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Polygenic Risk Score Predicts Sudden Death in Patients With Coronary Disease and Preserved Systolic Function
Roopinder K Sandhu1, Jacqueline S Dron2, Yunxian Liu3
1Department of Cardiology, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA; Division of Cardiology, University of Alberta, Edmonton, Alberta, Canada.
Insights
A high genome-wide polygenic score for coronary artery disease (GPSCAD) identifies patients with coronary artery disease at increased risk for sudden and/or arrhythmic death (SAD). This genetic risk score can help stratify patients who may benefit from defibrillator therapy.
Area of Science:
- Cardiovascular Genetics
- Genomic Risk Prediction
- Sudden Cardiac Death
Background:
- Familial predisposition to sudden and/or arrhythmic death (SAD) in coronary artery disease (CAD) patients is recognized, but its genetic underpinnings remain unclear.
- Understanding the genetic basis of SAD is crucial for risk stratification and targeted interventions in CAD management.
Purpose of the Study:
- To evaluate the utility of a genome-wide polygenic score for coronary artery disease (GPSCAD) in stratifying SAD risk among CAD patients without severe systolic dysfunction.
- To determine if GPSCAD can identify individuals at higher risk for SAD, potentially guiding therapeutic decisions.
Main Methods:
- A validated GPSCAD was generated from genome-wide genotyping data of 4,698 European ancestry participants with CAD and preserved ejection fraction.
- Participants were categorized into the top GPSCAD decile versus the remainder, and competing risk analyses were used to estimate absolute, proportional, and relative risks for SAD and non-SAD.
- Multivariable models adjusted for clinical factors, electrocardiogram parameters, and left ventricular ejection fraction to assess the independent association of top GPSCAD decile with SAD.
Main Results:
- Individuals in the top GPSCAD decile exhibited significantly elevated absolute (8.0% vs 4.8%) and proportional (29% vs 16%) risks of SAD over an 8.0-year median follow-up.
- After multivariable adjustment, the top GPSCAD decile was independently associated with an increased risk of SAD (subdistribution HR: 1.77; P = 0.002) but not non-SAD.
- The addition of GPSCAD to risk models significantly improved net reclassification indexes (NRIs), indicating enhanced risk prediction for SAD.
Conclusions:
- High GPSCAD specifically predicts SAD in CAD patients without severe systolic dysfunction, independent of traditional risk factors.
- GPSCAD effectively enriches for individuals at both absolute and proportional risk of SAD.
- These findings suggest that GPSCAD can identify a subgroup of CAD patients who may benefit from advanced therapies, such as defibrillator implantation.
Background:
A familial predisposition to sudden and/or arrhythmic death (SAD) in the setting of coronary artery disease (CAD) exists; however, the genetic basis is poorly understood.
Objectives:
The purpose of this study was to determine whether a genome-wide polygenic score for coronary artery disease (GPSCAD) might have utility in SAD risk stratification in CAD patients without severe systolic dysfunction.
Methods:
A previously validated GPSCAD was generated utilizing genome-wide genotyping in 4,698 PRE-DETERMINE participants of European ancestry with CAD and left ventricular ejection fraction >30%-35%. The population was dichotomized according to top GPSCAD decile as defined by the general population, and absolute, proportional, and relative risks for SAD and non-SAD were estimated using competing risk analyses.
Results:
Over a median follow-up of 8.0 years, participants in the top GPSCAD decile were at elevated absolute SAD risk (8.0%; 95% CI: 5.1%-12.4% vs 4.8%; 95% CI: 3.3%-7.0%; P = 0.005) and proportional SAD risk (29% vs 16%; P = 0.0003) compared with the remainder. After controlling for left ventricular ejection fraction, clinical factors, and electrocardiogram parameters, the top GPSCAD decile was associated with SAD (subdistribution HR: 1.77; 95% CI: 1.23-2.54; P = 0.002) but not non-SAD (subdistribution HR: 1.00; 95% CI: 0.80-1.25; P = 0.98) (P for Δ = 0.003). The addition of the top GPSCAD decile to the multivariable model significantly improved net reclassification indexes (NRIs) (continuous NRI: 14.0%; P = 0.024; and categorical NRI: 6.6%; P = 0.005) but not the C-index (difference in C-index: 0.007; P = 0.143).
Conclusions:
Among CAD patients without severe systolic dysfunction, high GPSCAD specifically predicted SAD and enriched for both absolute and proportional SAD risk, identifying a population who might benefit from defibrillator therapy.
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