Cardiovascular Genomics


Dr. Shu-Fen Wung, 1305 North Martin Avenue, Tucson, AZ 85721–0203. E-mail:


Purpose: This article provides an update on cardiovascular genomics using three clinically relevant exemplars, including myocardial infarction (MI) and coronary artery disease (CAD), stroke, and sudden cardiac death (SCD).

Organizational Construct: Recent advances in cardiovascular genomic research, testing, and clinical implications are presented.

Methods: Genomic nurse experts reviewed and summarized recent salient literature to provide updates on three selected cardiovascular genomic conditions.

Findings: Research is ongoing to discover comprehensive genetic markers contributing to many common forms of cardiovascular disease (CVD), including MI and stroke. However, genomic technologies are increasingly being used clinically, particularly in patients with long QT syndrome (LQTS) or hypertrophic cardiomyopathy (HCM) who are at risk for SCD.

Conclusions: Currently, there are no clinically recommended genetic tests for many common forms of CVD even though direct-to-consumer genetic tests are being marketed to healthcare providers and the general public. On the other hand, genetic testing for patients with certain single gene conditions, including channelopathies (e.g., LQTS) and cardiomyopathies (e.g., HCM), is recommended clinically.

Clinical Relevance: Nurses play a pivotal role in cardiogenetics and are actively engaged in direct clinical care of patients and families with a wide variety of heritable conditions. It is important for nurses to understand current development of cardiovascular genomics and be prepared to translate the new genomic knowledge into practice.

Cardiovascular disease (CVD) involving the heart, brain, and peripheral circulation is the leading cause of death worldwide. In 2008, approximately 17 million people died from CVDs, representing 30% of all deaths (World Health Organization, 2012). Genetics play a role in conferring risk for nearly all CVD disorders. Enormous effort has been undertaken to understand genes responsible for or protected from CVD. Even though genomics of many common forms of CVD is a work in progress, the most common forms of CVD are believed to be multifactorial genetic conditions, involving multiple genes or environmental factors. On the other hand, genetic testing for patients with certain single gene cardiovascular conditions is recommended clinically. In this overview, we provide the state-of-the-art knowledge on CVD genomics, using three exemplars, including myocardial infarction (MI) and coronary artery disease (CAD), stroke, and sudden cardiac death (SCD).

Myocardial Infarction and Coronary Artery Disease

There is substantial evidence that CAD and its clinical manifestations, such as MI, are heritable traits. As supported by several large prospective studies, a family history of a parent or a sibling is a risk factor for CAD (Hawe, Talmud, Miller, Humphries, & Second Northwick Park Heart Study, 2003; Murabito et al., 2005; Myers, Kiely, Cupples, & Kannel, 1990). About 15% of all MIs are attributable to familial factors, independent of other traditional risk factors (Andresdottir, Sigurdsson, Sigvaldason, Gudnason, & Reykjavik Cohort Study, 2002).

Since 1990, there has been an explosion of studies examining genetic markers conferring a risk for MI/CAD. These include genetic linkage analyses of families, candidate gene, and genome-wide association studies (GWAS). Several chromosomal regions harboring MI/CAD genes have been identified through family-based linkage analyses (Broeckel et al., 2002; Samani et al., 2005). However, identification of the underlying mutations is difficult, and when identified, mutations affected only a single family or had no functional relevance in other studies (Lieb et al., 2008). Worth mentioning is the linkage analysis performed by the deCODE group (Helgadottir et al., 2004) finding a peak at chromosomal region 13q12–13 in 296 Icelandic families enrolled for a history of MI. These researchers later found arachidonate 5-lipoxygenase-activating protein (ALOX5AP) gene associated with MI. ALOX5AP genetic variants have been linked to heightened inflammation, an undisputed cause of MI/CAD. Subsequently, these investigators reported that ALOX5AP was associated with CAD in British and stroke in Icelandic and Scottish populations (Helgadottir et al., 2005). We also found an association between an at-risk allele of the ALOX5AP gene and in a small sample of patients with acute coronary syndrome in the United States (Wung & Aouizerat, 2008).

