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1.
Jie Yang Jianhua Cheng Bo Sun Haijing Li Shengming Wu Fangting Dong Xianzhong Yan 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):40
Introduction
Hypoxia commonly occurs in cancers and is highly related with the occurrence, development and metastasis of cancer. Treatment of triple negative breast cancer remains challenge. Knowledge about the metabolic status of triple negative breast cancer cell lines in hypoxia is valuable for the understanding of molecular mechanisms of this tumor subtype to develop effective therapeutics.Objectives
Comprehensively characterize the metabolic profiles of triple negative breast cancer cell line MDA-MB-231 in normoxia and hypoxia and the pathways involved in metabolic changes in hypoxia.Methods
Differences in metabolic profiles affected pathways of MDA-MB-231 cells in normoxia and hypoxia were characterized using GC–MS based untargeted and stable isotope assisted metabolomic techniques.Results
Thirty-three metabolites were significantly changed in hypoxia and nine pathways were involved. Hypoxia increased glycolysis, inhibited TCA cycle, pentose phosphate pathway and pyruvate carboxylation, while increased glutaminolysis in MDA-MB-231 cells.Conclusion
The current results provide metabolic differences of MDA-MB-231 cells in normoxia and hypoxia conditions as well as the involved metabolic pathways, demonstrating the power of combined use of untargeted and stable isotope-assisted metabolomic methods in comprehensive metabolomic analysis.2.
Clara Pérez-Rambla Leonor Puchades-Carrasco María García-Flores José Rubio-Briones José Antonio López-Guerrero Antonio Pineda-Lucena 《Metabolomics : Official journal of the Metabolomic Society》2017,13(5):52
Introduction
Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.Objectives
In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.Methods
Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1H nuclear magnetic resonance (1H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.Results
The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.Conclusion
PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.3.
Dorothea Lesche Roland Geyer Daniel Lienhard Christos T. Nakas Gaëlle Diserens Peter Vermathen Alexander B. Leichtle 《Metabolomics : Official journal of the Metabolomic Society》2016,12(10):159
Background
Centrifugation is an indispensable procedure for plasma sample preparation, but applied conditions can vary between labs.Aim
Determine whether routinely used plasma centrifugation protocols (1500×g 10 min; 3000×g 5 min) influence non-targeted metabolomic analyses.Methods
Nuclear magnetic resonance spectroscopy (NMR) and High Resolution Mass Spectrometry (HRMS) data were evaluated with sparse partial least squares discriminant analyses and compared with cell count measurements.Results
Besides significant differences in platelet count, we identified substantial alterations in NMR and HRMS data related to the different centrifugation protocols.Conclusion
Already minor differences in plasma centrifugation can significantly influence metabolomic patterns and potentially bias metabolomics studies.4.
Anita Rácz Filip Andrić Dávid Bajusz Károly Héberger 《Metabolomics : Official journal of the Metabolomic Society》2018,14(3):29
Introduction
Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis.Objectives
The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles.Methods
Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates.Results
Baroni-Urbani–Buser (BUB) and Hawkins–Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis.Conclusion
Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.5.
Saleh Alseekh Luisa Bermudez Luis Alejandro de Haro Alisdair R. Fernie Fernando Carrari 《Metabolomics : Official journal of the Metabolomic Society》2018,14(11):148
Background
Until recently, plant metabolomics have provided a deep understanding on the metabolic regulation in individual plants as experimental units. The application of these techniques to agricultural systems subjected to more complex interactions is a step towards the implementation of translational metabolomics in crop breeding.Aim of Review
We present here a review paper discussing advances in the knowledge reached in the last years derived from the application of metabolomic techniques that evolved from biomarker discovery to improve crop yield and quality.Key Scientific Concepts of Review
Translational metabolomics applied to crop breeding programs.6.
Leigh Boardman Jesper G. Sørensen Vladimír Koštál Petr Šimek John S. Terblanche 《Metabolomics : Official journal of the Metabolomic Society》2016,12(12):176
Background
Insects are renowned for their ability to survive anoxia. Anoxia tolerance may be enhanced during chilling through metabolic suppression.Aims
Here, the metabolomic response of insects to anoxia, both with and without chilling, for different durations (12–36 h) was examined to assess the potential cross-tolerance mechanisms.Results
Chilling during anoxia (cold anoxia) significantly improved survival relative to anoxia at warmer temperatures. Reduced intermediate metabolites and increased lactic acid, indicating a switch to anaerobic metabolism, were characteristic of larvae in anoxia.Conclusions
Anoxia tolerance was correlated survival improvements after cold anoxia were correlated with a reduction in anaerobic metabolism.7.
