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Metabolites
Special Issues
Metabolomics for Clinical Biomarkers Discovery
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Metabolomics for Clinical Biomarkers Discovery

A Special Issue of Metabolites (ISSN 2218-1989) belonging to the section "Endocrinology and Clinical Metabolic Research".

Deadline for manuscript submissions: 30 April 2027 | Viewed by 1808

Editor

Dr. Cecília R.C. Calado

E-Mail Website
Guest Editor
Department of Chemical Engineering, ISEL-Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, 1959-007 Lisbon, Portugal
Interests: metabolomics; biomarkers discovery; drugs development
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Metabolomics can enable the discovery of abnormal metabolic patterns associated with pathological clinical processes by allowing for direct insight into a system’s functional metabolic outcomes; consequently, it can be used to discover and understand sub-classes of pathophysiological states. These patterns can lead to the discovery of new biomarkers, employed for clinical diagnosis, prognosis, monitoring disease progress and therapy, and measurements of pharmacodynamic and pharmacokinetics status, among others, improving medicinal precision and efficiency.

To further potentiate these discoveries, this Special Issue focuses on metabolomics applications enabling the sub-classification of the biological system towards the discovery of clinical biomarkers. The topics covered by this Special Issue will include advances in the following areas, among others:

  1. New metabolomic methodologies to capture the physiological state of the system.
  2. Metabolome perturbation according to pathophysiological states.
  3. Metabolome perturbation due to drugs, and other environmental variables.
  4. Clinical biomarker discovery based on metabolomics analysis.

Dr. Cecília R.C. Calado
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • metabolomics
  • biomarkers discovery
  • precision medicine

