Quantitative Profiling Method for Oxylipins in Neurodegenerative Diseases by Liquid Chromatography Coupled with Tandem Mass Spectrometry

Abstract

Aging is one of the major risk factors for many chronic diseases, including diabetes, neuropathy, hypertension, cancer, and neurodegenerative diseases. However, the mechanism behind aging and how aging affects a variety of disease progression remains unknown. Recent research demonstrated the cytochrome P450 (CYP)-epoxide hydrolase (EH) metabolites of polyunsaturated fatty acids (PUFAs) play a critical role in the abovementioned age-associated diseases. Therefore, aging could affect the abovementioned chronic diseases by modulating CYP-EH PUFA metabolism. Unfortunately, investigating how aging affects CYP-EH metabolism in human and mammalian models poses significant challenges.In this regard, we will useC. elegansas a model organism to investigate the aging effects on CYP-EH metabolism of PUFA, owing to its long history of being used to study aging and its associated benefits of conducting aging research. This project will develop analytical tools to measure the endogenous levels of CYP-EH PUFA metabolites inC. elegansusing state-of-the-art ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). These metabolites are very potent but present in low abundance. The dramatic increase in sensitivity in UPLC-MS/MS allows us to monitor these metabolites over the lifespan of C.eleganswith minimum samples. Our results show thatC. elegansproduces similar CYP PUFA metabolites to mammals and humans using our SPE-UPLC-MS/MS method. We will also show that our method successfully determined the CYP-EH PUFA metabolites profile changes induced by the inhibition ofC. elegansEH. The method developed from this project will significantly improve our understanding of the role of dietary PUFAs and associated metabolism on aging and neurodegeneration and will uncover new mechanisms of how aging affects neurodegeneration through the modulation of PUFA metabolic pathways.Graphical abstract