The Association Between apolipoprotein B and Risk of Cardiovascular Disease：Mendelian randomization analysis

Abstract Background: The threat of cardiovascular disease looms large across the globe and poses a significant risk to people's lives. One of the primary culprits causing this ailment is circulating lipoprotein lipids, and LDL is among the main contributors to atherosclerosis, a concerning condition. Recent studies have shown that lipoproteins are better predictors of arteriosclerosis risk than LDL and non-LDL cholesterol. To regulate cholesterol and lipid metabolism transmission, apolipoprotein B (apoB) plays a crucial role. Although apoB has been linked to CVDs in some studies, we need further research to understand the precise nature of this relationship. In this research, we utilized genetic apoB tools through two-sample Mendelian randomization to examine its causal role in the etiology of CVDs. Methods: The UK Biobank genome-wide association study (GWAS) of European populations has provided data on apolipoprotein B (n = 439,214), which has been used to identify single nucleotide polymorphisms (SNPs) associated with lipid levels. Large GWAS datasets have also been used to collect data on several cardiovascular diseases (CVD) in European populations. These include aortic aneurysm (AA) (n = 209,366), coronary heart disease (CHD) (n = 141,217), heart failure (HF) (n = 977,323), ischaemic stroke (IS) (n = 440,328), peripheral artery disease (PAD) (n = 213,639), and venous thromboembolism (VTE) (n = 218,792). This study used two-sample Mendelian randomisation (MR) analysis to determine the association between apoB and CVDs. Primary analysis method was IVW with 95% confidence intervals (CI) for odds ratios (OR). Other analysis methods such as MR-Egger, weighted median, simple mode and weighted mode were also used, as well as sensitivity analyses such as the Cochran Q test, the Egger intercept test and the leave-one-out analysis. Genetic engineering of the PCSK9 region was used to simulate the inhibitory effect of PCSK9 inhibitors on apoB. Results: The mean value for apoB was 1.03 (0.24) g/L. The GWAS identified multiple independent single nucleotide polymorphisms (SNPs) associated with apoB (n = 255) at P < 5×10− 8. Strong instrumental variables(IVs) were chosen with calculated F value greater than 10, thus selecting 183 SNPs. Our two-sample MR analysis, primarily using IVW, identified a causal association between apoB and several diseases, such as AA (OR = 1.34, 95%CI: 1.10–1.62; P < 0.05), CHD (OR = 1.69, 95%CI: 1.52–1.88, P < 0.001), HF (OR = 1.13, 95%CI: 1.04–1.23, P < 0.05), IS (OR = 1.13, 95%CI: 1.04–1.23, P < 0.05), and PAD (OR = 1.41, 95%CI: 1.21–1.62, P < 0.001), but with no effect on VTE (OR = 1.04, 95%CI: 0.90–1.21; P = 0.59). Moreover, a significant association was observed between the increase of apoB in the PCSK9 region and an increased risk of developing CHD (OR = 2.13, 95%CI: 1.66–2.74, P < 0.05) and HF (OR = 1.24, 95%CI: 1.02–1.51, P < 0.05). Conclusion: According to the research, elevated levels of apoB are associated with an increased risk of AA, CHD, HF, IS and PAD. Furthermore, there is no link between VTE and causality. PCSK9 inhibitor medications may reduce the risk of CHD and HF solely due to their impact on apoB loading.