Accurate mass and retention time library of serum lipids for type 1 diabetes research
Dysregulated lipid species are linked to various disease pathologies and implicated as potential biomarkers for type 1 diabetes (T1D). However, it is challenging to comprehensively profile the blood specimen lipidome with full structural details of every lipid molecule. The commonly used reversed-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS)-based lipidomics approach is powerful for the separation of individual lipid species, but lipids belonging to different classes may still co-elute and result in ion suppression and misidentification of lipids. Using offline mixed-mode and RPLC-based two-dimensional separations coupled with MS/MS, a comprehensive lipidomic profiling was performed on human sera pooled from healthy and T1D subjects. The elution order of lipid molecular species on RPLC showed good correlations to the total number of carbons in fatty acyl chains and total number of double bonds. This observation together with fatty acyl methyl ester analysis was used to enhance the confidence of identified lipid species. The final T1D serum lipid library database contains 753 lipid molecular species with accurate mass and RPLC retention time uniquely annotated for each of the species. This comprehensive human serum lipid library can serve as a database for high-throughput RPLC-MS-based lipidomic analysis of blood samples related to T1D and other childhood diseases.
KeywordsHuman serum lipidome Type 1 diabetes Lipid profiling Mixed-mode LC RPLC-MS/MS Accurate mass and time tag
The work was partially supported by National Institutes of Health (NIH) grants R21 GM104678 and R01 DK114345. Clinical sample collection was supported by NIH grant R01 DK32493.
Compliance with ethical standards
This research analyzed de-identified human serum samples collected from clinical studies and has IRB approval as stated in the “Materials and methods” section. All authors have read and agreed to the final version of this manuscript.
Conflict of interest
The authors declare that they have no competing interests.
- 7.Sorensen CM, Ding J, Zhang Q, Alquier T, Zhao R, Mueller PW, et al. Perturbations in the lipid profile of individuals with newly diagnosed type 1 diabetes mellitus: lipidomics analysis of a Diabetes Antibody Standardization Program sample subset. Clin Biochem. 2010;43(12):948–56.CrossRefGoogle Scholar
- 11.Cajka T, Fiehn O. Increasing lipidomic coverage by selecting optimal mobile-phase modifiers in LC–MS of blood plasma. Metabolomics. 2016;12(2).Google Scholar
- 39.Nakagawa Y, Horrocks LA. Separation of alkenylacyl, alkylacyl, and diacyl analogues and their molecular species by high performance liquid chromatography. J Lipid Res. 1983;24(9):1268–75.Google Scholar