The candidate gene approach involves analyzing genes representing different pathways in the pathogenesis of MI/CAD. Since 1992, associations between numerous (> 150) candidate genes and MI/CAD have been analyzed. Among the vast candidate genes studied, both positive and negative associations between risk alleles and MI/CAD were found for nearly all genes, but reproducible associations are few (Yamada, Ichihara, & Nishida, 2008). Only limited genes affecting low-density-lipoprotein cholesterol (LDL-C), such as proprotein convertase subtilisin/kexin type 9 (PCSK9) and apolipoprotein E (APO E), have been shown to be associate with MI/CAD (Schunkert, Erdmann, & Samani, 2010).

The GWAS approach genotypes the complete genome in many individuals. The GWAS is free of any hypothesis and thus has the potential to identify disease-associated markers in unknown genes. In 2007, three landmark GWAS identified a locus on chromosome 9p21.3 associated with MI/CAD (Helgadottir et al., 2007; McPherson et al., 2007; Samani et al., 2007). Since then, several studies have confirmed the role of the 9p21.3 locus on risk for MI/CAD, making it the strongest and most replicated genetic effect on MI/CAD risk known today (Schunkert et al., 2008). This 9p21 locus only harbors a long noncoding RNA called ANRIL (for antisense noncoding RNA in the INK4 locus). Researchers are actively investigating the role of this noncoding RNA in atherosclerosis.

Most recently, a global consortium (CARDIoGRAM) analyzed GWAS data from more than 20,000 CAD cases and 60,000 controls and discovered 13 novel as well as confirmed 10 previously reported chromosomal loci associated with CAD (Schunkert et al., 2011). The majority of these established and novel loci are not associated with traditional CAD risk factors and they reside in regions not previously suspected in the pathogenesis of CAD, suggesting that most genetic markers may act though novel pathways (Schunkert et al., 2011). However, these 23 established and novel loci are only able to explain a limited fraction of CAD heritability. This indicates that many other variants contributing to risk for CAD are yet unknown.

In sum, research is ongoing to discover comprehensive genetic markers contributing to MI/CAD pathogenicity. Several commercial CVD genotyping panels, usually limited to a small subset of genes or single nucleotide polymorphisms (SNPs), are being marketed to healthcare providers and general public. The accuracy of these limited genotyping panels for MI/CAD risk profiling is still yet to be determined. It is important for nurses to understand current developments of MI/CAD genomics so that accurate information can be provided to patients and families interested in genetic testing.


Stroke is currently the fourth leading cause of death and a major cause of adult disability. Annually, nearly 800,000 people experience a stroke in the United States. The majority of strokes (87%) are ischemic strokes (Roger et al., 2011). Ischemic stroke shares risk factors with MI/CAD, such as hypertension, dyslipidemia, diabetes, obesity, and inflammation. Another risk factor is a family history of stroke or MI, suggesting a genetic influence. Data from the Framingham study showed that parental histories of stroke (paternal relative risk [RR]= 2.4; maternal RR = 1.4) were associated with a higher risk for stroke in offspring (Callis, Jensen, Weck, & Willis, 2010). Twins studies also showed a nearly fivefold increase in stroke risk among monozygotic as compared with dizygotic twins (Brass, Isaacsohn, Merikangas, & Robinette, 1992).

Numerous genes have been associated with stroke. Some of these genes include apolipoprotein E, intracellular adhesion molecule 1, and others (Gallek & Ritter, 2011). The 9p21 locus, associated with MI/CAD, is also related to ischemic stroke, as reported by two GWAS (Gschwendtner et al., 2009; Olsson, Jood, Blomstrand, & Jern, 2011).

There are ethnic differences in risk for stroke. The estimated prevalence of stroke among African Americans is 3.8%, followed by Caucasians at 2.5%, and Asians at 1.3% (Pleis, Ward, & Lucas, 2010). The majority of genetic research in stroke has been performed on Caucasians from North America and Europe. Some studies have been replicated in other populations, such as Chinese or Japanese. Two examples of markers that were replicated in several ethnic groups include the protein kinase C eta gene (Kubo et al., 2007; Wu et al., 2009) and the SNP rs11052413, which is not associated with a gene (Ding et al., 2010; Matarin et al., 2007).

