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1.
Hailong Zhang Longzhen Cui Wen Liu Zhenfeng Wang Yang Ye Xue Li Huijuan Wang 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):47
Introduction
Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients.Objectives
We performed 1H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC.Methods
1H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n?=?40), LNM-negative GC patients (n?=?40) and normal controls (n?=?40).Results
There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM.Conclusion
To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC.2.
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.3.
Introduction
Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.Objectives
Assessment of the quality of raw data processing in untargeted metabolomics.Methods
Five published untargeted metabolomics studies, were reanalyzed.Results
Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.Conclusion
Incomplete raw data processing shows unexplored potential of current and legacy data.4.
Zrinka Raguz Nakic Gerhard Seisenbacher Francesc Posas Uwe Sauer 《BMC systems biology》2015,10(1):104
Background
Coordinated through a complex network of kinases and phosphatases, protein phosphorylation regulates essentially all cellular processes in eukaryotes. Recent advances in proteomics enable detection of thousands of phosphorylation sites (phosphosites) in single experiments. However, functionality of the vast majority of these sites remains unclear and we lack suitable approaches to evaluate functional relevance at a pace that matches their detection.Results
Here, we assess functionality of 26 phosphosites by introducing phosphodeletion and phosphomimic mutations in 25 metabolic enzymes and regulators from the TOR and HOG signaling pathway in Saccharomyces cerevisiae by phenotypic analysis and untargeted metabolomics. We show that metabolomics largely outperforms growth analysis and recovers 10 out of the 13 previously characterized phosphosites and suggests functionality for several novel sites, including S79 on the TOR regulatory protein Tip41. We analyze metabolic profiles to identify consequences underlying regulatory phosphorylation events and detecting glycerol metabolism to have a so far unknown influence on arginine metabolism via phosphoregulation of the glycerol dehydrogenases. Further, we also find S508 in the MAPKK Pbs2 as a potential link for cross-talking between HOG signaling and the cell wall integrity pathway.Conclusions
We demonstrate that metabolic profiles can be exploited for gaining insight into regulatory consequences and biological roles of phosphosites. Altogether, untargeted metabolomics is a fast, sensitive and informative approach appropriate for future large-scale functional analyses of phosphosites.5.
Patrick J. C. Tardivel Cécile Canlet Gaëlle Lefort Marie Tremblay-Franco Laurent Debrauwer Didier Concordet Rémi Servien 《Metabolomics : Official journal of the Metabolomic Society》2017,13(10):109
Introduction
Experiments in metabolomics rely on the identification and quantification of metabolites in complex biological mixtures. This remains one of the major challenges in NMR/mass spectrometry analysis of metabolic profiles. These features are mandatory to make metabolomics asserting a general approach to test a priori formulated hypotheses on the basis of exhaustive metabolome characterization rather than an exploratory tool dealing with unknown metabolic features.Objectives
In this article we propose a method, named ASICS, based on a strong statistical theory that handles automatically the metabolites identification and quantification in proton NMR spectra.Methods
A statistical linear model is built to explain a complex spectrum using a library containing pure metabolite spectra. This model can handle local or global chemical shift variations due to experimental conditions using a warping function. A statistical lasso-type estimator identifies and quantifies the metabolites in the complex spectrum. This estimator shows good statistical properties and handles peak overlapping issues.Results
The performances of the method were investigated on known mixtures (such as synthetic urine) and on plasma datasets from duck and human. Results show noteworthy performances, outperforming current existing methods.Conclusion
ASICS is a completely automated procedure to identify and quantify metabolites in 1H NMR spectra of biological mixtures. It will enable empowering NMR-based metabolomics by quickly and accurately helping experts to obtain metabolic profiles.6.
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.7.
