Abstract 170: Deep Phenotyping of HDL Particles: Characterization of Seven HDL Species and Their Relationship to Cardiometabolic Phenotypes in a Multi-Ethnic Population (Dallas Heart Study)

Abstract

Background: Size-based HDL particle analysis based on small, medium, and large categories has led to inconsistent associations with cardiovascular disease (CVD). A new algorithm expands characterization of HDL-P from three to seven species, but the clinical significance remains unknown. We investigated the relationships between the seven HDL species and traditional risk factors, lipids, and cardiometabolic phenotypes in the Dallas Heart Study, a multiethnic, probability-based, population cohort of Dallas county adults. Methods: This study included 2,996 DHS participants (56% women, 50% Black), excluding those with prior CVD and statin users. HDL species were determined by nuclear magnetic resonance using the LP4 algorithm, with increasing size from H1P to H7P. Insulin resistance was determined by homeostatic model assessment index (HOMA-IR). Visceral fat was measured by MRI. Results: The largest HDL species were most directly associated with HDL cholesterol (HDL-C) (H6P: r = 0.61, p < 0.0001; H7P: r = 0.66, p < 0.0001). H2P was inversely associated with all HDL species including H1P (r = -0.19, p < 0.0001) and HDL-C (r = -0.18, p < 0.0001), but was directly associated with total cholesterol, triglycerides, and LDL-C (p < 0.0001). Female gender and Black ethnicity were associated with lower H2P levels (p < 0.0001). H2P alone was directly associated with diabetes, hypertension, waist circumference, insulin resistance, and visceral fat (Figure, p < 0.0001 for all values) Conclusion: Our study of a novel 7-species designation of HDL particles revealed that the smallest HDL particle species (H1P and H2P) confer differential associations with cardiometabolic phenotypes. These findings suggest further investigation specifically into the role of H2P and CVD.