1
|
Xu C, Shao J. High-throughput omics technologies in inflammatory bowel disease. Clin Chim Acta 2024; 555:117828. [PMID: 38355001 DOI: 10.1016/j.cca.2024.117828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 02/06/2024] [Accepted: 02/10/2024] [Indexed: 02/16/2024]
Abstract
Inflammatory bowel disease (IBD) is a chronic, relapsing intestinal disease. Elucidation of the pathogenic mechanisms of IBD requires high-throughput technologies (HTTs) to effectively obtain and analyze large amounts of data. Recently, HTTs have been widely used in IBD, including genomics, transcriptomics, proteomics, microbiomics, metabolomics and single-cell sequencing. When combined with endoscopy, the application of these technologies can provide an in-depth understanding on the alterations of intestinal microbe diversity and abundance, the abnormalities of signaling pathway-mediated immune responses and functionality, and the evaluation of therapeutic effects, improving the accuracy of early diagnosis and treatment of IBD. This review comprehensively summarizes the development and advancement of HTTs, and also highlights the challenges and future directions of these technologies in IBD research. Although HTTs have made striking breakthrough in IBD, more standardized methods and large-scale dataset processing are still needed to achieve the goal of personalized medicine.
Collapse
Affiliation(s)
- Chen Xu
- Laboratory of Anti-infection and Immunity, College of Integrated Chinese and Western Medicine (College of Life Science), Anhui University of Chinese Medicine, Zhijing Building, 350 Longzihu Road, Xinzhan District, Hefei 230012, Anhui, PR China
| | - Jing Shao
- Laboratory of Anti-infection and Immunity, College of Integrated Chinese and Western Medicine (College of Life Science), Anhui University of Chinese Medicine, Zhijing Building, 350 Longzihu Road, Xinzhan District, Hefei 230012, Anhui, PR China; Institute of Integrated Traditional Chinese and Western Medicine, Anhui Academy of Chinese Medicine, Zhijing Building, 350 Longzihu Road, Xinzhan District, Hefei 230012, Anhui, PR China.
| |
Collapse
|
2
|
Vignoli A, Meoni G, Ghini V, Di Cesare F, Tenori L, Luchinat C, Turano P. NMR-Based Metabolomics to Evaluate Individual Response to Treatments. Handb Exp Pharmacol 2023; 277:209-245. [PMID: 36318327 DOI: 10.1007/164_2022_618] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The aim of this chapter is to highlight the various aspects of metabolomics in relation to health and diseases, starting from the definition of metabolic space and of how individuals tend to maintain their own position in this space. Physio-pathological stimuli may cause individuals to lose their position and then regain it, or move irreversibly to other positions. By way of examples, mostly selected from our own work using 1H NMR on biological fluids, we describe the effects on the individual metabolomic fingerprint of mild external interventions, such as diet or probiotic administration. Then we move to pathologies (such as celiac disease, various types of cancer, viral infections, and other diseases), each characterized by a well-defined metabolomic fingerprint. We describe the effects of drugs on the disease fingerprint and on its reversal to a healthy metabolomic status. Drug toxicity can be also monitored by metabolomics. We also show how the individual metabolomic fingerprint at the onset of a disease may discriminate responders from non-responders to a given drug, or how it may be prognostic of e.g., cancer recurrence after many years. In parallel with fingerprinting, profiling (i.e., the identification and quantification of many metabolites and, in the case of selected biofluids, of the lipoprotein components that contribute to the 1H NMR spectral features) can provide hints on the metabolic pathways that are altered by a disease and assess their restoration after treatment.
Collapse
Affiliation(s)
- Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Gaia Meoni
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Veronica Ghini
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
| | - Paola Turano
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy. .,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy. .,Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy.
| |
Collapse
|
3
|
Cediel G, Teis A, Codina P, Julve J, Domingo M, Santiago-Vacas E, Castelblanco E, Amigó N, Lupón J, Mauricio D, Alonso N, Bayés-Genís A. GlycA and GlycB as Inflammatory Markers in Chronic Heart Failure. Am J Cardiol 2022; 181:79-86. [PMID: 36008162 DOI: 10.1016/j.amjcard.2022.07.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/27/2022] [Accepted: 07/05/2022] [Indexed: 11/01/2022]
Abstract
The role of inflammation in heart failure (HF) has been extensively described, but it is uncertain whether inflammation exerts a different prognostic influence according to etiology. We aimed to examine the inflammatory state in chronic HF by measuring N-acetylglucosamine/galactosamine (GlycA) and sialic acid (GlycB), evolving proton nuclear magnetic resonance biomarkers of systemic inflammation, and explore their prognostic value in patients with chronic HF. The primary end point was a composite of all-cause death and HF readmission. A total of 429 patients were included. GlycB correlated with interleukin-1 receptor-like 1 in the whole cohort (r2 = 0.14, p = 0.011) and the subgroup of nonischemic etiology (r2 = 0.31, p <0.001). No association was found with New York Heart Association functional class or left ventricular ejection fraction. In patients with nonischemic HF (52.2%, n = 224), GlycA and GlycB exhibited significant association with the composite end point (hazard ratio [HR] 1.19, 95% confidence interval [CI] 1.06 to 1.33, p = 0.004 and HR 2.13, 95% CI 1.43 to 3.13, p <0.001; respectively) and GlycB with HF readmission after multivariable adjustment (HR 2.25, 95% CI 1.54 to 3.30, p <0.001). GlycB levels were also associated with a greater risk of HF-related recurrent admissions (adjusted incidence rate ratio 1.33, 95% CI = 1.07 to 1.65, p = 0.009). None of the markers were associated with the clinical end points in patients with ischemic HF. In conclusion, GlycA and GlycB represent an evolving approach to inflammation status with prognostic value in long-term outcomes in patients with nonischemic HF.
Collapse
Affiliation(s)
- German Cediel
- Heart Failure Unit and Cardiology Department, Hospital Universitari Germans Trias I Pujol, Badalona, Spain; Center for Biomedical Research on Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain
| | - Albert Teis
- Heart Failure Unit and Cardiology Department, Hospital Universitari Germans Trias I Pujol, Badalona, Spain; Center for Biomedical Research on Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Pau Codina
- Heart Failure Unit and Cardiology Department, Hospital Universitari Germans Trias I Pujol, Badalona, Spain
| | - Josep Julve
- Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain; Sant Pau Biomedical Research Institute (IIB Sant Pau), Barcelona, Spain
| | - Mar Domingo
- Heart Failure Unit and Cardiology Department, Hospital Universitari Germans Trias I Pujol, Badalona, Spain
| | - Evelyn Santiago-Vacas
- Heart Failure Unit and Cardiology Department, Hospital Universitari Germans Trias I Pujol, Badalona, Spain; Center for Biomedical Research on Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain
| | - Esmeralda Castelblanco
- Department of Internal Medicine, Endocrinology, Metabolism and Lipid Research Division, Washington University School of Medicine, St Louis, Missouri; Unitat de Suport a la Recerca Barcelona, Institut Universitari d'Investigació en Atenció Primària Jordi Gol i Gurina (IDIAP Jordi Gol), Barcelona, Spain
| | - Nuria Amigó
- Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain; Departamento de Ciencias Médicas Básicas, Universidad Rovira i Virgili, Tarragona, Spain; Biosfer Teslab - Metabolomic Platform, Universidad Rovira i Virgili, Tarragona, Spain
| | - Josep Lupón
- Heart Failure Unit and Cardiology Department, Hospital Universitari Germans Trias I Pujol, Badalona, Spain; Center for Biomedical Research on Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Didac Mauricio
- Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain; Unitat de Suport a la Recerca Barcelona, Institut Universitari d'Investigació en Atenció Primària Jordi Gol i Gurina (IDIAP Jordi Gol), Barcelona, Spain; Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau & Sant Pau Biomedical Research Institute (IIB Sant Pau), Barcelona, Spain; Faculty of Medicine, University of Vic (UVIC), Vic, Spain
| | - Nuria Alonso
- Center for Biomedical Research on Diabetes and Associated Metabolic Diseases (CIBERDEM), Instituto de Salud Carlos III, Madrid, Spain; Department of Endocrinology & Nutrition, Hospital Universitari Germans Trias i Pujol, Badalona, Spain
| | - Antoni Bayés-Genís
- Heart Failure Unit and Cardiology Department, Hospital Universitari Germans Trias I Pujol, Badalona, Spain; Center for Biomedical Research on Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, Universitat Autonoma de Barcelona, Barcelona, Spain.
| |
Collapse
|
4
|
Larkin JR, Anthony S, Johanssen VA, Yeo T, Sealey M, Yates AG, Smith CF, Claridge TD, Nicholson BD, Moreland JA, Gleeson F, Sibson NR, Anthony DC, Probert F. Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms. Clin Cancer Res 2022; 28:1651-1661. [PMID: 34983789 PMCID: PMC7613224 DOI: 10.1158/1078-0432.ccr-21-2855] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/08/2021] [Accepted: 11/16/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE Early diagnosis of cancer is critical for improving patient outcomes, but cancers may be hard to diagnose if patients present with nonspecific signs and symptoms. We have previously shown that nuclear magnetic resonance (NMR) metabolomics analysis can detect cancer in animal models and distinguish between differing metastatic disease burdens. Here, we hypothesized that biomarkers within the blood metabolome could identify cancers within a mixed population of patients referred from primary care with nonspecific symptoms, the so-called "low-risk, but not no-risk" patient group, as well as distinguishing between those with and without metastatic disease. EXPERIMENTAL DESIGN Patients (n = 304 comprising modeling, n = 192, and test, n = 92) were recruited from 2017 to 2018 from the Oxfordshire Suspected CANcer (SCAN) pathway, a multidisciplinary diagnostic center (MDC) referral pathway for patients with nonspecific signs and symptoms. Blood was collected and analyzed by NMR metabolomics. Orthogonal partial least squares discriminatory analysis (OPLS-DA) models separated patients, based upon diagnoses received from the MDC assessment, within 62 days of initial appointment. RESULTS Area under the ROC curve for identifying patients with solid tumors in the independent test set was 0.83 [95% confidence interval (CI): 0.72-0.95]. Maximum sensitivity and specificity were 94% (95% CI: 73-99) and 82% (95% CI: 75-87), respectively. We could also identify patients with metastatic disease in the cohort of patients with cancer with sensitivity and specificity of 94% (95% CI: 72-99) and 88% (95% CI: 53-98), respectively. CONCLUSIONS For a mixed group of patients referred from primary care with nonspecific signs and symptoms, NMR-based metabolomics can assist their diagnosis, and may differentiate both those with malignancies and those with and without metastatic disease. See related commentary by Van Tine and Lyssiotis, p. 1477.
Collapse
Affiliation(s)
- James R. Larkin
- Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom
| | - Susan Anthony
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Vanessa A. Johanssen
- Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom
| | - Tianrong Yeo
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
- Department of Neurology, National Neuroscience Institute, Singapore
- Duke-NUS Medical School, Singapore
| | - Megan Sealey
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Abi G. Yates
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Claire Friedemann Smith
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | | | - Brian D. Nicholson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Julie-Ann Moreland
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Fergus Gleeson
- Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Nicola R. Sibson
- Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom
| | - Daniel C. Anthony
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Fay Probert
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
- Department of Chemistry, University of Oxford, Oxford, United Kingdom
| |
Collapse
|
5
|
Ismaeel A, Lavado R, Koutakis P. Metabolomics of peripheral artery disease. Adv Clin Chem 2022; 106:67-89. [PMID: 35152975 DOI: 10.1016/bs.acc.2021.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The science of metabolomics has emerged as a novel tool for studying changes in metabolism that accompany different disease states. Several studies have applied this evolving field to the study of various cardiovascular disease states, which has led to improved understanding of metabolic changes that underlie heart failure and ischemic heart disease. A significant amount of progress has also been made in the identification of novel biomarkers of cardiovascular disease. Another common atherosclerotic disease, peripheral artery disease (PAD) affects arteries of the lower extremities. Although certain aspects of the disease pathophysiology overlap with other cardiovascular diseases in general, PAD patients suffer unique manifestations that lead to significant morbidity and mortality as well as severe functional limitations. Furthermore, because over half of PAD patients are asymptomatic, there is a need for improved diagnostic and screening methods. Identification of metabolites associated with the disease may thus be a promising approach for PAD. However, PAD remains highly understudied. In this chapter, we discuss the application of metabolomics to the study of PAD.
Collapse
Affiliation(s)
- Ahmed Ismaeel
- Department of Biology, Baylor University, Waco, TX, United States
| | - Ramon Lavado
- Department of Environmental Science, Baylor University, Waco, TX, United States
| | | |
Collapse
|
6
|
Metabolomics Insights into Inflammatory Bowel Disease: A Comprehensive Review. Pharmaceuticals (Basel) 2021; 14:ph14111190. [PMID: 34832973 PMCID: PMC8625096 DOI: 10.3390/ph14111190] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/11/2021] [Accepted: 11/17/2021] [Indexed: 02/06/2023] Open
Abstract
Inflammatory bowel disease (IBD) is a chronic, complex relapsing disorder characterised by immune dysregulation, gut microbiota alteration, and disturbed intestinal permeability. The diagnosis and the management of IBD are challenging due to the recurrent nature and complex evolution of the disease. Furthermore, the molecular mechanism underlying the aetiology and pathogenesis of IBD is still poorly understood. There is an unmet need for novel, reliable, and noninvasive tools for diagnosing and monitoring IBD. In addition, metabolomic profiles may provide a priori determination of optimal therapeutics and reveal novel targets for therapies. This review tries to gather scientific evidence to summarise the emerging contribution of metabolomics to elucidate the mechanisms underlying IBD and changes associated with disease phenotype and therapies, as well as to identify biomarkers with metabolic imbalance in those patients. Metabolite changes during health and disease could provide insights into the disease pathogenesis and the discovery of novel indicators for the diagnosis and prognosis assessment of IBD. Metabolomic studies in IBD have shown changes in tricarboxylic acid cycle intermediates, amino-acid and fatty-acid metabolism, and oxidative pathways. Metabolomics has made progress towards identifying metabolic alterations that may provide clinically useful biomarkers and a deeper understanding of the disease. However, at present, there is insufficient evidence evaluating the predictive accuracy of these molecular signatures and their diagnostic ability, which is necessary before metabolomic data can be translated into clinical practice.
