Metabolomics in Human Tissues and Materials

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Advances in Metabolomics".

Deadline for manuscript submissions: closed (30 April 2020) | Viewed by 39278

Special Issue Editor


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Guest Editor
1. Beaumont Health, Royal Oak, MI 48073, USA
2. Oakland University-William Beaumont School of Medicine, Rochester Hills, MI 48309, USA
Interests: metabolomics; neurodegenerative disease; biomarkers; etiology; pathophysiology; integrating omics; epigenetics; proteomics
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Special Issue Information

Dear Colleagues,

Large-scale metabolomics studies that use human peripheral tissues to identify biomarkers for the early prediction and/or diagnosis of disease have become very appealing due to the number of metabolites that can now be accurately measured and identified. Further, metabolomics is being incorporated into many high-impact studies that focus on the etiopathophysiology of disease due to its innate ability to provide the most comprehensive insight into any given phenotype. Moreover, metabolomics is being increasingly used in the nutritional field to determine the effects of environmental pressures on the human “ome”.  This list of applications is by no means comprehensive, and as such, this Special Issue is focused on (but not limited to) highlighting the use of metabolomics in studies that use human acquired specimens to do the following: (i) identify diagnostic and prognostic biomarkers of disease; (ii) study disease pathogenesis; (iii) conduct personalized/precision medicine; (iv) identify novel therapeutic targets; and (v) determine the effect of environmental exposure (including chemical and lifestyle exposures) on the human metabolome.  

Dr. Stewart Graham
Guest Editor

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Keywords

  • Biomarkers
  • Etiology
  • Pathophysiology
  • Nutrition
  • Precision medicine
  • Human specimens

Published Papers (8 papers)

