Association On Wnt/?-catenin Signaling Pathway Gene-gene And Gene-Environment Interaction With Ankylosing Spondylitis Susceptibility

ObjectivesThis study was undertanken to explore the relationship between Wnt/?-catenin signaling pathway gene polymorphismand genetic susceptibility to AS and clinical features of AS in the Chinese population.Furthermore,the gene-gene interaction and gene-environment interaction in the pathogenesis of AS were studied,therefore to provide scientific basis for further revealing the pathogenesis of AS.MethodsThe case-control study was used,and a total of 1 400 subjects were included in our study.The patients were recruited from the department of rheumatism and immunology at the First Affiliation Hospital of Anhui Medical University from 2011 to 2017.All AS patients were diagnosed by skillful rheumatologists according to the modified 1984 New York Criteria.Age-and gender-matched healthy controls were recruited from the local community,and they all confirmed that they did not have any chronic inflammatory or autoimmune disease or a family history of such a disease.Peripheral venous blood samples of AS patients and healthy controls were obtained in an ethylene diamine tetraacetic acid(EDTA)anticoagulant tube at enrollment,and all AS patients were requested to fill out a questionnaire to record the general demographic characteristics,clinical features and environmental risk factors.Disease activity of AS patients was measured by the Bath Ankylosing Spondylitis Disease Activity Index(BASDAI),and functional impairment was measured by the Bath Ankylosing Spondylitis Functional Index(BASFI).We included eleven SNPs: WNT3A(rs964941)?WNT3A(rs752107)? GSK3?(rs334558)? RUNX2(rs1406846)? RUNX2(rs2677108)?DKK1(rs1896368)? DKK1(rs1569198)? LRP5(rs3736228)? LRP6(rs2302685)?SOST(rs4792909)?SOST(rs6503475),SNPscan technic(Genesky Biotechnologies Inc.,Shanghai,China)based on double ligation and multiplex fluorescence polymerase chain reaction was used for SNP genotyping.The distribution of allele and genotype frequencies between cases and controls was compared,and subgroup analysis by gender was performed.Linkage disequilibrium analysis was performed among four polymorphisms(DKK1: rs1896368 and DKK1: rs1569198,SOST: rs4792909 and SOST: rs6503475).The single case group was stratified according to different HLA-B27 status,different disease function index and different disease activity index,the correlation between the genotype and allele frequency of this pathway and the difference in AS disease severity and functional index under different genotypes of this pathway were compared.In addition,the interaction between gene-gene and gene-environment was also analyzed.The epidemiological questionnaire of this study was recorded by double-entry method,Epidata 3.1 software was used to establish the database,statistical power was determined by PASS 11.0 software,and statistical analysis was performed using SPSS 16.0 software.The normal continuity data were represented by`X±S,the non-normal continuity data were represented by M(P25,P75),and the qualitative data were directly described by frequency and percentage.For comparison of quantitative data between groups,t test or F test was used for those conforming to normal distribution and homogeneity of variance,Mann-Whitney U test was used for non-parametric test of two independent samples that did not conform to normal distribution,and Kruskal Wallis H test was used for non-parametric test of three independent samples.Chi-square test was used to compare qualitative data between groups.Hardy-Weinberg equilibrium(HWE)was assessed in the control group by the Chi-square test.The risk was expressed by OR value and 95% CI,and the difference was considered to be statistically significant if P<0.05 in the bilateral test.Bonferroni method was used to correct for multiple comparisons.Linkage disequilibrium and haplotype analysis were performed by using Haploview version 4.2.We used additive and multiplicative models to analyze the gene-gene interaction.The additive interaction was evaluated by using a 4×2 table combining different risk genotypes exposure,multiplication interaction model was evaluated by Logistic regression model,and multiple factor dimension reduction method was used to analyze the higher order interactions between gene and gene.We used case only study design and Logistic regression to analysis the gene-environment interactions.The strength of the association was expressed by OR value and 95% CI.ResultsA total of 1 400 AS cases and healthy controls were recruited in this study,and 1 360 of them had all SNPs successfully genotyped,while 673 patients and 687 healthy controls were finally enrolled into the study.The mean ages of the patients and the healthy control group were 28.65±9.26 and 28.62±7.76,respectively.The sex ratios(male/female)were 548/125 and 560/127,respectively.There was no statistically significant difference between these two groups in terms of age(t=0.05,P=0.96)or sex(?~2= 0.002,P=0.97).The HLA-B27 positive ratio in the case group was 61.37%,and the BASFI and BASDAI scores were 0.9(0,2.6),2(0.6,3.8),respectively.The HWE tests in the control group showed that all SNPs were in HWE except LRP6: rs2302685 and SOST : rs4792909(all P < 0.01).Genetic susceptibility analysis compared the distribution of genotype,allele,dominant model,recessive model,homozygous model and superdominant model between case group and healthy control group.11 SNP locis of the 7 genes were included in the study,only SOST(rs4792909)in superdominance model have statistical significance(?~2=4.16,P<0.05),after Bonferroni correction the difference was not statistically significant(a=0.05/11?0.005).According to the subgroup analysis by gender,there was a statistically significant difference in the frequency distribution of GSK3?