Collapse
|
7
|
A Scoping Review of the Application of Metabolomics in Nutrition Research: The Literature Survey 2000-2019. Nutrients 2021; 13:nu13113760. [PMID: 34836016 PMCID: PMC8623534 DOI: 10.3390/nu13113760] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 10/19/2021] [Accepted: 10/19/2021] [Indexed: 12/29/2022] Open
Abstract
Nutrimetabolomics is an emerging field in nutrition research, and it is expected to play a significant role in deciphering the interaction between diet and health. Through the development of omics technology over the last two decades, the definition of food and nutrition has changed from sources of energy and major/micro-nutrients to an essential exposure factor that determines health risks. Furthermore, this new approach has enabled nutrition research to identify dietary biomarkers and to deepen the understanding of metabolic dynamics and the impacts on health risks. However, so far, candidate markers identified by metabolomics have not been clinically applied and more efforts should be made to validate those. To help nutrition researchers better understand the potential of its application, this scoping review outlined the historical transition, recent focuses, and future prospects of the new realm, based on trends in the number of human research articles from the early stage of 2000 to the present of 2019 by searching the Medical Literature Analysis and Retrieval System Online (MEDLINE). Among them, objective dietary assessment, metabolic profiling, and health risk prediction were positioned as three of the principal applications. The continued growth will enable nutrimetabolomics research to contribute to personalized nutrition in the future.
Collapse
|
8
|
From bedside to bench-practical considerations to avoid pre-analytical pitfalls and assess sample quality for high-resolution metabolomics and lipidomics analyses of body fluids. Anal Bioanal Chem 2021; 413:5567-5585. [PMID: 34159398 PMCID: PMC8410705 DOI: 10.1007/s00216-021-03450-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 05/24/2021] [Accepted: 05/31/2021] [Indexed: 11/22/2022]
Abstract
The stability of lipids and other metabolites in human body fluids ranges from very stable over several days to very unstable within minutes after sample collection. Since the high-resolution analytics of metabolomics and lipidomics approaches comprise all these compounds, the handling of body fluid samples, and thus the pre-analytical phase, is of utmost importance to obtain valid profiling data. This phase consists of two parts, sample collection in the hospital (“bedside”) and sample processing in the laboratory (“bench”). For sample quality, the apparently simple steps in the hospital are much more critical than the “bench” side handling, where (bio)analytical chemists focus on highly standardized processing for high-resolution analysis under well-controlled conditions. This review discusses the most critical pre-analytical steps for sample quality from patient preparation; collection of body fluids (blood, urine, cerebrospinal fluid) to sample handling, transport, and storage in freezers; and subsequent thawing using current literature, as well as own investigations and practical experiences in the hospital. Furthermore, it provides guidance for (bio)analytical chemists to detect and prevent potential pre-analytical pitfalls at the “bedside,” and how to assess the quality of already collected body fluid samples. A knowledge base is provided allowing one to decide whether or not the sample quality is acceptable for its intended use in distinct profiling approaches and to select the most suitable samples for high-resolution metabolomics and lipidomics investigations.
Collapse
|
9
|
Probert F, Yeo T, Zhou Y, Sealey M, Arora S, Palace J, Claridge TDW, Hillenbrand R, Oechtering J, Leppert D, Kuhle J, Anthony DC. Integrative biochemical, proteomics and metabolomics cerebrospinal fluid biomarkers predict clinical conversion to multiple sclerosis. Brain Commun 2021; 3:fcab084. [PMID: 33997784 PMCID: PMC8111065 DOI: 10.1093/braincomms/fcab084] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 03/18/2021] [Accepted: 03/19/2021] [Indexed: 12/23/2022] Open
Abstract
Eighty-five percent of multiple sclerosis cases begin with a discrete attack termed clinically isolated syndrome, but 37% of clinically isolated syndrome patients do not experience a relapse within 20 years of onset. Thus, the identification of biomarkers able to differentiate between individuals who are most likely to have a second clinical attack from those who remain in the clinically isolated syndrome stage is essential to apply a personalized medicine approach. We sought to identify biomarkers from biochemical, metabolic and proteomic screens that predict clinically defined conversion from clinically isolated syndrome to multiple sclerosis and generate a multi-omics-based algorithm with higher prognostic accuracy than any currently available test. An integrative multi-variate approach was applied to the analysis of cerebrospinal fluid samples taken from 54 individuals at the point of clinically isolated syndrome with 2-10 years of subsequent follow-up enabling stratification into clinical converters and non-converters. Leukocyte counts were significantly elevated at onset in the clinical converters and predict the occurrence of a second attack with 70% accuracy. Myo-inositol levels were significantly increased in clinical converters while glucose levels were decreased, predicting transition to multiple sclerosis with accuracies of 72% and 63%, respectively. Proteomics analysis identified 89 novel gene products related to conversion. The identified biochemical and protein biomarkers were combined to produce an algorithm with predictive accuracy of 83% for the transition to clinically defined multiple sclerosis, outperforming any individual biomarker in isolation including oligoclonal bands. The identified protein biomarkers are consistent with an exaggerated immune response, perturbed energy metabolism and multiple sclerosis pathology in the clinical converter group. The new biomarkers presented provide novel insight into the molecular pathways promoting disease while the multi-omics algorithm provides a means to more accurately predict whether an individual is likely to convert to clinically defined multiple sclerosis.
Collapse
Affiliation(s)
- Fay Probert
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK.,Department of Chemistry, University of Oxford, Oxford OX1 3TA, UK
| | - Tianrong Yeo
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK.,Department of Neurology, National Neuroscience Institute, Singapore 308437, Singapore
| | - Yifan Zhou
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
| | - Megan Sealey
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
| | - Siddharth Arora
- Mathematical Institute, University of Oxford, Oxford OX2 6GG, UK
| | - Jacqueline Palace
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK
| | | | | | - Johanna Oechtering
- Neurology, Departments of Medicine, Clinical Research and Biomedicine, University Hospital Basel, University of Basel, Basel CH-4031, Switzerland
| | - David Leppert
- Neurology, Departments of Medicine, Clinical Research and Biomedicine, University Hospital Basel, University of Basel, Basel CH-4031, Switzerland
| | - Jens Kuhle
- Neurology, Departments of Medicine, Clinical Research and Biomedicine, University Hospital Basel, University of Basel, Basel CH-4031, Switzerland
| | - Daniel C Anthony
- Department of Pharmacology, University of Oxford, Oxford OX1 3QT, UK
| |
Collapse
|
10
|
Rosli H, Shahar S, Rajab NF, Che Din N, Haron H. The effects of polyphenols-rich tropical fruit juice on cognitive function and metabolomics profile - a randomized controlled trial in middle-aged women. Nutr Neurosci 2021; 25:1577-1593. [PMID: 33666540 DOI: 10.1080/1028415x.2021.1880312] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Objectives: Polyphenols, particularly anthocyanins, have received attention in improving health issues during old age, including decline in cognitive function and other health parameters. We aimed to determine the effects of polyphenols-rich tropical fruit TP 3-in-1™ juice towards improving cognitive function, oxidative stress and metabolomics profiles among middle-aged women.Methods: This clinical trial involved 31 subjects with signs of poor cognitive function, as assessed using the Rey Auditory Verbal Learning Test (RAVLT). They were randomized to receive either TP 3-in-1™ juice (n = 16) or placebo (n = 15). Study subjects consumed 500 ml of beverages for three times per day, three days per week, for a period of ten weeks. Juice supplementation provided 9135 mg GAE of total phenolic content and 194.1 mg cyanidin-3-glucoside of total anthocyanin monomer.Results: There was a significant interaction effects on RAVLT immediate recall (p < 0.05) and Comprehensive Trail Making Test (CTMT) Trail 4 (p < 0.05). Metabolomics analysis showed the presence of metabolites related to polyphenols intake and cognitive functions with the intervention group showed increased urinary excretion of thyroxine and 3-methyladenine. Thyroxine and 3-methyladenine give stability to human transthyretin (TTR) and activate autophagy, respectively, which are associated with the pathogenesis of Alzheimer's disease.Conclusion: The result shows the potential of TP 3-in-1™ juice which is rich in anthocyanins in improving cognitive function, particularly learning, memory, processing speed, sequencing, mental flexibility and visual-motor skills domains, among middle-aged women.
Collapse
Affiliation(s)
- Hanisah Rosli
- Center for Healthy Ageing & Wellness (HCARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.,Faculty of Allied Health Sciences, University of Cyberjaya, Cyberjaya, Malaysia
| | - Suzana Shahar
- Center for Healthy Ageing & Wellness (HCARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Nor Fadilah Rajab
- Center for Healthy Ageing & Wellness (HCARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Normah Che Din
- Center for Healthy Ageing & Wellness (HCARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Hasnah Haron
- Center for Healthy Ageing & Wellness (HCARE), Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| |
Collapse
|
11
|
Fraga-Corral M, Carpena M, Garcia-Oliveira P, Pereira AG, Prieto MA, Simal-Gandara J. Analytical Metabolomics and Applications in Health, Environmental and Food Science. Crit Rev Anal Chem 2020; 52:712-734. [DOI: 10.1080/10408347.2020.1823811] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- M. Fraga-Corral
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Bragança, Portugal
| | - M. Carpena
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
| | - P. Garcia-Oliveira
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Bragança, Portugal
| | - A. G. Pereira
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Bragança, Portugal
| | - M. A. Prieto
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
| | - J. Simal-Gandara
- Nutrition and Bromatology Group, Department of Analytical and Food Chemistry, Faculty of Food Science and Technology, University of Vigo, Ourense, Spain
| |
Collapse
|
12
|
Fuertes-Martín R, Correig X, Vallvé JC, Amigó N. Title: Human Serum/Plasma Glycoprotein Analysis by 1H-NMR, an Emerging Method of Inflammatory Assessment. J Clin Med 2020; 9:E354. [PMID: 32012794 PMCID: PMC7073769 DOI: 10.3390/jcm9020354] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 01/13/2020] [Accepted: 01/17/2020] [Indexed: 12/17/2022] Open
Abstract
Several studies suggest that variations in the concentration of plasma glycoproteins can influence cellular changes in a large number of diseases. In recent years, proton nuclear magnetic resonance (1H-NMR) has played a major role as an analytical tool for serum and plasma samples. In recent years, there is an increasing interest in the characterization of glycoproteins through 1H-NMR in order to search for reliable and robust biomarkers of disease. The objective of this review was to examine the existing studies in the literature related to the study of glycoproteins from an analytical and clinical point of view. There are currently several techniques to characterize circulating glycoproteins in serum or plasma, but in this review, we focus on 1H-NMR due to its great robustness and recent interest in its translation to the clinical setting. In fact, there is already a marker in H-NMR representing the acetyl groups of the glycoproteins, GlycA, which has been increasingly studied in clinical studies. A broad search of the literature was performed showing a general consensus that GlycA is a robust marker of systemic inflammation. The results also suggested that GlycA better captures systemic inflammation even more than C-reactive protein (CRP), a widely used classical inflammatory marker. The applications reviewed here demonstrated that GlycA was potentially a key biomarker in a wide range of diseases such as cancer, metabolic diseases, cardiovascular risk, and chronic inflammatory diseases among others. The profiling of glycoproteins through 1H-NMR launches an encouraging new paradigm for its future incorporation in clinical diagnosis.
Collapse
Affiliation(s)
- Rocío Fuertes-Martín
- Biosfer Teslab SL, 43201 Reus, Spain; (R.F.-M.); (N.A.)
- Metabolomic s platform, IISPV, CIBERDEM, Rovira i Virgili University, 43007 Tarragona, Spain
| | - Xavier Correig
- Metabolomic s platform, IISPV, CIBERDEM, Rovira i Virgili University, 43007 Tarragona, Spain
| | - Joan-Carles Vallvé
- Metabolomic s platform, IISPV, CIBERDEM, Rovira i Virgili University, 43007 Tarragona, Spain
- Lipids and Arteriosclerosis Research Unit, Sant Joan de Reus University Hospital, 43201 Reus, Spain
| | - Núria Amigó
- Biosfer Teslab SL, 43201 Reus, Spain; (R.F.-M.); (N.A.)
