NMR‐based metabolomics coupled with pattern recognition methods in biomarker discovery and disease diagnosis

Molecular biomarkers could detect biochemical changes associated with disease processes. The key metabolites have become an important part for improving the diagnosis, prognosis, and therapy of diseases. Because of the chemical diversity and dynamic concentration range, the analysis of metabolites remains a challenge. Assessment of fluctuations on the levels of endogenous metabolites by advanced NMR spectroscopy technique combined with multivariate statistics, the so‐called metabolomics approach, has proved to be exquisitely valuable in human disease diagnosis. Because of its ability to detect a large number of metabolites in intact biological samples with isotope labeling of metabolites using nuclei such as H, C, N, and P, NMR has emerged as one of the most powerful analytical techniques in metabolomics and has dramatically improved the ability to identify low concentration metabolites and trace important metabolic pathways. Multivariate statistical methods or pattern recognition programs have been developed to handle the acquired data and to search for the discriminating features from biosample sets. Furthermore, the combination of NMR with pattern recognition methods has proven highly effective at identifying unknown metabolites that correlate with changes in genotype or phenotype. The research and clinical results achieved through NMR investigations during the first 13 years of the 21st century illustrate areas where this technology can be best translated into clinical practice. In this review, we will present several special examples of a successful application of NMR for biomarker discovery, implications for disease diagnosis, prognosis, and therapy evaluation, and discuss possible future improvements. Copyright © 2013 John Wiley & Sons, Ltd.     

Metabolomics: a revolution for novel cancer marker identification

The repertoire of small-molecular-weight substances present in cells, tissue and body fluids are known as the metabolites. The global analysis of metabolites, such as by high-resolution 1H nuclear magnetic resonance spectroscopy and mass spectrometry, is integral to the rapidly expanding field of metabolomics, which is making progress in various diseases. In the area of cancer and metabolic phenotype, the integrated analysis of metabolites may provide a powerful platform for detecting changes related to cancer diagnosis and discovering novel biomarkers. In this review, metabolomics including the technologies in metabolomics research and extracting information from metabolomics datasets are described. Then we discuss the challenges and opportunities in metabolomics for finding metabolic processes in cancer and discovering novel cancer biomarkers. Finally, we assess the clinical applicability of metabolomics.     

Application of magnetic solid phase extraction in separation and enrichment of glycoproteins and glycopeptides

The analysis of endogenous glycoproteins and glycopeptides in human body fluids is of great importance for screening and discovering disease biomarkers with clinical significance. However, the presence of interfering substances makes the direct quantitative detection of low-abundance glycoproteins and glycopeptides in human body fluids one of the great challenges in analytical chemistry. Magnetic solid phase extraction (MSPE) has the advantages of easy preparation, low cost and good magnetic responsiveness. Magnetic adsorbents are the core of MSPE technology, and magnetic adsorbents based on different functional materials are widely used in the quantitative analysis of glycoproteins and glycopeptides in human body fluids, making it possible to analyze glycoproteins and glycopeptides with low abundance as well as multiple types, which provides a technical platform for screening and evaluating glycoproteins and glycopeptides in body fluids as disease biomarkers. In this paper, we focus on the recent advances in the application of MSPE technology and magnetic adsorbents for the separation and enrichment of glycoproteins and glycopeptides in human body fluids, and the future trends and application prospects in this field are also presented.     

Bioanalytical methods for metabolomic profiling: Detection of head and neck cancer,including oral cancer

Metabolomics is an emerging field dealing with the measurement and interpretation of small molecular byproducts of biochemical processes, or metabolites, which can be used to generate profiles from biological samples. Promising for use in pathophysiology, metabolomic profiles give the immediate biological state of a sample. These profiles are altered in diseases and are detectable in biological samples, such as tissue, blood, urine, saliva, and others. Most remarkably, metabolic profiles usually are altered before symptoms appear in a patient. For this reason, metabolomics has potential as a reliable method for an early diagnosis of diseases through disease biomarker identification. This application is most prevalent in cancer, such as head and neck cancer (HNC). Metabolomic studies offer avenues to improve on current medical techniques through the application of mass spectrometry (MS), nuclear magnetic resonance spectroscopy (NMR), and statistical analysis to determine better biomarkers than those currently known. In this review, we discuss the use of MS and NMR tools for detecting biomarkers in tissue and fluid samples, and the appropriateness of metabolomics in analyzing cancer. Advantages, disadvantages, and recent studies on metabolomic profiling techniques in HNC analysis are also discussed herein.     