Numerous rare genetic disorders are associated with stroke, including mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes (MELSE); Fabry disease; and others. When there is a suspicion of these rare genetic disorders, testing can be ordered by healthcare professionals. For example, MELSE is characterized by normal early development but with stroke-like episodes before 40 years of age along with presentations, such as seizure and dementia. These stroke-like episodes do not involve a defined vascular distribution and occur without an embolic source or stenotic lesion. Diagnosis of MELSE is confirmed by genetic studies, such as mitochondrial DNA sequencing.

Genetic research in stroke is ever evolving. New technologies such as exome sequencing (sequencing of the exons only) are now being used to search for new variants. Although there are no clinically recommended genetic tests, numerous direct-to-consumer genetic tests claim to evaluate stroke risk. Risk estimates provided across these companies may be inconsistent due to the use of different SNPs (e.g., deCODE uses 2 SNPs associated with atrial fibrillation; uVGene genotypes an inflammatory lymphotoxin A gene) and different algorithms to predict risk. Nurses need to understand current progress on stroke genomics in order to provide accurate information to patients and family.

Sudden Cardiac Death

SCD accounts for an estimated 1 million deaths, making arrhythmias one of the most significant causes of death in the world (Ackerman et al., 2011). The genetic etiology of many of these cardiac monogenetic conditions is now known. Inherited cardiac diseases can be classified into two broad categories: the primary electrical diseases or channelopathies and the inherited cardiomyopathies. Many mutations have been associated with long QT syndrome (LQTS), short QT syndrome (SQTS), Brugada syndrome, catecholaminergic polymorphic ventricular tachycardia (CPVT), and arrhythmogenic right ventricular cardiomyopathy (ARVC; Ackerman et al., 2011). Most of these disorders are inherited as autosomal dominant traits. Therefore, an individual carrying a disease-causing mutation has a 50% chance of transmitting the mutation to his or her children. The diagnosis is based on clinical history, electrocardiographic (ECG) findings, and a complete three-generation family history, and is confirmed by genetic testing. Genetic testing for many cardiac channelopathies and cardiomyopathies (i.e., LQTS, SQTS, Brugada syndrome, CPVT, ARVD, hypertrophic cardiomyopathy [HCM], dialated cardiomyopathy) is commercially available and can be ordered by a licensed practitioner.

Cardiac channelopathies, such as LQTS, Brugada syndrome, CPVT, and ARVD, may be identified by the presence of characteristic ECG abnormalities, unique to each of the channelopathies (Ackerman et al., 2011). However, these characteristics are not always present in genetic carriers because some of these disorders can have low or incomplete penetrance and may or may not be associated with ECG abnormalities (Zipes et al., 2006). Penetrance is when an individual harboring a disease-causing genotype develops the associated disease ( Incomplete penetrance occurs when an individual with a disease-causing genotype does not manifest features of the disorder ( There are multiple causes of incomplete penetrance, including absence of environmental or genetic cofactors, epigenetic effects, age and sex-specific effects, or age-related expression differences.

Genetic testing may be the key to confirming the etiology for unexplained symptoms such as syncope, ventricular arrhythmias, or SCD within a family (Ackerman et al., 2011). Genetic testing in an affected patient with a cardiac channelopathy can reveal disease-causing genetic mutations, thus confirming the clinical diagnosis. This information can also assist in the identification of at-risk family members who may benefit from cardiac surveillance and treatment and can also be used for prenatal counseling and diagnosis.

