The TNFRSF13B rs34562254 Polymorphism is Associated with Hepatitis C Infection Risk in the Han Chinese Population

The TNFRSF13B rs34562254 Polymorphism is Associated with Hepatitis C Infection Risk in the Han Chinese 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 The TNFRSF13B rs34562254 Polymorphism is Associated with Hepatitis C Infection Risk in the Han Chinese Population Haozhi Fan, Zuqiang Fu, Zhijun Ge, Chen Dong, Chunhui Wang, Chao Shen, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-147629/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 Background Genetic variations in the tumor necrosis factor receptor superfamily ( TNFRSF) 13B have been reported to be associated with immune-related diseases. This study aimed to explore the relationship of tumor necrosis factor superfamily ( TNFSF ) 13 , TNFRSF13B , and TNFRSF14 missense mutations with hepatitis C virus (HCV) infection susceptibility. Methods Single-nucleotide polymorphisms (SNPs) in TNFSF13 (rs3803800, rs11552708), TNFRSF13B (rs34562254), and TNFRSF14 (rs4870) were genotyped in 469 intravenous drug users, 728 hemodialysis patients, and 1636 paid blood donors using a TaqMan real-time PCR assay. The USCS browser and RNAfold web servers were used to predict the biological functions of these selected SNPs. Results After adjusting for gender, age, levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), and route of infection, a logistic regression analysis showed that subjects carrying a homozygous TNFRSF13B rs34562254 TT mutant were more likely to be infected by HCV compared to those homozygous with the rs34562254 CC wild type (co-dominant model: OR = 1.52, 95% CI: 1.17–1.98, P = 0.002; recession model: OR = 1.41, 95% CI: 1.10–1.81, P = 0.007; additive model: OR = 1.21, 95% CI: 1.07–1.37, P = 0.002). The effect of the risk allele rs34562254-T was stronger in subjects that were female, older (≥ 50 years old), paid blood donors, and with lower ALT and AST levels (≤ 40 U/L). A bioinformatics analysis via the UCSC genome browser found that rs34562254 was located at the highest peak of the H3K4Me1 histone marker. Using the RNAfold web servers, the minimum free energy of the centroid secondary structure was found to be higher for the mutant rs34562254-T allele (-38.90 kcal/mol) than its wild type C allele (-45.60 kcal/mol). Additionally, the RegulomeDB score of rs34562254 was 3a. Altogether, the results of the bioinformatics analysis indicate that rs34562254 may affect gene expression levels by regulating the transcriptional activity of corresponding gene regions. Conclusions The rs34562254 polymorphisms in TNFRSF13B were significantly associated with HCV infection among the Han Chinese population. Infectious Diseases Figures Figure 1 Figure 2 Background The hepatitis C virus (HCV) is a positive-strand RNA virus mainly transmitted through exposure to blood, for example, via blood transfusion or reuse of contaminated medical equipment. Currently, more than 70 million people are estimated to be chronically infected with HCV [ 1 , 2 ] , which often leads to chronic hepatitis, liver failure, and hepatocellular carcinoma [ 3 – 5 ] . Despite the development of direct-acting antivirals (DAAs) over the last decade, reinfection after successful treatment remains a problem in people who engage in risky behavior. Additionally, a vaccine that effectively prevents HCV infection is not yet currently available [ 6 , 7 ] . Therefore, the factors affecting HCV infection outcomes are a critical issue and require further research. It is well known that the progression of HCV infection is mainly affected by its biological characteristics, the host’s immunity and genetic background, and the environment [ 8 ] . Among these factors, the immune system is generally recognized as an essential determinant of viral infection outcome [ 9 , 10 ] . The tumor necrosis factor receptor superfamily (TNFRSF), is naturally activated by members of the tumor necrosis factor superfamily (TNFSF), consists of 29 members in humans, and is mostly expressed in the immune system [ 11 – 13 ] . Previous studies have reported that TNFSF/TNFRSF significantly affects the development of numerous diseases, such as rheumatoid arthritis [ 14 ] , inflammatory bowel disease [ 15 ] , and multiple sclerosis [ 16 ] . Therefore, we hypothesize that TNFSF/TNFRSF, by regulating the immune response, can affect HCV infection outcome. We previously reported that genetic variants of TNFSF/TNFRSF such as TNFRSF1A [ 17 ] , TNFRSF5 [ 18 ] , TNFSF6 [ 19 ] , and TNFRSF11B [ 20 ] influence the immune response to HCV infection and are associated with various immune-related diseases. In addition, several studies have reported that genetic mutations of TNFSF13 , TNFRSF13B , and TNFRSF14 are significantly associated with immune-related diseases including chronic lymphocytic leukemia [ 21 ] , IgA deficiency [ 22 ] , systemic lupus erythematosus (SLE) [ 23 ] , asthma [ 24 ] , familial or sporadic immune thrombocytopenia, and common variable immunodeficiency (CVID) [ 22 , 25 ] . Thus, this study mainly focused on the association between single nucleotide polymorphisms (SNPs) in TNFSF13 , TNFRSF13B , and TNFRSF14 and HCV infection outcomes. More specifically, we assayed the TNFSF13 rs3803800, TNFSF13 rs11552708, TNFRSF13B rs34562254, and TNFRSF14 rs4870 polymorphisms in 2833 Chinese adults at high-risk of HCV infection and subsequently analyzed the association between these variants and HCV infection. Methods Participants 2833 Chinese adults (18–80 years old) from three high-risk groups (intravenous drug users, IVDU; hemodialysis patients, HD; and paid blood donors, PBD) were assayed. Data from the subjects were collected between 2008 to 2016 from three different centers: the Nanjing Compulsory Drug Rehabilitation Center in Jiangsu province (IVDU; n = 459), nine hospital hemodialysis centers in southern China (HD; n = 722), and paid blood donors from six villages in Zhenjiang (PBD; n = 1619). Each participant underwent structured interviews and answered standardized questionnaires for demographic information and environmental exposure histories. Subjects co-infected with other hepatotropic viruses or with human immunodeficiency virus (HIV), who suffered from other liver diseases, or received any antiviral therapy were excluded from the study. Structured interviews and standardized questionnaires were carried out with every participant to obtain demographic and environmental exposure history information. When exposed to HCV, some people may become infected by the virus and carry serapositive anti-HCV. Only 30% of these newly infected people can effectively clear the virus; that is, they carry serapositive anti-HCV and seranegative HCV RNA. Those who fail to clear HCV within 6 months will develop chronic HCV infection and carry serapositive anti-HCV and serapositive HCV RNA [ 26 , 27 ] . From these distinctions [ 27 ] , participants were assigned to three groups based on the state of their sera HCV antibody and sera HCV RNA. In Group A, the HCV uninfected control group, subjects carried seronegative anti-HCV and seronegative HCV RNA. Those who carried seropositive anti-HCV and seronegative HCV RNA formed the HCV spontaneous clearance group (Group B). Finally, subjects who carried seropositive anti-HCV and seropositive HCV RNA were classified into the HCV chronic infection group (Group C). Additionally, the HCV spontaneous clearance group (Group B) and HCV chronic infection group (Group C) were combined into a case group (Group B + C) and compared to the HCV uninfected control group (Group A). Thus, we compared genotype frequencies between Group A and Group (B + C) to explore the association between candidate SNPs and/or other risk factors to the susceptibility of HCV infection. We also compared genotype frequencies between Group B and Group C to determine whether candidate SNPs and/or other risk factors associate with chronic HCV infection. Serological testing 10 mL of venous blood collected in anticoagulative EDTA tubes was taken from the subjects. The plasma, white blood cells, and red blood cells were centrifuged and stored at -20 °C for later examination. Anti-HCV, viral load and genotype, HBV/HIV serological markers, and biochemical indicators of liver function (alanine aminotransferase [ALT], aspartate aminotransferase [AST]) were measured using commercial reagents according to the manufacturers’ instructions. SNPs selection Genetic information regarding the TNFSF13 , TNFRSF13B , and TNFRSF14 genes from HapMap (Phase II; CHB, Han Chinese in Beijing; upwards of 2 kb upstream and downstream) were downloaded from the 1000 Genomes database ( http://www.1000genomes.org/ ). To extract their corresponding tagSNPs, we loaded the data into Haploview 4.2 software and set the minor allele frequency (MAF) as > 0.05 and correlation coefficient r 2 as ≥ 0.8. Furthermore, we used the HaploReg database ( https://pubs.broadinstitute.org/mammals/haploreg/haploreg.php ) and SNP Function Prediction ( https://snpinfo.niehs.nih.gov/snpinfo/snpfunc.html ) to select four missense mutation SNP candidates (rs3803800, rs11552708, rs34562254, and rs4870) for analysis. SNPs genotyping Genomic DNA was extracted from venous blood using the phenol-chloroform method. DNA purity and concentration were determined with ultraviolet spectrophotometry, standardized, and stored at -20℃. SNPs were genotyped with a TaqMan allelic discrimination assay using the LightCycler® 480 II real-time PCR System (Roche, Switzerland). The primers and probe sequences for candidate SNPs are listed in Table S1. The genotyping was performed by experimenters who were blind to the subject’s assigned group. Each SNP had an accordance rate of 100% for repeated experiments of 10% random samples, and the genotyping success rate of each polymorphism was greater than 95%. In silico analysis We used the following to analyze the biological functions of our selected SNPs: the RegulomeDB online database ( http://www.regulomedb.org/ ) to obtain RegulomeDB scores representing regulatory potential (Table S2); Vienna RNA Web Servers ( http://rna.tbi.univie.ac.at/cgi-bin/RNAWeb Suite/RNAfold.cgi; ViennaRNA Package Version 2.4.4) to predict secondary structures of single stranded RNA sequences; and the UCSC Genome Bioinformatics website ( http://genome.ucsc.edu/ ) to elucidate potential biological functions. H3K4Me1 histone marker data from seven cell lines (GM12878, H1-hESC, HSMM, HUVEC, K562, NHEK, and NHLF) was also collected and analyzed. Statistical analysis For basic genetic information, a Hardy-Weinberg equilibrium (HWE) was estimated for each SNP among the control subjects (Group A) using a goodness-of-fit χ 2 test. To compare demographic differences among the three groups, we used one-way analysis of variance (ANOVA), chi-square (χ 2 ) test, or Kruskal-Wallis test where appropriate. The association between each SNP and HCV infection susceptibility or outcome was estimated by constructing logistic regression models based on age, gender, and route of infection. The associations were further clarified with odds ratios (ORs) and 95% confidence intervals (CIs) using co-dominant, dominant, recessive, and additive models. STATA14.0 software was used to perform statistical analyses. P -values < 0.05 were considered significant in all analyses except in multiple comparisons between SNPs, in which after Bonferroni corrections, P -values < 0.0125 (0.05/4) were considered significant. Results Participant characteristics Based on their anti-HCV and HCV RNA results, subjects were divided into three groups: HCV uninfected control group (Group A; n = 1543), HCV spontaneous clearance group (Group B; n = 522), and HCV chronic infection group (Group C; n = 758). The demographic and clinical information for the three groups were shown in Table 1 . The groups did not significantly differ in age or gender distributions (both P > 0.05). However, ALT and AST levels, infection route, and distribution of HCV genotypes significantly differed among the three groups (both P < 0.05). Table 1 Demographic and clinical characteristics among HCV uninfected control, spontaneous clearance and chronic infection groups. Variables Group A (%) Group B (%) Group C (%) P n = 1543 n = 522 n = 768 Age (years) 53.2 ± 13.7 50.3 ± 14.1 51.9 ± 12.4 < 0.001 a 0.067 b < 50 561(36.36) 212 (40.61) 312(40.63) ≥ 50 982(63.64) 310(59.39) 456(59.38) Gender 0.117 b Male 617(39.99) 199(38.12) 273(35.55) Female 926(60.01) 323(61.88) 495(64.45) ALT (U/L) < 0.001 b ≤ 40 1450(94.96) 416(79.85) 453(59.14) ༞40 77(5.04) 105(20.15) 313(40.86) AST (U/L) ≤ 40 1456(95.48) 424(82.65) 467(61.69) < 0.001 b ༞40 69(4.52) 89(17.35) 290(38.31) Route of infection < 0.001 b HD 561 (36.36) 91 (17.43) 76 (9.90) IVDU 181 (11.73) 148 (28.35) 140 (18.23) PBD 801 (51.91) 283 (54.21) 552 (71.88) HCV genotype < 0.001 b 1b -- 42(26.25) 223(46.07) Non-1b -- 118(73.75) 261(53.93) Group A: uninfected controls; Group B: spontaneous clearance subjects; Group C: chronic infection patients. Non-1b means viral strains other than 1b, including genotype 1a, 2, and 3 (either solely or mixed infection). Abbreviations: HCV, hepatitis C virus; SD, standard deviation; ALT, alanine transaminase; AST, aspartate transaminase; HD, hemodialysis patients; IVDU, Intravenous drug user; PBD, paid blood donors. a P value of Welch among three groups, heterogeneity of variance. b P value of χ 2 -test among three/two groups. Association of candidate SNPs with HCV infection outcomes The MAFs of the selected SNPs were greater than 20%, and all of them were consistent with HWEs from the HCV uninfected group (Group A; Table S1). As shown in Table 2 , after adjusting for age, gender, and other potential confounding factors, a logistic regression analysis found that participants carrying TNFRSF13B rs34562254-T had an increased risk of HCV infection (co-dominant model: OR = 1.52, 95% CI: 1.17–1.98, P = 0.002; additive model: OR = 1.21, 95% CI: 1.07–1.37, P = 0.002; recessive model: OR = 1.41, 95% CI = 1.10–1.81, P = 0.007). However, we did not find an association between SNPs and HCV infection outcome (all P > 0.05). Table 2 Genotypes distributions of TNFRSF genes among HCV uninfected control, spontaneous clearance and chronic infection groups. SNPs (genotype) Group A n (%) Group B n (%) Group C n (%) OR(95%CI) a P a OR(95%CI) b P b n = 1543 n = 522 n = 768 TNFSF13-rs3803800 0.834 * 0.593 ** GG 645 (44.00) 221 (43.50) 342 (46.22) 1.00 -- 1.00 -- GA 669 (45.63) 231 (45.47) 325 (43.92) 1.01 (0.85–1.21) 0.908 0.91 (0.70–1.17) 0.443 AA 152 (10.37) 56 (11.02) 73 (9.86) 1.00 (0.74–1.33) 0.977 0.85 (0.56–1.27) 0.421 Dominant model 1.01 (0.85–1.19) 0.93 0.89 (0.70–1.14) 0.361 Recessive model 1.00(0.75–1.31) 0.946 0.89 (0.60–1.31) 0.550 Additive model 1.00 (0.88–1.14) 0.971 0.91 (0.76–1.10) 0.334 TNFSF13-rs11552708 0.024 * 0.588 ** GG 573 (38.00) 183 (35.47) 249 (32.98) 1.00 -- 1.00 -- GA 684 (45.36) 252 (48.84) 390 (51.66) 1.18 (0.98–1.41) 0.080 1.06 (0.814–1.370) 0.680 AA 251 (16.64) 81 (15.7) 116 (15.36) 0.91 (0.711.72) 0.468 1.00(0.698–1.440) 0.991 Dominant model 1.11 (0.93–1.31) 0.257 1.04 (0.81–1.34) 0.736 Recessive model 0.83 (0.66–1.04) 0.112 0.97 (0.70–1.35) 0.856 Additive model 1.03(0.92–1.15) 0.615 1.05(0.89–1.24) 0.576 TNFRSF13B-rs34562254 0.009 * 0.251 ** CC 661 (43.95) 190 (36.54) 312 (41.16) 1.00 -- 1.00 -- CT 673 (44.75) 251 (48.27) 340 (44.85) 1.15 (0.96–1.38) 0.119 0.81 (0.63–1.05) 0.112 TT 170(11.30) 79 (15.19) 106 (13.98) 1.52 (1.17–1.98) 0.002 0.86(0.60–1.22) 0.401 Dominant model 1.22 (1.03–1.45) 0.019 0.82 (0.65–1.05) 0.114 Recessive model 1.41 (1.10–1.81) 0.007 0.96(0.69–1.34) 0.805 Additive model 1.21 (1.07–1.37) 0.002 0.90 (0.76–1.06) 0.213 TNFRSF14-rs4870 0.031 * 0.472 ** AA 455(29.88) 177 (34.57) 241 (31.84) 1.00 -- 1.00 -- AG 782 (51.35) 236(46.09) 352 (46.50) 0.77 (0.64–0.93) 0.043 1.06 (0.81–1.38) 0.684 GG 286 (18.78) 98 (19.34) 164 (21.66) 0.96(0.75–1.21) 0.708 1.25 (0.90–1.74) 0.186 Dominant model 0.82 (0.69–0.98 0.028 1.11 (0.87–1.43) 0.396 Recessive model 1.12 (0.91–1.38) 0.290 1.21 (0.904–1.63) 0.201 Additive model 0.95 (0.84–1.07) 0.391 1.11(0.94–1.31) 0.206 Abbreviations: CI, confidence interval; HCV, hepatitis C virus; OR, odds ratio; SNP, single nucleotide polymorphism. Group A: uninfected controls; Group B: spontaneous clearance subjects; Group C: chronic infection patients. * The P value of χ 2 -test refer to the distribution of SNPs between Group A and Group (B + C). ** The P value of χ2-test refer to the distribution of SNPs between Group B and Group C. a The P value, OR and 95% CIs of Group (B + C) versus Group A were calculated on the basis of the logistic regression model, adjusted by gender, age, ALT level, AST level and route of infection. b The P value, OR and 95% CIs of Group C versus Group B were calculated on the basis of the logistic regression model, adjusted by gender, age, ALT level, AST level and route of infection. Bonferroni correction was applied and the P value was adjusted to 0.0125 (0.05/4). Bold type indicates statistically significant results. Stratification analysis of TNFRSF13B rs34562254 To further explore the rs34562254 loci, we used stratified analysis based on the additive model to exclude the influence of confounding factors. As shown in Table 3 , the rs34562254 genotype remained significantly related to HCV susceptibility in the age and gender subgroups (both P < 0.0125). Additionally, other variables such as ALT ≤ 40 U/L (OR = 1.22, 95% CI = 1.07–1.39, P = 0.003), AST ≤ 40 U/L (OR = 1.23, 95% CI = 1.08–1.40, P = 0.002) and PBD (OR = 1.29, 95% CI = 1.09–1.53, P = 0.003), were also statistically correlated with HCV susceptibility. Based on these results, we further tested the heterogeneity of each stratified variable and found that no heterogeneity existed between the sub-layers (all P > 0.05). Table 3 Stratified analysis the association of rs34562254 with HCV susceptibility Subgroups Group A Group B Group C OR(95%CI) a P a P b n (CC/CT/TT) n (CC/CT/TT) n (CC/CT/TT) Age 0.632 < 50 221/232/78 78/99/35 131/122/56 1.17(0.97–1.41) 0.100 ≥ 50 440/441/92 112/152/44 181/218/50 1.26(1.07–1.66) 0.005 Gender 0.103 Male 234/290/73 63/103/33 122/108/42 1.07(0.89–1.31) 0.439 Female 427/383/97 127/148/46 190/232/64 1.32(1.12–1.55) 0.001 ALT (U/L) 0.759 ≤ 40 622/635/162 155/203/57 181/194/71 1.20(1.06–1.37) 0.004 > 40 33/36/8 35/48/21 130/145/35 1.13(0.78–1.62) 0.505 AST (U/L) 0.355 ≤ 40 624/636/160 160/201/58 174/202/71 1.22(1.07–1.39) 0.002 > 40 30/35/10 26/47/19 131/136/33 1.01(0.68–1.51) 0.950 Route of infection 0.706 HD 229/231/75 29/47/15 41/23/12 1.14(0.87–1.49) 0.357 IVDU 77/78/22 53/72/23 57/59/24 1.18(0.89–1.55) 0.250 PBD 355/364/73 108/132/41 214/258/70 1.29(1.09–1.53) 0.003 Abbreviations: CI, confidence interval; HCV, hepatitis C virus; OR, odds ratio; HD, hemodialysis patients; IVDU, Intravenous drug user; PBD, paid blood donors. Group A: uninfected controls; Group B: spontaneous clearance subjects; Group C: chronic infection patients. Group (B + C): Infected individuals (spontaneous clearance subjects + chronic infection patients). a The P value, OR and 95% CIs of Group (B + C) versus Group A were calculated on the basis of the additive model, adjusted by gender, age, ALT level, AST level and route of infection. b P -value for the heterogeneity test. In silico analysis As shown in Fig. 1 , rs34562254 had a RegulomeDB score of 3a, suggesting that it may be located at the transcription factor (TF) binding site, motif, and DNase peak. We used RNAfoldweb servers to predict TNFRSF13B RNA secondary structure. The MAF of the centroid secondary structure was higher for the mutant rs34562254 T allele (-38.90 kcal/mol) than its wildtype C allele (-45.60 kcal/mol), indicating that the rs34562254 polymorphism in TNFRSF13B could affect the transcription of related RNA (Fig. 1 ). We also explored the potential biological functions of rs34562254 in the Encyclopedia of DNA Elements (ENCODE) project using the UCSC genome browser. As shown in Fig. 2 , rs34562254 was located on the highest peak of the H3K4Me1 histone marker in seven cell lines. H3K4me1 is a major histone modification associated with enhancer elements in nucleosomes and is linked to the transcriptional regulation of genes. Discussion We found that TNFRSF13B rs34562254 was associated with HCV infection susceptibility. More specifically, compared to subjects with rs34562254-CC (the wild type), those with CT/TT have an increased risk of HCV infection. The T allele’s effect was stronger in subjects who were older (≥ 50 years old), female, PBDs, and those with lower ALT and AST levels (≤ 40 U/L). Moreover, our bioinformatics analysis found that rs34562254 was located at the highest peak of the H3K4Me1 histone marker and potentially regulates mRNA transcription by affecting TF binding. TNFRSF13B is a lymphocyte-specific tumor necrosis factor receptor that interacts with the NF-κB pathway and regulates B-cell development [ 28 , 29 ] . It has been reported to be associated with a variety of human immune-related diseases such as CVID [ 22 ] , asthma [ 24 ] , and SLE [ 23 ] . Furthermore, Rand et al. have found that the TNFRSF13 B rs34562254 polymorphism was correlated with multiple myeloma and coronary artery lesions [ 30 ] . In this study, based on the analyses of four genetic markers, we found that subjects with rs34562254-T were associated with an elevated risk of HCV infection. From the NCBIdbSNP browser ( https://www.ncbi.nlm.nih.gov/snp/ ), we found that rs34562254 is a missense mutation located in the exon region of TNFRSF13B . According to RegulomeDB, its RegulomeDB score is 3a ( https://www.regulomedb.org/regulome-search/?regions=rs34562254&genome=GRCh37 ). RegulomeDB is a database that links SNPs with known and predicted regulatory elements within the intergenic regions of the Homo sapiens genome. The RegulomeDB score represents a model integrating functional genomics features with continuous values such as the expression of quantitative trait loci, TF binding, TF motif, ChIP-seq signal, and DNase Footprint [ 31 ] . Therefore, the rs34562254 SNP might have transcriptional regulatory functions including TF binding and DNase peak. Through the RNAfold web server, we found that the wildtype C allele of the centroid secondary structure had a lower MFE than the mutant T allele (-45.60 versus − 38.90 kcal/mol). From the ENCODE project and the UCSC genome browser, we found that rs34562254 was located on the highest peak of the H3K4Me1 histone marker, a major histone modification around enhancer elements in nucleosomes. When enhancer regions are enriched with H3K4me1 modifications, the enhancer enters a state of equilibrium. In contrast, when enhancer regions become enriched with both H3K4me1 and H3K27ac modifications, the enhancer enters an activated state that promotes gene expression [ 32 ] . Consequently, we speculate that genetic variants in rs34562254 might affect TNFRSF13B expression by influencing TF binding. The stratified analysis showed that the rs34562254-T allele was significantly associated with HCV susceptibility in subjects that were female, over 50 years old, PBDs, and that had reduced ALT and AST levels (≤ 40 U/L). In general, compared to men, women usually develop more intense innate, humoral, and cellular immune responses to viral infections and vaccinations [ 33 ] , suggesting that the allele’s associated risk is more significant in females. ALT and AST level are major indicators of liver injury severity. In hepatitis C, ALT and AST levels become abnormal (> 40 U/L), which may confound the effects of the rs34562254-T allele [ 19 ] . HCV is a common infection among older adults in certain areas of China [ 34 ] . Generally, older people are less healthy and are more likely than younger people to be exposed to potentially contaminated needles or blood products [ 35 ] . Accordingly, our result showed that the risk effect of the allele was more significant in the over 50 years old subgroup. For PBDs, they may rely on blood donation as a source of income. Blood-borne diseases such as HCV and HIV were frequently detected among PBDs in China during the early 1980s [ 36 ] ; HCV infection was very prevalent [ 37 ] . Several limitations exist in this study. First, we did not test other SNPs in TNFSF / TNFRSF that may associate with HCV infection. Therefore, additional studies with more extensive genomic coverage are required to increase understanding of the role of TNFRSF13B polymorphisms in HCV infection. Second, in the multivariate regression analysis of TNFRSF SNP distribution and HCV infection outcome, HCV genotypes were not included due to a lack of data. Instead, we used existing HCV genotype data to perform a logistic regression on rs34562254 and found that the P value did not change. In future studies, we will collect as much baseline data as possible to improve our reliability. Finally, the potential biological functions of TNFRSF13B rs34562254 were speculated in the in silico analysis. The exact mechanisms of rs34562254 in TNFRSF13B in HCV infection need to be further investigated. Conclusions This study was the first to report that the TNFRSF13B missense mutation rs34562254 was significantly associated with HCV susceptibility among the Han Chinese population. Moreover, the increased risk of the mutant genotype was stronger in subjects who were females, older (≥ 50 years old), PBDs, and who had lower ALT and AST levels (≤ 40 U/L). These findings are valuable in deepening the understanding of HCV infection susceptibility and offer a reference to develop prevention and control strategies among populations at high risk of repeated HCV infections. Abbreviations TNFRSF: tumor necrosis factor receptor superfamily; TNFSF: tumor necrosis factor superfamily; HCV: hepatitis C virus; HCC: hepatic carcinoma; DAAs: direct-acting antivirals; RA: rheumatoid arthritis; IBD: inflammatory bowel disease; MS: multiple sclerosis; CLL: chronic lymphocytic leukemia; SLE: systemic lupus erythematosus; CVID: common variable immunodeficiency; SNPs: single nucleotide polymorphisms; IVDU: Intravenous drug users; HD: hemodialysis patients; PBD: paid blood donors; HIV: human immunodeficiency virus; HBV: hepatitis B virus; ALT: alanine aminotransferase; AST: aspartate aminotransferase; MAF: minor allele frequency; HWE: Hardy-Weinberg equilibrium; ANOVA: one-way analysis of variance; ORs: odds ratios; CI: confidence intervals; GWAS: genome-wide association study; TACI: transmembrane activator and CAML interactor; SAE: serious adverse event; TN: treatment-naïve; TE: treatment-experienced; WHO: World Health Organization. Declarations Ethics approval and consent to participate All study procedures were approved by the medical ethics committee of Nanjing Medical University in accordance with the Declaration of Helsinki. The written informed consent was obtained from each participant. Consent of publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The current study was financially supported by the National Natural Science Foundation of China (Grant No. 81773499), Science Foundation for Distinguished Young Scholars of Jiangsu Province (Grant No. BK20190106), Open Research Fund Program of the State Key Laboratory of Virology of China (Grant No. 2019KF005), Key Project of Natural Science Foundation of Yunnan Province (Grant No. 2019FA005) and Jiangsu Program for Young Medical Talents (Grant No. QNRC2016616) Authors’ contributions All authors made substantial contributions to editing and drafting of the manuscript. H.Z.F, Z.Q.F. and M.Y. designed and organized the study and supervised the whole project. H.Z.F, Z.Q.F., Z.J.G., C.H.W., J.L. and M.Y. contributed to field survey, data collection, laboratory detection and quality control. H.Z.F, Z.Q.F., D.C., C.S. and R.B.Y. performed data cleansing and statistical analysis. H.Z.F, Z.Q.F and Y.Z. provided analysis tools and performed data interpretation. H.Z.F., Z.Q.F., C.D. and M.Y. wrote and critical revised the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors wish to thank Peng Huang, Yan Wang, Xiangyu Ye, Zeyang Ni and Yuqing Hou, for all the contributions to make this study carried out. References WHO. Global hepatitis report. Geneva World Health Organization.2017 http://apps.who.int/iris/bitstream/10665/255016/1/9789241565455-eng.pdf?ua=1[J] . Agner KJ. Principles for automation of quantitative chemical analysis by a discontinous flow system and their application[J]. Scandinavian journal of clinical and laboratory investigation Supplementum,1967,100(139. Chinese Society of Hepatology and Chinese Society of Infectious Diseases CMA. Guidelines for the prevention and treatment of hepatitis C (2019 version)[J]. J Clin Hepatol,2019,35(12):1–17. Cacoub P, Comarmond C, Domont F, Savey L, Desbois AC, Saadoun D. Extrahepatic manifestations of chronic hepatitis C virus infection[J]. 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TNFRSF13B/TACI Alterations in Turkish Patients with Common Variable Immunodeficiency and IgA Deficiency[J]. Avicenna J Med Biotechnol. 2018;10(3):192–5. Wen L, Zhu C, Zhu Z, et al. Exome-wide association study identifies four novel loci for systemic lupus erythematosus in Han Chinese population[J].2018,77(3):417. Janzi M, Melén E, Kull I, Wickman M, Hammarström L. Rare mutations in TNFRSF13B increase the risk of asthma symptoms in Swedish children[J]. Genes Immun. 2012;13(1):59–65. Freiberger T, Ravcukova B, Grodecka L, et al. Sequence variants of the TNFRSF13B gene in Czech CVID and IgAD patients in the context of other populations[J]. Hum Immunol. 2012;73(11):1147–54. Spearman CW, Dusheiko GM, Hellard M, Sonderup M. Hepatitis. C[J]. Lancet,2019,394(10207):1451–66. Chinese Society of Hepatology and Chinese Society of Infectious Disease CMA. Guidelines for the prevention and treatment of hepatitis C (2019 version)[J]. Journal of Clinical Hepatology,2019,35(12):2670–86. Xia XZ, Treanor J, Senaldi G, et al. TACI is a TRAF-interacting receptor for TALL-1, a tumor necrosis factor family member involved in B cell regulation[J]. J Exp Med. 2000;192(1):137–43. Zhang X, Park CS, Yoon SO, et al. BAFF supports human B cell differentiation in the lymphoid follicles through distinct receptors[J]. Int Immunol,2005,17(6):779–88. Rand KA, Song C, Dean E, et al. A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci[J]. Cancer Epidemiol Biomarkers Prev. 2016;25(12):1609–18. Dong S, Boyle AP. Predicting functional variants in enhancer and promoter elements using RegulomeDB[J]. Hum Mutat,2019,40(9):1292–8. Tian Y, Jia Z, Wang J, et al. Global mapping of H3K4me1 and H3K4me3 reveals the chromatin state-based cell type-specific gene regulation in human Treg cells[J]. PLoS One. 2011;6(11):e27770. Fish EN. The X-files in immunity: sex-based differences predispose immune responses[J]. Nat Rev Immunol,2008,8(9):737–44. Zhang M, Sun XD, Mark SD, et al. Hepatitis C virus infection, Linxian, China[J]. Emerg Infect Dis,2005,11(1):17–21. He J, Lin J. HCV prevalence during the age range of peak sexual activity[J]. Lancet Infect Dis,2017,17(2):131–2. Shan H, Wang JX, Ren FR, et al. Blood banking in China[J]. Lancet,2002,360(9347):1770–5. Rao HY, Sun DG, Yang RF, et al. Outcome of hepatitis C virus infection in Chinese paid plasma donors: a 12-19-year cohort study[J]. J Gastroenterol Hepatol. 2012;27(3):526–32. Supplementary Files SupplementaryMaterial.docx 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-147629","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":8225665,"identity":"763e5e12-9477-483f-bd97-48c77dc982b2","order_by":0,"name":"Haozhi Fan","email":"","orcid":"","institution":"Jiangsu Province Hospital and Nanjing Medical University First Affiliated Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Haozhi","middleName":"","lastName":"Fan","suffix":""},{"id":8225666,"identity":"24c84655-ab93-4faf-97e9-b909f43bf94c","order_by":1,"name":"Zuqiang 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15:17:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-147629/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-147629/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":5069031,"identity":"10c06bd3-1e75-4d5f-93a7-337a10a0ab40","added_by":"auto","created_at":"2021-01-19 00:17:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40241,"visible":true,"origin":"","legend":"The influence of rs34562254 variants on mRNA centroid secondary structures of TNFRSF13B.","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-147629/v1/675030562b4acc586048becc.png"},{"id":5069072,"identity":"4f88fc18-71f6-4b37-9864-f34eec883582","added_by":"auto","created_at":"2021-01-19 00:20:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":9603,"visible":true,"origin":"","legend":"Functional annotation for SNP rs34562254 using ENCODE data from UCSC genome browser.","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-147629/v1/fe36c25a116bb623e390684f.png"},{"id":15671241,"identity":"c78c11c4-ca8d-42d8-9c9b-a1b3305cc66c","added_by":"auto","created_at":"2021-11-18 14:05:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":507563,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-147629/v1/776ebcad-045a-4e89-b9f3-9a8cc5f09193.pdf"},{"id":5069071,"identity":"139a8569-64c2-4ad7-a61b-8b1213d04b88","added_by":"auto","created_at":"2021-01-19 00:20:09","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":18592,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-147629/v1/13efd33d663de7501c3c7991.