Metabolite assignment of ultrafiltered synovial fluid extracted from knee joints of reactive arthritis patients using high resolution NMR spectroscopy

Currently, there are no reliable biomarkers available that can aid early differential diagnosis of reactive arthritis (ReA) from other inflammatory joint diseases. Metabolic profiling of synovial fluid (SF)—obtained from joints affected in ReA—holds great promise in this regard and will further aid monitoring treatment and improving our understanding about disease mechanism. As a first step in this direction, we report here the metabolite specific assignment of ¹H and ¹³C resonances detected in the NMR spectra of SF samples extracted from human patients with established ReA. The metabolite characterization has been carried out on both normal and ultrafiltered (deproteinized) SF samples of eight ReA patients (n = 8) using high-resolution (800 MHz) ¹H and ¹H─¹³C NMR spectroscopy methods such as one-dimensional ¹H CPMG and two-dimensional J-resolved¹H NMR and homonuclear ¹H─¹H TOCSY and heteronuclear¹H─¹³C HSQC correlation spectra. Compared with normal SF samples, several distinctive ¹H NMR signals were identified and assigned to metabolites in the ¹H NMR spectra of ultrafiltered SF samples. Overall, we assigned 53 metabolites in normal filtered SF and 64 metabolites in filtered pooled SF sample compared with nonfiltered SF samples for which only 48 metabolites (including lipid/membrane metabolites as well) have been identified. The established NMR characterization of SF metabolites will serve to guide future metabolomics studies aiming to identify/evaluate the SF-based metabolic biomarkers of diagnostic/prognostic potential or seeking biochemical insights into disease mechanisms in a clinical perspective.     

Strategy for metabonomics research based on high-performance liquid chromatography and liquid chromatography coupled with tandem mass spectrometry

Metabonomics, the study of metabolites and their roles in various disease states, is a novel methodology arising from the post-genomics era. This methodology has been applied in many fields. Current metabonomic practice has relied on mass spectrometry (MS), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR) to analyze metabolites. In this study, a strategy was developed for applying high-performance liquid chromatography (HPLC) and LC-MS-MS to metabonomics research. One of the key problems to be solved in this strategy is to match the peaks between the chromatograms. A peak alignment algorithm has been developed to match the chromatograms before the pattern recognition. As an application example, the strategy described above was applied to metabonomics research on liver diseases, and the false-positive result of live cancer diagnosis from the hepatocirrhosis and hepatitis diseases was effectively reduced to 7.40%. Based on the pattern recognition, several potential biomarkers were found and further identified by the following LC-MS-MS experiments. The structures of eight potential biomarkers were given for distinguishing the liver cancer from the hepatocirrhosis and hepatitis diseases.     

Recent advances in metabolomics in neurological disease, and future perspectives

Discovery of clinically relevant biomarkers for diseases has revealed metabolomics has potential advantages that classical diagnostic approaches do not. The great asset of metabolomics is that it enables assessment of global metabolic profiles of biofluids and discovery of biomarkers distinguishing disease status, with the possibility of enhancing clinical diagnostics. Most current clinical chemistry tests rely on old technology, and are neither sensitive nor specific for a particular disease. Clinical diagnosis of major neurological disorders, for example Alzheimer’s disease and Parkinson’s disease, on the basis of current clinical criteria is unsatisfactory. Emerging metabolomics is a powerful technique for discovering novel biomarkers and biochemical pathways to improve diagnosis, and for determination of prognosis and therapy. Identifying multiple novel biomarkers for neurological diseases has been greatly enhanced with recent advances in metabolomics that are more accurate than routine clinical practice. Cerebrospinal fluid (CSF), which is known to be a rich source of small-molecule biomarkers for neurological and neurodegenerative diseases, and is in close contact with diseased areas in neurological disorders, could potentially be used for disease diagnosis. Metabolomics will drive CSF analysis, facilitate and improve the development of disease treatment, and result in great benefits to public health in the long-term. This review covers different aspects of CSF metabolomics and discusses their significance in the postgenomic era, emphasizing the potential importance of endogenous small-molecule metabolites in this emerging field.     

