Urinary Metabolomic Profiling to Identify Potential Biomarkers for the Diagnosis of Behcet's Disease by Gas Chromatography/Time-of-Flight-Mass Spectrometry

Quantitative urinary proteome analysis reveals potential biomarkers for disease activity of Behcet's disease uveitis

PURPOSE

Behçet's disease-associated uveitis (BDU) is a severe, recurrent inflammatory condition affecting the eye and is part of a systemic vasculitis with unknown etiology, making biomarker discovery essential for disease management. In this study, we intend to investigate potential urinary biomarkers to monitor the disease activity of BDU.

METHODS

Firstly, label-free data-dependent acquisition (DDA) and tandem mass tag (TMT)-labeled quantitative proteomics methods were used to profile the proteomes of urine from active and quiescent BDU patients, respectively. For further exploration, the remaining fifty urine samples were analyzed by a data-independent acquisition (DIA) quantitative proteomics method.

RESULTS

Twenty-nine and 21 differential proteins were identified in the same urine from BDU patients by label-free DDA and TMT-labeled analyses, respectively. Seventy-nine differentially expressed proteins (DEPs) were significantly changed in other active BDU urine samples compared to those in quiescent BDU urine samples by IDA analysis. Gene Ontology (GO) and protein-protein interaction (PPI) analyses revealed that the DEPs were associated with multiple functions, including the immune and neutrophil activation responses. Finally, seven proteins were identified as candidate biomarkers for BDU monitoring and recurrence prediction, namely, CD38, KCRB, DPP4, FUCA2, MTPN, S100A8 and S100A9.

CONCLUSIONS

Our results showed that urine can be a good source of biomarkers for BDU. These dysregulated proteins provide potential urinary biomarkers for BDU activity monitoring and provide valuable clues for the analysis of the pathogenic mechanisms of BDU.

Effect of serum metabolites on the risk of iridocyclitis: a bidirectional Mendelian randomization study

Previous research has linked serum metabolite levels to iridocyclitis, yet their causal relationship remains unexplored. This study investigated this potential causality by analyzing pooled data from 7824 iridocyclitis patients in a Genome-Wide Association Study (GWAS) using Mendelian randomization (MR) and linkage disequilibrium score regression (LDSC). Employing rigorous quality control and comprehensive statistical methods, including sensitivity analyses, we examined the influence of 486 serum metabolites on iridocyclitis. Our MR analysis identified 23 metabolites with significant causal effects on iridocyclitis, comprising 17 known and 6 unidentified metabolites. Further refinement using Cochran's Q test and MR-PRESSO indicated 16 metabolites significantly associated with iridocyclitis risk. LDSC highlighted the heritability of certain metabolites, underscoring genetic influences on their levels. Notably, tryptophan, proline, theobromine, and 7-methylxanthine emerged as risk factors, while 3,4-dihydroxybutyrate appeared protective. These findings enhance our understanding of the metabolic interactions in iridocyclitis, offering insights for diagnosis, unraveling pathophysiological mechanisms, and informing potential avenues for prevention and personalized treatment.

Identification of biomarkers for abdominal aortic aneurysm in Behçet's disease via mendelian randomization and integrated bioinformatics analyses

Behçet's disease (BD) is a complex autoimmune disorder impacting several organ systems. Although the involvement of abdominal aortic aneurysm (AAA) in BD is rare, it can be associated with severe consequences. In the present study, we identified diagnostic biomarkers in patients with BD having AAA. Mendelian randomization (MR) analysis was initially used to explore the potential causal association between BD and AAA. The Limma package, WGCNA, PPI and machine learning algorithms were employed to identify potential diagnostic genes. A receiver operating characteristic curve (ROC) for the nomogram was constructed to ascertain the diagnostic value of AAA in patients with BD. Finally, immune cell infiltration analyses and single-sample gene set enrichment analysis (ssGSEA) were conducted. The MR analysis indicated a suggestive association between BD and the risk of AAA (odds ratio [OR]: 1.0384, 95% confidence interval [CI]: 1.0081-1.0696, p = 0.0126). Three hub genes (CD247, CD2 and CCR7) were identified using the integrated bioinformatics analyses, which were subsequently utilised to construct a nomogram (area under the curve [AUC]: 0.982, 95% CI: 0.944-1.000). Finally, the immune cell infiltration assay revealed that dysregulation immune cells were positively correlated with the three hub genes. Our MR analyses revealed a higher susceptibility of patients with BD to AAA. We used a systematic approach to identify three potential hub genes (CD247, CD2 and CCR7) and developed a nomogram to assist in the diagnosis of AAA among patients with BD. In addition, immune cell infiltration analysis indicated the dysregulation in immune cell proportions.