Yanhui Ge Mengmeng Sun Luis F. Salomé-Abarca Mei Wang Young Hae Choi 《Metabolomics : Official journal of the Metabolomic Society》2018,14(10):137
Introduction
The pharmacological activities of medicinal plants are reported to be due to a wide range of metabolites, therein, the concentrations of which are greatly affected by many genetic and/or environmental factors. In this context, a metabolomics approach has been applied to reveal these relationships. The investigation of such complex networks that involve the correlation between multiple biotic and abiotic factors and the metabolome, requires the input of information acquired by more than one analytical platform. Thus, development of new metabolomics techniques or hyphenations is continuously needed.Objectives
Feasibility of high performance thin-layer chromatography (HPTLC) were investigated as a supplementary tool for medicinal plants metabolomics supporting 1H nuclear magnetic resonance (1H NMR) spectroscopy.Method
The overall metabolic difference of plant material collected from two species (Rheum palmatum and Rheum tanguticum) in different geographical locations and altitudes were analyzed by 1H NMR- and HPTLC-based metabolic profiling. Both NMR and HPTLC data were submitted to multivariate data analysis including principal component analysis and orthogonal partial least square analysis.Results
The NMR and HPTLC profiles showed that while chemical variations of rhubarb are in some degree affected by all the factors tested in this study, the most influential factor was altitude of growth. The metabolites responsible for altitude differentiation were chrysophanol, emodin and sennoside A, whereas aloe emodin, catechin, and rhein were the key species-specific markers.Conclusion
These results demonstrated the potential of HTPLC as a supporting tool for metabolomics due to its high profiling capacity of targeted metabolic groups and preparative capability.8.
Tie-juan Shao Zhi-xing He Zhi-jun Xie Hai-chang Li Mei-jiao Wang Cheng-ping Wen 《Metabolomics : Official journal of the Metabolomic Society》2016,12(4):70
Introduction
The differences in fecal metabolome between ankylosing spondylitis (AS)/rheumatoid arthritis (RA) patients and healthy individuals could be the reason for an autoimmune disorder.Objectives
The study explored the fecal metabolome difference between AS/RA patients and healthy controls to clarify human immune disturbance.Methods
Fecal samples from 109 individuals (healthy controls 34, AS 40, and RA 35) were analyzed by 1H NMR spectroscopy. Data were analyzed with principal component analysis (PCA) and orthogonal projection to latent structure discriminant (OPLS-DA) analysis.Results
Significant differences in the fecal metabolic profiles could distinguish AS/RA patients from healthy controls but could not distinguish between AS and RA patients. The significantly decreased metabolites in AS/RA patients were butyrate, propionate, methionine, and hypoxanthine. Significantly increased metabolites in AS/RA patients were taurine, methanol, fumarate, and tryptophan.Conclusion
The metabolome variations in feces indicated AS and RA were two homologous diseases that could not be distinguished by 1H NMR metabolomics.9.
Phan Nguyen Thuy An Masamitsu Yamaguchi Eiichiro Fukusaki 《Metabolomics : Official journal of the Metabolomic Society》2017,13(3):29
Introduction
Metamorphosis is a complicated process in which cell proliferation, differentiation, and death are orchestrated to form the mature structures of insects. In Drosophila, this process is controlled by ecdysone, a steroid hormone responsible for tissue remodeling and organogenesis that gives rise to the adult fly.Objective
By using a metabolomics approach, this study aimed to elucidate global changes in the central metabolic pathways in Drosophila throughout metamorphosis and then further examine the effects of temperature and origin on metabolic profiles.Methods
Targeted and non-targeted metabolic profiling of time-course samples from Drosophila were constructed to cover a wide range of cellular metabolites during metamorphosis.Results
This was the first wide-scale metabolomics study of Drosophila metamorphosis focusing on central metabolism. The abundance of detected metabolites changed drastically and correlated strongly with the development of Drosophila pupae. In non-stress conditions, temperature affected the developmental time, but the metabolic state at a certain stage of metamorphosis remained stable. Between D. melanogaster Canton S and Oregon R, similar metabolic profiles throughout metamorphosis was observed. However, there were still differences in purine and pyrimidine metabolism at an early stage in the pupal period, which was matched by differences in ecdysteroid levels.Conclusion
This study supported the strength of metabolomics in the field of developmental biology. The results provided a general view on the metabolic profile of Drosophila during metamorphosis, which provides basic 3 knowledge for future metabolomics studies using Drosophila.10.