Kayoko Yoshida Chiyo K. Imamura Kanako Hara Mayumi Mochizuki Yusuke Tanigawara 《Metabolomics : Official journal of the Metabolomic Society》2017,13(8):98
Introduction
Everolimus selectively inhibits mammalian target of rapamycin complex 1 (mTORC1) and exerts an antineoplastic effect. Metabolic disturbance has emerged as a common and unique side effect of everolimus.Objectives
We used targeted metabolomic analysis to investigate the effects of everolimus on the intracellular glycometabolic pathway.Methods
Mouse skeletal muscle cells (C2C12) were exposed to everolimus for 48 h, and changes in intracellular metabolites were determined by capillary electrophoresis time-of-flight mass spectrometry. mRNA abundance, protein expression and activity were measured for enzymes involved in glycometabolism and related pathways.Results
Both extracellular and intracellular glucose levels increased with exposure to everolimus. Most intracellular glycometabolites were decreased by everolimus, including those involved in glycolysis and the pentose phosphate pathway, whereas no changes were observed in the tricarboxylic acid cycle. Everolimus suppressed mRNA expression of enzymes related to glycolysis, downstream of mTOR signaling enzymes and adenosine 5′-monophosphate protein kinases. The activity of key enzymes involved in glycolysis and the pentose phosphate pathway were decreased by everolimus. These results show that everolimus impairs glucose utilization in intracellular metabolism.Conclusions
The present metabolomic analysis indicates that everolimus impairs glucose metabolism in muscle cells by lowering the activities of glycolysis and the pentose phosphate pathway.8.
Olga A. Snytnikova Lyudmila V. Yanshole Igor A. Iskakov Vadim V. Yanshole Valery V. Chernykh Denis A. Stepakov Vladimir P. Novoselov Yuri P. Tsentalovich 《Metabolomics : Official journal of the Metabolomic Society》2017,13(12):152
Introduction
Cornea is the outermost part of the eye supplied mostly by aqueous humor (AH). Therefore, the comparison of the metabolomic compositions of AH and cornea may help to determine which compounds are produced inside the cornea, and which penetrate into cornea from AH for intra-corneal consumption. Keratoconus (KC) is the most common form of the cornea dystrophy, and the analysis of KC corneas can unravel the metabolomic changes occurring in AH and cornea of KC patients.Objectives
The work is aimed at the determination of concentrations of a wide range of metabolites in the human cornea and AH, the comparison of the metabolomic profiles of cornea and AH, and the comparison of the metabolomic compositions of samples taken from KC patients and normal donors (post-mortem).Methods
The quantitative metabolomic profiling was carried out with the use of two independent methods—high-frequency 1H NMR spectroscopy and HPLC with high-resolution ESI-MS detection.Results
The concentrations of 71 most abundant metabolites in cornea and AH from keratoconus patients and from human cadavers have been measured. It is found that the concentrations of purines and organic acids in cornea are significantly higher than in AH. The KC corneas are characterized by the enhanced levels of acetate and citrate, and also by low values of GSH/GSSG ratios.Conclusion
A significant difference in the metabolomic compositions of the human AH and cornea has been revealed. The concentrations of glucose and some amino acids in cornea are significantly lower than in AH, indicating their fast consumption inside the cornea. The high levels of organic acids, purines and GSH in cornea should be attributed to their production in the cornea. The enhanced levels of acetate and citrate as well as the low values of GSH/GSSG ratios in KC corneas are the indicators of the oxidative stress.9.
