慢性心功能衰竭患者尿液的代谢组学研究

采用基于液相色谱-质谱联用的方法对慢性心力衰竭(Chronic heart failure, CHF)患者和正常对照(Control)人群的尿液进行分析, 筛选慢性心力衰竭患者尿液中的差异代谢物, 研究其发病机制, 并为临床治疗提供科学依据.选择15个慢性心力衰竭患者(年龄(62.27±3.14)岁)及15个正常人(年龄(65.41±4.63)岁), 采用高分辨度快速液相色谱-四极杆-飞行时间串联质谱(RRLC-QTOF/MS)技术对尿液代谢物进行分析, 采用主成分分析(PCA)对两组代谢物进行分类, 并筛选潜在生物标记物;运用偏最小二乘判别分析法(PLS-DA)建模, 考察生物标记物对疾病筛选的预测能力.研究结果表明, CHF组和Control组尿液代谢物谱能得到很好的区分, 发现并鉴定了2种潜在生物标记物尿苷及丙氨酰色氨酸, 提示嘧啶代谢和色氨酸代谢可能在心力衰竭发生发展中有重要作用.     

小儿哮喘患者呼出气冷凝液代谢组学研究

利用气相色谱-质谱联用法(GC-MS/MS)对小儿哮喘患者(Childhood asthma)和健康儿童(Healthy control)的呼出气冷凝液(Exhaled breath condensate,EBC)进行分析,寻找小儿哮喘患者EBC中的潜在标记物,为其发病机制及早期筛查提供科学依据。收集了21例小儿哮喘患者(年龄(8.2±1.6)岁)及17例健康儿童(年龄(8.1±1.3)岁)的EBC样本,采用GC-MS/MS获得化学成分的全扫描数据,通过主成分分析法对两组代谢物进行聚类分析,使用Metaboanalyst 3.0归属涉及的代谢通路。结果表明,小儿哮喘组和正常组EBC代谢图谱能很好地区分,鉴定了8个差异表达物可作为潜在的内源性生物标记物,提示淀粉和蔗糖代谢、赖氨酸降解、氨基糖核苷酸糖代谢、苯丙氨酸代谢可能在小儿哮喘发生发展过程中发挥重要作用。     

超高效液相色谱-四极杆-静电场轨道阱质谱联用法用于宫颈癌患者尿液代谢组学研究

利用超高效液相色谱-四极杆-静电场轨道阱质谱联用(UHPLC-Q-Orbitrap MS)方法对宫颈癌(Cervical cancer,CC)患者和健康人(Healthy control,HC)的尿液进行分析,研究宫颈癌患者尿液中的潜在标志物,为其发病机制和诊断提供科学依据。筛选11例宫颈癌患者(Age(45.7±5.6)years)及11例健康人(Age(45.9±3.2)years)尿液样本,采用液相色谱-质谱联用技术对尿液进行测定,通过主成分分析(PCA)和偏最小二乘法-判别分析(OPLS-DA)处理数据,结果表明,两组人群代谢轮廓有显著差别,发现并鉴定了12种潜在的生物标志物,提示特定的肿瘤代谢途径中潜在的代谢标志物可能在宫颈癌发生发展中发挥重要作用。     

格列美脲治疗的2型糖尿病大鼠的尿液代谢组学研究

采用快速高分离度液相色谱-质谱技术(RRLC-MS)检测经格列美脲治疗的2型糖尿病大鼠尿液中代谢物的变化, 对糖尿病组、 给药组和健康对照组大鼠的尿液代谢物谱进行了分析. 采用主成分分析(PCA)对3组大鼠进行分类并寻找潜在生物标记物. 结果表明, 3组大鼠的尿液代谢物谱得到了很好的区分, 发现并鉴定了2个潜在生物标记物, 分别为4-脱氧三羟基丁酸和4-胍基丁酸. 格列美脲对2型糖尿病大鼠的药物作用可能体现为对氨基酸代谢的调节作用.     