Proteomic profiling of human urine using multi-dimensional protein identification technology

Human urine samples are ideal for proteomic profiling and have tremendous potential as sources of biomarkers. Multi-dimensional protein identification technology (MudPIT) is an effective approach to analyzing human urine or other fluids dominated by diverse metabolites. MudPIT analysis was used to identify 87 proteins in just 15 ml of human urine. A high throughput, reproducible, and sensitive technology, MudPIT may soon be used for more proteomic analyses of metabolites.     

From Chemistry to Translational Medicine: The Application of Proteomics to Cancer Biomarker Discovery and Diagnosis

The study of complex protein mixtures and their interactions in cells and tissues has been difficult due to the tedious process involved in their characterization and analysis. The recent emergence of fast‐evolving and state‐of‐the‐art proteomics methodologies has provided a rapid and scalable platform for understanding the comprehensive proteome profiles from complex whole tissues or cells of various biological sources. Therefore, proteomics has been increasingly valuable to examine real‐time changes in protein expression of various tissues or body fluids from patients with various diseases, especially cancer, resulting in the identification of clinically useful biomarkers for diagnosis, prognosis and disease staging. In this review, we focus on potential biomarkers for (1) Helicobacter pylori‐associated gastric cancer, (2) hepatocellular carcinoma (HCC), and (3) renal cell carcinoma (RCC). In addition to the conventional gel‐based proteomics (1‐D or 2‐D gels), we have utilized a more advanced proteomic approach by incorporating stable isotope dimethyl labelling and shotgun proteomics strategy in combination with nanoliquid chromatography and tandem mass spectrometry (nanoLC‐MS/MS) to better characterize the biomarkers in several cancer tissues. By establishing a high‐throughput proteomics platform based on multiple reaction monitoring (MRM), we have successfully detected and analyzed potential protein markers at low concentrations in various normal and tumor tissues. This platform not only highlights the utility of proteomics for biomarker discovery but also can be uniquely applied to disease‐oriented translational medicine for diagnosis of diverse types of cancers and other diseases.     

Methods for determining neurotransmitter metabolism markers for clinical diagnostics

Published data describing the current status and prospects for the development of clinical diagnostics of a number of neurodegenerative and neuroendocrine diseases associated with neurotransmitter balance disorders in a human body are generalized, systematized, and assessed in the review. Characteristics, advantages, and limitations of neuroimaging techniques and different diagnostic methods based on measuring concentrations of protein markers, catecholamines, and their metabolites are discussed. Prospects of the application of optical methods, such as fluorimetry and surface-enhanced Raman spectroscopy, to the development of sensor systems for the diagnosis of these diseases by the concentration of catecholamines and their metabolites in biological fluids are demonstrated.     

Determination of aminothiols in body fluids, cells, and tissues by capillary electrophoresis

Oxidative stress is present in cardiovascular diseases and hyperhomocysteinemia, an independent risk factor for these diseases. It may play a role by inducing production of oxygen free radicals. Reduced glutathione is the most abundant intracellular low-molecular-weight thiol and plays an essential role in protecting cells from toxic species. The thiol-containing compounds which are the most often considered in biological analysis, are homocysteine (Hcy), cysteine (Cys), glutathione (GSH), cysteinyl-glycine (Cys-Gly), gamma-glutamyl-cysteine (gammaGlu-Cys), and their derivatives. These aminothiols are present in body fluids or cells, associated with proteins or occur free (reduced and oxidized). These free forms may play a role in the pathogenesis of disease. Because Hcy (with Cys) exhibits pro-oxidative properties and GSH (with Cys-Gly) antioxidative properties, and because there is extensive interconversion between these metabolites, their simultaneous analysis in biological samples is necessary to examine their role in human disease. Capillary electrophoresis (CE) seems to be a solution to reach this goal. No extensive review reports the analysis of aminothiols using CE. This review describes the different CE approaches which have been used to separate and assay aminothiols, and the different obtained datas.     

Gas chromatography — mass spectrometry in diagnosis of human metabolic diseases

Many human diseases result in characteristic changes in the biochemical composition of the cells and body fluids. Gas chromatography-mass spectrometry (GC-MS) and computer handling of the data are suitable for detecting such changes, e.g. the production of abnormal metabolites in a patient. The methods can be used to diagnose and study about 100 different metabolic disorders and have resulted in the discovery of 30 new inborn errors of metabolism.     

