AIM: To develop a risk model for Crohn’s disease(CD) based on homogeneous population.METHODS: In our study were included 160 CD patients and 209 healthy individuals from Slovenia. The association study was performed for 112 single nucleotide polymorphisms(SNPs). We generated genetic risk scores(GRS) based on the number of risk alleles using weighted additive model. Discriminatory accuracy was measured by area under ROC curve(AUC). For risk evaluation, we divided individuals according to positive and negative likelihood ratios(LR) of a test, with LR > 5 for high risk group and LR < 0.20 for low risk group.RESULTS: The highest accuracy, AUC of 0.78 was achieved with GRS combining 33 SNPs with optimal sensitivity and specificity of 75.0% and 72.7%, respectively. Individuals with the highest risk(GRS >5.54) showed significantly increased odds of developing CD(OR = 26.65, 95%CI: 11.25-63.15) compared to the individuals with the lowest risk(GRS < 4.57) which is a considerably greater risk captured than in one SNP with the highest effect size(OR = 3.24). When more than 33 SNPs were included in GRS, discriminatory ability was not improved significantly; AUC of all 74 SNPs was 0.76.CONCLUSION: The authors proved the possibility of building accurate genetic risk score based on 33 risk variants on Slovenian CD patients which may serve as a screening tool in the targeted population. AIM: To develop a risk model for Crohn’s disease (CD) based on homogeneous population. METHODS: In our study were included 160 CD patients and 209 healthy individuals from Slovenia. The association study was performed for 112 single nucleotide polymorphisms (SNPs). We generated genetic risk scores (GRS) based on the number of risk alleles using weighted additive model. Discriminatory accuracy was measured by area under ROC curve (AUC). For risk evaluation, we divided individuals according to positive and negative likelihood ratios (LR) of a test with LR> 5 for high risk group and LR <0.20 for low risk group .RESULTS: The highest accuracy, AUC of 0.78 was achieved with GRS combining 33 SNPs with optimal sensitivity and specificity of 75.0% and 72.7%, respectively. Individuals with the highest risk (GRS> 5.54) were significantly increased odds of developing CD (OR = 26.65, 95% CI: 11.25-63.15) compared to the individuals with the lowest risk (GRS <4.57) ptured than in one SNP with the highest effect size (OR = 3.24). When more than 33 SNPs were included in GRS, the discriminatory ability was not improved significantly; AUC of all 74 SNPs was 0.76. CONCLUSION: The authors proved the possibility of building accurate genetic risk score based on 33 risk variants on Slovenian CD patients which may serve as a screening tool in the targeted population.