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Metabolomics in Medicine

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biology".

Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 27263

Special Issue Editors

Prof. Dr. Soumeya Bekri

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Guest Editor
Metabolic Biochemistry Department, Rouen University Hospital, France
Interests: Precision Medicine; Omics; Inherited metabolic diseases; Lysosomal storage diseases; Human genetics
Dr. Abdellah Tebani

E-Mail
Guest Editor
Metabolic Biochemistry Department, Rouen University Hospital, France
Interests: Precision Medicine; Integrative omics; Clinical chemistry; Inherited metabolic diseases; Chemometrics and Design of Experiments; Machine learning; Digital health

Special Issue Information

Dear Colleagues,

Precision medicine capitalizes on both conceptual paradigm shifts and technological disruptive advancements to reach a more integrative and holistic definition of health and disease states. It relies on both biological individuality and populational knowledge, which mutually nurture each other. It stands on two main pillars: Data generation and data modeling. High-throughput technologies now allow the retrieval of comprehensive, dynamic, and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and clinically actionable information. Metabolites can be defined as organic small molecules produced by enzymatic reactions. Metabolome refers to all metabolites present in a given biological system, fluid, cell, or tissue. Metabolomics is an -omics technology that retrieves a precious functional biochemical readout, which sets it as the closest to the phenotype. Hence, metabolic phenotyping is an appealing technology to interrogate the molecular phenotype of biological systems. Indeed, metabolomics has found different applications in newborn screening and in many disease studies and complex pathologies, with promising perspectives in screening, diagnosis, prognosis, patient stratification, and treatment follow-up. This promising centrality of metabolomics in the new healthcare landscape sets it as a key driver in the exciting era of precision medicine.

This Special Issue welcomes scientific contributions and critical reviews analyzing the role of metabolomics in the precision medicine era. It will consider the many translational and clinical dimensions of metabolomics, including: Sample handling and analytical development challenges, data analysis, metabolic modeling, and network analysis. Large-scale association studies and integrative -omics and the inherent bioinformatics and computing challenges will be also considered. Articles focusing on the current potential of clinical metabolomics, including screening, diagnosis, pathology, and imaging, in rare and common diseases are highly desired.

Potential topics include but are not limited to:

Clinical metabolomics;
Laboratory medicine;
Precision medicine;
Systems medicine;
Data analysis, bioinformatics, and big data challenges;
Metabolomics databases;
Metabolic modeling and network analysis;
Integrative -omics;
Disease screening and diagnosis;
Companion diagnostics;
Metabolomics-based imaging and pathology.

Prof. Dr. Soumeya Bekri
Dr. Abdellah Tebani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (5 papers)

