Investigation of the Pathogenic Variants Induced Sjogren’s Syndrome in Turkish Population

Investigation of the Pathogenic Variants Induced Sjogren’s Syndrome in Turkish Population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Investigation of the Pathogenic Variants Induced Sjogren’s Syndrome in Turkish Population Ulku Terzi, Ilker Ates, Abdulsamet Erden, Sinan Suzen, Lalu Muhammad Irham This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3978557/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Sjögren’s syndrome is a chronic autoimmune disorder of unspecified etiology implicating exocrine glands. SS patients illustrate dry eyes and mouth, joint pain, fever and neurological symptoms. Hormones, immune dysregulation, and environmental and genetic factors play the primary roles in the development of the disease. Previous studies reported that HLA-II, STAT4, BAFF and TINIP1 polymorphisms have a pivotal role in SS development, however, the variant on each gene has not been investigated in the Turkish population. Therefore, this study aims to identify and evaluate the association between four variants of the four mentioned genes above and the development of Sjögren's syndrome. This study recruited 40 healthy subjects and 115 patients with Sjögren's syndrome in a Turkish population. All genomic variants were detected using the PCR-RFLP technique. We observed that SNP rs1130380, rs7574865, rs9514828, and rs17728338 were associated with SS development. We herein highlighted that the subjects with 1/2 or 2/2 Allele (%) had a higher susceptibility to SS development than those with the 1/1 Allele. Furthermore, the allele frequency of each variant was then assessed in multiple continents, including African, American, European, and Asian cohorts. Interestingly, our data shows that upregulating variants are at higher frequencies compared to European American and Asian populations, which implies that Turkish populations might be relatively susceptible to SS development related to these variants. The results indicated that all variants were significantly associated with the development of the SS disease in the Turkish population. Sjögren’s syndrome gene polymorphism autoimmune diseases variants Figures Figure 1 1. Introduction Sjögren’s syndrome (SS) is a chronic autoimmune disease of unidentified etiology including exocrine glands. SS patients show dry eyes and mouth, joint pain, fever and neurological symptoms [ 1 ]. Yet uncertain interplay of genetic, epigenetic and environmental procedures accounts for the initiation, perpetuation, and sustainability of the autoimmune inflammatory reply towards the influenced epithelium [ 2 ]. SS is frequently named “autoimmune epithelitis” [ 3 ] since epithelial cells play a primary function in this disorder as both targets and initiators of the autoimmune process [ 4 ]. The epithelial cells create proinflammatory cytokines, which in turn guides to defective function of the salivary glands [ 5 ]. The SS can be disunited into primary SS (pSS) and secondary SS (sSS). A lack of disorders other than rheumatologic disease represents pSS [ 6 , 7 ], whereas sSS arises secondary to autoimmune diseases involving systemic sclerosis, systemic lupus erythematosus or rheumatoid arthritis. The moderate incidence of SS is 6.0 per 100.000 people and is 10-fold higher in women corresponded to men. The incidence of SS raises with age; the highest incidence in women happens at 55–64 years and in men at 65–74 years [ 8 ]. Multiple investigators have broadly examined the reasons underlying SS and have discovered multifactorial pathogenesis of SS such as genetic, environmental, neuroendocrine and immune (related to immune cells and cytokines) factors [ 9 ]. The pathogenesis of SS has not been completely clarified, and there stay problems in the clinical diagnosis of SS. Genetic preconception is a condition ( HLA-DRB1*03 : 01, DQA1*05: 01, DQB1*02: 01 [ 10 , 11 ], X chromosomes), but epigenetic changes [ 12 ] are also needed for the evolution of this autoimmune disorder. An improved risk for connective tissue illnesses (such as systemic lupus erythematosus [SLE], systemic scleroderma [SS]) or other autoimmune disorders has been exhibited in SS patients' families [ 13 ]. Other elements such as immune dysregulation, hormones, and environmental impacts among other factors, stress [ 14 ], infections [ 15 ], drugs [ 16 ], vaccines [ 17 ], or silicone breast implants [ 18 ] are currently being conferred then guide to misdirected activation of the innate and adaptive immune system. This triggers the type 1 and type 2 interferon signaling cascades that promote B cells' proliferation. Genetic susceptibility plays an essential role in SS pathogenesis. Actual data appeared in the last years ensuring that the essential players in SS pathogenesis are the continuous activation of type I interferon system (IFN) concurrently with autoreactive B and T cells and disease-associated autoantibodies, therefore, showing attractive targets for individualised therapeutic strategies in SS. Earlier studies utilised SS genome-wide association studies (GWAS) to specify HLA-II, BAFF, IRF5-TNPO3, STAT4, IL12A, FAM167A-BLK, DDX6-CXCR5 , and TNIP1 as risk locations, IRF5, and STAT4 as susceptibility genes for SS (11). HLA complex is positioned on the short arm of chromosome 6 [ 19 – 21 ]. HLA antigens are expressed on many cell surfaces and have a primary role in the acclaim of antigenic stimulants, stimulation of the immune system, and regulation of cellular and humoral immunity [ 20 ]. HLA complexes are categorized into three classes as Class I, Class II and Class III [ 21 ]. HLA Class II proteins have the most hereditable susceptibility to autoimmune diseases such as SS. HLA-DQB1 is the beta 1 subunit of the HLA-DQ surface receptor, in the Human Major Histocompatibility Complex (MHC), part of immune regulation. It is linked to immune conditions [ 22 ]. This gene is found to be associated with several diseases; DQB1*0201 and DQB1*0302 are high risk, particularly together in Type I diabetes, DQB1*06:02 form has been strongly linked with narcolepsy [ 23 – 25 ], The highest risk in Celiac disease is DQB1*02 form with the HLA-DQ2.5 heterodimer (HLA-DQA1*05-DQB1*02) [ 26 ], DQB1*0501 is associated with scleroderma in Chinese population [ 27 ], DQB1*03 confers susceptibility to hepatitis C in Japanese population [ 28 ] and DQB1*0202 is possibly connected to podoconiosis [ 29 – 30 ]. Although it has been shown that the HLA-DQB1 gene is associated with Sjögren's Syndrome, there is no scientific data on the effect of the HLA-DQB1*03 rs1130380 polymorphism on the development of the disease. The signal transducer and activator of transcription 4 (STAT4) is a partner of the STAT family and localizes to the cytoplasm. STAT4 is phosphorylated after a variety of cytokines [ 31 ] attach to the membrane and then dimerized STAT4 translocates to the nucleus to regulate gene expression. STAT4 plays a vital function in a wide variety of cells and the pathogenesis of diverse human disorders, particularly multiple kinds of autoimmune and inflammatory illnesses, through activation by various cytokines via the Janus kinase (JAK)-STAT signalling path [ 32 ]. Various combinations of STAT4 are induced by a variety of cytokines (cytokines play essential role in a broad spectrum of biological processes, particularly in inflammation and immune response, are key mediators of the toxic and pathogenic effects seen in humans [ 33 ] such as interleukin (IL)12, type I interferon (IFN-I), IL23, IL2, IL27, and IL35. B cell-activating factor (BAFF) is a partner of the TNF superfamily that regulates immune responses. BAFF is a cytokine with influential impacts on the development and selecting of B cells [ 1 ] It is expressed as membrane-bound (mBAFF) and soluble protein (sBAFF) [ 34 – 37 ]. Sjöstrand et al. [ 38 ] uncovered raised BAFF expression in the immune cells of pSS patients, mainly neutrophils. In addition, they specified an approvingly preserved IFN-stimulated response element (ISRE) area close to the BAFF gene promoter, which was functionally confirmed. The association of BAFF polymorphisms in the development of further autoimmune disorders has been revealed theretofore [ 39 – 47 ]. BAFF rs9514828 polymorphism is found to be linked to several inflammatory and autoimmune diseases via several scientific studies [ 48 – 52 ]. TNFAIP3 (Tumor necrosis factor-alpha inducible protein 3) interacting protein 1 (TNIP1) encoded by the TNIP1 gene is a vital signalling protein in the NF-κB path. It operates together with the TNFAIP3 protein to repress NF-κB activation. The association of TNIP1 gene polymorphism with many autoimmune diseases such as systemic sclerosis, rheumatoid arthritis (RA), psoriasis, and SLE was demonstrated [ 53 – 58 ]. TNIP1 rs17728338 polymorphism is revealed to be associated with some inflammatory and autoimmune diseases through scientific studies [ 59 – 62 ]. Although many variants have been identified which were associated with SS development, however the variants (rs1130380, rs7574865, rs9514828, rs17728338) have not been investigated in Turkish population. Thus, the purpose of this study was to investigate whether the polymorphisms ( HLA-DQB1*03 rs1130380, STAT4 rs7574865, BAFF rs9514828 and TINIP1 rs17728338) is associated with SS development in in in a group of Turkish patients. 2. Materials and methods 2.1 Study Population Our study group consisted 40 healthy subjects and 115 patients with age range of 18–75 with Sjögren's syndrome with SS who were attending the Rheumatology Clinic at the Ankara Bilkent City Hospital [Figure 1 ]. SS was diagnosed according to the criteria set out by American College of Rheumatology/European League Against Rheumatism classification criteria for primary Sjögren’s Syndrome [ 7 ]. Each subject responded a brief questionnaire that gives information about previous medical history, smoking and lifestyle. Informed consent was obtained from all subjects in accordance with the Helsinki Declaration (2013) of the World Medical Association [ 63 ]. We have had approval of the Ankara University Faculty of Medicine Ethic Committee for this research and possess informed consent of each subject participating in the study. The power analysis has been performed for choosing the number of control and patient group. 