For example, LQTS occurs in all ethnicities and has an estimated prevalence of at least 1 in 3,000 (Lehnart et al., 2007). SCD is often the first presentation in 10% to 15% of fatal LQTS events (Priori et al., 2003). LQTS has genetic causes in at least 75% of individuals diagnosed with LQTS, including the possibility of a mutation in one of 12 associated genes (Ackerman et al., 2011). Patients with an inherited form of LQTS often have a history of syncope (loss of consciousness) in the absence of other causes, such as QT-prolonging medications, cardiomyopathies, myocardial ischemia, or electrolyte imbalances. The circumstances under which syncope occurs may further suggest a specific subtype of LQTS. Increased risk of cardiac ventricular arrhythmic events is triggered by exercise in patients with LQT1 and auditory stimulation such as a loud sudden noise in patients with LQT2. Patients with LQT3 usually have arrhythmias during rest or sleep when the heart rate is slow. Patients with a history of aborted cardiac arrest or life-threatening ventricular arrhythmias are considered high risk (> 10% risk) for a subsequent life-threatening cardiac event (Priori et al., 2003). Further workup and possible genetic testing is warranted in patients with a history of syncope within the past 2 years, especially if recurrent, or a prolongation of corrected QT (QTc) is noted on the ECG (Ackerman et al., 2011). Affected individuals without a history of syncope and with QTc duration ≤ 0.50 s can be assigned a low risk (< 1%) for having a future event (Priori et al., 2003). However, this risk stratification represents a simplified approach, because risk factors in LQTS are time dependent and age specific. For example, men with LQTS tend to have their first cardiac event at an earlier age than women (Priori et al., 2003). This is believed to be due to cardioprotective effects of estrogen in women.

Depending on the subtype of LQTS, medical therapy may include beta-blockers, an implantable cardioverter defibrillator (ICD), or lifestyle modification to avoid triggers such as certain forms of exercise (i.e., swimming [LQT1]), sudden auditory triggers (LQT2), and avoidance of QT-prolonging drugs, in all subtypes. Knowledge of the LQTS genotype may be used to tailor the management plan. For example, patients with LQT3 benefit less from beta-blockers and more from the placement of an ICD to prevent SCD (Lehnart et al., 2007).

Recently, the Heart Rhythm Society and the European Heart Rhythm Association developed consensus recommendations on genetic testing for channelopathies and cardiomyopathies (Ackerman et al., 2011). The expert panel recommended genetic counseling for all patients and relatives with channelopathies and cardiomyopathies. Genetic counseling should include discussion of the risks, benefits, and options available for clinical or genetic testing. Treatment decisions, however, should not rely solely on an individual's genetic test result but rather comprehensive clinical evaluation and family history. It can be useful for genetic counseling, testing and the interpretation of results to be performed in centers experienced in genetic evaluation and family-based approach, and management of heritable arrhythmia syndromes and cardiomyopathies (Tester & Ackerman, 2011).

HCM is the most common monogenic CVD, with a prevalence of 1 in 500 in the general population (Gersh et al., 2011). HCM is a disorder in which myocytes increase in size (hypertrophy) and the increased myocardial thickness reduces the heart's ability to pump blood efficiently, which can lead to heart failure or cardiac arrhythmias. HCM is a genetically heterogeneous condition caused by mutations in a variety of genes encoding proteins of the cardiac sarcomere (Gersh et al., 2011). To date, in 40% to 60% of HCM cases, 18 disease-causing genes and greater than 500 mutations have been identified (Gollob et al., 2011). Many of these mutations are unique to individual families. Mutations in ß-myosin heavy chain (MYH7) and myosin-building protein C (MYBPC3) genes account for the majority of identified mutations (Gollob et al., 2011).

Genetic testing is commercially available and can be considered for patients who manifest clinical findings that may be due to an underlying HCM and for asymptomatic patients within a family with a known mutation. Once a mutation is identified in the index HCM case (proband), screening of family members can be done by targeting the specific mutation. Testing should be performed first on the family member who has a known mutation or is symptomatic. The three possible outcomes of genetic testing are positive, negative, and variant of unknown clinical significance. In the case of HCM in which a known mutation has been identified within a family, a negative test result provides reassurance that the specific disease-causing mutation is not present. However, in other inherited cardiogenetic syndromes, individuals who test negative may not be truly negative for an inherited syndrome, commercially available testing might not test for a particular mutation, or in other cases the mutation is yet to be discovered.

