Cardiovascular Efficacy of Lipid-Lowering Drug Targets Is Not Entirely Explained by Apolipoprotein B Reduction: Mendelian Randomization Evidence

Field: Medicine (Health Sciences)

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. Lipid-lowering therapies have proven efficacious for the primary and secondary prevention of CVD. Knowledge of causal biomarkers for CVD risk reduction is important for measuring efficacy when developing and evaluating novel therapies. Previous work has supported apolipoprotein B (ApoB) as a unifying biomarker to explain CVD risk reduction attributable to lipid-lowering therapies.1 Here, we sought to test this hypothesis using recently available genetic association data,2 as other genetic analyses have supported that lipoprotein lipase (LPL)-mediated lipolysis and low-density lipoprotein cholesterol (LDL-c)-lowering reduce coronary artery disease (CAD) risk through separate mechanisms.3 Genetic variants in the genes coding for lipid-lowering drug target proteins can be leveraged in the Mendelian randomization (MR) paradigm as instruments for studying the effects of perturbing that target pharmacologically. We used data from the most recent and largest published genome-wide association study of circulating lipids to compare the evidence for the causal biomarkers of CAD risk across distinct LDL-c lowering and LPL pathway targets. The data sources and study design are depicted in Figure. Only summary data were used in this work, and participant consent and ethical approval were obtained in the original studies. Genetic variants 100 kB above and below the genes (GRCh37/hg19 coordinates, as per Ensembl) for LDL-c lowering targets that have shown efficacy against CVD in phase 3 trials were considered: CETP (chr16:56,895,762-57,117,757), HMGCR (chr5:74,532,154-74,757,929), NPC1L1 (chr7:44,452,134-44,680,914), and PCSK9 (chr1:55,405,221-55,630,525). Instruments were selected as single-nucleotide polymorphisms that associate with LDL-c levels at genome-wide significance (P<5×10−8) after pruning to pairwise linkage disequilibrium r2<0.1 using the 1000G European reference panel. The same approach was taken for targets related to the LPL pathway, but considering circulating triglyceride levels to select genetic instruments instead of LDL-c: ANGPTL4 (chr19:8,428,173-8,439,257), APOC3 (chr11:116,600,422-116,803,788), and LPL (chr8:19,759,228-19,824,769). The ACLY and ANGPTL3 genes were not considered, because their common variants do not have established and reproducible MR associations with CVD risk. Random-effects inverse-variance weighted MR was performed to investigate the effect of lowering the corresponding lipid trait through each target on CAD risk separately, and when pooling the targets related to each respective mechanism (LDL-c lowering and LPL pathway) together. To investigate whether the MR association of these targets could be explained by ApoB lowering, all MR analyses were scaled to the association of the genetic variants with ApoB reduction. This means that MR associations for CAD risk are provided per SD reduction in ApoB. Evidence of heterogeneity between estimates for different targets was ascertained by a Cochran’s Q test P<0.05.