Joint Bayesian inference of risk variants and tissue-specific epigenomic enrichments across multiple complex human diseases.
Joint Bayesian inference of risk variants and tissue-specific epigenomic enrichments across multiple complex human diseases.
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DOI：
10.1093/nar/gkw627
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发表时间：
2016-10-14
影响因子：
14.9
通讯作者：
Kellis M
中科院分区：
文献类型：
--
作者：
Li Y;Kellis M
全基因组关联研究（GWAS）为揭示人类疾病相关变异提供了一种强有力的方法，但精确定位致病变异仍然是一个挑战。这部分通过优先考虑与GWAS富集的表观基因组注释重叠的疾病相关变体来补救。在这里，我们介绍了一个新的贝叶斯模型里维埃拉（风险变异推断使用表观基因组参考注释）的推理驱动程序的变异，从汇总统计在多个性状使用数百个表观基因组注释。在模拟实验中，里维埃拉在因果变量和因果注释的检测能力上有很大的提高，多特征联合推理进一步提高了检测能力。我们应用里维埃拉对9种自身免疫性疾病和精神分裂症的现有GWAS汇总统计量进行建模，方法是联合利用来自ENCODE/Roadmap联盟的848种组织特异性表观基因组学注释中的潜在因果富集，这些注释涵盖127种细胞/组织类型和8种主要表观基因组标记。里维埃拉鉴定了由H3 K4 me 1和H3 K27 ac定义的增强子区域的有意义的组织特异性富集，其在九种自身免疫性疾病中特异性地用于血液T细胞，并且脑特异性增强子活性仅在精神分裂症中。此外，来自95%可信集的变异体显示出位于转录因子结合位点和DNA超敏位点的GTEx全血eQTL的高度保守和富集。此外，通过同时推断和利用性状之间的潜在表观基因组相关性对9个免疫性状进行联合建模，与单性状模型相比，进一步改善了功能富集。
Genome wide association studies (GWAS) provide a powerful approach for uncovering disease-associated variants in human, but fine-mapping the causal variants remains a challenge. This is partly remedied by prioritization of disease-associated variants that overlap GWAS-enriched epigenomic annotations. Here, we introduce a new Bayesian model RiVIERA (Risk Variant Inference using Epigenomic Reference Annotations) for inference of driver variants from summary statistics across multiple traits using hundreds of epigenomic annotations. In simulation, RiVIERA promising power in detecting causal variants and causal annotations, the multi-trait joint inference further improved the detection power. We applied RiVIERA to model the existing GWAS summary statistics of 9 autoimmune diseases and Schizophrenia by jointly harnessing the potential causal enrichments among 848 tissue-specific epigenomics annotations from ENCODE/Roadmap consortium covering 127 cell/tissue types and 8 major epigenomic marks. RiVIERA identified meaningful tissue-specific enrichments for enhancer regions defined by H3K4me1 and H3K27ac for Blood T-Cell specifically in the nine autoimmune diseases and Brain-specific enhancer activities exclusively in Schizophrenia. Moreover, the variants from the 95% credible sets exhibited high conservation and enrichments for GTEx whole-blood eQTLs located within transcription-factor-binding-sites and DNA-hypersensitive-sites. Furthermore, joint modeling the nine immune traits by simultaneously inferring and exploiting the underlying epigenomic correlation between traits further improved the functional enrichments compared to single-trait models.
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影响因子：
64.8
作者：
Ernst, Jason;Kheradpour, Pouya;Mikkelsen, Tarjei S.;Shoresh, Noam;Ward, Lucas D.;Epstein, Charles B.;Zhang, Xiaolan;Wang, Li;Issner, Robbyn;Coyne, Michael;Ku, Manching;Durham, Timothy;Kellis, Manolis;Bernstein, Bradley E.
通讯作者：
Bernstein, Bradley E.
影响因子：
14.9
作者：
Kheradpour P;Kellis M
通讯作者：
Kellis M
影响因子：
64.5
作者：
Hnisz D;Abraham BJ;Lee TI;Lau A;Saint-André V;Sigova AA;Hoke HA;Young RA
通讯作者：
Young RA
DOI：
10.1126/science.1262110
发表时间：
2015-05-08
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
GTEx Consortium
通讯作者：
GTEx Consortium
DOI：
10.1126/science.1222794
发表时间：
2012-09-07
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Maurano MT;Humbert R;Rynes E;Thurman RE;Haugen E;Wang H;Reynolds AP;Sandstrom R;Qu H;Brody J;Shafer A;Neri F;Lee K;Kutyavin T;Stehling-Sun S;Johnson AK;Canfield TK;Giste E;Diegel M;Bates D;Hansen RS;Neph S;Sabo PJ;Heimfeld S;Raubitschek A;Ziegler S;Cotsapas C;Sotoodehnia N;Glass I;Sunyaev SR;Kaul R;Stamatoyannopoulos JA
通讯作者：
Stamatoyannopoulos JA