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eThe \u003cem\u003eTNFRSF13B\u003c/em\u003e rs34562254 Polymorphism is Associated with Hepatitis C Infection Risk in the Han Chinese Population\u003c/p\u003e","fulltext":[{"header":"Background","content":" \u003cp\u003eThe hepatitis C virus (HCV) is a positive-strand RNA virus mainly transmitted through exposure to blood, for example, via blood transfusion or reuse of contaminated medical equipment. Currently, more than 70\u0026nbsp;million people are estimated to be chronically infected with HCV \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, which often leads to chronic hepatitis, liver failure, and hepatocellular carcinoma \u003csup\u003e[\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Despite the development of direct-acting antivirals (DAAs) over the last decade, reinfection after successful treatment remains a problem in people who engage in risky behavior. Additionally, a vaccine that effectively prevents HCV infection is not yet currently available \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Therefore, the factors affecting HCV infection outcomes are a critical issue and require further research.\u003c/p\u003e \u003cp\u003eIt is well known that the progression of HCV infection is mainly affected by its biological characteristics, the host\u0026rsquo;s immunity and genetic background, and the environment \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Among these factors, the immune system is generally recognized as an essential determinant of viral infection outcome \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. The tumor necrosis factor receptor superfamily (TNFRSF), is naturally activated by members of the tumor necrosis factor superfamily (TNFSF), consists of 29 members in humans, and is mostly expressed in the immune system \u003csup\u003e[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Previous studies have reported that \u003cem\u003eTNFSF/TNFRSF\u003c/em\u003e significantly affects the development of numerous diseases, such as rheumatoid arthritis \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, inflammatory bowel disease \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e, and multiple sclerosis \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Therefore, we hypothesize that TNFSF/TNFRSF, by regulating the immune response, can affect HCV infection outcome.\u003c/p\u003e \u003cp\u003eWe previously reported that genetic variants of \u003cem\u003eTNFSF/TNFRSF\u003c/em\u003e such as \u003cem\u003eTNFRSF1A\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e, \u003cem\u003eTNFRSF5\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e, \u003cem\u003eTNFSF6\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e, and \u003cem\u003eTNFRSF11B\u003c/em\u003e \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e influence the immune response to HCV infection and are associated with various immune-related diseases. In addition, several studies have reported that genetic mutations of \u003cem\u003eTNFSF13\u003c/em\u003e, \u003cem\u003eTNFRSF13B\u003c/em\u003e, and \u003cem\u003eTNFRSF14\u003c/em\u003e are significantly associated with immune-related diseases including chronic lymphocytic leukemia \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e, IgA deficiency \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e, systemic lupus erythematosus (SLE) \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e, asthma \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e, familial or sporadic immune thrombocytopenia, and common variable immunodeficiency (CVID) \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Thus, this study mainly focused on the association between single nucleotide polymorphisms (SNPs) in \u003cem\u003eTNFSF13\u003c/em\u003e, \u003cem\u003eTNFRSF13B\u003c/em\u003e, and \u003cem\u003eTNFRSF14\u003c/em\u003e and HCV infection outcomes. More specifically, we assayed the \u003cem\u003eTNFSF13\u003c/em\u003e rs3803800, \u003cem\u003eTNFSF13\u003c/em\u003e rs11552708, \u003cem\u003eTNFRSF13B\u003c/em\u003e rs34562254, and \u003cem\u003eTNFRSF14\u003c/em\u003e rs4870 polymorphisms in 2833 Chinese adults at high-risk of HCV infection and subsequently analyzed the association between these variants and HCV infection.\u003c/p\u003e "},{"header":"Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section3\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003e2833 Chinese adults (18\u0026ndash;80\u0026nbsp;years old) from three high-risk groups (intravenous drug users, IVDU; hemodialysis patients, HD; and paid blood donors, PBD) were assayed. Data from the subjects were collected between 2008 to 2016 from three different centers: the Nanjing Compulsory Drug Rehabilitation Center in Jiangsu province (IVDU; \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;459), nine hospital hemodialysis centers in southern China (HD; \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;722), and paid blood donors from six villages in Zhenjiang (PBD; \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1619). Each participant underwent structured interviews and answered standardized questionnaires for demographic information and environmental exposure histories. Subjects co-infected with other hepatotropic viruses or with human immunodeficiency virus (HIV), who suffered from other liver diseases, or received any antiviral therapy were excluded from the study.\u003c/p\u003e \u003cp\u003eStructured interviews and standardized questionnaires were carried out with every participant to obtain demographic and environmental exposure history information. When exposed to HCV, some people may become infected by the virus and carry serapositive anti-HCV. Only 30% of these newly infected people can effectively clear the virus; that is, they carry serapositive anti-HCV and seranegative HCV RNA. Those who fail to clear HCV within 6 months will develop chronic HCV infection and carry serapositive anti-HCV and serapositive HCV RNA \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. From these distinctions \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e, participants were assigned to three groups based on the state of their sera HCV antibody and sera HCV RNA. In Group A, the HCV uninfected control group, subjects carried seronegative anti-HCV and seronegative HCV RNA. Those who carried seropositive anti-HCV and seronegative HCV RNA formed the HCV spontaneous clearance group (Group B). Finally, subjects who carried seropositive anti-HCV and seropositive HCV RNA were classified into the HCV chronic infection group (Group C). Additionally, the HCV spontaneous clearance group (Group B) and HCV chronic infection group (Group C) were combined into a case group (Group B\u0026thinsp;+\u0026thinsp;C) and compared to the HCV uninfected control group (Group A). Thus, we compared genotype frequencies between Group A and Group (B\u0026thinsp;+\u0026thinsp;C) to explore the association between candidate SNPs and/or other risk factors to the susceptibility of HCV infection. We also compared genotype frequencies between Group B and Group C to determine whether candidate SNPs and/or other risk factors associate with chronic HCV infection.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSerological testing\u003c/h2\u003e \u003cp\u003e10\u0026nbsp;mL of venous blood collected in anticoagulative EDTA tubes was taken from the subjects. The plasma, white blood cells, and red blood cells were centrifuged and stored at -20\u0026nbsp;\u0026deg;C for later examination. Anti-HCV, viral load and genotype, HBV/HIV serological markers, and biochemical indicators of liver function (alanine aminotransferase [ALT], aspartate aminotransferase [AST]) were measured using commercial reagents according to the manufacturers\u0026rsquo; instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSNPs selection\u003c/h2\u003e \u003cp\u003eGenetic information regarding the \u003cem\u003eTNFSF13\u003c/em\u003e, \u003cem\u003eTNFRSF13B\u003c/em\u003e, and \u003cem\u003eTNFRSF14\u003c/em\u003e genes from HapMap (Phase II; CHB, Han Chinese in Beijing; upwards of 2\u0026nbsp;kb upstream and downstream) were downloaded from the 1000 Genomes database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.1000genomes.org/\u003c/span\u003e\u003c/span\u003e). To extract their corresponding tagSNPs, we loaded the data into Haploview 4.2 software and set the minor allele frequency (MAF) as \u0026gt;\u0026thinsp;0.05 and correlation coefficient r\u003csup\u003e2\u003c/sup\u003e as \u0026ge;\u0026thinsp;0.8. Furthermore, we used the HaploReg database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubs.broadinstitute.org/mammals/haploreg/haploreg.php\u003c/span\u003e\u003c/span\u003e) and SNP Function Prediction (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://snpinfo.niehs.nih.gov/snpinfo/snpfunc.html\u003c/span\u003e\u003c/span\u003e) to select four missense mutation SNP candidates (rs3803800, rs11552708, rs34562254, and rs4870) for analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSNPs genotyping\u003c/h2\u003e \u003cp\u003eGenomic DNA was extracted from venous blood using the phenol-chloroform method. DNA purity and concentration were determined with ultraviolet spectrophotometry, standardized, and stored at -20℃. SNPs were genotyped with a TaqMan allelic discrimination assay using the LightCycler\u0026reg; 480 II real-time PCR System (Roche, Switzerland). The primers and probe sequences for candidate SNPs are listed in Table S1. The genotyping was performed by experimenters who were blind to the subject\u0026rsquo;s assigned group. Each SNP had an accordance rate of 100% for repeated experiments of 10% random samples, and the genotyping success rate of each polymorphism was greater than 95%.