亲水作用色谱/质谱联用方法用于膀胱癌患者血清代谢组学研究

膀胱癌是泌尿系统最常见的恶性肿瘤之一,具有高发病率、高复发率和高进展率的特点.本研究应用69个极性代谢物标样选择合适的分离系统,建立了两性离子亲水作用色谱/质谱联用的代谢组学分析方法.本方法线性范围较宽,检出限低于ng/mL数量级.将本方法用于血清代谢组学分析,85%以上代谢物峰面积的RSD<30%.对64例膀胱癌患者和32例正常人的血清进行代谢组学研究,发现溶血磷脂酰胆碱、游离脂肪酸、氨基酸、胆汁酸、有机酸、核苷等在患病组和正常组中存在显著差异.经筛选和验证,甘磷酸胆碱、胱氨酸、十二碳烯酸、二十碳烯酸和鹅去氧胆酸5种代谢物可以作为区分膀胱癌和正常人的潜在标志物.本研究结果表明,基于亲水作用色谱/质谱联用的代谢组学方法是发现癌症诊断潜在生物标志物的有效手段.     

运用液相色谱联合离子阱-飞行时间质谱法进行海洛因成瘾人员代谢组学研究

利用代谢组学的研究方法,对海洛因成瘾人员尿液及血清中可能的相关标志物进行筛选。运用液相色谱联合离子阱-飞行时间质谱(LC/MS-IT-TOF)联用技术对海洛因检测尿检条阴性的16名海洛因滥用成瘾者与16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,海洛因成瘾者和正常人聚类明显,血清和尿液中分别发现12种可能的潜在标志物。成瘾人员和正常人员在血清及尿液代谢水平上具有明显差异,差异代谢物的发现有助于为发现海洛因成瘾判定的潜在标志物提供依据。     

基于超高效液相色谱-四极杆-静电场轨道阱质谱的结直肠腺瘤患者血清代谢组学研究

采用超高效液相色谱－四极杆－静电场轨道阱质谱结合主成分分析、正交偏最小二乘判别分析对46例结直肠腺瘤患者（年龄57.8 ± 10.7岁）和45例健康人（年龄54.4 ± 8.2岁）的血清样本进行分析,通过变量权重投影分析和火山图筛选结直肠腺瘤患者血清中的代谢标志物,利用受试者工作特征曲线（ROC）验证代谢标志物的诊断能力。结果表明,两组血清的代谢轮廓有显著差异,筛选并鉴定了20个生物标志物,涉及缬氨酸、亮氨酸和异亮氨酸合成,花生四烯酸代谢、α-亚麻酸代谢、亚油酸代谢、氨酰-tRNA合成、鞘脂代谢、甘油磷脂代谢、色氨酸代谢,其生物标志物16-羟基棕榈酸、花生四烯酸、肌酸、缬氨酸、亮氨酸、色氨酸、α-亚麻酸、牛磺鹅脱氧胆酸、LysoPC（20∶3）的ROC曲线面积（AUC）均大于0.90,特异性与灵敏度较高,对于结直肠腺瘤筛查具有较高的诊断价值和临床应用潜力。研究结果可为基于代谢组学的结直肠腺瘤筛查提供参考资料。     

基于气相色谱-质谱联用技术的乙型肝炎血清代谢标志物的探究

探索了乙型肝炎患者和健康人血清代谢组的差异,寻找与疾病相关的潜在标志物。收集乙肝患者30例、健康对照35例,以气相色谱-质谱联用技术作为研究平台,应用主成分分析、正交偏最小二乘法-判别分析进行模式识别,然后通过变量重要性因子、非参数检验,结合数据库检索筛选鉴定有差异的代谢物。确认10个代谢物存在显著差异,其中柠檬酸、乌头酸、谷氨酰胺、N,N-二甲基甘氨酸、丙二酸与乙型肝炎患者组的相关性较好,受试者工作特征曲线下面积为0.975,具有较好的特异度和敏感度。因此这5个代谢物能够作为潜在的区分乙型肝炎患者和正常人的血清小分子标志物,有助于进一步了解病理机制,确定治疗目标。     

