Journal articles on the topic 'Metabolomics'
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1
Pann, Patrick, Martin Hrabě de Angelis, Cornelia Prehn, and Jerzy Adamski. "Mouse Age Matters: How Age Affects the Murine Plasma Metabolome." Metabolites 10, no. 11 (November 19, 2020): 472. http://dx.doi.org/10.3390/metabo10110472.
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A large part of metabolomics research relies on experiments involving mouse models, which are usually 6 to 20 weeks of age. However, in this age range mice undergo dramatic developmental changes. Even small age differences may lead to different metabolomes, which in turn could increase inter-sample variability and impair the reproducibility and comparability of metabolomics results. In order to learn more about the variability of the murine plasma metabolome, we analyzed male and female C57BL/6J, C57BL/6NTac, 129S1/SvImJ, and C3HeB/FeJ mice at 6, 10, 14, and 20 weeks of age, using targeted metabolomics (BIOCRATES AbsoluteIDQ™ p150 Kit). Our analysis revealed high variability of the murine plasma metabolome during adolescence and early adulthood. A general age range with minimal variability, and thus a stable metabolome, could not be identified. Age-related metabolomic changes as well as the metabolite profiles at specific ages differed markedly between mouse strains. This observation illustrates the fact that the developmental timing in mice is strain specific. We therefore stress the importance of deliberate strain choice, as well as consistency and precise documentation of animal age, in metabolomics studies.
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Ivanova, Lada, Oscar D. Rangel-Huerta, Haitham Tartor, Maria K. Dahle, Silvio Uhlig, and Christiane Kruse Fæste. "Metabolomics and Multi-Omics Determination of Potential Plasma Biomarkers in PRV-1-Infected Atlantic Salmon." Metabolites 14, no. 7 (July 2, 2024): 375. http://dx.doi.org/10.3390/metabo14070375.
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Metabolomic analysis has been explored to search for disease biomarkers in humans for some time. The application to animal species, including fish, however, is still at the beginning. In the present study, we have used targeted and untargeted metabolomics to identify metabolites in the plasma of Atlantic salmon (Salmo salar) challenged with Piscine orthoreovirus (PRV-1), aiming to find metabolites associated with the progression of PRV-1 infection into heart and skeletal muscle inflammation (HSMI). The metabolomes of control and PRV-1-infected salmon were compared at three time points during disease development by employing different biostatistical approaches. Targeted metabolomics resulted in the determination of affected metabolites and metabolic pathways, revealing a substantial impact of PRV-1 infection on lipid homeostasis, especially on several (lyso)phosphatidylcholines, ceramides, and triglycerides. Untargeted metabolomics showed a clear separation of the treatment groups at later study time points, mainly due to effects on lipid metabolism pathways. In a subsequent multi-omics approach, we combined both metabolomics datasets with previously reported proteomics data generated from the same salmon plasma samples. Data processing with DIABLO software resulted in the identification of significant metabolites and proteins that were representative of the HSMI development in the salmon.
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Zelentsova, Ekaterina A., Sofia S. Mariasina, Vadim V. Yanshole, Lyudmila V. Yanshole, Nataliya A. Osik, Kirill A. Sharshov, and Yuri P. Tsentalovich. "Quantitative Metabolomic Dataset of Avian Eye Lenses." Data 8, no. 8 (July 31, 2023): 125. http://dx.doi.org/10.3390/data8080125.
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Metabolomics is a powerful set of methods that uses analytical techniques to identify and quantify metabolites in biological samples, providing a snapshot of the metabolic state of a biological system. In medicine, metabolomics may help to reveal the molecular basis of a disease, make a diagnosis, and monitor treatment responses, while in agriculture, it can improve crop yields and plant breeding. However, animal metabolomics faces several challenges due to the complexity and diversity of animal metabolomes, the lack of standardized protocols, and the difficulty in interpreting metabolomic data. The current dataset includes quantitative metabolomic profiles of eye lenses from 26 bird species (111 specimens) that can aid researchers in developing new experiments, mathematical models, and integrating with other “-omics” data. The dataset includes raw 1H NMR spectra, protocols for sample preparation, and data preprocessing, with the final table containing information on the abundance of 89 reliably identified and quantified metabolites. The dataset is quantitative, making it relevant for supplementing with new specimens or comparison groups, followed by data mining and expected new interpretations. The data were obtained using the bird specimens collected in compliance with ethical standards and revealed potential differences in metabolic pathways due to phylogenetic differences or environmental exposure.
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Lankadurai, Brian P., Edward G. Nagato, and Myrna J. Simpson. "Environmental metabolomics: an emerging approach to study organism responses to environmental stressors." Environmental Reviews 21, no. 3 (September 2013): 180–205. http://dx.doi.org/10.1139/er-2013-0011.
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Metabolomics is the analysis of endogenous and exogenous low molecular mass metabolites within a cell, tissue, or biofluid of an organism in response to an external stressor. The sub-discipline of environmental metabolomics is the application of metabolomic techniques to analyze the interactions of organisms with their environment. There has been a rapid growth in environmental metabolomics over the past decade. This growth can be attributed to the comprehensive and rapid nature of nontargeted metabolomics and the ability to generate hypotheses involving complex environmental stressors, especially when the mode of action is unknown. Using a wide variety of model organisms, metabolomic studies have detected stress from abiotic factors such as xenobiotic exposure and temperature shifts as well as biotic stressors such as herbivory and competition. Nuclear magnetic resonance (NMR)-based metabolomics has been the dominant analytical platform used for environmental metabolomics studies, owing to its nonselectivity and ease of sample preparation. However, the number of mass spectrometry (MS)-based metabolomic studies is also increasing rapidly, owing to its high sensitivity for the detection of trace levels of metabolites. In this review, we provide an overview of the general experimental design, extraction methods, analytical instrumentation, and statistical methods used in environmental metabolomics. We then highlight some of the recent studies that have used metabolomics to elucidate hitherto unknown biochemical modes of actions of various environmental stressors to both terrestrial and aquatic organisms, as well as identify potential metabolite shifts as early bioindicators of these stressors. Through this, we emphasize the immense potential and versatility of environmental metabolomics as a routine tool for characterizing the responses of organisms to numerous types of environmental stressors.
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Sebastiani, Paola, and Nalini Raghavachari. "METABOLOMICS OF LONGEVITY AND LIFESPAN." Innovation in Aging 7, Supplement_1 (December 1, 2023): 631. http://dx.doi.org/10.1093/geroni/igad104.2056.
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Abstract Serum metabolomics has been an important source of biomarkers of aging and longevity for years. This symposium will bring together investigators from large studies of human longevity to provide an overview of recent discoveries on serum metabolomics of aging and extreme human longevity, their connections to genetic variations, and highlight the challenges of correlating metabolomic profiles of aging in human studies and across multiple species. Dr. Sebastiani will describe results from analyses of serum metabolomics of participants enrolled in the Long Life Family Study, highlight similarities and differences between metabolomic profiles of old age and extreme old age, and some connections with genetics of extreme human longevity. Dr. Rappaport will connect specific variations of the APOE alleles to metabolomic profiles and describe a possible role of bioenergetics pathways in mediating the effect of APOE to longevity and resistance to Alzheimer’s disease. Dr. Monti will expand the characterization of metabolomics of aging and extreme human longevity in a large metabolomic study of very old centenarians by using traditional statistical analyses and novel machine learning techniques. His analysis identifies rich signatures of aging and longevity that include well known metabolites and point to bile acids and several classes of steroids as important marker of longevity. Analytical innovations will be taken further by Dr. Schork who will introduce a novel approach based on distance of profiles to analyze multiple metabolites simultaneously and show the value of this approach to analyze metabolomic profiles of maximum lifespan across multiple species. This is a Geroscience Interest Group Sponsored Symposium.
