Economic modeling of polygenic risk prediction of coronary artery disease in childhood

TL;DR

This paper explores using DNA-based risk scores to identify children at high risk for heart disease and prevent it through early interventions.

Contribution

The study introduces a novel health economic model showing polygenic risk scores can guide cost-effective childhood prevention of coronary artery disease.

Findings

PRS-guided prevention could prevent 72 CAD events in 2000 high-risk children.

The model shows a 3.6% absolute event reduction and a 3614% return on investment.

Early targeted prevention improves outcomes and reduces lifetime costs.

Abstract

Risk factors and subclinical pathophysiology of coronary artery disease (CAD) begin in childhood, yet identifying candidates for primordial prevention remains challenging. Polygenic risk scores (PRS) provide a DNA-based risk marker from birth that can stratify children by lifetime CAD risk. We evaluated the potential clinical utility and cost-effectiveness of PRS-guided CAD prevention in children using health economic modeling. A Markov model compared PRS-guided prevention with standard prevention in a hypothetical group of 10,000 children. Children in the top 20% of PRS (n = 2000) were assumed to receive behavioral interventions. Assuming a 10-year CAD incidence of 12% during adulthood among those in the top 20% of the PRS distribution and a conservative 30% relative risk reduction with preventive intervention, PRS-guided prevention was projected to prevent 72 CAD events among 2000 high-risk children (3.6% absolute event reduction), yielding a return on investment of 3614%. PRS enables early, targeted prevention, improving outcomes, and lowering lifetime costs.

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