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Post hoc analyses of clinical trials show that PCSK9 inhibitors might lower lipoprotein(a), but whether this effect contributes to reductions in cardiovascular risk remains unknown. We aimed to assess whether genetically proxied PCSK9 inhibition influences lipoprotein(a) (Lp(a)), and whether any such effect could mediate its effects on coronary artery disease (CAD) and ischemic stroke (IS).To explore associations between the genetic proxies for PCSK9 inhibitors and Lp(a) levels, we used UK Biobank data (310,020 individuals). We identified 10 variants in the PCSK9 gene associated with lower PCSK9 and LDL-C levels as proxies for PCSK9 inhibition. We explored the effects of genetically proxied PCSK9 inhibition on Lp(a) levels, as well as on odds of CAD (60,801 cases, 184,305 controls) and IS (60,341 cases, 454,450 controls) in two-sample Mendelian randomization analyses. In mediation analyses, we assessed the effects of genetically proxied PCSK9 inhibition on CAD and IS mediated through reductions in Lp(a) levels.Genetically proxied PCSK9 inhibition (1-SD decrement in PCSK9 concentration; corresponding to 20.6 mg/dl decrement in LDL-C levels) was associated with a 4% decrease in log-Lp(a) levels (beta: -0.038, 95%CI: -0.053 to -0.023). We estimated a 0.8% reduction in the odds for CAD (OR: 0.992, 95%CI: 0.989-0.995) and a 0.5% reduction in the odds for atherosclerotic IS (OR: 0.995, 95%CI: 0.992-0.998) due to reductions in Lp(a) levels through genetically proxied PCSK9 inhibition, corresponding to 3.8% and 3.2% of the total effects, respectively.Genetic proxies for PCSK9 inhibition are associated with lower Lp(a) levels. However, Lp(a) lowering explains only a small proportion of the total effects of genetic proxies for PCSK9 inhibitors on risk of CAD and IS.

In 2022, the European Atherosclerosis Society (EAS) published a new consensus statement on lipoprotein(a) [Lp(a)], summarizing current knowledge about its causal association with atherosclerotic cardiovascular disease (ASCVD) and aortic stenosis. One of the novelties of this statement is a new risk calculator showing how Lp(a) influences lifetime risk for ASCVD and that global risk may be underestimated substantially in individuals with high or very high Lp(a) concentration. The statement also provides practical advice on how knowledge about Lp(a) concentration can be used to modulate risk factor management, given that specific and highly effective mRNA-targeted Lp(a)-lowering therapies are still in clinical development. This advice counters the attitude: "Why should I measure Lp(a) if I can't lower it?". Subsequent to publication, questions have arisen relating to how the recommendations of this statement impact everyday clinical practice and ASCVD management. This review addresses 30 of the most frequently asked questions about Lp(a) epidemiology, its contribution to cardiovascular risk, Lp(a) measurement, risk factor management and existing therapeutic options.

Funder: Monash University, Health economic analyses are essential for health services research, providing decision-makers and payers with evidence about the value of interventions relative to their opportunity cost. However, many health economic approaches are still limited, especially regarding the primary prevention of cardiovascular disease (CVD). In this article, we discuss some limitations to current health economic models and then outline an approach to address these via the incorporation of genomics into the design of health economic models for CVD. We propose that when a randomised clinical trial is not possible or practical, health economic models for primary prevention of CVD can be based on Mendelian randomisation analyses, a technique to assess causality in observational data. We discuss the advantages of this approach, such as integrating well-known disease biology into health economic models and how this may overcome current statistical approaches to assessing the benefits of interventions. We argue that this approach may provide the economic argument for integrating genomics into clinical practice and the efficient targeting of newer therapeutics, transforming our approach to the primary prevention of CVD, thereby moving from reactive to preventive healthcare. We end by discussing some limitations and potential pitfalls of this approach.

Clinical estimation of the combined effect of several risk factors is unreliable and this resulted in the development of a number of risk estimation systems to guide clinical practice. Here, after defining general principles of risk estimation, the authors describe the evolution of the European Society of Cardiology's (ESC) Systematic COronary Risk Evaluation (SCORE) risk estimation system and some learnings from the data. They move on to describe the establishment of the ESC's Cardiovascular Risk Collaboration and outline its proposed research directions. First among these is the evolution of SCORE 2, which provides updated, calibrated risk estimates for total cardiovascular events for low, moderate, high, and very high-risk regions of Europe. The authors conclude by considering that the future of risk estimation may be to express risk as years of exposure to a cardiovascular risk factor profile rather than risk over a fixed time period, such as 10 years, and how advances in genetics may permit individualized lifetime risk estimation from childhood on.