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Research

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12 pages, 688 KiB  
Article
Targeted Metabolic Profiling of Urine Highlights a Potential Biomarker Panel for the Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment: A Pilot Study
by Ali Yilmaz, Zafer Ugur, Halil Bisgin, Sumeyya Akyol, Ray Bahado-Singh, George Wilson, Khaled Imam, Michael E. Maddens and Stewart F. Graham
Metabolites 2020, 10(9), 357; https://doi.org/10.3390/metabo10090357 - 31 Aug 2020
Cited by 31 | Viewed by 4607
Abstract
The lack of sensitive and specific biomarkers for the early detection of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) is a major hurdle to improving patient management. A targeted, quantitative metabolomics approach using both 1H NMR and mass spectrometry was employed [...] Read more.
The lack of sensitive and specific biomarkers for the early detection of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) is a major hurdle to improving patient management. A targeted, quantitative metabolomics approach using both 1H NMR and mass spectrometry was employed to investigate the performance of urine metabolites as potential biomarkers for MCI and AD. Correlation-based feature selection (CFS) and least absolute shrinkage and selection operator (LASSO) methods were used to develop biomarker panels tested using support vector machine (SVM) and logistic regression models for diagnosis of each disease state. Metabolic changes were investigated to identify which biochemical pathways were perturbed as a direct result of MCI and AD in urine. Using SVM, we developed a model with 94% sensitivity, 78% specificity, and 78% AUC to distinguish healthy controls from AD sufferers. Using logistic regression, we developed a model with 85% sensitivity, 86% specificity, and an AUC of 82% for AD diagnosis as compared to cognitively healthy controls. Further, we identified 11 urinary metabolites that were significantly altered to include glucose, guanidinoacetate, urocanate, hippuric acid, cytosine, 2- and 3-hydroxyisovalerate, 2-ketoisovalerate, tryptophan, trimethylamine N oxide, and malonate in AD patients, which are also capable of diagnosing MCI, with a sensitivity value of 76%, specificity of 75%, and accuracy of 81% as compared to healthy controls. This pilot study suggests that urine metabolomics may be useful for developing a test capable of diagnosing and distinguishing MCI and AD from cognitively healthy controls. Full article
(This article belongs to the Special Issue Metabolomics in Human Tissues and Materials)
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12 pages, 1712 KiB  
Article
Metabolic Profiling Reveals Significant Perturbations of Intracellular Glucose Homeostasis in Enterovirus-Infected Cells
by Zijiao Zou, Jessica Oi-Ling Tsang, Bingpeng Yan, Kenn Ka-Heng Chik, Chris Chun-Yiu Chan, Jianli Cao, Ronghui Liang, Kaiming Tang, Feifei Yin, Zi-Wei Ye, Hin Chu, Jasper Fuk-Woo Chan, Shuofeng Yuan and Kwok-Yung Yuen
Metabolites 2020, 10(8), 302; https://doi.org/10.3390/metabo10080302 - 23 Jul 2020
Cited by 9 | Viewed by 2351
Abstract
Enterovirus A71 (EV-A71) is a common cause of hand, foot, and mouth disease. Severe EV-A71 infections may be associated with life-threatening neurological complications. However, the pathogenic mechanisms underlying these severe clinical and pathological features remain incompletely understood. Metabolites are known to play critical [...] Read more.
Enterovirus A71 (EV-A71) is a common cause of hand, foot, and mouth disease. Severe EV-A71 infections may be associated with life-threatening neurological complications. However, the pathogenic mechanisms underlying these severe clinical and pathological features remain incompletely understood. Metabolites are known to play critical roles in multiple stages of the replication cycles of viruses. The metabolic reprogramming induced by viral infections is essential for optimal virus replication and may be potential antiviral targets. In this study, we applied targeted metabolomics profiling to investigate the metabolic changes of induced pluripotent human stem cell (iPSC)-derived neural progenitor cells (NPCs) upon EV-A71 infection. A targeted quantitation of polar metabolites identified 14 candidates with altered expression profiles. A pathway enrichment analysis pinpointed glucose metabolic pathways as being highly perturbed upon EV-A71 infection. Gene silencing of one of the key enzymes of glycolysis, 6-phosphofructo-2-kinase (PFKFB3), significantly suppressed EV-A71 replication in vitro. Collectively, we demonstrated the feasibility to manipulate EV-A71-triggered host metabolic reprogramming as a potential anti-EV-A71 strategy. Full article
(This article belongs to the Special Issue Metabolomics in Human Tissues and Materials)
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16 pages, 1593 KiB  
