Clinical lipidomics: realizing the potential of lipid profiling

• Published in: Journal of lipid research Vol. 62; p. 100127
• Main Authors: Meikle, Thomas G., Huynh, Kevin, Giles, Corey, Meikle, Peter J.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.01.2021; American Society for Biochemistry and Molecular Biology; Elsevier
• Subjects: Alzheimer's disease; bioinformatics; biomarkers; cancer; cardiovascular disease; clinical lipidomics platform; clinical translation; diabetes; epidemiology; Humans; Lipid Metabolism; Lipidomics; Lipids - chemistry; Neoplasms - metabolism; risk assessment; Thematic Review Series; risk assessment; cardiovascular disease; QqTOF; clinical translation; biomarkers; LIPID MAPS; SRM; clinical lipidomics platform; epidemiology; PC; bioinformatics; LASSO; NIST; cancer; diabetes; Alzheimer's disease; ITSD; LIPID
• ISSN: 0022-2275; 1539-7262
• DOI: 10.1016/j.jlr.2021.100127

Dysregulation of lipid metabolism plays a major role in the etiology and sequelae of inflammatory disorders, cardiometabolic and neurological diseases, and several forms of cancer. Recent advances in lipidomic methodology allow comprehensive lipidomic profiling of clinically relevant biological samples, enabling researchers to associate lipid species and metabolic pathways with disease onset and progression. The resulting data serve not only to advance our fundamental knowledge of the underlying disease process but also to develop risk assessment models to assist in the diagnosis and management of disease. Currently, clinical applications of in-depth lipidomic profiling are largely limited to the use of research-based protocols in the analysis of population or clinical sample sets. However, we foresee the development of purpose-built clinical platforms designed for continuous operation and clinical integration—assisting health care providers with disease risk assessment, diagnosis, and monitoring. Herein, we review the current state of clinical lipidomics, including the use of research-based techniques and platforms in the analysis of clinical samples as well as assays already available to clinicians. With a primary focus on MS-based strategies, we examine instrumentation, analysis techniques, statistical models, prospective design of clinical platforms, and the possible pathways toward implementation of clinical lipidomics.