Abstract
Cardiovascular disease is a leading cause of mortality across Europe and the USA. Epidemiological studies and randomized clinical trials provide strong evidence that coronary disease is largely preventable and can be attributed principally to nine modifiable risk factors. However, a large proportion of coronary events occur in individuals who have intermediate levels of these risk factors, motivating the search for novel markers to improve screening and risk stratification. Work presented at the 78th European Atherosclerosis Society Congress outlined challenges faced in primary prevention as well as novel findings for risk factors. This article focuses on some of these factors, as well as risk prediction and detection, and concludes with the current state of antiatherogenic treatment strategies.
Environmental & nonclassical biomarkers & risk factors
Biomarkers can be used in the selection of therapy, early detection of subclinical disease, diagnosis of acute coronary syndromes and risk stratification. The recent MONICA, Risk, Genetics, Archiving and Monograph (MORGAM) biomarker project evaluated 30 novel biomarkers from different pathophysiological pathways for their associations with cardiovascular events Citation[1]. Although none of the biomarkers individually improved risk estimation, a biomarker score consisting of troponin I, C-reactive protein (CRP) and N-terminal probrain natriuretic peptide improved risk estimation (when using the risk metrics for discrimination, calibration and reclassification). Further work is being performed to examine whether composite biomarker scores perform better than single risk factors such as CRP, which has been the focus of a large number of studies and its predictive utility is still debated. Other inflammatory factors are also being evaluated, including IL-18 and lipoprotein-associated phospholipase A2, both of which are associated with cardiovascular disease (CVD) risk. However, more work is needed to examine their utility in risk estimation.
Whilst novel risk factors are being found to underlie an increasing proportion of risk in CVD, traditional risk factors and behaviors remain important for public and individual health. Eric Brunner (University College London, UK) highlighted the ongoing impact of socioeconomic deprivation on cardiovascular risk using data from the Whitehall I and II studies [Unpublished Data]. Importantly, the efficacy of risk factor-modifying interventions also follows a socioeconomic gradient with populations of lower socioeconomic status and at higher risk receiving less benefit from risk reduction than less deprived groups. Based on modeling estimates, measures to reduce blood pressure, total cholesterol and blood glucose, prevent diabetes and achieve complete smoking cessation could prevent 57% of coronary events. However, given the lifelong effect of socioeconomic status, it appears that short-term medical intervention cannot compensate for a lifetime of relative deprivation. Nick Wareham (Cambridge University, UK) presented data from the European Prospective Investigation of Cancer (EPIC)-Norfolk study on the effects of physical activity on CVD risk. While the protective role of physical activity in CVD remains clear, improved solutions for measuring activity levels and their use in risk prediction are required. Data from EPIC-Norfolk suggested that adding a measure of physical activity to the Framingham Risk Score provides additional predictive power, but such an instrument needs to be responsive to change in risk factors, which is a challenge when physical activity is used.
Metabolic risk factors
Obesity and metabolism are also attracting a large amount of interest, both in trying to identify novel risk factors as well as their use in risk detection. An insightful presentation by Luc Van Gaal (University of Antwerp, Belgium) gave an overview of abdominal obesity promoting insulin resistance and β-cell dysfunction. Adipose tissue is an active endocrine and paracrine organ that releases cytokines and bioactive mediators, such as leptin, adiponectin, IL-6 and TNF-α. Studies have demonstrated abdominal obesity to be a risk factor for CVD and several of the potential mechanisms for this association are believed to be related to insulin resistance. Several adipokines, such as leptin, adiponectin, TNF-α, IL-6, resistin, visfatin and retinol-binding protein 4 (RBP4), are thought to be linked to insulin resistance.
Adiponectin was shown to have antiatherogenic, antidiabetic and anti-inflammatory properties, and is decreased in obesity, diabetes and other insulin-resistant states Citation[2]. Recent studies have found associations between levels of plasma adiponectin and risk of myocardial infarction (MI). Data from the Stockholm Coronary Atherosclerosis Risk Factor study demonstrated that adiponectin levels were inversely associated with MI, with an odds ratio of 3.1 (95% CI: 1.3–7.6) for the lowest quartile compared with the highest quartile, after adjustment for traditional cardiovascular risk factors Citation[3]. Interactions between adiponectin, HDL-cholesterol and visceral fat were also demonstrated and a recent genetic association analysis showed genetic correlation between plasma adiponectin, HDL-cholesterol and plasma insulin, which is concordant with data indicating that insulin directly affects plasma adiponectin.