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Research

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16 pages, 1033 KiB  
Article
Blood Metabolite Signatures of Metabolic Syndrome in Two Cross-Cultural Older Adult Cohorts
by Uma V. Mahajan, Vijay R. Varma, Chiung-Wei Huang, Yang An, Toshiko Tanaka, Luigi Ferrucci, Toru Takebayashi, Sei Harada, Miho Iida, Cristina Legido-Quigley and Madhav Thambisetty
Int. J. Mol. Sci. 2020, 21(4), 1324; https://doi.org/10.3390/ijms21041324 - 16 Feb 2020
Cited by 15 | Viewed by 4242
Abstract
Metabolic syndrome (MetS) affects an increasing number of older adults worldwide. Cross-cultural comparisons can provide insight into how factors, including genetic, environmental, and lifestyle, may influence MetS prevalence. Metabolomics, which measures the biochemical products of cell processes, can be used to enhance a [...] Read more.
Metabolic syndrome (MetS) affects an increasing number of older adults worldwide. Cross-cultural comparisons can provide insight into how factors, including genetic, environmental, and lifestyle, may influence MetS prevalence. Metabolomics, which measures the biochemical products of cell processes, can be used to enhance a mechanistic understanding of how biological factors influence metabolic outcomes. In this study we examined associations between serum metabolite concentrations, representing a range of biochemical pathways and metabolic syndrome in two older adult cohorts: The Tsuruoka Metabolomics Cohort Study (TMCS) from Japan (n = 104) and the Baltimore Longitudinal Study of Aging (BLSA) from the United States (n = 146). We used logistic regression to model associations between MetS and metabolite concentrations. We found that metabolites from the phosphatidylcholines-acyl-alkyl, sphingomyelin, and hexose classes were significantly associated with MetS and risk factor outcomes in both cohorts. In BLSA, metabolites across all classes were uniquely associated with all outcomes. In TMCS, metabolites from the amino acid, biogenic amines, and free fatty acid classes were uniquely associated with MetS, and metabolites from the sphingomyelin class were uniquely associated with elevated triglycerides. The metabolites and metabolite classes we identified may be relevant for future studies exploring disease mechanisms and identifying novel precision therapy targets for individualized medicine. Full article
(This article belongs to the Special Issue Metabolomics in Medicine)
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20 pages, 4207 KiB  
Article
Blood Metabolite Signature of Metabolic Syndrome Implicates Alterations in Amino Acid Metabolism: Findings from the Baltimore Longitudinal Study of Aging (BLSA) and the Tsuruoka Metabolomics Cohort Study (TMCS)
by Jackson A. Roberts, Vijay R. Varma, Chiung-Wei Huang, Yang An, Anup Oommen, Toshiko Tanaka, Luigi Ferrucci, Palchamy Elango, Toru Takebayashi, Sei Harada, Miho Iida and Madhav Thambisetty
Int. J. Mol. Sci. 2020, 21(4), 1249; https://doi.org/10.3390/ijms21041249 - 13 Feb 2020
Cited by 20 | Viewed by 4989
Abstract
Rapid lifestyle and dietary changes have contributed to a rise in the global prevalence of metabolic syndrome (MetS), which presents a potential healthcare crisis, owing to its association with an increased burden of multiple cardiovascular and neurological diseases. Prior work has identified the [...] Read more.
Rapid lifestyle and dietary changes have contributed to a rise in the global prevalence of metabolic syndrome (MetS), which presents a potential healthcare crisis, owing to its association with an increased burden of multiple cardiovascular and neurological diseases. Prior work has identified the role that genetic, lifestyle, and environmental factors can play in the prevalence of MetS. Metabolomics is an important tool to study alterations in biochemical pathways intrinsic to the pathophysiology of MetS. We undertook a metabolomic study of MetS in serum samples from two ethnically distinct, well-characterized cohorts—the Baltimore Longitudinal Study of Aging (BLSA) from the U.S. and the Tsuruoka Metabolomics Cohort Study (TMCS) from Japan. We used multivariate logistic regression to identify metabolites that were associated with MetS in both cohorts. Among the top 25 most significant (lowest p-value) metabolite associations with MetS in each cohort, we identified 18 metabolites that were shared between TMCS and BLSA, the majority of which were classified as amino acids. These associations implicate multiple biochemical pathways in MetS, including branched-chain amino acid metabolism, glutathione production, aromatic amino acid metabolism, gluconeogenesis, and the tricarboxylic acid cycle. Our results suggest that fundamental alterations in amino acid metabolism may be central features of MetS. Full article
(This article belongs to the Special Issue Metabolomics in Medicine)
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20 pages, 1040 KiB  
Article
The Metabolomic Signature of the Placenta in Spontaneous Preterm Birth
by Summer Elshenawy, Sara E. Pinney, Tami Stuart, Paschalis-Thomas Doulias, Gabriella Zura, Samuel Parry, Michal A. Elovitz, Michael J. Bennett, Amita Bansal, Jerome F. Strauss III, Harry Ischiropoulos and Rebecca A. Simmons
Int. J. Mol. Sci. 2020, 21(3), 1043; https://doi.org/10.3390/ijms21031043 - 4 Feb 2020
Cited by 43 | Viewed by 5163
Abstract
The placenta is metabolically active and supports the growth of the fetus. We hypothesize that deficits in the capacity of the placenta to maintain bioenergetic and metabolic stability during pregnancy may result in spontaneous preterm birth (SPTB). To explore this hypothesis, we performed [...] Read more.
The placenta is metabolically active and supports the growth of the fetus. We hypothesize that deficits in the capacity of the placenta to maintain bioenergetic and metabolic stability during pregnancy may result in spontaneous preterm birth (SPTB). To explore this hypothesis, we performed a nested cased control study of metabolomic signatures in placentas from women with SPTB (<36 weeks gestation) compared to normal pregnancies (≥38 weeks gestation). To control for the effects of gestational age on placenta metabolism, we also studied a subset of metabolites in non-laboring preterm and term Rhesus monkeys. Comprehensive quantification of metabolites demonstrated a significant elevation in the levels of amino acids, prostaglandins, sphingolipids, lysolipids, and acylcarnitines in SPTB placenta compared to term placenta. Additional quantification of placental acylcarnitines by tandem mass spectrometry confirmed the significant elevation in SPTB human, with no significant differences between midgestation and term placenta in Rhesus macaque. Fatty acid oxidation as measured by the flux of 3H-palmitate in SPTB placenta was lower than term. Collectively, significant and biologically relevant alterations in the placenta metabolome were identified in SPTB placenta. Altered acylcarnitine levels and fatty acid oxidation suggest that disruption in normal substrate metabolism is associated with SPTB. Full article
(This article belongs to the Special Issue Metabolomics in Medicine)
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14 pages, 2900 KiB  
Article
Mass Spectrometry-Based Metabolomics Analysis of Obese Patients’ Blood Plasma
by Petr G. Lokhov, Elena E. Balashova, Oxana P. Trifonova, Dmitry L. Maslov, Elena A. Ponomarenko and Alexander I. Archakov
Int. J. Mol. Sci. 2020, 21(2), 568; https://doi.org/10.3390/ijms21020568 - 15 Jan 2020
Cited by 23 | Viewed by 4978
Abstract
Scientists currently use only a small portion of the information contained in the blood metabolome. The identification of metabolites is a huge challenge because only highly abundant and well-separated compounds can be easily identified in complex samples. However, new approaches that enhance the [...] Read more.
Scientists currently use only a small portion of the information contained in the blood metabolome. The identification of metabolites is a huge challenge because only highly abundant and well-separated compounds can be easily identified in complex samples. However, new approaches that enhance the identification of compounds have emerged; among them, the identification of compounds based on their involvement in a particular biological context is a recent development. In this work, this approach was first applied to identify metabolites in complex samples and, together with metabolite set enrichment analysis, was used for the evaluation of blood plasma from obese patients. The proposed approach was found to provide a statistically sound overview of the biochemical pathways, thus presenting additional information on obesity. Obesity progression was demonstrated to be accompanied by marked alterations in steroidogenesis, androstenedione metabolism, and androgen and estrogen metabolism. The findings of this study suggest that the workflow used for blood analysis is sufficient to demonstrate obesity at the biochemical pathway level as well as to monitor the response to treatment. This workflow is also expected to be suitable for studying other metabolic diseases. Full article
(This article belongs to the Special Issue Metabolomics in Medicine)
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Review

