Issue 18, 2022

Comprehensive two-dimensional gas chromatography with mass spectrometry: an advanced bioanalytical technique for clinical metabolomics studies

Abstract

The detection of human-derived metabolites as potential diagnostic biomarkers of genetic disorders, metabolic diseases, systemic diseases, and infectious diseases has been much studied in recent years, especially as technical capabilities improve, and statistical procedures are increasingly able to tease critical chemical attributes from complex data sets. Given the complex distribution of human biological matrices, the characterization and/or identification of these chemical entities is technically challenging, and is often confounded by incomplete chromatographic resolution or insufficient discriminatory power of the mass spectrometry (MS) domain. Recently, comprehensive two-dimensional gas chromatography (GC×GC) has evolved into a mature higher separation order technique that offers unprecedented resolving power, which in turn can greatly advantage clinical metabolomics studies via the expansion of metabolite coverage. In this contribution, the current state of knowledge in the development of GC×GC coupled to MS as a high-resolution bioanalytical technique for the analysis of clinical metabolites is reviewed. Selected recent applications (years 2012 to 2021) that emphasize improved GC×GC-MS strategies for clinical human metabolites’ detection, identification, and quantitative analysis are described. In addition, we share our perspectives on current challenges and potential future directions of GC×GC in clinical applications.

Graphical abstract: Comprehensive two-dimensional gas chromatography with mass spectrometry: an advanced bioanalytical technique for clinical metabolomics studies

Article information

Article type
Critical Review
Submitted
03 अप्रैल 2022
Accepted
27 जुलाई 2022
First published
28 जुलाई 2022

Analyst, 2022,147, 3974-3992

Comprehensive two-dimensional gas chromatography with mass spectrometry: an advanced bioanalytical technique for clinical metabolomics studies

A. Zaid, M. S. Khan, D. Yan, P. J. Marriott and Y. F. Wong, Analyst, 2022, 147, 3974 DOI: 10.1039/D2AN00584K

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