NEWS——基于色谱-质谱的潜在标志物分子结构鉴定系统方案（I）

在疾病研究中发现新的特异性生物标志物是当前研究的热点和难点。疾病标志物研究的方向正在由单一标志物向多标志物模式转变。代谢组学通过考察生物体系受刺激或基因改变后其代谢产物的变化来发现一系列潜在生物标志物,从而研究生物体系的代谢途径。潜在生物标志物主要通过多变量统计分析方法对样本的LC-MS指纹图谱进行分析得到。     

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。     

基于液相色谱-质谱联用系统的系统性红斑狼疮患者血浆代谢组学分析

应用快速分离液相色谱-串联四极杆飞行时间质谱(RRLC-Q-TOF/MS)系统对系统性红斑狼疮(SLE)患者血浆样本进行代谢指纹图谱的分析。分别应用监督模式识别方法正交信号校正结合偏最小二乘法-判别分析(OSC-PLS-DA)对代谢组数据进行处理,结果显示SLE患者与健康人群对照组的代谢指纹存在明显差异;进一步从SLE患者血清代谢图谱中筛选出10个对分类有显著贡献的离子,定性鉴定出7种代谢标志物,发现SLE患者存在异常的氨基酸、磷脂和卟啉的代谢状态。本研究可为SLE的监测和诊断以及SLE发病的分子基础研究提供科学依据。     

蟾酥急性毒性的代谢组学研究

本文中,我们运用代谢组学方法结合心电图分析对蟾酥导致的大鼠急性毒性进行了研究,通过超高效液相色谱-飞行时间质谱建立了大鼠血清的代谢指纹谱,采用主成分分析和正交偏最小二乘法判别分析法分析了对照组和各给药组之间的代谢物谱差异,通过变量重要性投影和T检验选取潜在的生物标志物,结合质谱同位素分析、数据库检索以及标准品对潜在生物标志物进行了鉴定。结果表明,蟾酥可导致心脏心率减慢、心律失常、甚至出现心肌梗塞现象,其导致心脏损伤的原因可能是通过阻碍自由脂肪酸再酰化或激活蛋白激酶通路干扰了脂质代谢,这对于阐述蟾酥毒性作用机理提供了新思路。     

基于色谱-质谱的潜在标志物分子结构鉴定系统方案(Ⅰ)

在疾病研究中发现新的特异性生物标志物是当前研究的热点和难点。疾病标志物研究的方向正在由单一标志物向多标志物模式转变。代谢组学通过考察生物体系受刺激或基因改变后其代谢产物的变化来发现一系列潜在生物标志物,从而研究生物体系的代谢途径。潜在生物标志物主要通过多变     

基于液相色谱-质谱联用技术的心肌缺血大鼠血清和心肌组织代谢组学

采用异丙肾上腺素诱导心肌缺血大鼠模型,使用液相色谱-质谱法检测血清和心肌中的内源性成分,应用软件对已鉴定的40余种目标成分进行靶向提取,用主成分分析（PCA）、有监督偏最小二乘法判别分析（PLS-DA）对代谢组学数据进行多维度统计分析,筛选潜在生物标志物。与对照组相比,在心肌缺血模型组大鼠血清、组织中检测出18个差异代谢物,涉及精氨酸和脯氨酸代谢、甘氨酸、丝氨酸和苏氨酸代谢、谷氨酰胺和谷氨酸代谢、牛磺酸和亚牛磺酸代谢等多条代谢通路。代谢产物可作为心肌缺血研究中的重要标志物,该研究结果有助于揭示心肌缺血的发病机制,可为临床疾病诊断提供思路。     

Metabolomic Profiling of Serum from Human Pancreatic Cancer Patients Using <Superscript>1</Superscript>H NMR Spectroscopy and Principal Component Analysis