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17 pages, 1464 KiB  
Review
Metabolomics to Improve the Diagnostic Efficiency of Inborn Errors of Metabolism
by Dylan Mordaunt, David Cox and Maria Fuller
Int. J. Mol. Sci. 2020, 21(4), 1195; https://doi.org/10.3390/ijms21041195 - 11 Feb 2020
Cited by 32 | Viewed by 7349
Abstract
Early diagnosis of inborn errors of metabolism (IEM)—a large group of congenital disorders—is critical, given that many respond well to targeted therapy. Newborn screening programs successfully capture a proportion of patients enabling early recognition and prompt initiation of therapy. For others, the heterogeneity [...] Read more.
Early diagnosis of inborn errors of metabolism (IEM)—a large group of congenital disorders—is critical, given that many respond well to targeted therapy. Newborn screening programs successfully capture a proportion of patients enabling early recognition and prompt initiation of therapy. For others, the heterogeneity in clinical presentation often confuses diagnosis with more common conditions. In the absence of family history and following clinical suspicion, the laboratory diagnosis typically begins with broad screening tests to circumscribe specialised metabolite and/or enzyme assays to identify the specific IEM. Confirmation of the biochemical diagnosis is usually achieved by identifying pathogenic genetic variants that will also enable cascade testing for family members. Unsurprisingly, this diagnostic trajectory is too often a protracted and lengthy process resulting in delays in diagnosis and, importantly, therapeutic intervention for these rare conditions is also postponed. Implementation of mass spectrometry technologies coupled with the expanding field of metabolomics is changing the landscape of diagnosing IEM as numerous metabolites, as well as enzymes, can now be measured collectively on a single mass spectrometry-based platform. As the biochemical consequences of impaired metabolism continue to be elucidated, the measurement of secondary metabolites common across groups of IEM will facilitate algorithms to further increase the efficiency of diagnosis. Full article
(This article belongs to the Special Issue Metabolomics in Medicine)
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