Background There are no studies that have specifically investigated the cost-effectiveness of cascade screening of children for heterozygous familial hypercholesterolemia (FH) and treatment of affected individuals with statins to prevent coronary heart disease (CHD). Purpose This study explores the cost-effectiveness of this strategy from the perspective of the Australian public healthcare system. Methods A lifetime Markov model with four health states (Alive without CHD, Alive with CHD, Dead from fatal CHD, and Dead from other causes) was developed to simulate the progression of ten- year-old children screened for FH and treated immediately with statins if found to have FH. The underlying prevalence of FH in this target population was assumed to be 56.8%, and the sensitivity and specificity of testing was 100%. The comparator was usual care, which assumed that subjects started statins spontaneously at a later point or when they experienced a cardiovascular event. The effect of reducing low-density lipoprotein cholesterol (LDL-C) on the risk of a first event at each age assumed that risk was proportional to total lifetime exposure and was implemented using Mendelian randomisation analysis data. Cost and other outcome data were sourced from published sources. Outcome of interests were costs in Australian dollars (AUD), life years gained (LYG) and quality-adjusted life years (QALYs) gained, as well as incremental cost-effectiveness ratios (ICERs) of costs per LYG and per QALY gained. All future costs and outcomes were discounted by 5% annually. Results Undiscounted results showed that compared with usual care, cascade screening of ten year-old children for FH and initiation of treatment of affected individuals saved 7.77 LYG and 7.53 QALYs per person over a lifetime. With 5% annual discounting, there were 0.97 LYG and 1.07 QALYs gained per person, at an additional cost of $3,244. These equated to ICERs of $3334 per LYG and $3023 per QALY gained. The equivalent ICERs in USD would be $5089 per LYG gained and $4615 per QALY gained. Sensitivity analysis showed the results to be robust. Conclusions Compared to usual care, cascade screening of ten year old children for FH and treating affected individuals is likely to be highly cost-effective. Table 1. Granular cost and benefit data Funding Acknowledgement Type of funding source: None

Background: Lipid management typically focuses on levels of LDL cholesterol (LDL-C) and, to a lesser extent, triglycerides (TG). Basic investigation and genetic studies, however, suggest that the atherogenic particle subpopulations (LDL & VLDL) are similarly important and that the number of particles is more important than their lipid content. Methods: We performed a prospective cohort analysis in two populations: 1) 389,529 primary prevention patients w/o lipid-lowering therapy from UK Biobank, and 2) 45,708 statin-treated patients w/ established atherosclerosis from the FOURIER and IMPROVE-IT trials. Incident MI was assessed over a median follow up of 11.1 yrs in UKBB and 3.6 yrs in the trials. Adjusted HRs were calculated to determine whether lipid content (non-HDL-C & TG) or particle type (using LDL-C concentration as a surrogate for LDL, and TG concentration as a surrogate for TG-rich lipoproteins) offer predictive value beyond atherogenic particle concentration (apoB). Results: In the primary prevention cohort, apoB, non-HDL-C, and TG each individually predicted incident MI. However, when assessed together, only apoB remained a significant predictor (adj HR per 1-SD = 1.28 [95%CI: 1.16,1.42], pFig, A/B ). Similarly, only apoB remained a predictor of MI in the secondary prevention cohort ( Fig, C/D ). Adjusting for apoB, there was no relationship between the ratio of TG to LDL-C (a surrogate for the ratio of TG-rich lipoproteins to LDL) and the risk of MI (p=0.32, Fig, E ), implying that for a given concentration of apoB-containing lipoproteins, the relative proportion of particle subpopulations is not an independent predictor of risk. Conclusion: Risk for MI is best captured by the number of apoB-containing lipoproteins, independent from lipid content (cholesterol or TG) or type of lipoprotein (LDL or TG-rich). Therefore, therapeutic strategies should take into account lowering the overall concentration of all apoB-containing lipoproteins.

Importance: Lipid management typically focuses on levels of low-density lipoprotein cholesterol (LDL-C) and, to a lesser extent, triglycerides (TG). However, animal models and genetic studies suggest that the atherogenic particle subpopulations (LDL and very-low-density lipoprotein [VLDL]) are both important and that the number of particles is more predictive of cardiac events than their lipid content. Objective: To determine whether common measures of cholesterol concentration, TG concentration, or their ratio are associated with cardiovascular risk beyond the number of apolipoprotein B (apoB)-containing lipoproteins. Design, Setting, and Participants: This prospective cohort analysis included individuals from the population-based UK Biobank and from 2 large international clinical trials, FOURIER and IMPROVE-IT. The median (IQR) follow-up was 11.1 (10.4-11.8) years in UK Biobank and 2.5 (2.0-4.7) years in the clinical trials. Two populations were studied in this analysis: 389529 individuals in the primary prevention group who were not taking lipid-lowering therapy and 40430 patients with established atherosclerosis who were receiving statin treatment. Exposures: ApoB, non-high-density lipoprotein cholesterol (HDL-C), LDL-C, and TG. Main Outcome and Measures: The primary study outcome was incident myocardial infarction (MI). Results: Of the 389529 individuals in the primary prevention group, 224097 (58%) were female, and the median (IQR) age was 56.0 (49.5-62.5) years. Of the 40430 patients with established atherosclerosis, 9647 (24%) were female, and the median (IQR) age was 63 (56.2-69.0) years. In the primary prevention cohort, apoB, non-HDL-C, and TG each individually were associated with incident MI. However, when assessed together, only apoB was associated (adjusted hazard ratio [aHR] per 1 SD, 1.27; 95% CI, 1.15-1.40; P

Background Heterozygous familial hypercholesterolemia (FH) is a highly-penetrant, autosomal dominant monogenic disorder that causes elevated plasma low-density cholesterol (LDL-C) levels and risk of premature coronary heart disease (CHD). To date, the cost-effectiveness of the emerging strategy of genomic screening of adult populations for FH has not been investigated. Purpose To assess the impact and cost-effectiveness of offering population genomic screening to all young adults in Australia to detect heterozygous familial hypercholesterolemia (FH). Methods We designed a decision analysis model to compare the current standard of care for heterozygous FH diagnosis in Australia (opportunistic cholesterol screening and genetic cascade testing) with population genomic screening of adults aged 18–40 years to detect pathogenic variants in the LDLR/APOB/PCSK9 genes. The model captured morbidity/mortality due to coronary heart disease (CHD) over a lifetime horizon, from a healthcare perspective. Risk of CHD, treatment effects, prevalence, and healthcare costs were estimated from published studies. Outcomes included quality adjusted life years (QALYs), costs and incremental cost-effectiveness ratio (ICER), discounted 5% annually. Sensitivity analyses were undertaken to explore the impact of key input parameters on the robustness of the model. The model structure was designed to be transferable to countries with different healthcare systems. Results Over the lifetime of the population (4,167,768 men; 4,129,961 women), the model estimated a gain of 62,722 years of life lived and 73,959 QALYs due to CHD prevention. Population genomic screening for FH would be cost-effective from a healthcare perspective if the cost per test was ≤AU$300 (∼US$233) which would yield an ICER AU$28,000 cost-saving. Conclusion Based on our model, offering population genomic screening to all young adults to detect FH could be cost-effective in the Australian healthcare system, at testing costs that are currently feasible. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): This work was supported by the Australian National Heart Foundation and Monash University Faculty of Medicine, Nursing and Health Sciences Results from scenario analysesResults from Monte Carlo simulations

