Epidemiology

For decades, cardiovascular disease (CVD) has been the leading cause of mortality on a global scale.¹ Concomitant with recent economic development in many emerging markets, coronary artery disease (CAD) and its complications has overtaken communicable diseases as the leading cause of mortality in many developing regions as well.² Although prevention of CAD has long been a focus of public health policy, clinical medicine and biomedical scientific investigation, the prevalence of CAD remains high, despite current strategies for prevention and treatment.

Globally in 2016, 9.5 million people died from CAD.² In addition to the massive human cost, this also results in a significant economic cost — in 2016, global deaths from ischemic heart disease accounted for 196 million years of life lost.³ In the US, economic estimates suggested a direct cost of CVD of $213.8 billion in the period 2014-2015.⁴ Of CVD, it is estimated that CAD is the largest contributor to these costs.⁵ Although CVD is typically manifested in later life, heart disease also accounts for a significant proportion of premature deaths in the US, particularly in males; it causes 15.5% of male deaths in ages 35-44, 22.6% in those aged 45-54 and 24.4% in those aged 55-64.⁶ These deaths are of particular social, emotional and economic cost, with many decades of economic and social contribution lost. Our current frameworks for identification of those at intermediate-term risk meriting more aggressive preventive measures are heavily influenced by age.⁷ Orthogonal strategies for risk refinement have been previously proposed, and now polygenic risk scoring (PRS) for CAD risk is proposed as one strategy to achieve this goal.⁸

Polygenic Risk Scoring for Coronary Artery Disease

Investigations for monogenic etiologies for premature CAD risk established familial hypercholesterolemia as a key risk factor. Rare pathogenic mutations in low-density lipoprotein receptor (LDLR), Apolipoprotein B (Apo B) and Proprotein convertase subtilisin/kexin type 9 (PCSK9) lead to marked elevations in low-density lipoprotein cholesterol and resultant marked increase in premature CAD risk.^9-11 In the general population, familial aggregation and twin analyses imply that CAD is a broadly heritable trait, implicating common genetic variation.^12-15 Genome-wide association studies (GWAS) of common genetic variants, or single nucleotide polymorphisms (SNPs), confirm the presence and estimate the influence of CAD risk SNPs across the genome.¹⁶

With increasing sample sizes and ethnic diversity of included participants, GWAS continue to identify an increasing number of CAD risk SNPs with improved risk estimates. Each SNP generally confers modest effect — odds ratios generally range 1.1 - 1.7 — but many risk SNPs can be present in any given individual. PRS was proposed as a method to take account of the total risk conferred by these individual SNPs in a person.¹⁷

Advances in statistical genetics now permit the interpretation of full common genomic variation to quantify genomic risk into a single number. Two recent studies derived and evaluated the performance of two genome-wide PRS for CAD. A 'metaGRS' risk score comprised of 1.7 million SNPs applied to nearly 500,000 individuals in the UK Biobank stratified them into quintiles of risk, with varying trajectories of CAD over the course of their lifetime.¹⁸ In this model, the top quintile of risk had a hazard ratio of 4.17 compared to those in the bottom quintile for risk of developing incident CAD – an age-independent risk trajectory established at embryogenesis. In addition, an 'LDPred'-based PRS for CAD comprised of 6.6 million SNPs using the UK Biobank as well, demonstrating that individuals in the top 5th percentile (i.e., 1 in 20) had a ~3.0-fold odds of CAD.¹⁹ In comparison, the presence of monogenic mutations for familial hypercholesterolemia confers an odds ratio of 3:4 for development of CAD, but is present in less than 1 in 200 people.^20,21 Unlike pathogenic mutations for familial hypercholesterolemia, an elevated CAD PRS was not readily identifiable by LDL cholesterol or other conventional CAD risk factors.

Implications for Lifestyle Modification

CAD risk SNPs are present from birth and remain throughout life. Thus, CAD risk SNPs are detectable in younger individuals before traditional, clinically apparent risk factors are present, such as hypertension or elevated lipids. In addition, lifestyle and environmental factors have been shown to be independent of and complementary to genetic risk. For example, in observational studies, those in the highest quintile of polygenic risk who also had favorable lifestyle factors had a greater than 50% reduction in risk compared to those in the same quintile who did not have favorable lifestyle factors.^22,23

Disclosure of CAD PRS is proposed as a mechanism to promote lifestyle modification and health promotion.²⁴ Small studies with limited follow-up to-date indicate increased engagement with PRS disclosure, but unclear effects on behavioral modification.²⁵ These observations have been similar for diabetes PRS disclosures.²⁶ Preliminary observations from the GeneRISK study, with a cohort of over 7,000 individuals, suggest that combined clinical and genetic risk disclosure may promote lifestyle modification.²⁷ To what degree this represents overall risk communication versus specifically genetic risk disclosure is not yet known.