Olga A. Snytnikova Anastasiya A. Khlichkina Lyudmila V. Yanshole Vadim V. Yanshole Igor A. Iskakov Elena V. Egorova Denis A. Stepakov Vladimir P. Novoselov Yuri P. Tsentalovich 《Metabolomics : Official journal of the Metabolomic Society》2017,13(1):5
Introduction
The optical elements of the eye—cornea, lens, and vitreous humor—are avascular tissues, and their nutrition and waste removal are provided by aqueous humor (AH). The AH production occurs through the active secretion and the passive diffusion/ultrafiltration of blood plasma. The comparison of the metabolomic profiles of AH and plasma is important for understanding of the mechanisms of biochemical processes and metabolite transport taking place in vivo in ocular tissues.Objectives
The work is aimed at the determination of concentrations of a wide range of most abundant metabolites in the human AH, the comparison of the metabolomic profiles of AH and serum, and the analysis of the post-mortem metabolomic changes in these two biological fluids.Methods
The quantitative metabolomic profiling was carried out with the use of two independent methods—high-frequency 1H NMR spectroscopy and HPLC with high-resolution ESI-MS detection.Results
The concentrations of 71 most abundant metabolites in blood serum and AH from living patients and human cadavers have been measured. It has been found that the level of ascorbate in AH is by two orders of magnitude higher than that in serum; the levels of other metabolites are either similar to that in serum, or differ from that by a factor of 2–5. The post-mortem metabolomic composition of both serum and AH undergoes rapid and strong changes.Conclusion
The differences between the metabolomic profiles of AH and serum for majority of metabolites can be attributed to the metabolic activity of the ocular tissues leading to the lack or excess of some metabolites, while the high concentration of ascorbate in AH demonstrates the activity of ascorbate-specific pumps at the blood-aqueous border. The post-mortem metabolomic changes are caused by the disruption of the major biochemical cycles and cell lysis. These changes should be taken into account in the analysis of disease-induced changes in post-mortem samples of the ocular tissues.10.
Applications of metabolomics in the study and management of preeclampsia: a review of the literature
Rachel S. Kelly Rachel T. Giorgio Bo L. Chawes Natalia I. Palacios Kathryn J. Gray Hooman Mirzakhani Ann Wu Kevin Blighe Scott T. Weiss Jessica Lasky-Su 《Metabolomics : Official journal of the Metabolomic Society》2017,13(7):86
Introduction
Preeclampsia represents a major public health burden worldwide, but predictive and diagnostic biomarkers are lacking. Metabolomics is emerging as a valuable approach to generating novel biomarkers whilst increasing the mechanistic understanding of this complex condition.Objectives
To summarize the published literature on the use of metabolomics as a tool to study preeclampsia.Methods
PubMed and Web of Science were searched for articles that performed metabolomic profiling of human biosamples using either Mass-spectrometry or Nuclear Magnetic Resonance based approaches and which included preeclampsia as a primary endpoint.Results
Twenty-eight studies investigating the metabolome of preeclampsia in a variety of biospecimens were identified. Individual metabolite and metabolite profiles were reported to have discriminatory ability to distinguish preeclamptic from normal pregnancies, both prior to and post diagnosis. Lipids and carnitines were among the most commonly reported metabolites. Further work and validation studies are required to demonstrate the utility of such metabolites as preeclampsia biomarkers.Conclusion
Metabolomic-based biomarkers of preeclampsia have yet to be integrated into routine clinical practice. However, metabolomic profiling is becoming increasingly popular in the study of preeclampsia and is likely to be a valuable tool to better understand the pathophysiology of this disorder and to better classify its subtypes, particularly when integrated with other omic data.11.
Antonella Del-Corso Mario Cappiello Roberta Moschini Francesco Balestri Umberto Mura 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):2
Introduction
While the evolutionary adaptation of enzymes to their own substrates is a well assessed and rationalized field, how molecules have been originally selected in order to initiate and assemble convenient metabolic pathways is a fascinating, but still debated argument.Objectives
Aim of the present study is to give a rationale for the preferential selection of specific molecules to generate metabolic pathways.Methods
The comparison of structural features of molecules, through an inductive methodological approach, offer a reading key to cautiously propose a determining factor for their metabolic recruitment.Results
Starting with some commonplaces occurring in the structural representation of relevant carbohydrates, such as glucose, fructose and ribose, arguments are presented in associating stable structural determinants of these molecules and their peculiar occurrence in metabolic pathways.Conclusions
Among other possible factors, the reliability of the structural asset of a molecule may be relevant or its selection among structurally and, a priori, functionally similar molecules.12.