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Yanagihara, M., F. Nakajima, and T. Tobino. "Metabolomic responses of an estuarine benthic amphipod to heavy metals at urban-runoff concentrations." Water Science and Technology 78, no. 11 (December 20, 2018): 2349–54. http://dx.doi.org/10.2166/wst.2018.518.
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Abstract Heavy metals released from urban areas have toxic effects on aquatic organisms. Heavy metals in aquatic environments exist in various forms and methods designed to assess their effects need to consider their bioavailability. This study aimed to explore biomarkers in an estuarine amphipod, Grandidierella japonica, for exposure to heavy metals using metabolomics. We exposed G. japonica to different heavy metals and analyzed their metabolomes using high-resolution mass spectrometry. Partial least squares discriminant analysis (PLS-DA) was used to extract biomarkers of exposure for each heavy metal. As a result, three models were built to predict discrimination based on metabolomic profiles, and 70, 106, and 168 metabolites were extracted as biomarkers for exposure to Cu, Zn, and Cd, respectively. Our results suggest that PLS-DA was effective in extracting biomarkers, and this study demonstrated the usefulness of metabolomics as biomarkers.
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Brennan, Lorraine. "Session 2: Personalised nutrition Metabolomic applications in nutritional research." Proceedings of the Nutrition Society 67, no. 4 (October 10, 2008): 404–8. http://dx.doi.org/10.1017/s0029665108008719.
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Metabolomics aims to profile all small molecules that are present in biological samples such as biofluids, tissue extracts and culture media. Combining the data obtained with multivariate data analysis tools allows the exploration of changes induced by a biological treatment or changes resulting from phenotype. Recently, there has been a large increase in interest in using metabolomics in nutritional research and because of the intimate relationship between nutrients and metabolism there exists great potential for the use of metabolomics within nutritional research. However, for metabolomics to reach its full potential within this field it is also important to be realistic about the challenges that are faced. Examples of such challenges include the necessity to have a clear understanding of the causes of variation in human metabolomic profiles, the effects of the gut microflora on the metabolomic profile and the interaction of the gut microflora with the host's metabolism. A further challenge that is particularly relevant for human nutritional research is the difficulty associated with biological interpretation of the data. Notwithstanding these and other challenges, several examples of successful applications to nutritional research exist. The link between the human metabolic phenotype, as characterised by metabolomic profiles, and dietary preferences proposes the potential role of metabolomics in personalised nutrition.
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Wishart, David S., Leo L. Cheng, Valérie Copié, Arthur S. Edison, Hamid R. Eghbalnia, Jeffrey C. Hoch, Goncalo J. Gouveia, et al. "NMR and Metabolomics—A Roadmap for the Future." Metabolites 12, no. 8 (July 23, 2022): 678. http://dx.doi.org/10.3390/metabo12080678.
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Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021—the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements.
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Liu, Rui, Zheng-Xue Bao, Pei-Ji Zhao, and Guo-Hong Li. "Advances in the Study of Metabolomics and Metabolites in Some Species Interactions." Molecules 26, no. 11 (May 31, 2021): 3311. http://dx.doi.org/10.3390/molecules26113311.
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In the natural environment, interactions between species are a common natural phenomena. The mechanisms of interaction between different species are mainly studied using genomic, transcriptomic, proteomic, and metabolomic techniques. Metabolomics is a crucial part of system biology and is based on precision instrument analysis. In the last decade, the emerging field of metabolomics has received extensive attention. Metabolomics not only provides a qualitative and quantitative method for studying the mechanisms of interactions between different species, but also helps clarify the mechanisms of defense between the host and pathogen, and to explore new metabolites with various biological activities. This review focuses on the methods and progress of interspecies metabolomics. Additionally, the prospects and challenges of interspecies metabolomics are discussed.
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Brennan, Lorraine. "Metabolomics in nutrition research: current status and perspectives." Biochemical Society Transactions 41, no. 2 (March 21, 2013): 670–73. http://dx.doi.org/10.1042/bst20120350.
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Metabolomics is the study of metabolites present in biological samples such as biofluids, tissue/cellular extracts and culture media. Combining metabolomic data with multivariate data analysis tools allows us to study alterations in metabolic pathways following different perturbations. Examples of perturbations can be disease state, drug or nutritional interventions with successful applications in the fields of drug toxicology, biomarker development and nutrition research. Application of metabolomics to nutrition research is increasing and applications range from assessing novel biomarkers of dietary intake to application of metabolomics in intervention studies. The present review highlights the use of metabolomics in nutrition research.
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Trongtrakul, Konlawij, Chanisa Thonusin, Chaicharn Pothirat, Siriporn C. Chattipakorn, and Nipon Chattipakorn. "Past Experiences for Future Applications of Metabolomics in Critically Ill Patients with Sepsis and Septic Shocks." Metabolites 12, no. 1 (December 21, 2021): 1. http://dx.doi.org/10.3390/metabo12010001.
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A disruption of several metabolic pathways in critically ill patients with sepsis indicates that metabolomics might be used as a more precise tool for sepsis and septic shock when compared with the conventional biomarkers. This article provides information regarding metabolomics studies in sepsis and septic shock patients. It has been shown that a variety of metabolomic pathways are altered in sepsis and septic shock, including amino acid metabolism, fatty acid oxidation, phospholipid metabolism, glycolysis, and tricarboxylic acid cycle. Based upon this comprehensive review, here, we demonstrate that metabolomics is about to change the world of sepsis biomarkers, not only for its utilization in sepsis diagnosis, but also for prognosticating and monitoring the therapeutic response. Additionally, the future direction regarding the establishment of studies integrating metabolomics with other molecular modalities and studies identifying the relationships between metabolomic profiles and clinical characteristics to address clinical application are discussed in this article. All of the information from this review indicates the important impact of metabolomics as a tool for diagnosis, monitoring therapeutic response, and prognostic assessment of sepsis and septic shock. These findings also encourage further clinical investigations to warrant its use in routine clinical settings.
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Jin, Qiao, and Ronald Ching Wan Ma. "Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies." Cells 10, no. 11 (October 21, 2021): 2832. http://dx.doi.org/10.3390/cells10112832.
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The increasing prevalence of diabetes and its complications, such as cardiovascular and kidney disease, remains a huge burden globally. Identification of biomarkers for the screening, diagnosis, and prognosis of diabetes and its complications and better understanding of the molecular pathways involved in the development and progression of diabetes can facilitate individualized prevention and treatment. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner. Providing information on underlying metabolic pathways, metabolomics can further identify mechanisms of diabetes and its progression. The application of metabolomics in epidemiological studies have identified novel biomarkers for type 2 diabetes (T2D) and its complications, such as branched-chain amino acids, metabolites of phenylalanine, metabolites involved in energy metabolism, and lipid metabolism. Metabolomics have also been applied to explore the potential pathways modulated by medications. Investigating diabetes using a systems biology approach by integrating metabolomics with other omics data, such as genetics, transcriptomics, proteomics, and clinical data can present a comprehensive metabolic network and facilitate causal inference. In this regard, metabolomics can deepen the molecular understanding, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The current review focused on metabolomic biomarkers for kidney and cardiovascular disease in T2D identified from epidemiological studies, and will also provide a brief overview on metabolomic investigations for T2D.
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Clendenen, Nathan, and Angelo D'Alessandro. "High Throughput Metabolomics in Clinical Studies: Review and New Applications to Remote Ischemic Preconditioning." Current Topics in Medicinal Chemistry 18, no. 25 (January 21, 2019): 2143–53. http://dx.doi.org/10.2174/1568026619666181130140937.
