Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways
Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways
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DOI：
10.1534/genetics.118.300805
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发表时间：
2018-05
期刊：
影响因子：
3.3
通讯作者：
Chong Wu;W. Pan
中科院分区：
文献类型：
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作者：
Chong Wu;W. Pan
要提高全基因组关联研究(GWAS)的统计能力，以识别更多可以解释“缺失遗传性”的风险变异或基因座，仍然具有挑战性。此外，由于大多数已识别的变异体不在基因编码区，对其功能的生物学解释在很大程度上是缺乏的。另一方面，最近的生物技术进步使实验测量基因组的三维组织成为可能，包括高分辨率的增强子-启动子相互作用。由于众所周知，增强子-启动子相互作用在调控基因表达程序中的关键作用，这些数据已被应用于将Gwas风险变量与其假定的目标基因联系起来，从而深入了解潜在的生物学机制。然而，它们在GWAS关联测试中的直接使用还有待开发。在这里，我们建议将增强子-启动子相互作用整合到GWAS关联分析中，以提高统计能力和提高可解释性。我们通过在两个大规模精神分裂症(SCZ)GWA总结数据集上的应用证明，所提出的方法可以识别一些与SCZ相关的新基因和通路(不包含显著的SNPs)。例如，经过Bonferroni校正后，对于包含36,989例病例和113,075名对照的更大的SCZ数据集，我们的方法应用于基因体和增强子区域，发现27个新基因和11个新的KEGG途径是显著的，所有这些都被转录组范围关联研究(TWAS)方法遗漏。我们的结论是，我们提出的方法是潜在的有用的，并是对TWAS和其他标准的基于基因和途径的方法的补充。
It remains challenging to boost statistical power of genome-wide association studies (GWASs) to identify more risk variants or loci that can account for “missing heritability.” Furthermore, since most identified variants are not in gene-coding regions, a biological interpretation of their function is largely lacking. On the other hand, recent biotechnological advances have made it feasible to experimentally measure the three-dimensional organization of the genome, including enhancer–promoter interactions in high resolutions. Due to the well-known critical roles of enhancer–promoter interactions in regulating gene expression programs, such data have been applied to link GWAS risk variants to their putative target genes, gaining insights into underlying biological mechanisms. However, their direct use in GWAS association testing is yet to be exploited. Here we propose integrating enhancer–promoter interactions into GWAS association analysis to both boost statistical power and enhance interpretability. We demonstrate that through an application to two large-scale schizophrenia (SCZ) GWAS summary data sets, the proposed method could identify some novel SCZ-associated genes and pathways (containing no significant SNPs). For example, after the Bonferroni correction, for the larger SCZ data set with 36,989 cases and 113,075 controls, our method applied to the gene body and enhancer regions identified 27 novel genes and 11 novel KEGG pathways to be significant, all missed by the transcriptome-wide association study (TWAS) approach. We conclude that our proposed method is potentially useful and is complementary to TWAS and other standard gene- and pathway-based methods.