2.2 Blood samples collection The 5 ml blood samples of the individuals of the control and patient groups participating in the study were taken under the supervision of a doctor at the Ankara Bilkent City Hospital Rheumatology Clinic. Blood samples were taken into heparinized tubes and then transferred to Ankara University Faculty of Pharmacy, Department of Pharmaceutical Toxicology Research Laboratory with cold chain without wasting any time, where all experiments were performed. DNA isolation method, which is the preliminary step of genotyping experiments, was applied to blood samples and DNA samplings of each individual in the experimental groups were isolated. These DNA samplings were stored at -20 0 C until genotyping experiments were performed. Genotyping experiments were performed using the PCR-RFLP (Polymerase Chain Reaction-Restriction Fragment Length Polymorphism) method. 2.3. DNA isolation and DNA quantification The Wizard Genomic DNA Purification kit, produced by Promega, was used for the isolation of each individuals' DNA sample. The purity of the DNA samples we obtained was determined by dividing the absorbance value read at 260 nm in the spectrophotometer by the absorbance value read at 280 nm. Accordingly, it was determined that DNA samples with values ​​between 1.7 and 2.0 were isolated with sufficient purity. 2.4. Genotyping experiments 2.4.1. Determination of HLA-DQB1*03 rs1130380 gene polymorphism The HLA-DQB1*03 rs1130380 encoded polymorphism was detected according to the method of Soetjipto et al [ 64 ]. HLA-DQB1*03 rs1130380 polymorphism analyses were performed using PCR and RFLP methods. 50 µl total reaction mix contains, 5 µl 10x PCR buffer, 100 mM MgCl 2 , 100µmol dNTP mix, 77 pmol forward primer DQBS43 (5'-TGC TAC TTC ACC A(C/T) GGG-3') and reverse primer DQBA249 (5'-GTA GTT GTG TCT GCA (C/T)A C-3'), 5 000U Taq DNA polymerase and 50 ng DNA. Following the PCR reaction, the RFLP method was applied by restriction with MspI restriction enzyme overnight at 37 0 C. After enzyme digestion, PAGE electrophoresis was performed and three bands of 99, 72 and 36 bp showed the wild type genotype (*0301), two bands of 171 and 36 bp showed heterozygous genotype (*0303) and a single band of 207 bp showed the presence of homozygous mutant genotype (*0601). 2.4.2. Determination of STAT4 rs7574865 gene polymorphism The STAT4 rs7574865 encoded polymorphism was detected according to the method of Migita et al [ 65 ]. STAT4 rs7574865 polymorphism analyses were performed using PCR and RFLP methods. 50 µl total reaction mix contains, 5 µl 10x PCR buffer, 100 mM MgCl 2 , 100µmol dNTP mix, 100 pmol forward primer (5'-AAA GAA GTG GGA TAA AAA GAA GTT TG-3') and reverse primer (5'-CCA CTG AAA TAA GAT AAC CAC TGT-3'), 5 000U Taq DNA polymerase and 50 ng DNA. Following the PCR reaction, the RFLP method was applied by restriction with HpaI restriction enzyme overnight at 37 0 C. After enzyme digestion, PAGE electrophoresis was performed and a single band of 147 bp showed the wild type genotype (G allele), three bands of 147, 122 and 25 bp showed heterozygous genotype (G/T allele) and a two bands of 122 and 25 bp showed the presence of homozygous mutant genotype (T allele). 2.4.3. Determination of BAFF rs9514828 gene polymorphism The BAFF rs9514828 encoded polymorphism was detected according to the method of Marin-Rosales et al [ 66 ]. BAFF rs9514828 polymorphism analyses were performed using PCR and RFLP methods. 30 µl total reaction mix contains, 5 µl 10x PCR buffer, 2 mM MgCl 2 , 200µmol dNTP mix, 25 ng forward primer (5'-TTG TAC ACC GAC CTG TTA GG-3') and reverse primer (5'-TGG AAG TAA GTC CAG ACT GGG AAT-3'), 5 000U Taq DNA polymerase and 40 ng DNA. Following the PCR reaction, the RFLP method was applied by restriction with HpaI restriction enzyme overnight at 37 0 C. After enzyme digestion, PAGE electrophoresis was performed and two bands of 261 and 137 bp showed the wild type genotype (C allele), three bands of 398, 261and 137 bp showed heterozygous genotype (C/T allele) and a single band of 398 bp showed the presence of homozygous mutant genotype (T allele). 2.4.4. Determination of TNIP1 rs17728338 gene polymorphism The TNIP1 rs17728338 encoded polymorphism was detected according to the method of Li et al [ 67 ]. TNIP1 rs17728338 polymorphism analyses were performed using PCR and RFLP methods. 20 µl total reaction mix contains, 5 µl 1x PCR buffer, 1.5 mM MgCl 2 , 200µmol dNTP mix, 30 ng forward primer (5'-GTA TGT TTT GCA CCT AGC ACG T-3') and reverse primer (5'-CCA TTC GGG AGC CTT TTG CCA-3'), 1U Taq DNA polymerase and 20 ng DNA. Following the PCR reaction, the RFLP method was applied by restriction with NcoI restriction enzyme overnight at 37 0 C. After enzyme digestion, PAGE electrophoresis was performed and a single band of 197 bp showed the wild type genotype (G allele), three bands of 197, 174and 23 bp showed heterozygous genotype (G/A allele) and two bands of 174 and 23 bp showed the presence of homozygous mutant genotype (A allele). 2.5. Statistical analysis Statistics analysis was performed by SPSS softwareversion 27.0 for windows (SPSS Inc., Chicago, IL, USA). The frequencies of genotypes and alleles for all the studied polymorphisms were determined assuming co-dominant inheritance. The statistical significance of the genotype and allele frequency variables between the patients with SS and control group was evaluated by chi-square test with Yates correction for small numbers. Using the chi-square test, Hardy-Weinberg equilibrium was tested for the studied four SNPs in patients with SS and controls. Relative risk associated with the significant genotype was estimated by the odds ratio (OR). OR with 95% confidence intervals (95% CI) was tested using a chi-square distribution, and the null hypothesis being tested is OR = 1. Allele frequencies were also evaluated. P-values < 0.05 were considered as statistically significant. 3. Results The aim of this study is to identify the association between four variants included rs1130380 encoded the HLA-DQB1*03 gene , rs7574865 encoded STAT4 gene, rs9514828 enoded the BAFF gene and rs17728338 enoded the TINIP1 gene and the development of the Sjögren's syndrome. This study recruited 155 subjects (40 healthy subjects, 115 patients with Sjögren's syndrome) in a Turkish population. In Table 1 the demographic data of the all subjects were shown. Table 1 Demographic data of the subjects Parameter Control group Patient group Male Female Male Female Number of subjects 3 37 10 105 Age (mean.±SD) 53,33 ± 4,51 53,43 ± 11,92 54,40 ± 7,97 53,79 ± 10,77 Smoking status (%) Yes No 1 (%33,3) 2 (%66,7) 8 (%21,6) 29 (%78,4) 2 (%20,0) 8 (%80,0) 21 (%20,0) 84 (%80,0) Correlations between SS age and smoking were evaluated by multiple linear regressions but no significant association was obtained. Table 2 Multiple logistic regression analysis for possible risk factors of SS Risk factor OR (95% CI) Age 0,67 (0,23 − 0,91) Smoking 1,21 (0,57 − 1,87) Gender 3,09 (2,07 − 5,78) b Family history (%) 1,48 (1,04 − 2,70) a anti -Ro/SSA seropositivity 3,17 (1,64 − 6,25) b anti- La/SSB seropositivity 2,91 (1,53 − 5,11) b RF seropositivity 2,55 (1,49 − 4,27) b ANA seropositivity 2,04 (1,63 − 3,78) b Primer/seconder SS 1,61 (1,15 − 3,44) a Disease Year (x̄) 2,21 (1,53 − 4,03) b a p < 0.05, b p < 0.01 Age, smoking, gender, family history, anti-Ro/SSA seropositivity, anti-La/SSB seropositivity, RF seropositivity, ANA seropositivity, SS type (primer/seconder) and disease year were evaluated as risk factors for SS so they were statistically analyzed by multiple logistic regression analysis. Due to the data, except age and smoking other all factors have a significant relationship with SS development (family history and type of SS factors’ significance limit is < 0.05; gender, disease year and all seropositivity factors’ significance limit is < 0.01). All the data related with these are shown in Table 2 . The genotypic distribution of all the studied gene polymorphisms were demonstrated in Table 3 . According to the outcomes, all examined variants displayed a significant relationship with the development of the disease. The HLA-DQB1*03 1/2 and 2/2 allele carriers were significantly over-represented in SS patients. The OR for SS with the HLA-DQB1*03 variant was admiringly raised (OR = 6.05: 95%CI, 2.78–13.20). The OR of the STAT4 variant was improved in SS patients about 6 fold similarly with HLA-DQB1*03 variant (OR = 5.88: 95%CI, 2.69–12.86). Likewise with the others, BAFF variant was amazingly triggered in SS patient about 7 fold compared with the controls (OR = 6.71: 95%CI, 3.05–14.79). In regards with the last studied variant TNIP1, it was also raised in SS patients compared with the controls and this enhancement had a significancy (OR = 4.87: 95%CI, 2.26–10.50). All the impacts had a P value smaller than 0.001. Genotype distributions for all the gene polymorphisms suit forecasts for Hardy–Weinberg equilibrium. Table 3 The genotypic distribution of the studied genes Region 1/1 Allele* (%) 1/2 or 2/2 Allele (%) Total OR * (CI) P HLA-DQB1*03 rs1130380 Control Patient 26 (65,0) 27 (23,5) 14 (35,0) 88 (76,5) 40 115 1,00 6,05 (2,78 − 13,20) < 0,001 STAT4 rs7574865 Control Patient 27 (67,5) 30 (26,1) 13 (32,5) 85 (73,9) 40 115 1,00 5,88 (2,69 − 12,86) < 0,001 BAFF rs9514828 Control Patient 24 (60,0) 21 (18,3) 16 (40,0) 94 (81,7) 40 115 1,00 6,71 (3,05–14,79) < 0,001 TNIP1 rs17728338 Control Patient 23 (57,5) 25 (21,7) 17 (42,5) 