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Biomarker Discovery in Medical and Health Contexts Using Metabolomics

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A special issue of International Journal of Translational Medicine (ISSN 2673-8937).

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 12108

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Special Issue Editors

Dr. François Fenaille

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Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, MetaboHUB, F-91191 Gif sur Yvette, France
Interests: mass spectrometry; metabolomics; lipidomics; glycomics; targeted proteomics; biomarkers; medical applications

Dr. Florence Castelli

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Département Médicaments et Technologies pour la Santé (DMTS), University Paris-Saclay, CEA, INRAE, MetaboHUB, 91191 Gif sur Yvette, France
Interests: mass spectrometry; metabolomics; lipidomics; glycomics; targeted proteomics; biomarkers; medical applications

Dr. Benoit Colsch

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Special Issue Information

Dear Colleagues,

Research and developments in biomarker discovery are central in modern health care for personalized and precision medicine. Omics approaches are particularly relevant and useful tools to identify new molecular biomarkers to improve the diagnosis and prognosis of various diseases, as well as to evaluate treatment efficacy. In this context, metabolomics represents an attractive strategy for profiling in patient biofluids or tissues samples a large panel of low molecular weight molecules closely related to (patho)physiological conditions and treatment response phenotypes.

This Special Issue of the International Journal of Translational Medicine will be devoted to the development and use of metabolomics approaches at both the translational and the clinical level. Topics may include but are not limited to metabolomics for biomarker discovery of specific diseases or in a personalized medicine context, molecular understanding of pathophysiological contexts, methodological developments (e.g., for broadening metabolome coverage or implementation of more sensitive approaches), and approaches for large-scale analysis of human cohorts. Other manuscripts dealing with the lipidome or the glycome that are “subsets” of the metabolome are also welcome.

Dr. François Fenaille
Dr. Florence Castelli
Dr. Benoit Colsch
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 Translational Medicine is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). 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.

Keywords

Metabolomics
Small molecules
Mass spectrometry
NMR
Personalized medicine
Biomarker discovery and validation

Published Papers (4 papers)

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Research

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16 pages, 2803 KiB

Open AccessArticle

A Multimodal Omics Exploration of the Motor and Non-Motor Symptoms of Parkinson’s Disease

by François-Xavier Lejeune, Farid Ichou, Etienne Camenen, Benoit Colsch, Florence Mauger, Caroline Peltier, Ivan Moszer, Emmanuel Gilson, Morgane Pierre-Jean, Edith Le Floch, Victor Sabarly, Arthur Tenenhaus, Jean-François Deleuze, Claire Ewenczyk, Marie Vidailhet and Fanny Mochel

Int. J. Transl. Med. 2022, 2(1), 97-112; https://0-doi-org.brum.beds.ac.uk/10.3390/ijtm2010009 - 08 Mar 2022

Cited by 1 | Viewed by 2783

Abstract

Parkinson’s disease (PD) is the second most common neurodegenerative disease clinically characterized by classical motor symptoms and a range of associated non-motor symptoms. Due to the heterogeneity of symptoms and variability in patient prognosis, the discovery of blood biomarkers is of utmost importance to identify the biological mechanisms underlying the different clinical manifestations of PD, monitor its progression and develop personalized treatment strategies. Whereas studies often rely on motor symptoms alone or composite scores, our study focused on finding relevant molecular markers associated with three clinical models describing either motor, cognitive or emotional symptoms. An integrative multiblock approach was performed using regularized generalized canonical correlation analysis to determine specific associations between lipidomics, transcriptomics and clinical data in 48 PD patients. We identified omics signatures confirming that clinical manifestations of PD in our cohort could be classified according to motor, cognition or emotion models. We found that immune-related genes and triglycerides were well-correlated with motor variables, while cognitive variables were linked to triglycerides as well as genes involved in neuronal growth, synaptic plasticity and mitochondrial fatty acid oxidation. Furthermore, emotion variables were associated with phosphatidylcholines, cholesteryl esters and genes related to endoplasmic reticulum stress and cell regulation. Full article

(This article belongs to the Special Issue Biomarker Discovery in Medical and Health Contexts Using Metabolomics)

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19 pages, 4227 KiB

Open AccessArticle

Serum Metabolic Profiling Identifies Key Differences between Patients with Single-Ventricle Heart Disease and Healthy Controls

by Julie Pires da Silva, Ashley E. Pietra, Angela N. Baybayon-Grandgeorge and Anastacia M. Garcia

Int. J. Transl. Med. 2022, 2(1), 78-96; https://0-doi-org.brum.beds.ac.uk/10.3390/ijtm2010008 - 23 Feb 2022

