Chemical Stabilization and Retention-Predictive Modeling for Regiospecific Profiling of Labile Monoacylglycerols by UHPLC–HRMS

Abstract

Abstract Regiospecific analysis of monoacylglycerols (MAGs) remains challenging because of their low endogenous abundance, the limited availability of regioisomeric standards, and rapid acyl migration between the sn-1 and sn-2 positions during sample handling. Here, we report an UHPLC–HRMS platform integrating chemical stabilization with retention-time prediction for confident profiling of MAG regioisomers in biological samples. Derivatization with 4-pyridineboronic acid (4-PyBA) selectively forms cyclic boronate esters with the glycerol cis-diol moiety, thereby suppressing acyl migration, enhancing electrospray ionization efficiency, and generating characteristic diagnostic ions. To minimize reliance on authentic standards, a three-dimensional quantitative structure–retention relationship (3D-QSRR) model was developed to predict chromatographic retention across structurally diverse MAGs. In parallel, a homologous series of fatty acid 1,2-pentanediol monoesters was synthesized as retention calibrants to correct retention time (RT) drift and improve method robustness. These components were integrated into a targeted parallel reaction monitoring (PRM) workflow supported by an in-house database of 288 annotated sn-1 and sn-2 MAGs. Application of this strategy to serum, brain, colon, and fecal samples from APP/PS1 mice and to serum samples from individuals with Alzheimer’s disease (AD) enabled the confident annotation of 118 endogenous MAGs, including 68 MAGs not currently catalogued in major public databases. Collectively, this integrated platform improves structural confidence and analytical robustness and establishes a transferable framework for regioisomer-resolved analysis of labile glycerolipids.