Comparing Data-Independent Acquisition and Parallel Reaction Monitoring in Their Abilities To Differentiate High-Density Lipoprotein Subclasses

• Published in: Journal of proteome research Vol. 19; no. 1; pp. 248 - 259
• Main Authors: Silva, Amanda R. M, Toyoshima, Marcos T. K, Passarelli, Marisa, Di Mascio, Paolo, Ronsein, Graziella E
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 03.01.2020
• Subjects: Adult; Aged; Calibration; Chromatography, High Pressure Liquid - methods; Humans; Limit of Detection; Lipoproteins, HDL - blood; Lipoproteins, HDL2 - blood; Lipoproteins, HDL3 - blood; Middle Aged; Proteomics - methods; Proteomics - statistics & numerical data; Quality Control; Tandem Mass Spectrometry - methods; Workflow; Young Adult; targeted proteomics; HDL; PRM; DIA
• ISSN: 1535-3893; 1535-3907
• DOI: 10.1021/acs.jproteome.9b00511

High-density lipoprotein (HDL) is a diverse group of particles with multiple cardioprotective functions. HDL proteome follows HDL particle complexity. Many proteins were described in HDL, but consistent quantification of HDL protein cargo is still a challenge. To address this issue, the aim of this work was to compare data-independent acquisition (DIA) and parallel reaction monitoring (PRM) methodologies in their abilities to differentiate HDL subclasses through their proteomes. To this end, we first evaluated the analytical performances of DIA and PRM using labeled peptides in pooled digested HDL as a biological matrix. Next, we compared the quantification capabilities of the two methodologies for 24 proteins found in HDL2 and HDL3 from 19 apparently healthy subjects. DIA and PRM exhibited comparable linearity, accuracy, and precision. Moreover, both methodologies worked equally well, differentiating HDL subclasses’ proteomes with high precision. Our findings may help to understand HDL functional diversity.