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eIn silico\u003c/span\u003e \u003cb\u003eanalysis\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe used the following to analyze the biological functions of our selected SNPs: the RegulomeDB online database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.regulomedb.org/\u003c/span\u003e\u003c/span\u003e) to obtain RegulomeDB scores representing regulatory potential (Table S2); Vienna RNA Web Servers (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://rna.tbi.univie.ac.at/cgi-bin/RNAWeb\u003c/span\u003e\u003c/span\u003e Suite/RNAfold.cgi; ViennaRNA Package Version 2.4.4) to predict secondary structures of single stranded RNA sequences; and the UCSC Genome Bioinformatics website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://genome.ucsc.edu/\u003c/span\u003e\u003c/span\u003e) to elucidate potential biological functions. H3K4Me1 histone marker data from seven cell lines (GM12878, H1-hESC, HSMM, HUVEC, K562, NHEK, and NHLF) was also collected and analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eFor basic genetic information, a Hardy-Weinberg equilibrium (HWE) was estimated for each SNP among the control subjects (Group A) using a goodness-of-fit χ\u003csup\u003e2\u003c/sup\u003e test. To compare demographic differences among the three groups, we used one-way analysis of variance (ANOVA), chi-square (χ\u003csup\u003e2\u003c/sup\u003e) test, or Kruskal-Wallis test where appropriate. The association between each SNP and HCV infection susceptibility or outcome was estimated by constructing logistic regression models based on age, gender, and route of infection. The associations were further clarified with odds ratios (ORs) and 95% confidence intervals (CIs) using co-dominant, dominant, recessive, and additive models.\u003c/p\u003e \u003cp\u003eSTATA14.0 software was used to perform statistical analyses. \u003cem\u003eP\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered significant in all analyses except in multiple comparisons between SNPs, in which after Bonferroni corrections, \u003cem\u003eP\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;0.0125 (0.05/4) were considered significant.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003eParticipant characteristics\u003c/h2\u003e\n\u003cp\u003eBased on their anti-HCV and HCV RNA results, subjects were divided into three groups: HCV uninfected control group (Group A; \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1543), HCV spontaneous clearance group (Group B; \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;522), and HCV chronic infection group (Group C; \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;758). The demographic and clinical information for the three groups were shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The groups did not significantly differ in age or gender distributions (both \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). However, ALT and AST levels, infection route, and distribution of HCV genotypes significantly differed among the three groups (both \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eDemographic and clinical characteristics among HCV uninfected control, spontaneous clearance and chronic infection groups.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eVariables\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGroup A (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGroup B (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGroup C (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;1543\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;522\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;768\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge (years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.3\u0026thinsp;\u0026plusmn;\u0026thinsp;14.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e51.9\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.067\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e561(36.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e212 (40.61)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e312(40.63)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e982(63.64)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e310(59.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e456(59.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGender\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.117\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e617(39.99)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e199(38.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e273(35.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e926(60.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e323(61.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e495(64.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eALT (U/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1450(94.96)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e416(79.85)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e453(59.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e༞40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e77(5.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e105(20.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e313(40.86)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAST (U/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1456(95.48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e424(82.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e467(61.69)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e༞40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e69(4.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e89(17.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e290(38.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRoute of infection\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e561 (36.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e91 (17.43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76 (9.90)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIVDU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e181 (11.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e148 (28.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e140 (18.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePBD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e801 (51.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e283 (54.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e552 (71.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHCV genotype\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42(26.25)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e223(46.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNon-1b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e118(73.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e261(53.93)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eGroup A: uninfected controls; Group B: spontaneous clearance subjects; Group C: chronic infection patients.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eNon-1b means viral strains other than 1b, including genotype 1a, 2, and 3 (either solely or mixed infection).\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003eAbbreviations: HCV, hepatitis C virus; SD, standard deviation; ALT, alanine transaminase; AST, aspartate transaminase; HD, hemodialysis patients; IVDU, Intravenous drug user; PBD, paid blood donors.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003e\u003csup\u003ea\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e value of Welch among three groups, heterogeneity of variance.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003e\u003csup\u003eb\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e value of \u0026chi;\u003csup\u003e2\u003c/sup\u003e-test among three/two groups.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n\u003ch2\u003eAssociation of candidate SNPs with HCV infection outcomes\u003c/h2\u003e\n\u003cp\u003eThe MAFs of the selected SNPs were greater than 20%, and all of them were consistent with HWEs from the HCV uninfected group (Group A; Table S1). As shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, after adjusting for age, gender, and other potential confounding factors, a logistic regression analysis found that participants carrying \u003cem\u003eTNFRSF13B\u003c/em\u003e rs34562254-T had an increased risk of HCV infection (co-dominant model: OR\u0026thinsp;=\u0026thinsp;1.52, 95% CI: 1.17\u0026ndash;1.98, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002; additive model: OR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 1.07\u0026ndash;1.37, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002; recessive model: OR\u0026thinsp;=\u0026thinsp;1.41, 95% CI\u0026thinsp;=\u0026thinsp;1.10\u0026ndash;1.81, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007). However, we did not find an association between SNPs and HCV infection outcome (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eGenotypes distributions of \u003cem\u003eTNFRSF\u003c/em\u003e genes among HCV uninfected control, spontaneous clearance and chronic infection groups.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSNPs (genotype)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGroup A n (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGroup B n (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGroup C n (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR(95%CI)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR(95%CI)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;1543\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;522\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;768\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eTNFSF13-rs3803800\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.834\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.593\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e645 (44.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e221 (43.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e342 (46.22)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e669 (45.63)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e231 (45.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e325 (43.92)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01 (0.85\u0026ndash;1.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.908\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.91 (0.70\u0026ndash;1.17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.443\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e152 (10.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e56 (11.02)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e73 (9.86)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00 (0.74\u0026ndash;1.