Combined Metabolome and Transcriptome Analysis Elucidates Sugar Accumulation in Wucai (Brassica campestris L.)

Wucai (Brassica campestris L.) is a leafy vegetable that originated in China, its soluble sugars accumulate significantly to improve taste quality during maturation, and it is widely accepted by consumers. In this study, we investigated the soluble sugar content at different developmental stages. Two periods including 34 days after planting (DAP) and 46 DAP, which represent the period prior to and after sugar accumulation, respectively, were selected for metabolomic and transcriptomic profiling. Differentially accumulated metabolites (DAMs) were mainly enriched in the pentose phosphate pathway, galactose metabolism, glycolysis/gluconeogenesis, starch and sucrose metabolism, and fructose and mannose metabolism. By orthogonal projection to latent structures-discriminant s-plot (OPLS-DA S-plot) and MetaboAnalyst analyses, D-galactose and β-D-glucose were identified as the major components of sugar accumulation in wucai. Combined with the transcriptome, the pathway of sugar accumulation and the interact network between 26 DEGs and the two sugars were mapped. CWINV4, CEL1, BGLU16, and BraA03g023380.3C had positive correlations with the accumulation of sugar accumulation in wucai. The lower expression of BraA06g003260.3C, BraA08g002960.3C, BraA05g019040.3C, and BraA05g027230.3C promoted sugar accumulation during the ripening of wucai. These findings provide insights into the mechanisms underlying sugar accumulation during commodity maturity, providing a basis for the breeding of sugar-rich wucai cultivars.

Finding the Needle in the Haystack: Serological and Urinary Biomarkers in Behçet's Disease: A Systematic Review

Urinary and serological markers play an essential role in the diagnostic process of autoimmune diseases. However, to date, specific and reliable biomarkers for diagnosing Behçet's disease (BD) are still lacking, negatively affecting the management of these patients. To analyze the currently available literature on serological and urinary BD biomarkers investigated in the last 25 years, we performed a systematic literature review using the Population, Intervention, Comparison, and Outcomes (PICO) strategy. One hundred eleven studies met the eligibility criteria (6301 BD patients, 5163 controls). Most of them were retrospective, while five (5%) were prospective. One hundred ten studies (99%) investigated serological biomarkers and only two (2%) focused on urinary biomarkers. One hundred three studies (93%) explored the diagnostic potential of the biomolecules, whereas sixty-two (56%) tested their effect on disease activity monitoring. Most articles reported an increase in inflammatory markers and pro-oxidant molecules, with a decrease in antioxidants. Promising results have been shown by the omics sciences, offering a more holistic approach. Despite the vast number of investigated markers, existing evidence indicates a persistent gap in BD diagnostic/prognostic indices. While new steps have been taken in the direction of pathogenesis and disease monitoring, international efforts for the search of a diagnostic marker for BD are still needed.

Integrative metabolomics of plasma and PBMCs identifies distinctive metabolic signatures in Behçet's disease

BACKGROUND

Behçet's disease (BD) is a systemic inflammatory disease that involves various organs. The clinical manifestation-based diagnosis of BD is a time-consuming process, which makes it difficult to distinguish from patients with similar symptoms. Moreover, an authentic biomarker has not been developed for accurate diagnosis yet. Our current study investigated the unique metabolic signatures of BD and explored biomarkers for precise diagnosis based on an untargeted metabolomic approach.

METHODS

Integrative metabolomic and lipidomic profiling was performed on plasma samples of BD patients (n = 40), healthy controls (HCs, n = 18), and disease controls (DCs, n = 17) using GC-TOF MS and LC-Orbitrap MS. Additionally, the lipid profiles of 66 peripheral blood mononuclear cells (PBMCs) were analyzed from 29 BD patients, 18 HCs, and 19 DCs.

RESULTS

Plasma metabolic dysfunction in BD was determined in carbohydrate, hydroxy fatty acid, and polyunsaturated fatty acid metabolisms. A plasma biomarker panel with 13 compounds was constructed, which simultaneously distinguished BD from HC and DC (AUCs ranged from 0.810 to 0.966). Dysregulated PBMC metabolome was signatured by a significant elevation in lysophosphatidylcholines (LPCs) and ether-linked lysophosphatidylethanolamines (EtherLPEs). Ten PBMC-derived lipid composites showed good discrimination power (AUCs ranged from 0.900 to 0.973). Correlation analysis revealed a potential association between disease activity and the metabolites of plasma and PBMC, including sphingosine-1 phosphate and EtherLPE 18:2.

