Review articleGenome-wide association studies of late-onset cardiovascular disease
Introduction
Over the 20th century, cardiovascular diseases have replaced infectious and nutritional disease as the leading cause of death globally [1], and are leading causes of hospitalization in western countries. Such diseases typically display a late onset in the lifecourse, and are associated with both mortality and greatly impaired quality of life in the elderly.
Much effort has been invested in the development of preventive as well as novel therapeutic strategies for cardiovascular disease, notably for coronary artery disease, stroke, aortic aneurysmal disease, heart failure, atrial fibrillation and valvular disease, to facilitate healthful aging. Unfortunately, more than 90% of compounds that enter clinical trials fail to demonstrate sufficient safety and efficacy to gain regulatory approval, in large part due to limited predictive value of preclinical models of disease [2], [3]. For aging-related disease, it is particularly difficult to create animal models that faithfully recapitulate human aging, as assessment of aging in animal models over extended time is often not feasible, as in studies of the degeneration of aortic valves or development of impaired myocardial relaxation with aging.
Recently, human genetics has emerged as an unbiased tool to identify novel molecular targets in late-onset human diseases, as inherited differences in protein abundance or function can identify potential therapeutic effects that may respond favorably to pharmacological modulation [2]. Recent examples of the success of this strategy within the cardiovascular field have been the rise of PCSK9 and APOC3 inhibitors, potent cholesterol- and triglyceride-lowering medications developed after loss-of-function mutations in these genes were shown to confer lowering of cholesterol and triglycerides, respectively, and protection against coronary artery disease [4], [5].
The recent progress and reduced costs of genotyping methods with arrays and next generation resequencing technologies have facilitated studies of genetic variation on a genome-wide scale. Particular success in terms of number of identified genetic loci has been observed with studies of common variants across the entire genome, termed genome-wide association studies (GWASs) [6].
The major cardiovascular diseases with a late onset in life have not traditionally been considered to be heritable, in contrast to diseases with early onset such as familial hypercholesterolemia, long QT syndrome or hypertrophic cardiomyopathy where familial aggregation was noted as early as in the 19th century. However, in recent years population-based studies have established a modest heritable component to the major cardiovascular diseases as well as many intermediate traits, motivating molecular genetic analyses of these diseases [7], [8], [9], [10], [11], [12], [13]. Genetic methods used to study early-onset Mendelian diseases, notably linkage analysis, have largely been unsuccessful in identifying variants associated with common disease, whereas GWAS has been highly successful. Importantly, even though large sample sizes are required in GWAS to detect comparatively modest genetic effects, the identification of novel genetic associations can improve our understanding of the pathophysiology of human disease and provide novel drug targets, with potentially much stronger effects on the fundamental molecular process. Therefore, GWAS has been applied to all the major cardiovascular diseases as well as for longevity and a multitude of intermediate phenotypes for cardiovascular disease, such as plasma lipids, blood pressure and myocardial repolarization [14], [15].
Importantly, GWAS has highlighted the importance of cardiovascular disease for aging and death. For example, the genetic locus most robustly associated with longevity is located at the ApoE gene. This locus has been associated both with coronary artery disease and dementia, highlighting among other things the importance of cardiovascular health for longevity [16], [17], [18], [19]. In addition, polygenic scores based on genetic variants associated with cardiovascular disease are associated with longevity (Smith JG, unpublished).
In this overview, we outline the central concepts of genome-wide association studies, describe findings from GWAS of aging-related cardiovascular phenotypes and diseases, and close with a discussion about the next steps to drawing biologic insights and potential drug targets from identified genetic loci. Most important to the cardiovascular disease spectrum at the population-level are atherosclerotic changes in the coronary and carotid circulations, as well as myocardial disease including heart failure and cardiac arrhythmia, each of which is discussed in a separate section. The clinical utility of genetic loci established as determinants of cardiovascular disease is currently limited due to comparatively modest effects and the multifactorial nature of these diseases, and is briefly discussed in a final section.
