# 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.

## Key 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.