- Metabolomic s platform, IISPV, CIBERDEM, Rovira i Virgili University, 43007 Tarragona, Spain
| |
Collapse
|
13
|
Liu X, Yin P, Shao Y, Wang Z, Wang B, Lehmann R, Xu G. Which is the urine sample material of choice for metabolomics-driven biomarker studies? Anal Chim Acta 2020; 1105:120-127. [PMID: 32138910 DOI: 10.1016/j.aca.2020.01.028] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Revised: 12/31/2019] [Accepted: 01/13/2020] [Indexed: 01/18/2023]
Abstract
Urine-based metabolomics-driven strategies for the discovery of biomarkers are increasingly developed and applied in analytical chemistry. But valid, data-based recommendations for a urine sample material of choice are lacking. We investigated first and second morning urine (MU), which are the most commonly used urine specimens. Potential major factors biasing metabolomics biomarker results in these sample materials were studied. First, 35 1st and 2nd MU samples were collected from healthy, young men after an overnight fast. Subsequently, two subgroups were built, one having fast food at lunch and dinner (n = 17), the other vegetarian meals (n = 18). Again 1st and 2nd MU were collected. Non-targeted liquid chromatography-mass spectrometry was applied for analyses. More than half of the >5400 urinary ion features showed a significant difference between 1st and 2nd MU. Just two fast food meals on previous day significantly affected around 30% of all metabolites in 1st and 2nd MU. In contrast, the effects of two vegetarian meals in 2nd MU were only minor. Additionally, we describe 47 metabolites in urine, possible hits in biomarker studies, which are susceptible to the diet the day before sample collection. They should be handled with caution until validation in diet-controlled studies. Based on our results we think the second MU, ideally collected after standardized vegetarian meals and drinking only water on the previous day, is most suitable for valid analysis of biomarkers in urine.
Collapse
Affiliation(s)
- Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 16023, Dalian, China
| | - Peiyuan Yin
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 16023, Dalian, China
| | - Yaping Shao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 16023, Dalian, China
| | - Zhichao Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 16023, Dalian, China
| | - Bohong Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 16023, Dalian, China
| | - Rainer Lehmann
- Institute for Clinical Chemistry and Pathobiochemistry, Department for Diagnostic Laboratory Medicine, University Hospital Tübingen, 72076, Tübingen, Germany; Core Facility DZD Clinical Chemistry Laboratory, Department for Molecular Diabetology, Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Zentrum München at the University of Tuebingen, Tuebingen, Germany; German Center for Diabetes Research (DZD), Tuebingen, Germany.
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 16023, Dalian, China.
| |
Collapse
|
14
|
Yeo T, Probert F, Jurynczyk M, Sealey M, Cavey A, Claridge TDW, Woodhall M, Waters P, Leite MI, Anthony DC, Palace J. Classifying the antibody-negative NMO syndromes: Clinical, imaging, and metabolomic modeling. NEUROLOGY-NEUROIMMUNOLOGY & NEUROINFLAMMATION 2019; 6:e626. [PMID: 31659123 PMCID: PMC6865851 DOI: 10.1212/nxi.0000000000000626] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 08/13/2019] [Indexed: 11/30/2022]
Abstract
Objective To determine whether unsupervised principal component analysis (PCA) of comprehensive clinico-radiologic data can identify phenotypic subgroups within antibody-negative patients with overlapping features of multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSDs), and to validate the phenotypic classifications using high-resolution nuclear magnetic resonance (NMR) plasma metabolomics with inference to underlying pathologies. Methods Forty-one antibody-negative patients were recruited from the Oxford NMO Service. Thirty-six clinico-radiologic parameters, focusing on features known to distinguish NMOSD and MS, were collected to build an unbiased PCA model identifying phenotypic subgroups within antibody-negative patients. Metabolomics data from patients with relapsing-remitting MS (RRMS) (n = 34) and antibody-positive NMOSD (Ab-NMOSD) (aquaporin-4 antibody n = 54, myelin oligodendrocyte glycoprotein antibody n = 20) were used to identify discriminatory plasma metabolites separating RRMS and Ab-NMOSD. Results PCA of the 36 clinico-radiologic parameters revealed 3 phenotypic subgroups within antibody-negative patients: an MS-like subgroup, an NMOSD-like subgroup, and a low brain lesion subgroup. Supervised multivariate analysis of metabolomics data from patients with RRMS and Ab-NMOSD identified myoinositol and formate as the most discriminatory metabolites (both higher in RRMS). Within antibody-negative patients, myoinositol and formate were significantly higher in the MS-like vs NMOSD-like subgroup; myoinositol (mean [SD], 0.0023 [0.0002] vs 0.0019 [0.0003] arbitrary units [AU]; p = 0.041); formate (0.0027 [0.0006] vs 0.0019 [0.0006] AU; p = 0.010) (AU). Conclusions PCA identifies 3 phenotypic subgroups within antibody-negative patients and that the metabolite discriminators of RRMS and Ab-NMOSD suggest that these groupings have some pathogenic meaning. Thus, the identified clinico-radiologic discriminators may provide useful diagnostic clues when seeing antibody-negative patients in the clinic.
Collapse
Affiliation(s)
- Tianrong Yeo
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK
| | - Fay Probert
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK
| | - Maciej Jurynczyk
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK
| | - Megan Sealey
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK
| | - Ana Cavey
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK
| | - Timothy D W Claridge
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK
| | - Mark Woodhall
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK
| | - Patrick Waters
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK
| | - Maria Isabel Leite
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK
| | - Daniel C Anthony
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK.
| | - Jacqueline Palace
- From the Department of Pharmacology (T.Y, F.P., M.S., D.C.A.), University of Oxford, UK; Department of Neurology (T.Y.), National Neuroscience Institute, Singapore; Nuffield Department of Clinical Neurosciences (M.J., A.C., M.W., P.W., M.I.L., J.P.), John Radcliffe Hospital, University of Oxford, UK; Department of Chemistry, (T.D.W.C.), Chemistry Research Laboratory, University of Oxford, UK.
| |
Collapse
|
15
|
Gardner A, Parkes HG, So PW, Carpenter GH. Determining bacterial and host contributions to the human salivary metabolome. J Oral Microbiol 2019; 11:1617014. [PMID: 34109015 PMCID: PMC7610937 DOI: 10.1080/20002297.2019.1617014] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Background: Salivary metabolomics is rapidly advancing. Aim and methods: To determine the extent to which salivary metabolites reflects host or microbial metabolic activity whole-mouth saliva (WMS), parotid saliva (PS) and plasma collected contemporaneously from healthy volunteers were analysed by 1H-NMR spectroscopy. Spectra underwent principal component analysis and k-means cluster analysis and metabolite quantification. WMS samples were cultured on both sucrose and peptide-enriched media. Correlation between metabolite concentration and bacterial load was assessed. Results: WMS contained abundant short-chain fatty acids (SCFAs), which were minimal in PS and plasma. WMS spectral exhibited greater inter-individual variation than those of PS or plasma (6.7 and 3.6 fold, respectively), likely reflecting diversity of microbial metabolomes. WMS bacterial load correlated strongly with SCFA levels. Additional WMS metabolites including amines, amino acids and organic acids were positively correlated with bacterial load. Lactate, urea and citrate appeared to enter WMS via PS and the circulation. Urea correlated inversely with WMS bacterial load. Conclusions: Oral microbiota contribute significantly to the WMS metabolome. Several WMS metabolites (lactate, urea and citrate) are derived from the host circulation. WMS may be particularly useful to aid diagnosis of conditions reflective of dysbiosis. WMS could also complement other gastrointestinal fluids in future metabolomic studies.
Collapse
Affiliation(s)
- Alexander Gardner
- Department of Mucosal and Salivary Biology, Dental Institute, King's College London, London, UK
| | - Harold G Parkes
- Division of Radiotherapy and Imaging, Institute of Cancer Research, London, UK
| | - Po-Wah So
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Maurice Wohl Clinical Neuroscience Institute, London, UK
| | - Guy H Carpenter
- Department of Mucosal and Salivary Biology, Dental Institute, King's College London, London, UK
| |
Collapse
|
16
|
Stojiljkovic N, Leroux F, Bubanj S, Popot MA, Paris A, Tabet JC, Junot C. Tracking main environmental factors masking a minor steroidal doping effect using metabolomic analysis of horse urine by liquid chromatography-high-resolution mass spectrometry. EUROPEAN JOURNAL OF MASS SPECTROMETRY (CHICHESTER, ENGLAND) 2019; 25:339-353. [PMID: 31096786 DOI: 10.1177/1469066719839034] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
There is an urgent need to implement holistic and untargeted doping control protocols with improved discriminatory power, compared to conventional methods that only target doping agents. Metabolomics, which aims to characterize all metabolites present in biological matrices, could fulfill this need. In this context, the aim of this study was to evaluate the impact of environmental factors on the ability to obtain a metabolic signature of stanozolol administration in horse doping situation. Urine samples from 16 horses breeded in two different places were collected over a one-year period, before, during and seven months after the administration of stanozolol, a horse doping agent. Metabolomic analysis was performed using ultra-high pressure reverse phase liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (MS). Results showed a major impact of the nutritional regimen, drug administration (for de-worming purpose) and breeding place on the metabolite profiles of horse urines, which hampered the detection of metabolic perturbations induced by stanozolol administration. After having used MS/MS experiments to characterize some MS features related to these environmental factors, we showed that highlighting and then removing the features impacted by these confounding factors before performing supervised multivariate statistical analyses could address this issue. In conclusion, adequate consideration should be given to environmental and physiological factors; otherwise, they can emerge as confounding factors and conceal doping administration.
Collapse
Affiliation(s)
- Natali Stojiljkovic
- 1 LCH, Laboratoire des Courses Hippiques, Verrières-le-Buisson, France
- 2 Sorbonne Universités, Campus Pierre et Marie Curie, IPCM, Paris, France
| | - Fanny Leroux
- 1 LCH, Laboratoire des Courses Hippiques, Verrières-le-Buisson, France
| | - Saša Bubanj
- 3 Faculty of Sport and Physical Education, University of Niš, Niš, Serbia
| | - Marie-Agnès Popot
- 1 LCH, Laboratoire des Courses Hippiques, Verrières-le-Buisson, France
| | - Alain Paris
- 4 Unité Molécules de communication et adaptation des microorganismes (MCAM), Muséum National d'Histoire Naturelle, CNRS, Paris, France
| | - Jean-Claude Tabet
- 2 Sorbonne Universités, Campus Pierre et Marie Curie, IPCM, Paris, France
- 5 Service de Pharmacologie et Immunoanalyse, Laboratoire d'Etude du Métabolisme des Médicaments, CEA, INRA, Université Paris Saclay, MetaboHUB, Gif-sur-Yvette, France
| | - Christophe Junot
- 5 Service de Pharmacologie et Immunoanalyse, Laboratoire d'Etude du Métabolisme des Médicaments, CEA, INRA, Université Paris Saclay, MetaboHUB, Gif-sur-Yvette, France
| |
Collapse
|
17
|
Silvestre R, Torrado E. Metabolomic-Based Methods in Diagnosis and Monitoring Infection Progression. EXPERIENTIA SUPPLEMENTUM (2012) 2019; 109:283-315. [PMID: 30535603 PMCID: PMC7124096 DOI: 10.1007/978-3-319-74932-7_7] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
A robust biomarker screening and validation is crucial for overcoming the current limits in the clinical management of infectious diseases. In this chapter, a general workflow for metabolomics is summarized. Subsequently, an overview of the major contributions of this omics science to the field of biomarkers of infectious diseases is discussed. Different approaches using a variety of analytical platforms can be distinguished to unveil the key metabolites for the diagnosis, prognosis, response to treatment and susceptibility for infectious diseases. To allow the implementation of such biomarkers into the clinics, the performance of large-scale studies employing solid validation criteria becomes essential. Focusing on the etiological agents and after an extensive review of the field, we present a comprehensive revision of the main metabolic biomarkers of viral, bacterial, fungal, and parasitic diseases. Finally, we discussed several articles which show the strongest validation criteria. Following these research avenues, precious clinical resources will be revealed, allowing for reduced misdiagnosis, more efficient therapies, and affordable costs, ultimately leading to a better patient management.
Collapse
Affiliation(s)
- Ricardo Silvestre
- Life and Health Sciences Research Institute, University of Minho, Braga, Portugal
| | - Egídio Torrado
- Life and Health Sciences Research Institute, University of Minho, Braga, Portugal
| |
Collapse
|
18
|
Rådjursöga M, Lindqvist HM, Pedersen A, Karlsson GB, Malmodin D, Brunius C, Ellegård L, Winkvist A. The 1H NMR serum metabolomics response to a two meal challenge: a cross-over dietary intervention study in healthy human volunteers. Nutr J 2019; 18:25. [PMID: 30961592 PMCID: PMC6454665 DOI: 10.1186/s12937-019-0446-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Accepted: 03/21/2019] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Metabolomics represents a powerful tool for exploring modulation of the human metabolome in response to food intake. However, the choice of multivariate statistical approach is not always evident, especially for complex experimental designs with repeated measurements per individual. Here we have investigated the serum metabolic responses to two breakfast meals: an egg and ham based breakfast and a cereal based breakfast using three different multivariate approaches based on the Projections to Latent Structures framework. METHODS In a cross over design, 24 healthy volunteers ate the egg and ham breakfast and cereal breakfast on four occasions each. Postprandial serum samples were subjected to metabolite profiling using 1H nuclear magnetic resonance spectroscopy and metabolites were identified using 2D nuclear magnetic resonance spectroscopy. Metabolic profiles were analyzed using Orthogonal Projections to Latent Structures with Discriminant Analysis and Effect Projections and ANOVA-decomposed Projections to Latent Structures. RESULTS The Orthogonal Projections to Latent Structures with Discriminant Analysis model correctly classified 92 and 90% of the samples from the cereal breakfast and egg and ham breakfast, respectively, but confounded dietary effects with inter-personal variability. Orthogonal Projections to Latent Structures with Effect Projections removed inter-personal variability and performed perfect classification between breakfasts, however at the expense of comparing means of respective breakfasts instead of all samples. ANOVA-decomposed Projections to Latent Structures managed to remove inter-personal variability and predicted 99% of all individual samples correctly. Proline, tyrosine, and N-acetylated amino acids were found in higher concentration after consumption of the cereal breakfast while creatine, methanol, and isoleucine were found in higher concentration after the egg and ham breakfast. CONCLUSIONS Our results demonstrate that the choice of statistical method will influence the results and adequate methods need to be employed to manage sample dependency and repeated measurements in cross-over studies. In addition, 1H nuclear magnetic resonance serum metabolomics could reproducibly characterize postprandial metabolic profiles and identify discriminatory metabolites largely reflecting dietary composition. TRIAL REGISTRATION Registered with ClinicalTrials.gov, identifier: NCT02039596 . Date of registration: January 17, 2014.
