Department of Periodontology, National Engineering Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, Peking University School and Hospital of Stomatology, Beijing, China.
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
J Clin Periodontol. 2020 May;47(5):583-593. doi: 10.1111/jcpe.13268. Epub 2020 Feb 20.
To identify risk variants associated with gene expression in peripheral blood and to identify genes whose expression change may contribute to the susceptibility to periodontitis.
We systematically integrated the genetic associations from a recent large-scale periodontitis GWAS and blood expression quantitative trait loci (eQTL) data using Sherlock, a Bayesian statistical framework. We then validated the potential causal genes in independent gene expression data sets. Gene co-expression analysis was used to explore the functional relationship for the identified causal genes.
Sherlock analysis identified 10 genes (rs7403881 for MT1L, rs12459542 for SIGLEC5, rs12459542 for SIGLEC14, rs6680386 for S100A12, rs10489524 for TRIM33, rs11962642 for HIST1H3E, rs2814770 for AIM2, rs7593959 for FASTKD2, rs10416904 for PKN1, and rs10508204 for WDR37) whose expression may influence periodontitis. Among these genes, AIM2 was consistent significantly upregulated in periodontium of periodontitis patients across four data sets. The cis-eQTL (rs2814770, ~16 kb upstream of AIM2) showed significant association with AIM2 (p = 6.63 × 10 ) and suggestive association with periodontitis (p = 7.52 × 10 ). We also validated the significant association between rs2814770 and AIM2 expression in independent expression data set. Pathway analysis revealed that genes co-expressed with AIM2 were significantly enriched in immune- and inflammation-related pathways.
Our findings implicate that AIM2 is a susceptibility gene, expression of which in gingiva may influence periodontitis risk. Further functional investigation of AIM2 may provide new insight for periodontitis pathogenesis.
鉴定与外周血基因表达相关的风险变异,并鉴定表达变化可能导致牙周炎易感性的基因。
我们使用 Sherlock(一种贝叶斯统计框架)系统地整合了最近一项大规模牙周炎 GWAS 和血液表达数量性状基因座(eQTL)数据中的遗传关联。然后,我们在独立的基因表达数据集验证了潜在的因果基因。基因共表达分析用于探索鉴定的因果基因的功能关系。
Sherlock 分析鉴定出 10 个基因(rs7403881 用于 MT1L、rs12459542 用于 SIGLEC5、rs12459542 用于 SIGLEC14、rs6680386 用于 S100A12、rs10489524 用于 TRIM33、rs11962642 用于 HIST1H3E、rs2814770 用于 AIM2、rs7593959 用于 FASTKD2、rs10416904 用于 PKN1 和 rs10508204 用于 WDR37),其表达可能影响牙周炎。在这些基因中,AIM2 在四个数据集的牙周炎患者的牙周组织中一致显著上调。cis-eQTL(rs2814770,AIM2 上游约 16kb)与 AIM2 显著相关(p=6.63×10-16),与牙周炎呈显著关联(p=7.52×10-10)。我们还在独立的表达数据集验证了 rs2814770 与 AIM2 表达之间的显著关联。通路分析表明,与 AIM2 共表达的基因在免疫和炎症相关途径中显著富集。
我们的研究结果表明,AIM2 是一个易感基因,其在牙龈中的表达可能影响牙周炎的风险。对 AIM2 的进一步功能研究可能为牙周炎发病机制提供新的见解。