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Abstract Background Despite the identification of many hub lipids for stroke, the underlying pathophysiology of stroke in elderly patients with leukoaraiosis (LA) remains poorly understood, which is important for the administration of antithrombotic therapy for LA patients. This study aims to illuminate the preliminary lipid metabolic process associated with stroke in LA patients (LS). Methods The study cohort consisted of 215 individuals undergoing magnetic resonance imaging(MRI), from which a subset 13 patients with stroke matched with a control group, and 48 LS patients matched with 40 LA patients were selected for further investigation after exclusion. Serum lipidome was profiled by UPLC-TOF. OPLS-DA was used for classification and identifying differential metabolites. Customizing structural equation (CSE) model was applied to assess the pathway weight of novel metabolites in stroke incidence. Linear regression and matrix correlation were used to investigate the relationships between differentiated metabolites and outcomes. Results Using lipid profiling and multivariate statistical analysis, we screened 168 different compounds between LA and LS. Based on the enrichment and Sankey diagram of pathway, 52 lipid molecules were regarded as differential metabolites associated with glycerolipid, glycerophospholipid, and sphingolipid metabolism. After CSE weighted the pathway node molecules, we finally identified 11 key metabolites achieving a prediction, in which DG(14:0/22:4) (OR = 5.33) and Cer(d18:1/24:1) (OR = 21.44) were significant risk factors for LS. All 11 metabolites exhibited correlations with the outcome (LS incidence), with particularly heightened metabolic disruption in the presence of high blood pressure. We conducted linear regression analysis and found changes in FA16:1; O, DG(12:0/17:2) and DG(14:0/22:4) out of 11 metabolites correlated with Fazekas scores between CK and LS group. Similarly, compared with LA group, DG(14:0/22:4) (OR = 5.33, p = 0.02) and Cer(d18:1/24:1) (OR = 21.44, p = 0.068) are risk factors for LS. Especially, Cer(d18:1/24:1) and PI(22:1/20:1) were significantly associated with the LS incidence. Conclusion This study identified 11 metabolites as key metabolites for stroke incidence in LA patients, including subgroups divided by Fazekas scores. This study provides novel insights into lipid metabolic process from LA to LS, in which the lipid disturbance in glycolipids and glycerophospholipids, as well as the regulatory role of Cer(18:1/24:1), which are valuable for further studies of LS.
Feng et al. (Tue,) studied this question.