Genome wide association study (GWAS) is a type of genetic analysis that looks for association between a particular disease or trait and single nucleotide polymorphism (SNP). The polygenic risk score is the sum of the number of risk alleles weighted the GWAS-estimated effect sizes of each SNP on a disease. Researchers have been exploring the use of polygenic risk score (PRS) to predict disease risk and personalize treatment plans, an approach known as precision medicine. Our study was the first to demonstrate that a PRS based on GWAS data for rheumatoid arthritis (RA) onset can also predict joint damage progression. In particular, we found that the PRS is more accurate for predicting joint damage progression in young-onset patients with RA. To facilitate large-scale validation of our findings, we developed an artificial intelligence-based joint damage scoring system. This system will enable us to further investigate the relationship between PRS and disease severity in a larger, more diverse population. Further research is needed to refine the PRS construction method, particularly in terms of identifying the most informative SNPs and optimizing the weighting scheme for risk alleles.