基于超高效液相色谱-四极杆飞行时间质谱的缺血性脑卒中的代谢组学研究

采用基于超高效液相色谱-四极杆飞行时间质谱的代谢组学方法,研究缺血性脑卒中患者和健康人群的血浆,分析了缺血性脑卒中的生物标志物.实验收集30例缺血性脑卒中患者和17例健康志愿者的血浆样品,采用主成分分析和正交偏最小二乘判别分析,研究了缺血性脑卒中患者组和健康对照组血浆中的代谢物差异,并进行了代谢通路分析.实验结果表明,患者组血浆中的二氢神经鞘氨醇、植物鞘氨醇等物质含量升高,谷氨酰胺、焦谷氨酸和2-酮丁酸等物质含量降低.结果表明,脑卒中不仅影响了鞘脂类和氨基酸的代谢,还对能量代谢产生了显著的影响.     

阳虚体质者血清和尿液的核磁共振代谢组学

采用基于核磁共振(NMR)的代谢组学方法研究了中医阳虚体质及平和体质(正常对照)的血清和尿液, 分析了阳虚体质的特征代谢物. 实验收集阳虚体质及平和体质各30人的血清及尿液样品, 采用多元统计分析方法研究了阳虚质组和对照组血清和尿液中的内源性代谢差异. 结果表明, 阳虚质血清中乳酸、 极低密度脂蛋白/低密度脂蛋白、N-乙酰糖蛋白、脂肪酸及不饱和脂肪酸的含量降低, 谷氨酰胺、葡萄糖、磷脂酰胆碱及高密度脂蛋白的含量增多; 尿液中肌酐的含量降低, 乳酸、二甲胺、柠檬酸及马尿酸的含量增多. 阳虚体质的潜在生物标志物的发现从代谢组学角度为个体差异提供了新的依据. 阳虚体质与平和体质存在能量代谢、脂代谢及糖代谢的差异以及相关脏腑功能的改变.     

基于UPLC/Q-TOF MS的糖尿病尿液代谢组学研究

利用超高效液相色谱-飞行时间质谱联用开展糖尿病尿液代谢组学研究。尿液样品经稀释过滤后进样分析,对采集的谱图进行峰提取、峰匹配和过滤后,采用主成分分析的偏最小二乘-判别分析进行数据分析。结果发现,糖尿病人较正常人尿液的代谢表型发生了显著变异,主成分分析得分散点图中健康对照组与患病组分类良好;根据谱库共筛选了18个表征标记物,对其中14个进行了结构鉴定。糖尿病患者尿液中的糖、脂、氨基酸等代谢通路均发生了紊乱,在糖类代谢物中,钠葡萄糖醛酸含量明显高于正常对照组;在脂肪酸类物质中,20-羧基花生四烯酸、棕榈酸及磷脂酰肌醇在糖尿病患者尿液中含量高于正常对照组;氨基酸类代谢物中,酪氨酸、N-β-丙氨酰-L组氨酸、色氨酸含量较正常人低,戊二酸、烟酰甘氨酸、天冬氨酸、苯丙氨酸等含量升高。     

硫酸氧钒毒性的核磁共振代谢组学方法研究

采用基于核磁共振(NMR)的代谢组学方法,结合生化指标分析及组织病理学检测,研究了具有类胰岛素活性的硫酸氧钒(VOSO4)对Wistar大鼠的毒性作用.通过不同剂量的VOSO4对Wistar大鼠连续灌胃给药16d,收集大鼠的血清和尿液,并采集样品的1H NMR谱进行多变量数据统计分析来辨识其特征代谢物,然后采用TICL(a web Tool for automatic Interpretation of Compound List)方法建立特征代谢物的代谢网络模型,分析受影响的主要代谢途径及其相互关系.研究结果表明:高剂量组(45mg/kg)和低剂量组(15mg/kg)的特征代谢物含量与对照组存在明显的差异;与对照组相比,高剂量和低剂量组血清中乳酸、肌氨酸酐以及牛磺酸等代谢物的含量增加,尿液中氧化三甲胺(TMAO)、肌酐、牛磺酸和甘氨酸等代谢物的含量增加,并呈现显著的剂量依赖关系;给药组中乙酸和琥珀酸的含量都降低.这些结果说明VOSO4可能影响大鼠体内的糖代谢、脂类代谢及肠道菌群代谢等多个代谢系统,高剂量的VOSO4会导致肝脏毒性和肾脏损伤.     

