Many lipid biomarkers of stroke have been identified, but the lipid metabolism in elderly patients with leukoaraiosis remains poorly understood. This study aims to explore lipid metabolic processes in stroke among leukoaraiosis patients, which could provide valuable insights for guiding future antithrombotic therapy. In a cohort of 215 individuals undergoing MRI, 13 stroke patients were matched with controls, and 48 stroke patients with leukoaraiosis were matched with 40 leukoaraiosis patients. Serum lipidomics was profiled using UPLC-TOF, and OPLS-DA was applied for metabolite identification. Partial Least Squares Path Model (PLS-PM) assessed pathway weights of novel metabolites in stroke risk, while linear regression explored correlations with clinical outcomes. Lipid profiling identified 168 distinct compounds. From these, 25 lipid molecules were associated with glycerolipid, glycerophospholipid, and sphingolipid metabolism. PLS-PM identified 12 key metabolites, including DG 36:4 (OR = 6.40) as a significant risk factor. Metabolites such as PE 38:5 and FA 16:1;O showed significant correlations with stroke in leukoaraiosis, particularly when the Fazekas score was ≥ 4. Twelve metabolites were identified as key factors in stroke incidence among leukoaraiosis patients. Lipid disturbances in glycerolipids and glycerophospholipids provide valuable insights for further studies on the progression from leukoaraiosis to stroke.
Keywords: Leukoaraiosis; Lipidomics; Metabolic pathway; Plasma; Stroke.
© 2024. The Author(s).