In-depth Mendelian randomization analysis of causal factors for coronary artery disease

HDL as a Treatment Target: Should We Abandon This Idea?

PURPOSE OF REVIEW

High-density lipoproteins (HDL) have long been regarded as an antiatherogenic lipoprotein species by virtue of their role in reverse cholesterol transport (RCT), as well as their established anti-inflammatory and antioxidant properties. For decades, HDL have been an extremely appealing therapeutic target to combat atherosclerotic cardiovascular diseases (ASCVD).

RECENT FINDINGS

Unfortunately, neither increasing HDL with drugs nor direct infusions of reconstituted HDL have convincedly proven to be positive strategies for cardiovascular health, raising the question of whether we should abandon the idea of considering HDL as a treatment target. The results of two large clinical trials, one testing the latest CETP inhibitor Obicetrapib and the other testing the infusion of patients post-acute coronary events with reconstituted HDL, are still awaited. If they prove negative, these trials will seal the fate of HDL as a direct therapeutic target. However, using HDL as a therapeutic agent still holds promise if we manage to optimize their beneficial properties for not only ASCVD but also outside the cardiovascular field.

Pravastatin for lowering lipids

BACKGROUND

A detailed summary and meta-analysis of the dose-related effect of pravastatin on lipids is not available.

OBJECTIVES

Primary objective To assess the pharmacology of pravastatin by characterizing the dose-related effect and variability of the effect of pravastatin on the surrogate marker: low-density lipoprotein (LDL cholesterol). The effect of pravastatin on morbidity and mortality is not the objective of this systematic review. Secondary objectives • To assess the dose-related effect and variability of effect of pravastatin on the following surrogate markers: total cholesterol; high-density lipoprotein (HDL cholesterol); and triglycerides. • To assess the effect of pravastatin on withdrawals due to adverse effects.

SEARCH METHODS

The Cochrane Hypertension Information Specialist searched the following databases for randomized controlled trials (RCTs) up to September 2021: CENTRAL (2021, Issue 8), Ovid MEDLINE, Ovid Embase, Bireme LILACS, the WHO International Clinical Trials Registry Platform, and ClinicalTrials.gov. We also contacted authors of relevant papers regarding further published and unpublished work. The searches had no language restrictions.

SELECTION CRITERIA

Randomized placebo-controlled trials evaluating the dose response of different fixed doses of pravastatin on blood lipids over a duration of three to 12 weeks in participants of any age with and without evidence of cardiovascular disease.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed eligibility criteria for studies to be included, and extracted data. We entered lipid data from placebo-controlled trials into Review Manager 5 as continuous data and withdrawal due to adverse effects (WDAEs) data as dichotomous data. We searched for WDAEs information from all trials. We assessed all trials using Cochrane's risk of bias tool under the categories of sequence generation, allocation concealment, blinding, incomplete outcome data, selective reporting, and other potential biases.

MAIN RESULTS

Sixty-four RCTs evaluated the dose-related efficacy of pravastatin in 9771 participants. The participants were of any age, with and without evidence of cardiovascular disease, and pravastatin effects were studied within a treatment period of three to 12 weeks. Log dose-response data over the doses of 5 mg to 160 mg revealed strong linear dose-related effects on blood total cholesterol and LDL cholesterol, and a weak linear dose-related effect on blood triglycerides. There was no dose-related effect of pravastatin on blood HDL cholesterol. Pravastatin 10 mg/day to 80 mg/day reduced LDL cholesterol by 21.7% to 31.9%, total cholesterol by 16.1% to 23.3%,and triglycerides by 5.8% to 20.0%. The certainty of evidence for these effects was judged to be moderate to high. For every two-fold dose increase there was a 3.4% (95% confidence interval (CI) 2.2 to 4.6) decrease in blood LDL cholesterol. This represented a dose-response slope that was less than the other studied statins: atorvastatin, rosuvastatin, fluvastatin, pitavastatin and cerivastatin. From other systematic reviews we conducted on statins for its effect to reduce LDL cholesterol, pravastatin is similar to fluvastatin, but has a decreased effect compared to atorvastatin, rosuvastatin, pitavastatin and cerivastatin. The effect of pravastatin compared to placebo on WADES has a risk ratio (RR) of 0.81 (95% CI 0.63 to 1.03). The certainty of evidence was judged to be very low.

AUTHORS' CONCLUSIONS

Pravastatin lowers blood total cholesterol, LDL cholesterol and triglyceride in a dose-dependent linear fashion. This review did not provide a good estimate of the incidence of harms associated with pravastatin because of the lack of reporting of adverse effects in 48.4% of the randomized placebo-controlled trials.

Uncovering genetic associations in the human diseasome using an endophenotype-augmented disease network

Many diseases exhibit complex multimorbidities with one another. An intuitive way to model the connections between phenotypes is with a disease-disease network (DDN), where nodes represent diseases and edges represent associations, such as shared single-nucleotide polymorphisms (SNPs), between pairs of diseases. To gain further genetic understanding of molecular contributors to disease associations, we propose a novel version of the shared-SNP DDN (ssDDN), denoted as ssDDN+, which includes connections between diseases derived from genetic correlations with endophenotypes. We hypothesize that a ssDDN+ can provide complementary information to the disease connections in a ssDDN, yielding insight into the role of clinical laboratory measurements in disease interactions. Using PheWAS summary statistics from the UK Biobank, we constructed a ssDDN+ revealing hundreds of genetic correlations between disease phenotypes and quantitative traits. Our augmented network uncovers genetic associations across different disease categories, connects relevant cardiometabolic diseases, and highlights specific biomarkers that are associated with cross-phenotype associations. Out of the 31 clinical measurements under consideration, HDL-C connects the greatest number of diseases and is strongly associated with both type 2 diabetes and diabetic retinopathy. Triglycerides, another blood lipid with known genetics causes in non-mendelian diseases, also adds a substantial number of edges to the ssDDN. Our study can facilitate future network-based investigations of cross-phenotype associations involving pleiotropy and genetic heterogeneity, potentially uncovering sources of missing heritability in multimorbidities.