Collapse
Affiliation(s)
| | - Helen M Lindqvist
- Department of Internal Medicine and Clinical Nutrition, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anders Pedersen
- Swedish NMR Centre, University of Gothenburg, Gothenburg, Sweden
| | - Göran B Karlsson
- Swedish NMR Centre, University of Gothenburg, Gothenburg, Sweden
| | - Daniel Malmodin
- Swedish NMR Centre, University of Gothenburg, Gothenburg, Sweden
| | - Carl Brunius
- Department of Biology and Biological Engineering Food and Nutrition Science Chalmers University of Technology, Gothenburg, Sweden
| | - Lars Ellegård
- Department of Internal Medicine and Clinical Nutrition, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Winkvist
- Department of Internal Medicine and Clinical Nutrition, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| |
Collapse
|
19
|
Felice F, Francini A, Domenici V, Cifelli M, Belardinelli E, Sebastiani L, Cantini C, Di Stefano R. Effects of Extra Virgin Olive Oil and Apples Enriched-Dark Chocolate on Endothelial Progenitor Cells in Patients with Cardiovascular Risk Factors: A Randomized Cross-Over Trial. Antioxidants (Basel) 2019; 8:antiox8040088. [PMID: 30987385 PMCID: PMC6523981 DOI: 10.3390/antiox8040088] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 03/29/2019] [Accepted: 04/01/2019] [Indexed: 12/12/2022] Open
Abstract
Background: Endothelial dysfunction has been associated to cardiovascular outcomes in patients with cardiovascular risk factors. Circulating endothelial progenitor cells (EPCs) play an important physiological role for their reparative potential of vascular integrity, but are numerically reduced and functionally impaired in patients with cardiovascular risks. This study assesses the effects of Extra Virgin Olive Oil (EVOO) and apple-enriched dark chocolate intake on the blood levels of EPCs. Methods: Thirty volunteers with cardiovascular risk factors, enrolled in a randomised, crossover, four-weeks trial, received a solid dark chocolate bar (40 g/day) containing 10% EVOO or 2.5% dry apples. Urine samples were analyzed for endogenous metabolites. Circulating EPCs levels, clinical data and anthropometric examinations were collected. Results: 26 volunteers (M/F:14/12, 51 ± 9 years of age) completed the study. Comparison of pre-post intervention revealed a significant increase in EPCs levels associated with EVOO-dark chocolate consumption. Most biochemical parameters were not significantly modified by both chocolates. Conclusions: This study shows that a daily consumption of a non fattening dose of dark chocolate enriched with EVOO improves blood levels of EPCs, a well known surrogate biologic marker for endothelial function.
Collapse
Affiliation(s)
- Francesca Felice
- Cardiovascular Research Laboratory, Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, 56100 Pisa, Italy.
| | - Alessandra Francini
- BioLabs, Institute of Life Sciences, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.
| | - Valentina Domenici
- Department of Chemistry and Industrial Chemistry, University of Pisa, 56100 Pisa, Italy.
| | - Mario Cifelli
- Department of Chemistry and Industrial Chemistry, University of Pisa, 56100 Pisa, Italy.
| | - Ester Belardinelli
- Cardiovascular Research Laboratory, Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, 56100 Pisa, Italy.
| | - Luca Sebastiani
- BioLabs, Institute of Life Sciences, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.
| | - Claudio Cantini
- Trees and Timber Institute, IVALSA-CNR, Sesto Fiorentino, 50019 Florence, Italy.
| | - Rossella Di Stefano
- Cardiovascular Research Laboratory, Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, 56100 Pisa, Italy.
- Interdepartmental Research Center "Nutraceuticals and Food for Health", University of Pisa, 56100 Pisa, Italy.
| |
Collapse
|
20
|
Pouralijan Amiri M, Khoshkam M, Salek RM, Madadi R, Faghanzadeh Ganji G, Ramazani A. Metabolomics in early detection and prognosis of acute coronary syndrome. Clin Chim Acta 2019; 495:43-53. [PMID: 30928571 DOI: 10.1016/j.cca.2019.03.1632] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 03/25/2019] [Accepted: 03/26/2019] [Indexed: 01/23/2023]
Abstract
Acute coronary syndrome (ACS) is one of the most dangerous types of coronary heart disease (CHD) and contributes to significant mortality and morbidity worldwide. Outcomes in these patients remain a challenge despite improvements in diagnosis and treatment. Risk stratification continues to be problematic and the identification of novel predictors is crucial for improved outcomes. As such, there is a strong need for the development of novel analytical methods as well as the characterization of better predictive and prognostic biomarkers to enable more personalized treatment. Metabolite profile analysis may greatly assist in interpreting altered pathway dynamics, especially when combined with other 'omics' technologies such as transcriptomics and proteomics. In this review, we describe ACS pathophysiology and recent advances in the role of metabolomics in the diagnosis and the molecular pathogenesis of ACS. We briefly describe key technologies used in metabolomics research and statistical approaches for data reduction and pathway analysis and discuss their application to CHD.
Collapse
Affiliation(s)
- Mohammad Pouralijan Amiri
- Department of Genetics & Molecular Medicine, Faculty of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran
| | - Maryam Khoshkam
- Chemistry Group, Faculty of Basic Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
| | - Reza M Salek
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
| | - Reza Madadi
- Department of Cardiology, Mousavi Hospital, Zanjan University of Medical Sciences, Zanjan, Iran
| | | | - Ali Ramazani
- Cancer Gene Therapy Research Center, Zanjan University of Medical Sciences, Zanjan, Iran; Zanjan Metabolic Diseases Research Center, Zanjan University of Medical Sciences, Zanjan, Iran.
| |
Collapse
|
21
|
Probert F, Walsh A, Jagielowicz M, Yeo T, Claridge TDW, Simmons A, Travis S, Anthony DC. Plasma Nuclear Magnetic Resonance Metabolomics Discriminates Between High and Low Endoscopic Activity and Predicts Progression in a Prospective Cohort of Patients With Ulcerative Colitis. J Crohns Colitis 2018; 12:1326-1337. [PMID: 30016408 PMCID: PMC6403054 DOI: 10.1093/ecco-jcc/jjy101] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND AND AIMS Endoscopic assessment of ulcerative colitis [UC] is one of the most accurate measures of disease activity, but frequent endoscopic investigations are disliked by patients and expensive for the healthcare system. A minimally invasive test that provides a surrogate measure of endoscopic activity is required. METHODS Plasma nuclear magnetic resonance [NMR] spectra from 40 patients with UC followed prospectively over 6 months were analysed with multivariate statistics. NMR metabolite profiles were compared with endoscopic [Ulcerative Colitis Endoscopic Index of Severity: UCEIS], histological [Nancy Index] and clinical [Simple Clinical Colitis Activity Index: SCCAI] severity indices, along with routine blood measurements. RESULTS A blinded principal component analysis spontaneously separated metabolite profiles of patients with low [≤3] and high [>3] UCEIS. Orthogonal partial least squares discrimination analysis identified low and high UCEIS metabolite profiles with an accuracy of 77 ± 5%. Plasma metabolites driving discrimination included decreases in lipoproteins and increases in isoleucine, valine, glucose and myo-inositol in high compared to low UCEIS. This same metabolite profile distinguished between low [Nancy 0-1] and high histological activity [Nancy 3-4] with a modest although significant accuracy [65 ± 6%] but was independent of SCCAI and all blood parameters measured. A different metabolite profile, dominated by changes in lysine, histidine, phenylalanine and tyrosine, distinguished between improvement in UCEIS [decrease ≥1] and worsening [increase ≥1] over 6 months with an accuracy of 74 ± 4%. CONCLUSION Plasma NMR metabolite analysis has the potential to provide a low-cost, minimally invasive technique that may be a surrogate for endoscopic assessment, with predictive capacity.
Collapse
Affiliation(s)
- Fay Probert
- Department of Pharmacology, University of Oxford, Oxford, UK
| | - Alissa Walsh
- Translational Gastroenterology Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Marta Jagielowicz
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, and Translational Gastroenterology Unit, John Radcliffe Hospital, Oxford, UK
| | - Tianrong Yeo
- Department of Pharmacology, University of Oxford, Oxford, UK,Department of Neurology, National Neuroscience Institute, Jalan Tan Tock Seng, Singapore
| | - Timothy D W Claridge
- Department of Chemistry, University of Oxford, Chemistry Research Laboratory, Oxford, UK
| | - Alison Simmons
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, and Translational Gastroenterology Unit, John Radcliffe Hospital, Oxford, UK
| | - Simon Travis
- Translational Gastroenterology Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK,Corresponding author: Clinical: Simon Travis, Translational Gastroenterology Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK. ; Analysis and interpretation: Daniel Anthony, Department of Pharmacology, University of Oxford, Oxford, UK.
| | - Daniel C Anthony
- Department of Pharmacology, University of Oxford, Oxford, UK,Corresponding author: Clinical: Simon Travis, Translational Gastroenterology Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK. ; Analysis and interpretation: Daniel Anthony, Department of Pharmacology, University of Oxford, Oxford, UK.
| |
Collapse
|
22
|
A validated multi-matrix platform for metabolomic fingerprinting of human urine, feces and plasma using ultra-high performance liquid-chromatography coupled to hybrid orbitrap high-resolution mass spectrometry. Anal Chim Acta 2018; 1033:108-118. [DOI: 10.1016/j.aca.2018.06.065] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 06/20/2018] [Accepted: 06/23/2018] [Indexed: 01/28/2023]
|
23
|
Wang M, Xia W, Li H, Liu F, Li Y, Sun X, Lu S, Xu S. Normal pregnancy induced glucose metabolic stress in a longitudinal cohort of healthy women: Novel insights generated from a urine metabolomics study. Medicine (Baltimore) 2018; 97:e12417. [PMID: 30290597 PMCID: PMC6200460 DOI: 10.1097/md.0000000000012417] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
During normal pregnancy, mothers face a unique physiological challenge in the adaptation of glucose metabolism in preparation for the metabolic stress presented by fetal development. However, the responsible mechanism remains elusive. The purpose of this study is to investigate the mechanism of the metabolic stress of glucose metabolism in pregnant women using metabolomics method.A Ultra Performance Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometer-based untargeted metabolomics study was performed to investigate the dynamic urinary signature of the intermediates of glucose metabolism in a longitudinal cohort of 232 healthy pregnant women in their first, second, and third trimesters.Twelve glucose metabolic intermediates were screened out from hundreds of candidate metabolites using partial least squares discriminant analysis models. These 12 markers were mainly involved in the metabolic pathways of insulin resistance, glycolysis/gluconeogenesis, tricarboxylic acid cycle, nonabsorbable carbohydrate metabolism, and N-glycan biosynthesis. In particular, L-acetylcarnitine, a metabolite that is beneficial for the amelioration of insulin resistance, decreased in a time-dependent manner during normal pregnancy. Moreover, thiamine pyrophosphate, an intermediate product of glycolysis/gluconeogenesis, significantly increased in the second trimester, and argininosuccinic acid and oxalosuccinic acid, intermediates involved in the tricarboxylic acid cycle, significantly decreased in the third trimester, suggesting an increased glucose demand in the maternal body during fetal development.These findings provide novel insight into the normal pregnancy-induced elevation of insulin resistance and glycolysis/gluconeogenesis, as well as the observed reduction in the aerobic oxidation of glucose.
Collapse
Affiliation(s)
- Mu Wang
- School of Computer Science and Technology, Huazhong University of Science and Technology
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Wuhan, Hubei, China
| | - Wei Xia
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Wuhan, Hubei, China
| | - Han Li
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Wuhan, Hubei, China
| | - Fang Liu
- School of Computer Science and Technology, Huazhong University of Science and Technology
| | - Yuanyuan Li
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Wuhan, Hubei, China
| | - Xiaojie Sun
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Wuhan, Hubei, China
| | - Songfeng Lu
- School of Computer Science and Technology, Huazhong University of Science and Technology
| | - Shunqing Xu
- Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Wuhan, Hubei, China
| |
Collapse
|
24
|
Duskova K, Vesely S, DO Carmo Silva J, Cernei N, Zitka O, Heger Z, Adam V, Havlova K, Babjuk M. Differences in Urinary Amino Acid Patterns in Individuals with Different Types of Urological Tumor Urinary Amino Acid Patterns as Markers of Urological Tumors. ACTA ACUST UNITED AC 2018; 32:425-429. [PMID: 29475932 DOI: 10.21873/invivo.11257] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2017] [Revised: 01/09/2018] [Accepted: 01/10/2018] [Indexed: 12/17/2022]
Abstract
BACKGROUND Insufficient specificity and invasiveness of currently used diagnostic methods raises the need for new markers of urological tumors. The aim of this study was to find a link between the urinary excretion of amino acids and the presence of urological tumors. MATERIALS AND METHODS Using ion-exchange chromatography, we tested urine samples of patients with prostate cancer (n=30), urinary bladder cancer (n=28), renal cell carcinoma (n=16) and healthy volunteers (control group; n=21). RESULTS In each category, we found a group of amino acids which differed in concentration compared to the control group. These differences were most significant in sarcosine in patients with prostate cancer; leucine, phenylalanine and arginine in those with bladder cancer; and sarcosine, glutamic acid, glycine, tyrosine and arginine in the those with renal cell carcinoma. CONCLUSION Results of our research imply a possible connection between the occurrence of specific types of amino acids in the urine and the presence of urological tumors.
