Abstract
Cardiovascular diseases (CVDs) pose a significant global health threat, with familial hypercholesterolemia (FH) being a key genetic contributor. The apolipoprotein E (APOE) gene plays a vital role in lipid metabolism, and its variants are associated with CVD risk. This study explores prevalent APOE variants (p.R163C, p.R176C, p.R246C and p.V254E) using genetic and structural analyses. The research, initiated by identifying high-frequency APOE variants through the ABraOM database, utilizes homology modeling and molecular dynamics (MD) simulations to understand the structural consequences. The major lipid-binding region, a critical domain for lipid metabolism, was a focal point. Structural dynamics, including principal component analyses and domain movement analyses, highlighted distinct patterns in APOE variants compared to the wild type (WT). Results revealed significant differences in the structural behavior of variants, particularly in the Major lipid-binding region. The identification of an ‘elbow’ structure with two states (Elbow I and Elbow II) provided insights into conformational changes. Notably, variants exhibited unique patterns in hydrogen bonding (hb) and hydrophobic interactions, indicating potential functional consequences. The study further associated APOE variants with clinical outcomes, including cognitive impairment and cholesterol levels. Specific variants demonstrated correlations with cognitive decline and variations in lipid profiles, emphasizing their relevance to cardiovascular and neurobiological health. In conclusion, this integrated approach enhances our understanding of APOE variants, shedding light on their role in lipid metabolism and cardiovascular health. The identified structural ‘elbows’ and their association with clinical outcomes offer a nuanced perspective, guiding future research toward targeted interventions for diseases linked to lipid metabolism and neurobiology.
Communicated by Ramaswamy H. Sarma
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Acknowledgments
MHH and GMF are a recipient of a fellowship from FAPESP, Brazil. We acknowledge Desmond Molecular Dynamics System, version 6.4, D. E. Shaw Research, New York, NY for making this software available for academics.
Author contributions
F.L.P, R.B.M, M.H.H and G.M.F. design in silico experiments and analysis. F.L.P, R.B.M, M.H.H and G.M.F. helped with the discussion and writing. M.H.H and G.M.F contributed to resources and overall study supervision. All authors prepared and reviewed the manuscript.
Disclosure statement
The authors declare no competing interests.