CONCLUSIONS

We identified metabolic biomarkers from plasma PBMC, which selectively discriminated BD from healthy control and patients with similar symptoms (recurrent mouth ulcers with/without genital ulcers). The strong correlation was determined between the BD activity and the lipid molecules. These findings may lead to the development for diagnostic and prognostic biomarkers based on a better understanding of the BD pathomechanism.

Kernel-based hierarchical structural component models for pathway analysis

MOTIVATION

Pathway analyses have led to more insight into the underlying biological functions related to the phenotype of interest in various types of omics data. Pathway-based statistical approaches have been actively developed, but most of them do not consider correlations among pathways. Because it is well known that there are quite a few biomarkers that overlap between pathways, these approaches may provide misleading results. In addition, most pathway-based approaches tend to assume that biomarkers within a pathway have linear associations with the phenotype of interest, even though the relationships are more complex.

RESULTS

To model complex effects including nonlinear effects, we propose a new approach, Hierarchical structural CoMponent analysis using Kernel (HisCoM-Kernel). The proposed method models nonlinear associations between biomarkers and phenotype by extending the kernel machine regression and analyzes entire pathways simultaneously by using the biomarker-pathway hierarchical structure. HisCoM-Kernel is a flexible model that can be applied to various omics data. It was successfully applied to three omics datasets generated by different technologies. Our simulation studies showed that HisCoM-Kernel provided higher statistical power than other existing pathway-based methods in all datasets. The application of HisCoM-Kernel to three types of omics dataset showed its superior performance compared to existing methods in identifying more biologically meaningful pathways, including those reported in previous studies.

AVAILABILITY AND IMPLEMENTATION

Freely available at http://statgen.snu.ac.kr/software/HisCom-Kernel/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Molecular Probes, Chemosensors, and Nanosensors for Optical Detection of Biorelevant Molecules and Ions in Aqueous Media and Biofluids

Synthetic molecular probes, chemosensors, and nanosensors used in combination with innovative assay protocols hold great potential for the development of robust, low-cost, and fast-responding sensors that are applicable in biofluids (urine, blood, and saliva). Particularly, the development of sensors for metabolites, neurotransmitters, drugs, and inorganic ions is highly desirable due to a lack of suitable biosensors. In addition, the monitoring and analysis of metabolic and signaling networks in cells and organisms by optical probes and chemosensors is becoming increasingly important in molecular biology and medicine. Thus, new perspectives for personalized diagnostics, theranostics, and biochemical/medical research will be unlocked when standing limitations of artificial binders and receptors are overcome. In this review, we survey synthetic sensing systems that have promising (future) application potential for the detection of small molecules, cations, and anions in aqueous media and biofluids. Special attention was given to sensing systems that provide a readily measurable optical signal through dynamic covalent chemistry, supramolecular host-guest interactions, or nanoparticles featuring plasmonic effects. This review shall also enable the reader to evaluate the current performance of molecular probes, chemosensors, and nanosensors in terms of sensitivity and selectivity with respect to practical requirement, and thereby inspiring new ideas for the development of further advanced systems.

Urinary levels of dimethoate, bisphenol A and benzo[a]pyrene in first-year students of Hohai University from different geographical regions

BACKGROUND

The objective of this study was to detect the urinary levels of dimethoate, benzo(a) pyrene (BaP), and bisphenol A (BPA) in first-year Hohai University students with different geographic origins.

METHODS

First-morning urine samples were collected from 540 healthy freshmen aged 17 to 19 years. Chemical levels were measured using β-glucuronidase hydrolysis followed by a high-performance liquid chromatography-tandem mass spectrometry-based method. Geometric means (GMs) of these three chemicals are presented by body mass index (BMI) and location in a volume-based and creatinine-standardized way.

RESULTS

GM concentrations of omethoate, BPA and 3-OHBaP were 9.47 μg/L (10.80 μg/g creatinine), 3.54 μg/L (4.04 μg/g creatinine) and 0.34 ng/L (0.39 ng/g creatinine), respectively. The GM concentration of omethoate in males was significantly higher than that in females. The individuals with a BMI higher than 23.9 had higher GM concentrations of omethoate, BPA, and 3-OHBaP. The inhabitants of Southwest China had significantly lower GM concentrations of omethoate, BPA, and 3-OHBaP than those who lived in other locations in China.