Collapse
Affiliation(s)
- Katerina Duskova
- Department of Urology, Second Faculty of Medicine, Charles University, and University Hospital Motol, Prague, Czech Republic
| | - Stepan Vesely
- Department of Urology, Second Faculty of Medicine, Charles University, and University Hospital Motol, Prague, Czech Republic
| | - Joana DO Carmo Silva
- Department of Urology, Second Faculty of Medicine, Charles University, and University Hospital Motol, Prague, Czech Republic
| | - Natalia Cernei
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic.,Department of Chemistry and Biochemistry, Mendel University in Brno, Brno, Czech Republic
| | - Ondrej Zitka
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic.,Department of Chemistry and Biochemistry, Mendel University in Brno, Brno, Czech Republic
| | - Zbynek Heger
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic.,Department of Chemistry and Biochemistry, Mendel University in Brno, Brno, Czech Republic
| | - Vojtech Adam
- Central European Institute of Technology, Brno University of Technology, Brno, Czech Republic.,Department of Chemistry and Biochemistry, Mendel University in Brno, Brno, Czech Republic
| | - Klara Havlova
- Department of Urology, Second Faculty of Medicine, Charles University, and University Hospital Motol, Prague, Czech Republic
| | - Marek Babjuk
- Department of Urology, Second Faculty of Medicine, Charles University, and University Hospital Motol, Prague, Czech Republic
| |
Collapse
|
25
|
Palmas F, Mussap M, Fattuoni C. Urine metabolome analysis by gas chromatography-mass spectrometry (GC-MS): Standardization and optimization of protocols for urea removal and short-term sample storage. Clin Chim Acta 2018; 485:236-242. [PMID: 30008426 DOI: 10.1016/j.cca.2018.07.006] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 06/25/2018] [Accepted: 07/05/2018] [Indexed: 12/13/2022]
Abstract
BACKGROUND Before derivatization, urine analyzed by gas chromatography-mass spectrometry (GC-MS) requires the complete removal of urea to avoid interferences. We aimed at establishing the most effective sample pretreatment for urea removing; moreover, we explored the impact of two short-term sample storage conditions on urine metabolome. METHODS 92 aliquots were obtained from a single sample collected from a healthy adult; they were divided into 6 groups. Group 1 consisted of untreated aliquots while groups 2-6 differed from each other for the addition of various defined urease solution volumes combined with either 30 min or 1-hour sonication time. Urine sample storage was tested by comparing 20 fresh aliquots analyzed after collection with 20 aliquots frozen at -80 °C for 72 h. RESULTS the most effective protocol consisted of the combination between 200 μL urease solution with 1-h sonication time; urease solution volumes >200 μL increase the risk to underestimate metabolite peaks because of sample dilution. Short-term storage of samples at -80 °C pointed out significant changes in the urine metabolic profile compared with that of fresh samples. CONCLUSIONS our study confirms the importance of urea removal for a reliable recognition and quantitation of metabolites; urine short-term storage at -80 °C should be carefully reconsidered.
Collapse
Affiliation(s)
- Francesco Palmas
- Department of Chemical and Geological Sciences, University of Cagliari, I-09042, Italy
| | - Michele Mussap
- Department of Surgical Sciences, University of Cagliari, Italy.
| | - Claudia Fattuoni
- Department of Chemical and Geological Sciences, University of Cagliari, I-09042, Italy
| |
Collapse
|
26
|
Khoshkam M, Baghdadchi Y, Arezumand R, Ramazani A. Synthesis, characterization and in vivo evaluation of cadmium telluride quantum dots toxicity in mice by toxicometabolomics approach. Toxicol Mech Methods 2018; 28:539-546. [DOI: 10.1080/15376516.2018.1471635] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Maryam Khoshkam
- Chemistry Group, Faculty of Basic Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
| | - Yasamin Baghdadchi
- Cancer Gene Therapy Research Center, Zanjan University of Medical Sciences, Zanjan, Iran
| | - Roghaye Arezumand
- Department of Medical Biotechnology and Molecular Science, School of Medicine, North Khorasan University of Medical Sciences, Bojnurd, Iran
| | - Ali Ramazani
- Cancer Gene Therapy Research Center, Zanjan University of Medical Sciences, Zanjan, Iran
| |
Collapse
|
27
|
Kaluarachchi M, Boulangé CL, Karaman I, Lindon JC, Ebbels TMD, Elliott P, Tracy RP, Olson NC. A comparison of human serum and plasma metabolites using untargeted 1H NMR spectroscopy and UPLC-MS. Metabolomics 2018; 14:32. [PMID: 30830335 PMCID: PMC7122646 DOI: 10.1007/s11306-018-1332-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Accepted: 01/30/2018] [Indexed: 12/21/2022]
Abstract
INTRODUCTION Differences in the metabolite profiles between serum and plasma are incompletely understood. OBJECTIVES To evaluate metabolic profile differences between serum and plasma and among plasma sample subtypes. METHODS We analyzed serum, platelet rich plasma (PRP), platelet poor plasma (PPP), and platelet free plasma (PFP), collected from 8 non-fasting apparently healthy women, using untargeted standard 1D and CPMG 1H NMR and reverse phase and hydrophilic (HILIC) UPLC-MS. Differences between metabolic profiles were evaluated using validated principal component and orthogonal partial least squares discriminant analysis. RESULTS Explorative analysis showed the main source of variation among samples was due to inter-individual differences with no grouping by sample type. After correcting for inter-individual differences, lipoproteins, lipids in VLDL/LDL, lactate, glutamine, and glucose were found to discriminate serum from plasma in NMR analyses. In UPLC-MS analyses, lysophosphatidylethanolamine (lysoPE)(18:0) and lysophosphatidic acid(20:0) were higher in serum, and phosphatidylcholines (PC)(16:1/18:2, 20:3/18:0, O-20:0/22:4), lysoPC(16:0), PE(O-18:2/20:4), sphingomyelin(18:0/22:0), and linoleic acid were lower. In plasma subtype analyses, isoleucine, leucine, valine, phenylalanine, glutamate, and pyruvate were higher among PRP samples compared with PPP and PFP by NMR while lipids in VLDL/LDL, citrate, and glutamine were lower. By UPLC-MS, PE(18:0/18:2) and PC(P-16:0/20:4) were higher in PRP compared with PFP samples. CONCLUSIONS Correction for inter-individual variation was required to detect metabolite differences between serum and plasma. Our results suggest the potential importance of inter-individual effects and sample type on the results from serum and plasma metabolic phenotyping studies.
Collapse
Affiliation(s)
- Manuja Kaluarachchi
- Metabometrix Ltd, Sir Alexander Fleming Building, Prince Consort Road, London, SW7 1BP, UK
| | - Claire L Boulangé
- Metabometrix Ltd, Sir Alexander Fleming Building, Prince Consort Road, London, SW7 1BP, UK
| | - Ibrahim Karaman
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - John C Lindon
- Metabometrix Ltd, Sir Alexander Fleming Building, Prince Consort Road, London, SW7 1BP, UK
- Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, UK
| | - Timothy M D Ebbels
- Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, UK
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
| | - Russell P Tracy
- Department of Biochemistry, The Robert Larner, M.D. College of Medicine at The University of Vermont, Burlington, VT, 05446, USA
- Department of Pathology and Laboratory Medicine, The Robert Larner, M.D. College of Medicine at The University of Vermont, Burlington, VT, 05446, USA
| | - Nels C Olson
- Department of Pathology and Laboratory Medicine, The Robert Larner, M.D. College of Medicine at The University of Vermont, Burlington, VT, 05446, USA.
| |
Collapse
|
28
|
Jurynczyk M, Probert F, Yeo T, Tackley G, Claridge TDW, Cavey A, Woodhall MR, Arora S, Winkler T, Schiffer E, Vincent A, DeLuca G, Sibson NR, Isabel Leite M, Waters P, Anthony DC, Palace J. Metabolomics reveals distinct, antibody-independent, molecular signatures of MS, AQP4-antibody and MOG-antibody disease. Acta Neuropathol Commun 2017; 5:95. [PMID: 29208041 PMCID: PMC5718082 DOI: 10.1186/s40478-017-0495-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Accepted: 11/13/2017] [Indexed: 11/11/2022] Open
Abstract
The overlapping clinical features of relapsing remitting multiple sclerosis (RRMS), aquaporin-4 (AQP4)-antibody (Ab) neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocyte glycoprotein (MOG)-Ab disease mean that detection of disease specific serum antibodies is the gold standard in diagnostics. However, antibody levels are not prognostic and may become undetectable after treatment or during remission. Therefore, there is still a need to discover antibody-independent biomarkers. We sought to discover whether plasma metabolic profiling could provide biomarkers of these three diseases and explore if the metabolic differences are independent of antibody titre. Plasma samples from 108 patients (34 RRMS, 54 AQP4-Ab NMOSD, and 20 MOG-Ab disease) were analysed by nuclear magnetic resonance spectroscopy followed by lipoprotein profiling. Orthogonal partial-least squares discriminatory analysis (OPLS-DA) was used to identify significant differences in the plasma metabolite concentrations and produce models (mathematical algorithms) capable of identifying these diseases. In all instances, the models were highly discriminatory, with a distinct metabolite pattern identified for each disease. In addition, OPLS-DA identified AQP4-Ab NMOSD patient samples with low/undetectable antibody levels with an accuracy of 92%. The AQP4-Ab NMOSD metabolic profile was characterised by decreased levels of scyllo-inositol and small high density lipoprotein particles along with an increase in large low density lipoprotein particles relative to both RRMS and MOG-Ab disease. RRMS plasma exhibited increased histidine and glucose, along with decreased lactate, alanine, and large high density lipoproteins while MOG-Ab disease plasma was defined by increases in formate and leucine coupled with decreased myo-inositol. Despite overlap in clinical measures in these three diseases, the distinct plasma metabolic patterns support their distinct serological profiles and confirm that these conditions are indeed different at a molecular level. The metabolites identified provide a molecular signature of each condition which is independent of antibody titre and EDSS, with potential use for disease monitoring and diagnosis.
Collapse
Affiliation(s)
- Maciej Jurynczyk
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Level 3, West Wing, Headley Way, Oxford, OX3 9DU, UK
- Department of Neurology, Medical University of Lodz, Lodz, Poland
| | - Fay Probert
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK.
| | - Tianrong Yeo
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK
- Department of Neurology, National Neuroscience Institute, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore
| | - George Tackley
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Level 3, West Wing, Headley Way, Oxford, OX3 9DU, UK
| | - Tim D W Claridge
- Chemistry Research Laboratory, Department of Chemistry, University of Oxford, Mansfield Road, Oxford, OX1 3TA, UK
| | - Ana Cavey
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Level 3, West Wing, Headley Way, Oxford, OX3 9DU, UK
| | - Mark R Woodhall
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Level 3, West Wing, Headley Way, Oxford, OX3 9DU, UK
| | - Siddharth Arora
- Mathematical Institute, University of Oxford, Woodstock Rd, Oxford, OX2 6GC, UK
| | | | - Eric Schiffer
- Numares AG, Am Biopark 9, 93053, Regensburg, Germany
| | - Angela Vincent
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Level 3, West Wing, Headley Way, Oxford, OX3 9DU, UK
| | - Gabriele DeLuca
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Level 3, West Wing, Headley Way, Oxford, OX3 9DU, UK
| | - Nicola R Sibson
- Cancer Research UK & Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, OX37DQ, Oxford, UK
| | - M Isabel Leite
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Level 3, West Wing, Headley Way, Oxford, OX3 9DU, UK
| | - Patrick Waters
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Level 3, West Wing, Headley Way, Oxford, OX3 9DU, UK
| | - Daniel C Anthony
- Department of Pharmacology, University of Oxford, Mansfield Road, Oxford, OX1 3QT, UK.
| | - Jacqueline Palace
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Level 3, West Wing, Headley Way, Oxford, OX3 9DU, UK.
| |
Collapse
|
29
|
Cartlidge CR, U MRA, Alkhatib AMA, Taylor-Robinson SD. The utility of biomarkers in hepatocellular carcinoma: review of urine-based 1H-NMR studies - what the clinician needs to know. Int J Gen Med 2017; 10:431-442. [PMID: 29225478 PMCID: PMC5708191 DOI: 10.2147/ijgm.s150312] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is the fifth most common malignancy, the third most common cause of cancer death, and the most common primary liver cancer. Overall, there is a need for more reliable biomarkers for HCC, as those currently available lack sensitivity and specificity. For example, the current gold-standard biomarker, serum alpha-fetoprotein, has a sensitivity of roughly only 70%. Cancer cells have different characteristic metabolic signatures in biofluids, compared to healthy cells; therefore, metabolite analysis in blood or urine should lead to the detection of suitable candidates for the detection of HCC. With the advent of metabonomics, this has increased the potential for new biomarker discovery. In this article, we look at approaches used to identify biomarkers of HCC using proton nuclear magnetic resonance (1H-NMR) spectroscopy of urine samples. The various multivariate statistical analysis techniques used are explained, and the process of biomarker identification is discussed, with a view to simplifying the knowledge base for the average clinician.
