Considerations for mass spectrometry-based multi-omic analysis of clinical samples

ABSTRACT

Introduction: The role of mass spectrometry in biomolecule analysis has become paramount over the last several decades ranging in the analysis across model systems and human specimens. Accordingly, the presence of mass spectrometers in clinical laboratories has also expanded alongside the number of researchers investigating the protein, lipid, and metabolite composition of an array of biospecimens. With this increase in the number of omic investigations, it is important to consider the entire experimental strategy from sample collection and storage, data collection and analysis.

Areas covered: In this short review, we outline considerations for working with clinical (e.g. human) specimens including blood, urine, and cerebrospinal fluid, with emphasis on sample handling, profiling composition, targeted measurements and relevance to disease. Discussions of integrated genomic or transcriptomic datasets are not included. A brief commentary is also provided regarding new technologies with clinical relevance.

Expert opinion: The role of mass spectrometry to investigate clinically related specimens is on the rise and the ability to integrate multiple omics datasets from mass spectrometry measurements will be crucial to further understanding human health and disease.

KEYWORDS:

• Mass spectrometry
• clinical

Article Highlights

• Incorporating mass spectrometry measurements in clinical research is becoming more common.

• The integration of different 'omic strategies can provide important insight into health and disease.

• Targeted and discovery experimental schemes are critical for multi-omics.

• Researchers should consider the entire experimental strategy for multi-omic studies from sample collection, processing to data processing.

• Future efforts are needed for more advanced analysis tools of such datasets.

Acknowledgments

We would like to thank Koralege C. Pathmasiri for critical insight.

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

This paper was funded by the Together Strong-NPC Foundation and the University of Illinois at Chicago.