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Metabolomic analysis has made substantial contributions to the understanding of diverse pathological processes and has the potential to improve diagnosis and identify novel therapeutic targets. As early success in perinatal medicine, nutrition, chronic diseases, cancer and trauma demonstrates, metabolomics is approaching feasibility in terms of guiding improvement in population-level diagnosis and treatment. A key barrier to implementing metabolomics as a routine diagnostic tool is rapid sample extraction and data analysis along with the establishment of normal values for novel metabolic markers. This review covers key advancements in clinical metabolomics and applies a high throughput metabolomics method as a proof of principle to identify novel metabolites associated with remote ischemic preconditioning.
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Tsuchida, Sachio, and Tomohiro Nakayama. "Metabolomics Research in Periodontal Disease by Mass Spectrometry." Molecules 27, no. 9 (April 30, 2022): 2864. http://dx.doi.org/10.3390/molecules27092864.
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Periodontology is a newer field relative to other areas of dentistry. Remarkable progress has been made in recent years in periodontology in terms of both research and clinical applications, with researchers worldwide now focusing on periodontology. With recent advances in mass spectrometry technology, metabolomics research is now widely conducted in various research fields. Metabolomics, which is also termed metabolomic analysis, is a technology that enables the comprehensive analysis of small-molecule metabolites in living organisms. With the development of metabolite analysis, methods using gas chromatography–mass spectrometry, liquid chromatography–mass spectrometry, capillary electrophoresis–mass spectrometry, etc. have progressed, making it possible to analyze a wider range of metabolites and to detect metabolites at lower concentrations. Metabolomics is widely used for research in the food, plant, microbial, and medical fields. This paper provides an introduction to metabolomic analysis and a review of the increasing applications of metabolomic analysis in periodontal disease research using mass spectrometry technology.
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Surendran, Arun, Negar Atefi, Hannah Zhang, Michel Aliani, and Amir Ravandi. "Defining Acute Coronary Syndrome through Metabolomics." Metabolites 11, no. 10 (October 6, 2021): 685. http://dx.doi.org/10.3390/metabo11100685.
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As an emerging platform technology, metabolomics offers new insights into the pathomechanisms associated with complex disease conditions, including cardiovascular diseases. It also facilitates assessing the risk of developing the disease before its clinical manifestation. For this reason, metabolomics is of growing interest for understanding the pathogenesis of acute coronary syndromes (ACS), finding new biomarkers of ACS, and its associated risk management. Metabolomics-based studies in ACS have already demonstrated immense potential for biomarker discovery and mechanistic insights by identifying metabolomic signatures (e.g., branched-chain amino acids, acylcarnitines, lysophosphatidylcholines) associated with disease progression. Herein, we discuss the various metabolomics approaches and the challenges involved in metabolic profiling, focusing on ACS. Special attention has been paid to the clinical studies of metabolomics and lipidomics in ACS, with an emphasis on ischemia/reperfusion injury.
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Yu, Ji-Woo, Min-Ho Song, Ji-Ho Lee, Jun-Hwan Song, Won-Ho Hahn, Young-Soo Keum, and Nam Mi Kang. "Urinary Metabolomic Differentiation of Infants Fed on Human Breastmilk and Formulated Milk." Metabolites 14, no. 2 (February 16, 2024): 128. http://dx.doi.org/10.3390/metabo14020128.
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Human breastmilk is an invaluable nutritional and pharmacological resource with a highly diverse metabolite profile, which can directly affect the metabolism of infants. Application of metabolomics can discriminate the complex relationship between such nutrients and infant health. As the most common biological fluid in metabolomic study, infant urinary metabolomics may provide the physiological impacts of different nutritional resources, namely human breastmilk and formulated milk. In this study, we aimed to identify possible differences in the urine metabolome of 30 infants (1–14 days after birth) fed with breast milk (n = 15) or formulated milk (n = 15). From metabolomic analysis with gas chromatography-mass spectrometry, 163 metabolites from single mass spectrometry (GC-MS), and 383 metabolites from tandem mass spectrometry (GC-MS/MS) were confirmed in urinary samples. Various multivariate statistical analysis were performed to discriminate the differences originating from physiological/nutritional variables, including human breastmilk/formulate milk feeding, sex, and duration of feeding. Both unsupervised and supervised discriminant analyses indicated that feeding resources (human breastmilk/formulated milk) gave marginal but significant differences in urinary metabolomes, while other factors (sex, duration of feeding) did not show notable discrimination between groups. According to the biomarker analyses, several organic acid and amino acids showed statistically significant differences between different feeding resources, such as 2-hydroxyhippurate.
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Emwas, Abdul-Hamid, Raja Roy, Ryan T. McKay, Leonardo Tenori, Edoardo Saccenti, G. A. Nagana Gowda, Daniel Raftery, et al. "NMR Spectroscopy for Metabolomics Research." Metabolites 9, no. 7 (June 27, 2019): 123. http://dx.doi.org/10.3390/metabo9070123.
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Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.
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Chen, Rirong, Jieqi Zheng, Li Li, Chao Li, Kang Chao, Zhirong Zeng, Minhu Chen, and Shenghong Zhang. "Metabolomics facilitate the personalized management in inflammatory bowel disease." Therapeutic Advances in Gastroenterology 14 (January 2021): 175628482110644. http://dx.doi.org/10.1177/17562848211064489.
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Inflammatory bowel disease (IBD) is a gastrointestinal disorder characterized by chronic relapsing inflammation and mucosal lesions. Reliable biomarkers for monitoring disease activity, predicting therapeutic response, and disease relapse are needed in the personalized management of IBD. Given the alterations in metabolomic profiles observed in patients with IBD, metabolomics, a new and developing technique for the qualitative and quantitative study of small metabolite molecules, offers another possibility for identifying candidate markers and promising predictive models. With increasing research on metabolomics, it is gradually considered that metabolomics will play a significant role in the management of IBD. In this review, we summarize the role of metabolomics in the assessment of disease activity, including endoscopic activity and histological activity, prediction of therapeutic response, prediction of relapse, and other aspects concerning disease management in IBD. Furthermore, we describe the limitations of metabolomics and highlight some solutions.
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Carrera, Fredy P., Carlos Noceda, María G. Maridueña-Zavala, and Juan M. Cevallos-Cevallos. "Metabolomics, a Powerful Tool for Understanding Plant Abiotic Stress." Agronomy 11, no. 5 (April 22, 2021): 824. http://dx.doi.org/10.3390/agronomy11050824.
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Metabolomics is a technology that generates large amounts of data and contributes to obtaining wide and integral explanations of the biochemical state of a living organism. Plants are continuously affected by abiotic stresses such as water scarcity, high temperatures and high salinity, and metabolomics has the potential for elucidating the response-to-stress mechanisms and develop resistance strategies in affected cultivars. This review describes the characteristics of each of the stages of metabolomic studies in plants and the role of metabolomics in the characterization of the response of various plant species to abiotic stresses.
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Shahid, Mohammad, Udai B. Singh, and Mohammad Saghir Khan. "Metabolomics-Based Mechanistic Insights into Revealing the Adverse Effects of Pesticides on Plants: An Interactive Review." Metabolites 13, no. 2 (February 8, 2023): 246. http://dx.doi.org/10.3390/metabo13020246.