Justin J. J. van der Hooft Sandosh Padmanabhan Karl E. V. Burgess Michael P. Barrett 《Metabolomics : Official journal of the Metabolomic Society》2016,12(7):125
Introduction
Mass spectrometry is the current technique of choice in studying drug metabolism. High-resolution mass spectrometry in combination with MS/MS gas-phase experiments has the potential to contribute to rapid advances in this field. However, the data emerging from such fragmentation spectral files pose challenges to downstream analysis, given their complexity and size.Objectives
This study aims to detect and visualize antihypertensive drug metabolites in untargeted metabolomics experiments based on the spectral similarity of their fragmentation spectra. Furthermore, spectral clusters of endogenous metabolites were also examined.Methods
Here we apply a molecular networking approach to seek drugs and their metabolites, in fragmentation spectra from urine derived from a cohort of 26 patients on antihypertensive therapy. The mass spectrometry data was collected on a Thermo Q-Exactive coupled to pHILIC chromatography using data dependent analysis (DDA) MS/MS gas-phase experiments.Results
In total, 165 separate drug metabolites were found and structurally annotated (17 by spectral matching and 122 by classification based on a clustered fragmentation pattern). The clusters could be traced to 13 drugs including the known antihypertensives verapamil, losartan and amlodipine. The molecular networking approach also generated clusters of endogenous metabolites, including carnitine derivatives, and conjugates containing glutamine, glutamate and trigonelline.Conclusions
The approach offers unprecedented capability in the untargeted identification of drugs and their metabolites at the population level and has great potential to contribute to understanding stratified responses to drugs where differences in drug metabolism may determine treatment outcome.13.
Wanlan Wang Kian-Kai Cheng Lingli Deng Jingjing Xu Guiping Shen Julian L. Griffin Jiyang Dong 《Metabolomics : Official journal of the Metabolomic Society》2017,13(1):10
Introduction
The metabolome of a biological system is affected by multiple factors including factor of interest (e.g. metabolic perturbation due to disease) and unwanted factors or factors which are not primarily the focus of the study (e.g. batch effect, gender, and level of physical activity). Removal of these unwanted data variations is advantageous, as the unwanted variations may complicate biological interpretation of the data.Objectives
We aim to develop a new unwanted variations elimination (UVE) method called clustering-based unwanted residuals elimination (CURE) to reduce metabolic variation caused by unwanted/hidden factors in metabolomic data.Methods
A mean-centered metabolomic dataset can be viewed as a combination of a studied factor matrix and a residual matrix. The CURE method assumes that the residual should be normally distributed if it only contains inter-individual variation. However, if the residual forms multiple clusters in feature subspace of principal components analysis or partial least squares discriminant analysis, the residual may contain variation due to unwanted factors. This unwanted variation is removed by doing K-means data clustering and removal of means for each cluster from the residuals. The process is iterated until the residual no longer forms multiple clusters in feature subspace.Results
Three simulated datasets and a human metabolomic dataset were used to demonstrate the performance of the proposed CURE method. CURE was found able to remove most of the variations caused by unwanted factors, while preserving inter-individual variation between samples.Conclusion
The CURE method can effectively remove unwanted data variation, and can serve as an alternative UVE method for metabolomic data.14.
Ekaterina A. Zelentsova Lyudmila V. Yanshole Olga A. Snytnikova Vadim V. Yanshole Yuri P. Tsentalovich Renad Z. Sagdeev 《Metabolomics : Official journal of the Metabolomic Society》2016,12(11):172
Introduction
The analysis of post-mortem metabolomic changes in biological fluids opens the way to develop new methods for the estimation of post-mortem interval (PMI). It may also help in the analysis of disease-induced metabolomic changes in human tissues when the postoperational samples are compared to the post-mortem samples from healthy donors.Objectives
The goals of this study are to observe and classify the post-mortem changes occurring in the rabbit blood, aqueous and vitreous humors (AH and VH), to identify the potential PMI markers among a wide range of metabolites, and also to determine which biological fluid—blood, AH or VH—is more suitable for the PMI estimation.Methods
The quantitative metabolomic profiling of samples of the rabbit serum, AH and VH taken at different PMIs has been performed with the combined use of high-frequency NMR and high-resolution LC–MS methods.Results
The quantitative levels of 61 metabolites in the rabbit serum, AH and VH at different PMIs have been measured. It has been found that the post-mortem metabolomic changes in AH and VH proceed slower than in blood, and the data scattering is lower. Among the metabolites whose concentrations increase with time, the most significant and linear growth is found for hypoxanthine, choline and glycerol.Conclusion
The obtained results suggest that the ocular fluids AH and VH may have some advantages over blood serum for the search of potential biochemical markers for the PMI estimation. Among the compounds studied in the present work, hypoxanthine, choline and glycerol give the biggest promise as the potential PMI biomarkers.15.
