An introduction to polygenic scores - methodological basics and recent advances

Area of Science:

• Genetics
• Bioinformatics
• Preventive Medicine

Background:

• Polygenic scores (PGS) estimate genetic predisposition to complex diseases and traits.
• Numerous PGS have been developed using genome-wide association studies (GWAS) and population biobanks.
• PGS summarize the effects of many genetic variants for risk stratification.

Purpose of the Study:

• To review the principles, generation, and application of PGS.
• To outline the translational role of PGS in precision medicine and personalized risk stratification.
• To discuss limitations and future perspectives for clinical integration of PGS.

Main Methods:

• Review of existing literature on polygenic scores.
• Explanation of PGS generation from GWAS data and biobanks.
• Discussion of PGS application in risk stratification and precision medicine.

Main Results:

• PGS can support risk stratification for multifactorial diseases.
• Potential exists for integrating PGS with clinical risk factors for personalized prevention.
• Limitations include generalizability across populations and missing heritability.

Conclusions:

• PGS offer a promising tool for personalized risk stratification and preventive medicine.
• Methodological developments are paving the way for clinical integration of PGS.
• Addressing limitations is crucial for the effective and equitable use of PGS in healthcare.