90 (78,3) 40 115 1,00 4,87 (2,26 − 10,50) < 0,001 *1 allele major variant, 2 allele minor variant In Table 4 , allele frequencies of all the studied gene polymorphisms were given. When we evaluate the results, it is clearly seen that the allele 2 frequencies were about two folds increased in SS patients compared to the controls. Table 4 Allele frequencies of the studied genes Allele Allele Frequency HLA-DQB1*03 STAT4 BAFF TNIP1 Control group 1/1 0.775 0.790 0.725 0.730 2/2 0.225 0.210 0.275 0.270 Patient group 1/1 0.505 0.510 0.465 0.510 2/2 0.495 0.490 0.535 0.490 P* < 0,01 < 0,01 < 0,05 < 0,05 * comparison between the 2/2 variant of the patients with those of controls The allele frequency of each variant (rs1130380, rs7574865, rs9514828, rs17728338) was then assessed in regional populations including African, American, European, and Asian cohorts. The results of our study indicate that (rs1130380, rs7574865, rs9514828, rs17728338)-upregulating variants are more common in Turkish populations than in European, American, and other Asian populations, suggesting Turkish populations may be more susceptible to the development of SS (Table 5 ). Table 5 Allele frequencies SNPs examined in this study and multiple continents SNP Position (hg19) (bp) Gene Location Allele Allele Frequencies(N) Ref Eff* EUR AFR AMR ASN Our rs1130380 chr6: 32632694 HLA-DQB1 Missense C A,G,T 0 0 0 0 0.495 rs7574865 chr2:191964633 STAT4 Intron T G 0.770 0.860 0.690 0.660 0.490 rs9514828 chr13:108921373 BAFF - C T 0.530 0.090 0.280 0.400 0.535 rs17728338 chr5:150478318 ANXA6 - C T 0.070 0.070 0.050 0.110 0.490 EUR, European; AFR, African; AMR, American; ASN, Asian. Ref, Reference and Eff, Effect allele of EUR, AFR, AMR, ASN were extracted from the HaploReg Version 4.1 ( https://pubs.broadinstitute.org/mammals/haploreg ). 4. Discussion To the best of our knowledge, this study is the first that all these four gene polymorphisms at the same time which are thought to have a relationship with SS development especially in Turksih population. Sjögren’s syndrome (SS) is a chronic autoimmune disease and genetic susceptibility plays a major role in SS pathogenesis. Chused and his coworkers [ 68 ] firstly demonstrated Human Leucocyte Antigen (HLA) genes as a risk factor for SS in 1977. The relationship between HLA-DR3 and SS was demonstrated especially in the white ethnicity. On the other side, association between SS and HLA-DR3-DQ haplotypes was revealed in various ethnic groups [ 10 , 69 – 78 ]. Numerous methods have been accustomed including the Genetic Linkage analysis, positional candidate gene analysis using microsatellite markers, and more newly the GWAS studies completed on a huge series of SS patients and controls with SNPs (single nucleotide polymorphism) markers [ 11 , 79 , 80 ]. Nevertheless, a meta-analysis pinpoints DRB1*0301, DQA1*0501, DQB1*0201, and DRB1*03 alleles as risk factors for SS, while pinpointing DQA1*0201, DQA1*0301 and DQB1*0501 alleles as preservatives [ 81 ]. Lately, a powerful connection between HLA-DRA, HLA-DQB1 and HLA-DQA1 and SS in 6p21 locus in an extensive study in Europe was documented [ 11 ]. In a Chinese research, HLA-DRB1/HLA-DQA1 in 6p21.3 locus and two separate signals linked with HLA-DPB1/COL11A2 [ 82 ]. Degeneration of autoreactive T cell toleration via the existence of unnatural antigen displays the primary role of HLAs in autoimmune diseases. The disorder association of HLA-suspected alleles is familiar in autoimmune diseases and further specific alleles and haplotypes are developed, additional alleles straightforward targeting of typical autoantigens [ 83 ]. HLA Class II is linked with autoantibody production in SS, whereas anti-Ro/SSA and anti-La/SSB are particularly more elevated in HLA-DQ1/HLA-DQ2 heterozygous patients [ 84 ] but not connected to further clinical characteristics [ 10 ]. HLA-DRB1*1501-DRB1*0301 is associated with anti-ACA (anticyclic citrullinated antibodies) [ 85 ]. Amino acid deviations in the hypervariable province (HVR) of the HLA complex influence peptide binding and T cell display; The association of specific divergences in binding wells 7 and 9 of HLA-DRB1 with differences in depth and polarity was established in the Chinese population [ 77 ]. Although HLA Class I and HLA Class III genes were also investigated in the subsequent years, investigations concentrated on HLA Class II genes. Multitudinous studies were performed that showing the relationship between HLA alleles and SS. Different genetic polymorphisms of HLA have been associated with predisposition and/or outcome of different infectious diseases such as hepatitis B virus (HBV), hepatitis C virus (HCV), Chikungunya, Chagas, dengue, influenza A(H1N1) and tuberculosis [ 86 – 90 ]. A meta-analysis performed by Cruz-Tapias et al., [ 81 ] pinpointed some of HLA alleles such as DRB1*0301, DQA1*0501, DQB1*0201, and DRB1*03 were risk factors for SS and the others including DQA1*0201, DQA1*0301 and DQB1*0501 as preservatives. Recently, a strong association between HLA-DRA, HLA-DQB1 and HLA-DQA1 and SS in 6p21 locus in a comprehensive study in Europe was reported [ 11 ]. HLA-DQB1 is the beta 1 subunit of the HLA-DQ surface receptor, in the MHC, part of immune regulation. It is linked to immune disorders [ 22 ]. This gene is found to be linked with some disorders such as Type I diabetes, narcolepsy, celiac disease and scleroderma. Although it has been documented that the HLA-DQB1 gene is associated with Sjögren's Syndrome, there is no scientific data on the impact of the HLA-DQB1*03 rs1130380 polymorphism on the development of the disease. From this point of view, our results are very valuable in terms of evaluating the possible effect of HLA-DQB1 gene variation on SS. Due to our results, HLA-DQB1*03 rs1130380 variation had a significant relationship with the development of SS about 6 fold compared with controls (OR = 6.05: 95%CI, 2.78–13.20). STAT4 is a member of the STAT family and it has a crucial position in a broad variety of cells and the pathogenesis of various human diseases, particularly multiple types of autoimmune and inflammatory disorders, via activation by different cytokines via the Janus kinase (JAK)-STAT signalling path [ 32 ]. STAT4 is a critical transcription factor for the transmission of IL-12, IL-23 and Type 1 interferon-mediated signals implicated in Th1 and Th17 differentiation, activation of monocytes and INFγ production [ 91 – 93 ]. STAT4 haplotypes have been suggested to be a risk factor for the development of SLE and RA in the caucasians and its connection with SS [ 94 ]. STAT4 polymorphism was investigated in different ethnic groups in other loci such as rs7574865 [ 95 ] and rs7582694 [ 96 ]. In these three studies, it was pointed that rs7582694 polymorphism posed a risk for SS. rs7574865 of the STAT4 gene has been reported in a massive study of Swedes to be connected to both lupus (SLE) and rheumatoid arthritis [ 97 ]. RA risk associated with rs7574865(T) allele was also discovered in studies of 923 Spanish, 273 Swedish, and 876 Dutch patients [ 98 ]. The rs7574865(T) allele is linkedwith an increased risk for type-1 diabetes established on a study of Greek patients [ 99 ]. In research including 2,776 Spanish subjects, it was observed that the rs7574865(T) allele was connected to rheumatoid arthritis, Crohn's disease, ulcerative colitis, and type-1 diabetes, but not with multiple sclerosis [ 100 ]. In a study of 124 Caucasian patients with primary SS, it was found that the rs7574865(T) allele was linked with a more elevated risk for this disease [ 94 ]. Similarly, we also found this variant had a tremendous increased effect on the development of SS about 6-fold compared to the controls (OR = 5.88: 95%CI, 2.69–12.86). BAFF is a member of the TNF superfamily which regulates immune responses. Sjöstrand et al. [ 38 ] discovered extended BAFF expression in the immune cells of pSS patients, especially neutrophils. They also established an admiringly preserved IFN-stimulated response element (ISRE) area close to the BAFF gene promoter, which was functionally confirmed. The association of BAFF polymorphisms in the development of additional autoimmune diseases has been displayed previously [ 39 – 47 ]. BAFF rs9514828 polymorphism is found to be connected with numerous autoimmune and inflammatory disorders such as SS, lymphoma, leukemia, haemophilia and periodontitis through some scientific investigations [ 48 – 52 ]. In an investigation by Nezos et al., [ 49 ] it was found that high risk pSS group was characterized by higher frequency of the minor T allele of the rs9514828 BAFF polymorphism compared to healthy controls. Our findings are also in line with this study in which we found that in SS patients the minor variant had approximately 7-fold risk compared to the controls (OR = 6.71: 95%CI, 3.05–14.79). TNIP1 is encoded by the TNIP1 gene which is a critical signalling protein in the NF-κB path. It functions with the TNFAIP3 protein together to suppress NF-κB activation. The connection of TNIP1 gene polymorphism with multiple autoimmune disorders such as systemic sclerosis, rheumatoid arthritis (RA), psoriasis, and SLE was demonstrated [ 53 – 58 ]. TNIP1 rs17728338 polymorphism is revealed to be linked to several inflammatory and autoimmune diseases including psoriatic arthritis and psoriasis via scientific investigations [ 59 – 62 ]. There are limited studies related with the TNIP1 rs17728338 polymorphism and SS. Nordmark et al.,[ 58 ] figured out that polymorphisms in TNIP1 are related with antibody-positive primary SS. We also found that minor variant of the TNIP1 polymorphism was a risk factor in SS patients with about 5-fold compared to the control group (OR = 4.87: 95%CI, 2.26–10.50). We acknowledge that our study needs to be validated by future studies in other population using more samples size, however, our study offers the findings that polymorphism of rs1130380, rs7574865, rs9514828, rs17728338 have a pivotal association with the SS in Turkish Population. 