Gas chromatography/flame ionisation detection mass spectrometry for the detection of endogenous urine metabolites for metabonomic studies and its use as a complementary tool to nuclear magnetic resonance spectroscopy

Metabonomics is a relatively new field of research in which the total pool of metabolites in body fluids or tissues from different patient groups is subjected to comparative analysis. Nuclear magnetic resonance (NMR) spectroscopy is the technology that is currently most widely used for the analysis of these highly complex metabolite mixtures, and hundreds of metabolites can be detected without any upfront separation. We have investigated in this study whether gas chromatography (GC) separation in combination with flame ionisation detection (FID) and mass spectrometry (MS) detection can be used for metabolite profiling from urine. We show that although GC sample preparation is much more involved than for NMR, hundreds of metabolites can reproducibly be detected and analysed by GC. We show that the data quality is sufficiently high--particularly if appropriate baseline correction and time-warping methods are applied--to allow for data comparison by chemometrics methods. A sample set of urines from eleven healthy human volunteers was analysed independently by GC and NMR, and subsequent chemometrics analysis of the two datasets showed some similar features. As judged by NIST database searches of the GC/MS data some of the major metabolites that are detected by NMR are also visible by GC/MS. Since in contrast to NMR every peak in GC corresponds to a single metabolite, the electron ionisation spectra can be used to quickly identify metabolites of interest if their reference spectra are present in a searchable database. In summary, we show that GC is a method that can be used as a complementary tool to NMR for metabolite profiling of urine samples.     

Exploratory urinary metabolic biomarkers and pathways using UPLC-Q-TOF-HDMS coupled with pattern recognition approach

Metabolomics represents an emerging and powerful discipline concerned with the comprehensive analysis of small molecules and provides a powerful approach to discover biomarkers in biological systems. Recent development of biomarkers for diagnosis and therapeutic monitoring of liver-stagnation and spleen-deficiency syndrome (LSS)-type disease remains challenging. This study was undertaken to discover novel potential biomarkers for the non-invasive early diagnosis of human LSS. Urine samples which are potentially a rich source of metabolites were collected from patients with LSS, together with healthy control samples. Metabolite profiling was performed by ultra-performance liquid-chromatography/electrospray-ionization synapt high-definition mass spectrometry (UPLC-Q-TOF-HDMS) in conjunction with multivariate data analysis and ingenuity pathway analysis that were used to select the metabolites to be used for the non-invasive diagnosis of LSS. Twelve urinary differential metabolites contributing to the complete separation of LSS patients from matched healthy controls were identified involving several key metabolic pathways such as pentose and glucuronate interconversions, ascorbate, aldarate, cysteine, methionine, tyrosine, tryptophan, amino sugar and nucleotide sugar metabolism. More importantly, of the 12 differential metabolites, 4 metabolite markers, prolylhydroxyproline, l-homocystine, 2-octenoylcarnitine and α-N-phenylacetyl-l-glutamine, were effective for the diagnosis of human LSS, with an achieved sensitivity of 93.0%. These results demonstrate that robust metabolomics has the potential as a non-invasive strategy and promising screening tool to evaluate the potential of these metabolites in the early diagnosis of LSS patients and provides new insight into pathophysiological mechanisms.     

基于质谱检测的相关色谱技术在阿尔茨海默病诊断中的应用

随着世界老年人口的急速增长,阿尔茨海默病发病人数也逐年增多,已成为继心脑血管疾病和恶性肿瘤之后威胁人类健康的“第三大杀手”。疾病的诊断和治疗同等重要,阿尔茨海默病诊断通常依靠典型的临床特征、神经影像技术以及检测疾病相关的生物标志物等。近些年来蛋白质组学和质谱技术迅速发展,可以利用这些技术寻找到与疾病相关的特异性的蛋白质分子作为早期诊断的生物标志物。本文就此进行了综述,主要包括基于蛋白质组学的诊断标志物的筛选和基于质谱检测的色谱技术在阿尔茨海默病诊断中的应用,引用文献34篇。     

Profiling of human body fluids in healthy and diseased states using gas chromatography and mass spectrometry, with special reference to organic acids.