Lifestyle modification is a key goal for CAD prevention, regardless of genetic risk. A high CAD PRS may be the basis for earlier more intensive lifestyle modification. However, further research is required to identify the optimal framework and tools for CAD PRS disclosure to facilitate lifestyle modification.

Implications for Primary Prevention Statin Prescriptions

Currently, statin prescriptions are allocated based on elevated intermediate-term (i.e., 10-year) CAD absolute risk estimation.²⁸ Subgroup analyses from statin clinical trials demonstrate that previously defined subgroups with higher absolute risk for CAD still have similar relative benefits from statins; thus, absolute benefit is optimized by generally greater absolute baseline risk.²⁹ Retrospective observational analyses of molecularly confirmed heterozygous familial hypercholesterolemia suggest that statin prescriptions are associated with a greater clinical benefit from statins. This is driven both by greater absolute baseline risk, and also greater relative statin benefit for a given degree of LDL cholesterol lowering.³⁰

Post hoc analyses in three primary prevention statin trials suggest that statin benefit may be optimized in the setting of high CAD PRS also due to a greater absolute risk and greater relative benefit from statins for a given degree of LDL cholesterol lowering.^31,32 Absolute risk remains low for patients at a young age with high CAD PRS; as such, the optimal timing of statin prescriptions when elevated CAD PRS is detected early in life is currently not known. Risk refinement and statin benefit should ideally be estimated in concert with established clinical risk factors.

The genetic architecture of CAD is highly concordant with subclinical coronary atherosclerosis, as quantified by a coronary artery calcium score.³³ Consistent with this observation, recent work suggests that knowledge of high CAD PRS could prompt earlier coronary artery calcification screening to potentially further guide statin prescription timing.³⁴ Nevertheless, even among individuals without subclinical atherosclerosis, an elevated CAD PRS still carries a heightened risk for all-cause mortality.³⁵

Further work is required to characterize the combination of absolute risk conferred by clinical and genetic risk factors, to clarify statin suitability and prescription timing where appropriate. Whether prescription timing should be influenced by the onset of subclinical coronary atherosclerosis versus earlier prescriptions requires further study.

Implications for Secondary Prevention

An increasing number of younger individuals are suffering from myocardial infarction.³⁶ Furthermore, a large fraction of young patients with myocardial infarctions have a paucity of readily identifiable conventional CAD risk factors.³⁷ Among individuals hospitalized for early-onset myocardial infarction, it is estimated that approximately 1.7% carry a familial hypercholesterolemia mutation and approximately 17% have a CAD PRS conferring a similar CAD risk as a familial hypercholesterolemia mutation.³⁸

In the scenario of early-onset myocardial infarction, CAD PRS quantification may better highlight unrecognized risk factors. Furthermore, a CAD PRS is also associated with recurrent CVD risk among individuals with prevalent CAD.³¹ Current guidelines support more intensive preventive strategies for patients with established CAD but at elevated risk for recurrence.²⁸ Whether intensification of preventive therapies is indicated for patients with prevalent CAD and elevated CAD PRS requires further study.

Conclusions

With direct-to-consumer genetic testing available in now tens of millions of individuals — and an additional several million genetic research participants — CAD PRS may soon be readily available. There is a pressing need to understand the immediate clinical role of a CAD PRS, which is likely to soon first interface with healthcare in a patient-to-doctor mechanism. While much research is necessary, a CAD PRS in concert with well-established clinical risk factors provides an opportunity for CAD risk prediction and potentially CAD risk reduction.

References

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Keywords: Apolipoproteins B, Atherosclerosis, Biological Specimen Banks, Calcium, Coronary Artery Disease, Cholesterol, LDL, Diabetes Mellitus, Economic Development, Follow-Up Studies, Genetic Testing, Genome-Wide Association Study, Genetic Research, Genomics, Health Promotion, Health Policy, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Hyperlipoproteinemia Type II, Hypertension, Life Style, Lipids, Mortality, Premature, Myocardial Infarction, Mutation, Odds Ratio, Polymorphism, Single Nucleotide, Prevalence, Primary Prevention, Receptors, LDL, Retrospective Studies, Risk Factors, Risk Reduction Behavior, Sample Size, Subtilisins, Secondary Prevention

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