5. Conclusion Our study showed that 4 SNPs (rs1130380, rs7574865, rs9514828, rs17728338) have a significant association with the SS in Turkish Population. According to our results it was obviously seen that all studied gene polymorphisms are crucial risk factors for the development of SS. 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Palomino-Morales RJ, Diaz-Gallo L-M, Witte T, Anaya J-M, Martin J . Influence of STAT4 polymorphism in primary Sjogren's syndrome. J Rheumatol. 2010;37(5):1016-9. Gestermann N, Mekinian A, Comets E, Loiseau P, Puechal X, Hachulla E, Gottenberg J-E, Mariette X, Miceli-Richard C . STAT4 is a confirmed genetic risk factor for Sjögren's syndrome and could be involved in type 1 interferon pathway signalling. Genes Immun. 2010;11(5):432-8. Yuan H, Feng J-B, Pan H-F, Qiu L-X, Li L-H, Zhang N, Ye D-Q . A meta-analysis of the association of STAT4 polymorphism with systemic lupus erythematosus. Mod Rheumatol. 2010;20(3):257-62. Orozco G, Alizadeh BZ, Delgado-Vega AM, Gonzalez-Gay MA, Balsa A, Pascual-Salcedo D, Fernandez-Gutierrez B, Gonzalez-Escribano MF, Petersson IF, van Riel PLCM, Barrera P, Coenen MJH, Radstake TRDJ, van Leeuwen MA, Wijmenga C, Koeleman BPC, Alarcon-Riquelme M, Martin J . Association of STAT4 with rheumatoid arthritis: a replication study in three European populations. Arthritis Rheum. 2008;58(7):1974-80. Zervou MI, Mamoulakis D, Panierakis C, Boumpas DT, Gouielmos GN . STAT4: a risk factor for type 1 diabetes? Hum Immunol. 2008;69(10):647-50. Martinez A, Varade J, Marquez A, Cenit MC, Espino L, Perdigones N, Santiago JL, Fernandez-Arquero M, de la Calle H, Arroyo R, Mendoza JL, Fernandez-Gutierrez B, de la Concha EG, Urcelay E . Association of the STAT4 gene with increased susceptibility for some immune-mediated diseases. Arthritis Rheum. 2008;58(9):2598-602. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3978557","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":274780351,"identity":"e8ade828-751a-4dad-8a2c-45a8bc9e59fd","order_by":0,"name":"Ulku Terzi","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Ulku","middleName":"","lastName":"Terzi","suffix":""},{"id":274780352,"identity":"4169def6-9251-41a0-aa13-5d903d65da06","order_by":1,"name":"Ilker Ates","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYBACNnY2KIu9/+ODD2ARQlqYwVoMGBh4DhgbzgCLELIGrkUiwUyYByxCQAcfM1vi44qaP3LyMxLSmG1+bZPnY2Zg/PAxB6/DDhueOWZgbHDmwbHHuX23DduYGZglZ27Dp4W9TbKBzSBxA3tiu3Fuz21GoBY2Zl78Wtp/NvwzqJ/fkMwmbdlz254ILWzHGBvbDBIYTqSxSTP8uJ1IjJZkycY+Y8MNZ84wG/Y23E5uY2ZsxusX+fY2w48N3+Tk5dt7GB/8+HPbdn5788EPH/FoQQWMbWCygVj1IPCHFMWjYBSMglEwUgAArAdKVlWM0GsAAAAASUVORK5CYII=","orcid":"","institution":"Ankara University","correspondingAuthor":true,"prefix":"","firstName":"Ilker","middleName":"","lastName":"Ates","suffix":""},{"id":274780353,"identity":"699ff0bb-b928-41db-94fd-1acf2659c91c","order_by":2,"name":"Abdulsamet Erden","email":"","orcid":"","institution":"Gazi University","correspondingAuthor":false,"prefix":"","firstName":"Abdulsamet","middleName":"","lastName":"Erden","suffix":""},{"id":274780354,"identity":"920f58cc-a427-4e40-a267-93af62bcd128","order_by":3,"name":"Sinan Suzen","email":"","orcid":"","institution":"Ankara University","correspondingAuthor":false,"prefix":"","firstName":"Sinan","middleName":"","lastName":"Suzen","suffix":""},{"id":274780355,"identity":"23a0935c-a316-4f80-950b-98f2e7f48b58","order_by":4,"name":"Lalu Muhammad Irham","email":"","orcid":"","institution":"Ahmad Dahlan University","correspondingAuthor":false,"prefix":"","firstName":"Lalu","middleName":"Muhammad","lastName":"Irham","suffix":""}],"badges":[],"createdAt":"2024-02-22 12:21:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3978557/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3978557/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51778256,"identity":"0ce1cc28-9bf0-4b6a-8c0f-6e27a95c3795","added_by":"auto","created_at":"2024-02-28 21:17:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":96965,"visible":true,"origin":"","legend":"\u003cp\u003eOur study group consisted 40 healthy subjects and 115 patients with age range of 18-75 with Sjögren's syndrome with SS who were attending the Rheumatology Clinic at the Ankara Bilkent City Hospital.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3978557/v1/f4b889d3a00ccac22b7a1f21.png"},{"id":54182745,"identity":"823c4019-4867-4419-aa3d-5d94372c0123","added_by":"auto","created_at":"2024-04-05 16:53:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":496054,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3978557/v1/16f8f669-0a49-4393-8104-f398c5aa18c9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eInvestigation of the Pathogenic Variants Induced Sjogren’s Syndrome in Turkish Population\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSj\u0026ouml;gren\u0026rsquo;s syndrome (SS) is a chronic autoimmune disease of unidentified etiology including exocrine glands. SS patients show dry eyes and mouth, joint pain, fever and neurological symptoms [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Yet uncertain interplay of genetic, epigenetic and environmental procedures accounts for the initiation, perpetuation, and sustainability of the autoimmune inflammatory reply towards the influenced epithelium [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. SS is frequently named \u0026ldquo;autoimmune epithelitis\u0026rdquo; [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] since epithelial cells play a primary function in this disorder as both targets and initiators of the autoimmune process [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The epithelial cells create proinflammatory cytokines, which in turn guides to defective function of the salivary glands [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe SS can be disunited into primary SS (pSS) and secondary SS (sSS). A lack of disorders other than rheumatologic disease represents pSS [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], whereas sSS arises secondary to autoimmune diseases involving systemic sclerosis, systemic lupus erythematosus or rheumatoid arthritis. The moderate incidence of SS is 6.0 per 100.000 people and is 10-fold higher in women corresponded to men. The incidence of SS raises with age; the highest incidence in women happens at 55\u0026ndash;64 years and in men at 65\u0026ndash;74 years [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Multiple investigators have broadly examined the reasons underlying SS and have discovered multifactorial pathogenesis of SS such as genetic, environmental, neuroendocrine and immune (related to immune cells and cytokines) factors [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The pathogenesis of SS has not been completely clarified, and there stay problems in the clinical diagnosis of SS. Genetic preconception is a condition (\u003cem\u003eHLA-DRB1*03\u003c/em\u003e: \u003cem\u003e01, DQA1*05: 01, DQB1*02: 01\u003c/em\u003e [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], X chromosomes), but epigenetic changes [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] are also needed for the evolution of this autoimmune disorder. An improved risk for connective tissue illnesses (such as systemic lupus erythematosus [SLE], systemic scleroderma [SS]) or other autoimmune disorders has been exhibited in SS patients' families [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOther elements such as immune dysregulation, hormones, and environmental impacts among other factors, stress [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], infections [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], drugs [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], vaccines [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], or silicone breast implants [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] are currently being conferred then guide to misdirected activation of the innate and adaptive immune system. This triggers the type 1 and type 2 interferon signaling cascades that promote B cells' proliferation.\u003c/p\u003e \u003cp\u003eGenetic susceptibility plays an essential role in SS pathogenesis. Actual data appeared in the last years ensuring that the essential players in SS pathogenesis are the continuous activation of type I interferon system (IFN) concurrently with autoreactive B and T cells and disease-associated autoantibodies, therefore, showing attractive targets for individualised therapeutic strategies in SS. Earlier studies utilised SS genome-wide association studies (GWAS) to specify \u003cem\u003eHLA-II, BAFF, IRF5-TNPO3, STAT4, IL12A, FAM167A-BLK, DDX6-CXCR5\u003c/em\u003e, and \u003cem\u003eTNIP1\u003c/em\u003e as risk locations, IRF5, and \u003cem\u003eSTAT4\u003c/em\u003e as susceptibility genes for SS (11).\u003c/p\u003e \u003cp\u003eHLA complex is positioned on the short arm of chromosome 6 [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. HLA antigens are expressed on many cell surfaces and have a primary role in the acclaim of antigenic stimulants, stimulation of the immune system, and regulation of cellular and humoral immunity [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. HLA complexes are categorized into three classes as Class I, Class II and Class III [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. HLA Class II proteins have the most hereditable susceptibility to autoimmune diseases such as SS. HLA-DQB1 is the beta 1 subunit of the HLA-DQ surface receptor, in the Human Major Histocompatibility Complex (MHC), part of immune regulation. It is linked to immune conditions [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This gene is found to be associated with several diseases; DQB1*0201 and DQB1*0302 are high risk, particularly together in Type I diabetes, DQB1*06:02 form has been strongly linked with narcolepsy [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], The highest risk in Celiac disease is DQB1*02 form with the HLA-DQ2.5 heterodimer (HLA-DQA1*05-DQB1*02) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], DQB1*0501 is associated with scleroderma in Chinese population [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], DQB1*03 confers susceptibility to hepatitis C in Japanese population [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and DQB1*0202 is possibly connected to podoconiosis [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Although it has been shown that the HLA-DQB1 gene is associated with Sj\u0026ouml;gren's Syndrome, there is no scientific data on the effect of the HLA-DQB1*03 rs1130380 polymorphism on the development of the disease.