Knowledge-driven analysis identifies a gene-gene interaction affecting high-density lipoprotein cholesterol levels in multi-ethnic populations.
Knowledge-driven analysis identifies a gene-gene interaction affecting high-density lipoprotein cholesterol levels in multi-ethnic populations.
复制标题
DOI：
10.1371/journal.pgen.1002714
复制
发表时间：
2012
期刊：
影响因子：
4.5
通讯作者：
Keinan A
中科院分区：
文献类型：
--
作者：
Ma L;Brautbar A;Boerwinkle E;Sing CF;Clark AG;Keinan A
总胆固醇、低密度脂蛋白胆固醇、甘油三酯和高密度脂蛋白胆固醇（HDL-C）水平是冠状动脉疾病最重要的危险因素之一。我们测试了影响这四种脂质水平的基因-基因相互作用，这是基于已建立的全基因组关联研究（GWAS）命中、蛋白质-蛋白质相互作用和途径信息的先验知识。使用来自社区动脉粥样硬化风险（ARIC）研究的9，713名欧洲裔美国人的基因型数据，我们确定了HMGCR和LIPC附近基因座之间的相互作用对HDL-C水平的影响（Bonferroni校正Pc = 0.002）。 使用自适应基因座为基础的验证程序，我们成功地验证了这种基因-基因相互作用的欧洲裔美国人队列的心脏研究（Pc = 0.002）和多种族研究的动脉粥样硬化（梅萨; Pc = 0.006）。 这两个基因座之间的相互作用也是显着的，在非洲裔美国人的样本从ARIC（Pc = 0.004）和西班牙裔美国人的样本从梅萨（Pc = 0.04）。 HMGCR和LIPC均参与脂质代谢，并且全基因组关联研究先前已确定LIPC与HDL-C水平相关。然而，HDL-C的新的基因-基因相互作用的影响，这里报道的是两倍的两个位点的边际效应的总和预测的显着。总之，基于知识驱动的上位性分析，再加上一个新的基于基因座的验证方法，我们成功地确定和验证了影响多民族人群中的复杂性状的相互作用。全基因组关联研究（GWAS）已经确定了许多与复杂人类性状或疾病相关的基因座。然而，这些基因座解释的遗传变异的比例往往相对较低。基因-基因互作可能在复杂性状或疾病中起重要作用，并且是导致遗传力缺失的许多可能因素之一。然而，到目前为止，只有少数相互作用已被发现，并在GWAS中进行了验证，由于有限的权力所造成的需要进行多次测试校正非常大量的测试。在这里，我们使用了三种类型的先验知识，已知的GWAS命中，蛋白质-蛋白质相互作用和途径信息，来指导我们寻找影响四种脂质水平的基因-基因相互作用。我们确定了HMGCR和LIPC附近的一个位点之间的相互作用，其对高密度脂蛋白胆固醇（HDL-C）的影响和另一对位点的相互作用，其对低密度脂蛋白胆固醇（LDL-C）的影响。我们在一些独立的多种族人群中验证了HDL-C的相互作用，而LDL-C的相互作用没有得到验证。先验知识驱动的搜索方法和基于基因座的验证程序显示了在当前和未来的GWAS中解剖和验证基因-基因相互作用的潜力。
Total cholesterol, low-density lipoprotein cholesterol, triglyceride, and high-density lipoprotein cholesterol (HDL-C) levels are among the most important risk factors for coronary artery disease. We tested for gene–gene interactions affecting the level of these four lipids based on prior knowledge of established genome-wide association study (GWAS) hits, protein–protein interactions, and pathway information. Using genotype data from 9,713 European Americans from the Atherosclerosis Risk in Communities (ARIC) study, we identified an interaction between HMGCR and a locus near LIPC in their effect on HDL-C levels (Bonferroni corrected P c = 0.002). Using an adaptive locus-based validation procedure, we successfully validated this gene–gene interaction in the European American cohorts from the Framingham Heart Study (P c = 0.002) and the Multi-Ethnic Study of Atherosclerosis (MESA; P c = 0.006). The interaction between these two loci is also significant in the African American sample from ARIC (P c = 0.004) and in the Hispanic American sample from MESA (P c = 0.04). Both HMGCR and LIPC are involved in the metabolism of lipids, and genome-wide association studies have previously identified LIPC as associated with levels of HDL-C. However, the effect on HDL-C of the novel gene–gene interaction reported here is twice as pronounced as that predicted by the sum of the marginal effects of the two loci. In conclusion, based on a knowledge-driven analysis of epistasis, together with a new locus-based validation method, we successfully identified and validated an interaction affecting a complex trait in multi-ethnic populations. Genome-wide association studies (GWAS) have identified many loci associated with complex human traits or diseases. However, the fraction of heritable variation explained by these loci is often relatively low. Gene–gene interactions might play a significant role in complex traits or diseases and are one of the many possible factors contributing to the missing heritability. However, to date only a few interactions have been found and validated in GWAS due to the limited power caused by the need for multiple-testing correction for the very large number of tests conducted. Here, we used three types of prior knowledge, known GWAS hits, protein–protein interactions, and pathway information, to guide our search for gene–gene interactions affecting four lipid levels. We identified an interaction between HMGCR and a locus near LIPC in their effect on high-density lipoprotein cholesterol (HDL-C) and another pair of loci that interact in their effect on low-density lipoprotein cholesterol (LDL-C). We validated the interaction on HDL-C in a number of independent multiple-ethnic populations, while the interaction underlying LDL-C did not validate. The prior knowledge-driven searching approach and a locus-based validation procedure show the potential for dissecting and validating gene–gene interactions in current and future GWAS.
登录
查看更多内容
DOI：
10.1038/nrg2579
发表时间：
2009-06
期刊：
Nature reviews. Genetics
影响因子：
--
作者：
Cordell HJ
通讯作者：
Cordell HJ
稀有变体会产生整个基因组的关联。
影响因子：
9.8
作者：
Dickson SP;Wang K;Krantz I;Hakonarson H;Goldstein DB
通讯作者：
Goldstein DB
DOI：
10.1073/pnas.0903103106
发表时间：
2009-06-09
影响因子：
11.1
作者：
Hindorff, Lucia A.;Sethupathy, Praveen;Manolio, Teri A.
通讯作者：
Manolio, Teri A.
影响因子：
5
作者：
Bild, DE;Bluemke, DA;Tracy, RP
通讯作者：
Tracy, RP
影响因子：
4.5
作者：
Dumitrescu L;Carty CL;Taylor K;Schumacher FR;Hindorff LA;Ambite JL;Anderson G;Best LG;Brown-Gentry K;Bůžková P;Carlson CS;Cochran B;Cole SA;Devereux RB;Duggan D;Eaton CB;Fornage M;Franceschini N;Haessler J;Howard BV;Johnson KC;Laston S;Kolonel LN;Lee ET;MacCluer JW;Manolio TA;Pendergrass SA;Quibrera M;Shohet RV;Wilkens LR;Haiman CA;Le Marchand L;Buyske S;Kooperberg C;North KE;Crawford DC
通讯作者：
Crawford DC