Genetic testing in the family can lead to identification of at-risk members who are clinically asymptomatic. It is recommended that family members who test positive for the familial mutation receive echocardiographic surveillance per established guidelines (Gersh et al., 2011). Alternatively, a negative genetic test result for the familial mutation may obviate the need for repeated cardiac examinations.

Racial or Ethnic and Gender Differences in Cardiovascular Disease

Health disparities observed between racial, ethnic, and gender groups may have some basis in genetic variations related to CVD and its risk factors (Taylor, 2009; Taylor, Maddox, & Wu, 2009). The National Health and Nutrition surveys have shown that African Americans were 8.4% less likely to achieve blood pressure control in comparison to their Caucasian counterparts (McWilliams, Meara, Zaslavsky, & Ayanian, 2009). Ruiz-Narvaez, Bare, Arellano, Catanese, and Campos (2010) found that for every 10% increase in West African ancestry there was a 29% increase in MI and a 30% increase risk for hypertension, and for every 10% increase in Native American ancestry there was a 14% increase in risk for metabolic syndrome and a 20% increase risk for impaired fasting glucose. The admixture within this cohort in the Central Valley of Costa Rica exemplifies the high variability of ethnic and racial differences relating to risk for CVD (Ruiz-Narvaez et al., 2010). See Table 1 for an illustration of gender differences for CVD genetic risk in the following ethnic or racial groups: African, European, Asian, Native American, and Hispanic.

Table 1.  Racial or Ethnic and Gender Differences in Genomics of Cardiovascular Disease
African AmericanWomenATPase, H+ transporting, lysosomal, 56/58-KD, V1 subunit B, isoform 1 ATP6V1B1_rs2266917↑ DBP Taylor et al. (2008)
  1. Note. DBP = diastolic blood pressure; SBP = systolic blood pressure; BMI = body mass index; CAC = coronary artery calcification; CAD = coronary artery disease; MI = myocardial infarction; LDL = low density lipoprotein.

 WomenMatrix metalloproteinase 3 MMP3_rs679620↑ DBP and BMI Taylor et al. (2008)
 WomenSolute carrier family 4 (sodium bicarbonate cotransporter), member 5 SLC4A5_rs10177833 SLC4A5_rs8179526↑ SBP ↑ SBP Taylor et al. (2012) Taylor et al. (2009)
 Men and womenSolute carrier family 4 (sodium bicarbonate cotransporter), member 5 SCN5A_rs3922844↑ prolonged PR interval on electrocardiogram Smith et al. (2011)
  Sodium channel, voltage-gated, type X, alpha subunit SCN10A_rs6798015  
   MEIS1, mouse, homolog of, 1 MEIS1_rs10865355  
  T-box 5 TBX5_rs7312625  
 Men and womenScavenger receptor class B, member 1 SCARB1_10846733↑ CAC, common and internal carotid intimal-medial thickness Benton et al. (2007); Tsai et al. (2008)
AsianMen and womenSolute carrier family 4 (sodium bicarbonate cotransporter), member 5 SCN5A_rs3922844↑ prolonged PR interval Smith et al. (2011)
  Sodium channel, voltage-gated, type X, alpha subunit SCN10A_rs6798015  
   MEIS1, mouse, homolog of, 1 MEIS1_rs10865355  
  T-box 5 TBX5_rs7312625  
 (Chinese) men and womenScavenger receptor class B, member 1 SCARB1_10846733↑ CAC, common and internal carotid intimal-medial thickness Benton et al., (2007); Tsai et al. (2008)
 (Chinese) men and women BRCA1-associated protein BRAP_rs11066001↑ CAD & diabetes Hsu et al. (2011)
 (Chinese) menPhosphodiesterase 4D, cAMP-specific PDE4D_rs702553↑ intimal-medial thickness Liao et al. (2010)
 (Chinese) men and womenNitric oxide synthase 3 ENOS-G894T↑ essential HTN Men, Tang, Lin, Li, and Zhan (2011)
 (Japanese) men and women 9p21_rs1333049 1q41_rs17465637↑ MI Hiura et al. (2008)
EuropeanMen and womenSolute carrier family 4 (sodium bicarbonate cotransporter), member 5 SCN5A_rs3922844↑ prolonged PR interval Smith et al. (2011)
  Sodium channel, voltage-gated, type X, alpha subunit SCN10A_rs6798015  
   MEIS1, mouse, homolog of, 1 MEIS1_rs10865355  
  T-box 5 TBX5_rs7312625  
 Men and womenScavenger receptor class B, member 1 SCARB1_10846733↑ CAC, common and internal carotid intimal-medial thickness Benton et al., (2007); Tsai et al. (2008)
 Men and women 9p21_rs1333049↑ MI & CADCAD Consortium et al. (2009); Saleheen et al. (2010)
Hispanic(Mexican) womenFocadhesin FOCAD_rs7875153↑ heart rate Melton et al. (2010)
 (Dominican) womenLDL, oxidized, receptor 1 OLR1_rs11053646↑ carotid plaque Wang et al. (2011)
 (Dominican) men and womenSry-box 6 SOX6_rs16933090↑ carotid plaque Dong et al. (2010)
 Men and womenScavenger receptor class B, member 1 SCARB1_10846733↑ CAC, common and internal carotid intimal-medial thickness Benton et al., (2007); Tsai et al. (2008)
Native AmericanWomenFocadhesin FOCAD_rs7875153↑ heart rate Melton et al. (2010)

