Phenome-wide association study (PheWAS) for detection of pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network.
Phenome-wide association study (PheWAS) for detection of pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network.
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DOI：
10.1371/journal.pgen.1003087
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发表时间：
2013
期刊：
影响因子：
4.5
通讯作者：
Ritchie MD
中科院分区：
文献类型：
--
作者：
Pendergrass SA;Brown-Gentry K;Dudek S;Frase A;Torstenson ES;Goodloe R;Ambite JL;Avery CL;Buyske S;Bůžková P;Deelman E;Fesinmeyer MD;Haiman CA;Heiss G;Hindorff LA;Hsu CN;Jackson RD;Kooperberg C;Le Marchand L;Lin Y;Matise TC;Monroe KR;Moreland L;Park SL;Reiner A;Wallace R;Wilkens LR;Crawford DC;Ritchie MD
使用全表型关联研究（PheWAS）方法，我们使用基因组学和流行病学（PAGE）网络全面测试了群体结构中70，061名研究参与者的遗传变异与表型的关联。我们的目的是更好地描述复杂性状的遗传结构，并确定新的多效性关系。该PheWAS借鉴了PAGE中代表四个主要种族/族裔群体（欧洲裔美国人（EA），非洲裔美国人（AA），西班牙裔/墨西哥裔美国人和亚洲/太平洋岛民）的五项基于人群的研究，每个研究中心都测量了多种性状，相关实验室指标和中间生物标志物。通过全基因组关联研究（GWAS）鉴定的83个单核苷酸多态性（SNP）在两个或多个PAGE研究地点进行基因分型。进行了按人种/种族分层的全面关联性检验，包括映射到105个表型类别的4，706个表型，并在研究中心之间比较了关联性结果。共有111个PheWAS结果与两个或多个PAGE研究中心显著相关，具有一致的效应方向，对于相同的种族/民族、SNP和表型类别，显著性阈值为p<0.01。在先前与表型（如血脂性状、2型糖尿病和体重指数）相关的SNP鉴定结果中，52个重复了先前发表的基因型-表型关联，26个代表与先前已知的基因型-表型关联密切相关的表型，33个代表具有多效性效应的潜在新型基因型-表型关联。大多数潜在的新结果是针对单一PheWAS表型类别，例如，对于CDKN 2A/B rs 1333049（先前与EA中的2型糖尿病相关），在AA中确定了PheWAS与血红蛋白水平的相关性。然而，值得注意的是，GALNT 2 rs 2144300（先前与EA中的高密度脂蛋白胆固醇水平相关）具有多种潜在的新型PheWAS关联，与AA中的高血压相关表型以及EA中的血清钙水平和冠状动脉疾病表型相关。PheWAS确定了假设生成和复杂性状遗传结构探索的关联。在全表型关联研究（PheWAS）中，系统地测试数据集中所有潜在的遗传变异与研究参与者中测量的所有可用表型和性状的关联。通过研究遗传变异和表型多样性之间的关系，有可能揭示单核苷酸多态性（SNP），表型和相关表型网络之间的新关系。PheWAS还可以揭示多效性，提供新的机制见解，并促进假设生成。这种方法是全基因组关联研究（GWAS）的补充，GWAS测试了数十万到超过一百万个单核苷酸多态性与单个表型或有限表型结构域之间的关联。使用基因组学和流行病学（PAGE）网络的人口结构具有广泛的表型和性状的措施，包括临床状况和风险因素的流行和事件状态，以及临床参数和中间生物标志物。我们以高通量的方式对一系列全基因组关联研究（GWAS）鉴定的SNP和PAGE网络中的一系列表型之间的关联进行了测试。我们复制了一些以前报道的关联，验证了PheWAS方法。我们还确定了新的基因型-表型协会可能代表多效性的影响。
Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype–phenotype associations, 26 represented phenotypes closely related to previously known genotype–phenotype associations, and 33 represented potentially novel genotype–phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits. In phenome-wide association studies (PheWAS) all potential genetic variants in a dataset are systematically tested for association with all available phenotypes and traits that have been measured in study participants. By investigating the relationship between genetic variation and a diversity of phenotypes, there is the potential for uncovering novel relationships between single nucleotide polymorphisms (SNPs), phenotypes, and networks of interrelated phenotypes. PheWAS also can expose pleiotropy, provide novel mechanistic insights, and foster hypothesis generation. This approach is complementary to genome-wide association studies (GWAS) that test the association between hundreds of thousands, to over a million, single nucleotide polymorphisms and a single phenotype or limited phenotypic domain. The Population Architecture using Genomics and Epidemiology (PAGE) network has measures for a wide array of phenotypes and traits, including prevalent and incident status for clinical conditions and risk factors, as well as clinical parameters and intermediate biomarkers. We performed tests of association between a series of genome-wide association study (GWAS)–identified SNPs and a comprehensive range of phenotypes from the PAGE network in a high-throughput manner. We replicated a number of previously reported associations, validating the PheWAS approach. We also identified novel genotype–phenotype associations possibly representing pleiotropic effects.
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影响因子：
16.2
作者：
Isomaa, B;Almgren, P;Groop, L
通讯作者：
Groop, L
与人类血液低密度脂蛋白胆固醇、高密度脂蛋白胆固醇或甘油三酯相关的六个新位点。
影响因子：
30.8
作者：
Kathiresan, Sekar;Melander, Olle;Guiducci, Candace;Surti, Aarti;Burtt, Noel P.;Rieder, Mark J.;Cooper, Gregory M.;Roos, Charlotta;Voight, Benjamin F.;Havulinna, Aki S.;Wahlstrand, Bjorn;Hedner, Thomas;Corella, Dolores;Tai, E. Shyong;Ordovas, Jose M.;Berglund, Goran;Vartiainen, Erkki;Jousilahti, Pekka;Hedblad, Bo;Taskinen, Marja-Riitta;Newton-Cheh, Christopher;Salomaa, Veikko;Peltonen, Leena;Groop, Leif;Altshuler, David M.;Orho-Melander, Marju
通讯作者：
Orho-Melander, Marju
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：
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
影响因子：
--
作者：
Johnson AD;O'Donnell CJ
通讯作者：
O'Donnell CJ