Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk.
Detecting genome-wide directional effects of transcription factor binding on polygenic disease risk.
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DOI：
10.1038/s41588-018-0196-7
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发表时间：
2018-10
期刊：
影响因子：
30.8
通讯作者：
Price AL
中科院分区：
文献类型：
--
作者：
Reshef YA;Finucane HK;Kelley DR;Gusev A;Kotliar D;Ulirsch JC;Hormozdiari F;Nasser J;O'Connor L;van de Geijn B;Loh PR;Grossman SR;Bhatia G;Gazal S;Palamara PF;Pinello L;Patterson N;Adams RP;Price AL
GWAS数据的生物学解释通常涉及评估SNP是否与生物过程相关，例如，转录因子（TF）的结合，显示疾病信号的无符号富集。然而，量化每个SNP等位基因是否促进或阻碍生物学过程的签名注释可以实现关于疾病机制的更强有力的陈述。我们介绍了一种方法，签署LD配置文件回归，用于检测全基因组的方向性影响签署功能注释疾病风险。我们通过模拟和应用于血液中的分子QTL，恢复已知的转录调节因子来验证该方法。我们将该方法应用于48个GTEx组织中的eQTL，确定了651个TF-组织关联，包括30个具有组织特异性的强有力证据。我们将该方法应用于46种疾病和复杂性状（平均N= 290 K），识别了代表12个独立TF-性状关联的77个注释-性状关联，并使用基因集富集分析来表征潜在的转录程序。我们的研究结果涉及新的致病基因和新的疾病机制。
Biological interpretation of GWAS data frequently involves assessing whether SNPs linked to a biological process, e.g., binding of a transcription factor (TF), show unsigned enrichment for disease signal. However, signed annotations quantifying whether each SNP allele promotes or hinders the biological process can enable stronger statements about disease mechanism. We introduce a method, signed LD profile regression, for detecting genome-wide directional effects of signed functional annotations on disease risk. We validate the method via simulations and application to molecular QTL in blood, recovering known transcriptional regulators. We apply the method to eQTL in 48 GTEx tissues, identifying 651 TF-tissue associations including 30 with robust evidence of tissue specificity. We apply the method to 46 diseases and complex traits (average N=290K), identifying 77 annotation-trait associations representing 12 independent TF-trait associations, and characterize the underlying transcriptional programs using gene-set enrichment analyses. Our results implicate new causal disease genes and new disease mechanisms.
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影响因子：
30.8
作者：
Bulik-Sullivan, Brendan K.;Loh, Po-Ru;Finucane, Hilary K.;Ripke, Stephan;Yang, Jian;Patterson, Nick;Daly, Mark J.;Price, Alkes L.;Neale, Benjamin M.
通讯作者：
Neale, Benjamin M.
遗传对人体组织基因表达的影响。
影响因子：
64.8
作者：
GTEx Consortium;Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group;Statistical Methods groups—Analysis Working Group;Enhancing GTEx (eGTEx) groups;NIH Common Fund;NIH/NCI;NIH/NHGRI;NIH/NIMH;NIH/NIDA;Biospecimen Collection Source Site—NDRI;Biospecimen Collection Source Site—RPCI;Biospecimen Core Resource—VARI;Brain Bank Repository—University of Miami Brain Endowment Bank;Leidos Biomedical—Project Management;ELSI Study;Genome Browser Data Integration &Visualization—EBI;Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz;Lead analysts:;Laboratory, Data Analysis &Coordinating Center (LDACC):;NIH program management:;Biospecimen collection:;Pathology:;eQTL manuscript working group:;Battle A;Brown CD;Engelhardt BE;Montgomery SB
通讯作者：
Montgomery SB
影响因子：
64.5
作者：
Boyle EA;Li YI;Pritchard JK
通讯作者：
Pritchard JK
影响因子：
2.5
作者：
BULLITT, E
通讯作者：
BULLITT, E
影响因子：
64.5
作者：
Aneichyk T;Hendriks WT;Yadav R;Shin D;Gao D;Vaine CA;Collins RL;Domingo A;Currall B;Stortchevoi A;Multhaupt-Buell T;Penney EB;Cruz L;Dhakal J;Brand H;Hanscom C;Antolik C;Dy M;Ragavendran A;Underwood J;Cantsilieris S;Munson KM;Eichler EE;Acuña P;Go C;Jamora RDG;Rosales RL;Church DM;Williams SR;Garcia S;Klein C;Müller U;Wilhelmsen KC;Timmers HTM;Sapir Y;Wainger BJ;Henderson D;Ito N;Weisenfeld N;Jaffe D;Sharma N;Breakefield XO;Ozelius LJ;Bragg DC;Talkowski ME
通讯作者：
Talkowski ME