Elba Garreta-Lara Bruno Campos Carlos Barata Silvia Lacorte Romà Tauler 《Metabolomics : Official journal of the Metabolomic Society》2016,12(5):86
Introduction
Climate change is a major concern for the scientific community, demanding novel information about the effects of environmental stressors on living organisms. Metabolic profiling is required for achieving the most extensive possible range of compounds and their concentration changes on stressed conditions.Objectives
Individuals of the crustacean species Daphnia magna were exposed to three different abiotic factors linked to global climate change: high salinity, high temperature levels and hypoxia. Advanced chemometric tools were used to characterize the metabolites affected by the exposure.Method
An exploratory analysis of gas chromatography-mass spectrometry (GC–MS) data was performed to discriminate between control and exposed daphnid samples. Due to the complexity of these GC–MS data sets, a comprehensive untargeted analysis of the full scan data was performed using multivariate curve resolution-alternating least squares (MCR-ALS) method. This approach enabled to resolve most of the metabolite signals from interference peaks caused by derivatization reactions. Metabolites with significant changes in their peak areas were tentatively identified and the involved metabolic pathways explored.Results
D. magna metabolic biomarkers are proposed for the considered physical factors. Metabolites related with energy metabolic pathways including some amino acids, carbohydrates, organic acids and nucleosides were identified as potential biomarkers of the investigated treatments.Conclusions
The proposed untargeted GC–MS metabolomics strategy and multivariate data analysis tools were useful to investigate D. magna metabolome under environmental stressed conditions.11.
Brooke A. Clemmons Robert I. Mihelic Ronique C. Beckford Joshua B. Powers Emily A. Melchior Zachary D. McFarlane Emily R. Cope Mallory M. Embree J. Travis Mulliniks Shawn R. Campagna Brynn H. Voy Phillip R. Myer 《Metabolomics : Official journal of the Metabolomic Society》2017,13(12):147
Introduction
Improving feed utilization in cattle is required to reduce input costs, increase production, and ultimately improve sustainability of the beef cattle industry. Characterizing metabolic differences between efficient and non-efficient animals will allow stakeholders to identify more efficient cattle during backgrounding.Objectives
This study used an untargeted metabolomics approach to determine differences in serum metabolites between animals of low and high residual feed intake.Methods
Residual feed intake was determined for 50 purebred Angus steers and 29 steers were selected for the study steers based on low versus high feed efficiency. Blood samples were collected from steers and analyzed using untargeted metabolomics via mass spectrometry. Metabolite data was analyzed using Metaboanalyst, visualized using orthogonal partial least squares discriminant analysis, and p-values derived from permutation testing. Non-esterified fatty acids, urea nitrogen, and glucose were measured using commercially available calorimetric assay kits. Differences in metabolites measured were grouped by residual feed intake was measured using one-way analysis of variance in SAS 9.4.Results
Four metabolites were found to be associated with differences in feed efficiency. No differences were found in other serum metabolites, including serum urea nitrogen, non-esterified fatty acids, and glucose.Conclusions
Four metabolites that differed between low and high residual feed intake have important functions related to nutrient utilization, among other functions, in cattle. This information will allow identification of more efficient steers during backgrounding.12.