Section snippets
Genome-wide association study (GWAS): a primer
The simple principle of GWAS entails the genotyping of hundreds of thousands of genetic variants and comparison of allele distributions between cases with a disease and controls without the disease [20]. Such studies became feasible with the development of highly-multiplexed genotyping arrays, sequencing of the human genome, and the recognition that the most common form of genetic variation is single nucleotide polymorphisms (SNPs) which are relatively correlated over sizable genetic distances
Vascular traits
With increasing age, arterial walls typically undergo gradual stiffening, thickening, accumulation of atherosclerotic plaques and deposition of calcium. Such structural changes as vascular thickness, calcification, plaque composition and pulse wave velocity can be measured using ultrasound or computed tomography. Functional assessment of vasodilator capacity can be assessed by flow-mediated dilatation. Several such markers of cardiovascular aging have been examined in GWAS.
For pulse wave
Coronary artery disease
Vascular degeneration in the coronary vasculature is the underlying pathophysiological process for the leading cause of death globally, myocardial infarction. Efforts to identify genetic regions associated with this disease have therefore been extensive.
To date, meta-analysis of GWASs of coronary disease including more than 60,000 cases and 130,000 controls have identified 46 genetic loci (Table 2) [18], [48]. Of these, a total of 16 loci are also consistently associated with known risk factors
Ischemic stroke and carotid vascular disease
Ischemic stroke is a highly complex phenotype, with multiple contributing disease processes. The most successful GWASs for this disease have therefore focused on distinct etiologic subtypes, including stroke of presumed cardioembolic origin, stroke with carotid artery disease and intracranial small-vessel disease (Table 3).
The most common identifiable cause of stroke is considered to be atrial fibrillation. It is therefore not surprising that genetic variants on chromosomes 4q25 and 16q22 that
Myocardial phenotypes related to the sarcomere
The myocardium also undergoes critical aging-related changes, including impaired cardiac conduction, prolonged repolarization and hypertrophy, leading to impaired relaxation during diastolic filling. These pathophysiologic processes lead respectively to bradycardia, arrhythmias, and heart failure. GWAS has also been performed for such traits as measured by electrocardiography or echocardiography in the general population, and are summarized elsewhere (Smith JG et al, submitted).
The ultimate
Cardiac phenotypes related to rhythm
The most common arrhythmias are atrial fibrillation (AF) and ventricular tachycardia and fibrillation, the latter two often manifesting as sudden cardiac arrest and death. AF can be easily identified from the EKG upon presentation to a hospital, whereas ventricular arrhythmia typically lead to sudden death if not successfully resuscitated and so are much more difficult to ascertain in genetic studies. GWAS has identified a total of 14 loci for AF [106], [107], [108], [109], [110], [111], [112]
Cardiac valvular phenotypes
With increasing age, cardiac valves can become increasingly dysfunctional and develop both stenosis and regurgitation. Calcification of the aortic valve cusps, a precursor to aortic stenosis, can be seen in nearly 30% of individuals at 70 years [123], more commonly than calcification of the mitral valve leaflets. In a recent GWAS of aortic and mitral calcification including 6942 individuals from the general population, a genetic variant in the LPA gene encoding lipoprotein(a) was found to be
Functional annotation: from genetic locus to biological mechanism
Inherent to most methods of genetic mapping approaches such as GWAS is the limitation that they can identify genomic loci through correlation among neighboring variants, but resolution to identify the causal variant and gene can be limited. Although loci may inform risk prediction and explain heritability, novel biologic insights can only be obtained by identifying the causal variant, gene and underlying mechanism. How can this be achieved?
A set of expert recommendations for investigating
Clinical implications
Genetic studies can be a powerful tool to identify and prioritize potential drug targets. In addition, the robust identification of genetic sequence variants associated with human traits may set the stage for genetic disease prediction and individually tailored therapy by incorporating genetic information, often termed ‘precision medicine’. Large governmental investments have been announced to facilitate such developments in the United States and elsewhere through resequencing of whole genomes
Conclusions
Over the past 10 years, GWASs have been highly successful in identifying genetic regions associated with many common diseases, including aging-related cardiovascular diseases. However, much additional work is required to understand the mechanisms linking these loci to disease. Major obstacles for mechanistic studies include both experimental, bioinformatic and statistical issues. This work is therefore likely to require collaboration across traditional scientific boundaries, but offers great
Disclosures
The authors have no conflicts of interest to report.
Funding
J.G.S. was supported by the Swedish Research Council (2014-2469), the Swedish Heart-Lung Foundation (20130534), the Crafoord Foundation, the Swedish Heart Association, the Märta Winkler Foundation, Skåne University Hospital and the Swedish National Health Service. C.N.-C. was supported by the National Institute of Health (R01HL113933, R01HL124262).
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