高脂与维生素D缺乏饮食诱导的2型糖尿病小鼠血清和肝脏代谢组学研究

采用高脂与维生素D缺乏(VDD)饮食长期(24周)喂养小鼠,诱导其形成2型糖尿病(T2DM),通过小鼠血清和肝脏代谢组学分析探究了T2DM发生、发展的代谢物和代谢通路变化机制.实验收集小鼠血清和肝脏样品,通过气相色谱-质谱联用技术和硅烷化衍生方法分析得到血清和肝脏代谢轮廓;利用正交偏最小二乘判别分析和非参数检验筛选血清和肝脏代谢组中具有显著性差异的代谢标志物,发现血清样品中乳酸、丙氨酸、甘油、苏氨酸和葡萄糖含量在高脂+VDD小鼠中显著升高,肝脏样品中乳酸、核糖、果糖、葡萄糖、油酸和棕榈酸含量在高脂+VDD小鼠中显著升高.本文还进行了血清和肝脏代谢轮廓整体分析和代谢通路探索,发现高脂+VDD小鼠中三羧酸循环、糖异生、氨基酸以及脂质代谢通量均显著增强,这些代谢路径相互影响共同促进T2DM的发生和发展.本文通过饮食诱导小鼠形成T2DM,得到血清和肝脏代谢物及其代谢通路的变化关系,可为T2DM诊断提供参考信息.     

基于HPLC/Q-TOF MS的4种农药联合暴露人群的代谢组学研究

采用基于高效液相色谱-飞行时间质谱联用(HPLC-TOF MS)的代谢组学方法,研究了啶虫脒、高效氯氟氰菊酯、联苯菊酯、甲氨基阿维菌素苯甲酸盐4种农药联合暴露所致的施药人群尿液中内源性代谢物的变化。采集30位农民喷洒4种复合农药前和喷洒农药期1,3,5,7 d的尿液进行检测。提取正常尿液中常见代谢物并通过质控样品评价手段进行分析,结果表明该方法具有良好的稳定性和精密度,可用于尿液中代谢物分析。多变量分析结果表明,暴露人群施药前后尿液的代谢物含量存在较大差异。对选取的36个差异离子进行鉴定,确定了8个生物标志物的结构。结果显示联合暴露组人群尿液中多巴胺、5-羟色胺、酪氨酸、色氨酸、牛磺酸和马尿酸的含量显著下降;犬尿素和肌酸的含量显著上升。4种农药联合暴露导致接触人群尿液中色氨酸代谢途径的中间产物含量降低,肝代谢和能量代谢相关的代谢物蓄积,可能与神经系统和肝脏功能的受损有关。     

基于核磁共振技术的临床尿毒症的代谢组学研究

采用核磁共振技术与统计学分析方法,结合尿液的生化指标,进行临床尿毒症尿样的代谢组学研究。结果表明,尿毒症患者和健康对照人群尿样的代谢轮廓存在明显差异,通过核磁共振氢谱鉴定出70种代谢物,其中20种具有显著差异。与健康人群相比,尿毒症患者尿液中2-羟基异丁酸、3-羟基丁酸、丙酮、丁酸、谷氨酸、肌氨酸、肌酐、赖氨酸、N,N-二甲基组氨酸、柠檬酸、天冬酰胺、乙醇和乙醇胺的含量明显偏低,而支链氨基酸(包括亮氨酸、缬氨酸、异亮氨酸)、牛磺酸、乳酸、α-葡萄糖和β-葡萄糖的含量明显偏高。这些代谢物涉及氨基酸代谢、能量代谢和脂质代谢中的多条代谢途径,可作为尿毒症代谢影响的潜在的生物标志物,有助于理解尿毒症发病的生化机制。     