Article
The Biochemical Profile of Post-Mortem Brain from People Who Suffered from Epilepsy Reveals Novel Insights into the Etiopathogenesis of the Disease
by Ashna M. Lalwani, Ali Yilmaz, Halil Bisgin, Zafer Ugur, Sumeyya Akyol and Stewart Francis Graham
Metabolites 2020, 10(6), 261; https://doi.org/10.3390/metabo10060261 - 23 Jun 2020
Cited by 8 | Viewed by 3523
Abstract
Epilepsy not-otherwise-specified (ENOS) is one of the most common causes of chronic disorders impacting human health, with complex multifactorial etiology and clinical presentation. Understanding the metabolic processes associated with the disorder may aid in the discovery of preventive and therapeutic measures. Post-mortem brain [...] Read more.
Epilepsy not-otherwise-specified (ENOS) is one of the most common causes of chronic disorders impacting human health, with complex multifactorial etiology and clinical presentation. Understanding the metabolic processes associated with the disorder may aid in the discovery of preventive and therapeutic measures. Post-mortem brain samples were harvested from the frontal cortex (BA8/46) of people diagnosed with ENOS cases (n = 15) and age- and sex-matched control subjects (n = 15). We employed a targeted metabolomics approach using a combination of proton nuclear magnetic resonance (1H-NMR) and direct injection/liquid chromatography tandem mass spectrometry (DI/LC-MS/MS). We accurately identified and quantified 72 metabolites using 1H-NMR and 159 using DI/LC-MS/MS. Among the 212 detected metabolites, 14 showed significant concentration changes between ENOS cases and controls (p < 0.05; q < 0.05). Of these, adenosine monophosphate and O-acetylcholine were the most commonly selected metabolites used to develop predictive models capable of discriminating between ENOS and unaffected controls. Metabolomic set enrichment analysis identified ethanol degradation, butyrate metabolism and the mitochondrial beta-oxidation of fatty acids as the top three significantly perturbed metabolic pathways. We report, for the first time, the metabolomic profiling of postmortem brain tissue form patients who died from epilepsy. These findings can potentially expand upon the complex etiopathogenesis and help identify key predictive biomarkers of ENOS. Full article
(This article belongs to the Special Issue Metabolomics in Human Tissues and Materials)
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14 pages, 1401 KiB  
Article
A Data Mining Metabolomics Exploration of Glaucoma
by Judith Kouassi Nzoughet, Khadidja Guehlouz, Stéphanie Leruez, Philippe Gohier, Cinzia Bocca, Jeanne Muller, Odile Blanchet, Dominique Bonneau, Gilles Simard, Dan Milea, Vincent Procaccio, Guy Lenaers, Juan M. Chao de la Barca and Pascal Reynier
Metabolites 2020, 10(2), 49; https://doi.org/10.3390/metabo10020049 - 28 Jan 2020
Cited by 29 | Viewed by 3503
Abstract
Glaucoma is an age related disease characterized by the progressive loss of retinal ganglion cells, which are the neurons that transduce the visual information from the retina to the brain. It is the leading cause of irreversible blindness worldwide. To gain further insights [...] Read more.
Glaucoma is an age related disease characterized by the progressive loss of retinal ganglion cells, which are the neurons that transduce the visual information from the retina to the brain. It is the leading cause of irreversible blindness worldwide. To gain further insights into primary open-angle glaucoma (POAG) pathophysiology, we performed a non-targeted metabolomics analysis on the plasma from POAG patients (n = 34) and age- and sex-matched controls (n = 30). We investigated the differential signature of POAG plasma compared to controls, using liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS). A data mining strategy, combining a filtering method with threshold criterion, a wrapper method with iterative selection, and an embedded method with penalization constraint, was used. These strategies are most often used separately in metabolomics studies, with each of them having their own limitations. We opted for a synergistic approach as a mean to unravel the most relevant metabolomics signature. We identified a set of nine metabolites, namely: nicotinamide, hypoxanthine, xanthine, and 1-methyl-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline with decreased concentrations and N-acetyl-L-Leucine, arginine, RAC-glycerol 1-myristate, 1-oleoyl-RAC-glycerol, cystathionine with increased concentrations in POAG; the modification of nicotinamide, N-acetyl-L-Leucine, and arginine concentrations being the most discriminant. Our findings open up therapeutic perspectives for the diagnosis and treatment of POAG. Full article
(This article belongs to the Special Issue Metabolomics in Human Tissues and Materials)
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Review

