Trends In Volatile Organic Compound-based Metabolomics For Biomarker Discovery

Abstract

Metabolomics studies are important to understand biological systems, and serve as a promising tool for disease diagnosis, and biomarker discovery. Volatile organic compounds (VOCs) provide a rich source of information about the body's overall health and can indicate disease onset and progression. However, sample collection, preparation, and preconcentration techniques pose some challenges to obtaining accurate and reliable information. This review discusses the various biological sources of VOCs, recent advances in VOC sample collection, preparation, pre-concentration, as well as the analytical platforms used for VOC analysis. It also highlights the techniques used in real-time detection of VOCs. Studies presenting modern applications of VOCs as potential biomarkers of different diseases were collected and analyzed. In addition, this review detailed supervised and unsupervised machine learning tools employed in metabolomics such as principal component analysis (PCA), partial least squares (PLS) regression, partial least squares-discriminant analysis (PLS-DA), volcano plots, and hierarchical clustering. These tools have been used to determine relationships among two or more sample groups and variables, enabling biomarker discovery. To improve the reproducibility and reliability of the results, which is a major challenge facing metabolomics studies, this review further explored the existing quality assurance methods in sample collection and analysis. Finally, it presents future directions in VOC-based metabolomics.

Department(s)

Chemistry

Keywords and Phrases

Biomarker discovery; Metabolomics; Preconcentration; Sample preparation; Volatile organic compounds

International Standard Serial Number (ISSN)

0026-265X

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2025 Elsevier, All rights reserved.

Publication Date

01 Jun 2025

Link to Full Text

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