不同干燥方法对芦苇不同组织GC/MS代谢组学分析的影响

基于气相色谱-质谱联用(GC/MS)技术,以超低温冷藏为对照,分析了真空冷冻干燥、45℃烘干和硅胶干燥处理对芦苇Phragmites australis叶、茎和根组织样品代谢组学分析结果的影响。共检测出51个色谱峰,鉴定出25种代谢物。主成分分析(PCA)和多响应置换过程分析(MRPP)表明,45℃烘干和硅胶干燥对芦苇不同组织样品代谢物组成影响均较大,而真空冷冻干燥只对叶样品代谢物组成具有显著影响。利用方差分析对鉴定出代谢物含量进行分析,结果真空冷冻干燥会导致叶样品中甘油、果糖、葡萄糖含量显著升高,蔗糖含量显著下降,但不会对根茎样品中代谢物含量产生显著影响。45℃烘干和硅胶干燥则能导致不同组织样品中氨基丁酸、甘油酸、苏糖酸、奎宁酸、葡糖酸、果糖、葡萄糖、半乳糖、麦芽糖和肌醇含量升高,而蔗糖和肌醇半乳糖苷含量下降。不同干燥方法对酶活抑制效率差异可能是导致上述结果的重要原因。因此,在进行芦苇代谢组学研究时,必须考虑不同干燥方法对不同组织代谢组学分析结果的影响。     

核磁共振技术测试不同性别大鼠尿液代谢物的研究

采用核磁共振波谱技术测试不同性别大鼠尿液代谢物,分析性别因素对大鼠尿液代谢成分的影响.大鼠尿液核磁共振氢谱（1HNMR谱）结果采用主成分分析（principal component analysis,PCA）和正交偏最小二乘判别分析（orthogonal to partial least squares discriminant analysis,OPLS-DA）方法分析,得到不同性别大鼠尿液中的差异性代谢物.PCA分析结果显示2组尿液代谢成分有明显的差异,进一步进行OPLS-DA分析可以判别出2组尿液中具有差异性的代谢物.结果显示,雌性大鼠尿液中的丙氨酸、缬氨酸、鸟氨酸等氨基酸类以及乙酸、硫胺、氨基马尿酸、苯乙胺、氧氨嘧啶等代谢物含量高于雄性大鼠,差异有统计学意义（p〈0.05）.雄性大鼠尿液中的甲胺、二甲胺、三甲胺、肌酸酐、尿囊素、延胡索酸、甲酸等代谢物则明显高于雌性大鼠,差异有统计学意义（p〈0.05）.性别因素对大鼠尿液中的代谢成分有一定的影响.     

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。     

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.     

Mass spectrometric characterization of urinary toremifene metabolites for doping control analyses

Toremifene is a selective estrogen receptor modulator included in the list of prohibited substances in sport by the World Anti-doping Agency. The aim of the present study was to investigate toremifene metabolism in humans in order to elucidate the structures of the most abundant urinary metabolites and to define the best marker to detect toremifene administration through the analysis of urine samples. Toremifene (Fareston) was administered to healthy volunteers and the urine samples were subjected to different preparation methods to detect free metabolites as well as metabolites conjugated with glucuronic acid or sulphate. Urinary extracts were analyzed by LC-MS/MS with triple quadrupole analyzer using selected reaction monitoring mode. Transitions for potential metabolites were selected by using the theoretical [M+H](+) as precursor ion and m/z 72 or m/z 58 as product ions for N,N-dimethyl and N-desmethyl metabolites, respectively. Toremifene and 20 metabolites were detected in excretion study samples, excreted free or conjugated with glucuronic acid or sulphate. Structures for most abundant phase I metabolites were proposed using accurate mass measurements performed by QTOF MS, based on fragmentation pattern observed for those metabolites available as reference standards. Several metabolic pathways including mono- and di-hydroxylation, N-desmethylation, hydroxymethylation, oxidation, dehalogenation and combinations were proposed. All metabolites were detected up to one month after toremifene administration; the most abundant metabolites were detected in the free fraction and they were metabolites resulting from dehalogenation. Several of the metabolites elucidated in this work have not been reported until now in the scientific literature.     

