Patients with familial hypercholesterolemia post extremely high cholesterol levels, even with lifestyle changes and statin therapy, while other patients must discontinue statin treatment because of side effects or intolerance or inability to achieve the desired effect, even on maximum dosages. A new class of drugs to lower LDL-C, injectable monoclonal antibodies that inhibit the PCSK9 protein, is a significant addition to therapies.
By Annette M. Boyle
BOSTON — Recent developments in genomics technology are beginning to bring the promise of precision medicine to the treatment of cardiovascular disease, just in time to help define which patients will benefit most from a new class of cholesterol-reducing drugs.
Precision medicine factors in variability in genes, environment and lifestyle to determine an individual’s risk of a specific disease and potential response to therapies. The national Precision Medicine Initiative has budgeted $130 million to build a large-scale national cohort to advance understanding of multiple diseases and genomics.
The VA’s Million Veteran Project ties into the Precision Medicine Initiative. One of its first studies is examining cardiovascular risk factors, including the genes that influence how obesity and lipid levels affect heart health.
“Precision medicine is already being applied in the VA in context of cancer in the Precision Oncology Program,” said Christopher O’Donnell, MD, MPH, chief of the Cardiology Section at Boston VA Healthcare and chief scientist for the VA Million Veteran Project. “Such programs will lead the way for implementation of precision medicine across the spectrum of diseases.”
For heart disease, the major clinical, lifestyle and biochemical atherosclerosis risk factors have been well-known for decades. Some, like family history, ethnicity and age, cannot be changed. Others, such physical inactivity, poor diet and excessive alcohol consumption, might be improved with lifestyle changes.
The biggest challenge has been identifying how to best address the last group of risk factors — hypercholesterolemia, hypertension, obesity and diabetes — which often require a combination of medication and lifestyle changes. The addition of genetic data could allow clinicians to select therapies that target specific mutations to achieve better outcomes for patients with these conditions and avoid prescribing medications that may have no — or negative — effects.
A study recently published in Circulation found that just discussing genomic risk may encourage more patients with moderate risk of coronary heart disease to start statins than reviewing only traditional risk factors. 1
The Myocardial Infarction Genes (MI-GENES) Clinical Trial included 203 participants who were randomly assigned to receive their 10-year probability of heart disease as determined by traditional risk factors alone or with the additional information provided by a genetic risk score. Nearly 40% of participants who received genetic risk scores started statins, compared with 22% of participants in the other arm. After six months, those who received the genetic risk scores had mean LDL-C levels of 96.5 mg/dL compared with 105.9 mg/dL for those who did not.
The difference was concentrated among the participants who received their genetic risk score and had a high risk. Their average LDL-C levels were 92.3 mg/dL. There was no significant difference between those who received conventional counseling and those who had low genetic risk scores, reported the authors.
The genetic risk scores were calculated based on additive impact of the estimated disease effect of each identified allele associated with coronary heart disease.
O’Donnell noted that the predictive benefit of genetic risk scores is currently “modest compared with the combined impact of traditional cardiovascular risk factors like hyperlipidemia, hypertension and diabetes.”
The indication from the MI-GENES study that those with the highest genetic risk were more likely to take statins, though, supports the inclusion of this additional information.
“Recent trials of statin use suggest that persons with higher genetic risk will benefit more from treatment with statin drugs,” he added, even if they reduce their cholesterol by the same amount as someone with lower risk.
“Lowering of LDL levels is generally associated with lowered risk of CVD, including in persons at high risk. On a population level, even a modest level of LDL reduction can still amount to a large number of lives saved,” O’Donnell told U.S. Medicine.
The impact of identifying and discussing the more than 150 common genetic variants that appear to alter levels of certain lipid fractions or the 50 common polymorphisms that modestly increase CHD risk may not be clear yet, noted O’Donnell and Pradeep Natarajan, MD, MMSc, cardiologist at Massachusetts General Hospital and an instructor at Harvard Medical School in an editorial that accompanied the Circulation study.
The importance of understanding the exceptional genetic risk conferred by specific mutations in the low-density lipoprotein receptor (LDLR), PCSK9 or APOB, however, are indisputable. These mutations underlie the predisposition for familial hypercholesterolemia.
Two conditions, familial homozygous and heterozygous hypercholesterolemia causes LDL levels that can rise sky-high despite lifestyle. Patients with the condition cannot achieve acceptable LDL-C levels, even on maximal statin therapy and with optimal diet and exercise.2
Two drugs recently gained Food and Drug Administration approval to treat familial heterozygous hypercholesterolemia, evolocumab and alirocumab. Evolocumab also received an indication for use in familial homozygous hypercholesterolemia.
Both are injectable monoclonal antibodies that inhibit the PCSK9 protein involved in regulating the lifespan of the liver receptors that eliminate cholesterol. When taken with statins, they can push LDL-C 30% to 60% lower than statins alone, according to the FDA.
The drugs are also approved to help patients with clinical atherosclerotic cardiovascular disease who require additional lowering of LDL-C in combination with statins or on their own. Many patients discontinue statin treatment because of side effects or statin intolerance, and up to 20% of individuals on statins are unable to control their cholesterol levels on the maximally tolerated dose and need additional risk reduction.
“Available evidence suggests that risk continues to decrease with lower LDL cholesterol,” O’Donnell said. “There is a biologically plausible rationale for investigating whether the benefits outweigh the risks for further lowering of LDL in very high risk persons beyond statins.”
Genomics could transform not only treatment for high cholesterol but also the therapeutic approach to cardiovascular disease of all types. Genomic information might help “predict increased risks for benefits of various cardiac drugs and to identify persons and families in the population who would benefit from treatment,” O’Donnell said.
But, he noted, “the availability of more than three billion base pairs of information from whole genome sequence information for each patient will place a significant demand upon the health system.” The costs associated with adapting current systems to support such a massive influx of data would be substantial.
The changes needed will extend well beyond IT systems, O’Donnell stressed. “The addition of genomics to the electronic health record will require system-wide adoption of practices such as standardized genomic interpretation and identification of actionable genetic abnormalities, confirmatory genetic testing, and genetic counseling.”
- Kullo IJ, Jouni H, Austin EE, Brown SA, Kruisselbrink TM, Isseh IN, Haddad RA, Marroush TS, Shameer K, Olson JE, Broeckel U, Green RC, Schaid DJ, Montori VM, Bailey KR. Incorporating a genetic risk score into coronary heart disease risk estimates: effect on low-density lipoprotein cholesterol levels (the MI-GENES Clinical Trial). Circulation. 2016;133:1181–1188.
- Natarajan P. O’Donnell CJ. Reducing Cardiovascular Risk Using Genomic Information in the Era of Precision Medicine. Circulation. 2016;133:1155-1159.