Also on the theme of adipose tissue was a presentation by Pirjo Nuutila (University of Turku, Finland), who gave an update on brown adipose tissue (BAT), which burns energy for thermogenesis. In contrast to muscle, which generates heat by reactions within its cytoplasm, BAT thermogenesis takes place in its numerous, densely-packed mitochondria containing the BAT-specific inner membrane protein uncoupling protein 1 (UCP-1). The presence of BAT has recently been identified using PET-computed tomography (PET-CT) in adults and cold activation studies have shown that these metabolically active BAT depots can be induced in response to cold temperatures and sympathetic nervous system activation. Furthermore, glucose uptake and free fatty acid synthesis increase in BAT during cold activation, and the fatty acid content decreases. These findings could provide new avenues for the future treatment of obesity and its related disorders.
Cardiovascular risk detection & prediction
High on the agenda of several sessions were novel approaches to risk detection, three modalities of which were presented by Martin Bennett (Cambridge University, UK). Intravascular ultrasound virtual histology (IVUS-VH) offers a minimally invasive and highly sensitive and specific method (95–97%), validated by postmortem studies, for determining plaque stage, constituents and vulnerability. A classification system for IVUS-VH findings can be used to predict risk based on plaque class and identification of high-risk plaques. Often employed in tandem is dual-source CT (DS-CT). Owing to its high spatial and temporal resolution, DS-CT can be used with IVUS-VH to map vessel branch points and the locations of vulnerable plaques to efficiently ascertain targets for intervention. A still less invasive approach is PET-CT, which identifies vulnerable plaques by mapping PET data onto CT images to allow accurate anatomical colocalization. Owing to the considerable uptake of the glucose-based tracer by cardiomyocytes, however, this technique does not allow imaging of the coronary vessels without the use of a specialized tracer.
Aroon Hingorani (University College London, UK) presented the current state of genetic risk prediction in CVD and Type 2 diabetes. He argued that whilst the tangible, clinical advances of the genomic revolution have not yet been as dramatic as originally anticipated, the role of genomics in CVD is nonetheless important. Shortcomings of genomic research so far include the modest phenotypic effects of common genetic variants, overfitting of data by analysis conducted in single samples, and the tendency to use statistically identified rather than functional variants as genetic instruments. Moreover, tests of prediction using single genes or gene scores that appear independently to predict CVD or diabetes risk do not effectively discriminate between individuals at higher or lower risk. The current trend for examining variants involved in known risk-modifying pathways may also leave unrelated but important variants overlooked. However, genetic data are a very powerful tool in examining etiological pathways and potential therapeutic targets in CVD, and rapidly developing technologies together with the inherent properties of genotype contribute significantly to their current utility in research. Hingorani suggested that the approach to genetic risk prediction in CVD could be focused more on determining disease susceptibility earlier in life with a view to effective risk modification, rather than the status quo of absolute prediction of events in older individuals.
Antiatherosclerotic treatments
The development of DNA-like antisense compounds has elicited a great deal of interest in recent years as a potential therapeutic treatment for CVD. Mipomersen is a second-generation antisense oligonucleotide that is designed to inhibit apolipoprotein B (apoB)100 protein synthesis through degradation of the apoB mRNA. Work in LDLR-deficient mice showed that apoB100 inhibition mitigates atherosclerotic lesion development, as well as reducing concentrations of apoB, LDL-cholesterol and total cholesterol. These findings led to studies in individuals with elevated cholesterol levels and patients with familial hypercholesterolemia that showed inhibition of apoB synthesis by mipomersen represents a novel, effective therapy to reduce LDL-cholesterol, total cholesterol, apoB and triglycerides Citation[4]. Other targets for inhibition are also being developed following promising results in animals and include proprotein convertase subtilisin/kexin type 9 (PCSK9), apoCIII and lipoprotein (a) Citation[5].
Conclusion
The main aims of the 78th European Atherosclerosis Society Congress were to improve understanding and knowledge about cardiovascular risk detection, prediction and modification. This article describes some of the emerging technologies that aim to improve risk detection and antiatherosclerotic therapeutics. A large focus of the Congress was on nonclassical risk factors and their use in predicting cardiovascular events in healthy individuals. Identifying individuals at risk of CVD earlier and more accurately, as well as developing novel therapies, may help to reduce global CVD burden and mortality.
Financial & competing interests disclosure
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
No writing assistance was utilized in the production of this manuscript.
References
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