Abstract: Objective: To evaluate the risk of leprosy by considering information on epidemic region and family history when combined with those? from 18 known susceptibility loci identified by genome-wide association studies (GWASs) associated with leprosy. Methods: Genetic risk score (GRS) and weighted genetic risk score (wGRS) were calculated to evaluate the joint effects of 18 susceptibility loci. Multiple models combining genetic loci and region and family history information were established. Receiver operating characteristic curve analysis was used to compare the power of different predictive models. Results: The model incorporating wGRS and information on epidemic region and family history was the best one to predict leprosy risk in Chinese population, with all area under curve of 0.758(95%CI: 0.750~0.766). Conclusion: Eighteen known susceptibility loci identified by GWASs jointly influence the leprosy risk?. The combination of 18 known susceptibility loci and information on epidemic region and family history can improve the performance of risk predictive model for the occurrence of leprosy.

Key words: leprosy, risk prediction model, GWAS