Rapid structure identification of nineteen metabolites of ondansetron in human urine using LC/MSn

Ondansetron, a 5‐hydroxytryptamine type 3 (5‐HT₃) receptor antagonist, is regarded as an excellent candidate to treat chemotherapy‐ and radiotherapy‐induced nausea and vomiting. To better understand the metabolic profiles of ondansetron in human urine, the metabolites were analyzed using liquid chromatography/mass spectrometry (LC/MSⁿ). Urine samples were collected after oral administration of 8 mg ondansetron to healthy volunteers. Then samples were treated by solid‐phase extraction and detected with LC/MSⁿ. Besides ondansetron, in human urine, a total of 19 metabolites including 13 new metabolites were detected and identified via comparing the retention time and product ion spectra with those of reference standards isolated and characterized. The results showed that ondansetron was metabolized via hydroxylation, glucuronidation, sulfation and minor N‐demethylation in human. LC/MSⁿ was demonstrated to be useful and sensitive in the metabolic study of ondansetron.     

Structural elucidation of new urinary tamoxifen metabolites by liquid chromatography quadrupole time‐of‐flight mass spectrometry

In this study, tamoxifen metabolic profiles were investigated carefully. Tamoxifen was administered to two healthy male volunteers and one female patient suffering from breast cancer. Urinary extracts were analyzed by liquid chromatography quadruple time‐of‐flight mass spectrometry using full scan and targeted MS/MS techniques with accurate mass measurement. Chromatographic peaks for potential metabolites were selected by using the theoretical [M + H]⁺ as precursor ion in full‐scan experiment and m/z 72, 58 or 44 as characteristic product ions for N,N‐dimethyl, N‐desmethyl and N,N‐didesmethyl metabolites in targeted MS/MS experiment, respectively. Tamoxifen and 37 metabolites were detected in extraction study samples. Chemical structures of seven unreported metabolites were elucidated particularly on the basis of fragmentation patterns observed for these metabolites. Several metabolic pathways containing mono‐ and di‐hydroxylation, methoxylation, N‐desmethylation, N,N‐didesmethylation, oxidation and combinations were suggested. All the metabolites were detected in the urine samples up to 1 week. Copyright © 2014 John Wiley & Sons, Ltd.     

Characterization of Metabolites in Plasma,Urine and Feces of Healthy Participants after Taking Brahmi Essence for Twelve Weeks Using LC-ESI-QTOF-MS Metabolomic Approach

Brahmi essence, developed from Bacopa monnieri (L.) Wettst. standardized extract and mulberry juice, was proven to improve the memory speed of healthy participants aged 55–80 years old, following a 12-week dietary program. However, the metabolites have not yet been reported. Our objective was to characterize the altered metabolites in the plasma, urine, and feces of healthy volunteers after consumption of Brahmi essence for 12 weeks, using the LC-MS metabolomics approach. The altered metabolites were selected from OPLS-DA S-plots; 15 metabolites in the plasma, 7 in the urine, and 17 in the feces samples were tentatively identified by comparison with an online database and literature. The metabolites in the plasma samples were in the classes of amino acids, acylcarnitine, and phospholipids. Benzeneactamide-4-O-sulphate and 3-hydroxyhippuric acid were found in urine samples. The metabolites in the class of amino acids, together with jujubogenin and pseudojujubogenin, were identified in the fecal samples. The aminoacyl-tRNA, aromatic amino acids, and branched-chain amino acid biosynthetic pathways were mainly related to the identified metabolites in all three samples. It could be implied that those metabolites and their pathways might be linked with the effect of Brahmi essence on memory speed.     