Pancreatic cancer is a malignant tumor with the worst prognosis among all cancers. At the time of diagnosis, surgical cure is no longer a feasible option for most patients, thus early detection of pancreatic cancer is crucial for its treatment. Metabolomics is a powerful new analytical approach to detect the metabolome of cells, tissue, or biofluids. Here, we report the application of ¹H nuclear magnetic resonance (NMR) combined with principal components analysis to discriminate pancreatic cancer patients from healthy controls based on metabolomic profiling of the serum. The metabolic analysis revealed significant lower of 3-hydroxybutyrate, 3-hydroxyisovalerate, lactate, and trimethylamine-N-oxide as well as significant higher level of isoleucine, triglyceride, leucine, and creatinine in the serum from pancreatic cancer patients compared to that of healthy controls. Our data demonstrate that the subtle differences in metabolite profiles in serum of pancreatic cancer patients and that of healthy subjects as a result of physiological and pathological variations could be identified by NMR-based metabolomics and exploited as metabolic markers for the early detection of pancreatic cancer.     

Expanded metabolomics approach to profiling endogenous carbohydrates in the serum of ovarian cancer patients

We applied hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry to the quantitative analysis of serum from 58 women, including ovarian cancer patients, ovarian benign tumor patients, and healthy controls. All of these ovarian cancer and ovarian benign tumor patients have elevated cancer antigen 125, which makes them clinically difficult to differentiate the malignant from the benign. All of the 16 endogenous carbohydrates were quantitatively detected in the human sera, of which, eight endogenous carbohydrates were significantly different (P‐value < 0.05) between the ovarian cancer and healthy control. According to the receiver operating characteristic curve analysis, arabitol was the most potentially specific biomarker for discriminating ovarian cancer from healthy control, having an area under the curve of 0.911. A panel of metabolite markers composed of maltose, maltotriose, raffinose, and mannitol was selected, which was able to discriminate the ovarian cancer from the benign ovarian tumor counterparts, with an area under concentration‐time curve value of 0.832. Endogenous carbohydrates in the expanded metabolomics approach after the global metabolic profiling are characterized and are potential biomarkers for the early diagnosis of ovarian cancer.     

气相色谱-质谱和液相色谱-质谱联用方法用于口腔癌代谢组学分析

口腔癌的发病率占全身恶性肿瘤的第6位,正确区分正常状态与良性和恶性口腔肿瘤,是恰当选择治疗方案的关键所在。本研究中,首先利用液相色谱-质谱和气相色谱-质谱联用方法分别得到健康人、良性口腔肿瘤患者和恶性口腔肿瘤患者血浆、尿液和唾液的代谢轮廓,然后应用正交信号校正的偏最小二乘法进行多变量统计分析。结果表明健康人、良性肿瘤患者和恶性肿瘤患者在血浆、尿液和唾液等3种体液代谢中都可以被区分开,而且找到和鉴定出19个重要差异代谢物。相关代谢通路分析显示,与健康人相比,良性和恶性口腔肿瘤患者都存在能量代谢紊乱和脂类代谢失衡的现象,但恶性口腔肿瘤患者还表现出三羧酸循环和肌醇代谢异常,这为临床诊断及治疗提供了重要信息。     

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.     

Serum metabolomics as a novel diagnostic approach for gastrointestinal cancer

Conventional tumor markers are unsuitable for detecting carcinoma at an early stage and lack clinical efficacy and utility. In this study, we attempted to investigate the differences in serum metabolite profiles of gastrointestinal cancers and healthy volunteers using a metabolomic approach and searched for sensitive and specific metabolomic biomarker candidates. Human serum samples were obtained esophageal (n = 15), gastric (n = 11), and colorectal (n = 12) cancer patients and healthy volunteers (n = 12). A model for evaluating metabolomic biomarker candidates was constructed using multiple classification analysis, and the results were assessed with receiver operating characteristic curves. Among the 58 metabolites, the levels of nine, five and 12 metabolites were significantly changed in the esophageal, gastric and colorectal cancer patients, respectively, compared with the healthy volunteers. Multiple classification analysis revealed that the variations in the levels of malonic acid and l ‐serine largely contributed to the separation of esophageal cancer; gastric cancer was characterized by changes in the levels of 3‐hydroxypropionic acid and pyruvic acid; and l ‐alanine, glucuronoic lactone and l ‐glutamine contributed to the separation of colorectal cancer. Our approach revealed that some metabolites are more sensitive for detecting gastrointestinal cancer than conventional biomarkers. Our study supports the potential of metabolomics as an early diagnostic tool for cancer. Copyright © 2011 John Wiley & Sons, Ltd.     