\u003c/p\u003e \u003cp\u003eThe signal transducer and activator of transcription 4 (STAT4) is a partner of the STAT family and localizes to the cytoplasm. STAT4 is phosphorylated after a variety of cytokines [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] attach to the membrane and then dimerized STAT4 translocates to the nucleus to regulate gene expression. STAT4 plays a vital function in a wide variety of cells and the pathogenesis of diverse human disorders, particularly multiple kinds of autoimmune and inflammatory illnesses, through activation by various cytokines via the Janus kinase (JAK)-STAT signalling path [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Various combinations of STAT4 are induced by a variety of cytokines (cytokines play essential role in a broad spectrum of biological processes, particularly in inflammation and immune response, are key mediators of the toxic and pathogenic effects seen in humans [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] such as interleukin (IL)12, type I interferon (IFN-I), IL23, IL2, IL27, and IL35.\u003c/p\u003e \u003cp\u003eB cell-activating factor (BAFF) is a partner of the TNF superfamily that regulates immune responses. BAFF is a cytokine with influential impacts on the development and selecting of B cells [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] It is expressed as membrane-bound (mBAFF) and soluble protein (sBAFF) [\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Sj\u0026ouml;strand et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] uncovered raised BAFF expression in the immune cells of pSS patients, mainly neutrophils. In addition, they specified an approvingly preserved IFN-stimulated response element (ISRE) area close to the BAFF gene promoter, which was functionally confirmed. The association of BAFF polymorphisms in the development of further autoimmune disorders has been revealed theretofore [\u003cspan additionalcitationids=\"CR40 CR41 CR42 CR43 CR44 CR45 CR46\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. BAFF rs9514828 polymorphism is found to be linked to several inflammatory and autoimmune diseases via several scientific studies [\u003cspan additionalcitationids=\"CR49 CR50 CR51\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTNFAIP3 (Tumor necrosis factor-alpha inducible protein 3) interacting protein 1 (TNIP1) encoded by the TNIP1 gene is a vital signalling protein in the NF-κB path. It operates together with the TNFAIP3 protein to repress NF-κB activation. The association of TNIP1 gene polymorphism with many autoimmune diseases such as systemic sclerosis, rheumatoid arthritis (RA), psoriasis, and SLE was demonstrated [\u003cspan additionalcitationids=\"CR54 CR55 CR56 CR57\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. TNIP1 rs17728338 polymorphism is revealed to be associated with some inflammatory and autoimmune diseases through scientific studies [\u003cspan additionalcitationids=\"CR60 CR61\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough many variants have been identified which were associated with SS development, however the variants (rs1130380, rs7574865, rs9514828, rs17728338) have not been investigated in Turkish population. Thus, the purpose of this study was to investigate whether the polymorphisms (\u003cem\u003eHLA-DQB1*03\u003c/em\u003e rs1130380, \u003cem\u003eSTAT4\u003c/em\u003e rs7574865, \u003cem\u003eBAFF\u003c/em\u003e rs9514828 and \u003cem\u003eTINIP1\u003c/em\u003e rs17728338) is associated with SS development in in in a group of Turkish patients.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Population\u003c/h2\u003e \u003cp\u003eOur study group consisted 40 healthy subjects and 115 patients with age range of 18\u0026ndash;75 with Sj\u0026ouml;gren's syndrome with SS who were attending the Rheumatology Clinic at the Ankara Bilkent City Hospital [Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e]. SS was diagnosed according to the criteria set out by American College of Rheumatology/European League Against Rheumatism classification criteria for primary Sj\u0026ouml;gren\u0026rsquo;s Syndrome [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Each subject responded a brief questionnaire that gives information about previous medical history, smoking and lifestyle. Informed consent was obtained from all subjects in accordance with the Helsinki Declaration (2013) of the World Medical Association [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. We have had approval of the Ankara University Faculty of Medicine Ethic Committee for this research and possess informed consent of each subject participating in the study. The power analysis has been performed for choosing the number of control and patient group.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Blood samples collection\u003c/h2\u003e \u003cp\u003eThe 5 ml blood samples of the individuals of the control and patient groups participating in the study were taken under the supervision of a doctor at the Ankara Bilkent City Hospital Rheumatology Clinic. Blood samples were taken into heparinized tubes and then transferred to Ankara University Faculty of Pharmacy, Department of Pharmaceutical Toxicology Research Laboratory with cold chain without wasting any time, where all experiments were performed. DNA isolation method, which is the preliminary step of genotyping experiments, was applied to blood samples and DNA samplings of each individual in the experimental groups were isolated. These DNA samplings were stored at -20\u003csup\u003e0\u003c/sup\u003eC until genotyping experiments were performed. Genotyping experiments were performed using the PCR-RFLP (Polymerase Chain Reaction-Restriction Fragment Length Polymorphism) method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. DNA isolation and DNA quantification\u003c/h2\u003e \u003cp\u003eThe Wizard Genomic DNA Purification kit, produced by Promega, was used for the isolation of each individuals' DNA sample.\u003c/p\u003e \u003cp\u003eThe purity of the DNA samples we obtained was determined by dividing the absorbance value read at 260 nm in the spectrophotometer by the absorbance value read at 280 nm. Accordingly, it was determined that DNA samples with values ​​between 1.7 and 2.0 were isolated with sufficient purity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Genotyping experiments\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1. Determination of HLA-DQB1*03 rs1130380 gene polymorphism\u003c/h2\u003e \u003cp\u003eThe HLA-DQB1*03 rs1130380 encoded polymorphism was detected according to the method of Soetjipto et al [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. HLA-DQB1*03 rs1130380 polymorphism analyses were performed using PCR and RFLP methods.\u003c/p\u003e \u003cp\u003e50 \u0026micro;l total reaction mix contains, 5 \u0026micro;l 10x PCR buffer, 100 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 100\u0026micro;mol dNTP mix, 77 pmol forward primer DQBS43 (5'-TGC TAC TTC ACC A(C/T) GGG-3') and reverse primer DQBA249 (5'-GTA GTT GTG TCT GCA (C/T)A C-3'), 5 000U Taq DNA polymerase and 50 ng DNA.\u003c/p\u003e \u003cp\u003eFollowing the PCR reaction, the RFLP method was applied by restriction with MspI restriction enzyme overnight at 37\u003csup\u003e0\u003c/sup\u003eC. After enzyme digestion, PAGE electrophoresis was performed and three bands of 99, 72 and 36 bp showed the wild type genotype (*0301), two bands of 171 and 36 bp showed heterozygous genotype (*0303) and a single band of 207 bp showed the presence of homozygous mutant genotype (*0601).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2. Determination of STAT4 rs7574865 gene polymorphism\u003c/h2\u003e \u003cp\u003eThe STAT4 rs7574865 encoded polymorphism was detected according to the method of Migita et al [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. STAT4 rs7574865 polymorphism analyses were performed using PCR and RFLP methods.\u003c/p\u003e \u003cp\u003e50 \u0026micro;l total reaction mix contains, 5 \u0026micro;l 10x PCR buffer, 100 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 100\u0026micro;mol dNTP mix, 100 pmol forward primer (5'-AAA GAA GTG GGA TAA AAA GAA GTT TG-3') and reverse primer (5'-CCA CTG AAA TAA GAT AAC CAC TGT-3'), 5 000U Taq DNA polymerase and 50 ng DNA.\u003c/p\u003e \u003cp\u003eFollowing the PCR reaction, the RFLP method was applied by restriction with HpaI restriction enzyme overnight at 37\u003csup\u003e0\u003c/sup\u003eC. After enzyme digestion, PAGE electrophoresis was performed and a single band of 147 bp showed the wild type genotype (G allele), three bands of 147, 122 and 25 bp showed heterozygous genotype (G/T allele) and a two bands of 122 and 25 bp showed the presence of homozygous mutant genotype (T allele).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3. Determination of BAFF rs9514828 gene polymorphism\u003c/h2\u003e \u003cp\u003eThe BAFF rs9514828 encoded polymorphism was detected according to the method of Marin-Rosales et al [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. BAFF rs9514828 polymorphism analyses were performed using PCR and RFLP methods.