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18 pages, 1088 KiB  
Review
Recommendations and Best Practices for Standardizing the Pre-Analytical Processing of Blood and Urine Samples in Metabolomics
by Raúl González-Domínguez, Álvaro González-Domínguez, Ana Sayago and Ángeles Fernández-Recamales
Metabolites 2020, 10(6), 229; https://doi.org/10.3390/metabo10060229 - 3 Jun 2020
Cited by 73 | Viewed by 9299
Abstract
Metabolomics can be significantly influenced by a range of pre-analytical factors, such as sample collection, pre-processing, aliquoting, transport, storage and thawing. This therefore shows the crucial need for standardizing the pre-analytical phase with the aim of minimizing the inter-sample variability driven by these [...] Read more.
Metabolomics can be significantly influenced by a range of pre-analytical factors, such as sample collection, pre-processing, aliquoting, transport, storage and thawing. This therefore shows the crucial need for standardizing the pre-analytical phase with the aim of minimizing the inter-sample variability driven by these technical issues, as well as for maintaining the metabolic integrity of biological samples to ensure that metabolomic profiles are a direct expression of the in vivo biochemical status. This review article provides an updated literature revision of the most important factors related to sample handling and pre-processing that may affect metabolomics results, particularly focusing on the most commonly investigated biofluids in metabolomics, namely blood plasma/serum and urine. Finally, we also provide some general recommendations and best practices aimed to standardize and accurately report all these pre-analytical aspects in metabolomics research. Full article
(This article belongs to the Special Issue Metabolomics in Human Tissues and Materials)
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15 pages, 227 KiB  
Review
Metabolomic Profiling in the Characterization of Degenerative Bone and Joint Diseases
by Katherine R. Swank, Jamie E. Furness, Erin A. Baker, Corinn K. Gehrke, Stephen P. Biebelhausen and Kevin C. Baker
Metabolites 2020, 10(6), 223; https://doi.org/10.3390/metabo10060223 - 29 May 2020
Cited by 24 | Viewed by 3005
Abstract
Osteoarthritis and inflammatory arthropathies are a cause of significant morbidity globally. New research elucidating the metabolic derangements associated with a variety of bone and joint disorders implicates various local and systemic metabolites, which further elucidate the underlying molecular mechanisms associated with these destructive [...] Read more.
Osteoarthritis and inflammatory arthropathies are a cause of significant morbidity globally. New research elucidating the metabolic derangements associated with a variety of bone and joint disorders implicates various local and systemic metabolites, which further elucidate the underlying molecular mechanisms associated with these destructive disease processes. In osteoarthritis, atty acid metabolism has been implicated in disease development, both locally and systemically. Several series of rheumatoid arthritis patients have demonstrated overlapping trends related to histidine and glyceric acid, while other series showed similar results of increased cholesterol and glutamic acid. Studies comparing osteoarthritis and rheumatoid arthritis reported elevated gluconic acid and glycolytic- and tricarboxylic acid-related substrates in patients with osteoarthritis, while lysosphingolipids and cardiolipins were elevated only in patients with rheumatoid arthritis. Other bone and joint disorders, including osteonecrosis, intervertebral disc degeneration, and osteoporosis, also showed significant alterations in metabolic processes. The identification of the molecular mechanisms of osteoarthritis and inflammatory arthropathies via metabolomics-based workflows may allow for the development of new therapeutic targets to improve the quality of life in these patient populations. Full article
(This article belongs to the Special Issue Metabolomics in Human Tissues and Materials)
14 pages, 642 KiB  
Review
The Application of Metabolomics to Probiotic and Prebiotic Interventions in Human Clinical Studies
by Thomas M. O’Connell
Metabolites 2020, 10(3), 120; https://doi.org/10.3390/metabo10030120 - 24 Mar 2020
Cited by 20 | Viewed by 4119
Abstract
There is an ever-increasing appreciation for our gut microbiota that plays a crucial role in the maintenance of health, as well as the development of disease. Probiotics are live bacteria that are consumed to increase the population of beneficial bacteria and prebiotics are [...] Read more.
There is an ever-increasing appreciation for our gut microbiota that plays a crucial role in the maintenance of health, as well as the development of disease. Probiotics are live bacteria that are consumed to increase the population of beneficial bacteria and prebiotics are dietary substrates intended to promote the propagation of beneficial bacteria. In order to optimize the use of probiotics and prebiotics, a more complete biochemical understanding of the impact that these treatments have on the community and functioning of the gut microbiota is required. Nucleic acid sequencing methods can provide highly detailed information on the composition of the microbial communities but provide less information on the actual function. As bacteria impart much of their influence on the host through the production of metabolites, there is much to be learned by the application of metabolomics. The focus of this review is on the use of metabolomics in the study of probiotic and prebiotic treatments in the context of human clinical trials. Assessment of the current state of this research will help guide the design of future studies to further elucidate the biochemical mechanism by which probiotics and prebiotics function and pave the way toward more personalized applications. Full article
(This article belongs to the Special Issue Metabolomics in Human Tissues and Materials)
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23 pages, 2128 KiB  
Review
Salivary Metabolomics: From Diagnostic Biomarker Discovery to Investigating Biological Function
by Alexander Gardner, Guy Carpenter and Po-Wah So
Metabolites 2020, 10(2), 47; https://doi.org/10.3390/metabo10020047 - 26 Jan 2020
Cited by 84 | Viewed by 8289
Abstract
Metabolomic profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, metabolomic analysis of saliva, the most readily-available human biofluid, has lagged. This review explores the history of saliva-based metabolomics and summarizes current [...] Read more.
Metabolomic profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, metabolomic analysis of saliva, the most readily-available human biofluid, has lagged. This review explores the history of saliva-based metabolomics and summarizes current knowledge of salivary metabolomics. Current applications of salivary metabolomics have largely focused on diagnostic biomarker discovery and the diagnostic value of the current literature base is explored. There is also a small, albeit promising, literature base concerning the use of salivary metabolomics in monitoring athletic performance. Functional roles of salivary metabolites remain largely unexplored. Areas of emerging knowledge include the role of oral host–microbiome interactions in shaping the salivary metabolite profile and the potential roles of salivary metabolites in oral physiology, e.g., in taste perception. Discussion of future research directions describes the need to begin acquiring a greater knowledge of the function of salivary metabolites, a current research direction in the field of the gut metabolome. The role of saliva as an easily obtainable, information-rich fluid that could complement other gastrointestinal fluids in the exploration of the gut metabolome is emphasized. Full article
(This article belongs to the Special Issue Metabolomics in Human Tissues and Materials)
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