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Metabolites
Special Issues
Towards Clinical Interpretation of Metabolomic Data
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Towards Clinical Interpretation of Metabolomic Data

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Bioinformatics and Data Analysis".

Deadline for manuscript submissions: 20 May 2025 | Viewed by 2207

Special Issue Editor

Prof. Dr. Tomáš Adam

E-Mail Website
Guest Editor
Institute of Molecular and Translational Medicine (IMTM), Metabolomic Laboratory, Palacký University, CZ 779 00 Olomouc, Czech Republic
Interests: purine metabolism; inherited metabolic disorders; computation methods in metabolomics

Special Issue Information

Dear Colleagues,

Biochemical diagnosing of human diseases benefits historically from the analysis of and interpretation of metabolite levels in biofluids. They play key diagnostic roles in major diseases ranging from diabetes to a large group of individually rare inherited metabolic diseases. Clinical use of metabolic intermediate levels in biofluid is complicated by many factors known to the biochemist from sampling and metabolite stability up to the heterogeneity of clinical cohorts in biomarker studies. These issues hinder the widespread use of metabolomic data in clinical diagnosing. The volume of the data available for clinical interpretation by the current metabolomic analysis methods allows us to discover data analysis tools that can substantially help with this difficult task.

This Special Issue aims to address and solve the problems that hamper the widespread use of metabolomic data in clinical decisions. 

Prof. Dr. Tomáš Adam
Guest Editor

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

  • biochemistry
  • data mining
  • metabolism
  • biochemical interpretation
  • plasma
  • serum
  • urine
  • cerebrispinal fluid
  • biofluids
  • human
  • biochemistry
  • metabolomic
  • metabolic diseases
  • clinical diagnosis

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Published Papers (2 papers)

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25 pages, 1841 KiB  
Article
Cytokine-Based Insights into Bloodstream Infections and Bacterial Gram Typing in ICU COVID-19 Patients
by Rúben Araújo, Luís Ramalhete, Cristiana P. Von Rekowski, Tiago A. H. Fonseca, Cecília R. C. Calado and Luís Bento
Metabolites 2025, 15(3), 204; https://doi.org/10.3390/metabo15030204 - 16 Mar 2025
Viewed by 529
Abstract
Background: Timely and accurate identification of bloodstream infections (BSIs) in intensive care unit (ICU) patients remains a key challenge, particularly in COVID-19 settings, where immune dysregulation can obscure early clinical signs. Methods: Cytokine profiling was evaluated to discriminate between ICU patients with and [...] Read more.
Background: Timely and accurate identification of bloodstream infections (BSIs) in intensive care unit (ICU) patients remains a key challenge, particularly in COVID-19 settings, where immune dysregulation can obscure early clinical signs. Methods: Cytokine profiling was evaluated to discriminate between ICU patients with and without BSIs, and, among those with confirmed BSIs, to further stratify bacterial infections by Gram type. Serum samples from 45 ICU COVID-19 patients were analyzed using a 21-cytokine panel, with feature selection applied to identify candidate markers. Results: A machine learning workflow identified key features, achieving robust performance metrics with AUC values up to 0.97 for BSI classification and 0.98 for Gram typing. Conclusions: In contrast to traditional approaches that focus on individual cytokines or simple ratios, the present analysis employed programmatically generated ratios between pro-inflammatory and anti-inflammatory cytokines, refined through feature selection. Although further validation in larger and more diverse cohorts is warranted, these findings underscore the potential of advanced cytokine-based diagnostics to enhance precision medicine in infection management. Full article
(This article belongs to the Special Issue Towards Clinical Interpretation of Metabolomic Data)
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38 pages, 1117 KiB  
Systematic Review
The Current Applications of Metabolomics in Understanding Endometriosis: A Systematic Review
by Blake Collie, Jacopo Troisi, Martina Lombardi, Steven Symes and Sean Richards
Metabolites 2025, 15(1), 50; https://doi.org/10.3390/metabo15010050 - 14 Jan 2025
Cited by 2 | Viewed by 1131
Abstract
Endometriosis is a common gynecological disease that affects approximately 10–15% of reproductive-aged women worldwide. This debilitating disease has a negative impact on the quality of life of those affected. Despite this condition being very common, the pathogenesis is not well understood. Metabolomics is [...] Read more.
Endometriosis is a common gynecological disease that affects approximately 10–15% of reproductive-aged women worldwide. This debilitating disease has a negative impact on the quality of life of those affected. Despite this condition being very common, the pathogenesis is not well understood. Metabolomics is the study of the array of low-weight metabolites in a given sample. This emerging field of omics-based science has proved to be effective at furthering the understanding of endometriosis. In this systematic review, we seek to provide an overview of the application of metabolomics in endometriosis. We highlight the use of metabolomics in locating biomarkers for identification, understanding treatment mechanisms and symptoms, and relating external factors to endometriosis. The literature search took place in the Web of Science, Pubmed, and Google Scholar based on the keywords “metabolomics” AND “endometriosis” or “metabolome” AND “endometriosis”. We found 58 articles from 2012 to 2024 that met our search criteria. Significant alterations of lipids, amino acids, as well as other compounds were present in human and animal models. Discrepancies among studies of significantly altered metabolites make it difficult to make general conclusions on the metabolic signature of endometriosis. However, several individual metabolites were elevated in multiple studies of women with endometriosis; these include 3-hydroxybutyrate, lactate, phosphatidic acids, succinate, pyruvate, tetradecenoylcarnitine, hypoxanthine, and xanthine. Accordingly, L-isoleucine and citrate were reduced in multiple studies of women with endometriosis. Including larger cohorts, standardizing testing methods, and studying the individual phenotypes of endometriosis may lead to more separable results. Full article
(This article belongs to the Special Issue Towards Clinical Interpretation of Metabolomic Data)
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