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.977\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.85 (0.56\u0026ndash;1.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.421\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDominant model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01 (0.85\u0026ndash;1.19)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.89 (0.70\u0026ndash;1.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.361\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRecessive model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00(0.75\u0026ndash;1.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.946\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.89 (0.60\u0026ndash;1.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.550\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdditive model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00 (0.88\u0026ndash;1.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.971\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.91 (0.76\u0026ndash;1.10)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.334\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eTNFSF13-rs11552708\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.024\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.588\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e573 (38.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e183 (35.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e249 (32.98)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e684 (45.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e252 (48.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e390 (51.66)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.18 (0.98\u0026ndash;1.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.080\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.06 (0.814\u0026ndash;1.370)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.680\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e251 (16.64)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e81 (15.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e116 (15.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.91 (0.711.72)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.468\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00(0.698\u0026ndash;1.440)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.991\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDominant model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.11 (0.93\u0026ndash;1.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.257\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.04 (0.81\u0026ndash;1.34)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.736\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRecessive model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.83 (0.66\u0026ndash;1.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.112\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.97 (0.70\u0026ndash;1.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.856\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdditive model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.03(0.92\u0026ndash;1.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.615\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.05(0.89\u0026ndash;1.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.576\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eTNFRSF13B-rs34562254\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.009\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.251\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e661 (43.95)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e190 (36.54)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e312 (41.16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e673 (44.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e251 (48.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e340 (44.85)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.15 (0.96\u0026ndash;1.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.119\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.81 (0.63\u0026ndash;1.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.112\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e170(11.30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e79 (15.19)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e106 (13.98)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.52 (1.17\u0026ndash;1.98)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.86(0.60\u0026ndash;1.22)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.401\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDominant model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.22 (1.03\u0026ndash;1.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.019\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.82 (0.65\u0026ndash;1.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.114\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRecessive model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.41 (1.10\u0026ndash;1.81)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.96(0.69\u0026ndash;1.34)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.805\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdditive model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.21 (1.07\u0026ndash;1.37)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.90 (0.76\u0026ndash;1.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.213\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eTNFRSF14-rs4870\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.031\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.472\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e455(29.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e177 (34.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e241 (31.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e782 (51.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e236(46.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e352 (46.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.77 (0.64\u0026ndash;0.93)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.043\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.06 (0.81\u0026ndash;1.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.684\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e286 (18.78)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e98 (19.34)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e164 (21.66)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.96(0.75\u0026ndash;1.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.708\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.25 (0.90\u0026ndash;1.74)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.186\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDominant model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.82 (0.69\u0026ndash;0.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.028\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.11 (0.87\u0026ndash;1.43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.396\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRecessive model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.12 (0.91\u0026ndash;1.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.290\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.21 (0.904\u0026ndash;1.63)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.201\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdditive model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.95 (0.84\u0026ndash;1.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.391\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.11(0.94\u0026ndash;1.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.206\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\"\u003eAbbreviations: CI, confidence interval; HCV, hepatitis C virus; OR, odds ratio; SNP, single nucleotide polymorphism.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\"\u003eGroup A: uninfected controls; Group B: spontaneous clearance subjects; Group C: chronic infection patients.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\"\u003e\u003csup\u003e*\u003c/sup\u003eThe \u003cem\u003eP\u003c/em\u003e value of \u0026chi;\u003csup\u003e2\u003c/sup\u003e-test refer to the distribution of SNPs between Group A and Group (B\u0026thinsp;+\u0026thinsp;C).\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\"\u003e\u003csup\u003e**\u003c/sup\u003eThe \u003cem\u003eP\u003c/em\u003e value of \u0026chi;2-test refer to the distribution of SNPs between Group B and Group C.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\"\u003e\u003csup\u003ea\u003c/sup\u003eThe \u003cem\u003eP\u003c/em\u003e value, OR and 95% CIs of Group (B\u0026thinsp;+\u0026thinsp;C) versus Group A were calculated on the basis of the logistic regression model, adjusted by gender, age, ALT level, AST level and route of infection.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\"\u003e\u003csup\u003eb\u003c/sup\u003eThe \u003cem\u003eP\u003c/em\u003e value, OR and 95% CIs of Group C versus Group B were calculated on the basis of the logistic regression model, adjusted by gender, age, ALT level, AST level and route of infection.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\"\u003eBonferroni correction was applied and the \u003cem\u003eP\u003c/em\u003e value was adjusted to 0.0125 (0.05/4).\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\"\u003eBold type indicates statistically significant results.