The risk assessment of distinct individuals is even more complex than grouping within gender or ethnicity or race and includes the synergistic effects of genetics and the environment on CVD risks and outcomes. However, understanding the genetic mechanisms for CVD risk among gender and ethnic or racial groupings allows for further insight, improved prevention, and treatment strategies in populations at risk. Knowledge of these genetic risks based on gender and ethnic or racial differences enhances patient and provider choice in treatment regimens, leading to improved cardiovascular health outcomes. Future work is essential to comprehend a genomic basis that explains diverse patient presentations related to genomic and environmental risks for CVD-related morbidity and mortality, particularly as it pertains to gender and race disparities.

Nursing Implications

Nurses play a pivotal role in cardiogenetics and are actively engaged in direct clinical care of patients and families with a wide variety of heritable conditions. Over the past 10 years, genetically trained nurses have been instrumental in recognizing genetic conditions, providing clinical care, ordering and interpreting genetic testing, and providing counseling, education, and support to patients and families (Hickey, Sciacca, & McCarthy, 2012). In the case of MI/CAD and stroke, although no comprehensive genetic testing is yet available to accurately profile risk for disease, having current genomics knowledge is helpful when counseling individuals interested in commercially available genetic testing.

The avoidance of medications known to prolong the QT interval ( is one area where nurses can provide counseling to patients and families with or at risk for LQTS. In the case of LQTS, genetically trained nurses are aware of the characteristic ECG findings and triggers related to each LQTS subtype and management options. Educational efforts undertaken by nurses include counseling on the avoidance of potential arrhythmic triggers and explaining the rationale of prescribed therapies such as beta-blockers or ICD therapy in protection against SCD. In those living with HCM, nurses are actively engaged in symptom evaluation and the response to prescribed management options.

Nurse scientists are actively engaged in genetic research as leaders and members of diverse, global interdisciplinary teams. Nurse scientists can lead the collaborative team using advanced technologies (e.g., sequencing) to search for novel and rare variants contributing to CVD in diverse populations, investigate gene-environment interactions, as well as determine the benefits of translating genetic information to clinical practice.


Genetic testing for common CVD, like MI and stroke, is commercially available but not recommended for clinical use at this time as genetic markers to comprehensively profile these diseases are still ongoing. On the other hand, genetic testing for LQTS and HCM can provide valuable information for nurses to tailor prevention and management strategies for individuals at risk for SCD. Future nursing studies are still needed to determine long term impact of incorporating genetic information into clinical practice.

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