Collapse
Affiliation(s)
| | - M R Abellona U
- Department of Surgery and Cancer, Division of Computational and Systems Medicine, Faculty of Medicine, Imperial College London, London, UK
| | - Alzhraa M A Alkhatib
- Department of Surgery and Cancer, Division of Computational and Systems Medicine, Faculty of Medicine, Imperial College London, London, UK
| | | |
Collapse
|
30
|
McNerney MP, Styczynski MP. Small molecule signaling, regulation, and potential applications in cellular therapeutics. WILEY INTERDISCIPLINARY REVIEWS-SYSTEMS BIOLOGY AND MEDICINE 2017; 10. [PMID: 28960879 DOI: 10.1002/wsbm.1405] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2017] [Revised: 07/20/2017] [Accepted: 08/14/2017] [Indexed: 12/19/2022]
Abstract
Small molecules have many important roles across the tree of life: they regulate processes from metabolism to transcription, they enable signaling within and between species, and they serve as the biochemical building blocks for cells. They also represent valuable phenotypic endpoints that are promising for use as biomarkers of disease states. In the context of engineering cell-based therapeutics, they hold particularly great promise for enabling finer control over the therapeutic cells and allowing them to be responsive to extracellular cues. The natural signaling and regulatory functions of small molecules can be harnessed and rewired to control cell activity and delivery of therapeutic payloads, potentially increasing efficacy while decreasing toxicity. To that end, this review considers small molecule-mediated regulation and signaling in bacteria. We first discuss some of the most prominent applications and aspirations for responsive cell-based therapeutics. We then describe the transport, signaling, and regulation associated with three classes of molecules that may be exploited in the engineering of therapeutic bacteria: amino acids, fatty acids, and quorum-sensing signaling molecules. We also present examples of existing engineering efforts to generate cells that sense and respond to levels of different small molecules. Finally, we discuss future directions for how small molecule-mediated regulation could be harnessed for therapeutic applications, as well as some critical considerations for the ultimate success of such endeavors. WIREs Syst Biol Med 2018, 10:e1405. doi: 10.1002/wsbm.1405 This article is categorized under: Biological Mechanisms > Cell Signaling Biological Mechanisms > Metabolism Translational, Genomic, and Systems Medicine > Therapeutic Methods.
Collapse
Affiliation(s)
- Monica P McNerney
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Mark P Styczynski
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| |
Collapse
|
31
|
Lussu M, Camboni T, Piras C, Serra C, Del Carratore F, Griffin J, Atzori L, Manzin A. 1H NMR spectroscopy-based metabolomics analysis for the diagnosis of symptomatic E. coli-associated urinary tract infection (UTI). BMC Microbiol 2017; 17:201. [PMID: 28934947 PMCID: PMC5609053 DOI: 10.1186/s12866-017-1108-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Accepted: 09/13/2017] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Urinary tract infection (UTI) is one of the most common diagnoses in girls and women, and to a lesser extent in boys and men younger than 50 years. Escherichia coli, followed by Klebsiella spp. and Proteus spp., cause 75-90% of all infections. Infection of the urinary tract is identified by growth of a significant number of a single species in the urine, in the presence of symptoms. Urinary culture is an accurate diagnostic method but takes several hours or days to be carried out. Metabolomics analysis aims to identify biomarkers that are capable of speeding up diagnosis. METHODS Urine samples from 51 patients with a prior diagnosis of Escherichia coli-associated UTI, from 21 patients with UTI caused by other pathogens (bacteria and fungi), and from 61 healthy controls were analyzed. The 1H-NMR spectra were acquired and processed. Multivariate statistical models were applied and their performance was validated using permutation test and ROC curve. RESULTS Orthogonal Partial Least Squares-discriminant Analysis (OPLS-DA) showed good separation (R2Y = 0.76, Q2=0.45, p < 0.001) between UTI caused by Escherichia coli and healthy controls. Acetate and trimethylamine were identified as discriminant metabolites. The concentrations of both metabolites were calculated and used to build the ROC curves. The discriminant metabolites identified were also evaluated in urine samples from patients with other pathogens infections to test their specificity. CONCLUSIONS Acetate and trimethylamine were identified as optimal candidates for biomarkers for UTI diagnosis. The conclusions support the possibility of a fast diagnostic test for Escherichia coli-associated UTI using acetate and trimethylamine concentrations.
Collapse
Affiliation(s)
- Milena Lussu
- Department of Biomedical Sciences, Microbiology and Virology Unit, University of Cagliari, S.S. 554, Bivio per Sestu, I-09042, Monserrato, Cagliari, Italy
| | - Tania Camboni
- Department of Biomedical Sciences, Microbiology and Virology Unit, University of Cagliari, S.S. 554, Bivio per Sestu, I-09042, Monserrato, Cagliari, Italy
| | - Cristina Piras
- Department of Biomedical Sciences, Microbiology and Virology Unit, University of Cagliari, S.S. 554, Bivio per Sestu, I-09042, Monserrato, Cagliari, Italy
| | - Corrado Serra
- Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Francesco Del Carratore
- Department of Biomedical Sciences, Microbiology and Virology Unit, University of Cagliari, S.S. 554, Bivio per Sestu, I-09042, Monserrato, Cagliari, Italy.,Faculty of Life Sciences, University of Manchester, Manchester, UK
| | - Julian Griffin
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Luigi Atzori
- Department of Biomedical Sciences, Microbiology and Virology Unit, University of Cagliari, S.S. 554, Bivio per Sestu, I-09042, Monserrato, Cagliari, Italy
| | - Aldo Manzin
- Department of Biomedical Sciences, Microbiology and Virology Unit, University of Cagliari, S.S. 554, Bivio per Sestu, I-09042, Monserrato, Cagliari, Italy.
| |
Collapse
|
32
|
Louis E, Cantrelle FX, Mesotten L, Reekmans G, Bervoets L, Vanhove K, Thomeer M, Lippens G, Adriaensens P. Metabolic phenotyping of human plasma by 1 H-NMR at high and medium magnetic field strengths: a case study for lung cancer. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2017; 55:706-713. [PMID: 28061019 DOI: 10.1002/mrc.4577] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2016] [Revised: 12/25/2016] [Accepted: 01/04/2017] [Indexed: 06/06/2023]
Abstract
Accurate identification and quantification of human plasma metabolites can be challenging in crowded regions of the NMR spectrum with severe signal overlap. Therefore, this study describes metabolite spiking experiments on the basis of which the NMR spectrum can be rationally segmented into well-defined integration regions, and this for spectrometers having magnetic field strengths corresponding to 1 H resonance frequencies of 400 MHz and 900 MHz. Subsequently, the integration data of a case-control dataset of 69 lung cancer patients and 74 controls were used to train a multivariate statistical classification model for both field strengths. In this way, the advantages/disadvantages of high versus medium magnetic field strength were evaluated. The discriminative power obtained from the data collected at the two magnetic field strengths is rather similar, i.e. a sensitivity and specificity of respectively 90 and 97% for the 400 MHz data versus 88 and 96% for the 900 MHz data. This shows that a medium-field NMR spectrometer (400-600 MHz) is already sufficient to perform clinical metabolomics. However, the improved spectral resolution (reduced signal overlap) and signal-to-noise ratio of 900 MHz spectra yield more integration regions that represent a single metabolite. This will simplify the unraveling and understanding of the related, disease disturbed, biochemical pathways. Copyright © 2017 John Wiley & Sons, Ltd.
Collapse
Affiliation(s)
- Evelyne Louis
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium
| | - Francois-Xavier Cantrelle
- CNRS UMR 8576, Unité de Glycobiologie Structurale et Fonctionnelle, Université des Sciences et Technologies de Lille 1, Cité Scientifique, 59655, Villeneuve d'Ascq Cedex, France
| | - Liesbet Mesotten
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium
- Department of Nuclear Medicine, Ziekenhuis Oost-Limburg, Schiepse Bos 6, 3600, Genk, Belgium
| | - Gunter Reekmans
- Applied and Analytical Chemistry, Institute for Materials Research, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Liene Bervoets
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium
| | - Karolien Vanhove
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium
- Department of Respiratory Medicine, Algemeen Ziekenhuis Vesalius, Hazelereik 51, 3700, Tongeren, Belgium
| | - Michiel Thomeer
- Faculty of Medicine and Life Sciences, Hasselt University, Martelarenlaan 42, 3500, Hasselt, Belgium
- Department of Respiratory Medicine, Ziekenhuis Oost-Limburg, Schiepse Bos 6, 3600, Genk, Belgium
| | - Guy Lippens
- CNRS UMR 8576, Unité de Glycobiologie Structurale et Fonctionnelle, Université des Sciences et Technologies de Lille 1, Cité Scientifique, 59655, Villeneuve d'Ascq Cedex, France
- Laboratoire d'Ingénierie des Systèmes Biologiques et des Procédés, INSA, University of Toulouse, CNRS, INRA, 135 Avenue de Rangueil, 31400, Toulouse, France
| | - Peter Adriaensens
- Applied and Analytical Chemistry, Institute for Materials Research, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| |
Collapse
|
33
|
Probert F, Ruiz-Rodado V, Vruchte DT, Nicoli ER, Claridge TDW, Wassif CA, Farhat N, Porter FD, Platt FM, Grootveld M. NMR analysis reveals significant differences in the plasma metabolic profiles of Niemann Pick C1 patients, heterozygous carriers, and healthy controls. Sci Rep 2017; 7:6320. [PMID: 28740230 PMCID: PMC5524790 DOI: 10.1038/s41598-017-06264-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Accepted: 06/09/2017] [Indexed: 02/07/2023] Open
Abstract
Niemann-Pick type C1 (NPC1) disease is a rare autosomal recessive, neurodegenerative lysosomal storage disorder, which presents with a range of clinical phenotypes and hence diagnosis remains a challenge. In view of these difficulties, the search for a novel, NPC1-specific biomarker (or set of biomarkers) is a topic of much interest. Here we employed high-resolution 1H nuclear magnetic resonance spectroscopy coupled with advanced multivariate analysis techniques in order to explore and seek differences between blood plasma samples acquired from NPC1 (untreated and miglustat treated), heterozygote, and healthy control subjects. Using this approach, we were able to identify NPC1 disease with 91% accuracy confirming that there are significant differences in the NMR plasma metabolic profiles of NPC1 patients when compared to healthy controls. The discrimination between NPC1 (both miglustat treated and untreated) and healthy controls was dominated by lipoprotein triacylglycerol 1H NMR resonances and isoleucine. Heterozygote plasma samples displayed also increases in the intensities of selected lipoprotein triacylglycerol 1H NMR signals over those of healthy controls. The metabolites identified could represent useful biomarkers in the future and provide valuable insight in to the underlying pathology of NPC1 disease.
Collapse
Affiliation(s)
- Fay Probert
- Department of Pharmacology, De Montfort University, Leicester, UK.,Department of Pharmacology, University of Oxford, Oxford, UK
| | | | | | | | | | - Christopher A Wassif
- Department of Pharmacology, University of Oxford, Oxford, UK.,Section of Molecular Dysmorphology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Health, Department of Health and Human Services, Bethesda, MD, USA
| | - Nicole Farhat
- Section of Molecular Dysmorphology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Health, Department of Health and Human Services, Bethesda, MD, USA
| | - Forbes D Porter
- Section of Molecular Dysmorphology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Health, Department of Health and Human Services, Bethesda, MD, USA
| | - Frances M Platt
- Department of Pharmacology, University of Oxford, Oxford, UK
| | - Martin Grootveld
- Department of Pharmacology, De Montfort University, Leicester, UK.
| |
Collapse
|
34
|
Maitre L, Lau CHE, Vizcaino E, Robinson O, Casas M, Siskos AP, Want EJ, Athersuch T, Slama R, Vrijheid M, Keun HC, Coen M. Assessment of metabolic phenotypic variability in children's urine using 1H NMR spectroscopy. Sci Rep 2017; 7:46082. [PMID: 28422130 PMCID: PMC5395814 DOI: 10.1038/srep46082] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Accepted: 03/08/2017] [Indexed: 12/02/2022] Open
Abstract
The application of metabolic phenotyping in clinical and epidemiological studies is limited by a poor understanding of inter-individual, intra-individual and temporal variability in metabolic phenotypes. Using 1H NMR spectroscopy we characterised short-term variability in urinary metabolites measured from 20 children aged 8-9 years old. Daily spot morning, night-time and pooled (50:50 morning and night-time) urine samples across six days (18 samples per child) were analysed, and 44 metabolites quantified. Intraclass correlation coefficients (ICC) and mixed effect models were applied to assess the reproducibility and biological variance of metabolic phenotypes. Excellent analytical reproducibility and precision was demonstrated for the 1H NMR spectroscopic platform (median CV 7.2%). Pooled samples captured the best inter-individual variability with an ICC of 0.40 (median). Trimethylamine, N-acetyl neuraminic acid, 3-hydroxyisobutyrate, 3-hydroxybutyrate/3-aminoisobutyrate, tyrosine, valine and 3-hydroxyisovalerate exhibited the highest stability with over 50% of variance specific to the child. The pooled sample was shown to capture the most inter-individual variance in the metabolic phenotype, which is of importance for molecular epidemiology study design. A substantial proportion of the variation in the urinary metabolome of children is specific to the individual, underlining the potential of such data to inform clinical and exposome studies conducted early in life.
