New Algorithm for Peak Alignment of Nuclear Magnetic Resonance

谱峰对齐是基于核磁共振的代谢组学数据预处理过程中的一个重要环节,谱峰对齐效果直接影响后续的多变量统计分析。提出了一种基于高斯平滑的谱峰对齐算法(gPA)。算法通过调节高斯卷积函数的窗口大小,实现波谱信号的多尺度平滑,进而由粗到细、逐步实现波谱信号的谱峰对齐。真实的核磁共振波谱实验结果表明:gPA算法可以快速准确地实现谱峰对齐,且对齐后的波谱信号在平均相似度、后续统计模型的解释能力等综合性能上的表现明显优于相关优化解缠(COW)和多尺度谱峰对齐(MSPA)等常用谱峰对齐算法。Peak alignment is an important step during metabolomics data pretreatment process based on nuclear magnetic resonance(NMR) and its effect plays a direct role on subsequent multivariate statistical analysis.A peak alignment algorithm based on Gaussian smoothing(GPA) is presented.Spectrum signals can be smoothed on multiple scales by adjusting sizes of the windows of Gaussian convolution function.And peak alignment can be realized step by step from coarse to fine.The true experiment results of NMR spectrum show that peak alignment can be realized quickly and accurately by GPA algorithm.Comparing with common peak alignment algorithms such as correlation optimized warping(COW) and multi-scale peak alignment(MSPA),the aligned spectrum signals are superior at integrated performances such as average similarity and explanation performances of subsequent statistical models obviously.国家自然科学基金(81171331;81201143); 中央高校基本科研业务费专项资金(2011121046

Metabolomics Data Filtering Method Based on PCA

代谢组学数据不可避免地受到各种刺激因素的作用,如何降低干扰因素的影响是代谢组学数据预处理的一个重要任务。详细分析了代谢组学数据方差的构成及其在特征空间中的分布特点,并在此基础上提出一种滤除未知干扰因素的新方法,提高感兴趣因素的显著性。文中采用真实的代谢组学数据验证新滤波算法的有效性,并与正交信号校正(OrTHOgOnAl SIgnAlCOrrECTIOn,OSC)方法进行比较。实验结果表明,新滤波方法可以在抑制未知干扰因素影响的同时,较好地保留感兴趣因素信息以及生物体内在的个体差异信息,降低模型发生过拟合的危险,使后续的统计分析结果更可靠。The metabolomics dataset is disturbed by various stimuli inevitably.The main task for metabolo mics data preprocessing is to reduce the impacts of the disturbing factors.In present work,the formation of data variance and their distribution in feature space are analyzed.Furthermore,a new method to filtrate unknown disturb ing factors is proposed and the significance of interesting factors is improved.The efficiency of the new filtering al gorithm is estimated by real metabolomics dataset.Comparing with orthogonal signal correction(OSC) method,the experiment shows that the new method is superior in reducing unknown disturbing factors and retaining useful in formation and intrinsic individual differences in organisms.In addition,it can also prevent the overfitting of model and make the subsequent statistical analysis more reliable.国家自然科学基金(81171331;11175149);中央高校基本科研业务费专项资金(2011121046