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In plant biology, metabolomics is often used to quantitatively assess small molecules, metabolites, and their intermediates in plants. Metabolomics has frequently been applied to detect metabolic alterations in plants exposed to various biotic and abiotic stresses, including pesticides. The widespread use of pesticides and agrochemicals in intensive crop production systems is a serious threat to the functionality and sustainability of agroecosystems. Pesticide accumulation in soil may disrupt soil–plant relationships, thereby posing a pollution risk to agricultural output. Application of metabolomic techniques in the assessment of the biological consequences of pesticides at the molecular level has emerged as a crucial technique in exposome investigations. State-of-the-art metabolomic approaches such as GC–MS, LC–MS/MS UHPLC, UPLC–IMS–QToF, GC/EI/MS, MALDI-TOF MS, and 1H-HR-MAS NMR, etc., investigating the harmful effects of agricultural pesticides have been reviewed. This updated review seeks to outline the key uses of metabolomics related to the evaluation of the toxicological impacts of pesticides on agronomically important crops in exposome assays as well as bench-scale studies. Overall, this review describes the potential uses of metabolomics as a method for evaluating the safety of agricultural chemicals for regulatory applications. Additionally, the most recent developments in metabolomic tools applied to pesticide toxicology and also the difficulties in utilizing this approach are discussed.
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Gardner, Alexander, Guy Carpenter, and Po-Wah So. "Salivary Metabolomics: From Diagnostic Biomarker Discovery to Investigating Biological Function." Metabolites 10, no. 2 (January 26, 2020): 47. http://dx.doi.org/10.3390/metabo10020047.
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Metabolomic profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, metabolomic analysis of saliva, the most readily-available human biofluid, has lagged. This review explores the history of saliva-based metabolomics and summarizes current knowledge of salivary metabolomics. Current applications of salivary metabolomics have largely focused on diagnostic biomarker discovery and the diagnostic value of the current literature base is explored. There is also a small, albeit promising, literature base concerning the use of salivary metabolomics in monitoring athletic performance. Functional roles of salivary metabolites remain largely unexplored. Areas of emerging knowledge include the role of oral host–microbiome interactions in shaping the salivary metabolite profile and the potential roles of salivary metabolites in oral physiology, e.g., in taste perception. Discussion of future research directions describes the need to begin acquiring a greater knowledge of the function of salivary metabolites, a current research direction in the field of the gut metabolome. The role of saliva as an easily obtainable, information-rich fluid that could complement other gastrointestinal fluids in the exploration of the gut metabolome is emphasized.
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Kessenikh, E. D., M. A. Migunova, M. I. Krivosheina, and E. A. Murashko. "Untargeted metabolomic analysis of adherent cell cultures: general recommendations for sample preparation." Russian Journal for Personalized Medicine 4, no. 3 (August 9, 2024): 268–75. http://dx.doi.org/10.18705/2782-3806-2024-4-3-268-275.
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Metabolomics is a comprehensive quantitative and qualitative analysis of metabolites in biological specimens (cells, biological fluids and tissues). It includes chemometric and statistical analysis of metabolomic data to assess group-wise differences. The reliability of the analytical data and the biological meaningful results of the metabolomics study are determined by the selection of appropriate procedures of sample preparation.The review outlines general recommendations for planning and organizing untargeted metabolomics studies of adherent cell cultures. The main strategies and procedures for optimization of sample preparation and selection of culture conditions, sampling, metabolism quenching and metabolite extraction are considered.
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Satori, Chad P., Marzieh Ramezani, Joseph S. Koopmeiners, Audrey F. Meyer, Jose A. Rodriguez-Navarro, Michelle M. Kuhns, Thane H. Taylor, Christy L. Haynes, Joseph J. Dalluge, and Edgar A. Arriaga. "Checkpoints for preliminary identification of small molecules found enriched in autophagosomes and activated mast cell secretions analyzed by comparative UPLC/MSe." Analytical Methods 9, no. 1 (2017): 46–54. http://dx.doi.org/10.1039/c6ay02500e.
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Saoi, Michelle, and Philip Britz-McKibbin. "New Advances in Tissue Metabolomics: A Review." Metabolites 11, no. 10 (September 30, 2021): 672. http://dx.doi.org/10.3390/metabo11100672.
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Metabolomics offers a hypothesis-generating approach for biomarker discovery in clinical medicine while also providing better understanding of the underlying mechanisms of chronic diseases. Clinical metabolomic studies largely rely on human biofluids (e.g., plasma, urine) as a more convenient specimen type for investigation. However, biofluids are non-organ specific reflecting complex biochemical processes throughout the body, which may complicate biochemical interpretations. For these reasons, tissue metabolomic studies enable deeper insights into aberrant metabolism occurring at the direct site of disease pathogenesis. This review highlights new advances in metabolomics for ex vivo analysis, as well as in situ imaging of tissue specimens, including diverse tissue types from animal models and human participants. Moreover, we discuss key pre-analytical and post-analytical challenges in tissue metabolomics for robust biomarker discovery with a focus on new methodological advances introduced over the past six years, including innovative clinical applications for improved screening, diagnostic testing, and therapeutic interventions for cancer.
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Zhou, Jinna, Donghai Hou, Weiqiu Zou, Jinhu Wang, Run Luo, Mu Wang, and Hong Yu. "Comparison of Widely Targeted Metabolomics and Untargeted Metabolomics of Wild Ophiocordyceps Sinensis." Molecules 27, no. 11 (June 6, 2022): 3645. http://dx.doi.org/10.3390/molecules27113645.
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The authors of this paper conducted a comparative metabolomic analysis of Ophiocordyceps sinensis (OS), providing the metabolic profiles of the stroma (OSBSz) and sclerotia (OSBSh) of OS by widely targeted metabolomics and untargeted metabolomics. The results showed that 778 and 1449 metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. The metabolites in OSBSz and OSBSh are significantly differentiated; 71 and 96 differentially expressed metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. This suggests that these 71 metabolites (riboflavine, tripdiolide, bromocriptine, lumichrome, tetrahymanol, citrostadienol, etc.) and 96 metabolites (sancycline, vignatic acid B, pirbuterol, rubrophen, epalrestat, etc.) are potential biomarkers. 4-Hydroxybenzaldehyde, arginine, and lumichrome were common differentially expressed metabolites. Using the widely targeted metabolomics approach, the key pathways identified that are involved in creating the differentiation between OSBSz and OSBSh may be nicotinate and nicotinamide metabolism, thiamine metabolism, riboflavin metabolism, glycine, serine, and threonine metabolism, and arginine biosynthesis. The differentially expressed metabolites identified using the untargeted metabolomics approach were mainly involved in arginine biosynthesis, terpenoid backbone biosynthesis, porphyrin and chlorophyll metabolism, and cysteine and methionine metabolism. The purpose of this research was to provide support for the assessment of the differences between the stroma and sclerotia, to furnish a material basis for the evaluation of the physical effects of OS, and to provide a reference for the selection of detection methods for the metabolomics of OS.
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Di Donato, Samantha, Alessia Vignoli, Chiara Biagioni, Luca Malorni, Elena Mori, Leonardo Tenori, Vanessa Calamai, et al. "A Serum Metabolomics Classifier Derived from Elderly Patients with Metastatic Colorectal Cancer Predicts Relapse in the Adjuvant Setting." Cancers 13, no. 11 (June 2, 2021): 2762. http://dx.doi.org/10.3390/cancers13112762.
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Adjuvant treatment for patients with early stage colorectal cancer (eCRC) is currently based on suboptimal risk stratification, especially for elderly patients. Metabolomics may improve the identification of patients with residual micrometastases after surgery. In this retrospective study, we hypothesized that metabolomic fingerprinting could improve risk stratification in patients with eCRC. Serum samples obtained after surgery from 94 elderly patients with eCRC (65 relapse free and 29 relapsed, after 5-years median follow up), and from 75 elderly patients with metastatic colorectal cancer (mCRC) obtained before a new line of chemotherapy, were retrospectively analyzed via proton nuclear magnetic resonance spectroscopy. The prognostic role of metabolomics in patients with eCRC was assessed using Kaplan–Meier curves. PCA-CA-kNN could discriminate the metabolomic fingerprint of patients with relapse-free eCRC and mCRC (70.0% accuracy using NOESY spectra). This model was used to classify the samples of patients with relapsed eCRC: 69% of eCRC patients with relapse were predicted as metastatic. The metabolomic classification was strongly associated with prognosis (p-value 0.0005, HR 3.64), independently of tumor stage. In conclusion, metabolomics could be an innovative tool to refine risk stratification in elderly patients with eCRC. Based on these results, a prospective trial aimed at improving risk stratification by metabolomic fingerprinting (LIBIMET) is ongoing.
