Recent advances in polygenic scores: translation, equitability, methods and FAIR tools

• Published in: Genome medicine Vol. 16; no. 1; pp. 33 - 14
• Main Authors: Xiang, Ruidong, Kelemen, Martin, Xu, Yu, Harris, Laura W, Parkinson, Helen, Inouye, Michael, Lambert, Samuel A
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 19.02.2024; BioMed Central; BMC
• Subjects: Accessible; Accuracy; And Reusable; Biobanks; Breast cancer; Cardiovascular disease; Clinical medicine; Clinical trials; Clinical utility; Communication; Cost analysis; Diabetes; FAIR (Findable; Family medical history; Genetic aspects; Genetic Predisposition to Disease; Genome-Wide Association Study; Genomes; Genomics; Health aspects; Health risk assessment; Humans; Interoperable; Medical screening; Multifactorial Inheritance; Polygenic score (PGS); Prostate; Review; Risk Factors; Type 2 diabetes; United Kingdom > UK; Clinical utility; Open-access; Polygenic score (PGS); Responsible use; And Reusable; FAIR (Findable; Genome-wide association studies (GWAS); Interoperable; Transferability; Accessible
• ISSN: 1756-994X; 1756-994X
• DOI: 10.1186/s13073-024-01304-9

Polygenic scores (PGS) can be used for risk stratification by quantifying individuals' genetic predisposition to disease, and many potentially clinically useful applications have been proposed. Here, we review the latest potential benefits of PGS in the clinic and challenges to implementation. PGS could augment risk stratification through combined use with traditional risk factors (demographics, disease-specific risk factors, family history, etc.), to support diagnostic pathways, to predict groups with therapeutic benefits, and to increase the efficiency of clinical trials. However, there exist challenges to maximizing the clinical utility of PGS, including FAIR (Findable, Accessible, Interoperable, and Reusable) use and standardized sharing of the genomic data needed to develop and recalculate PGS, the equitable performance of PGS across populations and ancestries, the generation of robust and reproducible PGS calculations, and the responsible communication and interpretation of results. We outline how these challenges may be overcome analytically and with more diverse data as well as highlight sustained community efforts to achieve equitable, impactful, and responsible use of PGS in healthcare.