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eStratification analysis of\u003c/strong\u003e \u003cspan class=\"BoldItalic\"\u003eTNFRSF13B\u003c/span\u003e \u003cstrong\u003ers34562254\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further explore the rs34562254 loci, we used stratified analysis based on the additive model to exclude the influence of confounding factors. As shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, the rs34562254 genotype remained significantly related to HCV susceptibility in the age and gender subgroups (both \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0125). Additionally, other variables such as ALT\u0026thinsp;\u0026le;\u0026thinsp;40\u0026nbsp;U/L (OR\u0026thinsp;=\u0026thinsp;1.22, 95% CI\u0026thinsp;=\u0026thinsp;1.07\u0026ndash;1.39, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), AST\u0026thinsp;\u0026le;\u0026thinsp;40\u0026nbsp;U/L (OR\u0026thinsp;=\u0026thinsp;1.23, 95% CI\u0026thinsp;=\u0026thinsp;1.08\u0026ndash;1.40, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and PBD (OR\u0026thinsp;=\u0026thinsp;1.29, 95% CI\u0026thinsp;=\u0026thinsp;1.09\u0026ndash;1.53, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), were also statistically correlated with HCV susceptibility. Based on these results, we further tested the heterogeneity of each stratified variable and found that no heterogeneity existed between the sub-layers (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eStratified analysis the association of rs34562254 with HCV susceptibility\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr style=\"height: 37px;\"\u003e\n\u003cth style=\"height: 37px;\" align=\"left\"\u003e\n\u003cp\u003eSubgroups\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"height: 37px;\" align=\"left\"\u003e\n\u003cp\u003eGroup A\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"height: 37px;\" align=\"left\"\u003e\n\u003cp\u003eGroup B\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"height: 37px;\" align=\"left\"\u003e\n\u003cp\u003eGroup C\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"height: 37px;\" align=\"left\"\u003e\n\u003cp\u003eOR(95%CI)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"height: 37px;\" align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"height: 37px;\" align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003en (CC/CT/TT)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003en (CC/CT/TT)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003en (CC/CT/TT)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.632\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e221/232/78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e78/99/35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e131/122/56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.17(0.97\u0026ndash;1.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e440/441/92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e112/152/44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e181/218/50\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.26(1.07\u0026ndash;1.66)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eGender\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.103\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e234/290/73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e63/103/33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e122/108/42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.07(0.89\u0026ndash;1.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.439\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e427/383/97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e127/148/46\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e190/232/64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.32(1.12\u0026ndash;1.55)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eALT (U/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.759\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e622/635/162\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e155/203/57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e181/194/71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.20(1.06\u0026ndash;1.37)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.004\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e33/36/8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e35/48/21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e130/145/35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.13(0.78\u0026ndash;1.62)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.505\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eAST (U/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e0.355\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e624/636/160\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e160/201/58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e174/202/71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.22(1.07\u0026ndash;1.39)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e30/35/10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e26/47/19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e131/136/33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.01(0.68\u0026ndash;1.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.950\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eRoute of infection\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.706\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eHD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e229/231/75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e29/47/15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e41/23/12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.14(0.87\u0026ndash;1.49)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.357\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003eIVDU\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e77/78/22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e53/72/23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e57/59/24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.18(0.89\u0026ndash;1.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.250\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003ePBD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e355/364/73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e108/132/41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\n\u003cp\u003e214/258/70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.29(1.09\u0026ndash;1.53)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr style=\"height: 13px;\"\u003e\n\u003ctd style=\"height: 13px;\" colspan=\"7\"\u003eAbbreviations: CI, confidence interval; HCV, hepatitis C virus; OR, odds ratio; HD, hemodialysis patients; IVDU, Intravenous drug user; PBD, paid blood donors.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 26px;\"\u003e\n\u003ctd style=\"height: 26px;\" colspan=\"7\"\u003eGroup A: uninfected controls; Group B: spontaneous clearance subjects; Group C: chronic infection patients. Group (B\u0026thinsp;+\u0026thinsp;C): Infected individuals (spontaneous clearance subjects\u0026thinsp;+\u0026thinsp;chronic infection patients).\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 28px;\"\u003e\n\u003ctd style=\"height: 28px;\" colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003e The \u003cem\u003eP\u003c/em\u003e value, OR and 95% CIs of Group (B\u0026thinsp;+\u0026thinsp;C) versus Group A were calculated on the basis of the additive model, adjusted by gender, age, ALT level, AST level and route of infection.\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 15px;\"\u003e\n\u003ctd style=\"height: 15px;\" colspan=\"7\"\u003e\u003csup\u003eb\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e-value for the heterogeneity test.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cspan class=\"BoldItalic\"\u003eIn silico\u003c/span\u003e \u003cstrong\u003eanalysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, rs34562254 had a RegulomeDB score of 3a, suggesting that it may be located at the transcription factor (TF) binding site, motif, and DNase peak. We used RNAfoldweb servers to predict \u003cem\u003eTNFRSF13B\u003c/em\u003e RNA secondary structure. The MAF of the centroid secondary structure was higher for the mutant rs34562254 T allele (-38.90\u0026nbsp;kcal/mol) than its wildtype C allele (-45.60\u0026nbsp;kcal/mol), indicating that the rs34562254 polymorphism in \u003cem\u003eTNFRSF13B\u003c/em\u003e could affect the transcription of related RNA (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). We also explored the potential biological functions of rs34562254 in the Encyclopedia of DNA Elements (ENCODE) project using the UCSC genome browser. As shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, rs34562254 was located on the highest peak of the H3K4Me1 histone marker in seven cell lines. H3K4me1 is a major histone modification associated with enhancer elements in nucleosomes and is linked to the transcriptional regulation of genes.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":" \u003cp\u003eWe found that \u003cem\u003eTNFRSF13B\u003c/em\u003e rs34562254 was associated with HCV infection susceptibility. More specifically, compared to subjects with rs34562254-CC (the wild type), those with CT/TT have an increased risk of HCV infection. The T allele\u0026rsquo;s effect was stronger in subjects who were older (\u0026ge;\u0026thinsp;50\u0026nbsp;years old), female, PBDs, and those with lower ALT and AST levels (\u0026le;\u0026thinsp;40\u0026nbsp;U/L). Moreover, our bioinformatics analysis found that rs34562254 was located at the highest peak of the H3K4Me1 histone marker and potentially regulates mRNA transcription by affecting TF binding.\u003c/p\u003e \u003cp\u003e \u003cem\u003eTNFRSF13B\u003c/em\u003e is a lymphocyte-specific tumor necrosis factor receptor that interacts with the NF-κB pathway and regulates B-cell development \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. It has been reported to be associated with a variety of human immune-related diseases such as CVID \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e, asthma \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e, and SLE \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Furthermore, Rand et al. have found that the \u003cem\u003eTNFRSF13\u003c/em\u003eB rs34562254 polymorphism was correlated with multiple myeloma and coronary artery lesions \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. In this study, based on the analyses of four genetic markers, we found that subjects with rs34562254-T were associated with an elevated risk of HCV infection.\u003c/p\u003e \u003cp\u003eFrom the NCBIdbSNP browser (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/snp/\u003c/span\u003e\u003c/span\u003e), we found that rs34562254 is a missense mutation located in the exon region of \u003cem\u003eTNFRSF13B\u003c/em\u003e. According to RegulomeDB, its RegulomeDB score is 3a (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.regulomedb.org/regulome-search/?regions=rs34562254\u0026amp;genome=GRCh37\u003c/span\u003e\u003c/span\u003e). RegulomeDB is a database that links SNPs with known and predicted regulatory elements within the intergenic regions of the \u003cem\u003eHomo sapiens\u003c/em\u003e genome. The RegulomeDB score represents a model integrating functional genomics features with continuous values such as the expression of quantitative trait loci, TF binding, TF motif, ChIP-seq signal, and DNase Footprint \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. Therefore, the rs34562254 SNP might have transcriptional regulatory functions including TF binding and DNase peak. Through the RNAfold web server, we found that the wildtype C allele of the centroid secondary structure had a lower MFE than the mutant T allele (-45.60 versus \u0026minus;\u0026thinsp;38.90\u0026nbsp;kcal/mol). From the ENCODE project and the UCSC genome browser, we found that rs34562254 was located on the highest peak of the H3K4Me1 histone marker, a major histone modification around enhancer elements in nucleosomes. When enhancer regions are enriched with H3K4me1 modifications, the enhancer enters a state of equilibrium. In contrast, when enhancer regions become enriched with both H3K4me1 and H3K27ac modifications, the enhancer enters an activated state that promotes gene expression \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Consequently, we speculate that genetic variants in rs34562254 might affect \u003cem\u003eTNFRSF13B\u003c/em\u003e expression by influencing TF binding.