Toxicity Study of VOSO_4 Using NMR-based Metabonomics

通讯作者：陈忠 E-mail: [email protected][中文文摘]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.[英文文摘]NMR-Based metabonomics combined with clinical biochemical analysis and histopathological examination was applied to investigate the toxicity effects of vanadyl sulfate with insulin-like activity in male Wistar rats. Male Wistar rats were administrated with VOSO4 at doses of 15 and 45 mg/kg body weight by intragastric administration for 16 d. Urine and serum samples were collected and analyzed by 1H NMR experiment. Multivariate analyses were employed to identify the characteristic metabolites for the toxicity effects of vanadyl sulfate.Then the metabolic networks of these characteristic metabolites were built up using TICL (a web Tool for automatic Interpretation of Compound List). The relationship between the characteristic metabolites and the main matebolic pathways perturbed were analyzed and discussed. The differences of metabolic profiles were examined among high-dose (45 mg/kg), low-dose (15 mg/kg) of VOSO4 and control groups. Compared to the control group, increased levels of lactate, creatinine and taurine in serum and increased excretion of trymethylamine-N2-oxide, creatinine, taurine and glycine in urine were found in both high- and low-dose groups which showed an obvious dose-dependent relationship. On the other hand, the concentration of acetate and succinate were decreased in both serum and urine samples of dosed groups. These results indicate that VOSO4 have disturbed the carbohydrate metabolism, lipid metabolism and gut microflora and the high-dosage of VOSO4 may cause liver and kidney injury.卫生部科学研究基金-福建省卫生教育联合攻关计划(No.WKJ2008-2-36);福建省自然科学基金(No.2009J01299)资助项

The Application of Metabolomics for Gestational Diabetes Mellitus

妊娠期糖尿病(gdM)易造成子痫前期、羊水过多、巨大儿等多种并发症。目前在妊娠中晚期检测血糖筛查gdM,确诊患者接受治疗的时间短,母婴健康存在严重隐患。代谢组学(METAbOlOMICS)是一种定量考察生命系统受内外界刺激或基因修饰后的代谢应答规律的学科。将代谢组学的方法应用于gdM研究,有望实现gdM的早期诊断,理解gdM的致病机制,对gdM的防治和母婴预后都有重要的意义。综述代谢组学方法在gdM及相关疾病研究中的应用。Gestational diabetes mellitus(GDM) easily lead to some complications,such as preeclampsia,polyhydramnios,macrosomia,and so on.The traditional diagnostic protocols for GDM mainly rely on detecting elevated glucose levels in blood,often late in the second trimester.Therefore the treatment time for the patients is not enough and the serious risk to maternal and child health raise.Metabolomics is an approach that investigates the metabolic responses of living systems to internal or external stimuli or genetic modification.The application of metabolomics to GDM research will help to interpret the pathogenesis of GDM.In addition,it can also provide the theoretical and experimental support for prevention and treatment of GDM as well as the prognosis of mothers and their infants.The characteristics of the common detection methods and the metabolomics studies of GDM were analyzed and compared in detail in this paper,and the metabolomic studies in GDM was further reviewed.国家自然科学基金(81201143;81371639); 中央高校基本科研业务费(2013121007

Toxicity Study of VOSO4 Using NMR-based Metabonomics

NMR-Based metabonomics combined with clinical biochemical analysis and histopathological examination was applied to investigate the toxicity effects of vanadyl sulfate with insulin-like activity in male Wistar rats. Male Wistar rats were administrated with VOSO4 at doses of 15 and 45 mg/kg body weight by intragastric administration for 16 d. Urine and serum samples were collected and analyzed by H-1 NMR experiment. Multivariate analyses were employed to identify the characteristic metabolites for the toxicity effects of vanadyl sulfate. Then the metabolic networks of these characteristic metabolites were built up using TICL (a web Tool for automatic Interpretation of Compound List). The relationship between the characteristic metabolites and the main matebolic pathways perturbed were analyzed and discussed. The differences of metabolic profiles were examined among high-dose (45 mg/kg), low-dose (15 mg/kg) of VOSO4 and control groups. Compared to the control group, increased levels of lactate, creatinine and taurine in serum and increased excretion of trymethylamine-N-2-oxide, creatinine, taurine and glycine in urine were found in both high- and low-dose groups which showed an obvious dose-dependent relationship. On the other hand, the concentration of acetate and succinate were decreased in both serum and urine samples of dosed groups. These results indicate that VOSO4 have disturbed the carbohydrate metabolism, lipid metabolism and gut microflora and the high-dosage of VOSO4 may cause liver and kidney injury