Collapse
Affiliation(s)
- Léa Maitre
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL) Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - Chung-Ho E. Lau
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
- Division of Cancer, Department of Surgery and Cancer, Imperial College London, Institute of Reproductive and Developmental Biology (IRDB), Hammersmith Hospital, London W12 0NN, UK
| | - Esther Vizcaino
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - Oliver Robinson
- MRC-PHE Centre for Environment and Health, School of Public Health, Faculty of Medicine, Imperial College London, London, W2 1PG, UK
| | - Maribel Casas
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL) Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Alexandros P. Siskos
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
- Division of Cancer, Department of Surgery and Cancer, Imperial College London, Institute of Reproductive and Developmental Biology (IRDB), Hammersmith Hospital, London W12 0NN, UK
| | - Elizabeth J. Want
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| | - Toby Athersuch
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Faculty of Medicine, Imperial College London, London, W2 1PG, UK
| | - Remy Slama
- Inserm, Univ. Grenoble Alpes, CNRS, IAB (Institute of Advanced Biosciences), Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, F-38000 Grenoble, France
| | - Martine Vrijheid
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL) Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Hector C. Keun
- Division of Cancer, Department of Surgery and Cancer, Imperial College London, Institute of Reproductive and Developmental Biology (IRDB), Hammersmith Hospital, London W12 0NN, UK
| | - Muireann Coen
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, SW7 2AZ, UK
| |
Collapse
|
35
|
Kim YJ, Huh I, Kim JY, Park S, Ryu SH, Kim KB, Kim S, Park T, Kwon O. Integration of Traditional and Metabolomics Biomarkers Identifies Prognostic Metabolites for Predicting Responsiveness to Nutritional Intervention against Oxidative Stress and Inflammation. Nutrients 2017; 9:nu9030233. [PMID: 28273855 PMCID: PMC5372896 DOI: 10.3390/nu9030233] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 02/19/2017] [Accepted: 02/28/2017] [Indexed: 01/01/2023] Open
Abstract
Various statistical approaches can be applied to integrate traditional and omics biomarkers, allowing the discovery of prognostic markers to classify subjects into poor and good prognosis groups in terms of responses to nutritional interventions. Here, we performed a prototype study to identify metabolites that predict responses to an intervention against oxidative stress and inflammation, using a data set from a randomized controlled trial evaluating Korean black raspberry (KBR) in sedentary overweight/obese subjects. First, a linear mixed-effects model analysis with multiple testing correction showed that four-week consumption of KBR significantly changed oxidized glutathione (GSSG, q = 0.027) level, the ratio of reduced glutathione (GSH) to GSSG (q = 0.039) in erythrocytes, malondialdehyde (MDA, q = 0.006) and interleukin-6 (q = 0.006) levels in plasma, and seventeen NMR metabolites in urine compared with those in the placebo group. A subsequent generalized linear mixed model analysis showed linear correlations between baseline urinary glycine and N-phenylacetylglycine (PAG) and changes in the GSH:GSSG ratio (p = 0.008 and 0.004) as well as between baseline urinary adenine and changes in MDA (p = 0.018). Then, receiver operating characteristic analysis revealed that a two-metabolite set (glycine and PAG) had the strongest prognostic relevance for future interventions against oxidative stress (the area under the curve (AUC) = 0.778). Leave-one-out cross-validation confirmed the accuracy of prediction (AUC = 0.683). The current findings suggest that a higher level of this two-metabolite set at baseline is useful for predicting responders to dietary interventions in subjects with oxidative stress and inflammation, contributing to the emergence of personalized nutrition.
Collapse
Affiliation(s)
- You Jin Kim
- Department of Nutritional Science and Food Management, Ewha Womans University, Seoul 03760, Korea.
| | - Iksoo Huh
- Department of Statistics, Seoul National University, Seoul 08826, Korea.
| | - Ji Yeon Kim
- Department of Food Science and Technology, Seoul National University of Science and Technology, Seoul 01811, Korea.
| | - Saejong Park
- Department of Sport Science, Korea Institute of Sport Science, Seoul 01794, Korea.
| | - Sung Ha Ryu
- College of Pharmacy, Dankook University, Chungnam 31116, Korea.
| | - Kyu-Bong Kim
- College of Pharmacy, Dankook University, Chungnam 31116, Korea.
| | - Suhkmann Kim
- Department of Chemistry and Chemistry Institute for Functional Materials, Pusan National University, Busan 46241, Korea.
| | - Taesung Park
- Department of Statistics, Seoul National University, Seoul 08826, Korea.
| | - Oran Kwon
- Department of Nutritional Science and Food Management, Ewha Womans University, Seoul 03760, Korea.
| |
Collapse
|
36
|
Mumtaz MW, Hamid AA, Akhtar MT, Anwar F, Rashid U, AL-Zuaidy MH. An overview of recent developments in metabolomics and proteomics – phytotherapic research perspectives. FRONTIERS IN LIFE SCIENCE 2017. [DOI: 10.1080/21553769.2017.1279573] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Muhammad Waseem Mumtaz
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang, Malaysia
- Department of Chemistry, Faculty of Science, University of Gujrat, Gujrat, Pakistan
| | - Azizah Abdul Hamid
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang, Malaysia
| | - Muhammad Tayyab Akhtar
- Institute of Bioscience, Laboratory of Natural Products, Universiti Putra Malaysia, Serdang, Malaysia
| | - Farooq Anwar
- Department of Chemistry, University of Sargodha, Sargodha, Pakistan
| | - Umer Rashid
- Institute of Advanced Technology, Universiti Putra Malaysia, Serdang, Malaysia
| | - Mizher Hezam AL-Zuaidy
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang, Malaysia
| |
Collapse
|
37
|
Amberg A, Riefke B, Schlotterbeck G, Ross A, Senn H, Dieterle F, Keck M. NMR and MS Methods for Metabolomics. Methods Mol Biol 2017; 1641:229-258. [PMID: 28748468 DOI: 10.1007/978-1-4939-7172-5_13] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Metabolomics, also often referred as "metabolic profiling," is the systematic profiling of metabolites in biofluids or tissues of organisms and their temporal changes. In the last decade, metabolomics has become more and more popular in drug development, molecular medicine, and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. The increasing popularity of metabolomics has been possible only due to the enormous development in the technology and bioinformatics fields. In particular, the analytical technologies supporting metabolomics, i.e., NMR, UPLC-MS, and GC-MS, have evolved into sensitive and highly reproducible platforms allowing the determination of hundreds of metabolites in parallel. This chapter describes the best practices of metabolomics as seen today. All important steps of metabolic profiling in drug development and molecular medicine are described in great detail, starting from sample preparation to determining the measurement details of all analytical platforms, and finally to discussing the corresponding specific steps of data analysis.
Collapse
Affiliation(s)
| | - Björn Riefke
- Investigational Toxicology, Metabolic Profiling and Clinical Pathology, Bayer Pharma AG, Muellerstr. 178, Berlin, 13353, Germany.
| | - Götz Schlotterbeck
- School of Life Sciences, Institute for Chemistry and Bioanalytics, University of Applied Sciences, Northwestern Switzerland, Muttenz, Switzerland
| | - Alfred Ross
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Hans Senn
- Heythrop College UCL, Kensington Square, London W85HN, UK
| | - Frank Dieterle
- New Products and Medical, Near Patient Testing, Novartis, Basel, Switzerland
| | - Matthias Keck
- Analytical Development 1, Bayer Pharma AG, Wupperal, 42096, Germany
| |
Collapse
|
38
|
Lehman-Mckeeman LD, Car BD. Metabonomics: Application in Predictive and Mechanistic Toxicology. Toxicol Pathol 2016. [DOI: 10.1080/01926230490462084] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
| | - Bruce D. Car
- Discovery Toxicology, Bristol-Myers Squibb Company,
Princeton, New Jersey 08543, USA
| |
Collapse
|
39
|
Uppal K, Walker DI, Liu K, Li S, Go YM, Jones DP. Computational Metabolomics: A Framework for the Million Metabolome. Chem Res Toxicol 2016; 29:1956-1975. [PMID: 27629808 DOI: 10.1021/acs.chemrestox.6b00179] [Citation(s) in RCA: 167] [Impact Index Per Article: 20.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
"Sola dosis facit venenum." These words of Paracelsus, "the dose makes the poison", can lead to a cavalier attitude concerning potential toxicities of the vast array of low abundance environmental chemicals to which humans are exposed. Exposome research teaches that 80-85% of human disease is linked to environmental exposures. The human exposome is estimated to include >400,000 environmental chemicals, most of which are uncharacterized with regard to human health. In fact, mass spectrometry measures >200,000 m/z features (ions) in microliter volumes derived from human samples; most are unidentified. This crystallizes a grand challenge for chemical research in toxicology: to develop reliable and affordable analytical methods to understand health impacts of the extensive human chemical experience. To this end, there appears to be no choice but to abandon the limitations of measuring one chemical at a time. The present review looks at progress in computational metabolomics to provide probability-based annotation linking ions to known chemicals and serve as a foundation for unambiguous designation of unidentified ions for toxicologic study. We review methods to characterize ions in terms of accurate mass m/z, chromatographic retention time, correlation of adduct, isotopic and fragment forms, association with metabolic pathways and measurement of collision-induced dissociation products, collision cross section, and chirality. Such information can support a largely unambiguous system for documenting unidentified ions in environmental surveillance and human biomonitoring. Assembly of this data would provide a resource to characterize and understand health risks of the array of low-abundance chemicals to which humans are exposed.
Collapse
Affiliation(s)
- Karan Uppal
- Clinical Biomarkers Laboratory, Department of Medicine, Emory University , Atlanta, Georgia 30322, United States
| | - Douglas I Walker
- Clinical Biomarkers Laboratory, Department of Medicine, Emory University , Atlanta, Georgia 30322, United States.,Hercules Exposome Research Center, Department of Environmental Health, Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States.,Department of Civil and Environmental Engineering, Tufts University , Medford, Massachusetts 02155, United States
| | - Ken Liu
- Clinical Biomarkers Laboratory, Department of Medicine, Emory University , Atlanta, Georgia 30322, United States
| | - Shuzhao Li
- Clinical Biomarkers Laboratory, Department of Medicine, Emory University , Atlanta, Georgia 30322, United States.,Hercules Exposome Research Center, Department of Environmental Health, Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States
| | - Young-Mi Go
- Clinical Biomarkers Laboratory, Department of Medicine, Emory University , Atlanta, Georgia 30322, United States
| | - Dean P Jones
- Clinical Biomarkers Laboratory, Department of Medicine, Emory University , Atlanta, Georgia 30322, United States.,Hercules Exposome Research Center, Department of Environmental Health, Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States
| |
Collapse
|
40
|
Bub A, Kriebel A, Dörr C, Bandt S, Rist M, Roth A, Hummel E, Kulling S, Hoffmann I, Watzl B. The Karlsruhe Metabolomics and Nutrition (KarMeN) Study: Protocol and Methods of a Cross-Sectional Study to Characterize the Metabolome of Healthy Men and Women. JMIR Res Protoc 2016; 5:e146. [PMID: 27421387 PMCID: PMC4967183 DOI: 10.2196/resprot.5792] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Accepted: 06/24/2016] [Indexed: 01/01/2023] Open
Abstract
Background The human metabolome is influenced by various intrinsic and extrinsic factors. A precondition to identify such biomarkers is the comprehensive understanding of the composition and variability of the metabolome of healthy humans. Sample handling aspects have an important impact on the composition of the metabolome; therefore, it is crucial for any metabolomics study to standardize protocols on sample collection, preanalytical sample handling, storage, and analytics to keep the nonbiological variability as low as possible. Objective The main objective of the KarMeN study is to analyze the human metabolome in blood and urine by targeted and untargeted metabolite profiling (gas chromatography-mass spectrometry [GC-MS], GC×GC-MS, liquid chromatography-mass spectrometry [LC-MS/MS], and1H nuclear magnetic resonance [NMR] spectroscopy) and to determine the impact of sex, age, body composition, diet, and physical activity on metabolite profiles of healthy women and men. Here, we report the outline of the study protocol with special regard to all aspects that should be considered in studies applying metabolomics. Methods Healthy men and women, aged 18 years or older, were recruited. In addition to a number of anthropometric (height, weight, body mass index, waist circumference, body composition), clinical (blood pressure, electrocardiogram, blood and urine clinical chemistry) and functional parameters (lung function, arterial stiffness), resting metabolic rate, physical activity, fitness, and dietary intake were assessed, and 24-hour urine, fasting spot urine, and plasma samples were collected. Standard operating procedures were established for all steps of the study design. Using different analytical techniques (LC-MS, GC×GC-MS,1H NMR spectroscopy), metabolite profiles of urine and plasma were determined. Data will be analyzed using univariate and multivariate as well as predictive modeling methods. Results The project was funded in 2011 and enrollment was carried out between March 2012 and July 2013. A total of 301 volunteers were eligible to participate in the study. Metabolite profiling of plasma and urine samples has been completed and data analysis is currently underway. Conclusions We established the KarMeN study applying a broad set of clinical and physiological examinations with a high degree of standardization. Our experimental approach of combining scheduled timing of examinations and sampling with the multiplatform approach (GC×GC-MS, GC-MS, LC-MS/MS, and1H NMR spectroscopy) will enable us to differentiate between current and long-term effects of diet and physical activity on metabolite profiles, while enabling us at the same time to consider confounders such as age and sex in the KarMeN study. Trial Registration German Clinical Trials Register DRKS00004890; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00004890 (Archived by WebCite at http://www.webcitation.org/6iyM8dMtx)
Collapse
Affiliation(s)
- Achim Bub
- Max Rubner-Institut, Department of Physiology and Biochemistry of Nutrition, Karlsruhe, Germany.
| | | | | | | | | | | | | | | | | | | |
Collapse
|
41
|
El-Chab A, Simpson C, Lightowler H. The reproducibility of a diet using three different dietary standardisation techniques in athletes. Eur J Clin Nutr 2016; 70:954-8. [PMID: 27094626 DOI: 10.1038/ejcn.2016.55] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Revised: 01/25/2016] [Accepted: 02/21/2016] [Indexed: 11/09/2022]
Abstract
BACKGROUND/OBJECTIVES Participants are often asked to replicate their diet before each trial to control dietary intake. However, little is known about the reproducibility of the diet using different approaches. The aim was to assess the reproducibility of a diet when a controlled diet (Cdiet), food record (Frecord) and 24-h dietary recall (Drecall) were used as dietary standardisation techniques. SUBJECTS/METHODS Thirty athletes completed six visits to the laboratory. On the first occasion, a Drecall was performed and subjects were asked to replicate exactly the same diet on the day before visit 2, when another Drecall was performed. The day before the third visit, subjects completed a Frecord, which was presented at visit 3 and assessed using Drecall to ensure comparability between methods. Subjects were asked to replicate this Frecord before visit 4, which was assessed using Drecall. Finally, subjects were provided with a Cdiet of known composition, which they consumed for 24 h before visits 5 and 6. For each method, the difference in energy and macronutrient intakes between both occasions was measured. RESULTS Despite finding no differences in mean energy and macronutrient intakes between visits for any technique, important within-subject differences were apparent. The range of percentage coefficient of variation for all variables was between 2.7 and 5.8% for Cdiet, 10.1 and 18.6% for Frecord and 7.1 and 11.7% for Drecall. CONCLUSIONS This study has shown that Cdiet is the best approach to standardise dietary intake, especially when the expected effect of an intervention is small and an enhanced reliability is required.
