Hierarchical modeling identifies novel lung cancer susceptibility variants in inflammation pathways among 10,140 cases and 11,012 controls.
Hierarchical modeling identifies novel lung cancer susceptibility variants in inflammation pathways among 10,140 cases and 11,012 controls.
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DOI：
10.1007/s00439-013-1270-y
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发表时间：
2013-05
期刊：
影响因子：
5.3
通讯作者：
Hung, Rayjean J.
中科院分区：
文献类型：
--
作者：
Brenner, Darren R.;Brennan, Paul;Boffetta, Paolo;Amos, Christopher I.;Spitz, Margaret R.;Chen, Chu;Goodman, Gary;Heinrich, Joachim;Bickeboeller, Heike;Rosenberger, Albert;Risch, Angela;Muley, Thomas;McLaughlin, John R.;Benhamou, Simone;Bouchardy, Christine;Lewinger, Juan Pablo;Witte, John S.;Chen, Gary;Bull, Shelley;Hung, Rayjean J.
最近的证据表明，炎症在肺癌的发展中起着关键作用。在这项研究中，我们使用了两阶段的方法来研究炎症途径中的遗传变异与肺癌风险之间的关联，基于全基因组关联研究（GWAS）数据。使用基因卡片和基因本体数据库中的关键词和途径搜索，从720个与炎症途径相关的基因中鉴定出总共7，650个序列变体。在第1阶段，来自国际肺癌联盟的6个GWAS数据集被合并（4，441例病例和5，094例欧洲血统对照），并使用分层建模（HM）方法将每个变体的先验信息纳入分析中。先验矩阵使用以下各项构建：（1）基因在炎症和免疫途径中的作用;（2）变体的物理性质，包括变体的位置、其保守性评分和氨基酸编码;（3）LD与其他功能变体;以及（4）研究间异质性的测量。HM影响变异的优先级排序，特别是在先前权重低、估计不精确和/或研究间异质性的变异中。在第2阶段，我们使用独立的NCI肺癌GWAS研究（5，699例病例和5，818例对照）进行计算机模拟复制。我们在多重比较校正的水平上发现了一个新的变异（EPHX 2中8q21.1的rs 2741354，p值= 7.4 × 10−6），并证实了TERT（rs 2736100）与HLA区域和肺癌风险之间的关联。HM允许将诸如来自生物信息学来源的先验知识系统地并入分析中，并且它代表了传统GWAS分析的补充分析方法。
Recent evidence suggests that inflammation plays a pivotal role in the development of lung cancer. In this study, we used a two-stage approach to investigate associations between genetic variants in inflammation pathways and lung cancer risk based on genome-wide association study (GWAS) data. A total of 7,650 sequence variants from 720 genes relevant to inflammation pathways were identified using keyword and pathway searches from Gene Cards and Gene Ontology databases. In Stage 1, six GWAS datasets from the International Lung Cancer Consortium were pooled (4,441 cases and 5,094 controls of European ancestry), and a hierarchical modeling (HM) approach was used to incorporate prior information for each of the variants into the analysis. The prior matrix was constructed using (1) role of genes in the inflammation and immune pathways; (2) physical properties of the variants including the location of the variants, their conservation scores and amino acid coding; (3) LD with other functional variants and (4) measures of heterogeneity across the studies. HM affected the priority ranking of variants particularly among those having low prior weights, imprecise estimates and/or heterogeneity across studies. In Stage 2, we used an independent NCI lung cancer GWAS study (5,699 cases and 5,818 controls) for in silico replication. We identified one novel variant at the level corrected for multiple comparisons (rs2741354 in EPHX2 at 8q21.1 with p value = 7.4 × 10−6), and confirmed the associations between TERT (rs2736100) and the HLA region and lung cancer risk. HM allows for prior knowledge such as from bioinformatic sources to be incorporated into the analysis systematically, and it represents a complementary analytical approach to the conventional GWAS analysis.
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影响因子：
30.8
作者：
McKay, James D.;Hung, Rayjean J.;Gaborieau, Valerie;Boffetta, Paolo;Chabrier, Amelie;Byrnes, Graham;Zaridze, David;Mukeria, Anush;Szeszenia-Dabrowska, Neonilia;Lissowska, Jolanta;Rudnai, Peter;Fabianova, Eleonora;Mates, Dana;Bencko, Vladimir;Foretova, Lenka;Janout, Vladimir;McLaughlin, John;Shepherd, Frances;Montpetit, Alexandre;Narod, Steven;Krokan, Hans E.;Skorpen, Frank;Elvestad, Maiken Bratt;Vatten, Lars;Njolstad, Inger;Axelsson, Tomas;Chen, Chu;Goodman, Gary;Barnett, Matt;Loomis, Melissa M.;Lubinski, Jan;Matyjasik, Joanna;Lener, Marcin;Oszutowska, Dorota;Field, John;Liloglou, Triantafillos;Xinarianos, George;Cassidy, Adrian;Zelenika, Diana;Boland, Anne;Delepine, Marc;Foglio, Mario;Lechner, Doris;Matsuda, Fumihiko;Blanche, Helene;Gut, Ivo;Heath, Simon;Lathrop, Mark;Brennan, Paul
通讯作者：
Brennan, Paul
影响因子：
5.8
作者：
Johnson, Andrew D.;Handsaker, Robert E.;de Bakker, Paul I. W.
通讯作者：
de Bakker, Paul I. W.
影响因子：
2.1
作者：
Heron, Elizabeth A.;O'Dushlaine, Colm;Gill, Michael
通讯作者：
Gill, Michael
影响因子：
11.2
作者：
Engels, Eric A.;Wu, Xifeng;Spitz, Margaret R.
通讯作者：
Spitz, Margaret R.
影响因子：
2.1
作者：
Gao, Xiaoyi;Stamier, Joshua;Martin, Eden R.
通讯作者：
Martin, Eden R.