New Methods for Metabolomic Data Analysis

代谢组学是系统生物学领域中继基因组学、蛋白质组学、转录组学之后发展起来的以代谢物组分析为基础，以高通量检测和数据处理为手段，以信息建模与系统整合为目标的新的交叉学科，已成为生命科学领域的研究热点之一。 数据分析在代谢组学研究过程中至关重要。随着代谢组学研究的不断深入，对数据分析提出了更高的要求。本论文对代谢组学数据分析中的几个关键性问题进行深入研究，主要成果包括： 一、提出了基于信息熵的变量尺度缩放（variablescaling）方法。该方法从信息熵的角度出发，在单位方差缩放法的基础上，利用Kullback-Leibler（K-L）散度来度量变量的重要性，并对其进行加权。由于K-L散度是...Metabolomics is a rapidly expanding area of scientific research and it is one of the new “-omics” joining genomics, transcriptomics and proteomics in an area of science trying to undersand global systems biology. Metabolomics refers to the analysis of the metabolome, that is, the metabolic profile of a system using high-throughput techniques. This generates high-dimensional data sets from high-thr...学位：工学博士院系专业：信息科学与技术学院_通信与信息系统学号：2332011015408

Investigation of --1H NMR Profile of Vegetarian Human Urine Using ANOVA-based Multi-factor Analysis

结合方差分析(AnOVA)和偏最小二乘法判别分析(PlS-dA)两种分析技术,对素食和普食人群的尿液1H nMr谱进行分析.利用AnOVA方法将数据矩阵分解为几个独立因素矩阵,滤除干扰因素后,再利用PlS-dA对单因素数据进行建模分析.实验结果表明,AnOVA/PlS-dA方法可以有效地减少饮食因素和性别因素之间的相互影响,使分析结果更具有生物学意义.In this study,a technique that combined both analysis of variance(ANOVA) and partial least squares-discriminant analysis(PLS-DA) was used to compare the urine 1H NMR spectra of healthy people from a vegetarian and omnivorous population.In ANOVA/PLS-DA,the variation in data was first decomposed into different variance components that each contains a single source of variation.Each of the resulting variance components was then analyzed using PLS-DA.The experimental results showed that ANOVA/PLS-DA is efficient in disentangling the effect of diet and gender on the metabolic profile,and the method could be used to extract biologically relevant information for result interpretation.国家自然科学基金(批准号:11175149;81171331);中央高校基本科研业务费专项资金(批准号:2011121046)资

New Variable Scaling Method for NMR-based Metabolomics Data Analysis

提出了一种新的尺度归一化方法,该方法不强调各变量在尺度上的归一,而是在原始数据的基础上,通过提高稳定性高且在不同类别样本中具有显著差异性的变量的权重,以增强与特征代谢物相关的信息.分别采用模拟数据和真实代谢组学数据对新归一化方法的性能进行评估,并与单位方差法(unIT VArIAnCE)、变量稳定性(VArIAblE STAbIlITy)和尺度缩放法(lEVEl SCAlIng)等常用的尺度归一化方法进行了比较.研究结果表明,新归一化方法能够提高多变量统计模型的预测能力,较好地保留了核磁共振谱的分子信息,有助于特征代谢物的识别,并使后续的数据分析结果具有更好的可解释性.Variable scaling is an important data pre-processing step in NMR metabolomics,especially for biomarkers identification.It aims to make the subsequent multivariate analysis more reliable and easier by highlighting the biomarkers-related variables,and reducing the contamination of the noise and irrelevant variables.A new scaling method is proposed in this paper.The proposed method adjusts the weight of variables by their significance and stabilities in order to enhance the variable probably related to signature metabolites.Both of simulated dataset and real metabolomic dataset are used to estimate the performance of the proposed method.Comparing with Unit variance(UV),Variable stability(VAST) and Level scaling(LS) methods,the new scaling method would be robust to preserve molecular information of NMR spectra,improving the predictive {ability} of multivariate statistical model and making the results of subsequent analysis more interpretable.Therefore,the method proposed herein is more suitable for biomarker identification.国家卫生部科学研究基金-福建省卫生教育联合攻关计划(批准号:WKJ2008-2-36);福建省自然科学基金(批准号:2009J01299)资