尿液代谢组学方法研究人参总皂苷治疗糖尿病心肌病大鼠作用机制

利用基于质谱的代谢组学方法考察了人参总皂苷(TG)治疗糖尿病心肌病(DCM)大鼠的效应机制;建立了糖尿病心肌病大鼠模型,并连续12周口服人参总皂苷,采用快速高分辨液相色谱/四级杆-飞行时间/质谱(RRLC/Q-TOF/MS)技术对糖尿病心肌病模型组(DCM组)和人参总皂苷治疗组(TG组)大鼠尿样的尿液代谢物进行分析,采用主成分分析(PCA)对两组代谢物进行分类,并寻找潜在生物标记物,同时检测心肌病理超微结构、血液生化指标和心肌氧化应激水平。RRLC/Q-TOF/MS检测结果表明,DCM组和TG组大鼠的尿液代谢物谱能得到很好的区分,发现并鉴定了3种生物标记物。TG降低了DCM大鼠心肌超微结构损伤并改善其血脂、血糖及心肌氧化应激水平,代谢组学研究结果表明:作用机制可能是TG对柠檬酸循环、脂肪酸代谢和氧化应激水平的调节作用。     

基于液相色谱-质谱联用技术的肺癌细胞代谢组学分析

通过高效液相色谱-四极杆飞行时间质谱(HPLC-Q-TOF/MS)分别对肺癌细胞与正常细胞的极性与非极性代谢物进行指纹图谱分析,进一步应用偏最小二乘判别分析(PLS-DA)对代谢组学数据进行多维统计分析。研究结果显示,与正常细胞相比,肿瘤细胞存在异常的蛋白质、脂肪酸、磷脂代谢,并发现31种对分类有显著贡献的代谢小分子物质。通过本研究,建立了基于液相色谱-质谱联用技术的肺癌细胞代谢组学分析方法,发现了肺癌潜在疾病标记物,可为肺癌分子标记物的发现及其早期诊断提供新思路和新方法。     

代谢组学法研究三聚氰胺对儿童尿液代谢的影响

运用代谢组学方法研究了三聚氰胺对儿童尿液代谢的影响.通过超高效液相色谱-飞行时间质谱(UPLC/TOF-MS)法分析儿童尿样的代谢指纹图谱,质谱数据采用MarkerLynx软件处理,然后使用主成分分析和偏最小二乘判别分析法分析病例组和正常对照组之间的代谢物谱差异,并通过变量重要性投影(VIP)选取潜在的生物标志物,结合质谱同位素分析和数据库检索对潜在的生物标志物进行鉴定.结果表明,三聚氰胺通过肾结石导致的物理性损伤干扰了柠檬酸代谢.代谢组学法能够应用于三聚氰胺导致的代谢异常的研究及三聚氰胺导致肾损伤的无创检测.     

基于快速高分辨液相色谱串联质谱技术的代谢组学尿液分析方法的建立

采用快速高分辨液相色谱(RRLC)分离系统与QTRAP型及QTOF型MS/MS仪联用技术,通过考察尿液样本前处理方法,优化液相色谱条件和质谱检测参数,建立了用于尿液中代谢物分析的RRLC-MS方法.采用本方法对尿液浓度下的20种代表性代谢物进行了检测,考察了方法的灵敏度和精密度,证明本方法适用于尿液代谢组学的研究.对穿...     

基于液相色谱/电喷雾飞行时间质谱技术的结石症尿液代谢组学探讨

探索了一种简便的尿液样品前处理流程,通过反相液相色谱(RPLC)与亲水相互作用色谱(HILIC)相结合的高效液相色谱/电喷雾飞行时间质谱的联用技术(HPLC/ESI-TOFMS),建立了泌尿系结石症的尿液代谢组学模型,研究结石症患者尿液样品中的代谢物浓度水平与健康人对照组间的差异情况。采用主成分分析(PCA)及偏最小二乘法-判别分析(PLS-DA)等多变量数据分析方法,寻找结石症患者组和对照组之间的差异性代谢谱。模型结果显示:结石症患者尿液代谢物水平与健康对照组具有明显差异,寻找其中潜在的差异性标志物群组,有望将该模型用于泌尿系结石症的快速预测和诊断。     