Miriam Reverter Marie-Aude Tribalat Thierry Pérez Olivier P. Thomas 《Metabolomics : Official journal of the Metabolomic Society》2018,14(9):114
Introduction
The study of natural variation of metabolites brings valuable information on the physiological state of the organisms as well as their phenotypic traits. In marine organisms, metabolome variability has mostly been addressed through targeted studies on metabolites of ecological or pharmaceutical interest. However, comparative metabolomics has demonstrated its potential to address the overall and complex metabolic variability of organisms.Objectives
In this study, the intraspecific (temporal and spatial) variability of two Mediterranean Haliclona sponges (H. fulva and H. mucosa) was investigated through an untargeted and then targeted metabolomics approach and further compared to their interspecific variability.Methods
Samples of both species were collected monthly during 1 year in the coralligenous habitat of the Northwestern Mediterranean sae at Marseille and Nice. Their metabolomic profiles were obtained by UHPLC-QqToF analyses.Results
Marked variations were noticed in April and May for both species including a decrease in Shannon’s diversity and concentration in specialized metabolites together with an increase in fatty acids and lyso-PAF like molecules. Spatial variations across different sampling sites could also be observed for both species, however in a lesser extent.Conclusions
Synchronous metabolic changes possibly triggered by physiological factors like reproduction and/or environmental factors like an increase in the water temperature were highlighted for both Mediterranean Haliclona species inhabiting close habitats but displaying different biosynthetic pathways. Despite significative intraspecific variations, metabolomic variability remains minor when compared to interspecific variations for these congenerous species, therefore suggesting the predominance of genetic information of the holobiont in the observed metabolome.16.
Daniel Cañueto Josep Gómez Reza M. Salek Xavier Correig Nicolau Cañellas 《Metabolomics : Official journal of the Metabolomic Society》2018,14(3):24
Introduction
Adoption of automatic profiling tools for 1H-NMR-based metabolomic studies still lags behind other approaches in the absence of the flexibility and interactivity necessary to adapt to the properties of study data sets of complex matrices.Objectives
To provide an open source tool that fully integrates these needs and enables the reproducibility of the profiling process.Methods
rDolphin incorporates novel techniques to optimize exploratory analysis, metabolite identification, and validation of profiling output quality.Results
The information and quality achieved in two public datasets of complex matrices are maximized.Conclusion
rDolphin is an open-source R package (http://github.com/danielcanueto/rDolphin) able to provide the best balance between accuracy, reproducibility and ease of use.17.
Justine Chervin Pierre Perio Nathalie Martins-Froment Chiobouaphong Pharkeovilay Karine Reybier Françoise Nepveu Nicolas Fabre Thierry Talou Valérie Bonzon-Ponnet Guillaume Marti 《Metabolomics : Official journal of the Metabolomic Society》2017,13(8):96
Introduction
In natural product research, bioassay-guided fractionation was previously widely employed but is now judged to be inadequate in terms of time and cost, particularly if only known compounds are ultimately isolated. The development of metabolomics, along with improvements in analytical tools, allows comprehensive metabolite profiling. This enables dereplication to target unknown active compounds early in the purification workflow.Objectives
Starting from an ethanolic extract of violet leaves, this study aims to predict redox active compounds within a complex matrix through an untargeted metabolomics approach and correlation analysis.Methods
Rapid fractionation of crude extracts was carried out followed by multivariate data analysis (MVA) of liquid chromatography–high resolution mass spectrometry (LC–HRMS) profiles. In parallel, redox active properties were evaluated by the capacity of the molecules to reduce 2,2-diphenyl-1-picrylhydrazyl (DPPH·) and superoxide (O2 ·?) radicals using UV–Vis and electron spin resonance spectroscopies (ESR), respectively. A spectral similarity network (molecular networking) was used to highlight clusters involved in the observed redox activities.Results
Dereplication on Viola alba subsp. dehnhardtii highlighted a reproducible pool of redox active molecules. Polyphenols, particularly O-glycosylated coumarins and C-glycosylated flavonoids, were identified and de novo dereplicated through molecular networking. Confirmatory analyses were undertaken by thin layer chromatography (TLC)–DPPH–MS assays and nuclear magnetic resonance (NMR) spectra of the most active compounds.Conclusion
Our dereplication strategy allowed the screening of leaf extracts to highlight new biologically active metabolites in few steps with a limited amount of crude material and reduced time-consuming manipulations. This approach could be applied to any kind of natural extract for the study of various biological activities.18.