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Barba, Ignasi, Mireia Andrés, and David Garcia-Dorado. "Metabolomics and Heart Diseases: From Basic to Clinical Approach." Current Medicinal Chemistry 26, no. 1 (March 14, 2019): 46–59. http://dx.doi.org/10.2174/0929867324666171006151408.
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Background:The field of metabolomics has been steadily increasing in size for the last 15 years. Advances in analytical and statistical methods have allowed metabolomics to flourish in various areas of medicine. Cardiovascular diseases are some of the main research targets in metabolomics, due to their social and medical relevance, and also to the important role metabolic alterations play in their pathogenesis and evolution. </P><P> Metabolomics has been applied to the full spectrum of cardiovascular diseases: from patient risk stratification to myocardial infarction and heart failure. However - despite the many proof-ofconcept studies describing the applicability of metabolomics in the diagnosis, prognosis and treatment evaluation in cardiovascular diseases - it is not yet used in routine clinical practice. </P><P> Recently, large phenome centers have been established in clinical environments, and it is expected that they will provide definitive proof of the applicability of metabolomics in clinical practice. But there is also room for small and medium size centers to work on uncommon pathologies or to resolve specific but relevant clinical questions. </P><P> Objectives: In this review, we will introduce metabolomics, cover the metabolomic work done so far in the area of cardiovascular diseases.Conclusion:The cardiovascular field has been at the forefront of metabolomics application and it should lead the transfer to the clinic in the not so distant future.
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Nishiumi, Shin, Yoshihiro Izumi, Akiyoshi Hirayama, Masatomo Takahashi, Motonao Nakao, Kosuke Hata, Daisuke Saigusa, et al. "Comparative Evaluation of Plasma Metabolomic Data from Multiple Laboratories." Metabolites 12, no. 2 (February 1, 2022): 135. http://dx.doi.org/10.3390/metabo12020135.
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In mass spectrometry-based metabolomics, the differences in the analytical results from different laboratories/machines are an issue to be considered because various types of machines are used in each laboratory. Moreover, the analytical methods are unique to each laboratory. It is important to understand the reality of inter-laboratory differences in metabolomics. Therefore, we have evaluated whether the differences in analytical methods, with the exception sample pretreatment and including metabolite extraction, are involved in the inter-laboratory differences or not. In this study, nine facilities are evaluated for inter-laboratory comparisons of metabolomic analysis. Identical dried samples prepared from human and mouse plasma are distributed to each laboratory, and the metabolites are measured without the pretreatment that is unique to each laboratory. In these measurements, hydrophilic and hydrophobic metabolites are analyzed using 11 and 7 analytical methods, respectively. The metabolomic data acquired at each laboratory are integrated, and the differences in the metabolomic data from the laboratories are evaluated. No substantial difference in the relative quantitative data (human/mouse) for a little less than 50% of the detected metabolites is observed, and the hydrophilic metabolites have fewer differences between the laboratories compared with hydrophobic metabolites. From evaluating selected quantitatively guaranteed metabolites, the proportion of metabolites without the inter-laboratory differences is observed to be slightly high. It is difficult to resolve the inter-laboratory differences in metabolomics because all laboratories cannot prepare the same analytical environments. However, the results from this study indicate that the inter-laboratory differences in metabolomic data are due to measurement and data analysis rather than sample preparation, which will facilitate the understanding of the problems in metabolomics studies involving multiple laboratories.
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Gaffney, Isabella, Jonathan Brett Sallach, Julie Wilson, Edmund Bergström, and Jane Thomas-Oates. "Metabolomic Approaches to Studying the Response to Drought Stress in Corn (Zea mays) Cobs." Metabolites 11, no. 7 (July 3, 2021): 438. http://dx.doi.org/10.3390/metabo11070438.
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Metabolomics is a technique that allows for the evaluation of the entire extractable chemical profile of a plant, for example, using high-resolution mass spectrometry (HRMS) and can be used to evaluate plant stress responses, such as those due to drought. Metabolomic analysis is dependent upon the efficiency of the extraction protocol. Currently, there are two common extraction procedures widely used in metabolomic experiments, those that extract from plant tissue processed in liquid nitrogen or extraction from lyophilised plant tissues. Here, we evaluated the two using non-targeted metabolomics to show that lyophilisation can stabilise the maize (Zea mays) extractable metabolome, increasing throughput and efficiency of extraction as compared to the more traditional processing in liquid nitrogen. Then, we applied the lyophilisation approach to explore the effect of drought upon the maize metabolome in a non-targeted HRMS metabolomics approach. Metabolomics revealed differences in the mature maize metabolome having undergone three drought conditions imposed at two critical development stages (three-leaf stage and grain-fill stage); moreover, this difference was observed across two tissue types (kernel and inner cob/pith). It was shown that under ideal conditions, the biochemical make-up of the tissue types is different. However, under stress conditions, the stress response dominates the metabolic profile. Drought-related metabolites known from other plant systems have been identified and metabolomics has revealed potential novel drought-stress indicators in our maize system.
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Paganelli, Alessia, Valeria Righi, Elisabetta Tarentini, and Cristina Magnoni. "Current Knowledge in Skin Metabolomics: Updates from Literature Review." International Journal of Molecular Sciences 23, no. 15 (August 7, 2022): 8776. http://dx.doi.org/10.3390/ijms23158776.
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Metabolomic profiling is an emerging field consisting of the measurement of metabolites in a biological system. Since metabolites can vary in relation to different stimuli, specific metabolic patterns can be closely related to a pathological process. In the dermatological setting, skin metabolomics can provide useful biomarkers for the diagnosis, prognosis, and therapy of cutaneous disorders. The main goal of the present review is to present a comprehensive overview of the published studies in skin metabolomics. A search for journal articles focused on skin metabolomics was conducted on the MEDLINE, EMBASE, Cochrane, and Scopus electronic databases. Only research articles with electronically available English full text were taken into consideration. Studies specifically focused on cutaneous microbiomes were also excluded from the present search. A total of 97 papers matched all the research criteria and were therefore considered for the present work. Most of the publications were focused on inflammatory dermatoses and immune-mediated cutaneous disorders. Skin oncology also turned out to be a relevant field in metabolomic research. Only a few papers were focused on infectious diseases and rarer genetic disorders. All the major metabolomic alterations published so far in the dermatological setting are described extensively in this review.
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Rogers, Angela J., and Michael A. Matthay. "Applying metabolomics to uncover novel biology in ARDS." American Journal of Physiology-Lung Cellular and Molecular Physiology 306, no. 11 (June 1, 2014): L957—L961. http://dx.doi.org/10.1152/ajplung.00376.2013.
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A better understanding of the pathogenesis and the resolution of the acute respiratory distress syndrome (ARDS) is needed. Although some progress has been made with the use of protein biomarkers and candidate gene studies in understanding the pathobiology of ARDS, we propose that new studies that measure the chemical breakdown products of cellular metabolism (metabolomics) may provide new insights into ARDS, in part because metabolomics targets a later point in the genomics cascade than is possible with studies of DNA, RNA, and protein biomarkers. Technological advances have made large-scale metabolomic profiling increasingly feasible. Metabolomic approaches have already achieved novel insights in nonpulmonary diseases such as diabetes mellitus and malignancy, as well as in sepsis, a major risk factor for developing ARDS. Metabolomic profiling is a promising approach to identify novel pathways in both patients at risk for developing ARDS as well as in the early phase of established ARDS.