Viewed by 2560

Abstract

There are growing numbers of infants and children living with single-ventricle congenital heart disease (SV). However, cardiac dysfunction and, ultimately, heart failure (HF) are common in the SV population and the ability to predict the progression to HF in SV patients has been limited, primarily due to an incomplete understanding of the disease pathogenesis. Here, we tested the hypothesis that non-invasive circulating metabolomic profiles can serve as novel biomarkers in the SV population. We performed systematic metabolomic and pathway analyses on a subset of pediatric SV non-failing (SVNF) and failing (SVHF) serum samples, compared with samples from biventricular non-failing (BVNF) controls. We determined that serum metabolite panels were sufficient to discriminate SVHF subjects from BVNF subjects, as well as SVHF subjects from SVNF subjects. Many of the identified significantly dysregulated metabolites were amino acids, energetic intermediates and nucleotides. Specifically, we identified pyruvate, palmitoylcarnitine, 2-oxoglutarate and GTP as promising circulating biomarkers that could be used for SV risk stratification, monitoring response to therapy and even as novel targets of therapeutic intervention in a population with few other options. Full article

(This article belongs to the Special Issue Biomarker Discovery in Medical and Health Contexts Using Metabolomics)

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22 pages, 4185 KiB

Open AccessArticle

The Action of Recombinant Human Lysosomal α-Glucosidase (rhGAA) on Human Liver Glycogen: Pathway to Complete Degradation

by Allen K. Murray

Int. J. Transl. Med. 2021, 1(3), 381-402; https://doi.org/10.3390/ijtm1030023 - 14 Dec 2021

Cited by 1 | Viewed by 3204

Abstract

Glycogen is present in all tissues, but it is primarily stored in the liver and in muscle. As a branched chain carbohydrate, it is broken down by phosphorylase and debrancher enzymes, which are cytoplasmic. It is also degraded by a lysosomal α-glucosidase (GAA) also known as acid α-glucosidase and lysosomal acid α-glucosidase. The deficiency of GAA in patients is known as Pompe disease, and the phenotypes as infantile, juvenile and later onset forms. Pompe disease is treated by enzyme replacement therapy (ERT) with a recombinant form of rhGAA. Following ERT in Pompe mice and human patients there is residual carbohydrate material present in the cytoplasm of cells. The goal of this work is to improve ERT and attempt to identify and treat the residual cytoplasmic carbohydrate. Initial experiments were to determine if rhGAA can completely degrade glycogen. The enzyme cannot completely degrade glycogen. There is a residual glycosylated protein as well as a soluble glycosylated protein, which is a terminal degradation product of glycogen and as such serves as a biomarker for lysosomal glycogen degradation. The glycosylated protein has a very unusual carbohydrate composition for a glycosylated protein: m-inositol, s-inositol and sorbitol as the major carbohydrates, as well as mannitol, mannose, glucose and galactose. This work describes the residual material which likely contains the same protein as the soluble glycosylated protein. The biomarker is present in serum of control and Pompe patients on ERT, but it is not present in the serum of Pompe mice not on ERT. Pompe mice not on ERT have another glycosylated protein in their serum which may be a biomarker for Pompe disease. This protein has multiple glycosylation sites, each with different carbohydrate components. These glycosylated proteins as well as the complexity of glycogen structure are discussed, as well as future directions to try to improve the outcome of ERT for Pompe patients by being able to monitor the efficacy of ERT in the short term and possibly to adjust the timing and dose of enzyme infusions. Full article

(This article belongs to the Special Issue Biomarker Discovery in Medical and Health Contexts Using Metabolomics)

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Review

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18 pages, 1059 KiB

Open AccessReview

Biological Analyses-Derived Translational Findings in the T Cell Receptor Alpha Chain Knockout Mouse as an Experimental Model for Ulcerative Colitis

by Emiko Mizoguchi, Takayuki Sadanaga and Toshiyuki Okada

Int. J. Transl. Med. 2021, 1(3), 187-204; https://0-doi-org.brum.beds.ac.uk/10.3390/ijtm1030014 - 08 Nov 2021

Viewed by 2742

Abstract

Inflammatory bowel disease (IBD) is a group of chronic inflammatory disorders that affects many individuals throughout their lives. Ulcerative colitis (UC) and Crohn’s disease (CD) are two major forms of IBD. Until the early 1990s, a murine model of spontaneous chronic colitis was unavailable. As a major breakthrough in the basic research field of IBD, three genetically manipulated murine chronic colitis models, including interleukin (IL)-2 knockout (KO), IL-10 KO, and T cell receptor alpha chain (TCRα) KO models, were established in 1993. Since then, complicated immunobiological mechanisms during the development of UC have been gradually discovered by utilizing a wide variety of murine models of IBD, including the TCRα KO mouse model. In particular, it has been recognized that four major factors, including enteric, environmental, and immunological factors as well as enteric microbiota are highly and mutually involved in the pathogenesis of UC. As a pioneer of the TCRα KO murine model of UC, our group has identified that the interactions between the unique TCRα-β+ T cell population and antigen-presenting cells, including dendritic cells and B cells, play a key role for the development and regulation of UC-like chronic colitis, respectively. Here we have summarized clinically proven pathogenic and regulatory factors which have been identified by this novel TCRα KO murine model of UC in the past nearly three decades. Full article

(This article belongs to the Special Issue Biomarker Discovery in Medical and Health Contexts Using Metabolomics)

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