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Common Heart Failure: Clinical Considerations of Heritable Factors

Reporter: Aviva Lev-Ari, PhD, RN

Clinical Considerations of Heritable Factors in Common Heart Failure

Thomas P. Cappola, MD, ScM and Gerald W. Dorn II, MD

Author Affiliations

From the Department of Medicine, University of Pennsylvania, Philadelphia, PA (T.P.C.), and Center for Pharmacogenomics, Washington University School of Medicine, St Louis, MO (G.W.D.II.).

Correspondence to Gerald W. Dorn II, MD, Center for Pharmacogenomics, Washington University, 660 S Euclid Ave, Campus Box 8220, St Louis, MO 63110. E-mail gdorn@dom.wustl.edu

Introduction

Heart failure is a common condition responsible for at least 290 000 deaths each year in the United States alone.1 A small minority of heart failure cases are attributed to Mendelian or familial cardiomyopathies. The majority of systolic heart failure cases are not familial but represent the end result of 1 or many conditions that primarily injure the myocardium sufficiently to diminish cardiac output in the absence of compensatory mechanisms. Paradoxically, because they also injure the myocardium, it is the chronic actions of the compensatory mechanisms that in many instances contribute to the progression from simple cardiac injury to dilated cardiomyopathy and overt heart failure. Thus, the epidemiology of common heart failure appears to be just as sporadic as its major antecedent conditions (atherosclerosis, diabetes, hypertension, and viral myocarditis).

Familial trends in preclinical cardiac remodeling2 and risk of developing heart failure3reveal an important role for genetic modifiers in addition to clinical and environmental factors. Candidate gene studies performed over the past 10 years have identified a few polymorphic gene variants that modify risk or progression of common heart failure.4 Whole-genome sequencing will lead to the discovery of other genetic modifiers that were not candidates.5 The imminent availability of individual whole-genome sequences at a cost competitive with available genetic tests for familial cardiomyopathy will no doubt further expand the list of putative genetic heart failure modifiers. Heart failure risk alleles along with traditional clinical factors will need to be considered by clinical cardiologists in their design of optimal disease surveillance and prevention programs and in individually tailoring heart failure management.

The use of individual genetic make-up is likely to have the earliest and greatest impact on managing patients with heart failure by tailoring available pharmacotherapeutics to optimize patient response and minimize adverse effects (ie, the area of pharmacogenetics). Modern heart failure management has been derived and directed by the results of large, randomized, multicenter clinical trials. When standard therapies are applied according to the selection criteria used in these trials, they prolong average survival across affected populations or decrease the incidence of heart failure in populations at risk.6 For this reason, standardized treatment guidelines prescribe heart failure therapies according to trial designs, aiming for the same target doses and general treatment approaches,7 and largely ignore individual characteristics. In this article, we review established and emerging knowledge of genetic influence on common heart failure and try to anticipate how these genetic factors may be best used to eschew the cookie-cutter approach to heart failure management and move toward implementing a personalized medicine approach for the treatment and prevention of this important and prevalent disease.

The Concept of Genotype-Directed Personal Medical Management in Heart Failure

Variation in clinical heart failure progression and therapeutic response (either benefits or side effects) supports the need for a more individualized approach to disease management. On the basis of clinical stratification (eg, by etiology of heart failure as ischemic versus nonischemic, functional status, comorbid disease), physicians try to match each patient’s specific heart failure syndrome with a therapeutic regime devised to provide the most benefit. Standard heart failure pharmacotherapy currently comprises a minimum of 3 medications (angiotensin-converting enzyme [ACE] inhibitors, β-blockers, and aldosterone antagonists), with consideration of additional medications (hydralazine/isosorbide, angiotensin receptor blockers) and diuretics. The recommended target dosages for these agents, derived from their respective clinical trials, is rarely achieved,8 partly because of untoward clinical side effects such as low blood pressure or renal dysfunction. Accordingly, the published guidelines most often are applied in each individual patient using ad hoc approaches derived from personal experience and the “art of medicine.”

Technological advances in human genomics promise a different approach and are bringing cardiology into an era of clinically applied pharmacogenetics9 (whether we want to or not). As sequencing costs decline, it is not hard to envision that patients will present having had their entire genome already sequenced. The imperative to apply genome information in clinical settings will increase, as demonstrated by recent proof-of-concept studies.10 Our field seems poorly prepared for this type of evolution in care; Roden et al9 identified 3 major barriers: First is the absence of rapidly available genotype information in the clinical workflow. This barrier is being overcome with whole-genome sequencing, which (with proper analysis) promises a permanent and largely immutable genetic roadmap for individual disease risk and drug response at a cost comparable to many other clinical tests.11 Second, we must have the knowledge to properly apply information on genetic variants for the diseases we are managing and the drugs we are using. As we describe, this knowledge is accumulating for heart failure and for other cardiac conditions, and the rate at which we are gaining additional information and developing further expertise appears to be accelerating.

The third and perhaps most formidable barrier is the lack of clinical evidence showing how real-time application of genetic information can best benefit patients. As has been broadly communicated to the medical community and lay public, common functional gene variants in CYP2C19 can impair the transformation of clopidogrel into its active metabolite, leading to increased risk of stent thrombosis after percutaneous coronary intervention.12 The relevant question thus becomes the following: If physicians have this information at the time of clinical care and reacted by adjusting clopidogrel dose or substituting prasugrel, which is unaffected by CYP2C19genotype,13 would there be any improvement in clinical outcome? It is also important to consider whether any observed benefits justify the additional costs of genetic testing and for the alternate drug. Studies are currently examining these questions, and similar clinical trials will prospectively examine whether a genotype-guided strategy of warfarin dosing will be superior to the standard genotype-blinded approach in reaching target anticoagulation goals. At this time, there are no similar prospective, randomized, blinded trials of genotype-guided care for common heart failure.

