LOW AND HIGH-DENSITY-LIPOPROTEIN METABOLISM IN ATHEROTHROMBOTIC BRAIN INFARCTION

Background and Purpose: Elevated low density lipoprotein and reduced high density lipoprotein cholesterol may increase the risk of atherothrombotic brain infarction, but the metabolic mechanisms accounting for this relation are poorly understood. Methods: The kinetic parameters of low density and high density lipoprotein were studied in nine subjects with atherothrombotic brain infarction or identifiable (by noninvasive testing) extracranial occlusive disease and in 12 control subjects. Autologous iodine-125-labeled lipoproteins were injected intravenously. Blood samples were drawn 10 minutes after injection and periodically thereafter for 10 days. Kinetic parameters were calculated from the decay curves. Results: The stroke-risk group showed significantly higher triglyceride (p<0.05), total cholesterol (p<0.02), and low density lipoprotein cholesterol (p<0.01). The fractional catabolic rate of low density lipoprotein was significantly lower (p<0.001) and the high density lipoprotein rate higher (p<0.02) in the stroke-risk group than in the control group. Regression analysis (using all subjects) of serum lipoproteins and their respective fractional catabolic rates correlated significantly (for low density lipoprotein, r=0.684, p<0.001; for high density lipoprotein, r=0.595, p<0.002). Mean percent stenosis showed a significant relation with triglyceride level (r=0.678, p<0.01) and low density lipoprotein cholesterol (r=0.535, p<0.02) but not with high density lipoprotein cholesterol. Mean percent stenosis also showed correlation with both fractional catabolic rate of low density lipoprotein (r=0.667, p<0.002) and with serum high density lipoprotein levels (r=0.504, p<0.02). Conclusions: Our study provides insights into the role of altered low and high density lipoprotein metabolism in the pathogenesis of carotid stenosis. The statistically significant association of serum lipoprotein metabolic rates with carotid stenosis, rather than their respective serum concentrations, implies that metabolic parameters may be more important in predicting stroke risk.