Metabolomics in Human Diseases and Health

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Advances in Metabolomics".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 1065

Special Issue Editors


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Guest Editor
Diabetes Center, First Department of Propaedeutic Internal Medicine, Laiko General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
Interests: diabetes; lipids; biomarkers; lipoproteins; obesity; microbiota; sepsis; antibiotics
Special Issues, Collections and Topics in MDPI journals

E-Mail
Guest Editor
Diabetes Center, First Department of Propaedeutic Internal Medicine, Medical School, National and Kapodistrian University of Athens, Laiko General Hospital, 11527 Athens, Greece
Interests: pharmacology; cardiac remodeling; cardiac regeneration; heart failure; sepsis; hypertension; atherogenesis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Metabolomics is a rapidly evolving field dedicated to the comprehensive identification and analysis of small molecules or metabolites present in various biological samples, including cells, tissues, and bodily fluids. Unlike other ‘omics’ technologies, metabolomics offers a direct reflection of the metabolic activity and status of cells and tissue, making it a promising tool for understanding molecular phenotypes. This field employs both untargeted and targeted approaches, with mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy being the primary analytical techniques. In the context of human health, metabolomics plays a pivotal role in identifying metabolic patterns associated with various diseases such as cancer, diabetes mellitus, cardiovascular diseases, and neurodegenerative disorders.

These unique signatures can serve as diagnostic markers, facilitating early disease detection, monitoring disease progression, and guiding personalized treatment strategies. Furthermore, metabolomics contributes to a deeper understanding of disease mechanisms, paving the way for the development of novel therapeutic interventions and precision-targeted treatments. It therefore holds significant potential for advancing our understanding of human diseases and improving patient care outcomes, offering valuable insights into diagnosis and prognosis.

The aim of this Special Issue, titled "Metabolomics in Human Diseases and Health", is to provide an in-depth overview of the field, focusing on the aspects mentioned above. We welcome original research and review articles that explore these themes and contribute to the advancement of metabolomics in human health.

Dr. Dimitris Kounatidis
Dr. Iordanis Mourouzis
Guest Editors

Manuscript Submission Information

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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

  • metabolomics
  • NAFLD
  • biomarkers
  • obesity
  • mass spectrometry
  • NMR spectroscopy
  • diabetes mellitus
  • cancer
  • cardiovascular diseases
  • neurodegenerative diseases

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Published Papers (1 paper)

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Research

19 pages, 1928 KiB  
Article
Automated Liquid Handling Extraction and Rapid Quantification of Underivatized Amino Acids and Tryptophan Metabolites from Human Serum and Plasma Using Dual-Column U(H)PLC-MRM-MS and Its Application to Prostate Cancer Study
by Tobias Kipura, Madlen Hotze, Alexa Hofer, Anna-Sophia Egger, Lea E. Timpen, Christiane A. Opitz, Paul A. Townsend, Lee A. Gethings, Kathrin Thedieck and Marcel Kwiatkowski
Metabolites 2024, 14(7), 370; https://doi.org/10.3390/metabo14070370 - 30 Jun 2024
Viewed by 831
Abstract
Amino acids (AAs) and their metabolites are important building blocks, energy sources, and signaling molecules associated with various pathological phenotypes. The quantification of AA and tryptophan (TRP) metabolites in human serum and plasma is therefore of great diagnostic interest. Therefore, robust, reproducible sample [...] Read more.
Amino acids (AAs) and their metabolites are important building blocks, energy sources, and signaling molecules associated with various pathological phenotypes. The quantification of AA and tryptophan (TRP) metabolites in human serum and plasma is therefore of great diagnostic interest. Therefore, robust, reproducible sample extraction and processing workflows as well as rapid, sensitive absolute quantification are required to identify candidate biomarkers and to improve screening methods. We developed a validated semi-automated robotic liquid extraction and processing workflow and a rapid method for absolute quantification of 20 free, underivatized AAs and six TRP metabolites using dual-column U(H)PLC-MRM-MS. The extraction and sample preparation workflow in a 96-well plate was optimized for robust, reproducible high sample throughput allowing for transfer of samples to the U(H)PLC autosampler directly without additional cleanup steps. The U(H)PLC-MRM-MS method, using a mixed-mode reversed-phase anion exchange column with formic acid and a high-strength silica reversed-phase column with difluoro-acetic acid as mobile phase additive, provided absolute quantification with nanomolar lower limits of quantification within 7.9 min. The semi-automated extraction workflow and dual-column U(H)PLC-MRM-MS method was applied to a human prostate cancer study and was shown to discriminate between treatment regimens and to identify metabolites responsible for discriminating between healthy controls and patients on active surveillance. Full article
(This article belongs to the Special Issue Metabolomics in Human Diseases and Health)
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