Recent advances in human genetics, together with a large body of epidemiologic, preclinical, and clinical trial results, provide strong support for a causal association between triglycerides (TG), TG-rich lipoproteins (TRL), and TRL remnants, and increased risk of myocardial infarction, ischaemic stroke, and aortic valve stenosis. These data also indicate that TRL and their remnants may contribute significantly to residual cardiovascular risk in patients on optimized low-density lipoprotein (LDL)-lowering therapy. This statement critically appraises current understanding of the structure, function, and metabolism of TRL, and their pathophysiological role in atherosclerotic cardiovascular disease (ASCVD). Key points are (i) a working definition of normo- and hypertriglyceridaemic states and their relation to risk of ASCVD, (ii) a conceptual framework for the generation of remnants due to dysregulation of TRL production, lipolysis, and remodelling, as well as clearance of remnant lipoproteins from the circulation, (iii) the pleiotropic proatherogenic actions of TRL and remnants at the arterial wall, (iv) challenges in defining, quantitating, and assessing the atherogenic properties of remnant particles, and (v) exploration of the relative atherogenicity of TRL and remnants compared to LDL. Assessment of these issues provides a foundation for evaluating approaches to effectively reduce levels of TRL and remnants by targeting either production, lipolysis, or hepatic clearance, or a combination of these mechanisms. This consensus statement updates current understanding in an integrated manner, thereby providing a platform for new therapeutic paradigms targeting TRL and their remnants, with the aim of reducing the risk of ASCVD., Graphical Abstract Formation of triglyceride-rich lipoprotein remnants and their role in atherogenesis. Metabolic scheme for the generation and clearance of triglyceride-rich lipoprotein remnant particles (A). In hypertriglyceridaemia, overproduction and inefficient lipolysis of both very low-density lipoprotein and chylomicrons lead to increased remnant formation. Triglyceride-rich lipoprotein remnants contribute to the initiation and progression of atherosclerotic lesions (B). Particle retention in the subendothelial space is followed by inflammation, cholesterol deposition, and macrophage foam cell formation.

Aims The aim of this study was to assess the impact and cost-effectiveness of offering population genomic screening to all young adults in Australia to detect heterozygous familial hypercholesterolaemia (FH). Methods and results We designed a decision analytic Markov model to compare the current standard of care for heterozygous FH diagnosis in Australia (opportunistic cholesterol screening and genetic cascade testing) with the alternate strategy of population genomic screening of adults aged 18–40 years to detect pathogenic variants in the LDLR/APOB/PCSK9 genes. We used a validated cost-adaptation method to adapt findings to eight high-income countries. The model captured coronary heart disease (CHD) morbidity/mortality over a lifetime horizon, from healthcare and societal perspectives. Risk of CHD, treatment effects, prevalence, and healthcare costs were estimated from published studies. Outcomes included quality-adjusted life years (QALYs), costs and incremental cost-effectiveness ratio (ICER), discounted 5% annually. Sensitivity analyses were undertaken to explore the impact of key input parameters on the robustness of the model. Over the lifetime of the population (4 167 768 men; 4 129 961 women), the model estimated a gain of 33 488years of life lived and 51 790 QALYs due to CHD prevention. Population genomic screening for FH would be cost-effective from a healthcare perspective if the per-test cost was ≤AU$250, yielding an ICER of Conclusion Based on our model, offering population genomic screening to all young adults for FH could be cost-effective, at testing costs that are feasible.

Drug development in cardiovascular disease is stagnating, with lack of validated targets a major roadblock to innovation. Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization (MR). Such genetic support can increase the probability of a clinical trial succeeding. MR is being widely applied to quantitative traits (e.g. adiposity and blood lipids) with the aim of identifying risk factors for disease that are both causal and amenable to therapeutic modification. However, there are important differences between genetic investigations of a biomarker (such as HDL-cholesterol) and a drug target that seeks to modify the same biomarker of interest (such as CETP), with implications on the methodology, interpretation and applications of MR to drug development. Differences include the comparative nature of the genetic architecture, i.e. that of a biomarker typically being polygenic, whereas that for a protein drug target being monogenic. and the potential for drug targets to show pleiotropic disease associations which may differ to those of the biomarker it is designed to modify. In this review, we compare and contrast the role of MR as applied to quantitative traits versus drug targets, describing differences between approaches and the function each plays. Our review will put into context findings emerging from this burgeoning field of scientific investigation, with the aim of clarifying the aetiological roles of biomarkers in disease, prioritizing candidate drug targets based on genetic-guided credibility of causation and in so doing, improve the odds of success in the drug development pipeline.

