孟德尔随机化
医学
优势比
内科学
单核苷酸多态性
载脂蛋白B
内分泌学
胆固醇
PCSK9
载脂蛋白E
甘油三酯
脂蛋白
心脏病学
低密度脂蛋白受体
遗传学
生物
疾病
基因型
基因
遗传变异
作者
Elias Björnson,Martin Adiels,Marja‐Riitta Taskinen,Stephen Burgess,Aidin Rawshani,Jan Borén,Chris J. Packard
标识
DOI:10.1093/eurheartj/ehad337
摘要
Abstract Aims The strength of the relationship of triglyceride-rich lipoproteins (TRL) with risk of coronary heart disease (CHD) compared with low-density lipoprotein (LDL) is yet to be resolved. Methods and results Single-nucleotide polymorphisms (SNPs) associated with TRL/remnant cholesterol (TRL/remnant-C) and LDL cholesterol (LDL-C) were identified in the UK Biobank population. In a multivariable Mendelian randomization analysis, TRL/remnant-C was strongly and independently associated with CHD in a model adjusted for apolipoprotein B (apoB). Likewise, in a multivariable model, TRL/remnant-C and LDL-C also exhibited independent associations with CHD with odds ratios per 1 mmol/L higher cholesterol of 2.59 [95% confidence interval (CI): 1.99–3.36] and 1.37 [95% CI: 1.27–1.48], respectively. To examine the per-particle atherogenicity of TRL/remnants and LDL, SNPs were categorized into two clusters with differing effects on TRL/remnant-C and LDL-C. Cluster 1 contained SNPs in genes related to receptor-mediated lipoprotein removal that affected LDL-C more than TRL/remnant-C, whereas cluster 2 contained SNPs in genes related to lipolysis that had a much greater effect on TRL/remnant-C. The CHD odds ratio per standard deviation (Sd) higher apoB for cluster 2 (with the higher TRL/remnant to LDL ratio) was 1.76 (95% CI: 1.58–1.96), which was significantly greater than the CHD odds ratio per Sd higher apoB in cluster 1 [1.33 (95% CI: 1.26–1.40)]. A concordant result was obtained by using polygenic scores for each cluster to relate apoB to CHD risk. Conclusion Distinct SNP clusters appear to impact differentially on remnant particles and LDL. Our findings are consistent with TRL/remnants having a substantially greater atherogenicity per particle than LDL.
科研通智能强力驱动
Strongly Powered by AbleSci AI