with caspase inhibitor z-VAD-fmk could significantly reduce the L02 hepatocyte cells death and lessen the degree of liver damage in mice caused by SSd. In order to further reveal the underlying mechanisms of caspase inhibition in SSd-induced hepatotoxicity, mass spectrometry based untargeted metabolomics was conducted. Significant alterations in metabolic profiling were observed in SSd-treated group, which could be restored by caspase inhibition. Bile acids and phospholipids were screened out to be most significant by spearman correlation analysis, heatmap analysis and S-Plot analysis. These findings were further confirmed by absolute quantitation of bile acids via targeted metabolomics approach. Furthermore, cytokine profiles were analyzed to identify potential associations between inflammation and metabolites. The study could provide deeper insight into the hepatotoxicity of SSd and the efficacy of caspase inhibition.

Metabolic characterization of directly reprogrammed renal tubular epithelial cells (iRECs)

Fibroblasts can be directly reprogrammed to induced renal tubular epithelial cells (iRECs) using four transcription factors. These engineered cells may be used for disease modeling, cell replacement therapy or drug and toxicity testing. Direct reprogramming induces drastic changes in the transcriptional landscape, protein expression, morphological and functional properties of cells. However, how the metabolome is changed by reprogramming and to what degree it resembles the target cell type remains unknown. Using untargeted gas chromatography-mass spectrometry (GC-MS) and targeted liquid chromatography-MS, we characterized the metabolome of mouse embryonic fibroblasts (MEFs), iRECs, mIMCD-3 cells, and whole kidneys. Metabolic fingerprinting can distinguish each cell type reliably, revealing iRECs are most similar to mIMCD-3 cells and clearly separate from MEFs used for reprogramming. Treatment with the cytotoxic drug cisplatin induced typical changes in the metabolic profile of iRECs commonly occurring in acute renal injury. Interestingly, metabolites in the medium of iRECs, but not of mIMCD-3 cells or fibroblast could distinguish treated and non-treated cells by cluster analysis. In conclusion, direct reprogramming of fibroblasts into renal tubular epithelial cells strongly influences the metabolome of engineered cells, suggesting that metabolic profiling may aid in establishing iRECs as in vitro models for nephrotoxicity testing in the future.

Urinary metabolomics reveals the therapeutic effect of HuangQi Injections in cisplatin-induced nephrotoxic rats

The side effects of cisplatin (CDDP), notably nephrotoxicity, greatly limited its use in clinical chemotherapy. HuangQi Injections (HI), a commonly used preparation of the well-known Chinese herbal medicine Astragali radix, appeared to be promising treatment for nephrotoxicity without compromising the anti-tumor activity of CDDP. In this study, the urinary metabolomics approach using liquid chromatography time of flight mass spectrometry (LC-TOF/MS) was developed to assess the toxicity-attenuation effects and corresponding mechanisms of HI on CDDP-exposed rats. As a result, successive administration of HI significantly recovered the decline of body weight and downregulated the abnormal increase of serum creatinine and urea. HI partly restored the CDDP-induced alteration of metabolic profiling back into normal condition. Totally 43 toxicity-attenuation potential biomarkers were screened and tentatively identified, which were involved in important metabolic pathways such as amino acid metabolism, TCA cycle, fatty acid metabolism, vitamin B6 metabolism and purine metabolism. The results clearly revealed that HI could alleviate CDDP-induced nephrotoxicity and improve the disturbed metabolic balance induced by repeated CDDP exposure. The present study provided reliable evidence for the protective effect of HI on CDDP-induced toxicity with the multi-target pharmacological characteristics.

Influences of Normalization Method on Biomarker Discovery in Gas Chromatography-Mass Spectrometry-Based Untargeted Metabolomics: What Should Be Considered?

Data reduction techniques in gas chromatography-mass spectrometry-based untargeted metabolomics has made the following workflow of data analysis more lucid. However, the normalization process still perplexes researchers, and its effects are always ignored. In order to reveal the influences of normalization method, five representative normalization methods (mass spectrometry total useful signal, median, probabilistic quotient normalization, remove unwanted variation-random, and systematic ratio normalization) were compared in three real data sets with different types. First, data reduction techniques were used to refine the original data. Then, quality control samples and relative log abundance plots were utilized to evaluate the unwanted variations and the efficiencies of normalization process. Furthermore, the potential biomarkers which were screened out by the Mann-Whitney U test, receiver operating characteristic curve analysis, random forest, and feature selection algorithm Boruta in different normalized data sets were compared. The results indicated the determination of the normalization method was difficult because the commonly accepted rules were easy to fulfill but different normalization methods had unforeseen influences on both the kind and number of potential biomarkers. Lastly, an integrated strategy for normalization method selection was recommended.

