Metabonomics Study of Heart Homogenates from Myocardial Infarction Rats Using Liquid Chromatography/Time of Flight Mass Spectrometry

In this study, a metabonomics analysis of heart homogenates from myocardial ischemic rats was performed by LC–TOF–MS. Hydrophilic interaction chromatography (HILIC) was used to separate the endogenous metabolites in heart homogenates. Partial least squares to latent structure-discriminant analysis (PLS-DA) was used for data analysis. Good separations were observed between the normal and model groups and 15 potential biomarkers were identified. The major disturbed metabolic pathways were purine metabolism, pyrimidine metabolism, urea cycle, and energy metabolism. The results demonstrated that a metabonomics approach based on HILIC-MS was useful for studying metabolic mechanism on target tissue of the myocardial infarction rat.

     

代谢组学应用于糖肾方治疗糖尿病肾病的疗效评价

建立了基于超高效液相色谱-飞行时间质谱(UPLC/TOF MS)分析技术的血浆代谢指纹谱,应用多元统计分析方法评价糖尿病肾病患者血浆代谢物变化差异及糖肾方的干预效果。通过研究糖肾方干预糖尿病肾病血浆内源性代谢物的变化,探索与该疾病密切相关的代谢途径,评价糖肾方的治疗效果。结果发现: 经糖肾方治疗后,血浆内源性代谢物发生了明显变化,磷脂代谢、脂肪酸代谢、氨基酸代谢、嘌呤嘧啶代谢、固醇类代谢等多个代谢途径得到纠正。本研究基于UPLC/TOF MS的代谢组学方法,能够从整体水平反映疾病治疗过程中代谢网络的变化趋势,证实糖肾方具有治疗糖尿病肾病的临床疗效并有助于阐释药物作用机理。     

The metabolomic study on atherosclerosis mice and its application in a traditional Chinese medicine Sishen granule

Although an atherosclerosis (AS) model using low‐density lipoprotein receptor deletion mice has been widely applied, its pathological pathway in metabolite level is still not clear. To further reveal the metabolite profile and identify the potential biomarkers in AS development, a serum metabolomic approach was developed based on reversed‐phase liquid chromatography/quadrupole time‐of‐flight mass spectrometry (LC‐Q‐TOF‐MS). The established metabolomic platform was also used for elucidating the therapeutic mechanism of a traditional Chinese medicine named Sishen granule (SSKL). Twenty‐one potential biomarkers in AS mouse serum were identified. Through functional analysis of these biomarkers, inflammation, proliferation, dysfunction of energy metabolism and amino acid metabolism were considered the most relevant pathological changes in AS. DNA damage products were found for the first time in the metabolomic study of AS. The network established by 20 biomarkers revealed that pyruvate metabolism, citrate cycle, fatty acid metabolism and urea metabolism were seriously disturbed. This metabolomic study not only supplied a systematic view of the progression of AS but also provided a theoretical basis for the treatment of AS. This metabolomic study also demonstrated that SSKL had therapeutic effectiveness for AS through partly reversing the inflammation reaction and amino acid metabolism dysfunction. Copyright © 2015 John Wiley & Sons, Ltd.     

Metabonomics study of liver cancer based on ultra performance liquid chromatography coupled to mass spectrometry with HILIC and RPLC separations

In this study, urinary metabolites from liver cancer patients and healthy volunteers were studied by a metabonomic method based on ultra performance liquid chromatography coupled to mass spectrometry. Both hydrophilic interaction chromatography (HILIC) and reversed-phase liquid chromatography (RPLC) were used to separate the urinary metabolites. Principle component analysis (PCA) and partial least squares to latent structure-discriminant analysis (PLS-DA) models were built to separate the healthy volunteers from the liver cancer patients and to find compounds that are expressed in significantly different amounts between the two populations. 21 metabolite ions were considered as potential biomarkers according to the Variable importance in the Project (VIP) value and S-plot. Compared with RPLC, a more sensitive and stable response can be recorded in HILIC mode due to the high content of organic solvent used. Moreover, the liver cancer group and the healthy volunteers can be better separated based on the data from the HILIC separation, which indicates that HILIC is suitable for urinary metabonomic analysis. In HILIC mode, several polar compounds related to arginine and proline metabolism, alanine and aspartate metabolism, lysine degradation, nicotinate and nicotinamide metabolism were found to be significantly changed in the concentrations of the two different populations: healthy and cancer. In contrast, in RPLC mode, these changed compounds are related to fatty acids oxidation.     