Stefan Weidt Jennifer Haggarty Ryan Kean Cristian I. Cojocariu Paul J. Silcock Ranjith Rajendran Gordon Ramage Karl E. V. Burgess 《Metabolomics : Official journal of the Metabolomic Society》2016,12(12):189
Introduction
Combined infections from Candida albicans and Staphylococcus aureus are a leading cause of death in the developed world. Evidence suggests that Candida enhances the virulence of Staphylococcus—hyphae penetrate through tissue barriers, while S. aureus tightly associates with the hyphae to obtain entry to the host organism. Indeed, in a biofilm state, C. albicans enhances the antimicrobial resistance characteristics of S. aureus. The association of these microorganisms is also associated with significantly increased morbidity and mortality. Due to this tight association we hypothesised that metabolic effects were also in evidence.Objectives
To explore the interaction, we used a novel GC-Orbitrap-based mass spectrometer, the Q Exactive GC, which combines the high peak capacity and chromatographic resolution of gas chromatography with the sub-ppm mass accuracy of an Orbitrap system. This allows the capability to leverage the widely available electron ionisation libraries for untargeted applications, along with expanding accurate mass libraries and targeted matches based around authentic standards.Methods
Optimised C. albicans and S. aureus mono- and co-cultured biofilms were analysed using the new instrument in addition to the fresh and spent bacterial growth media.Results
The targeted analysis experiment was based around 36 sugars and sugar phosphates, 22 amino acids and five organic acids. Untargeted analysis resulted in the detection of 465 features from fresh and spent medium and 405 from biofilm samples. Three significantly changing compounds that matched to high scoring library fragment patterns were chosen for validation.Conclusion
Evaluation of the results demonstrates that the Q Exactive GC is suitable for metabolomics analysis using a targeted/untargeted methodology. Many of the results were as expected: e.g. rapid consumption of glucose and fructose from the medium regardless of the cell type. Modulation of sugar-phosphate levels also suggest that the pentose phosphate pathway could be enhanced in the cells from co-cultured biofilms. Untargeted metabolomics results suggested significant production of cell-wall biosynthesis components and the consumption of non-proteinaceous amino-acids.13.
Stéphane Greff Mayalen Zubia Claude Payri Olivier P. Thomas Thierry Perez 《Metabolomics : Official journal of the Metabolomic Society》2017,13(4):33
Introduction
The Latitudinal Gradient Hypothesis (LGH) foresees that specialized metabolites are overexpressed under low latitudes, where organisms are subjected to higher herbivory pressure. The widespread macroalga Asparagopsis taxiformis is composed of six distinct genetic lineages, some of them being introduced in many regions.Objectives
To study (i) metabolic fingerprints of the macroalga and (ii) its bioactivity in space and time, both as proxies of its investment in defensive traits, in order to assess links between bioactivities and metabotypes with macroalgal invasiveness.Methods
289 macroalgal individuals, from four tropical and three temperate regions, were analyzed using untargeted metabolomics and the standardized Microtox® assay.Results
Metabotypes showed a low divergence between tropical and temperate populations, while bioactivities were higher in temperate populations. However, these phenotypes varied significantly in time, with a higher variability in tropical regions. Bioactivities were high and stable in temperate regions, whereas they were low and much variable in tropical regions. Although the introduced lineage two exhibited the highest bioactivities, this lineage could also present variable proliferation fates.Conclusion
The metabolomic approach partly discriminates macroalgal populations from various geographic origins. The production of chemical defenses assessed by the bioactivity assay does not match the macroalgal genetic lineage and seems more driven by the environment. The higher content of chemical defenses in temperate versus tropical populations is not in accordance with the LGH and cannot be related to the invasiveness of the macroalgae.14.
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.15.
