Accounting for population stratification in DNA methylation studies.
Accounting for population stratification in DNA methylation studies.
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DOI：
10.1002/gepi.21789
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发表时间：
2014-04
影响因子：
2.1
通讯作者：
Conneely, Karen N.
中科院分区：
文献类型：
--
作者：
Barfield, Richard T.;Almli, Lynn M.;Kilaru, Varun;Smith, Alicia K.;Mercer, Kristina B.;Duncan, Richard;Klengel, Torsten;Mehta, Divya;Binder, Elisabeth B.;Epstein, Michael P.;Ressler, Kerry J.;Conneely, Karen N.
DNA甲基化是一种重要的表观遗传机制，与复杂的疾病有关，并且作为基因组、环境和疾病之间的潜在联系而引起了研究人员的极大兴趣。随着DNA甲基化关联研究的规模接近全基因组关联研究（GWAS）的规模，需要解决人口分层等问题。有充分的证据表明，未能调整群体分层可能导致遗传关联研究中的假阳性，但在DNA甲基化研究中，群体分层通常未被考虑在内。在这里，我们提出了几种方法来纠正群体分层使用来自不同子集的全基因组甲基化数据的主成分。我们首先通过在388个个体（365个非裔美国人和23个高加索人）中展示DNA甲基化与种族之间的广泛关联来说明由于人口分层而导致的潜在混淆。随后，我们评估了主成分方法和其他方法在调整人口分层引起的混淆方面的表现。我们的模拟表明，1)所考虑的所有方法都能有效地消除由于人口分层造成的通货膨胀，2)基于snp的主成分可以获得最大功率，其次是基于甲基化的主成分，其性能优于替代变量分析和基因组控制。在我们计算基于甲基化的主成分的不同方法中，我们发现基于CpG位点的主成分选择具有替代附近SNP的潜力，可以在无法获得全基因组SNP数据时提供强大且计算效率高的方法来调整DNA甲基化研究中的群体分层。
DNA methylation is an important epigenetic mechanism that has been linked to complex disease and is of great interest to researchers as a potential link between genome, environment, and disease. As the scale of DNA methylation association studies approaches that of genome-wide association studies (GWAS), issues such as population stratification will need to be addressed. It is well-documented that failure to adjust for population stratification can lead to false positives in genetic association studies, but population stratification is often unaccounted for in DNA methylation studies. Here, we propose several approaches to correct for population stratification using principal components from different subsets of genome-wide methylation data. We first illustrate the potential for confounding due to population stratification by demonstrating widespread associations between DNA methylation and race in 388 individuals (365 African American and 23 Caucasian). We subsequently evaluate the performance of our principal-components approaches and other methods in adjusting for confounding due to population stratification. Our simulations show that 1) all of the methods considered are effective at removing inflation due to population stratification, and 2) maximum power can be obtained with SNP-based principal components, followed by methylation-based principal components, which out-perform both surrogate variable analysis and genomic control. Among our different approaches to computing methylation-based principal components, we find that principal components based on CpG sites chosen for their potential to proxy nearby SNPs can provide a powerful and computationally efficient approach to adjustment for population stratification in DNA methylation studies when genome-wide SNP data are unavailable.
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影响因子：
3.7
作者：
Boks MP;Derks EM;Weisenberger DJ;Strengman E;Janson E;Sommer IE;Kahn RS;Ophoff RA
通讯作者：
Ophoff RA
影响因子：
4.5
作者：
Christensen BC;Houseman EA;Marsit CJ;Zheng S;Wrensch MR;Wiemels JL;Nelson HH;Karagas MR;Padbury JF;Bueno R;Sugarbaker DJ;Yeh RF;Wiencke JK;Kelsey KT
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Kelsey KT
影响因子：
3.5
作者：
Heijmans, Bastiaan T.;Kremer, Dennis;Slagboom, P. Eline
通讯作者：
Slagboom, P. Eline
影响因子：
30.8
作者：
Kerkel, Kristi;Spadola, Alexandra;Tycko, Benjamin
通讯作者：
Tycko, Benjamin
影响因子：
12.8
作者：
Coit P;Jeffries M;Altorok N;Dozmorov MG;Koelsch KA;Wren JD;Merrill JT;McCune WJ;Sawalha AH
通讯作者：
Sawalha AH