Unraveling the Dyslipidemic Landscape in Moyamoya Disease: OxLDL as a Key Biomarker.

AIMS

The pathogenic mechanisms of moyamoya disease (MMD) remain unrecognized. Although genetic predisposition and hemodynamic changes have been focused on, emerging evidence suggests dyslipidemia may also contribute to MMD. Here, we performed a comprehensive analysis of lipid profiles, aiming to elucidate potential mechanisms in MMD.

METHODS

In this prospective case-control study, 222 MMD patients and 231 healthy controls (HCs) were enrolled. The comprehensive lipid profiling was performed, encompassing standard lipids, apolipoproteins, oxidized low-density lipoprotein (oxLDL), and small dense LDL (sdLDL). Statistical models of weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) were applied to capture individual and joint lipid effects on MMD risk.

RESULTS

Compared with HCs, MMD patients exhibited significantly higher oxLDL, sdLDL, and lipoprotein(a) (p < 0.05). OxLDL emerged as a robust independent risk factor for MMD (adjusted OR 1.146, 95% CI 1.102-1.210, p < 0.001). WQS analysis further identified oxLDL as the single greatest contributor to MMD risk, with additional support from BKMR showing marked synergistic interactions between oxLDL and homocysteine.

CONCLUSIONS

The study revealed a comprehensive dyslipidemic landscape in MMD, highlighting oxLDL as a pivotal biomarker. The results underscored the significance of lipid metabolism in MMD pathogenesis, warranting further investigation to guide novel diagnostic and therapeutic strategies.