Optimizing the extraction and analysis of DHEA sulfate, corticosteroids and androgens in urine: application to a study of the influence of corticosteroid intake on urinary steroid profiles

A method of detecting and quantifying dehydroepiandrosterone (DHEA) sulfate, corticosteroids, and androgens has been developed. All of the compounds were first extracted from urine using solid phase extraction (SPE), enzymatically hydrolyzed, and separated into three samples using a second SPE. A DHEA sulfate sample was acetylated and re-extracted using SPE for purification before analysis. Corticosteroid samples were oxidized and re-extracted using liquid/liquid extraction for analysis. Androgen samples were acetylated and re-extracted using SPE prior to analysis. The extraction and analysis methods were investigated and optimized. Analyses were performed with gas chromatography/mass spectrometry (GC/MS) and gas chromatography/flame ionization detection (GC/FID). The entire procedure was then applied to the study of urine profiles of healthy volunteers and patients treated with corticosteroids. The results showed that the quantities of androgens found in patient urines were lower than in those of healthy volunteers. In addition, other metabolites were detected in patient urines.     

Urine biomarkers discovery by metabolomics and machine learning for Parkinson's disease diagnoses

Parkinson’s disease(PD) is a complex neurological disorder that typically worsens with age. A wide range of pathologies makes PD a very heterogeneous condition, and there are currently no reliable diagnostic tests for this disease. The application of metabolomics to the study of PD has the potential to identify disease biomarkers through the systematic evaluation of metabolites. In this study, urine metabolic profiles of 215 urine samples from 104 PD patients and 111 healthy individuals were ass...     

Rapid determination of acetaminophen in physiological fluids by liquid chromatography using SDS mobile phase and ED detection

Acetaminophen is determined in serum and urine samples by a rapid, sensitive, and precise chromatographic method without any pretreatment step in a C18 column using a pure micellar mobile phase of 0.02M sodium dodecyl sulfate at pH 7. Acetaminophen is eluted in less than 5 min with no interference of the protein band. The use of electrochemical and UV detection is compared. Linearities (r > 0.999), as well as intra- and interday precision, are studied in the validation of the method. Limits of detection (LOD) are also calculated to be 0.56, 0.83, and 0.74 ng/mL in micellar solution, serum, and urine using electrochemical detection. The developed micellar liquid chromatographic method is useful for the quantitation of acetaminophen in serum and urine. Recoveries in the biological matrices are in the 98-107% range and results are compared with those obtained using a reference method. Drug excretion (in urine) and serum distribution are studied in several healthy volunteers, and no interference from metabolites is found. The developed procedure can be applied in routine analyses, toxicology, and therapeutic monitoring.     

基于1H-NMR的模式识别方法应用于异常黑胆质糖尿病患者的尿液代谢组学研究

探讨核磁共振氢谱结合模式识别方法应用于异常黑胆质糖尿病患者的尿液代谢组研究可行性。对32 例异常黑胆质糖尿病患者和29 例健康人尿液进行核磁共振氢谱检测,采用主成分分析(principal component analysis, PCA)、偏最小二乘法判别分析(partial least squares dis-criminant analysis, PLS-DA)、正交偏最小二乘法判别分析(orthogonal to partial least squares discriminant analysis,OPLS-DA)进行模式识别分析,比较3种模式识别方法的判别能力。运用3种模式识别均可以对2组数据进行有效的区分,但OPLS-DA较PCA、P[1]LS-DA更加有效,不仅提高了模式识别方法的判断能力,可以清楚的判断两组中有差异的代谢物。基于核磁共振氢谱结合模式识别分析方法可以为异常黑胆质糖尿病代谢标志物的寻找提供理论依据。OPLS-DA的模式识别方法较其它2种方法更具优势,在揭示维医理论本质上有着广阔的应用前景。