BACKGROUND AND AIMS: Trial evidence for the benefits of cholesterol-lowering is limited for familial hypercholesterolemia (FH) patients, since they have not been the focus of large outcome trials. We assess statin use in coronary artery disease (CAD) subjects with low-density lipoprotein cholesterol (LDL-C) ≥4.9 mmol/L with or without an FH phenotype. METHODS: The 4S trial randomized hypercholesterolemic CAD patients to simvastatin or placebo. We first stratified participants into baseline LDL-C

AimsReliably quantifying event rates in secondary prevention could aid clinical decision-making, including quantifying potential risk reductions of novel, and sometimes expensive, add-on therapies. We aimed to assess whether the SMART risk prediction model performs well in a real-world setting.Methods and resultsWe conducted a historical open cohort study using UK primary care data from the Clinical Practice Research Datalink (2000–2017) diagnosed with coronary, cerebrovascular, peripheral, and/or aortic atherosclerotic cardiovascular disease (ASCVD). Analyses were undertaken separately for cohorts with established (≥6 months) vs. newly diagnosed ASCVD. The outcome was first post-cohort entry occurrence of myocardial infarction, stroke, or cardiovascular death. Among the cohort with established ASCVD [n = 244 578, 62.1% male, median age 67.3 years, interquartile range (IQR) 59.2–74.0], the calibration and discrimination achieved by the SMART model was not dissimilar to performance at internal validation [Harrell’s c-statistic = 0.639, 95% confidence interval (CI) 0.636–0.642, compared with 0.675, 0.642–0.708]. Decision curve analysis indicated that the model outperformed treat all and treat none strategies in the clinically relevant 20–60% predicted risk range. Consistent findings were observed in sensitivity analyses, including complete case analysis (n = 182 482; c = 0.624, 95% CI 0.620–0.627). Among the cohort with newly diagnosed ASCVD (n = 136 445; 61.0% male; median age 66.0 years, IQR 57.7–73.2), model performance was weaker with more exaggerated risk under-prediction and a c-statistic of 0.559, 95% CI 0.556–0.562.ConclusionsThe performance of the SMART model in this validation cohort demonstrates its potential utility in routine healthcare settings in guiding both population and individual-level decision-making for secondary prevention patients.

Drug development in cardiovascular disease is stagnating, with lack of efficacy and adverse effects being barriers to innovation. Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization, with genetic support for causation increasing the probability of a clinical trial succeeding. Mendelian randomization applied to quantitative traits can identify risk factors for disease that are both causal and amenable to therapeutic modification. However, important differences exist between genetic investigations of a biomarker (such as HDL cholesterol) and a drug target aimed at modifying the same biomarker of interest (such as cholesteryl ester transfer protein), with implications for the methodology, interpretation and application of Mendelian randomization to drug development. Differences include the comparative nature of the genetic architecture - that is, biomarkers are typically polygenic, whereas protein drug targets are influenced by either cis-acting or trans-acting genetic variants - and the potential for drug targets to show disease associations that might differ from those of the biomarker that they are intended to modify (target-mediated pleiotropy). In this Review, we compare and contrast the use of Mendelian randomization to evaluate potential drug targets versus quantitative traits. We explain how genetic epidemiological studies can be used to assess the aetiological roles of biomarkers in disease and to prioritize drug targets, including designing their evaluation in clinical trials.

Clinical estimation of the combined effect of several risk factors is unreliable and this resulted in the development of a number of risk estimation systems to guide clinical practice. Here, after defining general principles of risk estimation, the authors describe the evolution of the European Society of Cardiology's (ESC) Systematic COronary Risk Evaluation (SCORE) risk estimation system and some learnings from the data. They move on to describe the establishment of the ESC's Cardiovascular Risk Collaboration and outline its proposed research directions. First among these is the evolution of SCORE 2, which provides updated, calibrated risk estimates for total cardiovascular events for low, moderate, high, and very high-risk regions of Europe. The authors conclude by considering that the future of risk estimation may be to express risk as years of exposure to a cardiovascular risk factor profile rather than risk over a fixed time period, such as 10 years, and how advances in genetics may permit individualized lifetime risk estimation from childhood on.

The Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS)

Background Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD. Methods and findings We conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39–73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10−8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%–93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10−8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation–higher trait; 95% CI: 1.49–1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25–1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56–1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31–2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57–1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02–1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation–higher HDL cholesterol (OR 0.80; 95% CI: 0.75–0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77–0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components. Conclusions These findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD., Author summary Why was this study done? There is uncertainty regarding which lipid or apolipoprotein trait is the predominant atherogenic agent involved in the aetiology of lipids and coronary heart disease (CHD). The elucidation of such is important because not only does it clarify the aetiological understanding of the pathogenesis of CHD, it also hones the focus on the lipid- or apolipoprotein-related trait that should be the focus when developing lipid-modifying interventions. What did the researchers do and find? We used data on up to 441,016 participants from the UK Biobank to conduct genome-wide association analyses to find genetic variants reliably associated with lipoprotein lipid and apolipoprotein concentrations: this led to the identification of multiple independent genetic variants, each associated very robustly (at P < 5 × 10−8) with LDL cholesterol (220 genetic variants), apolipoprotein B (255 genetic variants), triglycerides (440 genetic variants), HDL cholesterol (534 genetic variants), and apolipoprotein A–I (440 genetic variants). Hundreds of these variants identified were novel, to our knowledge. When we explored the potential causal role of these lipids and apolipoproteins in isolation using Mendelian randomisation, we found evidence compatible with LDL cholesterol, triglycerides, and apolipoprotein B increasing the risk of CHD and HDL cholesterol and apolipoproteins A-I lowering CHD risk. When we examined these lipids and apolipoproteins together in multivariable Mendelian randomisation, we found that only apolipoprotein B retained a robust relationship with the risk of CHD—the effect estimates for all other entities were either substantially attenuated to the null or reversed in direction. What do these findings mean? The analytical approach in this study implemented through multivariable Mendelian randomisation simultaneously accounts for genetic associations with lipids and apolipoproteins and should therefore provide more reliable insights into what is the underlying driver of CHD. These findings support that, amongst the repertoire of lipoprotein lipids and apolipoproteins that we investigated, apolipoprotein B has a fundamental role in the aetiology of CHD.