A Novel Metabolomic Data Scaling Method Based on K-L Divergence

在基于核磁共振(nMr)的代谢组学数据分析中,尺度缩放是关键的预处理步骤之一,其主要目的是通过调整数据的方差结构,改善后续的多变量统计分析的结果。从信息熵的角度出发,利用kullbACklEIblEr(k-l)散度来度量不同实验分组的生物样品的1 H nMr波谱数据的差异程度,并结合单位方差缩放法,提出一种基于k-l散度的尺度缩放方法。该方法先利用单位方差法将数据各变量的标准差调整到同一水平上,再利用k-l散度对各变量进行有监督地加权,增强重要变量、减弱无关变量。由于k-l散度是在概率分布的意义上度量数据间的差异程度,且对于高斯和非高斯分布的数据均适用,因此能更准确地度量不同实验分组样品的1 H nMr波谱数据的差异性,从而更有效地地对谱数据的重要变量进行识别和加权。人群尿液1 H nMr波谱数据的分析结果表明,基于k-l散度的尺度缩放方法能有效抑制噪声变量,同时很好地区分特征变量和非特征变量;提高主成分回归(PCr)模型的判别能力;改善偏最小二乘回归判别分析(PlS-dA)模型的解释能力、预测能力以及对特征代谢物的辨识能力。A new scaling method in the current study based on Kullback-Leibler(K-L)divergence is proposed for NMR metabolomic data.The proposed method(called K-L scaling)is a supervised scaling method as group information is incorporated in the scaling procedure.Notably,K-L divergence measures the difference between two different datasets by their probability distributions,it can be used for the analysis of data that either follows Gaussian or non-Gaussian distributions.In K-L scaling,all variables were first standardized to unit variance,then their variance was adjusted using Kullback-Leibler divergence to highlight the significant variables.K-L scaling can tell effectively the difference in spectral data points between two experimental groups,and then enhances the weights of biological-relevant variables,and at the same time reduces the weight of noise and uninformative variables.The developed method was applied to a 1 H-NMR metabolomic dataset acquired from human urine.Analysis results of the dataset showed that this new scaling method is efficient in suppressing the contribution of noise in the resulting multivariate model.In addition,it can increase the weights of important variables,and improve the interpretability and predictability of subsequent principal component regression(PCR)and partial least squares discriminant analysis(PLS-DA).Furthermore,the scaling method facilitated the identification of metabolic signatures.The current result suggested that the developed K-L scaling method may become a useful alternative for the preprocessing of NMR-based metabolomic data.国家自然科学基金项目(81371639;81201143); 中央高校基本科研业务费(2013121007)资

Investigation of (1)H NMR Profile of Vegetarian Human Urine Using ANOVA-based Multi-factor Analysis

【中文摘要】结合方差分析(ANOVA)和偏最小二乘法判别分析(PLS-DA)两种分析技术, 对素食和普食人群的尿液(1)H NMR 谱进行分析. 利用ANOVA 方法将数据矩阵分解为几个独立因素矩阵, 滤除干扰因素后, 再利用PLS-DA 对单因素数据进行建模分析. 实验结果表明,ANOVA/ PLS-DA方法可以有效地减少饮食因素和性别因素之间的相互影响, 使分析结果更具有生物学意义. 【Abstract】In this study, a technique that combined both analysis of variance (ANOVA) and partial least squares-discriminant analysis(PLS-DA) was used to compare the urine H-1 NMR spectra of healthy people from a vegetarian and omnivorous population. In ANOVA/PLS-DA, the variation in data was first decomposed into different variance components that each contains a single source of variation. Each of the resulting variance components was then analyzed using PLS-DA. The experimental results showed that ANOVA/PLS-DA is efficient in disentangling the effect of diet and gender on the metabolic profile, and the method could be used to extract biologically relevant information for result interpretation