Enhanced pseudotargeted analysis using a segment data dependent acquisition strategy by liquid chromatography–tandem mass spectrometry for a metabolomics study of liquiritin in the treatment of depression

An enhanced pseudotargeted method using a segment data‐dependent acquisition mode based on ultra‐high performance liquid chromatography–tandem mass spectrometry was developed. This segment data dependent acquisition‐based pseudotargeted method could improve the detection of co‐eluted ions and extend the coverage of analytes. A set of 502 multiple reaction monitoring channels were obtained by this segment strategy, which was twice the number created by the traditional data‐dependent acquisition mode. Compared with the untargeted method, the pseudotargeted profiling demonstrated higher sensitivity and higher precision. More than 90% of the metabolites detected by the enhanced pseudotargeted method had relative standard deviations less than 15%. The segment data dependent acquisition‐based pseudotargeted method was successfully applied to the metabolomics study of the depressed rats with the treatment of liquiritin. Forty‐seven differential metabolites were screened and five metabolic pathways were found to be related to depression including retinol metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, terpenoid backbone biosynthesis, and lysine degradation. The segment data dependent acquisition‐based pseudotargeted method widened the coverage of metabolites with good sensitivity and precision, which exhibited great potential in the discovery of differential metabolites in metabolomics studies.     

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.     

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.     

Study of metabolite differences of flue‐cured tobacco from different regions using a pseudotargeted gas chromatography with mass spectrometry selected‐ion monitoring method

A pseudotargeted method based on gas chromatography and mass spectrometry with selected‐ion monitoring was established to investigate the metabolite differences of flue‐cured tobacco from three different growing regions. The mixed solvent of acetonitrile/isopropanol/water (3:3:2, v/v/v) was chosen as the optimal extraction system based on the good repeatability and extraction efficiency. A self‐developed software coupled with commercial software was used to establish the pseudotargeted method including 289 peaks and 47 groups. Multivariable statistical analysis indicated that tobacco samples can be obviously separated based on the geographical origins. On the basis of a Mann–Whitney U test, organic acids, phenols, and alkaloids had higher levels in Hunan province. In contrast, a large proportion of amino acids (including l ‐tyrosine, l ‐proline, and serine), sucrose, and linoleic acid were the highest in Yunnan province. Meanwhile, multiple metabolic pathways (including carbohydrate metabolism, tricarboxylic acid cycle, and nitrogen metabolism) were influenced by growing regions. Twenty‐eight differential metabolites, which had great contributions to the classification of tobacco samples of three growing regions, were further defined. The results demonstrated that the developed pseudotargeted method was a powerful tool to investigate the metabolic profiling of tobacco leaves and discriminate tobacco leaves of different growing regions.     

Study of urinary nucleosides as biological marker in cancer patients analyzed by micellar electrokinetic capillary chromatography

Thirteen normal and modified nucleosides, primarily degradation products of transfer ribonucleic acid (tRNA), were evaluated as potential tumor markers for cancer patients. Their urinary concentrations were determined by means of micellar electrokinetic capillary chromatography (MEKC) in the urine from 54 healthy adults and 70 cancer patients, then quantitatively expressed as a function of creatinine excretion. It was found that urinary nucleosides for cancer patients were on the average significantly higher than those for healthy controls, however, no significant differences were found between male and female or between different ages. Based on 13 urinary nucleoside concentrations, principal component analysis (PCA) could be used to classify 72% of cancer patients from the healthy controls. The present study shows that the precise measurement of urinary nucleosides by MEKC in combining with PCA technique may provide a clinically useful approach for diagnosis of cancer.