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

43 pages, 4839 KB  
Article
Serum Metabolomic Profiling in a Neonatal Piglet Model of Perinatal Asphyxia: A Pilot Study in Search of Candidate Biomarkers of Acute Hypoxic Injury and Early Post-Resuscitation Recovery
by Efstathia-Danai Bikouli, Paris Christodoulou, Rozeta Sokou, Eleftheria Karampela, Vasiliki Mougiou, Antigoni Cheilari, Konstantinos Tsiantas, Nikolaos S. Thomaidis, Nicoletta M. Iacovidou, Theodoros Xanthos and Panagiotis Zoumpoulakis
Metabolites 2026, 16(8), 554; https://doi.org/10.3390/metabo16080554 - 5 Aug 2026
Viewed by 489
Abstract
Background/Objectives: Perinatal asphyxia (PA) is a major cause of neonatal mortality and morbidity both in the short and in the long term. The identification of novel reliable biomarkers is essential in order to improve early diagnosis and allow for accurate prognostication of [...] Read more.
Background/Objectives: Perinatal asphyxia (PA) is a major cause of neonatal mortality and morbidity both in the short and in the long term. The identification of novel reliable biomarkers is essential in order to improve early diagnosis and allow for accurate prognostication of short- and long-term outcomes. The aim of the current study was to identify serum metabolites substantially affected by PA and resuscitation, using an experimental model in neonate piglets. Methods: A prospective, randomized experimental pilot animal study was conducted in 33 neonate Landrace/Large White female piglets, 1–4 days old. Following initial preparation and stabilization, the animals were allocated to three groups. Group A served as the control group while Group B and Group C piglets underwent asphyxia until severe bradycardia or hypotension occurred. Group C animals were subsequently resuscitated, and after return of spontaneous circulation (ROSC), they were stabilized and remained under further monitoring for 30 min. Blood samples for metabolic profiling were obtained at predefined timepoints as defined below. “Baseline” samples were taken from all animals after the initial stabilization; “asphyxia” sampling was performed at the time of hemodynamic compromise, while “final” sampling was performed 1 h after baseline in Group A animals and 30 min post-ROSC in Group C animals. The serum samples obtained were further analyzed using nuclear magnetic resonance (NMR) spectroscopy. Results: Distinct metabolic phenotypes were observed between the “baseline” state and asphyxia. Post-resuscitation and post-ROSC, the metabolic phenotype appeared to partially shift back to the “baseline” cluster but remained distinct from both of the other groups. The results were further processed using a structured biomarker discovery pipeline. Key metabolites that were found to significantly differentiate “baseline” and “asphyxia” states were lactate, succinate, lysine, fumarate, hypoxanthine and isoleucine (decrease) (p < 0.001). As far as the “baseline” against stabilization post-ROSC comparison is concerned, lactate, lysine, fumarate, hypoxanthine, succinate, acetate, alanine, glutamine, glutamate and choline differed significantly (p < 0.001). No metabolite survived False Discovery Rate correction and reached statistical significance in the direct “Asphyxia” versus “Resuscitation” comparison. Conclusions: This pilot study demonstrates that severe asphyxia in neonatal piglets is associated with a distinct serum metabolic signature, and several abnormalities remain detectable 30 min after ROSC, suggesting incomplete early metabolic recovery. The findings support the candidacy of lactate, succinate, fumarate, hypoxanthine and related metabolites for further assessment and validation as markers of acute hypoxic injury. Further investigation focused on these metabolites could also contribute to the elucidation of the involved pathophysiological mechanisms of PA and the development of novel therapeutic approaches. Full article
(This article belongs to the Special Issue Metabolomics for Clinical Biomarkers Discovery)
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29 pages, 21085 KB  
Article
Metabolomic Signatures of Biotrauma Associated with Mortality in ICU Patients Requiring Invasive Mechanical Ventilation and ECMO
by Tiago A. H. Fonseca, Cristiana P. Von Rekowski, Rúben Araújo, Gonçalo C. Justino, M. Conceição Oliveira, Luís Bento and Cecília R. C. Calado
Metabolites 2026, 16(7), 516; https://doi.org/10.3390/metabo16070516 - 22 Jul 2026
Viewed by 692
Abstract
Background: Biotrauma from invasive mechanical ventilation (IMV) and extracorporeal membrane oxygenation (ECMO) drives systemic inflammation, metabolic dysregulation, and organ dysfunction in critically ill patients. Therefore, this study aimed to identify clinical and metabolomic features associated with ICU mortality in patients receiving IMV [...] Read more.
Background: Biotrauma from invasive mechanical ventilation (IMV) and extracorporeal membrane oxygenation (ECMO) drives systemic inflammation, metabolic dysregulation, and organ dysfunction in critically ill patients. Therefore, this study aimed to identify clinical and metabolomic features associated with ICU mortality in patients receiving IMV or ECMO, as these remain incompletely characterized. Methods: The retrospective analysis included 30 ICU patients on IMV and 22 on ECMO. Metabolomic and proteomic profiling were performed using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS), and serum spectral analysis by Fourier-transform infrared spectroscopy (FTIRS). Significant variables were incorporated into multivariate logistic regression models, ranked by AIC, AUC, and statistical significance. Model performance was evaluated using stratified 5-fold cross-validation. Final models were adjusted for relevant demographic and clinical covariates. Results: The IMV cohort showed discriminatory FTIRS wavenumbers across all preprocessings, and 155 metabolites plus 14 proteins were significantly altered, with unadjusted models achieving mean AUCs above 0.9. The ECMO cohort showed discriminatory FTIRS wavenumbers in one preprocessing, and 15 metabolites plus 3 proteins were highlighted. FTIRS, metabolomic, and proteomic models reached mean AUCs of 0.967, 0.867, and 0.783, respectively, with lower stability during cross-validation. Adjustment for demographic and clinical covariates reduced model robustness. Conclusions: Stronger and more reproducible molecular signatures related to ICU mortality were observed in the IMV cohort, whereas the ECMO cohort showed reduced model stability, likely reflecting increased biological heterogeneity and small sample size. These findings support the utility of integrated omics for characterizing critical illness and outcome stratification, while reinforcing the need for validation in larger and independent cohorts. Full article
(This article belongs to the Special Issue Metabolomics for Clinical Biomarkers Discovery)
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