Mass spectrometry-based metabolomics diagnostics – myth or reality?

ABSTACT

Introduction: Metabolomics, one of the most high-promising technologies, is the most recently developed post-genomics discipline for developing new diagnostic tests for future implementation in medicine. More than 2,000 scientific papers, using mass spectrometry-based (MS-based) metabolomics analysis for human disease diagnostics, have been published during the past two decades, and almost every metabolomics study shows high diagnostic accuracy. However, despite the great results and promising perspectives, there are currently no diagnostic tests based on metabolomics that have been approved and introduced into clinics.

Areas covered: In this report, the advantages and challenges of MS-based metabolomics are discussed with a focus on its developing role in diagnostics, and the current trends in implementing metabolomics diagnostics in the clinic.

Expert opinion: In the development of new clinical diagnostics tests, MS-based metabolomics has potential as both a preliminary discovery base for routine testing and a multi-test prototype, which is hoped to be introduced into clinical practice in the near future. A laboratory-developed test (LDT) is one possible way that multi-testing could be developed.

KEYWORDS:

• Diagnostics
• disease
• mass spectrometry
• metabolomics
• metabolites

Article highlights

• Metabolomics diagnostics is a promising field for the development of precise clinical tests.

• The advantages of MS-based metabolomic diagnostics are discussed with a focus on challenges to their implementation.

• To date, no diagnostic tests based on metabolomics have been approved or introduced into the clinic.

• No universal analytical platform for measuring the entire metabolome exists because of the wide range in concentration and diversity in physicochemical properties of metabolites.

• Protocols for standardizing the workflow of metabolomics research and general analysis approaches are required.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

The work was done in the framework of the Russian Federation fundamental research program for the long-term period for 2021-2030.