NMR-based metabolomics approach to target biomarkers for human prostate cancer

In the era of genomics and proteomics, metabolomics offers a unique way to probe the underlying biochemistry of malignant transformations. In the context of oncological metabolomics, the study of the global variation of metabolites involved in the development and progression of cancers, few existing techniques offer as much potential to discover biomarkers as nuclear magnetic resonance techniques. The most fundamental magnetic resonance methodologies with regard to human prostate cancer are magnetic resonance spectroscopy and magnetic resonance spectroscopic imaging. Recent in vivo explorations have examined crucial metabolites that may indicate cancerous lesions and have the potential to direct treatment; while ex vivo studies of prostatic fluids and tissues have defined novel diagnostic parameters and indicated that magnetic resonance methodologies will be paramount in future prostate cancer management.     

Metabolomic profiling reveals bacterial metabolic adaptation strategies and new metabolites

How has metabolomics helped our understanding of infectious diseases? With the threat of antimicrobial resistance to human health around the world, metabolomics has emerged as a powerful tool to comprehensively characterize metabolic pathways to identify new drug targets. However, its output is constrained to known metabolites and their metabolic pathways. Recent advances in instrumentation, methodologies, and computational mass spectrometry have accelerated the use of metabolomics to understand pathogen–host metabolic interactions. This short review discusses a selection of recent publications using metabolomics in infectious/bacterial diseases. These studies unravel the links between metabolic adaptations to environments and host metabolic responses. Moreover, they highlight the importance of enzyme function and metabolite characterization in identifying new drug targets and biomarkers, as well as precision medicine in monitoring therapeutics and diagnosing diseases.     

Ingenuity pathways analysis of urine metabolomics phenotypes toxicity of Chuanwu in Wistar rats by UPLC-Q-TOF-HDMS coupled with pattern recognition methods

Chuanwu (CW), a valuable traditional Chinese medicine (TCM), is the mother root of Aconitum carmichaelii Debx. The cause of CW-induced toxicity is still under ongoing research, although this is limited by the lack of sensitive and reliable biomarkers. Ingenuity pathway analysis (IPA) was performed to analyzing global metabolomics in order to characterize the phenotypically biochemical perturbations and potential mechanisms of the CW-induced toxicity. CW was administered to Wistar rats (0.027 g/200 g and 0.108 g/200 g bw, oral) for 6 months and urine samples were collected. The urinary metabolomics was performed by UPLC-Q-TOF-HDMS, and the mass spectra signals of the detected metabolites were systematically deconvoluted and analyzed by pattern recognition methods (PCA, PLS-DA, and OPLS-DA), revealing a time- and dose-dependency of the biochemical perturbations induced by CW toxicity. As a result, several metabolites responsible for pentose and glucuronate interconversions, alanine, aspartate and glutamate metabolism, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, purine metabolism, tryptophan metabolism, taurine and hypotaurine metabolism, fructose and mannose metabolism, fatty acid metabolism were characterized, and it was confirmed that biochemical perturbations can be foreseen from these biomarkers. The urinary metabolomics based IPA with pattern recognition methods also revealed that CW produced serious heart and liver toxicity, consistent with clinical biochemistry and histopathology. Significant changes of 17 metabolites were identified and validated as phenotypic biomarkers of CW toxicity. Overall, our work demonstrated the metabolomics has brought enormous opportunities for improved detection of toxicity and biomarker discovery, highlighting the powerful predictive potential of the IPA to study of drug toxicity.     

Metabolomics through the lens of precision cardiovascular medicine

Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular,metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed: 1) the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2) the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed.     

NMR-based metabolomics approach to target biomarkers for human prostate cancer

In the era of genomics and proteomics, metabolomics offers a unique way to probe the underlying biochemistry of malignant transformations. In the context of oncological metabolomics, the study of the global variation of metabolites involved in the development and progression of cancers, few existing techniques offer as much potential to discover biomarkers as nuclear magnetic resonance techniques. The most fundamental magnetic resonance methodologies with regard to human prostate cancer are magnetic resonance spectroscopy and magnetic resonance spectroscopic imaging. Recent in vivo explorations have examined crucial metabolites that may indicate cancerous lesions and have the potential to direct treatment; while ex vivo studies of prostatic fluids and tissues have defined novel diagnostic parameters and indicated that magnetic resonance methodologies will be paramount in future prostate cancer management.     