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Brennan, Lorraine. "Metabolomics in nutrition research–a powerful window into nutritional metabolism." Essays in Biochemistry 60, no. 5 (December 15, 2016): 451–58. http://dx.doi.org/10.1042/ebc20160029.
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Metabolomics is the study of small molecules present in biological samples. In recent years it has become evident that such small molecules, called metabolites, play a key role in the development of disease states. Furthermore, metabolomic applications can reveal information about alterations in certain metabolic pathways under different conditions. Data acquisition in metabolomics is usually performed using nuclear magnetic resonance (NMR)-based approaches or mass spectrometry (MS)-based approaches with a more recent trend including the application of multiple platforms in order to maximise the coverage in terms of metabolites measured. The application of metabolomics is rapidly increasing and the present review will highlight applications in nutrition research.
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Gomez-Casati, Diego F., Maria I. Zanor, and María V. Busi. "Metabolomics in Plants and Humans: Applications in the Prevention and Diagnosis of Diseases." BioMed Research International 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/792527.
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In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology. In this review, we emphasize the use and application of metabolomics in human diseases and plant research to improve human health.
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Gonzalez-Covarrubias, Vanessa, Eduardo Martínez-Martínez, and Laura del Bosque-Plata. "The Potential of Metabolomics in Biomedical Applications." Metabolites 12, no. 2 (February 19, 2022): 194. http://dx.doi.org/10.3390/metabo12020194.
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The metabolome offers a dynamic, comprehensive, and precise picture of the phenotype. Current high-throughput technologies have allowed the discovery of relevant metabolites that characterize a wide variety of human phenotypes with respect to health, disease, drug monitoring, and even aging. Metabolomics, parallel to genomics, has led to the discovery of biomarkers and has aided in the understanding of a diversity of molecular mechanisms, highlighting its application in precision medicine. This review focuses on the metabolomics that can be applied to improve human health, as well as its trends and impacts in metabolic and neurodegenerative diseases, cancer, longevity, the exposome, liquid biopsy development, and pharmacometabolomics. The identification of distinct metabolomic profiles will help in the discovery and improvement of clinical strategies to treat human disease. In the years to come, metabolomics will become a tool routinely applied to diagnose and monitor health and disease, aging, or drug development. Biomedical applications of metabolomics can already be foreseen to monitor the progression of metabolic diseases, such as obesity and diabetes, using branched-chain amino acids, acylcarnitines, certain phospholipids, and genomics; these can assess disease severity and predict a potential treatment. Future endeavors should focus on determining the applicability and clinical utility of metabolomic-derived markers and their appropriate implementation in large-scale clinical settings.
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Tirelli, Claudio, Sabrina Mira, Luca Alessandro Belmonte, Federica De Filippi, Mauro De Grassi, Marta Italia, Sara Maggioni, et al. "Exploring the Potential Role of Metabolomics in COPD: A Concise Review." Cells 13, no. 6 (March 7, 2024): 475. http://dx.doi.org/10.3390/cells13060475.
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Chronic Obstructive Pulmonary Disease (COPD) is a pathological condition of the respiratory system characterized by chronic airflow obstruction, associated with changes in the lung parenchyma (pulmonary emphysema), bronchi (chronic bronchitis) and bronchioles (small airways disease). In the last years, the importance of phenotyping and endotyping COPD patients has strongly emerged. Metabolomics refers to the study of metabolites (both intermediate or final products) and their biological processes in biomatrices. The application of metabolomics to respiratory diseases and, particularly, to COPD started more than one decade ago and since then the number of scientific publications on the topic has constantly grown. In respiratory diseases, metabolomic studies have focused on the detection of metabolites derived from biomatrices such as exhaled breath condensate, bronchoalveolar lavage, and also plasma, serum and urine. Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy are powerful tools in the precise identification of potentially prognostic and treatment response biomarkers. The aim of this article was to comprehensively review the relevant literature regarding the applications of metabolomics in COPD, clarifying the potential clinical utility of the metabolomic profile from several biologic matrices in detecting biomarkers of disease and prognosis for COPD. Meanwhile, a complete description of the technological instruments and techniques currently adopted in the metabolomics research will be described.
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González-Domínguez, Raúl, Álvaro González-Domínguez, Ana Sayago, and Ángeles Fernández-Recamales. "Recommendations and Best Practices for Standardizing the Pre-Analytical Processing of Blood and Urine Samples in Metabolomics." Metabolites 10, no. 6 (June 3, 2020): 229. http://dx.doi.org/10.3390/metabo10060229.
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Metabolomics can be significantly influenced by a range of pre-analytical factors, such as sample collection, pre-processing, aliquoting, transport, storage and thawing. This therefore shows the crucial need for standardizing the pre-analytical phase with the aim of minimizing the inter-sample variability driven by these technical issues, as well as for maintaining the metabolic integrity of biological samples to ensure that metabolomic profiles are a direct expression of the in vivo biochemical status. This review article provides an updated literature revision of the most important factors related to sample handling and pre-processing that may affect metabolomics results, particularly focusing on the most commonly investigated biofluids in metabolomics, namely blood plasma/serum and urine. Finally, we also provide some general recommendations and best practices aimed to standardize and accurately report all these pre-analytical aspects in metabolomics research.
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Hao, Dan, Jiangsong Bai, Jianyong Du, Xiaoping Wu, Bo Thomsen, Hongding Gao, Guosheng Su, and Xiao Wang. "Overview of Metabolomic Analysis and the Integration with Multi-Omics for Economic Traits in Cattle." Metabolites 11, no. 11 (October 30, 2021): 753. http://dx.doi.org/10.3390/metabo11110753.
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Metabolomics has been applied to measure the dynamic metabolic responses, to understand the systematic biological networks, to reveal the potential genetic architecture, etc., for human diseases and livestock traits. For example, the current published results include the detected relevant candidate metabolites, identified metabolic pathways, potential systematic networks, etc., for different cattle traits that can be applied for further metabolomic and integrated omics studies. Therefore, summarizing the applications of metabolomics for economic traits is required in cattle. We here provide a comprehensive review about metabolomic analysis and its integration with other omics in five aspects: (1) characterization of the metabolomic profile of cattle; (2) metabolomic applications in cattle; (3) integrated metabolomic analysis with other omics; (4) methods and tools in metabolomic analysis; and (5) further potentialities. The review aims to investigate the existing metabolomic studies by highlighting the results in cattle, integrated with other omics studies, to understand the metabolic mechanisms underlying the economic traits and to provide useful information for further research and practical breeding programs in cattle.
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Damiani, Chiara, Daniela Gaglio, Elena Sacco, Lilia Alberghina, and Marco Vanoni. "Systems metabolomics: from metabolomic snapshots to design principles." Current Opinion in Biotechnology 63 (June 2020): 190–99. http://dx.doi.org/10.1016/j.copbio.2020.02.013.
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Moing, Annick, Pierre Pétriacq, and Sonia Osorio. "Special Issue on “Fruit Metabolism and Metabolomics”." Metabolites 10, no. 6 (June 3, 2020): 230. http://dx.doi.org/10.3390/metabo10060230.
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Over the past 10 years, knowledge about several aspects of fruit metabolism has been greatly improved. Notably, high-throughput metabolomic technologies have allowed quantifying metabolite levels across various biological processes, and identifying the genes that underly fruit development and ripening. This Special Issue is designed to exemplify the current use of metabolomics studies of temperate and tropical fruit for basic research as well as practical applications. It includes articles about different aspects of fruit biochemical phenotyping, fruit metabolism before and after harvest, including primary and specialized metabolisms, and bioactive compounds involved in growth and environmental responses. The effect of genotype, stages of development or fruit tissue on metabolomic profiles and corresponding metabolism regulations are addressed, as well as the combination of other omics with metabolomics for fruit metabolism studies.
