A new testing strategy to identify rare variants with either risk or protective effect on disease.
A new testing strategy to identify rare variants with either risk or protective effect on disease.
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DOI：
10.1371/journal.pgen.1001289
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发表时间：
2011-02-03
期刊：
影响因子：
4.5
通讯作者：
Lange C
中科院分区：
文献类型：
--
作者：
Ionita-Laza I;Buxbaum JD;Laird NM;Lange C
测序技术的快速进步为在不久的将来进行的大规模医学测序工作奠定了基础，目标是评估稀有变异在复杂疾病中的重要性。新的疾病易感基因的发现需要强大的统计方法来进行罕见的变异分析。较低的频率和预计的大量此类变异给这些数据的分析带来了极大的困难。我们在这里提出了一种强大而强大的测试策略来研究稀有变异在影响对复杂特征的敏感性方面所起的作用。该策略的基础是评估一个基因区域中的罕见变异是否在病例中出现的频率比对照组高得多(反之亦然)。拟议方法的一个主要特点是，尽管这是一项同时评估可能大量罕见变种的总体测试，但疾病变种既可以是保护性变种，也可以是风险变种，当这两种类型的变种都存在时，统计能力会适度下降。通过模拟，我们证明了这种方法在复杂和一般的疾病模型下，以及在疾病易感性变异比例可能较小的较大遗传区域中是有效的。与已发表的模拟数据测试结果的比较表明，该方法比现有方法具有更好的性能。对最近发表的一项关于1型糖尿病的研究的应用发现，IFIH1基因的罕见变异对1型糖尿病具有保护作用。常见疾病的风险，如糖尿病、心脏病等，受到遗传和环境因素之间复杂相互作用的影响。到目前为止，大多数与疾病相关的研究都集中在常见的变异上，这些变异在基因分型平台上广泛存在。然而，测序技术的最新进展为大规模的医学测序研究铺平了道路，目的是阐明稀有变异在影响复杂特征易感性方面可能发挥的作用。大量的稀有变异及其低频率给这些数据的分析带来了巨大的挑战。我们在这里提出了一种基于加权和统计量的新的测试策略，该策略比现有的方法对所研究的遗传区域中存在的风险和保护性变异的敏感度较低。我们展示了对模拟数据和对1型糖尿病的真实数据集的应用。
Rapid advances in sequencing technologies set the stage for the large-scale medical sequencing efforts to be performed in the near future, with the goal of assessing the importance of rare variants in complex diseases. The discovery of new disease susceptibility genes requires powerful statistical methods for rare variant analysis. The low frequency and the expected large number of such variants pose great difficulties for the analysis of these data. We propose here a robust and powerful testing strategy to study the role rare variants may play in affecting susceptibility to complex traits. The strategy is based on assessing whether rare variants in a genetic region collectively occur at significantly higher frequencies in cases compared with controls (or vice versa). A main feature of the proposed methodology is that, although it is an overall test assessing a possibly large number of rare variants simultaneously, the disease variants can be both protective and risk variants, with moderate decreases in statistical power when both types of variants are present. Using simulations, we show that this approach can be powerful under complex and general disease models, as well as in larger genetic regions where the proportion of disease susceptibility variants may be small. Comparisons with previously published tests on simulated data show that the proposed approach can have better power than the existing methods. An application to a recently published study on Type-1 Diabetes finds rare variants in gene IFIH1 to be protective against Type-1 Diabetes. Risk to common diseases, such as diabetes, heart disease, etc., is influenced by a complex interaction among genetic and environmental factors. Most of the disease-association studies conducted so far have focused on common variants, widely available on genotyping platforms. However, recent advances in sequencing technologies pave the way for large-scale medical sequencing studies with the goal of elucidating the role rare variants may play in affecting susceptibility to complex traits. The large number of rare variants and their low frequencies pose great challenges for the analysis of these data. We present here a novel testing strategy, based on a weighted-sum statistic, that is less sensitive than existing methods to the presence of both risk and protective variants in the genetic region under investigation. We show applications to simulated data and to a real dataset on Type-1 Diabetes.
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影响因子：
30.8
作者：
Helbig I;Mefford HC;Sharp AJ;Guipponi M;Fichera M;Franke A;Muhle H;de Kovel C;Baker C;von Spiczak S;Kron KL;Steinich I;Kleefuss-Lie AA;Leu C;Gaus V;Schmitz B;Klein KM;Reif PS;Rosenow F;Weber Y;Lerche H;Zimprich F;Urak L;Fuchs K;Feucht M;Genton P;Thomas P;Visscher F;de Haan GJ;Møller RS;Hjalgrim H;Luciano D;Wittig M;Nothnagel M;Elger CE;Nürnberg P;Romano C;Malafosse A;Koeleman BP;Lindhout D;Stephani U;Schreiber S;Eichler EE;Sander T
通讯作者：
Sander T
影响因子：
9.8
作者：
Li, Bingshan;Leal, Suzanne M.
通讯作者：
Leal, Suzanne M.
影响因子：
2.1
作者：
Morris, Andrew P.;Zeggini, Eleftheria
通讯作者：
Zeggini, Eleftheria
影响因子：
4.3
作者：
Fearnhead, NS;Winney, B;Bodmer, WF
通讯作者：
Bodmer, WF
DOI：
10.1073/pnas.0407187101
发表时间：
2004-11-09
影响因子：
11.1
作者：
Fearnhead, NS;Wilding, JL;Bodmer, WF
通讯作者：
Bodmer, WF