Serum metabonomics study of pregnant women with gestational diabetes mellitus based on LC-MS

ObjectiveThrough metabolomics method, the objective of the paper is to differentially screen serum metabolites of GDM patients and healthy pregnant women, to explore potential biomarkers of GDM and analyze related pathways, and to explain the potential mechanism and biological significance of GDM.MethodsThe serum samples from 30 GDM patients and 30 healthy pregnant women were selected to conduct non-targeted metabolomics study by liquid chromatography-mass spectrometry. The differential metabolites between the two groups were searched and the metabolic pathway was analyzed by KEGG database.ResultsMultivariate statistical analysis found that serum metabolism in GDM patients was different significantly from healthy pregnant women, 36 differential metabolites and corresponding metabolic pathways were identified in serum, which involved several metabolic ways like, fatty acid metabolism, butyric acid metabolism, bile secretion, and amino acid metabolism.ConclusionThe discovery of these biomarkers provided a new theoretical basis and experimental basis for further study of the early diagnosis and pathogenesis of GDM. At the same time, LC-MS-based serum metabolomics methods also showed great application values in disease diagnosis and mechanism research.     

Multimodal biomarker discovery for active Onchocerca volvulus infection

The neglected tropical disease onchocerciasis, or river blindness, is caused by infection with the filarial nematode Onchocerca volvulus. Current estimates indicate that 17 million people are infected worldwide, the majority of them living in Africa. Today there are no non-invasive tests available that can detect ongoing infection, and that can be used for effective monitoring of elimination programs. In addition, to enable pharmacodynamic studies with novel macrofilaricide drug candidates, surrogate endpoints and efficacy biomarkers are needed but are non-existent. We describe the use of a multimodal untargeted mass spectrometry-based approach (metabolomics and lipidomics) to identify onchocerciasis-associated metabolites in urine and plasma, and of specific lipid features in plasma of infected individuals (O. volvulus infected cases: 68 individuals with palpable nodules; lymphatic filariasis cases: 8 individuals; non-endemic controls: 20 individuals). This work resulted in the identification of elevated concentrations of the plasma metabolites inosine and hypoxanthine as biomarkers for filarial infection, and of the urine metabolite cis-cinnamoylglycine (CCG) as biomarker for O. volvulus. During the targeted validation study, metabolite-specific cutoffs were determined (inosine: 34.2 ng/ml; hypoxanthine: 1380 ng/ml; CCG: 29.7 ng/ml) and sensitivity and specificity profiles were established. Subsequent evaluation of these biomarkers in a non-endemic population from a different geographical region invalidated the urine metabolite CCG as biomarker for O. volvulus. The plasma metabolites inosine and hypoxanthine were confirmed as biomarkers for filarial infection. With the availability of targeted LC-MS procedures, the full potential of these 2 biomarkers in macrofilaricide clinical trials, MDA efficacy surveys, and epidemiological transmission studies can be investigated.     

Metabolomic-based clinical studies and murine models for acute pancreatitis disease: A review

Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.     

Untargeted metabolomics: an overview of its usefulness and future potential in prenatal diagnosis

ABSTRACT

Introduction: Metabolomics opens up new avenues for biomarker discovery in different branches of medicine, including perinatology. Chromosomal aberration, preterm delivery (PTD), congenital heart defects, spina bifida, chorioamnionitis, and low birth weight are the main perinatal pathologies. Investigations using untargeted metabolomics have found the candidate metabolites for diagnostic biomarkers.

Areas covered: This review describes areas of prenatal diagnosis in which untargeted metabolomics has been used. Data on the disease, type of sample, techniques used, number of samples used in the study, and metabolites obtained including the sign of their regulation are summarized.

