Causal link between coronary heart disease and lipidomics: A Mendelian randomization analysis

The study aims to employ the 2-Sample Mendelian Randomization (MR) and Multivariable MR (MVMR) approaches to investigate the associations between specific lipid profiles and the risk of coronary heart disease (CHD). This study analyzed a comprehensive genome-wide association studies dataset comprising 179 lipidomic traits to assess the associations between various molecular subclasses of lipid traits and the risk of CHD. Causal relationships were investigated using the two-sample Mendelian randomization method, with supplementary analyses, including sensitivity analyses and MVMR, further refining the results. Heterogeneity and horizontal pleiotropy were evaluated using Cochran Q, the MR-Egger intercept test, and MR-PRESSO. Additionally, a leave-one-out sensitivity analysis was conducted to assess the influence of individual single nucleotide polymorphisms on the robustness of MR estimates. By examining 179 lipidomic traits as exposures and CHD as the outcome, this study identified significant causal relationships between glycerophospholipids, sphingolipids, and glycerolipids, which were associated with an increased risk of CHD. Specifically, levels of 5 triacylglycerols (TAGs) - (50:4), (52:3), (52:4), (52:5), and (56:5) - along with 2 phosphatidylethanolamines (PEs), namely (16:0_20:4) and (18:0_20:4), and 1 phosphatidylcholine (PC), namely (O-16:2_18:0), across 3 lipid categories were associated with an increased risk of CHD. The results of this study suggest that increased levels of TAGs, PEs, and PCs are associated with an elevated risk of CHD, implying that these lipid molecules may play a critical role in the pathogenesis of CHD. Furthermore, this study further elucidates the complex lipid metabolic pathways in CHD, highlighting structural alterations in distinct lipidomes that may differentially influence molecular subtypes.