Cell Biology and Toxicology

, Volume 34, Issue 6, pp 421–423 | Cite as

Is the clinical lipidomics a potential goldmine?

  • Linlin Zhang
  • Xianlin HanEmail author
  • Xiangdong WangEmail author
Short Communication


Clinical lipidomics is a new extension of lipidomics to study lipid profiles, pathways, and networks by characterizing and quantifying the complete lipid molecules in cells, biopsy, or body fluids of patients. It undoubtfully has more values if lipidomics can be integrated with the data of clinical proteomic, genomic, and phenomic profiles. A number of challenges, e.g., instability, specificity, and sensitivity, in lipidomics have to be faced and overcome before clinical application. The association of lipidomics data with gene expression and sequencing of lipid-specific proteins/enzymes should be furthermore clarified. Therefore, clinical lipidomics is expected to be more stable during handling, sensitive in response to changes, specific for diseases, efficient in data analyses, and standardized in measurements, in order to meet clinical needs. Clinical lipidomics will become a more important approach in clinical applications and will be the part of “natural” measures for early diagnosis and progress of disease. Thus, clinical lipidomics will be one of the most powerful approaches for disease-specific diagnosis and therapy, once the mystery of lipidomic profiles and metabolic enzymes is deciphered.


Clinic lipidomics Biomarkers Diseases Metabolism enzymes 


  1. Han X. Lipidomics for studying metabolism. Nat Rev Endocrinol. 2016;12(11):668–79.CrossRefPubMedGoogle Scholar
  2. Kim WS, Jary E, Pickford R, He Y, Ahmed RM, Piguet O, et al. Lipidomics analysis of behavioral variant frontotemporal dementia: a scope for biomarker development. Front Neurol. 2018;28(9):104.CrossRefGoogle Scholar
  3. Lv J, Zhang L, Yan F, Wang X. Clinical lipidomics: a new way to diagnose human diseases. Clin Transl Med. 2018;7(1):12.CrossRefPubMedPubMedCentralGoogle Scholar
  4. Lv J, Gao D, Zhang Y, Wu D, Shen L, Wang X. Heterogeneity of lipidomic profiles among lung cancer subtypes of patients. J Cell Mol Med. 2018.
  5. Postle AD. Lipidomics. Curr Opin Clin Nutr Metab Care. 2012;15(2):127–33.PubMedGoogle Scholar
  6. Vaz FM, Pras-Raves M, Bootsma AH, van Kampen AH. Principles and practice of lipidomics. J Inherit Metab Dis. 2015;38(1):41–52.CrossRefPubMedGoogle Scholar
  7. Wang X. New biomarkers and therapeutics can be discovered during COPD-lung cancer transition. Cell Biol Toxicol. 2016;32(5):359–61.CrossRefPubMedGoogle Scholar
  8. Wang X. Clinical trans-omics: an integration of clinical phenomes with molecular multiomics. Cell Biol Toxicol. 2018;34(3):163–6.CrossRefPubMedGoogle Scholar
  9. Xu M, Wang X. Critical roles of mucin-1 in sensitivity of lung cancer cells to tumor necrosis factor-alpha and dexamethasone. Cell Biol Toxicol. 2017;33(4):361–71.CrossRefPubMedGoogle Scholar
  10. Yang K, Han X. Lipidomics: techniques, applications, and outcomes related to biomedical sciences. Trends Biochem Sci. 2016;41(11):954–69.CrossRefPubMedPubMedCentralGoogle Scholar
  11. Yang L, Li M, Shan Y, Shen S, Bai Y, Liu H. Recent advances in lipidomics for disease research. J Sep Sci. 2016;39(1):38–50.CrossRefPubMedGoogle Scholar
  12. Zhu Z, Qiu S, Shao K, Hou Y. Progress and challenges of sequencing and analyzing circulating tumor cells. Cell Biol Toxicol. 2017; 22.Google Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Zhongshan Hospital Institute of Clinical Science, Shanghai Institute of Clinical BioinformaticsFudan University Shanghai Medical SchoolShanghaiChina
  2. 2.Barshop Institute for Longevity and Aging Studies, Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, Department of Medicine, Division of Diabetes, Department of Biochemistry and Structural BiologyUniversity of Texas Health Science Center at San AntonioSan AntonioUSA

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