Metabonomics Study of TCM Formula: Qutan Huayu Tongmai Granule as an Effective Treatment for Atherosclerosis in Mini-Pigs

To investigate the effects of QuTan HuaYu TongMai granule (QHTG) on the perturbed metabolism of atherosclerosis mini-pig model, a serum metabonomics method based on Liquid chromatography/mass spectrometry was developed. Principal component analysis and partial least squares-discriminate analysis models were established for the metabonomics analysis. The effect of high dose QHTG group is equivalent with those of positive drugs group in PCA score plots. Some significantly changed metabolites, including lyso-PCs, metabolites of vitamin D₃ and fatty acids were found to be reasonable in explaining the anti-atherosclerosis mechanism of QHTG. Metabonomic approach is helpful to further understand the pathophysiology of atherosclerosis in mini-pigs and the therapeutic mechanism of QHTG. Our work also indicated that the LC–MS based metabonomics method is a potential tool for performing intervention and mechanism research of traditional Chinese medicine (TCM).

     

Urinary Metabonomics Study of Heart Failure Patients with HILIC and RPLC Separation Coupled to TOF–MS

In this study, urinary metabolic profiles of patients with heart failure (HF) and healthy individuals were analyzed by LC-TOF–MS. Both reversed-phase chromatography and hydrophilic interaction chromatography were used to separate the endogenous metabolites in urine. Partial least-squares to latent structure-discriminant analysis was used for discriminating HF patients from healthy persons and the selection of potential biomarkers. The results suggested that the combination of LC–MS and multivariate statistical analysis could be used for HF diagnosis. The MS/MS experiments were carried out to identify the potential biomarkers which are important for the contribution to the discrimination. As a result, 12 potential biomarkers for HF were identified and the related metabolic pathways were studied.     

Fecal metabolome profiling of liver cirrhosis and hepatocellular carcinoma patients by ultra performance liquid chromatography-mass spectrometry

Fecal metabolome of healthy humans and patients suffering from liver cirrhosis and hepatocellular carcinoma (HCC) were studied using ultra performance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF MS). Metabolic features detected by the method were then statistically treated using partial least squares to latent structure-discriminant analysis (PLS-DA) models to discriminate between healthy and diseased states. PLS-DA was also used to discriminate between cirrhosis and HCC stressed fecal metabolomes and to identify potential biomarkers for cirrhosis and HCC that are expressed at significantly different amounts in fecal metabolomes. Score plots of pattern recognition analysis distinguished liver cirrhosis and HCC patients from healthy humans. Based on the variable of importance in the project (VIP) values and S-plots, six metabolites were considered as potential biomarkers with a strong increase in lysophosphatidylcholines and a dramatic decrease in bile acids and bile pigments in patients with liver cirrhosis and HCC in comparison with healthy humans. Results demonstrate the potential of UPLC-MS as an efficient and convenient method that can be applied to screen fecal samples and aid in the early diagnosis of cirrhosis and hepatocellular carcinoma.     

High-throughput lipidomics analysis to discover lipid biomarkers and profiles as potential targets for evaluating efficacy of Kai-Xin-San against APP/PS1 transgenic mice based on UPLC–Q/TOF–MS

Lipid metabolism has a significant function in the central nervous system and Alzheimer's disease (AD) is an age-related senile disease characterized by central nerve degeneration. The pathological development of AD is closely related to lipid metabolism disorders. To reveal the influence of Kai-Xin-San (KXS) on lipid metabolism in APP/PSI transgenic mice and potential therapeutic targets for treating AD, brain tissue samples were collected and analyzed by high-throughput lipidomics based on UPLC–Q/TOF-MS. The collected raw data were processed by multivariate data analysis to discover the potential biomarkers and lipid metabolic profiles. Compared with the control wild-type mouse group, nine potential lipid biomarkers were found in the AD model group, of which seven were up-regulated and two were down-regulated. Orally administrated KXS can reverse the changes in these potential biomarkers. Compared with the model group, a total of six differential metabolites showed a recovery trend and may be potential targets for KXS to treat AD. This study showed that high-throughput lipidomics can be used to discover the perturbed pathways and lipid biomarkers as potential targets to reveal the therapeutic effects of KXS.     

