Toward large-scale mass spectrometry-based omics for clinical applications

Area of Science:

• Biochemistry
• Clinical Research
• Personalized Medicine

Background:

• Mass spectrometry (MS) enables direct analysis of functional molecules like proteins, lipids, and metabolites.
• These analyses provide crucial insights into cellular biology, healthy states, and disease pathogenesis.
• Healthcare is transitioning from nucleic acid-based research to downstream molecular effector analysis.

Purpose of the Study:

• To review recent advancements in MS-based proteomics, lipidomics, and metabolomics for clinical practice.
• To highlight how technological improvements enhance the accessibility of large-scale clinical studies.
• To emphasize the potential of multi-omic data integration in clinical research.

Main Methods:

• Review of recent advancements in mass spectrometry methodology and technology.
• Focus on improvements in sample preparation and automation.
• Examination of multi-omics data integration techniques, including unsupervised methods.

Main Results:

• MS-based approaches offer direct analysis of functional molecules, yielding critical clinical information.
• Proteomics, lipidomics, and metabolomics provide complementary insights into biological states.
• Unsupervised integration of multi-omic data reveals complex biological processes.

Conclusions:

• Advancements in MS technology are making clinical proteomics, lipidomics, and metabolomics more accessible.
• Integrated multi-omic data analysis holds significant promise for advancing clinical research and personalized medicine.
• The field is poised to drive significant improvements in healthcare applications.