Genetic risk score could revolutionize primary prevention of CAD
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CAD, despite the success of secondary prevention, is pandemic and the leading cause of death in high-, middle- and low-income countries throughout the world. In the United States, individuals living a normal life span will have a 47% chance of experiencing at least one cardiac event. Since CAD has been shown to be a preventable disease, many have postulated that this is the last century for CAD. If we are to conquer this disease, we have to do so through primary prevention.
Yet, it is too costly and the efficacy less than ideal to treat everyone when, at the most, only one-half will benefit. A possible solution is evolving from harnessing of DNA predisposition whereby genetic screening and risk stratification for CAD would enable primary prevention to be initiated only in those who will benefit. A review of genetic risk screening for primary prevention of CAD and the therapeutic response to those selected at risk strongly suggest it will transform our approach to prevention of this pandemic disease.
Genetic risk for CAD
Epidemiologists have for decades claimed 40% to 60% of one’s susceptibility for CAD is genetic. The technology to pursue genetic risk variants did not become accessible until 2005. Millions of DNA markers became available in the form of single nucleotide polymorphisms (SNPs), which enabled spanning the whole genome with markers at high density comparing their frequency in cases with that in controls, referred to as the genome-wide association study (GWAS). Markers occurring more frequently in cases of CAD than controls indicate a predisposition of the DNA region (genetic risk variant) for CAD. The use of so many DNA markers required a corrected P value of .00000005, now known as genome-wide significance. In addition, it was required that the results be replicated in an independent population. Using this approach, we and two other groups independently and almost simultaneously identified the first genetic risk variant for CAD, now referred to as 9p21.
The 9p21 risk variant was associated with only a 25% increased risk for CAD and occurred in more than 75% of the population. This suggested CAD genetic risk would be due to multiple variants, each with minimal increased risk, and would require large populations to identify their location in the genome.
Those of us who were involved with performing GWAS combined our efforts in an international consortium, and pooled our populations and resources in pursuit of genetic risk variants for CAD. The international consortium referred to as CARDioGRAM included Canada, Germany, Iceland, the United Kingdom and the U.S. This consortium along with other independent groups during the next decade led to the discovery of more than 200 genetic risk variants for CAD, all of which are genome-wide significant and have been replicated in an independent population. Characteristics of these genetic variants are shown in the Graphic.
In keeping with our hypothesis, all of the variants are very common, with 50% of them occurring in more than 50% of the population. Secondly, the average increased RR per variant copy is less than 10%. We now know that the total genetic risk burden for CAD depends on the total number of genetic risk variants inherited, rather than any specific variant. It also emphasizes the necessity of determining genetic risk in addition to conventional risk if one is to perform comprehensive risk stratification for the prevention and management of CAD.
Insights gained
The discovery of genetic risk variants and their application to further understand the pathogenesis of CAD has already confirmed several epidemiological observations and refuted others.
We have shown that taller height is associated with decreased risk for CAD, with an increase in risk for CAD of 12% for each standard deviation decrease in height.
We also confirmed that blood groups A and B are associated with increased risk for CAD and together increase risk about 20%. Blood group O carries no increased risk for CAD, since it was mutated more than 100,000 years ago. This disenabled blood group O to transfer a carbohydrate moiety onto von Willebrand’s factor. Blood types A and B through the transfer of this moiety prolong the half-life of von Willebrand’s factor, which predisposes to coronary thrombosis.
Utilizing Mendelian randomization, we showed plasma HDL is not protective against CAD, as dogma had us to believe for more than 6 decades.
Lastly, and very importantly, less than one-third of the genetic risk variants mediate their risk through conventional risk factors: hypercholesterolemia, hypertension, diabetes, obesity, smoking, sedentary lifestyle and family history. The remaining two-thirds are through unknown mechanisms that have great implications for further elucidating the pathogenesis of coronary atherosclerosis and as targets for the development of novel therapies. Through nature’s errors, we have consistently benefited in our quest to improve therapy to prevent cardiac disease. Familial hypercholesterolemia led to the development of statin drugs, which today are the main drugs for prevention of CVD. Similarly, the discovery of loss-of-function mutations in the gene encoding PCSK9 being associated with decreased cardiac events led to the development of PCSK9 inhibitors.
Genetic CAD risk in a single number
Evidence is accumulating to indicate the genetic risk variants enable one to predict and stratify one’s risk for CAD. The total genetic risk for CAD can be expressed in a single number and utilized to risk-stratify for further management. The total genetic risk burden is calculated from knowing the number of risk variants inherited and their associated increased risk for CAD as determined by the OR for each risk variant. For each genetic risk variant, the number of copies inherited by each individual varies from 0 (neither parent transmitted it) to 1 (single parent transmitted) to 2 (both parents transmitted). The number of copies of an inherited variant times the log of its OR provides for the imparted risk of that variant. The sum of all of these products is the total genetic risk burden for CAD, referred to as the genetic risk score (GRS).