Expert commentary: Untargeted metabolomics is a powerful tool which can shed a new light on prenatal diagnostics. It helps to discover affected metabolic pathways what may help to reveal disease pathogenesis and propose potential biomarkers. Among others, glycerol and 2- and 3-hydroxybutyrate were proposed as markers of chromosomal aberration. Serum metabolic signature of PTD was characterized by increased lipids and decreased levels of hypoxanthine, tryptophane, and pyroglutamic acid. Lower level lipids and vitamin D3 metabolites together with increased bilirubin level in maternal serum were associated with macrosomia. However, to give a real value to those assays and allow their clinical application multicenter, large cohort validation studies are necessary.     

Metabolomics, pathway regulation, and pathway discovery

Metabolomics is a data-based research strategy, the aims of which are to identify biomarker pictures of metabolic systems and metabolic perturbations and to formulate hypotheses to be tested. It involves the assay by mass spectrometry or NMR of many metabolites present in the biological system investigated. In this minireview, we outline studies in which metabolomics led to useful biomarkers of metabolic processes. We also illustrate how the discovery potential of metabolomics is enhanced by associating it with stable isotopic techniques.     

Phospholipid capture combined with non-linear chromatographic correction for improved serum metabolite profiling

Serum analysis with LC/MS can yield thousands of potential metabolites. However, in metabolomics, biomarkers of interest will often be of low abundance, and ionization suppression from high abundance endogenous metabolites such as phospholipids may prevent the detection of these metabolites. Here a cerium-modified column and methyl-tert-butyl-ether (MTBE) liquid–liquid extraction were employed to remove phospholipids from serum in order to obtain a more comprehensive metabolite profile. XCMS, an in-house developed data analysis software platform, showed that the intensity of existing endogenous metabolites increased, and that new metabolites were observed. This application of phospholipid capture in combination with XCMS non-linear data processing has enormous potential in metabolite profiling, for biomarker detection and quantitation.     

Integration of pharmacometabolomics with pharmacokinetics and pharmacodynamics: towards personalized drug therapy

Personalized medicine, in modern drug therapy, aims at a tailored drug treatment accounting for inter-individual variations in drug pharmacology to treat individuals effectively and safely. The inter-individual variability in drug response upon drug administration is caused by the interplay between drug pharmacology and the patients’ (patho)physiological status. Individual variations in (patho)physiological status may result from genetic polymorphisms, environmental factors (including current/past treatments), demographic characteristics, and disease related factors. Identification and quantification of predictors of inter-individual variability in drug pharmacology is necessary to achieve personalized medicine. Here, we highlight the potential of pharmacometabolomics in prospectively informing on the inter-individual differences in drug pharmacology, including both pharmacokinetic (PK) and pharmacodynamic (PD) processes, and thereby guiding drug selection and drug dosing. This review focusses on the pharmacometabolomics studies that have additional value on top of the conventional covariates in predicting drug PK. Additionally, employing pharmacometabolomics to predict drug PD is highlighted, and we suggest not only considering the endogenous metabolites as static variables but to include also drug dose and temporal changes in drug concentration in these studies. Although there are many endogenous metabolite biomarkers identified to predict PK and more often to predict PD, validation of these biomarkers in terms of specificity, sensitivity, reproducibility and clinical relevance is highly important. Furthermore, the application of these identified biomarkers in routine clinical practice deserves notable attention to truly personalize drug treatment in the near future.     

Urine metabolomics analysis for biomarker discovery and detection of jaundice syndrome in patients with liver disease

Metabolomics is a powerful new technology that allows for the assessment of global metabolic profiles in easily accessible biofluids and biomarker discovery in order to distinguish between diseased and nondiseased status information. Deciphering the molecular networks that distinguish diseases may lead to the identification of critical biomarkers for disease aggressiveness. However, current diagnostic methods cannot predict typical Jaundice syndrome (JS) in patients with liver disease and little is known about the global metabolomic alterations that characterize JS progression. Emerging metabolomics provides a powerful platform for discovering novel biomarkers and biochemical pathways to improve diagnostic, prognostication, and therapy. Therefore, the aim of this study is to find the potential biomarkers from JS disease by using a nontarget metabolomics method, and test their usefulness in human JS diagnosis. Multivariate data analysis methods were utilized to identify the potential biomarkers. Interestingly, 44 marker metabolites contributing to the complete separation of JS from matched healthy controls were identified. Metabolic pathways (Impact-value≥0.10) including alanine, aspartate, and glutamate metabolism and synthesis and degradation of ketone bodies were found to be disturbed in JS patients. This study demonstrates the possibilities of metabolomics as a diagnostic tool in diseases and provides new insight into pathophysiologic mechanisms.     

