Lipidomics of human adipose tissue reveals diversity between body areas

PLoS One. 2020 Jun 16;15(6):e0228521. doi: 10.1371/journal.pone.0228521. eCollection 2020.

Abstract

Background and aims: Adipose tissue plays a pivotal role in storing excess fat and its composition reflects the history of person's lifestyle and metabolic health. Broad profiling of lipids with mass spectrometry has potential for uncovering new knowledge on the pathology of obesity, metabolic syndrome, diabetes and other related conditions. Here, we developed a lipidomic method for analyzing human subcutaneous adipose biopsies. We applied the method to four body areas to understand the differences in lipid composition between these areas.

Materials and methods: Adipose tissue biopsies from 10 participants were analyzed using ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. The sample preparation optimization included the optimization of the lipid extraction, the sample amount and the sample dilution factor to detect lipids in an appropriate concentration range. Lipidomic analyses were performed for adipose tissue collected from the abdomen, breast, thigh and lower back. Differences in lipid levels between tissues were visualized with heatmaps.

Results: Lipidomic analysis on human adipose biopsies lead to the identification of 186lipids in 2 mg of sample. Technical variation of the lipid-class specific internal standards were below 5%, thus indicating acceptable repeatability. Triacylglycerols were highly represented in the adipose tissue samples, and lipids from 13 lipid classes were identified. Long polyunsaturated triacylglycerols in higher levels in thigh (q<0.05), when compared with the abdomen, breast and lower back, indicating that the lipidome was area-specific.

Conclusion: The method presented here is suitable for the analysis of lipid profiles in 2 mg of adipose tissue. The amount of fat across the body is important for health but we argue that also the distribution and the particular profile of the lipidome may be relevant for metabolic outcomes. We suggest that the method presented in this paper could be useful for detecting such aberrations.

MeSH terms

  • Adipose Tissue / metabolism*
  • Adipose Tissue / pathology
  • Biopsy
  • Humans
  • Lipidomics*
  • Organ Specificity

Grants and funding

The authors received no specific funding for this work. The work was carried out at and paid by Steno Diabetes Center Copenhagen. Capio CFR provided sample material but did not provide funding. Biosyntia ApS did not provide funding and was not involved in the study at the time of carrying out the study. Apart from Trine Foged Henriksen, all authors were employees of Steno Diabetes Center Copenhagen at the time of carrying out the study. Capio CFR and Biosyntia ApS did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.