Paulin N. Wahjudi Qing-Yi Lu Mary E. Patterson Xuemei Zhang Vay Liang Go Jian Chen Wei-Lin Li W. N. Paul Lee 《Metabolomics : Official journal of the Metabolomic Society》2017,13(8):91
Introduction
Loquat leaf extract (LLE) is commonly used in China for a variety of ailments including diabetes. Several recent reports implicate LLE and a sesquiterpene glycoside, one of its components, as being an anti-hyperglycemic agent. However, the underlying mechanism of action of this anti-hyperglycemic agent has not been reported.Objective
We have conducted a tracer-based metabolomics study to investigate the effects of sesquiterpene and loquat extract on the balance of flux of central glucose metabolism in HepG2 cells and to compare with those of “insulin sensitizers”, metformin and rosiglitazone.Methods
Human hepatoma HepG2 cells in confluence culture were incubated in Dulbecco’s modified Eagle’s medium containing 50% [1, 2 13C2]-glucose in the presence of rosiglitazone, metformin, LLE or pure sesquiterpene. Cells were harvested in 48 h. Mass isotopomers of metabolites (glycogen, ribose, deoxyribose, glutamate and palmitate) were determined.Results
13C labeling in metabolic intermediates were summarized in a mass isotopomer matrix. Treatment with loquat extract/sesquiterpene, metformin and rosiglitazone each produced distinctive mass isotopomer patterns reflecting disparate effects on the contribution of glucose to various metabolites production, and on several metabolic flux ratios. The overall effect of LLE and sesquiterpene on glucose metabolism is clearly different from those of the known “insulin sensitizers”.Conclusion
Our study demonstrates the utility of isotopomer matrix in summarizing metabolic actions of LLE on the balance of fluxes occurring within the central glucose metabolism in HepG2 cells. 13C carbon tracing (tracer-based metabolomics) is a useful systems biology tool to elucidate glucose metabolic pathways affected by diabetes and its treatment.16.
Rachel A. Spicer Christoph Steinbeck 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):16
Introduction
Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.Objectives
(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.Methods
A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.Results
Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.Conclusion
Further efforts are required to improve data sharing in metabolomics.17.
Antonio Rosato Leonardo Tenori Marta Cascante Pedro Ramon De Atauri Carulla Vitor A. P. Martins dos Santos Edoardo Saccenti 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):37
Introduction
Metabolomics is a well-established tool in systems biology, especially in the top–down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.Objectives
This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.Methods
We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.Results
We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.Conclusions
Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.18.
Tushar H. More Ravindra Taware Khushman Taunk Venkatesh Chanukuppa Venkateshwarlu Naik Anupama Mane Srikanth Rapole 《Metabolomics : Official journal of the Metabolomic Society》2018,14(8):107
Introduction
Invasive ductal carcinoma (IDC) is a type of breast cancer, usually detected in advanced stages due to its asymptomatic nature which ultimately leads to low survival rate. Identification of urinary metabolic adaptations induced by IDC to understand the disease pathophysiology and monitor therapy response would be a helpful approach in clinical settings. Moreover, its non-invasive and cost effective strategy better suited to minimize apprehension among high risk population.Objective
This study aims toward investigating the urinary metabolic alterations of IDC by targeted (LC-MRM/MS) and untargeted (GC–MS) approaches for the better understanding of the disease pathophysiology and monitoring therapy response.Methods
Urinary metabolic alterations of IDC subjects (63) and control subjects (63) were explored by targeted (LC-MRM/MS) and untargeted (GC–MS) approaches. IDC specific urinary metabolomics signature was extracted by applying both univariate and multivariate statistical tools.Results
Statistical analysis identified 39 urinary metabolites with the highest contribution to metabolomic alterations specific to IDC. Out of which, 19 metabolites were identified from targeted LC-MRM/MS analysis, while 20 were identified from the untargeted GC–MS analysis. Receiver operator characteristic (ROC) curve analysis evidenced 6 most discriminatory metabolites from each type of approach that could differentiate between IDC subjects and controls with higher sensitivity and specificity. Furthermore, metabolic pathway analysis depicted several dysregulated pathways in IDC including sugar, amino acid, nucleotide metabolism, TCA cycle etc.Conclusions
Overall, this study provides valuable inputs regarding altered urinary metabolites which improved our knowledge on urinary metabolomic alterations induced by IDC. Moreover, this study identified several dysregulated metabolic pathways which offer further insight into the disease pathophysiology.19.
Florian Buettner Kyle Jay Harry Wischnewski Thomas Stadelmann Shady Saad Konstantins Jefimovs Madina Mansurova Juan Gerez Claus M. Azzalin Reinhard Dechant Alfredo J. Ibáñez 《Metabolomics : Official journal of the Metabolomic Society》2017,13(5):53