Plasma metabonomics study on toxicity biomarker in rats treated with Euphorbia fischeriana based on LC–MS

Lang‐du (LD) has been traditionally used to treat human diseases in China. Plasma metabolic profiling was applied in this study based on LC–MS to elucidate the toxicity in rats induced by injected ethanol extract of LD. LD injection was given by intraperitoneal injection at doses of 0.1, 0.05, 0.025 and 0 g kg^?1 body weight per day to rats. The blood biochemical levels of alanine aminotransferase, direct bilirubin, creatinine, serum β2‐microglobulin and low‐density lipoprotein increased in LD‐injected rats, and the levels of total protein and albumin decreased in these groups. The metabolic profiles of the samples were analyzed by multivariate statistics analysis, including principal component analysis, partial least squares discriminant analysis and orthogonal projection to latent structures discriminate analysis (OPLS‐DA). The metabolic characters in rats injected with LD were perturbed in a dose‐dependent manner. By OPLS‐DA, 18 metabolites were served as the potential toxicity biomarkers. Moreover, LD treatment resulted in an increase in the p‐cresol, p‐cresol sulfate, lysophosphatidylethanolamine (LPE) (18:0), LPE (16:0), lysophosphatidylcholine (16:0) and 12‐HETE concentrations, and a decrease in hippuric acid, cholic acid and N‐acetyl‐l ‐phenylalanine. These results suggested that chronic exposure to LD could cause a disturbance in lipids metabolism and amino acids metabolism, etc. Therefore, an analysis of the metabolic profiles can contribute to a better understanding of the adverse effects of LD. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

Identifying potential serum biomarkers of breast cancer through targeted free fatty acid profiles screening based on a GC–MS platform

Recent advances suggest that abnormal fatty acid metabolism highly correlates with breast cancer, which provide clues to discover potential biomarkers of breast cancer. This study aims to identify serum free fatty acid (FFA) metabolic profiles and screen potential biomarkers for breast cancer diagnosis. Gas chromatography–mass spectrometry and our in-house fatty acid methyl ester standard substances library were combined to accurately identify FFA profiles in serum samples of breast cancer patients and breast adenosis patients (as controls). Potential biomarkers were screened by applying statistical analysis. A total of 18 FFAs were accurately identified in serum sample. Two groups of patients were correctly discriminated by the orthogonal partial least squares–discriminant analysis model based on FFA profiles. Seven FFA levels were significantly higher in serum from breast cancer patients than that in controls, and exhibited positive correlation with malignant degrees of disease. Furthermore, five candidates (palmitic acid, oleic acid, cis-8,11,14-eicosatrienoic acid, docosanoic acid and the ratio of oleic acid to stearic acid) were selected as potential serum biomarkers for differential diagnosis of breast cancer. Our study will help to reveal the metabolic signature of FFAs in breast cancer patients, and provides valuable information for facilitating clinical noninvasive diagnosis.     

Serum fatty acid profiles and potential biomarkers of ankylosing spondylitis determined by gas chromatography–mass spectrometry and multivariate statistical analysis

Ankylosing spondylitis (AS) is a common chronic inflammatory rheumatic disease. Early and accurate detection is essential for effective disease treatment. Recently, research has focused on genomics and proteomics. However, the associated metabolic variations, especially fatty acid profiles, have been poorly discussed. In this study, the gas chromatography–mass spectrometry (GC‐MS) approach and multivariate statistical analysis were used to investigate the metabolic profiles of serum free fatty acids (FFAs) and esterified fatty acids (EFAs) in AS patients. The results showed that significant differences in most of the FFA (C12:0, C16:0, C16:1, C18:3, C20:4, C20:5, C22:5 and C22:6) and EFA (C12:0, C16:1, C18:0, C18:1, C18:2, C18:3, C20:4 and C22:6) concentrations were found between the AS patients and healthy controls (p < 0.05). Principal component analysis and partial least squares discriminant analysis were performed to classify the AS patients and controls. Additionally, FFAs C20:4, C12:0, C18:3 and EFAs C22:6, C12:0 were confirmed as potential biomarkers to identify AS patients and healthy controls. The present study highlights that differences in the serum FFA and EFA profiles of AS patients reflect the metabolic disorder. Moreover, FFA and EFA biomarkers appear to have clinical applications for the screening and diagnosis of AS. Copyright © 2014 John Wiley & Sons, Ltd.     