CONCLUSION

The average level of environmental chemical accumulation in freshmen is lower in Southwest China and differs in youth who live in different regions. In addition, obesity is correlated with higher toxin levels in youth.

Specific sweat metabolite profile in ocular Behcet's disease

BACKGROUND

Behcet's disease (BD) is an autoimmune disorder with the serious possibility of blindness, calling for further research on its pathogenesis. Our aim was to study the metabolite composition of sweat in BD and to identify possible biomarkers.

METHODS

Metabolomics analysis was performed on sweat samples from 20 BD patients and 18 normal controls by liquid chromatography tandem mass spectrometry.

RESULTS

A significantly different metabolic profile of sweat was observed when BD patients were compared with healthy controls. The result of the orthogonal partial least squared-discrimination analysis (OPLS-DA) showed that these two comparison groups could be separated with a relatively satisfactory fitting degree (R2Y = 0.995 and Q2 = 0.817 in positive ion mode; R2Y = 0.991 and Q2 = 0.721 in negative ion mode). Based on OPLS-DA, a panel of metabolites was selected as candidate biomarkers, including l-citrulline, l-pyroglutamic acid, urocanic acid, 2-oxoadipic acid, cholesterol 3-sulfate, and pentadecanoic acid.

CONCLUSION

This is the first report on the metabolite profile of sweat in BD. Our results demonstrated a significantly different metabolite composition of sweat in BD compared to that of healthy controls.

Metabolomics Analysis of Viral Therapeutics

Virotherapy, enabled by recent advances in the transdisciplinary field of biotechnology, has emerged as a powerful tool for use in anticancer treatment, gene therapy, immunotherapy, etc. Examining the effects of viruses and virus-derived immune-modulating therapeutics is of great fundamental and clinical interest. Here we describe a sample preparation protocol for metabolite extraction from virus-infected tissue, in addition to liquid chromatography-mass spectrometry conditions essential for subsequent analysis. This metabolomics approach delivers highly sensitive and specific metabolite information on various biospecimens. Such an approach may be adopted to monitor biological changes in over 30 relevant metabolic pathways in response to viral infection and also viral therapeutics.

Metabolomic Analysis of Aqueous Humor Identifies Aberrant Amino Acid and Fatty Acid Metabolism in Vogt-Koyanagi-Harada and Behcet's Disease

To investigate aqueous metabolic profiles in Vogt-Koyanagi-Harada (VKH) and Behcet's disease (BD), we applied ultra-high-performance liquid chromatography equipped with quadrupole time-of flight mass spectrometry in aqueous humor samples collected from these patients and controls. Metabolite levels in these three groups were analyzed by univariate logistic regression. The differential metabolites were subjected to subsequent pathway analysis by MetaboAnalyst. The results showed that both partial-least squares discrimination analysis and hierarchical clustering analysis showed specific aqueous metabolite profiles when comparing VKH, BD, and controls. There were 28 differential metabolites in VKH compared to controls and 29 differential metabolites in BD compared to controls. Amino acids and fatty acids were the two most abundant categories of differential metabolites. Furthermore, pathway enrichment analysis identified several perturbed pathways, including pantothenate and CoA biosynthesis when comparing VKH with the control group, and D-arginine and D-ornithine metabolism and phenylalanine metabolism when comparing BD with the control group. Aminoacyl-tRNA biosynthesis was altered in both VKH and BD when compared to controls. Our findings suggest that amino acids metabolism as well as two fatty acids, palmitic acid and oleic acid, may be involved in the pathogenesis of BD and VKH.

