Rapid lipidomic profiling based on ultra-high performance liquid chromatography–mass spectrometry and its application in diabetic retinopathy

• Published in: Analytical and bioanalytical chemistry Vol. 412; no. 15; pp. 3585 - 3594
• Main Authors: Xuan, Qiuhui, Zheng, Fujian, Yu, Di, Ouyang, Yang, Zhao, Xinjie, Hu, Chunxiu, Xu, Guowang
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2020; Springer; Springer Nature B.V
• Subjects: Analytical Chemistry; Biochemistry; Biological properties; Biological samples; Biology; blood lipids; blood serum; Characterization and Evaluation of Materials; Chemistry; Chemistry and Materials Science; Chromatography; Chromatography, High Pressure Liquid - economics; Chromatography, High Pressure Liquid - methods; Current Progress in Lipidomics; Data acquisition; data collection; Diabetes; Diabetes mellitus; Diabetic retinopathy; Diabetic Retinopathy - blood; Elution; Female; Food Science; High performance liquid chromatography; Humans; Laboratory Medicine; Limit of Detection; Linearity; lipidomics; Lipidomics - economics; Lipidomics - methods; Lipids; Lipids - analysis; Lipids - blood; Liquid chromatography; Male; Mass spectra; Mass spectrometry; Mass Spectrometry - economics; Mass Spectrometry - methods; Mass spectroscopy; Medical research; Medicine, Experimental; Middle Aged; Monitoring/Environmental Analysis; Precision medicine; rapid methods; Research Paper; Retinopathy; Risk analysis; Risk factors; Scientific imaging; Spectroscopy; Stability analysis; Time Factors; Canada; China; Diabetic retinopathy; Liquid chromatography–mass spectrometry; Lipidomic profiling; Lipidome; Differential lipids
• ISSN: 1618-2642; 1618-2650; 1618-2650
• DOI: 10.1007/s00216-020-02632-6

Lipidomics aims to characterize lipid alteration in response to internal or external subtle perturbations in complex biological samples. Lipid abnormality is a major risk factor for many diseases. Large-scale lipidomic studies may offer new insights into the pathophysiological mechanisms of diseases, new opportunities in systems biology, functional biology, and personalized medicine. To this end, a highly efficient and stable lipidomic method is highly in demand. We herein present a rapid and relatively high coverage lipidomic profiling approach based on ultra-high performance liquid chromatography–mass spectrometry by comparing the performance of different chromatographic columns, optimizing the elution gradient and selecting an appropriate data acquisition mode of mass spectra. As a result, a total of 481 lipids were detected from 40 μL serum sample within 13 min, covering 20 common lipid (sub)classes. The developed method was well validated with satisfactory analytical characteristics in linearity, repeatability, stability, and lipid coverage. To show the usefulness, the method was employed to investigate serum lipid profiling of 43 subjects with mild diabetic retinopathy and 44 normal controls, and successfully defined the differential lipids related to diabetic retinopathy. We believe that this rapid method will be beneficial for lipidomic analysis of large-scale clinical samples.