People who maintain ideal cardiovascular heath have a low lifetime risk of cardiovascular disease. Therefore, encouraging people to achieve ideal cardiovascular health represents an important opportunity to improve the prevention of cardiovascular disease. However, preventing cardiovascular disease by promoting ideal cardiovascular health requires shifting the focus from treating disease after it develops to preventing cardiovascular events before they happen by slowing the progression of atherosclerosis. Because atherogenic lipoproteins play a central causal role in the initiation and progression of atherosclerosis, maintaining optimal lipid levels is necessary to achieve ideal cardiovascular health. This review describes the cumulative effect of lipid-carrying lipoproteins on the risk of cardiovascular disease, estimates the magnitude of the clinical benefit that can be achieved by maintaining optimal lipid levels, identifies the most effective timing for implementing strategies designed to achieve optimal lipid levels, and provides a clinical pathway to help people achieve the lipid levels necessary for ideal cardiovascular health.

People who maintain ideal cardiovascular heath have a low lifetime risk of cardiovascular disease. Therefore, encouraging people to achieve ideal cardiovascular health represents an importa...

Mendelian randomization studies demonstrate that apolipoprotein B-containing lipoproteins have both causal and cumulative effects on the risk of atherosclerotic cardiovascular disease. The clinical benefit of lipid-lowering therapies depends on both the absolute reduction in circulating apolipoprotein B-containing lipoproteins and the total duration of exposure to these particles. Because atherosclerosis seems to be caused by the retention of apolipoprotein B-containing lipoproteins rather than by the cholesterol content carried by those lipoproteins, high-density lipoprotein-mediated efflux of cholesterol from the arterial wall may not reduce the risk of atherosclerotic cardiovascular disease.

Correction: Volume: 292 Pages: 160-162 DOI: 10.1016/j.atherosclerosis.2019.11.020 Published: JAN 2020

BACKGROUND: Trapping of apoB lipoprotein particles within the arterial wall initiates and drives the atherosclerotic process from beginning to end. Very low-density lipoprotein particles (VLDL) contain most of the triglyceride in plasma whereas low-density lipoprotein particles (LDL) particles contain most of the cholesterol. Smaller numbers of chylomicron and Lp(a) particles are also present in plasma. All these particles have one molecule of apoB. Therefore, plasma apoB equals the total number of apoB particles. Because the lipid content of apoB particles is variable, plasma triglyceride and cholesterol are not always accurate-measures of the number of apoB particles. THE CHOLESTEROL MODEL OF ATHEROSCLEROSIS: The conventional model of atherosclerosis presumes that the mass of cholesterol within VLDL and LDL particles is the principal determinant of the mass of cholesterol that will be deposited within the arterial wall and will drive atherogenesis. But cholesterol can only enter the arterial wall within apoB particles and the mass of cholesterol that will be deposited is determined by the rate at which apoB particles are trapped within the arterial wall rather than passing harmless through. THE APOB PARTICLE MODEL OF ATHEROGENESIS: The number of apoB particles that enter and are trapped within the arterial wall is determined primarily by the number of apoB particles within the arterial lumen. However, once within the arterial wall, smaller cholesterol-depleted apoB particles have a greater tendency to be trapped than larger cholesterol-enriched apoB particles because they bind more avidly to the glycosaminoglycans within the subintimal space of the arterial wall. If so, a cholesterol-enriched particle would deposit more cholesterol than a cholesterol-depleted apoB particle. By contrast, more smaller apoB particles that enter the arterial wall will be trapped than larger apoB particles. The net result is, with the exceptions of the abnormal chylomicron remnants in type III hyperlipoproteinemia and Lp(a), all apoB particles are equally atherogenic. ApoB, therefore, unifies, amplifies, and simplifies the information from the conventional lipid markers as to the atherogenic risk attributable to the apoB lipoproteins.

Background: Randomized trials of therapies that primarily lowered triglycerides have not consistently shown reductions in cardiovascular events. Methods: We performed a systematic review and trial-level meta-regression analysis of 3 classes of lipid-lowering therapies that reduce triglycerides to a greater extent than they do low-density lipoprotein cholesterol (LDL-C): fibrates, niacin, and marine-derived omega-3 fatty acids. Key inclusion criteria were a randomized controlled trial that reported major vascular events. We also incorporated data from a previous meta-regression of 25 statin trials. The main outcome measure was the risk ratio (RR) for major vascular events associated with absolute reductions in lipid parameters. Results: A total of 197 270 participants from 24 trials of nonstatin therapy with 25 218 major vascular events and 177 088 participants from 25 trials of statin therapy with 20 962 major vascular events were included, for a total of 374 358 patients and 46 180 major cardiovascular events. Starting with non–high-density lipoprotein cholesterol, a surrogate for very-low-density lipoproteins and low-density lipoproteins, the RR per 1-mmol/L reduction in non–high-density lipoprotein cholesterol was 0.79 (95% CI, 0.76–0.82; P P P =0.0026) per 1-mmol/L (0.92 per 40 mg/dL) reduction in triglycerides. REDUCE-IT (Reduction of Cardiovascular Events With Icosapent Ethyl–Intervention Trial) was a significant outlier and strongly influential trial in the meta-regression. When removed, the RRs became 0.79 (95% CI, 0.76–0.83; P P =0.06) per 1-mmol/L (0.96 per 40 mg/dL) reduction in triglycerides. In regard to omega-3 dose, each 1 g/d eicosapentaenoic acid administered was associated with a 7% relative risk reduction in major vascular events (RR, 0.93 [95% CI, 0.91–0.95]; P Conclusions: In randomized controlled trials, triglyceride lowering is associated with a lower risk of major vascular events, even after adjustment for LDL-C lowering, although the effect is less than that for LDL-C and attenuated when REDUCE-IT is excluded. Furthermore, the benefits of marine-derived omega-3 fatty acids, particularly high-dose eicosapentaenoic acid, appear to exceed their lipid-lowering effects.