Serum Metabolomic Profiling of Patients with Non-Infectious Uveitis

The activities of various metabolic pathways can influence the pathogeneses of autoimmune diseases, and intrinsic metabolites can potentially be used to diagnose diseases. However, the metabolomic analysis of patients with uveitis has not yet been conducted. Here, we profiled the serum metabolomes of patients with three major forms of uveitis (Behҫet's disease (BD), sarcoidosis, and Vogt-Koyanagi-Harada disease (VKH)) to identify potential biomarkers. This study included 19 BD, 20 sarcoidosis, and 15 VKH patients alongside 16 healthy control subjects. The metabolite concentrations in their sera were quantified using liquid chromatography with time-of-flight mass spectrometry. The discriminative abilities of quantified metabolites were evaluated by four comparisons: control vs. three diseases, and each disease vs. the other two diseases (such as sarcoidosis vs. BD + VKH). Among 78 quantified metabolites, 24 kinds of metabolites showed significant differences in these comparisons. Four multiple logistic regression models were developed and validated. The area under the receiver operating characteristic (ROC) curve (AUC) in the model to discriminate disease groups from control was 0.72. The AUC of the other models to discriminate sarcoidosis, BD, and VKH from the other two diseases were 0.84, 0.83, and 0.73, respectively. This study provides potential diagnostic abilities of sarcoidosis, BD, and VKH using routinely available serum samples that can be collected with minimal invasiveness.

A review of strategies for untargeted urinary metabolomic analysis using gas chromatography-mass spectrometry

BACKGROUND

Human urine gives evidence of the metabolism in the body and contains different metabolites at various concentrations. A number of analytical techniques including mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been used to obtain metabolites levels in urine samples. However, gas chromatography-mass spectrometry (GC-MS) is one of the most widely used techniques for urinary metabolomics studies due to its higher sensitivity, resolution, reproducibility, reliability, relatively low cost and ease of operation compared to liquid chromatography-mass spectrometry and NMR.

AIM OF REVIEW

This review looks at various aspects of urine preparation prior to analysis by GC-MS including sample storage, urease pretreatment, derivatization, use of internal standard and quality control samples for data correction. In addition, most common types of inlet liners, ionization techniques and columns are discussed and a summary of mass analyzers are also highlighted. Lastly, the role of retention index in metabolite identification and data normalization methods are presented.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is summarizing methods of sample storage, pretreatment, and GC-MS analysis that are mostly used in urine metabolomics studies. Specific emphasis is given to the critical steps within the GC-MS urine metabolomics that those new to this field need to be aware of and the remaining challenges that require further attention and studies.

Plasma metabolomics study of Vogt-Koyanagi-Harada disease identifies potential diagnostic biomarkers

Vogt-Koyanagi-Harada (VKH) disease is a common type of uveitis in China, but the diagnosis criteria of VKH disease is controversial. The aim of this study was to investigate potential diagnostic plasma biomarkers for VKH disease. A case-control study including 55 VKH patients (28 active patients and 27 inactive VKH patients) and 30 healthy controls in a tertiary referral center was performed. The metabolic phenotype of VKH patients showed a significant difference compared to healthy controls. Fifteen differentially expressed metabolites (DEMs) were identified between active VKH patients and healthy controls and nine DEMs were found between inactive VKH patients and healthy controls after controlling variable importance in the projection (VIP) value > 1 and false discovery rate (FDR) < 0.05. D-mannose, stearic acid and L-lysine were shown to be potential diagnostic biomarkers which can discriminate active VKH patients from healthy controls with a diagnostic performance with AUC = 0.965, 0.936 and 0.910 respectively in independent diagnosis and an AUC = 0.999 when combined. Sarcosine was recognized as an independent potential biomarker which could distinguish inactive VKH patients from healthy controls. This study reveals a significant difference of plasma metabolic phenotype and identifies diagnostic biomarkers for VKH disease. Changes in the metabolic profile may provide clues towards the pathophysiology of VKH disease.

Systematic re-evaluation of the long-used standard protocol of urease-dependent metabolome sample preparation

In the urinary metabolomics for finding biomarkers in urine, owing to high concentrations of urea, for chromatography-based metabolomic analysis, urea needed to be degraded by urease. This urease pretreatment has been the key step of sample preparation for standard urinary metabolomics until today even for mass spectrometry-based analysis. The urease pretreatment involving incubation of urine with urease contradicts the concept of metabolome sampling, which should immediately arrest metabolic reactions to prevent alterations of a metabolite profile. Nonetheless, the impact of urease pretreatment has not been clearly elucidated yet. We found that activities of urease and endogenous urinary enzymes and metabolite contaminants from the urease preparations introduce artefacts into metabolite profiles, thus leading to misinterpretation.

