WNT代谢通路相关基因与中国人群非综合征型唇腭裂发病风险的交互作用

目的:利用全基因组关联研究(genome-wide association study,GWAS)数据,从基因-基因交互作用和基因-环境交互作用方面探索WNT代谢通路相关基因在中国人群非综合征型唇腭裂(non-syndromic oral clefts,NSOC)发生风险中的作用。方法:本研究样本来自“唇腭裂基因和交互作用的国际合作研究”项目在中国地区募集的806个非综合征型唇裂合并或不合并腭裂(non-syndromic cleft lip with or without cleft palate,NSCL/P)核心家系和202个非综合征型单纯腭裂(non-syndromic cleft palate,NSCP)核心家系。通过收集研究对象的DNA样本和问卷调查获得基因型数据和母亲孕期环境暴露信息,利用此GWAS数据,采用条件Logistic回归模型探讨基因-基因交互作用和基因-环境交互作用,由R软件中的trio软件包完成。经过Bonferroni多重检验校正后,统计学检验的显著性阈值均设为P<3.47×10^-4。结果:经过数据质量控制后,NSCL/P核心家系和NSCP核心家系各纳入7个基因上的144个单核苷酸多态性(single nucleotide polymorphisms, SNPs)位点进入分析。在NSCL/P和NSCP家系中,分别有三对SNPs交互作用达到统计学显著性水平(P<3.47×10^-4):rs7618735(WNT5A)与rs10848543(WNT5B),rs631948(WNT11)与rs556874(WNT5A)以及rs631948(WNT11)与rs472631(WNT5A);rs589149(WNT11)与rs4765834(WNT5B),rs1402704(WNT11)与rs358792(WNT5A)以及rs1402704(WNT11)与rs358793(WNT5A)。此外,基因-环境交互作用分析未发现显著结果。结论:未发现WNT代谢通路相关基因-环境交互作用在NSCL/P和NSCP发病风险中的作用,但WNT代谢通路相关基因可能通过基因-基因交互作用影响NSOC的发病风险。

Evaluating the effect of WNT pathway genes considering interactions on the risk of non-syndromic oral clefts among Chinese populations

Objective: In this study, we used genome-wide association study (GWAS) data to explore whether WNT pathway genes were associated with non-syndromic oral clefts (NSOC) considering gene-gene interaction and gene-environment interaction. Methods: We conducted the analysis using 806 non-syndromic cleft lip with or without cleft palate (NSCL/P) case-parent trios and 202 non-syndromic cleft palate (NSCP) case-parent trios among Chinese populations selected from an international consortium established for a GWAS of non-syndromic oral clefts. Genotype data and maternal environmental exposures were collected through DNA samples and questionnaires. Conditional Logistic regression models were adopted to explore gene-gene interaction and gene-environment interaction using trio package in R software. The threshold of significance level was set as 3.47×10^-4 using Bonferroni correction. Results: A total of 144 single nucleotide polymorphisms (SNPs) in seven genes passed the quality control process in NSCL/P trios and NSCP trios, respectively. Totally six pairs of SNPs interactions showed statistically significant SNP-SNP interaction (P<3.47×10^-4) after Bonferroni correction, which were rs7618735 (WNT5A) and rs10848543 (WNT5B), rs631948 (WNT11) and rs556874 (WNT5A), and rs631948 (WNT11) and rs472631 (WNT5A) among NSCL/P trios; rs589149 (WNT11) and rs4765834 (WNT5B), rs1402704 (WNT11) and rs358792 (WNT5A), and rs1402704 (WNT11) and rs358793 (WNT5A) among NSCP trios, respectively. In addition, no significant result was found for gene-environment interaction analysis in both of the NSCL/P trios and NSCP trios. Conclusion: Though this study failed to detect significant association based on gene-environment interactions of seven WNT pathway genes and the risk of NSOC, WNT pathway genes may influence the risk of NSOC through potential gene-gene interaction.