阿卡波糖对Ⅱ型糖尿病大鼠尿液代谢轮廓的影响

采用超高效液相色谱-质谱联用(UPLC-MS/MS)方法研究了阿卡波糖对Ⅱ型糖尿病大鼠代谢轮廓的影响, 分析了健康组、 糖尿病模型组和糖尿病给予阿卡波糖组的大鼠尿样, 采用主成分分析法(PCA)和偏最小二乘法-判别分析(PLS-DA)对数据进行分析. PCA得分图表明, 健康组、 糖尿病组和阿卡波糖组的代谢轮廓有显著差别, 根据PLS-DA载荷图筛选, 将对各组分离贡献大的化合物的串联质谱分析数据经Human Metabolome Database(HMDB)和Mass Bank.jp等数据库检索, 进行质谱信息匹配, 鉴定出苯乙酰甘氨酸、 肌酐及葡萄糖酸等8种内源性代谢物为潜在生物标记物.     

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.     

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.     

Metabonomics investigation of human urine after ingestion of green tea with gas chromatography/mass spectrometry, liquid chromatography/mass spectrometry and (1)H NMR spectroscopy

A method using gas chromatography/mass spectrometry (GC/MS), liquid chromatography/mass spectrometry (LC/MS) and (1)H NMR with pattern recognition tools such as principle components analysis (PCA) was used to study the human urinary metabolic profiles after the intake of green tea. From the normalized peak areas obtained from GC/MS and LC/MS and peak heights from (1)H NMR, statistical analyses were used in the identification of potential biomarkers. Metabolic profiling by GC/MS provided a different set of quantitative signatures of metabolites that can be used to characterize the molecular changes in human urine samples. A comparison of normalized metabonomics data for selected metabolites in human urine samples in the presence of potential overlapping peaks after tea ingestion from LC/MS and (1)H NMR showed the reliability of the current approach and method of normalization. The close agreements of LC/MS with (1)H NMR data showed that the effects of ion suppression in LC/MS for early eluting metabolites were not significant. Concurrently, the specificity of detecting the stated metabolites by (1)H NMR and LC/MS was demonstrated. Our data showed that a number of metabolites involved in glucose metabolism, citric acid cycle and amino acid metabolism were affected immediately after the intake of green tea. The proposed approach provided a more comprehensive picture of the metabolic changes after intake of green tea in human urine. The multiple analytical approach together with pattern recognition tools is a useful platform to study metabolic profiles after ingestion of botanicals and medicinal plants.     

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.     

膀胱癌血清及尿液代谢组学研究

应用代谢组学研究方法,对与膀胱癌(Bladder cancer,BC)发病相关的生物标志物进行筛选,采用液相色谱-电喷雾质谱(LC-ESI/MS)联用技术对20名膀胱癌患者与24名正常人的血清和尿液进行研究.多变量统计分析结果表明,膀胱癌患者和正常人聚类明显,血清和尿液中分别发现13个潜在标志物.其中,(2E,6E,8E)-二十二碳三烯-1-醇、7-((1S,2S)-2-(庚胺)环己基)庚酸和(11E,14E,17E)-三烯-二十碳-1-醇首次在血清中发现,有潜力成为膀胱癌诊断标志物.液相色谱-质谱联用结合多变量分析的代谢组学研究技术在膀胱癌诊断中展现出巨大潜力.     

