Preventing premature deaths through polygenic risk scores.

Area of Science:

• Genetics and Public Health
• Preventive Medicine
• Computational Biology

Background:

• Polygenic risk scores (PRS) show predictive validity but their clinical utility needs quantification.
• PRS are stable and derivable from a single biological sample, making them suitable for lifelong health management.

Purpose of the Study:

• To explore the potential of PRS in optimizing existing screening programs.
• To quantify the clinical benefits of integrating PRS into screening for seven major diseases.
• To assess the impact of PRS-guided screening on reducing premature mortality.

Main Methods:

• Integrated modeling approach to quantify clinical benefits of PRS.
• Identification of individuals at high (OR>2) and very high (OR>3) genetic risk.
• Estimation of optimal screening ages based on equivalent risk levels.
• Leveraging published data on mortality and intervention outcomes.

Main Results:

• High-risk individuals could be screened significantly earlier (8.9-10.8 years).
• Case enrichment in high-risk groups ranged from 1.7 to 3.0.
• PRS-guided screening with interventions could reduce premature deaths by 23.3% across seven diseases.

Conclusions:

• Knowledge of genetic risk via PRS offers substantial public health benefits.
• Tailoring existing screening programs based on PRS can effectively reduce premature mortality.
• PRS integration into screening represents a promising strategy for personalized preventive medicine.