Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies.
Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies.
复制标题
使用全基因组关联研究的汇总统计数据推断表型之间的因果关系。
DOI：
10.1007/s00439-018-1876-1
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发表时间：
2018-03
期刊：
影响因子：
5.3
通讯作者：
Deng HW
中科院分区：
文献类型：
--
作者：
Meng XH;Shen H;Chen XD;Xiao HM;Deng HW
全基因组关联研究 (GWAS) 已成功识别出与多种复杂表型和疾病相关的众多遗传变异，并为使用汇总关联统计数据进行进一步分析提供了巨大的机会。最近，皮克雷尔等人。开发了一种使用独立的假定因果 SNP 进行因果推断的稳健方法。然而，当仅识别出有限数量的独立推定因果 SNP 时，该方法可能无法推断两种表型之间的因果关系。在这里，我们扩展了 Pickrell 的方法，使其更适用于一般情况。我们通过用领先 SNP（每个独立基因座中最重要的 SNP 集合）替换假定的因果 SNP 来扩展因果推断方法，并使用模拟和经验数据测试我们扩展方法的性能。模拟表明，当使用相同数量的遗传变异时，与 Pickrell 等人的原始方法相比，我们的扩展方法在零模型下具有相似的检验统计量分布，并且在因果模型下具有可比较的功效。但在实践中，我们的扩展方法通常会更强大，因为独立先导 SNP 的数量通常大于独立假定因果 SNP 的数量。另一方面，包含更多的 SNP 不会导致更多的误报。通过应用我们的扩展方法来总结 GWAS 血液代谢物和股骨颈骨矿物质密度 (FN-BMD) 的统计数据，我们成功识别出 10 种可能影响 FN-BMD 的血液代谢物。我们扩展了一种因果推断方法，使用 GWAS 的汇总统计来推断两种表型之间的假定因果关系，并确定了 FN-BMD 的许多潜在因果代谢物，这可能为骨质疏松症的病理生理机制提供新的见解。
Genome-wide association studies (GWAS) have successfully identified numerous genetic variants associated with diverse complex phenotypes and diseases, and provided tremendous opportunities for further analyses using summary association statistics. Recently, Pickrell et al. developed a robust method for causal inference using independent putative causal SNPs. However, this method may fail to infer the causal relationship between two phenotypes when only a limited number of independent putative causal SNPs identified. Here, we extended Pickrell’s method to make it more applicable for the general situations. We extended the causal inference method by replacing the putative causal SNPs with the lead SNPs (the set of the most significant SNPs in each independent locus) and tested the performance of our extended method by using both simulation and empirical data. Simulations suggested that when the same number of genetic variants are used, our extended method had similar distribution of test statistic under the null model as well as comparable power under the causal model compared with the original method by Pickrell et al. But in practice, our extended method would generally be more powerful because the number of independent lead SNPs was often larger than the number of independent putative causal SNPs. And including more SNPs on the other hand would not cause more false positives. By applying our extended method to summary statistics from GWAS for blood metabolites and femoral neck bone mineral density (FN-BMD), we successfully identified 10 blood metabolites that may causally influence FN-BMD. We extended a causal inference method for inferring putative causal relationship between two phenotypes using summary statistics from GWAS, and identified a number of potential causal metabolites for FN-BMD, which may provide novel insights into the pathophysiological mechanisms underlying osteoporosis.
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影响因子：
30.8
作者：
Kettunen, Johannes;Tukiainen, Taru;Sarin, Antti-Pekka;Ortega-Alonso, Alfredo;Tikkanen, Emmi;Lyytikainen, Leo-Pekka;Kangas, Antti J.;Soininen, Pasi;Wuertz, Peter;Silander, Kaisa;Dick, Danielle M.;Rose, Richard J.;Savolainen, Markku J.;Viikari, Jorma;Kahonen, Mika;Lehtimaki, Terho;Pietilainen, Kirsi H.;Inouye, Michael;McCarthy, Mark I.;Jula, Antti;Eriksson, Johan;Raitakari, Olli T.;Salomaa, Veikko;Kaprio, Jaakko;Jarvelin, Marjo-Riitta;Peltonen, Leena;Perola, Markus;Freimer, Nelson B.;Ala-Korpela, Mika;Palotie, Aarno;Ripatti, Samuli
通讯作者：
Ripatti, Samuli
影响因子：
30.8
作者：
Shin, So-Youn;Fauman, Eric B.;Petersen, Ann-Kristin;Krumsiek, Jan;Santos, Rita;Huang, Jie;Arnold, Matthias;Erte, Idil;Forgetta, Vincenzo;Yang, Tsun-Po;Walter, Klaudia;Menni, Cristina;Chen, Lu;Vasquez, Louella;Valdes, Ana M.;Hyde, Craig L.;Wang, Vicky;Ziemek, Daniel;Roberts, Phoebe;Xi, Li;Grundberg, Elin;Waldenberger, Melanie;Richards, J. Brent;Mohney, Robert P.;Milburn, Michael V.;John, Sally L.;Trimmer, Jeff;Theis, Fabian J.;Overington, John P.;Suhre, Karsten;Brosnan, M. Julia;Gieger, Christian;Kastenmueller, Gabi;Spector, Tim D.;Soranzo, Nicole
通讯作者：
Soranzo, Nicole
影响因子：
30.8
作者：
通讯作者：
--
影响因子：
30.8
作者：
Bulik-Sullivan B;Finucane HK;Anttila V;Gusev A;Day FR;Loh PR;ReproGen Consortium;Psychiatric Genomics Consortium;Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3;Duncan L;Perry JR;Patterson N;Robinson EB;Daly MJ;Price AL;Neale BM
通讯作者：
Neale BM
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y