Characterization of chemical constituents and absorbed components,screening the active components of gelanxinning capsule and an evaluation of therapeutic effects by ultra‐high performance liquid chromatography with quadrupole time of flight mass spectrometry

We revealed the potential biomarker and pathway of gelanxinning capsule on rat model with coronary heart disease, which aims to clarify holistic therapeutic effect and predict quality‐markers of gelanxinning capsule. Ultra‐high performance liquid chromatography coupled with mass spectrometry based on metabolomics technique was used to find the biomarkers and related metabolic pathways of coronary heart disease model, which evaluates the intervention effect of gelanxinning capsule. Using serum pharmacochemistry of traditional Chinese medicine and Pearson correlation analysis, effective ingredients in serum is analyzed to characterize the activity of gelanxinning capsule on coronary heart disease under valid state. A total of 20 biomarkers from coronary heart disease were identified and 12 of them were regulated by gelanxinning capsule treatment, which is mainly involved in sphingolipid metabolism and glycerophospholipid metabolism. With the high sensitivity liquid chromatography coupled with mass spectrometry technology, a total of 46 compounds from gelanxinning capsule were identified in vitro and 25 of them were absorbed in blood. The correlation analysis of serum biomarkers and absorbed components was used to find 11 compounds as quality‐markers to be responsible for the efficacy of gelanxinning capsule. This strategy was successfully applied to screening of potential mechanism and quality‐markers from herbal medicine.      

Metabolomic profiling of rat serum associated with isoproterenol-induced myocardial infarction using ultra-performance liquid chromatography/time-of-flight mass spectrometry and multivariate analysis

An ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC/TOF-MS)-based metabolomic approach was developed to characterize the metabolic profile associated with isoproterenol (ISO)-induced myocardial infarction (MI). Analysis of the serum samples revealed distinct changes in the biochemical patterns of ISO-induced rats. A multivariate statistical method, supervised partial least squares-discriminant analysis (PLS-DA), was then used for screening of potential biomarkers. As a result, 13 lipid biomarkers, including lysophosphatidylcholines (Lyso-PCs) and fatty acids were identified by the accurate mass measurement of TOF-MS. The relationship between abnormal lipid metabolism and the formation of MI were also studied. This work demonstrates the utility of UPLC/TOF-MS-based metabolic profiling combined with multivariate analysis as a powerful tool to further investigate the pathogenesis of cardiovascular diseases.     

A wide‐targeted urinary and serum metabolomics strategy reveals the effective substance of the Wu‐tou decoction

As an important Chinese medicine decoction, Wu‐tou decoction has been used to treat rheumatic arthritis for more than a thousand years. We previously reported that the Wu‐tou decoction could change the urinary and serum metabolites in adjuvant‐induced arthritis rats significantly. The purpose of this research was to confirm the potential biomarkers obtained by previous non‐targeted metabolomics study through quantitative analysis by liqui chromatography with tandem mass spectrometry, in the meantime, to further study the effective material basis of Wu‐tou decoction. Firstly, the important compounds in the tryptophan metabolism pathway, the arginine and proline metabolism pathway, the amino acid metabolism pathway, the tricarboxylic acid cycle, the vitamin B₆ metabolism pathway, and the phenylalanine metabolism pathway, which were identified as potential biomarkers in previous study, were selected for quantitative analysis. Then the linearity, limit of detection, limit of quantification, selectivity, accuracy, precision, stability, recovery, and matrix effect of the quantitative method were examined. Finally, ten and eighteen metabolites were quantitatively analyzed in the serum and urine, respectively. The results showed that seven out of ten serum potential biomarkers and ten out of eighteen urine potential biomarkers were confirmed as real biomarkers. This research provides a powerful reference for the study on effective material basis of Wu‐tou decoction.     

Urine metabolic profiling of dementia rats with vital energy deficiency using ultra-high-performance liquid chromatography coupled with an orbitrap mass spectrometer

Dementia is a chronic and multifactor-induced neurodegenerative disorder that occurs frequently in the elderly with weak constitution and insufficient vital energy. However, the relationship between vital energy deficiency and the occurrence and development of dementia is still unclear. In this study, a rat model of dementia with vital energy deficiency was established through intraperitoneal injection with d -galactose and AlCl₃ and combined with exhaustive swimming. Changes in the dementia with vital energy deficiency rat model were assessed by examining behaviors, hippocampal histopathological and biochemical parameters, and serum biochemical parameters. Urine metabolomics based on ultra-high-performance liquid chromatography coupled with an orbitrap mass spectrometer was also used to discover endogenous metabolic profile and disease-related biomarkers and investigate the potential mechanism of dementia with vital energy deficiency. Among the 31 potential biomarkers that were identified, nine involved metabolic pathways. The four main types were phenylalanine, tyrosine and tryptophan metabolism, taurine and hypotaurine metabolism, and citrate cycle and pyrimidine metabolism. The pathogenesis of dementia with vital energy deficiency is mainly neurotoxin accumulation and body aging that leads to oxidative stress injury and loss of neuronal protective substances. Vital energy deficiency inhibits the body's energy metabolism and eventually leads to aggravate the dementia.     