Emerging Variants

The variants described here are established, but new ones are emerging. Although findings in heart failure genome-wide association studies have been limited, we can expect additional common heart failure variants to emerge as sample sizes increase.65 The CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium published a genome-wide association study of incident heart failure that tested for associations between >2.4 million HapMap-imputed polymorphisms in >20 000 subjects.7 They identified 2 loci associated with heart failure, rs10519210 (15q22, containing USP3 encoding a ubiquitin-specific protease) in subjects of European ancestry and rs11172782 (12q14, containing LRIG3encoding a leucine-rich, immunoglobulin-like domain-containing protein of uncertain function) in subjects of African ancestry.66 In a companion study using the same population and genotyping results, mortality analysis of the subgroup of individuals who developed heart failure implicated an intronic SNP in CMTM7 (CKLF-like MARVEL transmembrane domain-containing 7).67 These genetic associations require independent replication and further study to identify the underlying biological mechanisms.

A recently published genome-wide association study by a European consortium on dilated cardiomyopathy identified common variants in BAG3 (BCL2-associated athanogene 3) associated with heart failure57 and identified rare BAG3 missense and truncation mutations that segregate with familial cardiomyopathy. These findings were consistent with an earlier exome-sequencing study that identifiedBAG3 as a familial dilated cardiomyopathy gene and showed recapitulation of cardiomyopathy with BAG3 morpholino knockdown in zebra fish.68 Together, these studies convincingly support variation in BAG3 as a genetic risk factor of cardiomyopathy and heart failure. It is noteworthy that both common and rare functional variations were identified at this locus. A unifying hypothesis for these findings, which needs to be formally tested, is that common variants in BAG3 serve as proxies for rare functional BAG3 mutations with large effects. In this situation, the underlying genetic lesion is a rare variant with a large functional effect. This has recently been described for common variants in MYH6 that correlated with rare functional MYH6 variants to cause sick sinus syndrome.69 It is premature to speculate on the clinical applications of these newer findings.

Moving Knowledge to Practice

A small number of genomic variants have been identified that modify heart failure by affecting well-understood physiological systems. The principal barrier preventing their adoption in practice may be lack of evidence showing how application of this information can best be used for clinical benefit. Trials testing genotype targeting of antiplatelet therapy and anticoagulation will be completed in the coming years. The findings from these studies will likely determine the level of enthusiasm for conducting genotype-guided trials of β-blockers and RAAS antagonists in heart failure. Given that the lifetime risk of heart failure in the United States is estimated at 1 in 5, even a small favorable effect on heart failure prevention or outcome through use of genome-guided therapy has the potential for a large public health impact. We therefore believe that a near-term goal should be to conduct pharmacogenomic trials in heart failure based on our current understanding of heart failure variants.

Looking ahead, unbiased approaches will continue to reveal a large number heart failure-modifying variants (both common and rare). Based on experience in other complex phenotypes, such has height70 and plasma lipid levels,71 the underlying genetic mechanisms for many new heart failure variants will be completely unknown, and their sheer number will preclude detailed experimentation using murine models to figure them out. Leveraging these variants for clinical application is a challenge that we will be forced to confront.

As our ability to identify rare, disease-causing variants improves through personal genome sequencing, we will be faced with the additional problem of how best to estimate the disease risk conferred by a sequence variant for which there has been no biological validation. In probabilistic terms, because there are 3 billion nucleotides in the human genome and over twice that many humans on the planet, it is likely that a nucleotide substitution for every position is represented in someone. Obviously, it will be impossible to recombinantly express and functionally characterize every DNA variant that is going to be implicated in heart failure. Bioinformatics filters have been used to try and separate functionally significant from insignificant variants based on the likelihood of changing transcript expression or protein function. These tools are limited but will improve if we tailor their results to the known characteristics of each gene product. For example, current approaches to categorize amino acid substitutions as conservative or nonconservative based only on charge or side chains can be improved by molecular modeling that incorporates protein-specific structure-function information. This approach has been used to estimate the pathogenicity of myosin heavy chain (MHC) mutations in an effort to determine which mutations are likely to cause familial cardiomyopathy when linkage analysis is not feasible.72 In concept, this approach can be applied to any protein for which structure-function activities have been finely mapped to distinct domains.

A promising extension of this approach may be to use evolutionary genetics to infer disease causality. Again, using the MHC genes as examples, human genome data show a greater prevalence of nonsynonymous gene variants in MYH6, which encodes the minor cardiac α-MHC isoform, compared with the adjacent MYH7, which encodes the major β-MHC isoform. This disparity suggests a greater tolerance for protein changes in the α-MHC isoform and negative selection against these in β-MHC. We can infer, therefore, that amino acid changes are more likely to have adverse impacts in MYH7-encoded β-MHC. If this paradigm survives prospective testing, then the forthcoming explosion of individual genetic data not only will present a massive problem in interpretation, but also will provide the genetic information by which analyses of rare sequence variants across large unaffected populations can help to differentiate the tolerable variants from those that are more likely to alter disease risk.

Each Reference above is found in:

http://circgenetics.ahajournals.org/content/4/6/701.full

SOURCE: 

Circulation: Cardiovascular Genetics.2011; 4: 701-709

doi: 10.1161/ CIRCGENETICS.110.959379