Fan Zhang Yuanyuan Zhang Chaofu Ke Ang Li Wenjie Wang Kai Yang Huijuan Liu Hongyu Xie Kui Deng Weiwei Zhao Chunyan Yang Ge Lou Yan Hou Kang Li 《Metabolomics : Official journal of the Metabolomic Society》2018,14(5):65
Background
Previous metabolomic studies have revealed that plasma metabolic signatures may predict epithelial ovarian cancer (EOC) recurrence. However, few studies have performed metabolic profiling of pre- and post-operative specimens to investigate EOC prognostic biomarkers.Objective
The aims of our study were to compare the predictive performance of pre- and post-operative specimens and to create a better model for recurrence by combining biomarkers from both metabolic signatures.Methods
Thirty-five paired plasma samples were collected from 35 EOC patients before and after surgery. The patients were followed-up until December, 2016 to obtain recurrence information. Metabolomics using rapid resolution liquid chromatography–mass spectrometry was performed to identify metabolic signatures related to EOC recurrence. The support vector machine model was employed to predict EOC recurrence using identified biomarkers.Results
Global metabolomic profiles distinguished recurrent from non-recurrent EOC using both pre- and post-operative plasma. Ten common significant biomarkers, hydroxyphenyllactic acid, uric acid, creatinine, lysine, 3-(3,5-diiodo-4-hydroxyphenyl) lactate, phosphohydroxypyruvic acid, carnitine, coproporphyrinogen, l-beta-aspartyl-l-glutamic acid and 24,25-hydroxyvitamin D3, were identified as predictive biomarkers for EOC recurrence. The area under the receiver operating characteristic (AUC) values in pre- and post-operative plasma were 0.815 and 0.909, respectively; the AUC value after combining the two sets reached 0.964.Conclusion
Plasma metabolomic analysis could be used to predict EOC recurrence. While post-operative biomarkers have a predictive advantage over pre-operative biomarkers, combining pre- and post-operative biomarkers showed the best predictive performance and has great potential for predicting recurrent EOC.19.
Wei-Wei Li Yan Yang Qi-Gang Dai Li-Li Lin Tong Xie Li-Li He Jia-Lei Tao Jin-Jun Shan Shou-Chuan Wang 《Metabolomics : Official journal of the Metabolomic Society》2018,14(7):90
Introduction
Neonatal cholestatic disorders are a group of hepatobiliary diseases occurring in the first 3 months of life. The most common causes of neonatal cholestasis are infantile hepatitis syndrome (IHS) and biliary atresia (BA). The clinical manifestations of the two diseases are too similar to distinguish them. However, early detection is very important in improving the clinical outcome of BA. Currently, a liver biopsy is the only proven and effective method used to differentially diagnose these two similar diseases in the clinic. However, this method is invasive. Therefore, sensitive and non-invasive biomarkers are needed to effectively differentiate between BA and IHS. We hypothesized that urinary metabolomics can produce unique metabolite profiles for BA and IHS.Objectives
The aim of this study was to characterize urinary metabolomic profiles in infants with BA and IHS, and to identify differences among infants with BA, IHS, and normal controls (NC).Methods
Urine samples along with patient characteristics were obtained from 25 BA, 38 IHS, and 38 NC infants. A non-targeted gas chromatography–mass spectrometry (GC–MS) metabolomics method was used in conjunction with orthogonal partial least squares discriminant analysis (OPLS-DA) to explore the metabolomic profiles of BA, IHS, and NC infants.Results
In total, 41 differentially expressed metabolites between BA vs. NC, IHS vs. NC, and BA vs. IHS were identified. N-acetyl-d-mannosamine and alpha-aminoadipic acid were found to be highly accurate at distinguishing between BA and IHS.Conclusions
BA and IHS infants have specific urinary metabolomic profiles. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be used to discriminate BA from IHS.20.
Fernanda Bertuccez Cordeiro Thais Regiani Cataldi Lívia do Vale Teixeira da Costa Beatriz Zappellini de Souza Daniela Antunes Montani Renato Fraietta Carlos Alberto Labate Agnaldo Pereira Cedenho Edson Guimarães Lo Turco 《Metabolomics : Official journal of the Metabolomic Society》2017,13(10):120