Mathematical Model-Assisted UHPLC-MS/MS Method for Global Profiling and Quantification of Cholesteryl Esters in Hyperlipidemic Golden Hamsters

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Abstract
Cholesteryl esters (CEs) are formed by the 3-hydroxyl group of cholesterol and a fatty acyl chain through an ester bond, and function as a biologically inert storage form of cholesterol. Abnormal CE levels are often related to various diseases, particularly hyperlipidemia and atherosclerosis. Herein, we developed a mathematical model-assisted ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) method for the untargeted identification to targeted quantification of CEs in plasma, different density lipoprotein samples from humans, rats, and golden hamsters. Using UHPLC-quadrupole-time-of-flight mass spectrometry (UHPLC-QTOF-MS), 81 CE candidates were detected in the above samples, of which 24 CEs were reported in the Human Metabolome Database and 57 CEs were newly identified based on a created database of theoretically possible CEs, including the computationally generated precursor ion m/z mass, carbon number and double bond numbers of the fatty acyl chain. Then three mathematical models based on the characteristic chromatographic retention behavior related to structural features were established and validated using commercial and synthetic CE standards. The mathematical model-assisted UHPLC-MS/MS strategy was proposed to provide a global profile and identification of CEs, especially unknown CEs. With the new efficient strategy, 74 CEs in plasma of golden hamster were identified, and then quantified in normal and hyperlipidemic golden hamsters by dynamic multiple reaction monitoring (dMRM). 21 CEs among 35 shared potential biomarkers were newly found for hyperlipidemia. Our study will contribute to the in-depth study the functions of CEs and the discovery of biomarkers for diseases.
Funding Information
  • CAMS Innovation Fund for Medical Sciences (2018PT35002, 2016-I2M-3-010)
  • Drug Innovation Major Project of China (2018ZX09721002-001-004)

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