Background: Circulating blood lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. We sought to explore the causal relationships of blood lipid traits with risk of CHD using multivariable Mendelian randomization. Methods: We conducted GWAS of circulating blood lipid traits in UK Biobank (up to n=440,546) for LDL cholesterol, triglycerides and apolipoprotein B to identify lipid-associated SNPs. Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable Mendelian randomization (MR) analyses. Similar analyses were conducted for HDL cholesterol and apolipoprotein A-I. Findings: GWAS identified multiple independent SNPs associated at P

IMPORTANCE: The relationship between exposure to lower low-density lipoprotein cholesterol (LDL-C) and lower systolic blood pressure (SBP) with the risk of cardiovascular disease has not been reliably quantified. OBJECTIVE: To assess the association of lifetime exposure to the combination of both lower LDL-C and lower SBP with the lifetime risk of cardiovascular disease. DESIGN, SETTING, AND PARTICIPANTS: Among 438 952 participants enrolled in the UK Biobank between 2006 and 2010 and followed up through 2018, genetic LDL-C and SBP scores were used as instruments to divide participants into groups with lifetime exposure to lower LDL-C, lower SBP, or both. Differences in plasma LDL-C, SBP, and cardiovascular event rates between the groups were compared to estimate associations with lifetime risk of cardiovascular disease. EXPOSURES: Differences in plasma LDL-C and SBP compared with participants with both genetic scores below the median. Genetic risk scores higher than the median were associated with lower LDL-C and lower SBP. MAIN OUTCOMES AND MEASURES: Odds ratio (OR) for major coronary events, defined as coronary death, nonfatal myocardial infarction, or coronary revascularization. RESULTS: The mean age of the 438 952 participants was 65.2 years (range, 40.4-80.0 years), 54.1% were women, and 24 980 experienced a first major coronary event. Compared with the reference group, participants with LDL-C genetic scores higher than the median had 14.7-mg/dL lower LDL-C levels and an OR of 0.73 for major coronary events (95% CI, 0.70-0.75; P

BACKGROUND: ATP citrate lyase is an enzyme in the cholesterol–biosynthesis pathway upstream of 3-hydroxy-3-methylglutaryl–coenzyme A reductase (HMGCR), the target of statins. Whether the genetic inhibition of ATP citrate lyase is associated with deleterious outcomes and whether it has the same effect, per unit decrease in the low-density lipoprotein (LDL) cholesterol level, as the genetic inhibition of HMGCR is unclear. METHODS: We constructed genetic scores composed of independently inherited variants in the genes encoding ATP citrate lyase (ACLY) and HMGCR to create instruments that mimic the effect of ATP citrate lyase inhibitors and HMGCR inhibitors (statins), respectively. We then compared the associations of these genetic scores with plasma lipid levels, lipoprotein levels, and the risk of cardiovascular events and cancer. RESULTS: A total of 654,783 participants, including 105,429 participants who had major cardiovascular events, were included in the study. The ACLY and HMGCR scores were associated with similar patterns of changes in plasma lipid and lipoprotein levels and with similar effects on the risk of cardiovascular events per decrease of 10 mg per deciliter in the LDL cholesterol level: odds ratio for cardiovascular events, 0.823 (95% confidence interval [CI], 0.78 to 0.87; P = 4.0×10(−14)) for the ACLY score and 0.836 (95% CI, 0.81 to 0.87; P= 3.9×10(−19)) for the HMGCR score. Neither lifelong genetic inhibition of ATP citrate lyase nor lifelong genetic inhibition of HMGCR was associated with an increased risk of cancer. CONCLUSIONS: Genetic variants that mimic the effect of ATP citrate lyase inhibitors and statins appeared to lower plasma LDL cholesterol levels by the same mechanism of action and were associated with similar effects on the risk of cardiovascular disease per unit decrease in the LDL cholesterol level. (Funded by Esperion Therapeutics and others.)

Randomized controlled trials and Mendelian randomization studies are two study designs that provide randomized evidence in human biological and medical research. Both exploit the power of randomization to provide unconfounded estimates of causal effect. However, randomized trials and Mendelian randomization studies have very different study designs and scientific objectives. As a result, despite sometimes being referred to as "nature's randomized trial," a Mendelian randomization study cannot be used to replace a randomized trial but instead provides complementary information. In this review, we explain the similarities and differences between randomized trials and Mendelian randomization studies, and suggest several ways that Mendelian randomization can be used to directly inform and improve the design of randomized trials illustrated with practical examples. We conclude by describing how Mendelian randomization studies can employ the principles of trial design to be framed as "naturally randomized trials" that can provide a template for the design of future randomized trials evaluating therapies directed against genetically validated targets.

