Pathway analysis of GWAS provides new insights into genetic susceptibility to 3 inflammatory diseases.
Pathway analysis of GWAS provides new insights into genetic susceptibility to 3 inflammatory diseases.
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DOI：
10.1371/journal.pone.0008068
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发表时间：
2009-11-30
期刊：
影响因子：
3.7
通讯作者：
Levin M
中科院分区：
文献类型：
--
作者：
Eleftherohorinou H;Wright V;Hoggart C;Hartikainen AL;Jarvelin MR;Balding D;Coin L;Levin M
尽管全基因组关联研究（GWAS）的引入大大增加了与常见疾病相关的基因数量，但迄今为止，预测的遗传贡献中只有一小部分得到了阐明。研究在功能通路中作用的多个基因多态性的累积变异，可能为理解常见疾病的遗传决定因素提供一种更常见的单SNP关联方法的补充方法。我们开发了一种新的基于途径的方法来评估在标准生物学途径中起作用的多种遗传变异的综合贡献，并将其应用于14,000名患有7种常见疾病的英国个体的数据。我们测试了炎症途径与克罗恩病（CD）、类风湿性关节炎（RA）和1型糖尿病（T1D）的关联，并以4种非炎症性疾病作为对照。使用变量选择算法，我们确定了负责通路关联的变体，并使用10倍交叉验证框架评估了它们在疾病预测中的用途，以便计算接受者工作曲线（AUC）下的样本外面积。这些预测模型的普遍性在芬兰北部的一个独立出生队列中进行了测试。多种典型炎症途径与CD、T1D和RA呈高度显著相关（p 10−3-10−20）。变量选择平均鉴定出205个SNPs（149个基因）用于T1D， 350个SNPs（189个基因）用于RA， 493个SNPs（277个基因）用于CD。这些SNPs的多态性模式被发现对T1D （91% AUC）和RA （85% AUC）具有高度预测作用，对CD （60% AUC）具有弱预测作用。T1D模型的预测能力（没有任何参数修改）在芬兰队列中具有良好的预测能力（79% AUC）。我们的分析表明，遗传对常见炎症性疾病的贡献是通过多个基因在功能途径中相互作用来实现的。
Although the introduction of genome-wide association studies (GWAS) have greatly increased the number of genes associated with common diseases, only a small proportion of the predicted genetic contribution has so far been elucidated. Studying the cumulative variation of polymorphisms in multiple genes acting in functional pathways may provide a complementary approach to the more common single SNP association approach in understanding genetic determinants of common disease. We developed a novel pathway-based method to assess the combined contribution of multiple genetic variants acting within canonical biological pathways and applied it to data from 14,000 UK individuals with 7 common diseases. We tested inflammatory pathways for association with Crohn's disease (CD), rheumatoid arthritis (RA) and type 1 diabetes (T1D) with 4 non-inflammatory diseases as controls. Using a variable selection algorithm, we identified variants responsible for the pathway association and evaluated their use for disease prediction using a 10 fold cross-validation framework in order to calculate out-of-sample area under the Receiver Operating Curve (AUC). The generalisability of these predictive models was tested on an independent birth cohort from Northern Finland. Multiple canonical inflammatory pathways showed highly significant associations (p 10−3–10−20) with CD, T1D and RA. Variable selection identified on average a set of 205 SNPs (149 genes) for T1D, 350 SNPs (189 genes) for RA and 493 SNPs (277 genes) for CD. The pattern of polymorphisms at these SNPS were found to be highly predictive of T1D (91% AUC) and RA (85% AUC), and weakly predictive of CD (60% AUC). The predictive ability of the T1D model (without any parameter refitting) had good predictive ability (79% AUC) in the Finnish cohort. Our analysis suggests that genetic contribution to common inflammatory diseases operates through multiple genes interacting in functional pathways.
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影响因子：
30.8
作者：
Fisher, Sheila A.;Tremelling, Mark;Anderson, Carl A.;Gwilliam, Rhian;Bumpstead, Suzannah;Prescott, Natalie J.;Nimmo, Elaine R.;Massey, Dunecan;Berzuini, Carlo;Johnson, Christopher;Barrett, Jeffrey C.;Cummings, Fraser R.;Drummond, Hazel;Lees, Charlie W.;Onnie, Clive M.;Hanson, Catherine E.;Blaszczyk, Katarzyna;Inouye, Mike;Ewels, Philip;Ravindrarajah, Radhi;Keniry, Andrew;Hunt, Sarah;Carter, Martyn;Watkins, Nick;Ouwehand, Willem;Lewis, Cathryn M.;Cardon, Lon;Lobo, Alan;Forbes, Alastair;Sanderson, Jeremy;Jewell, Derek P.;Mansfield, John C.;Deloukas, Panos;Mathew, Christopher G.;Parkes, Miles;Satsangi, Jack
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Satsangi, Jack
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14.9
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Kanehisa M;Araki M;Goto S;Hattori M;Hirakawa M;Itoh M;Katayama T;Kawashima S;Okuda S;Tokimatsu T;Yamanishi Y
通讯作者：
Yamanishi Y
影响因子：
4.5
作者：
Hoggart, Clive J.;Whittaker, John C.;De Iorio, Maria;Balding, David J.
通讯作者：
Balding, David J.
影响因子：
30.8
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Barton A;Thomson W;Ke X;Eyre S;Hinks A;Bowes J;Plant D;Gibbons LJ;Wellcome Trust Case Control Consortium;YEAR Consortium;BIRAC Consortium;Wilson AG;Bax DE;Morgan AW;Emery P;Steer S;Hocking L;Reid DM;Wordsworth P;Harrison P;Worthington J
通讯作者：
Worthington J
影响因子：
3.5
作者：
Janssens, A. Cecile J. W.;van Duijn, Cornelia M.
通讯作者：
van Duijn, Cornelia M.