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BackgroundDespite the recent progress in our understanding of the genetic predisposition to systemic lupus erythematosus (SLE) its clinical and functional significance is not fully clarified yet and needs to be implemented in personalized care [1].ObjectivesTo estimate the association between some single nucleotide polymorphisms (SNPs) of 9 non-HLA genes-candidates as STAT4 rs7574865, PTPN2 rs2542151, PTPN22 rs2476601, AGER rs1035798, TRAF1/C5 rs3761847, SLC7A11 rs13128867, RUNX1 rs9979383, IL6 rs1800795, IL6R rs2228145, IL6R rs4845618 and susceptibility to SLE in Belarusian women for the following predictive model development.MethodsWe examined 316 women: among them 59 SLE patients (mean age 39.84, CI95% 36.62-43.06) classified according to the 1997 American College of Rheumatology (ACR) revised classification criteria and 257 age-matched healthy controls (blood donors, mean age 38.12, 95% confidence interval (CI95%) 36.77-39.46). Deoxyribonucleic acid was extracted from peripheral blood samples by phenol-chloroform method. Genotyping was performed by real-time PCR with fluorescent probes. Descriptive analysis, test for Hardy–Weinberg equilibrium, multiple inheritance models (co-dominant, dominant, recessive, over-dominant and log-additive) for single SNPs, Akaike information criteria (AIC) and Bayesian information criteria (BIC) were analyzed using SNPStats web tool [2]. Pearson χ 2 (χ 2), two-way Fisher exact test (F, p 2-t), odds ratio (OR), likelihood ratio of positive (LR +) and negative (LR –) tests with corresponding CI95% were also calculated.ResultsExact test for all genotype frequencies distribution of all studied SNPs didn’t reveal significant differences with Hardy-Weinberg equilibrium in all controls and SLE groups. We noted significant increase of minor ТТ genotype frequency of STAT4 rs7574865 in SLE vs healthy women with recessive inheritance model as the best-fitting one according to its less AIC and BIC values (OR=3.78 (CI95% 1.35-10.62); p=0.016; LR + =3.45 (CI95% 1.37-8.60); LR – =0.91 (CI95% 0.84-0.98)). We revealed protection of minor A allele of AGER rs1035798 carriership with log-additive model of inheritance as the best-fitting one according to AIC and BIC values against SLE development in women (OR=0.52 (CI95% 0.33-0.83); p=0.004; LR + =0.70 (CI95% 0.50-0.93); LR – =1.47 (CI95% 1.10-1.86)). We also noted significant increase of minor allele G frequency of TRAF1/C5 rs3761847 in SLE vs healthy women with dominant inheritance model (OR=3.61 (CI95% 1.05-12.38); p=0.019; LR + =1.30 (CI95% 1.03-1.43); LR – =0.36 (CI95% 0.12-0.92)) and increase of AA genotype frequency in healthy women (p 2-t =0.041). We revealed that minor allele G of PTPN2 rs2542151 is more frequent in SLE women vs healthy controls and has overdominant model of inheritance (OR=1.98 (CI95% 1.09-3.59); p=0.026; LR + =1.57 (CI95% 1.07-2.20); LR – =0.79 (CI95% 0.62-0.97)).There were no significant differences in genotypes and alleles distribution for PTPN22 rs2476601, RUNX1 rs9979383, SLC7A11 rs13128867 and IL6 rs1800795 in studied population and we noted only non-significant tendency in minor SNP genotypes distribution of IL6R rs4845618 and IL6R rs2228145 between healthy controls and women with SLE.ConclusionOur data suggest the susceptibility to SLE in women with ТТ genotype of STAT4 rs7574865 polymorphism and allele G carriers of both TRAF1/C5 rs3761847 and PTPN2 rs2542151 as well as protective role of AGER rs1035798 A allele carriership againt SLE development in women of Belarusian population.References[1]Ghodke-Puranik Y, Niewold TB. Immunogenetics of systemic lupus erythematosus: A comprehensive review. J Autoimmun. 2015;64:125-36.[2]Solé X, Guinó E, Valls J, Iniesta R, Moreno V. SNPStats: a web tool for the analysis of association studies. Bioinformatics 2006;22(15):1928–29.AcknowledgementsThis research was supported by The Research Technical Program “DNA Identification” (2017–2021), project number: 6.4Disclosure of InterestsNone declared

