Rapid and simple lipidomic and metabolomic screening LC-HRMS-based methodology for serum samples of AMD patients

The increasing clinical relevance of lipidomics and metabolomics demands analytical methods that are not only sensitive and comprehensive but also rapid, reproducible, and operationally simple. Here, we present an integrated LC-HRMS-based workflow for the untargeted profiling of both lipids and (semi)polar metabolites from minimal serum volumes, specifically tailored for high-throughput clinical studies. The method combines a streamlined methanol:MTBE (1:1, v/v) extraction protocol with isotopically labeled internal standard normalization and a semi-automated Python-based script for data processing. The entire process—from extraction to data output—was completed in under 24 hours for 40 serum samples. Iterative MS/MS in dual polarity modes enabled the identification of close to 500 unique lipids spanning 23 lipid classes, alongside more than 500 metabolite features, facilitating integrated lipidomic-metabolomic analysis. Internal standard normalization improved reproducibility and analytical precision compared to conventional strategies, with 6% and 5% relative standard deviation in positive and negative ionization modes, respectively. Applied to serum from patients with age-related macular degeneration, the method revealed significant dysregulation of docosahexaenoic acid-rich triglycerides, sphingomyelins, and oxidized fatty acids. This workflow offers a robust and accessible platform for comprehensive serum lipidome and metabolome characterization in biomarker discovery and translational research.