Therapeutic Effects of Selaginella tamariscina on the Model of Acute Gout with Hyperuricemia in Rats Based on Metabolomics Analysis

Gout is a disease of purine metabolic disorders which results from long‐term hyperuricemia and the sodium urate deposition in and around the joints. Selaginella tamariscina (ST ) is an important traditional Chinese herbal medicine and is used for the treatment of gout and hyperuricemia. In this study, the rat model of acute gout with hyperuricemia was established by intraperitoneal injection of xanthine and oxonic acid potassium salt and articular injection monosodium urate (MSU ). The effect of ST in the treatment of gout was investigated by measuring joint swelling, the expression of IL ‐1β in serum and histological changes of joint by haematoxylin eosin (H&E) staining. Subsequently, urine metabolomics analysis for biomarkers discovery in acute gout with hyperuricemia rats was performed by the ultra‐performance liquid chromatography‐electrospray ionization quadruple time‐of‐flight mass spectrometry (UPLC‐ESI‐QTOF /MS ) combined with chemometric approach. Principal component analysis (PCA ) and orthogonal partial least squares‐discriminant analysis (OPLS‐DA ) were used to detect potential biomarkers. A total of 18 potential biomarkers were identified mainly including tryptophan metabolism; tyrosine metabolism; lysine methylation; pyrimidine metabolism; purine metabolism; TCA cycle and fatty acid metabolisms. This study indicates that ST could efficiently ameliorate the disease of acute gout with hyperuricemia in rats. The related metabolic biomarkers could provide useful information and the metabolic mechanism could be used for further study about the model of acute gout with hyperuricemia in rats.     

Urinary metabolomics of complete Freund's adjuvant‐induced hyperalgesia in rats

The aim of this study was to demonstrate the differences of metabolomics changes in a hyperalgesia model and find potent biomarkers of hyperalgesia. Seven rats were placed in metabolic cages. An emulsion containing 500 μg of Complete Freund's adjuvant (CFA) was used to induce hyperalgesia. Urine samples were collected prior to the injection of CFA and on post‐injection days 1, 3 and 7. Ultraperformance liquid chromatography, coupled with quadrupole‐time‐of‐flight mass spectrometry (UHPLC‐Q‐TOF/MS), was used for a quantitative analysis of urinary metabolic changes in the CFA‐induced hyperalgesia model. Differences between the metabolic profiles of the rats in the four groups were analyzed using partial least squares discriminant analysis. Thirty‐four potential urine metabolite biomarkers were identified, which changed in a trend similar to the pain threshold. These potential biomarkers were involved in 11 metabolic pathways, as follows: alanine, aspartate, and glutamate metabolism; ascorbate and aldarate metabolism; glycerolipid metabolism; glycerophospholipid metabolism; histidine metabolism; phenylalanine metabolism; sphingolipid metabolism; tryptophan metabolism; tyrosine metabolism; valine, leucine and isoleucine biosynthesis; and vitamin B6 metabolism. These results may improve our understanding of hyperalgesia and provide a basis for the clinical diagnosis of hyperalgesia.     

Identification of key genes and expression profiles in osteoarthritis by co-expressed network analysis

BackgroundThe underlying molecular characteristics of osteoarthritis (OA), a common age-related joint disease, remains elusive. Here, we aimed to identify potential early diagnostic biomarkers and elucidate underlying mechanisms of OA using weighted gene co-expression network analysis (WGCNA).Material and methodsWe obtained the gene expression profile dataset GSE55235, GSE55457, and GSE55584, from the Gene Expression Omnibus. WGCNA was used to investigate the changes in co-expressed genes between normal and OA synovial membrane samples. Modules that were highly correlated to OA were subjected to functional enrichment analysis using the R clusterProfiler package. Differentially expressed genes (DEGs) between the two samples were screened using the “limma” package in R. A Venn diagram was constructed to intersect the genes in significant modules and DEGs. RT -PCR was used to further verify the hub gene expression levels between normal and OA samples.ResultsThe preserved significant module was found to be highly associated with OA development and progression (P < 1e-200, correlation = 0.92). Functional enrichment analysis suggested that the antiquewhite4 module was highly correlated to FoxO signaling pathway, and the metabolism of fatty acids and 2-oxocarboxylic acid. A total of 13 hub genes were identified based on significant module network topology and DEG analysis, and RT-PCR confirmed that these genes were significantly increased in OA samples compared with that in normal samples.ConclusionsWe identified 13 hub genes correlated to the development and progression of OA, which may provide new biomarkers and drug targets for OA.