Side effects of statins: from pathophysiology and epidemiology to diagnostic and therapeutic implications

Treatment with statins, inhibitors of 3-hydroxy-3-methylglutaryl-coenzyme A reductase, has proven beneficial preventive effects on cardiovascular events. However, discontinuation due to intolerance and non-adherence remain two of the major gaps in both primary and secondary prevention. This leads many patients with high-risk of atherosclerotic cardiovascular disease (ASCVD) to be inadequately treated or not to achieve target lipid level goals, and as consequence they undergo an increased risk of cardiovascular events. The aim of this review is thus to give an overview of the reasons for discontinuation and on the possible mechanisms behind them. Although statins, as a class, are generally safe, they are associated with an increased risk of diabetes mellitus and hepatic transaminase elevations. Incidence of cataracts or cognitive dysfunction and others presented in the literature (e.g. proteinuria and haematuria) have been never confirmed to have a causal link. Conversely, debated remains the effect on myalgia. Muscle side effects are the most commonly reported, although myalgia is still believed by some to be the result of a nocebo/drucebo effect. Concerning mechanisms behind muscular side effects, no clear conclusions have been reached. Thus, if on one side it is important to identify individuals either at higher risk to develop a side effect, or with confirmed risk factors and conditions of statin intolerance, on the other side alternative strategies should be identified to avoid an increased ASCVD risk.

L-carnitine, a friend or foe for cardiovascular disease? A Mendelian randomization study

BACKGROUND

L-carnitine is emerging as an item of interest for cardiovascular disease (CVD) prevention and treatment, but controversy exists. To examine the effectiveness and safety of L-carnitine, we assessed how genetically different levels of L-carnitine are associated with CVD risk and its risk factors. Given higher CVD incidence and L-carnitine in men, we also examined sex-specific associations.

METHODS

We used Mendelian randomization to obtain unconfounded estimates. Specifically, we used genetic variants to predict L-carnitine, and obtained their associations with coronary artery disease (CAD), ischemic stroke, heart failure, and atrial fibrillation, as well as CVD risk factors (type 2 diabetes, glucose, HbA1c, insulin, lipid profile, blood pressure and body mass index) in large consortia and established cohorts, as well as sex-specific association in the UK Biobank. We obtained the Wald estimates (genetic association with CVD and its risk factors divided by the genetic association with L-carnitine) and combined them using inverse variance weighting. In sensitivity analysis, we used different analysis methods robust to pleiotropy and replicated using an L-carnitine isoform, acetyl-carnitine.

RESULTS

Genetically predicted L-carnitine was nominally associated with higher risk of CAD overall (OR 1.07 per standard deviation (SD) increase in L-carnitine, 95% CI 1.02 to 1.11) and in men (OR 1.09, 95% CI 1.02 to 1.16) but had a null association in women (OR 1.00, 95% CI 0.92 to 1.09). These associations were also robust to different methods and evident for acetyl-carnitine.

CONCLUSIONS

Our findings do not support a beneficial association of L-carnitine with CVD and its risk factors but suggest potential harm. L-carnitine may also exert a sex-specific role in CAD. Consideration of the possible sex disparity and exploration of the underlying pathways would be worthwhile.

The dawn of a new era of targeted lipid-lowering therapies

Lipid risk factors for cardiovascular disease depend in part on lifestyle, but optimum control of lipids often demands additional measures. Low-density lipoprotein (LDL) doubtless contributes causally to atherosclerosis. Recent human genetic findings have substantiated a number of novel targets for lipid-lowering therapy including apolipoprotein C-III, angiopoietin-like protein 3 and 4, apolipoprotein V, and ATP citrate lyase. These discoveries coupled with advances in biotechnology development afford new avenues for management of LDL and other aspects of lipid risk. Beyond LDL, new treatments targeting triglyceride-rich lipoproteins and lipoprotein(a) have become available and have entered clinical development. Biological and RNA-directed agents have joined traditional small-molecule approaches, which themselves have undergone considerable refinement. Innovative targeting strategies have increased efficacy of some of these novel interventions and markedly improved their tolerability. Gene-editing approaches have appeared on the horizon of lipid management. This article reviews this progress offering insight into novel biological and therapeutic discoveries, and places them into a practical patient care perspective.

Panomics: New Databases for Advancing Cardiology

The multifactorial nature of cardiology makes it challenging to separate noisy signals from confounders and real markers or drivers of disease. Panomics, the combination of various omic methods, provides the deepest insights into the underlying biological mechanisms to develop tools for personalized medicine under a systems biology approach. Questions remain about current findings and anticipated developments of omics. Here, we search for omic databases, investigate the types of data they provide, and give some examples of panomic applications in health care. We identified 104 omic databases, of which 72 met the inclusion criteria: genomic and clinical measurements on a subset of the database population plus one or more omic datasets. Of those, 65 were methylomic, 59 transcriptomic, 41 proteomic, 42 metabolomic, and 22 microbiomic databases. Larger database sample sizes and longer follow-up are often better suited for panomic analyses due to statistical power calculations. They are often more complete, which is important when dealing with large biological variability. Thus, the UK BioBank rises as the most comprehensive panomic resource, at present, but certain study designs may benefit from other databases.