Sex Differences in Predicting Dyslipidemia Using Polygenic Risk Score with Fatty Liver Index and Fibrotic Nonalcoholic Steatohepatitis Index

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are recognized risk factors for dyslipidemia. Current prediction models that rely solely on dyslipidemia polygenic risk score (PRS) have certain limitations. We aimed to validate simple indexes for NAFLD and NASH as predictors of dyslipidemia using the PRS. This study utilized cohort data from an urban population-based dataset comprising 48,263 South Koreans. The incidence of dyslipidemia was higher in men than in women (32.4% and 27.8%; p < 0.001). The PRS model predicted dyslipidemia more accurately in men (AUROC [95% confidence intervals]: 0.645 [0.636-0.754]). Notably, integrating the fatty liver index (FLI) and fibrotic NASH index (FNI) with the PRS model resulted in the highest accuracy in diagnosing dyslipidemia, particularly in men (AUROC [95% confidence intervals]: 0.704 [0.698-0.711]). In conclusion, a predictive model combining the PRS with FLI and FNI was validated. This model offers more accurate predictive value for diagnosing dyslipidemia, particularly in East Asian men. Thus, our study has the clinical potential for identifying high-risk individuals and determining preventive measures for dyslipidemia in a sex-specific manner.