Aims PCSK9 genetic variants that have large effects on low-density lipoprotein cholesterol (LDL-C) and coronary heart disease (CHD) have prompted the development of therapeutic PCSK9-inhibition. However, there is limited evidence that PCSK9 variants are associated with ischaemic stroke (IS). Methods and results Associations of the loss-of-function PCSK9 genetic variant (rs11591147; R46L), and five additional PCSK9 variants, with IS and IS subtypes (cardioembolic, large vessel, and small vessel) were estimated in a meta-analysis involving 10 307 IS cases and 19 326 controls of European ancestry. They were then compared with the associations of these variants with LDL-C levels (in up to 172 970 individuals) and CHD (in up to 60 801 CHD cases and 123 504 controls). The rs11591147 T allele was associated with 0.5 mmol/L lower LDL-C level (P = 9 × 10−143) and 23% lower CHD risk [odds ratio (OR): 0.77, 95% confidence interval (CI): 0.69–0.87, P = 7 × 10−6]. However, it was not associated with risk of IS (OR: 1.04, 95% CI: 0.84–1.28, P = 0.74) or IS subtypes. Information from additional PCSK9 variants also indicated consistently weaker effects on IS than on CHD. Conclusion PCSK9 genetic variants that confer life-long lower PCSK9 and LDL-C levels appear to have significantly weaker, if any, associations with risk of IS than with risk of CHD. By contrast, similar proportional reductions in risks of IS and CHD have been observed in randomized trials of therapeutic PCSK9-inhibition. These findings have implications for our understanding of when Mendelian randomization can be relied upon to predict the effects of therapeutic interventions.

Importance: Triglycerides and cholesterol are both carried in plasma by apolipoprotein B (ApoB)-containing lipoprotein particles. It is unknown whether lowering plasma triglyceride levels reduces the risk of cardiovascular events to the same extent as lowering low-density lipoprotein cholesterol (LDL-C) levels. Objective: To compare the association of triglyceride-lowering variants in the lipoprotein lipase (LPL) gene and LDL-C-lowering variants in the LDL receptor gene (LDLR) with the risk of cardiovascular disease per unit change in ApoB. Design, Setting, and Participants: Mendelian randomization analyses evaluating the associations of genetic scores composed of triglyceride-lowering variants in the LPL gene and LDL-C-lowering variants in the LDLR gene, respectively, with the risk of cardiovascular events among participants enrolled in 63 cohort or case-control studies conducted in North America or Europe between 1948 and 2017. Exposures: Differences in plasma triglyceride, LDL-C, and ApoB levels associated with the LPL and LDLR genetic scores. Main Outcomes and Measures: Odds ratio (OR) for coronary heart disease (CHD) - defined as coronary death, myocardial infarction, or coronary revascularization - per 10-mg/dL lower concentration of ApoB-containing lipoproteins. Results: A total of 654783 participants, including 91129 cases of CHD, were included (mean age, 62.7 years; 51.4% women). For each 10-mg/dL lower level of ApoB-containing lipoproteins, the LPL score was associated with 69.9-mg/dL (95% CI, 68.1-71.6; P = 7.1 × 10 -1363 ) lower triglyceride levels and 0.7-mg/dL (95% CI, 0.03-1.4; P =.04) higher LDL-C levels; while the LDLR score was associated with 14.2-mg/dL (95% CI, 13.6-14.8; P = 1.4 × 10 -465 ) lower LDL-C and 1.9-mg/dL (95% CI, 0.1-3.9; P =.04) lower triglyceride levels. Despite these differences in associated lipid levels, the LPL and LDLR scores were associated with similar lower risk of CHD per 10-mg/dL lower level of ApoB-containing lipoproteins (OR, 0.771 [95% CI, 0.741-0.802], P = 3.9 × 10 -38 and OR, 0.773 [95% CI, 0.747-0.801], P = 1.1 × 10 -46 , respectively). In multivariable mendelian randomization analyses, the associations between triglyceride and LDL-C levels with the risk of CHD became null after adjusting for differences in ApoB (triglycerides: OR, 1.014 [95% CI, 0.965-1.065], P =.19; LDL-C: OR, 1.010 [95% CI, 0.967-1.055], P =.19; ApoB: OR, 0.761 [95% CI, 0.723-0.798], P = 7.51 × 10 -20 ). Conclusions and Relevance: Triglyceride-lowering LPL variants and LDL-C-lowering LDLR variants were associated with similar lower risk of CHD per unit difference in ApoB. Therefore, the clinical benefit of lowering triglyceride and LDL-C levels may be proportional to the absolute change in ApoB.

Mendelian randomization studies and "human knock-out" studies of rare loss-of-function coding variants suggest that plasma levels of low-density lipoprotein-cholesterol LDL-C, triglycerides (TGs), and lipoprotein(a) (Lp(a)) are causally associated with the risk of cardiovascular disease, and, therefore, therapies directed against these targets should reduce the risk of cardiovascular events. However, several therapies directed against these targets have failed to reduce the risk of cardiovascular events in large-scale randomized trials, thus suggesting that causality is not sufficient evidence to establish genetic target validation. Instead, the critical question that needs to be answered to improve drug discovery and development is how much a causal biomarker needs to be changed to produce a clinically meaningful benefit in a short-term trial. This review describes how to use naturally randomized genetic evidence to accurately anticipate the results of randomized trials evaluating current and future lipid lowering therapies, inform the design of randomized trials, and transform the drug discovery and development process.