功能代谢组学技术在微生物研究中的应用

功能代谢组学是以代谢组学技术发现关键代谢物为基础,结合体内体外实验和分子生物学等技术手段,研究差异代谢物及相关蛋白、酶和基因的功能,从而揭示生物体内在的分子调控机制。功能代谢组学技术具有精准识别关键调控代谢物及其相关基因或酶的特性,近年来在微生物相关疾病的防控和工业化生产等方面受到了广泛的关注。本文介绍了功能代谢组学技术的分析流程、相关研究方法与平台及其在微生物研究方面的应用,其中重点阐述了真核、原核以及病毒微生物的代谢特性、调控靶点及相关防控策略等。最后,提出功能代谢组学研究在未来面临的问题与挑战,为后续功能代谢组学的研究与发展提供新的思路。     

荷瘤抑郁样模型小鼠的血清代谢组学研究

目的：从代谢组学角度开展肿瘤共病抑郁的研究,将在复杂疾病发生发展机制以及药物治疗新靶点方面做出有益探索。本实验采用代谢组学方法检测荷瘤抑郁样模型小鼠血清小分子代谢物的变化及抗抑郁药氟西汀的影响,探讨代谢组学在肿瘤共病抑郁研究中的应用。方法：制备移植性荷瘤小鼠模型,氟西汀处理组对荷瘤小鼠连续28d灌胃给药,观察各组行为学反应。采用液相色谱串联四级杆飞行时间质谱（LC—QToF／MS）获取荷瘤小鼠与正常小鼠的血清代谢轮廓,并用正交信号校正的偏最小二乘法（OPLS）进行多元统计分析,结合单维水平筛选结果,得到荷瘤小鼠区别于正常对照小鼠的特征性差异代谢物,并观察氟西汀对上述代谢物的影响。结果：行为学反应结果显示,与正常小鼠相比,荷瘤小鼠表现抑郁相关性行为改变,氟西汀对荷瘤引起的行为学变化有显著改善作用。代谢组学分析结果显示,荷瘤小鼠血清中乙酰肉碱和油酰胺的含量较正常小鼠显著降低,氟西汀处理后可增加荷瘤小鼠血清中的乙酰肉碱和油酰胺的含量。结论：基于代谢组学分析得到的特征性代谢产物的下调可能与荷瘤小鼠的抑郁样状态有关,氟西汀对这两种潜在生物标志物有明显的调节作用。代谢组学研究为疾病特异性生物标志物的筛选及药物药效的评价提供了新的思路与方法。     

Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis

The aim of this study is to find the potential biomarkers from the rat hepatocellular carcinoma (HCC) disease model by using a non-target metabolomics method, and test their usefulness in early human HCC diagnosis. The serum metabolic profiling of the diethylnitrosamine-induced rat HCC model, which presents a stepwise histopathological progression that is similar to human HCC, was performed using liquid chromatography-mass spectrometry. Multivariate data analysis methods were utilized to identify the potential biomarkers. Three metabolites, taurocholic acid, lysophosphoethanolamine 16:0, and lysophosphatidylcholine 22:5, were defined as "marker metabolites," which can be used to distinguish the different stages of chemical hepatocarcinogenesis. These metabolites represented the abnormal metabolism during the progress of hepatocarcinogenesis, which could also be found in patients. To test their diagnosis potential 412 sera from 262 patients with HCC, 76 patients with cirrhosis and 74 patients with chronic hepatitis B were collected and studied, it was found that 3 marker metabolites were effective for the discrimination of small liver tumor (solitary nodules of less than 2 cm in diameter) patients, achieved a sensitivity of 80.5% and a specificity of 80.1%,which is better than those of α-fetoprotein (53 and 64%, respectively). Moreover, they were also effective for the discrimination of all HCCs and chronic liver disease patients, which could achieve a sensitivity of 87.5% and a specificity of 72.3%, better than those of α-fetoprotein (61.2 and 64%). These results indicate metabolomics method has the potential of finding biomarkers for the early diagnosis of HCC.