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Patschan, Daniel, Susann Patschan, Igor Matyukhin, Oliver Ritter, and Werner Dammermann. "Metabolomics in Acute Kidney Injury: The Clinical Perspective." Journal of Clinical Medicine 12, no. 12 (June 16, 2023): 4083. http://dx.doi.org/10.3390/jcm12124083.
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Background: Acute kidney injury (AKI) affects increasing numbers of hospitalized patients worldwide. The diagnosis of AKI is made too late in most individuals since it is still based on dynamic changes in serum creatinine. In recent years, new AKI biomarkers have been identified; however, none of these can reliably replace serum creatinine yet. Metabolomic profiling (metabolomics) allows the concomitant detection and quantification of large numbers of metabolites from biological specimens. The current article aims to summarize clinical studies on metabolomics in AKI diagnosis and risk prediction. Methods: The following databases were searched for references: PubMed, Web of Science, Cochrane Library, and Scopus, and the period lasted from 1940 until 2022. The following terms were utilized: ‘AKI’ OR ‘Acute Kidney Injury’ OR ‘Acute Renal Failure’ AND ‘metabolomics’ OR ‘metabolic profiling’ OR ‘omics’ AND ‘risk’ OR ‘death’ OR ‘survival’ OR ‘dialysis’ OR ‘KRT’ OR ‘kidney replacement therapy’ OR ‘RRT’ OR ‘renal replacement therapy’ OR ‘recovery of kidney function’ OR ‘renal recovery’ OR ‘kidney recovery’ OR ‘outcome’. Studies on AKI risk prediction were only selected if metabolomic profiling allowed differentiation between subjects that fulfilled a risk category (death or KRT or recovery of kidney function) and those who did not. Experimental (animal-based) studies were not included. Results: In total, eight studies were identified. Six studies were related to the diagnosis of AKI; two studies were performed on metabolic analysis in AKI risk (death) prediction. Metabolomics studies in AKI already helped to identify new biomarkers for AKI diagnosis. The data on metabolomics for AKI risk prediction (death, KRT, recovery of kidney function), however, are very limited. Conclusions: Both the heterogenous etiology and the high degree of pathogenetic complexity of AKI most likely require integrated approaches such as metabolomics and/or additional types of ‘-omics’ studies to improve clinical outcomes in AKI.
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Huang, Katherine, Natalie Thomas, Paul R. Gooley, and Christopher W. Armstrong. "Systematic Review of NMR-Based Metabolomics Practices in Human Disease Research." Metabolites 12, no. 10 (October 12, 2022): 963. http://dx.doi.org/10.3390/metabo12100963.
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Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular “omics” technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research.
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Resurreccion, Eleazer P., and Ka-wing Fong. "The Integration of Metabolomics with Other Omics: Insights into Understanding Prostate Cancer." Metabolites 12, no. 6 (May 27, 2022): 488. http://dx.doi.org/10.3390/metabo12060488.
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Our understanding of prostate cancer (PCa) has shifted from solely caused by a few genetic aberrations to a combination of complex biochemical dysregulations with the prostate metabolome at its core. The role of metabolomics in analyzing the pathophysiology of PCa is indispensable. However, to fully elucidate real-time complex dysregulation in prostate cells, an integrated approach based on metabolomics and other omics is warranted. Individually, genomics, transcriptomics, and proteomics are robust, but they are not enough to achieve a holistic view of PCa tumorigenesis. This review is the first of its kind to focus solely on the integration of metabolomics with multi-omic platforms in PCa research, including a detailed emphasis on the metabolomic profile of PCa. The authors intend to provide researchers in the field with a comprehensive knowledge base in PCa metabolomics and offer perspectives on overcoming limitations of the tool to guide future point-of-care applications.
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Govorov, Igor, Stanislav Sitkin, Tatyana Pervunina, Alexey Moskvin, Denis Baranenko, and Eduard Komlichenko. "Metabolomic Biomarkers in Gynecology: A Treasure Path or a False Path?" Current Medicinal Chemistry 27, no. 22 (June 30, 2020): 3611–22. http://dx.doi.org/10.2174/0929867326666190104124245.
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Omic-technologies (genomics, transcriptomics, proteomics and metabolomics) have become more important in current medical science. Among them, it is metabolomics that most accurately reflects the minor changes in body functioning, as it focuses on metabolome – the group of the metabolism products, both intermediate and end. Therefore, metabolomics is actively engaged in fundamental and clinical studies and search for potential biomarkers. The biomarker could be used in diagnostics, management and stratification of the patients, as well as in prognosing the outcomes. The good example is gynecology, since many gynecological diseases lack effective biomarkers. In the current review, we aimed to summarize the results of the studies, devoted to the search of potential metabolomic biomarkers for the most common gynecological diseases.
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Gross, Thomas, Mark Mapstone, Ricardo Miramontes, Robert Padilla, Amrita K. Cheema, Fabio Macciardi, Howard J. Federoff, and Massimo S. Fiandaca. "Toward Reproducible Results from Targeted Metabolomic Studies: Perspectives for Data Pre-processing and a Basis for Analytic Pipeline Development." Current Topics in Medicinal Chemistry 18, no. 11 (August 28, 2018): 883–95. http://dx.doi.org/10.2174/1568026618666180711144323.
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Contemporary metabolomics experiments generate a rich array of complex high-dimensional data. Consequently, there have been concurrent efforts to develop methodological standards and analytical workflows to streamline the generation of meaningful biochemical and clinical inferences from raw data generated using an analytical platform like mass spectrometry. While such considerations have been frequently addressed in untargeted metabolomics (i.e., the broad survey of all distinguishable metabolites within a sample of interest), this methodological scrutiny has seldom been applied to data generated using commercial, targeted metabolomics kits. We suggest that this may, in part, account for past and more recent incomplete replications of previously specified biomarker panels. Herein, we identify common impediments challenging the analysis of raw, targeted metabolomic abundance data from a commercial kit and review methods to remedy these issues. In doing so, we propose an analytical pipeline suitable for the pre-processing of data for downstream biomarker discovery. Operational and statistical considerations for integrating targeted data sets across experimental sites and analytical batches are discussed, as are best practices for developing predictive models relating pre-processed metabolomic data to associated phenotypic information.
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Mamazhakypov, Argen, Astrid Weiß, Sven Zukunft, Akylbek Sydykov, Baktybek Kojonazarov, Jochen Wilhelm, Christina Vroom, et al. "Effects of macitentan and tadalafil monotherapy or their combination on the right ventricle and plasma metabolites in pulmonary hypertensive rats." Pulmonary Circulation 10, no. 4 (October 2020): 204589402094728. http://dx.doi.org/10.1177/2045894020947283.
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Pulmonary arterial hypertension is a severe respiratory disease characterized by pulmonary artery remodeling. RV dysfunction and dysregulated circulating metabolomics are associated with adverse outcomes in pulmonary arterial hypertension. We investigated effects of tadalafil and macitentan alone or in combination on the RV and plasma metabolomics in SuHx and PAB models. For SuHx model, rats were injected with SU5416 and exposed to hypoxia for three weeks and then were returned to normoxia and treated with either tadalafil (10 mg/kg in chow) or macitentan (10 mg/kg in chow) or their combination (both 10 mg/kg in chow) for two weeks. For PAB model, rats were subjected to either sham or PAB surgery for three weeks and treated with above-mentioned drugs from week 1 to week 3. Following terminal echocardiographic and hemodynamic measurements, tissue samples were collected for metabolomic, histological and gene expression analysis. Both SuHx and PAB rats developed RV remodeling/dysfunction with severe and mild plasma metabolomic alterations, respectively. In SuHx rats, tadalafil and macitentan alone or in combination improved RV remodeling/function with the effects of macitentan and combination therapy being superior to tadalafil. All therapies similarly attenuated SuHx-induced changes in plasma metabolomics. In PAB rats, only macitentan improved RV remodeling/function, while only tadalafil attenuated PAB-induced changes in plasma metabolomics.