\u003c/p\u003e \u003cp\u003eThe stratified analysis showed that the rs34562254-T allele was significantly associated with HCV susceptibility in subjects that were female, over 50\u0026nbsp;years old, PBDs, and that had reduced ALT and AST levels (\u0026le;\u0026thinsp;40\u0026nbsp;U/L). In general, compared to men, women usually develop more intense innate, humoral, and cellular immune responses to viral infections and vaccinations \u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e, suggesting that the allele\u0026rsquo;s associated risk is more significant in females. ALT and AST level are major indicators of liver injury severity. In hepatitis C, ALT and AST levels become abnormal (\u0026gt;\u0026thinsp;40\u0026nbsp;U/L), which may confound the effects of the rs34562254-T allele \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. HCV is a common infection among older adults in certain areas of China \u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. Generally, older people are less healthy and are more likely than younger people to be exposed to potentially contaminated needles or blood products \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Accordingly, our result showed that the risk effect of the allele was more significant in the over 50\u0026nbsp;years old subgroup. For PBDs, they may rely on blood donation as a source of income. Blood-borne diseases such as HCV and HIV were frequently detected among PBDs in China during the early 1980s \u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e; HCV infection was very prevalent \u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSeveral limitations exist in this study. First, we did not test other SNPs in \u003cem\u003eTNFSF\u003c/em\u003e/\u003cem\u003eTNFRSF\u003c/em\u003e that may associate with HCV infection. Therefore, additional studies with more extensive genomic coverage are required to increase understanding of the role of \u003cem\u003eTNFRSF13B\u003c/em\u003e polymorphisms in HCV infection. Second, in the multivariate regression analysis of \u003cem\u003eTNFRSF\u003c/em\u003e SNP distribution and HCV infection outcome, HCV genotypes were not included due to a lack of data. Instead, we used existing HCV genotype data to perform a logistic regression on rs34562254 and found that the \u003cem\u003eP\u003c/em\u003e value did not change. In future studies, we will collect as much baseline data as possible to improve our reliability. Finally, the potential biological functions of \u003cem\u003eTNFRSF13B\u003c/em\u003e rs34562254 were speculated in the \u003cem\u003ein silico\u003c/em\u003e analysis. The exact mechanisms of rs34562254 in \u003cem\u003eTNFRSF13B\u003c/em\u003e in HCV infection need to be further investigated.\u003c/p\u003e "},{"header":"Conclusions","content":" \u003cp\u003eThis study was the first to report that the \u003cem\u003eTNFRSF13B\u003c/em\u003e missense mutation rs34562254 was significantly associated with HCV susceptibility among the Han Chinese population. Moreover, the increased risk of the mutant genotype was stronger in subjects who were females, older (\u0026ge;\u0026thinsp;50\u0026nbsp;years old), PBDs, and who had lower ALT and AST levels (\u0026le;\u0026thinsp;40\u0026nbsp;U/L). These findings are valuable in deepening the understanding of HCV infection susceptibility and offer a reference to develop prevention and control strategies among populations at high risk of repeated HCV infections.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eTNFRSF: tumor necrosis factor receptor superfamily; TNFSF: tumor necrosis factor superfamily; HCV: hepatitis C virus; HCC: hepatic carcinoma; DAAs: direct-acting antivirals; RA: rheumatoid arthritis; IBD: inflammatory bowel disease; MS: multiple sclerosis; CLL: chronic lymphocytic leukemia; SLE: systemic lupus erythematosus; CVID: common variable immunodeficiency; SNPs: single nucleotide polymorphisms; IVDU: Intravenous drug users; HD: hemodialysis patients; PBD: paid blood donors; HIV: human immunodeficiency virus; HBV: hepatitis B virus; ALT: alanine aminotransferase; AST: aspartate aminotransferase; MAF: minor allele frequency; HWE: Hardy-Weinberg equilibrium; ANOVA: one-way analysis of variance; ORs: odds ratios; CI: confidence intervals; GWAS: genome-wide association study; TACI: transmembrane activator and CAML interactor; SAE: serious adverse event; TN: treatment-na\u0026iuml;ve; TE: treatment-experienced; WHO: World Health Organization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll study procedures were approved by the medical ethics committee of Nanjing Medical University in accordance with the Declaration of Helsinki. The written informed consent was obtained from each participant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent of publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe current study was financially supported by the National Natural Science Foundation of China (Grant No. 81773499), Science Foundation for Distinguished Young Scholars of Jiangsu Province (Grant No. BK20190106), Open Research Fund Program of the State Key Laboratory of Virology of China (Grant No. 2019KF005), Key Project of Natural Science Foundation of Yunnan Province (Grant No. 2019FA005) and Jiangsu Program for Young Medical Talents (Grant No. QNRC2016616)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors made substantial contributions to editing and drafting of the manuscript. H.Z.F, Z.Q.F. and M.Y. designed and organized the study and supervised the whole project. H.Z.F, Z.Q.F., Z.J.G., C.H.W., J.L. and M.Y. contributed to field survey, data collection, laboratory detection and quality control. H.Z.F, Z.Q.F., D.C., C.S. and R.B.Y. performed data cleansing and statistical analysis. H.Z.F, Z.Q.F and Y.Z. provided analysis tools and performed data interpretation. H.Z.F., Z.Q.F., C.D. and M.Y. wrote and critical revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank Peng Huang, Yan Wang, Xiangyu Ye, Zeyang Ni and Yuqing Hou, for all the contributions to make this study carried out.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWHO. Global hepatitis report. 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Outcome of hepatitis C virus infection in Chinese paid plasma donors: a 12-19-year cohort study[J]. J Gastroenterol Hepatol. 2012;27(3):526\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\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":"","lastPublishedDoi":"10.21203/rs.3.rs-147629/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-147629/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGenetic variations in the tumor necrosis factor receptor superfamily (\u003cem\u003eTNFRSF) 13B\u003c/em\u003e have been reported to be associated with immune-related diseases. This study aimed to explore the relationship of tumor necrosis factor superfamily (\u003cem\u003eTNFSF\u003c/em\u003e) \u003cem\u003e13\u003c/em\u003e, \u003cem\u003eTNFRSF13B\u003c/em\u003e, and \u003cem\u003eTNFRSF14\u003c/em\u003e missense mutations with hepatitis C virus (HCV) infection susceptibility.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eSingle-nucleotide polymorphisms (SNPs) in \u003cem\u003eTNFSF13\u003c/em\u003e (rs3803800, rs11552708), \u003cem\u003eTNFRSF13B\u003c/em\u003e (rs34562254), and \u003cem\u003eTNFRSF14\u003c/em\u003e (rs4870) were genotyped in 469 intravenous drug users, 728 hemodialysis patients, and 1636 paid blood donors using a TaqMan real-time PCR assay. The USCS browser and RNAfold web servers were used to predict the biological functions of these selected SNPs.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAfter adjusting for gender, age, levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), and route of infection, a logistic regression analysis showed that subjects carrying a homozygous \u003cem\u003eTNFRSF13B\u003c/em\u003e rs34562254 TT mutant were more likely to be infected by HCV compared to those homozygous with the rs34562254 CC wild type (co-dominant model: OR\u0026thinsp;=\u0026thinsp;1.52, 95% CI: 1.17\u0026ndash;1.98, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002; recession model: OR\u0026thinsp;=\u0026thinsp;1.41, 95% CI: 1.10\u0026ndash;1.81, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007; additive model: OR\u0026thinsp;=\u0026thinsp;1.21, 95% CI: 1.07\u0026ndash;1.37, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). The effect of the risk allele rs34562254-T was stronger in subjects that were female, older (\u0026ge;\u0026thinsp;50\u0026nbsp;years old), paid blood donors, and with lower ALT and AST levels (\u0026le;\u0026thinsp;40\u0026nbsp;U/L). A bioinformatics analysis via the UCSC genome browser found that rs34562254 was located at the highest peak of the H3K4Me1 histone marker. Using the RNAfold web servers, the minimum free energy of the centroid secondary structure was found to be higher for the mutant rs34562254-T allele (-38.90\u0026nbsp;kcal/mol) than its wild type C allele (-45.60\u0026nbsp;kcal/mol). Additionally, the RegulomeDB score of rs34562254 was 3a. Altogether, the results of the bioinformatics analysis indicate that rs34562254 may affect gene expression levels by regulating the transcriptional activity of corresponding gene regions.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe rs34562254 polymorphisms in \u003cem\u003eTNFRSF13B\u003c/em\u003e were significantly associated with HCV infection among the Han Chinese population.\u003c/p\u003e","manuscriptTitle":"The TNFRSF13B rs34562254 Polymorphism is Associated with Hepatitis C Infection Risk in the Han Chinese Population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-01-19 00:17:07","doi":"10.21203/rs.3.rs-147629/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":"6215cb92-1c29-4f70-9076-0e9ae1b6f47e","owner":[],"postedDate":"January 19th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":1933437,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"2021-01-19T00:17:08+00:00","versionOfRecord":[],"versionCreatedAt":"2021-01-19 00:17:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-147629","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-147629","identity":"rs-147629","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}