Polygenic Risk Scores for Kidney Function Decline in Japanese Population-Based Cohorts

Background: Large-scale genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with kidney function. However, most polygenic risk score models for kidney function were developed in European populations, limiting their accuracy in non-European groups. This study aimed to validate the clinical utility of polygenic risk scores for kidney function decline in the Japanese general population. Methods: We analyzed the Shika resident cohort cross-sectional and the Toshiba worker cohort prospectively to construct polygenic risk score models based on GWAS data from Japanese populations incorporating 344,577 and 352,151 genetic variants, respectively. The primary outcome was kidney function decline, defined as eGFR <60 mL/min/1.73 m 2 . With adjustments for traditional risk factors, multivariate logistic regression and Cox proportional hazards models were used to assess associations between the polygenic risk score and kidney function decline. Results: In the Shika resident cohort (n = 895, mean age 62 years), 157 participants (18%) had eGFR <60 mL/min/1.73 m 2 ; each standard deviation (SD) increase in the polygenic risk score conferred 55% higher odds (OR 1.55, 95% CI 1.28–1.89). In the Toshiba worker cohort (n = 6,769, mean age 40 years), 1,593 participants (24%) developed eGFR <60 mL/min/1.73 m 2 over median 8.3-year follow-up; each SD increase in the polygenic risk score was associated with 16% higher risk (HR 1.16, 95% CI 1.10–1.22). Adding the polygenic risk score to clinical models was associated with improved integrated discrimination in both cohorts, but the overall improvement in predictive ability was limited. Conclusions: The polygenic risk score was independently associated with kidney function decline beyond established risk factors and was associated with modestly improved risk prediction accuracy in Japanese populations, supporting its potential utility for personalized chronic kidney disease management.