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Jang, Won-Jun, Jae Yoon Choi, Byoungduck Park, Ji Hae Seo, Young Ho Seo, Sangkil Lee, Chul-Ho Jeong, and Sooyeun Lee. "Hair Metabolomics in Animal Studies and Clinical Settings." Molecules 24, no. 12 (June 12, 2019): 2195. http://dx.doi.org/10.3390/molecules24122195.
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Metabolomics is a powerful tool used to understand comprehensive changes in the metabolic response and to study the phenotype of an organism by instrumental analysis. It most commonly involves mass spectrometry followed by data mining and metabolite assignment. For the last few decades, hair has been used as a valuable analytical sample to investigate retrospective xenobiotic exposure as it provides a wider window of detection than other biological samples such as saliva, plasma, and urine. Hair contains functional metabolomes such as amino acids and lipids. Moreover, segmental analysis of hair based on its growth rate can provide information on metabolic changes over time. Therefore, it has great potential as a metabolomics sample to monitor chronic diseases, including drug addiction or abnormal conditions. In the current review, the latest applications of hair metabolomics in animal studies and clinical settings are highlighted. For this purpose, we review and discuss the characteristics of hair as a metabolomics sample, the analytical techniques employed in hair metabolomics and the consequence of hair metabolome alterations in recent studies. Through this, the value of hair as an alternative biological sample in metabolomics is highlighted.
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Astafyeva, O. V., Z. V. Zharkova, A. L. Yasenyavskaya, I. B. Nikitina, I. V. Goretova, I. V. Fedoseev, O. A. Bashkina, and M. A. Samotrueva. "Overview of metabolomic markers used for diagnosing cardiovascular diseases." Сибирский научный медицинский журнал 42, no. 1 (February 20, 2022): 13–29. http://dx.doi.org/10.18699/ssmj20220102.
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At present, metabolomics is an intensively developing approach to the specific diagnosis of cardiovascular diseases. Metabolic analysis allows the study of complete metabolomic profiles and their deviations resulting from changes, for example, gene and RNA expression, protein activity, or environmental factors. Analysis of the metabolomic blood profile helps in solving a large number of scientific and clinical problems, one of which is the search for markers of diseases, in particular, cardiovascular diseases (CVD). Aim of the study was to investigate metabolomic markers used for the diagnosis of cardiovascular diseases on the basis of literature data. Material and methods. The literature data was analyzed for key words: cardiovascular diseases, metabolomics, metabolic profile, metabolomic markers in da- tabases PubMed, Scopus, Web of Science, CyberLeninka, PatentDB, Science Direct Open Access, eLibrary. Results. Analysis of literature data and patent search confirms the high importance of metabolomic markers in the diagnosis of CVD. In the patent literature, BNP/NT-proBNP is most common used as a metabolic marker of CVD (11.27 %). The use of CRP (8.99 %) and troponin (8.49 %) is also common. PICP (0.02 %), sVCAM-1 (0.09 %), stimulating growth factor ST-2 (0.12 %) and thrombomodulin (0.12 %) as metabolic markers of CVD. Conclusions. Against the backdrop of analytical methods, metabolomics is the most important diagnostic area. At the same time, it should be noted that by combining the results of the analysis of metabolic studies with others, for example, genomic and proteomic, one can get a complete picture of the pathogenesis of diseases, assess the risk of complications, and also determine the effectiveness of the treatment.
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Stocchero, Matteo, Emanuela Locci, Ernesto d’Aloja, Matteo Nioi, Eugenio Baraldi, and Giuseppe Giordano. "PLS2 in Metabolomics." Metabolites 9, no. 3 (March 15, 2019): 51. http://dx.doi.org/10.3390/metabo9030051.
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Metabolomics is the systematic study of the small-molecule profiles of biological samples produced by specific cellular processes. The high-throughput technologies used in metabolomic investigations generate datasets where variables are strongly correlated and redundancy is present in the data. Discovering the hidden information is a challenge, and suitable approaches for data analysis must be employed. Projection to latent structures regression (PLS) has successfully solved a large number of problems, from multivariate calibration to classification, becoming a basic tool of metabolomics. PLS2 is the most used implementation of PLS. Despite its success, PLS2 showed some limitations when the so called ‘structured noise’ affects the data. Suitable methods have been recently introduced to patch up these limitations. In this study, a comprehensive and up-to-date presentation of PLS2 focused on metabolomics is provided. After a brief discussion of the mathematical framework of PLS2, the post-transformation procedure is introduced as a basic tool for model interpretation. Orthogonally-constrained PLS2 is presented as strategy to include constraints in the model according to the experimental design. Two experimental datasets are investigated to show how PLS2 and its improvements work in practice.
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Byers, Nathaniel, Amy Fleshman, Rushika Perera, and Claudia Molins. "Metabolomic Insights into Human Arboviral Infections: Dengue, Chikungunya, and Zika Viruses." Viruses 11, no. 3 (March 6, 2019): 225. http://dx.doi.org/10.3390/v11030225.
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The global burden of arboviral diseases and the limited success in controlling them calls for innovative methods to understand arbovirus infections. Metabolomics has been applied to detect alterations in host physiology during infection. This approach relies on mass spectrometry or nuclear magnetic resonance spectroscopy to evaluate how perturbations in biological systems alter metabolic pathways, allowing for differentiation of closely related conditions. Because viruses heavily depend on host resources and pathways, they present unique challenges for characterizing metabolic changes. Here, we review the literature on metabolomics of arboviruses and focus on the interpretation of identified molecular features. Metabolomics has revealed biomarkers that differentiate disease states and outcomes, and has shown similarities in metabolic alterations caused by different viruses (e.g., lipid metabolism). Researchers investigating such metabolomic alterations aim to better understand host–virus dynamics, identify diagnostically useful molecular features, discern perturbed pathways for therapeutics, and guide further biochemical research. This review focuses on lessons derived from metabolomics studies on samples from arbovirus-infected humans.
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Kráľová, Katarína, Josef Jampílek, and Ivan Ostrovský. "Metabolomics - Useful Tool for Study of Plant Responses to Abiotic Stresses." Ecological Chemistry and Engineering S 19, no. 2 (January 1, 2012): 133–61. http://dx.doi.org/10.2478/v10216-011-0012-0.
Full textAbstract:
Metabolomics - Useful Tool for Study of Plant Responses to Abiotic Stresses Abiotic stresses are produced by inappropriate levels of physical components of the environment and cause plant injury through unique mechanisms that result in specific responses. Metabolomics is a relatively new approach aimed at improved understanding of metabolic networks and the subsequent biochemical composition of plants and other biological organisms. The paper is focused on the use of metabolomics, metabolic profiling and metabolic fingerprinting to study plant responses to some environmental stresses (eg elevated temperature, chilling and freezing, drought, high salinity, UV radiation, high ozone levels, nutrient deficiency, oxidative stress, herbicides and heavy metals). Attention is also devoted to the effects of some environmental factors on plants such as high or low levels of CO2 or different levels of irradiance. Alterations of plants metabolites due to multiple abiotic stresses (drought-heat, drought-salinity, elevated CO2-salinity) are analysed as well. In addition, metabolomic approach to study plant responses to some artificial abiotic stresses, mechanical stress or pulsed electric field-induced stress is discussed. The most important analytical methods applied in metabolomics are presented and perspectives of metabolomics exploitation in the future are outlined, too.