Among the first attempts to risk-stratify for CAD with the GRS was in 2015 by Jessica L. Mega, MD, MPH, then from the TIMI Study Group of the cardiovascular division at Brigham and Women’s Hospital and Harvard Medical School and now chief medical officer at Verily, and colleagues. Utilizing 27 genetic risk variants, the researchers retrospectively genotyped patients from four large clinical trials (JUPITER, ASCOT, CARE and PROVE IT-TIMI 22) that evaluated the effect of statin therapy on cardiac events. The sample size was 48,421 individuals with 3,477 cardiac events. The population was stratified by GRS into low, intermediate and high risk for CAD. The effect of statin therapy was greatest in the group with highest genetic risk, indicating the GRS can be utilized to identify those who would benefit most from statin therapy. Furthermore, risk stratification with the GRS required treating only 25 individuals with statin to prevent one cardiac event.
In a similar analysis of participants from the WOSCOPS study, researchers genotyped 57 genetic risk variants in a sample size of 10,456 individuals. This study showed that the high-genetic-risk group exhibited an RR reduction of 44% from statin therapy compared with an RR reduction of 24% in others. Similar studies have confirmed these results, showing risk stratification based on the GRS is superior to that of the conventional risk factors, and is independent of age and relatively independent of conventional risk factors.
Adding more variants
It has been recognized that the proven genetic risk variants for CAD with genome-wide significance account for less than 20% of the predicted inheritability. The inclusion of more genetic risk variants predisposing to CAD would be expected to enhance the power of prediction and stratification of GRS. Two approaches added more genetic variants: one with the inclusion of a technique that predicts association of DNA variants with risk for CAD, and the other that used less stringent statistics and included genetic variants with false discovery rate of less than 0.05. The former, by Cardiology Today Next Gen Innovator Amit V. Khera, MD, MSc, associate director of the Precision Medicine Unit in the Center for Genomic Medicine at Massachusetts General Hospital and the Cardiovascular Disease Initiative at the Broad Institute of MIT and Harvard, and colleagues, included 6.6 million genetic risk variants, and the latter, by Michael Inouye, PhD, from the Cambridge Baker Systems Genomics Initiative in Melbourne, Australia, and Cambridge, United Kingdom, and colleagues, included 1.7 million genetic risk variants.
The polygenic microarray with 6.6 million variants was evaluated in a population of 120,000 individuals, of whom 3.4% were known to have CAD. Utilization of the array correctly identified 3.4% of the population with known CAD. Risk stratification was performed in a test-set with a large sample size of 288,978 from the UK Biobank. Results showed 8% of the population inherited a predisposition of at least threefold increased risk for CAD, 2.3% of the population inherited a predisposition of at least fourfold risk for CAD and 0.5% inherited a predisposition of at least fivefold increased risk for CAD. The array of 6.6 million variants performed better than previous microarrays using 50 genetic variants or 49,310 variants. In the group with threefold increased risk for CAD, conventional risk factors would have identified less than 30% of them.
Inouye and colleagues developed and tested the GRS with 1.7 million risk variants in 22,242 people with CAD and 460,387 controls from the UK Biobank. The 20% with the highest genetic risk score had a fourfold increased risk for CAD. A three- or fourfold increased risk for CAD is equivalent to the risk of inheriting familial hypercholesterolemia.
Lifestyle changes reduce genetic risk
In a recent study, Emmi Tikkanen, PhD, senior data scientist at Nightingale Health Ltd. in Helsinki, and colleagues studied the effect of physical fitness on risk for CAD as determined by the GRS. A large cohort of 502,635 individuals from the UK Biobank were followed for up to 6.8 years. Handgrip strength, objective and subjective physical activity and cardiorespiratory fitness (determined by oxygen consumption during cycle ergometry on a stationary bike) and their relation to CV events and all-cause death were studied. Among individuals with high genetic risk for CAD, high levels of cardiorespiratory fitness were associated with 49% lower risk for CAD. Individuals identified with increased genetic risk for CAD were shown to benefit most from increased physical activity.
Khera and colleagues quantified genetic risk for CAD in 55,685 individuals, using a polygenic score based on 6.6 million genetic risk variants. In the top quintile of polygenic scores — those at highest genetic risk — the RR for CAD was 91% higher compared with those with a lower GRS. Among these individuals with high GRS, a favorable lifestyle (no current smoking, no obesity, regular physical activity and healthy diet) reduced the RR for coronary events by about 46% compared with an unfavorable lifestyle. Identifying individuals with a high GRS and providing appropriate treatment confirms that genetic risk can be treated identical to that of any other risk factor.
The GRS and clinical practice guidelines
A premenopausal woman aged 40 to 49 years with LDL 180 mg/dL and no other risk factors for CAD is not recommended for any prevention treatment other than lifestyle changes. This would appear to be a missed opportunity for primary prevention. Current guidelines indicate plasma LDL should not exceed 70 mg/dL. Several clinical trials have shown 50 mg/dL is associated with fewer cardiac events and more recently, 30 mg/dL is associated with even fewer cardiac events. There is good evidence that LDL is the major culprit leading to the development of coronary atherosclerosis.