People who maintain ideal cardiovascular heath have a low lifetime risk of cardiovascular disease. Therefore, encouraging people to achieve ideal cardiovascular health represents an important opportunity to improve the prevention of cardiovascular disease. However, preventing cardiovascular disease by promoting ideal cardiovascular health requires shifting the focus from treating disease after it develops to preventing cardiovascular events before they happen by slowing the progression of atherosclerosis. Because atherogenic lipoproteins play a central causal role in the initiation and progression of atherosclerosis, maintaining optimal lipid levels is necessary to achieve ideal cardiovascular health. This review describes the cumulative effect of lipid-carrying lipoproteins on the risk of cardiovascular disease, estimates the magnitude of the clinical benefit that can be achieved by maintaining optimal lipid levels, identifies the most effective timing for implementing strategies designed to achieve optimal lipid levels, and provides a clinical pathway to help people achieve the lipid levels necessary for ideal cardiovascular health.

People who maintain ideal cardiovascular heath have a low lifetime risk of cardiovascular disease. Therefore, encouraging people to achieve ideal cardiovascular health represents an important opportunity to improve the prevention of cardiovascular disease. However, preventing cardiovascular disease by promoting ideal cardiovascular health requires shifting the focus from treating disease after it develops to preventing cardiovascular events before they happen by slowing the progression of atherosclerosis. Because atherogenic lipoproteins play a central causal role in the initiation and progression of atherosclerosis, maintaining optimal lipid levels is necessary to achieve ideal cardiovascular health. This review describes the cumulative effect of lipid-carrying lipoproteins on the risk of cardiovascular disease, estimates the magnitude of the clinical benefit that can be achieved by maintaining optimal lipid levels, identifies the most effective timing for implementing strategies designed to achieve optimal lipid levels, and provides a clinical pathway to help people achieve the lipid levels necessary for ideal cardiovascular health.

Mendelian randomization studies have the potential to transform our understanding of cardiovascular medicine by generating naturally randomized data that can fill evidence gaps when a randomized trial would be either impossible or impractical to conduct. Here, we review recent Mendelian randomization studies evaluating the effect of low-density lipoprotein cholesterol (LDL-C) on the risk of coronary heart disease (CHD).Mendelian randomization studies consistently demonstrate that LDL-C is causally associated with the risk of CHD. Furthermore, exposure to genetically mediated lower LDL-C appears to be associated with a much greater than expected reduction in CHD risk, thus suggesting that LDL-C has a cumulative effect on the risk of CHD. In addition, genetically mediated lower LDL-C is log-linearly associated with the risk of CHD and the effect of polymorphisms in multiple different genes on the risk of CHD is remarkably consistent when measured per unit lower LDL-C.The naturally randomized genetic evidence suggests that LDL-C has a causal and cumulative effect on the risk of CHD, and that the clinical benefit of exposure to lower LDL-C is determined by the absolute magnitude of exposure to lower LDL-C independent of the mechanism by which LDL-C is lowered.

Cardiovascular morbidity and mortality as a result of inhaled tobacco products continues to be a global healthcare crisis, particularly in low- and middle-income nations lacking the infrastructure to develop and implement effective public health policies limiting tobacco use. Following initiation of public awareness campaigns 50 years ago in the United States, considerable success has been achieved in reducing the prevalence of cigarette smoking and exposure to secondhand smoke. However, there has been a slowing of cessation rates in the United States during recent years, possibly caused by high residual addiction or fatigue from cessation messaging. Furthermore, tobacco products have continued to evolve faster than the scientific understanding of their biological effects. This review considers selected updates on the genetics and epigenetics of smoking behavior and associated cardiovascular risk, mechanisms of atherogenesis and thrombosis, clinical effects of smoking and benefits of cessation, and potential impact of electronic cigarettes on cardiovascular health.

Background Considerable uncertainty exists as to whether lowering low-density lipoprotein cholesterol (LDL-C) by inhibiting the Niemann-Pick C1-Like 1 (NPC1L1) receptor with ezetimibe, either alone or in combination with a 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibitor (statin), will reduce the risk of coronary heart disease (CHD). Objectives This study evaluated the effect of naturally random allocation to lower LDL-C mediated by polymorphisms in the NPC1L1 gene (target of ezetimibe), the HMGCR gene (target of statins), or both (target of combination therapy) on the risk of CHD. Methods We constructed NPC1L1 and HMGCR genetic LDL-C scores to naturally randomize participants into 4 groups: reference, lower LDL-C mediated by NPC1L1 polymorphisms, lower LDL-C mediated by HMGCR polymorphisms, or lower LDL-C mediated by polymorphisms in both NPC1L1 and HMGCR . We compared the risk of CHD (fatal or nonfatal myocardial infarction) among each group using a 2 × 2 factorial mendelian randomization study design. Results A total of 108,376 persons (10,464 CHD events) from 14 studies were included. There were no significant differences in baseline characteristics among the 4 groups, thus confirming that allocation was random. Compared to the reference group, the NPC1L1 group had 2.4 mg/dl lower LDL-C and 4.8% lower risk of CHD (odds ratio [OR]: 0.952, 95% confidence interval [CI]: 0.920 to 0.985); whereas the HMGCR group had 2.9 mg/dl lower LDL-C and a similar 5.3% lower risk of CHD (OR: 0.947, 95% CI: 0.909 to 0.986). The group with lower LDL-C mediated by both NPC1L1 and HMGCR polymorphisms had 5.8 mg/dl additively lower LDL-C and a 10.8% log-linearly additive lower risk of CHD (OR: 0.892, 95% CI: 0.854 to 0.932). Conclusions The effect of lower LDL-C on the risk of CHD mediated by polymorphisms in NPC1L1 , HMGCR, or both is approximately the same per unit lower LDL-C and log-linearly proportional to the absolute exposure to lower LDL-C.