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Advances in Liquid Chromatography–Mass Spectrometry-Based Lipidomics: A Look Ahead

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Abstract

Lipidomics is a subfield of metabolic phenotyping that focuses on high-throughput profiling and quantification of lipids. Essential roles of lipidomics in translational and clinical research have emerged, especially over the past decade. Most lipidomic pipelines have been developed using mass spectrometry (MS)-based methods. Because of the complexity of the data, generally, computational demands are much higher in untargeted lipidomic studies. In the current paper, we primarily discussed the recent advances in untargeted liquid chromatography–mass spectrometry-based lipidomics, covering various facets from analytical strategies to functional interpretations. The current practice of tandem MS-based lipid annotation in untargeted lipidomics studies was demonstrated. Notably, we highlighted the essential characteristics of machine learning models, together with a data partitioning strategy, to facilitate appropriate modeling and validation in metabolic phenotyping studies. Critical aspects of data sharing were briefly mentioned. Finally, certain recommendations were suggested toward more standardized and sustainable lipidomics analysis strategies as independent platforms, and as members of the omics family.

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Acknowledgements

We thank Tran Diem Nghi for excellent technical support and manuscript revision. Figures were created using some materials provided by Biorender illustration. This work was supported by BK21 Plus Program of Korea in 2020.

Funding

This work was supported by the Bio-Synergy Research Project of the Ministry of Science, ICT and Future Planning through the National Research Foundation of Korea (NRF-2012M3A9C4048796).

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Authors and Affiliations

  1. College of Pharmacy, Seoul National University, Seoul, 08826, Republic of Korea

    Nguyen Phuoc Long, Nguyen Hoang Anh, Sun Jo Kim, Hyung Min Kim, Sang Jun Yoon & Sung Won Kwon

  2. Department of Statistics, Seoul National University, Seoul, 08826, Republic of Korea

    Seongoh Park & Johan Lim

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  1. Nguyen Phuoc Long
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Contributions

SWK and JL supervised the overall project. NPL mainly contributed to this work. SP contributed to the data treatment and modeling section. NHA and SJK participated in the data processing and preparation of tables and illustrations. SWK, HMK, and SJY contributed to the sections of analytical aspects and the section of perspectives. JL gave a consultation in the data treatment and modeling section. All authors read, critically revised, and accepted the final content of the manuscript.

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Correspondence to Sung Won Kwon.

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Long, N.P., Park, S., Anh, N.H. et al. Advances in Liquid Chromatography–Mass Spectrometry-Based Lipidomics: A Look Ahead. J. Anal. Test. 4, 183–197 (2020). https://doi.org/10.1007/s41664-020-00135-y

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