The guidelines were developed to treat those who would benefit most with the fewest adverse effects. If one were to treat plasma LDL as the only criterion, everyone in the Western world older than 40 years would qualify for statin therapy. The mean LDL in women in the U.S. and most of the Western world is 121 mg/dL. This number is even higher (146 mg/dL) for men. Some have made the argument to treat everyone with a statin since such therapy is very safe, inexpensive and effective. David J. Heller, MD, assistant professor of global health and medicine at Icahn School of Medicine at Mount Sinai, and colleagues recently estimated the consequences of giving a statin to every man older than 40 years and every woman older than 55 years. It would mean 28 million more Americans receiving statin therapy at a cost of several million dollars. The investigators emphasized that many individuals would not benefit from this therapy and a small number would experience unnecessary adverse effects. This is based on the epidemiological observations that in the U.S., approximately 50% of men or women living a normal lifespan will be expected to experience at least one cardiac event. This would emphasize that only about one-half of the population would benefit from statin therapy. This further emphasizes the need for a method to risk-stratify for CAD to detect those who would benefit most from such therapy.
The GRS has been shown in more than 1 million individuals to effectively risk-stratify for CAD and select those who would benefit most from lifestyle changes or statin therapy. Based on these results, we can expect that, as shown in the Figure, about 20% to 30% will be at high risk and most appropriate for necessary therapy. The cutoff for increased risk for CAD, above which preventive therapy is recommended, will be arbitrary, but even if those with the highest risk are selected, it would decrease the cost by at least 20%, if not 50%, and increase efficacy as well as avoid unnecessary adverse events.
Thus, we recommend the GRS be adopted in the prevention and clinical management of CAD. The GRS could transform the primary prevention of CAD. It is worth noting that CAD has been shown to be highly preventive, yet its prevalence is pandemic. The prevention of its pandemic spread would only be possible by primary prevention. The genetic screen is inexpensive and can be performed anywhere.
We have shown secondary prevention is very effective, but to decrease the prevalence of CAD, we have to enhance our primary prevention. We have to be able to select those who are at high risk and do so early in their life. In men at high risk, we have to initiate prevention in their 20s, and for high-risk women, perhaps one can delay until their 40s. Until the development of the GRS, risk stratification has been less than adequate for primary prevention. We depended on the conventional risk factors that are dependent on age, just as our prediction programs are, including the Framingham risk score, Reynolds score and the American College of Cardiology/American Heart Association Pooled Cohort Equations. The GRS is independent of age and relatively independent of conventional risk factors. The GRS can be assessed any time after birth, as one’s DNA does not change in one’s lifetime. Furthermore, risk stratification based on GRS has been shown to be extremely responsive to changes in lifestyle and drug therapy.
Concerns for clinical application
All of the risk stratification and CAD prediction studies with GRS have been primarily in European individuals or those of European descent. We need much more experience in other ethnic groups. Nevertheless, the data suggest that East and South Asian individuals appear to have similar genetic predisposition. The studies in Hispanic individuals are limited, but the results are encouraging that the derived GRS from European individuals is applicable.
Given the large sample size in which GRS has been evaluated, it is time to assess its application in a routine clinical situation and determine its discriminatory power for different ethnic groups. The power of the GRS to risk stratify and predict for CAD will continue to evolve, but it is not a reason to restrict its clinical application. On the contrary, we believe its evolution would be enhanced by routine clinical application in the different ethnic groups.
- References:
- Helgadottir A, et al. Science. 2007;doi:10.1126/science.1142842.
- Heller DJ, et al. Circulation. 2017;doi:10.1161/CIRCULATIONAHA.117.027067.
- Inouye M, et al. J Am Coll Cardiol. 2018;doi:10.1016/j.jacc.2018.07.079.
- Khera AV, et al. N Engl J Med. 2017;doi:10.1056/NEJMoa1605086.
- McPherson R, et al. Science. 2007;doi:10.1126.science.1142447.
- Mega JL, et al. Lancet. 2015;doi:10.1016/S0140-6736(14)61730-X.
- Roberts R, et al. Trends Cardiovasc Med. 2019;doi:10.1016/j.tcm.2019.08.006.
- Shepherd J, et al. N Engl J Med. 1995;doi:10.1056/NEJM199511163332001.
- Tikkanen E, et al. Circulation. 2018;doi:10.1161/CIRCULATIONAHA.117.032432.
- Wellcome Trust Case Control Consortium. Nature. 2007;doi:10.1038/nature05911.
- For more information:
- Pallavi Bellamkonda, MBBS, FACC, is assistant professor of cardiology at Creighton University Medical Center and cardiologist at Dignity Health Medical Group.
- Robert Roberts, MD, FRSC, FRCPC, MACC, LLD (Hon.), FAHA, is professor of cardiology and chair of the International Society for Cardiovascular Translational Research at the University of Arizona and cardiologist at Dignity Health Medical Group. He is also a member of the Cardiology Today Editorial Board. The authors can be reached at 500 W. Thomas Road, Phoenix, AZ 85013; email: robert.roberts@dignityhealth.org.
Disclosures: The authors report no relevant financial disclosures.
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