Background:Rheumatoid arthritis (RA) is a chronic systemic disorder of the connective tissue of still unknown aetiology and complex autoimmune pathogenesis that primarily affects small joints. HLA alleles provide for 11-37% of the RA heritability, suggesting the substantial role of the non-HLA loci in genetic predisposition to RA. Among non-HLA loci,IL6, IL6RandSTAT4genes attract attention, however, the data concerning their influence on RA risk are somewhat contradictory.Objectives:The aim of the study was to analyze the involvement of four SNPs (STAT4rs7574865,IL6rs1800795,IL6Rrs2228145 and rs4845618) in RA susceptibility.Methods:187 patients diagnosed with RA (mean age 58.2 ± 11.9), and 380 healthy blood donors (mean age 37.18 ± 10.69 years) were included into the study. DNA extraction from peripheral blood samples was performed using the phenol-chloroform method. SNPs were genotyped using the real-time PCR with fluorescent probes. The allele and genotype frequencies were compared using the χ2 test. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using the VassarStats online tool.Results:Utilizing recessive genetic model we found an association between TT genotype ofSTAT4rs7574865 (OR = 2.362; 95%CI [1.0378 – 5.376], p = 0.038) and RA. ForIL6rs1800795, it was found that CC genotype had significantly higher frequency among patients with rheumatoid arthritis as compared to that in controls (OR = 1.52; 95%CI [1.02 – 2.27], p = 0.0456). No associations ofIL6Rrs2228145 and rs4845618 SNPs with risk of RA were found in the total group of patients vs. controls. It was also shown thatIL6rs1800795 CC genotype frequency was significantly higher among the patients with RF-negative status (p = 0.0019).Conclusion:Thus, we provide evidence for association of theSTAT4rs7574865 andIL6rs1800795 variants with risk of RA in the Belarusian population, some features of interplay being revealed between gene polymorphisms analyzed and RA antibody status. Abovementioned SNPs may contribute to RA genetic susceptibility in the Belarusian population.Disclosure of Interests:None declared

BackgroundAdverse drug reactions (ADRs) associated with glucocorticoid (GK) use are registered in 30-60% cases of GK therapy in rheumatoid arthritis (RA) patients when the prescribed daily doses exceed 10 mg during the period more than month. In the case of continuous GK therapy with the daily doses above 20 mg during the period more than 6 months GK dependence (GKD) develops. GK withdrawal syndrome is the main GKD criterion.ObjectivesTo reveal genetic markers of GK ADRs as GKD in RA patients.MethodsIn the observational trial of RA patients (n=522: 423 women, 99 men) detailed pharmacological anamnesis/catamnesis was collected. We investigated a number of genetic markers: erythrocytic antigens of AB0, Rh0, MN, P and Lewis blood groups, haptoglobin phenotypes, HLA antigens of A, B, C, DR, DQ locuses and Bw4-6 and DR51-53 super-types. Statistical significance was estimated by Fisher exact test (F). We selected the prognostic markers by means of Gamma correlation coefficient (RG). Likelihood ratio of positive (LR+) and negative (LR–) tests and prognostic odds ratio (pOR) of revealed markers as well as GK ADRs and GKD pre-test (Ppre) and post-test (Ppost) probabilities were calculated. Ppost was calculated by means of formula based on the Bayes theorem (Kullback information estimate).ResultsWe revealed GK ADRs in 50.9% RA patients (CI95 46.3-55.5%), in 54.6% women and in 34.9% men (F, p2-t=0,0015). GK ADRs as GKD was revealed in 45.5% RA patients (CI95 41.0-50.2%): in 48.8% women and in 31.3% men (p2-t=0.0048). Ppre=50% in women and Ppre=30% in men. Thus female sex is a predictor of GK ADRs and GKD. We revealed no association between AB0, Rh0, MN, P and Lewis blood groups and GKD (pi) for GKD presence and absence were calculated for 3 ranges: JHp1-1=0.252, JHp2-1=0.058, JHp2-2=0.204; total Ji=0.514 was above the significant level (Jxi≥0.5). Diagnostic coefficients (DC) used for the GKD prognosis in women were -4.7, -1.1 and 1.9 correspondingly, so Hp1-1 phenotype is GKD protective factor, and Hp2-2 phenotype is GKD risk factor.Some HLA antigens associated with GKD (table 1). Their informative values for the GKD prognosis were calculated (table 2).Table 1.Significant associations between HLA antigens and GKDHLA antigenRGZppcor1A190.512.90.00360.0284B120.362.90.00350.0546DR10.502.70.00620.0426DQ10.452.80.00470.01871p value after the Bonferroni correction.Table 2.Information value of HLA antigens for the GKD prognosisHLA antigenPhenotypeJxijJxiDCA19A19+0.280.672.1A19–0.39−2.9DR1DR1+0.340.642.6DR1–0.30−2.2DQ1DQ1+0.370.612.9DQ1–0.24−1.9Total Kullback information estimates for HLA A19, DR1 and DQ1 antigens were above the significant level (Jxi≥0.5).ConclusionsHLA A19, DR1 and DQ1 antigens could be used as GKD predictors in the case of indefinite prognosis.Disclosure of InterestNone declared