This review summarizes recent advances in the application of gas chromatography and mass spectrometry to the study of human diseases. Emphasis is placed upon the organic acid profiles of the various body fluids. Methods for sample work-up prior to separation and mass spectrometric analysis are reviewed, and artifacts and pitfalls are discussed. Organic acid profiles, obtained with packed or capillary columns attached to mass spectrometers with or without computer systems, have led to the discovery of new normal metabolites, new metabolic disorders, and to new knowledge about a number of other diseases. Stable isotopes and gas chromatography--mass spectrometry are suitable for quantitative analysis of many compounds in the body fluids, and well suited for investigation of metabolic pathways.     

Measurement of gut microbial metabolites in cardiometabolic health and translational research

The human gut microbiota is a functioning endocrine organ and stands at the intersection between dietary components and health or disease. There are very many microbial metabolites with numerous structures and functions arising from the gut microbial fermentation of foods and become signals for biological communication in the human body. These small molecules can be absorbed and delivered to distant organs through the circulatory system to build the gut–systemic axis. The gut microbial metabolomes are thus believed to play important roles in regulating cardiometabolic health and provide opportunities in mechanistic research and new drug discovery. Measurement of these novel microbial metabolites in clinical samples may serve as a tool for investigating disease biomarkers. In the past decade, the development of untargeted and targeted metabolomics approaches using NMR, LC/MS, and GC/MS has contributed to the exploration of gut microbial metabolomes in cardiometabolic health and disease. Some important targets are currently being translated into clinical applications. In this review article, we introduce an oral carnitine challenge test developed as an example to demonstrate the potential applications in personalized nutrition based on the function of gut microbiota. It is a method taking the gut microbiota as a bioreactor and provides fermentable materials as inputs and measures the outputs of targeted microbial byproducts in the blood or urine. This challenge test may be extended to measure metabolites from microbial fermentation related to other endocrinological or inflammatory diseases. We review current gut metabolome research approaches and propose a gut microbial functional measurement using a challenge test. We suggest that the maturation in measuring gut microbial metabolites may provide an important piece to complete the puzzle of precision medicine.     

Ultra-performance liquid chromatography coupled to mass spectrometry as a sensitive and powerful technology for metabolomic studies

Metabolomics is the comprehensive assessment of endogenous metabolites of a biological system. These large-scale analyses of metabolites are intimately bound to advancements in ultra-performance liquid chromatography-electrospray (UPLC) technologies and have emerged in parallel with the development of novel mass analyzers and hyphenated techniques. Recently, the combination of UPLC with MS covers a number of polar metabolites, thus enlarging the number of detected analytes in the widely used separation sciences. This technology has rapidly been accepted by the analytical community and is being gradually applied to various fields such as metabolomics and traditional Chinese medicine (TCM). Given the power of the technology, metabolomics has become increasingly popular in drug development, molecular medicine, traditional medicine and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. Hyphenated UPLC/MS technique is becoming a useful tool in the study of body fluids, represents a promising hyphenated microseparation platform in metabolomics and has a strong potential to contribute to disease diagnosis. This review describes the applications of UPLC/MS in metabolomic research, and comparison role of HPLC/MS, NMR and GC/MS, highlights its advantages and limitations with certain characteristic examples in the life and TCM sciences.     

纳米材料在用于癌症诊断的呼出气挥发性有机物检测中的应用

细胞新陈代谢的变化会导致挥发性有机化合物（VOCs）类型及含量发生变化,因此可通过分析某些标志性VOCs简立起多种疾病早期诊断的模型. 人体呼出物中特征VOCs的检测作为一种非侵入性、无损的检测手段,近些年在疾病检测领域已成为世界范围内的研究热点. 其中,纳米材料可用于增强传感器性能,并使传感器便携式小型化,推进检测传感器进入临床. 在这篇综述中,作者将种类繁多的传感器中用到的纳米材料归纳总结为金属、金属氧化物、碳基、复合物和MOFs基纳米材料等几类,并讨论了不同类纳米材料在VOCs检测中的优劣势. 本文所建立起的分析方法及讨论有助于进一步了解检测技术的优越性与局限性. 最后,作者对利用VOCs的检测实现癌症早期筛选的研究及发展提出了个人观点.