Quantitative Evaluation of the Compatibility Effects of Huangqin Decoction on the Treatment of Irinotecan-Induced Gastrointestinal Toxicity Using Untargeted Metabolomics

Huangqin decoction (HQD), a traditional Chinese medicine (TCM), has been widely used to treat gastrointestinal syndrome in China for thousands of years. Chemotherapy drug irinotecan (CPT-11) is used clinically to treat various kinds of cancers but limited by its side effects, especially delayed diarrhea. Nowadays, HQD has been proved to be effective in attenuating the intestinal toxicity induced by CPT-11. HQD consists of four medicinal herbs including Scutellaria baicalensis Georgi, Glycyrrhiza uralensis Fisch, Paeonia lactiflora Pall, and Ziziphus jujuba Mill. Due to its complexity, the role of each herb and the multi-herb synergistic effects of the formula are poorly understood. In order to quantitatively assess the compatibility effects of HQD, mass spectrometry-based untargeted metabolomics studies were performed. The serum metabolic profiles of rats administered with HQD, single S. baicalensis decoction, S. baicalensis-free decoction and baicalin/baicalein combination were compared. A time-dependent trajectory upon principal component analysis was firstly used to visualize the overall differences. Then metabolites deregulation score and relative area under the curve were calculated and used as parameters to quantitatively evaluate the compatibility effects of HQD from the aspect of global metabolic profile and the specifically altered metabolites, respectively. The collective results indicated that S. baicalensis played a crucial role in the therapeutic effect of HQD on irinotecan-induced diarrhea. Both HQD and SS decoction regulated glycine, serine and threonine pathway. This study demonstrated that metabolomics was a promising tool to elucidate the compatibility effects of TCM or combinatorial drugs.

Renal Medulla is More Sensitive to Cisplatin than Cortex Revealed by Untargeted Mass Spectrometry-Based Metabolomics in Rats

Nephrotoxicity has long been the most severe and life-threatening side-effect of cisplatin, whose anticancer effect is therefore restricted. Previous pathological studies have shown that both renal cortex and medulla could be injured by cisplatin. Our TUNEL (terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling) assay results further uncovered that medulla subjected more severe injury than cortex. In order to depict the underlying metabolic mechanism of spatial difference in response to cisplatin, in the present study, mass spectrometry-based untargeted metabolomics approach was applied to profile renal cortex and medulla metabolites of rat after receiving a single dose of cisplatin (2.5, 5 or 10 mg/kg). Eventually, 53 and 55 differential metabolites in cortex and medulla were screened out, respectively. Random forest, orthogonal partial least squares-discriminant analysis and metabolic cumulative fold change analysis revealed that metabolic changes in medulla were more obviously dose-dependent than those in cortex, which confirmed the conclusion that medulla was more sensitive to cisplatin exposure. Furthermore, 29 intermediates were recognized as the most contributive metabolites for the sensitivity difference. Metabolic pathways interrupted by cisplatin mainly included amino acid, energy, lipid, pyrimidine, purine, and creatine metabolism. Our findings provide new insight into the mechanism study of cisplatin-induced nephrotoxicity.

Discovery of Metabolite Biomarkers for Acute Ischemic Stroke Progression

Stroke remains a major public health problem worldwide; it causes severe disability and is associated with high mortality rates. However, early diagnosis of stroke is difficult, and no reliable biomarkers are currently established. In this study, mass-spectrometry-based metabolomics was utilized to characterize the metabolic features of the serum of patients with acute ischemic stroke (AIS) to identify novel sensitive biomarkers for diagnosis and progression. First, global metabolic profiling was performed on a training set of 80 human serum samples (40 cases and 40 controls). The metabolic profiling identified significant alterations in a series of 26 metabolites with related metabolic pathways involving amino acid, fatty acid, phospholipid, and choline metabolism. Subsequently, multiple algorithms were run on a test set consisting of 49 serum samples (26 cases and 23 controls) to develop different classifiers for verifying and evaluating potential biomarkers. Finally, a panel of five differential metabolites, including serine, isoleucine, betaine, PC(5:0/5:0), and LysoPE(18:2), exhibited potential to differentiate AIS samples from healthy control samples, with area under the receiver operating characteristic curve values of 0.988 and 0.971 in the training and test sets, respectively. These findings provided insights for the development of new diagnostic tests and therapeutic approaches for AIS.