(rs334558)genotype between the two groups(?~2=6.26,P<0.05),and a statistically significant difference in the frequency distribution of DKK1(rs1569198)allele between the two groups(?~2=4.55,P<0.05).The frequency distribution of the SOST(rs4792909)genotype in males was significantly different between the two groups(?~2=7.44,P<0.05).Linkage disequilibrium analysis showed a strong association between rs14068466 and rs2677108 of RUNX2 gene.Haplotype analysis did not reveal any differences in the distribution of haplotypes between AS patients and healthy controls,but subgroup analysis showed that the H2 haplotype(H2: T-G)in the DKK1 gene was associated with AS susceptibility in females(?~2= 4.14,P = 0.04).Stratified analysis by HLA-B27 revealed statistically significant differences in the frequency distribution of DKK1(rs1896368)genotype between the two groups(?~2=6.57,P<0.05),and SOST(rs4792909)genotype between the two groups(?~2=10.50,P<0.01).The other loci showed no significant difference in frequency distribution between the two groups.Stratified analysis of the case group based on BASDAI scores,the result showed that the frequency distribution of DKK1(rs1896368)genotype was statistically significant between the two groups(?~2 =10.12,P<0.01).The frequency distribution of RUNX2(rs1406846)allele was statistically significant between the two groups(?~2 =4.03,P < 0.05).The frequency distribution of DKK1(rs1896368)allele was statistically significant between the two groups(?~2=8.29,P<0.01).The other loci showed no significant difference in frequency distribution between the two groups.Stratified analysis of the case group based on BASFI scores,the result showed no significant difference in frequency distribution between the two groups.The differences in disease severity and functional indicators were compared among different genotypes of Wnt signaling genes.The results showed that the difference in CRP index between different genotypes in GSK3?(rs334558)was statistically significant(P<0.05),while the difference between different genotypes in LRP6(rs2302685)was statistically significant(P<0.05).Additive interaction analysis was conducted,significant positive additive interactionswere observed between WNT3A(rs752107)and DKK1(rs1569198)in the dominant model(RERI=0.55,95% CI= 0.004?1.09;AP=0.27,95% CI=0.03?0.51),the difference was still statistically significant after correction(P<0.001).Significant negative additive interactions were observed between DKK1(rs1569198)and LRP5(rs3736228)in the dominant model(RERI=0.40,95% CI=0.08?0.71;AP=0.51,95% CI=0.07 ? 0.94),significant negative additive interactions were observed between DKK1(rs1569198)and LRP5(rs3736228)in the dominant model(RERI=0.49,95%CI=0.12?0.86;AP=0.49,95% CI=0.17?0.82),significant negative additive interactions were observed between LRP5(rs3736228)and SOST(rs4792909)in the dominant model(RERI=0.33,95% CI=0.002?0.65;AP=0.41,95% CI=0.01?0.81),after Bonferroni correction all these differences were not statistically significant.No additive interaction was observed in the recessive model.Multiplicative interaction was analyzed,significant multiplicative interactions were observed between LRP5(rs3736228)and RUNX2(rs1406846)in the dominant model(P<0.05),significant multiplicative interactions were observed between SOST(rs6503475)and RUNX2(rs2677108)in the recessive model(P<0.05),after Bonferroni correction all these differences were not statistically significant.We used the MDR analysis to investigate the impact of the interaction among three or more SNPs,but all models were not statistically significant(all P>0.05).The analysis of the influence of environmental factors on the disease function index showed that there were statistically significant differences in BASFI scores among the groups with different smoking,drinking consumption,meat consumption and sleep quality(all P<0.05),and there were statistically significant differences in BASDAI scores among groups with different types of cooking oil,drinking water,noise and sleep quality.The interaction between genes and environmental risk factors was analyzed,there was an interaction between rs1569198 and smoking,milk consumption in the dominant model(P<0.05),and the interactions between rs1896368 and alcohol consumption were also observed in the dominant model(P<0.05),and no other interaction between the two SNPs and these environmental risk factors was observed in the recessive model.ConclusionsIn this study,we reported the association between the polymorphism of Wnt/?-catenin signaling pathway gene DKK1(rs1569198)and the genetic susceptibility of Chinese female population to AS.Our research implies a potential gene-gene interaction,for example,WNT3A(rs752107)and DKK1(rs1569198)may have additive interactions.It suggests that the simultaneous exposure of two susceptible genes may play a synergistic role,increasing the risk of AS.Our study also found gene-environment interactions,for example,there may be interactions between DKK1(rs1569198)polymorphism and smoking,milk consumption;DKK1(rs1896368)polymorphism and drinking,It suggests that smoking,drinking and low dairy intake may play a synergistic role in the presence of DKK1 susceptibility gene,increasing the risk of AS.Therefore,smoking cessation,limiting alcohol consumption and increasing the intake of dairy products may have very important public health value for the early prevention and control of this disease,thus revealing the importance of gene-gene and gene-environment interactions in the Wnt/?-catenin signaling pathway for understanding the genetic architecture of AS,but further studies are needed to confirm our conclusions.