Uric acid increases IL-1β secretion and Caspase-1 activation in PBMCs of Behçet's disease patients: The in vitro immunomodulatory effect of xanthine oxidase inhibitor Allopurinol

Behçet's disease (BD) is a multisystem disease, which shares some features with other diseases belonging to the autoinflammatory disorders panel. Recent studies have postulated that IL-1β/Caspase-1 may play a cardinal role in autoinflammatory diseases. In this study, we aimed to (i) elucidate the mechanism underlying the involvement of xanthine oxidase (XO) and Uric Acid (UA) in BD (ii) study the direct effects of UA and XO inhibitor "Allopurinol" on nitric oxide (NO) and caspase-1-mediated IL-1β release in peripheral blood mononuclear cells (PBMCs) of BD patients. In this context, plasma of BD patients and healthy controls (HC) were used to measure XO activity, UA, advanced oxidized proteins products (AOPP) and NO levels. In Addition, PBMCs of BD patients and HC were treated or not with either UA or Allopurinol. Then we quantified NO and IL-1β levels, and Caspase-1 Activity in the supernatants and lysates of PBMCs, respectively. We showed that plasma levels of XO activity, UA, AOPP and NO are significantly increased in BD patients compared to those of HC. Interestingly, a significant positive correlation between XO and UA was observed in BD patients. Additionally, while UA has markedly increased NO, IL-1β, and Caspase-1 activity levels in PBMCs of BD patients, Allopurinol has exerted an immunomodulatory effect resulting in reduced NO, IL-1β and Caspase-1 levels in PBMCs of BD patients particularly during the active stages. Collectively, our results indicate a potential clinical use of XO as a tool for assessing BD activity, and suggest that the in-vitro immunomodulatory effect of Allopurinol may have a promising therapeutic value in BD management.

Biomarkers in Vasculitides of the Nervous System

Besides being affected by the rare and severe primary angiitis of the central nervous system (PACNS) the nervous system is also affected by primary systemic vasculitides (PSV). In contrast to PACNS, PSV affect not only the central but also the peripheral nervous system, resulting in a large array of potential symptoms. Given the high burden of disease, difficulties in distinguishing between differential diagnoses, and incomplete pathophysiological insights, there is an urgent need for additional precise diagnostic tools to enable an earlier diagnosis and initiation of effective treatments. Methods available to date, such as inflammatory markers, antibodies, cerebrospinal fluid (CSF) analysis, imaging, and biopsy, turn out to be insufficient to meet all current challenges. We highlight the use of biomarkers as an approach to extend current knowledge and, ultimately, improve patient management. Biomarkers are considered to be useful for disease diagnosis and monitoring, for predicting response to treatment, and for prognosis in clinical practice, as well as for establishing outcome parameters in clinical trials. In this article, we review the recent literature on biomarkers which have been applied in the context of different types of nervous system vasculitides including PACNS, giant-cell arteritis, Takayasu's arteritis, polyarteritis nodosa, ANCA (anti-neutrophil cytoplasm antibody)-associated vasculitides, cryoglobulinemic vasculitis, IgA vasculitis, and Behçet's disease. Overall, the majority of biomarkers is not specific for vasculitides of the nervous system.

Application of GC/MS-Based Metabonomic Profiling in Studying the Therapeutic Effects of Aconitum carmichaeli with Ampelopsis japonica Extract on Collagen-Induced Arthritis in Rats

Aconitum carmichaeli with Ampelopsis japonica (AA) is a classical traditional Chinese medicine (TCM) formula. There are a lot of examples showing that AA can be used to treat rheumatoid arthritis, but its mechanism of action is still not completely clear. In this research, collagen-induced arthritis (CIA) was chosen as a rheumatoid arthritis (RA) model. Rats of treated groups were continuously administered Aconitum carmichaeli (AC), Ampelopsis japonica (AJ) and Aconitum carmichaeli + Ampelopsis japonica (AA) orally once a day from the day after the onset of arthritis (day 7) until day 42. The results showed that AA not only significantly reduced paw swelling, but also improved the levels of TNF-α and IL-6 in serum. GC-MS-based urine metabonomics was established to analysis metabolic profiles and 21 biomarkers of RA rats were identified by the Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machine (SVM) methods. The prediction rate of the SVM method for the 21 biomarkers was 100%. Twenty of 21 biomarkers, including D-galactose, inositol and glycerol, gradually returned to normal levels after administration of AA. Metabolomic Pathway Analysis (MetPA) generated three related metabolic pathways-galactose metabolism, glycerolipid metabolism and inositol phosphate metabolism-which explain the mechanism of AA treatment of rheumatoid arthritis. This research provides a better understanding of the therapeutic effects and possible therapeutic mechanism of action of a complex TCM (AA) on rheumatoid arthritis.