Combined monogenic, polygenic risk prediction spurs changes in CAD management
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A combined monogenic and polygenic risk assessment for CAD can identify individuals at high inherited risk before overt manifestation of traditional risk factors, potentially improving clinician decision-making on preventive interventions.
Clinical risk calculators such as the American College of Cardiology/American Heart Association Pooled Cohort Equations estimate 10-year atherosclerotic CVD risk to guide patient risk discussion around initiating statin therapy to lower LDL, Akl C. Fahed, MD, MPH, FACC, an interventional cardiologist and physician-scientist at Massachusetts General Hospital and instructor in medicine at Harvard Medical School, and colleagues wrote in JACC Advances. The researchers noted such risk calculators are dependent on the presence of clinical risk factors, such as hypertension or diabetes; CAD is a heritable disease, offering clinicians an opportunity to use genetic information to improve the identification of people at risk.
“Our study provides a framework for implementing combined monogenic and polygenic risk assessment for CAD in a preventive genomics setting,” Fahed told Healio. “By and large, participants found the risk assessment understandable and helpful, resulting in positive intent to make lifestyle changes. In 40% of cases, there was a change in clinical management following disclosure of genomic risk results.”
Genetic sequencing, counseling on risk
Fahed and colleagues analyzed data from 60 adults who attended an initial visit in a preventive genomics clinic and a disclosure visit to discuss results and recommendations, primarily via telemedicine, enrolled between December 2020 and August 2021. The mean age of participants was 51 years, 37% were women and 72% had no known CAD; half were referred by their cardiologists and half self-referred.
Participants provided saliva samples at the clinic or remotely via a ship-to-home kit; they received low-coverage whole genome sequencing and a multi-gene, next-generation sequencing panel test from Color Health Inc. Polygenic score calculation was performed using a previously published score of CAD consisting of 6.6 million variants. Results were returned virtually or in person during a follow-up visit with a cardiologist and/or a genetic counselor.
“During this visit, the clinicians disclosed the results of the test, discussed potential downstream implications and documented the results in the electronic medical record,” the researchers wrote. “Participants were then sent a monogenic test result report from the genetic testing company, a dedicated polygenic score report for CAD and a link to a polygenic score explainer website.”
Researchers assessed digital post-disclosure surveys and conducted chart reviews to evaluate the impact of disclosure.
Within the cohort, 3% had a monogenic variant pathogenic for familial hypercholesterolemia and 32% had a high polygenic score in the top quintile of the population distribution.
In a post-disclosure survey, both the genetic test report (in 80% of participants) and the discussion with the clinician (in 89% of participants) were ranked as “very” or “extremely” helpful in understanding the result. Of the 42 participants without CAD, 40% had a change in management.
“Despite the lack of clinical guidelines to initiate diagnostic or therapeutic interventions for CAD based on polygenic scores, physicians used the genetic test as an additional risk assessment tool in conjunction with clinical risk factors to guide additional interventions,” the researchers wrote. “Nearly half of participants without CAD had a change in management that fell into two categories. First, there were changes in pharmacotherapy, including the prescription or intensification of lipid-lowering medications to prevent or delay CAD development. Second, there were diagnostic coronary imaging scans to assess for existing coronary plaque or measure a coronary calcium score, both of which can potentially incentivize the initiation or intensification of lipid-lowering medication.”
Combined testing ‘feasible and understandable’
The researchers found that changes in clinical management occurred more frequently in younger participants, including 70% of those aged 20 to 39 years, 39% of those aged 40 to 59 years and in 11.1% of those aged 60 years or older. There were no differences by sex or referral pathway.
“In the context of CAD, our results suggest that combined testing of monogenic and polygenic drivers as part of a clinical visit is feasible and understandable to people,” the researchers wrote. “Testing also identified individuals who may benefit from preventive therapies or additional diagnostic testing resulting in a change in clinical management in participants at high inherited risk, especially when other clinical assessment tools failed to highlight their increased risk.”
The researchers noted that participants were from a high educational and economic backgrounds and likely more engaged in preventive medicine; more research is needed with participants from underrepresented groups.
“The findings from this study add another step in the direction towards clinical implementation of genomic risk assessment for CAD,” Amit V. Khera, MD, MSc, a physician-scientist at the Center for Genomic Medicine at Massachusetts General Hospital, told Healio. “To date, most studies on the clinical utility on polygenic scores leverage existing datasets, but there is growing need for prospective implementation studies to truly move towards clinical implementation.”
For more information:
Akl C. Fahed, MD, MPH, FACC, can be reached at afahed@partners.org; Twitter: @aklfahed.
Amit V. Khera, MD, MSc, can be reached at avkhera@mgh.harvard.edu. Twitter: @amitvkhera.
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