Collapse
Affiliation(s)
- A El-Chab
- Department of Sport & Health Sciences, Oxford Brookes University, Oxford, UK
| | - C Simpson
- Department of Sport & Health Sciences, Oxford Brookes University, Oxford, UK
| | - H Lightowler
- Department of Sport & Health Sciences, Oxford Brookes University, Oxford, UK
| |
Collapse
|
42
|
Using NMR-Based Metabolomics to Evaluate Postprandial Urinary Responses Following Consumption of Minimally Processed Wheat Bran or Wheat Aleurone by Men and Women. Nutrients 2016; 8:96. [PMID: 26901221 PMCID: PMC4772058 DOI: 10.3390/nu8020096] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Revised: 01/08/2016] [Accepted: 02/04/2016] [Indexed: 11/17/2022] Open
Abstract
Wheat bran, and especially wheat aleurone fraction, are concentrated sources of a wide range of components which may contribute to the health benefits associated with higher consumption of whole-grain foods. This study used NMR metabolomics to evaluate urine samples from baseline at one and two hours postprandially, following the consumption of minimally processed bran, aleurone or control by 14 participants (7 Females; 7 Males) in a randomized crossover trial. The methodology discriminated between the urinary responses of control, and bran and aleurone, but not between the two fractions. Compared to control, consumption of aleurone or bran led to significantly and substantially higher urinary concentrations of lactate, alanine, N-acetylaspartate acid and N-acetylaspartylglutamate and significantly and substantially lower urinary betaine concentrations at one and two hours postprandially. There were sex related differences in urinary metabolite profiles with generally higher hippurate and citrate and lower betaine in females compared to males. Overall, this postprandial study suggests that acute consumption of bran or aleurone is associated with a number of physiological effects that may impact on energy metabolism and which are consistent with longer term human and animal metabolomic studies that used whole-grain wheat diets or wheat fractions.
Collapse
|
43
|
Wu Q, Zou M, Yang M, Zhou S, Yan X, Sun B, Wang Y, Chang S, Tang Y, Liang F, Yu S. Revealing Potential Biomarkers of Functional Dyspepsia by Combining 1H NMR Metabonomics Techniques and an Integrative Multi-objective Optimization Method. Sci Rep 2016; 6:18852. [PMID: 26743458 PMCID: PMC4705523 DOI: 10.1038/srep18852] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 11/27/2015] [Indexed: 12/31/2022] Open
Abstract
Metabonomics methods have gradually become important auxiliary tools for screening disease biomarkers. However, recognition of metabolites or potential biomarkers closely related to either particular clinical symptoms or prognosis has been difficult. The current study aims to identify potential biomarkers of functional dyspepsia (FD) by a new strategy that combined hydrogen nuclear magnetic resonance (1H NMR)-based metabonomics techniques and an integrative multi-objective optimization (LPIMO) method. First, clinical symptoms of FD were evaluated using the Nepean Dyspepsia Index (NDI), and plasma metabolic profiles were measured by 1H NMR. Correlations between the key metabolites and the NDI scores were calculated. Then, LPIMO was developed to identify a multi-biomarker panel by maximizing diagnostic ability and correlation with the NDI score. Finally, a KEGG database search elicited the metabolic pathways in which the potential biomarkers are involved. The results showed that glutamine, alanine, proline, HDL, β-glucose, α-glucose and LDL/VLDL levels were significantly altered in FD patients. Among them, phosphatidycholine (PtdCho) and leucine/isoleucine (Leu/Ile) were positively and negatively correlated with the NDI Symptom Index (NDSI) respectively. Our procedure not only significantly improved the credibility of the biomarkers, but also demonstrated the potential of further explorations and applications to diagnosis and treatment of complex disease.
Collapse
Affiliation(s)
- Qiaofeng Wu
- Acupuncture and Tuina College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 610075, China
| | - Meng Zou
- National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100080, China
| | - Mingxiao Yang
- Acupuncture and Tuina College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 610075, China
| | - Siyuan Zhou
- Acupuncture and Tuina College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 610075, China
| | - Xianzhong Yan
- National Center of Biomedical Analysis, Beijing, 100850, China
| | - Bo Sun
- National Center of Biomedical Analysis, Beijing, 100850, China
| | - Yong Wang
- National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100080, China
| | - Shyang Chang
- Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan
| | - Yong Tang
- Acupuncture and Tuina College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 610075, China
| | - Fanrong Liang
- Acupuncture and Tuina College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 610075, China
| | - Shuguang Yu
- Acupuncture and Tuina College, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 610075, China
| |
Collapse
|
44
|
Budde K, Gök ÖN, Pietzner M, Meisinger C, Leitzmann M, Nauck M, Köttgen A, Friedrich N. Quality assurance in the pre-analytical phase of human urine samples by 1H NMR spectroscopy. Arch Biochem Biophys 2016; 589:10-7. [DOI: 10.1016/j.abb.2015.07.016] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Revised: 07/06/2015] [Accepted: 07/22/2015] [Indexed: 02/04/2023]
|
45
|
Wu J, Gao Y. Physiological conditions can be reflected in human urine proteome and metabolome. Expert Rev Proteomics 2015; 12:623-36. [PMID: 26472227 DOI: 10.1586/14789450.2015.1094380] [Citation(s) in RCA: 99] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Biomarkers are the measurable changes associated with physiological or pathophysiological processes. Urine, unlike blood, lacks mechanisms for maintaining homeostasis: it is therefore an ideal source of biomarkers that can reflect systemic changes. Urinary proteome and metabolome have been studied for their diagnostic capabilities, ability to monitor disease and prognostic utility. In this review, the effects of common physiological conditions such as gender, age, diet, daily rhythms, exercise, hormone status, lifestyle and extreme environments on human urine are discussed. These effects should be considered when biomarker studies of diseases are conducted. More importantly, if physiological changes can be reflected in urine, we have reason to expect that urine will become widely used to detect small and early changes in pathological and/or pharmacological conditions.
Collapse
Affiliation(s)
- Jianqiang Wu
- a 1 Department of Pathophysiology, National Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China
| | - Youhe Gao
- a 1 Department of Pathophysiology, National Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China.,b 2 Department of Biochemistry and Molecular Biology, Beijing Normal University, Gene Engineering and Biotechnology Beijing Key Laboratory, Beijing, 100875, China
| |
Collapse
|
46
|
MRI for Crohn's Disease: Present and Future. BIOMED RESEARCH INTERNATIONAL 2015; 2015:786802. [PMID: 26413543 PMCID: PMC4564596 DOI: 10.1155/2015/786802] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/18/2014] [Revised: 10/09/2014] [Accepted: 12/11/2014] [Indexed: 12/18/2022]
Abstract
Crohn's disease (CD) is a chronic inflammatory condition with relapsing-remitting behavior, often causing strictures or penetrating bowel damage. Its lifelong clinical course necessitates frequent assessment of disease activity and complications. Computed tomography (CT) enterography has been used as primary imaging modality; however, the concern for radiation hazard limits its use especially in younger population. Magnetic resonance (MR) imaging has advantages of avoiding radiation exposure, lower incidence of adverse events, ability to obtain dynamic information, and good soft-tissue resolution. MR enterography (MRE) with oral contrast agent has been used as primary MR imaging modality of CD with high sensitivity, specificity, and interobserver agreement. The extent of inflammation as well as transmural ulcers and fibrostenotic diseases can be detected with MRE. Novel MR techniques such as diffusion-weighted MRI (DWI), motility study, PET-MRI, and molecular imaging are currently investigated for further improvement of diagnosis and management of CD. MR spectroscopy is a remarkable molecular imaging tool to analyze metabolic profile of CD with human samples such as plasma, urine, or feces, as well as colonic mucosa itself.
Collapse
|
47
|
1H nuclear magnetic resonance-based extracellular metabolomic analysis of multidrug resistant Tca8113 oral squamous carcinoma cells. Oncol Lett 2015; 9:2551-2559. [PMID: 26137105 DOI: 10.3892/ol.2015.3128] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2014] [Accepted: 03/19/2015] [Indexed: 01/13/2023] Open
Abstract
A major obstacle of successful chemotherapy is the development of multidrug resistance (MDR) in the cancer cells, which is difficult to reverse. Metabolomic analysis, an emerging approach that has been increasingly applied in various fields, is able to reflect the unique chemical fingerprints of specific cellular processes in an organism. The assessment of such metabolite changes can be used to identify novel therapeutic biomarkers. In the present study, 1H nuclear magnetic resonance (NMR) spectroscopy was used to analyze the extracellular metabolomic spectrum of the Tca8113 oral squamous carcinoma cell line, in which MDR was induced using the carboplatin (CBP) and pingyangmycin (PYM) chemotherapy drugs in vitro. The data were analyzed using the principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) methods. The results demonstrated that the extracellular metabolomic spectrum of metabolites such as glutamate, glycerophosphoethanol amine, α-Glucose and β-Glucose for the drug-induced Tca8113 cells was significantly different from the parental Tca8113 cell line. A number of biochemicals were also significantly different between the groups based on their NMR spectra, with drug-resistant cells presenting relatively higher levels of acetate and lower levels of lactate. In addition, a significantly higher peak was observed at δ 3.35 ppm in the spectrum of the PYM-induced Tca8113 cells. Therefore, 1H NMR-based metabolomic analysis has a high potential for monitoring the formation of MDR during clinical tumor chemotherapy in the future.
Collapse
|
48
|
Proton nuclear magnetic resonance spectroscopy of urine samples in preterm asphyctic newborn: a metabolomic approach. Clin Chim Acta 2015; 444:250-6. [PMID: 25727514 DOI: 10.1016/j.cca.2015.02.004] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Revised: 02/03/2015] [Accepted: 02/03/2015] [Indexed: 11/23/2022]
Abstract
In order to highlight differences in the metabolic profile of healthy (control) compared with asphyxiated newborns, by using untargeted metabolomic approach coupled with (1)H NMR spectroscopy, we evaluated the effects of asphyxia on newborn urine metabolites. Our results showed that lactate, glucose and TMAO, together with threonine plus 3-hydroxyisovalerate are the metabolites more characterizing the asphyxiated group; lower contribute to discrimination is related to other metabolites such as dimethylglycine, dimethylamine, creatine, succinate, formate, urea and aconitate. After 24-48h from resuscitation preterm asphyctic neonates showed their recovery pattern that still can be differentiated by the controls.
Collapse
|
49
|
Wallner-Liebmann S, Gralka E, Tenori L, Konrad M, Hofmann P, Dieber-Rotheneder M, Turano P, Luchinat C, Zatloukal K. The impact of free or standardized lifestyle and urine sampling protocol on metabolome recognition accuracy. GENES AND NUTRITION 2014; 10:441. [PMID: 25403096 DOI: 10.1007/s12263-014-0441-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Accepted: 11/05/2014] [Indexed: 12/23/2022]
Abstract
Urine contains a clear individual metabolic signature, although embedded within a large daily variability. Given the potential of metabolomics to monitor disease onset from deviations from the "healthy" metabolic state, we have evaluated the effectiveness of a standardized lifestyle in reducing the "metabolic" noise. Urine was collected from 24 (5 men and 19 women) healthy volunteers over a period of 10 days: phase I, days 1-7 in a real-life situation; phase II, days 8-10 in a standardized diet and day 10 plus exercise program. Data on dietary intake and physical activity have been analyzed by a nation-specific software and monitored by published protocols. Urine samples have been analyzed by (1)H NMR followed by multivariate statistics. The individual fingerprint emerged and consolidated with increasing the number of samples and reaches ~100 % cross-validated accuracy for about 40 samples. Diet standardization reduced both the intra-individual and the interindividual variability; the effect was due to a reduction in the dispersion of the concentration values of several metabolites. Under standardized diet, however, the individual phenotype was still clearly visible, indicating that the individual's signature was a strong feature of the metabolome. Consequently, cohort studies designed to investigate the relation of individual metabolic traits and nutrition require multiple samples from each participant even under highly standardized lifestyle conditions in order to exploit the analytical potential of metabolomics. We have established criteria to facilitate design of urine metabolomic studies aimed at monitoring the effects of drugs, lifestyle, dietary supplements, and for accurate determination of signatures of diseases.
Collapse
Affiliation(s)
- Sandra Wallner-Liebmann
- Center of Molecular Medicine, Institute of Pathophysiology and Immunology, Medical University Graz, Heinrichstraße 31a, 8010, Graz, Austria,
| | | | | | | | | | | | | | | | | |
Collapse
|
50
|
Beisken S, Eiden M, Salek RM. Getting the right answers: understanding metabolomics challenges. Expert Rev Mol Diagn 2014; 15:97-109. [DOI: 10.1586/14737159.2015.974562] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
|