Metabonomic Analysis of Urine from Chronic Unpredictable Mild Stress Rats Using Gas Chromatography–Mass Spectrometry

Depression is a prevalent complex psychiatric disorder and its pathophysiological mechanism is not yet well understood. In this study, we investigated the metabolic profiling of urine samples from chronic unpredictable mild stress (CUMS) rats to find potential disease biomarkers and research pathology of depression. Metabolome in urine was analyzed using gas chromatography/mass spectrometry (GC/MS) in conjunction with multivariate statistical techniques. The urine samples of male Sprague–Dawley rats were collected at different time points and then were derivatized by methoximation/silylation. Clear separation between the model and control group was achieved, and 15 metabolites were identified, which suggested that the depressed state may be related to neurotransmitter, energy metabolism and immunity. The time-dependent trajectory of metabolites pattern revealed that the maximum biochemical change happened on the 21st day, which was consistent with the results of behavior tests. The study suggested that the metabonomic approach could be used as a potentially powerful tool to investigate the biochemical change in certain physiopathological conditions, such as depression, as an early diagnostic means.

     

Searching for Potential Markers of Glomerulopathy in Urine by HS-SPME-GC×GC TOFMS

Volatile organic compounds (VOCs) exiting in urine are potential biomarkers of chronic kidney diseases. Headspace solid phase microextraction (HS-SPME) was applied for extraction VOCs over the urine samples. Volatile metabolites were separated and identified by means of two-dimensional gas chromatography and time of flight mass spectrometry (GC × GC TOF MS). Patients with glomerular diseases (n = 27) and healthy controls (n = 20) were recruited in the study. Different VOCs profiles were obtained from patients and control. Developed methodology offers the opportunity to examine the metabolic profile associated with glomerulopathy. Four compounds found in elevated amounts in the patients group, i.e., methyl hexadecanoate; 9-hexadecen-1-ol; 6,10-dimethyl-5,9-undecadien-2-one and 2-pentanone were proposed as markers of glomerular diseases.     

Lysophosphatidylcholine Biomarkers of Lung Cancer Detected by Ultra-performance Liquid Chromatography Coupled with Quadrupole Time-of-flight Mass Spectrometry

Centrifugal ultrafiltration after methanol extraction of whole plasma was used as an optimal condition for the preparation of blood plasma before metabonomic studies. The plasma samples from 102 lung cancer patients and 34 healthy volunteers were prepared with this approach. With ultra-performance liquid chromatography(UPLC) coupled with quadrupole time-of-flight mass spectrometry(Q-TOF MS) analysis, the samples were investigated in order to find potential disease biomarkers. After data acquisition, orthogonal signal correction partial least squares models were built to differentiate the healthy volunteers from lung cancer patients and to identify metabolites that showed significantly different expression between the two groups. Several metabolite ions were identified as potential biomarkers according to the variable importance in the project(VIP) value in both ion modes. Five lysophosphatidylcholines were further identified as specifically lysoPC 16:0, isomer of lysoPC 16:0, lysoPC 18:0, lysoPC 18:1 and lysoPC 18:2. These results suggest that UPLC coupled with Q-TOF MS is an effective technique for the analysis of plasma metabolites in metabonomic studies.     

Exploring metabolic syndrome serum profiling based on gas chromatography mass spectrometry and random forest models

Metabolic syndrome (MetS) is a constellation of the most dangerous heart attack risk factors: diabetes and raised fasting plasma glucose, abdominal obesity, high cholesterol and high blood pressure. Analysis and representation of the variances of metabolic profiles is urgently needed for early diagnosis and treatment of MetS. In current study, we proposed a metabolomics approach for analyzing MetS based on GC–MS profiling and random forest models. The serum samples from healthy controls and MetS patients were characterized by GC–MS. Then, random forest (RF) models were used to visually discriminate the serum changes in MetS based on these GC–MS profiles. Simultaneously, some informative metabolites or potential biomarkers were successfully discovered by means of variable importance ranking in random forest models. The metabolites such as 2-hydroxybutyric acid, inositol and d-glucose, were defined as potential biomarkers to diagnose the MetS. These results obtained by proposed method showed that the combining GC–MS profiling with random forest models was a useful approach to analyze metabolites variances and further screen the potential biomarkers for MetS diagnosis.