Innovation and Development in NMR-Based Metabolomics for Disease Diagnostics

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Metabolomic Profiling Technology".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 2210

Special Issue Editors


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Guest Editor
National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London W120NN, UK
Interests: NMR/HR-MAS; metabolomics; bioanalytical chemistry; chemometrics; chem- bio-informatics software development

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Guest Editor
Department of Biological Applications and Technology, University of Ioannina, 45110 Ioannina, Greece
Interests: NMR spectroscopy; metabolomics; biophysical chemistry; structural biology; phytochemistry

Special Issue Information

Dear Colleagues,

Metabolomics field embodies a significant share of omics sciences, aiming at the chemical characterization of complex biological matrices through bioanalytical platforms such as nuclear magnetic resonance (NMR). Over the last few decades, both solution and high-resolution magic angle spinning (HR-MAS) NMR technologies have proven to be valuable for the detection as well as quantitation of various chemical entities (i.e., biomarkers) in biofluids, tissues, cells, etc., towards the prognosis and/or diagnosis of several diseases. The simplicity of NMR samples’ preparation, including its non-destructive nature as well as the impeccable reproducibility of NMR data, allow for the detection of unique signatures from pathological conditions, turning the whole NMR profile into a collective biomarker. The successful application of both targeted and untargeted NMR-based metabolomics in biomedicine is the consequence of the continuous advancements in NMR technology/methods/bioinformatics tools, which led to fully automated high-throughput analyses and data interpretation.

This Special Issue will highlight the recent developments in both experimental and computational methods of NMR/HR-MAS technologies in metabolomics combined with their application/validation on real-world samples from pathological conditions. In general, the present Special Issue is designed to cover all NMR/HR-MAS novel strategies (i.e., both experimental and computational methods/tools) for metabolomics studies, aiming at the detection of novel biomarkers for disease diagnosis and/or prognosis. The exploration of any disease metabolic profile via NMR-based approaches will also be considered. Submissions of original research as well as perspective articles are welcome.

Dr. Panteleimon Takis
Dr. Anastassios Troganis
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. Metabolites is an international peer-reviewed open access monthly 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 2700 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

  • NMR/HR-MAS
  • metabolomics
  • bioinformatics
  • cheminformatics
  • chemometrics
  • biomarkers
  • biofluids
  • tissues
  • diagnostics

Published Papers (1 paper)

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Research

14 pages, 1158 KiB  
Article
Blood-Derived Metabolic Signatures as Biomarkers of Injury Severity in Traumatic Brain Injury: A Pilot Study
by Elani A. Bykowski, Jamie N. Petersson, Sean P. Dukelow, Chester Ho, Chantel T. Debert, Tony Montina and Gerlinde A. S. Metz
Metabolites 2024, 14(2), 105; https://doi.org/10.3390/metabo14020105 - 2 Feb 2024
Viewed by 1437
Abstract
Metabolomic biomarkers hold promise in aiding the diagnosis and prognostication of traumatic brain injury. In Canada, over 165,000 individuals annually suffer from a traumatic brain injury (TBI), making it one of the most prevalent neurological conditions. In this pilot investigation, we examined blood-derived [...] Read more.
Metabolomic biomarkers hold promise in aiding the diagnosis and prognostication of traumatic brain injury. In Canada, over 165,000 individuals annually suffer from a traumatic brain injury (TBI), making it one of the most prevalent neurological conditions. In this pilot investigation, we examined blood-derived biomarkers as proxy measures that can provide an objective approach to TBI diagnosis and monitoring. Using a 1H nuclear magnetic resonance (NMR)-based quantitative metabolic profiling approach, this study determined whether (1) blood-derived metabolites change during recovery in male participants with mild to severe TBI; (2) biological pathway analysis reflects mechanisms that mediate neural damage/repair throughout TBI recovery; and (3) changes in metabolites correlate to initial injury severity. Eight male participants with mild to severe TBI (with intracranial lesions) provided morning blood samples within 1–4 days and again 6 months post-TBI. Following NMR analysis, the samples were subjected to multivariate statistical and machine learning-based analyses. Statistical modelling displayed metabolic changes during recovery through group separation, and eight significant metabolic pathways were affected by TBI. Metabolic changes were correlated to injury severity. L-alanine (R= −0.63, p < 0.01) displayed a negative relationship with the Glasgow Coma Scale. This study provides pilot data to support the feasibility of using blood-derived metabolites to better understand changes in biochemistry following TBI. Full article
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