\u003c/p\u003e \u003cp\u003e30 \u0026micro;l total reaction mix contains, 5 \u0026micro;l 10x PCR buffer, 2 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 200\u0026micro;mol dNTP mix, 25 ng forward primer (5'-TTG TAC ACC GAC CTG TTA GG-3') and reverse primer (5'-TGG AAG TAA GTC CAG ACT GGG AAT-3'), 5 000U Taq DNA polymerase and 40 ng DNA.\u003c/p\u003e \u003cp\u003eFollowing the PCR reaction, the RFLP method was applied by restriction with HpaI restriction enzyme overnight at 37\u003csup\u003e0\u003c/sup\u003eC. After enzyme digestion, PAGE electrophoresis was performed and two bands of 261 and 137 bp showed the wild type genotype (C allele), three bands of 398, 261and 137 bp showed heterozygous genotype (C/T allele) and a single band of 398 bp showed the presence of homozygous mutant genotype (T allele).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.4.4. Determination of TNIP1 rs17728338 gene polymorphism\u003c/h2\u003e \u003cp\u003eThe TNIP1 rs17728338 encoded polymorphism was detected according to the method of Li et al [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. TNIP1 rs17728338 polymorphism analyses were performed using PCR and RFLP methods.\u003c/p\u003e \u003cp\u003e20 \u0026micro;l total reaction mix contains, 5 \u0026micro;l 1x PCR buffer, 1.5 mM MgCl\u003csub\u003e2\u003c/sub\u003e, 200\u0026micro;mol dNTP mix, 30 ng forward primer (5'-GTA TGT TTT GCA CCT AGC ACG T-3') and reverse primer (5'-CCA TTC GGG AGC CTT TTG CCA-3'), 1U Taq DNA polymerase and 20 ng DNA.\u003c/p\u003e \u003cp\u003eFollowing the PCR reaction, the RFLP method was applied by restriction with NcoI restriction enzyme overnight at 37\u003csup\u003e0\u003c/sup\u003eC. After enzyme digestion, PAGE electrophoresis was performed and a single band of 197 bp showed the wild type genotype (G allele), three bands of 197, 174and 23 bp showed heterozygous genotype (G/A allele) and two bands of 174 and 23 bp showed the presence of homozygous mutant genotype (A allele).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistics analysis was performed by SPSS softwareversion 27.0 for windows (SPSS Inc., Chicago, IL, USA). The frequencies of genotypes and alleles for all the studied polymorphisms were determined assuming co-dominant inheritance. The statistical significance of the genotype and allele frequency variables between the patients with SS and control group was evaluated by chi-square test with Yates correction for small numbers. Using the chi-square test, Hardy-Weinberg equilibrium was tested for the studied four SNPs in patients with SS and controls. Relative risk associated with the significant genotype was estimated by the odds ratio (OR). OR with 95% confidence intervals (95% CI) was tested using a chi-square distribution, and the null hypothesis being tested is OR\u0026thinsp;=\u0026thinsp;1. Allele frequencies were also evaluated. P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered as statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe aim of this study is to identify the association between four variants included rs1130380 encoded the \u003cem\u003eHLA-DQB1*03 gene\u003c/em\u003e, rs7574865 encoded \u003cem\u003eSTAT4\u003c/em\u003egene, rs9514828 enoded the \u003cem\u003eBAFF\u003c/em\u003e gene and rs17728338 enoded the \u003cem\u003eTINIP1\u003c/em\u003e gene and the development of the Sj\u0026ouml;gren's syndrome. This study recruited 155 subjects (40 healthy subjects, 115 patients with Sj\u0026ouml;gren's syndrome) in a Turkish population. In Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e the demographic data of the all subjects were shown.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic data of the subjects\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ePatient group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of subjects\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (mean.\u0026plusmn;SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53,33\u0026thinsp;\u0026plusmn;\u0026thinsp;4,51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53,43\u0026thinsp;\u0026plusmn;\u0026thinsp;11,92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54,40\u0026thinsp;\u0026plusmn;\u0026thinsp;7,97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53,79\u0026thinsp;\u0026plusmn;\u0026thinsp;10,77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (%33,3)\u003c/p\u003e \u003cp\u003e2 (%66,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (%21,6)\u003c/p\u003e \u003cp\u003e29 (%78,4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (%20,0)\u003c/p\u003e \u003cp\u003e8 (%80,0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (%20,0)\u003c/p\u003e \u003cp\u003e84 (%80,0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCorrelations between SS age and smoking were evaluated by multiple linear regressions but no significant association was obtained.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple logistic regression analysis for possible risk factors of SS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk factor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,67 (0,23\u0026thinsp;\u0026minus;\u0026thinsp;0,91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,21 (0,57\u0026thinsp;\u0026minus;\u0026thinsp;1,87)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,09 (2,07\u0026thinsp;\u0026minus;\u0026thinsp;5,78)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,48 (1,04\u0026thinsp;\u0026minus;\u0026thinsp;2,70)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eanti\u003c/em\u003e-Ro/SSA seropositivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,17 (1,64\u0026thinsp;\u0026minus;\u0026thinsp;6,25)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eanti-\u003c/em\u003eLa/SSB seropositivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,91 (1,53\u0026thinsp;\u0026minus;\u0026thinsp;5,11)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRF seropositivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,55 (1,49\u0026thinsp;\u0026minus;\u0026thinsp;4,27)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANA seropositivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,04 (1,63\u0026thinsp;\u0026minus;\u0026thinsp;3,78)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimer/seconder SS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,61 (1,15\u0026thinsp;\u0026minus;\u0026thinsp;3,44)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease Year (x̄)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,21 (1,53\u0026thinsp;\u0026minus;\u0026thinsp;4,03)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ea\u003c/sup\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003eb\u003c/sup\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAge, smoking, gender, family history, anti-Ro/SSA seropositivity, anti-La/SSB seropositivity, RF seropositivity, ANA seropositivity, SS type (primer/seconder) and disease year were evaluated as risk factors for SS so they were statistically analyzed by multiple logistic regression analysis. Due to the data, except age and smoking other all factors have a significant relationship with SS development (family history and type of SS factors\u0026rsquo; significance limit is \u0026lt;\u0026thinsp;0.05; gender, disease year and all seropositivity factors\u0026rsquo; significance limit is \u0026lt;\u0026thinsp;0.01). All the data related with these are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe genotypic distribution of all the studied gene polymorphisms were demonstrated in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. According to the outcomes, all examined variants displayed a significant relationship with the development of the disease. The HLA-DQB1*03 1/2 and 2/2 allele carriers were significantly over-represented in SS patients. The OR for SS with the HLA-DQB1*03 variant was admiringly raised (OR\u0026thinsp;=\u0026thinsp;6.05: 95%CI, 2.78\u0026ndash;13.20). The OR of the STAT4 variant was improved in SS patients about 6 fold similarly with HLA-DQB1*03 variant (OR\u0026thinsp;=\u0026thinsp;5.88: 95%CI, 2.69\u0026ndash;12.86). Likewise with the others, BAFF variant was amazingly triggered in SS patient about 7 fold compared with the controls (OR\u0026thinsp;=\u0026thinsp;6.71: 95%CI, 3.05\u0026ndash;14.79). In regards with the last studied variant TNIP1, it was also raised in SS patients compared with the controls and this enhancement had a significancy (OR\u0026thinsp;=\u0026thinsp;4.87: 95%CI, 2.26\u0026ndash;10.50). All the impacts had a P value smaller than 0.001. Genotype distributions for all the gene polymorphisms suit forecasts for Hardy\u0026ndash;Weinberg equilibrium.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe genotypic distribution of the studied genes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/1 Allele* (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/2 or 2/2 Allele (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR * (CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHLA-DQB1*03 rs1130380\u003c/b\u003e\u003c/p\u003e \u003cp\u003eControl \u003c/p\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (65,0)\u003c/p\u003e \u003cp\u003e27 (23,5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (35,0)\u003c/p\u003e \u003cp\u003e88 (76,5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,00\u003c/p\u003e \u003cp\u003e6,05 (2,78\u0026thinsp;\u0026minus;\u0026thinsp;13,20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u003c/b\u003e\u0026thinsp;0,001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSTAT4\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ers7574865\u003c/b\u003e\u003c/p\u003e \u003cp\u003eControl \u003c/p\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (67,5)\u003c/p\u003e \u003cp\u003e30 (26,1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (32,5)\u003c/p\u003e \u003cp\u003e85 (73,9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,00\u003c/p\u003e \u003cp\u003e5,88 (2,69\u0026thinsp;\u0026minus;\u0026thinsp;12,86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u003c/b\u003e\u0026thinsp;0,001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBAFF\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ers9514828\u003c/b\u003e\u003c/p\u003e \u003cp\u003eControl \u003c/p\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (60,0)\u003c/p\u003e \u003cp\u003e21 (18,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (40,0)\u003c/p\u003e \u003cp\u003e94 (81,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,00\u003c/p\u003e \u003cp\u003e6,71 (3,05\u0026ndash;14,79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u003c/b\u003e\u0026thinsp;0,001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTNIP1\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ers17728338\u003c/b\u003e\u003c/p\u003e \u003cp\u003eControl \u003c/p\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (57,5)\u003c/p\u003e \u003cp\u003e25 (21,7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (42,5)\u003c/p\u003e \u003cp\u003e90 (78,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,00\u003c/p\u003e \u003cp\u003e4,87 (2,26\u0026thinsp;\u0026minus;\u0026thinsp;10,50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u003c/b\u003e\u0026thinsp;0,001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*1 allele major variant,\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003e2 allele minor variant\u003c/h3\u003e\n\u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, allele frequencies of all the studied gene polymorphisms were given. When we evaluate the results, it is clearly seen that the allele 2 frequencies were about two folds increased in SS patients compared to the controls.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAllele frequencies of the studied genes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAllele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eAllele Frequency\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHLA-DQB1*03\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSTAT4\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eBAFF\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eTNIP1\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.730\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2/2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatient group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.510\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2/2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u003c/b\u003e\u0026thinsp;0,01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u003c/b\u003e\u0026thinsp;0,01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u003c/b\u003e\u0026thinsp;0,05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u003c/b\u003e\u0026thinsp;0,05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e* comparison between the 2/2 variant of the patients with those of controls\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe allele frequency of each variant (rs1130380, rs7574865, rs9514828, rs17728338) was then assessed in regional populations including African, American, European, and Asian cohorts. The results of our study indicate that (rs1130380, rs7574865, rs9514828, rs17728338)-upregulating variants are more common in Turkish populations than in European, American, and other Asian populations, suggesting Turkish populations may be more susceptible to the development of SS (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAllele frequencies SNPs examined in this study and multiple continents\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSNP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePosition (hg19) (bp)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eAllele\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eAllele Frequencies(N)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEff*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEUR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAFR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAMR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eASN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eOur\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers1130380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003echr6: 32632694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eHLA-DQB1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMissense\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA,G,T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers7574865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003echr2:191964633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSTAT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers9514828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003echr13:108921373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eBAFF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ers17728338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003echr5:150478318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eANXA6\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003eEUR, European; AFR, African; AMR, American; ASN, Asian. Ref, Reference and Eff, Effect allele of EUR, AFR, AMR, ASN were extracted from the \u003cb\u003eHaploReg Version 4.1 (\u003c/b\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubs.broadinstitute.org/mammals/haploreg\u003c/span\u003e\u003cspan address=\"https://pubs.broadinstitute.org/mammals/haploreg\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eTo the best of our knowledge, this study is the first that all these four gene polymorphisms at the same time which are thought to have a relationship with SS development especially in Turksih population.\u003c/p\u003e \u003cp\u003eSj\u0026ouml;gren\u0026rsquo;s syndrome (SS) is a chronic autoimmune disease and genetic susceptibility plays a major role in SS pathogenesis. Chused and his coworkers [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e] firstly demonstrated Human Leucocyte Antigen (HLA) genes as a risk factor for SS in 1977. The relationship between HLA-DR3 and SS was demonstrated especially in the white ethnicity. On the other side, association between SS and HLA-DR3-DQ haplotypes was revealed in various ethnic groups [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR70 CR71 CR72 CR73 CR74 CR75 CR76 CR77\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. Numerous methods have been accustomed including the Genetic Linkage analysis, positional candidate gene analysis using microsatellite markers, and more newly the GWAS studies completed on a huge series of SS patients and controls with SNPs (single nucleotide polymorphism) markers [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNevertheless, a meta-analysis pinpoints DRB1*0301, DQA1*0501, DQB1*0201, and DRB1*03 alleles as risk factors for SS, while pinpointing DQA1*0201, DQA1*0301 and DQB1*0501 alleles as preservatives [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Lately, a powerful connection between HLA-DRA, HLA-DQB1 and HLA-DQA1 and SS in 6p21 locus in an extensive study in Europe was documented [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In a Chinese research, HLA-DRB1/HLA-DQA1 in 6p21.3 locus and two separate signals linked with HLA-DPB1/COL11A2 [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. Degeneration of autoreactive T cell toleration via the existence of unnatural antigen displays the primary role of HLAs in autoimmune diseases. The disorder association of HLA-suspected alleles is familiar in autoimmune diseases and further specific alleles and haplotypes are developed, additional alleles straightforward targeting of typical autoantigens [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. HLA Class II is linked with autoantibody production in SS, whereas anti-Ro/SSA and anti-La/SSB are particularly more elevated in HLA-DQ1/HLA-DQ2 heterozygous patients [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e] but not connected to further clinical characteristics [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. HLA-DRB1*1501-DRB1*0301 is associated with anti-ACA (anticyclic citrullinated antibodies) [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. Amino acid deviations in the hypervariable province (HVR) of the HLA complex influence peptide binding and T cell display; The association of specific divergences in binding wells 7 and 9 of HLA-DRB1 with differences in depth and polarity was established in the Chinese population [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Although HLA Class I and HLA Class III genes were also investigated in the subsequent years, investigations concentrated on HLA Class II genes.\u003c/p\u003e \u003cp\u003eMultitudinous studies were performed that showing the relationship between HLA alleles and SS. Different genetic polymorphisms of HLA have been associated with predisposition and/or outcome of different infectious diseases such as hepatitis B virus (HBV), hepatitis C virus (HCV), Chikungunya, Chagas, dengue, influenza A(H1N1) and tuberculosis [\u003cspan additionalcitationids=\"CR87 CR88 CR89\" citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. A meta-analysis performed by Cruz-Tapias et al., [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e] pinpointed some of HLA alleles such as DRB1*0301, DQA1*0501, DQB1*0201, and DRB1*03 were risk factors for SS and the others including DQA1*0201, DQA1*0301 and DQB1*0501 as preservatives. Recently, a strong association between HLA-DRA, HLA-DQB1 and HLA-DQA1 and SS in 6p21 locus in a comprehensive study in Europe was reported [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. HLA-DQB1 is the beta 1 subunit of the HLA-DQ surface receptor, in the MHC, part of immune regulation. It is linked to immune disorders [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This gene is found to be linked with some disorders such as Type I diabetes, narcolepsy, celiac disease and scleroderma. Although it has been documented that the HLA-DQB1 gene is associated with Sj\u0026ouml;gren's Syndrome, there is no scientific data on the impact of the HLA-DQB1*03 rs1130380 polymorphism on the development of the disease. From this point of view, our results are very valuable in terms of evaluating the possible effect of HLA-DQB1 gene variation on SS. Due to our results, HLA-DQB1*03 rs1130380 variation had a significant relationship with the development of SS about 6 fold compared with controls (OR\u0026thinsp;=\u0026thinsp;6.05: 95%CI, 2.78\u0026ndash;13.20).\u003c/p\u003e \u003cp\u003eSTAT4 is a member of the STAT family and it has a crucial position in a broad variety of cells and the pathogenesis of various human diseases, particularly multiple types of autoimmune and inflammatory disorders, via activation by different cytokines via the Janus kinase (JAK)-STAT signalling path [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. STAT4 is a critical transcription factor for the transmission of IL-12, IL-23 and Type 1 interferon-mediated signals implicated in Th1 and Th17 differentiation, activation of monocytes and INFγ production [\u003cspan additionalcitationids=\"CR92\" citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. STAT4 haplotypes have been suggested to be a risk factor for the development of SLE and RA in the caucasians and its connection with SS [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. STAT4 polymorphism was investigated in different ethnic groups in other loci such as rs7574865 [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e] and rs7582694 [\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e]. In these three studies, it was pointed that rs7582694 polymorphism posed a risk for SS. rs7574865 of the STAT4 gene has been reported in a massive study of Swedes to be connected to both lupus (SLE) and rheumatoid arthritis [\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e]. RA risk associated with rs7574865(T) allele was also discovered in studies of 923 Spanish, 273 Swedish, and 876 Dutch patients [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e]. The rs7574865(T) allele is linkedwith an increased risk for type-1 diabetes established on a study of Greek patients [\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e]. In research including 2,776 Spanish subjects, it was observed that the rs7574865(T) allele was connected to rheumatoid arthritis, Crohn's disease, ulcerative colitis, and type-1 diabetes, but not with multiple sclerosis [\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e]. In a study of 124 Caucasian patients with primary SS, it was found that the rs7574865(T) allele was linked with a more elevated risk for this disease [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e]. Similarly, we also found this variant had a tremendous increased effect on the development of SS about 6-fold compared to the controls (OR\u0026thinsp;=\u0026thinsp;5.88: 95%CI, 2.69\u0026ndash;12.86).\u003c/p\u003e \u003cp\u003eBAFF is a member of the TNF superfamily which regulates immune responses. Sj\u0026ouml;strand et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] discovered extended BAFF expression in the immune cells of pSS patients, especially neutrophils. They also established an admiringly preserved IFN-stimulated response element (ISRE) area close to the BAFF gene promoter, which was functionally confirmed. The association of BAFF polymorphisms in the development of additional autoimmune diseases has been displayed previously [\u003cspan additionalcitationids=\"CR40 CR41 CR42 CR43 CR44 CR45 CR46\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. BAFF rs9514828 polymorphism is found to be connected with numerous autoimmune and inflammatory disorders such as SS, lymphoma, leukemia, haemophilia and periodontitis through some scientific investigations [\u003cspan additionalcitationids=\"CR49 CR50 CR51\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In an investigation by Nezos et al., [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] it was found that high risk pSS group was characterized by higher frequency of the minor T allele of the rs9514828 BAFF polymorphism compared to healthy controls. Our findings are also in line with this study in which we found that in SS patients the minor variant had approximately 7-fold risk compared to the controls (OR\u0026thinsp;=\u0026thinsp;6.71: 95%CI, 3.05\u0026ndash;14.79).\u003c/p\u003e \u003cp\u003eTNIP1 is encoded by the TNIP1 gene which is a critical signalling protein in the NF-κB path. It functions with the TNFAIP3 protein together to suppress NF-κB activation. The connection of TNIP1 gene polymorphism with multiple autoimmune disorders such as systemic sclerosis, rheumatoid arthritis (RA), psoriasis, and SLE was demonstrated [\u003cspan additionalcitationids=\"CR54 CR55 CR56 CR57\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTNIP1 rs17728338 polymorphism is revealed to be linked to several inflammatory and autoimmune diseases including psoriatic arthritis and psoriasis via scientific investigations [\u003cspan additionalcitationids=\"CR60 CR61\" citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. There are limited studies related with the TNIP1 rs17728338 polymorphism and SS. Nordmark et al.,[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] figured out that polymorphisms in TNIP1 are related with antibody-positive primary SS. We also found that minor variant of the TNIP1 polymorphism was a risk factor in SS patients with about 5-fold compared to the control group (OR\u0026thinsp;=\u0026thinsp;4.87: 95%CI, 2.26\u0026ndash;10.50). We acknowledge that our study needs to be validated by future studies in other population using more samples size, however, our study offers the findings that polymorphism of rs1130380, rs7574865, rs9514828, rs17728338 have a pivotal association with the SS in Turkish Population.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur study showed that 4 SNPs (rs1130380, rs7574865, rs9514828, rs17728338) have a significant association with the SS in Turkish Population. According to our results it was obviously seen that all studied gene polymorphisms are crucial risk factors for the development of SS. All these polymorphisms could be a biomarker for evaluating the possible risk for SS.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eI.A. contributed to conceptualization, methodology, resources, writing review \u0026amp; editing, and supervision, U.T. contributed to visualization, investigation, experimental analysis, data Curation, and writing\u0026ndash;original draft. A.E. contributed to the methodology, visualization and investigation S.S. and L.M.I. contributed to writing-review \u0026amp; editing and supervision of the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTian Y, Yang H, Liu N, Li Y, Chen J. Advances in pathogenesis of Sj\u0026ouml;gren\u0026rsquo;s Syndrome. 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Arthritis Rheum. 2008;58(9):2598-602. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sjögren’s syndrome, gene polymorphism, autoimmune diseases, variants","lastPublishedDoi":"10.21203/rs.3.rs-3978557/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3978557/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSj\u0026ouml;gren\u0026rsquo;s syndrome is a chronic autoimmune disorder of unspecified etiology implicating exocrine glands. SS patients illustrate dry eyes and mouth, joint pain, fever and neurological symptoms. Hormones, immune dysregulation, and environmental and genetic factors play the primary roles in the development of the disease. Previous studies reported that HLA-II, STAT4, BAFF and TINIP1 polymorphisms have a pivotal role in SS development, however, the variant on each gene has not been investigated in the Turkish population. Therefore, this study aims to identify and evaluate the association between four variants of the four mentioned genes above and the development of Sj\u0026ouml;gren's syndrome. This study recruited 40 healthy subjects and 115 patients with Sj\u0026ouml;gren's syndrome in a Turkish population. All genomic variants were detected using the PCR-RFLP technique. We observed that SNP rs1130380, rs7574865, rs9514828, and rs17728338 were associated with SS development. We herein highlighted that the subjects with 1/2 or 2/2 Allele (%) had a higher susceptibility to SS development than those with the 1/1 Allele. Furthermore, the allele frequency of each variant was then assessed in multiple continents, including African, American, European, and Asian cohorts. Interestingly, our data shows that upregulating variants are at higher frequencies compared to European American and Asian populations, which implies that Turkish populations might be relatively susceptible to SS development related to these variants. The results indicated that all variants were significantly associated with the development of the SS disease in the Turkish population.\u003c/p\u003e","manuscriptTitle":"Investigation of the Pathogenic Variants Induced Sjogren’s Syndrome in Turkish Population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-28 21:17:49","doi":"10.21203/rs.3.rs-3978557/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e833b7a7-7d7e-4696-9c72-95e74242f932","owner":[],"postedDate":"February 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-26T01:43:50+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-28 21:17:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3978557","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3978557","identity":"rs-3978557","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}